UNIVERSIDADE ESTADUAL DE CAMPINAS

FACULDADE DE ODONTOLOGIA DE PIRACICABA

MABELLE DE FREITAS MONTEIRO

HERITABILITY IN GENERALIZED

AGGRESSIVE PERIODONTITIS:

MICROBIOLOGICAL, IMMUNOLOGICAL AND

PREVENTIVE ASPECTS

HEREDITARIEDADE NA PERIODONTITE

AGRESSIVA GENERALIZADA:

ASPECTOS MICROBIOLÓGICOS, IMUNOLÓGICOS

E PREVENTIVOS

Piracicaba

2019

MABELLE DE FREITAS MONTEIRO

HERITABILITY IN GENERALIZED AGGRESSIVE

PERIODONTITIS: MICROBIOLOGICAL, IMMUNOLOGICAL AND

PREVENTIVE ASPECTS

HEREDITARIEDADE NA PERIODONTITE AGRESSIVA

GENERALIZADA: ASPECTOS MICROBIOLÓGICOS,

IMUNOLÓGICOS E PREVENTIVOS

Thesis presented to the Piracicaba Dental School/University of Campinas in partial fulfillment of the requirements for the degree of Doctor in Clinical Dentistry, in Periodontics area. Tese apresentada à Faculdade de Odontologia de Piracicaba/Universidade Estadual de Campinas como parte dos requisitos exigidos para a obtenção do título de Doutora em Clínica Odontológica, na Área de Periodontia.

Supervisor: Prof. Dr. Renato Corrêa Viana Casarin This copy represents the final version of the thesis presented

by Mabelle de Freitas Monteiro and oriented by Prof. Dr. Renato Corrêa Viana Casarin

Piracicaba

2019

Agência(s) de fomento e nº(s) de processo(s): FAPESP, 2015/50264-0; FAPESP,

2016/03704-7; FAPESP, 2016/19970-8

ORCID: https://orcid.org/0000-0001-9333-4349

Ficha catalográfica Universidade Estadual de Campinas

Biblioteca da Faculdade de Odontologia de Piracicaba

Marilene Girello - CRB 8/6159

Monteiro, Mabelle de Freitas, 1990-

M764h MonHeritability in generalized aggressive periodontitis : microbiological,

immunological and preventive aspects / Mabelle de Freitas Monteiro. –

Piracicaba, SP : [s.n.], 2019.

MonOrientador: Renato Corrêa Viana Casarin.

MonTese (doutorado) – Universidade Estadual de Campinas, Faculdade de

Odontologia de Piracicaba.

Mon1. Periodontite agressiva. 2. Família. 3. Suscetibilidade a doenças. 4.

Microbiota. 5. Inflamação. I. Casarin, Renato Corrêa Viana, 1982-. II.

Universidade Estadual de Campinas. Faculdade de Odontologia de Piracicaba.

III. Título.

Informações para Biblioteca Digital

Título em outro idioma: Hereditariedade na periodontite agressiva generalizada : aspectos

microbiológicos, imunológicos e preventivos Palavras-chave em inglês:

Aggressive periodontitis

Family

Disease susceptibility

Microbiota

Inflammation

Área de concentração: Periodontia

Titulação: Doutora em Clínica Odontológica

Banca examinadora:

Renato Corrêa Viana Casarin [Orientador]

Marcia Pinto Alves Mayer

Purnima Kumar

Mauro Pedrine Santamaria

Enílson Antonio Sallum

Data de defesa: 26-02-2019

Programa de Pós-Graduação: Clínica Odontológica

Identificação e informações acadêmicas e professionais do(a) aluno(a):

- ORCID: https://orcid.org/0000-0001-9333-4349

- Currículo Lattes: http://lattes.cnpq.br/2234014499827931

UNIVERSIDADE ESTADUAL DE CAMPINAS Faculdade de Odontologia de Piracicaba

A Comissão Julgadora dos trabalhos de Defesa de Tese de Doutorado, em sessão pública

realizada em 26 de Fevereiro de 2019, considerou a candidata MABELLE DE FREITAS

MONTEIRO aprovada.

PROF. DR. RENATO CORRÊA VIANA CASARIN

PROFª. DRª. MARCIA PINTO ALVES MAYER

PROFª. DRª. PURNIMA KUMAR

PROF. DR. MAURO PEDRINE SANTAMARIA

PROF. DR. ENÍLSON ANTONIO SALLUM

A Ata da defesa, assinada pelos membros da Comissão Examinadora, consta no SIGA/Sistema de Fluxo de Dissertação/Tese e na Secretaria do Programa da Unidade.

DEDICATÓRIA

Primeiramente, dedico este trabalho a Deus, meu

guia, que permitiu que tudo isso acontecesse e que

orientou todas as minhas decisões.

Também dedico este trabalho à minha mãe,

Zulmira, pessoa a qual admiro imensamente e que

sempre esteve presente em minha vida. Você sempre foi

minha inspiração e meu maior exemplo, me fazendo

inclusive escolher esta profissão maravilhosa que é a

odontologia.

ACKNOWLEDGEMENTS

Firstly, I thank God first for all the beautiful opportunities he has given me, both

professional and personal, and that has made me grow and be who I am today. Thank you for

giving me patience and tranquility to wait for all the blessings I have received, always at the

right moment of my life. Thank you for being my guide, for guiding my decisions and for the

unshakeable faith that has always driven me to overcome the new challenges and achieve my

dreams.

I also thank my family, my mother Zulmira, my father Adenir, Felipe, Vera and my

sister Mayara. You are responsible for all my education and moral training, for which I am very

grateful. You are super special in my life and without your support and love I could never stay

in Piracicaba all this time and spend a year alone in Columbus. Having you as a safe haven and

as an example allowed me to overcome the enormous longing, the moments of discouragement

and difficulties, and I have always had you as an example. You can be sure that you are

responsible for my achievements, accomplishments, and the things I believe in. I love you!

My thanks to my love Marco Aurélio Versori for the love and affection offered during

these almost 5 years of relationship. Thank you for your support, companionship, understanding

in the most difficult moments and for always being by my side. I know you’ve abdicated various

things so I could live my dream, and I am eternally grateful for it. I'm sorry for my absence at

such a difficult and troubled time in your life, but I'll be here for whatever you need.

I thank Marinele Venturini and Rodolfo Versori, my mother-in-law and my father-in-

law, for all the support and care offered during these years. Thank you for treating me as a

daughter and for always supporting me.

I thank my dear friends Larissa Rezende Martins, Carolina Ventura, Thatiana Leite,

Diogo Henrique da Silva, João Otávio Barros, Bruno Micaroni, for the time we spent together

and for the joys that you have given me in all these 10 years of friendship. Thank you for taking

care of me and for helping me until these days, for giving me a hand (and often an arm) in the

moments of greatest difficulties and anguish. You were a source of inexhaustible strength to

me, people I could count on all the time, who comforted me, relieving a little of the weight of

the longing I’ve always felt. That gave me many moments of joy, which made me grow and

gave me the opportunity to create a new family in Piracicaba. That, of course, would not be

possible without you. You can always count on me!

I thank my friends and colleagues in the Periodontics Ana Lívia Fileto, Marcela di

Moura, Manuela Rocha, João Paulo Sangiorgio, Isabela Lima França, Tiago Taiete, Maria Alice

Gatti Palma, Thiago Bueno, Amanda Bandeira, Rafaela Videira, Aurélio Amorim, Thiago

Rangel, Roberta Gava, Rahyza Freire, Elis Lira, Thayane Businari, Tamires Dutra, Catharina

Sacramento, Javier Purisaca for the daily living, the help and the good experiences exchanged

during these 6 years of postgraduate. A special thanks to Ana Lívia Fileto, Manuela Rocha and

Marcela di Moura for the countless help, learning, laughter, and friendship of the "Feira" that I

will always carry in my heart. Thanks to Isabela Lima França, Thiago Bueno, Amanda

Bandeira, Rafaela Videira, Aurélio Amorim, Thiago Rangel for the friendship and for

welcoming me after my return to FOP. The readaptation would be much harder without you!

Special thanks to the family I built in the USA. Sally and Mark Sulc thank you for the

welcoming and for all the love addressed to me and to all the Brazilians you receive. You made

me realize how good people are anywhere in the world and gave me one of the greatest

examples of unconditional love and resignation I've ever witnessed. I would like to someday be

able to give others half of the love that you are able of offering. Thank you also for allowing

me to meet the best friends I've made in Columbus. Aline Gabbardo, Amanda Vilela, Lucas

Nardelli, Gabriel Abreu, Camila de Freria, Tássia Joi, Georgia Kleina, Brunna Vianna, Patrícia

Marques, Camila Fontes, Wagner Ferrari, Angelo Seolin, Patricia and Gesiel, Gardenia,

Rodolfo and Lavinia, Istvan and Natalia , Bob Williams, Stephanie Conner, Dani and Leo,

Claudineli, Fred and family you were responsible for making my stay in Columbus

unforgettable. Thank you for all the support, friendship, affection, songs, for the games, for the

rides, the shoulder friend, to comfort my sorrows and always have a word of love, trust, and

support to offer me. You are in my heart!!!

Thank you Angeire Huggins! In the 11 months I lived with you I had the opportunity to

realize that the world gave me another sister! And that Latinos are the most incredible people

ever. Thank you for the friendship, the shelter, the support, the conversations, the singing, for

protecting my tears, for teaching me English and Spanish at the same time, for the hugs, for the

good mornings, for the pancakes, for the arepas ... and especially for welcoming me with so

much receptivity and affection in his house. Without your support and advice in this period

surely my days would have been much more difficult and sadder. I can't wait to see you again,

my Venezuelan little sister, and give you a super hug. I'm here for whatever you need, and I'll

be waiting for you in Brazil!!!

I thank the professors of the discipline of Periodontics Prof. Dr. Antônio Wilson Sallum,

Prof. Dr. Enilson Antônio Sallum, Prof. Dr. Francisco Humberto Nociti Júnior, Prof. Dr. Márcio

Zaffalon Casati, Profa. Dr. Karina Gonzales Silvério Ruiz and Prof. Dr. Renato Corrêa Viana

Casarin, for the knowledge, offered, support and availability whenever I needed it. Thank you

for allowing me to participate in this graduate program.

Thank you Profa. Karina Gonzales Silvério Ruiz for all the assistance to obtain the

financial support to bring Prof. Purnima Kumar and to the realization of my defense.

I would like to thank Professor Prof. Dr. Márcio Zaffalon Casati, for opening the doors

of the periodontics to me and for all the confidence deposited in my work. Without your initial

support, I certainly would not be here. Being your master’s student was a great experience, a

moment of great learning and good examples.

Special thanks to Prof. Dr. Renato Corrêa Viana Casarin who has helped me and guided

me throughout my academic journey. Being your student since 2010 was of paramount

importance for me to get here and conquer everything I've achieved so far. I will never forget

the trust you deposited in that 20-year-old girl and all the support you still give me. Thank you

for the guidance and for everything you taught me in these more than 8 years of conviviality. I

have no doubt how important you are in my academic life and I know that much of what I have

conquered so far is due to your help, so I am willing to help you whenever you need to. I hope

one day to return everything you have done for me!

I am very grateful to Prof. Purnima Kumar for welcoming me in her laboratory at The

Ohio State University, for all the support during my stay and for all the knowledge that I could

get there. The internship in her laboratory was a watershed in my academic life, and all the

learning I got there, whether personal or professional, was of paramount importance to be who

I am today. Thank you very much to all the Kumar’s Lab team, especially Shareef Dabdoub,

Khaled Altabtbaei, Shweta Saraswat and Sukirth Ganesan for all the help with my Ph.D. project

and the company during this 1 year of work.

I thank the professors who participated in the qualification exam of this work: Profa.

Dr. Brenda Paula Figueiredo de Almeida Gomes, Profa. Dr. Renata de Oliveira Mattos Graner

and Prof. Dr. Raissa Micaella Marcello Machado for the suggestions and comments on this

thesis. Your contribution was of great value to this study.

I thank the professors for their participation in the defense exam: Prof. Dr. Renato

Corrêa Viana Casarin, Prof. Dr. Márcia Pinto Alves Mayer, Prof. Dr. Purnima Kumar, Prof. Dr.

Enilson Sallum, Prof. Dr. Mauro Pedrine Santamaria, Prof. Dr. Márcio Zaffalon Casati

(alternate), Prof. Dr. Tiago Taiete (alternate) and Prof. Dr. Fernanda Vieira Ribeiro (alternate)

for accepting promptly the invitation to compose the defense bank of this thesis, and certainly,

to assist in the development of this work .

Thank you to Regina Célia Corrêa Caetano da Silva, Mariana Piovezan Fugolin, Janaína

Leite, Eliete Ferreira Lima Marim and Cesar Sarkis for the constant help and patience during

all these postgraduate years.

I Thank the Post-Graduation Coordination and all its employees for all the guidance and

support during the postgraduation life.

I am grateful to the Piracicaba Dental Scholl - FOP/UNICAMP, for being my home

during these 10 years of academic life, from graduation to the completion of my doctorate. The

best years of my life I have had here, and it fills me with pride to be able to say that I am the

daughter of this institution. Thank you for all the infrastructure and material provided to carry

out this thesis.

Thanks also to The Ohio State University (OSU) for allowing the use of its laboratory

structure to perform some of the laboratory analyzes present in this work.

I thank the research funding agencies Coordination for the Improvement of Higher

Education Personnel (CAPES) and National Council for Scientific and Technological

Development (CNPq) for the periods in which I received a scholarship. In addition, I would

like to thank São Paulo Research Foundation (FAPESP) for its support and research funding in

conjunction with The Ohio State University (grant 2015/50264-0), with doctoral fellowships in

Brazil and BEPE (process 2016/03704-7 and 2016/19970-8) and with a fellowship for a

scientific initiation student (process 2016/20361-6) that made possible the accomplishment of

these studies.

Finally, thank you to all who have been with me, who have made my days much happier

and unconditionally supported me, often believing more in my potential than myself. Your

support was essential for this work.

To all, my sincere thanks!

ABSTRACT

Generalized aggressive periodontitis (GAgP) is a multifactorial disease caused by an unbalance

between the host response e the biofilm aggression. It is characterized by the familial

aggregation of cases, probably associated with the sharing of susceptibility aspects between

family member, what could increase the risk to GAgP descendants to develop GAgP. In this

context, the present report describes three different studies: the first aiming to characterize the

microbiome, as well its association to the host response, in GAgP subjects and their children;

the second study aiming to evaluate the effective of plaque control in altering the pathogenic

subgingival condition identified in GAgP descendants; the third aiming to evaluate the

efficiency of Triclosan-containing toothpaste as an adjunctive therapy to control the precocious

alteration demonstrated in GAgP descendants. In the first study, 15 GAgP parents with at least

a child between 6-12 years old and 15 health parents with at least one child between 6-12 years

old were selected. The clinical examination and the collection of subgingival biofilm and

gingival crevicular fluid (GCF) were performed for all subjects. The bacterial DNA of the

subgingival biofilm was extracted, the 16S rRNA was sequenced using the Illumina MiSeq

platform and bioinformatic tools were used to analyze the data. The gingival crevicular fluid

was analyzed with the Luminex MAGPIX technology for the identification of interferon (IFN)-

γ, and tumor necrosis factor (TNF)-α, interleukin (IL)-10, IL-4, IL-1β, IL-17, IL-6, IL-8 levels.

Children from GAgP parents presented the worst clinical condition as well as a more pathogenic

and dysbiotic microbiome than children from healthy parents. A strong correlation was

observed between the parent microbiome and his child microbiome. Differences in the

cytokines’ levels were only observed in parents with GAgP parent presenting lower levels of

IFN-γ, IL-10, and IL-17. Despite no differences in the cytokine levels, children from GAgP

parents presented alteration in the host-bacterial interactions and demonstrated a similar pattern

to their parents. In the second study, 18 children (6-12 years old) from GAgP parents and 18

children from periodontally healthy parents were included in a plaque control program for 3

months. All subjects were periodontally examined and subgingival biofilm and gingival

crevicular fluid (GCF) were collected at baseline and after 3 months of strict plaque control.

Next-generation sequencing and bioinformatic tools were used to evaluate the subgingival

microbiome and the Luminex/MAGPIX platform was used for the inflammatory analysis in

GCF. The Linear Discriminant Analysis of Morisita-Horn index demonstrated two massive

clusters separating children from AgP parents from children from healthy parents (Adonis test,

p=0.014), demonstrating a significant impact of parental periodontitis on the microbiome of

their descendants. A more pathogenic microbiome associated with more intense host-bacterial

interactions and worst clinical condition was identified in children from GAgP parents. The

dysbiotic microbiome of GAgP descendants showed a strong resilience against shifting after

plaque control, maintaining the diversity and the richness of disease-associated species even

after the clinical benefits achieved. In addition, plaque control was not sufficient to alter the

pattern of host-bacterial interaction in the subgingival environment. In the third study, 15

children from GAgP parents and 15 children from periodontally healthy parents were included

in this cross-over placebo study. Children were randomly allocated into Triclosan or Placebo

groups to participate in the first phase of the study. Initially, all children participate in a wash-

out period of 15 days using only the placebo toothpaste and posteriorly they started to use the

elected toothpaste for 45 days. After the first phase, they repeated the period of 15 days of wash-

out using only the placebo toothpaste. The groups were crossed, and the children used the other

paste for more 45 days. In each phase, clinical examination and saliva, GCF and subgingival

biofilm collection were performed at baseline and 45 days. The levels of IFN-γ, IL-4, IL-10,

IL-1β, IL-17, and TNF-α were analyzed by Luminex/MAGpix platform and subgingival and

salivary periodontal pathogens’ levels by qPCR. At baseline, children from AgP parents

presented higher levels of the gingival index (GI), plaque index (PI), and bleeding on probing

(BoP), a higher concentration of Aggregatibacter actinomycetemcomitans (Aa) in saliva and

subgingival biofilm, and lower levels of INF-ɣ, IL-4, IL-17 in the GCF. Placebo therapy only

reduced PI, in both groups. Triclosan toothpaste reduced PI, as well as GI, in both groups.

Moreover, Triclosan promoted the reduction of BoP and PPD, Aa salivary levels and IL-1β in

GAgP group. In Health group, Triclosan promoted a reduction of INF-ɣ and IL-4. In conclusion,

the microbiome and the host-bacterial interaction were altered in GAgP parent and their

descendants and a strong impact of the parents’ periodontal condition in their children

periodontal status was demonstrated. The dysbiosis was associated with more intense species

cytokines correlations and higher clinical inflammation. The plaque control was not able to

change the more pathogenic subgingival environment of GAgP descendants, that demonstrated

a strong resilience to subgingival microbial shifting after strict plaque control, highlighting the

higher risk for disease development. Furthermore, Triclosan dentifrice demonstrated to be more

efficient than placebo toothpaste to control the more pathogenic profile demonstrate in GAgP,

by reducing the bleeding on probing, probing depth, salivary Aa and IL-1β, in children from

GAgP parents.

Keywords: Aggressive periodontitis, family, disease susceptibility, microbiota, inflammation

RESUMO

Periodontite agressiva generalizada (PAG) é uma doença multifatorial causado por um

desequilíbrio entre a resposta do hospedeiro e as agressões do biofilme. Ela é caracterizada pela

agregação familiar dos casos, provavelmente associada ao compartilhamento de fatores de

susceptibilidade entre membros de uma mesma família, o que poderia aumentar o risco de

descendentes de indivíduos PAG também desenvolverem a doença. Neste contexto, o presente

trabalho descreve três estudos diferentes, um com o objetivo de caracterizar o microbioma,

assim como a sua associação com a resposta do hospedeiro, em indivíduos PAG e seus filhos

e o segundo estudo objetivando avaliar a pasta de dente contendo Triclosan como uma terapia

adjunta no controle das alterações precoces demonstradas em descendentes PAG. No primeiro

estudo 15 pais PAG com pelo menos um filho com idade entre 6 e 12 anos e 15 pais

periodontalmente saudáveis com pelo menos uma criança entre 6 e 12 anos foram selecionadas.

O exame clínico e a coleta de biofilme subgengival e fluido gengival (GCF) foram realizados

para todos os participantes. O DNA bacteriano do biofilme subgengival foi extraído, a região

16S do rRNA foi sequenciado utilizando a plataforma Illumina MiSeq e ferramentas de

bioinformática foram utilizadas para analisar os dados. O fluido crevicular gengival foi

analisado com a tecnologia Luminex MAGPIX para a identificação das citocinas interferon

(IFN) -γ, fator de necrose tumoral (TNF-α) e interleucinas (IL) -10, IL-17, IL-1β, IL-4, IL-6,

IL-8. Crianças de pais PAG apresentaram piores condições clínicas, bem como um microbioma

mais patogênico do que crianças de pais saudáveis. Uma forte correlação foi observada entre o

microbioma do pai e o microbioma de seu filho. Diferenças nos níveis de citocinas foram

observadas apenas em pais PAG que apresentaram níveis menores de IFN-γ, IL-10 e IL-17.

Apesar de não haver diferenças nos níveis de citocinas, as crianças dos pais PAG apresentaram

alteração nas interações entre bactérias e o hospedeiro e demonstraram um padrão similar ao

apresentado por seus pais. No segundo estudo, 18 crianças (entre 6 e 12 anos) filhas de

indivíduos PAG e 18 criança filhas de ambos os pais periodontalmente saudáveis foram

incluídas em um programa de controle de placa por 3 meses. Todos os indivíduos foram

periodontalmente avaliados e submetidos a coleta de biofilme subgengival e GCF no início do

estudo e após 3 meses de controle de placa. Sequenciamento de nova geração e ferramentas de

bioinformática foram utilizadas para a avaliação do biofilme subgengival enquanto a plataforma

Luminex/MAGPIX foi usada para aas análises inflamatórias no GCF. Análise de discriminantes

lineares do índice Morisita-Horn demonstrou dois aglomerados maciços separando filhos de

pais PAG de filhos de pais saudáveis (teste Adonis, p=0.014), demonstrando um impacto

significativo da doença periodontal parental no microbioma de dos seus descendentes. Um

microbioma mais patogênico associado com maior interrelação bactéria-hospedeiro e piores

condições clínicas foram identificadas em crianças PAG. O microbioma disbiótico de

descendentes PAG mostrou uma forte resiliência a mudança depois do controle de placa,

mantendo a diversidade e a riqueza de espécies associadas a doença periodontal mesmo depois

que benefícios clínicos forma atingidos. Além disso, o controle de placa não foi suficiente para

alterar o padrão de interações entre o microbioma e o hospedeiro. No terceiro estudo, 15

crianças de pais PAG e 15 crianças de pais periodontalmente saudáveis foram incluídas neste

estudo placebo cruzado. As crianças foram alocadas aleatoriamente nos grupos Triclosan ou

Placebo para participar da primeira fase do estudo. Inicialmente, todas as crianças participaram

de um período de wash-out de 15 dias usando apenas o creme dental placebo para

posteriormente começaram a usar o creme dental selecionado por 45 dias. Após a primeira fase,

eles repetiram o período de 15 dias de wash-out usando apenas o creme dental placebo. Os

grupos foram cruzados e as crianças usaram a outra pasta por mais 45 dias. Em cada fase, foram

realizados exame clínico e coleta de saliva, GCF e biofilme subgengival no exame inicial e aos

45 dias de estudo. Os níveis de IFN-γ, IL-17, IL-4, IL-1β, IL-10 e TNF-α foram analisados pela

plataforma Luminex / MAGpix e os níveis de patógenos periodontais salivares e subgengivais

por qPCR. No início do estudo, as crianças dos pais PAG apresentaram maiores índice de placa

(IP), índice gengival (IG) e sangramento à sondagem (SS), além de maiores concentrações de

Aggregatibacter actinomycetemcomitans (Aa) na saliva e no biofilme subgengival e menores

níveis de INF-ɣ, IL-4, IL-17 no GCF. A terapia com placebo apenas reduziu o IP, em ambos os

grupos. O creme dental com Triclosan reduziu o IP, assim como o IG, em ambos os grupos.

Além disso, o Triclosan promoveu redução adicional do SS, da profundidade de sondagem

(PS), dos níveis salivares Aa e IL-1β no grupo PAG. No grupo de saúde, Triclosan promoveu

uma redução de INF-ɣ e IL-4. Em conclusão, o microbioma e as interações hospedeiro-biofilme

foram alterados nos indivíduos PAG e seus descendentes e uma forte correlação entre o estado

periodontal dos pais e de seus filhos foi demonstrada. A disbiose foi relaciona com correlações

mais intensas entre as bactérias e o hospedeiro e maior inflamação clínica. O controle de placa

não foi suficiente para mudar o ambiente subgengival mais patogênico em descendentes PAG,

que demonstrou uma alta resiliência para as mudanças microbiológicas e destacou o maior risco

para o desenvolvimento de doença periodontal. Além disso, o creme dental com Triclosan

demonstrou-se mais eficiente do que o creme dental placebo em controlar o perfil mais

patogênico observado em PAG, uma vez que reduziu os níveis de sangramento a sondagem,

sondagem periodontal, Aa salivar e IL-1β, em crianças de pais PAG.

Palavras-chave: periodontite agressiva, família, suscetibilidade a doença, microbiota,

inflamação

SUMMARY

1 INTRODUCTION 15

2 ARTICLES 19

2.1 Article: Heritability of parental periodontal condition and susceptibility in generalized

aggressive periodontitis 19

2.2 Article: Resilience to Microbial Shift in Children from Periodontitis Parents. 42

2.3 Article: Triclosan as an adjunct therapy to plaque control in children from periodontitis

families. A crossover clinical trial. 61

3 DISCUSSION 80

4 CONCLUSION 84

REFERENCES 85

SUPPLEMENTS 89

Supplement 1 - Ethical Committee 89

Supplement 2 - Ethical Committee 90

Supplement 3 - Submission confirmation 91

Supplement 4 - Turnitin certificate 92

15

1 INTRODUCTION

Generalized aggressive periodontitis (GAgP) is a multifactorial disease that causes rapid

and severe destruction of the periodontal tissue and affects young and systemic health subjects

(Armitage 1999). Despite its low prevalence in the worldwide population (Susin et al., 2014),

GAgP can cause severe periodontal loss, and tooth loss when not treated, a situation that can

interfere directly in the functional, aesthetic and socioeconomic condition of the affected

subjects. The major etiological factor of GAgP is the subgingival biofilm that can trigger the

local inflammatory response and promote the periodontal tissue loss (Kinane et al., 2017).

Previously, some specific microorganisms, such as A. actinomycetemcomitans (Aa) and the red

complex (P. gingivalis, T. denticola, and T. forsythia) (Socransky et al., 1998), were suggested

as etiological agents of periodontitis (Casarin et al., 2010; Haubek, 2010; Nibali et al., 2012)

and intense investigations were performed trying to identify a specific microorganisms as the

main cause of periodontal destruction. Many studies, for example, pointed the Aa (more

specifically the JP2 clone) as the main etiological factor for Aggressive periodontitis and as a

potential risk factor for future attachment loss in adolescents (Haubek, 2010; Shaddox et al.,

2012; Fine et al., 2013; Höglund Åberg et al., 2014). However, many studies do not confirm

this association and no consensus was obtained about their role in periodontitis.

The new technologies for microbial evaluation, such as the non-culture techniques and

the DNA sequencing, allowed a broad interpretation of the biofilm that colonizes the

subgingival environment and the identification of new microorganisms with potential

involvement in the periodontitis initiation and progression (Hajishengallis and Lamont 2012).

Thus, a holistic view of the subgingival community was possible, favoring the understanding

of a multifactorial and complex disease as periodontitis. The current comprehension of

periodontal disease describes that the dysbiosis (a change in the relative abundances of

individual components of the microbiota compared with their abundance in health) in

subgingival environment is related to an unbalance between the host response and the microbial

aggression which can cause the periodontal breakdown (Hajishengallis et al., 2012; Könönen

and Müller, 2014; Lamont et al., 2018). Thus, alterations on the whole microbiome, and not in

some specific species, were essential for creating a pathogenic community able to promote

destruction. In this context, some microorganisms were described as essential to the modulation

of the whole community. The P. gingivalis was suggested as a keystone pathogen, a species

that even in low abundance has a large effect and importance in the community’s structure

(Hajishengallis et al., 2012). This microorganism would have the ability to impair the host

16

response and to modulate functionally the whole community, giving the environmental

conditions and supporting the overgrowth of commensal microorganisms, that under specific

conditions have the ability to disrupt the host homeostasis (pathobionts), and producing

dysbiosis (Hajishengallis et al., 2012).

Despite the importance of the microbial component in the periodontitis pathogenesis,

the host-related factors have an essential role in the initiation of periodontal destruction

(Kulkarni and Kinane, 2014; Vieira and Albandar, 2014). It is suggested that genetic alterations

that modulate the host response are involved on GAgP pathogenesis and that the quality of the

inflammatory response should be essential to determine the disease occurrence and severity

(Shaddox et al., 2010; Vieira and Albandar, 2014). Some studies have demonstrated how the

genetics can promote a selective pressure in the microbiome and influence the abundance of

some specific microorganism (Nibali et al., 2007; Nibali et al., 2009; Eskan et al., 2012; Cavalla

et al., 2018). Thus, by altering some specific colonization factors or by altering the host

response/the inflammatory pattern locally, the host could produce the ecologic conditions

necessary for the outgrowth of specific bacteria and the dysbiosis occurrence (Hajishengallis,

2014; Lamont et al., 2018). In fact, inflammation and dysbiosis are important to sustain each

other and positively reinforce the disease cycle, once dysbiosis stimulates the inflammatory

response at the same time that inflammation creates the environmental conditions to support

the growth of some “inflammophilic” bacteria and stabilizes the dysbiotic associated microbiota

(Lamont et al., 2018).

One of the most important characteristics of GAgP is the familial aggregation and the

accumulation of cases in the same family turns around 40 to 50% (Michalowicz et al., 2000;

Meng et al., 2011). It is attributed to the sharing of risk factors within family members, such as

genetic aspects, an altered inflammatory response, the bacterial transmission and the sharing of

environmental and behavioral conditions, increasing their susceptibility to also develop the

disease (Haubek, 2010). In this context, our research group started to evaluate descendants of

GAgP subjects, focusing in understand the aspects associated with susceptibility to disease and

many alterations were described even before the clinical sign of disease. Monteiro et al (2014),

described higher colonization for Aa in the saliva of children from GAgP parents when

compared to children from healthy parents and the fact of a parent be colonized by Aa increases

in 16 times the chance of a child to be colonized by this microorganism. Posteriorly, it was

demonstrated that children from GAgP parents presented the worst clinical conditions, higher

colonization by Aa in the subgingival environment and the higher levels of Aa were directly

17

correlated to gingival bleeding (Monteiro et al., 2015). These studies highlight that initial

changes were presented in GAgP descendants, and that they could be the initial sign of disease

or could represent a risk to this population that should be clinically monitored and the focus on

more investigations.

The study design of families, analyzing descendants of GAgP, demonstrated to be

effective in identifying alterations, what could help the comprehension of pathogenic aspects

still not completely understood and the identification of risk markers and alterations previously

to periodontal destruction. However, the comprehension of the complex and dysbiotic

microbiome that characterize GAgP, and its interplay with the host response, requires the use

of more robust technologies and the joint analysis of microbiological and inflammatory aspects

involved in the periodontal breakdown. Thus, a new study was necessary to characterize the

subgingival environment of GAgP, as well as to understand the impact of the parent periodontal

condition on the periodontal status of their offspring, investigating the possible aspects related

to the familial component and the susceptibility to periodontitis. Moreover, once the precocious

alterations were identified, clinical procedures were tested as an option to the treatment and the

preventive management of this risk population.

The plaque control is the first option to control oral conditions associated with plaque

accumulation, especially in a vulnerable group as children. It is a non-invasive therapy and it

has demonstrated efficacy in controlling the clinical inflammation (Löe et al., 1965; Trombelli

et al., 2004) and that way the risk for periodontal destruction in a long-term (Lang et al., 2009).

Thus, this approach should be tested as the initial option to modulate the pathogenic-associated

subgingival condition and risk. Additionally, the use of chemical agents in association with

plaque control is an interesting choice to increase the potential of plaque removal to modulate

the subgingival environmental conditions. The triclosan is an antimicrobial and anti-

inflammatory component commercially available in toothpaste (Riley and Lamont, 2013).

Clinical studies have demonstrated the potential of Triclosan-containing toothpaste to improve

the periodontal parameters (Panagakos et al., 2005; Ribeiro et al., 2018), to reduce pathogens

levels, such as Aa and P. gingivalis (Pancer et al., 2016), and to modulate the inflammatory

response in vitro and in vivo (Barros et al., 2010; Pancer et al., 2016; Ribeiro et al., 2018).

Moreover, the toothpaste with Triclosan is an easy-to-use and secure form of application and it

would represent no substantial change in children hygiene habits, facilitating the accessibility

and compliance.

18

Thus, three studies were proposed. The first study aimed to evaluate the microbiome, as

well its relationship with the host response, in GAgP subjects and their children compared to

healthy subjects and their children. The second study aimed to evaluate plaque control as a

therapeutic and preventive approach to modulate the clinical and subgingival pathogenic

alterations in the GAgP descendants. Finally, the third study aimed to test the efficiency of

Triclosan-containing toothpaste as adjunctive therapy to plaque control in children from GAgP

parents.

19

2 ARTICLES

2.1 Heritability of parental periodontal condition and susceptibility in generalized aggressive

periodontitis

Authors:

Mabelle Freitas Monteiro, MS*

Purnima Kumar, Ph.D.#

Khaled Altabtbaei, MS#

Shareef Dabdoub, Ph.D.#

Marcio Zaffalon Casati, Ph.D.*

Karina Gonzales Silvério, Ph.D.*

Enilson Antônio Sallum, Ph.D.*

Francisco Humberto Nociti Junior, Ph.D.*

Renato Corrêa Viana Casarin, Ph.D.*

* Periodontics Division, Piracicaba Dental School, University of Campinas, São Paulo, Brazil

# College of Dentistry, Ohio State University, Columbus, Ohio, United States

20

ABSTRACT

Aggressive Periodontitis (AgP) is a multifactorial disease caused by an unbalance between the host

response and the bacterial challenge and the transmission of characteristics from an affected subject to

their descendants is supposed to be related to disease susceptibility. Thus, this study aimed to evaluate

the clinical, microbiological and inflammatory pattern of AgP parents and their children compared to

healthy families. Fifteen AgP and 15 healthy families with children between 6-12 years old were selected

and clinical evaluation and samples collection was performed. The bacterial DNA of the subgingival

biofilm was extracted, the 16S rRNA was sequenced using the Illumina MiSeq platform and

bioinformatic tools were used to analyze the data. The gingival crevicular fluid was analyzed with the

Luminex MAGPIX technology for the identification of cytokine levels. Children from AgP parents

presented the worst clinical condition as well a more pathogenic microbiome than children from healthy

parents. A strong correlation was observed between the parent microbiome and his child microbiome.

Differences in the cytokines levels were only observed in parents with AgP parent presenting lower

levels of interleukin (IL)-10, IL-17 and interferon-ɣ. Despite no differences in the cytokine levels,

children from AgP parents presented alteration in the host-bacterial interactions and demonstrated a

similar pattern to their parents. In conclusion, the microbiome and the host-bacterial interaction were

altered in AgP parent and their descendants and a strong correlation between the parent and his child

periodontal status was demonstrated, which should be related to disease pathogenesis and to

susceptibility to AgP.

Keywords: periodontitis, family, microbiome, dysbiosis, inflammation

21

INTRODUCTION

Understanding periodontal disease is a challenging task because of its multifactorial nature. The

periodontal environment is colonized by a polymicrobial and complex biofilm that, in a health condition,

is balanced with the immune system (Kinane, Stathopoulou, and Papapanou 2017). However, it is

suggested that once a dysbiotic biofilm is established on the subgingival area, the way the immune

system deal with the local aggression changes, creating an unbalance in the host-bacterial interactions (

Hajishengallis and Lamont 2012). Despite all the efforts to identify the major factors associated to its

pathogenesis, it is still unclear the real impact of specific pathogens or the whole microbiome and the

host inflammatory response triggering the lesions on the periodontal tissue (Könönen and Müller 2014;

Vieira and Albandar 2014).

Most studies focus on investigating the microbial and the inflammatory components of

periodontitis separately, ignoring the clear association between the two aspects. Furthermore, they

generally evaluate both conditions when the disease already exists, identifying the disease aspects, such

as the microbiome composition or a hyperinflammatory condition, instead of the determinant events

prior to disease occurrence. Thus, evaluating diseased subjects can be important to understand the

diseased environment, while the evaluation of a risk population to develop disease allow the

identification of precocious alterations and pathogenic events associated with a periodontal breakdown.

In this context, our research group used the idea of familial aggregation of Aggressive

Periodontitis (AgP), one of the most important characteristics of the most severe case of periodontal

destruction (Armitage 1999), to search for a risk population for periodontitis development and to

understand the events associated to periodontitis etiology and its initiation. The study design of families

with a history of AgP was used previously (Monteiro et al. 2014, 2015), and it was demonstrated that

initial alterations can be identified in early ages and even before any clinical sign of disease. Higher

frequency of detection and concentration of A. actinomycetemcomitans (consider an important

periodontal pathogen of aggressive forms of periodontitis) in saliva and high risk of colonization by

these bacteria in children from AgP families were observed (Monteiro et al. 2014). In addition, high

colonization by this pathogen on the subgingival biofilm, and higher levels of bleeding and probing

depth were demonstrated on children from AgP families which could represent initial alterations

previously to disease diagnose (Monteiro et al. 2015). Despite these differences, these previous studies

focused on some specific microorganisms, suggested as important periodontal pathogens, to understand

the familial component and risk to AgP. Meanwhile, the emerging evidence points to the importance of

the whole microbiome, a dysbiotic community and an unbalance in the host response in disease

pathogenesis. Therefore, it is still necessary a more extensive characterization of this risk population by

investigating the composition of the whole microbiome and the periodontal inflammatory condition of

AgP descendants, as well as the impact of the parents periodontal status on their children periodontal

22

status, focusing mainly in identifying risk factors associated to disease occurrence, to understand the

etiological components associated with the periodontal breakdown and to identify who is the susceptible

group to periodontitis.

Thus, the goals of this study were to evaluate the microbiome, the inflammatory pattern, as well

the relationship between them, on parents with a history of AgP and their children compared to healthy

individuals and their children.

MATERIALS AND METHODS

The study was conducted at Piracicaba Dental School, University of Campinas, Brazil and was

approved by the local Ethical Committee, process 079/2013. The study was designed as an age- and

gender-matched, case-control trial to assess the clinical, microbiological and inflammatory

characteristics of subjects with a history of AgP and their children.

Thirty families were selected and divided into two groups:

- AgP group (n=15): families in which the parents (or at least one of them) present generalized

aggressive periodontitis and at least one child (age ranging from 6–12 years old);

- Health group (n=15): families in which the parents (both of them) present periodontal health and one

child (age ranging from 6–12 years old).

The inclusion criteria were:

- AgP parents (since the study begun in 2014, AgP diagnosis was based on AAP 1999 classification

(Armitage 1999)) i) less than 35 years old at the diagnosis; ii) at least 8 teeth with probing depth (PD)

and clinical attachment level (CAL) > 5mm (with at least 2 sites with PD > 7mm) at diagnosis; iii) at

least 20 teeth in the oral cavity; iv) good systemic health (Taiete et al. 2017).

- Health parents: i) Good systemic health; ii) at least 20 teeth in the oral cavity; iii) absence of periodontal

pockets/gingival sulcus with PD > 4mm; iv) absence of proximal bone loss (Taiete et al. 2017).

- Children: i) to present parents respecting the inclusion criteria for periodontal health or AgP; ii) 6 to

12 years of age at the beginning of the study iii) good systemic health iv) presence of first molars and

central incisors.

The exclusion criteria for all subjects were: i) the use of antibiotics and anti-inflammatory

medication 6 months prior to the study; ii) smoking habits iii) pregnancy or lactation.

All subjects were clinically assessed by a calibrated examiner (MFM - Intra-class

correlation=92% of PD). The clinical parameters evaluated were the following: plaque index – PI

(Ainamo and Bay 1975), gingival index – GI (Ainamo and Bay 1975), probing depth – PD (distance of

23

gingival margin to bottom of periodontal pocket/sulcus), clinical attachment level – CAL (distance from

the cementoenamel junction to the bottom of periodontal pocket/sulcus), bleeding on probing – BoP

(Mühlemann and Son 1971).

Microbiome analysis

Subgingival biofilm was collected from 2 permanent incisors and 2 permanent molars of

children and their parent by the examiner (MFM) at the deepest site of each teeth. Following

supragingival biofilm removal and relative isolation with cotton rolls, a sterile paper point (Nº35) was

inserted into the bottom of the periodontal pocket/gingival sulci for 30s. The paper points were placed

into sterile tubes containing 300 μL of Tris-EDTA 0.5mM and reserved in -20C until laboratory

evaluation.

Plaque samples were removed from the paper points by adding 200 ml of phosphate buffered

saline (PBS) and vortexed for 1 min. The paper points were removed, and DNA isolated using a Qiagen

MiniAmp kit (Valencia, CA) according to the manufacturer’s instructions.

The regions V1-V3 and V4-V5 of the 16S rRNA genes were sequenced. The library generation

was done using an Illumina TruSeq DNA sample preparation kit according to the manufacturer’s

instructions. Genomic DNA was enzymatically sheared yielding an average fragment size of 500 base

pairs. The fragment ends were blunted and adenylated, before ligation of barcodes and sequencing

adaptors. The adaptor-ligated sequences were enriched with 10 cycles of PCR with included Illumina

primers before the libraries are quantified and pooled. Pooled libraries were clustered on the MiSeq, and

300bp paired-end sequencing was performed according to the manufacturer’s protocols. The Illumina

base-calling pipeline was used to process the raw fluorescence images and call sequences. Raw reads

with >10% unknown nucleotides or with >50% low-quality nucleotides (quality value <20) was

discarded.

Processing pipeline:

Analyses were conducted using the QIIME (Caporaso et al. 2010) and PhyloToAST (Dabdoub

et al. 2016). Sequences with an average quality score of 30 over a sliding window of 50bp and length

>200 bp were assigned a taxonomic identity by alignment to the HOMD database (Chen et al. 2010)

using the Blastn algorithm at 99% identity. The chao1 method was used as estimators of alpha diversity,

and differences between alpha diversities group-wise were measured using the Kruskal-Wallis test. The

Morisita-Horn dissimilarity distance matrices were used to estimate beta diversity. Linear Discriminant

Analysis (LDA) was performed on distance matrices, and significance of clustering was interrogated

using Adonis with 999 permutations. LDA plot and confidence ellipses were generated by the R package

ggplot. Core species were identified using Qime’s script (core_microbiome.py) when species were

present in at least 75% of the patients in each group. The Bioconductor package for R, DESeq2, was

used to perform differential expression analysis of the annotated taxa (Love, Huber, and Anders 2014).

24

This function uses a negative binomial distribution of raw counts to estimate between-group differences

while accounting for sampling effort (library size) and dispersion of each category (taxon or functional

gene). p-values were adjusted for multiple testing (FDR < 0.1, FDR-adjusted Wald Test). The similarity

between the parent and his child microbiome were analyzed using the software EstimateS 9.1.0

(http://purl.oclc.org/estimates) to estimate the number of shared species and the β-diversity similarity

between a parent and his child and the SourceTracker 0.9.5 software with QIIME to predict the source

of child microbial community. The bacterial network correlations were determined by significant

pairwise using SparCC pipeline (p<0.01, r>0.75) (Pylro et al. 2014) and network graphs were calculated

in Python (Networkx package) and visualized in Gephi (Bastian, Heymann, and Jacomy 2009).

Cytokine profile assessment using multiplexed bead immunoassay (Luminex)

Gingival crevicular fluid (GCF) was collected from the same sites, after at least 30s of biofilm

collection. The area was isolated, dried and GCF was collected using filter paper strips (Periopaper,

Oraflow, Plainview, NY, USA) into the subgingival area for 15s. The fluid volume was measured with

a calibrated device (Periotron 8000, Oraflow, Plainview, NY, USA). The strips were placed into sterile

tubes containing 100 μL of phosphate-buffered saline (PBS) with 0.05% Tween-20. GCF samples were

immediately stored at -20°C until multiplexed using a bead immunoassay assay. Cytokine levels of

interferon (IFN)-γ, interleukin (IL)-17, IL-10, IL-1β, IL-8, IL-4, IL-6 and tumor necrosis factor (TNF)-

α in GCF were determined using the Sensitivity Human Cytokine 08-plex (Millipore Corporation,

Billerica, MA). Assays were carried out according to the manufacturer’s recommendations using the

MAGpix™ instrument (MiraiBio, Alameda, CA). The samples were collected as a pool and

concentrations were estimated from the standard curve using a five-parameter polynomial equation

using Xponent® software (Millipore, Corporation, Billerica, MA). The mean concentration of each

marker was calculated using the individual as a statistical unit and expressed as pg/ml. The cytokine

concentration was correlated with the bacterial abundance to analyze the bacterial-cytokine network.

The significant pairwise of Spearman’s correlation (p<0.05) was calculated and the network graphs were

visualized with Gephi software.

Data analysis

For the statistical analysis, the gender distribution was measured by the Chi-Square test while

the Student’s t-test was used for age. The differences between groups in the clinical parameters were

evaluated using the Mann-Whitney test due to the non-normal distribution. The inflammatory data were

normalized using the log transformation and the Shapiro-Wilk test was used to test the normality. As

the normal distribution was obtained, the Student’s t-test was used to test the differences between the

Health and AgP groups in parents and children. All tests considered alpha=5%.

25

RESULTS

The demographic and clinical data for both groups are observed in table 1. No differences were

observed regarding the groups’ demographic conditions, demonstrating the aged- and gender-matched

design of this study. The AgP parents demonstrated a higher level of PD, CAL, and BoP when compared

to health parents (p>0.05). Children from AgP parents, similarly to their parents, presented worse

clinical conditions with higher PD and BoP than children from health parents (p>0.05).

Table 1. Demographic and clinical data for parents and children

Parent Children

AgP (n=15) Health (n=15) AgP (n=18) Health (n=18)

Age (years±SD) 36.5±4.32 36.46±3.81 9.7±2.16 9.55±1.97

Gender (n female) 12 12 8 8

PI (%±SD) 34.2±14.1 38.5±16.9 55.7±13.9 50.6±22.1

GI (%±SD) 8.9±2.0 10.5±2.6 24.8±13.2 20±12.1

PD (mm±SD) 4.3±0.6 3.0±0.5 * 3.5±0.47 3.2±0.30*

BoP (%±SD) 35.9±11.7 25.5±12.3 * 37.3±14.4 25.8±12.1 *

CAL (mm±SD) 5.19±1.0 3.0±0.5 * - -

* Represents differences between AgP and Health (p<0.05, Mann-Whitney test). SD – Standard deviation; PI – Plaque Index;

GI – Gingival Index; PD – Probing Depth; BoP – Bleeding on Probing; CAL – Clinical Attachment Level

The cytokines concentration on the GCF for parents and their children for both groups is

demonstrated in table 2. AgP presented lower levels of IL-10, IFN-ɣ, and IL-17 than health parents

(p<0.05). In children, however, no differences were observed in the cytokine levels when the groups

were compared (p>0.05).

Table 2. Concentration (pg/mL±SD) of cytokines in the GCF in parents and children for both groups.

Parent Children

AgP (n=14) Health (n=15) AgP (n=18) Health (n=18)

IFN-y 14.37±14.81 27.91±21.55 * 15.75±16.64 17.16±21.9

IL-10 28.02±21.81 41.28±24.32 * 23.6±23.08 18.43±15.55

IL-17 8.92±7.34 17.33±13.53 * 8.07±7.08 8.65±9.51

IL-1β 49.65±47.9 52.94±32.99 28.46±47.39 11.35±10.59

IL-4 19.09±16.43 23.16±13.98 17.91±17.15 13.16±10.61

IL-6 20.37±15.67 30.44±24.45 19.41±26.03 11.13±9.65

IL-8 1987.71±1313.27 2069.5±1489.38 805.29±556.43 814.87±575.12

TNF-α 20.12±15.17 23.02±15.33 14.45±12.29 10.62±8.08

* Represents differences between AgP and Health (p<0.05, Student’s t-test). SD – Standard deviation; IFN - Interferon; IL –

Interleukin; TNF - Tumor necrosis factor.

26

Figure 1 demonstrated the differences in the microbiome of subgingival biofilm between

groups. Figure 1A represents the LDA of Morisita-Horn dissimilarity index. Two clusters were

observed, one composed by the AgP parents and their children and a second one by the healthy parents

and their children. No statistical difference was demonstrated between the AgP parent and their children

(Adonis, p=0.695) and between the health parent and their children (Adonis, p=0.998), while statistical

differences were demonstrated between AgP and healthy parents (Adonis, p=0.019) and between AgP

and healthy children (Adonis, p=0.01). The Alpha diversity is shown in figure 1B. Children from AgP

group presented a higher α-diversity than children from the healthy group (Mann-Whitney test, p=0.02)

and no differences were observed between parents (Mann-Whitney test, p>0.05). In 1C, D, E, F the

Deseq2 analysis have shown the bacteria differentially abundant between groups. There were

demonstrated on the graphs the fold-change between groups only for differences with the p adjusted

value of 0.05. Interestingly, the differences between aggressive and health groups, both for parent and

children, were higher than the differences between parents and children from the same group. This

suggests a high influence of the parent periodontal microbiome on the composition of their children

microbiome, and the occurrence of precocious alterations in the diversity and the abundance of some

bacteria in children from AgP parents when compared to children from healthy parents. Thus, the AgP

parents are influencing the colonization by a microbiome compatible with the disease in their offspring

since the childhood.

27

28

Figure 1 Differences in microbial diversity. A) β-diversity, LDA of Morisita-Horn Dissimilarity Index. B) α-diversity, Chao1 estimator. C) Bacteria differentially abundant between AgP and

health groups in parents. The red bars represent the bacteria increased in AgP parents and the dark green bars the bacteria increased in healthy parents. D) Bacteria differentially abundant between

AgP and health groups in children. The pink bars represent the bacteria increased in children from AgP parents and the light green bars the bacteria increased in children from healthy parents. E)

Bacteria differentially abundant between parent and children in AgP group. F) Bacteria differentially abundant between parent and children in the health group.

29

The similarities between the parent and their child are in figure 2. The core microbiome of all

groups is represented in 2A. A more abundant core is observed for AgP parents and their children,

suggesting that in the AgP condition a more homogeneous microbiome is observed between the subjects.

Furthermore, a similarity of the core between parent and children from the same group highlights a great

similarity within family members and the influence of the parental oral microbiome on their offspring.

Bacteria such as Filifactor alocis, S. parasanguinis, F. nucleatum, and Selenomonas genera were

exclusive of the AgP core, while P.gingivalis were exclusive for AgP children and T. forsythia was

exclusive for AgP parents, demonstrating that some periodontitis-related bacteria were highly prevalent

in the AgP group and could be related to disease pathogenesis. The figure 2B represents the percentage

of the child species that were shared with their related parent. A higher influence of the parent microbiota

is demonstrated in AgP group where 82% of the species of a child from AgP families is shared with his

parent while approximately 70% of shared species is observed in children from health group (p<0.003).

The β-diversity similarity between a parent and his child was measured using the Morisita-Horn

similarity index (figure 2C) and it reveals that the similarity between a parent and his child is higher

than the similarity between a parent and a non-related child (p=0.0002). In addition, the Source Tracker

analysis (figure 2D) revealed approximately 50% of the entire microbiome of a child comes from the

analyzed parent, with no differences between groups, and that the similarity between parents and their

children microbiome is greater than the similarity between a child and a non-related adult (p=0.0001).

30

Figure 2. The similarity between parents and children microbiome. A) Core microbiome, represent species that were present

in 75% of the subjects of a group. B) Represent the percentage of species of a child from AgP and health groups that were

shared with his related parent. C) Represents the similarity in the β-diversity between pairs of a parent and his child and a

parent and a non-related child. D) Demonstrate the Source Tracker results of the prediction of the child community that comes

from his parent or from a non-related parent.

31

Besides the composition of the biofilm, the study evaluates the correlations observed in the

subgingival environment. The network analysis was used to understand the relationship between the

species in the microbiome and between the microbiome and the inflammatory cytokines, as

demonstrated in figure 3. In 3A-D the correlation between bacteria in the subgingival biofilm was

demonstrated. The healthy parents presented a higher complexity of species correlations than AgP

parents and the same pattern is also observed for children, with children from health parents presenting

more complex correlation than children from aggressive parents. Interestingly, an opposite trend was

demonstrated in the networking between the cytokine’s concentration and the species abundance, where

a higher complexity of correlations was observed in the AgP group that presents the double of cytokine-

species correlations than the health group. (figure 3E-H). For health parents and their children, fewer

correlations were demonstrated between species and cytokines, what could suggest low levels of

aggression on the subgingival environment and equilibrium on the host response. For the AgP group,

on the other hand, intense host-bacterial interactions were demonstrated, suggesting an intense

stimulation of the immune system by the microbiome and an unbalance on the cytokine release.

32

Figure 3. Network analysis of bacteria (A-D). The graphs describe the SparCC correlations between the species abundance in

parents and children from health and AgP groups (r>0.75, p<0.01). Network analysis of host-bacterial interactions (E-H). The

graphs describe the Spearman’s correlation between the cytokine’s concentration and the bacteria abundance (p<0.05). The

green edges represent a positive correlation, while a red edge represents a negative correlation between two nodes. Each node

represents one bacteria or cytokine and the node size is proportional to the number of correlations presented by it.

33

DISCUSSION

The study of a risk population for disease development has been shown to be an important tool

to investigate pathogenesis and risk markers for disease (Fine et al. 2014). Our group has been using the

familial aggregation of AgP (one of its major characteristics) to search for a risk group population for

periodontitis development and to screen for factors possibly associated to the periodontal breakdown

and to the etiology of AgP. Some studies suggest that the familial aggregation of cases is between 40-

50% (Meng et al. 2011; Michalowicz et al. 2000) which increase the chance of finding susceptible

subjects with the study design of parents and their children. Meanwhile, also in this pre-disease status,

this study design was able to show microbial and inflammatory alterations on children from AgP parents

when compared to children from health parents, even in mixed dentition and young age. Particularly for

this study, many differences between AgP and health groups and a strong correlation between parents

and their children subgingival environment were demonstrated, suggesting that these similarities

between parents-child could be a condition associated to susceptibility and disease development.

The influence of parents’ microbiome, especially mothers, in the microbiome composition of

their children is widely described in the literature and it impacts many body sites, such as oral and gut

(Mason et al. 2018; Makino 2018; Ferretti et al. 2018; Shaffer and Lozuponea 2018). It was also

demonstrated that the similarity between environments is higher as higher is the contact between the

microbial communities (Drell et al. 2017). This can support the vertical transmission (transmission from

parents to their children) of microorganisms as an important way of oral microbiota acquisition once

close contact and the hygiene, feeding and social habits were shared between family members. In the

present study, the similarity between parents-children microbiome was demonstrated and the

subgingival microbiological alterations were evident in the AgP group, suggesting a strong impact of

the familiar periodontal status on the oral condition of their children. Regarding the β-diversity, a

different diversity was identified between AgP and health groups, while a similar diversity was observed

between AgP parent and their children and between health parents and their children. In terms of

bacterial abundance, it was possible to observe a great number of differently abundant bacteria when

the groups were compared. Interestingly, the differences between groups (AgP versus Health) were

much higher than in the comparison of parents-children from the same group. Especially when children

from AgP and health groups were compared using the DESeq2 analysis, bacteria belonging to

Capnocytophaga, Leptotrichia, Prevotella, Treponema, Tannerella genera (mainly gram-negatives and

anaerobes genera associated to high pathogenicity of the biofilm (Díaz and Kolenbrander 2009; Wade

2013)) were increased in children form AgP group. All together highlights the great influence of the

parents’ microbiome on the composition of their children subgingival microbiome and that the early

colonization by harmful microorganisms could be crucial for the emergence of a dysbiotic community

related to the periodontal breakdown.

34

The core, the shared species, and the source tracker analysis demonstrated the similarity between

a parent and his child microbiome. It was identified that 82% of the species from children from AgP

parents were also presented in their parents and that the impact of the parent-child similarity is greater

in AgP families than in healthy families. Furthermore, 50% of the child’s microbiome is estimated to

come from the analyzed parent, a higher estimation than when a child and a non-related adult were

compared, reinforcing the importance of bacterial transmission between family members. Other studies

have also demonstrated the influence of the maternal/family oral microbiota on their child’s microbiota,

influencing the transmission of some specific microorganisms and the similarity of the whole

microbiome (Monteiro et al. 2014; Pähkla et al. 2010; Mason et al. 2018; Tamura et al. 2006). Mason

et al (Mason et al. 2018), for example, demonstrated how the core microbiome of a child is highly

influenced by the core microbiome of his mother, which is in agreement with our study that revealed a

high similarity between parents and children, especially in diseased pairs. The core species denote to a

representative feature of the studied population and they play a structural important to the composition

on the microbiome and the functionality of that community (Huse et al. 2012; Turnbaugh et al. 2007;

Bjork et al. 2017). Among the bacteria present on the exclusive core for AgP group it was possible to

identify Filifactor alocis, S. parasanguinis, F. nucleatum, and Selenomonas genera shared between

parent and children, while P.gingivalis was exclusive for AgP children and T. forsythia was exclusive

for AgP parents. These bacteria were usually associated with a more pathogenic environment and more

specifically with aggressive periodontitis. Interestingly, Filifactor alocis and S. parasanguinis, in

association with A. actinomycetemcomitans, participate of a consortium associated to an early bone loss

in adolescents and associated to high risk to aggressive periodontitis (Fine et al. 2013). That way, the

subgingival environment of patients with AgP and their offspring is been driven for disease-associated

periodontal bacteria, which could be determinant for the establishment of a dysbiotic microbiota and to

be related to disease initiation and maintenance.

Regarding the importance of some microorganisms to the formation of a dysbiotic microbiome,

Hajishengallis et al have suggest the importance of P. gingivalis and other keystone pathogens (such as

Aa for aggressive forms of periodontitis) in modify the subgingival environment, subvert the host

immune response and stimulate the transition of an eubiosis to a dysbiosis (Hajishengallis, Darveau, and

Curtis 2012; Hajishengallis and Lamont 2012). The keystone pathogens, even in low abundance in the

environment, can elevate the virulence of the entire community, support the growth of some

“inflammophilic” bacteria and stabilizes the dysbiotic associated microbiota, which could lead to

changes in the host-microbe crosstalk sufficient to initiate chronic, non-resolving inflammatory disease

(Hajishengallis and Lamont 2012; Hajishengallis 2014). Thus, once a dysbiotic microbiome is

established, intense stimulation of the immune system can be a trigger and break the balance between

the host and the microbial aggression, reflecting in the clinical condition.

35

In the present study, the alteration in the microbial composition was accompanied by clinical

inflammation and the more intense correlation between the bacteria presented subgingivally and the

cytokines released in the GCF. Interestingly, when the cytokines were analyzed in conjunction with the

microbial data, using the network analysis, different patterns in the way the host interact with the

subgingival aggressions were demonstrated between health and AgP groups. The co-occurrence network

analysis revealed an intense correlation between the bacteria in healthy parents, where some hubs were

formed, but all of them were intensively connected with positive and negative correlations, suggesting

a high complexity and self-control of the bacteria correlation. This biofilm generated a small number of

correlations with the cytokines in the healthy parents, which could represent a small stimulation of the

inflammatory response. In the AgP condition, on the other hand, the dysbiotic biofilm presented in

disease was poorly connected itself, even though a higher number of cytokines-bacteria correlations

were noted. It could represent that in AgP subjects, the biofilm was able to produce a high stimulation

of the immune system, which could promote an unbalance on the homeostasis between the host and the

aggression and be directly correlated to the periodontal destruction (Hajishengallis and Lamont 2012).

Interestingly, the same pattern was identified in the children. In healthy children, more complex

correlations were demonstrated in the species network while in AgP children more intense host-bacterial

correlations were presented. It is important to highlight that, even though the children from AgP parent

presented fewer complex correlations than their parents, the same pattern could be observed between

parents-children. That way, it was demonstrated that the biofilm composition, as well as its interaction

with the host response, are altered in AgP descendants, and this unbalance between the biofilm

aggression and the inflammatory response, even before the disease occurrence, could be one of the key

points of periodontitis pathogenesis and reinforce the familial aggregation aspect of AgP.

Regarding the clinical data, the subgingival environmental alterations presented in AgP subjects

and their descendants reflected in their clinical condition. The children from AgP parents, even with no

clinical diagnose of attachment loss or bone loss, presented higher PD and BoP. These results

corroborated with previous studies showing alterations in the clinical condition in children from

periodontitis parents (Monteiro et al. 2015; Pähkla et al. 2010). The worst periodontal condition can be

associated with the presence of a dysbiotic microbiome and the more intense stimulation of the

inflammatory response producing initial clinical signs of periodontal disease. At the same time, the

higher PD and BoP could favor the establishment of a more pathogenic subgingival environment by

creating a hyper inflamed and more anaerobic environment and favoring the transition to a dysbiotic

microbiome (Kenney and Ash 1969; Díaz and Kolenbrander 2009; Loesche et al. 1983). Thus, the

clinical data reinforces the microbial results and the host-bacterial interactions identified and

demonstrates how these conditions could interfere in the periodontal health of these subjects.

Although this study points to the early acquisition of a pathogenic microbiome by vertical

transmission and its transition to a dysbiotic community as a possible factor associated with familial

36

aggregation of cases of AgP, it is still necessary to understand if and what host factors could be related

to dysbiosis, and what genetics and behavioral factors can alter the microbial composition and the host

response to the aggression. Nibali et al, for example, demonstrated how a polymorphism in the IL-6

gene can affect the colonization for P.gingivalis and Aa (Nibali et al. 2007), another study correlated

the host’s genetic profile with the occurrence of pathogens associated to periodontal disease (Cavalla et

al. 2018), and some results in mice also suggested that an alteration in the genetic background is able to

produces dysbiosis and periodontitis (Eskan et al. 2012). These results support that the host genetics

also promotes a selective pressure on the microbiota (Hajishengallis 2014), and by altering the host

response or the inflammatory pattern locally it could produce the ecologic conditions necessary for the

outgrowth of specific pathogens and the dysbiosis occurrence (Lamont, Koo, and Hajishengallis 2018).

That way, it is still unclear if the dysbiosis is the cause or the effect of the periodontal disease process

(Hajishengallis 2014). Despite the origin, dysbiosis and inflammation act in positive feedback and once

this cycle is established one can exacerbate the other, to break the subgingival homeostasis and to

produce periodontal disease.

A more pathogenic subgingival environment since childhood can increase the risk for the

periodontal disease development (Höglund Åberg et al. 2014; Shaddox et al. 2012), once it could, in a

long-term, trigger the periodontal breakdown and clinical attachment loss (Kinane, Stathopoulou, and

Papapanou 2017). Thus, the evidence that the parent’s periodontal status can affect the periodontal

condition of their children should be an important tool in the clinic focusing on prevention, early

diagnose and clinical management of this population. The clinician should be aware of the high-risk

population to disease development and should focus the attention on monitoring and early diagnose. The

family members of an AgP subject should be informed about their risk and oriented about hygiene

methods to prevent plaque accumulation. In addition, they should also be screened and periodically

examined, once the early diagnose of incipient lesions make the treatment easy and more predictable

than severe cases (Kinane, Stathopoulou, and Papapanou 2017). This study demonstrated that the

alteration on the subgingival environment happened in early ages, however, it is still unclear in which

phase the acquisition of a more pathogenic microbiome happen, what is the clinical impact of this

microbiota longitudinally and if there is an approach to control this early colonization, which should be

the focus of next studies.

The present study was delineated and developed according to the American Academy of

Periodontology periodontal disease classification of 1999 (Armitage 1999), however, a new

classification was released in 2018 (Caton et al. 2018). The AgP patients selected on our study were

now classified as stage III-IV, grade C periodontitis patients, with no systemic condition associated and

a rapid rate of progression of periodontal lesions. Despite no mention to the familial aggregation were

done on the new classification, the familial aggregation of more severe and rapidly progressive

periodontitis was extensively described in the previous literature (Meng et al. 2011; Nibali et al. 2008;

37

Vieira and Albandar 2014; Albandar 2014; Michalowicz et al. 2000) and this study reinforces the

importance of this feature on future studies and on disease management. Anyhow, this study brings new

ideas about how to understand the periodontal disease and its multifactorial nature, suggesting the

importance of the whole microbiome (instead of some specific bacteria) to characterize the disease, and

the importance of bacterial behavior and host-bacterial interactions on the subgingival environment.

In conclusion, a strong relationship between the parent and their children periodontal condition

was demonstrated and the transmission of that characteristics can be related to the familial aggregation

of severe cases of periodontitis. Furthermore, the microbiome, as such as their relationship to the host

immune system, is altered in diseased parents and their children, what may be associated with

periodontitis pathogenesis.

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2.2 Resilience to Microbial Shift in Children from Periodontitis Parents.

Authors:

Mabelle Freitas Monteiro, MS*

Purnima Kumar, Ph.D.#

Khaled Altabtbaei, MS#

Shareef Dabdoub, Ph.D.#

Marcio Zaffalon Casati, Ph.D.*

Karina Gonzales Silvério, Ph.D.*

Enilson Antônio Sallum, Ph.D.*

Francisco Humberto Nociti Junior, Ph.D.*

Renato Corrêa Viana Casarin, Ph.D.*

* Periodontics Division, Piracicaba Dental School, University of Campinas, São Paulo, Brazil

# College of Dentistry, Ohio State University, Columbus, Ohio, United States

43

ABSTRACT

Background: Pathogenic microbiota acquisition combined with altered host-response during childhood

can increase the risk to periodontitis and can be associated with the familial aggregation of aggressive

periodontitis (AgP). Controlling this microbiome through biofilm control is the landmark to prevent

progressive periodontitis. Thus, this study aimed to evaluate the effect of the plaque control on the

microbiome and the inflammatory response in children from periodontitis-affected parents.

Materials and methods: 18 children (6-12 years old) from GAgP parents and 18 from periodontally

healthy parents were selected. All subjects were periodontally examined and subgingival biofilm and

gingival crevicular fluid (GCF) were collected at baseline and after 3 months of strict plaque control.

Next-generation sequencing and bioinformatic tools were used to evaluate the subgingival microbiome

and the Luminex/MAGPIX platform was used for the inflammatory analysis in GCF.

Results: Linear Discriminant Analysis of Morisita-Horn index demonstrated two massive clusters

separating children from AgP parents from children from healthy parents (Adonis test, p=0.014),

demonstrating a significant impact of parental periodontitis on the microbiome of their descendants. A

more pathogenic microbiome associated with more intense host-bacterial interactions were identified in

children from AgP parents. The dysbiotic microbiome of AgP descendants showed a strong resilience

against shifting after plaque control, maintaining the diversity and the richness of disease-associated

species even after the clinical benefits achieved. In addition, plaque control was not able to alter the

pattern of host-bacterial interaction in the subgingival environment.

Conclusion: Besides the dysbiotic microbiome and the more pathogenic subgingival environment

identified in AgP descendants, children from periodontitis-affected parents presented a strong resilience

to subgingival microbial shifting after strict plaque control, highlighting the higher risk for disease

development.

Keywords: aggressive periodontitis, risk factors, family, microbiome, inflammation

44

INTRODUCTION

The familial aggregation is one of the most important features of Generalized Aggressive

Periodontitis (GAgP), nowadays classified as periodontitis grade C (Caton et al. 2018), a multifactorial

inflammatory disease in the periodontal tissue caused by an unbalance between the subgingival

microbial aggressions and the host response (Lamont et al. 2018). Some studies have demonstrated that

the aggregation of cases in the same family turns around 50% (Michalowicz et al. 2000; Meng et al.

2011). Many aspects, such as transmission of bacteria, genetical and behavioral factors, transmission of

susceptibility factors associated with microbial colonization and host response (Haubek 2010; Könönen

and Müller 2014; Vieira and Albandar 2014), can affect the risk of a subject to develop periodontitis

and the accumulation of susceptibility aspects can increase the accumulation of cases within families.

This way, children from parents affected for GAgP can be considered higher risk population to develop

the disease and the study of this group could be important for understanding the disease etiology, the

susceptibility factors and risk markers for periodontal disease.

Studies have been demonstrating that the periodontal condition of GAgP parents affects the

subgingival environment of their children by creating a more pathogenic oral condition even before the

clinical diagnose of disease and the periodontal destruction (Monteiro et al. 2014; Monteiro et al. 2015;

Monteiro et al. 2019). Higher colonization by A. actinomycetemcomitans (Aa), an established

periodontal pathogen, in saliva (Monteiro et al. 2014) and subgingival environment (Monteiro et al.

2015), as well higher levels of clinical inflammation were identified in children from GAgP parents

when compared to children from health parents (Monteiro et al. 2015). Furthermore, the parents’

microbiome strongly impacts the microbial composition of their offspring and the GAgP associated

subgingival microbiome was associated with dysbiosis, higher colonization for pathogens and more

intense host-bacterial interactions (Monteiro et al. 2019). Thus, this more pathogenic subgingival

environment since childhood could represent a risk to periodontitis development, being involved in

susceptibility and etiology of periodontitis.

These results highlight the importance of the monitoring of this higher risk population and the

need for preventive approaches to control/avoid the establishment of a more pathogenic microbiota,

higher levels of inflammation and the clinical impact of this alterations. The plaque control is the most

widely recommended approach to control the biofilm accumulation and the precocious clinical changes

in the periodontal tissue, especially in children, when an invasive approach usually is not necessary. The

experimental gingivitis studies have demonstrated how the biofilm control is efficient to reduce

gingivitis and establish the periodontal health (Löe et al. 1965; Trombelli et al. 2004), however, the

impact of the supragingival intervention in controlling the dysbiotic subgingival microbiota, specifically

in a higher risk population, is unclear. Therefore, this study was designed to evaluate the efficiency of

45

plaque control in controlling the clinical, microbiological and inflammatory subgingival condition of

children from GAgP parents.

MATERIAL AND METHODS

This study was approved by the local ethical Commit of Piracicaba Dental Scholl, University of

Campinas, Brazil, process 079/2013, where the study was conducted. The study was designed as an age-

and gender-matched, case-control clinical trial.

Eighteen children from GAgP parents and 18 from health parents were selected to compose the

groups:

- GAgP group: children aged 6 to 12 years, presenting the permanent first molars and incisors, with at

least one of the parents diagnosed with GAgP.

- Health group: children aged 6 to 12 years, presenting the permanent first molars and incisors, with

both parents periodontally healthy.

The parents diagnose respected the following criteria:

- GAgP parents: i) Less than 35 years old at the diagnosis; ii) at least 8 teeth with probing depth (PD)

and clinical attachment level (CAL) > 5mm (with at least 2 sites with PD > 7mm) at diagnosis; iii) at

least 20 teeth in the oral cavity; iv) good systemic health v) no smoking habits; vi) been in periodontal

supportive therapy for at least 6 months. (Monteiro et al. 2015).

- Health parents: i) Good systemic health; ii) at least 20 teeth in the oral cavity; iii) absence of periodontal

pockets/gingival sulcus with PD > 4mm; iv) absence of proximal bone loss; v) no smoking habits.

(Monteiro et al. 2015).

The exclusion criteria for children were: i) absence of good systemic health; ii) the use of

antibiotics and anti-inflammatory medication 6 months prior to the study; iii) alteration in the motor

condition that modifies the brushing habits;

All children were included in the strict plaque control program for 3 months. At baseline,

children were clinically evaluated and samples of subgingival biofilm and gingival crevicular fluid

(GCF) were collected. Additionally, they received professional plaque control and oral hygiene

orientation that include brushing with Bass technique 3 times per day and flossing. The monitoring and

the reorientation of hygiene habits were repeated one month later. Three months after the beginning of

plaque control, all children were reassessed for their clinical condition and for sample collections.

The children were clinically assessed for the plaque index – PI (Ainamo and Bay 1975), gingival

index – GI (Ainamo and Bay 1975), probing depth – PD (a distance of gingival margin to the bottom of

46

periodontal pocket/sulcus), bleeding on probing – BoP (Mühlemann and Son 1971). The examination

was performed by an experienced and calibrated examiner (MFM - Intra-class correlation=92% of PPD).

Microbiome analysis

Subgingival biofilm was collected from 2 incisors and 2 first molars of children by the same

examiner (MFM) that carried out the clinical evaluation. The collected sites were the ones with the

deepest PD of one molar and one incisor of superior arcade and one molar and one incisor of the inferior

arcade. Following supragingival biofilm removal and relative isolation with cotton rolls, a sterile paper

point (Nº35) was inserted into the bottom of the periodontal pocket/gingival sulci for 30s. The paper

points were placed into sterile tubes containing 300 μL of Tris-EDTA 0.5mM and reserved in -20C until

laboratory evaluation.

Plaque samples were removed from the paper points by adding 200 ml of phosphate buffered

saline (PBS) and vortexed for 1 minute. The paper points were removed, and DNA isolated using a

Qiagen MiniAmp kit (Valencia, CA) according to the manufacturer’s instructions. The regions V1-V3

and V4-V5 of the 16S rRNA genes were sequenced using the Illumina Miseq platform. The library

generation was done using an Illumina TruSeq DNA sample preparation kit according to the

manufacturer’s instructions. Genomic DNA was enzymatically sheared yielding an average fragment

size of 500 base pairs. The fragment ends were blunted and adenylated, before ligation of barcodes and

sequencing adaptors. The adaptor-ligated sequences were enriched with 10 cycles of PCR with included

Illumina primers before the libraries are quantified and pooled. Pooled libraries were clustered on the

MiSeq, and 300bp paired-end sequencing was performed according to the manufacturer’s protocols.

The Illumina base-calling pipeline was used to process the raw fluorescence images and call sequences.

Raw reads with >10% unknown nucleotides or with >50% low-quality nucleotides (quality value <20)

was discarded.

Processing pipeline:

Analyses were conducted using the QIIME (Caporaso et al. 2010) and PhyloToAST (Dabdoub et al.

2016). Sequences with an average quality score of 30 over a sliding window of 50bp and length >200

bp were assigned a taxonomic identity by alignment to the HOMD database (Chen et al. 2010) using the

Blastn algorithm at 99% identity. The chao1 method was used as estimators of alpha diversity, and

differences between alpha diversities group-wise were measured using the Kruskal-Wallis test. The

Morisita-Horn dissimilarity distance matrices were used to estimate beta diversity. Linear Discriminant

Analysis (LDA) was performed on distance matrices, and significance of clustering was interrogated

using Adonis with 999 permutations. LDA plot and confidence ellipses were generated by the R package

ggplot. Core species were identified using Qime’s script (core_microbiome.py) when species were

present in at least 75% of the patients in each group. The Bioconductor package for R, DESeq2, was

used to perform differential expression analysis of the annotated taxa (Love et al. 2014). This function

47

uses a negative binomial distribution of raw counts to estimate between-group differences while

accounting for sampling effort (library size) and dispersion of each category (taxon or functional gene).

p-values were adjusted for multiple testing (FDR < 0.1, FDR-adjusted Wald Test). The proportion of

the bacterial abundance regarding the gram status and oxygen requirement was calculated using Python

scripts (gramox_calc.py and pct_abd_gramox.py).

Cytokine profile assessment using multiplexed bead immunoassay (Luminex)

Gingival crevicular fluid (GCF) was collected from the same site the subgingival biofilm was

collected by the same examiner (MFM) that carried out the clinical evaluation. After the biofilm

collection, the area was isolated, dried and GCF was collected by placing filter paper strips (Periopaper,

Oraflow, Plainview, NY, USA) into the pocket until the clinician perceived a slight resistance, and then

leaving in place for 15 s. The fluid volume was measured with a calibrated device (Periotron 8000,

Oraflow, Plainview, NY, USA). The strips were placed into sterile tubes containing 100 μL of

phosphate-buffered saline (PBS) with 0.05% Tween-20. GCF samples were immediately stored at -20°C

until multiplexed using a bead immunoassay assay.

Cytokine levels of interleukin (IL)-10, IL-17, IL-1β, IL-8, IL-4, IL-6, interferon (IFN)-γ and

tumor necrosis factor (TNF)-α) in GCF were determined using the Sensitivity Human Cytokine 08-plex

(Millipore Corporation, Billerica, MA). Assays were performed according to the manufacturer’s

recommendations using the MAGpix™ equipment (MiraiBio, Alameda, CA). The samples were

collected as a pool and concentrations were estimated from the standard curve using a five-parameter

polynomial equation using Xponent® software (Millipore, Corporation, Billerica, MA). The calculation

of the mean concentration of each cytokine was performed using the individual as a statistical unit and

was expressed as pg/ml.

For the statistical analysis, the normality was tested with the Shapiro-Wilk test, and the data

were normalized using the log transformation when necessary. Once normal distribution was obtained

the Student’s t-test was used to test the differences in the cytokine’s concentration in the Health and

GAgP groups. The cytokine concentration was correlated with the bacterial abundance data. The

cytokine-bacterial network correlations were determined by significant pairwise using Spearman’s

correlation (p<0.05, ρ>0.6) and the result was visualized in Gephi software (Bastian et al. 2009)

48

RESULTS

The total of 18 children per group participated in the plaque control program and was included

in the analysis. The clinical data is demonstrated in table 1. It is possible to observe that the proposed

therapy was effective in controlling the clinical parameters initially different at baseline. At baseline,

GAgP group presented higher BoP (p=0.012) and PD (p=0.013). The plaque control reduced the PI for

both groups (GAgP p=0.003 and health p<0.001), and a benefit was only observed in the GAgP group

in a reduction in the GI (p=0.003) and PD (p<0.001). After 3 months controlling for plaque, no

differences were observed between groups (p>0.05).

Table 1. Demographic data and clinical parameters of GAgP and Health groups at baseline and after 3 months of

plaque control.

Baseline 3 months

Gender

(% female)

GAgP 44.4 -

Health 44.4 -

Age

(years±SD)

GAgP 9.7±2.16 -

Health 9.55±1.97 -

PI

(%±SD)

GAgP 55.7±13.9 32.8±17.3 *

Health 50.6±22.1 36.4±14.6 *

GI

(%±SD)

GAgP 24.8±13.2 17.3±8.0 $

Health 20±12.1 20.6±13.5

BoP

(%±SD)

GAgP 37.3±14.4 33.9±13.6

Health 25.8±12.1 # 25.3±13.9

PD site

(mm±SD)

GAgP 3.5±0.47 3.0±0.42 $

Health 3.2±0.30 # 3.0±0.42

Symbols indicate statistical differences: between groups # (Student’s T-test), between time points within groups * (Wilcoxon

test) and $ (paired Student’s T-test) (p<0.05).

The inflammatory data is described in table 2. At baseline, no differences were observed

between groups. The plaque control promoted a minimum effect in the cytokine concentration. No

changes were observed in the health group and an increase of IL-8 was observed in GAgP descendants.

At 3 months after plaque control program beginning, no differences were observed between groups.

49

Table 2. Cytokine concentration (pg/µl) in the gingival crevicular fluid for GAgP and Health groups at baseline

and after 3 months of plaque control.

Baseline 3 months

IFNy GAgP 15.75±16.64 12.63±10.17

Health 17.16±21.9 17.03±12.32

IL-10 GAgP 23.6±23.08 19.87±13.63

Health 18.43±15.55 20.99±13.89

IL-17 GAgP 8.07±7.08 8.2±6.96

Health 8.65±9.51 10.22±8.6

IL-1b GAgP 18.29±20.22 15.21±10.81

Health 11.35±10.59 12.02±6.52

IL-4 GAgP 17.91±17.15 15.62±10.05

Health 13.16±10.61 16.88±16.41

IL-6 GAgP 13.54±7.82 17.7±15.56

Health 12.29±9.61 16.2±11.42

IL-8 GAgP 841.68±553.39 1229.15±645.37 *

Health 814.87±575.12 1005.86±657.68

TNF-a GAgP 14.45±12.29 14.55±7.87

Health 10.62±8.08 13.08±8.01

* indicate statistical differences between time points within groups (paired Student’s T-test, p<0.05).

Figure 1 describes the effect of plaque control in the diversity indexes. The Alpha diversity

analysis of the Chao1 estimator (1A) describes the within sample differences between GAgP and health

groups and the reduced effect of control of plaque in change the microbial pattern of this children. The

aggressive group presented a higher diversity than health group in the baseline (p=0.022) and after 3

months of control of plaque (p=0.0003). Furthermore, no difference was observed between baseline and

3 months in health (p=0.97) and GAgP groups (p=0.081). PCoA of Bray-Curtis similarity index (Fig

1B) and LDA of the Morisita-Horn index (Fig 1C) demonstrated the formation of two clusters separating

the GAgP and the Health subjects, however, no separation was observed between the baseline and 3

months samples. There were statistical differences between GAgP and health at baseline and at 3 months

(p<0.05), while no difference was noted between baseline and 3 months in GAgP (Bray-Curtis distances,

p=0.632; Morisita-Horn distances, p=0.484) and health (Bray-Curtis distances, p=0.66; Morisita-Horn

distances, p=0.546). Despite no statistical difference between baseline and 3 months, there was a

graphical difference between time points in health group, which was not observed for GAgP, suggesting

a possible higher effect of the plaque control in health than in GAgP. This way, plaque accumulation

control was not efficient to reduce the subgingival microbial differences between groups after 3 months

50

(p=0.001). The proportion of microorganisms regarding the gram status and oxygen requirements was

represented in figure 1D. No difference was reported at baseline. The plaque control increased the

proportion of gram-positive facultative in the health group (paired Student’s T-test, p=0.02). At 3

months after plaque control, GAgP groups presented a higher proportion of gram-negative anaerobes in

the subgingival biofilm (Mann-Whitney test, p=0.01). In health group, there was a trend of a decrease

of gram-negative anaerobes after plaque control (paired Student’s T-test, p=0.08) and higher levels of

gram-positive facultative compared to GAgP group (Student’s T-test, p=0.08). In 1E, the core

microbiome reinforces the differences between groups and the reduced potential of plaque control to

decrease the differences between GAgP and Health groups. GAgP group presented a high number of

core exclusive species and bacteria such as F. alocis, S parasanguinis, F. nucleatum, P. gingivalis, and

T. forsythia (at 3 months), frequently correlated to periodontal disease, were described as exclusive for

the GAgP. That way, the diversity results indicate a strong effect of the family periodontal status on the

composition of the microbiome and resilience in the established microbiome diversity, reinforcing the

impact of initial colonization and host factors in the composition of the microbiome.

51

Figure 1 Differences in microbial diversity between groups and time points. A) α-diversity, Chao1 estimator. B) β-diversity,

represented in the PCoA of Bray-Curtis dissimilarity index. C) β-diversity, represented in the LDA of Morisita-Horn

Dissimilarity Index D) Bacteria relative abundance regarding the oxygen requirement and the gram status calculated for each

group and time point. * indicates statistical differences between groups and # indicates differences between time points within

groups (p<0.05). E) Core microbiome, representing species presented in at least 75% of the subjects of a group.

52

The DESeq2 were used to identify the bacteria differentially abundance between groups (figure

2). The results were expressed in fold change and the p-value was corrected for multiple comparisons.

The group's comparison at baseline (2A) demonstrated 98 species differentially expressed (84 increased

in GAgP children). It was possible to observe a higher abundance of Capnocytophaga, Haemophilus,

Leptotrichia, Prevotella, Tannerella, TM7, Treponema and Veillonella genera, mainly gram-negatives

and anaerobes and associated to a more pathogenic environment, were more abundant in GAgP. The

differences between time points were demonstrated in B and C. The plaque control changed 30 species

in health and 44 species in GAgP, changing species from diverse genera. It is important to highlight that

the abundance differences were higher when comparing the GAgP and the health groups than when

comparing the effect of plaque control (baseline to 3 months), suggesting that the influence of familial

Figure 2 Differential abundance analysis represented in fold change A) Bacteria differentially abundant between GAgP and

Health groups at baseline. The red bars represent the bacteria increased in GAgP group and the dark blue bars the bacteria

increased in the health group. B) Bacteria differentially abundant between baseline and 3 months in Health group. C) Bacteria

differentially abundant between baseline and 3 months in GAgP group. D) Bacteria differentially abundant between GAgP and

Health groups at 3 months after the plaque control.

53

periodontal status in the composition of the microbiome is more important than the plaque control when

the biofilm is already established. Interestingly, in the species-level analysis, the plaque control

accentuated the differences between children from health and GAgP groups at 3 months (2D) and 162

species were found to be differentially expressed, with 144 more abundant in GAgP. Most of this species

increased in GAgP were representative of gram-negative and anaerobes genera similarly as the baseline.

Additionally, important periodontal pathogens, such as A. actinomycetemcomitans, Filifactor alocis,

Streptococcus parasanguinis, Fusobacterium nucleatum, Porphyromonas gingivalis, Treponema

denticola, Tannerella forsythia, were increased in GAgP at 3 months.

Regarding the inflammatory results, although no differences on the cytokines levels were

observed between groups (Mann-Whitney test, p>0.05), the correlation analysis between the microbial

data and the cytokines showed a clearly different pattern of host-bacterial interactions between familial

disease history (figure 3). Considering only strong correlations (ρ>0.6), a healthy group at baseline

presented a hub of interactions between IL-8 and species, and strong correlations were observed between

cytokine-cytokine. On the other hand, the GAgP children at baseline were characterized for a higher

number of correlations between bacteria and cytokines, most of that negative correlations, and a reduced

number of strong correlations between cytokine-cytokine, what suggests more intense relationship

between the microbiome and the host response and a less orchestrated relationship between the proteins

responsible for the initial inflammatory response on the subgingival environment. The plaque control

promoted a reduction in the number of species-cytokine correlation in both groups, however, it was not

able to change the pattern of host-bacterial interactions demonstrated at baseline. For the health group,

the strong correlations between all cytokines was maintained and, in the GAgP group, despite an

increase on the number of cytokine-cytokine correlations, the cytokine-species correlation was still

strong, demonstrating the effect of microbiome and inflammation on each other and possibly higher

levels of aggression on the periodontal tissue of children from GAgP parents.

54

Figure 3. Network analysis of host-bacterial interactions. The graphs describe the Spearman’s correlation between the

cytokine’s concentration and the bacteria abundance (p<0.05, ρ>0.6). The green edges represent a positive correlation, while a

red edge represents a negative correlation between two nodes. Each node represents one bacteria or cytokine and the node size

is proportional to the number of correlations presented by it.

DISCUSSION

Periodontitis is a complex disease and understand its etiological and pathogenic aspects, as well

the factor associated with susceptibility to disease, is essential for the correct management and specific

treatment of the affected subjects (Kinane et al. 2017). The study of a risk population to develop the

disease, as is the case of descendants of GAgP patients, have been demonstrated to be an interesting

approach for the comprehension of periodontitis. It allowed the identification of periodontal conditions

altered previously to the periodontal breakdown, which could be associated to susceptibility to disease

and the periodontitis pathogenesis (Monteiro et al. 2014; Monteiro et al. 2015; Monteiro et al. 2019).

The present study, besides demonstrating subgingival alterations as consequence of familial origin and

identifying factors associated to risk to disease, demonstrated that the plaque control regimen proposed

in this study, even controlling the clinical parameters, was not enough to change the more pathogenic

subgingival environment in the risk population, suggesting a strong intrinsic factor in the determination

of the periodontal condition.

55

The baseline condition demonstrated in this study corroborate with a previous analysis that

identified a negative effect of the periodontal condition of GAgP families in their offspring (Monteiro

et al. 2019). In the present study, children from GAgP parents presented higher PD and BoP, and the

worst clinical condition was related to subgingival dysbiosis, higher frequency of pathogens in the

biofilm and the more intense correlation between the microbiome and the inflammatory condition. These

periodontal characteristics are compatible with the most recent explanation of periodontal disease

pathogenesis that suggested that the dysbiosis associated with alterations in the host-bacterial

interactions can produce an unbalance between the microbial aggression and the host immune response,

causing the periodontal breakdown (Lamont, 2018). Thus, the recent findings suggest that this

characteristics can increase the risk to GAgP descendants to also develop periodontitis and the

comprehension of this pathogenic environment can be the key point to understand the disease

susceptibility. Furthermore, the comprehension of risk reinforces the necessity of monitoring, preventive

activities and more specific therapeutic approaches to the population.

The plaque control and the oral hygiene instruction are the first choices and the most

recommended therapy to prevent/control conditions associated to plaque accumulation in the oral cavity,

especially in children during mixed dentition (Hilgert et al. 2017; Kinane et al. 2017). Controlling the

plaque accumulation and gingival inflammation is a non-invasive approach, essential to achieve oral

health in a long-term period (Lang et al. 2009). The benefits of plaque removal for the periodontal

healthy were confirmed by the experimental gingivitis studies, which demonstrated that the complete

removal of biofilm from the gingival margin is enough to control the gingival inflammation and

obtaining the clinical healthy gingiva (Löe et al. 1965; Trombelli et al. 2004). The clinical beneficial

effect of plaque removal and tooth brushing were also achieved in this study. It was able to reduce the

plaque accumulation for all children and an additional reduction of PD and GI in the GAgP group,

eliminating the clinical differences between groups. However, even controlling the clinical alterations,

the subgingival changes observed in the study were minimal, and they were not enough to modify the

microbial pattern presented at baseline. The plaque control does not affect the alpha and the beta

diversity of both groups and the core microbiome, composed by species highly frequent and with a

probable structural and functional importance to the microbial community (Turnbaugh et al. 2007; Huse

et al. 2012; Bjork et al. 2017), was maintained from baseline to 3 months of plaque control. Interestingly,

in terms of bacteria differentially abundant, the familial origin could be considered dominant once

plaque control induced only minor differences, highlighting the strong and important role of the familial

background and the host factors in the determination of the oral microbiota. In addition, a reduced effect

in the host-bacterial interaction was observed. Both groups presented a reduction in the number of

correlations between the bacterial abundance and the cytokine concentration, however, the alterations

were not enough to change the patterns observed at baseline. In GAgP group, a higher number of

correlation species-cytokines were observed, suggesting higher levels of aggression in the subgingival

56

environment. Otherwise, in a healthy group, and a strong correlation between cytokines were observed,

suggesting a balance between the molecules associated with periodontal inflammation. Thus, the plaque

control was not effective to change the disease-associated pattern presented by GAgP descendants,

maintaining the pathogenic subgingival environment and the risk associated with it.

Meanwhile, although the subgingival condition appears to be resistant to change, the plaque

control could promote some specific alterations. Plaque and gingival indexes reduction after 3 months

of strict control led to more effects in the health group than in the GAgP group. The relative abundance

analysis of species regarding their gram status and oxygen requirements revealed an increase in the

proportion of gram-positive facultative in the health group after plaque control. Moreover, a trend of

reduction in the proportion of gram-negative anaerobes was also observed in health, while no alteration

was identified in the GAgP group. The LDA graph (figure 2C) also suggested a higher influence of

plaque control in the health groups by demonstrating a slight separation in the microbiome of health

baseline and 3 months samples while the GAgP samples were all clustered together independent of the

hygiene intervention. Therefore, these results suggest that the disease-associated

microbiome/subgingival environment of GAgP descendants is more resilient to shift, once minimal

alterations in the microbial composition were achieved after biofilm removal. Microbial resilience is the

property of the microbial community that determines how fast, and to what extent, it will recover the

initial taxonomic and functional structure after perturbation (Holling 1973). This aspect is an ecological

property of the microbiomes, both in a symbiotic and in a dysbiotic state, that achieving the ideal

environmental conditions and equilibrium in the metabolic, nutritional and spatial requirements, get

more resistant to external interventions (Sommer et al. 2017). In this context the early acquisition of an

unhealthy and dysbiotic community with a high resilience potential during the childhood (a vulnerable

period for community acquisition), as suggested in the present study, may contribute to periodontitis

occurrence, at the same way it contributes to the chronicity of other dysbiosis-associated diseases (e.g.

obesity, metabolic syndrome) (Sommer et al. 2017). Furthermore, the genetic pressure in the

microbiome and the host factors can also be determinants to the maintenance of the microbiome and the

ecological conditions in GAgP subjects/descendants (Nibali et al. 2007; Nibali et al. 2013; Lamont et

al. 2018), reducing the importance of the decrease of plaque accumulation on the composition of the

community.

Despite the reduced effect in the microbial community, the plaque control was responsible for

increasing the differences between groups, probably a result of the changes demonstrated in the health

condition. The DESeq2 results of the comparison between groups at 3 months revealed an increase in

the number of bacteria differentially abundant, 144 were more abundant in GAgP and all pathobionts

linked to periodontal disease or to risk to future periodontal breakdown, such as A.

actinomycetemcomitans, Filifactor alocis, Streptococcus parasanguinis, Treponema denticola,

Fusobacterium nucleatum, Porphyromonas gingivalis, Tannerella forsythia were more abundant in

57

children from periodontitis parents. More specifically, A. actinomycetemcomitans, F. alocis and S.

parasanguinis, bacteria identified as a consortium related to risk and future bone loss in adolescents

(Fine et al. 2013), were identified as more abundant and as part of the core microbiome in GAgP.

Furthermore, the proportion of gram-negative and anaerobes identified in GAgP was higher than in

health after plaque control. The 3 months results highlighted the dysbiosis of the disease-associated

microbiome and reinforce the idea that the presence of this pathogenic periodontal conditions since

childhood can be a risk and can be related to susceptibility and the familial aspects of the most severe

cases of periodontitis. The dysbiosis and the higher presence of pathobionts can be crucial for the

intensification of the microbial aggressions and the amplification of the local inflammatory response,

breaking of the periodontal homeostasis and producing periodontal destruction (Lamont et al. 2018).

This study demonstrated that the control for plaque accumulation, the most used preventive

approach to prevent an oral condition associated to biofilm, is not enough to control the higher

pathogenicity of the subgingival environment in a risk population to periodontitis development.

Additionally, it underlines that the familiar effect on the microbial condition is higher than the impact

of plaque control, suggesting that the periodontal pathogenesis is more related to host/colonization

factors than just the absence of ideal oral hygiene. Thus, the present findings should be applied to the

dental clinic to allow the appropriate management of the population with increased risk to periodontitis.

The GAP patient should be aware of the risk to their relatives to also develop the disease and of the need

for periodic monitoring. The clinicians should assess risk and the familial component of periodontal

disease during the clinical evaluation and they should include the risk population in a rigid monitoring

and preventive activities focusing in controlling the precocious alteration and in the early diagnose.

Moreover, more effective approaches should be proposed to control the dysbiosis and the early

colonization for pathogenic microorganisms, as well to modulate the host response to the microbial

aggression, once the comprehension of the community aspect allows a specific intervention in the

disease drivers and in the microbial resilience (Rosier et al. 2018). This study offers an insight about the

identification of a risk population and susceptibility for periodontitis, besides the comprehension of

pathogenic aspects of periodontal destruction, however, it is still necessary a long-term evaluation of

the studied group to understand the real impact of the observed alterations and the identification of

etiological components and biomarker for periodontal disease.

In conclusion, besides the dysbiotic microbiome and the more pathogenic subgingival

environment identified in GAgP descendants, children from periodontitis-affected parents presented a

strong resilience to subgingival microbial shifting after strict plaque control, highlighting the higher risk

for disease development.

58

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2.3 Triclosan as an adjunct therapy to plaque control in children from periodontitis families.

A crossover clinical trial.

Authors:

Mabelle Freitas Monteiro, MS*

Henrique Tonelli, DDS*

Aurélio Amorim Reis, DDS*

Marcio Zaffalon Casati, PhD*

Karina Gonzales Silvério, PhD*

Enilson Antônio Sallum, PhD*

Francisco Humberto Nociti Junior, PhD*

Renato Corrêa Viana Casarin, PhD*

* Division of Periodontics, Piracicaba Dental School, University of Campinas, São Paulo, Brazil - Address: Av.

Limeira, 901 - Areião, Piracicaba - SP, Brazil; Zipcode: 13414-903

Submitted to Clinical Oral Investigation as documented in Supplement 3

Correspondence author:

Renato Corrêa Viana Casarin, Division of Periodontics, Piracicaba Dental School, University of

Campinas

Phone: +55 19 2106-5394 Email: casarinrcv@yahoo.com.br

Acknowledgment:

Acknowledgments to São Paulo Research Foundation for financial support with a scholarship (process

2016/20361-6). The authors declare that there is no conflict of interest in this study.

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Abstract

Objectives: Studies have demonstrated that children from Aggressive Periodontitis (AgP) parents

presented precocious alterations in their periodontal condition. This study aimed to evaluate the effect

of Triclosan toothpaste to modulate the clinical and subgingival condition in children from AgP parents.

Methods: 15 children from AgP parents and 15 from periodontally healthy parents were included in this

cross-over placebo study. Children were randomly allocated into Triclosan or Placebo therapy, using

selected toothpaste for 45 days. After 15 days of wash-out, groups were crossed changing the used

toothpaste. In each phase, clinical examination and saliva, crevicular gingival fluid (GCF) and

subgingival biofilm collection were performed at baseline and 45 days. GCF cytokines’ levels were

analyzed by Luminex/MAGpix platform and subgingival and salivary periodontal pathogens’ levels by

qPCR.

Results: At baseline, AgP group presented higher gingival index (GI), plaque index (PI), and bleeding

on probing (BoP), higher A. actinomycetemcomitans (Aa) abundance in saliva and subgingival biofilm,

and lower levels of INF-ɣ, IL-17, IL-4 in GCF. Placebo therapy only reduced PI in both groups.

Triclosan toothpaste reduced PI and GI in both groups. Triclosan promoted the reduction of BoP and

PD (probing depth), Aa salivary and IL-1β levels in AgP group. In Health group, Triclosan reduced

INF-ɣ and IL-4 concentration.

Conclusion: Triclosan toothpaste demonstrated to be more effective than placebo toothpaste to control

the periodontal condition in children from AgP parents, by reducing the BoP, PD, salivary Aa, and IL-

1β.

Clinical Relevance: Triclosan toothpaste can improve oral conditions in higher risk population for AgP.

Keywords: Aggressive periodontitis, family, triclosan, cytokines, Aggregatibacter

actinomycetemcomitans

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Introduction

Generalized aggressive periodontitis (GAgP) is a multifactorial disease caused by an unbalance

between the microbial challenge and the host response, in which an exacerbation of the inflammatory

process in the periodontium stimulate the periodontal breakdown and bone loss [1]. One important

characteristic of GAgP is the familial aggregation [2], and the sharing of susceptibility factors within

family members, either by the transmission of microorganisms, genetic factors and/or behavioral aspects

[3], has been influencing the prevalence around 50% of cases between family members [2]. Thus,

investigating this highly affected group could be an important approach to understand etiopathogenesis,

the identification of risk factors and prevention of periodontal disease.

Precocious alterations were demonstrated in children from parents affected by GAgP when they

were compared to children from healthy parents and this condition was observed even before the clinical

diagnose of periodontitis or bone loss [4, 5]. Children from GAgP parents have presented a higher

frequency of detection and concentration of A. actinomycetemcomitans (Aa) in saliva when compared

to children from both parents periodontally healthy and a child has 16 times more risk to be colonized

by Aa when a parent is Aa positive [4]. Furthermore, children from GAgP parents presented higher

plaque index, gingival index and probing depth and higher colonization by Aa in the subgingival

environment, with Aa is been highly correlated to gingival bleeding [5]. In addition, initial data about

inflammatory condition on the gingival crevicular fluid of those children demonstrated an unbalance on

the cytokines’ levels and on the host response pathways [6], reinforcing the idea that initial changes can

be observed precociously even before the clinical signs of periodontal breakdown, that those alterations

could represent a high risk to that population and that something should be done to control this high risk.

The most widely used approach to control the periodontal disease is to prevent the biofilm

accumulation, the colonization by more pathogenic microorganisms and establish a less inflamed

subgingival environment [7]. In addition to that, the use of antimicrobial and anti-inflammatory agents

in association with the plaque control could be an efficient method to improve the clinical and

subgingival environment alterations. The triclosan-containing toothpaste has demonstrated good

antimicrobial and anti-inflammatory properties, being efficient in improving the periodontal parameters

[8–10], reducing pathogens levels, such as Aa and P. gingivalis[11], and in modulating the inflammatory

response in vitro and in vivo [10, 12]. Moreover, the toothpaste with Triclosan is an easy-to-use and

secure form of application and would represent no substantial change in the children habits, facilitating

the accessibility and compliance. Thus, this study aimed to evaluate the efficiency of toothpaste with

triclosan to modulate clinical, microbiological and inflammatory conditions in the oral cavity of children

from GAgP families when compared to children from healthy families.

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Materials and Method

Study design

This study was developed at Piracicaba Dental School, University of Campinas, Brazil, with the

approval of local ethical Commit, process 103/2015 and it was registered at ClinicalTrials.gov with the

identifier NCT03642353. This study is a cross-over placebo-controlled clinical trial. Informed consent

was obtained from all individual participants included in the study.

Patient selection

Patients with a history of generalized aggressive periodontitis (GAgP) in supportive periodontal

therapy were accessed about the inclusion of their children in the study. After the selection of the GAgP

group, periodontally healthy families (both parents should be periodontally healthy) were accessed about

the inclusion of their children on the study. GAgP parents were selected respecting the following

inclusion criteria previously described in the literature: i) Less than 35 years of age at the time of

diagnosis; ii) at least 8 teeth with probing depth (PD) and clinical attachment level (CAL) > 5mm (with

at least 2 sites with PD > 7mm) at diagnosis; iii) at least 20 teeth in the oral cavity; iv) good systemic

health. The healthy parents were selected following the inclusion criteria: i) Good systemic health; ii) at

least 20 teeth in the oral cavity; iii) absence of periodontal pockets/gingival sulcus with PD > 4mm; iv)

absence of proximal bone loss [5].

The inclusion criteria for children were: i) to present parents that respect the inclusion criteria

for periodontal health or GAgP; ii) to present between 6 and 12 years old at the moment the study begun

iii) to present good systemic health. The exclusion criteria for children were: i) the use of antibiotics and

anti-inflammatory medication 6 months prior the study; ii) any alteration in the child's motor condition

that would affect the performance of oral hygiene procedures.

Fifteen children from GAgP parents and 15 children from both parents periodontally healthy

were selected to participate in this study by the researcher MFM.

Groups

Simple randomization between Triclosan and placebo was done, by the researcher RCVC. The

toothpaste was named as A (Triclosan) and B (placebo), and the toothpaste packs were only identified

by the letters. A computer-generated randomization list was used to randomly allocate the toothpaste A

or B to each child from GAgP and Health groups. That way, neither the children nor the operator

responsible for conducting the oral hygiene instruction and clinical examination known in which

toothpaste protocol they were included.

The study design was described in figure 1. All children were included in an initial period of 15

days to standardize oral hygiene procedures. They have received prophylaxis, calculus removal if

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necessary, oral hygiene instructions and they were oriented to use only the toothpaste and toothbrush

given by the research team. The children used the Bass technique to brush their teeth three times a day,

received training to floss each time they brushed, and they were oriented to do not use other hygiene

procedures or use any kind of mouthwash during the study. During this period, they used the placebo

toothpaste.

Figure 1 Study design flowchart.

After that, the children from GAgP and Health groups were divided into two subgroups,

respecting the randomization, one using the Triclosan (0.3% triclosan/2.0% copolymer/1450 ppm

fluoride toothpaste) and one using placebo (1450 ppm fluoride toothpaste). This way, the following

groups were obtained:

- Health-Triclosan group: children from periodontally healthy parents using triclosan toothpaste during

oral hygiene;

- Health-Placebo group: children from periodontally healthy using placebo toothpaste during oral

hygiene;

- GAgP-Triclosan group: children from GAgP parents using Triclosan toothpaste during oral hygiene;

- GAgP-Placebo group: children from GAgP parents using placebo toothpaste during oral hygiene;

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Each group used the respective toothpaste for 45 days. During these 45 days, they attend to 4

visits: a baseline visit for clinical evaluation, sample collection and hygiene instruction; a 15 and 30-

days visit to reinforce the hygiene instruction, motivation and to monitor the adherence to treatment;

and a 45-days visit to reevaluate the clinical status and sample collection. Posteriorly, all children were

included in a wash-out period for 15 days using only the placebo toothpaste. Then, the groups were

rearranged inverting the toothpaste they have used initially. This way, the subjects from Health-

Triclosan were reallocated in Health-Placebo, the subjects from Health-Placebo were reallocated in

Health-Triclosan, the subjects from GAgP-Triclosan were reallocated in GAgP-Placebo, and the ones

from GAgP-Placebo were included in GAgP-Triclosan, repeating the procedures described before for

more 45 days.

Clinical Evaluation

The clinical procedures and evaluation were performed by an experienced and calibrated

clinician (MFM), blinded for the subgroup’s allocation. The measurements were done at baseline and

45 days of Triclosan and placebo use, before and after the groups been crossed. The evaluated clinical

parameters were: i) plaque index – PI [13]; ii) gingival index – GI [13]; iii) bleeding on probing – BoP

[14]; iv) probing depth – PD (distance between the gingival margin to the bottom of the periodontal

pocket or sulcus); and they were measured 6 sites per tooth.

Microbiological evaluation

Saliva and subgingival biofilm were used for microbiological evaluation and were collected at

baseline and 45 days of Triclosan/Placebo toothpaste use. Unstimulated whole saliva was collected with

sterile Falcon tubes over 5 min and stored into Eppendorf tube, which was frozen at -20° C until the

laboratory evaluation. The subgingival biofilm was collected with one sterile paper point per site (nº 35)

from 2 central incisors and 2 first molar of each child and stored as a pool. The sites collected were the

ones with the deepest PD of one molar and one incisor of the superior arcade and one molar and one

incisor of the inferior arcade. After the supragingival biofilm removal and relative isolation with cotton

rolls, the paper point was inserted for 30 s in the periodontal pocket/gingival sulcus. The paper points

were stored in an Eppendorf with 300 µl of Tris-EDTA 0.5 mM and frozen at -20° C until the laboratory

evaluation.

The abundance of Porphyromonas gingivalis (Pg), Aggregatibacter actinomycetemcomitans

(Aa), and Tannerella forsythia (Tf) were measured using a quantitative PCR (qPCR) technique and

specific primers, as reported by Casarin et al [15]. The DNA was isolated from saliva and subgingival

biofilm. A real-time PCR was performed using the FastStart DNA Master SYBR Green kit (Roche

Diagnostics GmbH, Mannheim, Germany). The concentration of the DNA used in each run was 10

ng/ml. The determination of the DNA genome copies in the controls was based on the genome size of

each bacteria and the mean weight of one nucleotide pair.

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Inflammatory evaluation

Gingival crevicular fluid (GCF) was collected as a pool from the same sites the subgingival

biofilm was collected. After the subgingival biofilm was collected, the area was isolated, dried and GCF

was collected by placing filter paper strips (Periopaper, Oraflow, Plainview, NY, USA) into the pocket

until the clinician perceived a slight resistance, and then leaving in place for 15 s. The fluid volume was

measured with a calibrated device (Periotron 8000, Oraflow, Plainview, NY, USA). The strips were

placed into sterile tubes containing 100 μL of phosphate-buffered saline (PBS) with 0.05% Tween-20.

GCF samples were immediately stored at -20 °C until multiplexed using a bead immunoassay assay.

Cytokine levels of interferon (IFN)-γ, interleukin (IL)-10, IL-17, IL-1β, IL-4, and tumor

necrosis factor (TNF)-α) in GCF were determined using the Sensitivity Human Cytokine 08-plex

(Millipore Corporation, Billerica, MA). Assays were carried out according to the manufacturer’s

recommendations using the MAGpix™ instrument (MiraiBio, Alameda, CA). The sample’s

concentration was estimated from the standard curve using a five-parameter polynomial equation using

Xponent® software (Millipore, Corporation, Billerica, MA). The mean concentration of each marker

was calculated using the individual as a statistical unit and expressed as pg/ml.

Statistical analysis

Sample size calculation was done considering alpha=5%, a power level of 80% and effect size

of 1.0 (based on Cagetti et al [16]), a minimum population per arm was 11. In view of possible drop-

outs, 15 children were included per arm. All 30 children completed the plaque program, and all analysis

(clinical, microbiological and inflammatory) were done with 15 patients per group (n=30), with no

changes on the methods or on the randomization, allowing a per-protocol analysis. The Shapiro-Wilk

test was used to analyze the data normality. For gender distribution and age, Fisher’s exact and Student’s

t-tests were used respectively. For the clinical data analysis, non-paired (for groups comparison) and

paired (for timepoints comparisons) tests were performed depending on the normality. Moreover, in the

cytokine’s levels and in the bacterial concentration, due to the non-normal distribution, Mann-Whitney

and Wilcoxon non-parametric tests were used for inter- and intra-group analysis. All tests considered

alpha=5% and were done by a blinded statistician.

Results

Table 1 describes the demographic data and the baseline condition of patients divided per group.

A similar age and gender group composition demonstrated the homogeneity of the studied population.

Despite the same demographic characteristics, a different clinical condition could be observed in

children from GAgP parents, with higher PI, GI, and BoP (p<0.05). Higher abundance of Aa in saliva

and in the subgingival biofilm were observed in children from GAgP group (p<0.05). In addition, a

reduced level of IFN-ɣ, IL-4, and IL-17 were observed in the GAgP group (p<0.05).

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Table 1 Demographic, clinical, microbiological and inflammatory condition at baseline in children from

Health and GAgP groups.

GAgP (n=15) Health (n=15)

Gender (%fem) 60% 40%

Age (years±SD) 9.2±1.7 9.0±2.0

PI (%±SD) 36.2±14.7 & 25.1±13.1

GI (%±SD) 10.4±4.7 & 7.5±5.3

PD (mm±SD) 1.7±0.4 1.6±0.6

BoP (%±SD) 25.3±7.0 & 17.9±11.4

A.actinomycetemcomitans 3.1±2.8 * 1.6±2.2

Saliva

(log10±SD) P. gingivalis 1.4±1.0 1.3±1.1

T. forsythia 1.6±1.3 2.0±1.1

A.actinomycetemcomitans 2.6±2.0 * 1.7±1.7

Subgingival biofilm

(log10±SD)

P. gingivalis 1.1±1.7 0.3±1.1

T. forsythia 0.1±0.5 0±0

Gingival Crevicular Fluid

(pg/ml±SD)

TNF-α 6.0±4.6 13.1±22.1

IL-10 2.3±1.4 3.4±2.0

IL-1β 1376.4±1549.4 1458.1±1685.3

IFN-ɣ 58.9±36.3 * 137.4±141.0

IL-4 13.0±7.0 * 22.1±12.8

IL-17 10.8±6.11 * 17.8±11.4

Symbols indicate statistical difference between groups (&T -Student test and *Mann-Whitney test, p<0.05). PI – Plaque Index;

GI – Gingival Index; PD –Probing Depth; BoP – Bleeding on probing; SD – Standard deviation; TNF - Tumor necrosis factor;

IL – Interleukin; INF – Interferon.

Table 2 demonstrates the effect of plaque control in all studied population, reducing the PI in

45 days for both groups and both treatments (p<0.05). Besides plaque index reduction, Triclosan

toothpaste demonstrated to be efficient in reducing the GI for GAgP and Health groups (p<0.05). In the

GAgP group, the use of triclosan toothpaste additionally improved the BoP and the PD (p<0.05) after

45 days of use.

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Table 2 Clinical data of baseline and 45 days after the use of Triclosan and Placebo toothpaste per

group.

PI (%±SD) GI (%±SD) PD (mm±SD) BoP

(%±SD)

GAgP

Triclosan Baseline 30.8±15.8% 9.6±5.2% 1.8±0.3 26.4±11.4%

45 days 24.7±12.0%* 7.1±4.1%* 1.5±0.4# 22.8±8.9%*

Placebo Baseline 34.1±17.0% 10.6±5.6% 1.7±0.4 24.2±12.5%

45 days 27.7±11.1%* 10.4±8.1% 1.6±0.6 25.5±10.9%

Health

Triclosan Baseline 26.5±14.2% 8.4±5.2% 1.6±0.6 17.6±13.4%

45 days 20.1±13.4%* 5.3±4.4%* 1.6±0.6 17.5±9.5%

Placebo Baseline 26.0±12.9% 6.5±5.8% 1.6±0.6 18.6±10.2%

45 days 22.1±11.7%* 6.6±5.3% 1.3±0.8 19.1±15.3%

Symbols indicate statistical difference intragroup per treatment (#ANOVA two-way t-test and *Wilcoxon test,

p<0.05). PI – Plaque Index; GI – Gingival Index; PD – Probing Depth; BoP – Bleeding on probing; SD – Standard

deviation;

The levels of Aa, Pg, and Tf in saliva and subgingival biofilm before and after the plaque control

is observed in figure 2. In saliva, the plaque control with Triclosan toothpaste was able to reduce

significantly the concentration of Aa in children from GAgP parents (p<0.05), while no other difference

was observed for the other groups and other bacteria. Regarding the bacterial concentration in the

subgingival biofilm, the plaque control was not efficient to change the bacterial levels with any

toothpaste in both groups (p>0.05).

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Figure 2 Effect of plaque control using placebo and triclosan toothpaste in the bacterial concentration

in saliva and subgingival biofilm. * demonstrate statistical differences between timepoints, Wilcoxon test

(p<0.05).

The plaque control effect in the inflammatory condition was demonstrated in figure 3. The

placebo toothpaste use was not effective to change the cytokine concentration in the Health and GAgP

groups (p>0.05). The Triclosan toothpaste, on the other hand, promoted a reduction on the IL-1β

concentration in the GAgP group and a reduction in the IL-4 and IFN-ɣ in the Health group (p<0.05),

showing an additional anti-inflammatory effect on the subgingival environment.

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Figure 3 Effect of plaque control using placebo and triclosan toothpaste in the cytokine concentration in the

gingival crevicular fluid. * demonstrate statistical differences between timepoints, Wilcoxon test (p<0.05).

Discussion

The plaque control is the most wildly recommended approach to prevent periodontal disease

and another adverse condition associated with biofilm accumulation in children and adults [7, 17].

However, despite benefits in the clinical condition, no study has demonstrated the benefit of plaque

control alone on the subgingival condition of an already altered environment, as observed on the studied

population. This study has corroborated with the previous studies [4–6] demonstrating initial alterations

in the clinical, microbiological and inflammatory conditions in children from GAgP parents even before

the clinical sign of periodontitis, reinforcing the idea of susceptibility factors and a risk population for

GAgP development. That way, preventive approaches should be applied to this risk group focusing in

monitoring and controlling their adverse periodontal conditions and the use of chemical agents

presenting antimicrobial and anti-inflammatory properties, such as the Triclosan, should be considered

as a treatment option. In the present study, triclosan-containing toothpaste was able to promote some

additional benefits in clinical and host-response patterns of children from GAgP families.

This study has used a cross-over design to test the plaque control alone (placebo toothpaste) or

in association with Triclosan toothpaste in controlling the clinical, microbiological and immunological

alteration observed in children from GAgP parents. The plaque control demonstrated to be effective in

72

reducing the plaque levels for both protocols. This confirms the importance of mechanical therapy in

controlling biofilm accumulation and its potential to reduce plaque index, as well known in the literature

[7, 18, 19]. Moreover, the reduction in plaque index, in spite of toothpaste or familiar origin, also

reinforce the role of the clinician in introducing, motivating and periodically reinforcing the oral hygiene

instructions, maintaining an adequate, healthy-compatible, biofilm loading [19]. However, oral hygiene

and placebo toothpaste were only able to reduce biofilm accumulation, and no other clinical variable

was significantly changed over time. Triclosan toothpaste, on the other hand, demonstrated an additional

effect in the marginal inflammation for GAgP and Health groups. In the GAgP group, the effects were

even higher, reducing the BoP and the PD when the Triclosan toothpaste was used. Even though the PD

and BoP alone were not enough to periodontitis diagnosis (once no clinical sign of bone loss was

identified), these could be important signs of initial clinical alterations. The presence of higher levels of

bleeding, edema and a proinflammatory environment could be favorable to the establishment of a more

pathogenic subgingival condition (associated to reduced levels of oxygen, higher levels of proteins and

prooxidants [20–22]), favoring the colonization by Gram-negative, anaerobes and proteolytic bacteria

[18, 20–22] and triggering the periodontal breakdown. Thus, the reduction of these parameters can

represent an important improvement that could affect the long-term clinical condition of this population.

These additional clinical benefits corroborate with previous studies that also showed the potential of this

molecule in promoted good clinical benefits in adults and children [8, 9, 23–25]. All these benefits are

attributed to its antimicrobial and anti-inflammatory properties of Triclosan.

Triclosan is a broad-spectrum antibacterial agent, that acting in the bacterial cytoplasmic

membrane can achieve a bacteriostatic or bactericidal action depending on the dose [8]. Its action on

bacterial growth and the influence on key bacterial metabolic pathways, in both Gram-positive and

Gram-negative bacteria, is supposed to modulate the bacterial load in the biofilm [9]. This antimicrobial

activity was seen in the present study once only triclosan usage was able to reduce some bacterial

content. Triclosan toothpaste promoted a reduction of Aa in saliva in children from GAgP parents, a

situation that was not observed with the use of placebo toothpaste neither in children from healthy

parents. However, no effect was observed in the subgingival biofilm, suggesting a reduced effect of

Triclosan antimicrobial properties subgingivally. That condition could be explained by the reduced

access of this chemical agent in the subgingival environment and/or by the reduced ability of

antimicrobials to act in an organized and established biofilm [26, 27]. The effect of Triclosan toothpaste

in reducing Aa concentration has been demonstrated in experimental gingivitis studies and in the

maintenance of dental implants [11, 28], however, these studies evaluated its influence on the biofilm

formation and on a supragingival biofilm. When the subgingival biofilm was considered, a 5 years study

evaluating the effect of Triclosan toothpaste in the subgingival microbial composition and periodontitis

progression in cardiovascular patients was not able to demonstrate additional benefits of this

antimicrobial to change the microbial composition even slowing down the periodontitis progression

73

[29], suggesting a small effect of this agent on the subgingival microbiota. Another important aspect is

that GAgP children presented higher levels of Aa at baseline. The presence of Aa subgingivally has been

associated with the risk of periodontal disease, precocious bone loss and clinical attachment loss in

adolescents [30–33]. Thus, the higher levels of Aa in children from GAgP parents can represent a risk

and its reduction should be an important metric to be evaluated and monitored, especially in this risk

population. Thus, the reduction of Aa levels after the therapy would be a desirable effect when

considering the periodontitis prevention and disease control, and future studies should identify a therapy

that also promotes alterations in the subgingival pathogens. Anyway, despite this slight antimicrobial

effect noted only in GAgP children, Triclosan therapy exhibited a more pronounced reduction in

bleeding levels. This phenomenon could be attributed to another important characteristic of this

molecule – its anti-inflammatory potential.

Regarding the anti-inflammatory properties, in vitro studies have shown the efficiency of

triclosan in modulating the inflammatory response. It was demonstrated the Triclosan potential to reduce

the production of prostaglandin E2 (PGE2), a potent stimulator of bone resorption and inflammatory

events, by modulating the IL-1β and TNF-α actions [34, 35]. Furthermore, it was indicated that triclosan

inhibits human fibroblastic cells to produce and secrete IFN-ɣ after stimulation[36], and inhibit oral

epithelial cell to produce LPS-induced pro-inflammatory responses by inducing miRNA regulation of

the TLR-signaling pathway [37], modulating that way the tissue destruction. In the present study,

placebo toothpaste has not altered the cytokine levels in the gingival crevicular fluid in both groups,

despite the reduction on the plaque levels. On the other hand, the Triclosan toothpaste has reduced the

levels of IL-1β in the GAgP group and the levels of IL-4 and IFN-ɣ in the Health group. IL-1β is a pro-

inflammatory cytokine and its higher concentration on the GCF have been associated with periodontal

disease and clinical attachment loss[38]. In this context, some studies have demonstrated the ability of

Triclosan to modulate IL-1β during the microbial challenge. Skold-Larsson et al [34] have reported the

effect of Triclosan in reducing the IL-1β levels in orthodontic patients and Ribeiro et al [10] demonstrate

that triclosan was able to modulate the increasing of this cytokine during experimental mucositis. In

vitro study also demonstrated the downregulation of IL-1 after LPS stimulation in leukocytes cells

treated with Triclosan [12]. Regarding IFN and IL-4, Barros et al, demonstrate the efficiency of

Triclosan to regulate the expression of IFN molecules and suggest that triclosan can inhibit the acute

inflammatory response and may also inhibit the transition from an acute to chronic inflammatory state

[12]. Furthermore, IL-4 is reported to be an important anti-inflammatory cytokine that modulates the

osteoclastogenesis [39] and its reduction concomitantly to IFN-ɣ (a proinflammatory cytokine)

reduction can be associated with the decrease of clinical inflammatory levels promoted by brushing with

Triclosan toothpaste (as demonstrated by the reduction of GI) and the achievement of a more equilibrate

host-response. Interestingly, Triclosan differently acted in each population, by altering different

cytokines in GAgP and Health groups. This reinforces the intrinsic and unique characteristics of

74

aggressive periodontitis and future studies might investigate which cell mechanisms and inflammatory

pathways were affected in each condition.

In summary, the plaque control without the use of an antimicrobial and anti-inflammatory agent

reduced the plaque accumulation levels, although, no other change on the clinical parameters,

microbiological or inflammatory composition was demonstrated. On the other hand, the Triclosan

toothpaste leads to a broader effect by controlling the inflammatory clinical indexes and cytokines,

probably a result of its anti-inflammatory properties, and especially in the GAgP group also reducing

the BoP and salivary level of Aa that were altered at baseline. These results highlighted the beneficial

aspect of the use of chemical agents in association with plaque control, especially in a risk population

with precocious alterations, focusing in control the adverse condition that can trigger the periodontal

breakdown, preventing periodontal disease. Meanwhile, Triclosan toothpaste demonstrates to a be an

interesting option by controlling the inflammatory parameters at the same time that presents an easy

application, secure, and it does not change the children’s oral hygiene routine. However, due to no effect

on the subgingival levels of pathogens, more studies should be stimulated focusing in control the

subgingival microbial condition of this population. In addition, this study has analyzed a short-term

period of Triclosan uses (45 days) and more investigations should be conducted to evaluate if long-term

use of this chemical agent would be able to improve the periodontal condition achieved on this study,

especially for a high-risk population as the GAgP descendants.

This research has analyzed a reduced number of bacterial species and cytokines, what does not

allow a comprehensive evaluation of the biofilm, the inflammatory condition and the identification of

risk markers to that population. However, despite the limitations of this study, it reinforces that children

from GAgP parents are a risk group to development of periodontal disease and that the oral alterations

occur in early ages, even before any clinical sign of bone loss and disease diagnoses. Furthermore, it

was shown that the plaque control with a placebo toothpaste reduces the plaque accumulation, but it is

not enough to control the microbiological and inflammatory alterations, probably because they are not

a result of plaque accumulation alone but associated to the familial influence on the children periodontal

condition, on the inflammatory response pattern and on the colonization factors [5, 40, 41]. Thus, more

efficient and specific approaches should be recommended to that risk population, focusing on preventing

or controlling the establishment of more pathogenic conditions, and the triclosan toothpaste can be one

alternative to this purpose.

Conclusion

In conclusion, the triclosan toothpaste demonstrated to be more efficient than placebo toothpaste

to control the periodontal condition in children from GAgP parents, by reducing the BoP, PD, salivary

Aa, and IL-1β levels.

75

Compliance with ethical standards

Conflict of interest: The authors declare that they have no conflict of interest.

Mabelle de Freitas Monteiro declares that he has no conflict of interest.

Henrique Tonelli declares that he has no conflict of interest.

Aurélio Amorim Reis declares that he has no conflict of interest.

Aurélio Amorim Reis declares that he has no conflict of interest.

Marcio Zaffalon Casati declares that he has no conflict of interest.

Karina Gonzales Silvério declares that he has no conflict of interest.

Francisco Humberto Nociti Junior declares that he has no conflict of interest.

Enilson Antônio Sallum declares that he has no conflict of interest.

Renato Corrêa Viana Casarin declares that he has no conflict of interest.

Funding: This study was supported by FAPESP - São Paulo Research Foundation (scholarship process

2016/20361-6).

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical

standards of the institutional and/or national research committee and with the 1964 Helsinki declaration

and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

76

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3 DISCUSSION

The familial aggregation of GAgP is widely described in the literature (Michalowicz et

al., 2000; Nibali et al., 2008; Meng et al., 2011) and its occurrence is attributed to the

transmission of some specific risk factors, such as genetic, microbiological, behavioral and

environmental from one affected subject to their offspring (Haubek, 2010). This way, the

comprehension of these risk aspects will facilitate the understanding of the pathological aspects

and susceptibility to periodontal disease (still not fully understood (Könönen and Müller, 2014;

Vieira and Albandar, 2014)), besides to orient the implementation of preventive approaches to

that risk population. These were the motivation of the present research, focusing both in the

characterization of the subgingival environment of that population and in the management of

the precocious alterations.

The presented studies used the periodontal disease classification of the American

Academy of Periodontology, 1999 (Armitage, 1999) as the parameter for patient selection, once

they started in 2014 and 2016. However, a new classification was emerged in 2018 (Caton et

al., 2018) and the GAgP was extinct as a specific disease, been classified as periodontitis grade

C, characterized by the rapid rate of progression. The new classification does not mention the

familial aggregation as an important feature, but it offered the opportunity for the inclusion of

other risk aspects that alters the disease pathogenic course. Despite the extinction of the

nomenclature, the evidence that correlated the severe cases of periodontitis with rapid

progression to the accumulation of cases in the same family were vast (Michalowicz et al.,

2000; Nibali et al., 2008; Meng et al., 2011; Vieira and Albandar, 2014), justifying the

investigation of this aspect in rapidly progressive cases and the possible inclusion of this criteria

as a risk factor to disease occurrence.

The first study used of comprehensive analysis to demonstrate the effect of the familial

component in the periodontal disease and to identify possible risk factors associated with a

periodontal breakdown. The bioinformatics analysis revealed a strong influence of parents’

periodontal status in the periodontal condition of their children, both in the subgingival

microbiome and in the host response to its aggression, and the existence of some specific

pathogenic characteristics since childhood can be one of the explanations to the higher

susceptibility of GAgP descendants to also develop GAgP. The higher similarity within family

member just reinforces the use of the family study designs to investigate the cause of such

resemblance and to search for risk factors and biomarkers.

81

A dysbiotic microbiota was described in children from GAgP parents, with higher

abundance of gram-negative and anaerobic bacteria than demonstrated in children from healthy

parents. Furthermore, species and genera such as Filifactor alocis, S. parasanguinis, F.

nucleatum, T.forsythia, P.gingivalis, and Selenomonas, usually associated to periodontal

disease and GAgP (Faveri et al., 2008; Fine et al., 2013) were highly prevalent in the risk

population, suggesting a structural and functional importance of this bacteria to the composition

of the pathogenic environment related to the disease. The host response to this dysbiotic

microbiome was also altered, as demonstrated by the more intense correlations between species

and cytokines, suggesting an unbalance between the body defense and the microbial

aggressions. Nowadays, this unbalances and the break of the homeostasis is considered the

cause of periodontitis (Lamont et al., 2018). Altogether, point to a risk for children from the

GAgP parent, in a long-term, to develop the disease, a situation that will only be confirmed by

longitudinal studies.

The similarity between parents-children microbiome suggests the vertical transmission

and the precocious colonization for pathogenic bacteria as an important aspect of dysbiosis

establishment and disease occurrence. However, other factors should also be interfering on this

situation, such as susceptibility to colonization and an altered host response that creates the

environmental conditions for the establishment of the dysbiotic microbiota (Lamont et al.,

2018). Nibali et al, for example, described how the polymorphism in the IL-6 gene was

correlated to a higher colonization for A. actinomycetencomitans (Nibali et al., 2007; Nibali et

al., 2012) and they suggested the study of the infectogenomics (Nibali et al., 2009) (how the

genetic background can determine the dysbiosis/the colonization for some microorganisms).

Thus, other facts should be investigated to understand fully the susceptibility to periodontal

disease.

Once the precocious alterations were identified and a higher risk was suggested,

alternatives to prevent/control these changes should be proposed, in order to avoid the early

colonization by a pathogenic microbiome and the disease initiation. The plaque control is the

most used preventive approach to prevent periodontal disease since the biofilm accumulation

is related to disease etiology (Kinane et al., 2017). Furthermore, the experimental gingivitis

studies have demonstrated the effectiveness of plaque removal to control the clinical

inflammation (Löe et al., 1965; Trombelli et al., 2004) and that way reducing the risk of

periodontal loss in a long-term (Lang et al., 2009). In the present study, despite the beneficial

clinical results obtained by the plaque control, this therapy was not enough to modulate the

82

pathogenic microbial profile identified in GAgP parents’ descendants. In contrast, the plaque

removal increased the differences between children from GAgP and Health parents, evidencing

the higher pathogenicity of the subgingival environment of GAgP group by demonstrating that

most of the pathobionts correlated with periodontitis (such as A. actinomycetemcomitans,

Filifactor alocis, Streptococcus parasanguinis, Porphyromonas gingivalis, Treponema

denticola, Fusobacterium nucleatum, Tannerella forsythia) were increased and higher

prevalent in that microbiome. Additionally, the strong resilience observed in the GAgP

microbiome was an interesting finding of this study once it could guide the interventions for

that population. The resilience, the capacity of the microbiome to return to the initial condition

after catastrophic intervention (Sommer et al., 2017), of this dysbiotic microbiome,

demonstrated that profound intervention that exceeds the adaptative capacity of the community

should be proposed to reestablish a health-associated condition. Thus, the use of other

approaches in addition to plaque control, such as antimicrobial and anti-inflammatory agents

or probiotic modulation, should be tested as options for clinical management of that risk

population.

In this context, our groups tested the Triclosan-containing toothpaste as a therapeutic

alternative to control the pathogenic subgingival profile in children from GAgP parent once this

product presents important antimicrobial and anti-inflammatory properties and its clinical

efficacy in reducing plaque an inflammation was largely described in the literature (Barros et

al., 2010; Pancer et al., 2016; Ribeiro et al., 2018). Besides the chemical properties of triclosan,

the triclosan-containing toothpaste is commercially available, safe, it is accessible to the

population and its application does not cause an impact on the daily oral hygiene routine,

favoring the self-application, the clinical management and increasing the children’ compliance

to the proposed treatment. The study confirmed the low effectiveness of the plaque control

alone to modify the different periodontal pattern described in this research. The only effect of

plaque control alone was in the plaque index, confirming the necessity to use an adjunctive

approach in association to plaque control. On the other hand, the Triclosan toothpaste

demonstrated an interesting additional effect on the clinical indexes and in the cytokine

markers, demonstrating, somehow, the modulation of the inflammatory response against to the

subgingival aggressions. In contrast, an expected microbiological effect was not demonstrated

for triclosan, that failed to reduce the analyzed microorganisms. Thus, the evaluation of other

methods to control the precocious subgingival changes is still desirable, focusing in identify

effective methods to control the risk aspects in the susceptible population.

83

In summary, the research line demonstrated that the study of families is an important

tool to understand the periodontal disease pathogenesis, as well as to understand risk and

susceptibility in descendants of diseased subjects. Thus, more studies should be designed using

the familial aggregation concept, aiming the comprehension of the long-term consequences of

the described alterations and the role of the host factor (such as genetic and host response) in

the pathogenic process and in susceptibility. Furthermore, these studies can guide the clinical

practices by highlight the importance of the clinical management in descendants of subjects

with periodontal disease, that should be included in efficient preventive programs and should

be monitored periodically to allow the precocious diagnose and early treatment. Finally, the

discoveries of these researches break clinical paradigms by demonstrating that the plaque

control alone, the most used preventive approach to prevent periodontal disease and broadly

recommended for periodontists and pediatric dentist, is not efficient to control the alterations

in this risk population and more efficient approaches should be the focus of future studies.

84

4 CONCLUSIONS

In conclusion, the microbiome, as such as their relationship to the host immune system,

is altered in subjects affected by GAgP and their descendants, what may be related to with

periodontitis pathogenesis and susceptibility to disease. Furthermore, a strong relationship

between the parent and their children periodontal condition was demonstrated and the sharing

of that characteristics can be related to the familial aggregation of severe cases of periodontitis.

Additionally, besides the dysbiotic microbiome and the more pathogenic subgingival

environment identified in GAgP descendants, children from periodontitis-affected parents

presented a strong resilience to subgingival microbial shifting after plaque control, highlighting

the higher risk for disease development and the low effectiveness of plaque control to control

this risk.

Regarding the preventive approach, the plaque control with triclosan dentifrice

demonstrated to be more efficient than plaque control with placebo toothpaste in controlling

the more pathogenic profile of GAgP descendants, by reducing the BoP, PPD, salivary Aa and

IL-1β, in children from GAgP parents.

85

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SUPPLEMENT 4 – Turnitin certificate