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Mapping the Pathogenesisof Periodontitis: A New LookKenneth S. Kornman*

Chronic adult periodontitis is a bacterially induced chronic in-flammatory disease that destroys the connective tissue andbone that support teeth. Concepts of the specific mechanisms in-volved in the disease have evolved with new technologies andknowledge. Histopathologic observations of diseased human tis-sues were used previouslyto speculate on the causes of periodon-titis and to describe models of pathogenesis. Experimentalevidence later emerged to implicate bacterial plaque depositsas the primary factor initiating periodontitis. At the same time,specific bacteria and immunoinflammatory mechanisms weredifferentially implicated in the disease. In the mid-1990s, early in-sights about complex diseases, such as periodontitis, led to newconceptual models of the pathogenesis of periodontitis. Thosemodels included the bacterial activation of immunoinflammatorymechanisms, someof which targeted control of the bacterial chal-lenge and others that had adverse effects on bone and connectivetissue remodeling. Such models also acknowledged that differentenvironmental and genetic factors modified the clinical pheno-type of periodontal disease. However, the models did not capturethe dynamic nature of the biochemical processes, i.e., that innatedifferences among individuals and changes in environmental fac-tors may accelerate biochemical changes or dampen that shift.

With emerging genomic, proteomic, and metabolomic data andsystems biology tools for interpreting data, it is now possible tobegin describing the basic elements of a new model of pathogen-esis. Such a model incorporates gene, protein, and metabolitedata into dynamic biologic networks that include disease-initiat-ing and -resolving mechanisms. This type of model has a multi-level framework in which the biochemical networks that areregulated by innate and environmental factors can be describedand the interrelatedness of networks can be captured. Newmodels in the next few years will be merely frameworks for inte-grating key knowledge as it becomes available from the -omicstechnologies. However, it is possible to describe some of the key

elements of the new models and discuss distinctions between thenew and older models. It is hoped that improved conceptualmodels of pathogenesis will assist in focusing new research andspeedthetranslationofnewdataintopracticalapplications.J Peri-odontol 2008;79:1560-1568.

KEY WORDS

Pathogenesis; periodontal disease; periodontitis;systems biology.

Research into the pathogenesis ofdisease has traditionally involveda reductionist approach in which

discrete inflammatory pathways andprocesses are investigated to elucidateunderlyingmechanisms. Withadvancesin genomic, epigenetic, proteomic, andmetabolomic capabilities, an increasedinterest has emerged in a biologic sys-tems approach to define the complexregulatory networks that result in healthor disease.1 The biologic networks maybe implemented in executable modelsthat respond to perturbations in thesystem, or they may be captured asconceptual models to provide a struc-

tural framework for better communica-tions of relationships among data asthey relate to pathogenesis.

Periodontitis is a complex disease inwhich disease expression involves in-tricate interactions of the biofilm withthe host immunoinflammatory re-sponse and subsequent alterations inbone and connective tissue homeosta-sis.2-4 As such, conceptual models ofthe pathogenesis of periodontitis maybenefit from a systems approach, in

whichbiologicmechanismsare studiedand interpreted in a hierarchical set offunctional modules, such as the mi-crobial ecosystem or the immunoin-flammatory response, which may bemodifiedbyfactors(e.g.,smoking)thatoperate at the patient level. A model ofthe pathogenesis of periodontitis basedon systems biology approaches shouldallow investigators to better communi-cate the interrelatedness of various

* Interleukin Genetics, Waltham, MA.

doi: 10.1902/jop.2008.080213

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clinical expression of disease. Despite a strong and re-producible association between plaque accumulationand the development of gingivitis, these associationswerelessclearon a patient-to-patientanalysisandwereconfusing on an individual siteanalysis within the samepatient. In addition, although epidemiologic data sug-

gested that exposure to plaque accumulations overlongperiods of timeled to periodontitis,thelongitudinalanimal and human data were surprising. In a classicstudy25 in beagledogs, plaqueaccumulation wasasso-ciated with a progression to periodontitis, but two ofeight dogs failed to develop periodontitis, despite sub-stantial plaque and calculus accumulations and exten-sivegingivitis.Perhaps most strikingwerethe publishedreports from longitudinal studies26,27 of tea plantationworkers in Sri Lanka. As first reported, a failure to cleanteeth regularly resulted in thedevelopment of extensivegingivitis and in early and severe periodontitis.27,28

However, further analysis determined that there werethree distinct subsets of the population relative to thedevelopment of periodontitis in response to bacterialaccumulations, including one group that had poor oralhygiene and gingivitis but developed minimal to noperiodontitis.26

To add further complexity to the earlier conceptualmodels, there was a growing appreciation during thisperiod of the importance of genetic variations in deter-miningthedevelopmentandseverityofperiodontaldis-ease, withgenetic influences accountingfor as much as30% to 60% of the variability in the clinical severity of

periodontitis.29,30

The profound influence of genotypeon susceptibility to periodontitis was apparent fromstudies in twins,29,31,32 in which a greater variabilityintheriskforperiodontaldiseasewasfoundindizygotictwins compared to monozygotic twins,assuming a sim-ilar homeenvironment withinfamilies. As such, geneticdifferences among individuals seemed to be a signifi-cant determinant of risk for periodontal disease and,most importantly, there were gene variations that al-tered host responses and modified the clinical severityof disease.33

ORIGINS OF A NON-LINEAR MODEL

With new knowledge of the various factors contribut-ing to periodontal disease came recognition that clin-ical phenotype is not simply the microbial challengetranslated by a standard host response. Strong dataemerged showing that smoking34-37 and diabetes38-43

were powerful determinants of disease severity. Lab-oratory and clinical research demonstrated that theserisk factors were most likely influencing disease ex-pression by altering host protective and destructivemechanisms. In periodontal disease, although the mi-crobial challenge is a primary initiating factor, a num-ber of other factors seemed to be modifying disease

expression, but they were not, by themselves, causa-

tive factors. The contrast between modifying andcausative factors was a subtle, but important, distinc-tion. Earlier attempts to evaluate the role of variousrisk factors, such as smoking and diabetes, in peri-odontal disease had assumed an independent causa-tion model. Investigators were correct to conclude

that these factors did not cause disease, but priorto the 1980s, we incorrectly concluded that these fac-tors were not involved in pathogenesis.

In the absence of disease-modifying risk factors, itseems that the host responds appropriately to thebacterial accumulations by attempting to protectagainst bacterial invasion. In such situations, the hostseems capable of limiting periodontal tissue destruc-tion. Evidence began to accumulate that diseasemodifiers, such as smoking, in the presence of bacte-rial accumulations on the teeth, shifted the immuno-inflammatory responses outside of the normal

boundaries of host response and repair processes.In the presence of modifying factors, such as smok-ing, an exuberant host response and/or impaired re-pair mechanisms seem to lead to more destructiveperiodontitis. Of course, this raised many questions,including what controls the resolution of disease afterthe inflammatory cascades are activated.

The basic conceptual model of periodontitis wasre-vised in 1997 (Fig. 1C),44 in great part to acknowledgethat various risk factors operated by modifyinghost re-sponses led to changes in disease expression. In thismodel, host immunoinflammatory mechanisms are

activated by bacterial products. Such activation ofthehost response inducesthe expression of antibodiesas well as activating PMNs in an attempt to control themicrobial challenge in the gingival sulcus. In addition,cytokines and prostanoids, as well as matrix metallo-proteinases activated through the host response, maystimulate damage to connective tissue and bone andshape the clinical presentation of disease.

The primary conceptual change in the 1997 modelwas that it explicitly acknowledged the role of anumber of environmental and acquired risk factors,including genetics, as modifiers of the immunoinflam-matory response and in resulting connective tissueand bone metabolism. Thus, the clinical presentationand expected progression and responses to therapyare a net integration of how the host response, asmodified by patient genetics and acquired factors, ex-pressed protective and destructive biologic mediators.Simply put, modifying factors such as exposure tocigarette smoke and/or inherent genetic risk factorsmay alter the nature of the immunoinflammatory re-sponse to shift the balance to more severe periodontaldestruction. The 1997 model was non-linear. Thepresence of pathogenic bacteria did not automaticallylead to a single host-response pattern and severe de-

struction. The model implied that there were a range of

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host responses and a range of clinical expressions ofdisease that were primarily determined by geneticand environmental factors that modified the host re-sponse. Each combination of genetic variations andenvironmental factors may define a specific gene-expression pattern. It has been postulated, but not yet

proven, that someof the different gene-expression pat-terns, as measured by various biomarkers, define peri-odontal diseases with different clinical implications.3

ADVANCES IN KNOWLEDGE OF THE

PATHOGENESIS OF PERIODONTITIS

Although many of the concepts presented in the 1997non-linear model of periodontal disease remain rele-vant today, there have been advances in knowledgeabout periodontal disease that may alter our modelsof pathogenesis. First, it was demonstrated that micro-bial periodontal pathogens are found in ecologic com-

plexes, and an ecologic shift can lead to emergence ofa specific set of microbial pathogens.45,46 Second, anumber of studies33-41 confirmed that a small groupof disease modifiers, including diabetes, genotype,and smoking, contribute strongly to individual patientdifferences in the susceptibility to periodontitis. For ex-ample, in a recent prospective study47 of young adultsaged26to32years,asmanyastwo-thirdsofnewcasesofperiodontitiswereattributedtosmoking. Third,manystudies48-59 described associations between periodon-titis andotherdiseases,such as cardiovascular disease,and potentially explained such associations through

bacterial seeding, common inflammatory mechanisms,and/or common modifying factors. Fourth, there wasan extension of knowledge about specific bacterialmechanisms and immunoinflammatory mechanismsin periodontitis.60-64

ADVANCES IN KNOWLEDGE OF

COMPLEX DISEASES

During the same period of time, there were substantialadvances in knowledge about chronic diseases ingeneral that have influenced our thinking about thepathogenesis of periodontitis. First, inflammatorymechanisms were recognized as being common tomany chronicdiseasesofaging,such ascardiovasculardisease.65-67 Second, periodontitis and other chronicdiseases were acknowledged as complex in charac-ter. This means that the overall biologic system has adistinct behavior that is more than the sum of its parts,i.e., it exhibits emergent properties. A recent study68

emphasized that complex biologic traits, such as obe-sity, have molecular networks that display emergentproperties as a result of contributions from geneticand environmental factors.

Third, although the biology is complex, the inte-grated behavior of the entire system can be studied

using new simulation tools.69-71 For example, molec-

ular networks of specific biologic components, e.g.,the immunoinflammatory response, can be studiedas a functional module. Combinations of modulescan be integrated to study the overall system behaviorthat translates into clinical outcomes. Each module isdefined in terms of cellular and molecular inputs and

outputs. For example, the bacterial components thatactivate the immunoinflammatory systems are inputsto the module. In addition, the genetic and environ-mental factors that modify that modules responsesare inputs. The antibodies, cytokines, growth factors,prostanoids, reactive oxygen species, and other me-diators that are produced by the cells of the immu-noinflammatory responses are the modules internalfeedback mechanisms and outputs that provide in-puts to other modules. Although there are many dif-ferent combinations of inputs to a module, there arelimited ranges of responses and outputs because bio-

logic processes are well regulated within boundariesthat are consistent with life.

The behavior of the entire system has emergentproperties because of the interaction of the factorswithin each module and interactions among modules.An example of such a modular, yet complex, biologicsystem is the leptin-dependent sympathetic regula-tion of bone mass.72,73 Adipose tissue has a numberof different inputs and outputs, including the releaseof leptin that acts directly or indirectly on the hypo-thalamic neurons of the brain to modify sympatheticactivity. As such, adipose tissue may represent a dis-

tinct module, whereas the brain tissue is a separatemodule that has its own inputs and outputs. Stimula-tion of hypothalamic neurons by leptin leads to acti-vation of other modules through a neural mechanisminvolving b2-adrenergic receptors in osteoblasts,which indirectly drives osteoclastogenesis and altersbone metabolism. These observations may be directlyrelevant to periodontal diseases because leptin levelshave been associated with periodontal disease.74

The fourth learning about complex diseases thatmaybe applicable to models of periodontal pathogen-esis involves the roles of environmental factors. Addi-tional complexity in chronic disease biology seems toresult from the fact that environmental factors mayregulate gene expression in multiple ways. Environ-mental factors, including smoking and diabetes,which are associated with periodontal disease sever-ity, may influence the biology through multiple mech-anisms, and we may speculate that the multiple hitson the biology contribute to the magnitude of their in-fluence on the disease. For example, certain dietaryfactors may produce epigenetic alterations in DNAthat result in long-lasting changes in the expressionof selected genes. At different stages in life, the samedietary factors may act directly as transcription fac-

tors to regulate specific genes and alter their expression

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at that immediate point in time. To add further com-plexity to a conceptual model for periodontal disease,we must recognize that the modifying factors, such asa particular gene variant, may interact in a specificenvironmental context. Recently, Shen et al.75 reportedthat interleukin-1 gene variations were significantly

associated with parameters of metabolic syndrome,but only in individuals with low levels of polyunsatu-rated fatty acids.

Although nutritional factors do not cause periodon-titis, their role in periodontal disease may be re-examined in light of more current knowledge abouthow nutrients regulate gene expression. For example,a dietary influence on the severity of periodontitis wasdemonstrated in a primate model of periodontal dis-ease in which calorie restriction (30% of normalcaloricintake) was associated with decreased gingival bleed-ing, reduced clinical attachment loss, and a slower rate

of diseaseprogressioncompared to an ad libitumdiet.76

Other advances in the general knowledge ofchronic diseases included the use of genomic, proteo-mic, and metabolomic technologies to better explainthe molecular networks that are involved in specificgeneenvironment interactions in selected tissues.The massive amounts of information emerging fromthe new -omics technologies are being integratedinto systems biology models of complex diseases.1,71

ELEMENTS OF A NEW MODEL OF

PATHOGENESIS OF PERIODONTAL DISEASE

Many of the same factors considered in the 1997 con-ceptual model of the pathogenesis of periodontal dis-ease are still relevant today; however, the frameworkwould now be based on a multilevel hierarchical orga-nization, and the interactions are reflected in gene,protein, and metabolite expression patterns (Fig. 2).In such models, the top layer includes clinically ob-servable parameters, such as smoking, whereas thelevels below include tissue, cellular, and subcellularlayers, each divided into biologic networks.

We can start to define the elements of periodontalpathogenesis in terms of hierarchical models (Fig.3). At the lower levels, the biologic expression of theimmunoinflammatory network and bone and connec-tive tissue network are determined by the microbialfactors and the specific combination of environmentalfactors and genevariationsfor thatindividual. Buildinga systems biology model of periodontitis presentssubstantial requirements and challenges, but inves-tigators3,77-82 have started to provide data on theentities and gene and protein expressions associatedwith certain components of the periodontal model.

As shown in the lower level of Figure 3, the expres-sion patterns of an individual may be shapedby smok-ing >20 cigarettes per day and by a specific pattern of

gene variations. Data to incorporate into this frame-

work are emerging, e.g., array profiles, including geneexpression patterns from macrophages or macro-phage-like human cell lines following exposure to Por-phyromonas gingivalis,83 lipopolysaccharide,84 andnicotine.79

This individual response, including cytokines andlipid mediators, produced by the host, as well as alter-ations in bone and connective tissue, can be clearlycharacterized by a specific pattern of gene, protein,and metabolite expression. The expressed proteinsand metabolites provide feedback on the system toregulate the host response and bone and connectivetissue, while helping to control thebacterial challenge.

Although there has been progress in beginning todefine the expression of these biologic system maps,further detail is required in a number of areas. A morecomplete identification of expression profiles from thebacterial challenge is needed, including identifyingthe proteome and metabolome associated with vari-ous microbial complexes. In addition, it would be

valuable to define the factors that regulate microbial

Figure 2.A key organizing principle of systems biology is the use of multiplelevels to provide a framework for defining the interactions betweenthe cellular and molecular processes occurring at the lowest levels tothe clinical presentation of disease at the uppermost level. Forexample, level 1 may capture the factors that are inputs (*) to cell Xand that regulate signaling mechanisms to control gene expression.The inputs to level 1 may come from other cells, from cell X proteinsthat are produced on activation (Level 4, **), or from the individualsenvironment (e.g., dietary polyunsaturated fatty acids). The genesexpressed at level 1 may contribute proteins involved in cell energymetabolism (Level 2), cell differentiation (Level 3), or phenotypicexpression (Level 4) that are characteristic of the differentiated celltype (Cell Xa), e.g., monocytes activated by lipopolysaccharideproduce a characteristic cytokine profile. The tissue (Level 5) has amixture of cell types and differentiation states (e.g., Cell Xa, Cell Yd,

and Cell Za). At the clinical level (Level 6), tissue interactions areobservable as clinical outcomes.


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ecology under different genetic and environmentalconditions. Finally, a more complete understandingis needed of the biologic effects of known diseasemodifiers, such as smoking, diet, co-occurrence ofother diseases, and specific genetic variations that in-fluence the expression of periodontitis.

Ultimately, the goal will be to define expression pat-terns in the tissues with respect to each set of environ-mental and genetic conditions and to understand thecorresponding clinical parameters and profiles. Suchinformation willallow constructionof a systems biologymodel that includes the state of key parameters at thebasic biology level, which is critical to defining the reg-ulatorystatusofthetissueatanypointintime.Althougheven partial information should improve the ability toidentify an individuals susceptibility to disease and alikely response to treatment, the complete expressionof these networks should be a valuable tool for deter-mining new preventive and therapeutic approaches.Most importantly, research groups must commit to in-tegrate their own data, as well as thedata of others, into

comprehensive systems-based models. These models

are iterative and should in-form researchers about keymissingdata,whiletheyguidenewconceptsofdiseaseman-agement.

CONCLUSIONS

Over the past 50 years, anumber of conceptual modelsdescribing the pathogenesisof periodontal disease havebeen presented based on ex-isting knowledge at the time.The more recently exploredbiologic systems approachto modeling holds promisefor revolutionizing conceptualmodels of the past by provid-

ing a comprehensive viewof the disease process as acomplex regulatory network.Within this framework, dis-crete modules of genetic,environmental, and othermodifying factors would de-fine a specific expressionpattern that represents theshift from health to disease.Genomic, proteomic, andmetabolomic data related to

periodontal diseases are be-ing collected. When thesedataarecombinedwithknow-ledge of even a limited set

of environmental and genetic factors contributingto periodontitis, we should be able to build more ro-bust models of the pathogenesis of periodontal dis-eases.

ACKNOWLEDGMENTS

Dr. Kornman is the chief scientific officer, member ofthe Board of Directors, and a shareholder of Interleu-

kin Genetics. Interleukin Genetics has patents issuedand pending on the use of various genetic variations toassess the risk for diseases with inflammatory compo-nents, including periodontal disease. The initial draftof this manuscript was developed by a medical writer(Axon Medical Communications Group, Toronto, On-tario) based on content provided solely by the author.The final manuscript submitted was under the solecontrol of the author.

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Figure 3.A biologic systems model representing the pathogenesis of periodontitis may be defined by the bacterialcomponents, environmental factors, and hostgenetic variations associated with disease. Level A depictsthe biologic mechanisms involved in immunoinflammatory responses and in bone and connective tissuemetabolism, and level B depicts the observable clinical parameters and biomarkers. In level B, theproducts produced by different microbial complexes are represented by arrays (*). These products activatethe immunoinflammatory mechanisms, which subsequently influence the behavior of bone and connectivetissue metabolism. For each individual there are combinations of genetic variations and environmentalfactors (e.g., host genetic variation: pattern 1 and smoking>20 cigarettes/day). These genetic andenvironmental factors act on mechanisms in level A to modify the expression of genes activated by thebacterial products. The gene expression and proteins and metabolites produced in level A can be assayed

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Correspondence: Dr. Kenneth Kornman, Interleukin Ge-netics, 135 Beaver St., Waltham, MA 02452. Fax: 781/398-0720; e-mail: [email protected].

Submitted April 22, 2008; accepted for publication May30, 2008.


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