Subgingival bacterial colonization profiles correlate with gingival tissue gene expression

The 2 major forms of periodontitis, chronic (CP) and aggressive (AgP), do not display sufficiently distinct histopathological characteristics or microbiological/ immunological features. We used molecular profiling to explore biological differences between CP and AgP and subsequently carried out supervised classification using machine-learning algorithms including an internal validation. We used whole-genome gene expression profiles from 310 'healthy' or 'diseased' gingival tissue biopsies from 120 systemically healthy non-smokers, 65 with CP and 55 with AgP, each contributing with ≥ 2 'diseased' gingival papillae (n = 241; with bleeding-on-probing, probing depth ≥ 4 mm, and clinical attachment loss ≥ 3 mm), and, when available, a 'healthy' papilla (n = 69; no bleeding-on-probing, probing depth ≤ 4 mm, and clinical attachment loss ≤ 4 mm). Our analyses revealed limited differences between the gingival tissue transcriptional profiles of AgP and CP, with genes related to immune responses, apoptosis, and signal transduction overexpressed in AgP, and genes related to epithelial integrity and metabolism overexpressed in CP. Different classifying algorithms discriminated CP from AgP with an area under the curve ranging from 0.63 to 0.99. The small differences in gene expression and the highly variable classifier performance suggest limited dissimilarities between established AgP and CP lesions. Future analyses may facilitate the development of a novel, 'intrinsic' classification of periodontitis based on molecular profiling.

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“…Excellent correlation of array data and confirmatory qPCR was shown previously (Papapanou et al, 2009). …”

Section: Methodsmentioning

confidence: 92%

Molecular Differences between Chronic and Aggressive Periodontitis

et al. 2013

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“…Despite this, no unique pathogen has been found yet corresponding to the postulate modified by HenleKoch (21). Partly, the criteria have been met due to the fact that it's possible for periodontium to be infected by P.gingivalis (17) and immunisation against this pathogen prevents the development experimental periodontitis in the same animal model (17,23).…”

Section: Etiologymentioning

confidence: 99%

“…Research shows significant genetic impact on the antibiotic sensitivity in patients with CP (21). Genetic factors trigger immune reactions as a whole.…”

Section: Etiologymentioning

confidence: 99%

Chronic periodontitis and rheumatoid arthritis – microbiological aspects

Popova¹,

Panchovska²

2015

MedInform

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An overview of the literature on the role of periodontopathogenic microorganisms and chronic periodontitis in the emergence and development of rheumatoid arthritis is presented. The paper discusses the microbiological and genetic factors, environmental factors and the pathogenesis of the two diseases and presents evidence for the relationship between them. Porphyromonas gingivalis, associated with the severity of chronic periodontitis is the only microorganism documented to produce peptidylarginine deiminase (PAD), involved in the process of citrullination. P. gingivalis infection may generate citrullinated peptides, which trigger anti-cyclic citrullinated peptide (anti-CCP) antibodies against synovial lining of the joints. Citrullination by human PADs is important in normal physiology and inflammation. Porphyromonas gingivalis has not been detected in all investigated patients with rheumatoid arthritis and hasn`t been associated with the titer of rheumatoid factor / anti-cyclic citrullinated peptide (anti-CCP) antibodies. Probably in the process of citrullination another microorganism that will be shown in future studies takes an active role. The emphasis is placed on Anaeroglobus geminatus, which is associated with the titer of rheumatoid factor / anti-CCP antibodies and detected in all patients studied. The presence of Leptotrichia and Prevotella spp. only in patients with new-onset rheumatoid arthritis is highlighted.

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“…We demonstrated that distinct patterns of subgingival microbial colonization associate with discernible gene expression signatures in the adjacent gingival 653588J DRXXX10.1177/0022034516653588Journal of Dental ResearchMaster Regulator Genes in Human Periodontitis research-article2016 tissues (Papapanou et al 2009). Despite limited molecular differences among lesions from chronic or aggressive periodontitis (Kebschull et al 2013), gingival tissue transcriptomes identified 2 clusters of patients (Kebschull et al 2014) who differed with respect to periodontitis extent and severity, levels of specific subgingival microbiota, and serum IgG antibody responses to selected bacteria.…”

Section: Introductionmentioning

confidence: 99%

Identification of Master Regulator Genes in Human Periodontitis

et al. 2016

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Analytic approaches confined to fold-change comparisons of gene expression patterns between states of health and disease are unable to distinguish between primary causal disease drivers and secondary noncausal events. Genome-wide reverse engineering approaches can facilitate the identification of candidate genes that may distinguish between causal and associative interactions and may account for the emergence or maintenance of pathologic phenotypes. In this work, we used the algorithm for the reconstruction of accurate cellular networks (ARACNE) to analyze a large gene expression profile data set (313 gingival tissue samples from a cross-sectional study of 120 periodontitis patients) obtained from clinically healthy (n = 70) or periodontitis-affected (n = 243) gingival sites. The generated transcriptional regulatory network of the gingival interactome was subsequently interrogated with the master regulator inference algorithm (MARINA) and gene expression signature data from healthy and periodontitis-affected gingiva. Our analyses identified 41 consensus master regulator genes (MRs), the regulons of which comprised between 25 and 833 genes. Regulons of 7 MRs (HCLS1, ZNF823, XBP1, ZNF750, RORA, TFAP2C, and ZNF57) included >500 genes each. Gene set enrichment analysis indicated differential expression of these regulons in gingival health versus disease with a type 1 error between 2% and 0.5% and with >80% of the regulon genes in the leading edge. Ingenuity pathway analysis showed significant enrichment of 36 regulons for several pathways, while 6 regulons (those of MRs HCLS1, IKZF3, ETS1, NHLH2, POU2F2, and VAV1) were enriched for >10 pathways. Pathways related to immune system signaling and development were the ones most frequently enriched across all regulons. The unbiased analysis of genome-wide regulatory networks can enhance our understanding of the pathobiology of human periodontitis and, after appropriate validation, ultimately identify target molecules of diagnostic, prognostic, or therapeutic value.

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Subgingival bacterial colonization profiles correlate with gingival tissue gene expression

Cited by 85 publications

References 43 publications

Molecular Differences between Chronic and Aggressive Periodontitis

Molecular Differences between Chronic and Aggressive Periodontitis

Chronic periodontitis and rheumatoid arthritis – microbiological aspects

Identification of Master Regulator Genes in Human Periodontitis

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