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Deciphering genomic signatures associating human dental oral craniofacial diseases with cardiovascular diseases using machine learning approaches

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Abstract

Objectives

Periodontal diseases are chronic, inflammatory disorders that involve the destruction of supporting tissues surrounding the teeth which leads to permanent damage and substantially heightens systemic exposure. If left untreated, dental, oral, and craniofacial diseases (DOCs), especially periodontitis, can increase an individual’s risk in developing complex traits including cardiovascular diseases (CVDs). In this study, we are focused on systematically investigating causality between periodontitis with CVDs with the application of artificial intelligence (AI), machine learning (ML) algorithms, and state-of-the-art bioinformatics approaches using RNA-seq-driven gene expression data of CVD patients.

Materials and methods

In this study, we built a cohort of CVD patients, collected their blood samples, and performed RNA-seq and gene expression analysis to generate transcriptomic profiles. We proposed a nexus of AI/ML approaches for the identification of significant biomarkers, and predictive analysis. We implemented recursive feature elimination, Pearson correlation, chi-square, and analysis of variance to detect significant biomarkers, and utilized random forest and support vector machines for predictive analysis.

Results

Our AI/ML analyses have led us to the preliminary conclusion that GAS5, GPX1, HLA-B, and SNHG6 are the potential gene markers that can be used to explain the causal relationship between periodontitis and CVDs.

Conclusions

CVDs are relatively common in patients with periodontal disease, and an increased risk of CVD is associated with periodontal disease independent of gender. Genetic susceptibility contributing to periodontitis and CVDs have been suggested to some extent, based on the similar degree of heritability shared between both complex diseases.

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Fig. 1
Fig. 2

Data availability

The data analyzed in the current study are attached, and available from the corresponding author on reasonable request. All the source code reproducing the experiments of this study are available at GitHub < https://github.com/drzeeshanahmed/CVD-DOC_Association_Genomics > .

References

  1. Kholy KE, Genco RJ, Van Dyke TE (2015) Oral infections and cardiovascular disease. Trends Endocrinol Metab 26(6):315–321

    Article  PubMed  CAS  Google Scholar 

  2. Bartold PM (2018) Lifestyle and periodontitis: the emergence of personalized periodontics. Periodontol 2000 78(1):7–11

    Article  PubMed  Google Scholar 

  3. Eke PI, Dye BA, Wei L, Slade GD, Thornton-Evans GO, Borgnakke WS, Taylor GW, Page RC, Beck JD, Genco RJ (2015) Update on prevalence of periodontitis in adults in the United States: NHANES 2009 to 2012. J Periodontol 86(5):611–622

    Article  PubMed  PubMed Central  Google Scholar 

  4. Sloan NL, Shapiro MZ, Sabra A, Dasaro CR, Crane MA, Harrison DJ, Luft BJ, Moline JM, Udasin IG, Todd AC, Teitelbaum SL (2021) Cardiovascular disease in the World Trade Center Health Program General Responder Cohort. Am J Ind Med 64(2):97–107

    Article  PubMed  Google Scholar 

  5. Sanz M, Marco Del Castillo A, Jepsen S, Gonzalez-Juanatey JR, D’Aiuto F, Bouchard P, Chapple I, Dietrich T, Gotsman I, Graziani F, Herrera D, Loos B, Madianos P, Michel JB, Perel P, Pieske B, Shapira L, Shechter M, Tonetti M, Vlachopoulos C, … Wimmer G (2020) Periodontitis and cardiovascular diseases: consensus report. J Clin Periodontol 47(3):268–288

  6. Dhadse P, Gattani D, Mishra R (2010) The link between periodontal disease and cardiovascular disease: how far we have come in last two decades? J Indian Soc Periodontol 14(3):148–154

    Article  PubMed  PubMed Central  Google Scholar 

  7. Stewart R, West M (2016) Increasing evidence for an association between periodontitis and cardiovascular disease. Circulation 133(6):549–551

    Article  PubMed  Google Scholar 

  8. Leng Y, Hu Q, Ling Q, Yao X, Liu M, Chen J, Yan Z, Dai Q (2023) Periodontal disease is associated with the risk of cardiovascular disease independent of sex: a meta-analysis. Front Cardiovasc Med 10:1114927

    Article  PubMed  PubMed Central  Google Scholar 

  9. Vadapalli S, Abdelhalim H, Zeeshan S, Ahmed Z (2022) Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine. Brief Bioinform 23(5):bbac191. https://doi.org/10.1093/bib/bbac191

  10. Ahmed Z, Mohamed K, Zeeshan S, Dong X (2020) Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database: The Journal of Biological Databases and Curation 2020:baaa010. https://doi.org/10.1093/database/baaa010

  11. Venkat V, Abdelhalim H, Degroat W, Saman Z, Ahmed Z (2023) Implementing machine learning techniques at RNA-seq driven gene-expression data to investigate genes associated with HF, AF, and other CVDs, and predict disease with high accuracy. Genomics 115:2

    Google Scholar 

  12. Degroat W, Venkat V, Pierre-Louis W, Abdelhalim H, Ahmed Z (2023) Hygieia: AI/ML pipeline integrating healthcare and genomics data to investigate genes associated with targeted disorders and predict disease. Softw Impacts 16:100493. https://doi.org/10.1016/j.simpa.2023.100493

  13. Ahmed Z, Renart EG, Zeeshan S, Dong X (2021) Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis. Hum Genomics 15(1):37

    Article  PubMed  PubMed Central  Google Scholar 

  14. Zeng B, Li Y, Jiang F, Wei C, Chen G, Zhang W, Zhao W, Yu D (2019) LncRNA GAS5 suppresses proliferation, migration, invasion, and epithelial-mesenchymal transition in oral squamous cell carcinoma by regulating the miR-21/PTEN axis. Exp Cell Res 374(2):365–373

    Article  PubMed  CAS  Google Scholar 

  15. Duarte PM, Napimoga MH, Fagnani EC, Santos VR, Bastos MF, Ribeiro FV, Araújo VC, Demasi AP (2012) The expression of antioxidant enzymes in the gingivae of type 2 diabetics with chronic periodontitis. Arch Oral Biol 57(2):161–168

    Article  PubMed  CAS  Google Scholar 

  16. Lei C, Niu X, Wei J, Zhu J, Zhu Y (2009) Interaction of glutathione peroxidase-1 and selenium in endemic dilated cardiomyopathy. Clin Chim Acta Int J Clin Chem 399(1–2):102–108

    Article  CAS  Google Scholar 

  17. Greco A, De Virgilio A, Ralli M, Ciofalo A, Mancini P, Attanasio G, de Vincentiis M, Lambiase A (2018) Behçet’s disease: new insights into pathophysiology, clinical features and treatment options. Autoimmun Rev 17(6):567–575

    Article  PubMed  CAS  Google Scholar 

  18. Tan R, Liu J, Wang J, Zhang W, He M, Zhang Y (2023) Long noncoding RNA SNHG6 silencing sensitized esophageal cancer cells to 5-FU via EZH2/STAT pathway. Sci Rep 13(1):5363

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  19. Lang Z, Fan X, Lin H, Qiu L, Zhang J, Gao C (2021) Silencing of SNHG6 alleviates hypoxia/reoxygenation-induced cardiomyocyte apoptosis by modulating miR-135a-5p/HIF1AN to activate Shh/Gli1 signalling pathway. J Pharm Pharmacol 73(1):22–31

    Article  PubMed  Google Scholar 

  20. Matzaraki V, Kumar V, Wijmenga C, Zhernakova A (2017) The MHC locus and genetic susceptibility to autoimmune and infectious diseases. Genome Biol 18(1):76

    Article  PubMed  PubMed Central  Google Scholar 

  21. Handy DE, Loscalzo J (2022) The role of glutathione peroxidase-1 in health and disease. Free Radical Biol Med 188:146–161

    Article  CAS  Google Scholar 

  22. Li G, Qian L, Tang X, Chen Y, Zhao Z, Zhang C (2020) Long non coding RNA growth arrest specific 5 (GAS5) acts as a tumor suppressor by promoting autophagy in breast cancer. Mol Med Rep 22(3):2460–2468

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Jiang Y, Du T (2022) Relation of circulating lncRNA GAS5 and miR-21 with biochemical indexes, stenosis severity, and inflammatory cytokines in coronary heart disease patients. J Clin Lab Anal 36(2):e24202

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Shan H, Guo D, Zhang S, Qi H, Liu S, Du Y, He Y, Wang B, Xu M, Yu X (2020) SNHG6 modulates oxidized low-density lipoprotein-induced endothelial cells injury through miR-135a-5p/ROCK in atherosclerosis. Cell Biosci 10:4

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Dainis AM, Ashley EA (2018) Cardiovascular Precision Medicine in the Genomics Era. JACC Basic Transl Sci 3(2):313–326

    Article  PubMed  PubMed Central  Google Scholar 

  26. Genco R, Offenbacher S, and Beck J (2002) Periodontal disease and cardiovascular disease: epidemiology and possible mechanisms. J Am Dent Assoc (1939) 133 Suppl:14S–22S. https://doi.org/10.14219/jada.archive.2002.0375

  27. Patel K, Venkatesan C, Abdelhalim H, Saman Z, Arima Y, Linna-Kuosmanen S, Ahmed Z (2023) Genomics approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility. Hum Genomics 17:47

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Zeng Y, Cao S, Chen M (2022) Integrated analysis and exploration of potential shared gene signatures between carotid atherosclerosis and periodontitis. BMC Med Genomics 15(1):227

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Aarabi G, Zeller T, Seedorf H, Reissmann DR, Heydecke G, Schaefer AS, Seedorf U (2017) Genetic susceptibility contributing to periodontal and cardiovascular disease. J Dent Res 96(6):610–617

    Article  PubMed  CAS  Google Scholar 

  30. Mhatre I, Abdelhalim H, Degroat W, Ashok S, Liang BT, Ahmed Z (2023) Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases. Sci Rep 13(1):16769

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

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Acknowledgements

We appreciate great support by the Department of Medicine/Cardiovascular Disease and Hypertension, Rutgers Robert Wood Johnson Medical School (RWJMS); Rutgers Institute for Health, Health Care Policy, and Aging Research (IFH); and Rutgers Biomedical and Health Sciences (RBHS), at the Rutgers, The State University of New Jersey.

We thank members and collaborators of Ahmed Lab at Rutgers (RWJMS and IFH) for their support, participation, and contribution to this study.

Funding

This study was supported by the Department of Medicine/Cardiovascular Disease and Hypertension, Division of General Internal Medicine, Rutgers Robert Wood Johnson Medical School, and Institute for Health, Health Care Policy, and Aging Research which is the part of Rutgers Biomedical and Health Sciences at Rutgers, The State University of New Jersey.

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Authors and Affiliations

  1. Department of Medicine/Cardiovascular Disease and Hypertension, Robert Wood Johnson Medical School, Rutgers Biomedical and Health Sciences, 125 Paterson St, New Brunswick, NJ, USA

    Zeeshan Ahmed

  2. Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, 112 Paterson St, New Brunswick, NJ, USA

    Zeeshan Ahmed, William Degroat & Habiba Abdelhalim

  3. Department of Radiation Oncology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, USA

    Saman Zeeshan

  4. Department of Oral Biology, Rutgers School of Dental Medicine, 110 Bergen Street, Newark, NJ, USA

    Daniel Fine

Authors
  1. Zeeshan Ahmed
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  2. William Degroat
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  3. Habiba Abdelhalim
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  4. Saman Zeeshan
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  5. Daniel Fine
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Contributions

ZA led this study. ZA performed initial cohort building and integrative clinical data analysis of consented patients. ZA did RNA-seq data processing, quality checking, and gene expression analysis. WD performed AI/ML analysis. HA and SZ performed post computational analysis and evaluation of the results. DF guided and supported the study. ZA drafted the paper, and all authors have participated in reviewing and have approved it for publication.

Corresponding author

Correspondence to Zeeshan Ahmed.

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Ethical approval and consent to participate

Informed consent was obtained from all subjects. All human samples were used in accordance with relevant guidelines and regulations, and all experimental protocols were approved by the Institutional Review Board.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Ahmed, Z., Degroat, W., Abdelhalim, H. et al. Deciphering genomic signatures associating human dental oral craniofacial diseases with cardiovascular diseases using machine learning approaches. Clin Oral Invest 28, 52 (2024). https://doi.org/10.1007/s00784-023-05406-3

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