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Cited by 77Oral microbiology and periodontitis researchBiosensors and Analytical DetectionMicrofluidic and Capillary Electrophoresis Applications

Biosensor and Lab-on-a-chip Biomarker-identifying Technologies for Oral and Periodontal Diseases

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Steigmann, Larissa, Maekawa, Shogo, Sima, Corneliu, Travan, Suncica, Wang, Chin-Wei, Giannobile, William V.·2020·Frontiers in Pharmacology
DOI 10.3389/fphar.2020.588480PMC PMC7748088
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Abstract

Periodontitis is a complex multifactorial disease that can lead to destruction of tooth supporting tissues and subsequent tooth loss. The most recent global burden of disease studies highlight that severe periodontitis is one of the most prevalent chronic inflammatory conditions affecting humans. Periodontitis risk is attributed to genetics, host-microbiome and environmental factors. Empirical diagnostic and prognostic systems have yet to be validated in the field of periodontics. Early diagnosis and intervention prevents periodontitis progression in most patients. Increased susceptibility and suboptimal control of modifiable risk factors can result in poor response to therapy, and relapse. The chronic immune-inflammatory response to microbial biofilms at the tooth or dental implant surface is associated with systemic conditions such as cardiovascular disease, diabetes or gastrointestinal diseases. Oral fluid-based biomarkers have demonstrated easy accessibility and potential as diagnostics for oral and systemic diseases, including the identification of SARS-CoV-2 in saliva. Advances in biotechnology have led to innovations in lab-on-a-chip and biosensors to interface with oral-based biomarker assessment. This review highlights new developments in oral biomarker discovery and their validation for clinical application to advance precision oral medicine through improved diagnosis, prognosis and patient stratification. Their potential to improve clinical outcomes of periodontitis and associated chronic conditions will benefit the dental and overall public health.

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  • Buffer systems, artificial saliva, and selected saliva/serum samples show that PDA-based biosensing platforms can achieve improved biomolecule immobilization, signal transduction, fluorescence/electrochemical/SERS detection, and salivary biomarker analysis.

    “Buffer systems, artificial saliva, and selected saliva/serum samples show improved biomolecule immobilization, signal transduction, fluorescence/electrochemical/SERS detection, and salivary biomarker analysis.”

    From Polydopamine-Based Biomaterials in Oral Medicine: Applications, Mechanisms, and Translational Challenges (2026) · cites this paper as [97]

    The “Biosensors and Microelectro-Mechanical Systems” section describes biosensors detecting analytes in saliva, and “Salivary and Crevicular Fluid Diagnostics” discusses salivary biomarker analysis (page numbers unavailable). Our copy does not connect those findings to PDA-based platforms or report improved immobilization, signal transduction, fluorescence/electrochemical/SERS detection, or testing in buffer systems, artificial saliva, and selected saliva/serum samples. (LLM, conf=0.81)

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References 227 · Cited by 77

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  1. Aardema, 2002, Toxicology and genetic toxicology in the new era of “toxicogenomics”: impact of “-omics” technologies, Mutat. Res. Fund Mol. Mech. Mutagen, 499, 13, 10.1016/s0027-5107(01)00292-5 · DOI
  2. Afacan, 2020, Effect of non‐surgical periodontal treatment on gingival crevicular fluid hypoxia inducible factor‐1 alpha, vascular endothelial growth factor and tumor necrosis factor‐alpha levels in generalized aggressive periodontitis patients, J. Periodontol., 1, 10.1002/JPER.19-0521 · DOI
  3. Agard, 2013, PGE2 suppression of innate immunity during mucosal bacterial infection, Front. Cell Infect. Microbiol., 3, 4, 10.3389/fcimb.2013.00045 · DOI
  4. Ahrens, 2014, Oral health, dental care and mouthwash associated with upper aerodigestive tract cancer risk in Europe: the ARCAGE study, Oral Oncol., 50, 616, 10.1016/j.oraloncology.2014.03.001 · DOI
  5. Akdis, 2011, Interleukins, from 1 to 37, and interferon-γ: receptors, functions, and roles in diseases, J. Allergy Clin. Immunol., 127, 701, 10.1016/j.jaci.2010.11.050 · DOI
  6. Akram, 2016, Cytokine profile in chronic periodontitis patients with and without obesity: a systematic review and meta-analysis, Dis. Markers, 2016, 1, 10.1155/2016/4801418 · DOI
  7. Almeida, 2018, Is there an association between periodontitis and atherosclerosis in adults? A systematic review, Curr. Vasc. Pharmacol., 16, 569, 10.2174/1570161115666170830141852 · DOI
  8. Al-Rawi, 2020, Salivary microRNA 155, 146a/b and 203: a pilot study for potentially non-invasive diagnostic biomarkers of periodontitis and diabetes mellitus, PLoS One, 15, e0237004, 10.1371/journal.pone.0237004 · DOI
  9. Al-Shammari, 2001, Effect of non-surgical periodontal therapy on C-telopeptide pyridinoline cross-links (ICTP) and interleukin-1 levels, J. Periodontol., 72, 1045, 10.1902/jop.2001.72.8.1045 · DOI
  10. Antezack, 2020, Rapid diagnosis of periodontitis, a feasibility study using MALDI-TOF mass spectrometry, PLoS One, 15, e0230334, 10.1371/journal.pone.0230334 · DOI
  11. Artese, 2015, Periodontal therapy and systemic inflammation in type 2 diabetes mellitus: a meta-analysis, PLoS One, 10, e0128344, 10.1371/journal.pone.0128344 · DOI
  12. Arweiler, 2016, The oral microbiota, Adv. Exp. Med. Biol., 902, 45, 10.1007/978-3-319-31248-4_4 · DOI
  13. Atieh, 2014, Cytokines in patients with type 2 diabetes and chronic periodontitis: a systematic review and meta-analysis, Diabetes Res. Clin. Pract., 104, e38, 10.1016/j.diabres.2014.02.002 · DOI
  14. Atsawasuwan, 2018, Secretory microRNA-29 expression in gingival crevicular fluid during orthodontic tooth movement, PLoS One, 13, e0194238, 10.1371/journal.pone.0194238 · DOI
  15. Austermann, 2018, S100 proteins in rheumatic diseases, Nat. Rev. Rheumatol., 14, 528, 10.1038/s41584-018-0058-9 · DOI
  16. Azzi, 2020, Saliva is a reliable tool to detect SARS-CoV-2, J. Infect., 81, e45, 10.1016/j.jinf.2020.04.005 · DOI
  17. Baeza, 2020, Effect of periodontal treatment in patients with periodontitis and diabetes: systematic review and meta-analysis, J. Appl. Oral Sci., 28, e20190248, 10.1590/1678-7757-2019-0248 · DOI
  18. Bahekar, 2007, The prevalence and incidence of coronary heart disease is significantly increased in periodontitis: a meta-analysis, Am. Heart J., 154, 830, 10.1016/j.ahj.2007.06.037 · DOI
  19. Barros, 2020, Epigenetic reprogramming in periodontal disease: dynamic crosstalk with potential impact in oncogenesis, Periodontol. 2000, 82, 157, 10.1111/prd.12322 · DOI
  20. Barros, 2020, Maintaining barrier function of infected gingival epithelial cells by inhibition of DNA methylation, J. Periodontol., S68, 10.1002/JPER.20-0262 · DOI
  21. Bartel, 2004, MicroRNAs, Cell, 116, 281, 10.1016/s0092-8674(04)00045-5 · DOI
  22. Bartold, 2020, Periodontitis and rheumatoid arthritis: an update 2012–2017, Periodontol. 2000, 83, 189, 10.1111/prd.12300 · DOI
  23. Bender, 2017, Serum antibody levels against Porphyromonas gingivalis in patients with and without rheumatoid arthritis - a systematic review and meta-analysis, Clin. Oral Invest., 21, 33, 10.1007/s00784-016-1938-5 · DOI
  24. Bianchi, 2020, Osteoarthritis of the temporomandibular joint can be diagnosed earlier using biomarkers and machine learning, Sci. Rep., 10, 8012, 10.1038/s41598-020-64942-0 · DOI
  25. Blaizot, 2009, Periodontal diseases and cardiovascular events: meta-analysis of observational studies, Int. Dent. J., 59, 197, 10.1922/IDJ_2114Sixou13 · DOI
  26. Bostanci, 2007, Gingival crevicular fluid levels of RANKL and OPG in periodontal diseases: implications of their relative ratio, J. Clin. Periodontol., 34, 370, 10.1111/j.1600-051X.2007.01061.x · DOI
  27. Brinkmann, 2011, Salivary biomarkers for periodontal disease diagnostics, Expert Opin. Med. Diagn., 5, 25, 10.1517/17530059.2011.542144 · DOI
  28. Bryant, 2020, Serology for SARS-CoV-2: apprehensions, opportunities, and the path forward, Sci. Immunol., 5, eabc6347, 10.1126/sciimmunol.abc6347 · DOI
  29. Buck, 1992, Degradation of extracellular-matrix proteins by human cathepsin B from normal and tumour tissues, Biochem. J., 282, 273, 10.1042/bj2820273 · DOI
  30. Buhlin, 2009, Risk factors for atherosclerosis in cases with severe periodontitis, J. Clin. Periodontol., 36, 541, 10.1111/j.1600-051X.2009.01430.x · DOI
  31. Cagney, 2018, The FDA NIH biomarkers, endpointS, and other tools (BEST) resource in neuro-oncology, Neuro Oncol., 20, 1162, 10.1093/neuonc/nox242 · DOI
  32. Calderaro, 2017, Influence of periodontal treatment on rheumatoid arthritis: a systematic review and meta-analysis, Rev. Bras. Reumatol., 57, 238, 10.1016/j.rbre.2016.11.011 · DOI
  33. Chauhan, 2016, Recent advances in mycotoxins detection, Biosens. Bioelectron., 81, 532, 10.1016/j.bios.2016.03.004 · DOI
  34. Chen, 2015, Cyclic stretch and compression forces alter microRNA-29 expression of human periodontal ligament cells, Gene, 566, 13, 10.1016/j.gene.2015.03.055 · DOI
  35. Christersson, 1985, Microbiological and clinical effects of surgical treatment of localized juvenile periodontitis, J. Clin. Periodontol., 12, 465, 10.1111/j.1600-051x.1985.tb01382.x · DOI
  36. Cullinan, 2001, A longitudinal study of interleukin-1 gene polymorphisms and periodontal disease in a general adult population, J. Clin. Periodontol., 28, 1137, 10.1034/j.1600-051x.2001.281208.x · DOI
  37. Darré, 2008, Efficacy of periodontal treatment on glycaemic control in diabetic patients: a meta-analysis of interventional studies, Diabetes Metabol., 34, 497, 10.1016/j.diabet.2008.03.006 · DOI
  38. Delima, 2001, Soluble antagonists to interleukin-1 (IL-1) and tumor necrosis factor (TNF) inhibits loss of tissue attachment in experimental periodontitis, J. Clin. Periodontol., 28, 233, 10.1034/j.1600-051x.2001.028003233 · DOI
  39. Eicher, 2020, Metabolomics and multi-omics integration: a survey of computational methods and resources, Metabolites, 10, 202, 10.3390/metabo10050202 · DOI
  40. Engebretson, 2013, Evidence that periodontal treatment improves diabetes outcomes: a systematic review and meta-analysis, J. Clin. Periodontol., 40, S153, 10.1111/jcpe.12084 · DOI
  41. Erdemir, 2004, Effects of smoking on clinical parameters and the gingival crevicular fluid levels of IL-6 and TNF-alpha in patients with chronic periodontitis, J. Clin. Periodontol., 31, 99, 10.1111/j.0303-6979.2004.00454.x · DOI
  42. Eskandari-Nasab, 2017, Meta-analysis of risk association between interleukin-17a and F gene polymorphisms and inflammatory diseases, J. Interferon Cytokine Res., 37, 165, 10.1089/jir.2016.0088 · DOI
  43. Faggion, 2016, An overview of systematic reviews on the effectiveness of periodontal treatment to improve glycaemic control, J. Periodontal. Res., 51, 716, 10.1111/jre.12358 · DOI
  44. Fine, 2013, A consortium of aggregatibacter actinomycetemcomitans, Streptococcus parasanguinis, and Filifactor alocis is present in sites prior to bone loss in a longitudinal study of localized aggressive periodontitis, J. Clin. Microbiol., 51, 2850, 10.1128/JCM.00729-13 · DOI
  45. Freitag-Wolf, 2019, Smoking modifies the genetic risk for early-onset periodontitis, J. Dent. Res., 98, 1332, 10.1177/0022034519875443 · DOI
  46. Frencken, 2017, Global epidemiology of dental caries and severe periodontitis - a comprehensive review, J. Clin. Periodontol., 44, S94, 10.1111/jcpe.12677 · DOI · Paper page
  47. Fujimori, 2019, Detection of salivary miRNAs reflecting chronic periodontitis: a pilot study, Molecules, 24, 4, 10.3390/molecules24061034 · DOI
  48. Garde, 2019, Periodontal therapy for improving lipid profiles in patients with type 2 diabetes mellitus: a systematic review and meta-analysis, Int. J. Mol. Sci., 20, 3826, 10.3390/ijms20153826 · DOI
  49. Giannobile, 1999, C-telopeptide pyridinoline cross-links: sensitive indicators of periodontal tissue destruction, Ann. N. Y. Acad. Sci., 878, 404, 10.1111/j.1749-6632.1999.tb07698.x · DOI
  50. Giannobile, 2012, Salivary diagnostics for periodontal diseases, J. Am. Dent. Assoc., 143, 6S, 10.14219/jada.archive.2012.0341 · DOI
  51. Giannobile, 2013, Patient stratification for preventive care in dentistry, J. Dent. Res., 92, 694, 10.1177/0022034513492336 · DOI
  52. Giannobile, 2013, Personalized medicine enters dentistry, J. Am. Dent. Assoc., 144, 874, 10.14219/jada.archive.2013.0200 · DOI
  53. Giannobile, 1995, Crevicular fluid osteocalcin and pyridinoline cross-linked carboxyterminal telopeptide of type I collagen (ICTP) as markers of rapid bone turnover in periodontitis. A pilot study in beagle dogs, J. Clin. Periodontol., 22, 903, 10.1111/j.1600-051x.1995.tb01793.x · DOI
  54. Goodson, 1984, The relationship between attachment level loss and alveolar bone loss, J. Clin. Periodontol., 11, 348, 10.1111/j.1600-051x.1984.tb01331.x · DOI
  55. Goodson, 1982, Patterns of progression and regression of advanced destructive periodontal disease, J. Clin. Periodontol., 9, 472, 10.1111/j.1600-051x.1982.tb02108.x · DOI
  56. Grassl, 2016, Ultra-deep and quantitative saliva proteome reveals dynamics of the oral microbiome, Genome Med., 8, 44, 10.1186/s13073-016-0293-0 · DOI
  57. Gürsoy, 2018, Molecular forms and fragments of salivary MMP‐8 in relation to periodontitis, J. Clin. Periodontol., 45, 1421, 10.1111/jcpe.13024 · DOI
  58. Hajishengallis, 2014, Immunomicrobial pathogenesis of periodontitis: keystones, pathobionts, and host response, Trends Immunol., 35, 3, 10.1016/j.it.2013.09.001 · DOI · Paper page
  59. Hajishengallis, 2017, Revisiting the Page & Schroeder model: the good, the bad and the unknowns in the periodontal host response 40 years later, Periodontol. 2000, 75, 116, 10.1111/prd.12181 · DOI
  60. Han, 2012, Effect of anti-rheumatic agents on periodontal parameters and biomarkers of inflammation: a systematic review and meta-analysis, J. Periodontal Implant Sci., 42, 3, 10.5051/jpis.2012.42.1.3 · DOI
  61. Han, 2020, Salivry small extracellular vesicles associated miRNAs in periodontal status-A pilot study, Int. J. Mol. Sci., 21, 2809, 10.3390/ijms21082809 · DOI
  62. Hartenbach, 2020, Proteomic analysis of whole saliva in chronic periodontitis, J. Proteom., 213, 103602, 10.1016/j.jprot.2019.103602 · DOI
  63. Heikenfeld, 2019, Accessing analytes in biofluids for peripheral biochemical monitoring, Nat. Biotechnol., 37, 407, 10.1038/s41587-019-0040-3 · DOI · Paper page
  64. Heikkilä, 2018, Periodontitis and cancer mortality: register-based cohort study of 68,273 adults in 10-year follow-up, Int. J. Canc., 142, 2244, 10.1002/ijc.31254 · DOI
  65. Heinze, 2016, Longer-term increased cortisol levels in young people with mental health problems, Psychiatr. Res., 236, 98, 10.1016/j.psychres.2015.12 · DOI
  66. Heitzer, 2019, Current and future perspectives of liquid biopsies in genomics-driven oncology, Nat. Rev. Genet., 20, 71, 10.1038/s41576-018-0071-5 · DOI · Paper page
  67. Hussain, 2020, Is there a bidirectional association between rheumatoid arthritis and periodontitis? A systematic review and meta-analysis, Semin. Arthritis Rheum., 50, 414, 10.1016/j.semarthrit.2020.01.009 · DOI
  68. Iwasaki, 2020, Comparison of SARS-CoV-2 detection in nasopharyngeal swab and saliva, J. Infect., 81, e145, 10.1016/j.jinf.2020.05.071 · DOI
  69. Jain, 2019, Effect of scaling and root planing as monotherapy on glycemic control in patients of type 2 diabetes with chronic periodontitis: a systematic review and meta-analysis, J. Indian Soc. Periodontol., 23, 303, 10.4103/jisp.jisp_417_18 · DOI
  70. Jiménez, 2002, Lichen sclerosus et atrophicus manifesting with localized loss of periodontal attachment, Oral Dis., 8, 310, 10.1034/j.1601-0825.2002.02858.x · DOI
  71. Joshi, 2019, Detection of periodontal microorganisms in coronary atheromatous plaque specimens of myocardial infarction patients: a systematic review and meta-analysis, Trends Cardiovasc. Med., 30175, 10.1016/j.tcm.2019.12.005 · DOI
  72. Kaisti, 2017, Detection principles of biological and chemical FET sensors, Biosens. Bioelectron., 98, 437, 10.1016/j.bios.2017.07.010 · DOI
  73. Kang, 2019, Association between central obesity and tooth loss in the non‐obese people: results from the continuous National Health and Nutrition Examination Survey ( NHANES ) 1999–2012, J. Clin. Periodontol., 46, 430, 10.1111/jcpe.13091 · DOI
  74. Kassebaum, 2014, Global burden of severe periodontitis in 1990-2010, J. Dent. Res., 93, 1045, 10.1177/0022034514552491 · DOI · Paper page
  75. Kaur, 2014, Does periodontal treatment influence clinical and biochemical measures for rheumatoid arthritis? A systematic review and meta-analysis, Semin. Arthritis Rheum., 44, 113, 10.1016/j.semarthrit.2014.04.009 · DOI
  76. Kc, 2020, Diagnostic sensitivity and specificity of host‐derived salivary biomarkers in periodontal disease amongst adults: systematic review, J. Clin. Periodontol., 47, 289, 10.1111/jcpe.13218 · DOI
  77. Kebschull, 2015, Mini but mighty: microRNAs in the pathobiology of periodontal disease, Periodontol. 2000, 69, 201, 10.1111/prd.12095 · DOI
  78. Kinney, 2014, Crevicular fluid biomarkers and periodontal disease progression, J. Clin. Periodontol., 41, 113, 10.1111/jcpe.12194 · DOI
  79. Kinney, 2007, Oral fluid-based biomarkers of alveolar bone loss in periodontitis, Ann. N. Y. Acad. Sci., 1098, 230, 10.1196/annals.1384.028 · DOI
  80. Kitamoto, 2020, The intermucosal connection between the mouth and gut in commensal pathobiont-driven colitis, Cell, 182, 447, 10.1016/j.cell.2020.05.048 · DOI
  81. Kobayashi, 2016, Increased expression of interleukin-6 (IL-6) gene transcript in relation to IL-6 promoter hypomethylation in gingival tissue from patients with chronic periodontitis, Arch. Oral Biol., 69, 89, 10.1016/j.archoralbio.2016.05.018 · DOI
  82. Kornman, 2008, Mapping the pathogenesis of periodontitis: a new look, J. Periodontol., 79, 1560, 10.1902/jop.2008.080213 · DOI
  83. Kornman, 1997, The interleukin-1 genotype as a severity factor in adult periodontal disease, J. Clin. Periodontol., 24, 72, 10.1111/j.1600-051x.1997.tb01187.x · DOI
  84. Kornman, 2017, Quo vadis: what is the future of periodontics? How will we get there?, Periodontol. 2000, 75, 353, 10.1111/prd.12217 · DOI
  85. Kornman, 1997, The host response to the microbial challenge in periodontitis: assembling the players, Periodontol. 2000, 14, 33, 10.1111/j.1600-0757.1997.tb00191.x · DOI
  86. Kornman, 1985, Clinical and microbiological evaluation of therapy for juvenile periodontitis, J. Periodontol., 56, 443, 10.1902/jop.1985.56.8.443 · DOI
  87. Korte, 2016, Personalized medicine: an update of salivary biomarkers for periodontal diseases, Periodontol. 2000, 70, 26, 10.1111/prd.12103 · DOI
  88. Kröger, 2018, The severity of human peri‐implantitis lesions correlates with the level of submucosal microbial dysbiosis, J. Clin. Periodontol., 45, 1498, 10.1111/jcpe.13023 · DOI
  89. Kwok, 2007, Commentary: prognosis revisited: a system for assigning periodontal prognosis, J. Periodontol., 78, 2063, 10.1902/jop.2007.070210 · DOI
  90. Larsson, 2015, Epigenetics and its role in periodontal diseases: a state-of-the-art review, J. Periodontol., 86, 556, 10.1902/jop.2014.140559 · DOI
  91. Latella, 2009, Interleukin 1 gene cluster, myocardial infarction at young age and inflammatory response of human mononuclear cells, Immunol. Invest., 38, 203, 10.1080/08820130902766142 · DOI
  92. Lauritano, 2019, Prevalence of oral lesions and correlation with intestinal symptoms of inflammatory bowel disease: a systematic review, Diagnostics, 9, 77, 10.3390/diagnostics9030077 · DOI
  93. Lee, 2012, Bacterial and salivary biomarkers predict the gingival inflammatory profile, J. Periodontol., 83, 79, 10.1902/jop.2011.110060 · DOI
  94. Liu, 2020, Ability of S100 proteins and matrix metalloproteinase‐9 to identify periodontitis in a ligature‐induced periodontitis dog model, J. Clin. Periodontol., 47, 182, 10.1111/jcpe.13215 · DOI
  95. Loe, 1978, The natural history of periodontal disease in man, J. Periodontal. Res., 13, 563, 10.1111/j.1600-0765.1978.tb00210.x · DOI
  96. Luan, 2018, MicroRNAs and immunity in periodontal health and disease, Int. J. Oral Sci., 10, 24, 10.1038/s41368-018-0025-y · DOI
  97. Luan, 2017, MicroRNAs and periodontal homeostasis, J. Dent. Res., 96, 491, 10.1177/0022034516685711 · DOI
  98. MacGregor, 2005, Defining the normal bacterial flora of the oral cavity, J. Clin. Microbiol., 43, 5721, 10.1128/jcm.43.11.5721-5732.2005 · DOI · Paper page
  99. Maekawa, 2019, RNA sequencing for ligature induced periodontitis in mice revealed important role of S100A8 and S100A9 for periodontal destruction, Sci. Rep., 9, 14663, 10.1038/s41598-019-50959-7 · DOI
  100. Mager, 2005, The salivary microbiota as a diagnostic indicator of oral cancer: a descriptive, non-randomized study of cancer-free and oral squamous cell carcinoma subjects, J. Transl. Med., 3, 27, 10.1186/1479-5876-3-27 · DOI
  101. Martinez, 2019, Effect of smoking on the DNA methylation pattern of the SOCS1 promoter in epithelial cells from the saliva of patients with chronic periodontitis, J. Periodontol., 90, 1279, 10.1002/JPER.18-0692 · DOI
  102. Matsui, 2016, Effects of miR-223 on expression of IL-1β and IL-6 in human gingival fibroblasts, J. Oral Sci., 58, 101, 10.2334/josnusd.58.101 · DOI
  103. McCauley, 2002, Mediators of periodontal osseous destruction and remodeling: principles and implications for diagnosis and therapy, J. Periodontol., 73, 1377, 10.1902/jop.2002.73.11.1377 · DOI
  104. McGuire, 1996, Prognosis versus actual outcome. II. The effectiveness of clinical parameters in developing an accurate prognosis, J. Periodontol., 67, 658, 10.1902/jop.1996.67.7.658 · DOI
  105. McGuire, 1999, Prognosis versus actual outcome. IV. The effectiveness of clinical parameters and IL-1 genotype in accurately predicting prognoses and tooth survival, J. Periodontol., 70, 49, 10.1902/jop.1999.70.1.49 · DOI
  106. Meikle, 1994, Immunolocalization of matrix metalloproteinases and TIMP-1 (tissue inhibitor of metalloproteinases) in human gingival tissues from periodontitis patients, J. Periodontal. Res., 29, 118, 10.1111/j.1600-0765.1994.tb01100.x · DOI
  107. Meisel, 2012, Association of periodontitis with the risk of oral leukoplakia, Oral Oncol., 48, 859, 10.1016/j.oraloncology.2012.02.022 · DOI
  108. Michalowicz, 2000, Evidence of a substantial genetic basis for risk of adult periodontitis, J. Periodontol., 71, 1699, 10.1902/jop.2000.71.11.1699 · DOI
  109. Mico-Martinez, 2018, miR-1226 detection in GCF as potential biomarker of chronic periodontitis: a pilot study, Med. Oral, 23, e308, 10.4317/medoral.22329 · DOI
  110. Mukhopadhyay, 2019, Fibrinolysis and inflammation in venous thrombus resolution, Front. Immunol., 10, 1348, 10.3389/fimmu.2019.01348 · DOI
  111. Muñoz Aguilera, 2020, Periodontitis is associated with hypertension: a systematic review and meta-analysis, Cardiovasc. Res., 116, 28, 10.1093/cvr/cvz201 · DOI · Paper page
  112. Munz, 2018, Genome-wide association meta-analysis of coronary artery disease and periodontitis reveals a novel shared risk locus, Sci. Rep., 8, 13678, 10.1038/s41598-018-31980-8 · DOI
  113. Mustapha, 2007, Markers of systemic bacterial exposure in periodontal disease and cardiovascular disease risk: a systematic review and meta-analysis, J. Periodontol., 78, 2289, 10.1902/jop.2007.070140 · DOI
  114. Nascimento, 2019, Salivary levels of MPO, MMP-8 and TIMP-1 are associated with gingival inflammation response patterns during experimental gingivitis, Cytokine, 115, 135, 10.1016/j.cyto.2018.12.002 · DOI
  115. Nguyen, 2018, From lab on a chip to point of care devices: the role of open source microcontrollers, Micromachines, 9, 403, 10.3390/mi9080403 · DOI
  116. Nibali, 2019, What is the heritability of periodontitis? A systematic review, J. Dent. Res., 98, 632, 10.1177/0022034519842510 · DOI
  117. Nisha, 2019, Identification of a novel salivary biomarker miR‐143‐3p for periodontal diagnosis: a proof of concept study, J. Periodontol., 90, 1149, 10.1002/JPER.18-0729 · DOI
  118. Nowicki, 2018, Microbiota and metatranscriptome changes accompanying the onset of gingivitis, mBio, 9, e00575, 10.1128/mBio.00575-18 · DOI
  119. Offenbacher, 2010, Changes in gingival crevicular fluid inflammatory mediator levels during the induction and resolution of experimental gingivitis in humans, J. Clin. Periodontol., 37, 324, 10.1111/j.1600-051X.2010.01543.x · DOI
  120. Offenbacher, 2016, Genome-wide association study of biologically informed periodontal complex traits offers novel insights into the genetic basis of periodontal disease, Hum. Mol. Genet., 25, 2113, 10.1093/hmg/ddw069 · DOI
  121. Offenbacher, 2018, GWAS for Interleukin-1β levels in gingival crevicular fluid identifies IL37 variants in periodontal inflammation, Nat. Commun., 9, 3686, 10.1038/s41467-018-05940-9 · DOI
  122. Oliveira, 2009, DNA methylation status of theIL8gene promoter in oral cells of smokers and non-smokers with chronic periodontitis, J. Clin. Periodontol., 36, 719, 10.1111/j.1600-051X.2009.01446.x · DOI
  123. Ouyang, 2019, IL-10 family cytokines IL-10 and IL-22: from basic science to clinical translation, Immunity, 50, 871, 10.1016/j.immuni.2019.03.020 · DOI
  124. Page, 1997, The pathogenesis of human periodontitis: an introduction, Periodontol. 2000, 14, 9, 10.1111/j.1600-0757.1997.tb00189.x · DOI
  125. Papageorgiou, 2017, Inflammatory bowel disease and oral health: systematic review and a meta-analysis, J. Clin. Periodontol., 44, 382, 10.1111/jcpe.12698 · DOI
  126. Papageorgiou, 2015, Effect of overweight/obesity on response to periodontal treatment: systematic review and a meta-analysis, J. Clin. Periodontol., 42, 247, 10.1111/jcpe.12365 · DOI
  127. Papapanou, 2015, Systemic effects of periodontitis: lessons learned from research on atherosclerotic vascular disease and adverse pregnancy outcomes, Int. Dent. J., 65, 283, 10.1111/idj.12185 · DOI
  128. Papapanou, 2018, Periodontitis: consensus report of workgroup 2 of the 2017 world workshop on the classification of periodontal and peri-implant diseases and conditions, J. Clin. Periodontol., 45, S162, 10.1111/jcpe.12946 · DOI
  129. Paraskevas, 2008, A systematic review and meta-analyses on C-reactive protein in relation to periodontitis, J. Clin. Periodontol., 35, 277, 10.1111/j.1600-051X.2007.01173.x · DOI · Paper page
  130. Parker, 2010, Mass spectrometry for proteomics
  131. Parkhill, 2000, Association of interleukin-1 gene polymorphisms with early-onset periodontitis, J. Clin. Periodontol., 27, 682, 10.1034/j.1600-051x.2000.027009682.x · DOI
  132. Penoni, 2017, Bone density and clinical periodontal attachment in postmenopausal women: a systematic review and meta-analysis, J. Dent. Res., 96, 261, 10.1177/0022034516682017 · DOI
  133. Perri, 2012, MicroRNA modulation in obesity and periodontitis, J. Dent. Res., 91, 33, 10.1177/0022034511425045 · DOI
  134. Pietruska, 2009, Assessment of aprotinin influence on periodontal clinical status and matrix metalloproteinases 1, 2 and their tissue inhibitors saliva concentrations in patients with chronic periodontitis, Adv. Med. Sci., 54, 239, 10.2478/v10039-009-0027-2 · DOI
  135. Pitts, 2017, Dental caries, Nat. Rev. Dis. Primers, 3, 17030, 10.1038/nrdp.2017.30 · DOI · Paper page
  136. Qiao, 2020, Rheumatoid arthritis risk in periodontitis patients: a systematic review and meta-analysis, Joint Bone Spine, 10.1016/j.jbspin.2020.04.024 · DOI
  137. Radovic, 2018, MicroRNA-146a and microRNA-155 as novel crevicular fluid biomarkers for periodontitis in non-diabetic and type 2 diabetic patients, J. Clin. Periodontol., 45, 663, 10.1111/jcpe.12888 · DOI
  138. Rai, 2016, Relation between periodontal status and pre-cancerous condition (oral lichen planus): a pilot study, Adv. Clin. Exp. Med., 25, 763, 10.17219/acem/59014 · DOI
  139. Renvert, 2017, Cytokine and microbial profiles in relation to the clinical outcome following treatment of peri-implantitis, Clin. Oral Implants Res., 28, 1127, 10.1111/clr.12927 · DOI
  140. Reynolds, 1997, Mechanisms of connective tissue matrix destruction in periodontitis, Periodontol. 2000, 14, 144, 10.1111/j.1600-0757.1997.tb00195.x · DOI
  141. Rhodin, 2014, Chronic periodontitis genome-wide association studies, J. Dent. Res., 93, 882, 10.1177/0022034514544506 · DOI
  142. Ridker, 2008, Inflammation, C-reactive protein, and atherothrombosis, J. Periodontol., 79, 1544, 10.1902/jop.2008.080249 · DOI
  143. Rogus, 2008, IL1B gene promoter haplotype pairs predict clinical levels of interleukin-1β and C-reactive protein, Hum. Genet., 123, 387, 10.1007/s00439-008-0488-6 · DOI
  144. Romandini, 2018, Periodontitis and platelet count: a new potential link with cardiovascular and other systemic inflammatory diseases, J. Clin. Periodontol., 45, 1299, 10.1111/jcpe.13004 · DOI
  145. Sabino-Silva, 2020, Coronavirus COVID-19 impacts to dentistry and potential salivary diagnosis, Clin. Oral Invest., 24, 1619, 10.1007/s00784-020-03248-x · DOI
  146. Saito, 2017, MicroRNA profiling in gingival crevicular fluid of periodontitis-a pilot study, FEBS Open Bio., 7, 981, 10.1002/2211-5463.12238 · DOI
  147. Salminen, 2014, Salivary biomarkers of bacterial burden, inflammatory response, and tissue destruction in periodontitis, J. Clin. Periodontol., 41, 442, 10.1111/jcpe.12234 · DOI
  148. Sanz, 2018, Scientific evidence on the links between periodontal diseases and diabetes: consensus report and guidelines of the joint workshop on periodontal diseases and diabetes by the International Diabetes Federation and the European Federation of Periodontology, J. Clin. Periodontol., 45, 138, 10.1111/jcpe.12808 · DOI · Paper page
  149. Sawle, 2016, Identification of master regulator genes in human periodontitis, J. Dent. Res., 95, 1010, 10.1177/0022034516653588 · DOI
  150. Schaefer, 2018, Genetics of periodontitis: discovery, biology, and clinical impact, Periodontol. 2000, 78, 162, 10.1111/prd.12232 · DOI
  151. Schmidl, 2018, Epigenetic mechanisms regulating T-cell responses, J. Allergy Clin. Immunol., 142, 728, 10.1016/j.jaci.2018.07.014 · DOI
  152. Schulthess, 2019, The short chain fatty acid butyrate imprints an antimicrobial program in macrophages, Immunity, 50, 432, 10.1016/j.immuni.2018.12.018 · DOI · Paper page
  153. Sehic, 2017, Regulatory roles of microRNAs in human dental tissues, Gene, 596, 9, 10.1016/j.gene.2016.10.009 · DOI
  154. Seker, 2011, Solving medical problems with BioMEMS, IEEE Pulse, 2, 51, 10.1109/MPUL.2011.942928 · DOI
  155. Sen, 2018, Periodontal disease, regular dental care use, and incident ischemic stroke, Stroke, 49, 355, 10.1161/STROKEAHA.117.018990 · DOI
  156. She, 2020, Periodontitis and inflammatory bowel disease: a meta-analysis, BMC Oral Health, 20, 67, 10.1186/s12903-020-1053-5 · DOI
  157. Shi, 2018, The subgingival microbiome of periodontal pockets with different probing depths in chronic and aggressive periodontitis: a pilot study, Front. Cell. Infect. Microbiol., 8, 124, 10.3389/fcimb.2018.00124 · DOI
  158. Shin, 2019, Deep sequencing salivary proteins for periodontitis using proteomics, Clin. Oral Invest., 23, 3571, 10.1007/s00784-018-2779-1 · DOI
  159. Sierra, 2020, Sensor-integrated microfluidic approaches for liquid biopsies applications in early detection of cancer, Sensors, 20, 1317, 10.3390/s20051317 · DOI
  160. Sima, 2013, Diabetes mellitus and periodontal diseases, Curr. Diabetes Rep., 13, 445, 10.1007/s11892-013-0367-y · DOI
  161. Sims, 2010, The IL-1 family: regulators of immunity, Nat. Rev. Immunol., 10, 89, 10.1038/nri2691 · DOI
  162. Sipert, 2014, MicroRNA-146a and microRNA-155 show tissue-dependent expression in dental pulp, gingival and periodontal ligament fibroblasts in vitro, J. Oral Sci., 56, 157, 10.2334/josnusd.56.157 · DOI
  163. Slots, 2020, Primer on etiology and treatment of progressive/severe periodontitis: a systemic health perspective, Periodontol. 2000, 83, 272, 10.1111/prd.12325 · DOI
  164. Slots, 1983, Suppression of the periodontopathic microflora in localized juvenile periodontitis by systemic tetracycline, J. Clin. Periodontol., 10, 465, 10.1111/j.1600-051x.1983.tb02179.x · DOI
  165. Socransky, 1992, The bacterial etiology of destructive periodontal disease: current concepts, J. Periodontol., 63, 322, 10.1902/jop.1992.63.4s.322 · DOI
  166. Sorsa, 2020, Active MMP-8 (aMMP-8) as a grading and staging biomarker in the periodontitis classification, Diagnostics, 10, 61, 10.3390/diagnostics10020061 · DOI
  167. Spielmann, 2011, Saliva: diagnostics and therapeutic perspectives, Oral Dis., 17, 345, 10.1111/j.1601-0825.2010.01773.x · DOI
  168. Stoecklin-Wasmer, 2012, MicroRNAs and their target genes in gingival tissues, J. Dent. Res., 91, 934, 10.1177/0022034512456551 · DOI
  169. Streit, 2004, Metagenomics - the key to the uncultured microbes, Curr. Opin. Microbiol., 7, 492, 10.1016/j.mib.2004.08.002 · DOI
  170. Sudo, 2017, Association of NOD2 mutations with aggressive periodontitis, J. Dent. Res., 96, 1100, 10.1177/0022034517715432 · DOI
  171. Takagi, 2020, S100A9 increases IL-6 and RANKL expressions through MAPKs and STAT3 signaling pathways in osteocyte-like cells, BioMed Res. Int., 2020, 1, 10.1155/2020/7149408 · DOI
  172. Tang, 2017, A possible link between rheumatoid arthritis and periodontitis: a systematic review and meta-analysis, Int. J. Periodont. Restor. Dent., 37, 79, 10.11607/prd.2656 · DOI
  173. Teeuw, 2014, Treatment of periodontitis improves the atherosclerotic profile: a systematic review and meta-analysis, J. Clin. Periodontol., 41, 70, 10.1111/jcpe.12171 · DOI
  174. Teles, 2016, Modelling changes in clinical attachment loss to classify periodontal disease progression, J. Clin. Periodontol., 43, 426, 10.1111/jcpe.12539 · DOI
  175. Teles, 2018, Patterns of periodontal disease progression based on linear mixed models of clinical attachment loss, J. Clin. Periodontol., 45, 15, 10.1111/jcpe.12827 · DOI
  176. Teng, 2015, Prediction of early childhood caries via spatial-temporal variations of oral microbiota, Cell Host Microbe, 18, 296, 10.1016/j.chom.2015.08.005 · DOI
  177. To, Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study, Lancet Infect. Dis., 20, 565, 10.1016/S1473-3099(20)30196-1 · DOI
  178. To, Consistent detection of 2019 novel coronavirus in saliva, Clin. Infect. Dis., 71, 841, 10.1093/cid/ciaa149 · DOI
  179. Tonetti, 2018, Staging and grading of periodontitis: framework and proposal of a new classification and case definition, J. Periodontol., 89, S159, 10.1002/JPER.18-0006 · DOI · Paper page
  180. Vila, 2019, The power of saliva: antimicrobial and beyond, PLoS Pathog., 15, e1008058, 10.1371/journal.ppat.1008058 · DOI
  181. Wade, 2011, Has the use of molecular methods for the characterization of the human oral microbiome changed our understanding of the role of bacteria in the pathogenesis of periodontal disease?, J. Clin. Periodontol., 38, 7, 10.1111/j.1600-051X.2010.01679.x · DOI
  182. Walker, 2000, Genetic polymorphisms of the IL-1α and IL-1β genes in african-American LJP patients and an african-American control population, J. Periodontol., 71, 723, 10.1902/jop.2000.71.5.723 · DOI
  183. Wan, 2017, Liquid biopsies come of age: towards implementation of circulating tumour DNA, Nat. Rev. Canc., 17, 223, 10.1038/nrc.2017.7 · DOI · Paper page
  184. Wang, 2015, Maresin 1 biosynthesis and proresolving anti-infective functions with human-localized aggressive periodontitis leukocytes, Infect. Immun., 84, 658, 10.1128/IAI.01131-15 · DOI
  185. Wang, 2016, Protein biomarkers and microbial profiles in peri-implantitis, Clin. Oral Implants Res., 27, 1129, 10.1111/clr.12708 · DOI
  186. Wang, 2015, Detection of somatic mutations and HPV in the saliva and plasma of patients with head and neck squamous cell carcinomas, Sci. Transl. Med., 7, 293ra104, 10.1126/scitranslmed.aaa8507 · DOI
  187. Wang, 2018, Meta-analysis of the prognostic value of the neutrophil-to-lymphocyte ratio in oral squamous cell carcinoma, J. Oral Pathol. Med., 47, 353, 10.1111/jop.12688 · DOI
  188. Wong, 2012, Salivaomics, J. Am. Dent. Assoc., 143, 19S, 10.14219/jada.archive.2012.0339 · DOI
  189. Wyllie, 2020, Saliva is more sensitive for SARS-CoV-2 detection in COVID-19 patients than nasopharyngeal swabs, N. Engl. J. Med., 1283, 10.1056/NEJMc2016359 · DOI
  190. Xie, 2011, Comparison of microRNA profiles of human periodontal diseased and healthy gingival tissues, Int. J. Oral Sci., 3, 125, 10.4248/IJOS11046 · DOI
  191. Xu, 2020, Associations between osteoporosis and risk of periodontitis: a pooled analysis of observational studies, Oral Dis., 10.1111/odi.13531 · DOI
  192. Yao, 2014, Association of periodontal disease with oral cancer: a meta-analysis, Tumor Biol., 35, 7073, 10.1007/s13277-014-1951-8 · DOI
  193. Ye, 2016, Correlation between periodontal disease and oral cancer risk: a meta-analysis, J. Canc. Res. Therapeut., 12, 237, 10.4103/0973-1482.200746 · DOI
  194. Yost, 2015, Functional signatures of oral dysbiosis during periodontitis progression revealed by microbial metatranscriptome analysis, Genome Med., 7, 27, 10.1186/s13073-015-0153-3 · DOI
  195. Zeng, Periodontal disease and risk of head and neck cancer: a meta-analysis of observational studies, PLoS One, 8, e79017, 10.1371/journal.pone.0079017 · DOI
  196. Zeng, Tooth loss and head and neck cancer: a meta-analysis of observational studies, PLoS One, 8, e79074, 10.1371/journal.pone.0079074 · DOI
  197. Zhang, 2016, Saliva in the diagnosis of diseases, Int. J. Oral Sci., 8, 133, 10.1038/ijos.2016.38 · DOI
  198. Zhang, 2019, Distinct gene expression characteristics in epithelial cell-porphyromonas gingivalis interactions by integrating transcriptome analyses, Int. J. Med. Sci., 16, 1320, 10.7150/ijms.33728 · DOI
  199. Zhang, 2016, Biomarker levels in gingival crevicular fluid of subjects with different periodontal conditions: a cross-sectional study, Arch. Oral Biol., 72, 92, 10.1016/j.archoralbio.2016.08.020 · DOI
  200. Zhang, 2010, Alteration of PTGS2 promoter methylation in chronic periodontitis, J. Dent. Res., 89, 133, 10.1177/0022034509356512 · DOI

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Authors
Steigmann, L., Maekawa, S., Sima, C., Travan, S., Wang, C.-W., & Giannobile, W. V.
Affiliations
  • University of Michigan (US)
  • Tokyo Medical and Dental University (JP)
  • Harvard University (US)
Corresponding author
Giannobile, William V.
ORCID
Venue
Frontiers in Pharmacology
Publisher
Frontiers Media SA
Published
2020-11-09
Volume
11
Pages
588480-588480
ISSN
1663-9812 (ISSN-L)
DOI
10.3389/fphar.2020.588480
PMC
PMC7748088
OpenAlex
W3101335700
Cited by
77
References
227
Citations by year
2026: 17 · 2025: 16 · 2024: 17 · 2023: 10 · 2022: 11 · 2021: 5
FWCI
1.06
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Pharmacology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Osteology Foundation
Topics
  • Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
  • Physical Sciences › Engineering › Biomedical Engineering › Biosensors and Analytical Detection
  • Physical Sciences › Engineering › Biomedical Engineering › Microfluidic and Capillary Electrophoresis Applications
Keywords
periodontitis, oral biomarkers, lab-on-a-chip, biosensors, early diagnosis, periodontal disease, host-microbe interactions, dental implants, saliva, COVID-19 detection, systemic inflammation, patient stratification

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