ABSTRACT
Amelogenesis imperfecta (AI) is a genetic disease characterized by poor formation of tooth enamel. AI occurs due to mutations, especially in AMEL, ENAM, KLK4, MMP20, and FAM83H, associated with changes in matrix proteins, matrix proteases, cell-matrix adhesion proteins, and transport proteins of enamel. Due to the wide variety of phenotypes, the diagnosis of AI is complex, requiring a genetic test to characterize it better. Thus, there is a demand for developing low-cost, noninvasive, and accurate platforms for AI diagnostics. This case-control pilot study aimed to test salivary vibrational modes obtained in attenuated total reflection fourier-transformed infrared (ATR-FTIR) together with machine learning algorithms: linear discriminant analysis (LDA), random forest, and support vector machine (SVM) could be used to discriminate AI from control subjects due to changes in salivary components. The best-performing SVM algorithm discriminates AI better than matched-control subjects with a sensitivity of 100%, specificity of 79%, and accuracy of 88%. The five main vibrational modes with higher feature importance in the Shapley Additive Explanations (SHAP) were 1010 cm-1, 1013 cm-1, 1002 cm-1, 1004 cm-1, and 1011 cm-1 in these best-performing SVM algorithms, suggesting these vibrational modes as a pre-validated salivary infrared spectral area as a potential biomarker for AI screening. In summary, ATR-FTIR spectroscopy and machine learning algorithms can be used on saliva samples to discriminate AI and are further explored as a screening tool.
Subject(s)
Amelogenesis Imperfecta , Machine Learning , Saliva , Humans , Amelogenesis Imperfecta/diagnosis , Amelogenesis Imperfecta/genetics , Amelogenesis Imperfecta/metabolism , Saliva/metabolism , Saliva/chemistry , Spectroscopy, Fourier Transform Infrared/methods , Female , Case-Control Studies , Male , Algorithms , Adult , Support Vector Machine , Pilot Projects , Discriminant Analysis , Biomarkers , Triage/methods , Adolescent , Young AdultABSTRACT
In this narrative review, we aim to point out the close relationship between mpox virus (MPXV) infection and the role of saliva as a diagnostic tool for mpox, considering the current molecular approach and in the perspective of OMICs application. The MPXV uses the host cell's rough endoplasmic reticulum, ribosomes, and cytoplasmic proteins to replicate its genome and synthesize virions for cellular exit. The presence of oral mucosa lesions associated with mpox infection is one of the first signs of infection; however, current diagnostic tools find it difficult to detect the virus before the rashes begin. MPXV transmission occurs through direct contact with an infected lesion and infected body fluids, including saliva, presenting a potential use of this fluid for diagnostic purposes. Currently available diagnostic tests for MPXV detection are performed either by real-time quantitative PCR (RT-qPCR) or ELISA, which presents several limitations since they are invasive tests. Despite current clinical trials with restricted sample size, MPXV DNA was detected in saliva with a sensitivity of 85%-100%. In this context, the application of transcriptomics, metabolomics, lipidomics, or proteomics analyses coupled with saliva can identify novel disease biomarkers. Thus, it is important to note that the identification and quantification of salivary DNA, RNA, lipid, protein, and metabolite can provide novel non-invasive biomarkers through the use of OMICs platforms aiding in the early detection and diagnosis of MPXV infection. Untargeted mass spectrometry (MS)-based proteomics reveals that some proteins also expressed in saliva were detected with greater expression differences in blood plasma when comparing mpox patients and healthy subjects, suggesting a promising alternative to be applied in screening or diagnostic platforms for mpox salivary diagnostics coupled to OMICs.
Subject(s)
Body Fluids , Communicable Diseases , Mpox (monkeypox) , Humans , Pathology, Oral , SalivaABSTRACT
Accurate, self-collected, and non-invasive diagnostics are critical to perform mass-screening diagnostic tests for COVID-19. This systematic review with meta-analysis evaluated the accuracy, sensitivity, and specificity of salivary diagnostics for COVID-19 based on SARS-CoV-2 RNA compared with the current reference tests using a nasopharyngeal swab (NPS) and/or oropharyngeal swab (OPS). An electronic search was performed in seven databases to find COVID-19 diagnostic studies simultaneously using saliva and NPS/OPS tests to detect SARS-CoV-2 by RT-PCR. The search resulted in 10,902 records, of which 44 studies were considered eligible. The total sample consisted of 14,043 participants from 21 countries. The accuracy, specificity, and sensitivity for saliva compared with the NPS/OPS was 94.3% (95%CI= 92.1;95.9), 96.4% (95%CI= 96.1;96.7), and 89.2% (95%CI= 85.5;92.0), respectively. Besides, the sensitivity of NPS/OPS was 90.3% (95%CI= 86.4;93.2) and saliva was 86.4% (95%CI= 82.1;89.8) compared to the combination of saliva and NPS/OPS as the gold standard. These findings suggest a similarity in SARS-CoV-2 RNA detection between NPS/OPS swabs and saliva, and the association of both testing approaches as a reference standard can increase by 3.6% the SARS-CoV-2 detection compared with NPS/OPS alone. This study supports saliva as an attractive alternative for diagnostic platforms to provide a non-invasive detection of SARS-CoV-2.
ABSTRACT
Background: Metallothioneins (MTs) gene polymorphisms have been associated with the ability of free radicalscavenging and detoxification of heavy metals leading to cancer development. Our aim was to revisit, in a Brazil-ian population, single-nucleotide polymorphisms (SNPs) of the MT gene family previously associated with oralsquamous cell carcinoma (OSCC).Material and Methods: A case-control investigation with 28 OSCC patients and 45 controls was conducted, usingconventional risk factors (tobacco use and alcohol consumption) as covariates. SNPs genotyping for rs8052334(MT1B), rs964372 (MT1B), and rs1610216 (MT2A) was performed by PCR-RFLP, and SNPs for rs11076161(MT1A) were analyzed by TaqMan assay.Results: The only SNP associated with increased risk for OSCC was the MT-1A AA genotype (OR = 4.7; p = 0.01).We have also evidenced for the first time a significant linkage disequilibrium between the SNPs of MT-2A andMT-1A in this population with the highest frequency (30%) of the unfavorable haplotype G/A/C/T (rs1610216 /rs11076161 / rs964372 / rs8052334) of MT gene polymorphisms (OR = 6.2; p = 0.04). Interestingly, after removingthe effects of conventional risk factors, we have uncovered the significance of the AA genotype of the rs11076161with increased odds of 19-fold higher towards OSCC development.Conclusions: This is the first demonstration that a significant linkage disequilibrium among gene polymor-phisms of the MT family may affect susceptibility to oral cancer, which is conditioned by the G/A/C/T haplotype(rs1610216/rs11076161/rs964372/ rs8052334) and the MT-1A gene polymorphism has a potential clinical utility forthe OSCC risk assessment.(AU)