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Background: A study was conducted to develop and validate a screening model using risk scores to identify individuals at high risk for developing upper aerodigestive tract (UADT) cancers in an Indian population.Methods: A hospital-based case-control study (n = 480) was conducted in Pune, India. We assessed risk factors for UADT cancers by administering a questionnaire through face-to-face interviews. We developed a risk factor model based on the statistically significant risk factors in multiple logistic regression. A total, single risk score was calculated per individual based on the adjusted odds ratio for each of their risk factors. Standard receiver operator characteristic curve was plotted for the total score and the presence of UADT cancers. The stratification ability of the model was determined using the c-statistic. The optimal criterion value was determined at the point on curve at which the Youden's index was maximal. Confidence intervals were calculated by bootstrapping.Results: Total risk score for each individual ranged from 0 to 26. Area under the receiver operating characteristic curve (95.8; P < 0.001) suggests strong predictive ability. A risk score criterion value of ≤10 produced optimal sensitivity (93.5%), specificity (71.1%), false-positive rate (28.8%), false-negative rate (6.4%), positive predictive value (74.8%), and negative predictive value (96.6%).Conclusion: This risk factor-based model has the potential of satisfactorily screening and detection of UADT cancers at its early stage in a high-risk population like India. The identified at-risk individuals can then be targeted for clinical examination and for focused preventive/treatment measures at the hospital. [ABSTRACT FROM AUTHOR]

Autoimmune diseases are complex disorders of largely unknown etiology. Genetic studies have identified a limited number of causal genes from a marginal number of individuals, and demonstrated a high degree of discordance in monozygotic twins. Studies have begun to reveal epigenetic contributions to these diseases, primarily through the study of DNA methylation, but chromatin and non-coding RNA changes are also emerging. Moving forward an integrative analysis of genomic, transcriptomic and epigenomic data, with the latter two coming from specific cell types, will provide an understanding that has been missed from genetics alone. We provide an overview of the current state of the field and vision for deriving the epigenomics of autoimmunity. [ABSTRACT FROM AUTHOR]

Gaining interests and expediency of precision medicine for various diseases has led to the search for non invasive techniques like liquid biopsies involving study of circulating cell free DNA (cfDNA) for diagnostic as well as prognostic applications. Present study reports that cfDNA in plasma of patients with Rheumatoid Arthritis are fragmented, modified and hence remain undetected using qPCR, the commonly used analytical assay. They are immunogenic to peripheral blood cells and stimulate them to secrete TNF‐α, a pro‐inflammatory cytokine making it imperative to detect cfDNA in patients for an effective therapeutic intervention. Hereby a non‐invasive colorimetric assay for naked eye discernment of cfDNA using gold nanoparticles is proposed which is potent in detecting long and short cfDNA fragments from small amount of blood, is inexpensive, label free, easy to perform and allows visual detection. This can be further explored to assess its diagnostic and prognostics implications in various human disorders. Unmodified gold nanoparticles (AuNPs) have affinity towards cfDNA and show distinct color change upon interaction, but fail to do same with fragmented cfDNA. This mechanism has been further exploited to identify fragmentation status of cfDNA of RA patients which are found to be more fragmented and immunogenic in nature when compared with control samples. [ABSTRACT FROM AUTHOR]