ArticleJournal of Ayurveda and integrative medicine
Association of coronary artery disease related single nucleotide-polymorphisms with extreme Prakriti types: Insights from a case control study.
Article in Journal of Ayurveda and integrative medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCoronary artery disease has well-established genetic variants but identification of susceptible ones is needed. Ayurveda stratifies people phenotypically termed as "Prakriti" to assess the risk.
objectivesThe present research was aimed to identify Prakriti stratified genetic risks for CAD. MATERIAL AND
methodsInitially, literature search was done using bioinformatics and manual-curation, to identify susceptible SNPs. Further, global-screening-array was performed to evaluate association of these polymorphisms in Prakriti stratified 200 CAD patients and 100 healthy controls. Thereafter, association of these polymorphisms with already done biochemical parameters and biomarkers was explored.
resultsBioinformatic approach resulted in 466 PMIDs reporting 694 SNPs associated with CAD. Further, manual search for only susceptible resulted in 255 susceptible SNPs across 134 candidate genes with 2.09 cumulative odds ratio in diverse populations. Among 255 SNPs, GSA analysis of isolated DNA samples of present cohort identified 5 SNPs (rs1544410, rs731236, rs1801133, rs7975232, and rs3825807) in VDR, MTHFR, ADAMTS7 genes in overall comparisons. While Prakriti stratification showed association of 4 SNPs in Vata, 8 SNPs in Pitta and 1 SNP in Kapha Prakriti group which were comparable with already documented biochemical parameters and biomarkers. Overall, stratification helped in assessing disease predisposition in specific Prakriti like Vata may be predisposed due to inflammatory pathways, Pitta due to Vitamin D deficiency and Kapha due to disturbed glycemic index.
conclusionOverall, we could identify 255 SNPs as risk factors for CAD in diverse populations and 5 SNPs in Indian cohort. Further, integrating Prakriti stratification could help in identifying more précised risks for personalized CAD management.
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