A novel gene THSD7A is associated with obesity.

Body mass index (BMI) is a non-invasive measurement of obesity. It is commonly used for assessing adiposity and obesity-related risk prediction. Genetic differences between ethnic groups are important factors, which contribute to the variation in phenotypic effects. India inhabited by the first out-of-Africa human population and the contemporary Indian populations are admixture of two ancestral populations; ancestral north Indians (ANI) and ancestral south Indians (ASI). Although ANI are related to Europeans, ASI are not related to any group outside Indian-subcontinent. Hence, we expect novel genetic loci associated with BMI. In association analysis, we found eight genic SNPs in extreme of distribution (P⩽3.75 × 10(-5)), of which WWOX has already been reported to be associated with obesity-related traits hence excluded from further study. Interestingly, we observed rs1526538, an intronic SNP of THSD7A; a novel gene significantly associated with obesity (P=2.88 × 10(-5), 8.922 × 10(-6) and 2.504 × 10(-9) in discovery, replication and combined stages, respectively). THSD7A is neural N-glycoprotein, which promotes angiogenesis and it is well known that angiogenesis modulates obesity, adipose metabolism and insulin sensitivity, hence our result find a correlation. This information can be used for drug target, early diagnosis of obesity and treatment.

DNA methylation analysis of phenotype specific stratified Indian population.

BACKGROUND: DNA methylation and its perturbations are an established attribute to a wide spectrum of phenotypic variations and disease conditions. Indian traditional system practices personalized medicine through indigenous concept of distinctly descriptive physiological, psychological and anatomical features known as prakriti. Here we attempted to establish DNA methylation differences in these three prakriti phenotypes. METHODS: Following structured and objective measurement of 3416 subjects, whole blood DNA of 147 healthy male individuals belonging to defined prakriti (Vata, Pitta and Kapha) between the age group of 20-30years were subjected to methylated DNA immunoprecipitation (MeDIP) and microarray analysis. After data analysis, prakriti specific signatures were validated through bisulfite DNA sequencing. RESULTS: Differentially methylated regions in CpG islands and shores were significantly enriched in promoters/UTRs and gene body regions. Phenotypes characterized by higher metabolism (Pitta prakriti) in individuals showed distinct promoter (34) and gene body methylation (204), followed by Vata prakriti which correlates to motion showed DNA methylation in 52 promoters and 139 CpG islands and finally individuals with structural attributes (Kapha prakriti) with 23 and 19 promoters and CpG islands respectively. Bisulfite DNA sequencing of prakriti specific multiple CpG sites in promoters and 5'-UTR such as; LHX1 (Vata prakriti), SOX11 (Pitta prakriti) and CDH22 (Kapha prakriti) were validated. Kapha prakriti specific CDH22 5'-UTR CpG methylation was also found to be associated with higher body mass index (BMI). CONCLUSION: Differential DNA methylation signatures in three distinct prakriti phenotypes demonstrate the epigenetic basis of Indian traditional human classification which may have relevance to personalized medicine.

Genome-wide analysis correlates Ayurveda Prakriti.

The practice of Ayurveda, the traditional medicine of India, is based on the concept of three major constitutional types (Vata, Pitta and Kapha) defined as "Prakriti". To the best of our knowledge, no study has convincingly correlated genomic variations with the classification of Prakriti. In the present study, we performed genome-wide SNP (single nucleotide polymorphism) analysis (Affymetrix, 6.0) of 262 well-classified male individuals (after screening 3416 subjects) belonging to three Prakritis. We found 52 SNPs (p ≤ 1 × 10(-5)) were significantly different between Prakritis, without any confounding effect of stratification, after 10(6) permutations. Principal component analysis (PCA) of these SNPs classified 262 individuals into their respective groups (Vata, Pitta and Kapha) irrespective of their ancestry, which represent its power in categorization. We further validated our finding with 297 Indian population samples with known ancestry. Subsequently, we found that PGM1 correlates with phenotype of Pitta as described in the ancient text of Caraka Samhita, suggesting that the phenotypic classification of India's traditional medicine has a genetic basis; and its Prakriti-based practice in vogue for many centuries resonates with personalized medicine.

Immunophenotyping of normal individuals classified on the basis of human dosha prakriti.

BACKGROUND: Human variations related to immune response and disease susceptibility is well-documented in Ayurveda. Prakriti (body constitution) is the basic constitution of an individual established at the time of birth and distinguishes variations, into three broad phenotype categories such as vata, pitta and kapha. Variation in immune response is often attributed to and measured from the difference in cluster differentiation (CD) markers expressed in lymphocytes. Currently, there are no reports available on the expression of CD markers related to prakriti. OBJECTIVE: This is a pilot study performed to evaluate a panel of lymphocyte subset CD markers in dominant prakriti individuals. MATERIALS AND METHODS: Immunophenotyping was carried out using whole blood from a total of healthy 222 subjects, who are grouped into kapha (n = 95), pitta (n = 57) and vata (n = 70) prakritis. CD markers such as CD3, CD4, CD8, CD14, CD25, CD56, CD69, CD71 and HLA-DR were analyzed using flow cytometry method. Differences between groups were analyzed using one-way ANOVA or Kruskal-Wallis analysis of variance (ANOVA) and multiple comparisons between groups were performed by Bonferroni or Mann-Whitney U test with corrections for type I error respectively. Significance was evaluated by ANOVA and Pearson's correlation. RESULTS: We observed a significant difference (P < 0.05) in the expression of CD markers such as CD14 (monocytes), CD25 (activated B cells) and CD56 (Natural killer cells) between different prakriti groups. CD25 and CD56 expression was significantly higher in kapha prakriti samples than other prakriti groups. Similarly, slightly higher levels of CD14 were observed in pitta prakriti samples. CONCLUSION: Significant difference in the expression of CD14, CD25 and CD56 markers between three different prakriti is demonstrated. The increased level of CD25 and CD56 in kapha prakriti may indicate ability to elicit better immune response, which is in conformity with textual references in Ayurveda.

Determinants of prakriti, the human constitution types of Indian traditional medicine and its correlation with contemporary science.

BACKGROUND: Constitutional type of an individual or prakriti is the basic clinical denominator in Ayurveda, which defines physical, physiological, and psychological traits of an individual and is the template for individualized diet, lifestyle counseling, and treatment. The large number of phenotype description by prakriti determination is based on the knowledge and experience of the assessor, and hence subject to inherent variations and interpretations. OBJECTIVE: In this study we have attempted to relate dominant prakriti attribute to body mass index (BMI) of individuals by assessing an acceptable tool to provide the quantitative measure to the currently qualitative ayurvedic prakriti determination. MATERIALS AND METHODS: The study is cross sectional, multicentered, and prakriti assessment of a total of 3416 subjects was undertaken. Healthy male, nonsmoking, nonalcoholic volunteers between the age group of 20-30 were screened for their prakriti after obtaining written consent to participate in the study. The prakriti was determined on the phenotype description of ayurvedic texts and simultaneously by the use of a computer-aided prakriti assessment tool. Kappa statistical analysis was employed to validate the prakriti assessment and Chi-square, Cramer's V test to determine the relatedness in the dominant prakriti to various attributes. RESULTS: We found 80% concordance between ayurvedic physician and software in predicting the prakriti of an individual. The kappa value of 0.77 showed moderate agreement in prakriti assessment. We observed a significant correlations of dominant prakriti to place of birth and BMI with Chi-square, P < 0.01 (Cramer's V-value of 0.156 and 0.368, respectively). CONCLUSION: The present study attempts to integrate knowledge of traditional ayurvedic concepts with the contemporary science. We have demonstrated analysis of prakriti classification and its association with BMI and place of birth with the implications to one of the ways for human classification.