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.

Background and ObjectivesPotassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene have a key role in insulin secretion and is of substantial interest as a candidate gene for type 2 diabetes (T2D). The current work was performed to delineate the genetic influence of KCNJ11 polymorphisms on risk of T2D in South Indian population through case-control association study along with systematic review and meta-analysis.MethodsA case-control study of 400 T2D cases and controls of South Indian origin were performed to analyze the association of KCNJ11 polymorphisms (rs5219, rs5215, rs41282930, rs1800467) and copy number variations (CNV) on the risk of T2D. In addition a systematic review and meta-analysis for KCNJ11 rs5219 was conducted in 3,831 cases and 3,543 controls from 5 published reports from South-Asian population by searching various databases. Odds ratio with 95% confidence interval (CI) was used to assess the association strength. Cochran's Q, I2 statistics were used to study heterogeneity between the eligible studies.Results KCNJ11 rs5215, C-G-C-C haplotype and two loci analysis (rs5219 vs rs1800467) showed a significant association with T2D but CNV analysis did not show significant variation between T2D cases and control subjects. Lower age of disease onset (P = 0.04) and higher body mass index (BMI) (P = 0.04) were associated with rs5219 TT genotype in T2D patients. The meta-analysis of KCNJ11 rs5219 on South Asian population showed no association on susceptibility to T2D with an overall pooled OR = 0.98, 95% CI = 0.83–1.16. Stratification analysis showed East Asian population and global population were associated with T2D when compared to South Asians.Conclusion KCNJ11 rs5219 is not independently associated with T2D in South-Indian population and our meta-analysis suggests that KCNJ11 polymorphism (rs5219) is associated with risk of T2D in East Asian population and global population but this outcome could not be replicated in South Asian sub groups.

Inflammation is known to adversely affect adult neurogenesis, wherein the source of inflammation is largely thought to be extraneous to the neurogenic niche. Here, we demonstrate that the adult hippocampal neural progenitors harbor an inflammatory potential that is proactively suppressed by transcription factor 4 (Tcf4). Deletion of Tcf4 in hippocampal nestin-expressing progenitors causes loss of proliferative capacity and acquisition of myeloid inflammatory properties. This transformation abolishes their differentiation potential and causes production of detrimental factors that adversely affect niche cells, causing inflammation in the dentate gyrus. Thus, on one hand, Tcf4 deletion causes abrogation of proliferative progenitors leading to reduction of adult neurogenesis, while on the other, their accompanying inflammatory transformation inflicts inflammation in the niche. Taken together, we provide the first evidence for a latent inflammatory potential of adult hippocampal neural progenitors and identify Tcf4 as a critical regulator that facilitates adult neurogenesis via proactive suppression of this detrimental potential.

Translating genome-wide association loci to therapies requires knowledge of the causal genes, their directionality of effect and the cell-types in which they act. To infer these relationships in the human brain, we implemented Mendelian randomisation using single cell-type expression quantitative trait loci (eQTLs) as genetic anchors. Expression QTLs were mapped across 8 major cell-types in brain tissue exclusively ascertained from donors with no history of brain disease. We report evidence for a causal association between the change in expression of 118 genes and one or more of 16 brain phenotypes, revealing candidate targets for risk mitigation and opportunities for shared preventative therapeutic strategies. We highlight key causal genes for neurodegenerative and neuropsychiatric disease and for each, we report its cellular context and the therapeutic directionality required for risk mitigation. Our use of control samples establishes a new resource for the causal interpretation of GWAS risk alleles for human brain phenotypes.