Ayurgenomics for stratified medicine: TRISUTRA consortium initiative across ethnically and geographically diverse Indian populations.

Abstract Background Genetic differences in the target proteins, metabolizingenzymes and transporters that contribute to inter-individual differences in drug response are not integrated in contemporary drug development programs. Ayurveda, that has propelled many drug discoveryprograms albeit for the search of new chemical entitiesincorporates inter-individual variability “ Prakriti ” in development and administration of drug in an individualized manner. Prakriti of an individual largely determines responsiveness to external environment including drugs as well as susceptibility to diseases. Prakriti has also been shown to have molecular and genomic correlates. We highlight how integration of Prakriti concepts can augment the efficiency of drug discoveryand development programs through a unique initiative of Ayurgenomics TRISUTRA consortium. Methods Five aspects that have been carried out are (1) analysis of variability in FDA approved pharmacogenomicsgenes/SNPs in exomesof 72 healthy individuals including predominant Prakriti types and matched controls from a North Indian Indo-European cohort (2) establishment of a consortium network and development of five genetically homogeneous cohorts from diverse ethnic and geo-climatic background (3) identification of parameters and development of uniform standard protocols for objective assessment of Prakriti types (4) development of protocols for Prakriti evaluation and its application in more than 7500 individuals in the five cohorts (5) Development of data and sample repository and integrative omics pipelines for identification of genomic correlates. Results Highlight of the study are (1) Exomesequencing revealed significant differences between Prakriti types in 28 SNPs of 11 FDA approved genes of pharmacogenomicsrelevance viz. CYP2C19, CYP2B6, ESR1, F2, PGR, HLA-B, HLA-DQA1, HLA-DRB1, LDLR, CFTR, CPS1. These variations are polymorphic in diverse Indian and world populations included in 1000 genomes project. (2) Based on the phenotypic attributes of Prakriti we identified anthropometry for anatomical features, biophysical parameters for skin types, HRV for autonomic function tests, spirometry for vital capacity and gustometry for taste thresholds as objective parameters. (3) Comparison of Prakriti phenotypes across different ethnic, age and gender groups led to identification of invariant features as well as some that require weighted considerations across the cohorts. Conclusion Considering the molecular and genomics differences underlying Prakriti and relevance in disease pharmacogenomicsstudies, this novel integrative platformwould help in identification of differently susceptible and drug responsive population. Additionally, integrated analysis of phenomicand genomic variations would not only allow identification of clinical and genomic markers of Prakriti for application in personalized medicinebut also its integration in drug discoveryand development programs.