👤 Mitali Mukerji

We investigated the relationship between cerebrospinal fluid (CSF) and plasma biomarkers of inflammation, neurodegeneration, and neurocognitive performance in people with HIV (PWH), using longitudinal samples from two previously published cohorts: ACTG A5090 (virally suppressed on antiretroviral therapy, ART) and A736 (ART-naïve or failing). We analyzed paired CSF and plasma samples, as well as 7-domain standardized neurocognitive test scores, at baseline and 24 weeks. Biomarkers included markers of inflammation (e.g., TNF-α, IL-6, IP-10) and neurodegeneration (e.g., NFL, p-Tau217, Aβ42), which were quantified via high-sensitivity immunoassays. Associations with cognition were tested using regression, mediation, and interaction models. Cross-sectional analyses revealed nominal associations between inflammatory markers and cognitive performance, with plasma IL-6 and IP-10 at baseline, and CSF TNFα at week 24 showing the strongest correlations (p < 0.05, uncorrected); however, none survived correction for multiple comparisons. Conversely, higher CSF Aβ42 and plasma BDNF were positively associated with memory and executive function. Longitudinally, biomarker changes did not significantly predict change in global cognition (ΔNPZ-8); the strongest trend (p-Tau217, ρ = -0.12, p = 0.38) was not statistically significant, and multivariate models failed to identify robust predictors (R These results suggest a potential role of CSF TNFα in mediating the neurocognitive effects of HIV and highlight compartment-specific inflammatory dynamics. Plasma TNFα, GFAP, and NFL may serve as peripheral indicators of CNS pathology, though with only moderate concordance. Astrocyte-tau interactions require cautious interpretation pending replication in larger cohorts. Show less

Genetic differences in the target proteins, metabolizing enzymes 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 discovery programs albeit for the search of new chemical entities incorporates 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 discovery and development programs through a unique initiative of Ayurgenomics TRISUTRA consortium. Five aspects that have been carried out are (1) analysis of variability in FDA approved pharmacogenomics genes/SNPs in exomes of 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. Highlight of the study are (1) Exome sequencing revealed significant differences between Prakriti types in 28 SNPs of 11 FDA approved genes of pharmacogenomics relevance 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. Considering the molecular and genomics differences underlying Prakriti and relevance in disease pharmacogenomics studies, this novel integrative platform would help in identification of differently susceptible and drug responsive population. Additionally, integrated analysis of phenomic and genomic variations would not only allow identification of clinical and genomic markers of Prakriti for application in personalized medicine but also its integration in drug discovery and development programs. Show less