Pharmacogenomic biomarkers in coronary artery disease: a narrative review.

Coronary artery disease (CAD) has a high mortality rate. Despite various therapeutic targets, non-responsiveness to drugs remains a prevalent issue. Pharmacogenomics assesses the way an individual's genetic attributes affect their likely response to drug therapy. Single-nucleotide polymorphisms play a crucial role in determining these outcomes. This review offers an overview of single-nucleotide polymorphisms investigated in clinical studies and their associations with drug response/nonresponse in the treatment of CAD. A total of 104 studies of whole sets of chromosomes and several genes were explored. A total of 161 polymorphisms exhibited associations with drug response/nonresponse in CAD across diverse ethnic populations. This pool can serve as a pharmacogenomic biomarker for predicting response to drug therapy in patients with CAD.

Exonized Alu repeats in the 3'UTR of a CYP20A1_Alu-LT transcript act as a miRNA sponge.

OBJECTIVE: Alu repeats have gained huge importance in the creation and modification of regulatory networks. We previously reported a unique isoform of human CYP20A1 i.e. CYP20A1_Alu-LT with 23 Alu repeats exonized in its 9 kb long 3'UTR with 4742 potential binding sites for 994 miRNAs. The role of this transcript was hypothesized as a potential miRNA sponge in primary neurons as its expression correlated with that of 380 genes having shared miRNA sites and enriched in neuro-coagulopathy. This study provides experimental evidence for the miRNA sponge activity of CYP20A1_Alu-LT in neuronal cell lines. RESULTS: We studied the Alu-rich fragment of the CYP20A1_Alu-LT extended 3'UTR with > 10 binding sites for miR-619-5p and miR-3677-3p. Enrichment of the Alu-rich fragment with Ago2 confirmed miRNA association of this transcript. Cloning the fragment downstream of a reporter gene led to a 90% decrease in luciferase activity. Overexpression and knockdown studies revealed a positive correlation between the expression of CYP20A1_Alu-LT and miR-619-5p / miR-3677-3p target genes. GAP43, one of the key modulators of nerve regeneration, was significantly altered by the expression of CYP20A1_Alu-LT. This study, for the first time, provides evidence for a unique regulatory function of exonized Alu repeats as miRNA sponges.

Ayurgenomics-based frameworks in precision and integrative medicine: Translational opportunities.

In today's globalized and flat world, a patient can access and seek multiple health and disease management options. A digitally enabled participatory framework that allows an evidence-based informed choice is likely to assume an immense importance in the future. In India, traditional knowledge systems, like Ayurveda, coexist with modern medicine. However, due to limited crosstalk between the clinicians of both disciplines, a patient attempts integrative medicine by seeking both options independently with limited understanding and evidence. There is a need for an integrative medicine platform with a formalized approach, which allows practitioners from the two diverse systems to crosstalk, coexist, and coevolve for an informed cross-referral that benefits the patients. To be successful, this needs frameworks that enable the bridging of disciplines through a common interface with shared ontologies. Ayurgenomics is an emerging discipline that explores the principles and practices of Ayurveda combined with genomics approaches for mainstream integration. The present review highlights how in conjunction with different disciplines and technologies this has provided frameworks for (1) the discovery of molecular correlates to build ontological links between the two systems, (2) the discovery of biomarkers and targets for early actionable interventions, (3) understanding molecular mechanisms of drug action from its usage perspective in Ayurveda with applications in repurposing, (4) understanding the network and P4 medicine perspective of Ayurveda through a common organizing principle, (5) non-invasive stratification of healthy and diseased individuals using a compendium of system-level phenotypes, and (6) developing evidence-based solutions for practice in integrative medicine settings. The concordance between the two contrasting streams has been built through extensive explorations and iterations of the concepts of Ayurveda and genomic observations using state-of-the-art technologies, computational approaches, and model system studies. These highlight the enormous potential of a trans-disciplinary approach in evolving solutions for personalized interventions in integrative medicine settings.

Heart rate variability during head-up tilt shows inter-individual differences among healthy individuals of extreme Prakriti types.

Autonomic modulation is critical during various physiological activities, including orthostatic stimuli and primarily evaluated by heart rate variability (HRV). Orthostatic stress affects people differently suggesting the possibility of identification of predisposed groups to autonomic dysfunction-related disorders in a healthy state. One way to understand this kind of variability is by using Ayurvedic approach that classifies healthy individuals into Prakriti types based on clinical phenotypes. To this end, we explored the differential response to orthostatic stress in different Prakriti types using HRV. HRV was measured in 379 subjects(Vata = 97, Pitta = 68, Kapha = 68, and Mixed Prakriti = 146) from two geographical regions(Vadu and Delhi NCR) for 5 min supine (baseline), 3 min head-up-tilt (HUT) at 60°, and 5 min resupine. We observed that Kapha group had lower baseline HRV than other two groups, although not statistically significant. The relative change (%Δ1&2 ) in various HRV parameters in response to HUT was although minimal in Kapha group. Kapha also had significantly lower change in HR, LF (nu), HF (nu), and LF/HF than Pitta in response to HUT. The relative change (%Δ1 ) in HR and parasympathetic parameters (RMSSD, HF, SD1) was significantly greater in the Vata than in the Kapha. Thus, the low baseline and lower response to HUT in Kapha and the maximum drop in parasympathetic activity of Vata may indicate a predisposition to early autonomic dysfunction and associated conditions. It emphasizes the critical role of Prakriti-based phenotyping in stratifying the differential responses of cardiac autonomic modulation in various postures among healthy individuals across different populations.

Population history and genome wide association studies of birth weight in a native high altitude Ladakhi population.

Pathological low birth weight due to fetal growth restriction (FGR) is an important predictor of adverse obstetric and neonatal outcomes. It is more common amongst native lowlanders when gestating in the hypoxic environment of high altitude, whilst populations who have resided at high altitude for many generations are relatively protected. Genetic study of pregnant populations at high altitude permits exploration of the role of hypoxia in FGR pathogenesis, and perhaps of FGR pathogenesis more broadly. We studied the umbilical cord blood DNA of 316 neonates born to pregnant women managed at the Sonam Norboo Memorial Hospital, Ladakh (altitude 3540m) between February 2017 and January 2019. Principal component, admixture and genome wide association studies (GWAS) were applied to dense single nucleotide polymorphism (SNP) genetic data, to explore ancestry and genetic predictors of low birth weight. Our findings support Tibetan ancestry in the Ladakhi population, with subsequent admixture with neighboring Indo-Aryan populations. Fetal growth protection was evident in Ladakhi neonates. Although no variants achieved genome wide significance, we observed nominal association of seven variants across genes (ZBTB38, ZFP36L2, HMGA2, CDKAL1, PLCG1) previously associated with birthweight.

Landscape of Variability in Chemosensory Genes Associated With Dietary Preferences in Indian Population: Analysis of 1029 Indian Genomes.

Perception and preferences for food and beverages determine dietary behaviour and health outcomes. Inherent differences in chemosensory genes, ethnicity, geo-climatic conditions, and sociocultural practices are other determinants. We aimed to study the variation landscape of chemosensory genes involved in perception of taste, texture, odour, temperature and burning sensations through analysis of 1,029 genomes of the IndiGen project and diverse continental populations. SNPs from 80 chemosensory genes were studied in whole genomes of 1,029 IndiGen samples and 2054 from the 1000 Genomes project. Population genetics approaches were used to infer ancestry of IndiGen individuals, gene divergence and extent of differentiation among studied populations. 137,760 SNPs including common and rare variants were identified in IndiGenomes with 62,950 novel (46%) and 48% shared with the 1,000 Genomes. Genes associated with olfaction harbored most SNPs followed by those associated with differences in perception of salt and pungent tastes. Across species, receptors for bitter taste were the most diverse compared to others. Three predominant ancestry groups within IndiGen were identified based on population structure analysis. We also identified 1,184 variants that exhibit differences in frequency of derived alleles and high population differentiation (FST ≥0.3) in Indian populations compared to European, East Asian and African populations. Examples include ADCY10, TRPV1, RGS6, OR7D4, ITPR3, OPRM1, TCF7L2, and RUNX1. This is a first of its kind of study on baseline variations in genes that could govern cuisine designs, dietary preferences and health outcomes. This would be of enormous utility in dietary recommendations for precision nutrition both at population and individual level.

Anti-SARS-CoV-2 potential of Cissampelos pareira L. identified by connectivity map-based analysis and in vitro studies.

BACKGROUND: Viral infections have a history of abrupt and severe eruptions through the years in the form of pandemics. And yet, definitive therapies or preventive measures are not present. Herbal medicines have been a source of various antiviral compounds such as Oseltamivir, extracted using shikimic acid from star anise (Illicium verum) and Acyclovir from Carissa edulis are FDA (Food and Drug Administration) approved antiviral drugs. In this study, we dissect the anti-coronavirus infection activity of Cissampelos pareira L (Cipa) extract using an integrative approach. METHODS: We analysed the signature similarities between predicted antiviral agents and Cipa using the connectivity map ( https://clue.io/ ). Next, we tested the anti-SARS-COV-2 activity of Cipa in vitro. Molecular docking analyses of constituents of with key targets of SARS-CoV2 protein viz. spike protein, RNA­dependent RNA­polymerase (RdRp) and 3C­like proteinase. was also performed. A three-way comparative analysis of Cipa transcriptome, COVID-19 BALF transcriptome and CMAP signatures of small compounds was also performed. RESULTS: Several predicted antivirals showed a high positive connectivity score with Cipa such as apcidin, emetine, homoharringtonine etc. We also observed 98% inhibition of SARS-COV-2 replication in infected Vero cell cultures with the whole extract. Some of its prominent pure constituents e.g. pareirarine, cissamine, magnoflorine exhibited 40-80% inhibition. Comparison of genes between BALF and Cipa showed an enrichment of biological processes like transcription regulation and response to lipids, to be downregulated in Cipa while being upregulated in COVID-19. CMAP also showed that Triciribine, torin-1 and VU-0365114-2 had positive connectivity with BALF 1 and 2, and negative connectivity with Cipa. Amongst all the tested compounds, Magnoflorine and Salutaridine exhibited the most potent and consistent strong in silico binding profiles with SARS-CoV2 therapeutic targets.

Whole Exome Sequencing in Healthy Individuals of Extreme Constitution Types Reveals Differential Disease Risk: A Novel Approach towards Predictive Medicine.

Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed "Prakriti". It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy Prakriti stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 (IFIT5) and rs941590 (SERPINA10) that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.

An Alu insertion map of the Indian population: identification and analysis in 1021 genomes of the IndiGen project.

Actively retrotransposing primate-specific Alu repeats display insertion-deletion (InDel) polymorphism through their insertion at new loci. In the global datasets, Indian populations remain under-represented and so do their Alu InDels. Here, we report the genomic landscape of Alu InDels from the recently released 1021 Indian Genomes (IndiGen) (available at https://clingen.igib.res.in/indigen). We identified 9239 polymorphic Alu insertions that include private (3831), rare (3974) and common (1434) insertions with an average of 770 insertions per individual. We achieved an 89% PCR validation of the predicted genotypes in 94 samples tested. About 60% of identified InDels are unique to IndiGen when compared to other global datasets; 23% of sites were shared with both SGDP and HGSVC; among these, 58% (1289 sites) were common polymorphisms in IndiGen. The insertions not only show a bias for genic regions, with a preference for introns but also for the associated genes showing enrichment for processes like cell morphogenesis and neurogenesis (P-value < 0.05). Approximately, 60% of InDels mapped to genes present in the OMIM database. Finally, we show that 558 InDels can serve as ancestry informative markers to segregate global populations. This study provides a valuable resource for baseline Alu InDels that would be useful in population genomics.

HLA-SPREAD: a natural language processing based resource for curating HLA association from PubMed abstracts.

Extreme complexity in the Human Leukocyte Antigens (HLA) system and its nomenclature makes it difficult to interpret and integrate relevant information for HLA associations with diseases, Adverse Drug Reactions (ADR) and Transplantation. PubMed search displays ~ 146,000 studies on HLA reported from diverse locations. Currently, IPD-IMGT/HLA (Robinson et al., Nucleic Acids Research 48:D948-D955, 2019) database houses data on 28,320 HLA alleles. We developed an automated pipeline with a unified graphical user interface HLA-SPREAD that provides a structured information on SNPs, Populations, REsources, ADRs and Diseases information. Information on HLA was extracted from ~ 28 million PubMed abstracts extracted using Natural Language Processing (NLP). Python scripts were used to mine and curate information on diseases, filter false positives and categorize to 24 tree hierarchical groups and named Entity Recognition (NER) algorithms followed by semantic analysis to infer HLA association(s). This resource from 109 countries and 40 ethnic groups provides interesting insights on: markers associated with allelic/haplotypic association in autoimmune, cancer, viral and skin diseases, transplantation outcome and ADRs for hypersensitivity. Summary information on clinically relevant biomarkers related to HLA disease associations with mapped susceptible/risk alleles are readily retrievable from HLASPREAD. The resource is available at URL http://hla-spread.igib.res.in/ . This resource is first of its kind that can help uncover novel patterns in HLA gene-disease associations.

Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes.

During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying variants of concern (VOC). Viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host single nucleotide variations (iSNVs). Analysing 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.

Genetic epidemiology of autoinflammatory disease variants in Indian population from 1029 whole genomes.

BACKGROUND: Autoinflammatory disorders are the group of inherited inflammatory disorders caused due to the genetic defect in the genes that regulates innate immune systems. These have been clinically characterized based on the duration and occurrence of unprovoked fever, skin rash, and patient's ancestry. There are several autoinflammatory disorders that are found to be prevalent in a specific population and whose disease genetic epidemiology within the population has been well understood. However, India has a limited number of genetic studies reported for autoinflammatory disorders till date. The whole genome sequencing and analysis of 1029 Indian individuals performed under the IndiGen project persuaded us to perform the genetic epidemiology of the autoinflammatory disorders in India. RESULTS: We have systematically annotated the genetic variants of 56 genes implicated in autoinflammatory disorder. These genetic variants were reclassified into five categories (i.e., pathogenic, likely pathogenic, benign, likely benign, and variant of uncertain significance (VUS)) according to the American College of Medical Genetics and Association of Molecular pathology (ACMG-AMP) guidelines. Our analysis revealed 20 pathogenic and likely pathogenic variants with significant differences in the allele frequency compared with the global population. We also found six causal founder variants in the IndiGen dataset belonging to different ancestry. We have performed haplotype prediction analysis for founder mutations haplotype that reveals the admixture of the South Asian population with other populations. The cumulative carrier frequency of the autoinflammatory disorder in India was found to be 3.5% which is much higher than reported. CONCLUSION: With such frequency in the Indian population, there is a great need for awareness among clinicians as well as the general public regarding the autoinflammatory disorder. To the best of our knowledge, this is the first and most comprehensive population scale genetic epidemiological study being reported from India.

A rigorous framework for detecting SARS-CoV-2 spike protein mutational ensemble from genomic and structural features.

The recent release of SARS-CoV-2 genomic data from several countries has provided clues into the potential antigenic drift of the coronavirus population. In particular, the genomic instability observed in the spike protein necessitates immediate action and further exploration in the context of viral-host interactions. By temporally tracking 527,988 SARS-CoV-2 genomes, we identified invariant and hypervariable regions within the spike protein. We evaluated combination of mutations from SARS-CoV-2 lineages and found that maximum number of lineage-defining mutations were present in the N-terminal domain (NTD). Based on mutant 3D-structural models of known Variants of Concern (VOCs), we found that structural properties such as accessibility, secondary structural type, and intra-protein interactions at local mutation sites are greatly altered. Further, we observed significant differences between intra-protein networks of wild-type and Delta mutant, with the latter showing dense intra-protein contacts. Extensive molecular dynamics simulations of D614G mutant spike structure with hACE2 further revealed dynamic features with 47.7% of mutations mapping on flexible regions of spike protein. Thus, we propose that significant changes within spike protein structure have occurred that may impact SARS-CoV-2 pathogenesis, and repositioning of vaccine candidates is required to contain the spread of COVID-19 pathogen.

Transcriptome analysis and connectivity mapping of Cissampelos pareira L. provides molecular links of ESR1 modulation to viral inhibition.

Bioactive fractions obtained from medicinal plants which have been used for the treatment of multiple diseases could exert their effects by targeting common pathways. Prior knowledge of their usage could allow us to identify novel molecular links. In this study, we explored the molecular basis of action of one such herbal formulation Cissampelos pareira L. (Cipa), used for the treatment of female hormone disorders and fever. Transcriptomic studies on MCF7 cell lines treated with Cipa extract carried out using Affymetrix arrays revealed a downregulation of signatures of estrogen response potentially modulated through estrogen receptor α (ERα). Molecular docking analysis identified 38 Cipa constituents that potentially bind (ΔG < - 7.5) with ERα at the same site as estrogen. The expression signatures in the connectivity map ( https://clue.io/; ) revealed high positive scores with translation inhibitors such as emetine (score: 99.61) and knockdown signatures of genes linked to the antiviral response such as ribosomal protein RPL7 (score: 99.92), which is a reported ERα coactivator. Further, gene knockdown experiments revealed that Cipa exhibits antiviral activity in dengue infected MCF7 cells potentially modulated through estrogen receptor 1. This approach reveals a novel pathway involving the ESR1-RPL7 axis which could be a potential target in dengue viral infection.

Genetic Risk Prediction of COVID-19 Susceptibility and Severity in the Indian Population.

Host genetic variants can determine their susceptibility to COVID-19 infection and severity as noted in a recent Genome-wide Association Study (GWAS). Given the prominent genetic differences in Indian sub-populations as well as differential prevalence of COVID-19, here, we compute genetic risk scores in diverse Indian sub-populations that may predict differences in the severity of COVID-19 outcomes. We utilized the top 100 most significantly associated single-nucleotide polymorphisms (SNPs) from a GWAS by Pairo-Castineira et al. determining the genetic susceptibility to severe COVID-19 infection, to compute population-wise polygenic risk scores (PRS) for populations represented in the Indian Genome Variation Consortium (IGVC) database. Using a generalized linear model accounting for confounding variables, we found that median PRS was significantly associated (p < 2 x 10-16) with COVID-19 mortality in each district corresponding to the population studied and had the largest effect on mortality (regression coefficient = 10.25). As a control we repeated our analysis on randomly selected 100 non-associated SNPs several times and did not find significant association. Therefore, we conclude that genetic susceptibility may play a major role in determining the differences in COVID-19 outcomes and mortality across the Indian sub-continent. We suggest that combining PRS with other observed risk-factors in a Bayesian framework may provide a better prediction model for ascertaining high COVID-19 risk groups and to design more effective public health resource allocation and vaccine distribution schemes.

Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes.

Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians.

Next-Generation Sequencing for Congenital Nephrotic Syndrome: A Multi-Center Cross-Sectional Study from India.

OBJECTIVE: Information on etiology of congenital nephrotic syndrome in non-Caucasian populations is limited. This study aimed to determine the genetic basis of congenital nephrotic syndrome in Indian patients. METHODS: In this observational, cross-sectional study, whole exome sequencing was performed on samples from all children diagnosed with congenital nephrotic syndrome, presenting at centers collaborating in a nationwide registry and biorepository. Analysis was targeted to focus on reported or novel, pathogenic or likely pathogenic variants in 89 genes implicated in etiology of nephrotic syndrome. Sanger sequencing was used to confirm disease-causing variants in patients and allelic segregation of compound heterozygous variants in samples from parents. Inheritance of a shared haplotype was analyzed among ten individuals carrying the most common variant. RESULTS: During 2017-2019, 34 patients with congenital nephrotic syndrome were screened. Consanguinity and similar illness in siblings were reported in eleven patients each. Homozygous or compound heterozygous, pathogenic or likely pathogenic variants were found in NPHS1 in 24 cases, including two novel variants. One patient each had homozygous pathogenic or likely pathogenic known or novel variant in NPHS2, PLCE1, OSGEP and LAMB2 genes. Patients with OSGEP and LAMB2 mutations had phenotype typical of Galloway Mowat and Pierson syndromes, respectively. Three variants in NPHS1 were common to 16 individuals. One reported variant in exon 19 (c.2600G>A; p.Gly867Asp) appears to share a common founder. CONCLUSIONS: A genetic cause was determined for 82.4% patients with congenital nephrotic syndrome. Variants in NPHS1 are most common in Indian patients and founder mutations might be present.

Baseline cell proliferation rates and response to UV differ in lymphoblastoid cell lines derived from healthy individuals of extreme constitution types.

Differences in human phenotypes and susceptibility to complex diseases are an outcome of genetic and environmental interactions. This is evident in diseases that progress through a common set of intermediate patho-endophenotypes. Precision medicine aims to delineate molecular players for individualized and early interventions. Functional studies of lymphoblastoid cell line (LCL) model of phenotypically well-characterized healthy individuals can help deconvolute and validate these molecular mechanisms. In this study, LCLs are developed from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda. LCLs were characterized by karyotyping and immunophenotyping. Growth characteristics and response to UV were studied in these LCLs. Significant differences in cell proliferation rates were observed between the contrasting groups such that one type (Kapha) proliferates significantly slower than the other two (Vata, Pitta). In response to UV, one of the fast growing groups (Vata) shows higher cell death but recovers its numbers due to an inherent higher rates of proliferation. This study reveals that baseline differences in cell proliferation could be a key to understanding the survivability of cells under UV stress. Variability in baseline cellular phenotypes not only explains the cellular basis of different constitution types but can also help set priors during the design of an individualized therapy with DNA damaging agents. This is the first study of its kind that shows variability of intermediate patho-phenotypes among healthy individuals with potential implications in precision medicine.