Multivariate genetic architecture reveals testosterone-driven sexual antagonism in contemporary humans.

Sex difference (SD) is ubiquitous in humans despite shared genetic architecture (SGA) between the sexes. A univariate approach, i.e., studying SD in single traits by estimating genetic correlation, does not provide a complete biological overview, because traits are not independent and are genetically correlated. The multivariate genetic architecture between the sexes can be summarized by estimating the additive genetic (co)variance across shared traits, which, apart from the cross-trait and cross-sex covariances, also includes the cross-sex-cross-trait covariances, e.g., between height in males and weight in females. Using such a multivariate approach, we investigated SD in the genetic architecture of 12 anthropometric, fat depositional, and sex-hormonal phenotypes. We uncovered sexual antagonism (SA) in the cross-sex-cross-trait covariances in humans, most prominently between testosterone and the anthropometric traits - a trend similar to phenotypic correlations. 27% of such cross-sex-cross-trait covariances were of opposite sign, contributing to asymmetry in the SGA. Intriguingly, using multivariate evolutionary simulations, we observed that the SGA acts as a genetic constraint to the evolution of SD in humans only when selection is sexually antagonistic and not concordant. Remarkably, we found that the lifetime reproductive success in both the sexes shows a positive genetic correlation with anthropometric traits, but not with testosterone. Moreover, we demonstrated that genetic variance is depleted along multivariate trait combinations in both the sexes but in different directions, suggesting absolute genetic constraint to evolution. Our results indicate that testosterone drives SA in contemporary humans and emphasize the necessity and significance of using a multivariate framework in studying SD.

Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data.

High-throughput sequencing (HTS) has revolutionized science by enabling super-fast detection of genomic variants at base-pair resolution. Consequently, it poses the challenging problem of identification of technical artifacts, i.e. hidden non-random error patterns. Understanding the properties of sequencing artifacts holds the key in separating true variants from false positives. Here, we develop Mapinsights, a toolkit that performs quality control (QC) analysis of sequence alignment files, capable of detecting outliers based on sequencing artifacts of HTS data at a deeper resolution compared with existing methods. Mapinsights performs a cluster analysis based on novel and existing QC features derived from the sequence alignment for outlier detection. We applied Mapinsights on community standard open-source datasets and identified various quality issues including technical errors related to sequencing cycles, sequencing chemistry, sequencing libraries and across various orthogonal sequencing platforms. Mapinsights also enables identification of anomalies related to sequencing depth. A logistic regression-based model built on the features of Mapinsights shows high accuracy in detecting 'low-confidence' variant sites. Quantitative estimates and probabilistic arguments provided by Mapinsights can be utilized in identifying errors, bias and outlier samples, and also aid in improving the authenticity of variant calls.

Uncovering novel regulatory variants in carbohydrate metabolism: a comprehensive multi-omics study of glycemic traits in the Indian population.

Clinical biomarkers such as fasting glucose, HbA1c, and fasting insulin, which gauge glycemic status in the body, are highly influenced by diet. Indians are genetically predisposed to type 2 diabetes and their carbohydrate-centric diet further elevates the disease risk. Despite the combined influence of genetic and environmental risk factors, Indians have been inadequately explored in the studies of glycemic traits. Addressing this gap, we investigate the genetic architecture of glycemic traits at genome-wide level in 4927 Indians (without diabetes). Our analysis revealed numerous variants of sub-genome-wide significance, and their credibility was thoroughly assessed by integrating data from various levels. This identified key effector genes, ZNF470, DPP6, GXYLT2, PITPNM3, BEND7, and LORICRIN-PGLYRP3. While these genes were weakly linked with carbohydrate intake or glycemia earlier in other populations, our findings demonstrated a much stronger association in the Indian population. Associated genetic variants within these genes served as expression quantitative trait loci (eQTLs) in various gut tissues essential for digestion. Additionally, majority of these gut eQTLs functioned as methylation quantitative trait loci (meth-QTLs) observed in peripheral blood samples from 223 Indians, elucidating the underlying mechanism of their regulation of target gene expression. Specific co-localized eQTLs-meth-QTLs altered the binding affinity of transcription factors targeting crucial genes involved in glucose metabolism. Our study identifies previously unreported genetic variants that strongly influence the diet-glycemia relationship. These findings set the stage for future research into personalized lifestyle interventions integrating genetic insights with tailored dietary strategies to mitigate disease risk based on individual genetic profiles.

Multi-faceted dysregulated immune response for COVID-19 infection explaining clinical heterogeneity.

Clinical heterogeneity and varied prognosis are well noted for SARS-CoV-2 infection. Altered immune response is a major feature for the adverse prognosis however focus on altered immune response has been primarily limited to hyper-inflammatory responses like Cytokine storm. A deeper understanding of viral pathobiology and the interplay of innate and adaptive immune cells against SARS-CoV-2 infection is essential to optimize intervention strategy and future preparedness for SARS-CoV-2 or its related viral diseases. To uncover the immunological signatures driving the progression of SARS-CoV-2 infection, we performed an extensive immunophenotype on blood samples from 79 hospitalized patients with mild/moderate to severe infections as well as from healthy controls and recovered donors to understand the interplay between innate and adaptive responses impacting severity and prognosis. We observed multifarious immune dysregulation, varied across patients of the clinical spectrum. We observed 4 major dysregulations of immune phenotypes 1) depletion of M1φ (impaired antiviral response as APC), 2) immune suppression/exhaustion via activation of repressor like CD4+/CD8+PD1, TIM3, LAG3 3) inappropriate differentiation of lymphocyte (extreme elevated proportion of CD4 naive, memory B and T cells along with reduction of inflammatory activator like TLR2/4/TIGIT) and 4) cytokine storm. Our results show the identification of biomarkers to differentiate the different trajectories for SARS-CoV-2 infection.

Autosomal recessive inheritance of a novel missense mutation of ITGB4 for Epidermolysis-Bullosa pyloric-atresia: a case report.

Epidermolysis-Bullosa (EB), a rare Mendelian disorder, exhibits complex phenotypic and locus-heterogeneity. We identified a nuclear family of clinically unaffected parents with two offsprings manifesting EB-Pyloric-Atresia (EB-PA), with a variable clinical severity. We generated whole exome sequence data on all four individuals to (1) identify the causal mutation behind EB-PA (2) understand the background genetic variation for phenotype variability of the siblings. We assumed an autosomal recessive mode of inheritance and used suites of bioinformatic and computational tools to collate information through global databases to identify the causal genetic variant for the disease. We also investigated variations in key genes that are likely to impact phenotype severity. We identified a novel missense mutation in the ITGB4 gene (p.Ala1227Asp), for which the parents were heterozygous and the children homozygous. The mutation in ITGB4 gene, predicted to reduce the stability of the primary alpha6beta4-plectin complex compared to all previously studied mutations on ITGB4 reported to cause EB.

Insights into the demographic history of Asia from common ancestry and admixture in the genomic landscape of present-day Austroasiatic speakers.

BACKGROUND: The demographic history of South and Southeast Asia (S&SEA) is complex and contentious, with multiple waves of human migration. Some of the earliest footfalls were of the ancestors of modern Austroasiatic (AA) language speakers. Understanding the history of the AA language family, comprising of over 150 languages and their speakers distributed across broad geographical region in isolated small populations of various sizes, can help shed light on the peopling of S&SEA. Here we investigated the genetic relatedness of two AA groups, their relationship with other ethno-linguistically distinct populations, and the relationship of these groups with ancient genomes of individuals living in S&SEA at different time periods, to infer about the demographic history of this region. RESULTS: We analyzed 1451 extant genomes, 189 AAs from India and Malaysia, and 43 ancient genomes from S&SEA. Population structure analysis reveals neither language nor geography appropriately correlates with genetic diversity. The inconsistency between "language and genetics" or "geography and genetics" can largely be attributed to ancient admixture with East Asian populations. We estimated a pre-Neolithic origin of AA language speakers, with shared ancestry between Indian and Malaysian populations until about 470 generations ago, contesting the existing model of Neolithic expansion of the AA culture. We observed a spatio-temporal transition in the genetic ancestry of SEA with genetic contribution from East Asia significantly increasing in the post-Neolithic period. CONCLUSION: Our study shows that contrary to assumptions in many previous studies and despite having linguistic commonality, Indian AAs have a distinct genomic structure compared to Malaysian AAs. This linguistic-genetic discordance is reflective of the complex history of population migration and admixture shaping the genomic landscape of S&SEA. We postulate that pre-Neolithic ancestors of today's AAs were widespread in S&SEA, and the fragmentation and dissipation of the population have largely been a resultant of multiple migrations of East Asian farmers during the Neolithic period. It also highlights the resilience of AAs in continuing to speak their language in spite of checkered population distribution and possible dominance from other linguistic groups.

Pre-therapeutic Biomarkers for Ranibizumab Therapy among Type 2 Diabetic Patients with Diabetic Macular Edema.

SIGNIFICANCE: A differential outcome in randomized controlled trials of anti-vascular endothelial growth factor (anti-VEGF) therapy, including ranibizumab, for diabetic macular edema is a major dilemma for planning, optimizing, and managing clinical usage. The variable outcome of the therapeutics necessitates the importance of finding a predictive biomarker for anti-VEGF therapy to improve subject selection. PURPOSE: Our study correlates the baseline pro- and anti-VEGF isoforms and its three receptors (VEGFReceptor1, VEGFReceptor2, and VEGFReceptor3) for circulatory candidate protein molecules among diabetic patients with macular edema, with the clinical outcome of ranibizumab therapy. METHODS: This study included 86 individuals who were anti-VEGF naive at the time of ascertainment but have completed the standardized therapy regimen of the clinic. Plasma proteins for pro- and anti-VEGF isoforms and its three receptors were determined in replicate by an enzyme-linked immunosorbent assay. RESULTS: The study demonstrated that 56 (65.12%) individuals benefited from the therapy in terms of letter gain (Snellen chart). Baseline plasma soluble VEGF receptor 2 (sVEGFR-2) was significantly higher among responders (65.10 pg/mL; 95% confidence interval, 55.41 to 74.80 pg/mL) compared with nonresponders (46.38 pg/mL; 95% confidence interval, 38.69 to 54.07 pg/mL; PFDR = .03). Diffuse diabetic macular edema with proliferative diabetic retinopathy increases the risk of nonresponse to the therapy by 3.03-fold (PFDR = .04). CONCLUSIONS: The present study postulates that diffuse diabetic macular edema with proliferative diabetic retinopathy and baseline circulatory soluble VEGF receptor 2 may be potential candidates as therapy-stratifying markers for ranibizumab treatment among patients with diabetic macular edema.

Multifaceted genome-wide study identifies novel regulatory loci in SLC22A11 and ZNF45 for body mass index in Indians.

Obesity, a risk factor for multiple diseases (e.g. diabetes, hypertension, cancers) originates through complex interactions between genes and prevailing environment (food habit and lifestyle) that varies across populations. Indians exhibit a unique obesity phenotype with high abdominal adiposity for a given body weight compared to matched white populations suggesting presence of population-specific genetic and environmental factors influencing obesity. However, Indian population-specific genetic contributors for obesity have not been explored yet. Therefore, to identify potential genetic contributors, we performed a two-staged genome-wide association study (GWAS) for body mass index (BMI), a common measure to evaluate obesity in 5973 Indian adults and the lead findings were further replicated in 1286 Indian adolescents. Our study revealed novel association of variants-rs6913677 in BAI3 gene (p = 1.08 × 10-8) and rs2078267 in SLC22A11 gene (p = 4.62 × 10-8) at GWAS significance, and of rs8100011 in ZNF45 gene (p = 1.04 × 10-7) with near GWAS significance. As genetic loci may dictate the phenotype through modulation of epigenetic processes, we overlapped genetic data of identified signals with their DNA methylation patterns in 236 Indian individuals and performed methylation quantitative trait loci (meth-QTL) analysis. Further, functional roles of discovered variants and underlying genes were speculated using publicly available gene regulatory databases (ENCODE, JASPAR, GeneHancer, GTEx). The identified variants in BAI3 and SLC22A11 genes were found to dictate methylation patterns at unique CpGs harboring critical cis-regulatory elements. Further, BAI3, SLC22A11 and ZNF45 variants were located in repressive chromatin, active enhancer, and active chromatin regions, respectively, in human subcutaneous adipose tissue in ENCODE database. Additionally, these genomic regions represented potential binding sites for key transcription factors implicated in obesity and/or metabolic disorders. Interestingly, GTEx portal identify rs8100011 as a robust cis-expression quantitative trait locus (cis-eQTL) in subcutaneous adipose tissue (p = 1.6 × 10-7), and ZNF45 gene expression in skeletal muscle of Indian subjects showed an inverse correlation with BMI indicating its possible role in obesity. In conclusion, our study discovered 3 novel population-specific functional genetic variants (rs6913677, rs2078267, rs8100011) in 2 novel (SLC22A11 and ZNF45) and 1 earlier reported gene (BAI3) for BMI in Indians. Our study decodes key genomic loci underlying obesity phenotype in Indians that may serve as prospective drug targets in future.

Comparison of plasma adipocytokines & C-reactive protein levels in healthy schoolgoing adolescents from private & government-funded schools of Delhi, India.

Background & objectives: Obesity-mediated chronic inflammatory state is primarily governed by lifestyle and food habits in adolescents and marked by alterations in the level of various inflammatory markers. This cross-sectional study was aimed to compare the inflammatory status of healthy Indian adolescents vis-à-vis their obesity profile. The inflammatory state of urban adolescents attending private and government-funded schools, and the relationship between inflammatory marker levels and anthropometric indices in the study participants from both groups were examined. Methods: A total of 4438 study participants (10-17 yr) were chosen from various schools of Delhi, India, and their anthropometric parameters were measured. Plasma adipocytokines (adiponectin, leptin and resistin) of the study participants were measured by enzyme-linked immunosorbent assay, and plasma C-reactive protein (CRP) levels were assayed by a biochemical analyzer. Metabolic syndrome-related risk factors such as waist circumference, hip circumference (HC), fasting glucose, fasting insulin, Homeostatic Model Assessment of Insulin Resistance, total cholesterol, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol and triglycerides of normal-weight adolescents were also evaluated. Results: The level of leptin and CRP increased with increasing adiposity, whereas adiponectin levels were found to be negatively related to obesity. All plasma cytokine levels (adiponectin, leptin and resistin) were significantly elevated in female than male adolescents. Age-based classification revealed a distinct trend of variability in the levels of all the inflammatory markers among adolescents of varying age groups. Significant differences were observed between private and government schoolgoing adolescents in terms of anthropometric and inflammatory parameters, with higher adiposity indices in the former group. The relationship of plasma adipokine and CRP levels with various adiposity indices was found to be distinctly different between private and government schoolgoing students. Interpretation & conclusions: Inflammatory markers were significantly elevated in overweight/obese adolescents. The socio-economic condition of urban Indian schoolgoing adolescents reflecting lifestyle transition has profound effects on their adiposity indices and inflammatory states. Longitudinal studies in different regions of the country need to be done to further confirm the findings.

Hepatic transcriptome signature correlated with HOMA-IR explains early nonalcoholic fatty liver disease pathogenesis.

INTRODUCTION AND OBJECTIVES: Non-alcoholic fatty liver disease (NAFLD) is multistage with heterogeneous outcomes. We studied the influence of insulin resistance (IR) on the hepatic transcriptome of early NAFLD stages, to understand disease development. MATERIALS AND METHODS: In this cross-sectional study, possible clinicopathological risk factors were compared between mild-NAFL (N = 72) and non-alcoholic steatohepatitis (NASH; N = 51) patients. Liver tissue-transcriptome difference was studied between a subset of 25 mild-NAFL and 20 NASH biopsies and validated on another subset of 12 mild-NAFL and 13 NASH biopsies, using RT-PCR. The relationship between IR driven gene expression changes with fibrosis in NASH was investigated. RESULTS: Significantly higher weight (p = 0.005) and elevated levels of HbA1c (p = 0.009), FBG (p = 0.03) and HOMA-IR (p = 0.009) were found in NASH patients. Five differentially expressed genes (DEGs, fold change > 1.5) were identified in NASH-FABP4, FABP5L2, CD24, PRAP1, and SPP1. The DEGs were positively associated with disease severity and HOMA-IR, and were found to be efficient classifiers of mild-NAFL and NASH. Additional 1218 genes identified related to IR (IrCGs), which can classify NASH-with-fibrosis patients separately from mild-NAFL and NASH patients. IrCGs can promote intra-hepatic fat accumulation, dysregulation of the lipid metabolism, lipotoxicity, and activation of cell survival pathways including activation of cell proliferation and differentiation pathways. CONCLUSIONS: Hepatic expression of genes associated with insulin resistance may drive NAFLD development and progression.