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Association of ERBB4 and SHBG gene polymorphisms with polycystic ovarian syndrome in South Indian women: a case-control genetic analysis.

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a multifactorial endocrinological disorder with a substantial genetic component. However, the role of genes involved in follicular development and androgen regulation remains incompletely understood, particularly in South Indian populations. This study aimed to evaluate how variations in the ERBB4 and SHBG genes affect PCOS risk. METHODOLOGY: A hospital-based case-control study was conducted among 400 South Indian women, comprising 200 women with PCOS and 200 age-matched healthy controls. Genomic DNA was extracted to study SNPs at ERBB4 (rs2178575 and rs1351592) and SHBG (rs1799941 and rs727428) using ARMS-PCR genotyping. The study compared genotype and allele frequencies between cases and controls while assessing their associations with allelic, homozygous, heterozygous, dominant, recessive, and over-dominant genetic models. Genotyping accuracy was confirmed by re-genotyping and Sanger sequencing of a subset of samples. RESULTS: The ERBB4 rs2178575 polymorphism demonstrated a significant association with PCOS, as the AA genotype and A allele combination increased risk across all three genetic models, including homozygous, recessive, and allelic models. The ERBB4 rs1351592 variant was associated with 3-fold higher risk of PCOS in heterozygous and GC carriers. The SHBG rs1799941 polymorphism showed a significant link to PCOS through its effects on heterozygous and allelic states, whereas rs727428 displayed no significant connection due to its monomorphic distribution. CONCLUSION: These findings suggest that polymorphisms in ERBB4 and SHBG may contribute to PCOS susceptibility in South Indian women in a locus- and model-specific manner, revealing the intricate genetic structure that defines this medical condition.

Humans

Sex- and age-specific associations of VEGFA polymorphisms with multiple sclerosis susceptibility.

AIM: To evaluate six VEGFA polymorphisms (rs1570360, rs699947, rs3025033, rs2146323, rs1413711 and rs833061) and serum VEGFA concentrations in 270 Lithuanian patients with multiple sclerosis (MS) and 270 matched healthy controls. METHODS: Genotyping was performed using real-time PCR, and serum VEGFA levels were measured by enzyme-linked immunosorbent assay. Statistical analyses were conducted using IBM SPSS version 31.0. RESULTS: Nominal differences in VEGFA genotype and allele distributions were observed in sex- and age-stratified analyses. Among females, the rs1413711 C allele was more frequent (p = 0.005), whereas the rs833061 C allele was less frequent (p = 0.006), in MS patients than controls. In participants aged >38 years, the rs1413711 C allele was also more frequent in MS cases (57.5% vs. 46.0%, p = 0.008). Logistic regression identified nominal associations, particularly for rs1413711, rs699947 and rs833061, but none remained significant after correction for multiple testing. Serum VEGFA levels were higher in MS patients than controls (p = 0.004). Nominal genotype-related differences in serum VEGFA levels and haplotype associations with reduced MS odds were also observed, but did not remain significant after multiple-testing correction. No consistent associations were found between VEGFA variants and clinical parameters. CONCLUSION: VEGFA genetic variation and elevated serum VEGFA may be associated with MS, but the genetic findings require confirmation in larger independent cohorts.

Humans

Investigating telomere length and hTERT-MNS16A VNTR polymorphism in Bipolar disorder: Insights into clinical features.

OBJECTIVE: To compare leukocyte telomere length (LTL; T/S ratio) and hTERT-MNS16A VNTR polymorphism between patients with bipolar disorder (BD) and healthy controls, and to examine their associations with clinical features in BD. METHODS: A total of 179 participants (100 BD patients, 79 healthy controls) were enrolled. Relative LTL was assessed by qPCR-based T/S ratio; hTERT-MNS16A VNTR genotyping by PCR and gel electrophoresis. Clinical variables including episode frequency, illness duration, age at onset, symptom severity scales, first episode polarity, and family history of mood disorder were evaluated. RESULTS: No significant differences were observed between BD patients and healthy controls in T/S ratio or hTERT-MNS16A VNTR genotype distributions (all p > 0.05). Within the BD group, S allele carriers (L/S or S/S) had significantly more depressive episodes than L/L homozygotes (1.45 &#xb1; 2.58 vs. 0.61 &#xb1; 1.52; p = .040). Significant inverse correlations were identified between T/S ratio and depressive episode count (&#x3c1; = -0.220, p = .028) and total mood episodes (&#x3c1; = -0.207, p = .039). Multivariable negative binomial regression revealed four independent predictors of depressive episode frequency: lower T/S ratio (p = 0.005), S allele carriage (L/S or S/S genotypes) (p = 0.001), first depressive episode polarity (p < 0.001), and family history of mood disorder (p = 0.035). CONCLUSION: Although LTL and hTERT-MNS16A VNTR genotype did not differ between BD patients and healthy controls, shorter telomere length and S allele carriage were independently associated with higher depressive episode frequency within the BD group, implicating telomere biology and hTERT genetic variation in the biological substrate of depressive illness burden.

Humans

Protective association of the ELMO1 rs741301 variant against diabetes mellitus and diabetic nephropathy: a systematic meta-analysis of case-control studies.

CONTEXT: Diabetes mellitus (DM), an endocrine disorder, is characterised by persistently elevated blood glucose levels due to inadequate insulin production. Diabetic nephropathy (DN), is a critical complication associated with DM, often leading to end-stage renal failure and increased mortality. OBJECTIVE: This meta-analysis aimed to evaluate the association between the ELMO1 rs741301 polymorphism and susceptibility to DN among individuals with diabetes. METHOD: A systematic literature search was conducted for studies published between 2014 and 2024 using Embase, Google Scholar, and PubMed. Eligible case-control studies investigating the association between ELMO1 rs741301 and DN among individuals with DM were selected according to predefined inclusion criteria. Nine case-control studies comprising 880 individuals with DM and 1008 individuals with DN were included in the meta-analysis. RESULTS: The pooled analysis demonstrated a significant protective association between the ELMO1 rs741301 polymorphism and DN under the allelic model (OR = 0.77, 95% CI: 0.67-0.88), recessive model (OR = 0.74, 95% CI: 0.61-0.90), and dominant model (OR = 0.68, 95% CI: 0.53-0.88). In contrast, no statistically significant association was observed under the over-dominant model. CONCLUSION: The findings suggest that the ELMO1 rs741301 polymorphism may be associated with a reduced susceptibility to DN among individuals with DM. These findings provide evidence for a potential genetic contribution of ELMO1 to DN susceptibility and may help improve understanding of the genetic factors underlying diabetic complications. Further well-designed studies in diverse populations are warranted to validate this association.

Humans

Genetic determinants of gestational diabetes mellitus in thai pregnant women: role of GCKR, CDKAL1, TCF7L2, NEDD1, and CMIP variants.

BACKGROUND: Gestational diabetes mellitus (GDM) has a high global prevalence and arises from complex interactions between genetic predisposition and environmental factors. GDM is associated with metabolic disturbances and chronic low-grade inflammation, both of which contribute to its pathogenesis. This study aimed to investigate the association between GDM and 135 single-nucleotide polymorphisms (SNPs) across 20 genes related to metabolic traits. METHODS: In this case-control study, 152 pregnant women with GDM and 684 pregnant women with normal glucose tolerance (NGT) who underwent antenatal examination at Siriraj Hospital, Bangkok, were enrolled. Clinical data and blood samples were collected from all participants. Genomic DNA was isolated and subjected to whole-genome sequencing using the DNBSEQ-T7RS high-throughput sequencing platform. Genotype analyses were performed using R software, and haplotype analyses were conducted using the online SNPStats software. RESULTS: After adjusting for maternal age and pre-pregnancy body mass index, polymorphisms in TCF7L2 (rs34872471, rs7901695, rs4506565, rs7903146, rs12243326, and rs12255372), NEDD1 (rs10431408, rs11830756, rs249579, rs249585, and rs4762339), CMIP (rs2306115 and rs201681534), CDKAL1 (rs4710942), GCKR (rs2293572 and rs2293571), and GCK (rs5883890) were significantly associated with the risk of GDM. Haplotype analysis demonstrated that the TCF7L2 rs12243326-rs12255372 CA haplotype was associated with a decreased risk of GDM (OR = 0.44, 95% CI: 0.23-0.81), while the NEDD1 rs249579-rs249585-rs4762339 GGT haplotype was associated with an increased risk of GDM (OR = 1.40, 95% CI: 1.08-1.82). CONCLUSIONS: These findings suggest that genetic variations in TCF7L2, NEDD1, CMIP, CDKAL1, GCK, and GCKR contribute to GDM susceptibility in the Thai population.

Humans

Peripheral pain threshold, glycaemic status, and LAMP3 genetic variation: A community-based analysis.

Diabetic polyneuropathy is a common complication of diabetes, yet substantial inter-individual variation in peripheral pain perception suggests underlying genetic influences. This population-based study investigated clinical, metabolic, and genetic determinants of pain threshold using intraepidermal electrical stimulation in 906 participants from the Iwaki Health Promotion Project 2017. Genome-wide association analysis identified 12 loci showing suggestive associations, among which a missense variant in LAMP3 (rs482912) was prioritized as a biologically plausible candidate. Phenotype-stratified analyses showed that individuals carrying the CT or CC genotypes had lower PINT indices than those with the TT genotype, indicating reduced pain thresholds. Notably, the CC genotype retained an association with lower pain threshold using intraepidermal electrical stimulation under conditions of metabolic stress, including impaired glucose tolerance, elevated HbA1c, and obesity, whereas this association was attenuated in the presence of hypertension. Single-cell RNA sequencing analysis of human skin revealed that LAMP3-positive mature dendritic cells, enriched in immunoregulatory molecules, exhibited transcriptional enrichment of inflammatory, antigen-presenting, and nociception-related pathways, including NF-&#x3ba;B, JAK-STAT, cytokine signaling, and neuroimmune sensitization cascades. Autopsy-based skin analysis further demonstrated genotype-associated differences in dermal LAMP3-positive cell infiltration and CD8-positive T-cell abundance, while CD4-positive T-cell abundance and intraepidermal nerve fiber density remained unchanged across genotypes. Taken together, these findings suggest a potential association between LAMP3 variation and individual differences in peripheral pain threshold and provide biological context supporting a role for neuroimmune interactions in early sensory modulation under metabolic stress. Given the suggestive genetic evidence and indirect mechanistic data, these observations should be interpreted as exploratory and hypothesis-generating.

Humans

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans

Genetic Diversity Analysis of Red Fox Populations (Vulpes vulpes L., 1758) in Natural and Anthropogenic Isolation.

This study presents a comparative analysis of the genetic structure and diversity of three red fox (Vulpes vulpes L.) populations representing different microevolutionary scenarios: panmixia (free-ranging Belarusian foxes), geographic isolation (free-ranging Scottish foxes), and anthropogenic selection (farm-bred foxes). Using a validated set of STR markers, multivariate statistical analysis was conducted to assess the genetic structure and the degree of genetic erosion across the studied groups. The wild red fox population in Belarus has been shown to maintain a state close to panmixia (PHWE&#x2009;=&#x2009;0.090), characterized by a high effective population size (Ne&#x2009;=&#x2009;694) and high allelic diversity. The island population from Scotland exhibits moderate gene pool depletion (Ne&#x2009;=&#x2009;75.9) and a pronounced heterozygote deficiency (FIS&#x2009;=&#x2009;0.18). Critical genetic erosion, which was characterized by a minimal effective population size (Ne&#x2009;=&#x2009;60.2) and allelic fixation, was detected in the farm-bred group. The genetic distance between farm-bred and wild foxes (FST&#x2009;=&#x2009;0.279; p&#x2009;=&#x2009;0.001) reflects both the phylogeographic divergence between the Nearctic ancestors of farmed lineages and Palearctic wild populations, and the consequences of prolonged anthropogenic isolation, genetic drift, and selective breeding. These data indicate that artificial isolation and the impacts of genetic drift and targeted selection lead to a substantial depletion of the species' adaptive potential.

Animals

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype&#x2011;dependent opioid consumption over 72&#xa0;h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non&#x2011;carriers, despite reporting similar subjective pain scores. This consistent genotype&#x2011;dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3

Pervasive hybridization and introgression in Diervilleae (Caprifoliaceae).

Diervilleae (Caprifoliaceae) is a horticulturally important lineage with striking floral diversity and a long history of interspecific crossing, suggesting reticulate evolution. We integrated nuclear SNPs and whole plastome data to reconstruct a phylogenomic backbone for the tribe and to identify hybrids, cultivated accessions, and introgression among lineages. Nuclear and plastid phylogenies consistently recover Weigela and Diervilla as reciprocally monophyletic and resolve four major lineages within Weigela, providing a reproducible framework for revising sectional limits and species boundaries. Cultivated accessions form a well supported clade sister to W. florida and show predominantly W. florida ancestry while retaining contributions from multiple wild lineages, consistent with recurrent crossing, backcrossing, and selection. Analyses of wild populations reveal recurrent hybrids and enable plausible parental combinations to be inferred. Tests across the genome further indicate strong evidence for historical introgression across Diervilleae, with the strongest signals involving W. middendorffiana, W. maximowiczii, and Diervilla. Fossil evidence, divergence time estimation, and paleodistribution modelling together suggest range expansion during the Miocene and Pliocene followed by climate driven contraction, providing a spatiotemporal context for episodic contact, introgression, and the East Asia-North America disjunction.

Hybridization, Genetic

Genome-wide SNP data support species boundaries in sympatric Polylepis Ruiz & Pav. (Rosaceae) species from Bolivia and Ecuador.

Species delimitation in the South American genus Polylepis is notoriously challenging due to high morphological similarity and phenotypic plasticity, likely driven by hybridization and gene flow. Previous phylogenetic studies suggested that genetic structure aligns more strongly with geography than with taxonomy, questioning existing species concepts and hampering conservation efforts. We used double-digest RAD sequencing (ddRADseq) to generate genome-wide SNP data for 11 Polylepis species sampled across multiple localities in Bolivia and Ecuador. Population genetic analyses, phylogenetic inference, and network approaches were combined to assess whether genetic structure aligns more closely with taxonomy or geography. Morphologically defined species formed largely cohesive genetic lineages across regions, with species identity explaining substantially more genetic variation than locality. While localized admixture and reticulation were detected among closely related taxa, widespread species showed strong genetic cohesion and clear separation from congeners. Our results indicate that the sampled Polylepis species from Bolivia and Ecuador maintain distinct genetic identities despite localized signals consistent with gene flow. This genome-wide support for current taxonomy highlights Polylepis as a valuable model for studying speciation under gene flow and indicates that multiple geographic sampling will be essential in reconstructing a robust phylogeny of the genus, with important implications for conservation planning in Andean montane forests.

Bolivia

Analyzing salinity tolerance in grass carp (Ctenopharyngodon idella): Insights from genome-wide association study and genomic selection.

Grass carp (Ctenopharyngodon idella) is one of the most widely cultured freshwater fish species globally. However, the expansion of its farming scale faces severe limitation owing to freshwater scarcity; therefore, the development of strains with greater salinity tolerance is key for expanding production using brackish water resources. To investigate the genetic basis of salinity tolerance in grass carp, a genome-wide association study (GWAS) was conducted using 200 individuals representing extreme phenotypes, namely salinity-tolerant and salinity-sensitive groups. In total, 17 single nucleotide polymorphisms (SNPs) related to salinity tolerance were detected, which were distributed across 11 chromosomes. Through gene annotation, 38 candidate genes were obtained from these loci. Enrichment analysis revealed these candidate genes are primarily implicated in key biological processes, including osmotic regulation, energy metabolism, and stress responses. Analyses of different SNP densities revealed that the 5&#xa0;K SNP density panel can balance prediction accuracy and computational efficiency. The BayesA model achieved the highest prediction accuracy under the GWAS_Evenly selection strategy, with substantial reductions in mean absolute error and mean square error. This study reveals the genetic mechanisms of salinity tolerance in grass carp, which might be optimized through genomic selection, and provides insights for selectively breeding new varieties with greater salinity tolerance.

Animals

Pharmacogenomics of antipsychotic-induced weight gain: A systematic review.

BACKGROUND: Antipsychotic-induced weight gain (AIWG) is a major clinical concern, affecting approximately 30% of patients. Clinical predictors explain only part of AIWG risk. Genetic and molecular variations are hypothesized to contribute to susceptibility. The purpose of this review is to summarize recent results to identify replicated and novel findings. STUDY DESIGN: Applying PRISMA guidelines, we searched MEDLINE, Embase, and PsycINFO (May 2018-May 2026) for studies on genetic and molecular associations with AIWG, extending our prior review. Reviews, editorials, and conference abstracts were excluded. We extracted study characteristics (design, diagnosis, antipsychotic exposure, sample size, ancestry, genetic variants, and AIWG outcomes) (e.g., &#x2265;7% weight gain, BMI change). RESULTS: Fifty-three studies met inclusion criteria. In candidate gene studies, the most consistently replicated genes associated with AIWG were observed for DRD2, HTR2C, and MC4R. Multiple novel associations were identified by genome-wide association studies (GWAS) (e.g., MAP2K1, ZDBF2, PEPD), polygenic risk scores (PRS) (e.g., body mass index PRS), gene expression (e.g., CYP3A4, EP300), and epigenetic analyses (e.g., cg12034943 at CRTC1). CONCLUSIONS: Polymorphisms in candidate genes related to neurotransmission and appetite regulation continue to be investigated for associations with AIWG, while novel findings have emerged from GWAS, gene expression, and epigenetic studies. Evidence remains inconsistent due to limited replication, methodological variability, sparse ancestry data, and geographical underrepresentation. No single genetic variant is ready for clinical use, and multi-omic and multi-ancestry models are needed to improve prediction and clinical utility.

Humans

Genomic and One Health insights into Vibrio parahaemolyticus from environmental, seafood and clinical sources.

Vibrio parahaemolyticus is a leading cause of seafood-borne gastroenteritis worldwide, with climate warming facilitating its spread to high-latitude areas. In this study, we analyzed 212 genomes of environmental and seafood-associated isolates collected from seven cities in Zhejiang Province, China (2019-2024), alongside 228 clinical genomes from public databases. The 212 isolates were assigned to 172 sequence types (STs), with ST490 being the most frequent (5/212, 2.36%). Forty-four serotypes were identified, dominated by OL3:KUT (12.68%). High ST and serotype diversity were observed across different sample types and sources, with median pairwise single nucleotide polymorphisms (SNPs) ranging from 57,431 to 58,378, indicating comparable genetic diversity across groups. All isolates carried tlh and T3SS1 but lacked tdh and T3SS2. Resistance rates against ampicillin and cefazolin were 54.72% (116/212) and 44.34% (94/212), respectively, with multidrug resistance (MDR) detected in nine isolates, predominantly from seafood (7/9). A total of 63 distinct antimicrobial resistance genes (ARGs) spanning seven classes were identified. Isolates from aquaculture farms and wet markets exhibited greater resistance category diversity and higher ARG carriage than those from coastal or riverine sites. In contrast, the 228 clinical isolates harbored only 25 ARGs across two classes, with a significantly lower proportion of isolates carrying multiple ARG classes (0.44% vs. 6.13%, P&#xa0;<&#xa0;0.001). Human isolates formed tighter phylogenetic clusters, although a minority were closely related to environmental/foodborne strains. Overall, our findings demonstrate the genetic diversity and resistance potential of V. parahaemolyticus across environmental, seafood, and clinical sources, highlighting the importance of the One Health approach to comprehensive public health risk assessment.

Vibrio parahaemolyticus

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques

Whole-exome characterization of host genetic variation in HIV-associated genes across the high-prevalence Mizo population, Northeast India.

BACKGROUND: The Mizoram state of Northeast India has one of the highest HIV prevalence rates in Asia, yet the host genetic factors influencing HIV susceptibility in this Tibeto-Burman population remain uncharacterised. METHODS: We performed whole-exome sequencing using Illumina NovaSeq 6000, mean coverage 100X on 76 HIV-negative Mizo individuals. Variants were called using GATK HaplotypeCaller v4.3 against GRCh38p14, annotated with ANNOVAR, and filtered using hard-quality thresholds (QD&#xa0;&#x2265;&#xa0;2, SOR&#xa0;&#x2264;&#xa0;3, MQ&#xa0;&#x2265;&#xa0;40, DP&#xa0;&#x2265;&#xa0;10, GQ&#xa0;&#x2265;&#xa0;20). The allele frequencies were compared against gnomAD v2.1.1 population databases. Hardy-Weinberg equilibrium was assessed using the Wigginton exact test with Bonferroni correction. RESULTS: Post-quality filtering resulted in 12,011 sample-variants across 2,821 unique positions from 36 HIV-associated loci (33 protein-coding genes, 2 chemokine ligands, and 3 lncRNA targets). Of these, 784 observations (51 unique positions) were high-impact nonsynonymous or loss-of-function variants. ADAR rs2229857 (p.K384R, NM_015840) was the most frequently observed variant (Mizo carrier frequency&#xa0;=&#xa0;0.895; 95% CI: 0.806-0.946). CXCR1 rs16858808 (p.R335C) showed the greatest population enrichment (Mizo carrier frequency&#xa0;=&#xa0;0.197; 95% CI: 0.123-0.300; 7.65-fold carrier-frequency enrichment versus gnomAD South Asian; CADD&#xa0;=&#xa0;15.60). Sixteen of 20 tested variants deviated from Hardy-Weinberg equilibrium after Bonferroni correction (p&#xa0;<&#xa0;0.0025), predominantly showing excess homozygosity consistent with the endogamous Mizo population. The protective variant CCR5-&#x394;32 was absent in all the 76 individuals tested. CONCLUSION: This first whole-exome characterization of HIV host genes in the Mizo population identifies CXCR1 rs16858808 as the most population-enriched functional variant and reveals a pervasive endogamy signature. These findings provide a population-specific genetic framework for future HIV susceptibility studies and ART pharmacogenomics research.

Humans

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans