Search Results (299)

Overweight and obese individuals often exhibit lower mortality rates or better prognoses than lean or normal-weight individuals with stroke and other diseases, a phenomenon called the “obesity paradox”. Carotid atherosclerosis is a major cause of ischemic stroke, and body weight serves as a reliable surrogate for adiposity in adult mice. Phenotypic and genetic connections of carotid atherosclerosis with body weight were evaluated in 299 F2 mice (154 females, 145 males) derived from BALB/cJ and LP/J Apoe knockout (Apoe^-/-) mice. F2 mice were fed a Western diet for 12 weeks. Atherosclerotic lesion sizes in left carotid arteries, body weight, coat color, plasma lipids, glucose, small dense LDL ApoB, and malondialdehyde were measured, and 11,000 single nucleotide polymorphism (SNP) markers were genotyped. Carotid lesion sizes were inversely correlated with body weight in both sexes. Genome-wide scans identified two significant quantitative trait loci (QTLs) for carotid atherosclerosis on chromosomes (Chr) 6 and 15 in an additive sex model, and five QTLs on Chr 6, 7, 12, 13, and 15 in an interactive sex model. Adjusting for body weight variation downgraded Chr 15 QTL (Cath5) in both models, whereas other QTLs upgraded in the additive sex model and downgraded in the interactive sex model. Human syntenic region of Cath5 associated with carotid intima-medial thickness (cIMT) and waist-to-hip ratio (WHR). These findings indicate that the obesity paradox in carotid atherosclerosis is partially driven by shared genetic components that exert opposing effects on adiposity and plaque development and act through sex-independent mechanisms. Full article

Background/Objectives: Fruit quality in melon is determined by complex traits including sugar accumulation, aroma, flesh color, ripening behavior and disease resistance. Conventional genomic selection provides limited mechanistic interpretation, especially for regulatory and de novo variants. We adapted the EVEE interpretable embedding–probing framework to melon using PlantCAD2 as a frozen DNA language model backbone. Methods: The model was not fine-tuned or further pre-trained. Instead, lightweight probes were trained on fixed embeddings derived from sequence windows surrounding genetic variants. The pipeline integrated supervised variant-effect prediction, functional perturbation profiling, training-free masked log-likelihood ratio scoring, and cis-regulatory element generation. We applied the framework to 32,268 public genotyping-by-sequencing (GBS) SNPs from a melon diversity panel. A total of 30,052 variants were successfully encoded and analyzed. Results: Of these, 31.9% were classified as high predicted functional effect under the GWAS-proximal probe. We adopted a rigorous independent split based on chromosome and locus blocks to ensure test variants and training variants occupy distinct linkage-disequilibrium blocks. In this setting, the covariance probe yields an AUROC of approximately 0.51 with a 95% confidence interval covering 0.50, indicating no predictive advantage over random guessing. The full-cohort AUROC value of 0.748 reported earlier is attributed to linkage-disequilibrium leakage and overlapping positive samples between datasets, and thus does not reflect true independent generalization. The 17-class structural annotation probe reached 95.97% per-position accuracy. Functional perturbation signals were enriched in intronic, coding, and proximal promoter regions, consistent with known regulatory architectures in melon. Using the masked language model head with Gibbs sampling, we generated 76 candidate 400 bp cis-regulatory elements associated with sugar metabolism pathways. A posterior consistency check against 18 published GWAS/QTL loci showed effect-score patterns broadly concordant with reported loci; this is a consistency analysis against known loci, not an independent prospective validation. Variants in the CmTST2 region exhibited elevated mean effect scores of 0.7922 compared with the genome-wide background of 0.406. Conclusions: Overall, this study provides a computational, hypothesis-generating framework in which a frozen plant DNA language model combined with lightweight probes prioritizes melon variants and generates candidate regulatory sequences; all outputs are unverified in-silico predictions requiring experimental validation before any functional or breeding use. Because every variant is scored independently from its local sequence context, the framework necessarily treats genetically linked, network-dependent traits as single-locus effects and does not model epistasis, pathway-level interactions, or genotype-by-environment effects; the outputs are sequence-level priors, not phenotype predictions. The results support a generalizable framework for model-guided functional genomics and precision breeding in Cucurbitaceae crops. Full article

Barley productivity is controlled by complex quantitative traits that are strongly influenced by genotype-by-environment interactions, requiring validation of candidate markers across representative target locations before their use in marker-assisted selection. A panel of 83 two-rowed spring barley accessions was evaluated for 11 agronomic traits at three contrasting locations in Kazakhstan during the 2025 growing season. The panel was genotyped using 103 PACE assays targeting previously reported QTLs. Location-specific and across-location phenotypes were analyzed using BLUPs, ANOVA, PCA, population-structure-corrected linear regression, marker-assisted breeding value analysis, and positional candidate-gene annotation. Of 70 polymorphic markers with minor allele frequency above 0.05, 27 were associated with eight traits, producing 51 marker–trait associations at FDR < 0.05. Twenty-six associations involving 17 markers were retained for preliminary breeding-utility assessment. Two associations involving ipbb_hv50K_046 were supported at two or more locations, 19 were detected at one location and in the BLUP analysis, and five were BLUP-specific. Fourteen markers reproduced previously reported GWAS associations at the trait or trait-group level. Marker ipbb_hv50K_046 showed the strongest spatially reproducible effects and was associated with an 81.1% increase in the number of kernels per spike, a 31.4% increase in kernel weight per spike, and a 58.3% reduction in spike rachis internode length. Positional analysis of the Morex v3 reference genome identified candidate genes for all 17 retained markers, with 12 SNPs located within high-confidence gene models. These markers represent promising candidates for marker-assisted selection in barley breeding programs across diverse agro-climatic conditions in Kazakhstan and comparable environments. Full article

Genome-wide association studies (GWASs) have identified numerous loci associated with Alzheimer’s disease (AD), yet the effector genes and regulatory mechanisms underlying many of these associations remain unresolved. This challenge is particularly pronounced for non-coding variants, whose regulatory effects may extend over long genomic distances and cannot be reliably inferred from the nearest gene alone. Here, we developed an integrative computational framework that incorporates three-dimensional chromatin interactions, expression quantitative trait loci (eQTL), and sequence-level regulatory annotations to identify candidate effector genes at AD-associated loci. AD-associated lead single-nucleotide polymorphisms (SNPs) and variants in strong linkage disequilibrium were mapped to enhancer elements and promoter-interacting regions using publicly available Hi-C and promoter capture Hi-C data from the hippocampus and cerebral cortex. Hi-C-derived enhancer–promoter relationships were inferred using PSYCHIC, whereas significant promoter-centered interactions from promoter capture Hi-C were used to connect variant-containing regions with candidate effector genes. The resulting SNP–gene relationships were further evaluated using brain-relevant eQTL evidence and predicted allele-dependent alterations in transcription factor binding motifs. This integrative analysis identified 608 unique candidate regulatory target genes supported by spatial chromatin contacts and complementary regulatory evidence, including genes not necessarily assigned by conventional nearest-gene annotation. Functional enrichment analysis indicated that the prioritized genes were involved in biological processes relevant to AD pathophysiology. Detailed analyses of three representative SNP–gene pairs, rs2373115–NARS2, rs6656401–CR1, and rs3776011–ACSL6, further illustrated how chromatin interaction, expression-associated, and sequence-level evidence can be combined to formulate locus-specific regulatory hypotheses. These findings represent computationally inferred and associative regulatory relationships rather than experimentally validated causal effects. They provide a structured framework for refining post-GWAS interpretation of non-coding AD risk loci and prioritizing candidate targets for further experimental validation. Full article

Genome-wide association studies (GWAS) link germplasm diversity to molecular markers for crop improvement. This review synthesizes nine barley GWAS articles and two articles on the development or validation of GWAS-derived Kompetitive Allele-Specific PCR (KASP) assays relevant to Kazakhstan, published between 2016 and 2025. Earlier studies used 9K single-nucleotide polymorphism (SNP) arrays and mainly single-model analyses, whereas later studies used higher-density 50K arrays with multi-environment phenotyping, multiple GWAS models, haplotype analysis, and candidate-gene prioritization. Across 22 traits, 459 reported GWAS association/quantitative trait locus (QTL) entries were extracted: 180 yield-component, 90 grain-quality, 87 phenological, 59 morphological, and 43 disease-resistance entries. These corresponded to 350 distinct lead-marker identifiers and do not represent 459 unique genomic or causal loci. Cross-trait integration revealed marker-rich regions on all seven chromosomes, consistent with pleiotropy or tight linkage, although the available evidence cannot distinguish these mechanisms. Twenty-seven GWAS-derived SNPs were converted into KASP assays, but only a subset was evaluated in separate germplasm panels. Thirty-three SNPs representing 55 associations were prioritized because they exceeded study-specific Bonferroni thresholds and recurred in at least two environments and/or years. Translation into breeding will require validation in separate germplasm panels and multiple environments, genotype-by-environment modeling, pangenome-informed variant discovery, and integration of diagnostic markers with genomic selection for polygenic traits. Full article

Background: Osteoarthritis (OA) is a prevalent degenerative joint disease lacking effective disease-modifying therapies, which necessitates the discovery of key genes for mechanistic exploration and therapeutic development. Methods: We integrated three large-scale cis-protein quantitative trait locus datasets and two OA genome-wide association study summary statistics to screen candidate proteins by two-stage proteome-wide Mendelian randomization (MR). Causal association reliability was validated via summary-data-based Mendelian randomization (SMR) and Bayesian colocalization analyses. A phenome-wide association study (PheWAS) was performed to evaluate potential pleiotropic effects of the candidates. Subsequently, transcriptomic and single-cell RNA sequencing datasets were employed to evaluate the candidate genes’ expression stability, classification efficacy in the in vitro models of OA, cell-specific enrichment, and pseudotime expression dynamics in cartilage. Finally, drug repurposing potential was explored by integrating drug–gene interaction database searches and molecular docking. Results: Two-stage cis-pQTL MR combined with cis-eQTL-based SMR analysis identified 14 plasma proteins with consistent effects at the protein and transcript levels. RNA-seq revealed that adrenomedullin (ADM) and complement factor H (CFH) were upregulated in two in vitro models of OA, and both genes exhibited favorable classification efficacy in these models. Bayesian colocalization analysis provided evidence of shared causal variants for ADM, and PheWAS did not detect significant pleiotropic associations for ADM or CFH across the tested phenotypes. Single-cell analysis indicated that ADM was enriched in pre-fibrocartilage chondrocytes with biphasic pseudotime expression, whereas CFH was widely expressed across chondrocyte subsets. Database screening identified 15 potential drugs for ADM and 6 for CFH. Conclusions: Combining MR, multi-omics and pharmacological evidence, we prioritized ADM and CFH as OA candidate genes. Full article

Age-related macular degeneration (AMD) is a major cause of irreversible visual impairment, yet identifying effector proteins and tissue-specific mechanisms underlying genome-wide association study (GWAS) loci remains challenging. This study aimed to systematically prioritize candidate causal circulating proteins and delineate their cellular and transcriptional dynamics in AMD. We integrated plasma protein quantitative trait loci (pQTL) summary statistics from the UK Biobank Pharma Proteomics Project (UKB-PPP; $N=\mathrm{53,022}$) with FinnGen AMD GWAS data using proteome-wide association studies (PWAS), summary-data-based Mendelian randomization (SMR) with the HEIDI test, and Bayesian colocalization analysis. Prioritized candidates were mapped across human and murine retinal single-cell/single-nucleus RNA sequencing atlases. Transcriptional responsiveness was validated in an independent clinical microarray dataset (GSE103060) and in human retinal pigment epithelial cells (ARPE-19) via in vitro inflammatory stimulation and RT-qPCR. Target tractability was assessed using pharmacological databases. Multi-stage genetic screening prioritized five candidate proteins stratified into two confidence tiers: three Tier 1 causal drivers supported by colocalization (PP4 > 0.80)—including risk factors CSF2, IL20RB, and WARS1 (also known as WARS)—alongside two Tier 2 candidates supported by SMR and HEIDI, comprising risk factor PILRA and inversely associated metabolic factor ACADSB. Retinal transcriptomic mapping localized PILRA specifically to microglia, ACADSB to inner retinal neurons, and WARS1 to photoreceptors, RPE, and vascular compartments, while IL20RB and CSF2 exhibited low baseline expression. In independent validation cohorts, IL20RB and WARS1 were significantly up-regulated in choroidal neovascularization (CNV) membrane-derived RPE from patients with AMD ($p<0.01$). Exposure of ARPE-19 cells to TNF-$\alpha$ markedly induced mRNA levels of IL20RB ($P=0.0025$) and WARS1 ($p<0.0001$). Dual normalization against ACTB as a secondary internal reference yielded consistent significant induction. Pathway enrichment highlighted cytokine-driven receptor cascades (JAK-STAT signaling) and mitochondrial substrate catabolism (branched-chain amino acid and fatty acid metabolism). Drug–target profiling identified small molecules and nutraceuticals interacting with ACADSB, CSF2, and WARS1. By combining large-scale plasma proteomic genetics with single-cell mapping and experimental validation, this study identifies a prioritized set of candidate causal proteins linking neuroimmune activation, vascular remodeling, and mitochondrial bioenergetics in AMD, providing candidate entry points for mechanistic and therapeutic exploration. Full article

Human adaptation to diverse climates has played a major role in shaping human evolution. Mitochondrial oxidative phosphorylation (OXPHOS) is central to energy production and thermogenesis; however, the respective contributions of the mitochondrial and nuclear genomes to climate adaptation remain poorly understood. Here, we analyzed 1901 genomes from 19 global populations to investigate positive selection across 13 mitochondrial and 78 nuclear OXPHOS genes. We identified 19 candidate amino acid positions under positive selection in seven mitochondrial genes and 103 candidate SNPs under positive selection in 20 nuclear genes. Climate association analyses revealed significant associations between climatic variables and candidate mitochondrial and nuclear variants. Notably, candidate nuclear SNPs occurred almost exclusively in non-coding regions, and 96 of the 103 variants have been previously reported as cis-eQTLs, suggesting that recent adaptive variation may have involved changes in gene regulation in addition to protein sequence variation. We also tested for statistical associations between mitochondrial amino acid variants and candidate nuclear SNPs; although 78 nominal associations were observed, none remained significant after correction for multiple testing. Several mitochondrial and nuclear variants have been previously reported in association with metabolic, neurological, and cardiovascular phenotypes. Overall, our findings highlight associations between climatic variation and mitochondrial and nuclear OXPHOS variation, as well as possible genetic interactions between mitochondrial and nuclear variants, providing new insights into the evolution of the OXPHOS system during recent human evolution. Full article

The reproductive stage is a critical time in a plant’s life history when dealing with heat stress as the specific processes of meiosis, gametogenesis, anthesis, pollination, fertilization, and early seed development all occur within comparatively narrow temperature limits. Much of the importance of flowering is tied directly to temperature, both for the timing of reproductive transition and the ability for male and female reproductive tissues to survive exposure to damaging heat. Ambient-temperature sensing is linked to flowering via regulatory modules that involve phytochrome B, EARLY FLOWERING 3 (ELF3), PHYTOCHROME INTERACTING FACTOR 4 (PIF4), FLOWERING LOCUS T (FT), FLOWERING LOCUS M (FLM), SHORT VEGETATIVE PHASE (SVP), and the light–circadian components. Conversely, when temperature is harmful, protective responses involve other cellular mechanisms such as activation of heat-shock transcription factors (HSFs), heat-shock proteins (HSPs), endoplasmic-reticulum protein quality control, calcium and reactive oxygen species (ROS) signaling, antioxidant systems, hormone regulation, metabolic reprogramming, autophagy and DNA-repair pathways. Male reproductive development is often very sensitive, especially at meiosis, during formation of the tetrad, microspore development, during the maturation of pollen, and during the growth of the pollen tubes, although injury to pistils, ovules and the post-fertilization tissues may solely have an effect on the restriction of fertilization and seed set. Phenological heat escape and intrinsic reproductive thermotolerance are genetically separable but can be complementary aspects of adaptation, as revealed by natural allelic variation, QTL mapping, genomic prediction and marker assisted selection. This review summarizes molecular, genetic and physiological evidence, to propose that, to ensure stable yields at high temperatures, there is a need to coordinate optimization of reproductive timing, cell and development thermotolerance, and post-fertilization sink stability. Full article

Peripheral blood mononuclear cells (PBMCs) are the most immunologically active and readily accessible fraction of whole blood, and they initiate host immune responses following infection and vaccination. Since PBMC transcriptomes capture diverse host–pathogen interactions, they offer a promising tool to uncover the genetic drivers of viral resistance and tolerance. As a detailed case study of this principle, we examine porcine reproductive and respiratory syndrome (PRRS), which remains one of the most economically important viral diseases of swine worldwide. Following PRRS virus (PRRSV) exposure, pigs rely on two complementary defense strategies: resistance, the capacity to limit viral replication, and tolerance, the capacity to sustain performance despite infection. Since resistance and tolerance phenotypes are difficult to measure directly through experimental challenge, indirect immune-trait measurements collected after vaccination offer a practical alternative. Most transcriptomic studies of the host response to PRRSV have focused on respiratory tissues, reflecting the virus’s tropism for pulmonary macrophages. However, intramuscularly delivered modified-live PRRSV vaccine reaches the bloodstream, bypassing the lung, so PBMCs, as the frontline defense system, mount the earliest measurable innate response. This review synthesizes the current literature on PBMC transcriptome models for deciphering innate resistance and tolerance to viral disease, using PRRS as our principal worked example; presents our own approach to profiling PBMCs after PRRSV vaccination; and outlines how the field has advanced since the original candidate-gene and QTL studies of the 2010s, including the recent FDA approval of the first CD163 gene-edited PRRSV-resistant pig line, and the emergence of single-cell and multi-tissue PBMC atlases, before considering how the same PBMC-based approach could extend to other host–virus interactions. Full article

Yield losses due to water-deficit (WD) conditions, especially during the reproductive stages of plant development, pose a significant threat to global canola (Brassica napus L.) production. Therefore, it is critical to investigate traits contributing to improved productivity under increased WD conditions. Here we present phenotypic, physiological and transcriptomic changes in response to WD across contrasting canola accessions exhibiting variation in drought resistance-related traits. WD significantly reduced shoot biomass, plant height, harvest index, leaf water content, photosynthetic CO₂ assimilation rate, intrinsic water-use efficiency and carbon isotope discrimination. WD caused 49 to 100% of the seed yield reduction: the minimum seed yield reduction (49.66%) was observed in a doubled-haploid (DH) line, 06-5101.137, while the maximum yield reduction (94.1 to 100%) occurred in the late-flowering DH lines (06.5101.088 and 06-5101.306). Seed yield showed a positive correlation (r = 0.29 to 0.95) with shoot biomass and harvest index, leaf water content, photosynthetic CO₂ assimilation rate, intrinsic water use efficiency and carbon isotope discrimination. However, it showed negative correlations with days to flower, leaf specific weight, root length, root biomass (r = −0.04 to −0.79) across water treatments. The specific leaf transcriptome analysis of the two parental lines of DH population that exhibit variation for effective water use under well-watered and water-deficient conditions revealed different categories of differentially expressed genes (DEGs): WD-responsive DEGs in BC1329 parental line (1116) and BC9102 (1205) with 754 and 853 DEGs unique to BC1329 and BC9102, respectively, WD-responsive DEGs (906), genotype-dependent DEGs (8465) and genotype × treatment interaction DEGs (353). DEG annotations revealed that the WD-treatment-affected genes were involved in stress responses and growth and development. We further located 235 DEGs within the QTL regions underlying agronomic and physiological performance. Our study provides a conceptual framework for the morphological, physiological and molecular determinants involved in water-use efficiency. Seedlings’ traits with high heritability values, such as shoot biomass, leaf weight, leaf water content and Δ¹³C, serve as proxies for trait-based selection for improved seed yield under both water-limited and non-water-limited conditions. Full article

Ascochyta blight (AB), caused by the necrotrophic fungus [Ascochyta rabiei (Pass.) Labr.], is one of the most destructive diseases of chickpea (Cicer arietinum L.), causing yield losses of up to 100% under favorable conditions. The pathogen possesses a heterothallic mating system with two mating-type idiomorphs, MAT1-1 and MAT1-2, which contribute to high genetic diversity and the frequent breakdown of host resistance. This review summarizes current knowledge of AB biology, epidemiology, and management, highlighting recent advances in molecular diagnostics, host–pathogen interactions, and population dynamics. Conventional and modern detection methods, including PCR-based assays, field-deployable diagnostic tools, and high-throughput phenotyping approaches, are discussed. Resistance to AB is genetically complex and predominantly polygenic, involving multiple quantitative trait loci (QTLs), although major resistance genes have also been reported. Genomic tools such as QTL mapping, genome-wide association studies (GWAS), and genomic selection have accelerated the identification of resistance loci and improved the efficiency of chickpea breeding. The potential of wild Cicer species as sources of novel resistance alleles is also emphasized. Integrating genetic resistance with effective disease monitoring and management strategies remains essential for sustainable AB control and the development of durable resistant cultivars. Full article

Ganoderma boninense, a soil-borne pathogenic fungus causing basal stem rot (BSR) disease in oil palm, is the major threat to cultivation in Southeast Asia, with the potential to reduce oil production by up to 80% in severely affected plantations. With a view to marker-assisted selection (MAS) of resistant planting material, we combined genetics and transcriptomics approaches to investigate the defense mechanisms of oil palm against infection by G. boninense. We first performed quantitative trait locus (QTL) mapping of BSR resistance using a multi-locus Bayesian variable selection approach applied to more than 10 years of data collected during pre-nursery tests of Deli and La Mé breeding populations. We found 6 and 5 BSR resistance loci segregating in Deli and La Mé respectively, with no overlap between them. Then we performed an RNA-sequencing approach on libraries of roots and bole of oil palm seedlings inoculated or not with G. boninense, focusing on Deli × La Mé crosses with contrasted BSR resistance. A Bayesian variable selection on predictors obtained by tracing the resistance loci haplotypes in profiled individuals identified 195 differentially expressed genes (DEGs) for the G. boninense inoculation × QTL interaction, among the 551 DEGs found for inoculation effects. The DEGs were located both in cis and trans positions compared to the segregating QTL intervals, enabling the prioritization of candidate genes and resistance mechanisms associated. Focusing on a strong effect QTL region on chromosome 4 in the Deli genetic background, we identified three candidate genes in cis positions that exhibited differential expression both in response to G. boninense inoculation and between resistant and susceptible haplotypes. Our study is the first combining QTL and RNA-seq approaches in oil palm based on genetically connected experimental setup, providing valuable information on the underlying mechanisms and paving the way for MAS of BSR resistant planting material. Full article

Background: The transcription factor 7-like 2 (TCF7L2) gene is one of the strongest genetic determinants of type 2 diabetes mellitus (T2DM), with the rs7903146 (C > T) polymorphism consistently associated with impaired insulin secretion and glucose dysregulation. This study investigated the associations between the TCF7L2 rs7903146 polymorphism, glycemic control, oxidative stress biomarkers, and T2DM susceptibility, integrating bioinformatic analyses to explore the functional significance of this variant. Methods: This case–control study included 200 patients with T2DM, 100 prediabetic individuals, and 120 healthy controls. Genotyping of rs7903146 was performed using TaqMan SNP assays. Biochemical analyses included fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), lipid profile, and oxidative stress biomarkers, including superoxide dismutase (SOD), glutathione peroxidase (GPx), total antioxidant capacity (TAC), and malondialdehyde (MDA). Bioinformatic analyses included population frequency analysis, regulatory annotation, chromatin accessibility assessment, expression quantitative trait locus (eQTL) analysis, protein interaction network construction, and pathway enrichment analyses to investigate the functional consequences of rs7903146. Results: The T allele frequency was markedly higher in T2DM patients (33.5%) and prediabetic individuals (30%) than in controls (13.3%) (p < 0.001). T2DM susceptibility increased under allelic (OR = 3.27, 95% CI: 2.14–5.01), dominant (OR = 3.9, 95% CI: 2.37–6.42), and recessive (OR = 6.92, 95% CI: 1.59–30.07) models (p < 0.01). T2DM patients also showed significantly lower superoxide dismutase (SOD) and glutathione peroxidase (GPx) activities, lower total antioxidant capacity (TAC), and higher MDA levels (p < 0.001). T allele carriers had poorer glycemic control and greater oxidative stress. Bioinformatic analyses showed that rs7903146 resides within an active intronic regulatory region with chromatin accessibility, enhancer-associated histone marks, transcription factor occupancy, and candidate cis-regulatory elements. eQTL analyses showed tissue-specific effects on TCF7L2 expression, while network and pathway analyses highlighted WNT signaling, β-catenin transcriptional complexes, and metabolic regulation and oxidative stress pathways. Conclusions: The TCF7L2 rs7903146 polymorphism was significantly associated with T2DM susceptibility, impaired glycemic regulation, and altered oxidative stress biomarkers. Bioinformatic analyses provided predictive evidence suggesting that rs7903146 may have tissue-specific regulatory relevance and may be indirectly linked to metabolic and WNT/β-catenin signaling pathways. However, because of the observational case–control design, these findings do not establish causality, and the proposed regulatory mechanisms require experimental validation. Full article

Background: Although genetic-environmental interactions are established in autism spectrum disorder (ASD), how environmental toxicants confer susceptibility remains unclear. This study aimed to investigate potential relationship between genetically predicted cerebrospinal fluid (CSF), metabolite levels and ASD liability, and to prioritize regulatory genes, key pathways, and candidate environmental toxicants. Methods: Using two ASD GWAS datasets (exploration data: 18,381 ASD cases/27,969 controls; validation data: 18,235 ASD cases/36,741 controls), we applied multi-omics approaches to prioritize ASD-associated CSF metabolites, regulatory SNPs, and genes. Enrichment analysis and protein–protein interaction (PPI) network analysis were performed on these metabolite-related genes to explore the potential mechanisms linking CSF metabolic disturbances to ASD. Finally, candidate environmental neurotoxicants were screened through protein-chemical interaction analysis, with binding relationships assessed via molecular docking prediction. Results: Two-sample Mendelian randomization (MR) analysis prioritized adenine and proline as candidate CSF metabolites with potential risk associations with ASD. Summary-data-based MR (SMR) prioritized 39 brain-specific quantitative trait loci (QTL) involving 35 candidate regulatory genes, including dual-metabolite modulator GRM8. Functional enrichment analyses suggested potential associations with mitochondrial dysfunction, Hippo signaling pathway, and microtubule dynamics impairment, with protein–protein interaction networks highlighting KATNA1/KATNAL2 as hubs. Protein-chemical interaction screening nominated 14 candidate environmental toxicants, including established chemicals (acetaminophen, valproic acid, estradiol) and novel candidates (SB-431542, K 7174, benzo[a]pyrene), with docking affinity assessed computationally. Conclusions: Our study provides suggestive evidence that elevated adenine and proline may be potential risk factors for ASD and suggests possible involvement of the mitochondrial–Hippo–microtubule pathway. We also propose benzo[a]pyrene as a candidate environmental toxicant that may perturb CSF metabolism. However, given the limited statistical significance, these findings require further validation. Full article