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Multi-Ancestry Survival GWAS of Substance Use Initiation in the ABCD Study.

BACKGROUND: Substance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. METHODS: We conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes-alcohol, nicotine, cannabis, and any substance use-using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochran's Q and I 2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. RESULTS: In the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol ~ 1 &#xd7; 10-7, any ~ 1 &#xd7; 10-7, cannabis ~ 5 &#xd7; 10-8, nicotine ~ 1 &#xd7; 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 &#xd7; 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. CONCLUSIONS: Survival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

ABCD↗

A multi-model genome-wide association study identifies genetic variants underlying resistance to Largemouth Bass Ranavirus (LMBV) in Micropterus salmoides.

Largemouth bass (Micropterus salmoides) is an economically important freshwater aquaculture species, yet recurrent outbreaks of Largemouth Bass Ranavirus (LMBV) continue to impair production and cause substantial losses. The genetic basis of host variation in LMBV resistance remains insufficiently characterized. Here, we applied a multi-model genome-wide association study (GWAS) to identify loci associated with resistance following a controlled challenge with the LMBV-23PY strain. Whole-genome resequencing was performed for 146 phenotyped fish, including 72 susceptible and 74 resistant individuals. After stringent quality control, 877,262 high-quality variants were retained and tested using six GWAS models. Across binary survival status and survival time phenotypes, 32 shared suggestive variants were consistently detected across models, representing suggestive loci for LMBV-23PY resistance. Genes within &#xb1;50&#xa0;kb of these loci were annotated, and functional enrichment highlighted immune- and redox-related biological processes. Three prioritized candidates-GSTT3L (glutathione S-transferase theta-3-like), CGRP2 (calcitonin gene-related peptide 2), and NPPC (natriuretic peptide C)-were associated with pathways involved in oxidative stress responses and immune regulation. Collectively, these results provide insight into the genetic architecture of LMBV-23PY resistance in largemouth bass and identify suggestive variants and associated candidate genes for downstream validation, functional interrogation, and the development of marker-assisted and genome-enabled breeding strategies.

Animals↗

Bioavailable testosterone reduces the risk of lung squamous cell carcinoma: a comprehensive data study.

BACKGROUND: The association between testosterone and lung cancer remains unclear. This study investigates the relationship between testosterone levels and lung cancer risk, focusing on bioavailable testosterone levels (BTLs), total testosterone levels (TTLs), and sex hormone-binding globulin (SHBG) in relation to lung cancer subtypes. METHODS: We utilized bidirectional and multivariable Mendelian randomization (MR) analyses based on genome-wide association studies (GWAS) to assess causal links. To validate the findings clinically, immunohistochemical (IHC) staining for androgen receptor (AR) expression and survival analyses were conducted on a cohort of 90 patients with lung squamous cell carcinoma (LUSC). RESULTS: MR analysis demonstrated that higher BTLs were significantly associated with a reduced risk of LUSC (OR&#x2009;=&#x2009;0.365, P&#x2009;=&#x2009;0.001), while no significant associations were observed for TTLs or SHBG. Reverse MR analysis found no causal effect of lung cancer on testosterone levels. Multivariable MR confirmed BTLs as an independent protective factor. In the clinical cohort, AR expression was significantly associated with better prognosis, showing improved median progression-free survival (12.3 vs. 9.0 months, P&#x2009;=&#x2009;0.01) and median overall survival (35.3 vs. 29.4 months, P&#x2009;<&#x2009;0.01). Cox regression identified AR expression as an independent protective factor for patient outcomes. However, study limitations include potential residual confounding, ethnic heterogeneity between European GWAS data and Asian clinical cohorts, and the lack of direct experimental validation. CONCLUSIONS: Our findings suggest that higher BTLs may play a protective role against LUSC. BTLs and AR expression show potential as valuable biomarkers for the diagnosis and prognostic assessment of LUSC.

Humans↗

Genome-wide association study reveals two novel genetic loci associated with chronic lung allograft dysfunction.

BACKGROUND: Chronic lung allograft dysfunction (CLAD) leads to declining respiratory function and high mortality, representing the main barrier to long-term survival in lung transplantation (LT). We performed the first genome-wide association study (GWAS) investigating donor's and recipient's genetic factors associated with CLAD. METHOD: We genotyped 392 donor-recipient pairs from the multicentric Cohort in Lung Transplantation. We tested 4.5 million SNPs for association with CLAD using multivariable logistic regression models corrected for age, sex, initial disease and genetic ancestry. Three levels of explanatory variables were separately considered to conduct GWAS: donors-only, recipients-only, and donor-recipient mismatches. We also ran HLA-centric analyses using the same models. RESULTS: Our analysis confirmed the deleterious impact of HLA allelic and epitopic mismatches on CLAD risk, mostly driven by class I HLA (p=0.004). No significant associations with CLAD were found for donors' genotypes or donor-recipient non-HLA mismatches. We highlighted two independent recipient's loci associated with CLAD, including one protective signal (0.39 in CLAD vs 0.66 in non-CLAD recipients, p-value=5.05&#xd7;10-7, q-value=0.017, OR=0.35) encompassing the PLXDC2 gene, and one risk signal (0.66 in CLAD vs 0.38 in non-CLAD recipients, p-value=9.86&#xd7;10-7, q-value=0.017, OR=2.83) encompassing the ZNF518A/BLNK genes. These non-coding SNPs are putative regulatory variants of gene expression. Importantly, our single-cell RNA-sequencing showed a down-regulation of PLXDC2 in fibroblasts and lung epithelium in CLAD vs healthy controls. CONCLUSION: This first LT GWAS revealed two candidate loci from the recipient's genome, both biologically relevant for CLAD pathogenesis. Our study calls for larger LT genomic initiatives to increase power for signal discovery.

Humans↗

Exploring the Relationship Between Serological Metabolites and Oral Cancer: A Mendelian Randomization Study.

BACKGROUND: Oral cancer is a prevalent malignant tumor, comprising &#x223c;5% to 6% of all tumors. The 5-year survival rate for this condition is &#x223c;50%. However, the early symptoms of oral cancer are often inconspicuous and easily overlooked, leading to frequent misdiagnosis or missed diagnosis. Although some previous studies have investigated the correlation between oral cancer and serum metabolites, the exact relationship remains unclear. Consequently, it is of utmost importance to develop effective early diagnosis methods and explore the pathogenesis of oral cancer to enhance patients' survival rates and quality of life. METHODS: This Mendelian randomization (MR) study utilized the Genome-Wide Association Study (GWAS) catalog to obtain instrumental variables (IVs) that link 486 serum metabolites with oral cancer. The study then conducted a causal analysis, using serological metabolites as exposure factors and oral cancer as the outcome. The samples used in the study were exclusively from the European population. The main method used for the univariate MR analysis was the inverse variance weighting method. After excluding confounding factors, MR analysis was performed again. Sensitivity analyses were subsequently conducted to enhance the robustness of the MR results. Furthermore, metabolic pathway analysis was carried out on serum metabolites associated with oral cancer, aiming to identify and explore potential metabolic pathways. RESULTS: After MR analysis, 8 serum metabolites were screened out that are highly correlated with the causal relationship with oral cancer, including androsterone sulfate (OR=2.11, 95% CI: 1.37-3.27, P =0.0007), X-12100--hydroxytryptophan (OR=0.12, 95% CI: 0.02-0.73, P =0.022), gamma-glutamylphenylalanine (OR=7.57, 95% CI: 1.17-48.85, P =0.033), 7-methylxanthine (OR=0.22, 95% CI: 0.05-0.90, P =0.035), urate (OR=12.03, 95% CI: 1.16-124.32, P =0.037), palmate (16:0) (OR=11.01, 95% CI: 1.11-109.13, P =0.040), creatinine (OR=0.03, 95% CI: 0.00-0.90, P =0.047), guanosine (OR=2.66, 95% CI: 1.00-7.04, P =0.049), and the absence of heterogeneity and horizontal pleiotropy in this study indicates that the MR results obtained are quite reliable. CONCLUSION: Androsterone sulfate, gamma-glutamylphenylalanine, urate, palmitate (16:0), creatinine, and guanosine have been identified as risk factors for oral cancer. In contrast, X-12100--hydroxytryptophan and 7-methylxanthine may have a protective effect against oral cancer. The findings of this study have significant implications for early oral cancer diagnosis and offer valuable insights into the disease's pathogenesis.

Mendelian Randomization Analysis↗

A minimal three-arm oral regimen for healthspan: mechanistic alignment with transcriptomic signals from a large parental-lifespan GWAS.

A large genome-wide association study of parental lifespan was reported in 2019. A later transcriptome-wide association study (TWAS) based on those summary statistics identified a set of transcriptional programs associated with longer genetically predicted survival, including increased brain NAD + salvage, especially NMNAT2, reduced glucose-stimulated insulin secretion, a shift toward synaptic pruning with less broad plasticity, and a glial pattern characterized by relatively greater microglial and lower astrocytic signatures, with only weak pan-tissue senescence signals. Building on those directional findings, this short communication proposes a minimal three-arm oral regimen with unequal evidentiary weight: first, the Cheung Glutamatergic Regimen, consisting of low-dose dextromethorphan potentiated by a CYP2D6 inhibitor together with piracetam and L-glutamine, as an exploratory adjunct aimed at preserving residual functional connectivity; second, daily nicotinamide mononucleotide and N-acetylcysteine with pulsed senolytics for NAD + salvage and senescence modulation; and third, GLP-1 receptor agonism for metabolic reprogramming. The NAD+/senescence arm is the primary mechanistic anchor, GLP-1 receptor agonism provides secondary metabolic support, and the glutamatergic arm is exploratory. Each arm targets a separate node within the pruning-plasticity-metabolic triad. The regimen is fully oral, uses conservative dosing, and draws on prior therapeutic or human-exposure data, although the proposed combination has no established safety profile. Although direct combination data are lacking and the foundational TWAS remains a preprint, the components show plausible but uneven mechanistic alignment with the TWAS signals and may justify carefully designed, safety-focused pilot evaluation.

GLP-1↗

Wildlife Trade and Genetic Basis of Disease Susceptibility: A Review.

The surge in the trade of wildlife and wildlife products drives several species to extinction while coinciding with the increase in several zoonotic diseases. It is therefore essential to explore the roles of wildlife trade in disease transmission, and how the knowledge of genetics and immunogenetics can help in alleviating the attending challenges.&#xa0;Pathogen-driven selection plays a fundamental role in maintaining immune gene diversity, as individuals with alleles conferring resistance to endemic diseases have higher survival rate. However, anthropogenic disturbances, such as wildlife exploitation, can disrupt these evolutionary processes, leading to reduced genetic diversity and increased disease vulnerability. Advanced genomic tools, such as next-generation sequencing (NGS), whole-genome sequencing (WGS), CRISPR-Cas9 gene editing, genome-wide association studies (GWAS), epigenetics and transcriptomic analysis, can help identify immune gene variations and predict disease susceptibility in both wild and captive populations.&#xa0;Massive research targeting wildlife markets and the interface between the wild and the market players is necessary. It would be interesting to understand dynamics of pathogens and disease susceptibility, through the application of genetics and immunogenetics, thereby enhancing efforts to address the challenges posed by wildlife trade and zoonotic disease emergence.

Animals↗

Genome-wide association and selective sweep analyses reveal genetic loci for teat number trait in pigs.

Teat number is a key reproductive trait for the commercial pig industry, as an optimum number enhances weaned piglet survival rate. This study aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with teat number in the Large White sow. A total of 1000 French Large White sows were used in an analysis of total, left/right, and maximum unilateral teat number. Environmental factor, Spearman correlation, genome-wide association study (GWAS), linkage disequilibrium, and selective sweep analyses were conducted, with validation performed in a population of 1145 Landrace pigs. Genetic statistics showed that this population's teat number had moderate-low genomic heritability (h2&#xa0;=&#xa0;0.17-0.21) and weak negative correlation with weaned piglet litter weight. Parity and season affected teat development. GWAS identified 17 candidate SNPs on SSC 4, 7, and 17. Combined with selective sweep analysis, two key regions on SSC 7 were found, with four teat number-related SNPs, annotated to VRTN, DIO2, NRXN3. These candidate genes are associated with thoracic vertebrae development, hormone regulation during the early stage of teat formation, and nervous system development. These five SNPs showed similar results in the Landrace pig validation population; non-mutant homozygotes had 0.25-1.15 more teats than mutant ones in both populations. This study contributes to the identification of key variant loci associated with teat number-related traits in sows, thereby providing reliable molecular markers and a theoretical basis for marker-assisted selection of sow reproductive performance.

Animals↗

Genomic background of gestation length and calving-related traits in Holstein cattle.

The reproductive success of cows directly influences the profitability of dairy farms. Reproductive traits, particularly calving-related traits, generally have low heritability but sufficient additive genetic variance to enable genetic progress through genomic selection. Thus, the primary objectives of this study were to estimate genetic parameters and perform single-step genome-wide association studies (ssGWAS) for calf size, calving ease, gestation length, and stillbirth in Holstein cattle. Variance components were estimated based on animal models and Bayesian inference using a data set containing 226,717 animals with phenotypic records, 15,761 animals genotyped with 45,101 SNP markers, and 461,819 animals in the pedigree. SNP effects were estimated using the single-step GBLUP method. For direct and maternal genetic effects, heritability estimates (posterior standard deviation) ranged from 0.001 (0.002) for gestation length in heifers to 0.16 (0.001) for gestation length in cows. Genetic correlations ranged from -0.57 (0.01) between calving ease and stillbirth in heifers to 0.74 (0.01) between gestation length evaluated in heifers and cows. The ssGWAS results supported a highly polygenic architecture for calving-related traits, with most genomic signals not reaching genome-wide significance. A genome-wide significant association was detected for calving ease in cows on BTA23, highlighting FARS2 as a positional candidate gene. The strongest GWAS signals for each trait harbored additional biologically important candidate genes, including NPPA, NPPB, BCHE, EPHA4, DLD, and GTF2I. Given the generally low heritability estimates and the predominantly polygenic architecture observed for these traits, genomic selection may contribute to the genetic improvement of calving-related traits in Holstein cattle, with potential benefits for cow welfare, calf survival, and overall dairy production efficiency.

dairy cattle↗

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4&#x202f;= 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4&#x202f;= 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗

Multi-omics analysis identifies key genes and functional loci affecting teat number in American Large White and Landrace pigs and their application in optimizing genomic selection models.

BACKGROUND: Teat number is a crucial economic trait in pigs. It directly affects the ability of sows to lactate, which in turn influences the survival and health of piglets. The teat number of French Large White pigs is close to 16, while the teat number of American Large White and Landrace pigs is about 14. In order to improve the teat number of American Landrace and Large White pigs through molecular approaches and precise breeding techniques, we genotyped 2,131 American Landrace and 4,564 American Large White with teat number phenotype using a 50&#xa0;K SNP chip. Then, the SNP-chip data was imputed to the level of whole-genome sequencing (iWGS). Based on iWGS data, we conducted GWAS to identify novel, significant SNPs associated with teat number and to incorporate them into genomic selection. RESULTS: In Landrace pigs, significant SNPs for TTN mapped to SSC2, SSC7, SSC8, and SSC14; the SSC8 and SSC14 effects are novel. LTN mapped to SSC7, RTN to SSC7 and SSC8. The lead SSC7 SNP explained 2.60% of TTN phenotypic variance. In Large White pigs, significant SNPs were detected on SSC7 and SSC10 for TTN; SSC7, SSC10, and SSC12 for LTN; and SSC7 and SSC10 for RTN. The most significant locus on SSC7 accounted for 2.99% of the phenotypic variance in TTN. Additionally, a multi-population meta-analysis detected significant novel SNPs for LTN on SSC1 and SSC8. By utilizing Bayesian fine mapping, the most precise QTL confidence interval on SSC7 for both TTN and RTN in Large White pigs was reduced to 40&#xa0;kb. By integrating functional gene annotation with RNA-seq and ATAC-seq data from Erhualian and Bamaxiang pigs mammary placodes at embryonic day 26, we prioritized PTPN13, TRPV3, ZDHHC13, and BRD2 as novel candidate genes for teat number. We then incorporated the significant SNPs to GBLUP and benchmarked genomic-selection accuracy. In both breeds, fitting the top SNP as fixed maximized prediction for TTN and RTN, whereas treating all significant loci as an additional random effect optimized LTN. CONCLUSIONS: Our findings provide a theoretical basis for dissecting new key genes affecting teat number and for advancing molecular breeding of teat number in pigs.

Animals↗

Genetic Correlation Between Brain Imaging Phenotypes and Externalizing Behavior: A Large-Scale LDSC Analysis of UK Biobank IDPs.

Externalizing has been associated with differences in brain structure and function; however, it remains unclear whether these associations reflect shared common-variant genetic influences. Cross-trait linkage disequilibrium score regression was used to estimate genome-wide genetic correlations between externalizing genome-wide association study (GWAS) results and 3,935 brain imaging-derived phenotypes from the UK Biobank BIG40 resource. The imaging phenotypes covered structural magnetic resonance imaging (MRI), diffusion MRI, susceptibility-weighted imaging, resting-state functional MRI, and task-based functional MRI. Results were included in the primary analysis when the imaging phenotype had positive single-nucleotide polymorphism (SNP) heritability, a heritability Z statistic of at least 1.96, a mean GWAS chi-square statistic of at least 1.02, at least 200,000 regression SNPs, and a complete LDSC result without a fatal error. Technical imaging quality-control phenotypes were excluded from biological inference. Individual results were corrected using the Benjamini-Hochberg false discovery rate procedure. Aggregated Cauchy association tests (ACATs) were used to evaluate evidence across all imaging phenotypes and within predefined imaging categories. Statistical power, simultaneous confidence bounds, and alternative quality-control definitions were examined in sensitivity analyses. Of the 3,935 imaging phenotypes, 3,716 produced estimable genetic correlations, 2,980 met the primary LDSC quality-control criteria, and 2,967 were classified as biological imaging phenotypes. No individual phenotype survived false discovery rate correction. The smallest unadjusted P value was 0.0005, and the minimum adjusted q value was 0.486. The distribution of genetic correlations was centered near zero, with a median genetic correlation of 0.0014 and a median absolute genetic correlation of 0.0338. ACAT provided no evidence of an aggregate association across all biological imaging phenotypes (P = 0.302), and no predefined imaging category survived multiple-testing correction. The median minimum detectable genetic correlation at 80% power was 0.216. Bonferroni-adjusted simultaneous confidence intervals were fully contained within the interval [-0.30, 0.30] for 80.0% of phenotypes in the primary analysis and 88.0% under the stringent heritability quality-control definition. Broad and stringent sensitivity analyses produced the same overall conclusions. In this study, no statistically robust evidence of genome-wide genetic correlations between externalizing and individual UK Biobank brain imaging phenotypes was found. Nevertheless, small, localized, mixed-direction, or developmentally specific genetic effects remain possible.

Journal Article↗

Associations of genetically predicted interleukin-6 and tumor necrosis factor signaling pathways with mortality among persons with colorectal cancer: a two-sample Mendelian randomization.

BACKGROUND: Despite significant progress in identifying risk factors for colorectal cancer (CRC), factors influencing survival in people with CRC remain less understood. Pro-inflammatory cytokines like interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-&#x3b1;) have been implicated in cancer progression and may influence CRC outcomes. We investigated associations between genetically predicted levels of IL-6 and TNF-&#x3b1; signaling pathways and mortality in people with CRC. METHODS: We conducted a two-sample Mendelian randomization (MR) analysis using cis-acting single nucleotide polymorphisms (SNPs) associated with soluble IL-6 receptor alpha (sIL6-RA) and IL-6 signal transducer gp130 (IL6ST), representing IL-6 signaling, and with TNF-&#x3b1;, and its soluble receptors (sTNF-R1, sTNF-R2). SNPs were obtained separately from two large genome-wide association studies (GWAS): deCODE and UK Biobank (UKB). The outcome was CRC-specific mortality among 16,964 CRC cases (4010 deaths) in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Analyses were stratified by tumor site and stage. The inverse variance weighted (IVW) method, incorporating a correlation matrix for dependent SNPs, was used for primary analyses. Because literature links TNF-&#x3b1; to CRC incidence, we additionally performed a simulation study to evaluate the potential impact of collider bias resulting from restricting analyses to CRC cases. RESULTS: Genetically predicted sIL6-RA was weakly positively associated with CRC-specific mortality (deCODE-SNPs (n&#x2009;=&#x2009;13) HR per 1 SD increase: 1.06; 95% CI: 1.00-1.12; UKB-SNPs (n&#x2009;=&#x2009;11) HR: 1.09; 95% CI: 1.02-1.17). Genetically proxied IL6ST levels showed no association with CRC-specific mortality in the overall sample (deCODE-SNPs (n&#x2009;=&#x2009;19) HR: 1.04; 95% CI: 0.90-1.21; UKB-SNPs (n&#x2009;=&#x2009;9) HR: 1.11; 95% CI: 0.87-2.42), while higher IL6ST levels were associated with increased mortality among patients with stage 2/3 disease (deCODE-SNPs (n&#x2009;=&#x2009;19) HR: 1.45; 95% CI: 1.10-1.91; UKB-SNPs (n&#x2009;=&#x2009;9) HR: 1.87; 95% CI: 1.22-2.89). No associations were observed for TNF-&#x3b1;, sTNF-R1, or sTNF-R2. Findings for all exposures were consistent across both GWAS datasets. Simulation analyses for TNF-&#x3b1; indicated collider bias was present but limited in magnitude. CONCLUSIONS: Our findings suggest that IL-6 signaling may play a role in CRC progression although of limited magnitude, whereas TNF-related pathways appear less relevant for prognosis.

Humans↗

Human IL-34 Deficiency Primes Microglia Toward Alzheimer's Disease-Associated States.

BACKGROUND: Genome-wide association studies (GWAS), with independent replication in large European consortia, have identified a common nonsense variant in IL-34 (Y213X) as a genetic risk factor for late-onset Alzheimer's disease (AD). However, the biological consequences of this IL-34 mutation in humans, its prevalence in the population, and the mechanisms by which IL-34-Y213X alters microglial homeostasis, cerebrospinal fluid (CSF) proteomic networks, and amyloid pathology remain poorly understood. METHODS: We combined human genetics, cerebrospinal fluid (CSF) and serum proteomics, transcriptomics, large-scale phenome-wide association analyses, and preclinical experimental models to define the impact of human IL-34 deficiency. IL-34 concentrations were first quantified in CSF and serum from deeply phenotyped AD cohorts stratified by the common IL-34-Y213X nonsense variant. IL-34 levels and IL-34-Y213X status were then integrated with unbiased CSF proteomic networks and AD biomarkers. Transcriptomic profiling of purified microglia from IL-34 knockout mice was performed to assess disease-associated microglial programs. Using APP/PS1 mice lacking IL-34, we examined the effects of IL-34 deficiency on microglial survival, tiling, and plaque encapsulation. Finally, we performed postmortem analyses of temporal cortex from AD patients carrying IL-34-Y213X to assess microglial density, spatial organization, and plaque-associated responses. FINDINGS: IL-34-Y213X was a strong, dose-dependent loss-of-function (LOF) allele that reduced IL-34 levels by up to 2.5 standard deviations in CSF and serum and was common in multiple populations. IL-34 deficiency reshaped CSF proteomic networks, downregulating axon guidance and microglial support modules while upregulating inflammatory and extracellular matrix signatures, and showed pleiotropic associations with neurological, inflammatory, and metabolic traits. Transcriptomic analysis of sorted microglia from healthy 9-month-old IL-34KO compare to wild-type mice revealed a profound pro-inflammatory and disease-associated microglial transcriptional program enriched for disease-associated microglia (DAM) signatures, inflammatory pathways, and AD risk genes including APOE, CLU, and CASS4. In APP/PS1 mice, genetic IL-34 deletion selectively depleted homeostatic gray-matter microglia, disrupted microglial tiling, and impaired plaque encapsulation, resulting in altered amyloid structure and enhancing neuritic injury. Concordantly, AD patients homozygous for IL-34-Y213X displayed markedly reduced cortical microglial density and increased microglial spatial dispersion, indicating a breakdown of the microglial network organization in the human brain. INTERPRETATION: A common human IL-34 LOF variant creates a naturally occurring model of IL-34 deficiency that links microglial survival, CSF network signatures, and amyloid pathology in both mice and humans. Importantly, IL-34 deficiency alone is sufficient to induce inflammatory, AD-associated microglial states beyond simply reducing microglial number. These findings identify IL-34/CSF1R signaling as a critical determinant of microglial resilience and a potential upstream pathway linking human genetic variation to AD susceptibility, highlighting IL-34-dependent pathways as promising targets for disease modification. FUNDING: This work was supported by grants from the Spanish Ministerio de Ciencia, Innovaci&#xf3;n y Universidades/FEDER/UE (PID2024-157400OB-I00) and FORTALECE program (FORT23/00008; Instituto de Salud Carlos III, Spain) to RRL and JLV, ISCIII of Spain co-financed by FEDER funds (European Union) through grants PI24/00308 (JV) and CIBERNED collaborative grant 2022/01 to JV, PID2023-147125OB-I00 and CEX2023-001386-S (Severo Ochoa Programme) to SMTBC. A.R. is supported by STAR Award. University of Texas System. Tx, United States, The South Texas ADRC. National Institute of Aging. National Institutes of Health. USA. (P30AG066546), the Keith M. Orme and Pat Vigeon Orme Endowed Chair in Alzheimer's and Neurodegenerative Diseases (2024-2025) and Patricia Ruth Frederick Distinguished Chair for Precision Therapeutics in Alzheimer's and Neurodegenerative Diseases (2025-2028). AR is also supported by the Agency for Innovation and Entrepreneurship (VLAIO) grant N&#xb0; PR067/21 for the HARPONE project and the ADAPTED project the EU/EFPIA Innovative Medicines Initiative Joint Undertaking Grant N&#xb0; 115975 and CIBERNED (ISCIII).

Journal Article↗

Hypothesis-free evaluation of circulating metabolome provides cell-specific insights regarding the role of energy substrate availability in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with limited therapeutic options. The circulating metabolome comprises small molecules present in plasma/serum which are the intermediates and end-products of cellular metabolism, and is linked to ALS pathogenesis. METHODS: We conducted hypothesis-free two-sample Mendelian randomisation (MR) analysis of the concentration of 575 plasma/serum metabolites, to determine which are causally linked to risk of ALS. Significant metabolites were validated in an independent GWAS of plasma/serum metabolite concentrations and evaluated for sex-specific effects. Correlations between directly measured patient biofluid metabolite concentrations and ALS risk/severity were examined in 94 ALS patients and 40 controls. We experimentally assessed metabolic function in a murine neurons and human astrocytes carrying an ALS-associated G4C2-repeat expansion within C9orf72. RESULTS: MR causally associated five metabolites with ALS risk after multiple-testing correction. Higher serum concentration of glycoprotein acetyls (P&#x2009;=&#x2009;9.7e&#x2009;-&#x2009;9, &#x3b2;&#x2009;=&#x2009;0.21) and the peptide DSGEGDFXAEGGGVR (P&#x2009;=&#x2009;8.0e&#x2009;-&#x2009;6, &#x3b2;&#x2009;=&#x2009;0.22) was associated with increased ALS risk, whereas higher plasma concentration of phenylalanylserine, isobutyrylcarnitine, and acetylcarnitine was protective (P&#x2009;<&#x2009;5e&#x2009;-&#x2009;5, &#x3b2;&#x2009;= -&#x2009;0.29 to&#x2009;-&#x2009;0.72). DSGEGDFXAEGGGVR has been linked to glucose metabolism but we have used genetic fine-mapping to link DSGEGDFXAEGGGVR, neuronal glucose uptake through GLUT3, and ALS risk. Direct measurement of metabolite concentrations in patient biofluids revealed elevated acetylcarnitine levels in patients with ALS, which were associated with delayed symptom onset (Cox regression, P&#x2009;=&#x2009;0.02, HR&#x2009;=&#x2009;0.4). Similarly, lactate is elevated in ALS patient CSF (ANOVA, P&#x2009;=&#x2009;1.3e&#x2009;-&#x2009;3) and in patients with longer survival time (Cox regression, P&#x2009;=&#x2009;0.03, HR&#x2009;=&#x2009;0.3). Plasma fructose is elevated in ALS patients with shorter survival time (Cox regression, P&#x2009;=&#x2009;0.02, HR&#x2009;=&#x2009;1.1). In vitro, neurons and astrocytes carrying an ALS-associated G4C2-repeat expansion within C9orf72 demonstrated reduced metabolic flexibility. CONCLUSIONS: We provide evidence that impaired energy substrate availability contributes to ALS risk and severity. CNS cell types differ in their use of energy substrates and therefore we postulate the relative importance of different cell types for different stages of disease. Our findings support further investigation of metabolic interventions to treat or prevent ALS.

Amyotrophic Lateral Sclerosis↗

Dissecting the shared genetic architecture between migraine subtypes and cardiovascular diseases: a multi-layered genomic analysis.

BACKGROUND: Epidemiological studies have linked migraine to an increased risk of cardiovascular disease (CVD); however, the shared genetic basis and putative causal relationships between migraine subtypes and cardiovascular traits remain poorly understood. METHODS: Leveraging large-scale GWAS summary statistics for migraine phenotypes (overall migraine, migraine with aura [MA], and migraine without aura [MO]) from FinnGen R12, along with seven cardiovascular diseases from publicly available consortia, we conducted a multi-layered genetic analysis. This integrative framework encompassed genetic correlation [linkage disequilibrium score regression (LDSC) and high-definition likelihood (HDL)], cross-trait meta-analysis (CPASSOC and PLACO), Bayesian colocalization, summary-data-based Mendelian randomization (SMR) using GTEx v8 eQTL data, and bidirectional two-sample Mendelian randomization (MR). RESULTS: Significant genetic correlations were identified between migraine and multiple cardiovascular traits, with hypertension and coronary artery disease (CAD) showing the most robust associations. MA exhibited broader genetic overlap with cardiovascular diseases than MO, including a notably stronger correlation with ischemic stroke, whereas MO demonstrated a stronger correlation with hypertension. Cross-trait meta-analysis identified 160 pleiotropic loci across 17 of 21 trait pairs. Colocalization analysis confirmed 32 loci harboring shared causal variants, mapped to 13 candidate genes, of which 7 (PHACTR1, LRP1, SOX7, ABO, FHOD3, MEI1, XKR6) were further validated by SMR as exhibiting tissue-specific regulatory effects. Among these, PHACTR1 displayed the broadest pleiotropic profile across migraine phenotypes and vascular diseases. After MR-PRESSO outlier removal, bidirectional MR identified 10 MR-supported associations, two of which (genetic liability to hypertension on overall migraine, and CAD on MA) survived Bonferroni correction, all free of detectable horizontal pleiotropy. Genetic liability to hypertension was associated with increased migraine risk (OR&#x2009;=&#x2009;1.90, 95% CI 1.25-2.90, P&#x2009;=&#x2009;2.64&#x2009;&#xd7;&#x2009;10&#x207b;&#xb3;), atherosclerotic diseases showed subtype-specific effects (inverse for MO, positive for MA), and, in the reverse direction, migraine was associated with increased ischemic stroke risk. CONCLUSIONS: This study provides a comprehensive and systematic characterization of the shared genetic architecture between migraine subtypes and cardiovascular diseases. By identifying pleiotropic genes and bidirectional putative causal relationships with subtype-specific patterns, our findings carry implications for the development of targeted therapeutics and subtype-specific cardiovascular risk stratification.

Humans↗

Genomic study for pregnancy loss in Brahman cattle.

Reproduction has major influence on productivity of beef cattle operations. Maintaining an animal in the herd for an extended period without producing a marketable product can result in significant economic losses, compromising the efficiency of the production system. Understanding genetic variation's role in pregnancy loss (PL) is crucial for improving reproductive success in cattle. Identifying genomic regions that influence embryo and fetal survival, as well as pinpointing candidate genes associated with PL, can enhance breeding strategies. The objective of this study was to estimate variance components and investigate genetic factors associated with PL in Brahman cattle. Phenotypic records consisted of 29,905 pregnancy (28,691) and abortion (1,214) records from nulliparous, primiparous, and multiparous cows. A total of 921 animals were genotyped using a medium-density SNP chip (&#x223c;52K markers). Variance components were estimated using a threshold model to assess the binary response to PL through a single-step genomic BLUP procedure. The heritability estimate for PL was low (0.11), but the presence of genetic variance suggests that selection for improved reproductive performance is feasible. Genome-wide association analyses identified 17 candidate regions containing 92 genes. Regions on BTA4, 7, 8, 9, 11, 12, 16, 18, 19, 21, 22, and 29 harbored genes associated with embryonic development and implantation, fertilization, G protein-coupled receptors, embryonic brain development, olfactory receptor activity, and calcium signaling. Orthologous genes were also identified in humans (Homo sapiens), rats (Rattus norvegicus), and mice (Mus musculus). The candidate regions reported in this study provide insights for identifying and selecting animals with improved reproductive performance, ultimately enhancing the productivity of Brahman cattle. Moreover, our findings contribute to a better understanding of the genetic and physiological mechanisms underlying pregnancy retention in beef cattle.

Animals↗