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A survey of genetic and epigenetic variation affecting human gene expression.

The identification of human sequence polymorphisms that regulate gene expression is key to understanding human genetic diseases. We report a survey of human genes that demonstrate allelic differences in gene expression, reflecting the presence of putative allele-specific cis-acting factors of either genetic or epigenetic nature. The expression of allelic transcripts in heterozygous samples is assessed directly by relative quantitation of intragenic marker alleles in messenger or heteronuclear RNA derived from cells or tissues. This survey used 193 single-nucleotide polymorphisms (SNPs) from 129 genes expressed in lymphoblastoid cell lines, to identify 23 genes (18%) with common allele-specific transcripts whose expression deviated from the expected equimolar ratio. A subset of these deviations, or "allelic imbalances," can be observed in multiple samples derived from reference CEPH ("Centre d'Etude du Polymorphisme Humain") pedigrees and demonstrate a spectrum of patterns of transmission, including cosegregation of allelic skewing across generations compatible with Mendelian inheritance as well as random monoallelic expression for three genes (IL1A, HTR2A, and FGB). Additional studies for BTN3A2 provide evidence of SNPs and haplotypes in complete linkage disequilibrium with high- and low-expressing transcripts. The pipeline described herein offers tools for efficient identification and characterization of allelic expression allowing identification of regulatory sequence variants as well as epigenetic variation affecting human gene expression.

Allelic Imbalance↗

Association among blood pressure, antihypertensive drugs, and amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease. The impacts of antihypertensive drugs and blood pressure (BP) on ALS are currently debatable. OBJECTIVE: To evaluate the causal relationship involving antihypertensive drugs, BP, and ALS through a Mendelian randomization (MR) analysis. METHODS: The causal relationship between BP and ALS was evaluated by a bidirectional two-sample MR analysis. Then, a sensitivity analysis was performed using a secondary BP genome-wide association study. The drug-target MR was employed to evaluate the impact of antihypertensive drugs on ALS. Furthermore, we used cis-expression quantitative trait loci (cis-eQTLs) data from brain tissue and blood to validate the positive results by a summary-based MR method. RESULTS: We found that an increment in systolic BP (SBP) could elevate the risk of ALS (inverse-variance weighted [IVW] odds ratio [OR] = 1.003; 95% confidence interval [95%CI]: 1.001-1.006; per 10-mmHg increment) and ALS might be protected by angiotensin-converting enzyme inhibitors (ACEIs; OR = 0.970; 95%CI: 0.956-0.984; p = 1.96 × 10-5; per 10-mmHg decrement). A causal relationship was not observed between diastolic BP and other antihypertensive drugs in ALS. CONCLUSION: In the present study, genetic support for elevated SBP serves as a risk factor for ALS. Besides, ACEIs hold promise as a candidate for ALS.

Humans↗

Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.

BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.

Humans↗

Genetic pleiotropy underlying obesity and autoimmune disorders: a large-scale cross-trait gwas analysis in European ancestry populations.

BACKGROUND: Obesity and autoimmune disorders represent a significant comorbidity burden, yet their shared genetic architecture is not fully understood. Elucidating the pleiotropic genetic basis underlying both conditions is crucial for unraveling the mechanisms driving their co-occurrence and advancing therapeutic strategies. METHODS: We conducted a large-scale cross-trait analysis integrating genome-wide association study (GWAS) summary data for obesity and 17 autoimmune diseases. Genetic correlations were assessed using LD score regression and high-definition likelihood. Cross-trait pleiotropic analysis was performed using Stratified Pleiotropic Locus Mapping (PLACO) to identify shared loci, followed by Bayesian colocalization to confirm shared causal variants. Gene-level and tissue-specific heritability analyses were conducted, and drug targets were prioritized via summary-based Mendelian randomization (SMR). Finally, immune co-localization and bidirectional Mendelian randomization were employed to elucidate immunological mechanisms and causal relationships. RESULTS: Our analysis identified eight autoimmune diseases with significant genetic correlations to obesity. We discovered 10,324 pleiotropic SNPs, which mapped to 52 independent risk loci, with nine loci confirmed as shared causal variants by colocalization. Gene-level analysis revealed 133 unique pleiotropic genes, including CLN3, SH2B1, and MMEL1, enriched in pathways of hematopoietic cell differentiation and immune homeostasis. Tissue-specific heritability was most prominent in the spleen, whole blood, and EBV-transformed lymphocytes. Immuno-co-localization implicated six IgD+ CD38- %B cell-related traits as key pathological conduits. Bidirectional Mendelian randomization established a causal role of obesity in hypothyroidism, psoriasis, and multiple sclerosis, while revealing an inverse causal association of type 1 diabetes with obesity risk. CONCLUSIONS: This study demonstrates a robust shared genetic foundation between obesity and multiple autoimmune diseases, pinpointing specific pleiotropic loci, genes, and immune cell subsets. Our findings provide a mechanistic framework for their comorbidity and highlight potential targets for therapeutic intervention.

Humans↗

Glaucoma and brain functional networks: a bidirectional Mendelian randomisation study.

OBJECTIVE: Glaucoma is a complex neurodegenerative ocular disorder accompanied by brain functional abnormalities that extend beyond the visual system. However, the causal association between the two remains unclear at present. This study aimed to investigate the potential causal relationships between glaucoma and brain functional networks in order to provide novel insights into the neuropathic mechanism of glaucoma. METHODS AND ANALYSIS: Based on the genome-wide association studies data of glaucoma and resting-state functional MRI (Rs-fMRI), a bidirectional Mendelian randomisation (MR) analysis was conducted between glaucoma and brain functional networks. Inverse variance weighting was applied as the primary method to estimate causality with false discovery rate correction. Additional sensitivity analyses were conducted to evaluate the robustness of the results. RESULTS: Forward MR analysis suggested that glaucoma was causally associated with two brain networks between the subcortical cerebellum and the attention or visual network (p=0.022), as well as the default mode and central executive network (p=0.008), but without significance after false discovery rate correction (q>0.1). Reverse MR analysis revealed 19 Rs-fMRI traits related to glaucoma risk, including the salience or central executive network in the frontal region (p=0.0005, q=0.08) and the motor network (p=0.0009, q=0.08) with significant causality. CONCLUSIONS: This MR study revealed potentially causal relationships between glaucoma and brain functional networks. Especially, the functional connectivity of the motor network between the postcentral or precentral areas may potentially lead to increased risk of glaucoma.

Humans↗

Genetically Proxied Inhibition of Cholesterol-Lowering Drug Targets and Survival in HPV-Positive and Non-HPV-Driven Head and Neck Cancer: A Multicentre MR Study.

BACKGROUND: Cholesterol pathways may influence head and neck squamous cell carcinoma (HNSCC) progression, but evidence on prognosis is inconsistent. We used Mendelian randomization (MR) to test whether genetically proxied inhibition of major low-density lipoprotein cholesterol (LDL-C)-lowering drug targets and circulating lipid traits affects overall survival (OS) in HPV-positive and non-HPV-driven HNSCCs. METHODS: We proxied lifelong LDL-C lowering using 55 cis-acting single-nucleotide polymorphisms in HMGCR, NPC1L1, PCSK9, and LDL-receptor (LDLR) from the updated 2021 Global Lipids Genetics Consortium and instrumented circulating lipid traits. Two-sample MR estimated effects on OS in 4,869 multicentre HNSCC cases (1,291 HPV-positive; 3,578 non-HPV-driven) using minimally adjusted Cox models. Sensitivity analyses additionally adjusted for tumor stage and treatment, assessed collider bias using an external HNSCC incidence genome-wide association study, and examined between-center heterogeneity and colocalization. RESULTS: Using the updated Global Lipids Genetic Consortium 2021 instruments, genetically proxied HMGCR inhibition showed a directionally protective but nonsignificant association with OS in HPV-positive oropharyngeal HNSCC in the primary analysis [inverse variance weighted (IVW) HR = 0.19; 95% confidence interval (CI), 0.03-1.18; P = 0.08], with directionally concordant weighted median results. No corresponding protective association was observed for HMGCR in non-HPV-driven disease (IVW HR = 1.68; 95% CI, 0.78-3.63; P = 0.19). No clear evidence of association was observed for NPC1L1, PCSK9, LDLR, or circulating lipid traits in either HPV stratum. Colocalization did not support a shared causal variant. CONCLUSIONS: These analyses provide suggestive evidence that genetically proxied HMGCR inhibition may influence survival in HPV-positive oropharyngeal HNSCC. IMPACT: HMGCR-related pathways may be relevant to prognosis in HPV-positive oropharyngeal HNSCC, whereas clear survival effects of other cholesterol-lowering targets were not supported.

Humans↗

Integrative multi-omics analyses suggest a candidate microbial metabolite-associated host gene network in ulcerative colitis.

Ulcerative colitis (UC) is associated with gut microbial dysbiosis, but the host molecular alterations potentially linked to microbially derived metabolites remain incompletely understood. We integrated Mendelian randomization (MR), microbial metabolite annotation, computational target prediction, colonic transcriptomics, network analysis, and machine learning. MiBioGen microbiome GWAS data were used as exposures and FinnGen Release 12 ULCERENTER as the outcome. Metabolites linked to MR-prioritized taxa were retrieved from GutMGene, and human targets were predicted using SwissTargetPrediction and SEA. UC-related genes were defined by integrating differential expression analysis and WGCNA and then intersected with predicted metabolite targets. MR prioritized one family and eight genera showing nominal genetically supported associations with UC, but none remained significant after Benjamini-Hochberg FDR correction. Three prioritized genera were linked to 15 microbe-metabolite records, corresponding to 13 unique metabolites; nine were retained for target prediction, yielding 277 unique predicted human targets. Transcriptomic analysis identified 1,530 DEGs and a 312-gene MEgrey60 module, with 273 overlapping genes, producing 1,569 unique UC-related genes. Their intersection with the 277 predicted targets yielded 47 candidate genes. Enrichment analyses highlighted mainly metabolic and lipid-related processes. Random Forest showed the highest mean AUC across the two independent external benchmarking cohorts, and SHAP prioritized EPHX1, HSD17B2, IGFBP5, and MMP10. IBDome analysis showed inflammation-associated expression differences in these genes. This study provides a genomics-informed, hypothesis-generating framework that prioritizes candidate microbe-metabolite-host relationships in UC for future experimental validation.

Humans↗

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with &#x223c;5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p&#xa0;<&#xa0;0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Humans↗

Integrative multi-omics quantitative trait loci prioritize CASP7 as a candidate protective gene for cataract.

Cataracts are the leading cause of vision loss worldwide. Despite surgery being the only effective treatment, its economic burden highlights the necessity of exploring the pathogenesis of cataracts. In this study, we analyzed 4 large-scale GWAS (genome-wide association study) datasets for cataracts and performed SMR analysis along with heterogeneity in dependent instruments (HEIDI) testing to explore the effects of methylation, expression, and protein QTLs on cataracts. We further validated shared genetic variants through COLOC analysis. Additionally, we searched datasets related to cataracts from the Gene Expression Omnibus (GEO) database for differentially expressed genes (DEGs) and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses. By integrating summary-based Mendelian randomization (SMR) results with bioinformatics findings, CASP7 showed a consistent protective-direction association with cataract risk (mQTL: OR [95% CI]&#x2005;=&#x2005;0.959 [0.941-0.977], FDR-adjusted P&#x2005;=&#x2005;.039; eQTL: OR [95% CI]&#x2005;=&#x2005;0.897 [0.860-0.937], FDR-adjusted P&#x2005;=&#x2005;.0046; pQTL: OR [95% CI]&#x2005;=&#x2005;0.597 [0.483-0.738], FDR-adjusted P&#x2005;=&#x2005;.00083). GEO-based analyses provided transcriptomic support for CASP7 involvement in cataract-related lens biology. These findings prioritize CASP7 as a genetically supported candidate protective gene associated with cataract risk. Because this study is based on public summary-level and transcriptomic datasets, the results should be interpreted cautiously and require functional validation in human lens-relevant systems.

Quantitative Trait Loci↗

The relationship between vitamin D levels and depression: a genetically informed study.

BACKGROUND: Low vitamin D (vitD) levels are consistently associated with an increased risk of depression. However, the biological mechanisms underlying this relationship and potential shared genetic overlap remain elusive. METHODS: We investigated the genetic overlap and causal relationships between depression (N&#x2009;=&#x2009;589,356) and vitD levels (N&#x2009;=&#x2009;417,580) using genome-wide association study (GWAS) summary statistics. We performed genome-wide and local genetic correlation analyses, followed by quantification of polygenic overlap variants. Shared genetic loci were identified and mapped to genes, which were further analyzed through gene expression and lifespan brain expression trajectory analyses. Bidirectional causal relationships were examined using multiple Mendelian randomization approaches. RESULTS: We observed significant negative genetic correlations (rg = -0.079) and identified genetic overlap (N&#x2009;=&#x2009;410 variants). Genes mapped to the 13 shared loci showed opposing expression patterns. Tissue- and cell-specific functional enrichment analyses revealed significant signals related to brain development, with distinct patterns emerging between fetal development and adulthood. Shared genes (TRMT61A, ITIH4, RASGRP1, CTNND1, HERC1, IP6K1, FURIN ESR1, ZMYND and GRM5) exhibited notable expression variation in the brian throughout the lifespan, aligning with functional enrichment findings. CONCLUSIONS: Our findings elucidate the shared biological mechanisms underlying the relationship between vitD and depression, suggesting that vitD play an important role in the development of depression through altered early neurodevelopmental processes.

Humans↗

Exploring birth options after three or four cesarean sections in Poland: maternal and neonatal outcomes following vaginal vs repeat surgical deliveries.

OBJECTIVES: The study aimed to analyze maternal and neonatal outcomes of women with a history of three or four caesarean sections (CS) and to evaluate the feasibility and safety of vaginal birth after multiple caesarean sections (VBAC &#x2265; 3) in Polish clinical practice. MATERIAL AND METHODS: A retrospective analysis was conducted on medical records of 186 women with three or four prior CS who delivered at St. Sophia Specialist Hospital in Warsaw between 2017 and 2024. Data on delivery mode, obstetric management, complications, and neonatal outcomes were assessed. Multivariate logistic regression was applied to identify factors associated with successful VBAC. RESULTS: Of the study group, 62 women attempted trial of labour after caesarean (TOLAC), resulting in 32 successful vaginal births (success rate 53.2%). 124 women chose Elective CS. Logistic regression showed that prior vaginal birth (OR = 20.34; p = 0.008) and the use of epidural anaesthesia (OR = 22.88; p = 0.006) significantly increased the likelihood of successful VBAC. Spontaneous onset of labour showed a positive but non-significant trend (OR = 2.52; p = 0.230). The model demonstrated a classification accuracy of 77.4% and a good overall fit (Nagelkerke R&#xb2; = 0.456). Uterine rupture occurred in three cases (4.8%), while no maternal or neonatal deaths were reported. CONCLUSIONS: Vaginal birth after three or more CS may be a viable option for carefully selected women, provided it is offered in tertiary centers with immediate surgical readiness. Key predictors of success include prior vaginal birth and epidural anaesthesia. Further large-scale studies are needed to refine guidelines and inform clinical practice in this high-risk group.

Humans↗

Genome-Wide Aggregated Trans Effects Analysis Identifies Genes Encoding Immune Checkpoints as Core Genes for Rheumatoid Arthritis.

OBJECTIVE: The sparse effector "omnigenic" hypothesis postulates that the polygenic effects of common single nucleotide polymorphisms (SNPs) on a typical complex trait are mediated by trans effects that coalesce on expression of a relatively sparse set of core genes. The objective of this study was to identify core genes for rheumatoid arthritis by testing for association of rheumatoid arthritis with genome-wide aggregated trans effects (GATE) scores for expression of each gene as transcript in whole blood or as circulating protein levels. METHODS: GATE scores were calculated for 5,400 cases and 453,705 non-cases of primary rheumatoid arthritis in UK Biobank participants of European ancestry. RESULTS: Testing for association with GATE scores identified 16 putative core genes for rheumatoid arthritis outside the HLA region, of which six-TP53BP1, PDCD1, TNFRSF14, LAIR1, LILRA4, and IDO1-were supported by Mendelian randomization analysis based on the marginal likelihood of the causal effect parameter. Five of these 16 genes were validated by a reported association of rheumatoid arthritis with SNPs within 200 kb of the transcription site, eight by association of the measured protein level with rheumatoid arthritis in UK Biobank, 10 by experimental perturbation in mouse models of inflammatory arthritis, and two-CTLA4 and PDCD1-by evidence that drugs targeting the gene cause or ameliorate inflammatory arthritis in humans. Fourteen of these 16 genes are in pathways affecting immunity or inflammation, and six-CD5, CTLA4, TIGIT, LAIR1, TNFRSF14, and PDCD1-encode receptors that have been characterized as immune checkpoints exploited by cancer cells to escape the immune response. CONCLUSION: These results highlight the key role of immune checkpoints in rheumatoid arthritis and identify possible therapeutic targets.

Humans↗

Genetic Relationship Between Endometriosis and Melanoma.

Epidemiological studies have observed that risk of endometriosis is associated with history of cutaneous melanoma and vice versa. Evidence for shared biological mechanisms between the two traits is limited. The aim of this study was to investigate the genetic correlation and causal relationship between endometriosis and melanoma. Summary statistics from genome-wide association meta-analyses (GWAS) for endometriosis and melanoma were used to estimate the genetic correlation between the traits and Mendelian randomization was used to test for a causal association. When using summary statistics from separate female and male melanoma cohorts we identified a significant positive genetic correlation between melanoma in females and endometriosis (r g = 0.144, se = 0.065, p = 0.025). However, we find no evidence of a correlation between endometriosis and melanoma in males or a combined melanoma dataset. Endometriosis was not genetically correlated with skin color, red hair, childhood sunburn occasions, ease of skin tanning, or nevus count suggesting that the correlation between endometriosis and melanoma in females is unlikely to be influenced by pigmentary traits. Mendelian Randomization analyses also provided evidence for a relationship between the genetic risk of melanoma in females and endometriosis. Colocalization analysis identified 27 genomic loci jointly associated with the two diseases regions that contain different causal variants influencing each trait independently. This study provides evidence of a small genetic correlation and relationship between the genetic risk of melanoma in females and endometriosis. Genetic risk does not equate to disease occurrence and differences in the pathogenesis and age of onset of both diseases means it is unlikely that occurrence of melanoma causes endometriosis. This study instead provides evidence that having an increased genetic risk for melanoma in females is related to increased risk of endometriosis. Larger GWAS studies with increased power will be required to further investigate these associations.

endometriosis↗

Investigating the causal role of smoking in gout: A triangulation approach combining NHANES data, genetic correlation, and Mendelian randomization.

The relationship between smoking and the development of gout is not well understood. To address this, we adopted a triangulation framework that integrates observational analysis, genetic correlation estimation, and two-sample Mendelian randomization (MR) to examine whether smoking confers a causal risk for gout. We first performed a cross-sectional analysis using information for 13,626 participants from the National Health and Nutrition Examination Survey between 2013 and 2018. The association of smoking with gout was subsequently assessed through logistic regression models. We next investigated the extent of shared genetic factors between smoking phenotypes and gout. We were able to demonstrate this using the linkage disequilibrium score regression applied to genome-wide association study data of European ancestry. Finally, to verify the causality of our relationship, we carried out a two-sample MR analysis. We selected the inverse-variance weighted (IVW) method and confirmed the consistency of using the IVW method with other statistical methods, including weighted median, weighted mode, and simple mode, as well as MR-Egger regression. We performed sensitivity analyses to investigate the heterogeneity of the hypothesis and stability of the data. Our findings based on National Health and Nutrition Examination Survey data reveal that there is a strong positive association between smoking and the risk of gout (odds ratio [OR]&#x2005;=&#x2005;1.94, 95% confidence interval [CI]&#x2005;=&#x2005;1.48-2.55, P&#x2005;<&#x2005;.001). This association persisted after confounding adjustments (OR&#x2005;=&#x2005;1.41, 95% CI&#x2005;=&#x2005;1.04-1.91, P&#x2005;=&#x2005;.027). In the subgroup analyses, former smokers and current smokers of 10 to 20 cigarettes per day had a substantially increased risk. Post-linkage disequilibrium score regression analysis revealed that the significantly positive genetic correlations of smoking initiation and lifetime smoking index with gout risk were both significantly positive. Additional evidence for causality is presented by MR. Genetic prediction of smoking initiation statistically increases gout risk (IVW OR&#x2005;=&#x2005;1.55, 95% CI&#x2005;=&#x2005;1.26-1.90, P&#x2005;=&#x2005;3.17&#x2005;&#xd7;&#x2005;10-5). A much stronger association is evident for lifetime smoking index (IVW OR&#x2005;=&#x2005;1.99, 95% CI&#x2005;=&#x2005;1.44-2.76, P&#x2005;=&#x2005;3.24&#x2005;&#xd7;&#x2005;10-5). These findings are the same with or without heterogeneity by sensitivity analysis. In light of our integrated analysis, smoking is a causative factor for gout. This suggests that public health interventions like anti-smoking campaigns might reduce gout incidence.

Humans↗

Genetic Downregulation of Interleukin-6 Signaling, Coagulation Function, and Risk of Thromboembolic Disease.

BACKGROUND: Although genetic evidence supports IL-6 (interleukin-6) signaling inhibition as protective against atherosclerotic disease, its potential effects on thromboembolic outcomes are not well established. We conducted a Mendelian randomization analysis to investigate the association of genetically proxied IL-6 signaling inhibition with venous thromboembolism, cardioembolic stroke, and coagulation cascade protein levels. METHODS: IL-6 signaling inhibition was proxied using the rs2228145 IL6R missense variant, which impairs classical IL-6 signaling and lowers CRP (C-reactive protein) levels. Genetic associations with thromboembolic disease outcomes were obtained from genome-wide association studies of venous thromboembolism (81&#x2009;190 cases) and cardioembolic stroke (10&#x2009;804 cases). As atherosclerotic comparator traits, we included coronary artery disease (181&#x2009;522 cases) and large-artery atherosclerotic stroke (6399 cases). Genetic associations with 35 coagulation cascade protein levels were obtained from the UK Biobank (n=6218) and deCODE cohorts (n=35&#x2009;559). Mendelian randomization estimates were derived using the Wald ratio method, scaled per 1-unit decrease in natural log-transformed CRP levels. RESULTS: Genetically proxied IL-6 signaling inhibition was associated with increased risk of venous thromboembolism (odds ratio [OR], 1.31 [95% CI, 1.16-1.47], P=6.5&#xd7;10-6) but not with cardioembolic stroke (OR, 1.25 [95% CI, 0.73-2.14], P=0.42). Conversely, protective associations were observed for both coronary artery disease and large-artery atherosclerotic stroke. Proteomic analyses demonstrated significant reductions in levels of 5 procoagulant and 7 anticoagulant or antifibrinolytic proteins. CONCLUSIONS: These findings suggest that IL-6 signaling inhibition dysregulates coagulation homeostasis and increases venous thromboembolism risk. Further experimental, translational, and epidemiologic studies are warranted to delineate underlying mechanisms and to evaluate thromboembolic safety in pharmacologic IL-6 signaling inhibition.

Humans↗

Distinct Genetic Risk Profile in Aortic Stenosis Compared With Coronary Artery Disease.

IMPORTANCE: Aortic stenosis (AS) and coronary artery disease (CAD) frequently coexist. However, it is unknown which genetic and cardiovascular risk factors might be AS-specific and which could be shared between AS and CAD. OBJECTIVE: To identify genetic risk loci and cardiovascular risk factors with AS-specific associations. DESIGN, SETTING, AND PARTICIPANTS: This was a genomewide association study (GWAS) of AS adjusted for CAD with participants from the European Consortium for the Genetics of Aortic Stenosis (EGAS) (recruited 2000-2020), UK Biobank (recruited 2006-2010), Estonian Biobank (recruited 1997-2019), and FinnGen (recruited 1964-2019). EGAS participants were collected from 7 sites across Europe. All participants were of European ancestry, and information on comorbid CAD was available for all participants. Follow-up analyses with GWAS data on cardiovascular traits and tissue transcriptome data were also performed. Data were analyzed from October 2022 to July 2023. EXPOSURES: Genetic variants. MAIN OUTCOMES AND MEASURES: Cardiovascular traits associated with AS adjusted for CAD. Replication was performed in 2 independent AS GWAS cohorts. RESULTS: A total of 18&#x202f;792 participants with AS and 434&#x202f;249 control participants were included in this GWAS adjusted for CAD. The analysis found 17 AS risk loci, including 5 loci with novel and independently replicated associations (RNF114A, AFAP1, PDGFRA, ADAMTS7, HAO1). Of all 17 associated loci, 11 were associated with risk specifically for AS and were not associated with CAD (ALPL, PALMD, PRRX1, RNF144A, MECOM, AFAP1, PDGFRA, IL6, TPCN2, NLRP6, HAO1). Concordantly, this study revealed only a moderate genetic correlation of 0.15 (SE, 0.05) between AS and CAD (P&#x2009;=&#x2009;1.60&#x2009;&#xd7;&#x2009;10-3). Mendelian randomization revealed that serum phosphate was an AS-specific risk factor that was absent in CAD (AS: odds ratio [OR], 1.20; 95% CI, 1.11-1.31; P&#x2009;=&#x2009;1.27&#x2009;&#xd7;&#x2009;10-5; CAD: OR, 0.97; 95% CI 0.94-1.00; P&#x2009;=&#x2009;.04). Mendelian randomization also found that blood pressure, body mass index, and cholesterol metabolism had substantially lesser associations with AS compared with CAD. Pathway and transcriptome enrichment analyses revealed biological processes and tissues relevant for AS development. CONCLUSIONS AND RELEVANCE: This GWAS adjusted for CAD found a distinct genetic risk profile for AS at the single-marker and polygenic level. These findings provide new targets for future AS research.

Humans↗

Genetic evidence links hypertension to accelerated brain aging.

Hypertension affects one-third of adults and is a major comorbidity of neurocognitive disorders. The causal relationship, shared genetic architecture, and upstream mechanisms linking hypertension to brain aging remain unclear. Hypertension GWAS datasets from MVP and FinnGen R12 were meta-analyzed as the exposure, and a European-ancestry brain age gap (BAG) GWAS derived from the UK Biobank and LIFE-Adult cohorts was used as the outcome. MR and GSMR assessed causality. LDSC, HDL, and S-LDSC estimated genetic correlation. Four TWAS methods (MAGMA, FUSION, JTI-PrediXcan, FOCUS) mapped associations to genes, followed by SMR for causal validation and PoPS for prioritization. GSMAP with spatial transcriptomics characterized regional and cell-type enrichment. Hypertension and brain aging were genetically correlated, and MR and GSMR analyses suggested a causal effect of hypertension on increased brain age gap. TWAS identified 15 shared Hypertension-BAG genes, 10 supported by SMR. PoPS prioritized TRIM47 as the core gene. Shared signals were enriched in meninges, fiber tracts, cortical layer 1, and CA1 stratum lacunosum/radiatum, with cell-type enrichment in meninges, smooth muscle cells, oligodendrocytes, and astrocyte subtypes. Hypertension is genetically correlated with, and shows evidence of a causal effect on, accelerated brain aging. TRIM47 is a core gene bridging hypertension and BAG. GSMAP-based spatial enrichment provides a hypothesis-generating framework for understanding vascular, meningeal, and myelin-related pathways linking hypertension to increased brain age gap.

Humans↗

Large-Scale Proteomic Profiling of Incident Heart Failure and Its Subtypes in Older Adults.

BACKGROUND: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment. METHODS: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference. RESULTS: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NPDC1 [neural proliferation differentiation and control protein 1], APOF [apolipoprotein F], LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization. CONCLUSIONS: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Humans↗