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PubMed2025

Automated Deep Learning-Based Detection of Early Atherosclerotic Plaques in Carotid Ultrasound Imaging.

BACKGROUND: Carotid plaque presence is associated with cardiovascular risk, even among asymptomatic individuals. While deep learning has shown promise for carotid plaque phenotyping in patients with advanced atherosclerosis, its application in population-based settings of asymptomatic individuals remains unexplored. METHODS: We developed a YOLOv8-based model for plaque detection using carotid ultrasound images from 19,499 participants of the population-based UK Biobank (UKB) and fine-tuned it for external validation in the BiDirect study (N = 2,105). Cox regression was used to estimate the impact of plaque presence and count on major cardiovascular events. To explore the genetic architecture of carotid atherosclerosis, we conducted a genome-wide association study (GWAS) meta-analysis of the UKB and CHARGE cohorts. Mendelian randomization (MR) assessed the effect of genetic predisposition to vascular risk factors on carotid atherosclerosis. RESULTS: Our model demonstrated high performance with accuracy, sensitivity, and specificity exceeding 85%, enabling identification of carotid plaques in 45% of the UKB population (aged 47-83 years). In the external BiDirect cohort, a fine-tuned model achieved 86% accuracy, 78% sensitivity, and 90% specificity. Plaque presence and count were associated with risk of major adverse cardiovascular events (MACE) over a follow-up of up to seven years, improving risk reclassification beyond the Pooled Cohort Equations. A GWAS meta-analysis of carotid plaques uncovered two novel genomic loci, with downstream analyses implicating targets of investigational drugs in advanced clinical development. Observational and MR analyses showed associations between smoking, LDL cholesterol, hypertension, and odds of carotid atherosclerosis. CONCLUSIONS: Our model offers a scalable solution for early carotid plaque detection, potentially enabling automated screening in asymptomatic individuals and improving plaque phenotyping in population-based cohorts. This approach could advance large-scale atherosclerosis research.

atherosclerosis↗

PubMed2025

THE CAUSAL ASSOCIATION OF CARDIOMETABOLIC DISEASES AND SEPSIS-RELATED OUTCOMES: A MENDELIAN RANDOMIZATION AND POPULATION STUDY.

Objective: The causality between cardiometabolic disease (CMD) and sepsis has remained largely unknown. To elucidate this, we conducted a Mendelian randomization (MR) and population study. Methods: First, we used univariable and multivariable MR analyses to investigate causal associations between CMD and sepsis-related outcomes. We obtained genome-wide association study summary from both the MRC Integrative Epidemiology Unit and the FinnGen consortium. Subsequently, a two-step mediation MR analysis was performed to explore mediators. Afterward, we conducted an observational study using the Medical Information Mart for Intensive Care IV database, in which multivariable logistic regression models were utilized to examine the relationship between CMD and sepsis-related outcomes. Results: In the MR study, type 2 diabetes mellitus (OR = 1.058, 95% CI = 1.017-1.100, P = 0.005), obesity (OR = 1.113, 95% CI = 1.057-1.172, P < 0.001), and heart failure (HF) (OR = 1.178, 95% CI = 1.063-1.305, P = 0.002) were independently causally related to sepsis. Obesity (OR = 1.215, 95% CI = 1.027-1.437, P = 0.023) and HF (OR = 1.494, 95% CI = 1.080-2.065, P = 0.015) also showed independent causal associations with sepsis critical care admission. Mediation MR analysis identified 23 blood metabolites potentially causally linked to sepsis ( P < 0.05), yet none mediated the relationship between CMD and sepsis. In the observational study, we found associations between sepsis and several conditions including type 2 diabetes mellitus, obesity, hypertension, stroke, HF, and hyperlipidemia after adjusting for confounding factors. Moreover, hypertension, stroke, HF, coronary artery disease, and hyperlipidemia were linked to sepsis critical care admission. Conclusion: This study has, for the first time, revealed indicative evidence of a causal relationship between CMD and sepsis through observational and genetic evidence. Taken together, clinical attention to sepsis may be warranted among patients with CMD.

Humans↗

PubMed2024

No causal relationship between glucose and inflammatory bowel disease: a bidirectional two-sample mendelian randomization study.

BACKGROUND: Association between glucose and inflammatory bowel disease (IBD) was found in previous observational studies and in cohort studies. However, it is not clear whether these associations reflect causality. Thus, this study investigated whether there is such a causal relation between elevated glucose and IBD, Crohn's disease (CD) and ulcerative colitis (UC). METHODS: We performed a two-sample Mendelian Randomization (MR) with the independent genetic instruments identified from the largest available genome-wide association study (GWAS) for IBD (5,673 cases; 213,119 controls) and its main subtypes, CD and UC. Summarized data for glucose which included 200,622 cases and glycemic traits including HbA1c and type 2 diabetes(T2DM) were obtained from different GWAS studies. Primary and secondary analyses were conducted by preferentially using the radial inverse-variance weighted (IVW) approach. A number of other meta-analysis approach and sensitivity analyses were carried out to assess the robustness of the results. RESULTS: We did not find a causal effect of genetically predicted glucose on IBD as a whole (OR 0.858; 95% CI 0.649-1.135; P = 0.286). In subtype analyses glucose was also suggestively not associated with Crohn's disease (OR 0.22; 95% CI 0.04-1.00; P = 0.05) and ulcerative colitis (OR 0.940; 95% CI 0.628-1.407; P = 0.762). In the other direction, IBD and its subtypes were not related to glucose and glycemic traits. CONCLUSIONS: This MR study is not providing any evidence for a causal relationship between genetically predicted elevated glucose and IBD as well as it's subtypes UC and CD. Regarding the other direction, no causal associations could be found. Future studies with robust genetic instruments are needed to confirm this conclusion.

Humans↗

PubMed2025

Exploring Potential Causality and Molecular Mechanisms between Heart Failure and Renal Failure: Insights from Mendelian Randomization Studies, the MIMIC-IV Database and the Gene Expression Omnibus Database.

UNLABELLED: Introduction: Heart failure (HF) and renal failure (RF) frequently coexist as cardiorenal syndrome, but their underlying causal mechanisms remain poorly defined. METHODS: This study applied Mendelian randomization (MR) using genome-wide association study (GWAS) datasets to investigate the causal effect of HF on RF. The inverse variance weighted method assessed causality, and summary-data-based MR (SMR) was used to identify therapeutic targets. Additional analyses included 211 gut microbiota traits and 1,400 serum metabolites. Validation was performed using the MIMIC-IV database. Transcriptomic data were analyzed to identify differentially expressed genes (DEGs) and key transcription factors (TFs). RESULTS: This study found that HF significantly increases the risk of RF (OR = 1.54, 95% CI: 1.07-2.23, p = 0.020). SMR analysis identified SURF1 and MAP3K11 as potential therapeutic targets for HF and RF. One gut microbiota genus and one serum metabolite showed causal associations with both diseases. MIMIC-IV data supported the HF-RF association (OR = 2.94, 95% CI: 2.81-3.07, p < 0.001). A total of 11 overlapping DEGs were enriched in the MAPK cascade, with RELA identified as a key TF. CONCLUSION: This study provides genetic and molecular evidence supporting a causal role of HF in RF, highlighting microbial, metabolic, and immune mechanisms as potential therapeutic targets. .

Humans↗

PubMed2026

Causal Relationship Between Ischemic Stroke and Vascular Dementia: A Mendelian Randomization Study.

Ischemic stroke (IS) is a major cause of disability and mortality worldwide, and vascular dementia (VaD) is a common dementia subtype associated with cerebrovascular injury. Observational studies have suggested a relationship between IS and VaD, but these studies are vulnerable to confounding and reverse causality. This protocol describes a reproducible two-sample Mendelian randomization (MR) workflow for evaluating the potential causal association between IS and VaD using publicly available genome-wide association study (GWAS) summary statistics. Genetic instruments associated with IS were extracted from a public GWAS dataset, and outcome associations for VaD were obtained from a public VaD GWAS dataset. The corresponding dataset IDs are provided in the Protocol section. After outcome matching and allele harmonization, 51 single-nucleotide polymorphisms (SNPs) were retained for the final MR analysis. The workflow includes instrumental variable selection, linkage disequilibrium clumping, allele harmonization, instrument strength assessment, inverse variance weighted (IVW) analysis, weighted median analysis, MR-Egger analysis, heterogeneity testing, horizontal pleiotropy assessment, and leave-one-out sensitivity analysis. In the representative analysis, the IVW method showed a positive association between genetically predicted IS and VaD risk, and the weighted median method yielded a directionally concordant result. The MR-Egger estimate was directionally consistent but did not reach statistical significance. Therefore, these findings should be interpreted as suggestive evidence of a possible causal effect, rather than definitive proof of causality. This protocol may help researchers apply a transparent and reproducible MR workflow to investigate cerebrovascular disease-related outcomes using public GWAS data.

Humans↗

PubMed2026

Genetic Evidence Linking Circulating Epidermal Growth Factor to Sjögren's Syndrome Risk.

BACKGROUND: This study aimed to explore the potential causal correlations between circulating expression levels of six growth factors - epidermal growth factor (EGF), vascular endothelial growth factor (VEGF), fibroblast growth factor (FGF), transforming growth factor-beta (TGF-β), platelet-derived growth factor (PDGF), and nerve growth factor (NGF) - and the risk of developing Sjögren's syndrome (SS), from the perspective of genetic variation, using a Mendelian Randomization (MR) approach. METHODS: Genetic data related to SS and the six growth factors were obtained from the IEU OpenGWAS project [GWAS IDs: "finn-b-M13_SJOGREN" (SS), "ebi-a-GCST90010212" (EGF), "ebi-a-GCST90011995" (VEGF), "ebi-a-GCST004459" (FGF), "ebi-a-GCST90000481" (TGF-β), "ebi-a-GCST004432" (PDGF), and "prot-b-40" (NGF)]. A two-sample MR analysis was conducted to estimate the causal effect of each growth factor on SS risk. Five complementary MR methods were employed to ensure robustness: Inverse Variance Weighted (IVW), MR-Egger, Weighted Median, Simple Mode, and MR-PRESSO. We further assessed heterogeneity and horizontal pleiotropy using Cochran's Q test and MR-Egger intercept, and performed leave-one-out analyses to test the sensitivity and reliability of the results. RESULTS: The MR analysis provided evidence supporting a causal association between elevated EGF levels and increased SS risk. Both IVW (p = 0.0485, OR [95%] = 1.0696 [1.0004 - 1.1436]) and MR-PRESSO (p = 0.0406, OR [95% CI] = 1.0684 [1.0080 - 1.1325]) yielded statistically significant results. No significant causal associations were observed between SS and the other five growth factors across all MR methods. Sensitivity analyses supported the robustness of the observed association between EGF and SS. CONCLUSIONS: The findings suggest that elevated circulating EGF levels may play a causal role in the development of Sjögren's syndrome, supporting EGF as a potential biomarker for early diagnosis and risk prediction. These results provide novel insights into the pathogenesis of SS and highlight EGF as a potential target for future diag-nostic and therapeutic strategies. Further research is needed to explore the clinical utility of growth factor-targeted approaches for SS prevention and treatment.

Humans↗

PubMed2024

The associations between functional dyspepsia and potential risk factors: A comprehensive Mendelian randomization study.

BACKGROUND: Previous cross-sectional studies have identified multiple potential risk factors for functional dyspepsia (FD). However, the causal associations between these factors and FD remain elusive. Here we aimed to fully examine the causal relationships between these factors and FD utilizing a two-sample MR framework. METHODS: A total of 53 potential FD-related modifiable factors, including those associated with hormones, metabolism, disease, medication, sociology, psychology, lifestyle and others were obtained through a comprehensive literature review. Independent genetic variants closely linked to these factors were screened as instrumental variables from genome-wide association studies (GWASs). A total of 8875 FD cases and 320387 controls were available for the analysis. The inverse variance weighted (IVW) method was employed as the primary analytical approach to assess the relationship between genetic variants of risk factors and the FD risk. Sensitivity analyses were performed to evaluate the consistency of the findings using the weighted median model, MR-Egger and MR-PRESSO methods. RESULTS: Genetically predicted depression (OR 1.515, 95% confidence interval (CI) 1.231 to 1.865, p = 0.000088), gastroesophageal reflux disease (OR 1.320, 95%CI 1.153 to 1.511, p = 0.000057) and years of education (OR 0.926, 95%CI 0.894 to 0.958, p = 0.00001) were associated with risk for FD in univariate MR analyses. Multiple medications, alcohol consumption, poultry intake, bipolar disorder, mood swings, type 1 diabetes, elevated systolic blood pressure and lower overall health rating showed to be suggestive risk factors for FD (all p<0.05 while ≥0.00167). The positive causal relationship between depression, years of education and FD was still significant in multivariate MR analyses. CONCLUSIONS: Our comprehensive MR study demonstrated that depression and lower educational attainment were causal factors for FD at the genetic level.

Humans↗

PubMed2026

DNA Methylation, SERPING1 Expression, and Immune-related Traits in Osteoporosis: A Mendelian Randomization Study And Supportive Ex Vivo Evidence.

INTRODUCTION: Osteoporosis (OP) is a major public health burden; however, the role of SERPIN family proteins remains incompletely understood. This study aimed to investigate genetically inferred associations between SERPINs and OP and to explore potential regulatory relationships. METHODS: Genome-wide association study (GWAS) summary statistics were used to perform two-sample Mendelian randomization (MR) and summary-data-based Mendelian randomization (SMR) analyses. Primary MR estimates were derived using inverse-variance-weighted (IVW), MR-Egger, weighted median, simple mode, and weighted mode methods. Cancellous bone tissue from the greater trochanter of the femur was collected from three patients with OP and three non-osteoporotic controls. qPCR and WB were used to analyze the whole bone homogenate, IHC was used to detect decalcified bone sections, and mediation analysis was used to explore potential regulatory associations. RESULTS: Among the proteins of the SERPIN family, only SERPING1 had an obvious positive correlation with the risk of osteoporosis (OR = 1.06, P = 0.0012). qPCR, WB, and IHC analyses demonstrated increased SERPING1 mRNA and protein expression in bone tissue from OP patients. Mediation analyses suggested that cg15918732 DNA methylation may serve as an upstream regulatory factor for SERPING1 expression. In addition, the downstream associations also consist of the alteration of immune cell conditions, like the decrease in the quantity of natural killer cells and T cells, and the rise in the level of mononuclear cells, and so forth. DISCUSSION: These findings provide genetic evidence for the possible role of SERPING1 in OP, which may be achieved through epigenetic regulation and immune pathways. Due to the corresponding characteristics of genetic inference and the small sample size, these results are hypothetical and generative. CONCLUSION: This study shows that DNA methylation of cg15918732 may be associated with SERPING1 expression in osteoporosis and immune-related traits. These findings provide new insights into potential epigenetic and immunological pathways in osteoporosis, which may contribute to future mechanistic and translational research.

Humans↗

PubMed2001

Uniform GFP-expression in transgenic medaka (Oryzias latipes) at the F0 generation.

A green fluorescent protein (GFP) cDNA flanked by inverted terminal repeats (ITR) of adeno-associated virus was constructed. The construct sharply improved the efficiency and specificity of the transient expression of genes driven by two general promoters (cytomegalovirus and medaka beta-actin) and one muscle-specific promoter (zebrafish alpha-actin) in transgenic medaka. In addition, treatment with ITR sequence-containing constructs resulted in a dramatic increase in the number of embryos showing uniform GFP-expression at F0. Of the GFP-positive embryos, 34.6% (81/234), 10% (10/60), and 18% (38/212) showed homogenous GFP-expression for the derivative constructs of the cytomegalovirus, alpha-actin, and beta-actin promoters, respectively. As a result of uniform GFP-expression, green fluorescence in founders was (a) extended for an entire lifetime without degradation, and (b) transmitted as a genetic trait to F1 and F2 progeny of some transgenic lines via Mendelian inheritance. A Southern blot analysis revealed a random integration of the transgene into the genome of founders and progeny in both head-to-tail and tail-to-tail concatemerization patterns. Interestingly, some transgenic medaka with uniform and strong fluorescence could be visually noticeable to the unaided eye.

Actins↗

PubMed2026

Modelling time-varying genetic effects on binary disease risk via functional Mendelian randomization.

MOTIVATION: Genome-wide association studies have identified thousands of genetic variants associated with complex traits, establishing Mendelian randomization (MR) as a powerful framework for causal inference using variants as natural experiments. However, existing MR methods treat causal effects as static, relying on cross-sectional exposure measurements and ignoring how genetic predispositions to disease operate dynamically across the life course. Recovering age-specific causal effect functions from longitudinal data requires combining functional data representations of exposure trajectories with instrumental variable estimation strategies suitable for binary disease endpoints, a methodological gap that has remained unaddressed. RESULTS: We develop a functional MR framework for binary outcomes that integrates functional principal component analysis with two-stage residual inclusion (2SRI), ensuring consistent estimation under the nonlinear logistic link function that renders standard instrumental variable estimators inconsistent. Simulations across different causal effect trajectory shapes, varying measurement densities, and varying instrument strengths demonstrate accurate recovery of time-varying genetically predicted effects with minimal bias. Applied to UK Biobank data, the framework identifies an age-specific causal effect of genetically predicted body mass index on type 2 diabetes risk concentrated in early mid-adulthood and progressively attenuating thereafter. Concordance between the proposed 2SRI estimator applied to type 2 diabetes and the established continuous-outcome functional MR estimator applied to the paired glycated haemoglobin marker in the same cohort provides indirect empirical support for the validity of the proposed approach. AVAILABILITY AND IMPLEMENTATION: The method is implemented in the R package mvfmr, with a full tutorial vignette.

Mendelian Randomization Analysis↗

PubMed2024

Assessing the causal link between liver function and acute pancreatitis: A Mendelian randomisation study.

A correlation has been reported to exist between exposure factors (e.g. liver function) and acute pancreatitis. However, the specific causal relationship remains unclear. This study aimed to infer the causal relationship between liver function and acute pancreatitis using the Mendelian randomisation method. We employed summary data from a genome-wide association study involving individuals of European ancestry from the UK Biobank and FinnGen. Single-nucleotide polymorphisms (SCNPs), closely associated with liver function, served as instrumental variables. We used five regression models for causality assessment: MR-Egger regression, the random-effect inverse variance weighting method (IVW), the weighted median method (WME), the weighted model, and the simple model. We assessed the heterogeneity of the SNPs using Cochran's Q test. Multi-effect analysis was performed using the intercept term of the MR-Egger method and leave-one-out detection. Odds ratios (ORs) were used to evaluate the causal relationship between liver function and acute pancreatitis risk. A total of 641 SNPs were incorporated as instrumental variables. The MR-IVW method indicated a causal effect of gamma-glutamyltransferase (GGT) on acute pancreatitis (OR = 1.180, 95%CI [confidence interval]: 1.021-1.365, P = 0.025), suggesting that GGT may influence the incidence of acute pancreatitis. Conversely, the results for alkaline phosphatase (ALP) (OR = 0.997, 95%CI: 0.992-1.002, P = 0.197) and aspartate aminotransferase (AST) (OR = 0.939, 95%CI: 0.794-1.111, P = 0.464) did not show a causal effect on acute pancreatitis. Additionally, neither the intercept term nor the zero difference in the MR-Egger regression attained statistical significance (P = 0.257), and there were no observable gene effects. This study suggests that GGT levels are a potential risk factor for acute pancreatitis and may increase the associated risk. In contrast, ALP and AST levels did not affect the risk of acute pancreatitis.

Humans↗

PubMed2026

Life-course influence of birthweight and subsequent pathways on healthy aging: a Mendelian randomization study.

BACKGROUND: Birthweight readily measurable marker of fetal growth that may influence health across the lifespan. We aimed to investigate the potential causal association between birthweight and healthy aging and to identify the mediating roles of subsequent socioeconomic, behavioral, functional, and disease-related factors to inform life-course strategies to promote healthy aging and reduce health inequities. METHODS: We performed two-sample Mendelian randomization analyses in European-ancestry participants to estimate the effect of birthweight (n = 298,142-423,683) on two robust, composite healthy aging phenotypes (genetically independent phenotype of aging (aging-GIP) and multivariate aging-related genetic factor (mvAge)) and six individual aging phenotypes, including healthspan, resilience, parental lifespan, self-rated health, phenotypic age deceleration, and 90th percentile self-longevity (n = 34,710-1,958,774), and screened for 100 candidate mediators (n = 14,267-1,812,017) using a two-step mediation analysis. RESULTS: Genetically determined each 1-SD higher birthweight was associated with higher aging-GIP (β [95% CI] in different models ranging from 0.131 [0.066-0.196] to 0.162 [0.089-0.235] SDs) and mvAge (0.036 [0.010-0.063] to 0.045 [0.024-0.067]), independent of later-life obesity indicators; also with more interpretable benefits, including 12%-16% higher odds of longer healthspan, a 0.079-0.089 SD improvement in resilience, and a 1.22-1.74 year increase in parental lifespan. Of 100 candidates, 26 and 25 mediated the effect of birthweight on aging-GIP and mvAge, respectively, including socioeconomic indicators (education, household income, occupational attainment; individual mediation proportion: 12.72%-27.79%); behaviors (e.g., cheese intake, age at first sex; 10.38%-29.56%); physical functions (e.g., blood pressure, grip strength; 7.57%-42.65%); and cardiometabolic diseases (e.g., type 2 diabetes, cardiovascular diseases; 25.02%-70.11%). CONCLUSIONS: Higher birthweight within the normal range directly promotes healthy aging, mediated by multifaceted modifiable factors. Our findings advocate adopting a life-course approach to foster healthy aging, starting with optimal birthweight and extending to interventions that enhance socioeconomic status, promote healthy behaviors, strengthen physical functions, and prevent cardiometabolic diseases.

Mendelian Randomization Analysis↗

PubMed2026

Assessing the Association Between Age at First Sexual Intercourse and HIV Infection Risk Using A Two-sample Mendelian Randomization Framework.

This study applied a two-sample Mendelian randomization framework to investigate the potential association between age at first sexual intercourse (AFS) and the risk of Human Immunodeficiency Virus (HIV) infection. Summary-level Genome-Wide Association Study (GWAS) data from European populations were analyzed, including 214,547 individuals for AFS and 357 HIV cases with 218,435 controls from the FinnGen R5 dataset. Independent single-nucleotide polymorphisms significantly associated with AFS were selected as instrumental variables following linkage disequilibrium clumping and instrument-strength assessment. Causal estimates were evaluated using inverse-variance weighting (IVW), MR-Egger regression, weighted median, weighted mode, and simple mode. Cochran's Q test, MR-Egger intercept analysis, MR-PRESSO assessment, and leave-one-out sensitivity analyses were performed to evaluate heterogeneity, pleiotropy, and robustness. The IVW analysis suggested that genetically predicted later AFS was associated with reduced HIV infection risk (OR = 0.192, 95% CI = 0.062-0.592, P = 0.004), whereas earlier sexual debut corresponded to increased HIV susceptibility. Directionally consistent findings across multiple Mendelian randomization methods supported the stability of the observed association. However, the findings should be interpreted cautiously because the HIV outcome analysis relied on a single dataset with a limited number of HIV cases. These results support a potential association between earlier sexual debut and HIV susceptibility and demonstrate the utility of Mendelian randomization for investigating behavioral risk factors associated with infectious disease outcomes.

Humans↗

PubMed2026

Protein mediators of chronic kidney disease in Type 2 diabetes: A mendelian randomization study.

BACKGROUND: Chronic kidney disease (CKD) occurs in 20-50% of the people living with Type 2 diabetes (T2D) and is the leading cause of kidney failure worldwide. The cause of CKD is not fully understood, and few interventions prevent CKD in individuals living with diabetes. Here, we use large-scale proteomics data to identify circulating proteins that mediate the relationship between T2D and kidney disorders. METHODS AND FINDINGS: First, we used two-sample mendelian randomization (MR) and identified 71 circulating proteins whose levels were altered by genetic predisposition to T2D based on circulating proteomic GWAS from deCODE with 35,559 individuals and T2D GWAS with 80,154 cases. Then, we used cis-genetic variants to proxy the causal effect of some of these T2D-influenced circulating proteins and found that, collectively, five proteins (INHBC, GNPTG, LPO, AGRN, and CTSD) affected three kidney traits (blood urea nitrogen [BUN], estimated glomerular filtration rate [eGFR] and CKD risk) based on GWAS with up to 1,004,040 participants. Notably, we found that higher levels of circulating INHBC protein were estimated to lead to a lower eGFR and higher BUN based on MR analyses. We then replicated this MR analysis with proteomic GWAS from four additional cohorts, namely, UKB-PPP, Fenland, ARIC, and EPIC-Norfolk. We observed a consistent direction of effect across all four proteomic GWAS datasets, supporting the robustness of our results against platform and cohort variation. In observational analyses, increased circulating INHBC levels were associated with increased hazard for kidney disease diagnosis in 37,854 UK Biobank participants. We estimated that circulating INHBC levels mediate 1.3% (95% confidence interval [0.85%, 1.9%]) of the association between T2D and kidney disease diagnosis. There are important limitations in this study. Firstly, although we observed limited evidence for violations to the MR assumptions, some are untestable. Secondly, our study was not based on individuals with diabetic kidney diseases, but rather independent population-based studies assessing diabetes and kidney function separately. Therefore, additional functional analyses in disease specific cohort are needed. CONCLUSIONS: Collectively, these findings suggest that T2D influences the risk of CKD, in part, through increased circulating INHBC levels.

Humans↗

PubMed2024

Causal association of menstrual reproductive factors on the risk of osteoarthritis: A univariate and multivariate Mendelian randomization study.

OBJECTIVE: Several observational studies have revealed a potential relationship between menstrual reproductive factors (MRF) and osteoarthritis (OA). However, the precise causal relationship remains elusive. This study performed Mendelian randomization (MR) to provide deeper insights into this relationship. METHODS: Utilizing summary statistics of genome-wide association studies (GWAS), we conducted univariate MR to estimate 2 menstrual factors (Age at menarche, AAM; Age at menopause, AMP) and 5 reproductive factors (Age at first live birth, AFB; Age at last live birth, ALB; Number of live births, NLB; Age first had sexual intercourse, AFSI; Age started oral contraceptive pill, ASOC) on OA (overall OA, OOA; knee OA, KOA and hip OA, HOA). The sample size of MRF ranged from 123846 to 406457, and the OA sample size range from 393873 to 484598. Inverse variance weighted (IVW) method was used as the primary MR analysis methods, and MR Egger, weighted median was performed as supplements. Sensitivity analysis was employed to test for heterogeneity and horizontal pleiotropy. Finally, multivariable MR was utilized to adjust for the influence of BMI on OA. RESULTS: After conducting multiple tests (P<0.0023) and adjusting for BMI, MR analysis indicated that a lower AFB will increase the risk of OOA (odds ratio [OR] = 0.97, 95% confidence interval [CI]: 0.95-0.99, P = 3.39×10-4) and KOA (OR = 0.60, 95% CI: 0.47-0.78, P = 1.07×10-4). ALB (OR = 0.61, 95% CI: 0.45-0.84, P = 2.06×10-3) and Age AFSI (OR = 0.66, 95% CI: 0.53-0.82, P = 2.42×10-4) were negatively associated with KOA. In addition, our results showed that earlier AMP adversely affected HOA (OR = 1.12, 95% CI: 1.01-1.23, P = 0.033), and earlier ASOC promote the development of OOA (OR = 0.97, 95% CI: 0.95-1.00, P = 0.032) and KOA (OR = 0.58, 95% CI: 0.40-0.84, P = 4.49×10-3). ALB (OR = 0.98, 95% CI: 0.96-1.00, P = 0.030) and AFSI (OR = 0.98, 95% CI: 0.97-0.99, P = 2.66×10-3) also showed a negative association with OOA but they all did not pass multiple tests. The effects of AAM and NLB on OA were insignificant after BMI correction. CONCLUSION: This research Certificates that Early AFB promotes the development of OOA, meanwhile early AFB, ALB, and AFSI are also risk factors of KOA. Reproductive factors, especially those related to birth, may have the greatest impact on KOA. It provides guidance for promoting women's appropriate age fertility and strengthening perinatal care.

Humans↗

PubMed2026

Hidradenitis Suppurativa and Smoking, Obesity, Psoriasis, Inflammatory Bowel Disease, and Systemic Sclerosis: Results From A 2-Sample Mendelian Randomization Study.

IMPORTANCE: Smoking and obesity are associated with risk of hidradenitis suppurativa, and both are considered important environmental risk factors. However, a causal relationship remains unproven. OBJECTIVE: To primarily investigate the relationship between body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) and smoking and HS, and secondarily to investigate potential relationships between 3 inflammatory diseases (psoriasis, inflammatory bowel disease [IBD], and systemic sclerosis [SSc]) and HS. DESIGN, SETTING, AND PARTICIPANTS: A mendelian randomization (MR) study conducted in 2024 on 5 exposure phenotypes (BMI, smoking, psoriasis, IBD, and SSc) on the outcome of phenotype HS was conducted. The MR analyses used large genetic White European cohorts from genome-wide association studies (GWAS) of each of the 6 phenotypes. Initial analyses were conducted May, 2024, and were updated in May, 2025. EXPOSURE: The 5 exposure phenotypes using predetermined genome-wide significant single-nucleotide variants as proxies for each particular exposure. RESULTS: The GWAS on HS included 4814 case patients and more than 1.2 million controls from Denmark, Iceland, Finland, the UK, and the US. The BMI GWAS involved 700 000 individuals from the UK Biobank and GIANT consortium. Smoking data were obtained from 1.23 million participants in an international consortium. The psoriasis GWAS analyzed 39 498 case patients and 286 769 controls from White European populations and a DNA genetic testing company. The IBD GWAS meta-analysis included 38 155 case patients and 48 485 controls from the International Inflammatory Bowel Disease (IBD) Genetics Consortium. The SSc GWAS included 9095 case patients and 17 584 controls from White European populations. Genetic correlations (rg) were found between HS and all exposure phenotypes except SSc (BMI: rg = 0.36, P < .001; smoking: rg = 0.33, P < .001; IBD: rg = 0.25, P < .001; psoriasis: rg = 0.34, P < .001; SSc: rg = 0.33, P = .22). MR analyses supported an effect of BMI on HS (β = 0.87; odds ratio [OR] per BMI unit, 1.20; 95% CI, 1.17-1.23; P < .001) without signs of pleiotropy (slope: β = 0.91, P < .001, P for intercept = .76). Smoking showed a significant causal estimate (β = 0.59, P < .001), but results became inconclusive in subsequent sensitivity analyses. Among IBD, psoriasis, and SSc, results supported a causal effect of IBD on HS (β = 0.18, OR = 1.20; 95% CI, 1.15-1.24; P < .001), without signs of pleiotropy. CONCLUSIONS AND RELEVANCE: These findings indicate causal effects of IBD and increased BMI on the risk of HS. This information may help physicians inform patients about disease risk contributed by modifiable lifestyle behaviors, which can be beneficial for planning lifestyle interventions.

Humans↗

PubMed2026

Multi-omics integration and colocalization analyses prioritize candidate molecular loci associated with hypothermia.

BACKGROUND: Hypothermia is a life-threatening condition lacking specific pharmacological treatments. This study aimed to prioritize genetically supported molecular loci associated with hypothermia and to explore their pharmacological tractability using multi-omics data. METHODS: Initially, 2532 druggable genes were curated from the Drug-Gene Interaction Database and established literature. These were cross-referenced with cis-eQTL and cis-pQTL datasets, encompassing 870,655 and 114,281 SNPs for blood, respectively, alongside 2379 shared SNPs across adipose, skeletal muscle, and heart tissues. Matched instrumental variables were integrated with hypothermia GWAS summary statistics for two-sample Mendelian randomization (MR) and Bayesian colocalization. Transcriptomic differential expression analysis (DEA) was subsequently conducted as an exploratory analysis of cold-exposure-associated expression changes. Database-derived compound annotations were systematically re-evaluated according to target specificity, established pharmacological mechanism, and concordance with the direction of the MR estimates. RESULTS: Among 671 gene-level MR tests, 36 genes reached nominal significance, whereas only ABCC8 remained significant after FDR correction. Colocalization was evaluable for 8 of these 36 genes, and 4 loci (COL18A1, SLC1A7, ADIPOQ, and MERTK) met the prespecified PP.H4>0.90 threshold. The remaining 28 loci were not evaluable because sufficient overlapping regional variants were unavailable after harmonization. Transcriptomic analysis identified altered expression of SLC1A3 and SLCO4A1 under cold exposure, although these findings did not directly validate the colocalization-supported loci. Re-evaluation of database-derived compound annotations did not identify any direct, selective, and directionally concordant drug-repurposing candidate for hypothermia. CONCLUSIONS: COL18A1, SLC1A7, ADIPOQ, and MERTK showed colocalization support among the 8 evaluable nominal MR-associated loci. Because colocalization coverage was limited, these genes should be regarded as preliminary candidate loci rather than established therapeutic targets. The pharmacological annotations were indirect, non-selective, unsupported, or directionally inconsistent and should be interpreted solely as hypothesis-generating information.

Bayesian colocalization↗

PubMed2026

Role of IFIT1 and IFIT3 in systemic lupus erythematosus: modeling a diagnosis and exploring immune regulation.

Systemic lupus erythematosus (SLE) is a complex autoimmune disorder characterized by multi-organ involvement and a protracted clinical course. Current diagnostic strategies, which rely heavily on clinical symptoms and serology, are often insufficient for early detection. Therefore, highly accurate diagnostic biomarkers are urgently needed to facilitate early intervention and optimize personalized treatment strategies. D atasets GSE61635 and GSE135779 were integrated to identify differentially expressed genes. Weighted gene co-expression network analysis (WGCNA) was performed to isolate the module with the strongest clinical relevance. Mendelian randomization and single‑cell RNA‑seq were used to identify key disease‑relevant genes. A diagnostic model was then constructed, and gene set variation analysis (GSVA), along with gene set enrichment analysis (GSEA), was conducted to elucidate the underlying molecular pathways. IFIT1 and IFIT3 were identified as 2 core genes highly expressed in monocytes and T cells of SLE patients. Functional enrichment analysis revealed that these genes were enriched in immune-related pathways, metabolic pathways related to inflammation and genomic stability. The diagnostic model showed good accuracy, with an area under the curve (AUC) of 0.974 on the training set and 0.912 on the validation set. IFIT1 and IFIT3 represent promising biomarkers for diagnosing SLE and appear to mediate key immune and metabolic disturbances. Furthermore, the developed model serves as an accurate and reliable instrument for early diagnosis and personalized therapy. Large-scale clinical studies are warranted to further validate these findings and evaluate their clinical application.

Humans↗