Large Genome-wide Association Studies Research Articles

Unsupervised electrocardiogram feature extraction using deep learning empowers discovery of genetic and phenotypic determinants of cardiac electrophysiology

Abstract Background Conventional analysis of the electrocardiogram (ECG) is based on the extraction of human-defined, visually recognisable features. However, these are not optimised to capture all the information content in the ECG. The variational autoencoder (VAE), a form of unsupervised machine learning, can address this shortcoming by computationally extracting comprehensive and interpretable new ECG features, called latent factors. These latent factors provide a low-dimensional representation of the ECG that maximises capture of data content. This approach could expand our understanding of electrophysiology by identifying novel genetic and phenotypic traits associations with the ECG. Purpose This study aims to uncover genetic determinants of VAE latent factors, comparing them to determinants of conventional, human-derived ECG parameters to gain novel insights into cardiac electrophysiology and related diseases. Methods Over one million median beat ECGs derived from a United States (US) based secondary care centre were used to train a machine learning VAE model, with external validation in the UK Biobank (UKB). We performed common and rare variant association studies for VAE latent factors and conventional ECG traits on quality-controlled UKB data. Associated genetic variants were compared to loci for conventional ECG parameters available in the UKB and literature. Novel GWAS associations were validated in a withheld subset of the UKB cohort. Additionally, we compared the associations of the VAE latent factors and conventional ECG traits with phenotypic traits, disease codes and echocardiographic traits. Results Utilising median beat ECGs, the VAE model identified 20 features, with partial correlations to traditional ECG traits. A genome-wide association study (GWAS) identified 105 associated genomic regions, compared with 62 regions identified with conventional ECG traits on the same dataset. Most discovered loci have been previously associated with ECG features in larger GWAS, providing a positive control validation. We also discovered and validated five genomic regions not previously linked to the ECG (mapped to TRIOBP, EFEMP1, NEDD9, ATP10A and P2RX1). We found rare variant associations for seven genes (NEK6, IL17RA, NME7, MYBPC3, CCT8, ADAMTS6 and SCN5A). The latent factors uncovered associations with 158 phenotypic traits (2093 phenotypes tested) and 147 disease codes (2074 disease phecodes tested) which were not identified by ECG traits. Out of 38 echocardiographic traits, 35 showed higher correlations with the latent factors, while six exhibited significant associations exclusively with the latent factors. Conclusion Our study demonstrates that VAE-derived latent factors outperform conventional ECG parameters in uncovering novel genetic and phenotypic associations. Our findings underscore the opportunity for optimised data-driven feature extraction to enhance our understanding of cardiac electrophysiology.

Association of serum testosterone levels with left atrial size, function, and risk of atrial fibrillation in adult men: observational and mendelian randomization analyses

Abstract Background Numerous studies have investigated the association between serum testosterone levels, testosterone replacement therapy (TRT), and cardiovascular risk. However, research examining the relationship between testosterone levels and atrial fibrillation (AF) risk remains limited. We comprehensively analyzed the association between total testosterone (TT) levels, intermediary phenotypes such as left atrium (LA) size and function, and the risk of AF in middle-aged and older men. Methods We utilized data from the UK Biobank, a population-based prospective cohort, focusing on 179,988 White men who had complete serum TT level data and no AF history. Observational associations between TT levels and LA imaging traits, as well as AF risk, were estimated using multivariable regression and time-dependent Cox regression models, treating TT levels as a time-varying variable. Genetic associations were examined by Mendelian randomization (MR), using both UK Biobank and external large consortia genome-wide association study data. Results During the median follow-up of 11.8 years (IQR 10.9–12.5), we observed 13,847 incident AF cases (7.7%). Participants with normal TT levels (≥ 300 ng/dL) showed a 15% reduced risk of AF (HR of 0.85 [95% CI, 0.82–0.89]) compared to those with low TT (< 300 ng/dL). Interestingly, participants undergoing TRT experienced a 51% higher risk of AF (1.51 [1.09–2.07]). Furthermore, each 1-standard deviation increase in TT levels was associated with a reduced AF risk (OR of 0.91 [0.89–0.93]) and an improved LA emptying fraction (1.29 [1.06–1.58]). Applying age-specific cutoff values for low TT levels highlighted a more pronounced AF risk reduction in participants with normal TT. MR analyses supported these observations, suggesting potential causal relationships between TT levels and both LA function and AF risk. Conclusions Our findings suggest that low TT levels are associated with reduced LA function and increased risk of AF, both observationally and genetically, indicating that serum TT could serve as a surrogate marker or even a potential causal mediator in the development of AF.Abstract tableAbstract figure

Cannabis use disorder increases risk of large-artery atherosclerotic stroke and migraine with aura through mendelian randomization study

Observational studies have shown some association between cannabis use disorder (CUD) and neurological disorders, but their causal relationship is unclear. In this study, we tested the potential causal relationship between CUD and three common neurological disorders using two-sample Mendelian randomization (TSMR) and multivariate MR (MVMR) methods. Thirty-two genetic loci were extracted as exposure factors from the largest genome-wide association study (GWAS) summary statistics for CUD to date. TSMR results showed that genetic prediction of CUD with all stroke, ischemic stroke, large-artery atherosclerotic stroke, migraine with aura, and Alzheimer’s disease (AD) had a positive causal relationship (P < 0.05), which was not found in several other diseases. The association between CUD and stroke, ischemic stroke, and AD in the MVMR study may have been influenced by confounding factors (P > 0.05). Subgroup analyses highlighted a causal relationship between genetically predicted CUD and large-artery atherosclerotic stroke (OR = 1.169; 95%CI 1.030–1.328; P = 0.016) and migraine with aura (OR = 1.142; 95% 1.021–1.278; P = 0.020). Our further functional mapping and annotation enrichment analyses using FUMA suggest that the brain-gut axis may serve as another layer of explanation for the existence of an association between CUD and neurological disorders.

Using genetic variations to reveal the complex relationships between vegetarianism and well-being, depressive symptoms and neuroticism

BackgroundThe relationship between vegetarianism and mental well-being remains a debated topic in traditional observational studies. Recent studies have revealed the genetic factors in vegetarianism. We aimed to use genetic variations to explore the potential causal relationships between vegetarianism and mental well-being, offering insights from a new perspective.MethodsWe conducted the inverse variance weighted approach as the primary analysis to explore the bidirectional genetic associations between vegetarianism (N = 442,589) and depressive symptoms (N = 180,866), neuroticism (N = 170,910), and subjective well-being (N = 298,420). The analysis used the summary data from the largest genome-wide association studies (GWAS). We also performed sensitivity analyses to ensure the robustness of the findings, accounting for potential heterogeneity and pleiotropy.ResultsGenetically predicted vegetarianism showed positive causal relationships with depressive symptoms (odds ratio [OR], 3.26; 95% confidence interval [CI], 1.03–10.31; p = 0.044) and neuroticism (OR, 6.72; 95% CI, 2.29–19.74; p = 5.31 × 10−4), as well as a negative causal relationship with subjective well-being (OR, 0.20; 95% CI, 0.05–0.77; p = 0.019). Additionally, depressive symptoms were found to have a causal influence on vegetarianism (OR, 1.01; 95% CI, 1.00–1.02; p = 6.87 × 10−3). No significant heterogeneity or pleiotropy was detected.ConclusionVegetarianism is causally correlated with negative mental well-being, reflected in an increased risk of depressive symptoms and neuroticism, as well as lower subjective well-being. Further research should explore the underlying mechanisms in broader populations.

Tracing links between micronutrients and type 2 diabetes risk: the singular role of selenium.

Type 2 diabetes (T2D) is a growing global health concern. While micronutrients are crucial for physiological functions and metabolic balance, their precise links to T2D are not fully understood. We investigated the causal relationships between 15 key micronutrients and T2D risk using both univariate and multivariate Mendelian randomization (MR) methods. Our analysis leveraged data from a large prospective cohort genome-wide association study (GWAS) on these micronutrients and T2D. We employed MR techniques such as inverse variance weighting (IVW), MR Egger, weighted median, and simple models. Multivariate analysis adjusted for diabetes-related factors like body mass index (BMI) and hypertension to assess the independent effects of micronutrients, particularly selenium, on T2D risk. Selenium intake was associated with an increased risk of T2D, with an odds ratio (OR) of 1.045, a 95% confidence interval (CI) ranging from 1.009 to 1.082, and a P-value of 0.015. This association was consistent in multivariate analyses, suggesting an independent effect of selenium on T2D risk after adjusting for confounders. Our study presents novel evidence of a positive correlation between selenium intake and T2D risk, underscoring the importance of micronutrients in diabetes prevention and treatment strategies. Further research is necessary to confirm these findings and to clarify the specific biological mechanisms through which selenium influences diabetes risk.

Causal Relationship Between Gastroesophageal Reflux Disease and the Risk of Chronic Rhinosinusitis: Insights from Multivariable and Mediation Mendelian Randomization Analysis.

Background: Previous studies have shown an association between chronic rhinosinusitis (CRS) and gastroesophageal reflux disease (GERD). However, the findings of these studies are controversial, and evaluating this association could help in the treatment of CRS. Thus, we aimed to clarify the relationship between GERD and CRS. Methods: We conducted a Mendelian randomization (MR) study. Pooled data on CRS, GERD, and their associated risk factors were extracted from large genome-wide association studies. Independent single-nucleotide polymorphisms were rigorously screened as instrumental variables. Causal associations between GERD and CRS were assessed, and mediation analyses were performed using multivariate and 2-step MR. Asthma served as a mediator because of its association with both CRS and GERD. Sensitivity tests were also performed. Results: MR analysis showed that genetically predicted GERD was associated with an increased risk of CRS (P < .001). Multivariate MR analysis showed that the effect of GERD on CRS was relatively independent. Mediation analysis showed that asthma mediated the association with a mediation effect of 21.07% (95% CI, 2.70%-40.18%). Sensitivity analyses did not reveal any significant effects of pleiotropy and heterogeneity. Conclusions: We found a causal relationship between genetically predicted GERD and an increase in the risk of CRS. As a mediator, asthma contributed to the effect of GERD on CRS. This study provides high-quality causal evidence for the prevention of CRS.

Neurobiological correlates of comorbidity in disorders across the affective disorders-psychosis spectrum

Disorders across the affective disorders-psychosis spectrum such as major depressive disorder (MDD), bipolar disorder (BD), schizoaffective disorder (SCA), and schizophrenia (SCZ), have overlapping symptomatology and high comorbidity rates with other mental disorders. So far, however, it is largely unclear why some of the patients develop comorbidities. In particular, the specific genetic architecture of comorbidity and its relationship with brain structure remain poorly understood. Therefore, we performed systematic analyses of clinical, genetics and brain structural measures to gain further insights into the neurobiological correlates of mental disorder’s comorbidity. We investigated a sub-sample of the Marburg/Münster Cohort Study (MACS), comprising DSM-IV-TR diagnosed patients with a single disorder in the affective disorders-psychosis spectrum (SD, n=470, MDD; BD; SCA; SCZ), with additional mental disorder’s comorbidities (COM, n=310), and healthy controls (HC, n=649). We investigated group differences regarding a) the global severity index (based on SCL90-R), b) a cross-disorder polygenic risk score (PRS) calculated with PRS-continuous shrinkage (PRS-CS) using the summary statistics of a large genome-wide association study across mental disorders, and c) whole brain grey matter volume (GMV). The SCL90-R score significantly differed between groups (COM>SD>HC). While SD and COM did not differ in cross-disorder PRS and GMV, SD and COM versus HC displayed increased cross-disorder PRS and decreased GMV in the bilateral insula, the left middle temporal, the left inferior parietal, and several frontal gyri. Our results thus suggest that disorders in the affective disorders-psychosis spectrum with or without additional comorbidities differ in self-reported clinical data, but not on genetic or brain structural levels.

Potential causal relationships between blood metabolites, inflammatory cytokines, and venous thromboembolism.

Venous thromboembolism (VTE) is the abnormal coagulation of blood in deep veins, which impairs venous return and includes deep vein thrombosis (DVT) and pulmonary embolism (PE). The incidence of VTE is increasing, leading to severe complications and sequelae. Despite the widespread application of multi-omics analyses in vascular disease research, identifying the specific links between various metabolic products, cytokines, and VTE, as well as their potential mediating roles, requires further validation due to confounding factors. Summary statistics for 1,091 metabolites, 309 metabolite ratios (8,299 individuals), and 41 inflammatory cytokines (8,293 individuals) were obtained from the largest genome-wide association studies (GWAS). Summary statistics for VTE (21,021 cases, 391,160 controls), DVT (6,501 cases, 357,111 controls), and PE (10,046 cases, 401,128 controls) were derived from the FinnGen R10 dataset. We initially examined causal relationships using two-sample MR analysis, followed by Two-step Mendelian Randomization (TSMR) and Multivariable Mendelian Randomization (MVMR) to identify potential mediating mechanisms. We identified causal associations for 78 blood metabolites with VTE, 79 with DVT, and 81 with PE. Among all 41 inflammatory cytokines included, only platelet-derived growth factor BB (PDGF-BB) levels showed a causal relationship with increased risks of VTE, DVT, and PE. MVMR analysis revealed that the associations between glycocholate levels and VTE, DVT, and PE were mediated by PDGF-BB, accounting for 14.54% (p=2.84E-04), 17.10% (p=3.64E-05), and 10.44% (p=1.39E-02), respectively. Furthermore, the associations between dodecanedioate (C12:1-DC) levels and VTE and DVT were also mediated by PDGF-BB, accounting for 12.79% (p=6.10E-04) and 12.17% (p=2.13E-04), respectively. This study reveals significant associations between specific blood metabolites and the risks of VTE, DVT, and PE, with some associations potentially mediated by PDGF-BB.

Causal links between blood inflammation markers and postherpetic neuralgia risk: insights from a two-sample Mendelian randomization study.

Previous studies have suggested an association between blood inflammation-related factors and postherpetic neuralgia. However, the causal relationship between blood inflammation-related factors and postherpetic neuralgia remains unclear. We employed a bidirectional Two-sample Mendelian randomization (MR) analysis to explore the causal relationship between blood inflammation-related factors and postherpetic neuralgia. The instrumental variables were obtained from a large Genome-wide association study (GWAS) meta-analysis dataset of European descent. The instrumental variables of the blood inflammation-related factors come from the database numbers GCST004420 to GCST004460 and GCST90029070. Postherpetic neuralgia has 195,191 samples with a total of 16,380,406 single nucleotide polymorphisms (SNPs). MR analyses were performed using inverse-variance weighted, MR-Egger, and weighted median methods. The MR results revealed a significant causal effect of Macrophage Inflammatory Protein 1 Beta (MIP1β) on reducing the risk of postherpetic neuralgia (95%CI = 0.492-0.991, p = 0.044). Additionally, higher levels of interleukin (IL)-10 (95%CI = 0.973-0.998, p = 0.019) and IL-12p70 (95%CI = 0.973-0.997, p = 0.013) were associated with a lower risk of postherpetic neuralgia. Other inflammatory markers showed no significant causal relationship with this condition. This study identifies MIP1β, IL-10, and IL-12p70 as potential therapeutic targets for preventing or treating postherpetic neuralgia, underscoring the need for further research in this area.

Causal relationship between gut microbiota and insulin-like growth factor 1: a bidirectional two-sample Mendelian randomization study.

The causal relationship between gut microbiota and insulin-like growth factor 1 (IGF-1) remains unclear. The purpose of this study was to explore the causal relationship between gut microbiota and IGF-1 in men and women. Single-nucleotide polymorphisms (SNPs) related to gut microbiota were derived from pooled statistics from large genome-wide association studies (GWASs) published by the MiBioGen consortium. Pooled data for IGF-1 were obtained from a large published GWAS. We conducted Mendelian randomization (MR) analysis, primarily using the inverse variance weighted (IVW) method. Additionally, we performed sensitivity analyses to enhance the robustness of our results, focusing on assessing heterogeneity and pleiotropy. In forward MR analysis, 11 bacterial taxa were found to have a causal effect on IGF-1 in men; 14 bacterial taxa were found to have a causal effect on IGF-1 in women (IVW, all P < 0.05). After false discovery rate (FDR) correction, all bacterial traits failed to pass the FDR correction. In reverse MR analysis, IGF-1 had a causal effect on nine bacterial taxa in men and two bacterial taxa in women respectively (IVW, all P < 0.05). After FDR correction, the causal effect of IGF-1 on order Actinomycetales (PFDR = 0.049) remains in men. The robustness of the IVW results was further confirmed after heterogeneity and pleiotropy analysis. Our study demonstrates a bidirectional causal link between the gut microbiota and IGF-1, in both men and women.

No genetic causal relationship between acne and prostate cancer through Mendelian randomization combined with meta-analysis.

Previous observational studies regarding the relationship between acne and prostate cancer have reported inconsistent results. As such studies are prone to biases, we conducted this Mendelian randomization (MR) analysis to better explore the causal association between acne and prostate cancer. The genetic data for assessing acne were acquired from the largest genome-wide association study (GWAS) of acne by far, and the genetic data for assessing prostate cancer were acquired from the FinnGen consortium, UK Biobank, European Bioinformatics Institute, and IEU OpenGWAS project. We performed two-sample MR analyses using data from these GWASs followed by a meta-analysis to provide an overall evaluation. The primary MR methods used included inverse variance weighted, MR-Egger, and weighted median. Leave-one-out sensitivity tests, Cochran's Q tests, and MR-Egger intercept tests were used to bolster the robustness of the MR results. Through MR combined with meta-analysis, our study found no genetic causal relationship between acne and prostate cancer (p=0.378; odds ratio=0.985; 95% confidence interval, 0.954-1.018). Sensitivity tests ensured the robustness of this result. Acne should not be considered as a morbidity hazard factor for prostate cancer.

Causal Associations of Sleep Apnea With Alzheimer Disease and Cardiovascular Disease: A Bidirectional Mendelian Randomization Analysis.

Sleep apnea (SA) has been linked to an increased risk of dementia in numerous observational studies; whether this is driven by neurodegenerative, vascular, or other mechanisms is not clear. We sought to examine the bidirectional causal relationships between SA, Alzheimer disease (AD), coronary artery disease (CAD), and ischemic stroke using Mendelian randomization. Using summary statistics from 4 recent, large genome-wide association studies of SA (n=523 366), AD (n=94 437), CAD (n=1 165 690), and stroke (n=1 308 460), we conducted bidirectional 2-sample Mendelian randomization analyses. Our primary analytic method was fixed-effects inverse variance-weighted (IVW) Mendelian randomization; diagnostics tests and sensitivity analyses were conducted to verify the robustness of the results. We identified a significant causal effect of SA on the risk of CAD (odds ratio [ORIVW]=1.35 per log-odds increase in SA liability [95% CI=1.25-1.47]) and stroke (ORIVW=1.13 [95% CI=1.01-1.25]). These associations were somewhat attenuated after excluding single-nucleotide polymorphisms associated with body mass index (ORIVW=1.26 [95% CI=1.15-1.39] for CAD risk; ORIVW=1.08 [95% CI=0.96-1.22] for stroke risk). SA was not causally associated with a higher risk of AD (ORIVW=1.14 [95% CI=0.91-1.43]). We did not find causal effects of AD, CAD, or stroke on risk of SA. These results suggest that SA increased the risk of CAD, and the identified causal association with stroke risk may be confounded by body mass index. Moreover, no causal effect of SA on AD risk was found. Future studies are warranted to investigate cardiovascular pathways between sleep disorders, including SA, and dementia.

A GWAS of ACE Inhibitor-Induced Angioedema in a South African Population.

Angiotensin-converting enzyme inhibitor-induced angioedema (AE-ACEI) is a life-threatening adverse event and, globally, the commonest cause of emergency presentations with angioedema. Several large genome-wide association studies (GWAS) have found genomic associations with AE-ACEI. However, despite African Americans having a 5-fold increased risk of AE-ACEI, there are no published GWAS from Africa. The aim of this study was to conduct a case-control GWAS of AE-ACEI in a South African population and perform a meta-analysis with an African American and European American population. The GWAS included 202 South African adults with a history of AE-ACEI and 513 controls without angioedema following angiotensin-converting enzyme inhibitor (ACEI) treatment for at least 2 years. A meta-analysis was conducted with GWAS summary statistics from an African American and European American cohort (from Vanderbilt/Marshfield with 174 cases and 489 controls). No SNPs attained genome-wide significance. However, 26 SNPs in the post-imputation standard GWAS of the South African cohort and 37 SNPs in the meta-analysis were associated to AE-ACEI with suggestive threshold(p-value<5.0×10-06). Some of these SNPs were found to be located close to the genes PRKCQ and RIMS1, previously linked with drug-induced angioedema, and also close to the CSMD1 gene linked to ACEI cough, providing replication at the gene level, but with novel lead SNPs. Our results highlight the importance of African populations to detect novel variants in replication studies. Further increased sampling across the continent and matched functional work are needed to confirm the importance of genetic variation in understanding the biology of AE-ACEI.

Inhibitory neuron links the causal relationship from air pollution to psychiatric disorders: a large multi-omics analysis

Psychiatric disorders are severe health challenges that exert a heavy public burden. Air pollution has been widely reported as related to psychiatric disorder risk, but their casual association and pathological mechanism remained unclear. Herein, we systematically investigated the large genome-wide association studies (6 cohorts with 1,357,645 samples), single-cell RNA (26 samples with 157,488 cells), and bulk-RNAseq (1595 samples) datasets to reveal the genetic causality and biological link between four air pollutants and nine psychiatric disorders. As a result, we identified ten positive genetic correlations between air pollution and psychiatric disorders. Besides, PM2.5 and NO2 presented significant causal effects on schizophrenia risk which was robust with adjustment of potential confounders. Besides, transcriptome-wide association studies identified the shared genes between PM2.5/NO2 and schizophrenia. We then discovered a schizophrenia-derived inhibitory neuron subtype with highly expressed shared genes and abnormal synaptic and metabolic pathways by scRNA analyses and confirmed their abnormal level and correlations with the shared genes in schizophrenia patients in a large RNA-seq cohort. Comprehensively, we discovered robust genetic causality between PM2.5, NO2, and schizophrenia and identified an abnormal inhibitory neuron subtype that links schizophrenia pathology and PM2.5/NO2 exposure. These discoveries highlight the schizophrenia risk under air pollutants exposure and provide novel mechanical insights into schizophrenia pathology, contributing to pollutant-related schizophrenia risk control and therapeutic strategies development.Graphical

Risk Variants Associated With Normal Pressure Hydrocephalus: Genome-Wide Association Study in the FinnGen Cohort.

Large-scale genome-wide studies of chronic hydrocephalus have been lacking. We conducted a genome-wide association study (GWAS) in normal pressure hydrocephalus (NPH). We used a case-control study design implementing FinnGen data containing 473,691 Finns with genotypes and nationwide health records. Patients with NPH were selected based on ICD-10 G91.2 diagnosis. To select patients with idiopathic NPH (iNPH) for sensitivity analysis, we excluded patients with a potentially known etiology of the condition using an algorithm on their disease history. The controls were the remaining non-hydrocephalic participants. For a replication analysis, the NPH cohort from UK Biobank (UKBB) was used. We included 1,522 patients with NPH (mean age 72.2 years, 53% women) and 451,091 controls (mean age 60.5 years, 44% women). In the GWAS comparing patients with NPH with the controls, we identified 6 gene regions significantly (p < 5.0e-8) associated with NPH that replicated in a meta-analysis with UKBB (NPH n = 173). The top loci near the following genes were rs7962263, SLCO1A2 (odds ratio [OR] 0.71, 95% CI 0.65-0.78, p = 1.0e-14); rs798495, AMZ1/GNA12 (OR 1.29, 95% CI 1.20-1.39, p = 2.9e-12); rs10828247, MLLT10 (OR 0.77, 95% CI 0.71-0.83, p = 1.5e-11); rs561699566 and rs371919113, CDCA2 (OR 0.76, 95% CI 0.70-0.82, p = 1.5e-11); rs56023709, C16orf95 (OR 1.24, 95% CI 1.16-1.33, p = 3.0e-9); and rs62434144, PLEKHG1 (OR 1.23, 95% CI 1.14-1.32, p = 1.4e-8). In the sensitivity analysis comparing only patients with iNPH (n = 1,055) with the controls (n = 451,091), 4 top loci near the following genes remained significant: rs7962263, SLCO1A2 (OR 0.70, 95% CI 0.63-0.78, p = 2.1e-11); rs10828247, MLLT10 (OR 0.74, 95% CI 0.62-0.82, p = 4.6e-10); rs798511, AMZ1/GNA12 (OR 1.28, 95% CI 1.17-1.39, p = 1.7e-8); and rs56023709, C16orf95 (OR 1.28, 95% CI 1.17-1.39, p = 1.7e-8). We identified 6 loci significantly associated with NPH in the thus far largest GWAS in chronic hydrocephalus. The genes near the top loci have previously been associated with blood-brain barrier and blood-CSF barrier function and with increased lateral brain ventricle volume. The effect sizes and allele frequencies remained similar in NPH and iNPH cohorts, indicating the identified loci are risk determinants for iNPH and likely not explained by associations with other etiologies. However, the exact role of these loci is still unknown, warranting further studies.

Investigating the Shared Genetic Architecture Between Psychiatric Disorders and Executive Function

BackgroundEvidence for widespread comorbidity of executive dysfunctions with psychiatric disorders suggests common mechanisms underlying their pathophysiology. However, the shared genetic architectures between psychiatric disorders and executive function (EF) remain poorly understood. MethodsLeveraging large genome-wide association study datasets of European ancestry on bipolar disorder (N = 353,899), major depressive disorder (N = 674,452), and schizophrenia (N = 130,644) from the Psychiatric Genomics Consortium and iPSYCH and a common factor of EF (N = 427,037) from UK Biobank, we systematically investigated the shared genomic architectures between psychiatric disorders and EF with a set of statistical genetic, functional genomic, and gene-level analyses. ResultsOur study demonstrated substantial genetic overlaps and significant genetic correlations between psychiatric disorders and EF. EF showed an estimated 95.9%, 98.1%, and 99.2% of phenotype-influencing variants, as well as 50, 23, and 130 genomic loci shared with bipolar disorder, major depressive disorder, and schizophrenia, respectively. Single nucleotide polymorphism heritability enrichment suggests that the genetic architecture of psychiatric disorders and EF involves the brain’s frontal cortex and prefrontal glutamatergic neurons 1 and 2. Functional genomic analysis of shared variants identified 12 functional regulatory variants that regulate gene expression by affecting the binding affinities of 5 transcription factors. In addition, functional characterization analyses of shared genes revealed potential common biological mechanisms related to synaptic processes and fetal brain development. ConclusionsOur findings provide evidence for extensive shared genetic architectures between psychiatric disorders and EF and have valuable implications for future mechanistic investigations and drug development efforts.

Serum folate levels and risk of metabolic dysfunction-associated steatotic liver disease: results from a cross-sectional study and Mendelian randomization analysis.

Evidence from observational studies on the association between folate and metabolic dysfunction-associated steatotic liver disease (MASLD) is conflicting. This study aimed to investigate the association between serum folate concentration and MASLD and further assess the causal relationship using Mendelian randomization (MR) analysis. To investigate the causal relationship between serum folate and MASLD, we conducted a cross-sectional study that selected 1,117 participants from the 2017-2020 National Health and Nutrition Examination Survey (NHANES). The association between serum folate level and the risk of MASLD was evaluated under a multivariate logistic regression model. In addition, we conducted a two-sample MR study using genetic data from a large genome-wide association study (GWAS) to compare serum folate level (37,465 individuals) and MASLD (primary analysis: 8,434 cases/770,180 controls; Secondary analysis:1,483 cases/17,781 controls) were performed to infer causal relationships between them. Inverse variance weighted (IVW) was used as the primary method of MR Analysis. The results from the NHANES database showed that Tertile 3 group (Tertile 3: ≥ 48.6 nmol/L) had a significantly lower risk (OR = 0.58, 95% CI: 0.38-0.88, p = 0.010) of MASLD than Tertile 1 group (Tertile 1: < 22.3 nmol/L) after complete adjustments. However, in the IVW of MR analysis, there was no causal relationship between serum folate level and MASLD risk in the primary analysis (OR = 0.75, 95% CI: 0.55-1.02, p = 0.065) and secondary analysis (OR = 0.83, 95% CI: 0.39-1.74, p = 0.618). In observational analyses, we observed an inverse association between higher serum folate concentrations and a reduced risk of MASLD. Our MR study generated similar results, but the association failed to reach the significance threshold of p < 0.05, suggesting that our MR study does not support a causal relationship between serum folate levels and MASLD risk. Additional research involving a larger number of cases would contribute to enhancing the confirmation of our preliminary findings.

Exploring the causal link among statin drugs and the osteoarthritis risk based on Mendelian randomization research.

Statins may have a protective effect against osteoarthritis (including knee osteoarthritis and hip osteoarthritis); however, the link between statins and osteoarthritis risk is incompletely established. The aim of this study was to explore the relationship between statins and osteoarthritis risk through Mendelian randomization analysis using pooled information from a large population-wide genome-wide association study (GWAS). Statin-related single-nucleotide polymorphisms (SNPs) were obtained from FinnGen's latest 9th edition database, and data on osteoarthritis, knee osteoarthritis, and hip osteoarthritis were acquired from the IEU OpenGWAS, the UK Biobank, and Arthritis Research UK Osteoarthritis Genetics (ArcOGEN) database, respectively. The inverse-variance weighting method is an important analysis method to estimate the causal effect. Weighted median method, simple median method, weighted median estimator method, and MR-Egger regression were employed to supplement the explanation. Odds ratio and 95%CI were used to evaluate the causal relationship among statins and the osteoarthritis risk, osteoarthritis in the knee, and osteoarthritis in the hip. Second, sensitivity analysis was carried out to validate the reliability of the results. Cochran's Q test was employed to test heterogeneity, MR-Egger intercept was employed to test whether horizontal pleiotropy existed, and single-nucleotide polymorphisms with potential influence were determined by the one-method analysis. (1) The results of the inverse variance weighting method showed Gene prediction indicated that statins were associated with osteoarthritis (OR = 0.998, 95% CI: 0.996-0.999, P = 0.01) and knee osteoarthritis (OR = 0.964, 95% CI: knee (0.940-0.989, P = 0.005) and hip osteoarthritis risk were associated (OR = 0.928, 95% CI: 0.901-0.955, P = 4.28 × 10-7). (2) MR-Egger intercept analysis did not detect potential horizontal pleiotropy (osteoarthritis: P = 0.658; knee osteoarthritis: P = 0.600; and hip osteoarthritis: P = 0.141). (3) The findings provide evidence that statins reduce osteoarthritis risk, osteoarthritis in the knee, and osteoarthritis in the hip, as described in observational studies, and the specific mechanisms by which statins treat osteoarthritis require further investigation. The results of this study, at the genetic level, reveal a negative causal relationship between statins and osteoarthritis, and this causal relationship is also present in knee and hip osteoarthritis. This study provides evidence against the potential of statins in the treatment of osteoarthritis, prompting the clinical treatment of osteoarthritis to consider improving the start and compliance of statins in the future.

Evidence of survival bias in the association between APOE-Є4 and age at ischemic stroke onset.

Large genome-wide association studies (GWASs) using case-control study designs have now identified tens of loci associated with ischemic stroke (IS). As a complement to these studies, we performed GWAS in a case-only design to identify loci influencing the age at onset (AAO) of ischemic stroke. Analyses were conducted in a discovery cohort of 10,857 ischemic stroke cases using a linear regression framework. We meta-analyzed all SNPs with p-value <1 x 10-5 in a sexcombined or sex-stratified analysis using summary data from two additional replication cohorts. In the women-only meta-analysis, we detected significant evidence for the association of AAO with rs429358, an exonic variant in apolipoprotein E (APOE) that encodes for the APOE-Є4 allele. Each copy of the rs429358:T>C allele was associated with a 1.29-year earlier stroke AAO (meta p-value = 2.48 x 10-11). This APOE variant has previously been associated with increased mortality and ischemic stroke AAO. We hypothesized that the association with AAO may reflect a survival bias attributable to an age-related decrease in mortality among APOE-Є4 carriers and have no association to stroke AAO per se. A simulation study showed that a variant associated with overall mortality might indeed be detected with an AAO analysis. A variant with a 2-fold increase in mortality risk would lead to an observed effect of AAO that is comparable to what we found. In conclusion, we detected a robust association of the APOE locus with stroke AAO and provided simulations to suggest that this association may be unrelated to ischemic stroke per se but related to a general survival bias.

Causal associations between gut microbiota and premature rupture of membranes: a two-sample Mendelian randomization study.

Previous study has indicated a potential link between gut microbiota and maternal pregnancy outcomes. However, the causal relationship between gut microbiota and premature rupture of membranes (PROM) remains a topic of ongoing debate. A two-sample Mendelian Randomization (MR) study was used to investigate the relationship between gut microbiota and PROM. Genetic data on gut microbiota was obtained from the MiBioGen consortium's largest genome-wide association study (GWAS) (n=14,306). Genetic data on PROM (3011 cases and 104247 controls) were sourced from publicly available GWAS data from the Finnish National Biobank FinnGen consortium. Various methods including Inverse variance weighted (IVW), MR-Egger, simple mode, weighted median, and weighted mode were utilized to assess the causal relationship by calculating the odd ratio (OR) value and confidence interval (CI). Sensitivity analyses for quality control were performed using MR-Egger intercept tests, Cochran's Q tests, and leave-one-out analyses. The IVW method revealed that class Mollicutes (IVW, OR=0.773, 95%CI: 0.61-0.981, pval = 0.034), genus Marvinbryantia (IVW, OR=00.736, 95%CI: 0.555-0.977, pval = 0.034), genus Ruminooccaceae UCG003 (IVW, OR=0.734, 95%CI: 0.568-0.947, pval = 0.017) and phylum Tenericutes (IVW, OR=0.773, 95%CI: 0.566-1.067, pval = 0.034) were associated with a reduced risk of PROM, while genus Collinsella (IVW, OR=1.444, 95%CI: 1.028-2.026, pval = 0.034), genus Intestinibacter (IVW, OR=1.304, 95%CI: 1.047-1.623, pval = 0.018) and genus Turicibacter (IVW, OR=1.282, 95%CI: 1.02-1.611, pval = 0.033) increased the risk of PROM. Based on the other four supplementary methods, six gut microbiota may have a potential effect on PROM. Due to the presence of pleiotropy (pval=0.045), genus Lachnoclostridium should be ruled out. No evidence of horizontal pleiotropy or heterogeneity was found in other microbiota (pval >0.05). In this study, we have discovered a causal relationship between the presence of specific probiotics and pathogens in the host and the risk of PROM. The identification of specific gut microbiota associated with PROM through MR studies offers a novel approach to diagnosing and treating this condition, thereby providing a new strategy for clinically preventing PROM.