Linkage Disequilibrium Score Regression Research Articles

Causal effects of potential risk factors on postpartum depression: a Mendelian randomization study.

Postpartum depression (PPD) is a type of depressive episode related to parents after childbirth, which causes a variety of symptoms not only for parents but also affects the development of children. The causal relationship between potential risk factors and PPD remains comprehensively elucidated. Linkage disequilibrium score regression (LDSC) analysis was conducted to screen the heritability of each instrumental variant (IV) and to calculate the genetic correlations between effective causal factors and PPD. To search for the causal effect of multiple potential risk factors on the incidence of PPD, random effects of the inverse variance weighted (IVW) method were applied. Sensitivity analyses, including weighted median, MR-Egger regression, Cochrane's Q test, and MR Pleiotropy Residual Sum and Outlier (MR-PRESSO), were performed to detect potential Mendelian randomization (MR) assumption violations. Multivariable MR (MVMR) was conducted to control potential multicollinearity. A total of 40 potential risk factors were investigated in this study. LDSC regression analysis reported a significant genetic correlation of potential traits with PPD. MR analysis showed that higher body mass index (BMI) (Benjamini and Hochberg (BH) corrected p = 0.05), major depression (MD) (BH corrected p = 5.04E-19), and schizophrenia (SCZ) (BH corrected p = 1.64E-05) were associated with the increased risk of PPD, whereas increased age at first birth (BH corrected p = 2.11E-04), older age at first sexual intercourse (BH corrected p = 3.02E-15), increased average total household income before tax (BH corrected p = 4.57E-02), and increased years of schooling (BH corrected p = 1.47E-11) led to a decreased probability of PPD. MVMR analysis suggested that MD (p = 3.25E-08) and older age at first birth (p = 8.18E-04) were still associated with an increased risk of PPD. In our MR study, we found multiple risk factors, including MD and younger age at first birth, to be deleterious causal risk factors for PPD.

Positive association between omega-3/6 polyunsaturated fatty acids and idiopathic normal pressure hydrocephalus: a mendelian randomization study.

Background: Idiopathic normal pressure hydrocephalus (iNPH) is a common disease among the elderly, which brings great harm to the health of patients and imposes a huge economic burden on the healthcare system. Research has shown that it is possible to prevent iNPH through nutritional and dietary interventions. Intake of omega-3 and omega-6 polyunsaturated fatty acids (PUFAs) can reduce the risk of many diseases. In this study, we aimed to explore the association between omega-3/6 PUFAs and iNPH. Methods: We conducted a two-sample Mendelian randomization (MR) study using summary data from publicly available genome-wide association studies (GWAS) to evaluate the potential impact of omega-3 and omega-6 PUFAs on the risk of iNPH in European populations. Inverse variance weighting was used as the main method for MR analysis, with Wald ratio, weighted median, MR-Egger, simple mode, and weighted mode as supplementary methods. In addition, we performed a series of instrument variable strength evaluations and sensitivity analyses to test the reliability of the study results. Finally, we also conducted a linkage disequilibrium score regression (LDSC) analysis to assess the genetic correlation and distinguish between causal associations and shared genetic variants between PUFAs and iNPH. Results: One SD increase in genetically predicted levels of total omega-3 PUFAs (OR: 0.748; 95% CI: 0.597-0.937; p = 0.012; IVW), DHA (OR: 0.709; 95% CI: 0.532-0.945; p = 0.019; IVW), ALA (OR: 0.001; 95% CI: 1.17E-06-0.423; p = 0.026; Wald ratio), and DHA (OR: 0.709; 95% CI: 0.532-0.945; p = 0.019; IVW) were associated with a reduced iNPH risk. LDSC did not reveal any significant genetic correlations. Conclusion: Higher genetically predicted levels of total omega-3 PUFAs, ALA, DHA, and DPA are associated with a reduced risk of iNPH. These findings have important implications for preventing iNPH and future nutritional guidance.

Genetically predicted 486 blood metabolites concerning risk of systemic lupus erythematosus: a Mendelian randomization study

Metabolic abnormalities constitute a significant characteristic of systemic lupus erythematosus (SLE). We utilised a two-sample Mendelian randomisation (MR) study to evaluate the potential causal association between 486 blood metabolites and SLE. Exposure data at the metabolite level were extracted from 7824 European Genome-wide association studies (GWAS). Preliminary analysis utilised SLE GWAS data from FinnGen. The primary method for causal analysis relied on random inverse variance weighting (IVW). To ensure robustness, sensitivity analyses included the Cochran Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. Steiger testing and linkage disequilibrium score regression were employed to validate the identified metabolites. This study identified 12 metabolites, comprising six known chemical structures: 1,5-anhydroglucitol(1,5-AG) [odds ratio (OR) = 0.100, 95% confidence interval (CI): 0.015–0.773, P = 0.027), gamma-glutamylthreonine (OR = 0.077, 95% CI: 0.010–0.574, P = 0.012), 5-dodecenoate(12:1n7) (OR = 0.205, 95% CI: 0.061–0.685, P = 0.010), linoleoylglycerophosphoethanolamine * (OR = 0.159, 95% CI: 0.027–0.933, P = 0.044), erythrose (OR = 88.331,95% CI:1.098–63.214, P = 0.040) and 1-, adrenate (22:4n6) (OR = 9.876, 95% CI: 1.753–55.639, P = 0.001)]. Additionally, we found associations between SLE and six unknown chemical structures: X-06351 (OR = 0.071, 95% CI: 0.006–0.817, P = 0.034), X-10810 (OR = 4.268 95% CI: 1.260–14.459, P = 0.020), X-11412 (OR = 5.418 95% CI: 1.068–27.487, P = 0.041), X-11905 (OR = 0.551, 95%CI: 0.304–0.997, P = 0.049), X-12038 (OR = 0.178 95%CI: 0.032–0.988, P = 0.045), X-12217 (OR = 0.174 95%CI: 0.044–0.680, P = 0.014). This study offers evidence supporting a causal relationship between SLE and 12 circulating metabolites, six of which have known chemical structures and six that remain unidentified. These findings introduce a new perspective for further exploration of SLE mechanisms.

Evidence for a shared genetic contribution to loneliness and borderline personality disorder

Loneliness, influenced by genetic and environmental factors such as childhood maltreatment, is one aspect of interpersonal dysfunction in Borderline Personality Disorder (BPD). Numerous studies link loneliness and BPD and twin studies indicate a genetic contribution to this association. The aim of our study was to investigate whether genetic predisposition for loneliness and BPD risk overlap and whether genetic risk for loneliness contributes to higher loneliness reported by BPD patients, using genome-wide genotype data. We assessed the genetic correlation of genome-wide association studies (GWAS) of loneliness and BPD using linkage disequilibrium score regression and tested whether a polygenic score for loneliness (loneliness-PGS) was associated with case-control status in two independent genotyped samples of BPD patients and healthy controls (HC; Witt2017-sample: 998 BPD, 1545 HC; KFO-sample: 187 BPD, 261 HC). In the KFO-sample, we examined associations of loneliness-PGS with reported loneliness, and whether the loneliness-PGS influenced the association between childhood maltreatment and loneliness. We found a genetic correlation between the GWAS of loneliness and BPD in the Witt2017-sample (rg = 0.23, p = 0.015), a positive association of loneliness-PGS with BPD case-control status (Witt2017-sample: NkR² = 2.3%, p = 2.7*10–12; KFO-sample: NkR² = 6.6%, p = 4.4*10–6), and a positive association between loneliness-PGS and loneliness across patient and control groups in the KFO-sample (β = 0.186, p = 0.002). The loneliness-PGS did not moderate the association between childhood maltreatment and loneliness in BPD. Our study is the first to use genome-wide genotype data to show that the genetic factors underlying variation in loneliness in the general population and the risk for BPD overlap. The loneliness-PGS was associated with reported loneliness. Further research is needed to investigate which genetic mechanisms and pathways are involved in this association and whether a genetic predisposition for loneliness contributes to BPD risk.

Observational and genetic analyses of the bidirectional relationship between depression and hypertension

BackgroundWhile the association between depression and hypertension has been extensively investigated, the pattern and nature of such association remain inconclusive. We sought to investigate the bidirectional relationship between depression and hypertension and its causal. MethodsWe first performed observational analyses using longitudinal data from the UK Biobank. We then performed genetic analyses leveraging summary statistics from large-scale genome-wide association studies (GWASs) conducted in European ancestry for depression and hypertension. ResultsObservational analysis suggested a significant bidirectional phenotypic association between depression and hypertension (Depression → Hypertension: HR = 1.27, 95 % CI: 1.19, 1.36; Hypertension → Depression: HR = 1.65, 95 % CI: 1.58, 1.72). Linkage disequilibrium score regression demonstrated a positive genetic correlation between the two conditions (rg=0.15, P = 5.75 × 10−10). Bidirectional two-sample Mendelian randomization (MR) suggested that genetic liability to depression was significantly associated with an increased risk of hypertension (OR = 1.27, 95 % CI: 1.12, 1.43), while the genetic liability to hypertension was not associated with the risk of depression (OR = 1.01, 95 % CI: 0.99, 1.03). Multivariate MR, after adjusting for smoking, drinking, and body mass index, further supported an independent causal effect of genetic liability to depression on hypertension risk (OR = 1.10, 95 % CI: 1.02, 1.18). Limitations(1) interference of confounders, (2) absence of adequate statistical power, and (3) limitation to European populations. ConclusionOur study indicates depression is a causal risk factor for hypertension, whereas the reverse maybe not. Findings support that prevention of depression might help in decreasing hypertension incidence.

Elucidating the relationship between breast cancer and brain cortical structure: a Mendelian randomization study.

Cancer-associated cognitive impairment is a significant challenge for individuals who have survived breast cancer, affecting their quality of life. In this study, we conducted an inaugural comprehensive Mendelian randomization analysis discerning the causal relationship between breast cancer, including its two subtypes, and the cerebral cortical structure. Our analysis indicated that estrogen receptor-negative breast cancer significantly decreased surface area (β = -593.01mm2, 95% CI: -1134.9 to -51.1mm2, P =0.032). At the regional level, estrogen receptor-negative breast cancer showed a significant association with surface area and thickness in 17 cortical regions. These regions included the insula, posterior cingulate, superior frontal, precuneus, fusiform, lateral occipital, and rostral middle frontal. Specifically, estrogen receptor-negative breast cancer had a significant impact on decreasing the surface area of the insula without considering global weight (β = -14.09mm2, 95% CI: -22.91 to -5.27mm2, P = 0.0017). The results from meta-analysis and LD Score Regression provide support for our findings. This investigation unveils the correlations between breast cancer, its various subcategories, and the cerebral cortical structure. Notably, breast cancer of the estrogen receptor-negative variety may elicit more widespread cerebral atrophy.

Genome-wide association study of preserved ratio impaired spirometry (PRISm).

Preserved ratio impaired spirometry (PRISm) is defined as a forced expiratory volume in 1 s (FEV1) <80% predicted and FEV1/forced vital capacity ≥0.70. PRISm is associated with respiratory symptoms and comorbidities. Our objective was to discover novel genetic signals for PRISm and see if they provide insight into the pathogenesis of PRISm and associated comorbidities. We undertook a genome-wide association study (GWAS) of PRISm in UK Biobank participants (Stage 1), and selected single nucleotide polymorphisms (SNPs) reaching genome-wide significance for replication in 13 cohorts (Stage 2). A combined meta-analysis of Stage 1 and Stage 2 was done to determine top SNPs. We used cross-trait linkage disequilibrium score regression to estimate genome-wide genetic correlation between PRISm and pulmonary and extrapulmonary traits. Phenome-wide association studies of top SNPs were performed. 22 signals reached significance in the joint meta-analysis, including four signals novel for lung function. A strong genome-wide genetic correlation (rg) between PRISm and spirometric COPD (rg=0.62, p<0.001) was observed, and genetic correlation with type 2 diabetes (rg=0.12, p=0.007). Phenome-wide association studies showed that 18 of 22 signals were associated with diabetic traits and seven with blood pressure traits. This is the first GWAS to successfully identify SNPs associated with PRISm. Four of the signals, rs7652391 (nearest gene MECOM), rs9431040 (HLX), rs62018863 (TMEM114) and rs185937162 (HLA-B), have not been described in association with lung function before, demonstrating the utility of using different lung function phenotypes in GWAS. Genetic factors associated with PRISm are strongly correlated with risk of both other lung diseases and extrapulmonary comorbidity.

Human blood metabolites and risk of sepsis: A Mendelian randomization investigation.

Evidence supports the observational correlations between human blood metabolites and sepsis. However, whether these associations represent a causal relationship is unknown. In this study, we applied two-sample Mendelian randomization (MR) analyses to examine causality between genetically proxied 486 blood metabolites and sepsis risk. We used summary data from genome-wide association studies (GWAS) on 486 metabolites involving 7824 individuals as exposure and a sepsis GWAS including 11,643 cases and 474,841 controls as the outcome. The inverse-variance weighted (IVW) was the primary method to estimate the causal relationship between exposure and outcome, with MR-Egger and weighted median serving as supplements. Sensitivity analyses were implemented with Cochrane's Q test, MR-Egger intercept, MR-PRESSO and leave-one-out analysis. In addition, we performed replication MR, meta-analysis, Steiger test, linkage disequilibrium score (LDSC) regression and multivariable MR (MVMR) to thoroughly verify the causation. We identified that genetically determined high levels of 1-oleoylglycerophosphoethanolamine (odds ratio (OR) = .52, 95% confidence interval (CI): .31-.87, p = .0122), alpha-glutamyltyrosine (OR = .75, 95% CI: .60-.93, p = .0102), heptanoate (7:0) (OR = .51, 95% CI: .33-.81, p = .0041) and saccharin (OR = .84, 95% CI: .74-.94, p = .0036) were causally associated with a lower risk of sepsis. MVMR analysis demonstrated the independent causal effect of these metabolites on sepsis. These findings indicated that four blood metabolites have a protective impact on sepsis, thus providing novel perspectives into the metabolite-mediated development mechanism of sepsis by combining genomics and metabolomics.

Evaluation of the Causal Effects of COVID‐19 on Alzheimer’s Disease: LD Score Regression Analysis and Mendelian Randomization Study

AbstractBackgroundCOVID‐19 is an acute respiratory infection that is frequently followed by short‐ or long‐term neurological abnormalities, and may increase the risk of developing Alzheimer’s disease (AD). However, the genetic and biological mechanisms underlying this risk are poorly understood. Utilizing publicly available large genome‐wide association studies (GWAS), we explored the possible causal effects of three different COVID‐19 phenotypes on AD.MethodCOVID‐19 GWAS data from European cohorts were obtained from the Host Genetics Initiative website in its most recent release (HGI7‐EUR) with three phenotypes: 1) critically ill COVID‐19 (case/ctrl: 13,769/1,072,442); 2) hospitalized COVID‐19 (case/ctrl: 32,519/2,062,805); 3) regular COVID‐19 infection (case/ctrl: 2,475,240/12,597,856). European AD GWAS data were retrieved from Jansen et al.’s study (case/ctrl: 71,880/ 383,378). The linkage disequilibrium score regression (LDSC) and Mendelian randomization (MR) methods were used to analyze the genetic correlation and possible causal effects among the three COVID‐19 phenotypes and AD.ResultLDSC indicated that AD had significant positive correlations with the critically ill COVID‐19 (FDR = 0.021, z = 2.45, rg = 0.224) and hospitalized COVID‐19 (FDR = 0.020, z = 2.71, rg = 0.241) phenotypes, but not regular COVID‐19 infection (FDR = 0.133). On the other hand, MR with the fixed‐effects inverse variance weighted method indicated that regular COVID‐19 had some causal effect on AD (P = 0.019, beta = 0.032). Marginal causal effects on AD were also found from critical COVID‐19 (P = 0.072, beta = 0.008) and hospitalized COVID‐19 (P = 0.082, beta = 0.013). In addition, MR with weighed mode method showed significant effects on AD from three COVID‐19 phenotypes (P = 0.040‐0.003), while MR‐Egger method did not show any significance between the two diseases.ConclusionUsing LDSC and MR approaches, our preliminary data identified a genetic correlation between hospitalized and critically ill COVID‐19 phenotypes and AD, and possible causal effects on AD through genetic variants shared with standard COVID‐19 infection. With the continuing COVID‐19 epidemic and the high comorbidity and mortality of AD from COVID‐19 infection, our observations emphasize the urgency of understanding the overlapping genetic risk for the two diseases. Further studies might shed light on the long‐term neurological influence of COVID‐19 and further provide strategies for disease intervention against COVID‐19 and AD.

Functionally Informed Polygenic Risk Scores for Alzheimer’s Disease

AbstractBackgroundAlzheimer’s Disease (AD) is a heritable, neurodegenerative disease. Most AD cases can be categorized as Late Onset Alzheimer’s Disease (LOAD) cases, which are polygenic. Genome Wide Association Studies (GWAS) of LOAD have identified several associated single nucleotide polymorphisms (SNPs). These variants are in 75 genetic loci, and have implicated a diverse array of genes, cell types, and biological pathways in LOAD. Additionally, many associated variants are not in protein coding regions of the genome. However, it is difficult to determine if all associated variants are functionally relevant and contribute to the etiology or progression of the disease. Here, we present CoRE‐BED, a variant annotation tool that can categorize SNPs into functional classes, such as promoters or enhancers, for a given cell type. These functional variants in each cell type are subsequently used to determine functional variant contributions to LOAD heritability and risk.MethodWe annotated a recently published GWAS of AD (Bellenguez et al 2022) using CoRE‐BED. CoRE‐BED leverages 19 functional assays across 33 distinct cell types from EpiMap to classify variants into functional categories for each supported cell type. Annotated variants were used to estimate cell type specific partitioned heritability using LD Score Regression. Finally, annotated variants were used to build cell type specific Polygenic Risk Scores (PRS). PRS was tested using multiple PRS software and utilized the annotated GWAS as a training dataset and independent cases and controls derived from Vanderbilt University’s biobank, BioVU.ResultCoRE‐BED provided functional classifications for all variants in the GWAS for individual tissue types. Variants that pass genome wide significance (P &lt; 5×10−8) are enriched for functional annotations. Immune related cell types contribute the greatest proportion of partitioned heritability. Standard PRS methods outperform cell type informed PRS measures.ConclusionCoRE‐BED is a robust annotation tool that can determine functional annotations at the SNP level. AD GWAS significant associations overlap with functionally annotated SNPs in multiple cell types. Partitioned heritability indicates that immune related cell types may play an important role in the heritability of AD. However, conventional methods for PRS still provide the most robust means to predict AD risk.

Causal relationships between anthropometric traits, bone mineral density, osteoarthritis and spinal stenosis: A Mendelian randomisation investigation

ObjectiveSpinal stenosis is a common condition among older individuals, with significant morbidity attached. Little is known about its risk factors but degenerative conditions, such as osteoarthritis (OA) have been identified for their mechanistic role. This study aims to explore causal relationships between anthropometric risk factors, osteoarthritis, and spinal stenosis using Mendelian randomization (MR) techniques. DesignWe applied two-sample MR to investigate the causal relationships between genetic liability for select risk factors and spinal stenosis. Next, we examined the genetic relationship between osteoarthritis and spinal stenosis with LD score regression and CAUSE MR method. Finally, we used multivariable MR to explore whether osteoarthritis and BMI mediate the causal pathways identified. ResultsOur analysis revealed strong evidence for the effect of higher BMI (OR=1.54, 95%CI:1.41-1.69, p-value=2.7 x 10-21), waist (OR=1.43, 95%CI:1.15-1.79, p-value=1.5x10-3) and hip (OR=1.50, 95%CI:1.27-1.78, p-value=3.3x10-6) circumference on spinal stenosis. Strong evidence of causality was also observed for higher bone mineral density (BMD): total body (OR=1.21, 95%CI:1.12-1.29, p-value=1.6x10-7), femoral neck (OR=1.35, 95%CI:1.09-1.37, p-value=7.5x10-7), and lumbar spine (OR=1.38, 95%CI:1.25-1.52, p-value=4.4x10-11). We detected high genetic correlations between spinal stenosis and osteoarthritis (rg range: 0.47-0.66), with CAUSE results supporting a causal effect of osteoarthritis on spinal stenosis (ORallOA=1.6, 95%CI:1.41-1.79). Direct effects of BMI, BMD on spinal stenosis remained after adjusting for osteoarthritis in the multivariable MR. ConclusionsGenetic susceptibility to anthropometric risk factors, particularly higher BMI and BMD can increase the risk of spinal stenosis, independent of osteoarthritis status. These results may inform preventative strategies and treatments.

Genetically Determined Metabolites in Graves Disease: Insight From a Mendelian Randomization Study.

Graves disease (GD) is a prevalent autoimmune disorder with a complex etiology. The association between serum metabolites and GD remains partially understood. This study aimed to elucidate the causal connections between serum metabolites and predisposition to GD, examining potential genetic interplay. A 1-sample Mendelian randomization (MR) study was conducted on the GD analysis that included 2836 cases and 374 441 controls. We utilized genome-wide association study summary data from the FinnGen project, analyzing the causal impact of 486 serum metabolites on GD. Approaches used were the inverse variance weighted methodology, Cochran's Q test, MR-Egger regression, MR-PRESSO, Steiger test, and linkage disequilibrium score regression analyses to assess genetic influence on metabolites and GD. 19 metabolites were identified as having a pronounced association with GD risk, of which 10 maintained noteworthy correlations after stringent sensitivity assessments. Three metabolites exhibited significant heritability: kynurenine (OR 3.851, P = 6.09 × 10-4), a risk factor; glycerol 2-phosphate (OR 0.549, P = 3.58 × 10-2) and 4-androsten-3beta,17beta-diol disulfate 2 (OR 0.461, P = 1.34 × 10-2) were recognized as protective factors against GD. Crucially, all 3 exhibited no shared genetic interrelation with GD, further substantiating their potential causal significance in the disease. This study unveils pivotal insights into the intricate relationships between serum metabolites and GD risk. By identifying specific risk and protective factors, it opens avenues for more precise disease understanding and management. The findings underline the importance of integrating genomics with metabolomics to fathom the multifaceted nature of GD.

Genome-Wide Association Study of Blood Mercury in European Pregnant Women and Children.

Mercury has high industrial utility and is present in many products, and environmental contamination and occupational exposure are widespread. There are numerous biological systems involved in the absorption, metabolism, and excretion of Hg, and it is possible that some systems may be impacted by genetic variation. If so, genotype may affect tissue concentrations of Hg and subsequent toxic effects. Genome-wide association testing was performed on blood Hg samples from pregnant women of the Avon Longitudinal Study of Parents and Children (n = 2893) and children of the Human Early Life Exposome (n = 1042). Directly-genotyped single-nucleotide polymorphisms (SNPs) were imputed to the Haplotype Reference Consortium r1.1 panel of whole genotypes and modelled againstlog-transformed Hg. Heritability was estimated using linkage disequilibrium score regression. The heritability of Hg was estimated as 24.0% (95% CI: 16.9% to 46.4%) in pregnant women, but could not be determined in children. There were 16 SNPs associated with Hg in pregnant women above a suggestive p-value threshold (p < 1 × 10-5), and 21 for children. However, no SNP passed this threshold in both studies, and none were genome-wide significant (p < 5 × 10-8). SNP-Hg associations were highly discordant between women and children, and this may reflect differences in metabolism, a gene-age interaction, or dose-response effects. Several suggestive variants had plausible links to Hg metabolism, such as rs146099921 in metal transporter SLC39A14, and two variants (rs28618224, rs7154700) in potassium voltage-gated channel genes. The findings would benefit from external validation, as suggestive results may contain both true associations and false positives.

Gut microbiome and frailty: insight from genetic correlation and mendelian randomization

ABSTRACT Observational studies have shown that the gut microbiome is associated with frailty. However, whether these associations underlie causal effects remains unknown. Thus, this study aimed to assess the genetic correlation and causal relationships between the genetically predicted gut microbiome and frailty using linkage disequilibrium score regression (LDSC) and Mendelian Randomization (MR). Summary statistics for the gut microbiome were obtained from a genome-wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340). Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene (N = 175,226). We used LDSC and MR analyses to estimate the genetic correlation and causality between the genetically predicted gut microbiome and frailty. Our findings indicate a suggestive genetic correlation between Christensenellaceae R-7 and frailty. Moreover, we found evidence for suggestive causal effects of twelve genus-level gut microbes on frailty using at least two MR methods. There was no evidence of horizontal pleiotropy or heterogeneity in the MR analysis. This study provides suggestive evidence for a potential genetic correlation and causal association between several genetically predicted gut microbes and frailty. More population-based observational studies and animal experiments are required to clarify this association and the underlying mechanisms.

An Atlas Characterizing the Shared Genetic Architecture of Inflammatory Bowel Disease with Clinical and Behavioral Traits

Abstract Background Inflammatory bowel disease (IBD) development is a complex, multifactorial process that involves extrinsic and intrinsic factors such as host genetics, the immune system, the gut microbiome, and environmental risks. To help understand the genetic contribution of clinical, behavioral, psychiatric, and diet-related traits, we aim to provide a deep and comprehensive characterization of the shared genetic architecture between IBD and hundreds of potentially related traits. Methods Utilizing publicly available summary statistics from a previously published IBD genome-wide association study and hundreds of traits from the United Kingdom BioBank (UKBB), we performed linkage disequilibrium score regression (LDSR) analysis to estimate cross-trait genetic correlations between Crohn’s disease (CD), ulcerative colitis (UC), and IBD summary statistics with the UKBB traits of interest. Results Nominally significant (P &amp;lt; .05) genetic correlations were observed for 181 traits in overall IBD, 239 traits in CD, and 94 traits in UC. We replicate the known association between smoking behavior and CD/UC, namely that current tobacco smoking has a positive genetic correlation with CD (rg = 0.12, P = 4.2 × 10-4), while “ever smoking” has a negative genetic correlation with UC (rg = −0.07, P = .042). Globally, all 3 strata (IBD, CD, and UC) demonstrated increased genetic correlations for psychiatric-related traits related to anxiety and depression. Conclusion The present analysis reveals the shared genetic architecture between multiple traits and IBD, CD, and UC. Understanding the relevance of joint occurrences of IBD with psychiatric diseases may moderate management of these diseases for individuals jointly affected by them.

Is diet related to osteoarthritis? A univariable and multivariable Mendelian randomization study that investigates 45 dietary habits and osteoarthritis.

Diet is a safe intervention for many chronic diseases as a modifiable lifestyle. However, the potential causal effect of many dietary intake habits on the risk of osteoarthritis has not been fully understood. The purpose of this study was to reveal the potential causal relationship of 45 genetically predicted dietary intakes with osteoarthritis and its subtypes. Data on 45 dietary intakes were obtained from the UK Biobank study of approximately 500,000 participants, and data on six osteoarthritis-related phenotypes were obtained from the Genetics of Osteoarthritis Consortium study of 826,690 participants. We performed univariable Mendelian randomization (MR), multivariable MR and linkage disequilibrium score regression (LDSC) analyses. In univariate analyses, 59 potential associations between diet and osteoarthritis were found. After false discovery rate (FDR) correction and sensitivity analyses, 23 reliable causal evidence were identified. In multivariate analyses, controlling separately for the effects of body mass index, total body bone mineral density, and smoking status, eight robust causal relationships remained: Muesli intake was negatively associated with knee osteoarthritis, spine osteoarthritis and total knee replacement. Dried fruit intake had a negative association with osteoarthritis of knee and total knee replacement. Eating cheese may reduce the risk of osteoarthritis in the knee and spine. And alcohol usually taken with meals was associated with a reduced risk of total knee replacement. LDSC analyses showed significant genetic correlations between all exposures and their corresponding outcomes, respectively, in these eight causal relationships. Evidence of dietary effects on osteoarthritis is provided in our study, which has important implications for the prevention, management, and intervention of osteoarthritis in common sites through rational dietary modification.

Serum uric acid and risk of diabetic neuropathy: a genetic correlation and mendelian randomization study.

Previous observational studies have indicated an association between serum uric acid (SUA) and diabetic neuropathy (DN), but confounding factors and reverse causality have left the causality of this relationship uncertain. Univariate Mendelian randomization (MR), multivariate MR and linkage disequilibrium score (LDSC) regression analysis were utilized to assess the causal link between SUA and DN. Summary-level data for SUA were drawn from the CKDGen consortium, comprising 288,648 individuals, while DN data were obtained from the FinnGen consortium, with 2,843 cases and 271,817 controls. Causal effects were estimated primarily using inverse variance weighted (IVW) analysis, supplemented by four validation methods, with additional sensitivity analyses to evaluate pleiotropy, heterogeneity, and result robustness. The LDSC analysis revealed a significant genetic correlation between SUA and DN (genetic correlation = 0.293, P = 2.60 × 10-5). The primary methodology IVW indicated that each increase of 1 mg/dL in SUA would increase DN risk by 17% (OR = 1.17, 95% CI 1.02-1.34, P = 0.02), while no causal relationship was found in reverse analysis (OR = 1.00, 95% CI 0.98~1.01, P = 0.97). Multivariate MR further identified that the partial effect of SUA on DN may be mediated by physical activity, low density lipoprotein cholesterol (LDL-C), insulin resistance (IR), and alcohol use. The study establishes a causal link between elevated SUA levels and an increased risk of DN, with no evidence for a reverse association. This underscores the need for a comprehensive strategy in DN management, integrating urate-lowering interventions with modulations of the aforementioned mediators.

Brainwide Mendelian Randomization Study of Anxiety Disorders and Symptoms

BackgroundTo gain insights into the role of brain structure and function on anxiety (ANX), we conducted a genetically informed investigation leveraging information from ANX genome-wide association studies available from the UK Biobank (n = 380,379), the FinnGen Program (n = 290,361), and the Million Veteran Program (n = 175,163) together with UK Biobank genome-wide data (n = 33,224) related to 3935 brain imaging–derived phenotypes (IDPs). MethodsA genetic correlation analysis between ANX and brain IDPs was performed using linkage disequilibrium score regression. To investigate ANX–brain associations, a 2-sample Mendelian randomization was performed considering multiple methods and sensitivity analyses. A subsequent multivariable Mendelian randomization was conducted to distinguish between direct and indirect effects. Finally, a generalized linear model was used to explore the associations of brain IDPs with ANX symptoms. ResultsAfter false discovery rate correction (q < .05), we identified 41 brain IDPs genetically correlated with ANX without heterogeneity among the datasets investigated (i.e., UK Biobank, FinnGen, and Million Veteran Program). Six of these IDPs showed genetically inferred causal effects on ANX. In the subsequent multivariable Mendelian randomization analysis, reduced area of the right posterior middle cingulate gyrus (β = −0.09, p = 8.01 × 10−4) and reduced gray matter volume of the right anterior superior temporal gyrus (β = −0.09, p = 1.55 × 10−3) had direct effects on ANX. In the ANX symptom-level analysis, the right posterior middle cingulate gyrus was negatively associated with "tense, sore, or aching muscles during the worst period of anxiety" (β = −0.13, p = 8.26 × 10−6). ConclusionsThis study identified genetically inferred effects that are generalizable across large cohorts, thereby contributing to our understanding of how changes in brain structure and function can lead to ANX.

Identification of genetic loci jointly influencing COVID-19 and coronary heart diseases

BackgroundComorbidities of coronavirus disease 2019 (COVID-19)/coronary heart disease (CHD) pose great threats to disease outcomes, yet little is known about their shared pathology. The study aimed to examine whether comorbidities of COVID-19/CHD involved shared genetic pathology, as well as to clarify the shared genetic variants predisposing risks common to COVID-19 severity and CHD risks.MethodsBy leveraging publicly available summary statistics, we assessed the genetically determined causality between COVID-19 and CHD with bidirectional Mendelian randomization. To further quantify the causality contributed by shared genetic variants, we interrogated their genetic correlation with the linkage disequilibrium score regression method. Bayesian colocalization analysis coupled with conditional/conjunctional false discovery rate analysis was applied to decipher the shared causal single nucleotide polymorphisms (SNPs).FindingsBriefly, we observed that the incident CHD risks post COVID-19 infection were partially determined by shared genetic variants. The shared genetic variants contributed to the causality at a proportion of 0.18 (95% CI 0.18–0.19) to 0.23 (95% CI 0.23–0.24). The SNP (rs10490770) located near LZTFL1 suggested direct causality (SNPs → COVID-19 → CHD), and SNPs in ABO (rs579459, rs495828), ILRUN(rs2744961), and CACFD1(rs4962153, rs3094379) may simultaneously influence COVID-19 severity and CHD risks.InterpretationFive SNPs located near LZTFL1 (rs10490770), ABO (rs579459, rs495828), ILRUN (rs2744961), and CACFD1 (rs4962153, rs3094379) may simultaneously influence their risks. The current study suggested that there may be shared mechanisms predisposing to both COVID-19 severity and CHD risks. Genetic predisposition to COVID-19 is a causal risk factor for CHD, supporting that reducing the COVID-19 infection risk or alleviating COVID-19 severity among those with specific genotypes might reduce their subsequent CHD adverse outcomes. Meanwhile, the shared genetic variants identified may be of clinical implications for identifying the target population who are more vulnerable to adverse CHD outcomes post COVID-19 and may also advance treatments of ‘Long COVID-19.’

Genome-Wide Assessment of Shared Genetic Architecture Between Rheumatoid Arthritis and Cardiovascular Diseases.

Background Patients with rheumatoid arthritis (RA) have a 2- to 10-fold increased risk of cardiovascular disease (CVD), but the biological mechanisms and existence of causality underlying such associations remain to be investigated. We aimed to investigate the genetic associations and underlying mechanisms between RA and CVD by leveraging large-scale genomic data and genetic cross-trait analytic approaches. Methods and Results Within UK Biobank data, we examined the genetic correlation, shared genetics, and potential causality between RA (Ncases=6754, Ncontrols=452 384) and cardiovascular diseases (CVD, Ncases=44 238, Ncontrols=414 900) using linkage disequilibrium score regression, cross-trait meta-analysis, and Mendelian randomization. We observed significant genetic correlations of RA with myocardial infarction (rg:0.40 [95% CI, 0.24-0.56), angina (rg:0.42 [95% CI, 0.28-0.56]), coronary heart diseases (rg:0.41 [95% CI, 0.27-0.55]), and CVD (rg:0.43 [95% CI, 0.29-0.57]) after correcting for multiple testing (P<0.05/5). When stratified by frequent use of analgesics, we found increased genetic correlation between RA and CVD among participants without aspirin usage (rg:0.54 [95% CI, 0.30-0.78] for angina; Pvalue=6.69×10-6) and among participants with paracetamol usage (rg:0.75 [95% CI, 0.20-1.29] for myocardial infarction; Pvalue=8.90×10-3), whereas others remained similar. Cross-trait meta-analysis identified 9 independent shared loci between RA and CVD, including PTPN22 at chr1p13.2, BCL2L11 at chr2q13, and CCR3 at chr3p21.31 (Psingle trait<1×10-3 and Pmeta<5×10-8), highlighting potential shared pathogenesis including accelerating atherosclerosis, upregulating oxidative stress, and vascular permeability. Finally, Mendelian randomization estimates showed limited evidence of causality between RA and CVD. Conclusions Our results supported shared genetic pathogenesis rather than causality in explaining the observed association between RA and CVD. The identified shared genetic factors provided insights into potential novel therapeutic target for RA-CVD comorbidities.