Large Genome-wide Association Studies Research Articles

Role of low-density lipoprotein in mediating the effect of air pollution on coronary heart disease: a two-step multivariate Mendelian randomization study.

Air pollution is affecting the health of millions of people all over the world. The causal correlations of PM2.5, PM10, and nitrogen dioxide (NOx), as the main fine particulate matter, and coronary heart disease (CHD) are yet to be explored. Low-density lipoprotein (LDL) has been a principal factor in the pathogenesis of CHD. It is an interesting issue to consider whether LDL mediates the effect of air pollutants in CHD pathogenesis. A genome-wide association study (GWAS) on the European population, followed up from 2010 to 2018, involving over 400,000 participants, was based on a land-use regression model. The annual mean concentrations of major air pollutant particles, PM2.5 (n=423,796), PM10 (n=423,796), and NOx (n=456,380), were recorded. The large GWAS database of CHD covered over ten million SNPs with independent single nucleotide polymorphisms (SNPs). LDL database collected major biochemical blood parameters from over 400,000 patients (n=440,546). Taken together, we conducted independent two-sample Mendelian randomization (MR) analyses for the causality between air pollutants (PM2.5, PM10, and NOx) and CHD. Multivariate MR analysis was conducted using causal relationships to determine the direct effects of exposure on outcome. The fixed-effect inverse variance weighted (IVW2) method was mainly employed to assess this relationship, with a confidence interval of 95% for the odds ratio (OR). Also, MR-Egger, weighted median, maximum likelihood ratio method, and random-effects inverse variance-weighted (IVW1) method were adopted as supplementary methods. Two-sample MR results based on the IVW2 method suggested positive correlations between PM2.5 and CHD [OR 1.875 (1.279-2.748), p=0.001], PM10 and CHD [OR 2.586 (1.479-4.523), p=0.001], and NOx and CHD [OR 2.991 (2.021-4.427), p=4.37E-08]. The direct effect and mediating proportion were calculated using multivariable Mendelian randomization (MVMR). Lastly, the mediating proportions of LDL in the regulatory roles of PM2.5, PM10, and NOx in CHD were 2.82%, 4.73%, and 9.54%, respectively. PM2.5, PM10, and NOx share direct causal associations with CHD, and LDL performs a mediating role in this pathogenic process. Early prevention against air pollution (such as increasing green areas and reducing large-scale industrial dust emissions) and early lipid-lowering treatment can effectively prevent the occurrence of CHD.

Associations between genetically predicted plasma N-glycans and pancreatic cancer risk

Objectives: Previous studies have suggested a potential link between glycan levels and pancreatic cancer. To better characterize this relationship, we performed a study to evaluate the association between genetically predicted N-glycan levels in plasma and pancreatic cancer risk. Methods: Using genetic variants identified to be associated with plasma N-glycan levels in large genome-wide association studies (GWAS) as instruments, we evaluated the associations between plasma N-glycans and pancreatic cancer risk by analyzing data from 8275 pancreatic cancer cases and 6723 controls. Results: We observed that lower predicted PGP110 levels were significantly associated with an increased risk of pancreatic cancer after adjusting for multiple comparisons. Conclusions: Our study did not support strong associations between human plasma N-glycans and the risk of pancreatic cancer, although the observed association with PGP110 warrants further investigation. Simple summary Objectives: Pancreatic cancer is a fatal malignancy. Therefore, there is an urgent need to better understand its risk factors and identify markers for better predicting individual risk of developing this cancer. Previous research has suggested that glycans may play a role in the development of pancreatic cancer. To better understand their relationship, we conducted a study to assess the associations between N-glycan levels predicted by genetic factors and pancreatic cancer risk. Methods: We used genetic factors related to blood N-glycan levels as instruments. We further evaluated the associations between plasma N-glycans and pancreatic cancer risk by analyzing data from 8275 pancreatic cancer patients and 6723 controls. Results: We only observed one association between predicted levels of PGP110 and pancreatic cancer risk. Conclusions: Our study did not support strong associations between N-glycan levels and pancreatic cancer risk, although the observed association with PGP110 can be further studied.

Breakfast Skipping and Traits of Cardiometabolic Health: A Mendelian Randomization Study

BackgroundBreakfast skipping has been linked to poor cardiometabolic health in observational studies, but the causality remains unknown. Herein, we used Mendelian randomization (MR) approach to elucidate the potential causal effects of breakfast skipping on cardiometabolic traits. MethodsGenetic association estimates for breakfast skipping, cardiometabolic diseases, and cardiometabolic risk factors were extracted from the UK Biobank and several large genome-wide association studies. Two-sample MR analyses were performed primarily using the inverse variance weighted method, followed by sensitivity analysis to test the reliability of results. ResultsMR results indicated no causal relationship between breakfast shipping with coronary heart disease (odds ratio [OR]: 1.079, 95% confidence interval [CI]: 0.817–1.426; p = 0.591), stroke (OR: 0.877, 95% CI: 0.680–1.131; p = 0.311), and type 2 diabetes mellitus (OR: 1.114, 95% CI: 0.631–1.970; p = 0.709). However, genetically predicted breakfast skipping was significantly associated with increased body mass index (β: 0.250, standard error [SE]: 0.079; p = 0.001), waist-to-hip ratio (β: 0.177, SE: 0.076; p = 0.019), and low-density lipoprotein cholesterol (β: 0.260, SE: 0.115; p = 0.024). We found no evidence of association of genetic liability to breakfast skipping with blood pressure, glycemic traits, and other blood lipids. Sensitivity analysis supported the above results. ConclusionOur study suggested that breakfast skipping is causally linked to weight gain and higher serum low-density lipoprotein cholesterol, which may mediate the increased risk of cardiometabolic diseases reported in epidemiological studies.

DIGITAL CLOCK DRAWING PERFORMANCE ASSOCIATIONS WITH ALZHEIMER’S DISEASE GENETIC RISK SCORE AND APOE IN OLDER ADULTS

Abstract Alzheimer’s disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until clinical signs and symptoms are present. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection. We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker. We used two primary independent variables, Apolipoprotein E (APOE) ɛ4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures. We used existing data from the Framingham Heart Study (FHS), a community-based study with the largest dataset of digital clock drawing data to date. The sample consisted of 2,398 older adults ages 60-94 with DCTclockTM data (mean age of 72.3, 55% female and 92% White). PRS was calculated using 38 variants identified in a recent large genome-wide association study (GWAS) and meta-analysis of late-onset AD (LOAD). Results showed that DCTclockTM performance decreased with advancing age, lower education, and the presence of one or more copies of APOE ε4. Lower DCTclockTM Total Score as well as lower composite scores for Information Processing Speed and Drawing Efficiency were significantly associated with higher PRS levels and more copies of APOE ε4. Associations displayed similar effect sizes in men and women. This is the first study to demonstrate significant differences in clock drawing performance on the basis of APOE status or PRS.

Causal relationships between risk of venous thromboembolism and 18 cancers: a bidirectional Mendelian randomization analysis.

People with cancer experience high rates of venous thromboembolism (VTE). Risk of subsequent cancer is also increased in people experiencing their first VTE. The causal mechanisms underlying this association are not completely understood, and it is unknown whether VTE is itself a risk factor for cancer. We used data from large genome-wide association study meta-analyses to perform bidirectional Mendelian randomization analyses to estimate causal associations between genetic liability to VTE and risk of 18 different cancers. We found no conclusive evidence that genetic liability to VTE was causally associated with an increased incidence of cancer, or vice versa. We observed an association between liability to VTE and pancreatic cancer risk [odds ratio for pancreatic cancer: 1.23 (95% confidence interval: 1.08-1.40) per log-odds increase in VTE risk, P = 0.002]. However, sensitivity analyses revealed this association was predominantly driven by a variant proxying non-O blood group, with inadequate evidence to suggest a causal relationship. These findings do not support the hypothesis that genetic liability to VTE is a cause of cancer. Existing observational epidemiological associations between VTE and cancer are therefore more likely to be driven by pathophysiological changes which occur in the setting of active cancer and anti-cancer treatments. Further work is required to explore and synthesize evidence for these mechanisms.

Mendelian randomization reveals systemic lupus erythematosus and rheumatoid arthritis and risk of adverse pregnancy outcomes

BackgroundThe effect of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) on adverse pregnancy outcomes is a controversial topic. This study aimed to use Mendelian randomization (MR) analysis to assess the causal relationship between SLE, RA and adverse pregnancy outcomes. MethodsGenetic variants for SLE and RA, as well as adverse pregnancy outcomes, were derived from pooled statistics from large public genome-wide association studies. Several methods, such as inverse variance weighting (IVW), MR-Egger, weighted median and MR-Pleiotropic Residuals Sum and Outliers, were employed to estimate two-sample causality. ResultsGenetic prediction of SLE was associated with higher odds of preterm labour [odds ratio (OR) 1.03, 95 % confidence interval (CI) 1.01–1.05; p = 0.008]. RA was associated with higher odds of preterm labour (OR 1.03, 95 % CI 1.01–1.06; p = 0.009), pre-eclampsia or eclampsia (OR 1.04, 95 % CI 1.01–1.07; p = 0.005), and poor fetal growth (OR 1.08, 95 % CI 1.04–1.12; p = 2.91 × 10−5). The results of bidirectional MR analysis did not indicate that SLE was associated with spontaneous abortion, pre-eclampsia or eclampsia, preterm rupture of membranes, or poor fetal growth (p-value for IVW 0.13–0.97). ConclusionsThis study found a genetic association between SLE and the risk of preterm labour, and highlights the importance of perinatal care and monitoring for patients with SLE. Furthermore, RA was found to be associated with a wide range of adverse outcomes, including preterm labour, pre-eclampsia or eclampsia, and poor fetal growth; as such, there is a need for more intensive therapeutic interventions and prenatal monitoring.

Genetic perspectives on the influence of circulating cytokines on acne: A Mendelian randomization study.

Previous studies have reported that the occurrence and development of acne are closely associated with immune-inflammatory responses. Mendelian randomization was performed to further assess the causal correlation between 41 inflammatory cytokines and acne. Mendelian two-sample randomization utilized genetic variants for acne from a large open genome-wide association study (1299 cases and 211,139 controls of European ancestry) and inflammatory cytokines from a genome-wide association study abstract containing 8293 healthy participants. The causal relationship between exposure and outcome was explored primarily using an inverse variance weighting approach. In addition, multiple sensitivity analyses including MR-Egger, weighted median, simple model, weighted model, and MR-PRESSO were applied simultaneously to enhance the final results. The results suggest that il-10, MIP-1A, and SCGF-β are suggestive of the risk of acne in clinical practice (OR = 0.799, 95% CI = 0.641-0.995, P = .045; OR = 0.55, 95% CI = 0.388-0.787, P = .001; OR = 1. 152, 95% CI = 1.001-1.325, P = .048). Our study conclusively identified a causal relationship between il-10 and circulating levels of acne risk and a suggestive link between MIP-1A and SCGF-β and acne. Our study may provide greater insight into the pathogenesis of acne and develop effective management strategies for the clinic. We believe that IL-10, MIP-1A, and SCGF-β could be potential therapeutic targets for acne development.

The impact of COVID-19 on pulmonary, neurological, and cardiac outcomes: evidence from a Mendelian randomization study.

Long COVID is a clinical entity characterized by persistent health problems or development of new diseases, without an alternative diagnosis, following SARS-CoV-2 infection that affects a significant proportion of individuals globally. It can manifest with a wide range of symptoms due to dysfunction of multiple organ systems including but not limited to cardiovascular, hematologic, neurological, gastrointestinal, and renal organs, revealed by observational studies. However, a causal association between the genetic predisposition to COVID-19 and many post-infective abnormalities in long COVID remain unclear. Here we employed Mendelian randomization (MR), a robust genetic epidemiological approach, to investigate the potential causal associations between genetic predisposition to COVID-19 and long COVID symptoms, namely pulmonary (pneumonia and airway infections including bronchitis, emphysema, asthma, and rhinitis), neurological (headache, depression, and Parkinson's disease), cardiac (heart failure and chest pain) diseases, and chronic fatigue. Using two-sample MR, we leveraged genetic data from a large COVID-19 genome-wide association study and various disorder-specific datasets. This analysis revealed that a genetic predisposition to COVID-19 was significantly causally linked to an increased risk of developing pneumonia, airway infections, headache, and heart failure. It also showed a strong positive correlation with chronic fatigue, a frequently observed symptom in long COVID patients. However, our findings on Parkinson's disease, depression, and chest pain were inconclusive. Overall, these findings provide valuable insights into the genetic underpinnings of long COVID and its diverse range of symptoms. Understanding these causal associations may aid in better management and treatment of long COVID patients, thereby alleviating the substantial burden it poses on global health and socioeconomic systems.

Preselecting Variants from Large-Scale Genome-Wide Association Study Meta-Analyses Increases the Genomic Prediction Accuracy of Growth and Carcass Traits in Large White Pigs.

Preselected variants associated with the trait of interest from genome-wide association studies (GWASs) are available to improve genomic prediction in pigs. The objectives of this study were to use preselected variants from a large GWAS meta-analysis to assess the impact of single-nucleotide polymorphism (SNP) preselection strategies on genome prediction of growth and carcass traits in pigs. We genotyped 1018 Large White pigs using medium (50k) SNP arrays and then imputed SNPs to sequence level by utilizing a reference panel of 1602 whole-genome sequencing samples. We tested the effects of different proportions of selected top SNPs across different SNP preselection strategies on genomic prediction. Finally, we compared the prediction accuracies by employing genomic best linear unbiased prediction (GBLUP), genomic feature BLUP and three weighted GBLUP models. SNP preselection strategies showed an average improvement in accuracy ranging from 0.3 to 2% in comparison to the SNP chip data. The accuracy of genomic prediction exhibited a pattern of initial increase followed by decrease, or continuous decrease across various SNP preselection strategies, as the proportion of selected top SNPs increased. The highest level of prediction accuracy was observed when utilizing 1 or 5% of top SNPs. Compared with the GBLUP model, the utilization of estimated marker effects from a GWAS meta-analysis as SNP weights in the BLUP|GA model improved the accuracy of genomic prediction in different SNP preselection strategies. The new SNP preselection strategies gained from this study bring opportunities for genomic prediction in limited-size populations in pigs.

#207 : Mendelian Randomization Study Reveals a Casual Effect of Blood Lipids and Apolipoprotein on Uterine Fibroids

Background and Aims: Despite an early insight into the risk factors of uterine fibroids (UFs), there is still controversy about the roles of blood lipids and apolipoprotein on UFs. Therefore, to provide more reliable evidence, we investigated the causal effect of blood lipids and apolipoprotein on the risk of UFs through Mendelian randomization (MR). Method: We utilized the large genome-wide association studies of blood lipids and apolipoprotein as instruments and integrated them in the inverse-variance-weighted (IVW) model in two-sample MR to investigate their causal relationship in large sample sizes. To eliminate potential pleiotropy, we listed a conclusive table of genes related to confounding factors, such as body mass index, waist circumference, blood pressure, glucose, hypertension, the metabolic syndrome and smoking and removed the repeated SNPs in the exposure data.To adjust for multiple comparisons, the statistical significance of the MR effect estimates was evaluated in a false discovery rate correlation of less than 5%. Neither pleiotropy nor heterogeneity was reported in all MR sensitivity analysis, including IVW, MR-Egger, simple median, weighted median, weighted mode and Mendelian Randomization Pleiotropy Residual Sum and Outlier methods. Results: Total triglycerides, very low-density lipoprotein (VLDL) cholesterol, including large, medium and small VLDL particles and free cholesterol in large VLDL cholesterol showed positive association with UFs. Meanwhile, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1, free cholesterol in small and medium VLDL and total cholesterol are not statistically related to the development of UFs. Conclusion: Exposure to various aberrant blood lipids increases the risk of UFs, providing genetic evidence for the vital role of aberrant lipid levels in the pathogenesis of UFs. Meanwhile, our results provided genetic insights suggesting intervention in blood lipids might be a prospective strategy in the early prevention and treatment of UFs.

Multi‐cohort genome‐wide association study on flortaucipir PET identifies novel risk loci associated with tau deposition and its role in AD pathology

AbstractBackgroundAmyloid‐β plaques and tau neurofibrillary tangles are the pathological hallmarks of Alzheimer’s disease (AD). Previously, genetic studies on amyloid‐β mediated AD pathogenesis dominated the field, and genetic studies on tau pathology are limited by comparison. Prior studies suggest that the spread of tau neurofibrillary tangles within the medial temporal lobe occurs following abnormal deposition of amyloid‐β, leading to cognitive impairment. Although amyloid‐β and tau both play a role in AD pathogenesis, exact genetic pathways associated with them are still unknown.MethodWe performed genome‐wide association study (GWAS) with brain Tau standard uptake value ratios (SUVRs) measured from positron emission tomography (PET) images from the A4 ((N = 311 with preclinical AD;female = 62%;tau mean‐SUVR = 1.076±0.06) and ADNI studies (N = 375‐280 cognitively normal, 76 mild cognitively impaired and 19 AD;female = 53%;tau mean‐SUVR = 1.12±0.13). Models were adjusted for age, sex and APOE‐ε4 dosage. Additionally, we evaluated the association of amyloid‐β and tau SUVRs with AD polygenic risk scores (PRS). PRS was calculated using genome‐wide variants, excluding 1MB region flanking APOE, and effect sizes from Kunkle et al GWAS study of clinical AD.ResultAnalysis of tau‐SUVR in 686 participants, identified five genome‐wide significant loci: rs78636169 (P = 1.37×10−9) in JARID2, rs114272033 (P = 7.87×10−9) in ISCA1P2, rs7292124 (P = 1.73×10−8) in RP1‐272J12.1, rs114742337 (P = 2.85×10−8) in RP4‐771M4.2, and rs138338441 (P = 3.91×10−8) in AC092684.1. Rs13412014 in AC007364.1 and rs9393067 in RP11‐314C16.1 were also associated with amyloid‐SUVR in a previous large GWAS. Two loci previously associated with clinical AD in a recent large GWA study, INPP5D (rs10933431) and SEC61G (rs76928645), were also nominally associated (P<0.05) with tau deposition in our study. Genes associated with Tau‐SUVR are enriched in the Schaffer axonal collaterals (P<1×10−05) that form synapses in hippocampus. Genome‐wide PRS of AD (excluding APOE region) was strongly associated with amyloid‐SUVR (P = 3.21×10−11;R2 = 0.077) but only weakly associated with tau‐SUVR (P = 1.38×10−04;R2 = 0.027). We are in the process of replicating our results in an independent cohort of 700 participants with measurements of tau deposition.ConclusionWe identified five novel genetic loci associated with tau pathology. Several genes involved in tau deposition were also associated with amyloid load in the brain. Taken together, our findings will clarify the genetic pathways that effect both amyloid and tau pathology in AD.

Causal associations of thyroid function and sudden sensorineural hearing loss: a bidirectional and multivariable Mendelian randomization study

BackgroundObservational studies have indicated a potential association between thyroid dysfunction and the risk of sudden sensorineural hearing loss (SSNHL). However, the precise causal relationship between the two remains uncertain. The objective of our study was to assess the causal influence of thyroid function on SSNHL by employing a bidirectional and multivariable Mendelian randomization (MR) approach.MethodsSingle-nucleotide polymorphisms (SNPs) associated with free thyroid (FT4) and thyroid stimulating hormone (TSH) were selected from the summary data of a large genome-wide association study (GWAS) conducted on European individuals. The summary-level data of SSNHL were also obtained from a GWAS, which included 196,592 participants (1,491 cases and 195,101 controls). The MR analysis primarily utilized the inverse variance weighted (IVW) method, with sensitivity analyses performed using the weighted median, MR-Egger, and MR-PRESSO approaches.ResultsIn the IVW method, an elevated genetically predicted FT4 level was found to effectively reduce the risk of SSNHL (OR = 0.747, 95% CI = 0.565–0.987, P = 0.04). These findings were consistent when conducting multivariate MR analysis, which adjusted for TSH levels (OR = 0.929, 95% CI = 0.867–0.995, P = 0.036). However, genetically predicted TSH levels did not emerge as a risk factor for SSNHL (OR = 1.409, 95% CI = 0.895–1.230, P = 0.547). Furthermore, even after adjusting for FT4 levels in the multivariate MR analysis, no evidence of a direct causal relationship between TSH levels and the risk of SSNHL was observed (OR = 1.011, 95% CI = 0.880–1.161, P = 0.867). The reverse MR analysis showed that there was no evidence of a direct causal relationship between SSNHL and the risk of FT4 level (OR = 1.026, 95% CI = 0.999–1.054, P = 0.056) or TSH level (OR = 1.002, 95% CI = 0.989–1.015, P = 0.702).ConclusionWithin the normal range, genetic variants associated with higher FT4 levels demonstrate a potential protective effect against SSNHL, whereas there is no direct causal relationship between TSH levels and the risk of SSNHL.

Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value

Where sufficiently large genome-wide association study (GWAS) samples are not currently available or feasible, methods that leverage increasing knowledge of the biological function of variants may illuminate discoveries without increasing sample size. We comprehensively evaluated 17 functional weighting methods for identifying novel associations. We assessed the performance of these methods using published results from multiple GWAS waves across each of five complex traits. Although no method achieved both high sensitivity and positive predictive value (PPV) for any trait, a subset of methods utilizing pleiotropy and expression quantitative trait loci nominated variants with high PPV (>75%) for multiple traits. Application of functionally weighting methods to enhance GWAS power for locus discovery is unlikely to circumvent the need for larger sample sizes in truly underpowered GWAS, but these results suggest that applying functional weighting to GWAS can accurately nominate additional novel loci from available samples for follow-up studies.

Depression and sarcopenia-related traits: A Mendelian randomization study

BACKGROUND Observational studies have suggested that depression is associated with sarcopenia. However, the causal relationship between depression and sarcopenia remains unclear. AIM To investigate the causal relationship between depression and sarcopenia. METHODS We performed a Mendelian randomization (MR) analysis to identify the bidirectional relationship between depression and sarcopenia-related traits. Summary-level data and independent variants used as instrumental variables came from large genome-wide association studies of depression (414055 cases and 892299 controls), of appendicular lean mass (ALM, 450243 participants), and of hand grip strength (exposure: 360000 participants; outcome: 334925 participants). RESULTS We identified a negative association of depression with lower ALM [odds ratio (OR): 0.932, 95% confidence interval (95%CI): 0.889-0.979, P = 0.005]. In the reverse MR analysis, we also observed an inverse association of hand grip strength with depression (OR: 0.200, 95%CI: 0.108-0.370, P < 0.001). Similar results were obtained in sensitivity analyses. CONCLUSION Depression was causally related to decreased muscle mass, and declined muscle strength might lead to a higher risk of depression.

Integrative genome-wide analyses identify novel loci associated with kidney stones and provide insights into its genetic architecture

Kidney stone disease (KSD) is a complex disorder with high heritability and prevalence. We performed a large genome-wide association study (GWAS) meta-analysis for KSD to date, including 720,199 individuals with 17,969 cases in European population. We identified 44 susceptibility loci, including 28 novel loci. Cell type-specific analysis pinpointed the proximal tubule as the most relevant cells where susceptibility variants might act through a tissue-specific fashion. By integrating kidney-specific omics data, we prioritized 223 genes which strengthened the importance of ion homeostasis, including calcium and magnesium in stone formation, and suggested potential target drugs for the treatment. The genitourinary and digestive diseases showed stronger genetic correlations with KSD. In this study, we generate an atlas of candidate genes, tissue and cell types involved in the formation of KSD. In addition, we provide potential drug targets for KSD treatment and insights into shared regulation with other diseases.

Exploring genetic associations between vitiligo and mental disorders using Mendelian randomization.

Although a large number of existing studies have confirmed that people with vitiligo are prone to mental disorders, these observational studies may be subject to confounding factors and reverse causality, so the true causal relationship is inconclusive. We conducted a bidirectional Mendelian randomization (MR) analysis to assess the causality between vitiligo and mental disorders, namely depression, anxiety, insomnia, schizophrenia, bipolar disorder, obsessive-compulsive disorder (OCD) and attention-deficit hyperactivity disorder (ADHD). Summary statistics from large available genome-wide association study (GWAS) datasets for generalized vitiligo (n = 44 266), depression (n = 173 005), anxiety (n = 17 310), insomnia (n = 386 988), schizophrenia (n = 130 644), bipolar disorder (n = 413 466), OCD (n = 9725) and ADHD (n = 225 534) were utilized. Inverse-variance weighted (IVW), MR-Egger and weighted median were employed to estimate causal effects. Sensitivity analysis and MR Pleiotropy Residual Sum and Outliers (MR PRESSO) were conducted to assess heterogeneity and pleiotropy, ensuring the robustness of the results. Additionally, we corrected for estimating bias that might be brought on by sample overlap using MRlap. In our findings, none of the rigorous bidirectional MR analyses uncovered a significant causal association. Even after applying the MRlap correction, the effect sizes remained statistically nonsignificant, thereby reinforcing the conclusions drawn via IVW. In summary, our genetic-level investigation did not reveal a causal link between generalized vitiligo and mental disorders.

Causal association of nonalcoholic fatty liver disease with 22 extrahepatic cancers: A Mendelian randomization study.

It is unclear whether nonalcoholic fatty liver disease (NAFLD) acts as a direct contributing factor to multiple extrahepatic cancers. We aimed to systematically investigate the causal relationships of NAFLD with extrahepatic cancers. We conducted a two-sample Mendelian randomization analysis to assess the causal effects of NAFLD on 22 extrahepatic cancers. We examined the association of NAFLD with extrahepatic cancers using multiple methods in the largest genome-wide association study meta-analysis to date. We also replicated the analyses and performed two independent sensitivity analysis in the largest genome-wide association study of UK Biobank. Using the weighted median method, genetically predicted NAFLD was significantly associated with female breast cancer risk (odds ratio [OR] 15.99; 95% confidence interval [CI] 9.58-26.69). Genetically predicted NAFLD is associated with cervical and laryngeal cancers using the inverse variance weighting method, and the ORs were 2.44 (95% CI 1.43-4.14) and 1.94 (95% CI 1.35-2.78), respectively. We observed that patatin-like phospholipase domain-containing protein 3-driven and transmembrane 6 superfamily member 2-driven NAFLD were associated with increased risks of leukemia, lung cancer, and prostate cancers (all with p<0.05). Furthermore, we confirmed the causal association between NAFLD and breast cancer using five known single-nucleotide polymorphisms of NAFLD and six genome-wide association study-identified variants. The ORs of the weighted median estimator was 10.76 (95% CI 8.27-13.98) and 10.76 (95% CI 8.25-14.04), respectively (p<0.001). Genetically predicted NAFLD is associated with an increased risk of female breast cancer, as well as cervical, laryngeal, leukemia, lung, and prostate cancers.

Large scale genome-wide association analyses identify novel genetic loci and mechanisms in hypertrophic cardiomyopathy

Abstract Background Hypertrophic cardiomyopathy (HCM) is an important cause of morbidity and mortality with both monogenic and polygenic components. Prior genome-wide association studies (GWAS) identified few genomic loci and disease genes due to limited sample size. Purpose To discover novel genetic loci, genes and mechanisms implicated in HCM using a large scale GWAS and multi-trait analysis of GWAS (MTAG). Methods and results We performed the largest HCM GWAS meta-analysis and MTAG to date including 5,900 HCM cases, 68,359 controls, and 36,083 UK Biobank (UKB) participants with cardiac magnetic resonance (CMR) imaging. We estimated the heritability of HCM attributable to common genetic variation (h2SNP) to be 0.25±0.02 using genome-based restricted maximum likelihood (GREML), with higher h2SNP in non-sarcomeric (0.29±0.02) compared to sarcomeric HCM (0.16±0.04). We identified a total of 70 loci (50 novel) associated with HCM (Figure 1), and 62 loci (32 novel) associated with relevant left ventricular (LV) structural or functional traits. Amongst the common variant HCM loci, we identify a novel HCM disease gene, SVIL, which encodes the actin-binding protein supervillin. We performed rare variant burden analysis including 1,845 clinically-diagnosed unrelated HCM cases and 37,481 controls and demonstrated a 10.5-fold (95% CI: 4.1-26.8; P=0.0000002) excess burden of SVIL loss of function (LoF) variants in HCM cases. Two-sample mendelian randomization analyses using LV contractility as exposure and obstructive (oHCM) and non-obstructive HCM (nHCM) as outcomes support a causal role of increased LV contractility in both oHCM and nHCM (Figure 2), suggesting common disease mechanisms and anticipating shared response to therapy. Conclusion We identify 50 novel genomic loci associated with HCM. Our data suggest that LoF variants in SVIL are a cause of HCM, and that increased contractility mediate both nHCM and oHCM. Taken together, the findings significantly increase our understanding of the genetic basis and molecular mechanisms of HCM, with potential implications for disease management.Figure 1Figure 2

Polygenic risk score for hypertrophic cardiomyopathy predicts population disease risk, penetrance in sarcomeric rare variant carriers and survival in cases

Abstract Background Hypertrophic cardiomyopathy (HCM) is an important cause of mortality, caused by rare pathogenic variants (sarcomere-positive) in around one third of cases. Recent large genome-wide association studies (GWAS) highlight the important contributions of common genetic variation on HCM risk and heritability1-3. Polygenic scores (PGS) quantify the cumulative individual risk from common genetic variation, and may provide important clinical utility. Purpose The aim of this study is to generate PGS for HCM, and evaluate its performance in predicting HCM in the general population, HCM penetrance in sarcomere-positive carriers, and risk of adverse outcomes in individuals with HCM. Methods The PGS was generated using a Bayesian framework (PRS-CS) with individual SNP effect estimates derived from the largest published HCM GWAS (5900 cases and 68359 controls of European ancestry from 7 cohorts) and multi-trait analysis of GWAS (MTAG) (incorporating GWAS of genetically correlated cardiac magnetic resonance imaging (CMR) traits from 36203 White British individuals in the UK Biobank [UKB])1. Genome-wide PGS were calculated using an additive model for participants in two cohorts (UKB and 100,000 Genomes Project [GeL]). To evaluate the effect of PGS on penetrant HCM in sarcomere-positive carriers, we identified individuals with pathogenic or likely pathogenic variants in 8 definitive HCM-causing genes (MYBPC3, MYH7, TNNT2, TNNI3, TPM1, ACTC1, MYL3, and MYL2) in UKB and GeL. Results In 343,182 unrelated White British ancestry participants from the UK Biobank (UKB), PGS was associated with an increased risk of HCM (OR per PGS SD 2.3, P&amp;lt;2x10-16), with 75% of HCM cases having a PGS above the population mean (Figure 1A). Individuals with PGS in the top centile had a substantially increased risk of HCM compared with those in the median (OR 14.5, P&amp;lt;2x10-16) and bottom centile (OR 36.6, 3x10-25) (Figure 1B). PGS had significant effects on stratifying HCM penetrance in 640 sarcomere-positive carriers in the UKB (top vs. middle quintile HCM OR: 3.7, P 0.009), and risk of being a HCM case in 599 sarcomere-positive carriers in GeL (top vs. middle quintile HCM OR 9.5, P 4x10-5) (Figure 1C), highlighting the important interactive effect of common and rare genetic variants. Finally, PGS predicted risk of all-cause mortality and major adverse cardiovascular events (MACE) after HCM diagnosis in 382 cases in UKB (all-cause mortality: top vs. bottom quintile: HR 3.9, P 0.013; MACE: top vs. bottom quintile: HR 3.5, P 4.x10-4), and all-cause mortality in 683 cases in GeL (top vs. bottom quintile: HR 6.3, P 1x10-6) (Figure 1D). Conclusions We derive a PGS for HCM risk prediction, and demonstrate potential clinical utility in stratifying risk of penetrant HCM in sarcomere-positive carriers, and in predicting risk of adverse outcomes in individuals with HCM.Figure 1

Abstract 12129: Using a Polygenic Risk Score to Account for Genomic Risk Factors in a Model to Detect Individuals With Dilated Ascending Thoracic Aortas

Background: Ascending thoracic aortic dilation is a complex trait that involves modifiable and non-modifiable risk factors and can lead to thoracic aortic aneurysm and dissection. Clinical risk factors have been shown to predict ascending thoracic aortic diameter. Polygenic risk scores (PRS) are increasingly used to assess clinical risk for multifactorial diseases. The degree to which a PRS improves aortic diameter risk prediction is not known. In this study we tested the extent to which the addition of PRS to clinical prediction algorithms improves the prediction of aortic diameter. Methods: Training and validation cohorts comprised 6,790 Penn Medicine Biobank (PMBB) participants with clinical data linked to whole exome sequencing. Linear regression models integrated PRS weights derived from a large genome wide association study of thoracic aortic diameter in the UK biobank and were compared to the performance of the standard and a reweighted variation of the recently published AORTA Score. Results: The training cohort of 5,092 participants (56% male) had a median age of 61 years (IQR 52-70) with a mean ascending aortic diameter of 3.4 cm (SD 0.5). Compared to the AORTA Score which explained 29.1% (95% CI 27.9%-30.8%) of the variance in aortic diameter, AORTA Score + PRS (explained 29.7%, 95% CI 28.5%-30.9%), the reweighted AORTA score (explained 30.7%, 95% CI 29.4%-32.3%), and the reweighted AORTA Score + PRS (explained 31.5%, 95% CI 30.0%-32.8%) had superior performance. For the predictive ability to identify thoracic aortic diameter of ≥ 4 cm, the addition of a PRS to both the AORTA Score and the reweighted AORTA Score improved sensitivity at a range of model threshold values. The respective areas under the receiver operator characteristic curve for the AORTA Score + PRS (0.762, 95% CI 0.731-0.794) and reweighted AORTA Score + PRS (0.779, 95% CI 0.749-0.809) were greater than the standard AORTA Score (0.758, 95% CI 0.727-0.789) and reweighted AORTA Score (0.775, 95% CI 0.745-0.805). Conclusions: We demonstrated that inclusion of a PRS to the AORTA Score results in a small performance enhancement. Further investigation is necessary to determine if incorporation of genetics into clinical risk prediction improve outcomes for thoracic aortic disease.