Genomic Structural Equation Modeling Combined With Post‐GWAS Analysis Identifies Two Risk Gene Loci and Functionally Sensitive Genes Associated With Cardiac Conduction Block

Sickle cell trait is not independently associated with susceptibility to end-stage renal disease in African Americans

Uncovering causal genetic mediators linking redefined obesity to osteoarthritis: Multidimensional analysis from population to genetic mechanisms.

The association between obesity and cholelithiasis has been identified. However, the causal relationship between age-specific childhood obesity and adult cholelithiasis remains unclear. In addition, the biological basis for the association between childhood obesity and adult cholelithiasis is poorly understood, which poses a challenge for preventing adult cholelithiasis in specific biological pathways. Summary statistics of genome-wide association studies (GWASs) of childhood age-specific body mass index (BMI) at 12 time points and adult cholelithiasis derived from FinnGen were used in this study, with the former covering data from birth to 8 years. Linkage disequilibrium score regression (LDSC) analyses were used to assess the genetic correlations of age-specific childhood BMI to cholelithiasis. Two-sample Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) analyses were utilized to explore the causal associations. As downstream analyses, summary-based Mendelian randomization (SMR) analyses, transcriptome-wide association studies (TWAS), and Bayesian colocalization were conducted to discover the shared transcriptomic signals. The GWAS summary statistics of cholelithiasis from the UK Biobank were used for sensitivity analyses. LDSC analyses revealed significant genetic correlations between 11 age-specific childhood BMIs and adult cholelithiasis (except for birth BMI). Two-sample MR and MVMR analyses indicated causal relationships between birth BMI and BMI at 8 months, 1.5 years, 7 years, and 8 years after birth and adult cholelithiasis. SMR, TWAS, and colocalization analyses identified MLXIPL as the strongest overlapping signal between age-specific BMI and adult cholelithiasis. This study provides new evidence on the relationships between childhood obesity and adult cholelithiasis, highlighting the role of early intervention for obesity in childhood at key time points. MLXIPL gene expression was identified as a potential biological pathway, suggesting potential therapeutic targets and precise intervention strategies for childhood obesity and adult cholelithiasis.

Background Recent research underscores a potential correlation between chronic obstructive pulmonary disease (COPD) and frailty, suggesting a shared genetic foundation. However, specific genetic factors and mechanisms underlying this association remain unclear. This study aimed to explore genetic connections between COPD and frailty using genome-wide association studies to enhance our understanding and improve clinical management and prevention strategies for these conditions. Method We utilised summary statistics for genome-wide association studies to examine the genetic correlations between COPD and frailty using linkage disequilibrium score regression. Local genetic correlations were evaluated using the ρ-heritability estimates from summary statistics method. Using the established two-sample Mendelian randomization approach, causal relationships have been identified. Shared genetic variants were quantified using a bivariate causal mixture model. Shared loci and single nucleotide polymorphisms were identified by conjoint false discovery rate (conjFDR). Gene enrichment and transcriptome-wide association studies (TWAS) were conducted to explore potential transcriptomic associations across tissues. Results We observed a significant genetic correlation between COPD and frailty (Rg = 0.4324, P = 6.09 × 10 − 26). MiXeR estimated 3,200-shared causal variants. Additionally, we discovered 16 shared loci linked to 91 genes, offering novel insights into gene expression across diverse tissues. The TWAS revealed 25 shared genes, representing a significant advance in understanding the genetic overlap between COPD and frailty. Furthermore, out of the 25 SNPs identified through TWAS, 4 overlapped with the lead SNPs, specifically [HLA-DRB1, PBX3, SLC22A5/OCTN2, SLMAP]. Conclusions Our study shows a common genetic foundation for COPD and frailty, identifying multiple shared loci and offering insights into their underlying causal connections. These findings enhance our understanding of the biological mechanisms linking these conditions and may guide future research and treatment strategies for related diseases.

APOL1 renal risk variants are strongly associated with chronic kidney disease in Black adults, but reported associations with cardiovascular disease (CVD) have been conflicting. We examined associations of APOL1 with incident coronary heart disease (n=323), ischemic stroke (n=331), and the composite CVD outcome (n=500) in 10 605 Black participants of the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Primary analyses compared individuals with APOL1 high-risk genotypes to APOL1 low-risk genotypes in Cox proportional hazards models adjusted for CVD risk factors and African ancestry. APOL1 high-risk participants were younger and more likely to have albuminuria at baseline than APOL1 low-risk participants. The risk of incident stroke, coronary heart disease, or composite CVD end point did not significantly differ by APOL1 genotype status in multivariable models. The association of APOL1 genotype with incident composite CVD differed by diabetes mellitus status (Pinteraction=0.004). In those without diabetes mellitus, APOL1 high-risk genotypes associated with greater risk of incident composite CVD (hazard ratio, 1.67; 95% confidence interval, 1.12-2.47) compared with those with APOL1 low-risk genotypes in multivariable adjusted models. This latter association was driven by ischemic strokes (hazard ratio, 2.32; 95% confidence interval, 1.33-4.07), in particular, those related to small vessel disease (hazard ratio, 5.10; 95% confidence interval, 1.55-16.56). There was no statistically significant association of APOL1 genotypes with incident CVD in subjects with diabetes mellitus. The APOL1 high-risk genotype was associated with higher stroke risk in individuals without but not those with chronic kidney disease in fully adjusted models. APOL1 high-risk status is associated with CVD events in community-dwelling Black adults without diabetes mellitus.

The past decade has seen major developments in our understanding of ancestry-specific rates of CKD and outcomes after kidney donation and transplantation. Genetic association between the G1 and G2 nephropathy risk variants in the apo L1 gene ( APOL1 ) and CKD is recognized as among the strongest in

Race, Ancestry, and Genetic Risk for Kidney Failure

ObjectivesThis study aims to clarify the genetic associations between Sjögren’s Disease (SD) and cardiovascular disease (CVD) outcomes, and to conduct an in-depth exploration of specific pleiotropic susceptibility genes.MethodsWe performed two-sample and multivariable Mendelian randomization (MR) analysis to investigate the association between SD and the risk of ischemic heart disease (IHD) and stroke. Linkage disequilibrium score regression (LDSC) and Bayesian co-localization analyses were employed to assess the genetic associations between traits. Cross-phenotype analyses were employed to identify shared variants and genes, followed by a Transcriptome-Wide Association Study (TWAS) and Multi-marker Analysis of Genomic Annotation (MAGMA) based on Multi-Trait Analysis of GWAS (MTAG) results. To validate the pleiotropic genes, we further analyzed tissue-specific differentially expressed genes (DEGs) related to SD using RNA sequencing data.ResultsThe two-sample and multivariable MR analyses revealed that SD confers a genetic vulnerability to IHD and stroke. LDSC and co-localization analyses indicated a strong genetic linkage between SD and CVDs. Cross-phenotype analyses identified 38 and 37 pleiotropic single nucleotide polymorphisms (SNPs) for SD-Stroke and SD-IHD, respectively, primarily located within the MHC class region on 6p21.32:33 loci. Additionally, TWAS and MAGMA analyses identified pleiotropic genes located outside the MHC regions—seven associated with stroke (UHRF1BP1, SNRPC, BLK, FAM167A, ARHGAP27, C8orf12, and PLEKHM1) and two associated with IHD (UHRF1BP1 and SNRPC). Proxy variants within these genes in SD suggested an increased causal risk for stroke or IHD. Co-localization analysis further reinforced that SD and stroke share significant SNPs within the loci of FAM167A, BLK, C8orf12, SNRPC, and UHRF1BP1. DEG analysis revealed a significant up-regulation of the identified genes in SD-specific tissues.ConclusionsSD appears genetically predisposed to an increased risk of CVDs. Moreover, this research not only identified pleiotropic genes shared between SD and CVDs, but also, for the first time, detected key gene expressions that elevate CVD risk in SD patients—findings that may offer promising therapeutic targets for patient management.

Transcriptome-wide association studies: a view from Mendelian randomization.

Background: To date, most genome-wide association studies (GWAS) of breast cancer have been conducted only among women of Asian and European ancestry. It is difficult to generalize results from those studies to women of African ancestry (AA). We conducted a large genetic association study of breast cancer in women of AA by analyzing both genetic and transcriptomic data. Methods: This collaborative study included 11,073 cases and 11,095 controls of AA who were participants in more than 15 studies conducted in the U.S. and Africa. Genotyping data were harmonized and imputed using the 1000 Genomes Project database as the reference. Imputed genotypes were used for GWAS to identify novel genetic risk loci for breast cancer. To search for susceptibility genes, we conducted a transcriptome-wide association study (TWAS), in which gene expression prediction models were built using genetic and tumor tissue RNA sequencing data from ~400 AA patients and used to impute expression levels of genes across the transcriptome for association analyses in all cases and controls included in the GWAS mentioned above. Results: We identified five loci (5p15.33, 5q31.3, 10q26.13, 18q12.1, and 19p13.11) associated with breast cancer risk at P < 5 × 10−8, including a novel locus at 5q31.3 (allelic odds ratio, OR = 1.18, 95% CI = 1.11-1.25, P = 4.65 × 10−8, nearby gene, ARHGAP26). This locus was also identified in association with estrogen receptor (ER) positive breast cancer at P < 5 × 10−8. Analyses stratified by ER status replicated known loci associated specifically with ER-positive (10q26.13) or ER-negative (2q14.2, 2p11.2, 5p15.33) breast cancer at P < 5 × 10−8. Of the 165 lead risk SNPs reported from previous breast cancer GWAS, 35 SNPs were replicated with the same association direction at P < 0.05. We constructed a polygenic risk score using these 35 replicated SNPs and the lead risk SNP at the novel locus and estimated the AUC to be 0.575. Of the 7,592 genes tested in the TWAS, we identified one gene, AC091053.1, with an association at a Bonferroni-corrected threshold of 6.64 × 10−6 (0.05/7,592). AC091053.1 is a long non-coding RNA gene at locus 11p15.4, where no risk variants have been identified in any previous breast cancer GWAS. AC091053.1 is located in the region of protein coding gene DENND2B, which acts as a regulator of MAPK1/ERK2 kinase and reduces the tumorigenic phenotype in cells. The gene AC091053.1 was associated with ER-positive breast cancer with P = 4.11 × 10−5 and ER-negative breast cancer with P = 0.032. Conclusions: Our study, the largest genetic study conducted to date in AA, identified novel breast cancer risk loci at 5q31.3 and 11p15.4 (AC091053.1) among women of AA and replicated >30 associations reported in previous studies. Studies with a larger sample size are needed to further investigate genetic variants and genes associated with breast cancer risk in AA women. Citation Format: Guochong Jia, Jie Ping, Yaohua Yang, Maureen Sanderson, Qiuyin Cai, Xingyi Guo, William J. Blot, Bingshan Li, Elisa V. Bandera, Manjeet K. Bolla, Montserrat García-Closas, Douglas F. Easton, Mary K. Fadden, Jian Gu, Dezheng Huo, Esther M. John, Kathryn L. Lunetta, Olufunmilayo I. Olopade, Xiang Shu, Melissa A. Troester, Song Yao, Breast Cancer Association Consortium, Andrew F. Olshan, Christine B. Ambrosone, Christopher A. Haiman, Jirong Long, Julie R. Palmer, Wei Zheng. Integrating genomic and transcriptomic data to identify genetic loci associated with breast cancer risk in women of African ancestry [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 28.

APOL1, Black Race, and Kidney Disease: Turning Attention to Structural Racism

Comprehensive Investigation of White Blood Cell and Gene Expression Profiles As Risk Factors for Multiple Myeloma in African Americans

Multi-Omics Analysis Identifies Genetic Mechanisms and Therapeutic Targets for Acne Vulgaris.

There is considerable uncertainty regarding the associations between various risk factors and Parkinson’s Disease (PD). This study systematically screened and validated a wide range of potential PD risk factors from 502,364 participants in the UK Biobank. Baseline data for 1851 factors across 11 categories were analyzed through a phenome-wide association study (PheWAS). Polygenic risk scores (PRS) for PD were used to diagnose Parkinson’s Disease and identify factors associated with PD diagnosis through PheWAS. Two-sample Mendelian randomization (MR) analysis was employed to assess causal relationships. PheWAS results revealed 267 risk factors significantly associated with PD-PRS among the 1851 factors, and of these, 27 factors showed causal evidence from MR analysis. Compelling evidence suggests that fluid intelligence score, age at first sexual intercourse, cereal intake, dried fruit intake, and average total household income before tax have emerged as newly identified risk factors for PD. Conversely, maternal smoking around birth, playing computer games, salt added to food, and time spent watching television have been identified as novel protective factors against PD. The integration of phenotypic and genomic data may help to identify risk factors and prevention targets for PD.

Rheumatoid arthritis (RA) is the most prevalent autoimmune inflammatory joint disorder worldwide. We aimed to identify the genetic variants contributing to RA and investigate the potential influence of related diseases on RA risk. We performed genome-wide association studies (GWAS) on RA using the 2019 UK Biobank pain questionnaire. We conducted a primary GWAS (9,389 RA cases; 132,108 controls) and separate sex-stratified GWAS for females (4,832 cases; 75,184 controls) and males (4,557 cases; 56,924 controls). We incorporated 12 phenotypes from downstream analyses, such as genetic correlation analyses, transcriptome-wide association studies (TWAS), phenome-wide association studies (PheWAS), and Mendelian randomization (MR) studies to determine causal relationships with RA. Two loci reached genome-wide significance in the primary GWAS. The top SNP, rs35139284 (p = 3.67 × 10-25) in the HLA-DRB1 gene on chromosome 6, exhibited a robust replication. Another locus, harboring the top SNP rs539837 (p = 6.26 × 10-9) near the LINC01680 gene on chromosome 1, also showed a significant association. In the female-specific GWAS, rs35139284 (p = 1.91 × 10-22) remained the top signal, whereas the male-specific GWAS revealed a suggestive significance at rs9267989 (p = 5.28 × 10-8) in TSBP1-AS1. TWAS and tissue specificity studies pointed to the spleen, lung, and small intestine as key tissues implicated in RA. PheWAS and MR analyses highlighted asthma and eosinophils associated with RA. Our findings confirmed an RA locus at chromosome 6 and highlighted associations between RA and a spectrum of immune-related and inflammatory phenotypes. Further analyses may provide greater insights into the genetic architecture of RA. Key Points •Leveraging the 2019 UK Biobank pain questionnaire, our genome-wide association studies (GWAS) confirmed a risk locus on chromosome 6 associated with rheumatoid arthritis (RA). •Sex-stratified analyses revealed significant differences in RA susceptibility between males and females, paving the way for personalized therapeutic strategies by demonstrating sex-specific genetic risks. •Mendelian randomization underscored the associations of both asthma and eosinophils with RA while identifying key hub genes, thereby deepening our understanding of RA's underlying molecular mechanisms and suggesting potential targets for future interventions.