UK Biobank Genome-wide Association Study Research Articles

Statistical power of transcriptome-wide association studies.

Transcriptome-Wide Association Studies (TWASs) have become increasingly popular in identifying genes (or other endophenotypes or exposures) associated with complex traits. In TWAS, one first builds a predictive model for gene expressions using an expression quantitative trait loci (eQTL) data set in stage 1, then tests the association between the predicted gene expression and a trait based on a large, independent genome-wide association study (GWAS) data set in stage 2. However, since the sample size of the eQTL data set is usually small and the coefficient of multiple determination (i.e., ) of the model for many genes is also small, a question of interest is to what extent these factors affect the statistical power of TWAS. In addition, in contrast to a standard (univariate) TWAS (UV-TWAS) considering only a single gene at a time, multivariate TWAS (MV-TWAS) methods have recently emerged to account for the effects of multiple genes, or a gene's nonlinear effects, simultaneously. With the absence of the power analysis for these MV-TWAS methods, it would be of interest to investigate whether one can gain or lose power by using the newly proposed MV-TWAS instead of UV-TWAS. In this paper, we first outline a general method for sample size/power calculations for two-sample TWAS, then use real data-the Alzheimer's Disease Neuroimaging Initiative (ADNI) expression quantitative trait loci (eQTL) data and the Genotype-Tissue Expression (GTEx) eQTL data for stage 1, the International Genomics of Alzheimer's Project Alzheimer's disease (AD) GWAS summary data and UK Biobank (UKB) individual-level data for stage 2-to empirically address these questions. Our most important conclusions are the following. First, a sample size of a few thousands (~8000) would suffice in stage 1, where the power of TWAS would be more determined by cis-heritability of gene expression. Second, as in the general case of simple regression versus multiple regression, the power of MV-TWAS may be higher or lower than that of UV-TWAS, depending on the specific relationships among the GWAS trait and multiple genes (or linear and nonlinear terms of the same gene's expression levels), such as their correlations and effect sizes. Interestingly, several top genes with large power gains in MV-TWAS (over that in UV-TWAS)were known to be (and in our data more significantly) associated with AD. We also reached similar conclusions in an application to the GTEx whole blood gene expression data and UKB GWAS data of high-density lipoprotein cholesterol. The proposed method and the conclusions are expected to be useful in planning and designing future TWAS and other related studies (e.g., Proteome- or Metabolome-Wide Association Studies) when determining the sample sizes for the two stages.

Integrated analysis of direct and proxy genome wide association studies highlights polygenicity of Alzheimer's disease outside of the APOE region.

Recent meta-analyses combining direct genome-wide association studies (GWAS) with those of family history (GWAX) have indicated very low SNP heritability of Alzheimer’s disease (AD). These low estimates may call into question the prospects of continued progress in genetic discovery for AD within the spectrum of common variants. We highlight dramatic downward biases in previous methods, and we validate a novel method for the estimation of SNP heritability via integration of GWAS and GWAX summary data. We apply our method to investigate the genetic architecture of AD using GWAX from UK Biobank and direct case-control GWAS from the International Genomics of Alzheimer’s Project (IGAP). We estimate the liability scale common variant SNP heritability of Clinical AD outside of APOE region at ~7–11%, and we project the corresponding estimate for AD pathology to be up to approximately 23%. We estimate that nearly 90% of common variant SNP heritability of Clinical AD exists outside the APOE region. Rare variants not tagged in standard GWAS may account for additional variance. Our results indicate that, while GWAX for AD in UK Biobank may result in greater attenuation of genetic effects beyond that conventionally assumed, it does not introduce appreciable contamination of signal by genetically distinct traits relative to direct case-control GWAS in IGAP. Genetic risk for AD represents a strong effect of APOE superimposed upon a highly polygenic background.

A suggested shared aetiology of dementia - a colocalization study

Identification of shared causal genes between dementia and its related clinical outcomes can help understand shared aetiology and multimorbidity surrounding dementia. We performed the HyPrColoc colocalization analysis to detect possible shared causal genes between dementia or Alzheimer's disease (AD) and 5 selected traits: stroke, diabetes, atherosclerosis, cholesterol level, and alcohol consumption within 601 dementia or AD associated genetic regions using summary results of the UK Biobank genome-wide association studies. Functional analysis was performed on the candidate causal genes to explore potential biological pathways. Rs150562240 in the LPIN3 gene was identified as a candidate shared causal variant across dementia, AD and atherosclerosis. Evidence for pairwise colocalization between dementia and stroke, dementia (or AD) and atherosclerosis, and dementia (or AD) and diabetes was found in 2, 6 and 2 genetic regions respectively. Colocalization signals between diabetes and the other 3 non-dementia/AD traits were detected in 5 regions. The colocalization evidence shown in our study suggested shared aetiology between dementia and related diseases such as stroke, atherosclerosis, and diabetes.

Genome-Wide Identification of Associations of Circulating Molecules With Spontaneous Coronary Artery Dissection and Aortic Aneurysm and Dissection.

Circulating proteins play functional roles in various biological processes and disease pathogenesis. The aim of this study was to highlight circulating proteins associated with aortic aneurysm and dissection (AAD) and spontaneous coronary artery dissection (SCAD). We examined the associations of circulating molecule levels with SCAD by integrating data from a genome-wide association study (GWAS) of CanSCAD and 7 pQTL studies. Mendelian randomization (MR) analysis was applied to examine the associations between circulating molecule levels and AAD by using data from UK Biobank GWAS and pQTL studies. The SCAD-associated SNPs in 1q21.2 were strongly associated with circulating levels of extracellular matrix protein 1 (ECM1) and 25 other proteins (encoded by CTSS, CAT, CNDP1, KNG1, SLAMF7, TIE1, CXCL1, MBL2, ESD, CXCL16, CCL14, KCNE5, CST7, PSME1, GPC3, MAP2K4, SPOCK3, LRPPRC, CLEC4M, NOG, C1QTNF9, CX3CL1, SCP2D1, SERPINF2, and FN1). These proteins were enriched in biological processes such as regulation of peptidase activity and regulation of cellular protein metabolic processes. Proteins (FGF6, FGF9, HGF, BCL2L1, and VEGFA) involved in the Ras signaling pathway were identified to be related to AAD. In addition, SCAD- and AAD-associated SNPs were associated with cytokine and lipid levels. MR analysis showed that circulating ECM1, SPOCK3 and IL1b levels were associated with AAD. Circulating levels of low-density lipoprotein cholesterol and small very-low-density lipoprotein particles were strongly associated with AAD. The present study found associations between circulating proteins and lipids and SCAD and AAD. Circulating ECM1 and low-density lipoprotein cholesterol may play a role in the pathology of SCAD and AAD.

Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases.

Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (eGFR). The relationship between polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS ( n =765,348) and UK Biobank GWAS (90% of the cohort; n =451,508), followed by best-parameter selection using the remaining 10% of UK Biobank data ( n =45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study ( n =8866) with incident CKD, ESKD, kidney failure, and AKI. We also examined associations between the PRS and 4877 plasma proteins measured at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. The developed PRS showed a significant association with all outcomes. Hazard ratios per 1 SD lower PRS ranged from 1.06 (95% CI, 1.01 to 1.11) to 1.33 (95% CI, 1.28 to 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin C, collagen α -1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for five proteins, including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.

Characterisation of insomnia as an environmental risk factor for asthma via Mendelian randomization and gene environment interaction

Asthma is a complex disease that is reportedly associated with insomnia. However, the causal directionality of this association is still unclear. We used asthma and insomnia-associated single nucleotide polymorphisms (SNPs) and genome-wide association study (GWAS) summary statistics to test the causal directionality between insomnia and asthma via Mendelian randomization (MR) analysis. We also performed a cross-trait meta-analysis using UK Biobank GWAS summary statistics and a gene–environment interaction study using data from UK Biobank. The interaction of genetic risk score for asthma (GRSasthma) with insomnia on asthma was tested by logistic regression. Insomnia was a risk factor for the incidence of asthma, as revealed by three different methods of MR analysis. However, asthma did not act as a risk factor for insomnia. The cross-trait meta-analysis identified 28 genetic loci shared between asthma and insomnia. In the gene–environment interaction study, GRSasthma interacted with insomnia to significantly affect the risk of asthma. The results of this study highlight the importance of insomnia as a risk factor of asthma, and warrant further analysis of the mechanism through which insomnia affects the risk of asthma.

In silico genome-wide gene-based association analysis reveals new genes predisposing to coronary artery disease.

Genome-wide association study (GWAS) have identified more than 300 single nucleotide polymorphisms at 163 independent loci associated with coronary artery disease (CAD). However, there is no full understanding about the causal genes for CAD and the mechanisms of their action. We aimed to perform a post GWAS analysis to identify genes whose polymorphism may influence the risk of CAD. Using the UK Biobank GWAS summary statistics, we performed a gene-based association analysis. We found 63 genes significantly associated with CAD due to their within-gene polymorphisms. Many of these genes are well known. Some known CAD genes such as FURIN and SORT1 did not show the gene-based association because their variants had low GWAS signals or gene-based association was inflated by the strong GWAS signal outside the gene. For several known CAD genes, we demonstrated that their effects could be explained not only or not at all by their own variants but by the variants within the neighboring genes controlling their expression. Using several bioinformatics techniques, we suggested potential mechanisms underlying gene-CAD associations. Three genes, CDK19, NCALD, and ARHGEF12 were not previously associated with CAD. The role of these genes should be clarified in further studies.

Genetically Predicted Lifelong Circulating 25(OH)D Levels are Associated With Serum Calcium Levels and Kidney Stone Risk.

To assess whether lifelong higher circulating 25-hydroxyvitamin D [25(OH)D] levels increase serum calcium levels and kidney stone disease (KSD) risk. Summary data for KSD were obtained from the UK biobank genome-wide association study (6536 cases and 388 508 controls). We acquired summary data for 25(OH)D from 120 618 Europeans and another large-scale analysis (443 734 Europeans) for primary and secondary analysis. Random-effect inverse-variance weighted (IVW) and 7 additional sensitivity analyses were applied. Next, multivariable Mendelian randomization (MVMR) was performed by introducing data for serum calcium levels. Genetic predisposition for a 1-SD higher 25(OH)D level was associated with increased serum calcium levels (IVW; beta, 0.014; 95% CI, 0.010-0.018; P = 7.64E-10). Genetically predicted higher circulating 25(OH)D levels were associated with increased the risk of KSD, with per 1-SD odds ratios (ORs) of 1.47 (95% CI, 1.22-1.77; P = 5.49E-05) and 1.36 (95% CI, 1.03-1.80; P = 0.029) using the IVW and MVMR-Egger methods, respectively. In secondary analysis, similar results were found: 25(OH)D was associated with an increased risk of KSD in univariate Mendelian randomization (IVW; OR 1.71; 95% CI, 1.26-2.32; P = 0.001) and MVMR (OR 1.43; 95% CI, 1.16-1.76; P < 0.001) analyses. Most sensitivity analyses were consistent with the primary results, both for the primary and secondary analyses. Our study supports that higher genetically predicted lifelong circulating 25(OH)D levels are associated with higher calcium levels and KSD risk. The effects of 25(OH)D on KSD were partially attenuated-but still significant-in MVMR.

Susceptibility loci and polygenic architecture highlight population specific and common genetic features in inguinal hernias: genetics in inguinal hernias.

BackgroundThe underlying pathology of inguinal hernia is still not fully known; thus, further investigations of genetic backgrounds is needed. Here, we aimed to identify genetic factors attributing to inguinal hernias and explore the polygenic architecture of which some components are population-specific, while others are more common among populations.MethodsWe performed a genome-wide association study (GWAS) on subjects with inguinal hernias using BioBank Japan (BBJ) data with 1,983 cases and 172,507 controls, followed by a trans-ethnic meta-analysis with UK Biobank (UKBB) data. We performed downstream analyses in order to identify the mechanisms underlying inguinal hernias supported by genetic findings.FindingsWe identified a locus closest to ELN, which encodes elastin, at the GWAS significant level. The trans-ethnic meta-analysis revealed 23 additional significant loci, including five loci newly identified not significant in BBJ or UKBB GWAS: TGFB2, RNA5SP214/VGLL2, LOC646588, HMCN2, and ATP5F1CP1/CDKN3. Downstream analyses revealed the overlap of GWAS significant signals in extracellular components, including elastin fiber formation. We also found a highly shared polygenic architecture across different populations (trans-ethnic genetic-effect correlation = 0•77, standard error = 0•26) and population-specific lead variants in ELN, indicating the critical role of elastin in inguinal hernias.InterpretationWe identified a significant locus of the ELN gene in the Japanese population and five additional loci across different populations. Downstream analyses revealed highly shared genetic architectures across populations and highlighted the important roles of extracellular components in the development of inguinal hernias. These findings deepen our understanding of the mechanisms underlying inguinal hernia.FundingThe Japan Agency for Medical Research and Development (AMED) (Grant Number: JP19km0605001)

Three genes associated with anterior and posterior cruciate ligament injury : a genome-wide association analysis.

AimsThe aim of this study was to screen the entire genome for genetic markers associated with risk for anterior cruciate ligament (ACL) and posterior cruciate ligament (PCL) injury.MethodsGenome-wide association (GWA) analyses were performed using data from the Kaiser Permanente Research Board (KPRB) and the UK Biobank. ACL and PCL injury cases were identified based on electronic health records from KPRB and the UK Biobank. GWA analyses from both cohorts were tested for ACL and PCL injury using a logistic regression model adjusting for sex, height, weight, age at enrolment, and race/ethnicity using allele counts for single nucleotide polymorphisms (SNPs). The data from the two GWA studies were combined in a meta-analysis. Candidate genes previously reported to show an association with ACL injury in athletes were also tested for association from the meta-analysis data from the KPRB and the UK Biobank GWA studies.ResultsThere was a total of 2,214 cases of ACL and PCL injury and 519,869 controls within the two cohorts, with three loci demonstrating a genome-wide significant association in the meta-analysis: INHBA, AEBP2, and LOC101927869. Of the eight candidate genes previously studied in the literature, six were present in the current dataset, and only COL3A1 (rs1800255) showed a significant association (p = 0.006).ConclusionGenetic markers in three novel loci in this study and one previously-studied candidate gene were identified as potential risk factors for ACL and PCL injury and deserve further validation and investigation of molecular mechanisms.Cite this article: Bone Jt Open 2021;2(6):414–421.

Assessment of causal factors for Parkinson's disease in European populations: A phenome-wide Mendelian randomisation analysis.

To assess the causality of potentially modifiable factors, including lifestyle, nutrients, lipids, anthropometric traits, and inflammatory factors of Parkinson's disease (PD), genetic instruments for modifiable factors were identified from genome-wide association studies (GWAS). Genetic associations for PD (1,239 cases and 451,025 matched controls) were extracted from the UK Biobank GWAS summary statistics. The causal effects of modifiable factors on the risk of PD were estimated using the multiplicative random-effects inverse variance weighted method (IVW). In the IVW analysis, a decreased risk for PD was causally associated with genetically predicted smoking cessation (odds ratio 0.41, [95% confidence interval] 0.32-0.78; p<0.001), and higher bone mineral density (0.43, 0.38 -0.71; p<0.001), higher concentrations of vitamin B-12 (0.56, 0.43-0.91; p<0.001), docosahexenoic acid (0.52, 0.37-0.71; p<0.001), and sIL-6R (0.69, 0.58-0.75; p<0.001). Instead, analysis further supported the role of apolipoprotein (a) isoform size(1.67, 1.36-1.71; p<0.001), being a genetically morning person (2.18, 1.12-4.72; p<0.001), and number of cigarette smoking (1.05, 1.01-1.08; p<0.001) in contributing to the risk of developing PD. Our findings provide new evidence for the potential positive causal association of cigarette smoking number and apolipoprotein (a) isoform size and the inverse causal association of vitamin B-12, docosahexaenoic acid, smoking cessation, and soluble interleukin-6 receptor with PD, which contributes to the development of new interventions for PD.

GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background.

Genome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. We describe UK Biobank GWAS results for three molecular traits-urate, IGF-1, and testosterone-with better-understood biology than most other complex traits. We find that many of the most significant hits are readily interpretable. We observe huge enrichment of associations near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of each trait, including differences in testosterone regulation between females and males. At the same time, even these molecular traits are highly polygenic, with many thousands of variants spread across the genome contributing to trait variance. In summary, for these three molecular traits we identify strong enrichment of signal in putative core gene sets, even while most of the SNP-based heritability is driven by a massively polygenic background.

Integration of genetically regulated gene expression and pharmacological library provides therapeutic drug candidates.

Approaches toward new therapeutics using disease genomics, such as genome-wide association study (GWAS), are anticipated. Here, we developed Trans-Phar [integration of transcriptome-wide association study (TWAS) and pharmacological database], achieving in silico screening of compounds from a large-scale pharmacological database (L1000 Connectivity Map), which have inverse expression profiles compared with tissue-specific genetically regulated gene expression. Firstly we confirmed the statistical robustness by the application of the null GWAS data and enrichment in the true-positive drug–disease relationships by the application of UK-Biobank GWAS summary statistics in broad disease categories, then we applied the GWAS summary statistics of large-scale European meta-analysis (17 traits; naverage = 201 849) and the hospitalized COVID-19 (n = 900 687), which has urgent need for drug development. We detected potential therapeutic compounds as well as anisomycin in schizophrenia (false discovery rate (FDR)-q = 0.056) and verapamil in hospitalized COVID-19 (FDR-q = 0.068) as top-associated compounds. This approach could be effective in disease genomics-driven drug development.

A genome-wide association study for shoulder impingement and rotator cuff disease.

The purpose of the study was to identify genetic variants associated with rotator cuff disease by performing a genome-wide association study (GWAS) for shoulder impingement using the UK Biobank (UKB) cohort and then combining the GWAS data with a prior GWAS for rotator cuff tears. The loci identified by the GWAS and meta-analysis were examined for changes in expression following rotator cuff tearing using RNA sequencing. A GWAS was performed using data from UKB with 3864 cases of shoulder impingement. The summary statistics from shoulder impingement and a prior study on rotator cuff tears were combined in a meta-analysis. Also, the previous association of 2 single-nucleotide polymorphisms (SNPs) with shoulder impingement from a published GWAS using the UKB was tested. Rotator cuff tendon biopsies were obtained from 24 patients with full-thickness rotator cuff tears who underwent arthroscopic rotator cuff repair (cases) and 9 patients who underwent open reduction internal fixation for a proximal humeral fracture (controls). Total RNA was extracted and differential gene expression was measured by RNA sequencing for genes with variants associated with rotator cuff tearing. The shoulder impingement GWAS identified 4 new loci: LOC100506457, LSP1P3, LOC100506207, and MIS18BP1/LINC00871. Combining data with a prior GWAS for rotator cuff tears in a meta-analysis resulted in the identification of an additional 7 loci: SLC39A8/UBE2D3, C5orf63, ASTN2, STK24, FRMPD4, ACOT9/SAT1, and LINC00890/ALG13. Many of the identified loci have known biologic functions or prior associations with diseases, suggesting possible biologic pathways leading to rotator cuff disease. RNA sequencing experiments show that expression of STK24 increases whereas expression of SAT1 and UBE2D3 decreases following rotator cuff tearing. Two SNPs previously reported to show an association with shoulder impingement from a prior UKB GWAS were not validated in our study. This is the first GWAS for shoulder impingement in which new data from UKB enabled the identification of 4 loci showing a genetic association. A meta-analysis with a prior GWAS for rotator cuff tearing identified an additional 7 loci. The known biologic roles of many of the 11 loci suggest plausible biologic mechanisms underlying the etiology of rotator cuff disease. The risk alleles from each of the genetic loci can be used to assess the risk for rotator cuff disease in individual patients, enabling preventative or restorative actions via personalized medicine.

Causal Associations of Anthropometric Measurements With Fracture Risk and Bone Mineral Density: A Mendelian Randomization Study.

Uncovering additional causal clinical traits and exposure variables is important when studying osteoporosis mechanisms and for the prevention of osteoporosis. Until recently, the causal relationship between anthropometric measurements and osteoporosis had not been fully revealed. In the present study, we utilized several state-of-the-art Mendelian randomization (MR) methods to investigate whether height, body mass index (BMI), waist-to-hip ratio (WHR), hip circumference (HC), and waist circumference (WC) are causally associated with two major characteristics of osteoporosis, bone mineral density (BMD) and fractures. Genomewide significant (p ≤ 5× 10-8 ) single-nucleotide polymorphisms (SNPs) associated with the five anthropometric variables were obtained from previous large-scale genomewide association studies (GWAS) and were utilized as instrumental variables. Summary-level data of estimated bone mineral density (eBMD) and fractures were obtained from a large-scale UK Biobank GWAS. Of the MR methods utilized, the inverse-variance weighted method was the primary method used for analysis, and the weighted-median, MR-Egger, mode-based estimate, and MR pleiotropy residual sum and outlier methods were utilized for sensitivity analyses. The results of the present study indicated that each increase in height equal to a single standard deviation (SD) was associated with a 9.9% increase in risk of fracture (odds ratio [OR]=1.099; 95% confidence interval [CI] 1.067-1.133; p=8.793× 10-10 ) and a 0.080 SD decrease of estimated bone mineral density (95% CI -0.106-(-0.054); p=2.322 × 10-9 ). We also found that BMI was causally associated with eBMD (beta=0.129, 95% CI 0.065-0.194; p=8.113× 10-5 ) but not associated with fracture. The WHR adjusted for BMI, HC adjusted for BMI, and WC adjusted for BMI were not found to be related to fracture occurrence or eBMD. In conclusion, the present study provided genetic evidence for certain causal relationships between anthropometric measurements and bone mineral density or fracture risk. © 2021 American Society for Bone and Mineral Research (ASBMR).

Genetic variants associated with rotator cuff tearing utilizing multiple population-based genetic resources

The etiology of rotator cuff tearing is likely multifactorial, including a potential genetic predisposition. The purpose of the study was to identify genetic variants associated with rotator cuff tearing utilizing the UK Biobank (UKB) cohort, confirm variants using a separate genetic database, and evaluate tissue expression of genes with associated variants following rotator cuff tearing using RNA sequencing. Genome-wide association study (GWAS): A GWAS was performed using data from UKB with 5701 cases of rotator cuff injury. RNA sequencing analyses: rotator cuff biopsies were obtained from 24 patients with full-thickness rotator cuff tears who underwent arthroscopic rotator cuff repair (cases) and 9 patients who underwent open reduction internal fixation for a proximal humerus fracture (controls). Total RNA was extracted and differential gene expression was measured by RNAseq for genes with variants associated with rotator cuff tearing. The results of the UKB GWAS identified 3 loci that reached genome-wide statistical significance: 2 loci on chromosome 7 in GLCCI1 (rs4725069; P = 5.0E-09) and THSD7A (rs575224171; P = 5.3E-09), and 1 locus on chromosome 2 in ZNF804A (rs775583810; P = 3.9E-09). The association with rotator cuff injury of the GLCCI1 single-nucleotide polymorphism (SNP; rs4725069) was confirmed in the Kaiser Permanente Research Bank cohort (P = .008). Twenty previously reported SNPs in 12 genes were evaluated using summary statistics from the UKB GWAS, which confirmed 3 SNPs in TNC with rotator cuff injury (rs1138545, rs72758637, and rs7021589; all P < .0024). Of 17 genes with variants associated with rotator cuff injury (14 previously from literature plus 3 new genes from current UKB GWAS), TIMP2, Col5A1, TGFBR1, and TNC were upregulated (P < .001 for all) and THSD7A was downregulated (P = .005) in tears vs. controls in the RNA sequencing data set. The UKB GWAS has identified 3 novel loci associated with rotator cuff tearing (ZNF804A, GLCCI1, THSD7A). Expression of the THSD7A gene was significantly downregulated in rotator cuff tears vs. controls supporting a potential functional role. Three previously reported SNPs in the TNC gene were validated in the UKB GWAS, supporting a role for this gene in rotator cuff tearing. Finally, TIMP2, Col5A1, TGFBR1, and TNC genes were found to have significantly upregulated tissue expression in cases vs. controls supporting a biologic role in tearing for these genes.

Assessing the genetic relationships between osteoarthritis and human plasma proteins: a large scale genetic correlation scan.

BackgroundOsteoarthritis (OA) is a multifactorial complex disease. The impact of plasma proteins on OA remains elusive now.MethodsThe UK Biobank genome-wide association study data of OA was used here. Genome-wide SNP genotyping was performed using the Affymetrix UK BiLEVE Axiom or UK Biobank Axiom array. Equally, the GWAS summary data of 3,622 plasma proteins was derived from a recently published study. Consequently, linkage disequilibrium score regression (LD score regression) analysis was performed to evaluate the genetic correlation between each plasma protein and different sites of OA.ResultsSeveral suggestive plasma proteins were identified for OA. For hand OA, evidence of genetic correlation was observed for inter-alpha-trypsin inhibitor heavy chain H1 (coefficient =−0.3854, P value =0.0198), multiple inositol polyphosphate phosphatase 1 (coefficient =−1.1721, P value =0.0303). For hip OA, 7 suggestive genetic correlation signals were observed, such as Transmembrane glycoprotein NMB (coefficient =0.6944, P value =0.0098), Endothelial cell-specific molecule 1 (coefficient =0.6337, P value =0.03). For Knee OA, 12 suggestive genetic correlation signals were identified, including Elafin (coefficient =−0.5562, P value =0.0092), Interleukin-16 (coefficient =0.3949, P value =0.0435).ConclusionsWe investigated the genetic correlations between plasma proteins and different sites of OA in a systematic way. Our results provide novel evidence that OA is a heterogeneous disease.

Polygenic Risk Scores and Physical Activity

Polygenic risk scores (PRS) summarize genome-wide genotype data into a single variable that produces an individual-level risk score for genetic liability. PRS has been used for prediction of chronic diseases and some risk factors. As PRS has been studied less for physical activity (PA), we constructed PRS for PA and studied how much variation in PA can be explained by this PRS in independent population samples. We calculated PRS for self-reported and objectively measured PA using UK Biobank genome-wide association study summary statistics, and analyzed how much of the variation in self-reported (MET-hours per day) and measured (steps and moderate-to-vigorous PA minutes per day) PA could be accounted for by the PRS in the Finnish Twin Cohorts (FTC; N = 759-11,528) and the Northern Finland Birth Cohort 1966 (NFBC1966; N = 3263-4061). Objective measurement of PA was done with wrist-worn accelerometer in UK Biobank and NFBC1966 studies, and with hip-worn accelerometer in the FTC. The PRS accounted from 0.07% to 1.44% of the variation (R) in the self-reported and objectively measured PA volumes (P value range = 0.023 to <0.0001) in the FTC and NFBC1966. For both self-reported and objectively measured PA, individuals in the highest PRS deciles had significantly (11%-28%) higher PA volumes compared with the lowest PRS deciles (P value range = 0.017 to <0.0001). PA is a multifactorial phenotype, and the PRS constructed based on UK Biobank results accounted for statistically significant but overall small proportion of the variation in PA in the Finnish cohorts. Using identical methods to assess PA and including less common and rare variants in the construction of PRS may increase the proportion of PA explained by the PRS.

Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits.

Volumetric variations of human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank (UKB) sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding significance threshold of 4.9 × 10−10, adjusted for testing multiple phenotypes. Gene-based association study found 157 associated genes (124 new), and functional gene mapping analysis linked 146 additional genes. Many of the discovered genetic variants and genes have previously been implicated in cognitive and mental health traits. Using genome-wide polygenic risk score prediction, more than 6% of phenotypic variance (P = 3.13 × 10−24) in four other independent studies could be explained by the UKB GWAS results. In conclusion, our study identifies many new genetic associations at variant, locus and gene levels and advances our understanding of the pleiotropy and genetic co-architecture between brain volumes and other traits.

Integrating transcriptome-wide study and mRNA expression profiles yields novel insights into the biological mechanism of chondropathies

BackgroundChondropathies are a group of cartilage diseases, which share some common pathogenetic features. The etiology of chondropathies is still largely obscure now.MethodsA transcriptome-wide association study (TWAS) was performed using the UK Biobank genome-wide association study (GWAS) data of chondropathies (including 1314 chondropathy patients and 450,950 controls) with gene expression references of muscle skeleton (MS) and peripheral blood (YBL). The candidate genes identified by TWAS were further compared with three gene expression profiles of osteoarthritis (OA), cartilage tumor (CT), and spinal disc herniation (SDH), to confirm the functional relevance between the chondropathies and the candidate genes identified by TWAS. Functional mapping and annotation (FUMA) was used for the gene ontology enrichment analyses. Immunohistochemistry (IHC) was conducted to validate the accuracy of integrative analysis results.ResultsIntegrating TWAS and mRNA expression profiles detected 84 candidate genes for knee OA, such as DDX20 (PTWAS YBL = 1.79 × 10− 3, fold change (FC) = 2.69), 10 candidate genes for CT, such as SRGN (PTWAS YBL = 1.46 × 10− 3, FC = 3.36), and 4 candidate genes for SDH, such as SUPV3L1 (PTWAS YBL = 3.59 × 10− 3, FC = 3.22). Gene set enrichment analysis detected 73 GO terms for knee OA, 3 GO terms for CT, and 1 GO term for SDH, such as mitochondrial protein complex (P = 7.31 × 10− 5) for knee OA, cytokine for CT (P = 1.13 × 10− 4), and ion binding for SDH (P = 3.55 × 10− 4). IHC confirmed that the protein expression level of DDX20 was significantly different between knee OA cartilage and healthy control cartilage (P = 0.0358).ConclusionsMultiple candidate genes and GO terms were detected for chondropathies. Our findings may provide a novel insight in the molecular mechanisms of chondropathies.