Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the ...need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (<ext-link ext-link-type="uri" xlink:href="http://www.mrbase.org">http://www.mrbase.org</ext-link>): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma ...protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.
Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of ...therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer's Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer's disease, 6 genes with Parkinson's disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.
Objective
To examine relationships between known osteoarthritis (OA) susceptibility loci and hip shape in a population‐based cohort of perimenopausal women in order to investigate whether hip shape ...contributes to OA development.
Methods
Hip shape was measured, using statistical shape modeling, on dual x‐ray absorptiometry scans of the hip from mothers in the Avon Longitudinal Study of Parents and Children (ALSPAC). The proximal femur and superior acetabulum were outlined, and independent hip shape modes were generated. In a subregional model, points were restricted to the acetabulum and superior femoral head. Associations between 11 OA‐related single‐nucleotide polymorphisms, identified by literature search, and shape modes were analyzed in a multivariate canonical correlation analysis.
Results
A total of 3,111 women (mean age 48 years) had genetic and hip shape data. The KLHDC5/PTHLH rs10492367 OA risk allele was associated with a wider upper femur in the whole shape model (P = 1 × 10−5). The DOT1L rs12982744 OA risk allele was associated with reduced superior joint space in the subregional shape model (P = 2 × 10−3). The COL11A1 rs4907986 OA risk allele was associated with lateral displacement of the femoral head relative to the acetabulum in the subregional shape model (P = 5 × 10−4). Regional association plots identified an additional COL11A1 locus in moderate linkage disequilibrium with rs4907986, which was more strongly associated with hip shape (rs10047217; P = 3 × 10−6). Colocalization analysis indicated sharing of genetic signals for hip shape and hip OA for the KLHDC5/PTHLH and COL11A1 loci.
Conclusion
Hip OA susceptibility loci were associated with shape in this study, suggesting that these loci (and potentially yet‐to‐be‐identified hip OA loci) could contribute to hip OA in later life via perturbing biologic pathways that mediate morphology development.
Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the ...BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P < 1.25 × 10−10, 117 cis‐pQTLs and 59 trans‐pQTLs). Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs. pQTLs for CSF and plasma proteins were overall correlated, but CSF‐specific pQTLs were also observed. Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP‐10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease. CSF levels of GRN, MMP‐10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively. These findings point to pathways to be explored for novel therapies. The novel finding that ventricular volume confounded pQTLs has implications for design of future studies of the genetic regulation of the CSF proteome.
Synopsis
The genetic regulation of cerebrospinal fluid (CSF) proteins can be explored to increase the understanding of brain disease mechanisms. This study explored protein quantitative trait loci (pQTLs) for 398 CSF proteins analyzed by highly specific protein extension assays in a large human population.
176 significant CSF pQTLs were identified, most of which were novel and had not been described previously for CSF proteins.
When combining the results with external GWAS data sources in Mendelian randomization experiments, proteins were identified with potential causal roles in neurological diseases, including Alzheimer's disease, Parkinson's disease, and others.
When combining the CSF pQTL results with brain magnetic resonance imaging (MRI), ventricle volume was identified as a possible confounder for some of the pQTLs.
The genetic regulation of cerebrospinal fluid (CSF) proteins can be explored to increase the understanding of brain disease mechanisms. This study explored protein quantitative trait loci (pQTLs) for 398 CSF proteins analyzed by highly specific protein extension assays in a large human population.
Bone accrual impacts lifelong skeletal health, but genetic discovery has been primarily limited to cross-sectional study designs and hampered by uncertainty about target effector genes. Here, we ...capture this dynamic phenotype by modeling longitudinal bone accrual across 11,000 bone scans in a cohort of healthy children and adolescents, followed by genome-wide association studies (GWAS) and variant-to-gene mapping with functional follow-up.
We identify 40 loci, 35 not previously reported, with various degrees of supportive evidence, half residing in topological associated domains harboring known bone genes. Of several loci potentially associated with later-life fracture risk, a candidate SNP lookup provides the most compelling evidence for rs11195210 (SMC3). Variant-to-gene mapping combining ATAC-seq to assay open chromatin with high-resolution promoter-focused Capture C identifies contacts between GWAS loci and nearby gene promoters. siRNA knockdown of gene expression supports the putative effector gene at three specific loci in two osteoblast cell models. Finally, using CRISPR-Cas9 genome editing, we confirm that the immediate genomic region harboring the putative causal SNP influences PRPF38A expression, a location which is predicted to coincide with a set of binding sites for relevant transcription factors.
Using a new longitudinal approach, we expand the number of genetic loci putatively associated with pediatric bone gain. Functional follow-up in appropriate cell models finds novel candidate genes impacting bone accrual. Our data also raise the possibility that the cell fate decision between osteogenic and adipogenic lineages is important in normal bone accrual.
Recent omic studies prioritised several drug targets associated with coronavirus disease 2019 (COVID-19) severity. However, little evidence was provided to systematically estimate the effect of drug ...targets on COVID-19 severity in multiple ancestries.
In this study, we applied Mendelian randomization (MR) and colocalization approaches to understand the putative causal effects of 16,059 transcripts and 1608 proteins on COVID-19 severity in European and effects of 610 proteins on COVID-19 severity in African ancestry. We further integrated genetics, clinical and literature evidence to prioritise drug targets. Additional sensitivity analyses including multi-trait colocalization and phenome-wide MR were conducted to test for MR assumptions.
MR and colocalization prioritized four protein targets, FCRL3, ICAM5, ENTPD5 and OAS1 that showed effect on COVID-19 severity in European ancestry. One protein target, SERPINA1 showed a stronger effect in African ancestry but much weaker effect in European ancestry (odds ratio OR in Africans=0.369, 95%CI=0.203 to 0.668, P = 9.96 × 10
; OR in Europeans=1.021, 95%CI=0.901 to 1.157, P = 0.745), which suggested that increased level of SERPINA1 will reduce COVID-19 risk in African ancestry. One protein, ICAM1 showed suggestive effect on COVID-19 severity in both ancestries (OR in Europeans=1.152, 95%CI=1.063 to 1.249, P = 5.94 × 10
; OR in Africans=1.481, 95%CI=1.008 to 2.176; P = 0.045). The OAS1, SERPINA1 and ICAM1 effects were replicated using updated COVID-19 severity data in the two ancestries respectively, where alternative splicing events in OAS1 and ICAM1 also showed marginal effects on COVID-19 severity in Europeans. The phenome-wide MR of the prioritised targets on 622 complex traits provided information on potential beneficial effects on other diseases and suggested little evidence of adverse effects on major complications.
Our study identified six proteins as showing putative causal effects on COVID-19 severity. OAS1 and SERPINA1 were targets of existing drugs in trials as potential COVID-19 treatments. ICAM1, ICAM5 and FCRL3 are related to the immune system. Across the six targets, OAS1 has no reliable instrument in African ancestry; SERPINA1, FCRL3, ICAM5 and ENTPD5 showed a different level of putative causal evidence in European and African ancestries, which highlights the importance of more powerful ancestry-specific GWAS and value of multi-ancestry MR in informing the effects of drug targets on COVID-19 across different populations. This study provides a first step towards clinical investigation of beneficial and adverse effects of COVID-19 drug targets.
No.
Y-chromosomal (Y-DNA) haplogroups are more widely used in population genetics than in genetic epidemiology, although associations between Y-DNA haplogroups and several traits, including ...cardiometabolic traits, have been reported. In apparently homogeneous populations defined by principal component analyses, there is still Y-DNA haplogroup variation which will result from population history. Therefore, hidden stratification and/or differential phenotypic effects by Y-DNA haplogroups could exist. To test this, we hypothesised that stratifying individuals according to their Y-DNA haplogroups before testing for associations between autosomal single nucleotide polymorphisms (SNPs) and phenotypes will yield difference in association. For proof of concept, we derived Y-DNA haplogroups from 6537 males from two epidemiological cohorts, Avon Longitudinal Study of Parents and Children (ALSPAC) (
= 5080; 816 Y-DNA SNPs) and the 1958 Birth Cohort (
= 1457; 1849 Y-DNA SNPs), and studied the robust associations between 32 SNPs and body mass index (BMI), including SNPs in or near Fat Mass and Obesity-associated protein (
) which yield the strongest effects. Overall, no association was replicated in both cohorts when Y-DNA haplogroups were considered and this suggests that, for BMI at least, there is little evidence of differences in phenotype or SNP association by Y-DNA structure. Further studies using other traits, phenome-wide association studies (PheWAS), other haplogroups and/or autosomal SNPs are required to test the generalisability and utility of this approach.
Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain ...datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.
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