Meta-analysis fine-mapping is often miscalibrated at single-variant resolution

Funding Information: We acknowledge all the participants and researchers of the 23 biobanks that have contributed to the GBMI. Biobank-specific acknowledgments are included in the Data S3 . We thank H. Huang, A.R. Martin, B.M. Neale, Y. Okada, K. Tsuo, J.C. Ulirsch, Y. Wang, and all the members of Finucane and Daly labs for their helpful feedback. M.K. was supported by a Nakajima Foundation Fellowship and the Masason Foundation . H.K.F. was funded by NIH grant DP5 OD024582 . Publisher Copyright: © 2022 The Author(s)Meta-analysis is pervasively used to combine multiple genome-wide association studies (GWASs). Fine-mapping of meta-analysis studies is typically performed as in a single-cohort study. Here, we first demonstrate that heterogeneity (e.g., of sample size, phenotyping, imputation) hurts calibration of meta-analysis fine-mapping. We propose a summary statistics-based quality-control (QC) method, suspicious loci analysis of meta-analysis summary statistics (SLALOM), that identifies suspicious loci for meta-analysis fine-mapping by detecting outliers in association statistics. We validate SLALOM in simulations and the GWAS Catalog. Applying SLALOM to 14 meta-analyses from the Global Biobank Meta-analysis Initiative (GBMI), we find that 67% of loci show suspicious patterns that call into question fine-mapping accuracy. These predicted suspicious loci are significantly depleted for having nonsynonymous variants as lead variant (2.7×; Fisher's exact p = 7.3 × 10−4). We find limited evidence of fine-mapping improvement in the GBMI meta-analyses compared with individual biobanks. We urge extreme caution when interpreting fine-mapping results from meta-analysis of heterogeneous cohorts.Peer reviewe

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics

Publisher Copyright: © 2022 The Author(s)The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor—the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.Peer reviewe

An expanded analysis framework for multivariate GWAS connects inflammatory biomarkers to functional variants and disease

Multivariate methods are known to increase the statistical power to detect associations in the case of shared genetic basis between phenotypes. They have, however, lacked essential analytic tools to follow-up and understand the biology underlying these associations. We developed a novel computational workflow for multivariate GWAS follow-up analyses, including fine-mapping and identification of the subset of traits driving associations (driver traits). Many follow-up tools require univariate regression coefficients which are lacking from multivariate results. Our method overcomes this problem by using Canonical Correlation Analysis to turn each multivariate association into its optimal univariate Linear Combination Phenotype (LCP). This enables an LCP-GWAS, which in turn generates the statistics required for follow-up analyses. We implemented our method on 12 highly correlated inflammatory biomarkers in a Finnish population-based study. Altogether, we identified 11 associations, four of which (F5, ABO, C1orf140 and PDGFRB) were not detected by biomarker-specific analyses. Fine-mapping identified 19 signals within the 11 loci and driver trait analysis determined the traits contributing to the associations. A phenome-wide association study on the 19 representative variants from the signals in 176,899 individuals from the FinnGen study revealed 53 disease associations (p <1 x 10(-4)). Several reported pQTLs in the 11 loci provided orthogonal evidence for the biologically relevant functions of the representative variants. Our novel multivariate analysis workflow provides a powerful addition to standard univariate GWAS analyses by enabling multivariate GWAS follow-up and thus promoting the advancement of powerful multivariate methods in genomics.Peer reviewe

Global Biobank Meta-analysis Initiative : Powering genetic discovery across human disease

Funding Information: The work of the contributing biobanks was supported by numerous grants from governmental and charitable bodies. Biobank-specific acknowledgments and more detailed acknowledgments are included in Data S2. Initiative management, S.B.C. J.C. N.J.C. M.J.D. E.E.K. A.R.M. B.M.N. Y.O. A.V.P. D.A.v.H. R.G.W. C.J.W. W.Z. and S.Z.; individual biobank analysis, A.B. Y.B. B.M.B. C.D.B. S.C. T.-T.C. K.C. S.M.D. M.D. G.H.d.B. Y.D. N.J.D. M.-J.F. Y.-C.A.F. S.F. V.L.F. L.G.F. E.R.G. T.R.G. D.H.G. C.R.G. G.G.-A. S.E.G. L.A.G. C.H. J.B.H. W.E.H. H.H. K.H. N.I. A.I. R.J. M. Kurki, J.K. N.K. E.E.K. J.T.K. M. Kanai, T.L. K.L. M.H.L. S.L. K.L. Y.-F.L. V.L.F. R.J.F.L. E.A.L.-M. A.R.-M. S.M.-G. R.M. R.E.M. H.C.M. A.R.M. Y.M. H.M. S.E.M. I.Y.M. B.M. S.M. K.N. S.N. M.A.N.-A. K.N. Y.O. P.P. A.L.-P. A.P. B.P. S.P. M.H.P. D.J.R. N.R. M.D.R. A.R. C.S. S.S. S.S.S. J.A.S. P.S. I.S. T.T. R.T. K.T. J.U. D.A.v.H. B.V. M.V. Y.V. J.M.V. R.G.W. Y.W. S.J.W. B.N.W. K.-H.H.W. M.Z. X.Z. and S.Z.; individual biobank management, N.A. A.A.T. K.M.A.-D. P.A. K.C.B. M. Boehnke, M. Boezen, C.D.B. A.C. Z.C. C.-Y.C. J.C. N.J.C. S.M.D. S.F. Y.-C.A.F. S.F. E.F. T.G. C.R.G. C.J.G. Y.G. H.H. K.A.H. K.H. S.I.I. N.M.J. N.K. E.E.K. J.T.K. C.L. M.H.L. M.T.M.L. L.L. K.L. Y.-F.L. R.J.F.L. J.L. S.M. Y.M. K.M. I.Y.M. Y.O. C.M.O. A.V.P. B.P. D.J.P. D.J.R. M.D.R. S.S. J.W.S. H.S. K.S. T.T. U.T. R.C.T. D.A.v.H. M.V. R.G.W. D.C.W. C.W. J.W. M.Z. X.Z. and S.Z.; study design and interpretation of results, A.B. M. Boehnke, M. Boezen, B.M.B. T.-T.C. C.-Y.C. M.J.D. G.D.S. N.J.D. S.F. M.-J.F. H.K.F. E.R.G. A.G. T.G. J.B.H. J.H. K.H. R.J. M.K. E.E.K. T.K. C.M.L. V.L.F. E.A.L.-M. A.R.M. S.N. B.M.N. C.M.O. J.J.P. B.P. N.R. H.R. J.A.S. I.S. K.T. D.A.v.H. R.G.W. Y.W. D.C.W. S.J.W. C.J.W. B.N.W. J.W. K.-H.H.W. M.Z. H.Z. J.Z. W.Z. X.Z. and S.Z.; drafted and edited the paper, A.B. M. Boehnke, M. Boezen, M.J.D. G.H.d.B. N.J.D. T.R.G. J.B.H. N.I. N.M.J. M.K. V.L.F. S.M. A.R.M. H.M. S.N. B.M.N. C.M.O. B.P. H.R. C.S. J.A.S. J.W.S. K.T. Y.W. D.C.W. C.J.W. K.-H.H.W. H.Z. J.Z. W.Z. and S.Z.; primary meta-analysis and quality control, M.J.D. H.K.F. M. Kanai, J.K. J.T.K. M. Kurki, M.M. B.M.N. C.J.W. K.-H.H.W. and W.Z.; drug discovery: S.N. T.K. K.-H.H.W. W.Z. and Y.O.; fine mapping, M. Kanai, W.Z. M.J.D. and H.K.F.; polygenic risk score, Y.W. S.N. E.A.L.-M. S.K. K.T. K.L. M. Kanai, W.Z. K.W. M.-J.F. L.B. P.A. P.D. V.L.F. R.M. Y.M. B.B. S.S. J.U. E.R.G. N.J.C. I.S. Y.O. A.R.M. and J.B.H.; proteome-wide Mendelian randomization, H.Z. H.R. A.B. G.H. G.D.S. B.M.B. W.Z. B.M.N. T.R.G. and J.Z.; transcriptome-wide association study, A.B. J.B.H. W.Z. J.Z. M. Kanai, B.P. E.R.G. and N.J.C.; asthma, K.T. W.Z. Y.W. M. Kanai, S.N. Y.O. B.M.N. M.J.D. and A.R.M.; heart failure, K.-H.H.W. N.J.D. B.N.W. I.S. S.E.G. J.B.H. N.J.C. M.P. R.J.F.L. M.J.D. B.M.N. W.Z. W.E.H. and C.J.W.; idiopathic pulmonary fibrosis, J.J.P. W.Z. M.J.D. J.T.K. N.J.C. and J.B.H.; primary open-angle glaucoma, V.L.F. A.B. W.Z. Y.W. K.L. M. Kanai, E.A.L.-M. P.S. R.T. X.Z. S.N. S.S. Y.O. N.I. S.M. H.S. I.S. C.W. A.R.M. E.R.G. N.M.J. N.J.C. and J.B.H.; stroke, I.S. K.-H.H.W. W.H. B.N.W. W.Z. J.E.H. A.P. B.B. A.H.S. M.E.G. R.G.W. K.H. C.K. S.Z. M.J.D. B.M.N. and C.J.W.; venous thromboembolism, B.N.W. I.S. K.-H.H.W. B.B. V.L.F. K.T. M.D. B.N. W.Z. J.A.S. and C.J.W. All authors reviewed the manuscript. M.J.D. is a founder of Maze Therapeutics. B.M.N. is a member of the scientific advisory board at Deep Genomics and a consultant for Camp4 Therapeutics, Takeda Pharmaceutical, and Biogen. The spouse of C.J.W. works at Regeneron Pharmaceuticals. C.-Y.C. is employed by Biogen. C.R.G. owns stock in 23andMe, Inc. T.R.G. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. E.E.K. has received speaker fees from Regeneron, Illumina, and 23andMe and is a member of the advisory board for Galateo Bio. R.E.M. has received speaker fees from Illumina and is a scientific advisor to the Epigenetic Clock Development Foundation. G.D.S. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. K.S. and U.T. are employed by deCODE Genetics/Amgen, Inc. J.Z. has received research funding from various pharmaceutical companies to support the application of Mendelian randomization to drug target prioritization. S.M. is a co-founder of and holds stock in Seonix Bio. Publisher Copyright: © 2022Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.Peer reviewe

Global Biobank Meta-analysis Initiative:Powering genetic discovery across human disease

Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)—a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.</p

Leveraging global multi-ancestry meta-analysis in the study of idiopathic pulmonary fibrosis genetics

The research of rare and devastating orphan diseases, such as idiopathic pulmonary fibrosis (IPF) has been limited by the rarity of the disease itself. The prognosis is poor—the prevalence of IPF is only approximately four times the incidence, limiting the recruitment of patients to trials and studies of the underlying biology. Global biobanking efforts can dramatically alter the future of IPF research. We describe a large-scale meta-analysis of IPF, with 8,492 patients and 1,355,819 population controls from 13 biobanks around the globe. Finally, we combine this meta-analysis with the largest available meta-analysis of IPF, reaching 11,160 patients and 1,364,410 population controls. We identify seven novel genome-wide significant loci, only one of which would have been identified if the analysis had been limited to European ancestry individuals. We observe notable pleiotropy across IPF susceptibility and severe COVID-19 infection and note an unexplained sex-heterogeneity effect at the strongest IPF locus MUC5B.publishedVersionPeer reviewe

KIF15 missense variant is associated with the early onset of idiopathic pulmonary fibrosis

Abstract Background Idiopathic pulmonary fibrosis (IPF) has an unknown aetiology and limited treatment options. A recent meta-analysis identified three novel causal variants in the TERT, SPDL1, and KIF15 genes. This observational study aimed to investigate whether the aforementioned variants cause clinical phenotypes in a well-characterised IPF cohort. Methods The study consisted of 138 patients with IPF who were diagnosed and treated at the Helsinki University Hospital and genotyped in the FinnGen FinnIPF study. Data on > 25 clinical parameters were collected by two pulmonologists who were blinded to the genetic data for patients with TERT loss of function and missense variants, SPDL1 and KIF15 missense variants, and a MUC5B variant commonly present in patients with IPF, or no variants were separately analysed. Results The KIF15 missense variant is associated with the early onset of the disease, leading to progression to early-age transplantation or death. In patients with the KIF15 variant, the median age at diagnosis was 54.0 years (36.5–69.5 years) compared with 72.0 years (65.8–75.3 years) in the other patients (P = 0.023). The proportion of KIF15 variant carriers was 9- or 3.6-fold higher in patients aged < 55 or 65 years, respectively. The variants for TERT and MUC5B had similar effects on the patient’s clinical course, as previously described. No distinct phenotypes were observed in patients with the SPDL1 variant. Conclusions Our study indicated the potential of KIF15 to be used in the genetic diagnostics of IPF. Further studies are needed to elucidate the biological mechanisms of KIF15 in IPF

KIF15 missense variant is associated with the early onset of idiopathic pulmonary fibrosis

Abstract Background: Idiopathic pulmonary fibrosis (IPF) has an unknown aetiology and limited treatment options. A recent meta-analysis identified three novel causal variants in the TERT, SPDL1, and KIF15 genes. This observational study aimed to investigate whether the aforementioned variants cause clinical phenotypes in a well-characterised IPF cohort. Methods: The study consisted of 138 patients with IPF who were diagnosed and treated at the Helsinki University Hospital and genotyped in the FinnGen FinnIPF study. Data on &gt; 25 clinical parameters were collected by two pulmonologists who were blinded to the genetic data for patients with TERT loss of function and missense variants, SPDL1 and KIF15 missense variants, and a MUC5B variant commonly present in patients with IPF, or no variants were separately analysed. Results: The KIF15 missense variant is associated with the early onset of the disease, leading to progression to early-age transplantation or death. In patients with the KIF15 variant, the median age at diagnosis was 54.0 years (36.5–69.5 years) compared with 72.0 years (65.8–75.3 years) in the other patients (P = 0.023). The proportion of KIF15 variant carriers was 9- or 3.6-fold higher in patients aged &lt; 55 or 65 years, respectively. The variants for TERT and MUC5B had similar effects on the patient’s clinical course, as previously described. No distinct phenotypes were observed in patients with the SPDL1 variant. Conclusions: Our study indicated the potential of KIF15 to be used in the genetic diagnostics of IPF. Further studies are needed to elucidate the biological mechanisms of KIF15 in IPF

How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior : an Observational Follow-up Study

Background: Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear. Methods: We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior. Results: When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently. Conclusions: Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention