Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

Yin, Xianyong; Chan, Lap Sum; Bose, Debraj; Jackson, Anne; VandeHaar, Peter; Locke, Adam E.; Fuchsberger, Christian; Stringham, Heather M.; Welch, Ryan; Yu, Ketian; Silva, Lilian Fernandes; Service, Susan; Zhang, Daiwei; Hector, Emily C.; Young, Erica; Ganel, Liron; Das, Indraniel; Abel, Haley J.; Erdos, Michael R.; Bonnycastle, Lori L.; Kuusisto, Johanna; Stitziel, Nathan O.; Hall, Ira M.; Wagner, Gregory R.; Kang, Jian; Morrison, Jean; Burant, Charles F.; Collins, Francis S.; Ripatti, Samuli; Palotie, Aarno; Freimer, Nelson A.; Mohlke, Karen L.; Scott, Laura J.; Wen, Xiaoquan; Fauman, Eric B.; Laakso, Markku; Boehnke, Michael

doi:10.1038/s41467-022-29143-5

Cited by 76 publications

(118 citation statements)

References 86 publications

(93 reference statements)

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“…Even though previous metabolite GWAS have benefited from a larger sample size or more metabolites tested, our study queries the entire coding space, which, due to the high cost of sequencing is infeasible for many mGWAS studies, who often use imputed genotype data [ 5 , 6 , 7 , 8 ]. Despite the smaller size of our panel compared to others, the Biocrates kit used here measures some metabolites missed by other common platforms, such as Metabolon [ 5 , 6 , 8 , 29 , 30 ] or Nightingale [ 6 , 11 ]. For example, Nightingale does not measure the amino acids tryptophan, arginine, or aspartate, and neither Metabolon nor Nightingale measures the biogenic amines histamine, spermine, or putrescine, or the acylcarnitines decadienylcarnitine or dodecanedioylcarnitine.…”

Section: Discussionmentioning

confidence: 99%

Whole Exome Sequencing Enhanced Imputation Identifies 85 Metabolite Associations in the Alpine CHRIS Cohort

et al. 2022

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Metabolites are intermediates or end products of biochemical processes involved in both health and disease. Here, we take advantage of the well-characterized Cooperative Health Research in South Tyrol (CHRIS) study to perform an exome-wide association study (ExWAS) on absolute concentrations of 175 metabolites in 3294 individuals. To increase power, we imputed the identified variants into an additional 2211 genotyped individuals of CHRIS. In the resulting dataset of 5505 individuals, we identified 85 single-variant genetic associations, of which 39 have not been reported previously. Fifteen associations emerged at ten variants with >5-fold enrichment in CHRIS compared to non-Finnish Europeans reported in the gnomAD database. For example, the CHRIS-enriched ETFDH stop gain variant p.Trp286Ter (rs1235904433-hexanoylcarnitine) and the MCCC2 stop lost variant p.Ter564GlnextTer3 (rs751970792-carnitine) have been found in patients with glutaric acidemia type II and 3-methylcrotonylglycinuria, respectively, but the loci have not been associated with the respective metabolites in a genome-wide association study (GWAS) previously. We further identified three gene-trait associations, where multiple rare variants contribute to the signal. These results not only provide further evidence for previously described associations, but also describe novel genes and mechanisms for diseases and disease-related traits.

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Section: Discussionmentioning

confidence: 99%

Whole Exome Sequencing Enhanced Imputation Identifies 85 Metabolite Associations in the Alpine CHRIS Cohort

et al. 2022

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“…Its limitation lies in that transcript abundance is unlikely to be the most relevant molecular phenotype in revealing gene-trait relationships for all scenarios. Many authors have shown that isoform usage [47, 48, 49, 50], RNA degradation [51, 52, 53], protein abundance [54, 55, 56], and many other molecular traits [21, 57, 58] play critical roles in the etiology of different diseases. This point is also evidenced by our analyses in which eQTL data only explain a fraction of significant GWAS loci in both Sinnott-Armstrong et al .…”

Section: Discussionmentioning

confidence: 99%

“…Its limitation lies in that transcript abundance is unlikely to be the most relevant molecular phenotype in revealing gene-trait relationships for all scenarios. Many authors have shown that isoform usage [47,48,49,50], RNA degradation [51,52,53], protein abundance [54,55,56], and many other molecular traits [21,57,58] We illustrate that with proper probabilistic quantification of evidence, rigorous gene set enrichment analysis can be performed by applying INTACT-GSE. We note that utilizing the estimated enrichment parameters and gene set information can further boost the discovery of putative causal genes.…”

Section: Discussionmentioning

confidence: 99%

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Probabilistic integration of transcriptome-wide association studies and colocalization analysis prioritizes molecular pathways of complex traits

Okamoto

Yin

Luca

et al. 2022

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Transcriptome-wide association studies (TWAS) and colocalization analysis are complementary integrative genetic association approaches routinely used to identify functional units underlying complex traits in post-genome-wide association study (post-GWAS) analyses. Recent studies suggest that both approaches are individually imperfect, but joint usage can yield robust and powerful inference results. This paper introduces a new statistical framework, INTACT, to perform probabilistic integration of TWAS and colocalization evidence for implicating putative causal genes. This procedure is flexible and can work with a wide range of existing TWAS and colocalization approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly-desirable feature, we describe an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated TWAS and colocalization analysis results. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. Finally, we apply the proposed methods to the GTEx data and a variety of GWAS summary statistics derived from complex and molecular traits previously analyzed by Hukku et al. and Sinnott-Armstrong et al. We find empirical evidence that the proposed methods improve and complement existing putative gene implication methods and are advantageous in evaluating and identifying key gene sets and biological pathways.

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“…Non-targeted metabolomics profiling was performed at Metabolon, Inc. (Morrisville, NC, USA) on EDTA plasma samples obtained after an overnight fast from 8679 participants, as previously described in detail [ 51 , 52 , 53 ]. The Metabolon DiscoveryHD4 platform was applied to assay named metabolites.…”

Section: Methodsmentioning

confidence: 99%

Metabolite Signature in the Carriers of Pathogenic Genetic Variants for Cardiomyopathy: A Population-Based METSIM Study

et al. 2022

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Hypertrophic (HCM) and dilated (DCM) cardiomyopathies are among the leading causes of sudden cardiac death. We identified 38 pathogenic or likely pathogenic variant carriers for HCM in three sarcomere genes (MYH7, MYBPC3, TPMI) among 9.928 participants of the METSIM Study having whole exome sequencing data available. Eight of them had a clinical diagnosis of HCM. We also identified 20 pathogenic or likely pathogenic variant carriers for DCM in the TTN gene, and six of them had a clinical diagnosis of DCM. The aim of our study was to investigate the metabolite signature in the carriers of the pathogenic or likely pathogenic genetic variants for HCM and DCM, compared to age- and body-mass-index-matched controls. Our novel findings were that the carriers of pathogenic or likely pathogenic variants for HCM had significantly increased concentrations of bradykinin (des-arg 9), vanillactate, and dimethylglycine and decreased concentrations of polysaturated fatty acids (PUFAs) and lysophosphatidylcholines compared with the controls without HCM. Additionally, our novel findings were that the carriers of pathogenic or likely pathogenic variants for DCM had significantly decreased concentrations of 1,5-anhydrogluticol, histidine betaine, N-acetyltryptophan, and methylsuccinate and increased concentrations of trans-4-hydroxyproline compared to the controls without DCM. Our population-based study shows that the metabolite signature of the genetic variants for HCM and DCM includes several novel metabolic pathways not previously described.

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Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci

Cited by 76 publications

References 86 publications

Whole Exome Sequencing Enhanced Imputation Identifies 85 Metabolite Associations in the Alpine CHRIS Cohort

Whole Exome Sequencing Enhanced Imputation Identifies 85 Metabolite Associations in the Alpine CHRIS Cohort

Probabilistic integration of transcriptome-wide association studies and colocalization analysis prioritizes molecular pathways of complex traits

Metabolite Signature in the Carriers of Pathogenic Genetic Variants for Cardiomyopathy: A Population-Based METSIM Study

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