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蛋白质编码变异对英国生物库血液代谢物测量和临床生物标志物的影响。

Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank.

机构信息

Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.

Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Waltham, MA, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX 77030, USA.

出版信息

Am J Hum Genet. 2023 Mar 2;110(3):487-498. doi: 10.1016/j.ajhg.2023.02.002. Epub 2023 Feb 20.

Abstract

Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p < 1 × 10) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 and CREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provide insights into novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.

摘要

全基因组关联研究(GWAS)已经确定了常见和低频变体对英国生物库(UKB)中代谢血液测量的贡献。为了补充现有 GWAS 的发现,我们评估了稀有蛋白编码变体与 355 种代谢血液测量值(包括 325 种主要与脂质相关的核磁共振(NMR)衍生血液代谢物测量值(Nightingale Health Plc)和 30 种临床血液生物标志物)之间的关系,使用了 UKB 中来自四个遗传多样化血统的 412,393 个外显子序列。进行了基因水平的汇总分析,以评估代谢血液测量值的各种稀有变体结构。总共确定了 205 个不同基因的显著关联(p<1×10),这些基因与 Nightingale 血液代谢物测量值的 1,968 个显著关系和 331 个临床血液生物标志物相关。其中包括 PLIN1 和 CREB3L3 中的稀有非同义变体与脂质代谢物测量值以及 SYT7 与肌酸酐之间的关联等,这不仅可以深入了解新的生物学机制,还可以加深我们对已建立疾病机制的理解。在全基因组范围内具有显著临床生物标志物关联的研究中,40%的关联在分析同一队列中编码变异的 GWAS 时并未被检测到,这进一步强调了研究稀有变异以全面了解代谢血液测量的遗传结构的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a7/10027475/cc9735b59b94/gr1.jpg

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