美国斯坦福大学Manuel A. Rivas、Yosuke Tanigawa和Nasa Sinnott-Armstrong研究组合作，揭示了英国生物库中35种血液和尿液生物标志物的遗传学。这一研究成果发表在2021年1月18日的《自然-遗传学》上。

他们评估了英国生物库（n = 363,228个人）中35个血液和尿液实验室测量值的遗传基础。他们确定了与至少一个性状相关的1,857个基因座，其中包含3,374个精细映射的关联以及其他大范围改变蛋白质的作用，人类白细胞抗原（HLA）和拷贝数变异（CNV）关联的集合（> >0.1 s.d.）。

通过孟德尔随机（MR）分析，他们发现了51种因果关系，包括先前已知的尿酸对痛风和半胱氨酸蛋白酶抑制剂C的激动作用。最后，他们为每种生物标记物开发多基因风险评分（PRS），并同时使用35种PRS建立疾病的“多PRS”模型，从而改善了慢性肾脏疾病、2型糖尿病、痛风和酒精性肝硬化的遗传风险分层（在独立数据集中，FinnGen； n = 135,500）。

总之，他们的结果描述了生物标志物的遗传基础及其对疾病的因果影响，并改善了常见疾病的遗传风险分层。

附：英文原文

Title: Genetics of 35 blood and urine biomarkers in the UK Biobank

Author: Nasa Sinnott-Armstrong, Yosuke Tanigawa, David Amar, Nina Mars, Christian Benner, Matthew Aguirre, Guhan Ram Venkataraman, Michael Wainberg, Hanna M. Ollila, Tuomo Kiiskinen, Aki S. Havulinna, James P. Pirruccello, Junyang Qian, Anna Shcherbina, Fatima Rodriguez, Themistocles L. Assimes, Vineeta Agarwala, Robert Tibshirani, Trevor Hastie, Samuli Ripatti, Jonathan K. Pritchard, Mark J. Daly, Manuel A. Rivas

Issue&Volume: 2021-01-18

Abstract: Clinical laboratory tests are a critical component of the continuum of care. We evaluate the genetic basis of 35 blood and urine laboratory measurements in the UK Biobank (n=363,228 individuals). We identify 1,857 loci associated with at least one trait, containing 3,374 fine-mapped associations and additional sets of large-effect (>0.1s.d.) protein-altering, human leukocyte antigen (HLA) and copy number variant (CNV) associations. Through Mendelian randomization (MR) analysis, we discover 51 causal relationships, including previously known agonistic effects of urate on gout and cystatin C on stroke. Finally, we develop polygenic risk scores (PRSs) for each biomarker and build ‘multi-PRS’ models for diseases using 35 PRSs simultaneously, which improved chronic kidney disease, type 2 diabetes, gout and alcoholic cirrhosis genetic risk stratification in an independent dataset (FinnGen; n=135,500) relative to single-disease PRSs. Together, our results delineate the genetic basis of biomarkers and their causal influences on diseases and improve genetic risk stratification for common diseases.

DOI: 10.1038/s41588-020-00757-z

Source: https://www.nature.com/articles/s41588-020-00757-z