Current genome-wide association studies do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype genome-wide association studies (diseases, biomarkers and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (n_total = 628,000) identified ~5,000 new loci, which improved the resolution of the genomic map of human traits. This atlas elucidated the landscape of pleiotropy as represented by the major histocompatibility complex locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (for example, allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics.

当前的全基因组关联研究尚未捕获足够的种群多样性和表型范围。为了扩展非欧洲人群的遗传关联图谱，我们在日本生物银行 ( n  = 179,000) 中进行了 220 项深度表型全基因组关联研究（疾病、生物标志物和药物使用），方法是结合既往病史和文本挖掘的电子病历。与 UK Biobank 和 FinnGen 的荟萃分析（_总计n = 628,000) 确定了约 5,000 个新位点，提高了人类特征基因组图谱的分辨率。该图谱阐明了以主要组织相容性复合基因座为代表的多效性景观，我们在该基因座上进行了 HLA 精细定位。最后，我们对表型组范围的汇总统计矩阵进行了统计分解，并确定了潜在的遗传成分，这些成分确定了当前人群中疾病分类的潜在变异和生物学机制。分解的成分使类似疾病（例如，过敏性疾病）的遗传学亚型成为可能。我们的研究提出了通过遗传学对人类疾病进行无假设重新调查的潜在途径。