The development of alternative medications for urate-lowering therapies is imperative for patients that are intolerant to current treatments. Despite GWAS have identified hundreds of loci associated with serum urate levels, the mechanistic understanding and discovery of drug targets remain difficult. This difficulty arises from the multiple-independent-associations challenge in the genomic studies of complex diseases as hyperuricemia. Here, we introduced a locus-specific stratification (LSS) and gene regulatory prioritization score (GRPS) approach to address the multiple-independent-associations challenge. By integrating with kidney single-cell chromatin accessibility and gene expression, LSS identified functional SNPs, regulatory elements, and genes for 118 loci. The interpretability was increased by 1.4 to 5.2 fold. GRPS prioritized genes and nominated under-explored drug target with high confidence, which was validated using CRISPR activation and phenotypic assays. Our findings not only identified top causal genes but also proposed the regulatory mechanisms for pathogenic genes, expanding our knowledge of the genetic contribution in complex diseases as hyperuricemia.

中文翻译：

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位点特异性分层和优先顺序揭示了高尿酸血症的高风险基因

对于对当前治疗不耐受的患者来说，开发降尿酸疗法的替代药物势在必行。尽管 GWAS 已经识别出数百个与血清尿酸水平相关的位点，但药物靶点的机制理解和发现仍然很困难。这一困难源于高尿酸血症等复杂疾病的基因组研究中的多重独立关联挑战。在这里，我们引入了位点特异性分层（LSS）和基因调控优先级评分（GRPS）方法来解决多重独立关联的挑战。通过与肾脏单细胞染色质可及性和基因表达相结合，LSS 鉴定了 118 个位点的功能性 SNP、调控元件和基因。可解释性提高了 1.4 至 5.2 倍。GRPS 对基因进行优先排序，并以高置信度提名尚未探索的药物靶点，并使用 CRISPR 激活和表型测定进行了验证。我们的研究结果不仅确定了主要致病基因，还提出了致病基因的调控机制，扩大了我们对高尿酸血症等复杂疾病的遗传贡献的认识。