The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples. We identified 3,885 associations for 1,883 proteins, including 2,885 new pQTLs, demonstrating unique genetic regulation in CSF. We identified CSF-enriched pleiotropic regions on chromosome (chr)3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron specificity and neurological development. We integrated our associations with Alzheimer’s disease (AD) through proteome-wide association study (PWAS), colocalization and Mendelian randomization and identified 38 putative causal proteins, 15 of which have drugs available. Finally, we developed a proteomics-based AD prediction model that outperforms genetics-based models. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits.

数量性状位点 （QTL） 与疾病全基因组关联研究 （GWAS） 的整合已被证明成功地在疾病相关位点上优先考虑候选基因。QTL 定位主要集中在多组织表达 QTL 或血浆蛋白 QTL （pQTL） 上。我们通过测量 3,506 个样本中的 6,361 个蛋白质生成了脑脊液 （CSF） pQTL 图谱。我们确定了 1,883 种蛋白质的 3,885 个关联，包括 2,885 个新的 pQTL，证明了 CSF 中独特的遗传调控。我们在 OSTN 附近的染色体 （chr）3q28 和 APOE 附近的 chr19q13.32 上鉴定了富含 CSF 的多效性区域，这些区域富含神经元特异性和神经发育。我们通过蛋白质组范围关联研究 （PWAS） 、共定位和孟德尔随机化整合了我们与阿尔茨海默病 （AD） 的关联，并确定了 38 种推定的致病蛋白，其中 15 种有可用的药物。最后，我们开发了一种基于蛋白质组学的 AD 预测模型，该模型优于基于遗传学的模型。这些发现将有助于进一步了解生物学并确定大脑和神经特征的因果和可药物蛋白。