Bhattacharyya Upasana, John Jibin, Lam Max, Fisher Jonah, Sun Benjamin, Baird Denis, Chen Chia-Yen, Lencz Todd
Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY.
Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY.
medRxiv. 2024 Jan 19:2024.01.18.24301455. doi: 10.1101/2024.01.18.24301455.
Research on peripheral (e.g., blood-based) biomarkers for psychiatric illness has typically been low-throughput in terms of both the number of subjects and the range of assays performed. Moreover, traditional case-control studies examining blood-based biomarkers are subject to potential confounds of treatment and other exposures common to patients with psychiatric illnesses. Our research addresses these challenges by leveraging large-scale, high-throughput proteomics data and Mendelian Randomization (MR) to examine the causal impact of circulating proteins on psychiatric phenotypes and cognitive task performance.
We utilized plasma proteomics data from the UK Biobank (3,072 proteins assayed in 34,557 European-ancestry individuals) and deCODE Genetics (4,719 proteins measured across 35,559 Icelandic individuals). Significant proteomic quantitative trait loci (both cis-pQTLs and trans-pQTLs) served as MR instruments, with the most recent GWAS for schizophrenia, bipolar disorder, major depressive disorder, and cognitive task performance (all excluding overlapping UK Biobank participants) as phenotypic outcomes.
MR revealed 109 Bonferroni-corrected causal associations (44 novel) involving 88 proteins across the four phenotypes. Several immune-related proteins, including interleukins and complement factors, stood out as pleiotropic across multiple outcome phenotypes. Drug target enrichment analysis identified several novel potential pharmacologic repurposing opportunities, including anti-inflammatory agents for schizophrenia and bipolar disorder and duloxetine for cognitive performance.
Identification of causal effects for these circulating proteins suggests potential biomarkers for these conditions and offers insights for developing innovative therapeutic strategies. The findings also indicate substantial evidence for the pleiotropic effects of many proteins across different phenotypes, shedding light on the shared etiology among psychiatric conditions and cognitive ability.
关于精神疾病外周（如血液）生物标志物的研究，在受试者数量和所进行的检测范围方面通常都是低通量的。此外，传统的基于血液生物标志物的病例对照研究容易受到治疗以及精神疾病患者常见的其他暴露因素的潜在混杂影响。我们的研究通过利用大规模、高通量蛋白质组学数据和孟德尔随机化（MR）来检验循环蛋白对精神表型和认知任务表现的因果影响，从而应对这些挑战。
我们利用了英国生物银行的血浆蛋白质组学数据（在34,557名欧洲血统个体中检测了3,072种蛋白质）和 deCODE 遗传学公司的数据（在35,559名冰岛个体中测量了4,719种蛋白质）。显著的蛋白质组定量性状位点（顺式 pQTL 和反式 pQTL）用作 MR 工具，以精神分裂症、双相情感障碍和重度抑郁症的最新全基因组关联研究（GWAS）以及认知任务表现（均排除英国生物银行的重叠参与者）作为表型结果。
MR 揭示了涉及四种表型中88种蛋白质的109个经 Bonferroni 校正的因果关联（44个为新发现）。包括白细胞介素和补体因子在内的几种免疫相关蛋白在多种结果表型中表现出多效性。药物靶点富集分析确定了几个新的潜在药物重新利用机会，包括用于精神分裂症和双相情感障碍的抗炎药以及用于认知表现的度洛西汀。
确定这些循环蛋白的因果效应提示了这些疾病的潜在生物标志物，并为开发创新治疗策略提供了见解。研究结果还表明许多蛋白质在不同表型中存在多效性的大量证据，揭示了精神疾病和认知能力之间的共同病因。
