多组学分析优先筛选阻塞性睡眠呼吸暂停的潜在生物标志物和药物靶点。

文献信息

中文摘要

研究目的： 阻塞性睡眠呼吸暂停（OSA）仍然是一种常见的睡眠障碍，其分子机制尚未完全阐明，药物治疗选择也在不断演变。我们旨在识别与OSA相关的分子生物标志物，并优先筛选候选标志物以供进一步评估。
方法： 使用全转录组关联研究和全蛋白质组关联研究，对OSA全基因组关联研究汇总统计量与血液和脑来源的表达及蛋白质数量性状位点（QTL）数据进行分析。随后使用基于汇总数据的孟德尔随机化（MR）、HEIDI检验和贝叶斯共定位来评估已识别的基因和蛋白质。使用替代QTL资源和OSA GWAS数据评估候选生物标志物。多变量MR在考虑体重指数（BMI）后评估符合条件的关联。功能富集、甲基化相关分析和药理学分析提供了下游表征。
结果： 在血液/血浆和脑中优先筛选出28个独特的基因和蛋白质。使用替代QTL资源和独立的OSA GWAS数据集支持了18个候选生物标志物。在可评估的生物标志物中，MAP7D1、MCM6、L3MBTL2和LCT在考虑BMI后仍与OSA相关，而PCSK1和大多数其他关联减弱。富集分析涉及葡萄糖代谢、自噬-溶酶体过程和凋亡相关通路。中介分析确定了41个CpG位点通过基因表达或蛋白质丰度对OSA的43个显著间接效应。药物数据库筛选为若干生物标志物确定了候选药物，而分子对接支持涉及BID和GPD2的靶点-化合物相互作用。
结论： 本研究优先筛选出28个与OSA相关的分子生物标志物，并进一步表征了其生物学和调控背景，同时选定的候选标志物值得进一步的实验评估。

英文摘要

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) remains a prevalent sleep disorder with incompletely characterized molecular mechanisms and evolving pharmacological options. We aimed to identify molecular biomarkers associated with OSA and prioritize candidates for further evaluation.
METHODS: OSA genome-wide association study summary statistics were analyzed with blood- and brain-derived expression and protein quantitative trait loci (QTL) data using transcriptome-wide and proteome-wide association studies. Summary data-based Mendelian randomization (MR), HEIDI testing and Bayesian colocalization were then used to evaluate the identified genes and proteins. Candidate biomarkers were assessed using alternative QTL resources and OSA GWAS data. Multivariable MR assessed eligible associations after accounting for body mass index (BMI). Functional enrichment, methylation-related analyses, and pharmacological analyses provided downstream characterization.
RESULTS: 28 unique genes and proteins were prioritized across blood/plasma and brain. 18 candidate biomarkers were supported using alternative QTL resources and the independent OSA GWAS dataset. Among assessable biomarkers, MAP7D1, MCM6, L3MBTL2, and LCT remained associated with OSA after accounting for BMI, whereas PCSK1 and most other associations were attenuated. Enrichment analyses implicated glucose metabolism, autophagy-lysosome processes and apoptosis-related pathways. Mediation analyses identified 43 significant indirect effects of 41 CpG sites on OSA through gene expression or protein abundance. Drug-database screening identified candidate drugs for several biomarkers, while molecular docking supported target-compound interactions involving BID and GPD2.
CONCLUSIONS: This study prioritized 28 molecular biomarkers associated with OSA and further characterized their biological and regulatory context, while selected candidates warrant further experimental evaluation.