Song Yanhong, Wu Xiaodong, Wu Ziyi, Zhao Ping
Department of Anesthesiology, Shengjing Hospital of China Medical University, Shenyang 110004, China.
Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, China.
J Affect Disord. 2025 Mar 15;373:438-448. doi: 10.1016/j.jad.2025.01.020. Epub 2025 Jan 8.
Metabolomics research is a promising orientation for the diagnosis and intervention of several diseases, and observational studies have found many metabolic profiles to be associated with mental disorders. However, the causal relationship between plasma and cerebrospinal fluid (CSF) metabolites and mental disorders has not been established.
We identified independent genetic variants associated with plasma, CSF metabolites, and mental disorders from pooled data in the published Genome-wide association studies (GWASs) and performed Mendelian randomization (MR) to investigate causal relationships. Genetic information on the screened mental disorders were derived from separate GWAS data sources as exploratory and validation datasets. Inverse variance weighting (IVW) was adopted as the primary method for MR analysis. We also applied sensitivity analyses to examine the reliability of the MR analysis results. Further enrichment analyses provided a deeper insight into the biological mechanisms of the three mental disorders.
A dual analysis of the exploratory and validation datasets identified eight plasma metabolites and three CSF metabolites causally associated with MDD, two plasma metabolites and one CSF metabolite causally associated with anxiety disorders, and four plasma metabolites and two CSF causally associated with ASD. Horizontal pleiotropy and heterogeneity tests indicate the validity of our MR studies. Enrichment analysis uncovered metabolic pathways associated with disease.
Our study identified plasma and cerebrospinal fluid metabolites that were causally associated with 3 mental disorders. Characterization of disease-associated metabolites not only deepens the understanding of pathological mechanisms, but also supports clinical diagnosis and prognosis.
代谢组学研究是多种疾病诊断和干预的一个有前景的方向，观察性研究已发现许多代谢谱与精神障碍相关。然而，血浆和脑脊液代谢物与精神障碍之间的因果关系尚未确立。
我们从已发表的全基因组关联研究（GWAS）的汇总数据中识别出与血浆、脑脊液代谢物及精神障碍相关的独立基因变异，并进行孟德尔随机化（MR）以研究因果关系。筛选出的精神障碍的遗传信息来自不同的GWAS数据源，作为探索性和验证性数据集。采用逆方差加权（IVW）作为MR分析的主要方法。我们还进行了敏感性分析以检验MR分析结果的可靠性。进一步的富集分析深入洞察了这三种精神障碍的生物学机制。
对探索性和验证性数据集的双重分析确定了8种血浆代谢物和3种脑脊液代谢物与重度抑郁症存在因果关联，2种血浆代谢物和1种脑脊液代谢物与焦虑症存在因果关联，4种血浆代谢物和2种脑脊液与自闭症谱系障碍存在因果关联。水平多效性和异质性检验表明我们的MR研究有效。富集分析揭示了与疾病相关的代谢途径。
我们的研究确定了与3种精神障碍存在因果关联的血浆和脑脊液代谢物。对疾病相关代谢物的表征不仅加深了对病理机制的理解，也为临床诊断和预后提供了支持。
