Table 2_Multi-omic insights into mitochondrial dysfunction and prostatic disease: evidence from transcriptomics, proteomics, and methylomics.docx

BackgroundProstatic diseases, consisting of prostatitis, benign prostatic hyperplasia (BPH), and prostate cancer (PCa), pose significant health challenges. While single-omics studies have provided valuable insights into the role of mitochondrial dysfunction in prostatic diseases, integrating multi-omics approaches is essential for uncovering disease mechanisms and identifying therapeutic targets.
MethodsA genome-wide meta-analysis was conducted for prostatic diseases using the genome-wide association studies (GWAS) data from FinnGen and UK Biobank. Mitochondrial dysfunction-related genes were reviewed based on MitoCarta 3.0, with a library containing 1,244 mitochondrial genes. We integrated multi-omics through quantitative trait loci (QTL) across gene expression (eQTLs), protein abundance (pQTLs), and DNA methylation (mQTLs). We prioritized prostatic disease-related mitochondrial genes into three confidence tiers: Tier 1 (two eQTLs + pQTL + mQTL); Tier 2 (two eQTLs + pQTL/mQTL); and Tier 3 (eQTL + pQTL/mQTL). Further mediation analyses were performed to explore potential mediating pathways for the interaction between mitochondrial dysfunction and prostatic diseases, with 1,400 metabolomics and 731 immunomics.
ResultsWe identified DCXR as the gene with Tier 1 evidence for BPH, validated by multi-omics integration through transcriptomic, proteomic, and methylomic signatures. We revealed two Tier 2 genes (NOA1 and ELAC2) and one Tier 3 gene (ACAT1) for BPH, two Tier 3 genes (TRMU and SFXN5) for prostatitis, and six Tier 3 genes (MRPL24, NDUFS6, PUS1, NBR1, GLOD4, and PCBD2) for PCa. We also explored the mediating pathways of mitochondrial genes (within the 3-tiers evidence) on prostatic diseases, and identified 8, 4, and 13 metabolites mediating the interaction between mitochondrial genes and BPH, prostatitis, and PCa, respectively, without the involvement of immune characters.
ConclusionThese findings highlight the roles of mitochondrial dysfunction-related genes in prostatic diseases and identify key genes and pathways for potential therapeutic targets.

背景 前列腺疾病（prostatic diseases）涵盖前列腺炎（prostatitis）、良性前列腺增生（benign prostatic hyperplasia, BPH）与前列腺癌（prostate cancer, PCa），均对人类健康构成重大挑战。尽管单组学研究已为线粒体功能异常在前列腺疾病中的作用提供了宝贵见解，但整合多组学策略对于揭示疾病发病机制、筛选治疗靶点至关重要。
方法 本研究针对前列腺疾病开展全基因组荟萃分析，采用来自FinnGen与英国生物库（UK Biobank）的全基因组关联研究（genome-wide association studies, GWAS）数据。基于收录1244个线粒体基因的MitoCarta 3.0数据库，我们梳理了与线粒体功能异常相关的基因集。我们通过整合跨基因表达（expression quantitative trait loci, eQTLs）、蛋白质丰度（protein abundance quantitative trait loci, pQTLs）与DNA甲基化（DNA methylation quantitative trait loci, mQTLs）的数量性状位点（quantitative trait loci, QTL）实现多组学整合。我们将前列腺疾病相关线粒体基因划分为三个置信层级：层级1（2个eQTL + 1个pQTL + 1个mQTL）；层级2（2个eQTL + 1个pQTL/mQTL）；层级3（1个eQTL + 1个pQTL/mQTL）。进一步开展介导分析，以探究线粒体功能异常与前列腺疾病之间相互作用的潜在介导通路，本次分析纳入1400个代谢组学特征与731个免疫组学特征。
结果 我们鉴定出DCXR为良性前列腺增生（BPH）的层级1证据基因，该结论通过转录组学、蛋白质组学与甲基组学特征的多组学整合得到验证。我们明确了良性前列腺增生的2个层级2基因（NOA1与ELAC2）、1个层级3基因（ACAT1），前列腺炎的2个层级3基因（TRMU与SFXN5），以及前列腺癌（PCa）的6个层级3基因（MRPL24、NDUFS6、PUS1、NBR1、GLOD4与PCBD2）。此外，我们探究了具备三级证据的线粒体基因对前列腺疾病的介导通路，并分别鉴定出8、4与13个代谢物介导线粒体基因与良性前列腺增生、前列腺炎、前列腺癌之间的相互作用，未发现免疫特征参与其中。
结论 本研究结果凸显了线粒体功能异常相关基因在前列腺疾病中的关键作用，并鉴定出可作为潜在治疗靶点的核心基因与通路。