Institute for Medical Informatics, Statistics and Epidemiology, Leipzig University, Leipzig, Germany.
Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, Leipzig University, Leipzig, Germany.
J Mol Med (Berl). 2023 Oct;101(10):1305-1321. doi: 10.1007/s00109-023-02362-z. Epub 2023 Sep 6.
Investigating the cross talk of different omics layers is crucial to understand molecular pathomechanisms of metabolic diseases like obesity. Here, we present a large-scale association meta-analysis of genome-wide whole blood and peripheral blood mononuclear cell (PBMC) gene expressions profiled with Illumina HT12v4 microarrays and metabolite measurements from dried blood spots (DBS) characterized by targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) in three large German cohort studies with up to 7706 samples. We found 37,295 associations comprising 72 amino acids (AA) and acylcarnitine (AC) metabolites (including ratios) and 8579 transcripts. We applied this catalogue of associations to investigate the impact of associating transcript-metabolite pairs on body mass index (BMI) as an example metabolic trait. This is achieved by conducting a comprehensive mediation analysis considering metabolites as mediators of gene expression effects and vice versa. We discovered large mediation networks comprising 27,023 potential mediation effects within 20,507 transcript-metabolite pairs. Resulting networks of highly connected (hub) transcripts and metabolites were leveraged to gain mechanistic insights into metabolic signaling pathways. In conclusion, here, we present the largest available multi-omics integration of genome-wide transcriptome data and metabolite data of amino acid and fatty acid metabolism and further leverage these findings to characterize potential mediation effects towards BMI proposing candidate mechanisms of obesity and related metabolic diseases. KEY MESSAGES: Thousands of associations of 72 amino acid and acylcarnitine metabolites and 8579 genes expand the knowledge of metabolome-transcriptome associations. A mediation analysis of effects on body mass index revealed large mediation networks of thousands of obesity-related gene-metabolite pairs. Highly connected, potentially mediating hub genes and metabolites enabled insight into obesity and related metabolic disease pathomechanisms.
研究不同组学层面之间的相互作用对于理解肥胖等代谢性疾病的分子病理机制至关重要。在这里,我们进行了一项大规模的全基因组全血和外周血单核细胞(PBMC)基因表达的关联荟萃分析,这些基因表达谱是使用 Illumina HT12v4 微阵列进行分析的,并对来自三个大型德国队列研究的干血斑(DBS)中的代谢物进行了靶向液相色谱串联质谱(LC-MS/MS)的特征描述,这些研究中最多包含了 7706 个样本。我们发现了 37295 个关联,包含 72 个氨基酸(AA)和酰基辅酶 A(AC)代谢物(包括比值)和 8579 个转录本。我们应用这组关联来研究关联转录本-代谢物对身体质量指数(BMI)的影响,BMI 是一种代谢特征。这是通过进行全面的中介分析来实现的,该分析将代谢物视为基因表达效应的中介,反之亦然。我们发现了包含 27023 个潜在中介效应的大型中介网络,这些中介效应存在于 20507 个转录本-代谢物对中。高度连接(枢纽)转录本和代谢物的网络被用来深入了解代谢信号通路的机制。总之,在这里,我们提出了迄今为止最大规模的全基因组转录组数据和氨基酸和脂肪酸代谢的代谢物数据的多组学整合,并进一步利用这些发现来描述对 BMI 的潜在中介效应,提出肥胖和相关代谢性疾病的候选机制。
72 种氨基酸和酰基辅酶 A 代谢物以及 8579 个基因的数千个关联扩展了代谢组-转录组关联的知识。对体重指数影响的中介分析揭示了数千个与肥胖相关的基因-代谢物对的大型中介网络。高度连接的、潜在的中介枢纽基因和代谢物使我们能够深入了解肥胖和相关代谢性疾病的病理机制。