Department of Biostatistical Sciences, Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA.
Department of Internal Medicine, School of Medicine, Wake Forest University, Winston-Salem, North Carolina, USA.
Obesity (Silver Spring). 2018 Mar;26(3):559-569. doi: 10.1002/oby.22113. Epub 2018 Jan 29.
Tissue-specific gene expression is associated with individual metabolic measures. However, these measures may not reflect the true but latent underlying biological phenotype. This study reports gene expression associations with multidimensional glucometabolic characterizations of obesity, glucose homeostasis, and lipid traits.
Factor analysis was computed by using orthogonal rotation to construct composite phenotypes (CPs) from 23 traits in 256 African Americans without diabetes. Genome-wide transcript expression data from adipose and muscle were tested for association with CPs, and expression quantitative trait loci (eQTLs) were identified by associations between cis-acting single-nucleotide polymorphisms (SNPs) and gene expression.
The factor analysis identified six CPs. CPs 1 through 6 individually explained 34%, 12%, 9%, 8%, 6%, and 5% of the variation in 23 glucometabolic traits studied. There were 3,994 and 929 CP-associated transcripts identified in adipose and muscle tissue, respectively; CP2 had the largest number of associated transcripts. Pathway analysis identified multiple canonical pathways from the CP-associated transcripts. In adipose and muscle, significant cis-eQTLs were identified for 558 and 164 CP-associated transcripts (q-value < 0.01), respectively.
Adipose and muscle transcripts comprehensively define pathways involved in regulating glucometabolic disorders. Cis-eQTLs for CP-associated genes may act as primary causal determinants of glucometabolic phenotypes by regulating transcription of key genes.
组织特异性基因表达与个体代谢指标相关。然而，这些指标可能无法反映真实但潜在的基础生物学表型。本研究报告了基因表达与肥胖、葡萄糖稳态和脂质特征的多维糖代谢特征的关联。
通过使用正交旋转对 256 名非糖尿病的非洲裔美国人的 23 个特征进行因子分析，构建复合表型（CPs）。对脂肪和肌肉的全基因组转录表达数据进行与 CPs 的关联测试，并通过顺式作用单核苷酸多态性（SNP）与基因表达之间的关联来鉴定表达数量性状基因座（eQTLs）。
因子分析确定了六个 CPs。CP1 到 CP6 分别解释了 23 个糖代谢特征研究中 34%、12%、9%、8%、6%和 5%的变化。在脂肪和肌肉组织中分别鉴定出 3994 个和 929 个与 CP 相关的转录本；CP2 具有最多数量的相关转录本。通路分析从 CP 相关转录本中鉴定出多个经典通路。在脂肪和肌肉中，分别为 558 个和 164 个 CP 相关转录本鉴定出显著的顺式-eQTL（q 值<0.01）。
脂肪和肌肉转录本全面定义了参与调节糖代谢紊乱的途径。CP 相关基因的顺式-eQTL 可能通过调节关键基因的转录，作为糖代谢表型的主要因果决定因素。
