Discovery of sexual dimorphisms in metabolic and genetic biomarkers.

Discovery of sexual dimorphisms in metabolic and genetic biomarkers.
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DOI:
10.1371/journal.pgen.1002215
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发表时间:
2011-08
期刊:
影响因子:
4.5
通讯作者:
Illig T
Illig T
中科院分区:
生物学2区
文献类型:
--
作者:
Mittelstrass K;Ried JS;Yu Z;Krumsiek J;Gieger C;Prehn C;Roemisch-Margl W;Polonikov A;Peters A;Theis FJ;Meitinger T;Kronenberg F;Weidinger S;Wichmann HE;Suhre K;Wang-Sattler R;Adamski J;Illig T

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代谢组学分析和全基因组遗传关联数据的整合已被证明是全面探索基因调控网络和在分子水平研究遗传变异影响的有力工具。血清代谢物浓度可以直接读出生物过程,并且特定代谢组学特征与复杂疾病(例如阿尔茨海默病、心血管和代谢紊乱)之间的关联已被证明。性别与疾病的发病率、患病率、发病年龄、症状和严重程度以及对药物的反应之间存在众所周知的相关性。然而,迄今为止发表的大多数研究都没有考虑性别二态性的作用,也没有分析按性别分层的数据。本研究调查了血清代谢物浓度的性别特异性差异及其潜在的遗传决定。为了发现和复制,我们使用了来自 KORA F3 和 F4 的 3,300 多个独立个体,对 131 种代谢物进行了代谢物测量,包括氨基酸、磷脂酰胆碱、鞘磷脂、酰基肉碱和 C6-糖。线性回归方法显示,131 种代谢物中有 102 种在男性和女性之间存在显着浓度差异(p 值<3.8×10−4;Bonferroni 校正阈值)。性别特异性全基因组关联研究 (GWAS) 显示,甘氨酸 CPS1 位点(氨基甲酰磷酸合酶 1,显着性水平:p<3.8×10−10;Bonferroni 校正阈值)中 SNP 的 β 估计存在全基因组显着差异。我们发现男性和女性的代谢谱存在显着差异,此外,代谢相关基因中的特定遗传变异描绘了性别二态性。我们的研究为细胞调节过程的性别特异性差异提供了新的重要见解,并强调研究应在设计和解释中考虑性别特异性影响。过去几年,基因组和代谢研究的结合提供了惊人的结果。然而,迄今为止发表的大多数研究都没有考虑性别二态性的作用,也没有分析按性别分层的数据。对超过 3,300 个人群样本 (KORA F3/F4) 的 131 种血清代谢物浓度的研究揭示了男性和女性代谢物谱的显着差异。此外,还研究了人类新陈代谢中性别特异性遗传变异的全基因组图谱(来自 KORA F3/F4 队列的超过 2,000 名受试者)。性别特异性全基因组关联研究(GWAS)显示遗传变异对男性和女性代谢物的影响存在差异。 CPS1(氨基甲酰磷酸合酶 1)基因座中的 SNP 在甘氨酸的性别特异性关联分析的 β 估计中显示出全基因组范围内的显着差异(显着性水平:3.8×10−10)。随着全球代谢组学技术越来越完善,可以识别单个生物样本中的更多化合物,这项新技术的预测能力将大大增强。这表明代谢物可以用作预测生物标志物来指示疾病的存在或严重程度,但必须根据性别选择性地使用。
Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8×10−4; Bonferroni-corrected threshold). Sex-specific genome-wide association studies (GWAS) showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8×10−10; Bonferroni-corrected threshold) for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and interpretation. The combination of genomic and metabolic studies during the last years has provided astonishing results. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by sex. The investigation of 131 serum metabolite concentrations of >3,300 population-based samples (KORA F3/F4) revealed significant differences in the metabolite profile of males and females. Furthermore, a genome-wide picture of sex-specific genetic variations in human metabolism (>2,000 subjects from KORA F3/F4 cohorts) was investigated. Sex-specific genome-wide association studies (GWAS) showed differences in the effect of genetic variations on metabolites in men and women. SNPs in the CPS1 (carbamoyl-phosphate synthase 1) locus showed genome-wide significant differences in beta-estimates of sex-specific association analysis (significance level: 3.8×10−10) for glycine. As global metabolomic techniques are more and more refined to identify more compounds in single biological samples, the predictive power of this new technology will greatly increase. This suggests that metabolites, which may be used as predictive biomarkers to indicate the presence or severity of a disease, have to be used selectively depending on sex.
DOI: 10.1371/journal.pgen.1000672
发表时间: 2009-10
期刊: PLoS genetics
影响因子: 4.5
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