Microbiome-derived metabolites in early to mid-pregnancy and risk of gestational diabetes: a metabolome-wide association study.

IF 7 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL BMC Medicine Pub Date : 2024-10-11 DOI:10.1186/s12916-024-03606-6
Sita Manasa Susarla, Oliver Fiehn, Ines Thiele, Amanda L Ngo, Dinesh K Barupal, Rana F Chehab, Assiamira Ferrara, Yeyi Zhu
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Abstract

Background: Pre-diagnostic disturbances in the microbiome-derived metabolome have been associated with an increased risk of diabetes in non-pregnant populations. However, the roles of microbiome-derived metabolites, the end-products of microbial metabolism, in gestational diabetes (GDM) remain understudied. We examined the prospective association of microbiome-derived metabolites in early to mid-pregnancy with GDM risk in a diverse population.

Methods: We conducted a prospective discovery and validation study, including a case-control sample of 91 GDM and 180 non-GDM individuals within the multi-racial/ethnic The Pregnancy Environment and Lifestyle Study (PETALS) as the discovery set, a random sample from the PETALS (42 GDM, 372 non-GDM) as validation set 1, and a case-control sample (35 GDM, 70 non-GDM) from the Gestational Weight Gain and Optimal Wellness randomized controlled trial as validation set 2. We measured untargeted fasting serum metabolomics at gestational weeks (GW) 10-13 and 16-19 by gas chromatography/time-of-flight mass spectrometry (TOF-MS), liquid chromatography (LC)/quadrupole TOF-MS, and hydrophilic interaction LC/quadrupole TOF-MS. GDM was diagnosed using the 3-h, 100-g oral glucose tolerance test according to the Carpenter-Coustan criteria around GW 24-28.

Results: Among 1362 annotated compounds, we identified 140 of gut microbiome metabolism origin. Multivariate enrichment analysis illustrated that carbocyclic acids and branched-chain amino acid clusters at GW 10-13 and the unsaturated fatty acids cluster at GW 16-19 were positively associated with GDM risk (FDR < 0.05). At GW 10-13, the prediction model that combined conventional risk factors and LASSO-selected microbiome-derived metabolites significantly outperformed the model with only conventional risk factors including fasting glucose (discovery AUC: 0.884 vs. 0.691; validation 1: 0.945 vs. 0.731; validation 2: 0.987 vs. 0.717; all P < 0.01). At GW 16-19, similar results were observed (discovery AUC: 0.802 vs. 0.691, P < 0.01; validation 1: 0.826 vs. 0.780; P = 0.10).

Conclusions: Dysbiosis in microbiome-derived metabolites is present early in pregnancy among individuals progressing to GDM.

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妊娠早中期微生物衍生代谢物与妊娠糖尿病风险:全代谢组关联研究。
背景:在非妊娠人群中,微生物组衍生代谢组的诊断前紊乱与糖尿病风险增加有关。然而,微生物代谢的最终产物--微生物衍生代谢产物在妊娠糖尿病(GDM)中的作用仍未得到充分研究。我们研究了在不同人群中,孕早期至孕中期微生物衍生代谢物与 GDM 风险的前瞻性关联:我们进行了一项前瞻性发现和验证研究,包括以多种族/民族妊娠环境和生活方式研究(PETALS)中的 91 名 GDM 和 180 名非 GDM 患者的病例对照样本作为发现集,以 PETALS 中的随机样本(42 名 GDM、372 名非 GDM)作为验证集 1,以妊娠体重增加和最佳健康随机对照试验中的病例对照样本(35 名 GDM、70 名非 GDM)作为验证集 2。我们采用气相色谱/飞行时间质谱 (TOF-MS)、液相色谱/四极杆 TOF-MS 和亲水相互作用液相色谱/四极杆 TOF-MS 方法测量了妊娠周 (GW) 10-13 和 16-19 的非目标空腹血清代谢组学。根据 Carpenter-Coustan 在 GW 24-28 左右的标准,采用 3 小时 100 克口服葡萄糖耐量试验诊断 GDM:结果:在 1362 种注释化合物中,我们发现了 140 种源于肠道微生物组代谢的化合物。多变量富集分析表明,GW 10-13 的碳环酸类和支链氨基酸簇以及 GW 16-19 的不饱和脂肪酸簇与 GDM 风险呈正相关(FDR 结论):在进展为 GDM 的人群中,妊娠早期就存在微生物衍生代谢产物的菌群失调。
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来源期刊
BMC Medicine
BMC Medicine 医学-医学:内科
CiteScore
13.10
自引率
1.10%
发文量
435
审稿时长
4-8 weeks
期刊介绍: BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.
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