دورية أكاديمية

Using metabolite profiling to construct and validate a metabolite risk score for predicting future weight gain.

التفاصيل البيبلوغرافية
العنوان: Using metabolite profiling to construct and validate a metabolite risk score for predicting future weight gain.
المؤلفون: Nina Geidenstam, Yu-Han H Hsu, Christina M Astley, Josep M Mercader, Martin Ridderstråle, Maria E Gonzalez, Clicerio Gonzalez, Joel N Hirschhorn, Rany M Salem
المصدر: PLoS ONE, Vol 14, Iss 9, p e0222445 (2019)
بيانات النشر: Public Library of Science (PLoS), 2019.
سنة النشر: 2019
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Medicine, Science
الوصف: BACKGROUND:Excess weight gain throughout adulthood can lead to adverse clinical outcomes and are influenced by complex factors that are difficult to measure in free-living individuals. Metabolite profiling offers an opportunity to systematically discover new predictors for weight gain that are relatively easy to measure compared to traditional approaches. METHODS AND RESULTS:Using baseline metabolite profiling data of middle-aged individuals from the Framingham Heart Study (FHS; n = 1,508), we identified 42 metabolites associated (p < 0.05) with longitudinal change in body mass index (BMI). We performed stepwise linear regression to select 8 of these metabolites to build a metabolite risk score (MRS) for predicting future weight gain. We replicated the MRS using data from the Mexico City Diabetes Study (MCDS; n = 768), in which one standard deviation increase in the MRS corresponded to ~0.03 increase in BMI (kg/m2) per year (i.e. ~0.09 kg/year for a 1.7 m adult). We observed that none of the available anthropometric, lifestyle, and glycemic variables fully account for the MRS prediction of weight gain. Surprisingly, we found the MRS to be strongly correlated with baseline insulin sensitivity in both cohorts and to be negatively predictive of T2D in MCDS. Genome-wide association study of the MRS identified 2 genome-wide (p < 5 × 10-8) and 5 suggestively (p < 1 × 10-6) significant loci, several of which have been previously linked to obesity-related phenotypes. CONCLUSIONS:We have constructed and validated a generalizable MRS for future weight gain that is an independent predictor distinct from several other known risk factors. The MRS captures a composite biological picture of weight gain, perhaps hinting at the anabolic effects of preserved insulin sensitivity. Future investigation is required to assess the relationships between MRS-predicted weight gain and other obesity-related diseases.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1932-6203
العلاقة: https://doaj.org/toc/1932-6203Test
DOI: 10.1371/journal.pone.0222445
الوصول الحر: https://doaj.org/article/5be5d20972a6444d9f735b667efa0821Test
رقم الانضمام: edsdoj.5be5d20972a6444d9f735b667efa0821
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:19326203
DOI:10.1371/journal.pone.0222445