Early Life Factors, Obesity Risk, and the Metabolome of Young Adults

Rauschert, Sebastian; Mori, Trevor A.; Beilin, Lawrence J.; Jacoby, Peter; Uhl, Olaf; Koletzko, Berthold; Oddy, Wendy H.; Hellmuth, Christian

doi:10.1002/oby.21915

Cited by 9 publications

(6 citation statements)

References 37 publications

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“…All cohort members were invited to attend follow-up, which involved questionnaires, collection of anthropometric data ( 28 ), and collection of serum for analysis for testosterone, estradiol (E 2 ) and estrone (E 1 ), luteinizing hormone (LH), follicle stimulating hormone (FSH), and inhibin B (inhB) concentrations. A testicular ultrasound examination was performed (at King Edward Memorial Hospital) and a semen sample analyzed at the IVF unit (Fertility Specialists of Western Australia) as previously reported ( 1 ).…”

Section: Methodsmentioning

confidence: 99%

The Possible Impact of Antenatal Exposure to Ubiquitous Phthalates Upon Male Reproductive Function at 20 Years of Age

et al. 2018

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Phthalates are ubiquitous environmental endocrine-disrupting chemicals suspected to interfere with developmental androgen action leading to adverse effects on male reproductive function. Prenatal exposure studies in rodents show cryptorchidism, hypospadias and reduced testicular volume (TV), testosterone and anogenital distance in males. It is postulated that there is a developmental window in utero when phthalate exposure has the most potent adverse effects. Some human studies show associations between prenatal phthalate exposure and reduced calculated “free” serum testosterone in infant boys and shorter anogenital distance. However, there are no data available yet which link antenatal exposure to long-term effects in men. We aimed to correlate antenatal phthalate exposure with adult TV, semen parameters and serum reproductive hormone concentrations. 913 men from the Western Australian (Raine) Pregnancy Cohort were contacted aged 20–22 years. 423 (56%) agreed to participate; 404 underwent testicular ultrasound examination; 365 provided semen samples, and reproductive hormones were measured in 384. Maternal antenatal serum phthalate metabolite measurements were available for 185 and 111 men, who provided serum and semen, respectively. Maternal serum collected at 18 and 34 weeks gestation, stored at −80°C, was pooled and analyzed for 32 phthalate metabolites by liquid chromatography-tandem mass spectrometry. TV was calculated, semen analysis performed by WHO approved methods, and serum concentrations of gonadotrophins, inhibin B, and testosterone measured. Eleven phthalate metabolites were detected. Primary and secondary metabolites of di-(2-ethyl-hexyl) phthalate (DEHP) and di-iso-nonyl phthalate (DiNP) were positively correlated. After correction for adult height, BMI, presence of a varicocele and exposure to maternal smoking mono-iso-nonyl phthalate (MiNP) (r = −0.22) and sums of DEHP and DiNP metabolites (r = −0.24) and the sum of the metabolites of the high molecular weight phthalates (r = −0.21) were negatively correlated with TV (all p < 0.05). After adjustment for BMI adult serum total testosterone was positively associated with exposure to the following antenatal serum phthalate metabolites: mono-(2-ethylhexyl) phthalate (r = 0.26), MiNP (r = 0.18), the sum of metabolites for DEHP (r = 0.21) and DiNP (r = 0.18), and the sum of high molecular phthalates (r = 0.20) (p = 0.0005 to p = 0.02). Given sample size, storage duration and confounding through postnatal exposures, further studies are required.

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Section: Methodsmentioning

confidence: 99%

The Possible Impact of Antenatal Exposure to Ubiquitous Phthalates Upon Male Reproductive Function at 20 Years of Age

et al. 2018

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“…After exclusion of outliers, the coefficients of variation (CV; SD/mean) for each batch (intra-batch) and for all batches (inter-batch) of the QC samples were calculated for each metabolite. In line with previous studies (Hellmuth et al 2017a;Lindsay et al 2015;Rauschert et al 2017b;Shokry et al 2019), for each metabolite we excluded batches with an intra-batch CV higher than 25%. Data on complete metabolites were excluded for metabolites with inter-batch CV higher than 35% or if less than 50% of the batches passed the QC (i.e.…”

Section: Quality Control and Pre-processingmentioning

confidence: 99%

A population-based resource for intergenerational metabolomics analyses in pregnant women and their children: the Generation R Study

et al. 2020

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Introduction Adverse exposures in early life may predispose children to cardio-metabolic disease in later life. Metabolomics may serve as a valuable tool to disentangle the metabolic adaptations and mechanisms that potentially underlie these associations. Objectives To describe the acquisition, processing and structure of the metabolomics data available in a population-based prospective cohort from early pregnancy onwards and to examine the relationships between metabolite profiles of pregnant women and their children at birth and in childhood. Methods In a subset of 994 mothers-child pairs from a prospective population-based cohort study among pregnant women and their children from Rotterdam, the Netherlands, we used LC-MS/MS to determine concentrations of amino acids, nonesterified fatty acids, phospholipids and carnitines in blood serum collected in early pregnancy, at birth (cord blood), and at child's age 10 years. Results Concentrations of diacyl-phosphatidylcholines, acyl-alkyl-phosphatidylcholines, alkyl-lysophosphatidylcholines and sphingomyelines were the highest in early pregnancy, concentrations of amino acids and non-esterified fatty acids were the highest at birth and concentrations of alkyl-lysophosphatidylcholines, free carnitine and acyl-carnitines were the highest at age 10 years. Correlations of individual metabolites between pregnant women and their children at birth and at the age of 10 years were low (range between r = − 0.10 and r = 0.35). Conclusion Our results suggest that unique metabolic profiles are present among pregnant women, newborns and school aged children, with limited intergenerational correlations between metabolite profiles. These data will form a valuable resource to address the early metabolic origins of cardio-metabolic disease. Keywords Metabolomics • Amino acids • Fatty acids • Phospholipids • Carnitines • Birth cohort Abbreviations AA Amino acids AAA Aromatic amino acids APCI Atmospheric pressure chemical ionization BCAA Branched-chain amino acids Carn Carnitines Carn.a Acyl-carnitines Berthold Koletzko and Romy Gaillard have contributed equally.

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“…Over the last decade, numerous reports and reviews have addressed the metabolic changes associated with obesity in both humans and animal models (Abu Bakar et al 2015 ; Adams 2011 ; Calvani et al 2014 ; Du et al 2013 ; Fiehn et al 2010 ; Gogna et al 2015 ; He et al 2012 ; Hivert et al 2015 ; Kim and Park 2010 ; Kim et al 2010a ; Mihalik et al 2012 ; Moore et al 2013 ; Morris et al 2012 ; Newgard 2017 ; Newgard et al 2009 ; Oberbach et al 2011 ; Pietiläinen et al 2007 ; Rauschert et al 2014 , 2016 ; Rauschert et al 2017 ; Rauschert et al 2017 ; Shore and Cho 2016 ; Tulipani et al 2016a ; Villarreal-Pérez et al 2014 ; Wahl et al 2012 ; Williams et al 2006 ; Xie et al 2012 ; Zeng et al 2010 ; Zhang et al 2013 ; Zhao et al 2016a , b ). Many of them describe changes in the metabolic profile associated with obesity and diabetes, and notably features associated with IR (Abu Bakar et al 2015 ; Adams 2011 ; Fiehn et al 2010 ; Gogna et al 2015 ; Mihalik et al 2012 ; Newgard 2017 ; Newgard et al 2009 ; Rauschert et al 2016 ; Villarreal-Pérez et al 2014 ; Zhao et al 2016a , b ), and the majority report the results of targeted analyses.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, the identified metabolites can serve as biomarkers of the pathophysiological mechanisms involved in the development of obesity and, subsequently, T2DM. Elevated levels of branched-chain AAs (BCAAs) (leucine, isoleucine, and valine) and aromatic AAs (phenylalanine, tyrosine, tryptophan and methionine), as well as some of their tissue metabolites, have been detected in both subjects with obesity and diabetes, whereas glutamine and glycine levels are decreased (Adams 2011 ; Mihalik et al 2012 ; Morris et al 2012 ; Newgard 2017 ; Newgard et al 2009 ; Rauschert et al 2017 ), although the results have not always been consistent (Fiehn et al 2010 ; Kim et al 2010b ; Oberbach et al 2011 ; Wahl et al 2012 ). The levels of other non-protein nitrogen compounds, such as nucleotides, nucleosides, and their metabolites, namely, uridine and uric acid, vary considerably, depending on the degree of IR in obese subjects (Fiehn et al 2010 ; Park et al 2015 ; Wahl et al 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies

2019

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Introduction Obesity is a disorder characterized by a disproportionate increase in body weight in relation to height, mainly due to the accumulation of fat, and is considered a pandemic of the present century by many international health institutions. It is associated with several non-communicable chronic diseases, namely, metabolic syndrome, type 2 diabetes mellitus (T2DM), cardiovascular diseases (CVD), and cancer. Metabolomics is a useful tool to evaluate changes in metabolites due to being overweight and obesity at the body fluid and cellular levels and to ascertain metabolic changes in metabolically unhealthy overweight and obese individuals (MUHO) compared to metabolically healthy individuals (MHO). Objectives We aimed to conduct a systematic review (SR) of human studies focused on identifying metabolomic signatures in obese individuals and obesity-related metabolic alterations, such as inflammation or oxidative stress. Methods We reviewed the literature to identify studies investigating the metabolomics profile of human obesity and that were published up to May 7th, 2019 in SCOPUS and PubMed through an SR. The quality of reporting was evaluated using an adapted of QUADOMICS. Results Thirty-three articles were included and classified according to four types of approaches. (i) studying the metabolic signature of obesity, (ii) studying the differential responses of obese and non-obese subjects to dietary challenges (iii) studies that used metabolomics to predict weight loss and aimed to assess the effects of weight loss interventions on the metabolomics profiles of overweight or obese human subjects (iv) articles that studied the effects of specific dietary patterns or dietary compounds on obesity-related metabolic alterations in humans. Conclusion The present SR provides state-of-the-art information about the use of metabolomics as an approach to understanding the dynamics of metabolic processes involved in human obesity and emphasizes metabolic signatures related to obesity phenotypes.

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Early Life Factors, Obesity Risk, and the Metabolome of Young Adults

Cited by 9 publications

References 37 publications

The Possible Impact of Antenatal Exposure to Ubiquitous Phthalates Upon Male Reproductive Function at 20 Years of Age

The Possible Impact of Antenatal Exposure to Ubiquitous Phthalates Upon Male Reproductive Function at 20 Years of Age

A population-based resource for intergenerational metabolomics analyses in pregnant women and their children: the Generation R Study

Are we close to defining a metabolomic signature of human obesity? A systematic review of metabolomics studies

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