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18 pages, 873 KiB

Open AccessArticle

Changes in Metabolites During an Oral Glucose Tolerance Test in Early and Mid-Pregnancy: Findings from the PEARLS Randomized, Controlled Lifestyle Trial

by Danielle E. Haslam, Jun Li, Liming Liang, Marijulie Martinez, Cristina Palacios, Maria A. Trak-Fellermeier, Paul W. Franks, Kaumudi Joshipura and Shilpa N. Bhupathiraju

Metabolites 2020, 10(7), 284; https://doi.org/10.3390/metabo10070284 - 10 Jul 2020

Cited by 3 | Viewed by 2840

Abstract

The oral glucose tolerance test (OGTT) is used to diagnose gestational and other types of diabetes. We examined metabolite changes during an OGTT, and how a comprehensive diet and physical activity intervention may influence these changes in a population of overweight/obese Hispanic pregnant [...] Read more.

The oral glucose tolerance test (OGTT) is used to diagnose gestational and other types of diabetes. We examined metabolite changes during an OGTT, and how a comprehensive diet and physical activity intervention may influence these changes in a population of overweight/obese Hispanic pregnant women. Integration of changes in metabolites during an OGTT may help us gain preliminary insights into how glucose metabolism changes during pregnancy. Among women from the Pregnancy and EARly Lifestyle improvement Study (PEARLS), we measured metabolites during a multipoint OGTT (fasting, 30, 60 and 120 min) at early and mid-pregnancy. Metabolite levels were measured by liquid chromatography–mass spectrometry in plasma samples in the lifestyle intervention (n = 13) and control (n = 16) arms of the study. A total of 65 candidate metabolites were selected that displayed changes during an OGTT in previous studies. Paired and unpaired t-tests were used to examine differences in Δfast-120 min: (1) at early and mid-pregnancy; and (2) by intervention assignment. We applied principal component analysis (PCA) to identify those metabolites that differed by intervention assignment and OGTT time points. Most of the characteristic changes in metabolites post-OGTT were similar at both gestational time points. PCA identified characteristic metabolite patterns associated with OGTT time points at both early and mid-pregnancy. These metabolites included ketone bodies, tryptophan, acyl carnitines, polyunsaturated fatty acids, and biomarkers related to bile acid, urea cycle, arginine, and proline metabolism. PCA identified distinct Δfast-120 min in fatty acid, acyl carnitine, bile acid, ketone body, and amino acid levels at mid- compared to early pregnancy. Participants in the intervention group did not display mean decreases in Δfast-120 min of several long-chain acyl carnitines that were observed in the control group. These findings provide preliminary insight into metabolites, whose role in increased insulin resistance during pregnancy, should be explored further in future studies. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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12 pages, 2716 KiB

Open AccessArticle

Identification of Plasma Lipidome Changes Associated with Low Dose Space-Type Radiation Exposure in a Murine Model

by Maarisha Upadhyay, Meena Rajagopal, Kirandeep Gill, Yaoxiang Li, Shivani Bansal, Vijayalakshmi Sridharan, John B. Tyburski, Marjan Boerma and Amrita K. Cheema

Metabolites 2020, 10(6), 252; https://doi.org/10.3390/metabo10060252 - 17 Jun 2020

Cited by 11 | Viewed by 2774

Abstract

Long-term exposures to low dose space radiation may have adverse effects on human health during missions in deep space. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as biomarkers of organ- and tissue-specific radiation injury, particularly of [...] Read more.

Long-term exposures to low dose space radiation may have adverse effects on human health during missions in deep space. Conventional dosimetry, monitoring of prodromal symptoms, and peripheral lymphocyte counts are of limited value as biomarkers of organ- and tissue-specific radiation injury, particularly of injuries that appear weeks or months after radiation exposure. To assess the feasibility of using plasma metabolic and lipidomic profiles as biomarkers of injury from space radiation, we used a mouse model of exposure to low doses of oxygen ions (¹⁶O) and protons (¹H). Plasma profiles were compared with those of mice exposed to γ-rays as a reference set. Our results demonstrate major changes in glycerophospholipid metabolism, amino acid metabolism, as well as fatty acid metabolism. We also observed dyslipidemia and lipid peroxidation, suggesting an inflammatory phenotype with possible long-term consequences to overall health upon exposure to low doses of high linear energy transfer (LET) radiation. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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14 pages, 1945 KiB

Open AccessArticle

Impact of Pre-Blood Collection Factors on Plasma Metabolomic Profiles

by Sheetal Hardikar, Richard D. Albrechtsen, David Achaintre, Tengda Lin, Svenja Pauleck, Mary Playdon, Andreana N. Holowatyj, Biljana Gigic, Petra Schrotz-King, Juergen Boehm, Nina Habermann, Stefanie Brezina, Andrea Gsur, Eline H. van Roekel, Matty P. Weijenberg, Pekka Keski-Rahkonen, Augustin Scalbert, Jennifer Ose and Cornelia M. Ulrich

Metabolites 2020, 10(5), 213; https://doi.org/10.3390/metabo10050213 - 21 May 2020

Cited by 8 | Viewed by 2352

Abstract

Demographic, lifestyle and biospecimen-related factors at the time of blood collection can influence metabolite levels in epidemiological studies. Identifying the major influences on metabolite concentrations is critical to designing appropriate sample collection protocols and considering covariate adjustment in metabolomics analyses. We examined the [...] Read more.

Demographic, lifestyle and biospecimen-related factors at the time of blood collection can influence metabolite levels in epidemiological studies. Identifying the major influences on metabolite concentrations is critical to designing appropriate sample collection protocols and considering covariate adjustment in metabolomics analyses. We examined the association of age, sex, and other short-term pre-blood collection factors (time of day, season, fasting duration, physical activity, NSAID use, smoking and alcohol consumption in the days prior to collection) with 133 targeted plasma metabolites (acylcarnitines, amino acids, biogenic amines, sphingolipids, glycerophospholipids, and hexoses) among 108 individuals that reported exposures within 48 h before collection. The differences in mean metabolite concentrations were assessed between groups based on pre-collection factors using two-sided t-tests and ANOVA with FDR correction. Percent differences in metabolite concentrations were negligible across season, time of day of collection, fasting status or lifestyle behaviors at the time of collection, including physical activity or the use of tobacco, alcohol or NSAIDs. The metabolites differed in concentration between the age and sex categories for 21.8% and 14.3% metabolites, respectively. In conclusion, extrinsic factors in the short period prior to collection were not meaningfully associated with concentrations of selected endogenous metabolites in a cross-sectional sample, though metabolite concentrations differed by age and sex. Larger studies with more coverage of the human metabolome are warranted. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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16 pages, 1378 KiB

Open AccessArticle

Plasma 25-Hydroxyvitamin D Concentrations are Associated with Polyunsaturated Fatty Acid Metabolites in Young Children: Results from the Vitamin D Antenatal Asthma Reduction Trial

by Mengna Huang, Rachel S. Kelly, Priyadarshini Kachroo, Su H. Chu, Kathleen Lee-Sarwar, Bo L. Chawes, Hans Bisgaard, Augusto A. Litonjua, Scott T. Weiss and Jessica Lasky-Su

Metabolites 2020, 10(4), 151; https://doi.org/10.3390/metabo10040151 - 14 Apr 2020

Cited by 6 | Viewed by 2685

Abstract

Vitamin D deficiency contributes to a multitude of health conditions, but its biological mechanisms are not adequately understood. Untargeted metabolomics offers the opportunity to comprehensively examine the metabolic profile associated with variations in vitamin D concentrations. The objective of the current analysis was [...] Read more.

Vitamin D deficiency contributes to a multitude of health conditions, but its biological mechanisms are not adequately understood. Untargeted metabolomics offers the opportunity to comprehensively examine the metabolic profile associated with variations in vitamin D concentrations. The objective of the current analysis was to identify metabolites and metabolic pathways associated with plasma 25-hydroxyvitamin D [25(OH)D] concentrations. The current study included children of pregnant women in the Vitamin D Antenatal Asthma Reduction Trial, who had 25(OH)D and global metabolomics data at age 1 and 3 years. We assessed the cross-sectional associations between individual metabolites and 25(OH)D using linear regression adjusting for confounding factors. Twelve metabolites were significantly associated with plasma 25(OH)D concentrations at both age 1 and 3 after correction for multiple comparisons, including three members of the n-6 polyunsaturated fatty acid (PUFA) metabolism pathway (linoleate, arachidonate, and docosapentaenoate) inversely associated with 25(OH)D. These PUFAs along with four other significant metabolites were replicated in the independent Childhood Asthma Management Program (CAMP) cohort. Both vitamin D and n-6 PUFAs are involved in inflammatory processes, and evidence from cell and animal studies demonstrate a plausible biological mechanism where the active form of 25(OH)D may influence n-6 PUFA metabolism. These relationships warrant further investigation in other populations. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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13 pages, 419 KiB

Open AccessArticle

A Metabolomics Analysis of Adiposity and Advanced Prostate Cancer Risk in the Health Professionals Follow-Up Study

by Barbra A. Dickerman, Ericka M. Ebot, Brian C. Healy, Kathryn M. Wilson, A. Heather Eliassen, Alberto Ascherio, Claire H. Pernar, Oana A. Zeleznik, Matthew G. Vander Heiden, Clary B. Clish, Edward Giovannucci and Lorelei A. Mucci

Metabolites 2020, 10(3), 99; https://doi.org/10.3390/metabo10030099 - 10 Mar 2020

Cited by 11 | Viewed by 3278

Abstract

Obesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson [...] Read more.

Obesity is associated with a higher risk of advanced prostate cancer, but men with the same body mass index (BMI) may differ in their underlying metabolic health. Using metabolomics data from nested case-control studies in the Health Professionals Follow-Up Study, we calculated Pearson correlations between 165 circulating metabolites and three adiposity measures (BMI, waist circumference, and derived fat mass from a validated prediction equation) to identify adiposity-associated metabolites. We used Lasso to further select metabolites for prediction models of adiposity measures, which we used to calculate metabolic scores representing metabolic obesity. In an independent set of 212 advanced prostate cancer cases (T3b/T4/N1/M1 or lethal during follow-up) and 212 controls, we used logistic regression to evaluate the associations between adiposity measures and metabolic scores with risk of advanced disease. All adiposity measures were associated with higher blood levels of carnitines (Pearson r range, 0.16 to 0.18) and lower levels of glutamine (r = −0.19) and glycine (r, −0.29 to −0.20), in addition to alterations in various lipids. No adiposity measure or metabolic score was associated with risk of advanced prostate cancer (e.g., odds ratio for a 5 kg/m² increase in BMI 0.96 (95% CI: 0.73, 1.27) and BMI metabolic score 1.18 (95% CI: 0.57, 2.48)). BMI, waist circumference, and derived fat mass were associated with a broad range of metabolic alterations. Neither adiposity nor metabolic scores were associated with risk of advanced prostate cancer. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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Review

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18 pages, 765 KiB

Open AccessReview

Integrative Metabolomics to Identify Molecular Signatures of Responses to Vaccines and Infections

by Joann Diray-Arce, Maria Giulia Conti, Boryana Petrova, Naama Kanarek, Asimenia Angelidou and Ofer Levy

Metabolites 2020, 10(12), 492; https://doi.org/10.3390/metabo10120492 - 30 Nov 2020

Cited by 38 | Viewed by 5425

Abstract

Approaches to the identification of metabolites have progressed from early biochemical pathway evaluation to modern high-dimensional metabolomics, a powerful tool to identify and characterize biomarkers of health and disease. In addition to its relevance to classic metabolic diseases, metabolomics has been key to [...] Read more.

Approaches to the identification of metabolites have progressed from early biochemical pathway evaluation to modern high-dimensional metabolomics, a powerful tool to identify and characterize biomarkers of health and disease. In addition to its relevance to classic metabolic diseases, metabolomics has been key to the emergence of immunometabolism, an important area of study, as leukocytes generate and are impacted by key metabolites important to innate and adaptive immunity. Herein, we discuss the metabolomic signatures and pathways perturbed by the activation of the human immune system during infection and vaccination. For example, infection induces changes in lipid (e.g., free fatty acids, sphingolipids, and lysophosphatidylcholines) and amino acid pathways (e.g., tryptophan, serine, and threonine), while vaccination can trigger changes in carbohydrate and bile acid pathways. Amino acid, carbohydrate, lipid, and nucleotide metabolism is relevant to immunity and is perturbed by both infections and vaccinations. Metabolomics holds substantial promise to provide fresh insight into the molecular mechanisms underlying the host immune response. Its integration with other systems biology platforms will enhance studies of human health and disease. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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13 pages, 239 KiB

Open AccessReview

Find the Needle in the Haystack, Then Find It Again: Replication and Validation in the ‘Omics Era

by Wei Perng and Stella Aslibekyan

Metabolites 2020, 10(7), 286; https://doi.org/10.3390/metabo10070286 - 12 Jul 2020

Cited by 14 | Viewed by 2542

Abstract

Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon [...] Read more.

Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon balancing false-positive associations with generalizability. Given the foundational role of reproducibility in scientific inference, replication and validation of ‘omics findings are cornerstones of this effort. In this narrative review, we define key terms relevant to replication and validation, present issues surrounding each concept with historical and contemporary examples from genomics (the most well-established and upstream ‘omics), discuss special issues and unique considerations for replication and validation in metabolomics (an emerging field and most downstream ‘omics for which best practices remain yet to be established), and make suggestions for future research leveraging multiple ‘omics datasets. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

20 pages, 295 KiB

Open AccessReview

Precision Nutrition and Childhood Obesity: A Scoping Review

by Yue Wu, Wei Perng and Karen E. Peterson

Metabolites 2020, 10(6), 235; https://doi.org/10.3390/metabo10060235 - 08 Jun 2020

Cited by 12 | Viewed by 5499

Abstract

Environmental exposures such as nutrition during life stages with high developmental plasticity—in particular, the in utero period, infancy, childhood, and puberty—may have long-lasting influences on risk of chronic diseases, including obesity-related conditions that manifest as early as childhood. Yet, specific mechanisms underlying these [...] Read more.

Environmental exposures such as nutrition during life stages with high developmental plasticity—in particular, the in utero period, infancy, childhood, and puberty—may have long-lasting influences on risk of chronic diseases, including obesity-related conditions that manifest as early as childhood. Yet, specific mechanisms underlying these relationships remain unclear. Here, we consider the study of ‘omics mechanisms, including nutrigenomics, epigenetics/epigenomics, and metabolomics, within a life course epidemiological framework to accomplish three objectives. First, we carried out a scoping review of population-based literature with a focus on studies that include ‘omics analyses during three sensitive periods during early life: in utero, infancy, and childhood. We elected to conduct a scoping review because the application of multi-‘omics and/or precision nutrition in childhood obesity prevention and treatment is relatively recent, and identifying knowledge gaps can expedite future research. Second, concomitant with the literature review, we discuss the relevance and plausibility of biological mechanisms that may underlie early origins of childhood obesity identified by studies to date. Finally, we identify current research limitations and future opportunities for application of multi-‘omics in precision nutrition/health practice. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

13 pages, 738 KiB

Open AccessReview

Systems Biology ARDS Research with a Focus on Metabolomics

by Sayed M. Metwaly and Brent W. Winston

Metabolites 2020, 10(5), 207; https://doi.org/10.3390/metabo10050207 - 19 May 2020

Cited by 15 | Viewed by 4241

Abstract

Acute respiratory distress syndrome (ARDS) is a clinical syndrome that inflicts a considerably heavy toll in terms of morbidity and mortality. While there are multitudes of conditions that can lead to ARDS, the vast majority of ARDS cases are caused by a relatively [...] Read more.

Acute respiratory distress syndrome (ARDS) is a clinical syndrome that inflicts a considerably heavy toll in terms of morbidity and mortality. While there are multitudes of conditions that can lead to ARDS, the vast majority of ARDS cases are caused by a relatively small number of diseases, especially sepsis and pneumonia. Currently, there is no clinically agreed upon reliable diagnostic test for ARDS, and the detection or diagnosis of ARDS is based on a constellation of laboratory and radiological tests in the absence of evidence of left ventricular dysfunction, as specified by the Berlin definition of ARDS. Virtually all the ARDS biomarkers to date have been proven to be of very limited clinical utility. Given the heterogeneity of ARDS due to the wide variation in etiology, clinical and molecular manifestations, there is a current scientific consensus agreement that ARDS is not just a single entity but rather a spectrum of conditions that need further study for proper classification, the identification of reliable biomarkers and the adequate institution of therapeutic targets. This scoping review aims to elucidate ARDS omics research, focusing on metabolomics and how metabolomics can boost the study of ARDS biomarkers and help to facilitate the identification of ARDS subpopulations. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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10 pages, 416 KiB

Open AccessReview

Metabolome–Microbiome Crosstalk and Human Disease

by Kathleen A. Lee-Sarwar, Jessica Lasky-Su, Rachel S. Kelly, Augusto A. Litonjua and Scott T. Weiss

Metabolites 2020, 10(5), 181; https://doi.org/10.3390/metabo10050181 - 01 May 2020

Cited by 48 | Viewed by 6675

Abstract

In this review, we discuss the growing literature demonstrating robust and pervasive associations between the microbiome and metabolome. We focus on the gut microbiome, which harbors the taxonomically most diverse and the largest collection of microorganisms in the human body. Methods for integrative [...] Read more.

In this review, we discuss the growing literature demonstrating robust and pervasive associations between the microbiome and metabolome. We focus on the gut microbiome, which harbors the taxonomically most diverse and the largest collection of microorganisms in the human body. Methods for integrative analysis of these “omics” are under active investigation and we discuss the advances and challenges in the combined use of metabolomics and microbiome data. Findings from large consortia, including the Human Microbiome Project and Metagenomics of the Human Intestinal Tract (MetaHIT) and others demonstrate the impact of microbiome-metabolome interactions on human health. Mechanisms whereby the microbes residing in the human body interact with metabolites to impact disease risk are beginning to be elucidated, and discoveries in this area will likely be harnessed to develop preventive and treatment strategies for complex diseases. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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13 pages, 233 KiB

Open AccessEditor’s ChoiceReview

A Review of Lipidomics of Cardiovascular Disease Highlights the Importance of Isolating Lipoproteins

by Ming Ding and Kathryn M. Rexrode

Metabolites 2020, 10(4), 163; https://doi.org/10.3390/metabo10040163 - 23 Apr 2020

Cited by 67 | Viewed by 5084

Abstract

Cutting-edge lipidomic profiling measures hundreds or even thousands of lipids in plasma and is increasingly used to investigate mechanisms of cardiovascular disease (CVD). In this review, we introduce lipidomic techniques, describe distributions of lipids across lipoproteins, and summarize findings on the association of [...] Read more.

Cutting-edge lipidomic profiling measures hundreds or even thousands of lipids in plasma and is increasingly used to investigate mechanisms of cardiovascular disease (CVD). In this review, we introduce lipidomic techniques, describe distributions of lipids across lipoproteins, and summarize findings on the association of lipids with CVD based on lipidomics. The main findings of 16 cohort studies were that, independent of total and high-density lipoprotein cholesterol (HDL-c), ceramides (d18:1/16:0, d18:1/18:0, and d18:1/24:1) and phosphatidylcholines (PCs) containing saturated and monounsaturated fatty acyl chains are positively associated with risks of CVD outcomes, while PCs containing polyunsaturated fatty acyl chains (PUFA) are inversely associated with risks of CVD outcomes. Lysophosphatidylcholines (LPCs) may be positively associated with risks of CVD outcomes. Interestingly, the distributions of the identified lipids vary across lipoproteins: LPCs are primarily contained in HDLs, ceramides are mainly contained in low-density lipoproteins (LDLs), and PCs are distributed in both HDLs and LDLs. Thus, the potential mechanism behind previous findings may be related to the effect of the identified lipids on the biological functions of HDLs and LDLs. Only eight studies on the lipidomics of HDL and non-HDL particles and CVD outcomes have been conducted, which showed that higher triglycerides (TAGs), lower PUFA, lower phospholipids, and lower sphingomyelin content in HDLs might be associated with a higher risk of coronary heart disease (CHD). However, the generalizability of these studies is a major concern, given that they used case–control or cross-sectional designs in hospital settings, included a very small number of participants, and did not correct for multiple testing or adjust for blood lipids such as HDL-c, low-density lipoprotein cholesterol (LDL-c), or TAGs. Overall, findings from the literature highlight the importance of research on lipidomics of lipoproteins to enhance our understanding of the mechanism of the association between the identified lipids and the risk of CVD and allow the identification of novel lipid biomarkers in HDLs and LDLs, independent of HDL-c and LDL-c. Lipidomic techniques show the feasibility of this exciting research direction, and the lack of high-quality epidemiological studies warrants well-designed prospective cohort studies. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

13 pages, 574 KiB

Open AccessReview

An Integrative Approach to Assessing Diet–Cancer Relationships

by Rachel Murphy

Metabolites 2020, 10(4), 123; https://doi.org/10.3390/metabo10040123 - 25 Mar 2020

Cited by 8 | Viewed by 3957

Abstract

The relationship between diet and cancer is often viewed with skepticism by the public and health professionals, despite a considerable body of evidence and general consistency in recommendations over the past decades. A systems biology approach which integrates ‘omics’ data including metabolomics, genetics, [...] Read more.

The relationship between diet and cancer is often viewed with skepticism by the public and health professionals, despite a considerable body of evidence and general consistency in recommendations over the past decades. A systems biology approach which integrates ‘omics’ data including metabolomics, genetics, metagenomics, transcriptomics and proteomics holds promise for developing a better understanding of how diet affects cancer and for improving the assessment of diet through biomarker discovery thereby renewing confidence in diet–cancer links. This review discusses the application of multi-omics approaches to studies of diet and cancer. Considerations and challenges that need to be addressed to facilitate the investigation of diet–cancer relationships with multi-omic approaches are also discussed. Full article

(This article belongs to the Special Issue Integrative-Metabolomics in Epidemiological Studies)

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