Metabolic phenotyping for discovery of urinary biomarkers of diet, xenobiotics and blood pressure in the INTERMAP Study: an overview

Metabolomics analysis of pathways underlying radiation-induced salivary gland dysfunction stages

Salivary gland hypofunction is an adverse side effect associated with radiotherapy for head and neck cancer patients. This study delineated metabolic changes at acute, intermediate, and chronic radiation damage response stages in mouse salivary glands following a single 5 Gy dose. Ultra-high performance liquid chromatography-mass spectrometry was performed on parotid salivary gland tissue collected at 3, 14, and 30 days following radiation (IR). Pathway enrichment analysis, network analysis based on metabolite structural similarity, and network analysis based on metabolite abundance correlations were used to incorporate both metabolite levels and structural annotation. The greatest number of enriched pathways are observed at 3 days and the lowest at 30 days following radiation. Amino acid metabolism pathways, glutathione metabolism, and central carbon metabolism in cancer are enriched at all radiation time points across different analytical methods. This study suggests that glutathione and central carbon metabolism in cancer may be important pathways in the unresolved effect of radiation treatment.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Charged metabolite biomarkers of food intake assessed via plasma metabolomics in a population-based observational study in Japan

Food intake biomarkers can be critical tools that can be used to objectively assess dietary exposure for both epidemiological and clinical nutrition studies. While an accurate estimation of food intake is essential to unravel associations between the intake and specific health conditions, random and systematic errors affect self-reported assessments. This study aimed to clarify how habitual food intake influences the circulating plasma metabolome in a free-living Japanese regional population and to identify potential food intake biomarkers. To achieve this aim, we conducted a cross-sectional analysis as part of a large cohort study. From a baseline survey of the Tsuruoka Metabolome Cohort Study, 7,012 eligible male and female participants aged 40-69 years were chosen for this study. All data on patients' health status and dietary intake were assessed via a food frequency questionnaire, and plasma samples were obtained during an annual physical examination. Ninety-four charged plasma metabolites were measured using capillary electrophoresis mass spectrometry, by a non-targeted approach. Statistical analysis was performed using partial-least-square regression. A total of 21 plasma metabolites were likely to be associated with long-term food intake of nine food groups. In particular, the influential compounds in each food group were hydroxyproline for meat, trimethylamine-N-oxide for fish, choline for eggs, galactarate for dairy, cystine and betaine for soy products, threonate and galactarate for carotenoid-rich vegetables, proline betaine for fruits, quinate and trigonelline for coffee, and pipecolate for alcohol, and these were considered as prominent food intake markers in Japanese eating habits. A set of circulating plasma metabolites was identified as potential food intake biomarkers in the Japanese community-dwelling population. These results will open the way for the application of new reliable dietary assessment tools not by self-reported measurements but through objective quantification of biofluids.

Study protocol: The INTERMAP China Prospective (ICP) study

Background: Unfavourable blood pressure (BP) level is an established risk factor for cardiovascular diseases (CVD), while the exact underlying reasons for unfavourable BP are poorly understood.  The INTERMAP China Prospective (ICP) Study is a prospective cohort to investigate the relationship of environmental and nutritional risk factors with key indicators of vascular function (BP, arterial stiffness, carotid-intima media thickness) among middle-aged/older men and women. Methods: A total of 839 Chinese participants aged 40-59 years from three diverse regions of China were enrolled in INTERMAP in 1997/98; data collection included repeated BP measurements, 24-hour urine specimens, and 24-hour dietary recalls.  In 2015/16, 574 of these 839 persons were re-enrolled along with 208 new participants aged 40-59 years that were randomly selected from the same study villages.  Participant’s environmental and dietary exposures and health outcomes were assessed in this open cohort study, including BP, 24-hour dietary recalls, personal exposures to air pollution, grip strength, arterial stiffness, carotid-media thickness and plaques, cognitive function, and sleep patterns.  Serum and plasma specimens were collected with 24-hour urine specimens. A follow-up visit has been scheduled for 2020-2021. Discussion:  Winter and summer assessments of a comprehensive set of vascular indicators and their environmental and nutritional risk factors were conducted with high precision.  We will leverage advances in exposome research to identify biomarkers of exposure to environmental and nutritional risk factors and improve our understanding of the mechanisms and pathways of their hazardous cardiovascular effects.  The ICP Study is observational by design, thus subject to several biases including selection bias (e.g., loss to follow-up), information bias (e.g., measurement error), and confounding that we sought to mitigate through our study design and measurements.  However, extensive efforts will apply to minimize those limitations (continuous observer training, repeated measurements of BP, standardized methods in data collection and measurements, and on-going quality control).

Study protocol: The INTERMAP China Prospective (ICP) study

Background: Unfavourable blood pressure (BP) level is an established risk factor for cardiovascular diseases (CVD), while the exact underlying reasons for unfavourable BP are poorly understood.  The INTERMAP China Prospective (ICP) Study is a prospective cohort to investigate the relationship of environmental and nutritional risk factors with key indicators of vascular function including BP, arterial stiffness, and carotid-intima media thickness. Methods: A total of 839 Chinese participants aged 40-59 years from three diverse regions of China were enrolled in INTERMAP in 1997/98; data collection included repeated BP measurements, 24-hour urine specimens, and 24-hour dietary recalls.  In 2015/16, 574 of these 839 persons were re-enrolled along with 208 new participants aged 40-59 years that were randomly selected from the same study villages.  Participant’s environmental and dietary exposures and health outcomes were assessed in this open cohort study, including BP, 24-hour dietary recalls, personal exposures to air pollution, grip strength, arterial stiffness, carotid-media thickness and plaques, cognitive function, and sleep patterns.  Serum and plasma specimens were collected with 24-hour urine specimens. Discussion:  Winter and summer assessments of a comprehensive set of vascular indicators and their environmental and nutritional risk factors were conducted with high precision.  We will leverage advances in exposome research to identify biomarkers of exposure to environmental and nutritional risk factors and improve our understanding of the mechanisms and pathways of their hazardous cardiovascular effects.  The ICP Study is observational by design, thus subject to several biases including selection bias (e.g., loss to follow-up), information bias (e.g., measurement error), and confounding that we sought to mitigate through our study design and measurements.  However, extensive efforts will apply to minimize those limitations (continuous observer training, repeated measurements of BP, standardized methods in data collection and measurements, and on-going quality control).

The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies

The Consortium of Metabolomics Studies (COMETS) was established in 2014 to facilitate large-scale collaborative research on the human metabolome and its relationship with disease etiology, diagnosis, and prognosis. COMETS comprises 47 cohorts from Asia, Europe, North America, and South America that together include more than 136,000 participants with blood metabolomics data on samples collected from 1985 to 2017. Metabolomics data were provided by 17 different platforms, with the most frequently used labs being Metabolon, Inc. (14 cohorts), the Broad Institute (15 cohorts), and Nightingale Health (11 cohorts). Participants have been followed for a median of 23 years for health outcomes including death, cancer, cardiovascular disease, diabetes, and others; many of the studies are ongoing. Available exposure-related data include common clinical measurements and behavioral factors, as well as genome-wide genotype data. Two feasibility studies were conducted to evaluate the comparability of metabolomics platforms used by COMETS cohorts. The first study showed that the overlap between any 2 different laboratories ranged from 6 to 121 metabolites at 5 leading laboratories. The second study showed that the median Spearman correlation comparing 111 overlapping metabolites captured by Metabolon and the Broad Institute was 0.79 (interquartile range, 0.56-0.89).

Serum Concentrations of Citrate, Tyrosine, 2- and 3- Hydroxybutyrate are Associated with Increased 3-Month Mortality in Acute Heart Failure Patients

Considering the already established relationship between the extent of the metabolic dysfunction and the severity of heart failure (HF), it is conceivable that the metabolomic profile of the serum may have a prognostic capacity for 3-month mortality in acute heart failure (AHF). Out of 152 recruited patients, 130 serum samples were subjected to the metabolomic analyses. The 3-month mortality rate was 24.6% (32 patients). Metabolomic profiling by nuclear magnetic resonance spectroscopy found that the serum levels of 2-hydroxybutyrate (2-HB), 3-hydoxybutyrate (3-HB), lactate, citrate, and tyrosine, were higher in patients who died within 3 months compared to those who were alive 3 months after onset of AHF, which was confirmed by univariable logistic regression analyses (p = 0.009, p = 0.005, p = 0.008, p<0.001, and p<0.001, respectively). These associations still remained significant for all tested metabolites except for lactate after adjusting for established prognostic parameters in HF. In conclusion, serum levels of 2-HB, 3-HB, tyrosine, and citrate measured at admission are associated with an increased 3-month mortality rate in AHF patients and might thus be of prognostic value in AHF.

Gut microbiota and inflammation in chronic kidney disease and their roles in the development of cardiovascular disease

The health and proper functioning of the cardiovascular and renal systems largely depend on crosstalk in the gut-kidney-heart/vessel triangle. Recent evidence suggests that the gut microbiota has an integral function in this crosstalk. Mounting evidence indicates that the development of chronic kidney and cardiovascular diseases follows chronic inflammatory processes that are affected by the gut microbiota via various immune, metabolic, endocrine, and neurologic pathways. Additionally, deterioration of the function of the cardiovascular and renal systems has been reported to disrupt the original gut microbiota composition, further contributing to the advancement of chronic cardiovascular and renal diseases. Considering the interaction between the gut microbiota and the renal and cardiovascular systems, we can infer that interventions for the gut microbiota through diet and possibly some medications can prevent/stop the vicious cycle between the gut microbiota and the cardiovascular/renal systems, leading to a decrease in chronic cardiovascular and renal diseases.

A randomized controlled crossover trial evaluating differential responses to antihypertensive drugs (used as mono- or dual therapy) on the basis of ethnicity: The comparIsoN oF Optimal Hypertension RegiMens; part of the Ancestry Informative Markers in HYpertension program-AIM-HY INFORM trial

Background

Ethnicity, along with a variety of genetic and environmental factors, is thought to influence the efficacy of antihypertensive therapies. Current UK guidelines use a “black versus white” approach; in doing so, they ignore the United Kingdom's largest ethnic minority: Asians from South Asia.

Study design

The primary purpose of the AIM-HY INFORM trial is to identify potential differences in response to antihypertensive drugs used as mono- or dual therapy on the basis of self-defined ethnicity. A multicenter, prospective, open-label, randomized study with 2 parallel, independent trial arms (mono- and dual therapy), AIM-HY INFORM plans to enroll a total of 1,320 patients from across the United Kingdom. Those receiving monotherapy (n = 660) will enter a 3-treatment (amlodipine 10 mg od; lisinopril 20 mg od; chlorthalidone 25 mg od), 3-period crossover, lasting 24 weeks, whereas those receiving dual therapy (n = 660) will enter a 4-treatment (amlodipine 5 mg od and lisinopril 20 mg od; amlodipine 5 mg od and chlorthalidone 25 mg od; lisinopril 20 mg od and chlorthalidone 25 mg od; amiloride 10 mg od and chlorthalidone 25 mg od), 4-period crossover, lasting 32 weeks. Equal numbers of 3 ethnic groups (white, black/black British, and Asian/Asian British) will ultimately be recruited to each of the trial arms (ie, 220 participants per ethnic group per arm). Seated, automated, unattended, office, systolic blood pressure measured 8 weeks after each treatment period begins will serve as the primary outcome measure.

Conclusion

AIM-HY INFORM is a prospective, open-label, randomized trial which aims to evaluate first- and second-line antihypertensive therapies for multiethnic populations.

Beyond genomics: understanding exposotypes through metabolomics

BACKGROUND

Over the past 20 years, advances in genomic technology have enabled unparalleled access to the information contained within the human genome. However, the multiple genetic variants associated with various diseases typically account for only a small fraction of the disease risk. This may be due to the multifactorial nature of disease mechanisms, the strong impact of the environment, and the complexity of gene-environment interactions. Metabolomics is the quantification of small molecules produced by metabolic processes within a biological sample. Metabolomics datasets contain a wealth of information that reflect the disease state and are consequent to both genetic variation and environment. Thus, metabolomics is being widely adopted for epidemiologic research to identify disease risk traits. In this review, we discuss the evolution and challenges of metabolomics in epidemiologic research, particularly for assessing environmental exposures and providing insights into gene-environment interactions, and mechanism of biological impact.

MAIN TEXT

Metabolomics can be used to measure the complex global modulating effect that an exposure event has on an individual phenotype. Combining information derived from all levels of protein synthesis and subsequent enzymatic action on metabolite production can reveal the individual exposotype. We discuss some of the methodological and statistical challenges in dealing with this type of high-dimensional data, such as the impact of study design, analytical biases, and biological variance. We show examples of disease risk inference from metabolic traits using metabolome-wide association studies. We also evaluate how these studies may drive precision medicine approaches, and pharmacogenomics, which have up to now been inefficient. Finally, we discuss how to promote transparency and open science to improve reproducibility and credibility in metabolomics.

CONCLUSIONS

Comparison of exposotypes at the human population level may help understanding how environmental exposures affect biology at the systems level to determine cause, effect, and susceptibilities. Juxtaposition and integration of genomics and metabolomics information may offer additional insights. Clinical utility of this information for single individuals and populations has yet to be routinely demonstrated, but hopefully, recent advances to improve the robustness of large-scale metabolomics will facilitate clinical translation.

Reliability of plasma polar metabolite concentrations in a large-scale cohort study using capillary electrophoresis-mass spectrometry

Background

Cohort studies with metabolomics data are becoming more widespread, however, large-scale studies involving 10,000s of participants are still limited, especially in Asian populations. Therefore, we started the Tsuruoka Metabolomics Cohort Study enrolling 11,002 community-dwelling adults in Japan, and using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography–mass spectrometry. The CE-MS method is highly amenable to absolute quantification of polar metabolites, however, its reliability for large-scale measurement is unclear. The aim of this study is to examine reproducibility and validity of large-scale CE-MS measurements. In addition, the study presents absolute concentrations of polar metabolites in human plasma, which can be used in future as reference ranges in a Japanese population.

Methods

Metabolomic profiling of 8,413 fasting plasma samples were completed using CE-MS, and 94 polar metabolites were structurally identified and quantified. Quality control (QC) samples were injected every ten samples and assessed throughout the analysis. Inter- and intra-batch coefficients of variation of QC and participant samples, and technical intraclass correlation coefficients were estimated. Passing-Bablok regression of plasma concentrations by CE-MS on serum concentrations by standard clinical chemistry assays was conducted for creatinine and uric acid.

Results and conclusions

In QC samples, coefficient of variation was less than 20% for 64 metabolites, and less than 30% for 80 metabolites out of the 94 metabolites. Inter-batch coefficient of variation was less than 20% for 81 metabolites. Estimated technical intraclass correlation coefficient was above 0.75 for 67 metabolites. The slope of Passing-Bablok regression was estimated as 0.97 (95% confidence interval: 0.95, 0.98) for creatinine and 0.95 (0.92, 0.96) for uric acid. Compared to published data from other large cohort measurement platforms, reproducibility of metabolites common to the platforms was similar to or better than in the other studies. These results show that our CE-MS platform is suitable for conducting large-scale epidemiological studies.