Effects of Preanalytical Sample Collection and Handling on Comprehensive Metabolite Measurements in Human Urine Biospecimens.

Epidemiology studies evaluate associations between the metabolome and disease risk. Urine is a common biospecimen used for such studies due to its wide availability and non-invasive collection. Evaluating the robustness of urinary metabolomic profiles under varying preanalytical conditions is thus of interest.

Metabolomics 2023 workshop report: moving toward consensus on best QA/QC practices in LC-MS-based untargeted metabolomics.

Introduction: During the Metabolomics 2023 conference, the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) presented a QA/QC workshop for LC-MS-based untargeted metabolomics.

Objectives: The Best Practices Working Group disseminated recent findings from community forums and discussed aspects to include in a living guidance document.

Methods: Presentations focused on reference materials, data quality review, metabolite identification/annotation and quality assurance.

Workshop report - interdisciplinary metabolomic epidemiology: the pathway to clinical translation.

Metabolomic epidemiology studies are complex and require a broad array of domain expertise. Although many metabolite-phenotype associations have been identified; to date, few findings have been translated to the clinic. Bridging this gap requires understanding of both the underlying biology of these associations and their potential clinical implications, necessitating an interdisciplinary team approach.

Effects of Preanalytical Sample Collection and Handling on Comprehensive Metabolite Measurements in Human Urine Biospecimens.

Epidemiology studies evaluate associations between the metabolome and disease risk. Urine is a common biospecimen used for such studies due to its wide availability and non-invasive collection. Evaluating the robustness of urinary metabolomic profiles under varying preanalytical conditions is thus of interest.

Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics.

Background: Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities.

Metabolomics 2022 workshop report: state of QA/QC best practices in LC-MS-based untargeted metabolomics, informed through mQACC community engagement initiatives.

Introduction: The Metabolomics Quality Assurance and Quality Control Consortium (mQACC) organized a workshop during the Metabolomics 2022 conference.

Objectives: The goal of the workshop was to disseminate recent findings from mQACC community-engagement efforts and to solicit feedback about a living guidance document of QA/QC best practices for untargeted LC-MS metabolomics.

Methods: Four QC-related topics were presented.

Characteristics of Cancer Epidemiology Studies That Employ Metabolomics: A Scoping Review.

An increasing number of cancer epidemiology studies use metabolomics assays. This scoping review characterizes trends in the literature in terms of study design, population characteristics, and metabolomics approaches and identifies opportunities for future growth and improvement. We searched PubMed/MEDLINE, Embase, Scopus, and Web of Science: Core Collection databases and included research articles that used metabolomics to primarily study cancer, contained a minimum of 100 cases in each main analysis stratum, used an epidemiologic study design, and were published in English from 1998 to June 2021.

An evaluation of the National Institutes of Health grants portfolio: identifying opportunities and challenges for multi-omics research that leverage metabolomics data.

Background: Through the systematic large-scale profiling of metabolites, metabolomics provides a tool for biomarker discovery and improving disease monitoring, diagnosis, prognosis, and treatment response, as well as for delineating disease mechanisms and etiology. As a downstream product of the genome and epigenome, transcriptome, and proteome activity, the metabolome can be considered as being the most proximal correlate to the phenotype. Integration of metabolomics data with other -omics data in multi-omics analyses has the potential to advance understanding of human disease development and treatment.

Building infrastructure at the National Cancer Institute to support metabolomic analyses in epidemiological studies.

In recent years, metabolomic analyses have been increasingly performed in studies with an epidemiological design. Since 2012, the National Cancer Institute has recognized the importance of supporting these efforts by strategically building resources and infrastructure to move this area forward. This review outlines those efforts, including building infrastructure, leveraging existing resources, establishing the COnsortium of METabolomics Studies (COMETS), and improving rigor and reproducibility.

COMETS Analytics: An Online Tool for Analyzing and Meta-Analyzing Metabolomics Data in Large Research Consortia.

Consortium-based research is crucial for producing reliable, high-quality findings, but existing tools for consortium studies have important drawbacks with respect to data protection, ease of deployment, and analytical rigor. To address these concerns, we developed COnsortium of METabolomics Studies (COMETS) Analytics to support and streamline consortium-based analyses of metabolomics and other -omics data. The application requires no specialized expertise and can be run locally to guarantee data protection or through a Web-based server for convenience and speed.

Preanalytical Sample Handling Conditions and Their Effects on the Human Serum Metabolome in Epidemiologic Studies.

Many epidemiologic studies use metabolomics for discovery-based research. The degree to which sample handling may influence findings, however, is poorly understood. In 2016, serum samples from 13 volunteers from the US Department of Agriculture's Beltsville Human Nutrition Research Center were subjected to different clotting (30 minutes/120 minutes) and refrigeration (0 minutes/24 hours) conditions, as well as different numbers (0/1/4) and temperatures (ice/refrigerator/room temperature) of thaws.

Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review.

Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019.

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.

The Metabolomics Society-Current State of the Membership and Future Directions.

In 2017, the Metabolomics Society conducted a survey among its members to assess the degree of its current success, define opportunities for improving its service to the community and make plans to establish future goals and direction of the Society. A 32-question online survey was sent via e-mail to all Metabolomics Society members as of 19 June 2017 (n = 644). In addition to the direct e-mails, the link to access the survey was made available through social media.

Metabolomics in epidemiologic research: challenges and opportunities for early-career epidemiologists.

Background: The application of metabolomics to epidemiologic studies is increasing.

Aim Of Review: Here, we describe the challenges and opportunities facing early-career epidemiologists aiming to apply metabolomics to their research.

Key Scientific Concepts Of Review: Many challenges inherent to metabolomics may provide early-career epidemiologists with the opportunity to play a pivotal role in answering critical methodological questions and moving the field forward.

Towards quality assurance and quality control in untargeted metabolomics studies.

We describe here the agreed upon first development steps and priority objectives of a community engagement effort to address current challenges in quality assurance (QA) and quality control (QC) in untargeted metabolomic studies. This has included (1) a QA and QC questionnaire responded to by the metabolomics community in 2015 which recommended education of the metabolomics community, development of appropriate standard reference materials and providing incentives for laboratories to apply QA and QC; (2) a 2-day 'Think Tank on Quality Assurance and Quality Control for Untargeted Metabolomic Studies' held at the National Cancer Institute's Shady Grove Campus and (3) establishment of the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) to drive forward developments in a coordinated manner.

Novel colon cancer susceptibility variants identified from a genome-wide association study in African Americans.

Genome-wide association studies (GWAS) in ethnic/racial minority populations can help to fine-map previously identified risk regions or discover new risk loci because of the genetic diversity in these populations. We conducted a GWAS of colorectal cancer (CRC) in 6,597 African Americans (1,894 cases and 4,703 controls) (Stage 1) and followed up the most promising markers in a replication set of 2,041 participants of African descent (891 cases and 1,150 controls) (Stage 2). We identified a novel variant, rs56848936 in the gene SYMPK at 19q13.

Genome-wide association study confirms lung cancer susceptibility loci on chromosomes 5p15 and 15q25 in an African-American population.

Objectives: Genome-wide association studies (GWAS) of lung cancer have identified regions of common genetic variation with lung cancer risk in Europeans who smoke and never-smoking Asian women. This study aimed to conduct a GWAS in African Americans, who have higher rates of lung cancer despite smoking fewer cigarettes per day when compared with Caucasians. This population provides a different genetic architecture based on underlying African ancestry allowing the identification of new regions and exploration of known regions for finer mapping.

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome.

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events.

Navigating the road ahead: addressing challenges for use of metabolomics in epidemiology studies.

Metabolomics platforms allow for the measurement of hundreds to thousands of unique small chemical entities, as well as offer extensive coverage of metabolic markers related to obesity, diet, smoking, and other exposures of high interest to health scientists. Nevertheless, its potential use as a tool in population-based study design has not been fully explored. As the field of metabolomics continues to mature, and in part, accelerate through the National Institutes of Health (NIH) investment of ≤65 million in the Common Fund's Metabolomics Program (https://common fund.

Characterization of large structural genetic mosaicism in human autosomes.

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals.

The use of metabolomics in population-based research.

The NIH has made a significant commitment through the NIH Common Fund's Metabolomics Program to build infrastructure and capacity for metabolomics research, which should accelerate the field. Given this investment, it is the ideal time to start planning strategies to capitalize on the infrastructure being established. An obvious gap in the literature relates to the effective use of metabolomics in large-population studies.

Genome-wide scan of 29,141 African Americans finds no evidence of directional selection since admixture.

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture.

Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33.

Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis.

Impact of obesity on cancer survivorship and the potential relevance of race and ethnicity.

Evidence that obesity is associated with cancer incidence and mortality is compelling. By contrast, the role of obesity in cancer survival is less well understood. There is inconsistent support for the role of obesity in breast cancer survival, and evidence for other tumor sites is scant.