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. 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. 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.

Women have a lower incidence of colorectal cancer (CRC) than men, however, they have a higher incidence of right-sided colon cancer (RCC). This is of concern as patients with RCC have the poorest clinical outcomes among all CRC patients. Aberrant metabolism is a known hallmark and therapeutic target for cancer. We propose that metabolic subphenotypes exist between CRCs due to intertumoral molecular and genomic variation, and differences in environmental milieu of the colon which vary between the sexes. Metabolomics analysis of patient colon tumors (n = 197) and normal tissues (n = 39) revealed sex-specific metabolic subphenotypes dependent on anatomic location. Tumors from women with RCC were nutrient-deplete, showing enhanced energy production to fuel asparagine synthesis and amino acid uptake. The clinical importance of our findings were further investigated in an independent data set from The Cancer Genomic Atlas, and demonstrated that high asparagine synthetase (ASNS) expression correlated with poorer survival for women. This is the first study to show a unique, nutrient-deplete metabolic subphenotype in women with RCC, with implications for tumor progression and outcomes in CRC patients.

Background: Colorectal cancer (CRC) incidence is rising in the young, yet the age of those affected is not clearly defined. In this study, we identify such cohorts and define clinicopathological features of early-onset colon and rectal cancers. Methods: The Surveillance, Epidemiology and End Results Program (SEER) database was queried to compare clinicopathological characteristics of colon and rectal cancers diagnosed during 1973–1995 with those diagnosed during 1995–2014. Results: We identified 430,886 patients with colon and rectal cancers. From 1973–1995 to 1995–2014, colon cancer incidence increased in patients aged 20–44 years, while rectal cancer incidence increased in patients aged ≤54 years. The percent change of cancer incidence was greatest for rectal cancer with a 41.5% (95% confidence interval (CI): 37.4–45.8%) increase compared to a 9.8% (CI: 6.2–13.6%) increase in colon cancer. Colon cancer has increased in tumors located in ascending, sigmoid, and rectosigmoid locations. Adenocarcinoma histology has increased in both colon and rectal cancers (P < 0.01), but mucinous and signet ring cell subtypes have not increased (P = 0.13 and 0.08, respectively). Incidence increases were race-specific, with rectal cancer seeing similar rises in white (38.4%, CI: 33.8–43.1%) and black populations (38.0%, CI: 26.2–51.2%), while colon cancer as a whole saw a rise in white (11.5%, CI: 7.2–15.9%) but not black populations (−6.8%, CI: −14.6–1.9%). Conclusions: Our study underscores the existence of key differences between early-onset colon (20–44 years) and rectal cancers (≤54 years) and provides evidence-based inclusion criteria for future investigations. We recommend that future research of CRC in the young should avoid investigating these cases as a single entity.

Racial and ethnic disparities have long been reported in the health care system, and the COVID-19 pandemic has further highlighted these inequities in medicine with disproportionately higher rates of both infection and death in Black and Hispanic patients.^1-3 Cancer treatment has not been immune to these incongruities, with racial and ethnic disparities consistently observed in survival outcomes.^4,5 Although national treatment guidelines exist, differences in care of patients based on sociodemographic features still persist and may contribute to these observed survival inequities.^6,7

Background: The aim of this study was to examine the differences in clinicopathological features, treatment strategies and prognosis between patients with proximal gastric cancer (PGC) and distal gastric cancer (DGC).