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. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage.
Abstract
Social isolation is associated with higher mortality in studies comprising mostly white adults, yet associations among black adults are unclear. In this prospective cohort study, we ...evaluated whether associations of social isolation with all-cause, cardiovascular disease, and cancer mortality differed by race and sex. Adults enrolled in Cancer Prevention Study II in 1982/1983 were followed for mortality through 2012 (n = 580,182). Sex- and race-specific multivariable-adjusted hazard ratios and 95% confidence intervals were estimated for associations of a 5-point social isolation score with risk of death. Social isolation was associated with all-cause mortality in all subgroups (P for trend ≤ 0.005); for the most isolated versus the least isolated, the hazard ratios were 2.34 (95% confidence interval (CI): 1.58, 3.46) and 1.60 (95% CI: 1.41, 1.82) among black men and white men, respectively (P for interaction = 0.40) and 2.13 (95% CI: 1.44, 3.15) and 1.84 (95% CI: 1.68, 2.01) among black women and white women, respectively (P for interaction = 0.89). The association did not differ between black men and black women (P for interaction = 0.33) but was slightly stronger in white women than in white men (P for interaction = 0.01). Social isolation was associated with cardiovascular disease mortality in each subgroup (P for trend < 0.03) but with cancer mortality only among whites (P for trend < 0.0001). Subgroup differences in the influence of specific social isolation components were identified. Identifying and intervening with socially isolated adults could improve health outcomes.
Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and ...etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk.
Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case-cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling.
A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association ranging from RR = 0.85 (95% CI 0.80-0.92) to RR = 0.88 (95% CI 0.82-0.94) and one having a positive association RR = 1.14 (95% CI 1.06-1.23). An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81-0.94) to RR = 0.91 (95% CI 0.85-0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05-1.22) to RR = 1.11 (95% CI 1.02-1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products.
Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer.
Recent studies suggest that untargeted metabolomics is a promising tool to identify novel biomarkers of individual foods. However, few large cross-sectional studies with comprehensive data on ...habitual diet and circulating metabolites have been conducted.
We aimed to identify potential food biomarkers and evaluate their predictive accuracy.
We conducted a cross-sectional analysis of consumption of 91 food groups or items, assessed by a 152-item food-frequency questionnaire, in relation to 1186 serum metabolites measured by mass spectrometry-based platforms from 1369 nonsmoking postmenopausal women (mean age = 68.3 y). Diet-metabolite associations were selected by Pearson's partial correlation analysis (P < 4.63 × 10−7, |r| > 0.2). The predictive accuracy of the selected food metabolites was evaluated from the area under the curve (AUC) calculated from receiver operating characteristic analysis conducted among women in the top and bottom quintiles of dietary intake.
We identified 379 diet-metabolite associations. Forty-two food groups or items were correlated with 199 serum metabolites. We replicated 63 metabolites as biomarkers of habitual food intake reported in previous cross-sectional studies. Among those not previously shown to be associated with habitual diet, several are biologically plausible and were reported in acute feeding studies including: banana and dopamine 3-O-sulfate (r = 0.34, AUC = 76%) and dopamine 4-O-sulfate (r = 0.33, AUC = 74%), garlic and alliin (r = 0.24, AUC = 69%), N-acetylalliin (r = 0.27, AUC = 70%), and S-allylcysteine (r = 0.23, AUC = 69). Two unannotated metabolites were the strongest predictors for dark fish (X-02269, r = 0.51, AUC = 94%) and coffee intake (X-21442, r = 0.62, AUC = 98%).
In this comprehensive, cross-sectional analysis of habitual food intake and serum metabolites among postmenopausal women, we identified several potentially novel food biomarkers and replicated others. Our findings contribute to the limited literature on food-based biomarkers and highlight the significant and promising role that large cohort studies with archived blood samples could play in this field. This study was registered at clinicaltrials.gov as NCT03282812.
Background Studies of breast cancer in women and laboratory studies provide evidence that shift work involving circadian rhythm disruption is a probable human carcinogen. However, evidence linking ...shift work and other circadian disruption factors to prostate cancer risk is limited. Purpose To examine associations of work schedule (i.e., rotating shift work, fixed night and fixed afternoon/evening shift work); sleep duration; and insomnia frequency with prostate cancer mortality. Methods The Cancer Prevention Study–II is a large prospective cohort study of U.S. adults. Work schedule, sleep duration, insomnia frequency, and other information was self-reported in 1982. Among 305,057 employed men, aged ≥29 years who were cancer free at baseline, there were 4974 prostate cancer deaths during follow-up through 2010. In 2013, multivariable-adjusted relative risks (RRs) and 95% CIs were computed using Cox proportional hazards regression. Results Work schedule and insomnia frequency were not associated with risk of fatal prostate cancer. Short sleep duration was associated with higher risk of prostate cancer during the first 8 years of follow-up, compared to 7 hours/night, the RRs (95% CIs) for 3–5 and 6 hours/night were 1.64 (1.06, 2.54), and 1.28 (0.98, 1.67), respectively. There was no association between sleep duration and fatal prostate cancer during later follow-up. Conclusions These results do not support associations of work schedule or insomnia frequency with prostate cancer mortality. The association between short sleep duration and higher risk of fatal prostate cancer only during the first 8 years of follow-up suggests that short sleep duration could affect later stages of prostate carcinogenesis.
Quitting smoking provides important health benefits to patients with cancer. A cancer diagnosis may motivate quitting-potentially providing a teachable moment in which oncologists can encourage and ...assist patients to quit-but little is known about whether a recent cancer diagnosis (including diagnosis of a cancer that is less strongly linked to smoking) is associated with increased quitting.
Cancer Prevention Study-II Nutrition Cohort participants reported smoking status at enrollment in 1992 to 1993 and approximately biennially through 2009. Quit rates of smokers diagnosed with cancer during 2- and 4-year intervals were compared with those of smokers not diagnosed with cancer (12,182 and 12,538 smokers in 2- and 4-year analyses, respectively). Cancers likely to cause physical limitations or symptoms that could influence smoking (cancers of the lung, head and neck, esophagus, or any metastatic cancer) were excluded. Logistic regressions calculated quit rates controlling for age, sex, survey year, cardiovascular disease, and chronic obstructive pulmonary disease.
The 2-year quit rate was higher among the 772 smokers who were diagnosed with cancer (31.3%; 95% CI, 28.0% to 34.5%) than among smokers not diagnosed with cancer (19.5%; 95% CI, 19.0% to 19.9%). A similar difference was observed for 4-year quit rates (43.0% v 33.8%). Results were similar by cancer site and stage.
A diagnosis of cancer, even a cancer not strongly related to smoking and with a relatively good prognosis, may be associated with increased quitting that is sustained well after diagnosis. Results support the hypothesis that a cancer diagnosis presents a teachable moment that can be capitalized on to promote cessation.
Healthy diet patterns are associated with lower risk of cancer and other chronic diseases. Metabolomics has the potential to expand dietary biomarker development to include dietary patterns, which ...may provide a complement or alternative to self-reported diet.
This study examined the correlation of serum untargeted metabolomic markers with 4 diet pattern scores—the alternate Mediterranean diet score (aMED), alternate Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension (DASH) diet, and the Healthy Eating Index (HEI)-2015—and used multivariate methods to identify discriminatory metabolites for each pattern.
Among 1367 US postmenopausal women with serum metabolomic data in the Cancer Prevention Study-II Nutrition Cohort, we conducted partial correlation analysis, adjusted for demographic and lifestyle variables, to examine cross-sectional correlations between serum metabolomic markers and healthy diet pattern scores. In a randomly selected “training” set (50%), we conducted orthogonal partial least-squares discriminant analysis to identify metabolites that discriminated the top from bottom diet score quintiles. Combinations of metabolites with a variable importance in projection (VIP) score ≥2.5 were tested for predictability in the “testing” set based on the use of receiver operating characteristic curves.
Out of 1186 metabolites, 32 unique metabolites were considered discriminatory based on a VIP score ≥2.5 in the training dataset with some overlap across scores (aMED=16; AHEI=17; DASH=13; HEI=12). Spearman partial correlation analyses, applying a cut-point (|r|≥0.15) and Bonferroni correction (P<1.05×10−5), identified similar key metabolites. The top 5 metabolites for each pattern mostly distinguished high compared with low scores; 4 of the 5 (fish-derived) metabolites were the same for aMED and AHEI, 2 of which were identified for HEI; 4 DASH metabolites were unique.
Metabolomic methods that used a split-sample approach identified potential biomarkers for 4 healthy diet patterns. Similar metabolites across scores reflect fish consumption in healthy dietary patterns. These findings should be replicated in independent populations.
For infections to be maintained in a population, pathogens must compete to colonize hosts and transmit between them. We use an experimental approach to investigate within-and-between host dynamics ...using the pathogen Pseudomonas aeruginosa and the animal host Caenorhabditis elegans. Within-host interactions can involve the production of goods that are beneficial to all pathogens in the local environment but susceptible to exploitation by non-producers. We exposed the nematode host to ‘producer’ and two ‘non-producer’ bacterial strains (specifically for siderophore production and quorum sensing), in single infections and coinfections, to investigate within-host colonization. Subsequently, we introduced infected nematodes to pathogen-naive populations to allow natural transmission between hosts. We find that producer pathogens are consistently better at colonizing hosts and transmitting between them than non-producers during coinfection and single infection. Non-producers were poor at colonizing hosts and between-host transmission, even when coinfecting with producers. Understanding pathogen dynamics across these multiple levels will ultimately help us predict and control the spread of infections, as well as contribute to explanations for the persistence of cooperative genotypes in natural populations.
Defining the complex role of the microbiome in colorectal cancer and the discovery of novel, protumorigenic microbes are areas of active investigation. In the present study, culturing and ...reassociation experiments revealed that toxigenic strains of Clostridioides difficile drove the tumorigenic phenotype of a subset of colorectal cancer patient-derived mucosal slurries in germ-free ApcMin/+ mice. Tumorigenesis was dependent on the C. difficile toxin TcdB and was associated with induction of Wnt signaling, reactive oxygen species, and protumorigenic mucosal immune responses marked by the infiltration of activated myeloid cells and IL17-producing lymphoid and innate lymphoid cell subsets. These findings suggest that chronic colonization with toxigenic C. difficile is a potential driver of colorectal cancer in patients.
Colorectal cancer is a leading cause of cancer and cancer-related deaths worldwide, with a multifactorial etiology that likely includes procarcinogenic bacteria. Using human colon cancer specimens, culturing, and murine models, we demonstrate that chronic infection with the enteric pathogen C. difficile is a previously unrecognized contributor to colonic tumorigenesis. See related commentary by Jain and Dudeja, p. 1838. This article is highlighted in the In This Issue feature, p. 1825.
PDF
