Investigation of microbe-metabolite relationships in the gut is needed to understand and potentially reduce colorectal cancer (CRC) risk.
Microbiota and metabolomics profiling were performed on ...lyophilized feces from 42 CRC cases and 89 matched controls. Multivariable logistic regression was used to identify statistically independent associations with CRC. First principal coordinate-component pair (PCo1-PC1) and false discovery rate (0.05)-corrected P-values were calculated for 116,000 Pearson correlations between 530 metabolites and 220 microbes in a sex*case/control meta-analysis.
Overall microbe-metabolite PCo1-PC1 was more strongly correlated in cases than in controls (Rho 0.606 vs 0.201, P = 0.01). CRC was independently associated with lower levels of Clostridia, Lachnospiraceae, p-aminobenzoate and conjugated linoleate, and with higher levels of Fusobacterium, Porphyromonas, p-hydroxy-benzaldehyde, and palmitoyl-sphingomyelin. Through postulated effects on cell shedding (palmitoyl-sphingomyelin), inflammation (conjugated linoleate), and innate immunity (p-aminobenzoate), metabolites mediated the CRC association with Fusobacterium and Porphyromonas by 29% and 34%, respectively. Overall, palmitoyl-sphingomyelin correlated directly with abundances of Enterobacteriaceae (Gammaproteobacteria), three Actinobacteria and five Firmicutes. Only Parabacteroides correlated inversely with palmitoyl-sphingomyelin. Other lipids correlated inversely with Alcaligenaceae (Betaproteobacteria). Six Bonferroni-significant correlations were found, including low indolepropionate and threnoylvaline with Actinobacteria and high erythronate and an uncharacterized metabolite with Enterobacteriaceae.
Feces from CRC cases had very strong microbe-metabolite correlations that were predominated by Enterobacteriaceae and Actinobacteria. Metabolites mediated a direct CRC association with Fusobacterium and Porphyromonas, but not an inverse association with Clostridia and Lachnospiraceae. This study identifies complex microbe-metabolite networks that may provide insights on neoplasia and targets for intervention.
Abstract
Background
Per- and polyfluoroalkyl substances (PFAS) are highly persistent chemicals that have been detected in the serum of over 98% of the US population. Studies among highly exposed ...individuals suggest an association with perfluorooctanoic acid (PFOA) exposure and kidney cancer. It remains unclear whether PFOA or other PFAS are renal carcinogens or if they influence risk of renal cell carcinoma (RCC) at concentrations observed in the general population.
Methods
We measured prediagnostic serum concentrations of PFOA and 7 additional PFAS in 324 RCC cases and 324 individually matched controls within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Multivariable conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs) relating serum PFAS concentrations and RCC risk. Individual PFAS were modeled continuously (log2-transformed) and categorically, with adjustment for kidney function and additional potential confounders. All statistical tests were 2-sided.
Results
We observed a positive association with RCC risk for PFOA (doubling in serum concentration, ORcontinuous = 1.71, 95% CI = 1.23 to 2.37, P = .002) and a greater than twofold increased risk among those in the highest quartile vs the lowest (OR = 2.63, 95% CI = 1.33 to 5.20, Ptrend = .007). The association with PFOA was similar after adjustment for other PFAS (ORcontinuous = 1.68, 95% CI = 1.07 to 2.63, P = .02) and remained apparent in analyses restricted to individuals without evidence of diminished kidney function and in cases diagnosed 8 or more years after phlebotomy.
Conclusions
Our findings add substantially to the weight of evidence that PFOA is a renal carcinogen and may have important public health implications for the many individuals exposed to this ubiquitous and highly persistent chemical.
The epidemiologic evidence for associations between dietary factors and breast cancer is weak and etiologic mechanisms are often unclear. Exploring the role of dietary biomarkers with metabolomics ...can potentially facilitate objective dietary characterization, mitigate errors related to self-reported diet, agnostically test metabolic pathways, and identify mechanistic mediators.
The aim of this study was to evaluate associations of diet-related metabolites with the risk of breast cancer in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial.
We examined prediagnostic serum concentrations of diet-related metabolites in a nested case-control study in 621 postmenopausal invasive breast cancer cases and 621 matched controls in the multicenter PLCO cohort. We calculated partial Pearson correlations between 617 metabolites and 55 foods, food groups, and vitamin supplements on the basis of the 2015 Dietary Guidelines for Americans and derived from a 137-item self-administered food-frequency questionnaire. Diet-related metabolites (P-correlation < 1.47 × 10−6) were evaluated in breast cancer analyses. ORs for the 90th compared with the 10th percentile were calculated by using conditional logistic regression, with body mass index, physical inactivity, other breast cancer risk factors, and caloric intake controlled for (false discovery rate <0.2).
Of 113 diet-related metabolites, 3 were associated with overall breast cancer risk (621 cases): caprate (10:0), a saturated fatty acid (OR: 1.77; 95% CI = 1.28, 2.43); γ-carboxyethyl hydrochroman (γ-CEHC), a vitamin E (γ-tocopherol) derivative (OR: 1.64; 95% CI: 1.18, 2.28); and 4-androsten-3β,17β-diol-monosulfate (1), an androgen (OR: 1.61; 95% CI: 1.20, 2.16). Nineteen metabolites were significantly associated with estrogen receptor (ER)–positive (ER+) breast cancer (418 cases): 12 alcohol-associated metabolites, including 7 androgens and α-hydroxyisovalerate (OR: 2.23; 95% CI: 1.50, 3.32); 3 vitamin E (tocopherol) derivatives (e.g., γ-CEHC; OR: 1.80; 95% CI: 1.20, 2.70); butter-associated caprate (10:0) (OR: 1.81; 95% CI: 1.23, 2.67); and fried food–associated 2-hydroxyoctanoate (OR: 1.46; 95% CI: 1.03, 2.07). No metabolites were significantly associated with ER-negative breast cancer (144 cases).
Prediagnostic serum concentrations of metabolites related to alcohol, vitamin E, and animal fats were moderately strongly associated with ER+ breast cancer risk. Our findings show how nutritional metabolomics might identify diet-related exposures that modulate cancer risk. This trial was registered at clinicaltrials.gov as NCT00339495.
Abstract
Background
Elevated body mass index (BMI) is associated with increased risk of postmenopausal breast cancer. The underlying mechanisms, however, remain elusive.
Methods
In a nested ...case–control study of 621 postmenopausal breast cancer case participants and 621 matched control participants, we measured 617 metabolites in prediagnostic serum. We calculated partial Pearson correlations between metabolites and BMI, and then evaluated BMI-associated metabolites (Bonferroni-corrected α level for 617 statistical tests = P < 8.10 × 10-5) in relation to invasive breast cancer. Odds ratios (ORs) of breast cancer comparing the 90th vs 10th percentile (modeled on a continuous basis) were estimated using conditional logistic regression while controlling for breast cancer risk factors, including BMI. Metabolites with the lowest P values (false discovery rate < 0.2) were mutually adjusted for one another to determine those independently associated with breast cancer risk.
Results
Of 67 BMI-associated metabolites, two were independently associated with invasive breast cancer risk: 16a-hydroxy-DHEA-3-sulfate (OR = 1.65, 95% confidence interval CI = 1.22 to 2.22) and 3-methylglutarylcarnitine (OR = 1.67, 95% CI = 1.21 to 2.30). Four metabolites were independently associated with estrogen receptor–positive (ER+) breast cancer risk: 16a-hydroxy-DHEA-3-sulfate (OR = 1.84, 95% CI = 1.27 to 2.67), 3-methylglutarylcarnitine (OR = 1.91, 95% CI = 1.23 to 2.96), allo-isoleucine (OR = 1.76, 95% CI = 1.23 to 2.51), and 2-methylbutyrylcarnitine (OR = 1.89, 95% CI = 1.22 to 2.91). In a model without metabolites, each 5 kg/m2 increase in BMI was associated with a 14% higher risk of breast cancer (OR = 1.14, 95% CI = 1.01 to 1.28), but adding 16a-hydroxy-DHEA-3-sulfate and 3-methylglutarylcarnitine weakened this association (OR = 1.06, 95% CI = 0.93 to 1.20), with the logOR attenuating by 57.6% (95% CI = 21.8% to 100.0+%).
Conclusion
These four metabolites may signal metabolic pathways that contribute to breast carcinogenesis and that underlie the association of BMI with increased postmenopausal breast cancer risk. These findings warrant further replication efforts.
In genome-wide association studies, ordinal categorical phenotypes are widely used to measure human behaviors, satisfaction, and preferences. However, because of the lack of analysis tools, methods ...designed for binary or quantitative traits are commonly used inappropriately to analyze categorical phenotypes. To accurately model the dependence of an ordinal categorical phenotype on covariates, we propose an efficient mixed model association test, proportional odds logistic mixed model (POLMM). POLMM is computationally efficient to analyze large datasets with hundreds of thousands of samples, can control type I error rates at a stringent significance level regardless of the phenotypic distribution, and is more powerful than alternative methods. In contrast, the standard linear mixed model approaches cannot control type I error rates for rare variants when the phenotypic distribution is unbalanced, although they performed well when testing common variants. We applied POLMM to 258 ordinal categorical phenotypes on array genotypes and imputed samples from 408,961 individuals in UK Biobank. In total, we identified 5,885 genome-wide significant variants, of which, 424 variants (7.2%) are rare variants with MAF < 0.01.
Abstract
Background
The authors investigated the durability of vaccine efficacy (VE) against human papillomavirus (HPV)16 or 18 infections and antibody response among nonrandomly assigned women who ...received a single dose of the bivalent HPV vaccine compared with women who received multiple doses and unvaccinated women.
Methods
HPV infections were compared between HPV16 or 18-vaccinated women aged 18 to 25 years who received one (N = 112), two (N = 62), or three (N = 1365) doses, and age- and geography-matched unvaccinated women (N = 1783) in the long-term follow-up of the Costa Rica HPV Vaccine Trial. Cervical HPV infections were measured at two study visits, approximately 9 and 11 years after initial HPV vaccination, using National Cancer Institute next-generation sequencing TypeSeq1 assay. VE and 95% confidence intervals (CIs) were estimated. HPV16 or 18 antibody levels were measured in all one- and two-dose women, and a subset of three-dose women, using a virus-like particle-based enzyme-linked immunosorbent assay (n = 448).
Results
Median follow-up for the HPV-vaccinated group was 11.3 years (interquartile range = 10.9–11.7 years) and did not vary by dose group. VE against prevalent HPV16 or 18 infection was 80.2% (95% CI = 70.7% to 87.0%) among three-dose, 83.8% (95% CI = 19.5% to 99.2%) among two-dose, and 82.1% (95% CI = 40.2% to 97.0%) among single-dose women. HPV16 or 18 antibody levels did not qualitatively decline between years four and 11 regardless of the number of doses given, although one-dose titers continue to be statistically significantly lower compared with two- and three-dose titers.
Conclusion
More than a decade after HPV vaccination, single-dose VE against HPV16 or 18 infection remained high and HPV16 or 18 antibodies remained stable. A single dose of bivalent HPV vaccine may induce sufficiently durable protection that obviates the need for more doses.
INTRODUCTION/PURPOSETo assess the utility of measurement methods that may be more accurate and precise than traditional questionnaire-based estimates of habitual physical activity and sedentary ...behavior we compared the measurement properties of a past year questionnaire (AARP) and more comprehensive measuresan internet-based 24-h recall (ACT24), and a variety of estimates from an accelerometer (ActiGraph).
METHODSParticipants were 932 adults (50–74 yr) in a 12-month study that included reference measures of energy expenditure from doubly labeled water (DLW) and active and sedentary time via activPAL.
RESULTSAccuracy at the group level (mean differences) was generally better for both ACT24 and ActiGraph than the AARP questionnaire. The AARP accuracy for energy expenditure ranged from −4% to −13% lower than DLW, but its accuracy was poorer for physical activity duration (−48%) and sedentary time (−18%) versus activPAL. In contrast, ACT24 accuracy was within 3% to 10% of DLW expenditure measures and within 1% to 3% of active and sedentary time from activPAL. For ActiGraph, accuracy for energy expenditure was best for the Crouter 2-regression method (−2% to −7%), and for active and sedentary time the 100 counts per minute cutpoint was most accurate (−1% to 2%) at the group level. One administration of the AARP questionnaire was significantly correlated with long-term average from the reference measures (ρTX = 0.16–0.34) overall, but four ACT24 recalls had higher correlations (ρTX = 0.48–0.60), as did 4 d of ActiGraph assessment (ρTX = 0.54–0.87).
CONCLUSIONSNew exposure assessments suitable for use in large epidemiologic studies (ACT24, ActiGraph) were more accurate and had higher correlations than a traditional questionnaire. Use of better more comprehensive measures in future epidemiologic studies could yield new etiologic discoveries and possibly new opportunities for prevention.
Diet plays an important role in chronic disease etiology, but some diet-disease associations remain inconclusive because of methodologic limitations in dietary assessment. Metabolomics is a novel ...method for identifying objective dietary biomarkers, although it is unclear what dietary information is captured from metabolites found in serum compared with urine.
We compared metabolite profiles of habitual diet measured from serum with those measured from urine.
We first estimated correlations between consumption of 56 foods, beverages, and supplements assessed by a food-frequency questionnaire, with 676 serum and 848 urine metabolites identified by untargeted liquid chromatography mass spectrometry, ultra-high performance liquid chromatography tandem mass spectrometry, and gas chromatography mass spectrometry in a colon adenoma case-control study (n = 125 cases and 128 controls) while adjusting for age, sex, smoking, fasting, case-control status, body mass index, physical activity, education, and caloric intake. We controlled for multiple comparisons with the use of a false discovery rate of <0.1. Next, we created serum and urine multiple-metabolite models to predict food intake with the use of 10-fold crossvalidation least absolute shrinkage and selection operator regression for 80% of the data; predicted values were created in the remaining 20%. Finally, we compared predicted values with estimates obtained from self-reported intake for metabolites measured in serum and urine.
We identified metabolites associated with 46 of 56 dietary items; 417 urine and 105 serum metabolites were correlated with ≥1 food, beverage, or supplement. More metabolites in urine (n = 154) than in serum (n = 39) were associated uniquely with one food. We found previously unreported metabolite associations with leafy green vegetables, sugar-sweetened beverages, citrus, added sugar, red meat, shellfish, desserts, and wine. Prediction of dietary intake from multiple-metabolite profiles was similar between biofluids.
Candidate metabolite biomarkers of habitual diet are identifiable in both serum and urine. Urine samples offer a valid alternative or complement to serum for metabolite biomarkers of diet in large-scale clinical or epidemiologic studies.
Physical activity is associated lower risk for a broad range of non-communicable diseases and early mortality, and even small changes in daily activity levels could have a profound effect on public ...health at the population level. The COVID-19 pandemic reshaped daily life for United States (US) adults resulting in reductions in physical activity early in the pandemic, but its longer-term effects on daily activities are unknown. To examine the longer-term impact of the pandemic on daily activity levels, we conducted a nationwide longitudinal study of 1,635 adults (20–75 years) in AmeriSpeak. Previous-day recalls of time-use, sedentary time, and physical activity were completed on randomly selected days in Fall 2019 (pre-pandemic) and Fall 2020. Overall, US adults reported less time in transportation (-0.47 hrs/d), more total discretionary time (0.40 hrs/d), but no changes in total sedentary time (0.10 hrs/d) or leisure-time physical activity (-0.06 hrs/d). Women reported significantly less total activity (-0.36 hrs/d) and participants with children < 13 yrs reported more sedentary time (0.60 to 0.82 hrs/d) and less moderate-to-vigorous intensity activity (-0.84 to -0.72 hrs/d). Adults without children reported no changes in sedentary time (0.02 hrs/d) or moderate-vigorous intensity activity (-0.06 hrs/d). Adults who started working from home reported no changes in physical activity, but they were among the most sedentary and least active population groups at both timepoints. Our findings describe the complex inter-play between competing behaviors as time-use demands have changed in response to the pandemic, particularly for adults with younger children. Many US adults are likely to continue working from home; therefore, implementation of evidence-based approaches to increase physical activity and reduce sedentary time in this growing population subgroup appears warranted.
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