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Background: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis., Methods: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only., Findings: There were 86 proteins nominally associated with mortality (p < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10-1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61-0.66), compared with 0.62 (95% CI: 0.59-0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: -0.003 to 0.035)., Interpretation: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information., Funding: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute (U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden (AMP19-962), and Swedish Department of Health Ministry., Competing Interests: Declaration of interests Jian-Min Yuan has a declaration on NIH grant funding, and the other authors have no conflicts of interest., (Copyright © 2023 World Health Organization. Published by Elsevier B.V. All rights reserved.)

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction  = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Circulating concentrations of metabolites (collectively called kynurenines) in the kynurenine pathway of tryptophan metabolism increase during inflammation, particularly in response to interferon-gamma (IFN-γ). Neopterin and the kynurenine/tryptophan ratio (KTR) are IFN-γ induced inflammatory markers, and together with C-reactive protein (CRP) and kynurenines they are associated with various diseases, but comprehensive data on the strength of associations of inflammatory markers with circulating concentrations of kynurenines are lacking. We measured circulating concentrations of neopterin, CRP, tryptophan and seven kynurenines in 5314 controls from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). The associations of neopterin, KTR and CRP with kynurenines were investigated using regression models. In mixed models, one standard deviation (SD) higher KTR was associated with a 0.46 SD higher quinolinic acid (QA), and 0.31 SD higher 3-hydroxykynurenine (HK). One SD higher neopterin was associated with 0.48, 0.44, 0.36 and 0.28 SD higher KTR, QA, kynurenine and HK, respectively. KTR and neopterin respectively explained 24.1% and 16.7% of the variation in QA, and 11.4% and 7.5% of HK. CRP was only weakly associated with kynurenines in regression models. In summary, QA was the metabolite that was most strongly associated with the inflammatory markers. In general, the inflammatory markers were most strongly related to metabolites located along the tryptophan-NAD axis, which may support suggestions of increased production of NAD from tryptophan during inflammation., (© 2023. The Author(s).)

Background: 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., Methods: 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., Results: 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., Conclusions: 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., (© 2023. The Author(s).)

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies., (Copyright © 2022. Published by Elsevier Inc.)

Background: Cannabis use is increasing, including among smokers, an at-risk population for cancer. Research is equivocal on whether using cannabis inhibits quitting cigarettes. The current longitudinal study investigated associations between smoking cannabis and subsequently quitting cigarettes., Methods: Participants were 4,535 adult cigarette smokers from a cohort enrolled in the American Cancer Society's Cancer Prevention Study-3 in 2009-2013. Cigarette quitting was assessed on a follow-up survey in 2015-2017, an average of 3.1 years later. Rates of quitting cigarettes at follow-up were examined by retrospectively assessed baseline cannabis smoking status ( never, former, recent ), and by frequency of cannabis smoking among recent cannabis smokers ( low : ≤3 days/month; medium : 4-19 days/month; high : ≥20 days/month). Logistic regression models adjusted for sociodemographic factors, smoking- and health-related behaviors, and time between baseline and follow-up., Results: Adjusted cigarette quitting rates at follow-up did not differ significantly by baseline cannabis smoking status [never 36.2%, 95% confidence interval (CI), 34.5-37.8; former 34.1%, CI, 31.4-37.0; recent 33.6%, CI, 30.1-37.3], nor by frequency of cannabis smoking (low 31.4%, CI, 25.6-37.3; moderate 36.7%, CI, 30.7-42.3; high 34.4%, CI, 28.3-40.2) among recent baseline cannabis smokers. In cross-sectional analyses conducted at follow-up, the proportion of cigarette smokers intending to quit smoking cigarettes in the next 30 days did not differ by cannabis smoking status ( P = 0.83)., Conclusions: Results do not support the hypothesis that cannabis smoking inhibits quitting cigarette smoking among adults., Impact: Future longitudinal research should include follow-ups of >1 year, and assess effects of intensity/frequency of cannabis use and motivation to quit on smoking cessation., (©2021 The Authors; Published by the American Association for Cancer Research.)

Imbalances of blood biomarkers are associated with disease, and biomarkers may also vary non-pathologically across population groups. We described variation in concentrations of biomarkers of one-carbon metabolism, vitamin status, inflammation including tryptophan metabolism, and endothelial and renal function among cancer-free older adults. We analyzed 5167 cancer-free controls aged 40-80 years from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). Centralized biochemical analyses of 40 biomarkers in plasma or serum were performed. We fit multivariable linear mixed effects models to quantify variation in standardized biomarker log-concentrations across four factors: age, sex, smoking status, and body mass index (BMI). Differences in most biomarkers across most factors were small, with 93% (186/200) of analyses showing an estimated difference lower than 0.25 standard-deviations, although most were statistically significant due to large sample size. The largest difference was for creatinine by sex, which was - 0.91 standard-deviations lower in women than men (95%CI - 0.98; - 0.84). The largest difference by age was for total cysteine (0.40 standard-deviation increase per 10-year increase, 95%CI 0.36; 0.43), and by BMI was for C-reactive protein (0.38 standard-deviation increase per 5-kg/m 2 increase, 95%CI 0.34; 0.41). For 31 of 40 markers, the mean difference between current and never smokers was larger than between former and never smokers. A statistically significant (p < 0.05) association with time since smoking cessation was observed for 8 markers, including C-reactive protein, kynurenine, choline, and total homocysteine. We conclude that most blood biomarkers show small variations across demographic characteristics. Patterns by smoking status point to normalization of multiple physiological processes after smoking cessation.

Germline variation and smoking are independently associated with pancreatic ductal adenocarcinoma (PDAC). We conducted genome-wide smoking interaction analysis of PDAC using genotype data from four previous genome-wide association studies in individuals of European ancestry (7,937 cases and 11,774 controls). Examination of expression quantitative trait loci data from the Genotype-Tissue Expression Project followed by colocalization analysis was conducted to determine whether there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P < 5 × 10 -8 was considered statistically significant. Genome-wide significant evidence of qualitative interaction was identified on chr2q21.3 in intron 5 of the transmembrane protein 163 (TMEM163) and upstream of the cyclin T2 (CCNT2). The most significant SNP using the Empirical Bayes method, in this region that included 45 significantly associated SNPs, was rs1818613 [per allele OR in never smokers 0.87, 95% confidence interval (CI), 0.82-0.93; former smokers 1.00, 95% CI, 0.91-1.07; current smokers 1.25, 95% CI 1.12-1.40, P interaction = 3.08 × 10 -9 ). Examination of the Genotype-Tissue Expression Project data demonstrated an expression quantitative trait locus in this region for TMEM163 and CCNT2 in several tissue types. Colocalization analysis supported a shared SNP, rs842357, in high linkage disequilibrium with rs1818613 ( r 2 = 0. 94) driving both the observed interaction and the expression quantitative trait loci signals. Future studies are needed to confirm and understand the differential biologic mechanisms by smoking status that contribute to our PDAC findings. SIGNIFICANCE: This large genome-wide interaction study identifies a susceptibility locus on 2q21.3 that significantly modified PDAC risk by smoking status, providing insight into smoking-associated PDAC, with implications for prevention., (©2021 American Association for Cancer Research.)

Previous cross-sectional metabolomics studies have identified many potential dietary biomarkers, mostly in blood. Few studies examined urine samples although urine is preferred for dietary biomarker discovery. Furthermore, little is known regarding the reproducibility of urinary metabolomic biomarkers over time. We aimed to identify urinary metabolomic biomarkers of diet and assess their reproducibility over time. We conducted a metabolomics analysis among 648 racially/ethnically diverse men and women in the Diet Assessment Sub-study of the Cancer Prevention Study-3 cohort to examine the correlation between >100 food groups/items [101 by a food frequency questionnaire (FFQ), and 105 by repeated 24 h diet recalls (24HRs)] and 1391 metabolites measured in 24 h urine sample replicates, six months apart. Diet-metabolite associations were examined by Pearson's partial correlation analysis. Biomarkers were evaluated for prediction accuracy assessed using area under the curve (AUC) calculated from the receiver operating characteristic curve and for reproducibility assessed using intraclass correlation coefficients (ICCs). A total of 1708 diet-metabolite associations were identified after Bonferroni correction for multiple comparisons and restricting correlation coefficients to >0.2 or <-0.2 (1570 associations using the FFQ and 933 using 24HRs), 513 unique metabolites correlated with 79 food groups/items. The median ICCs of the 513 putative biomarkers was 0.53 (interquartile range 0.42-0.62). In this study, with comprehensive dietary data and repeated 24 h urinary metabolic profiles, we identified a large number of diet-metabolite correlations and replicated many found in previous studies. Our findings revealed the promise of urine samples for dietary biomarker discovery in a large cohort study and provide important information on biomarker reproducibility, which could facilitate their utilization in future clinical and epidemiological studies.

Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer (NSCLC) risk, biological mechanisms of these variants remain largely unknown. By integrating a large-scale genotype data of 15 581 lung adenocarcinoma (AD) cases, 8350 squamous cell carcinoma (SqCC) cases, and 27 355 controls, as well as multiple transcriptome and epigenomic databases, we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants. We identified 3064 credible risk variants for NSCLC, which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites. Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific. Functional annotation and gene-based analysis implicated 894 target genes, including 274 specifics for AD and 123 for SqCC, which were overrepresented in somatic driver genes (ER = 1.95, P = 0.005). Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways, while SqCC genes were homologous recombination deficiency related. Our results illustrate the molecular basis of both well-studied and new susceptibility loci of NSCLC, providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations., (Copyright © 2021 American Society of Human Genetics. All rights reserved.)

Background: Valid assessment of dietary intake in diverse populations is important for studies of chronic disease risk in the United States., Objectives: We evaluated the reproducibility and validity of a food frequency questionnaire (FFQ) modified for the American Cancer Society's Cancer Prevention Study-3 (CPS-3) prospective cohort, among a racially/ethnically diverse subgroup., Methods: The Diet Assessment Substudy included 677 CPS-3 participants (64% women; 61% non-Hispanic white, 24% non-Hispanic black, 15% Hispanic), aged 31-70 y, who completed 2 FFQs 1 y apart (FFQ1, FFQ2), 4-6 telephone-administered 24-h dietary recalls (24HRs), and 2 fasting blood samples and 24-h urine collections ∼6 mo apart in the interim. Spearman rank correlation coefficients (ρ) were used to evaluate FFQ reproducibility and validity compared with 24HRs for 67 nutrient exposures. For 18 of these nutrients, we used the method of triads to calculate validity coefficients (VCs, ρ) from pairwise correlations of FFQ2, 24HRs, and biomarkers. Analyses were stratified by sex, race/ethnicity, education, and BMI., Results: Mean (range) FFQ reproducibility correlations were ρ = 0.65 (0.50-0.91) for men and ρ = 0.63 (0.37-0.89) for women; mean (range) energy-adjusted, deattenuated correlations of FFQ2 with 24HRs were ρ = 0.60 (0.33-0.84) for men and ρ = 0.55 (0.21-0.79) for women. FFQ2 VCs (ρ) among men ranged from 0.42 for β-cryptoxanthin to 0.91 for omega-3 (n-3) fatty acids and, among women, from 0.41 for sodium to 0.79 for total vitamin D. Mean FFQ reproducibility and validity were highest among whites (ρ = 0.68, ρ = 0.58, respectively) and slightly lower among blacks (ρ = 0.57, ρ = 0.49, respectively) and Hispanics (ρ = 0.59, 0.55, respectively). FFQ reproducibility and validity were slightly lower among those with less than a 4-y college degree, and those with a BMI ≥30 kg/m2., Conclusions: Reproducibility and validity of the CPS-3 FFQ were comparable with similar studies for most nutrients, among all subgroups. These findings support future dietary analyses in the contemporary CPS-3 cohort and other similar cohorts., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition.)

Untargeted metabolomic studies have identified potential biomarkers of colorectal cancer risk, but evidence is still limited and broadly inconsistent. Among 39,239 Cancer Prevention Study II Nutrition cohort participants who provided a blood sample between 1998-2001, 517 newly diagnosed colorectal cancers were identified through 30 June 2015. In this nested case-control study, controls were matched 1:1 to cases on age, sex, race and date of blood draw. Mass spectroscopy-based metabolomic analyses of pre-diagnostic plasma identified 886 named metabolites, after quality control exclusions. Conditional logistic regression models estimated multivariable-adjusted odds ratios (OR) and 95% confidence intervals (CI) for 1 standard deviation (SD) increase in each metabolite with risk of colorectal cancer. Six metabolites were associated with colorectal cancer risk at a false discovery rate < 0.20. These metabolites were of several classes, including cofactors and vitamins, nucleotides, xenobiotics, lipids and amino acids. Five metabolites (guanidinoacetate, 2'-O-methylcytidine, vanillylmandelate, bilirubin (E,E) and N -palmitoylglycine) were positively associated (OR per 1 SD = 1.29 to 1.32), and one (3-methylxanthine) was inversely associated with CRC risk (OR = 0.79, 95% CI, 0.69-0.89). We did not replicate findings from two earlier prospective studies of 250 cases each after adjusting for multiple comparisons. Large pooled prospective analyses are warranted to confirm or refute these findings and to discover and replicate metabolites associated with colorectal cancer risk.

Breast cancer is the most common cancer in women, but its incidence can only be partially explained through established risk factors. Our aim was to use metabolomics to identify novel risk factors for breast cancer and to validate recently reported metabolite-breast cancer findings. We measured levels of 1275 metabolites in prediagnostic serum in a nested case-control study of 782 postmenopausal breast cancer cases and 782 matched controls. Metabolomics analysis was performed by Metabolon Inc using ultra-performance liquid chromatography and a Q-Exactive high resolution/accurate mass spectrometer. Controls were matched by birth date, date of blood draw, and race/ethnicity. Odds ratios (ORs) and 95% confidence intervals (CIs) of breast cancer at the 90th versus 10th percentile (modeled on a continuous basis) of metabolite levels were estimated using conditional logistic regression, with adjustment for age. Twenty-four metabolites were significantly associated with breast cancer risk at a false discovery rate <0.20. For the nine metabolites positively associated with risk, the ORs ranged from 1.75 (95% CI: 1.29-2.36) to 1.45 (95% CI: 1.13-1.85), and for the 15 metabolites inversely associated with risk, ORs ranged from 0.59 (95% CI: 0.43-0.79) to 0.69 (95% CI: 0.55-0.87). These metabolites largely comprised carnitines, glycerolipids, and sex steroid metabolites. Associations for three sex steroid metabolites validated findings from recent studies and the remainder were novel. These findings contribute to growing data on metabolite-breast cancer associations by confirming prior findings and identifying novel leads for future validation efforts.

Background: Little is known about the underlying molecular mechanisms of prostate cancer, especially advanced and fatal prostate cancer., Objective: To examine associations of prediagnostic plasma metabolomic profiles with advanced and fatal prostate cancer., Design, Setting, and Participants: In a case-cohort study of the Cancer Prevention Study-II Nutrition Cohort, of 14 210 cancer-free men with a blood sample in 1998-2001, 129 were diagnosed with advanced prostate cancer (T3-T4 or N1 or M1) through June 2013 and 112 died from prostate cancer through December 2014. Plasma samples from advanced and fatal cases, and a randomly selected subcohort of 347 men were metabolically profiled using untargeted mass spectroscopy-based platforms., Outcome Measurements and Statistical Analysis: Prentice-weighted Cox proportional hazards regression models were used to assess associations of 699 known metabolites with advanced and fatal prostate cancer., Results and Limitations: Two metabolites derived from fatty acid metabolism (ethylmalonate and butyrylcarnitine), aspartate, sphingomyelin (d18:1/18:0), and two γ-glutamyl amino acids (γ-glutamylmethionine and γ-glutamylglutamine) were statistically significantly associated (false discovery rate <0.2) with fatal prostate cancer. One standard deviation (SD) increase in each γ-glutamyl amino acid was associated with 34-38% decreased risk, whereas one SD increase in each of the other metabolites was associated with 45-53% increased risk. A metabolic risk score based on four of these metabolites (excluding butyrylcarnitine and γ-glutamylglutamine, which were not independent predictors) was strongly associated with fatal prostate cancer (relative risk per SD: 2.72, 95% confidence interval: 2.05-3.60). No metabolites were statistically significantly associated with advanced prostate cancer. These results were observational and may not be causal., Conclusions: These findings identified metabolic pathways that are altered in the development of fatal prostate cancer. Further research into these pathways may provide insights into the etiology of fatal prostate cancer., Patient Summary: In a large follow-up study of cancer-free men, those with a certain metabolomic profile had a higher risk of dying from prostate cancer., (Copyright © 2019 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Background: Some evidence suggests the association between body mass index (BMI) and pancreatic cancer risk is weaker among current smokers than among never smokers., Methods: We examined the association between BMI and pancreatic cancer mortality among adults who reported smoking status at enrollment into Cancer Prevention Study-II in 1982, including 420,543 never smokers, 282,244 former cigarette smokers, and 219,885 current cigarette smokers. After excluding the first 3 years of follow-up to reduce reverse causation, we calculated multivariable-adjusted hazard ratios (HR)., Results: During the full follow-up period from 1985 to 2014, 7,904 participants died of pancreatic cancer. The HR per 5 BMI units was lower among current smokers [HR = 1.14; 95% confidence interval (CI), 1.07-1.20] than never smokers (HR = 1.22; 95% CI, 1.17-1.27), although this difference was not statistically significant ( P = 0.06). BMI was significantly less strongly associated with pancreatic cancer mortality among current smokers reporting ≥20 cigarettes/day (HR = 1.10; 95% CI, 1.03-1.18) than among never smokers. During follow-up within 10 years of enrollment, when current smokers at enrollment were the most likely to have still been smoking, BMI was not associated with pancreatic cancer mortality among current smokers (HR = 1.02; 95% CI, 0.90-1.16, P = 0.03 for difference between current and never smokers). BMI HRs were similar among former and never smokers., Conclusions: These results support a weaker association between BMI and pancreatic cancer among current smokers than among never smokers., Impact: In populations with low smoking prevalence, the pancreatic cancer burden due to BMI is likely to be higher than that predicted by risk estimates from studies including substantial numbers of smokers., (©2020 American Association for Cancer Research.)

Cadmium and lead are persistent environmental toxins that are known or probable carcinogens, based on evidence for causality for nonhematologic cancers. Associations of these metals with risk of non-Hodgkin lymphoma (NHL) and multiple myeloma (MM) are unknown but biologically plausible. To examine the associations of circulating levels of lead and cadmium exposure with risk of B-cell NHL (B-NHL) and multiple myeloma, we conducted a nested case-control study among 299 incident B-cell NHLs and 76 MM cases within the Cancer Prevention Study-II Nutrition Cohort (CPS-II NC). Each case was incidence-density matched to two eligible controls on age, race, sex and blood draw date. Conditional logistic regression was used to estimate relative risks (RR) and 95% confidence intervals (CI) for lymphoid malignancies overall and stratified by subtype. We observed a significant positive association between high erythrocyte lead concentration and risk of lymphoid malignancies overall (RR = 1.16, 95% CI: 1.02-1.33 per 17.6 μg/L (1 standard deviation [SD])) and follicular lymphoma in particular (RR = 1.80, 95% CI: 1.15-2.80 per SD). In contrast, there was no association between erythrocyte cadmium and risk of B-NHL (RR = 0.89, 95% CI: 0.75-1.06 per 0.37 μg/L [1 SD]), or any B-NHL subtypes; but a strong inverse association with MM risk (RR = 0.59, 95% CI: 0.38-0.89, per SD). Results from our study suggest a positive association between erythrocyte lead level and risk of lymphoid malignancies and a possible inverse association between cadmium and myeloma. Additional research is needed to confirm and further explore these findings., (© 2020 UICC.)

Deficient intake of micronutrients involved in one-carbon metabolism (eg, choline, methionine, vitamin B 12 and folic acid) leads to hepatocellular carcinoma (HCC) development in rodents, but is under-investigated in humans. We investigated the association between one-carbon metabolism-related micronutrient intake and HCC risk in a prospective cohort of 494 860 participants with 16 years of follow-up in the NIH-AARP study. Dietary intakes and supplement use were ascertained at baseline using a food-frequency questionnaire. Total intake (diet plus supplements) of the following one-carbon metabolism-related micronutrients were calculated: folate, methionine and vitamins B 2 (riboflavin), B 3 (niacin), B 6 and B 12 . These micronutrients were examined both individually and simultaneously, with adjustment for covariates. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Over the 16-year follow-up period, 647 incident HCC cases were diagnosed. When examined individually, higher total vitamin B 3 intake was associated with a lower HCC risk (HR Q5 vs Q1 = 0.60; 95% CI = 0.42-0.85; P trend = .008), and the association remained significant when all six micronutrients were examined simultaneously (HR Q5 vs Q1 = 0.32; 95% CI = 0.18-0.55; P trend < .0001). Among participants with >3 years of follow-up, higher total vitamin B 3 intake was again associated with lower risk (HR Q5 vs Q1 = 0.37; 95% CI = 0.20-0.68; P trend = .001), whereas higher total vitamin B 6 intake was associated with higher risk (HR Q5 vs Q1 = 2.04; 95% CI = 1.02-4.07; P trend = .04). Restricted cubic spline analyses showed a dose-response inverse association between total vitamin B 3 intake and HCC risk, and dose-response positive association between total vitamin B 6 intake and HCC risk. The study suggests that higher vitamin B 3 intake is associated with lower HCC risk, whereas higher vitamin B 6 intake is associated with increased risk., (© 2020 UICC.)

Previous metabolomic studies have identified putative blood biomarkers of dietary intake. These biomarkers need to be replicated in other populations and tested for reproducibility over time for the potential use in future epidemiological studies. We conducted a metabolomics analysis among 671 racially/ethnically diverse men and women included in a diet validation study to examine the correlation between >100 food groups/items (101 by a food frequency questionnaire (FFQ), 105 by 24-h diet recalls (24HRs)) with 1141 metabolites measured in fasting plasma sample replicates, six months apart. Diet-metabolite associations were examined by Pearson's partial correlation analysis. Biomarker reproducibility was assessed using intraclass correlation coefficients (ICCs). A total of 677 diet-metabolite associations were identified after Bonferroni adjustment for multiple comparisons and restricting absolute correlation coefficients to greater than 0.2 (601 associations using the FFQ and 395 using 24HRs). The median ICCs of the 238 putative biomarkers was 0.56 (interquartile range 0.46-0.68). In this study, with repeated FFQs, 24HRs and plasma metabolic profiles, we identified several potentially novel food biomarkers and replicated others found in our previous study. Our findings contribute to the growing literature on food-based biomarkers and provide important information on biomarker reproducibility which could facilitate their utilization in future nutritional epidemiological studies.

Although men of African ancestry have a high risk of prostate cancer (PCa), no genes or mutations have been identified that contribute to familial clustering of PCa in this population. We investigated whether the African ancestry-specific PCa risk variant at 8q24, rs72725854, is enriched in men with a PCa family history in 9052 cases, 143 cases from high-risk families, and 8595 controls of African ancestry. We found the risk allele to be significantly associated with earlier age at diagnosis, more aggressive disease, and enriched in men with a PCa family history (32% of high-risk familial cases carried the variant vs 23% of cases without a family history and 12% of controls). For cases with two or more first-degree relatives with PCa who had at least one family member diagnosed at age <60 yr, the odds ratios for TA heterozygotes and TT homozygotes were 3.92 (95% confidence interval [CI] = 2.13-7.22) and 33.41 (95% CI = 10.86-102.84), respectively. Among men with a PCa family history, the absolute risk by age 60 yr reached 21% (95% CI = 17-25%) for TA heterozygotes and 38% (95% CI = 13-65%) for TT homozygotes. We estimate that in men of African ancestry, rs72725854 accounts for 32% of the total familial risk explained by all known PCa risk variants. PATIENT SUMMARY: We found that rs72725854, an African ancestry-specific risk variant, is more common in men with a family history of prostate cancer and in those diagnosed with prostate cancer at younger ages. Men of African ancestry may benefit from the knowledge of their carrier status for this genetic risk variant to guide decisions about prostate cancer screening., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated., Methods: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project., Results: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery ( P < 0.001) and validation ( P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10 -6 ). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele ( TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 ( HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10 -3 )., Conclusions: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility., Impact: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility., (©2020 American Association for Cancer Research.)

Purpose: To investigate the association of postdiagnosis body mass index (BMI) and weight change with prostate cancer-specific mortality (PCSM), cardiovascular disease-related mortality (CVDM), and all-cause mortality among survivors of nonmetastatic prostate cancer., Methods: Men in the Cancer Prevention Study II Nutrition Cohort diagnosed with nonmetastatic prostate cancer between 1992 and 2013 were followed for mortality through December 2016. Current weight was self-reported on follow-up questionnaires approximately every 2 years. Postdiagnosis BMI was obtained from the first survey completed 1 to < 6 years after diagnosis. Weight change was the difference in weight between the first and second postdiagnosis surveys. Deaths occurring within 4 years of the follow-up were excluded to reduce bias from reverse causation. Analyses of BMI and weight change included 8,330 and 6,942 participants, respectively., Results: Postdiagnosis BMI analyses included 3,855 deaths from all causes (PCSM, n = 500; CVDM, n = 1,155). Using Cox proportional hazards models, hazard ratios (HRs) associated with postdiagnosis obesity (BMI ≥ 30 kg/m 2 ) compared with healthy weight (BMI 18.5 to < 25.0 kg/m 2 ) were 1.28 for PCSM (95% CI, 0.96 to 1.67), 1.24 for CVDM (95% CI, 1.03 to 1.49), and 1.23 for all-cause mortality (95% CI, 1.11 to 1.35). Weight gain analyses included 2,973 deaths (PCSM, n = 375; CVDM, n = 881). Postdiagnosis weight gain (> 5% of body weight), compared with stable weight (± < 3%), was associated with a higher risk of PCSM (HR, 1.65; 95% CI, 1.21 to 2.25) and all-cause mortality (HR, 1.27; 95% CI, 1.12 to 1.45) but not CVDM., Conclusion: Results suggest that among survivors of nonmetastatic prostate cancer with largely localized disease, postdiagnosis obesity is associated with higher CVDM and all-cause mortality, and possibly higher PCSM, and that postdiagnosis weight gain may be associated with a higher mortality as a result of all causes and prostate cancer.

Background: Research on the relationship of meat, fish, and egg consumption and mortality among prostate cancer survivors is limited., Methods: In the Cancer Prevention Study-II Nutrition Cohort, men diagnosed with nonmetastatic prostate cancer between baseline in 1992/1993 and 2015 were followed for mortality until 2016. Analyses of pre- and postdiagnosis intakes of red and processed meat, poultry, fish, and eggs included 9,286 and 4,882 survivors, respectively. Multivariable-adjusted RRs and 95% confidence intervals (CI) were estimated using Cox proportional hazards models., Results: A total of 4,682 and 2,768 deaths occurred during follow-up in pre- and postdiagnosis analyses, respectively. Both pre- and postdiagnosis intakes of total red and processed meat were positively associated with all-cause mortality (quartile 4 vs. 1: RR = 1.13; 95% CI, 1.03-1.25; P trend = 0.02; RR = 1.22; 95% CI, 1.07-1.39; P trend = 0.03, respectively), and both pre- and postdiagnosis poultry intakes were inversely associated with all-cause mortality (quartile 4 vs. 1 RR = 0.90; 95% CI, 0.82-0.98; P trend = 0.04; RR = 0.84; 95% CI, 0.75-0.95; P trend = 0.01, respectively). No associations were seen for prostate cancer-specific mortality, except that higher postdiagnosis unprocessed red meat intake was associated with lower risk., Conclusions: Higher red and processed meat, and lower poultry, intakes either before or after prostate cancer diagnosis were associated with higher risk of all-cause mortality., Impact: Our findings provide additional evidence that prostate cancer survivors should follow the nutrition guidelines limiting red and processed meat consumption to improve overall survival. Additional research on the relationship of specific meat types and mortality is needed., (©2020 American Association for Cancer Research.)

Cell-mediated immune suppression may play an important role in lung carcinogenesis. We investigated the associations for circulating levels of tryptophan, kynurenine, kynurenine:tryptophan ratio (KTR), quinolinic acid (QA) and neopterin as markers of immune regulation and inflammation with lung cancer risk in 5,364 smoking-matched case-control pairs from 20 prospective cohorts included in the international Lung Cancer Cohort Consortium. All biomarkers were quantified by mass spectrometry-based methods in serum/plasma samples collected on average 6 years before lung cancer diagnosis. Odds ratios (ORs) and 95% confidence intervals (CIs) for lung cancer associated with individual biomarkers were calculated using conditional logistic regression with adjustment for circulating cotinine. Compared to the lowest quintile, the highest quintiles of kynurenine, KTR, QA and neopterin were associated with a 20-30% higher risk, and tryptophan with a 15% lower risk of lung cancer (all p trend < 0.05). The strongest associations were seen for current smokers, where the adjusted ORs (95% CIs) of lung cancer for the highest quintile of KTR, QA and neopterin were 1.42 (1.15-1.75), 1.42 (1.14-1.76) and 1.45 (1.13-1.86), respectively. A stronger association was also seen for KTR and QA with risk of lung squamous cell carcinoma followed by adenocarcinoma, and for lung cancer diagnosed within the first 2 years after blood draw. This study demonstrated that components of the tryptophan-kynurenine pathway with immunomodulatory effects are associated with risk of lung cancer overall, especially for current smokers. Further research is needed to evaluate the role of these biomarkers in lung carcinogenesis and progression., (© 2019 UICC.)

We have recently completed the largest GWAS on lung cancer including 29,266 cases and 56,450 controls of European descent. The goal of our study has been to integrate the complete GWAS results with a large-scale expression quantitative trait loci (eQTL) mapping study in human lung tissues (n = 1,038) to identify candidate causal genes for lung cancer. We performed transcriptome-wide association study (TWAS) for lung cancer overall, by histology (adenocarcinoma, squamous cell carcinoma and small cell lung cancer) and smoking subgroups (never- and ever-smokers). We performed replication analysis using lung data from the Genotype-Tissue Expression (GTEx) project. DNA damage assays were performed in human lung fibroblasts for selected TWAS genes. As expected, the main TWAS signal for all histological subtypes and ever-smokers was on chromosome 15q25. The gene most strongly associated with lung cancer at this locus using the TWAS approach was IREB2 (p TWAS = 1.09E-99), where lower predicted expression increased lung cancer risk. A new lung adenocarcinoma susceptibility locus was revealed on 9p13.3 and associated with higher predicted expression of AQP3 (p TWAS = 3.72E-6). Among the 45 previously described lung cancer GWAS loci, we mapped candidate target gene for 17 of them. The association AQP3-adenocarcinoma on 9p13.3 was replicated using GTEx (p TWAS = 6.55E-5). Consistent with the effect of risk alleles on gene expression levels, IREB2 knockdown and AQP3 overproduction promote endogenous DNA damage. These findings indicate genes whose expression in lung tissue directly influences lung cancer risk., (© 2019 UICC.)

We investigated whether genetic susceptibility to tuberculosis (TB) influences lung adenocarcinoma development among never-smokers using TB genome-wide association study (GWAS) results within the Female Lung Cancer Consortium in Asia. Pathway analysis with the adaptive rank truncated product method was used to assess the association between a TB-related gene-set and lung adenocarcinoma using GWAS data from 5512 lung adenocarcinoma cases and 6277 controls. The gene-set consisted of 31 genes containing known/suggestive associations with genetic variants from previous TB-GWAS. Subsequently, we followed-up with Mendelian Randomization to evaluate the association between TB and lung adenocarcinoma using three genome-wide significant variants from previous TB-GWAS in East Asians. The TB-related gene-set was associated with lung adenocarcinoma (p = 0.016). Additionally, the Mendelian Randomization showed an association between TB and lung adenocarcinoma (OR = 1.31, 95% CI: 1.03, 1.66, p = 0.027). Our findings support TB as a causal risk factor for lung cancer development among never-smoking Asian women., (Copyright © 2019. Published by Elsevier Inc.)

Higher body mass index (BMI; weight (kg)/height (m)2) is associated with increased risk of pancreatic cancer in epidemiologic studies. However, BMI has usually been assessed at older ages, potentially underestimating the full impact of excess weight. We examined the association between BMI and pancreatic cancer mortality among 963,317 adults who were aged 30-89 years at their enrollment in Cancer Prevention Study II in 1982. During follow-up through 2014, a total of 8,354 participants died of pancreatic cancer. Hazard ratios per 5 BMI units, calculated using proportional hazards regression, declined steadily with age at BMI assessment, from 1.25 (95% confidence interval: 1.18, 1.33) in persons aged 30-49 years at enrollment to 1.13 (95% confidence interval: 1.02, 1.26) in those aged 70-89 years at enrollment (P for trend = 0.005). On the basis of a hazard ratio of 1.25 per 5 BMI units at age 45 years, we estimated that 28% of US pancreatic cancer deaths among persons born in 1970-1974 will be attributable to BMI ≥25.0-nearly twice the equivalent proportion of those born in the 1930s, a birth cohort with much lower BMI in middle age. These results suggest that BMI before age 50 years is more strongly associated with pancreatic cancer risk than BMI at older ages, and they underscore the importance of avoiding excess weight gain before middle age for preventing this highly fatal cancer., (© The Author(s) 2019. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objective: To examine the association between prediagnostic plasma polyunsaturated fatty acids levels (PUFA) and amyotrophic lateral sclerosis (ALS)., Methods: We identified 275 individuals who developed ALS while enrolled in 5 US prospective cohorts, and randomly selected 2 controls, alive at the time of the case diagnosis, matched on cohort, birth year, sex, ethnicity, fasting status, and time of blood draw. We measured PUFA, expressed as percentages of total fatty acids, using gas liquid chromatography and used conditional logistic regression to estimate risk ratios (RR) and 95% confidence intervals (CI) for the association between PUFA and ALS., Results: There was no association between total, n-3, and n-6 PUFA, eicosapentaenoic acid, or docosapentaenoic acid levels and ALS. Higher plasma α-linolenic acid (ALA) in men was associated with lower risk of ALS in age- and matching factor-adjusted analyses (top vs bottom quartile: RR = 0.21 [95% CI 0.07, 0.58], p for trend = 0.004). In women, higher plasma arachidonic acid was associated with higher risk (top vs bottom quartile: RR = 1.65 [95% CI 0.99, 2.76], p for trend = 0.052). Multivariable adjustment, including correlated PUFA, did not change the findings for ALA and arachidonic acid. In men and women combined, higher plasma docosahexaenoic acid (DHA) was associated with higher risk of ALS (top vs bottom quartile: RR = 1.56 [95% CI 1.01, 2.41], p for trend = 0.054), but in multivariable models the association was only evident in men., Conclusions: The majority of individual PUFAs were not associated with ALS. In men, ALA was inversely and DHA was positively related to risk of ALS, while in women arachidonic acid was positively related. These findings warrant confirmation in future studies., (© 2019 American Academy of Neurology.)

Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Objective: This study was undertaken to identify metabolites associated with BMI and waist circumference (WC) in women and to determine whether these metabolites are associated with biomarkers of metabolic health., Methods: Untargeted metabolomic analysis was done on serum from 1,534 women. Metabolites associated with BMI and WC were identified using linear regression with a Bonferroni-corrected P value. Clustered blocks of these metabolites were then defined whose association with the anthropometric measures could be represented by a single metabolite. The association of these representative metabolites with biomarkers for diabetes and inflammation was then determined., Results: About one-third of 781 metabolites included in the analyses were associated with BMI and/or WC. Associations were found for some novel metabolites, including several sphingolipids, nucleotides, and modified fatty acids. Among metabolites most strongly inversely associated with BMI, the choline-containing plasmalogen (O-16:0/18:1) (β = -0.30, P = 6.62 × 10 -32 ) was also inversely associated with c-peptide and positively associated with adiponectin. Adjustment for BMI attenuated the metabolite-biomarker associations more for hemoglobin A1c (> 100%) and c-peptide (58.8% to > 100%) than for C-reactive protein (10.5%-40.0%) and adiponectin (7.0%-30.4%)., Conclusions: These results add to the list of metabolites associated with adiposity and indicate that some may influence processes that contribute to the development of obesity-related diseases., (© 2019 The Obesity Society.)

Vitamin B supplementation can have side effects for human health, including cancer risk. We aimed to elucidate the role of vitamin B12 in lung cancer etiology via direct measurements of pre-diagnostic circulating vitamin B12 concentrations in a nested case-control study, complemented with a Mendelian randomization (MR) approach in an independent case-control sample. We used pre-diagnostic biomarker data from 5183 case-control pairs nested within 20 prospective cohorts, and genetic data from 29,266 cases and 56,450 controls. Exposures included directly measured circulating vitamin B12 in pre-diagnostic blood samples from the nested case-control study, and 8 single nucleotide polymorphisms associated with vitamin B12 concentrations in the MR study. Our main outcome of interest was increased risk for lung cancer, overall and by histological subtype, per increase in circulating vitamin B12 concentrations. We found circulating vitamin B12 to be positively associated with overall lung cancer risk in a dose response fashion (odds ratio for a doubling in B12 [OR log2B12 ] = 1.15, 95% confidence interval (95%CI) = 1.06-1.25). The MR analysis based on 8 genetic variants also indicated that genetically determined higher vitamin B12 concentrations were positively associated with overall lung cancer risk (OR per 150 pmol/L standard deviation increase in B12 [OR SD ] = 1.08, 95%CI = 1.00-1.16). Considering the consistency of these two independent and complementary analyses, these findings support the hypothesis that high vitamin B12 status increases the risk of lung cancer., (© 2018 International Agency for Research on Cancer (IARC/WHO); licensed by UICC.)

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.

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)., (Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2019.)

Background: 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., Objective: 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., Methods: 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., Results: 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., Conclusions: 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., (Copyright © American Society for Nutrition 2019.)

Background: Platelets are a critical element in coagulation and inflammation, and activated platelets are linked to cancer risk through diverse mechanisms. However, a causal relationship between platelets and risk of lung cancer remains unclear., Methods: We performed single and combined multiple instrumental variable Mendelian randomization analysis by an inverse-weighted method, in addition to a series of sensitivity analyses. Summary data for associations between SNPs and platelet count are from a recent publication that included 48,666 Caucasian Europeans, and the International Lung Cancer Consortium and Transdisciplinary Research in Cancer of the Lung data consisting of 29,266 cases and 56,450 controls to analyze associations between candidate SNPs and lung cancer risk., Results: Multiple instrumental variable analysis incorporating six SNPs showed a 62% increased risk of overall non-small cell lung cancer [NSCLC; OR, 1.62; 95% confidence interval (CI), 1.15-2.27; P = 0.005] and a 200% increased risk for small-cell lung cancer (OR, 3.00; 95% CI, 1.27-7.06; P = 0.01). Results showed only a trending association with NSCLC histologic subtypes, which may be due to insufficient sample size and/or weak effect size. A series of sensitivity analysis retained these findings., Conclusions: Our findings suggest a causal relationship between elevated platelet count and increased risk of lung cancer and provide evidence of possible antiplatelet interventions for lung cancer prevention., Impact: These findings provide a better understanding of lung cancer etiology and potential evidence for antiplatelet interventions for lung cancer prevention., (©2019 American Association for Cancer Research.)

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r g  = 0.57, p = 4.6 × 10 -8 ), breast and ovarian cancer (r g  = 0.24, p = 7 × 10 -5 ), breast and lung cancer (r g  = 0.18, p =1.5 × 10 -6 ) and breast and colorectal cancer (r g  = 0.15, p = 1.1 × 10 -4 ). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Background: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation., Methods and Findings: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44-1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40-1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44-1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30-2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11-1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84-1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose., Conclusions: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: TE declared employment, research support, and stock in AstraZeneca and research support from Bayer and Pfizer. PCH is a population health fellow of Cancer Research UK. GDS is a member of the Editorial Board of PLOS Medicine.

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.

Background: Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR)., Methods: The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium., Results: Thirty-five metabolites were strongly associated with prostate cancer ( P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal., Conclusions: We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk., Impact: The metabolome provides a promising set of biomarkers that may aid prostate cancer classification., (©2018 American Association for Cancer Research.)

Background: Self-reported smoking is the principal measure used to assess lung cancer risk in epidemiological studies. We evaluated if circulating cotinine-a nicotine metabolite and biomarker of recent tobacco exposure-provides additional information on lung cancer risk., Methods: The study was conducted in the Lung Cancer Cohort Consortium (LC3) involving 20 prospective cohort studies. Pre-diagnostic serum cotinine concentrations were measured in one laboratory on 5364 lung cancer cases and 5364 individually matched controls. We used conditional logistic regression to evaluate the association between circulating cotinine and lung cancer, and assessed if cotinine provided additional risk-discriminative information compared with self-reported smoking (smoking status, smoking intensity, smoking duration), using receiver-operating characteristic (ROC) curve analysis., Results: We observed a strong positive association between cotinine and lung cancer risk for current smokers [odds ratio (OR ) per 500 nmol/L increase in cotinine (OR500): 1.39, 95% confidence interval (CI): 1.32-1.47]. Cotinine concentrations consistent with active smoking (≥115 nmol/L) were common in former smokers (cases: 14.6%; controls: 9.2%) and rare in never smokers (cases: 2.7%; controls: 0.8%). Former and never smokers with cotinine concentrations indicative of active smoking (≥115 nmol/L) also showed increased lung cancer risk. For current smokers, the risk-discriminative performance of cotinine combined with self-reported smoking (AUCintegrated: 0.69, 95% CI: 0.68-0.71) yielded a small improvement over self-reported smoking alone (AUCsmoke: 0.66, 95% CI: 0.64-0.68) (P = 1.5x10-9)., Conclusions: Circulating cotinine concentrations are consistently associated with lung cancer risk for current smokers and provide additional risk-discriminative information compared with self-report smoking alone.

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10 -15 ), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.

Introduction: Processing delays after blood collection is a common pre-analytical condition in large epidemiologic studies. It is critical to evaluate the suitability of blood samples with processing delays for metabolomics analysis as it is a potential source of variation that could attenuate associations between metabolites and disease outcomes., Objectives: We aimed to evaluate the reproducibility of metabolites over extended processing delays up to 48 h. We also aimed to test the reproducibility of the metabolomics platform., Methods: Blood samples were collected from 18 healthy volunteers. Blood was stored in the refrigerator and processed for plasma at 0, 15, 30, and 48 h after collection. Plasma samples were metabolically profiled using an untargeted, ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) platform. Reproducibility of 1012 metabolites over processing delays and reproducibility of the platform were determined by intraclass correlation coefficients (ICCs) with variance components estimated from mixed-effects models., Results: The majority of metabolites (approximately 70% of 1012) were highly reproducible (ICCs ≥ 0.75) over 15-, 30- or 48-h processing delays. Nucleotides, energy-related metabolites, peptides, and carbohydrates were most affected by processing delays. The platform was highly reproducible with a median technical ICC of 0.84 (interquartile range 0.68-0.93)., Conclusion: Most metabolites measured by the UPLC-MS/MS platform show acceptable reproducibility up to 48-h processing delays. Metabolites of certain pathways need to be interpreted cautiously in relation to outcomes in epidemiologic studies with prolonged processing delays.

Over-the-counter analgesic use is common and is typically assessed through self-report; therefore, it is subject to misclassification. Detection of drug metabolites in biofluids offers a viable tool for validating self-reported analgesic use. Thus, the aim of this study was to determine the utility of a metabolomics approach for the validation of acetaminophen and ibuprofen use in blood samples. Untargeted mass spectrometry-based metabolomics analysis was conducted in serum samples from 1547 women and plasma samples from 556 men. The presence of two metabolites each for acetaminophen and ibuprofen at levels at or above a defined cutoff value was used to determine concordance with self-reported use. For acetaminophen use based on the presence of both acetaminophen and acetamidophenylglucuronide, concordance was 98.5⁻100% among individuals reporting use today, and 79.8⁻91.4% for those reporting never or rare use. Ibuprofen use based on the presence of both carboxyibuprofen and hydroxyibuprofen resulted in concordance of 51.3⁻52.5% for individuals reporting use today and 99.4⁻100% for those reporting never or rare use. Our findings suggest that an untargeted metabolomics approach in blood samples may be useful for validating self-reported acetaminophen use. However, this approach appears unlikely to be suitable for validating ibuprofen use.