Structural and Biochemical Characterization of the Nucleosome Containing Variants H3.3 and H2A.Z.

Variant H3.3, along with H2A.Z, is notably enriched at promoter regions and is commonly associated with transcriptional activation. However, the specific molecular mechanisms through which H3.3 influences chromatin dynamics at transcription start sites, and its role in gene regulation, remain elusive. Using a combination of biochemistry and cryo-electron microscopy (cryo-EM), we show that the inclusion of H3.3 alone does not induce discernible changes in nucleosome DNA dynamics. Conversely, the presence of both H3.3 and H2A.Z enhances DNA's flexibility similarly to H2A.Z alone. Interestingly, our findings suggest that the presence of H3.3 in the H2A.Z nucleosome provides slightly increased protection to DNA at internal sites within the nucleosome. These results imply that while H2A.Z at active promoters promotes the formation of more accessible nucleosomes with increased DNA accessibility to facilitate transcription, the simultaneous presence of H3.3 offers an additional mechanism to fine-tune nucleosome accessibility and the chromatin environment.

Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools.

BACKGROUND: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test. METHODS: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided. RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model. CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.

Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis.

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.

A prospective case-cohort analysis of plasma metabolites and breast cancer risk.

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.

A cross-sectional study of inflammatory markers as determinants of circulating kynurenines in the Lung Cancer Cohort Consortium.

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.

Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program.

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.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

Rapid Point-of-Care Tests Using Staphylococcal Protein A Can Detect Early IgM Responses in HIV-1 and Treponema pallidum Infections.

Serological assays detecting IgM antibodies in addition to IgG antibodies have a diagnostic advantage in finding early infections. Staphylococcal protein A (SpA), widely used as an antibody-detecting reagent in various immunoassays, is considered to have a high binding affinity mainly to IgG, although its interaction with other classes of immunoglobulins has also been documented. Using 28 samples from 22 HIV-1 seroconversion panels, the present study demonstrated detection of early IgM antibodies by SpA-based rapid point-of-care tests, including DPP HIV 1/2, DPP HIV-Syphilis, STAT-PAK HIV 1/2, and Sure Check HIV 1/2. Samples with predominant IgM antibodies were identified by in-house IgM assays and confirmed by pretreatment with 0.1 M 2-mercaptoethanol. Likewise, the detection of treponemal IgM antibodies was shown by DPP HIV-Syphilis assay in eight samples collected at early syphilis infection. Direct interaction between IgM and SpA immobilized in solid phase or in solution was demonstrated with purified human polyclonal IgM. A strong correlation was found between the antibody levels detected by SpA and anti-IgM reagent in the early seroconversion samples, thus supporting the evidence for IgM binding by SpA. These assays demonstrated the ability to detect IgM antibodies, which may increase test sensitivity in early infections due to a reduced serodiagnostic window. IMPORTANCE Sexually transmitted infections, including HIV and syphilis, remain a global public health concern. The main laboratory testing approach for HIV and syphilis relies on serological assays. Detection of the IgM class of antibodies may have a diagnostic advantage in finding early infections. The present study using well-characterized HIV-1 and syphilis samples has demonstrated that staphylococcal protein A employed for antibody detection in rapid point-of-care tests, including DPP HIV 1/2, DPP HIV-Syphilis, STAT-PAK HIV 1/2, and Sure Check HIV 1/2, can capture IgM antibodies in addition to IgG antibodies. The findings strongly suggest that the ability to detect IgM antibodies by these immunoassays may facilitate the identification of acute-stage HIV and syphilis infections.

Correlation of antimicrobial fraction unbound and sieving coefficient in critically ill patients on continuous renal replacement therapy: a systematic review.

BACKGROUND: Fraction unbound has been used as a surrogate for antimicrobial sieving coefficient (SC) to predict extracorporeal clearance in critically ill patients on continuous renal replacement therapy (CRRT), but this is based largely on expert opinion. OBJECTIVES: To examine relationships between package insert-derived fraction unbound (Fu-P), study-specific fraction unbound (Fu-S), and SC in critically ill patients receiving CRRT. METHODS: English-language studies containing patient-specific in vivo pharmacokinetic parameters for antimicrobials in critically ill patients requiring CRRT were included. The primary outcome included correlations between Fu-S, Fu-P, and SC. Secondary outcomes included correlations across protein binding quartiles, serum albumin, and predicted in-hospital mortality, and identification of predictors for SC through multivariable analysis. RESULTS: Eighty-nine studies including 32 antimicrobials were included for analysis. SC was moderately correlated to Fu-S (R2 = 0.55, P < 0.001) and Fu-P (R2 = 0.41, P < 0.001). SC was best correlated to Fu-S in first (<69%) and fourth (>92%) quartiles of fraction unbound and above median albumin concentrations of 24.5 g/L (R2 = 0.71, P = 0.07). Conversely, correlation was weaker in patients with mortality estimates greater than the median of 55% (R2 = 0.06, P = 0.84). SC and Fu-P were also best correlated in the first quartile of antimicrobial fraction unbound (R2 = 0.66, P < 0.001). Increasing Fu-P, flow rate, membrane surface area, and serum albumin, and decreasing physiologic charge significantly predicted increasing SC. CONCLUSIONS: Fu-S and Fu-P were both reasonably correlated to SC. Caution should be taken when using Fu-S to calculate extracorporeal clearance in antimicrobials with 69%-92% fraction unbound or with >55% estimated in-hospital patient mortality. Fu-P may serve as a rudimentary surrogate for SC when Fu-S is unavailable.

Retrospective Comparison of Andexanet Alfa and 4-Factor Prothrombin Complex for Reversal of Factor Xa-Inhibitor Related Bleeding.

The aim of this retrospective study was to compare andexanet alfa and 4-factor prothrombin complex (4F-PCC) for reversal of factor Xa (FXa)-inhibitor bleeding. Patients that received andexanet alfa for reversal were included. An equivalent number of patients administered 4F-PCC for FXa-inhibitor bleeding were randomly selected as historical controls. The primary outcome was effective hemostasis achievement within 12 h, defined using ANNEXA-4 criteria. Thromboembolic events and mortality within 30 days were also evaluated. A total of 32 patients were included. Baseline characteristics were not statistically different between andexanet alfa (n = 16) and 4F-PCC (n = 16). Intracranial bleeding was the primary reversal indication in 43.8% versus 62.5% of patients, respectively. Effective hemostasis was reached in 75.0% of andexanet alfa patients compared to 62.5% of 4F-PCC patients (P = .70). Thromboembolic events occurred in 4 (25.0%) patients and 3 (18.8%) patients, respectively (P = .99). Mortality incidence was 12.5% and 31.3%, respectively (P = .39). Andexanet alfa and 4F-PCC attained hemostasis in a majority of patients. A high, but a similar rate of thromboembolic events was seen with both treatments. Prospective studies are needed to elucidate comparative risks and benefits of the 2 agents.

Association between Smoking Cannabis and Quitting Cigarettes in a Large American Cancer Society Cohort.

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.

Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults.

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/m2 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.

Pre-Diagnostic Circulating Metabolites and Colorectal Cancer Risk in the Cancer Prevention Study-II Nutrition Cohort.

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.

Identification and Reproducibility of Urinary Metabolomic Biomarkers of Habitual Food Intake in a Cross-Sectional Analysis of the Cancer Prevention Study-3 Diet Assessment Sub-Study.

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.

A Metabolomics Analysis of Postmenopausal Breast Cancer Risk in the Cancer Prevention Study II.

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.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

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.

The Cancer Prevention Study-3 FFQ Is a Reliable and Valid Measure of Nutrient Intakes among Racial/Ethnic Subgroups, Compared with 24-Hour Recalls and Biomarkers.

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 ß-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.