Faculty Bibliography

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.

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 if there was support for common SNP(s) underlying the observed associations. Statistical tests were two sided and P-values < 5 x 10-8 were 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 which included 45 significantly associated SNPs, was rs1818613 (per allele OR in never smokers 0.87, 95% 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, interaction P-value=3.08x10-9). 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 LD with rs1818613 (r2=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.

BACKGROUND:The association between prediagnostic antibody responses to Fusobacterium nucleatum (F. nucleatum) and subsequent risk of colorectal cancer (CRC) is not established. METHODS:We conducted a nested case-control study of 8,126 participants in a consortium of 10 prospective cohorts in the United States. RESULTS:Higher seroprevalence of any F. nucleatum antibody was observed among non-White participants (51.1%) compared to White participants (31.2%). We did not find any statistically significant association between seropositivity to any of the eight F. nucleatum proteins and CRC risk. CONCLUSIONS:Prediagnostic antibody responses to F. nucleatum proteins were not associated with the risk of CRC. IMPACT/CONCLUSIONS:Future studies may consider a more specific detection of the immunoglobulin isotypes or focus on examining F. nucleatum in stool or tissue samples.

Background/UNASSIGNED:Incidence of early-onset (younger than 50 years of age) colorectal cancer (CRC) is increasing in many countries. Thus, elucidating the role of traditional CRC risk factors in early-onset CRC is a high priority. We sought to determine whether risk factors associated with late-onset CRC were also linked to early-onset CRC and whether association patterns differed by anatomic subsite. Methods/UNASSIGNED:Using data pooled from 13 population-based studies, we studied 3767 CRC cases and 4049 controls aged younger than 50 years and 23 437 CRC cases and 35 311 controls aged 50 years and older. Using multivariable and multinomial logistic regression, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) to assess the association between risk factors and early-onset CRC and by anatomic subsite. Results/UNASSIGNED: = .04). Conclusion/UNASSIGNED:In this large study, we identified several nongenetic risk factors associated with early-onset CRC, providing a basis for targeted identification of those most at risk, which is imperative in mitigating the rising burden of this disease.

A full-term pregnancy is associated with reduced endometrial cancer risk; however, whether the effect of additional pregnancies is independent of age at last pregnancy is unknown. The associations between other pregnancy-related factors and endometrial cancer risk are less clear. We pooled individual participant data from 11 cohort and 19 case-control studies participating in the Epidemiology of Endometrial Cancer Consortium (E2C2) including 16,986 women with endometrial cancer and 39,538 control women. We used one- and two-stage meta-analytic approaches to estimate pooled odds ratios (OR) for the association between exposures and endometrial cancer risk. Ever having a full-term pregnancy was associated with a 41% reduction in risk of endometrial cancer compared to never having a full-term pregnancy (OR=0.59, 95% confidence interval (CI) 0.56-0.63). The risk reduction appeared greatest for the first full-term pregnancy (OR=0.78, 95%CI 0.72-0.84), with a further ~15% reduction per pregnancy up to eight pregnancies (OR=0.20, 95%CI 0.14-0.28) that was independent of age at last full-term pregnancy. Incomplete pregnancy was also associated with decreased endometrial cancer risk (7-9% reduction per pregnancy). Twin births appeared to have the same effect as singleton pregnancies. Our pooled analysis shows that, while the magnitude of the risk reduction is greater for a full-term pregnancy than an incomplete pregnancy, each additional pregnancy is associated with further reduction in endometrial cancer risk, independent of age at last full-term pregnancy. These results suggest the very high progesterone level in the last trimester of pregnancy is not the sole explanation for the protective effect of pregnancy.

BACKGROUND:Many studies have addressed effects of dietary supplementation with soy protein, but most have been inconsistent and few have been long-term studies in men. OBJECTIVES/OBJECTIVE:This study was a secondary analysis of body weight, blood pressure, thyroid hormones, iron status, and clinical chemistry in a 2-y trial of soy protein supplementation in middle-aged to older men. METHODS:Data were analyzed as secondary outcomes of a randomized controlled trial of dietary supplementation with 20 g/d soy protein isolate, providing 41 mg/d total isoflavones and 23 mg/d genistein, in 44- to 75-y-old men who were at risk of cancer recurrence following prostatectomy randomized to soy (n = 50) or a casein-based placebo (n  = 43). Weight, blood pressure, and blood samples were collected at baseline, every 2 mo in year 1, and every 3 mo in year 2. RESULTS:Compared with casein, soy supplementation did not affect body weight, blood pressure, serum total cholesterol, calcium, phosphorus, and thyroid hormones. Serum ferritin concentrations doubled over 2 y in both groups (117-129%), whereas hemoglobin and hematocrit increased slightly. In an exploratory subgroup analysis of soy group data, weight increased in subjects producing equol but not in nonproducers. Blood pressure was reduced in nonequol producers but not in producers. Other endpoints were not affected by equol production status. CONCLUSIONS:Soy protein supplementation for 2 y compared with a casein-based placebo did not affect body weight, blood pressure, serum total cholesterol, iron status parameters, calcium, phosphorus, and thyroid hormones. Exploratory analysis suggests that equol production status of subjects on soy may modify effects of soy on body weight and possibly blood pressure. This trial was registered at clinicaltrials.gov as NCT00765479.

Associations between anthropometric factors and breast cancer (BC) risk have varied inconsistently by estrogen and/or progesterone receptor (ER/PR) status. Associations between prediagnostic anthropometric factors and risk of premenopausal and postmenopausal BC overall and ER/PR status subtypes were investigated in a pooled analysis of 20 prospective cohorts, including 36,297 BC cases among 1,061,915 women, using multivariable Cox regression analyses, controlling for reproductive factors, diet and other risk factors. We estimated dose-response relationships and tested for nonlinear associations using restricted cubic splines. Height showed positive, linear associations for premenopausal and postmenopausal BC risk (6-7% RR increase per 5 cm increment), with stronger associations for receptor-positive subtypes. Body mass index (BMI) at cohort baseline was strongly inversely associated with premenopausal BC risk, and strongly positively-and nonlinearly-associated with postmenopausal BC (especially among women who never used hormone replacement therapy). This was primarily observed for receptor-positive subtypes. Early adult BMI (at 18-20 years) showed inverse, linear associations for premenopausal and postmenopausal BC risk (21% and 11% RR decrease per 5 kg/m², respectively) with stronger associations for receptor-negative subtypes. Adult weight gain since 18-20 years was positively associated with postmenopausal BC risk, stronger for receptor-positive subtypes, and among women who were leaner in early adulthood. Women heavier in early adulthood generally had reduced premenopausal BC risk, independent of later weight gain. Positive associations between height, baseline (adult) BMI, adult weight gain and postmenopausal BC risk were substantially stronger for hormone receptor-positive versus negative subtypes. Premenopausal BC risk was positively associated with height, but inversely with baseline BMI and weight gain (mostly in receptor-positive subtypes). Inverse associations with early adult BMI seemed stronger in receptor-negative subtypes of premenopausal and postmenopausal BC.

Sub-cohort sampling designs, such as nested case-control (NCC) and case-cohort (CC) studies, have been widely used to estimate biomarker-disease associations because of their cost effectiveness. These designs have been well studied and shown to maintain relatively high efficiency compared to full-cohort designs, but their performance of building risk prediction models has been less studied. Moreover, sub-cohort sampling designs often use matching (or stratifying) to further control for confounders or to reduce measurement error. Their predictive performance depends on both the design and matching procedures. Based on a dataset from the NYU Women's Health Study (NYUWHS), we performed Monte Carlo simulations to systematically evaluate risk prediction performance under NCC, CC, and full-cohort studies. Our simulations demonstrate that sub-cohort sampling designs can have predictive accuracy (i.e. discrimination and calibration) similar to that of the full-cohort design, but could be sensitive to the matching procedure used. Our results suggest that researchers can have the option of performing NCC and CC studies with huge potential benefits in cost and resources, but need to pay particular attention to the matching procedure when developing a risk prediction model in biomarker studies.

Previously, we found that risk of colorectal cancer (CRC) is increased in individuals with serum antibody response to both Helicobacter pylori (HP) Vacuolating Cytotoxin (VacA) toxin or Streptococcus gallolyticus (SGG) pilus protein Gallo2178. In the present analysis, we tested the hypothesis that combined seropositivity to both antigens is a better indicator of CRC risk than seropositivity to single antigens. We used multiplex serologic assays to analyze pre-diagnostic serum for antibody responses from 4063 incident CRC cases and 4063 matched controls from 10 US cohorts. To examine whether combined SGG Gallo2178 and HP VacA sero-status was associated with CRC risk, we used conditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Compared to dual sero-negative individuals, there was no increased risk for individuals sero-positive to SGG Gallo2178 only (OR: 0.93; 95% CI: 0.66-1.31) or to HP VacA only (OR: 1.08; 95% CI: 0.98-1.19). However, dual sero-positive individuals had a >50% increased odds of developing CRC (OR: 1.54; 95% CI: 1.16-2.04), suggesting an interaction between antibody responses to these two pathogens and CRC risk (p_interaction = 0.06). In conclusion, this study suggests that dual sero-positivity to HP VacA and SGG Gallo2178 is an indicator of increased risk of CRC.

BACKGROUND:Although 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies (GWAS) in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown. METHODS:To discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study (TWAS) in Europeans using three approaches, FUSION, MetaXcan and SMulTiXcan. We integrated GWAS summary statistics from 9,040 pancreatic cancer cases and 12,496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics, LTG (n = 95) and Genotype-Tissue Expression, GTEx v7 (n = 174) datasets), and data from 48 different tissues (GTEx v7, n = 74-421 samples). RESULTS:We identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (FDR < 0.05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12:, PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at 6 known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci, and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1 and BCAR1 at known loci) remained statistically significant after Bonferroni correction. CONCLUSIONS:By integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.