Nilanjan Chatterjee

Absolute Risk of Endometrial Carcinoma During 20-Year Follow-Up Among Women With Endometrial Hyperplasia

PURPOSE The severity of endometrial hyperplasia (EH)-simple (SH), complex (CH), or atypical (AH)-influences clinical management, but valid estimates of absolute risk of clinical progression to carcinoma are lacking. Materials and METHODS We conducted a case-control study nested in a cohort of 7,947 women diagnosed with EH (1970-2002) at one prepaid health plan who remained at risk for at least 1 year. Patient cases (N = 138) were diagnosed with carcinoma, on average, 6 years later (range, 1 to 24 years). Patient controls (N = 241) were matched to patient cases on age at EH, date of EH, and duration of follow-up, and they were counter-matched to patient cases on EH severity. After we independently reviewed original slides and medical records of patient controls and patient cases, we combined progression relative risks (AH v SH, CH, or disordered proliferative endometrium [ie, equivocal EH]) from the case-control analysis with clinical censoring information (ie, hysterectomy, death, or left the health plan) on all cohort members to estimate interval-specific (ie, 1 to 4, 5 to 9, and 10 to 19 years) and cumulative (ie, through 4, 9, and 19 years) progression risks. Results For nonatypical EH, cumulative progression risk increased from 1.2% (95% CI, 0.6% to 1.9%) through 4 years to 1.9% (95% CI, 1.2% to 2.6%) through 9 years to 4.6% (95% CI, 3.3% to 5.8%) through 19 years after EH diagnosis. For AH, cumulative risk increased from 8.2% (95% CI, 1.3% to 14.6%) through 4 years to 12.4% (95% CI, 3.0% to 20.8%) through 9 years to 27.5% (95% CI, 8.6% to 42.5%) through 19 years after AH. CONCLUSION Cumulative 20-year progression risk among women who remain at risk for at least 1 year is less than 5% for nonatypical EH but is 28% for AH.

Developing and evaluating polygenic risk prediction models for stratified disease prevention

Knowledge of genetics and its implications for human health is rapidly evolving in accordance with recent events, such as discoveries of large numbers of disease susceptibility loci from genome-wide association studies, the US Supreme Court ruling of the non-patentability of human genes, and the development of a regulatory framework for commercial genetic tests. In anticipation of the increasing relevance of genetic testing for the assessment of disease risks, this Review provides a summary of the methodologies used for building, evaluating and applying risk prediction models that include information from genetic testing and environmental risk factors. Potential applications of models for primary and secondary disease prevention are illustrated through several case studies, and future challenges and opportunities are discussed.

Kin-cohort estimates for familial breast cancer risk in relation to variants in DNA base excision repair, BRCA1 interacting and growth factor genes

BackgroundSubtle functional deficiencies in highly conserved DNA repair or growth regulatory processes resulting from polymorphic variation may increase genetic susceptibility to breast cancer. Polymorphisms in DNA repair genes can impact protein function leading to genomic instability facilitated by growth stimulation and increased cancer risk. Thus, 19 single nucleotide polymorphisms (SNPs) in eight genes involved in base excision repair (XRCC1, APEX, POLD1), BRCA1 protein interaction (BRIP1, ZNF350, BRCA2), and growth regulation (TGFß1, IGFBP3) were evaluated.MethodsGenomic DNA samples were used in Taqman 5-nuclease assays for most SNPs. Breast cancer risk to ages 50 and 70 were estimated using the kin-cohort method in which genotypes of relatives are inferred based on the known genotype of the index subject and Mendelian inheritance patterns. Family cancer history data was collected from a series of genotyped breast cancer cases (N = 748) identified within a cohort of female US radiologic technologists. Among 2,430 female first-degree relatives of cases, 190 breast cancers were reported.ResultsGenotypes associated with increased risk were: XRCC1 R194W (WW and RW vs. RR, cumulative risk up to age 70, risk ratio (RR) = 2.3; 95% CI 1.3–3.8); XRCC1 R399Q (QQ vs. RR, cumulative risk up to age 70, RR = 1.9; 1.1–3.9); and BRIP1 (or BACH1) P919S (SS vs. PP, cumulative risk up to age 50, RR = 6.9; 1.6–29.3). The risk for those heterozygous for BRCA2 N372H and APEX D148E were significantly lower than risks for homozygotes of either allele, and these were the only two results that remained significant after adjusting for multiple comparisons. No associations with breast cancer were observed for: APEX Q51H; XRCC1 R280H; IGFPB3 -202A>C; TGFß1 L10P, P25R, and T263I; BRCA2 N289H and T1915M; BRIP1 -64A>C; and ZNF350 (or ZBRK1) 1845C>T, L66P, R501S, and S472P.ConclusionSome variants in genes within the base-excision repair pathway (XRCC1) and BRCA1 interacting proteins (BRIP1) may play a role as low penetrance breast cancer risk alleles. Previous association studies of breast cancer and BRCA2 N372H and functional observations for APEX D148E ran counter to our findings of decreased risks. Due to the many comparisons, cautious interpretation and replication of these relationships are warranted.

A prospective investigation of serum 25-hydroxyvitamin D and risk of lymphoid cancers

Studies indicate that higher sun exposure, especially in the recent past, is associated with reduced risk of non‐Hodgkin lymphoma (NHL). Ultraviolet radiation‐derived vitamin D may be protective against lymphomagenesis. We examined the relationship between prediagnostic serum 25‐hydroxyvitamin D (25(OH)D) and lymphoid cancer risk in a case–control study nested within the Alpha‐Tocopherol Beta‐Carotene Cancer Prevention Study cohort (1985–2002) of 29,133 Finnish male smokers (ages 50–69). We identified 270 incident lymphoid cancer cases and matched them individually with 538 controls by birth‐year and month of fasting blood draw at baseline. In conditional logistic regression models for 10 nmol/L increments or tertile comparisons, serum 25(OH)D was not associated with the risk of overall lymphoid cancers, NHL (n = 208) or multiple myeloma (n = 41). Odds ratios (OR) for NHL for higher tertiles were 0.75 (95% confidence interval (CI), 0.50, 1.14) and 0.82 (95% CI, 0.53, 1.26). The 25(OH)D‐NHL association, however, differed by follow‐up duration at diagnosis. Cases diagnosed less than 7 years from the baseline showed an inverse association (OR for highest vs. lowest tertile = 0.43; 95% CI: 0.23, 0.83; p for trend = 0.01), but not later diagnoses (OR = 1.52; 95% CI: 0.82, 2.80; p for trend = 0.17). The inverse association found for close exposure to diagnosis was not confounded by other risk factors for lymphoma or correlates of 25(OH)D. Although our findings suggest that circulating 25(OH)D is not likely associated with overall lymphoid cancer, they indicate a potentially protective effect on short‐term risk of NHL.

Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States

ImportancenAn improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention.nnnObjectivenTo evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors.nnnDesign, Setting, and ParticipantsnUsing a total of 17u202f171 cases and 19u202f862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality.nnnExposuresnSingle nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors.nnnMain Outcomes and MeasuresnDegree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking).nnnResultsnThe average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population.nnnConclusions and RelevancenThis model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.

Common genetic variation and risk of gallbladder cancer in India: a case-control genome-wide association study

BACKGROUNDnGallbladder cancer is highly lethal, with notable differences in incidence by geography and ethnic background. The aim of this study was to identify common genetic susceptibility alleles for gallbladder cancer.nnnMETHODSnIn this case-control genome-wide association study (GWAS), we did a genome-wide scan of gallbladder cancer cases and hospital visitor controls, both of Indian descent, followed by imputation across the genome. Cases were patients aged 20-80 years with microscopically confirmed primary gallbladder cancer diagnosed or treated at Tata Memorial Hospital, Mumbai, India, and enrolled in the study between Sept 12, 2010, and June 8, 2015. We only included patients who had been diagnosed less than 1 year before the date of enrolment and excluded patients with any other malignancies. We recruited visitor controls aged 20-80 years with no history of cancer visiting all departments or units of Tata Memorial Hospital during the same time period and frequency matched them to cases on the basis of age, sex, and current region of residence. We estimated association using logistic regression, adjusting for age, sex, and five eigenvectors. We recruited samples for a replication cohort from patients visiting Tata Memorial Hospital between Aug 4, 2015, and May 17, 2016, and patients visiting the Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India, between July, 2010, and May, 2015. We used the same inclusion and exclusion criteria for the replication set. We examined three of the most significant single-nucleotide polymorphisms (SNPs) in the replication cohort and did a meta-analysis of the GWAS discovery and replication sets to get combined estimates of association.nnnFINDINGSnThe discovery cohort comprised 1042 gallbladder cancer cases and 1709 controls and the replication cohort contained 428 gallbladder cancer cases and 420 controls. We observed genome-wide significant associations for several markers in the chromosomal region 7q21.12 harbouring both the ABCB1 and ABCB4 genes, with the most notable SNPs after replication and meta-analysis being rs1558375 (GWAS p=3·8u2008×u200810-9; replication p=0·01; combined p=2·3u2008×u200810-10); rs17209837 (GWAS p=2·0u2008×u200810-8; replication p=0·02; combined p=2·3u2008×u200810-9), and rs4148808 (GWAS p=2·4u2008×u200810-8; replication p=0·008; combined p=2·7u2008×u200810-9). Combined estimates of per-allele trend odds ratios were 1·47 (95% CI 1·30-1·66; p=2·31u2008×u200810-10) for rs1558375, 1·61 (1·38-1·89; p=2·26u2008×u200810-9) for rs17209837, and 1·57 (1·35-1·82; p=2·71u2008×u200810-9) for rs4148808. GWAS heritability analysis suggested that common variants are associated with substantial variation in risk of gallbladder cancer (sibling relative risk 3·15 [95% CI 1·80-5·49]).nnnINTERPRETATIONnTo our knowledge, this study is the first report of common genetic variation conferring gallbladder cancer risk at genome-wide significance. This finding, along with in-silico and biological evidence indicating the potential functional significance of ABCB1 and ABCB4, underlines the likely importance of these hepatobiliary phospholipid transporter genes in the pathology of gallbladder cancer.nnnFUNDINGnThe Tata Memorial Centre and Department of Biotechnology.

Constrained Maximum Likelihood Estimation for Model Calibration Using Summary-Level Information From External Big Data Sources

Information from various public and private data sources of extremely large sample sizes are now increasingly available for research purposes. Statistical methods are needed for using information from such big data sources while analyzing data from individual studies that may collect more detailed information required for addressing specific hypotheses of interest. In this article, we consider the problem of building regression models based on individual-level data from an “internal” study while using summary-level information, such as information on parameters for reduced models, from an “external” big data source. We identify a set of very general constraints that link internal and external models. These constraints are used to develop a framework for semiparametric maximum likelihood inference that allows the distribution of covariates to be estimated using either the internal sample or an external reference sample. We develop extensions for handling complex stratified sampling designs, such as case-control sampling, for the internal study. Asymptotic theory and variance estimators are developed for each case. We use simulation studies and a real data application to assess the performance of the proposed methods in contrast to the generalized regression calibration methodology that is popular in the sample survey literature. Supplementary materials for this article are available online.

Genetic variation in catechol-O-methyltransferase (COMT) and obesity in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial

Catechol-O-methyltransferase (COMT) is an important modulator in the catabolism of extraneural dopamine, which plays an important role in drug reward mechanisms. It is hypothesized that genetic variations in the COMT gene, which can result in a three to fourfold difference in COMT enzyme activity, may be associated with several reward-motivated behaviors. The aim of our study was to examine the relationship between COMT polymorphisms with smoking, obesity and alcohol. Three single nucleotide polymorphisms (SNPs) in COMT were genotyped in 2,371 participants selected randomly from the screening arm of the PLCO Cancer Screening Trial after stratifying by sex, age, and smoking status. Smoking, obesity, and alcohol consumption were assessed by questionnaire. SNP and haplotype associations were estimated using odds ratios (ORs) and 95% confidence intervals (CIs) derived from conditional logistic regression models, adjusted for race/ethnicity. The COMT Ex4-76Cxa0>xa0G (Leu136Leu) polymorphism was statistically significantly associated with individuals who had >30% increases in BMI from ages 20 to 50xa0years, compared to those with 0–5% increase in BMI (0–5%) over the same age period: (CC is referent; ORCGxa0=xa01.42, ORGGxa0=xa01.46, Ptrendxa0=xa00.06). By sex, the increased risk was further pronounced among females (ORCGxa0=xa01.50, ORGGxa0=xa02.10, Ptrendxa0=xa00.03). Consistent with our analyses of single polymorphisms, individuals whose BMI increased >30% from ages 20 to 50xa0years were more likely than individuals with 0–5% increases in BMI to possess COMT haplotypes [COMT Ex3-104Cxa0>xa0T–COMT Ex4-76 Cxa0>xa0G–COMT Ex4-12 Axa0>xa0G] that included the variant allele for COMT Ex4-76 Cxa0>xa0G: C-G-G (T-C-A is referent: ORC-G-Gxa0=xa01.33, 95% CI 1.01–1.77) and C-G-A (ORC-G-Axa0=xa01.79, 95% CI 0.72–4.49). We observed no association between any of the COMT polymorphisms with smoking behavior or alcohol intake. The COMT Ex4-76Cxa0>xa0G (Leu136Leu) polymorphism appears to play a role in large increases in BMI. The null association with smoking and alcohol and the pronounced association with increasing BMI among women further implicates COMT’s role in estrogen metabolism as a potentially culpable pathway. Our results support a need for comprehensive evaluation of COMT variations and their functional relevance as COMT may be an important molecular target to evaluate for new treatments regarding obesity.

Nonsteroidal anti-inflammatory drugs and other analgesic use and bladder cancer in northern New England.

A few epidemiologic studies have found that use of nonsteroidal anti‐inflammatory drugs (NSAIDs) is associated with reduced risk of bladder cancer. However, the effects of specific NSAID use and individual variability in risk have not been well studied. We examined the association between NSAIDs use and bladder cancer risk, and its modification by 39 candidate genes related to NSAID metabolism. A population‐based case–control study was conducted in northern New England, enrolling 1,171 newly diagnosed cases and 1,418 controls. Regular use of nonaspirin, nonselective NSAIDs was associated with reduced bladder cancer risk, with a statistically significant inverse trend in risk with duration of use (ORs of 1.0, 0.8, 0.6 and 0.6 for <5, 5–9, 10–19 and 20+ years, respectively; ptrend = 0.015). This association was driven mainly by ibuprofen; significant inverse trends in risk with increasing duration and dose of ibuprofen were observed (ptrend = 0.009 and 0.054, respectively). The reduced risk from ibuprofen use was limited to individuals carrying the T allele of a single nucleotide polymorphism (rs4646450) compared to those who did not use ibuprofen and did not carry the T allele in the CYP3A locus, providing new evidence that this association might be modified by polymorphisms in genes that metabolize ibuprofen. Significant positive trends in risk with increasing duration and cumulative dose of selective cyclooxygenase (COX‐2) inhibitors were observed. Our results are consistent with those from previous studies linking use of NSAIDs, particularly ibuprofen, with reduced risk. We observed a previously unrecognized risk associated with use of COX‐2 inhibitors, which merits further evaluation.

A Powerful Procedure for Pathway-Based Meta-analysis Using Summary Statistics Identifies 43 Pathways Associated with Type II Diabetes in European Populations.

Meta-analysis of multiple genome-wide association studies (GWAS) has become an effective approach for detecting single nucleotide polymorphism (SNP) associations with complex traits. However, it is difficult to integrate the readily accessible SNP-level summary statistics from a meta-analysis into more powerful multi-marker testing procedures, which generally require individual-level genetic data. We developed a general procedure called Summary based Adaptive Rank Truncated Product (sARTP) for conducting gene and pathway meta-analysis that uses only SNP-level summary statistics in combination with genotype correlation estimated from a panel of individual-level genetic data. We demonstrated the validity and power advantage of sARTP through empirical and simulated data. We conducted a comprehensive pathway-based meta-analysis with sARTP on type 2 diabetes (T2D) by integrating SNP-level summary statistics from two large studies consisting of 19,809 T2D cases and 111,181 controls with European ancestry. Among 4,713 candidate pathways from which genes in neighborhoods of 170 GWAS established T2D loci were excluded, we detected 43 T2D globally significant pathways (with Bonferroni corrected p-values < 0.05), which included the insulin signaling pathway and T2D pathway defined by KEGG, as well as the pathways defined according to specific gene expression patterns on pancreatic adenocarcinoma, hepatocellular carcinoma, and bladder carcinoma. Using summary data from 8 eastern Asian T2D GWAS with 6,952 cases and 11,865 controls, we showed 7 out of the 43 pathways identified in European populations remained to be significant in eastern Asians at the false discovery rate of 0.1. We created an R package and a web-based tool for sARTP with the capability to analyze pathways with thousands of genes and tens of thousands of SNPs.