Hung, Rayjean J.

Abstract Pancreatic cancer disproportionately affects Black individuals in the United States, but they have limited representation in genetic studies of pancreatic ductal adenocarcinoma (PDAC). To address this gap, we performed admixture mapping and genome-wide association analysis (GWAS) in genetically inferred African ancestry individuals (1,030 cases and 889 controls). Admixture mapping identified three regions with a significantly higher proportion of African ancestry in cases compared to controls (5q33.3, 10p1, 22q12.3). GWAS identified a genome-wide significant association at 5p15.33 ( CLPTM1L , rs383009:T>C, T Allele Frequency=0.51, OR:1.45, P value=1.24×10 -8 ), a locus previously associated with PDAC. Known loci at 5p15.33, 7q32.3, 8q24.21 and 7q25.1 also replicated (P value <0.01). Multi-ancestral fine-mapping identified two potential causal SNPs (rs3830069 and rs2735940) at 5p15.33. Collectively these findings identified novel PDAC risk loci and expanded our understanding of this deadly cancer in underrepresented populations, emphasizing the multifactorial nature of PDAC risk including inherited genetic and non-genetic factors. Statement of Significance To understand how genetic variation contributes to PDAC risk in Black people in North American, we studied individuals of genetically-inferred African ancestry. We identified novel risk loci and differences in the contribution of known loci. This demonstrates that ancestry-informed genetic analyses improve our understanding of PDAC risk and enhances discovery.

Abstract Background The associations between different types of diabetes, characterized by distinct pathophysiology and genetic architecture, and pancreatic ductal adenocarcinoma (PDAC) risk are not understood. Methods We investigated associations of genetic susceptibility to type 2 diabetes (T2D), 8 T2D mechanistic clusters, type 1 diabetes (T1D), and maturity-onset diabetes of the young (MODY) with PDAC risk. We used genome-wide association study (GWAS) summary-level statistics for T2D (242 283 cases, 1 569 734 controls), T1D (18 942 cases, 501 638 controls), and PDAC (10 244 cases and 360 535 controls) in individuals of European ancestry. Results Two-sample Mendelian randomization (MR) using the Robust Adjusted Profile Score (MR-RAPS) method indicated that genetically predicted T2D was associated with PDAC risk (OR = 1.10; 95% CI = 1.05 to 1.15), particularly the T2D obesity (OR = 1.28; 95% CI = 1.15 to 1.42) and lipodystrophy (OR = 1.25; 95% CI = 1.03 to 1.51) clusters. No association was observed for T1D with PDAC risk (OR = 1.01; 95% CI = 0.99 to 1.02). Pathway/gene-set analysis using the summary-based Adaptive Rank Truncated Product (sARTP) method revealed a significant association between the MODY gene-sets and PDAC risk (P = 1.5 × 10−8), which remained after excluding 20 known PDAC GWAS loci (P = 7.6 × 10−4). HNF1A, FOXA3, and HNF4A were the top contributing genes after excluding the previously identified GWAS loci regions. Conclusions Our results from this genetic association study support that T2D, particularly the obesity and lipodystrophy mechanistic clusters, and MODY genomic susceptibility regions play a role in the etiology of PDAC.

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Abstract Background: Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk. Methods: We conducted a genome-wide interaction analysis of single-nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than three drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies. Our analysis included 3,707 cases and 4,167 controls from case–control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed-effect meta-analyses were conducted. Results: A potential novel region of association on 10p11.22, lead SNP rs7898449 (interaction P value (Pinteraction) = 5.1 × 10−8 in the meta-analysis; Pinteraction = 2.1 × 10−9 in the case–control studies; Pinteraction = 0.91 in the cohort studies), was identified. An SNP correlated with this lead SNP is an expression quantitative trait locus for the neuropilin 1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004). Conclusions: We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an expression quantitative trait locus for neuropilin 1, a protein that plays an important role in the development and progression of pancreatic cancer. Impact: This work can provide insights into the etiology of pancreatic cancer, particularly in heavy drinkers.

Abstract Background: Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer. Methods: We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer. Results: Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P &lt; 5 × 10−8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear &gt; 20). Different risk patterns were observed for the variants among the different groups by smoking behavior. Conclusions: We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies. Impact: Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

Abstract Background: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. Methods: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. Results: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88–1.22; MR-Egger OR, 0.89; 95% CI, 0.65–1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90–1.27; MR-Egger OR, 0.93; 95% CI, 0.67–1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. Conclusions: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. Impact: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.

Abstract Background The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. Methods We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. Results We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. Conclusions Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome‐wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage‐PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta‐Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross‐phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (G corr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (G corr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). Conclusions We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Abstract Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene–sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency &lt; 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10−8); rs79942605 (OR = 2.17, P = 2.81×10−8) and rs208908 (OR = 0.70, P = 4.54×10−8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Abstract Background: Somatic EGFR mutations define a subset of non–small cell lung cancers (NSCLC) that have clinical impact on NSCLC risk and outcome. However, EGFR-mutation-status is often missing in epidemiologic datasets. We developed and tested pragmatic approaches to account for EGFR-mutation-status based on variables commonly included in epidemiologic datasets and evaluated the clinical utility of these approaches. Methods: Through analysis of the International Lung Cancer Consortium (ILCCO) epidemiologic datasets, we developed a regression model for EGFR-status; we then applied a clinical-restriction approach using the optimal cut-point, and a second epidemiologic, multiple imputation approach to ILCCO survival analyses that did and did not account for EGFR-status. Results: Of 35,356 ILCCO patients with NSCLC, EGFR-mutation-status was available in 4,231 patients. A model regressing known EGFR-mutation-status on clinical and demographic variables achieved a concordance index of 0.75 (95% CI, 0.74–0.77) in the training and 0.77 (95% CI, 0.74–0.79) in the testing dataset. At an optimal cut-point of probability-score = 0.335, sensitivity = 69% and specificity = 72.5% for determining EGFR-wildtype status. In both restriction-based and imputation-based regression analyses of the individual roles of BMI on overall survival of patients with NSCLC, similar results were observed between overall and EGFR-mutation-negative cohort analyses of patients of all ancestries. However, our approach identified some differences: EGFR-mutated Asian patients did not incur a survival benefit from being obese, as observed in EGFR-wildtype Asian patients. Conclusions: We introduce a pragmatic method to evaluate the potential impact of EGFR-status on epidemiological analyses of NSCLC. Impact: The proposed method is generalizable in the common occurrence in which EGFR-status data are missing.