Berndt, Sonja I.

Abstract Background: Waist circumference (WC) and its allometric counterpart, “a body shape index” (ABSI), are risk factors for colorectal cancer; however, it is uncertain whether associations with these body measurements are limited to specific molecular subtypes of the disease. Methods: Data from 2,772 colorectal cancer cases and 3,521 controls were pooled from four cohort studies within the Genetics and Epidemiology of Colorectal Cancer Consortium. Four molecular markers (BRAF mutation, KRAS mutation, CpG island methylator phenotype, and microsatellite instability) were analyzed individually and in combination (Jass types). Multivariable logistic and multinomial logistic models were used to assess the associations of WC and ABSI with overall colorectal cancer risk and, in case-only analyses, to evaluate heterogeneity by molecular subtype, respectively. Results: Higher WC (ORper 5 cm = 1.06, 95% confidence interval, 1.04–1.09) and ABSI (ORper 1-SD = 1.07, 95% confidence interval, 1.00–1.14) were associated with elevated colorectal cancer risk. There was no evidence of heterogeneity between the molecular subtypes. No difference was observed regarding the influence of WC and ABSI on the four major molecular markers in proximal colon, distal colon, and rectal cancers, as well as in early- and late-onset colorectal cancers. Associations did not differ in the Jass-type analysis. Conclusions: Higher WC and ABSI were associated with elevated colorectal cancer risk; however, they do not differentially influence all four major molecular mutations involved in colorectal carcinogenesis but underscore the importance of maintaining a healthy body weight in colorectal cancer prevention. Impact: The proposed results have potential utility in colorectal cancer prevention.

Introduction: WM is a rare subtype of lymphoma, identified by the presence of IgM paraprotein, infiltration of clonal, small lymphoplasmacytic B cells in the bone marrow, and the somatic mutation, MYD88 L265P, which is observed in over 90% of WM patients. We previously identified two rare variants at 6p25.3 (EXOC2) and 14q32.13 (TCL1) that were significantly associated with an increased risk of WM/LPL (PMID: 30305637). However, the genetic basis for WM/LPL predisposition remains largely unknown. We conducted the largest WM/LPL GWAS to discover further germline susceptibility loci for WM/LPL. Methods: Our meta-analysis discovery set included 1,707 cases and 58,328 controls of European ancestry from the InterLymph Consortium, genotyped on a high-density SNP array and imputed to TOPMed, providing over 10 million common variants for association testing. Germline genetic loci with suggestive significance (P<5x10-6) were selected for replication in four independent sets (570 cases and 771,770 controls; UK Biobank, Copenhagen Hospital Biobank, FinnGen, Mayo Clinic), giving us a total of 2,277 WM/LPL cases and 831,098 controls. Conditional and sensitivity analyses were performed considering family history and sex. A transcriptome-wide association study (TWAS) was performed using FUSION with expression quantitative trait loci (eQTL) data from GTEx and Young Finns Study in whole blood, lymphocytes, and other tissues. Functional annotations were done using FUMA, F-MAGMA, FORGE, and OpenTarget. Colocalization was measured using CoLoC with whole blood gene expression data. Results & Discussion: We identified 11 germline genetic loci associated with WM/LPL risk that replicated and reached genome-wide significance (P< 5x10-8), including the two known loci on 6p25.3 and 14q32.13 and nine novel loci in the following regions: 6p25.3 (n=2 independent loci), 2q37.1, 9p13.2, 6p21.32, 10q23.31, 16q21, 1p31.1, and 15q15.1. Four of the discovered variants showed strong associations with WM/LPL [odds ratios (ORs) >10]. Enrichment was observed for enhancer and promoter elements in B-cells (FDR q < 0.01), and gene-based and colocalization analyses identified several potential biological pathways. Colocalization analyses show the intronic PAX5 risk variant on 9p (OR=1.5, P= 2.3x10-25) associated with whole blood eQTL expression of PAX5, which plays an essential role in regulating lymphoid progenitors to the B-lymphocyte lineage, as well as RP11-297B17.3 (RNA gene, antisense to PAX5). In addition, GWAS have shown this variant is in linkage disequilibrium (LD) with GWAS loci for CD20 on IgD+ CD38- B cell that represents a specific immunophenotype that helps identify and characterize B cells involved with WM and other similar conditions. The 2q37.1 (SP140) locus (OR=1.6, P=1.2x10-33) contains variants linked to chronic lymphocytic leukemia (CLL) and autoimmune diseases, including multiple sclerosis and Crohn's disease. This locus is important in chromatin-mediated gene regulation, suggesting a significant role in the immune system. The specific variant influences exon-skipping and potentially protein expression, altering the gene's function. The variants on 10q23.31 in FAS (OR=1.3, P=4.4x10-13) and 15q15.1 (OR=1.2, P=8.5x10-11) in BCL2 modifying factor (BMF), are in strong LD with known CLL susceptibility variants. The 15q variant is also linked with multiple lymphoid leukemia GW significant SNPs. Sex-specific analyses identified one novel locus at 20q13.33 associated with the expression of ZGPAT and UCKL1 in males (OR=1.9, P=9.5x10-10). TWAS identified associations with CRHR1 and CDKN2A; overexpression of both are shown to be associated with an increased risk of WM/LPL. Expression of CDKN2A has been linked to childhood acute lymphoblastic leukemia, while CRHR1 has been associated with breast cancer risk. Conclusions: Our study, the largest GWAS of WM to date, has identified 11 susceptibility loci, including two previously known and nine novel regions. The findings underscore the genetic complexity of WM, with the PAX5 and SP140 loci implicated in both chromatin-mediated gene regulation and immune system functions. These insights not only enhance our understanding of WM predisposition but also pave the way for future research focused on functional understanding of these loci, potentially leading to new therapeutic strategies.

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.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769 ), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047 ), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Abstract Background: The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors’ association with colorectal cancer risk and survival differs by SBS88. Methods: Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer–specific survival using Cox proportional hazards regression (N = 3,465 cases). Results: 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66–0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer–specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47–7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78–1.21, Pheterogeneity = 0.066). Conclusions: Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer–specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. Impact: This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.

Importance Germline gene panel testing is recommended for men with advanced prostate cancer (PCa) or a family history of cancer. While evidence is limited for some genes currently included in panel testing, gene panels are also likely to be incomplete and missing genes that influence PCa risk and aggressive disease. Objective To identify genes associated with aggressive PCa. Design, Setting, and Participants A 2-stage exome sequencing case-only genetic association study was conducted including men of European ancestry from 18 international studies. Data analysis was performed from January 2021 to March 2023. Participants were 9185 men with aggressive PCa (including 6033 who died of PCa and 2397 with confirmed metastasis) and 8361 men with nonaggressive PCa. Exposure Sequencing data were evaluated exome-wide and in a focused investigation of 29 DNA repair pathway and cancer susceptibility genes, many of which are included on gene panels. Main Outcomes and Measures The primary study outcomes were aggressive (category T4 or both T3 and Gleason score ≥8 tumors, metastatic PCa, or PCa death) vs nonaggressive PCa (category T1 or T2 and Gleason score ≤6 tumors without known recurrence), and metastatic vs nonaggressive PCa. Results A total of 17 546 men of European ancestry were included in the analyses; mean (SD) age at diagnosis was 65.1 (9.2) years in patients with aggressive PCa and 63.7 (8.0) years in those with nonaggressive disease. The strongest evidence of association with aggressive or metastatic PCa was noted for rare deleterious variants in known PCa risk genes BRCA2 and ATM ( P ≤ 1.9 × 10 −6 ), followed by NBN ( P = 1.7 × 10 −4 ). This study found nominal evidence ( P < .05) of association with rare deleterious variants in MSH2 , XRCC2 , and MRE11A . Five other genes had evidence of greater risk (OR≥2) but carrier frequency differences between aggressive and nonaggressive PCa were not statistically significant: TP53 , RAD51D , BARD1 , GEN1 , and SLX4 . Deleterious variants in these 11 candidate genes were carried by 2.3% of patients with nonaggressive, 5.6% with aggressive, and 7.0% with metastatic PCa. Conclusions and Relevance The findings of this study provide further support for DNA repair and cancer susceptibility genes to better inform disease management in men with PCa and for extending testing to men with nonaggressive disease, as men carrying deleterious alleles in these genes are likely to develop more advanced disease.

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 genotoxin colibactin, produced by Escherichia coli containing the pks island, is associated with a tumor single base substitution (SBS) mutational signature SBS88. It is unknown whether lifestyle and environmental factors related to gut dysbiosis impact colorectal cancer (CRC) risk and survival differently by colibactin signature status. Methods: Utilizing the resources of the Genetic Epidemiology of Colorectal cancer Consortium and Colon Cancer Family Registry (GECCO-CCFR), a consortium including both case-control and cohort study designs, SBS88 tumor mutational signature was measured in 4308 CRC cases who were microsatellite stable (MSS) and had at least five somatic single nucleotide variants for signature decomposition. Associations of 13 lifestyle and environmental factors with CRC risk by colibactin signature status were assessed using logistic and multinomial regression; associations with CRC survival were assessed using Cox proportional hazards regression. Results: 392 (9%) of the 4308 MSS tumors were positive for SBS88. Having a BMI ≥30 kg/m2 (versus a BMI 18.5-24.9 kg/m2) was strongly associated with worse CRC-specific survival among those with the SBS88 signature, but not among those with SBS88 negative CRC [further adjusted hazard ratio (HR) = 3.40 95% confidence interval (CI) 1.47, 7.84, and HR = 0.97 95% CI 0.78, 1.21, respectively, P for heterogeneity = 0.066]. Associations of fruit intake with CRC risk may be differential by SBS88 status. In minimally adjusted models, those in the highest quartile of fruit intake (versus the first quartile) had 0.53 (95% CI 0.37, 0.76) times the risk of SBS88 positive CRC, as opposed to 0.75 (95% CI 0.66, 0.85) times the risk of SBS88 negative CRC (P for heterogeneity = 0.047). Among cohort studies specifically, associations between CRC risk and BMI, alcohol, and fruit intake also differed by SBS88 status (P for heterogeneity ranging 0.02-0.05). Conclusions: Higher BMI may be associated with worse CRC-specific survival among those with SBS88 positive tumors. BMI, alcohol, and dietary factors may be differentially associated with CRC risk based on SBS88 status. Citation Format: Claire Elizabeth Thomas, Peter Georgeson, Conghui Qu, Robert S. Steinfelder, Daniel D. Buchanan, Mark A. Jenkins, Andrea Gsur, Jane C. Figueiredo, Polly A. Newcomb, Peter T. Campbell, Christina Newton, Caroline Y. Um, Lisa Boardman, Victor Moreno, Jenny Chang-Claude, Michael Hoffmeister, Marc J. Gunter, Andrew T. Chan, Shuji Ogino, Ellen L. Goode, Brigid Lynch, Yohannes A. Melaku, Steven Gallinger, Sonja I. Berndt, Wen-Yi Huang, Ulrike Peters, Amanda I. Phipps. Lifestyle and environmental factors in relation to colorectal cancer risk and survival by colibactin tumor mutational signature status [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6453.

Abstract Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. Significance: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.

Multiple myeloma (MM) arises following malignant proliferation of plasma cells in the bone marrow, that secrete high amounts of specific monoclonal immunoglobulins or light chains, resulting in the massive production of unfolded or misfolded proteins. Autophagy can have a dual role in tumorigenesis, by eliminating these abnormal proteins to avoid cancer development, but also ensuring MM cell survival and promoting resistance to treatments. To date no studies have determined the impact of genetic variation in autophagy-related genes on MM risk. We performed meta-analysis of germline genetic data on 234 autophagy-related genes from three independent study populations including 13,387 subjects of European ancestry (6863 MM patients and 6524 controls) and examined correlations of statistically significant single nucleotide polymorphisms (SNPs; p < 1 × 10−9) with immune responses in whole blood, peripheral blood mononuclear cells (PBMCs), and monocyte-derived macrophages (MDM) from a large population of healthy donors from the Human Functional Genomic Project (HFGP). We identified SNPs in six loci, CD46, IKBKE, PARK2, ULK4, ATG5, and CDKN2A associated with MM risk (p = 4.47 × 10−4−5.79 × 10−14). Mechanistically, we found that the ULK4rs6599175 SNP correlated with circulating concentrations of vitamin D3 (p = 4.0 × 10−4), whereas the IKBKErs17433804 SNP correlated with the number of transitional CD24+CD38+ B cells (p = 4.8 × 10−4) and circulating serum concentrations of Monocyte Chemoattractant Protein (MCP)-2 (p = 3.6 × 10−4). We also found that the CD46rs1142469 SNP correlated with numbers of CD19+ B cells, CD19+CD3− B cells, CD5+IgD− cells, IgM− cells, IgD−IgM− cells, and CD4−CD8− PBMCs (p = 4.9 × 10−4−8.6 × 10−4) and circulating concentrations of interleukin (IL)-20 (p = 0.00082). Finally, we observed that the CDKN2Ars2811710 SNP correlated with levels of CD4+EMCD45RO+CD27− cells (p = 9.3 × 10−4). These results suggest that genetic variants within these six loci influence MM risk through the modulation of specific subsets of immune cells, as well as vitamin D3−, MCP-2−, and IL20-dependent pathways.