Canzian, Federico

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 Monoclonal gammopathy of undetermined significance (MGUS) is a necessary precursor condition to multiple myeloma (MM). Given the role of autophagy in modulating MM risk, we investigated whether genetic variation in autophagy‐related genes influences susceptibility to MGUS. We analyzed the association of 34,042 common autophagy‐related single nucleotide polymorphisms (SNPs) with MGUS across six independent cohorts, five from Europe and one from North America, comprising 2317 MGUS cases and 282,358 controls. We also assessed their impact on immune parameters, including absolute counts of 91 blood‐derived immune cell subsets and 103 circulating immunological proteins. Meta‐analysis revealed a genome‐wide significant association between the ULK4 rs6599175C allele and increased MGUS risk ( p = 3.35 × 10 −8 ). Carriers of this allele showed reduced counts of memory B cell subsets (IgM+CD38+CD27+ and IgD+IgM+CD27+; p = .0038 and p = .0056, respectively) and natural effector B cells (CD24+CD38+IgD+IgM+ cells; p = .0060). Although these associations were not statistically significant after multiple testing correction, they suggest a role of ULK4 in early B‐cell differentiation. Additionally, the CDKN2A rs2811710 variant showed a suggestive association with MGUS risk ( p = 2.17 × 10 −4 ), affecting transcription factor binding involved in B‐cell proliferation and differentiation, although it lacked association with immune markers. In conclusion, we confirm a genome‐wide significant association of the ULK4 locus and MGUS risk, supporting its role in early B‐cell differentiation, and identify CDKN2A as a candidate susceptibility locus warranting further investigation.

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 Obesity has been associated with non‐Hodgkin lymphoma (NHL), but the evidence is inconclusive. We examined the association between genetically determined adiposity and four common NHL subtypes: diffuse large B‐cell lymphoma (DLBCL), follicular lymphoma, chronic lymphocytic leukemia, and marginal zone lymphoma, using eight genome‐wide association studies of European ancestry ( N = 10,629 cases, 9505 controls) and constructing polygenic scores for body mass index (BMI), waist‐to‐hip ratio (WHR), and waist‐to‐hip ratio adjusted for BMI (WHRadjBMI). Higher genetically determined BMI was associated with an increased risk of DLBCL [odds ratio (OR) per standard deviation (SD) = 1.18, 95% confidence interval (95% CI): 1.05–1.33, p = .005]. This finding was consistent with Mendelian randomization analyses, which demonstrated a similar increased risk of DLBCL with higher genetically determined BMI (OR per SD = 1.12, 95% CI: 1.02–1.23, p = .03). No significant associations were observed with other NHL subtypes. Our study demonstrates a positive link between a genetically determined BMI and an increased risk of DLBCL, providing additional support for increased adiposity as a risk factor for DLBCL.

Abstract We investigated the influence of 55 583 autophagy-related single-nucleotide polymorphisms (SNPs) on chronic lymphocytic leukemia (CLL) risk across 4 independent populations comprising 5472 CLL cases and 726 465 controls. We also examined their impact on overall survival (OS), time to first treatment (TTFT), autophagy flux, and immune responses. A meta-analysis of the 4 populations identified, to our knowledge, for the first time, significant associations between CDKN2A (rs3731204) and BCL2 (rs4940571, rs12457371, and rs1026825) SNPs and CLL risk, with CDKN2A showing the strongest association (P = 1.57 × 10−12). We also validated previously reported associations for FAS, BCL2, and BAK1 SNPs with CLL risk (P = 4.73 × 10−21 to 3.39 × 10−9). The CDKN2Ars3731204 and FASrs1926194 SNPs associated with increased CDKN2A and ACTA2 messenger RNA expression levels in the whole blood and/or lymphocytes (P = 5.1 × 10−7, P = 1.58 × 10−21, and P = 7.8 × 10−41), although no significant effect on autophagy flux was observed. However, associations were found between CDKN2A, BCL2, and FAS SNPs and various T-cell subsets, cytokine production, and circulating concentrations of interferon gamma, tumor necrosis factor–related apoptosis-inducing ligand, CD40, chemokine ligand 20, and interleukin-2 receptor subunit β proteins (P ≤ .005). No significant association was detected between autophagy variants and OS or TTFT, suggesting that these variants drive disease initiation rather than progression. In conclusion, this study identified 4 novel associations for CLL and provided insights into the biological pathways that influence CLL development.

AbstractWe conducted the first large genome‐wide association study to identify novel genetic variants that predict better (or poorer) prognosis in colorectal cancer patients receiving standard first‐line oxaliplatin‐based chemotherapy vs chemotherapy without oxaliplatin. We used data from two phase III trials, NCCTG N0147 and NCCTG N9741 and a population‐based patient cohort, DACHS. Multivariable Cox proportional hazards models were employed, including an interaction term between each SNP and type of treatment for overall survival (OS) and progression‐free survival. The analysis was performed for studies individually, and the results were combined using fixed‐effect meta‐analyses separately for resected stage III colon cancer (3098 patients from NCCTG N0147 and 549 patients from DACHS) and mCRC (505 patients from NCCTG N9741 and 437 patients from DACHS). We further performed gene‐based analysis as well as in silico bioinformatics analysis for CRC‐relevant functional genomic annotation of identified loci. In stage III colon cancer patients, a locus on chr22 (rs11912167) was associated with significantly poorer OS after oxaliplatin‐based chemotherapy vs chemotherapy without oxaliplatin (Pinteraction < 5 × 10−8). For mCRC patients, three loci on chr1 (rs1234556), chr12 (rs11052270) and chr15 (rs11858406) were found to be associated with differential OS (P < 5 × 10−7). The locus on chr1 located in the intronic region of RCSD1 was replicated in an independent cohort of 586 mCRC patients from ALGB/SWOG 80405 (Pinteraction = .04). The GWA gene‐based analysis yielded for RCSD1 the most significant association with differential OS in mCRC (P = 6.6 × 10−6). With further investigation into its biological mechanisms, this finding could potentially be used to individualize first‐line treatment and improve clinical outcomes.

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.

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.

Chronic lymphocytic leukemia (CLL) is the most common leukemia among adults worldwide. Although genome-wide association studies (GWAS) have uncovered the germline genetic component underlying CLL susceptibility, the potential use of GWAS-identified risk variants to predict disease progression and patient survival remains unexplored. Here, we evaluated whether 41 GWAS-identified risk variants for CLL could influence overall survival (OS) and disease progression, defined as time to first treatment (TTFT) in a cohort of 1039 CLL cases ascertained through the CRuCIAL consortium. Although this is the largest study assessing the effect of GWAS-identified susceptibility variants for CLL on OS, we only found a weak association of ten single nucleotide polymorphisms (SNPs) with OS (p < 0.05) that did not remain significant after correction for multiple testing. In line with these results, polygenic risk scores (PRSs) built with these SNPs in the CRuCIAL cohort showed a modest association with OS and a low capacity to predict patient survival, with an area under the receiver operating characteristic curve (AUROC) of 0.57. Similarly, seven SNPs were associated with TTFT (p < 0.05); however, these did not reach the multiple testing significance threshold, and the meta-analysis with previous published data did not confirm any of the associations. As expected, PRSs built with these SNPs showed reduced accuracy in prediction of disease progression (AUROC = 0.62). These results suggest that susceptibility variants for CLL do not impact overall survival and disease progression in CLL patients.

Abstract Background: Associations between candidate germline genetic variants and treatment outcome of oxaliplatin, a drug commonly used for patients with colorectal cancer, have been reported but not robustly established. This study aimed to construct polygenic hazard scores (PHSs) as predictive markers for oxaliplatin treatment outcome by using a supervised principal component approach (PCA). Methods: Genome-wide association analysis for overall survival, including interaction terms (SNP*treatment type) was carried out using two phase III trials, 3,098 resected stage III colon cancer (rCC) patients of NCCTG N0147 and 506 metastatic colorectal cancer (mCRC) patients of NCCTG N9741, separately. SNPs showing interaction with genome-wide significance (P &lt; 5 × 10–8) were selected for PCA to derive a PHS. PHS interaction with treatment was included in Cox regression models to predict outcome. Replication of prediction models was performed in an independent cohort, DACHS. Results: The two PHSs based on the first two principal components of selected SNPs (15SNPs for rCC and 13SNPs for mCRC) were used to construct interaction terms with treatment type and included in models adjusted for clinical covariables. However, in the DACHS study, the addition of the two PHS terms to clinical models did not improve the prediction error in either patients with rCC or mCRC. PHS interaction was also not replicated. Conclusions: The PHSs derived using principal components efficiently combined multiple predictive SNPs for estimating likelihood of benefit from oxaliplatin versus other treatment but could not be replicated. Impact: These results highlight the potential but also challenges in generating evidence for a predictive polygenic score for oxaliplatin efficacy.