Jia, Guochong

Abstract Background Breast cancer genome-wide association studies (GWAS) have identified more than 200 susceptibility loci, but most studies are dominated by European and East Asian populations. Methods We analyzed breast cancer GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR), and Hispanic/Latina (H/L) samples (159,297 cases and 212,102 controls). We estimated logit-scale SNP-based heritability, polygenicity, and cross-ancestry genetic correlation, partitioned heritability across functional annotations, and integrated GWAS results with the Tabula Sapiens single-cell atlas using scDRS+. Results The logit-scale heritability of breast cancer ranged from ℎ 2 =0.47 (SE = 0.07) in EAS to AFR ℎ 2 =0.61 (SE = 0.10), with no significant differences across ancestries (p=0.63). The estimated number of susceptibility markers in a sparse normal-mixture effects model also varied from 4,446 (SE = 3,100) in EAS to 8,308 (SE = 2,751) in AFR, but differences were not significant across ancestries (p=0.55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (𝜌 = 0.79, SE = 0.08) and weakest between AFR and H/L (𝜌 = 0.26, SE = 0.24). Regulatory annotations were enriched for breast cancer heritability across samples. Integration with single-cell expression profiles implicated ancestry-shared associations with innate immune, secretory epithelial, and stromal cell types. Conclusion These results indicate substantial cross-ancestry sharing of breast cancer polygenic architecture, highlight a consistent contribution of regulatory variation, and identify convergent cellular contexts that motivate functional follow-up and inform expectations for the transferability and attainable performance of common-variant risk prediction across populations.

Abstract Introduction: Breast cancer genome-wide association studies (GWAS) have identified over 200 susceptibility loci, many replicated in diverse populations. However, cross-ancestry evaluation of breast cancer genetic architecture remains limited. We examined breast cancer genetic architecture using GWAS summary results from European (EUR; cases (ca) = 188,474, controls (co) = 96,201), East Asian (EAS; ca = 20,393, co = 86,329), African American (AA; ca = 9,235, co = 10,184), and US Hispanic/Latina and Latin American (H/L; ca = 2,396, co =7,468) studies. Methods: GWAS results were derived from the Breast Cancer Association Consortium, the African Ancestry Breast Cancer Genetics Consortium (AABCG), Biobank Japan, and a meta-analysis of five studies of H/L women with breast cancer. Linkage disequilibrium (LD) scores were generated for EUR, EAS, and AMR using the 1000 Genomes Project, while AA LD scores were derived from a subset of AABCG controls. Heritability was estimated for each ancestry group using LD score regression. Genetic correlations between populations were assessed via Popcorn. Polygenicity was analyzed using GENESIS; however, due to the limited sample size in the H/L studies, these estimates were restricted to AA, EAS, and EUR. Enrichment of heritability across regulatory elements was evaluated using stratified LD score regression across all populations. Results: The logit-scale heritability and corresponding standard error (SE) were 0.466 (0.066) for EAS, 0.501 (0.050) for EUR, 0.588 (0.360) for H/L, and 0.614 (0.095) for AA. The estimated number of independent susceptibility loci was 4,446 for EAS, 5,235 for EUR, and 8,308 for AA. Using a clumping and thresholding approach, an optimal set of common variants were projected to explain 38.6% (EUR), 39.4% (EAS), and 26.2% (AA) of genetic variance for samples of 100,000 cases and 100,000 controls with AUCs from corresponding estimated polygenic risk scores (PRSs) of 0.621 (EUR), 0.634 (EAS), and 0.611 (AA). Genetic correlations were strongest between EUR and EAS (ρ = 0.79, SE = 0.08) and EUR and H/L (ρ = 0.68, SE = 0.21), and weakest between AA and EAS (ρ = 0.42, SE = 0.14) and AA and H/L (ρ = 0.26, SE = 0.24). Among 73 genomic features, we found significant (P < 0.05/73) enrichment in heritability in EUR for ‘ancient promoter’ regions, transcription factor binding sites, H3K4me3, ‘super-enhancers’, H3K4me1, H3K27ac; in EAS for ‘super-enhancers’; and in AA for H3K27ac. No genomic features were significantly enriched in H/L, likely due to limited power. Conclusion: These findings suggest a shared breast cancer genetic architecture across diverse populations, as well as the potential for a similar level of breast cancer risk stratification by PRS in these populations. Expanding GWAS in underrepresented populations is essential to improve genetic risk predictions and foster equitable cancer prevention. Citation Format: James L. Li, Maria Zanti, Jacob Williams, Om Jahagirdar, Guochong Jia, Qiang Hu, Jean-Tristan Brandenburg, Li Yan, Weang-Kee Ho, Jingmei Li, José P. Miranda, Devika Godbole, Julie-Alexia Dias, Leila Dorling, Wenlong C. Chen, Nicholas Boddicker, Ying Wang, Alicia Martin, Martin J. Zhang, Yan Zhang, Joe Dennis, Esther M. John, Gabriela Torres-Mejia, Larry Kushi, Jeffrey Weitzel, Susan L. Neuhausen, Luis Carvajal-Carmona, Christopher Haiman, Elad Ziv, Laura Fejerman, Wei Zheng, Dezheng Huo, Douglas Easton, Nilanjan Chatterjee, Peter Kraft, Montserrat Garcia-Closas, Wendy Wong, Kyriaki Michailidou, Qianqian Zhu, Diptavo Dutta, Thomas U. Ahearn, Haoyu Zhang. Genetic architecture of breast cancer across diverse populations: Assessing heritability, genetic correlation, and polygenicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2282.

AbstractBiliary tract cancer (BTC) is a rare and aggressive malignancy with increasing incidence. Most BTC cases are diagnosed with metastatic disease which carries a 5‐year survival rate of <5%. Physical activity, diet, and obesity might be associated with BTC risk, but studies have been limited particularly in African descendants. We addressed this knowledge gap by evaluating associations of BTC risk with obesity, physical activity, and dietary intakes in 723,326 adult participants in four cohort studies conducted in China, the United Kingdom, and the United States. Cox regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) in each cohort; results were combined using meta‐analysis. All cohorts had ≥11 median follow‐up years with 839 incident BTC cases combined. BTC risk was positively associated with body mass index (BMI) and waist‐to‐hip ratio (WHR) whereas physical activity, fruit intake, and fish intake were inversely associated. HR and (95% CI) comparing BMI >35.0 to 18.5–24.9: 1.71 (1.26, 2.31), p‐trend <.0001; comparing BMI‐adjusted WHR top to bottom quartile: 1.20 (0.94, 1.53), p‐trend = .05; comparing ≥15–0 metabolic equivalent task‐hours/week 0.76 (0.61, 0.94), p‐trend = .009; comparing highest to lowest intake tertile for fruit and fish 0.79 (0.66, 0.95), p‐trend = .01; 0.82 (0.68, 0.98), p‐trend = .04, respectively. Associations were, in general, similar across ancestry groups. Our study provides strong evidence for important roles of obesity, diet, and physical activity in BTC etiology and stresses the need for lifestyle modification to combat the rising incidence of this fatal malignancy.

Abstract Epithelial ovarian cancer (EOC) is the most common gynecological cancer, and ranks fifth in cancer deaths among women in the United States. Previous studies have identified several circulating proteins biomarkers for EOC risk, such as CA125 antigen and insulin-like growth factor-1 (IGF-1). However, previous studies on protein biomarkers for EOC were limited with small sample sizes, and only a few proteins investigated. In this study, we integrated genomics and proteomics data to search for novel circulating protein biomarkers for EOC risk. We constructed study instruments using genetic variants for protein quantitative trait loci (pQTL) for over 1,400 circulating proteins. Beta coefficients and standard errors of the selected pQTL variants in relation to EOC risk were obtained from 25,509 EOC cases and 40,941 controls from the Ovarian Cancer Association Consortium (OCAC). An inverse-variance weighted method was used to evaluate the association of these genetically predicted protein levels and risk of overall and serous EOC. We identified 35 protein biomarkers, for which their genetically predicted levels were significantly associated with the risk of either overall or serous EOC (false discovery rate &lt;0.05). There are 25 proteins showing significant associations with both overall and serous EOC; most of the associations were stronger for serous EOC than overall EOC. The association for 31 proteins could be attributed, in part, to variants at ABO 9q34.2, a known ovarian cancer susceptibility locus. Five ABO locus-related proteins are in the PI3K-Akt signaling pathway, including insulin-like growth factor 1 receptor, hepatocyte growth factor receptor, interleukin-3 receptor subunit alpha, insulin receptor, and vascular endothelial growth factor receptor 2. Four of these proteins are also in the Rap1 and Ras signaling pathway. These five proteins are all inversely associated with the risk of overall EOC, with odds ratios ranging from 0.64 to 0.93 per unit increase in genetic risk scores (p values: 7.55×10-7 to 5.66×10-2). Four EOC associated proteins which were not influenced by variants in 9q34.2 are microfibrillar-associated protein 2, protein delta homolog 1, semenogelin-2, and netrin-G1, all of which showed significant associations with overall EOC, but not the serous subtype. Our study identifies potential novel biomarkers for ovarian cancer and suggests that genetic variants at locus 9q34.2 may play a role in the relation between levels of these proteins and risk of ovarian cancer. Citation Format: Guochong Jia, Xiang Shu, Xiao-Ou Shu, Jirong Long, Qiuyin Cai, Kirsten B. Moysich, Ellen L. Goode, Thomas A. Sellers, Wei Zheng. Genetically predicted concentration of circulating proteins and epithelial ovarian cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 598.

Abstract Background: Chronic inflammation is implicated in pancreatic cancer carcinogenesis. Advanced glycation end-products (AGEs), which are rich in cooked red meat and cigarette smoke, can perpetuate inflammation by binding to the receptor for advanced glycation end products (AGER, also known as RAGE). We hypothesized that genetic variation of the AGEs/AGER pathway affects pancreatic cancer risk by modulating chronic inflammation. Methods: We conducted a two-stage case-control study to examine the association between 96 single nucleotide polymorphisms (SNPs) in 21 genes (GLO1, MSR1, PINK1, KIF17, AGPAT1, AKR1B1, DDOST, CD36, SCARB1, AGER, APP, HMGB1, S100A8, S100B, S100P, S100A12, MMP9, ADAM10, PPARG, NOTCH4, and PDGF) of the AGEs/AGER pathway and risk of pancreatic cancer. The discovery study was conducted in 672 pancreatic cancer cases and 1361 controls ascertained from the Women’s Health Initiative (WHI) Study matched on age, race/ethnicity and study arm. The validation study was conducted in a PANC4 pooled hospital-based case-control study of 1,034 women cases and 989 women controls. A pooled analysis of 1706 cases and 2350 controls was also performed. SNP data were obtained or imputed from the previously performed GWASs. Pancreatic cancer risk was calculated as odds ratios (ORs) and 95% confidence intervals (Cis) using logistic regression models adjusting for age, race/ethnicity, body mass index (BMI), type 2 diabetes, and smoking using an additive genetic model. The potential interaction between individual SNP and red meat intake and cigarette smoking was examined. A false discovery rate (FDR) adjusted q value &lt; 0.20 was considered statistically significant in the pooled analyses. We also conducted logistic-Kernel machine (LKM) test to examine the association between sets of SNP and risk of pancreatic cancer in the pooled dataset. Results: We identified 11 SNPs with raw P values &lt; 0.10 in the discovery stage in the WHI study. However, none of the SNPs was validated in the validation and pooled dataset. The LKM test showed that sets of SNPs in CD36 (P = 9.3E-10), GLO1(P =2.0E-7), and DDOST (P = 2.5E-4) were significantly associated with pancreatic cancer risk. We found an interaction effect between the GLO1 SNP rs6932648 and smoking status (never versus ever) in the WHI study (P for interaction = 0.01) and the pooled dataset (P for interaction = 0.049). In the pooled dataset, the variant T allele of rs6932648 (MAF = 0.12) was associated with increased risk of pancreatic cancer among ever smokers (additive OR = 1.26, 95% CI: 1.02-1.55), but not among never smokers (additive OR = 0.94, 95% CI: 0.78-1.14), compared with the C allele. Summary and Conclusion: We did not observe significant association between any of 96 single SNP and pancreatic cancer risk. However, we found combined set of SNPs in the GLO1, DDOST, and CD36 genes were associated with risk of pancreatic cancer. GLO SNP rs6932648 may modify the association between smoking and risk of pancreatic cancer. GLO1, DDOST, and CD36 are involved in detoxification or clearance of AGEs compounds. Further investigation of AGEs and receptors systems in pancreatic cancer is warranted. Citation Format: Guochong Jia, Kathryn Royse, Hongwei Tang, Donghui Li, Liang Chen, Lesley Tinker, Gloria Petersen, Alison Klein, Peter Richardson, Donna White, Haleh Sangi-Haghapeykar, Hashem B. El-Serag, Li Jiao. Genetic variations in the AGEs/AGER pathway and risk of pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-160. doi:10.1158/1538-7445.AM2017-LB-160