Abstract Hepatocellular carcinoma (HCC) mortality is increasing globally, partly due to the growing prevalence of nonviral liver diseases. Genome‐wide association studies (GWAS) have identified genetic variants associated with HCC development. Leveraging GWAS summary statistics and linkage disequilibrium score regression (LDSR), we investigated disease co‐development with hepatitis C virus‐negative (HCV‐negative) HCC to provide unique insights into HCC etiology and prioritize relationships for further causal inquiry. We utilized the LDSR statistical framework to estimate the genetic correlation and heritability between HCV‐negative HCC with 901 epidemiologic, behavioral, and clinical traits from the United Kingdom Biobank (UKBB). First, we set the threshold for observed scale heritability of each trait at 0.02 to ensure reliable inferences with adequate study power. Next, we observed significant positive genetic correlations between HCV‐negative HCC and blood‐based biomarkers of liver injury (ALT, GGT) and allostatic load (including glycated hemoglobin, blood pressure, and total albumin). We also identified a positive genetic correlation between HCV‐negative HCC and diseases associated with metabolic dysfunction‐associated steatotic liver disease (MASLD), including diabetes, hypertension, chronic ischemic heart disease, and others. Taken together, our results help to identify polygenic and pleiotropic signals related to different phenotypic traits associated with HCC and support further exploration of the predictive power of blood‐based biomarkers identified in this study for inferring HCC development among HCV‐negative individuals.
Germline Sequencing Analysis to Inform Clinical Gene Panel Testing for Aggressive Prostate Cancer
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.
Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci
AbstractBackgroundKnown risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.MethodsSingle nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer–related cell types.ResultsWe identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.ConclusionsCNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.