James D. McKay

Introduction: Smoking cessation substantially reduces tobacco-related morbidity and mortality, with earlier cessation conferring greater health benefits. Polygenic scores (PGSs) for smoking persistence may provide insight into cessation timing across diverse populations. This study examined the association between a multi-ancestry PGS for smoking persistence and smoking cessation timing in a genetically diverse population. Methods: This study included 139,129 current and former smokers with genetic data from the All of Us Research Program. A multi-ancestry PGS for smoking persistence was constructed using genome-wide association study summary statistics from the GWAS & Sequencing Consortium of Alcohol and Nicotine Use Phase 2 (GSCAN2). Smoking status and cessation timing were examined across the PGS distribution, with a focus on differences between the highest and lowest deciles. Median cessation ages and cumulative cessation probabilities were estimated, while Cox proportional hazards models compared cessation hazards across PGS groups overall and by genetic ancestry. Results: Among 139,129 participants, the proportion of current smokers increased across the PGS distribution, from 35.5% in the lowest decile to 51.9% in the highest decile. Unadjusted median cessation ages were 38 and 50 years in the lowest and highest deciles, respectively (N = 125,047). After adjusting for sex, educational attainment, household income, cigarettes smoked per day, and genetic population structure, estimated median cessation ages were 40 years (95% CI: 40-40) and 48 years (95% CI: 47-50), respectively, representing an 8-year difference. Participants in the highest decile also had a lower cessation hazard than those in the lowest decile (HR = 0.67, 95% CI: 0.65-0.70), with associations observed across genetic ancestry groups, although estimates varied in precision. Conclusion: A multi-ancestry PGS for smoking persistence was associated with substantial differences in cessation timing across genetically diverse populations. These findings suggest that genetic liability to smoking persistence may help characterize risk of delayed cessation and inform earlier, more targeted smoking cessation support.

Background: Genome-wide association studies (GWAS) have identified numerous lung cancer susceptibility loci based on single nucleotide polymorphisms (SNPs), yet a substantial proportion of heritability remains unexplained. We therefore evaluated germline copy number variants (CNVs) as an underexplored source of genetic susceptibility and potential contributors to genomic instability in lung cancer. Methods: We conducted a genome-wide analysis of germline CNVs using 19,342 cases and 15,917 controls from the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium, with replication in two independent cohorts. High-confidence CNVs were identified by integrating two CNV callers including PennCNV and modSaRa2. Association analyses were performed using both gene-based and CNV region–based approaches. Polygenic risk scores (PRS) were constructed from top loci, and functional validation was conducted using siRNA-mediated knockdown in lung fibroblast cells. Results: We identified CNVs in four genomic regions (1p36.22, 2q31.2, 6p21.32, and 19q13.32) significantly or suggestively associated with lung cancer risk. Two loci (1p36.22 and 2q31.2) were consistently supported across both analytical strategies. A CNV-based PRS constructed from four key genes (CLCN6, NFE2L2, OPA3, and PSMB8) was significantly associated with lung cancer risk and replicated across independent datasets. Functional assays demonstrated that knockdown of NFE2L2 and OPA3 increased endogenous DNA damage, supporting a role in genomic stability. Conclusions: Germline CNVs contribute to lung cancer susceptibility and may influence carcinogenesis through mechanisms related to genomic instability. Impact: These findings expand our knowledge of the genetic architecture of lung cancer and suggest that the cumulative burden of germline CNVs may contribute to lung cancer susceptibility.

Background: Tobacco, alcohol, and human papillomavirus (HPV) are major risk factors for oral cavity and oropharyngeal cancers, yet their specific contributions to the tumor molecular landscape remain incompletely understood. Methods: We analyzed somatic alterations in 1086 tumors (606 oral cavity cancers and 480 oropharyngeal cancers, including 287 HPV-positive oropharyngeal cancers) profiled with a 1109-gene panel and evaluated their associations with exposures. Results: PIK3CA alterations were widespread but context specific: HPV-positive oropharyngeal cancers featured APOBEC-driven mutations and co-occurrence of FGFR3 mutations in a subset of cases, while HPV-negative oropharyngeal cancers and oral cavity cancers were marked by 3q26/28 (PIK3CA/TP63/SOX2) amplifications. TP53 was the most frequently mutated gene in HPV-negative tumors, with strong enrichment among smokers in HPV-negative oropharyngeal cancers, whereas TP53 mutation frequencies in oral cavity cancers were consistently high, regardless of smoking status. CCND1 amplifications were largely restricted to HPV-negative tumors and were most frequent in individuals reporting combined tobacco and alcohol use. This combined effect was replicated in The Cancer Genome Atlas oral cavity cancer–oropharyngeal cancer cohort and mirrored at the transcriptomic level, where CCND1 messenger RNA expression was highest in dual tobacco-alcohol users. Within oral cavity cancers, characterization of 1 of the largest cohorts of tumors from never smoker–never drinkers to date (n = 100) showed that patients were more likely to be female and to exhibit enrichment for FAT1 and CASP8 mutations compared with tumors from ever smoker–ever drinkers (n = 353). Conclusions: Together, these findings define distinct, exposure-driven patterns of somatic alterations by subsite and HPV status and provide a molecular framework that may inform etiological-based risk stratification in head and neck cancer.

Background: Cholesterol pathways may influence head and neck squamous cell carcinoma (HNSCC) progression, but evidence on prognosis is inconsistent. We used Mendelian randomization (MR) to test whether genetically proxied inhibition of major LDL-C–lowering drug targets and circulating lipid traits affects overall survival (OS) in HPV-positive and non-HPV driven HNSCC. Methods: We proxied lifelong LDL-C lowering using 55 cis-acting SNPs in HMGCR, NPC1L1, PCSK9, and LDLR from the updated 2021 Global Lipids Genetics Consortium, and instrumented circulating lipid traits. Two-sample MR estimated effects on OS in 4,869 multi-centre HNSCC cases (1,291 HPV-positive; 3,578 non-HPV driven) using minimally adjusted Cox models. Sensitivity analyses additionally adjusted for tumour stage and treatment, assessed collider bias using an external HNSCC incidence GWAS, and examined between-centre heterogeneity and colocalization. Results: Using the updated GLGC 2021 instruments, genetically proxied HMGCR inhibition showed a directionally protective but non-significant association with OS in HPV-positive oropharyngeal HNSCC in the primary analysis (IVW HR=0.19, 95% CI 0.03–1.18; P=0.08), with directionally concordant weighted median results. No corresponding protective association was observed for HMGCR in non-HPV-driven disease (IVW HR=1.68, 95% CI 0.78–3.63; P=0.19). No clear evidence of association was observed for NPC1L1, PCSK9, LDLR, or circulating lipid traits in either HPV stratum. Colocalization did not support a shared causal variant. Conclusions: These analyses provide suggestive evidence that genetically proxied HMGCR inhibition may influence survival in HPV-positive oropharyngeal HNSCC. Impact: HMGCR-related pathways may be relevant to prognosis in HPV-positive oropharyngeal HNSCC, whereas clear survival effects of other cholesterol-lowering targets were not supported.

Background: High body mass index (BMI) is a causal risk factor for endometrial cancer, but the tumor molecular mechanisms affected by adiposity remain poorly understood. Here, we characterize the tumor multi-omic landscape of endometrial cancers that have developed on a background of lifelong germline genetic liability to elevated BMI. Methods: We built a polygenic score (PGS) for BMI in women using data on independent, genome-wide significant variants associated with adult BMI in 434,794 women. We performed germline (blood) genotype quality control and imputation on data from 354 endometrial cancer cases from The Cancer Genome Atlas (TCGA). We assigned each case in this TCGA cohort their genetically predicted BMI based on the BMI PGS. Multivariable generalized linear models adjusted for age, stage, microsatellite status and genetic principal components were used to test for associations between the BMI germline PGS and endometrial cancer tumor genome-wide genomic, transcriptomic, proteomic, epigenomic and immune traits in TCGA. Results: High BMI germline PGS was associated with (i) upregulated tumor gene expression in IL6-JAK-STAT3 signaling (FDR = 4.2 × 10⁻⁷) and in other immune/inflammatory pathways; (ii) increased estimated intra-tumor activated mast cell infiltration (FDR = 0.008); and (iii) increased single base substitution (SBS) mutational signature 1 (FDR = 0.03), implicating age-related mutagenesis. In contrast, BMI at diagnosis associated with elevated progesterone receptor expression and alterations in estrogen and androgen signaling. Conclusions: Thus, we integrated germline, somatic and clinical data to identify associations between genetically predicted lifelong liability to higher BMI and endometrial cancer tumor molecular features. These associations inform our understanding of how high BMI may influence the development of this cancer, shaping endometrial tumor biology differentially over the long term.

Chromosome 5p15.33 harbors several independent association signals which demonstrate antagonistic pleiotropy across cancer types, with causal mechanisms largely unresolved. To identify functional variants and enhancer elements at this locus, we performed statistical fine-mapping followed by massively parallel reporter assays (MPRA) and proliferation based CRISPRi screens. This approach identified eight multi-cancer functional variants (MCFVs) across three GWAS signals. Targeting rs421629 (part of the CLPTM1L signal marked by rs465498) with CRISPRi revealed opposing effects on TERT expression in pancreatic versus lung cancer cells, consistent with the antagonistic pleiotropy observed for this signal. Furthermore, CRISPRi nominated an intronic CLPTM1L variable number tandem repeat (VNTR) as a potent enhancer. Long-read sequencing established VNTR polymorphisms as potential causal variants for the rs465498 signal. We showed that Hippo-pathway transcription factors mediate VNTR enhancer activity in lung and pancreatic cancer cells. Together, these findings indicate that cancer susceptibility at 5p15.33 may be mediated by both SNPs and VNTRs and provide an integrated framework for resolving complex pleiotropic loci.

Background: Elevated absolute lymphocyte count is often used as a first indication for diagnostic investigation of chronic lymphocytic leukemia (CLL). The absolute risk of CLL as a function of age, sex, and absolute lymphocyte count has not been described. Methods: We used information about prediagnostic absolute lymphocyte cell count on 475 399 longitudinally followed research participants from UK Biobank, with a median follow-up of 11.6 years, during which 854 participants were diagnosed with CLL. A CLL risk model was developed based on sex, age at recruitment, and prediagnostic absolute lymphocyte count using flexible parametric survival modelling. Results: Compared with research participants who had absolute lymphocyte counts below 2 × 109/L, the risk of CLL was almost 8 times higher for individuals with absolute lymphocyte counts of 3 to 4 × 109/L (hazard ratio = 7.76, 95% CI = 6.24 to 9.65). The absolute risk of CLL was 2-fold higher in male than in female individuals. For 60-year-old persons with absolute lymphocyte counts of 5 ×109/L, 10-year CLL risk was estimated at 6.5% (95% CI = 5.6% to 7.5%) for men and 3.5% (95% CI = 3.0% to 4.1%) for women. The 10-year risk of CLL for participants with absolute lymphocyte counts of 5 ×109/L varied between 0.91% (95% CI = 0.68% to 1.2%) for a 40-year-old woman and 12% (95% CI = 11% to 15%) for a 70-year-old man. Conclusion: The absolute risk of CLL is strongly influenced by age, sex, and absolute lymphocyte count. A crude absolute lymphocyte count cutoff to indicate further investigation for CLL without taking age and sex into consideration will identify some individuals who are at low risk. These results may be considered when establishing guidelines for clinical management in patients with elevated absolute lymphocyte counts.

Supplementary Data from Circulating Isovalerylcarnitine and Lung Cancer Risk: Evidence from Mendelian Randomization and Prediagnostic Blood Measurements

Background/Objectives: Family history is a known risk factor for multiple myeloma (MM) and its precursor condition, monoclonal gammopathy of undetermined significance (MGUS). Previous genome-wide association studies (GWASs) have identified 35 common loci associated with MM risk and 21 associated with MGUS. The objective of this study was to identify less common and rare genetic loci predisposing to MM/MGUS through whole-exome sequencing (WES)-based linkage analysis. Methods:Multipoint linkage analysis was conducted using the Multipoint Engine for Rapid Likelihood Inference (MERLIN) with the Lander–Green algorithm on germline WES data from 79 pedigrees with 2 or more affected relatives (120 MM, 86 MGUS, and 21 unaffected). Genome-wide linkage was evaluated using 12,946 independent single-nucleotide variants (linkage disequilibrium r² < 0.05). Results: Significant linkage was observed at chromosome 6q22.33–q24.2 by the non-parametric model (logarithm-of-odds (LOD) = 3.3) and suggestive linkage by the dominant parametric model (heterogeneity LOD (HLOD) = 2.5). Fourteen rare variants within this region were prioritized using family-specific partial LOD scores and in silico functional prediction tools. Nine of these variants, REPS1, THEMIS, TAAR6, AHI1, VNN1, VNN3, MTFR2/FAM54A, LAMA2, and PHACTR2, overlapped immune-regulatory regions in blood cell lines and were not previously identified in GWASs. Conclusions: This study demonstrates the utility of applying a linkage analysis framework to familial WES data for identifying genomic regions and candidate genes that may contribute to MM/MGUS predisposition. These findings provide new insight into the inherited risk and etiology of familial MM and MGUS.

Dozens of genome-wide association studies (GWAS) have identified thousands of single nucleotide polymor-phisms (SNPs) associated with lung cancer risk. However, it remains challenging to translate these findings to clinical insights. One well-known obstacle is the large amount of type I error attached to GWAS; attempted solutions such as setting a p -value threshold across multiple cohorts or looking for small meta-analysis p -values have only somewhat reduced false positive findings. In contrast, here we advocate for a statistical model-based replication analysis. We first demonstrate that a formal statistical test for the replication com-posite null hypothesis - i.e. that the regression coefficient of a SNP falls in the same direction in multiple cohorts simultaneously - can curate a smaller, higher-quality list of significant SNPs than common alterna-tives. In two-way simulations, the false discovery rate (FDR) of model-based replication analysis is 6.4 times lower than that of meta-analysis with a p < 10 ⁻⁸ threshold. In three-way replication analysis, 9.8% of the International Lung Cancer Consortium GWAS significant SNPs are replicated for squamous cell lung cancer while 33.8% are replicated for lung adenocarcinoma. Finally, we construct polygenic risk scores (PRSs) and find the replication-based PRS achieves virtually identical performance to a GWAS-significant PRS while us-ing 87.3% fewer variants. Thus, formal model-based replication analysis can greatly reduce spurious findings while still identifying important variants, allowing for more robust and more efficient translation of GWAS results.