Christopher I. Amos’s research while affiliated with University of New Mexico and other places

Despite lung cancer affecting all races and ethnicities, disparities are observed in incidence and mortality rates among different ethnic groups in the United States. Non-Hispanic African Americans had a high incidence rate of lung cancer at 55.8 per 100 000 people, as well as the highest death rate at 37.2 per 100 000 people from 2016 to 2020. While previous genome-wide association studies (GWAS) have identified over 45 susceptibility risk loci that influence lung cancer development, few GWAS have investigated the etiology of lung cancer in African Americans. To address this gap in knowledge, we conducted GWAS of lung cancer focused on studying African Americans, comprising 2267 lung cancer cases and 4264 controls. We identified three loci associated with lung cancer, one with lung adenocarcinoma, and four with lung squamous cell carcinoma in this population at the genomic-wide significance level. Among them, three novel loci were identified near VWF at 12p13.31 for overall lung cancer and GACAT3 at 2p24.3 and LMAN1L at 15q24.1 for lung squamous cell carcinoma. In addition, we confirmed previously reported risk loci with known or new lead variants near CHRNA5 at 15q25.1 and CYP2A6 at 19q13.2 associated with lung cancer and TRIP13 at 5p15.33 and ERC1 at 12p13.33 associated with lung squamous cell carcinoma. Further multi-step functional analyses shed light on biological mechanisms underlying these associations of lung cancer in this population. Our study highlights the importance of ancestry-specific studies for the potential alleviation of lung cancer burden in African Americans.

Inflammatory bowel disease (IBD) is an autoimmune disease (AD) characterized by chronic, relapsing intestinal inflammation. Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multisystem involvement and overactivation of both innate and adaptive immunity. The extra intestinal manifestations (EIMs) that commonly occur in IBD include many of the organ sites that are affected by SLE. ADs are often comorbid with one another and may have shared underlying genetic features and architectures contributing to their pathogenesis and disease course. We performed both epidemiological and post-genome wide association study (GWAS) analyses to investigate the shared genetic features between IBD and systemic lupus erythematosus (SLE). Specifically, we performed epidemiological association analysis in the All of Us Research Program (AoURP) and genome-wide/local genetic correlation analysis and cell-type specific SNP heritability enrichment analysis using previously published summary level data. A significant epidemiologic association exists between IBD and SLE with an adjusted odds ratio (aOR) of 2.94 (95% CI: 2.45–3.53; P < 0.001) in a multivariable model accounting for confounders in the AoURP data. Genome-wide genetic correlation analysis in previously published summary level data demonstrated a significant genetic correlation between IBD, CD, and UC with SLE, and local genetic correlation analysis demonstrated several positive and significant correlations in local genomic regions harboring disease variants in genes common to both SLE and IBD etiology, including variants in ELF1, CD226, JAZF1, WDFY4, and JAK2. Cell-type SNP heritability enrichment analysis identified both overlapping and distinct functional categories contributing to SNP heritability across IBD phenotypes. Notably, IBD-related phenotypes demonstrated significant enrichment in T-lymphocyte functional groups while SLE signal appeared in distinct categories, such as B-lymphocytes (along with CD). Gene-level collapsing analysis of rare variants in the United Kingdom BioBank (UKBB) identified overlapping nominally-significant genes between SLE and IBD, CD, and UC. By leveraging several post-GWAS methods, the present study identifies shared genetic features between IBD and SLE, highlighting similarities and differences in the genetic features that contribute to the pathogenesis of each disease.

Background/Aims The idiopathic inflammatory myopathies (IIMs) are a group of rare autoimmune disorders involving muscle tissue as well as skin, lung, and joints. Genetic association studies have highlighted the role of human leukocyte antigen (HLA) polymorphisms in IIM. The HLA-associated risk may arise from altered binding affinity for autoantigens and interactions between HLA alleles, referred to as non-additive effects. Here, we aimed to characterise non-additive effects on IIM risk across HLA alleles. Methods This study included a total of 3,206 IIM cases and 11,697 controls of European descent. The cases were classified into dermatomyositis, polymyositis, inclusion body myositis and anti-Jo-1 subgroups. HLA alleles were imputed using a multi-ancestry HLA panel. Logistic regressions were conducted to estimate the non-additive effects of HLA alleles. Subgroup analysis, calculation of phenotypic variance explained, and stepwise conditional analyses were also conducted. Results We identified significant non-additive effects in five HLA genes, particularly in the core alleles of ancestral haplotype 8.1 (AH 8.1), including HLA-B*08:01, HLA-C*07:01 HLA-DQA1*05:01, HLA-DQB1*02:01, and HLA-DRB1*03:01 (Table 1). Noteworthy risk difference between heterozygotes and homozygotes was observed in IIM, such as HLA-DRB1*03:01 (homozygote OR = 2.17; heterozygote OR = 3.13). The non-additive effects explained a larger proportion of phenotypic variation than additive effects alone. Conditional analysis indicates the independent non-additive effect of HLA-DRB1*03:01 in AH 8.1 and amino acid residue Arg-74 in HLA-DRB1. Conclusion This study systematically evaluated and identified significant non-additive effects within the HLA region. These findings may reflect the impact of HLA heterozygosity on antigen presentation in IIM development. The non-additive genetic risk model could also provide more accurate individual risk estimates and patient stratification in clinical management. Disclosure G. Chen: None. C. Zhu: None. H. Chinoy: None. C. Amos: None. A. Morris: None. J.A. Lamb: None.

Background Lung cancer is a leading cause of death. Despite advancements in early diagnosis and treatment, most patients are diagnosed at later stages, and the average 5-year survival rate is < 30%. Lung adenocarcinoma (LUAD) is the most common non-small cell lung cancer (NSCLC), representing about 40% of cases, followed by lung squamous cell carcinoma (LUSC) at 25%. The biological patterns and molecular characteristics of LUAD and LUSC exhibit differences. Changes in DNA methylation levels of various genes have been observed in lung cancer subtypes, yet research on differences in DNA methylation patterns between LUAD and LUSC is limited. Methods The methylation microarray dataset (GSE39279, Illumina HumanMethylation450 BeadChip) from Gene Expression Omnibus at the National Center for Biotechnology Information was used. The dataset comprised 444 NSCLC samples derived from tumor tissues, of which 322 were LUAD and 122 were LUSC. We used the Champ (Chip Analysis Methylation Pipeline) package to identify differentially methylated probes (DMPs, Benjamini-Hochberg adjusted p-value < 0.05) and genes representing specific biological pathways between LUAD and LUSC. Singular Value Decomposition regression analysis was used to estimate the impact of age, sex, and smoking status and then adjusted for the covariates with p-values < 0.05. We used the eFORGE TF database to calculate the Find Individual Motif Occurrences (FIMO) p-values for the overlap with transcription factor binding sites. The Gene Expression Profiling Interactive Analysis database was used to measure the gene expression levels of LUAD and LUSC samples in the Genotype-Tissue Expression and the Cancer Genome Atlas Program portals. Results In total, 223,007 DMPs were identified by comparing LUAD and LUAC, with 130,610 hypomethylated and 92,467 hypermethylated. Using the absolute difference of β values between groups ≥ 0.3, we identified 15 DMPs, 11 hypomethylated and four hypermethylated. The DMPs on promoter regions were all hypomethylated in LUSC compared to LUAD (cg00415665 and cg22997040 in ZHX2, cg27649037 in ST18, cg20691436 in CALML3, and cg24580076 in C7orf20). We also identified DMPs based on the importance scores (> 0.1) from a 5-fold cross-validation random forest analysis. The two DMPs in the ZHX2 gene had the highest importance scores (> 8.0). Among those, cg00415665 was covered by the Zfp161_secondary motif (FIMO p-value: < 10-5). The average expression level of ZHX2 in LUSC (transcripts per million, TPM=9.7) was higher than in LUAD (TPM=8.2). Conclusions We characterized the methylation landscape of NSCLCs by histological subtypes and identified that the methylation pattern of cg00415665 in ZHX2, a tumor suppressor gene, was significantly associated with the histological subtype of NSCLC. Further investigation of these findings will provide additional insight into the biology and genetics of LUAD and LUSC. Citation Format Hyeyeun Lim, Christopher I. Amos, Jinyoung Byun, Aaron P. Aaron. Comparing the methylation profiles between lung adenocarcinoma and squamous cell carcinoma [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 2106.

Background Rare, functionally deleterious genetic variants have been implicated as having substantially larger effect sizes than common variants, potentially accounting for much of the missing heritability in lung cancer (LC). Over 25 years, the Genetic Epidemiology of LC Consortium (GELCC) has curated an invaluable resource of specimens and data from individuals with a strong family history of LC. Methods Whole-genome and exome sequencing data were analyzed in 129 high-risk familial LC (FLC) families, defined as having two first-degree relatives or three or more second-degree relatives affected by LC (177 affected FLC and 309 unaffected relatives). The discovery focused on rare (allele frequency < 1% in gnomAD global population) and deleterious variations (missense, stop-gained, frameshift) enriched in FLC. Promising candidates were further external validated in 2,408 sporadic lung cancer (SLC) cases and 885 population controls from the International Lung Cancer Consortium. Results We identified 168 variants with moderate-to-large effects on FLC risk, 100 of which were validated for SLC risk (Table 1 Table 1. Top 20 candidates Gene Rare (MAF < 1%), deleterious variants No. of variant carrier counts Odds Ratio, LC vs Control FLC | Relative | SLC | Control FLC+SLC SLC Oncogene ERBB3 / HER3 p.A1131T 3 | 1 | 2 | 0 35 15 JAK p.V651M 2 | 3 | 7 | 0 62 51 NOTCH3 p.R1560P 3 | 1 | 4 | 0 48 29 ROS1 p.N785X 6 | 4 | 10 | 0 110 74 USP6 p.R522 fs del 3 | 6 | 6 | 0 62 45 Tumor suppressor gene ATM p.L2332P 3 | 2 | 8 | 0 76 59 LZTS2 p.K458R 4 | 4 | 18 | 0 152 133 NPIPB13 p.V270 fs del 13 | 14 | 10 | 0 159 74 PARK2 / PRKN p.P153R 3 | 3 | 8 | 0 76 59 RB1 p.A525G 3 | 0 | 6 | 0 62 45 SLX4 p.S1716T 3 | 2 | 9 | 0 83 66 SYNE1 p.M6566I 2 | 0 | 7 | 0 62 52 TGFBRAP1 p.T301R 5 | 0 | 11 | 0 110 82 WNK1 p.K583 fs del 4 | 0 | 23 | 0 187 171 Other cancer-associated gene CFTR p.R74W 4 | 2 | 4 | 0 55 30 FLG p.R3404 fs del 7 | 2 | 4 | 0 69 30 LTN1 p.R349H 6 | 1 | 10 | 0 110 74 MLNR p.Q334 fs del 3 | 2 | 19 | 0 152 134 SLC39A11 p.R38Q 4 | 2 | 13 | 0 117 96 TTYH2 p.R493C 5 | 4 | 14 | 0 131 104 Dose effect of the top candidates No. candidates 0 variant allele 67 | 194 | 1911 | 834 reference reference 1 variant allele 50 | 66 | 363 | 50 3.5 (2.6 - 4.7) 3.2 (2.3 - 4.3) 2 variant alleles 15 | 18 | 62 | 1 32 (4.5 - 230) 27 (3.8 - 195) 3+ variant alleles 45 | 31 | 72 | 0 98 (6 - 1506) 62 (3.9 -1012) lists 20 top hits). Among these, 15 variants mapped to our previously identified lung cancer linkage locus at 6q23-25 (ROS1, PARK2, SYNE1). Others were enriched in oncogenes (ERBB3, JAK1, MET), tumor suppressor genes (ATM, BRCA2, RB1), and genes involved in the extracellular matrix (COL6A3, FLG, MUC5B). Importantly, individuals carrying more than two combinations of these variants exhibited exceptionally strong dose effects, with odds ratios (OR) exceeding 27. Conclusion Our findings underscore the significant role of rare, high-penetrance variants in FLC etiology and highlight promising targets for early detection and personalized treatment. Future in-depth mechanistic studies are planned to evaluate the pathogenic effects of these specific alleles. Citation Format Yanhong Liu, Claudio Pikielny, Xiangjun Xiao, Bo Peng, Yafang Li, Jinyoung Byun, Chao Cheng, Dakai Zhu, Spiridon Tsavachidis, Colette Gaba, Elena Kupert, Ellen L. Goode, Erin L. Crawford, Kristen Purrington, Marshall Anderson, Michael Cole, Paul Brennan, Geoffrey Liu, James McKay, John K. Field, Rayjean J. Hung, David C. Christiani, Diptasri Mandal, James C. Willey, Ann Schwartz, Joan Bailey-Wilson, Susan M. Pinney, Christopher I. Amos. High-penetrance rare variants underlying familial lung cancer risk: Insights from the Genetic Epidemiology of Lung Cancer Consortium [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 3815.

Hepatocellular carcinoma (HCC) mortality is increasing globally, partly due to the growing prevalence of non-viral 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 non-viral 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 non-viral HCC with 923 epidemiologic, behavioral, and clinical traits from the United Kingdom Biobank (UKBB) cohort. We observed a SNP-array heritability (h2 obs) of 0.20 for non-viral HCC. Next, we estimated the pairwise genetic correlation between non-viral HCC and heritable (h2 obs > 0.02) UKBB traits, identifying significant positive genetic correlations between non-viral 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 non-viral HCC and diseases associated with metabolic dysfunction-associated steatotic liver disease (MASLD), including diabetes, hypertension, chronic ischemic heart disease, and others. Non-viral HCC was negatively associated with filtered coffee intake but positively associated with instant coffee intake. In addition, smoking behavior and the amount of alcohol consumption in the UKBB cohort showed a positive association with non-viral HCC. Our study provides an atlas of cross-trait genetic correlations in non-viral HCC. Taken together, our results demonstrate possible polygenic pleiotropy between non-viral HCC and different phenotypic traits. The results support further exploration of the predictive power of blood-based biomarkers and selected behaviors for inferring HCC development among non-viral individuals. Citation Format Younghun Han, Vikram Shaw, Jinyoung Byun, Rikita Hatia, Katherine McGlynn, Lewis Roberts, Manal Hassan, Christopher I. Amos. Linkage disequilibrium score regression identifies genetic correlations between hepatocellular carcinoma and clinically relevant traits [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 2284.

Background Currently implemented lung cancer risk prediction models consider a limited set of risk factors and insufficiently stratify patients for screening, leaving a large proportion of lung cancer patients, particularly those from non-European ancestries, ineligible for low-dose CT scans. Polygenic risk scores (PRS) have demonstrated potential for improving lung cancer risk prediction, but are predominantly derived from participants of European-ancestry, limiting their applicability to other populations. This study aims to develop a novel multi-ancestry PRS for lung cancer and evaluate its ability to enhance equitable risk stratification. Methods We constructed multi-ancestry PRS using the largest available lung cancer genome-wide associate studies (GWAS), which include 33, 023 European cases and 339, 471 controls, 11, 506 East Asian cases and 179, 654 controls, and 2, 379 African American cases and 6, 908 controls. We trained four genome-wide multi-ancestry PRS models (PRS-CSx, JointPRS, CT-SLEB, and PROSPER) using a reference panel of 1, 287, 077 SNPs, and compared them to a previously published 128-SNP PRS based on known lung cancer risk loci. PRS models were validated in 1, 047 lung cancer cases and 214, 403 controls from the All of Us Research Program biobank and their performance was evaluated in a pooled multi-ancestry analysis as well as stratified by genetic ancestry. Results PRS-CSx demonstrated the highest performance among all tested methods, with an adjusted-AUC (conditional on sex, age, and the top 16 principal components) of 0.60 (95% CI: 0.58-0.62) and an OR of 1.43 (95% CI: 1.35-1.52) in the pooled analysis. Comparable performance was observed in the European ancestry subgroup (OR: 1.48, 95% CI: 1.37-1.59, 697 cases, 112, 145 controls). The PRS-CSx PRS also performed well in the African American population (OR 1.36, 95% CI: 1.17-1.58, 178 cases, 47, 701 controls), and in the Admixed American/Latino population (OR: 1.34, 95% CI: 1.03-1.74, 55 cases, 32, 936 controls). Individuals in the top decile of the PRS distribution had a 1.96-fold increased risk of lung cancer (95% CI: 1.60-2.40) compared to the average group in the 40-60th percentile. Furthermore, on average, individuals in the top decile reached a 1.5% 5-year absolute risk of lung cancer 8 years earlier than those with average PRS values. Conclusions Multi-ancestry PRS outperform a single-ancestry PRS model. Integrating a multi-ancestry PRS into a lung cancer risk prediction model can improve risk stratification, addressing disparities in screening eligibility across diverse populations. This approach has the potential to improve early detection and reduce lung cancer mortality equitably across ancestry groups. Citation Format Nina Adler, Tony Chen, Jinyoung Byun, Christopher Amos, Qing Lan, David C. Christiani, Mattias Johansson, James McKay, Maria T. Landi, Geoffrey Liu, Loic Le Marchand, The International Lung Cancer Consortium, Esteban J. Parra, Linda Kachuri, Haoyu Zhang, Rayjean J. Hung. A multi-ancestry polygenic risk score improves lung cancer risk stratification across diverse populations [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 7397.

Smoking may be associated with an increased risk of lung metastasis in cancers of non-lung origin. We leverage survey and electronic health record data from the diverse All of Us Research Program (AoURP) database to investigate whether smoking and smoking-related behaviors increase the risk of lung metastasis in non-lung primary cancers. The results suggest that cigarette use, measured by four continuous variables, does not increase the risk of lung metastasis in seven common cancer types but demonstrates a small significant effect in a cohort including all types of cancer in the database in both univariable and multivariable analyses. An increased odds ratio of electronic smoke use in patients with lung metastasis was seen in multivariable analyses of the all cancer (OR = 1.29, 95% CI = 1.04–1.59, P = 0.02) and liver cancer (OR = 1.57, 95% CI = 1.06–2.28, P = 0.02) groups. After adjusting for estimated cigarette pack years in the multivariable model, the result remained significant for liver cancer (OR = 1.60, 95% CI = 1.02–2.47, P = 0.04) but not the all cancer cohort. These results warrant further inquiry and suggest that smoking and e-cigarettes may be associated with lung metastasis risk in patients with non-lung tumors. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-89209-4.

Background Inflammatory bowel disease (IBD) is an autoimmune disease (AD) characterized by chronic, relapsing intestinal inflammation. Systemic lupus erythematosus (SLE) is a complex autoimmune disease with multisystem involvement and overactivation of both innate and adaptive immunity. The extra intestinal manifestations (EIMs) that commonly occur in IBD include many of the organ sites that are affected by SLE. ADs are often comorbid with one another and may have shared underlying genetic features and architectures contributing to their pathogenesis and disease course. Methods We performed both epidemiological and post-genome wide association study (GWAS) analyses to investigate the shared genetic features between IBD and systemic lupus erythematosus (SLE). Specifically, we performed epidemiological association analysis in the All of Us Research Program (AoURP) and genome-wide/local genetic correlation analysis and cell-type specific SNP heritability enrichment analysis using previously published summary level data. Results A significant epidemiologic association exists between IBD and SLE with an adjusted odds ratio (aOR) of 2.94 (95% CI: 2.45–3.53; P < 0.001) in a multivariable model accounting for confounders in the AoURP data. Genome-wide genetic correlation analysis in previously published summary level data demonstrated a significant genetic correlation between IBD, CD, and UC with SLE, and local genetic correlation analysis demonstrated several positive and significant correlations in local genomic regions harboring disease variants in genes common to both SLE and IBD etiology, including variants in ELF1, CD226, JAZF1, WDFY4, and JAK2. Cell-type SNP heritability enrichment analysis identified both overlapping and distinct functional categories contributing to SNP heritability across IBD phenotypes. Notably, IBD-related phenotypes demonstrated significant enrichment in T-lymphocyte functional groups while SLE signal appeared in distinct categories, such as B-lymphocytes (along with CD). Gene-level collapsing analysis of rare variants in the United Kingdom BioBank (UKBB) identified overlapping significant genes between SLE and IBD, CD, and UC. Conclusion By leveraging several post-GWAS methods, the present study identifies shared genetic features between IBD and SLE, highlighting similarities and differences in the genetic features that contribute to the pathogenesis of each disease.