Amos, Christopher I.

Abstract Cholangiocarcinoma (CCA) is a rare and aggressive cancer of the bile ducts, with a poor prognosis and limited treatment options. CCA are classified as intrahepatic and extrahepatic based on anatomical location. CCA are often diagnosed at an advanced stage because there are no effective tools for early detection. Although genome-wide association studies (GWASs) have discovered many genome-wide significant contributing risk loci, the genetic underpinning of cholangiocarcinoma remains poorly understood. To date, there is no cholangiocarcinoma-specific GWAS. We conducted GWAS of cholangiocarcinoma in 9,648 individuals of European ancestry using TOPMed reference panel. The putative associations in or near THSD7A on chromosome 7 (OR=2.61, P=7.13 × 10−8), ZBTB16 on 11 (OR=0.16, P=6.02 × 10−8) for non-PSC-related CCA, PUM3 on 9 (OR=10.74, P=6.12 × 10−8), AGBL1 on 15 (OR=2.08, P=5.67 × 10−8) for PSC-related CCA, and LINC02506 on 4 (OR=0.16, P=8.83 × 10−9) for extrahepatic CCA. We also implemented linkage disequilibrium score regression (LDSR) analysis to quantify the genetic correlation between phenotypes using publicly available GWAS summary statistics. Our study aimed to identify possible clinical and epidemiological traits associated with CCA. We identified numerous biomarkers, medical conditions, environmental and behavioral traits, and physical measurements showing high heritability, which is the proportion of phenotypic variance explained by all SNPs included in the analysis, and pairwise genetic correlation with CCA and other CCA subtypes. Elevations of selected biomarkers such as alkaline phosphatase, cystatin C, HbA1c, monocyte count, and white blood cell count show a positive genetic association with CCA in European-ancestry population. Also, autoimmune-mediated conditions show a strong positive genetic association with CCA, non-PSC related CCA, and intrahepatic CCA. The GWAS of CCA and CCA subtypes revealed potential genetic susceptibility associations and will allow us to compare the genetic architecture underlying CCA and other diseases of the bile ducts such as primary sclerosing cholangitis and liver cancer. LDSR provided an improved understanding of the genetic architecture between CCA and potential comorbid conditions and biomarkers. Mendelian randomization analysis will be needed to elucidate the causal relationship between CCA and traits of interest. Citation Format: Younghun Han, Katherine A. McGlynn, Jinyoung Byun, Matthew A. Cooley, Manal M. Hassan, Christopher I. Amos, Lewis R. Roberts, The International Consortium for the Genetics of Biliary Tract Cancers. Genome-wide association study and LD score regression analysis for cholangiocarcinoma. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5228.

Abstract Background The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. Methods We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. Results We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. Conclusions Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Abstract Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome‐wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage‐PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta‐Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross‐phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (G corr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (G corr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). Conclusions We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Abstract Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Abstract Introduction: Radiotherapy has long been examined in association with second malignancies, but the impact of radiotherapy for initial primary lung cancer (IPLC) on the risk of second primary lung cancer (SPLC) remains controversial. We evaluated associations between IPLC radiotherapy and the risks of SPLC and overall mortality among lung cancer survivors. Methods: We identified 689,785 patients diagnosed with IPLC in 1988-2013 from SEER. We applied cause-specific Cox (CSC) regression to evaluate association between IPLC radiotherapy and SPLC risk, adjusting for age at IPLC diagnosis, IPLC stage and histology, and prior history of cancer. To allow a latency period of exposure to IPLC radiotherapy on SPLC risk, we performed subgroup analyses restricted to patients who survived ≥5 and ≥10 years after IPLC diagnosis. Using Cox regression, we evaluated association between IPLC radiotherapy and overall mortality, adjusting for the same covariates used in the CSC analysis. Mediation analysis quantified the indirect effect of IPLC radiotherapy on overall mortality mediated through radiotherapy-driven SPLC diagnosis. Validation utilized data from 7,758 IPLC patients (496 SPLCs) at Mayo Clinic. Results: Of 689,785 IPLC patients, 18,818 (2.7%) developed SPLC in SEER. IPLC patients treated with radiotherapy had a reduced SPLC risk versus non-irradiated patients when evaluated at the time of initial diagnosis (cause-specific hazard ratio [csHR]=0.90, P<1x10-6). However, the association between IPLC radiotherapy and SPLC risk was reversed when analyses were restricted to those who survived at least 5 years (csHR=1.08, P=0.01) and 10 years (csHR=1.16, P=0.009), thus long-term survivors treated with IPLC radiotherapy having a significantly increased risk of SPLC. Mayo Clinic data showed consistent results, with the effect of IPLC radiotherapy increasing from csHR of 2.41 (P<1x10-6) to 3.38 (P=0.001) among 5-year and 10-year survivors, respectively. Similarly, compared to non-irradiated patients, those treated with IPLC radiotherapy showed a significantly increased risk of overall mortality among 10-year survivors (hazard ratio [HR]=1.46, P<1x10-6 in SEER and HR=1.54, P=5.1X10-5 in Mayo Clinic). Mediation analysis showed that a substantial proportion of the total effect of IPLC radiotherapy on overall mortality—ranging from 32% to 59%—was due to radiotherapy-driven SPLC among 10-year survivors in SEER and Mayo Clinic. Conclusions: IPLC radiotherapy is associated with increased risks of SPLC and overall mortality, with its effects more pronounced among long-term survivors. Citation Format: Eunji Choi, Vicky T. Lam, Jacqueline A. Aredo, Ashok V. Kumar, Jason Wampfler, Julie T. Wu, David C. Christiani, Iona Cheng, Christopher I. Amos, Rayjean J. Hung, Leah M. Backhus, Joel W. Neal, Heather A. Wakelee, Ping Yang, Summer S. Han. Long term effect of radiotherapy on risk of second primary lung cancer and overall mortality among lung cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3445.

Abstract Lung cancer (LC) is the most common cause of cancer mortality and the third most common cancer by incidence in the United States. While environmental factors play an important role in its development, LC risk also exhibits a high degree of heritability. Linkage analyses and genome-wide association studies have identified multiple loci associated with increased LC risk; however, much of the heritability has yet to be explained by these loci. Structural mutations, including copy number variations (CNVs), contribute to phenotypic diversity through dosage and/or cis-regulatory effects. Unbiased CNV mapping is only possible with the use of high-depth, short-read sequencing and remains much more complicated and prone to false positives than SNP detection. As the tools necessary for CNV detection have improved, both somatic and germline CNVs have been shown to play an important role in disease, especially cancer, and often they account for a significant proportion of pathogenic variants. Little has been done to understand the role of germline CNVs in the biological pathways of hereditary lung cancer (HLC). The goal of the current project is to utilize the whole exome sequencing (WES) data in identifying the CNVs in the HLC families (≥3 LC/family) recruited by the Genetic Epidemiology of Lung Cancer Consortium (GELCC). This work uses germline WES data from 203 individuals (60 with a LC diagnosis) from 25 HLC families (≥3 LC affected/family). We limited our investigation to CNVs called by two independent tools using read depth to infer copy number changes and genomic breakpoints: GATK 4 (https://gatk.broadinstitute.org) and XHMM (https://atgu.mgh.harvard.edu/xhmm/). We have identified CNVs (deletions) in the following protein coding genes: KIR2DL1 (19q13.42; OR=1.77), DMBT1 (10q26.13; OR=1.56), SIBPB1 (20p13; OR=1.53), LILRA6 (20p13; OR=1.53), and HLA-DRB5 (6p21.32; OR=1.64) in ≥3 families in at least two individuals/family. All of these genes with the exception of HLA-DRB5 were previously reported in LC studies; HLA-DRB5 was reported in other cancer studies. DMBT1 was reported to be a candidate tumor suppressor gene and frequent loss of heterozygosity (LOH) was observed in several human tumors. It is highly expressed in lung and loss of expression was reported in LC cell lines. All CNVs identified in our study are consistent with Mendelian expectations and appear to be uncommon in the general population. CNVs in these genes may contribute to the lung cancer risk in the HLC families. Further validation of the identified variants is ongoing. We will consider overall CNV burden and disease association with identified deletions and duplications. The enrichment of rare variants in oncogenically associated genes that co-segregate with LC provides specific mutations for future work and improves our understanding of the inheritance and pathogenesis of LC. Citation Format: John Waldron, Kirsten W. Termine, Anthony M. Musolf, Mariza de Andrade, Colette Gaba, Ramaswamy Govindan, Ping Yang, Ming You, Ellen Jaeger, Angelle F. Bencaz, Marshall W. Anderson, Ann G. Schwartz, Susan M. Pinney, Christopher I. Amos, Joan E. Bailey-Wilson, Diptasri M. Mandal. Analyses of whole exome sequencing (WES) data of hereditary lung cancer families identify germline copy number variations (CNVs) in multiple genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1452.

Polygenic diseases, which are genetic disorders caused by the combined action of multiple genes, pose unique and significant challenges for the diagnosis and management of affected patients. A major goal of cardiovascular medicine has been to understand how genetic variation leads to the clinical heterogeneity seen in polygenic cardiovascular diseases (CVDs). Recent advances and emerging technologies in artificial intelligence (AI), coupled with the ever-increasing availability of next generation sequencing (NGS) technologies, now provide researchers with unprecedented possibilities for dynamic and complex biological genomic analyses. Combining these technologies may lead to a deeper understanding of heterogeneous polygenic CVDs, better prognostic guidance, and, ultimately, greater personalized medicine. Advances will likely be achieved through increasingly frequent and robust genomic characterization of patients, as well the integration of genomic data with other clinical data, such as cardiac imaging, coronary angiography, and clinical biomarkers. This review discusses the current opportunities and limitations of genomics; provides a brief overview of AI; and identifies the current applications, limitations, and future directions of AI in genomics.

Abstract Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene–sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10−8); rs79942605 (OR = 2.17, P = 2.81×10−8) and rs208908 (OR = 0.70, P = 4.54×10−8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Abstract There is growing evidence showing that sex disparity in lung cancer risk cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotype from a lung cancer cohort including ~ 47,000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 (OR=0.71, p=4.29x10-8); rs79942605 (OR=2.17, p=2.81x10-8); and rs208908 (OR=0.70, p=4.54x10-8), were identified with different risk effect of lung cancer between men and women. Further eQTL and functional annotation analysis suggested rs208908 affect lung cancer risk through differential regulation of CXADR (Coxsackie Virus And Adenovirus Receptor) gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Abstract Although lung cancer is known to be caused by environmental factors, it has also been shown to have genetic components, and the genetic etiology of lung cancer remains understudied. We previously identified a lung cancer risk locus on 6q23-25 using microsatellite data in families with a history of lung cancer. To further elucidate that signal, we performed targeted sequencing on nine of our most strongly linked families. Two-point linkage analysis of the sequencing data revealed that the signal was heterogeneous and that different families likely had different risk variants. Three specific haplotypes were shared by some of the families: 6q25.3-26 in families 42 and 44, 6q25.2-25.3 in families 47 and 59, and 6q24.2-25.1 in families 30, 33, and 35. Region-based logarithm of the odds scores and expression data identified the likely candidate genes for each haplotype overlap: ARID1B at 6q25.3, MAP3K4 at 6q26, and UTRN (6q24.1) and PHACTR2 (6q24.2). Further annotation was used to zero in on potential risk variants in those genes. All four genes are good candidate genes for lung cancer risk, having been linked to either lung cancer specifically or other cancers. However, this is the first time any of these genes has been implicated in germline risk. Functional analysis of these four genes is planned for future work. Significance: This study identifies four genes associated with lung cancer risk, which could help guide future lung cancer prevention and treatment approaches.