Andrade, Mariza de

ABSTRACT Background Primary Biliary Cholangitis (PBC) is an autoimmune cholangiopathy with polygenic architecture and unknown aetiology. Evidence links Neanderthal‐derived genetic variants to autoimmune conditions; however, their contribution to PBC susceptibility remains unexplored. Objective We investigate whether archaic alleles influence PBC risk. Design Genotype data from four PBC cohorts were analysed: CANUK (4615 cases, 9233 controls), OLD IT (444 cases, 901 controls), NEW IT (255 cases, 579 controls) and MAYO (891 cases, 621 controls). Association testing with 235 592 Neanderthal Informative Markers (NIMs) was performed, adjusting for population stratification. Heritability was estimated using RHE‐mc and temporal haplotype dynamics were assessed using ancient DNA data from Europe and Asia. Results A Neanderthal‐derived variant in TNPO3 (rs12531711), previously reported by Cordell et al. showed strong association in CANUK ( p = 2.04 × 10 −26 ) and replicated across all validation cohorts. This variant functions as an eQTL, upregulating IRF5 and downregulating TNPO3 in blood. It is rare in African populations but common both in Europeans and Asians. Temporal analysis of the haplotype carrying rs12531711 revealed frequency increased substantially during the Bronze Age (5000–3000 BP), rising from 2.0% to 7.7% in Europe and 3.4% to 17.4% in Asia, before stabilizing. Despite this strong single‐variant association, the heritability explained by NIMs was not significantly different from that of non‐NIM variants. Conclusion A Neanderthal‐derived variant contributes to PBC risk and its frequency increased in the Bronze Age, possibly due to pathogen‐driven selection. Archaic introgression overall has limited influence on PBC heritability. Functional studies are needed to elucidate the role of rs12531711.

Background Bleomycin-induced chromosomal breaks (CB) and sister chromatid exchange (SCE) in peripheral blood lymphocytes have been shown to be sensitive cytological markers for susceptibility to DNA damage in patients with various types of cancer and in healthy controls. Factors such as age, sex, smoking, and alcohol consumption could affect the values of some of these biomarkers and should be considered as covariates when analyzing cytogenetic biomarkers because these factors can affect the frequency of CB and SCE. Methods We propose a statistical method using negative binomial (NB) distribution to evaluate the numbers of CB and SCE. In order to determine the best model to represent the frequency of CB and SCE, we compared the NB model with the widely used Poisson model and log-transformed normal model by using generalized linear models. To demonstrate the better fit of the NB model, we analyzed three different data sets from studies conducted at The University of Texas M.D. Anderson Cancer Center. The first set was a case-control study of lung cancer in a population of African Americans and Mexican Americans (286 cases and 156 con-trols), the second set consisted of 311 head and neck cancer patients, and the third set consisted of 105 Hodgkin's disease patients. Results For CB, the estimates of the variability for Hodgkin's disease, head and neck, and lung cancers were 487.24, 502.82, and 520.15, respectively. For SCE, the esti-mates of the variability for Hodgkin's disease was 9777.01. For CB, the dispersion estimates under the three models (Poisson, NB, and Normal) for Hodgkin's disease, head and neck, and lung cancers were: 12.30, 1.20, 0.85; 8.94, 1.05, 0.22; and 10.10, 1.05, 0.25, respectively. For SCE (Hodgkin's disease only), the dispersion estimates under the three models (Poisson, NB, and Normal) were 30.91, 1.11, 0.10, respec-tively. Conclusions Our results demonstrate that the NB model provides a better interpretation and fit for the frequency of CB and SCE in different cancer types. Therefore, we recom-mend it as a model for the analysis of cytogenetic biomarkers.

Abstract Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-sequencing data in GTEx V8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased whole genome sequencing data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

Nononcogenic somatic mutations are thought to be uncommon and inconsequential. To test this, we analyzed 43,693 National Heart, Lung and Blood Institute Trans-Omics for Precision Medicine blood whole genomes from 37 cohorts and identified 7131 non-missense somatic mutations that are recurrently mutated in at least 50 individuals. These recurrent non-missense somatic mutations (RNMSMs) are not clearly explained by other clonal phenomena such as clonal hematopoiesis. RNMSM prevalence increased with age, with an average 50-year-old having 27 RNMSMs. Inherited germline variation associated with RNMSM acquisition. These variants were found in genes involved in adaptive immune function, proinflammatory cytokine production, and lymphoid lineage commitment. In addition, the presence of eight specific RNMSMs associated with blood cell traits at effect sizes comparable to Mendelian genetic mutations. Overall, we found that somatic mutations in blood are an unexpectedly common phenomenon with ancestry-specific determinants and human health consequences.

Background: Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies. Methods: The 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants). Results: Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only PROC (odds ratio, 6.2 for carriers of rare variants; P =7.4×10 −14 ) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at PROC (odds ratio, 3.8; P =1.6×10 −14 ), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: PROS1 became significant (minimum P =1.8×10 −6 with the secondary filter), while SERPINC1 did not (minimum P =4.4×10 −5 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, MS4A1 , became significant ( P =4.4×10 −7 using all missense variants with minor allele frequency <0.0005). Conclusions: Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel MS4A1 locus and to identify additional rare variation associated with venous thromboembolism.

Background: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. Methods: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. Results: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. Conclusions: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Abstract With aging, somatic mutations in hematopoietic stem and progenitor cells (HSPC) can give rise to clonal hematopoiesis of indeterminate potential (CHIP), a premalignant state associated with diverse age-related diseases. Here we report the largest multi-ancestry genome-wide analysis of CHIP to date (N = 1,018,305), including individuals of African (N = 85,978), Admixed American (N = 191,371), East Asian (N = 13,532), European (N = 694,015), and South Asian (N = 13,193) ancestry. Multi-ancestry meta-analyses identified 72 genome-wide significant loci, including 44 novel associations implicating genes such as AFF1 , ATF7IP , ATP8B4 , BCL2 , CEBPA , CYRIA , DNM2 , ELF1 , NKX2-3 , PIK3CB , PRDM16 , RPN1 , TERC , and TRIM4 . Notably, variants at MECOM and PHF20L1 showed opposite allelic effects between DNMT3A - and non- DNMT3A -driven CHIP, highlighting driver-specific germline influences. Implicated loci converge on pathways regulating telomere maintenance, cell-cycle control, hematopoietic transcription, DNA damage response and immune signaling. These findings support a model in which germline variation both expands the HSPC pool and biases clonal selection in a driver-dependent manner, providing a mechanistic basis for inter-individual heterogeneity in CHIP. Phenome-wide association analyses further linked CHIP to hematologic, neoplastic, and circulatory traits, with enrichment across hematopoietic and non-hematopoietic cell types. Together, this work expands the genomic and phenomic landscape of CHIP and reveals germline–somatic interactions that shape clonal evolution during aging.

Abstract Biallelic mutations in Fanconi anemia complementation group genes disrupt DNA repair and result in the complex Fanconi anemia phenotype. In addition, germ line mutations in the BRCA2/FANCD1 Fanconi anemia complementation group gene have also been implicated in predisposition to a number of cancers including pancreatic cancer. The recent identification of FANCC and FANCG mutations in resected pancreatic tumors selected for loss of heterozygosity on chromosome 9, some of which were present in the germ line DNA, suggests that inactivation of these and other Fanconi complementation group genes may contribute to pancreatic cancer. To further assess the relevance of FANCC and FANCG mutations to pancreatic cancer we conducted a mutation screen of these genes in DNA from blood of 421 sequentially collected pancreatic cancer cases diagnosed at the Mayo Clinic. Two truncating FANCC mutations but no truncating FANCG mutations were identified in young onset (&lt;55 years) pancreatic cancer cases with no family history of pancreatic cancer. Both mutations were associated with loss of heterozygosity of the wild-type allele in corresponding pancreatic tumors. In addition, no truncating mutations were identified in germ line DNA from blood of 658 control individuals undergoing routine colonoscopy. Taken together these data support the assertion that inherited mutations in FANCC can predispose to pancreatic cancer.

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.