Diverse Ancestry Research Articles

Genome-wide study of half a million individuals with major depression identifies 697 independent associations, infers causal neuronal subtypes and biological targets for novel pharmacotherapies.

In a genome-wide association study (GWAS) of 685,808 individuals with major depression (MD) and 4,364,225 controls from 29 countries and across diverse and admixed ancestries, we identify 697 independent associations at 636 genetic loci, 293 of which are novel. Using fine-mapping and functional genomic datasets, we find 308 high-confidence gene associations and enrichment of postsynaptic density and receptor clustering. Leveraging new single-cell gene expression data, we conducted a causal neural cell type enrichment analysis that implicated excitatory and inhibitory midbrain and forebrain neurons, peptidergic neurons, and medium spiny neurons in MD. Critically, our findings are enriched for the targets of antidepressants and provide potential antidepressant repurposing opportunities (e.g., pregabalin and modafinil). Polygenic scores (PGS) from European ancestries explained up to 5.7% of the variance in liability to MD in European samples and PGS trained using either European or multi-ancestry data significantly predicted case control status across all four diverse ancestries. These findings represent a major advance in our understanding of MD across global populations. We provide evidence that MD GWAS reveals known and novel biological targets that may be used to target and develop pharmacotherapies addressing the considerable unmet need for effective treatment.

MethylGenotyper: Accurate Estimation of SNP Genotypes and Genetic Relatedness from DNA Methylation Data.

Epigenome-wide association studies (EWAS) are susceptible to widespread confounding caused by population structure and genetic relatedness. Nevertheless, kinship estimation is challenging in EWAS without genotyping data. Here, we proposed MethylGenotyper, a method that for the first time enables accurate genotyping at thousands of single nucleotide polymorphisms (SNPs) directly from commercial DNA methylation microarrays. We modeled the intensities of methylation probes near SNPs with a mixture of three beta distributions corresponding to different genotypes and estimated parameters with an expectation-maximization algorithm. We conducted extensive simulations to demonstrate the performance of the method. When applying MethylGenotyper to the Infinium EPIC array data of 4662 Chinese samples, we obtained genotypes at 4319 SNPs with a concordance rate of 98.26%, enabling the identification of 255 pairs of close relatedness. Furthermore, we showed that MethylGenotyper allows for the estimation of both population structure and cryptic relatedness among 702 Australians of diverse ancestry. We also implemented MethylGenotyper in a publicly available R package (https://github.com/Yi-Jiang/MethylGenotyper) to facilitate future large-scale EWAS.

Resolving haplotype variation and complex genetic architecture in the human immunoglobulin kappa chain locus in individuals of diverse ancestry

Immunoglobulins (IGs), critical components of the human immune system, are composed of heavy and light protein chains encoded at three genomic loci. The IG Kappa (IGK) chain locus consists of two large, inverted segmental duplications. The complexity of the IG loci has hindered use of standard high-throughput methods for characterizing genetic variation within these regions. To overcome these limitations, we use long-read sequencing to create haplotype-resolved IGK assemblies in an ancestrally diverse cohort (n = 36), representing the first comprehensive description of IGK haplotype variation. We identify extensive locus polymorphism, including novel single nucleotide variants (SNVs) and novel structural variants harboring functional IGKV genes. Among 47 functional IGKV genes, we identify 145 alleles, 67 of which were not previously curated. We report inter-population differences in allele frequencies for 10 IGKV genes, including alleles unique to specific populations within this dataset. We identify haplotypes carrying signatures of gene conversion that associate with SNV enrichment in the IGK distal region, and a haplotype with an inversion spanning the proximal and distal regions. These data provide a critical resource of curated genomic reference information from diverse ancestries, laying a foundation for advancing our understanding of population-level genetic variation in the IGK locus.

Improving a polygenic risk score (PRS) for breast cancer (BC) risk assessment in diverse ancestries.

10533 Background: Accurate BC risk assessment is essential to identify women for whom screening and preventive interventions may be lifesaving. Incorporation of PRS into clinical models can improve risk prediction, but most PRS have shown suboptimal performance among non-Europeans. We previously described a multiple-ancestry PRS (MA-149) based on 56 ancestry-informative and 93 BC-associated single-nucleotide polymorphisms (SNPs). MA-149 achieved accuracy for diverse populations by characterizing genetic ancestry at each SNP in terms of fractions attributable to reference ancestries (African, East Asian, European) and applying ancestry-specific risks and frequencies. MA-149 significantly outperformed the Tyrer-Cuzick (TC) model, and integration of MA-149 with TC improved predictive accuracy by roughly two-fold over TC alone. Here, we aimed to improve MA-149 by expanding the set of BC SNPs and refining ancestry-specific risks. Methods: We developed a novel stepwise regression methodology accounting for linkage disequilibrium to select an optimal set of BC SNPs. Women referred for hereditary cancer testing and negative for pathogenic variants in BC genes were divided into consecutive cohorts to (1) refine ancestry-specific SNP risks ( N=58,191 Black/African; N=27,160 East Asian), (2) develop the PRS ( N=184,322), and (3) conduct independent validation ( N=146,110). Predictive accuracy and calibration of the new PRS were evaluated in the full cohort and subpopulations of different ancestries. Odds ratios (OR) from multivariable regression are reported per standard deviation. Results: A set of 385 SNPs (56 ancestry, 329 BC) was selected for the new PRS (MA-385). MA-385 improved upon clinical factors and outperformed MA-149 within each ancestry (Table). Among non-Europeans, MA-385 was a better BC risk predictor (OR=1.47, 95% CI: 1.42-1.52) than MA-149 (OR=1.40, 95% CI: 1.35-1.45). The strongest associations were observed in Ashkenazi Jewish and Hispanic women (Table). MA-385 identified more women at >2-fold increased risk than MA-149 (6.5 % vs 2%). Goodness-of-fit tests showed that MA-385 was well-calibrated while a 385-SNP PRS with European weights was miscalibrated for non-Europeans. Conclusions: MA-385 was well-calibrated, improved upon clinical factors, and outperformed existing PRS in all tested ancestries. Incorporation of MA-385 into risk assessment could improve the early detection and prevention of BC. [Table: see text]

Biallelic variants in CSMD1 are implicated in a neurodevelopmental disorder with intellectual disability and variable cortical malformations

CSMD1 (Cub and Sushi Multiple Domains 1) is a well-recognized regulator of the complement cascade, an important component of the innate immune response. CSMD1 is highly expressed in the central nervous system (CNS) where emergent functions of the complement pathway modulate neural development and synaptic activity. While a genetic risk factor for neuropsychiatric disorders, the role of CSMD1 in neurodevelopmental disorders is unclear. Through international variant sharing, we identified inherited biallelic CSMD1 variants in eight individuals from six families of diverse ancestry who present with global developmental delay, intellectual disability, microcephaly, and polymicrogyria. We modeled CSMD1 loss-of-function (LOF) pathogenesis in early-stage forebrain organoids differentiated from CSMD1 knockout human embryonic stem cells (hESCs). We show that CSMD1 is necessary for neuroepithelial cytoarchitecture and synchronous differentiation. In summary, we identified a critical role for CSMD1 in brain development and biallelic CSMD1 variants as the molecular basis of a previously undefined neurodevelopmental disorder.

#3010 Characteristics of a Brazilian cohort with primary hyperoxaluria type 1 (PH1), an admixed population with different ethnic origins

Abstract Background and Aims Primary Hyperoxaluria type 1 (PH1) is caused by biallelic variants in the AGXT gene, leading to alanine:glyoxylate aminotransferase deficiency, hepatic overproduction of oxalate, hyperoxaluria, nephrolithiasis (NL), and/or nephrocalcinosis (NC), often progressing to chronic kidney disease (CKD) with variable phenotypes. Brazilian population is unique due to its diverse ancestry and high admixture rate, which makes this population an interesting group to expand clinical and genetic profile of PH1. Method A descriptive study of genetic confirmed PH1 patients from various regions of Brazil, involving demographic, clinical-laboratory, and genetic data. Results Twenty-one patients (17 families) were identified; 4 detected by family screening (2 with active disease). Parental consanguinity detected in 4 families (23.5%). Nineteen symptomatic patients (12 males) included. At PH1 diagnosis, 3 patients were on CKD stage 1, 1 on CKD 3 and 15 were on CKD 5. We observed notable clinical heterogeneity, and 3 groups are described according to the age at onset. Table 1 shows data for each group and symptomatic cases. All patients have received pyridoxine since PH1 diagnosis. Conclusion In this Brazilian cohort we observed a high percentage of patients diagnosed on CKD 5, detected by recurrence in the renal graft after isolated renal transplantation, and patients achieving CKD 5 after obstructive kidney stones episode. Several factors, including the broad phenotypic spectrum, the lack of awareness among physicians about the disease and the scarcity of diagnostic tools, may explain this delay in diagnosis. Therefore, there is a need to improve information to the Brazilian medical community. The genetic findings are similar to European and North America genetic descriptions and 2 novel variants were identified expanding the AGXT variants profile. However, it is noteworthy, the high percentage of compound heterozygous variants compared with other cohorts worldwide, which may be characteristic of an admixed population.

Exploring the relationship between admixture and genetic susceptibility to attention deficit hyperactivity disorder in two Latin American cohorts

Contemporary research on the genomics of Attention Deficit Hyperactivity Disorder (ADHD) often underrepresents admixed populations of diverse genomic ancestries, such as Latin Americans. This study explores the relationship between admixture and genetic associations for ADHD in Colombian and Mexican cohorts. Some 546 participants in two groups, ADHD and Control, were genotyped with Infinium PsychArray®. Global ancestry levels were estimated using overall admixture proportions and principal component analysis, while local ancestry was determined using a method to estimate ancestral components along the genome. Genome-wide association analysis (GWAS) was conducted to identify significant associations. Differences between Colombia and Mexico were evaluated using appropriate statistical tests. 354 Single-nucleotide polymorphisms (SNPs) and Single-nucleotide variants (SNVs) related to some genes and intergenic regions exhibited suggestive significance (p-value < 5*10e−5) in the GWAS. None of the variants revealed genome-wide significance (p-value < 5*10e−8). The study identified a significant relationship between risk SNPs and the European component of admixture, notably observed in the LOC105379109 gene. Despite differences in risk association loci, such as FOXP2, our findings suggest a possible homogeneity in genetic variation’s impact on ADHD between Colombian and Mexican populations. Current reference datasets for ADHD predominantly consist of samples with high European ancestry, underscoring the need for further research to enhance the representation of reference populations and improve the identification of ADHD risk traits in Latin Americans.

Resolving haplotype variation and complex genetic architecture in the human immunoglobulin kappa and lambda chain loci in individuals of diverse ancestry

Abstract Immunoglobulins (IGs), critical components of the human immune system, are composed of heavy and light protein chains encoded at three genomic loci. The IG Kappa (IGK) chain locus consists of two large, inverted segmental duplications. The complexity of IG loci has hindered effective use of standard high-throughput methods for characterizing genetic variation within these regions. To overcome these limitations, we leverage long-read sequencing to create haplotype-resolved IGK assemblies in an ancestrally diverse cohort (n=36), representing the first comprehensive description of IGK haplotype variation. We identify extensive locus polymorphism, including novel single nucleotide variants (SNVs) and a common novel ∼24.7 Kbp structural variant harboring a functional IGKV gene. Among 47 functional IGKV genes, we identify 141 alleles, 64 (45.4%) of which were not previously curated. We report inter-population differences in allele frequencies for 14 IGKV genes, including alleles unique to specific populations within this dataset. In addition, we identify haplotypes carrying signatures of gene conversion that associate with enrichment of SNVs in the IGK distal region. Finally, we identify extensive polymorphism in the IG Lambda (IGL) locus, including copy number variation for genes encoding IGLC and IGLJ genes. These data lay a foundation for advancing our understanding of how genetic variation in IG loci impacts expressed antibody repertoires in human populations.

A harmonized public resource of deeply sequenced diverse human genomes.

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N= 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

Multi-trait GWAS for diverse ancestries: mapping the knowledge gap

BackgroundApproximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores.MethodsHere, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), and South-East Asian (SAS)).ResultsWe detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multi-trait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome p.vivax induced malaria.ConclusionsMulti-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.

Abstract LB137: Comparison of HPV virus-induced oropharyngeal cancer by self-reported race and the potential implications on treatment

Abstract African Americans exhibit lower survival rates from Human Papillomavirus (HPV)-induced squamous cell carcinomas in comparison to other population groups. While socioeconomic status and access to healthcare may contribute to these disparities, mounting evidence indicates that significant biological differences between diverse ancestries play a role in the severity of different cancers such as breast cancer, colorectal cancer, and squamous cell carcinomas. The purpose of the study is to investigate diagnostic and biological differences in HPV-induced squamous cell carcinomas of the oropharynx by self-reported race. The study population consists of oropharynx cases identified at the University of Michigan (non-Hispanic White) and through the Louisiana Tumor Registry (African American). A total of 52 individuals from two study sites were included in this study, 40 of whom are men, two are women and 10 are unknown. Forty-four percent (23/52) of individuals were African Americans (AA), and 46 % (19/52) were Non-Hispanic White (NHW). Formalin-fixed paraffin-embedded (FFPE) tumors from these patients were tested for p16 expression via immunohistochemistry as a proxy for HPV status. Fifty-two percent (27/52) tested negative (p16-) and 48% (25/52) tested positive (p16+). Total RNA from these samples was extracted, sequenced, and bioinformatically analyzed to test for the presence of HPV. Among AA samples, 61% were negative for both p16 and HPV RNA (p16-/RNA-), 26% were p16+/RNA-, 13% were p16+/RNA+ and none were p16-/RNA+. Among NHWs, 37% were p16-/RNA-, 16% were p16-/RNA+, 47% were p16+/RNA+ and none were p16+/RNA-. Interestingly, 6 of 20 HPV RNA- AA samples were p16+, whereas 0 of 7 HPV RNA- NHW samples were p16+. We performed data dimensionality reduction using Principal Component Analysis (PCA) implemented in the PCAtools Bioconductor package. Four groups were separated in a plot of the first two PCs, comprising, (i) all p16+/RNA+ (18/18), (ii) dominantly p16-/RNA- (6/7), (iii) p16-/RNA- mixed with p16+/RNA-, and (iv) p16-/RNA+ in the middle of all the groups and mixing with some p16+/RNA+ samples. A total of 13/17 (76%) p16-/RNA- samples in group (iii) that were mixed with p16+/RNA- samples were AA, 3 (18%) were NHW and 1 was unknown. Based on clinical data, the PCA group (iii) consisted of samples that were characterized as invasive, keratinizing, and moderately differentiated, whereas group (ii) samples were mostly clinically characterized as nonkeratinizing. A total of 13/14 AA samples that tested p16-/RNA- possessed similar clinical attributes as samples classified as p16+/RNA-, suggesting that the p16 expression via immunohistochemistry test might be classifying a significant percent of HPV-negative AA samples as positive. Taken together, these results suggest that the p16 immunohistochemistry test for oropharyngeal cancer may be overly sensitive for classifying AA oropharynx cancer samples. Clinical decisions regarding treatment for AA based on this test have the potential to negatively impact outcomes. Citation Format: Batsirai M. Mabvakure, Shiting Li, Deborah de la Caridad Delgado Herrera, William Benjamin, Lucia Martinez Cruz, Siddhi Patil, Elham Mohebbi, Gregory T. Wolf, Anju Duttargi, Christina Lefante, Mei-Chin Hsieh, Nisha J. D'Silva, Maureen Sartor, Laura Rozek. Comparison of HPV virus-induced oropharyngeal cancer by self-reported race and the potential implications on treatment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB137.

The VEGF-Hypoxia Signature Is Upregulated in Basal-like Breast Tumors from Women of African Ancestry and Associated with Poor Outcomes in Breast Cancer.

Black women experience the highest breast cancer mortality rate compared with women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry. We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n = 182) and the University of Chicago (Chicago, IL; n = 161). We also analyzed RNA sequencing data from Nigeria (n = 84) and The Cancer Genome Atlas (TCGA) datasets (n = 863). Patient prognosis was analyzed using multiple datasets. The VEGF-hypoxia signature was highest in the basal-like subtype compared with other subtypes, with greater expression in Black women compared with White women. In TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared with non-necrosis tumors (P < 0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation, and necrosis. T-cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in TCGA dataset. Finally, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (P < 0.0001) and SCAN-B datasets (P = 0.002). These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora.

A genome-wide spectrum of tandem repeat expansions in 338,963 humans

The Genome Aggregation Database (gnomAD), widely recognized as the gold-standard reference map of human genetic variation, has largely overlooked tandem repeat (TR) expansions, despite the fact that TRs constitute ∼6% of our genome and are linked to over 50 human diseases. Here, we introduce the TR-gnomAD (https://wlcb.oit.uci.edu/TRgnomAD), a biobank-scale reference of 0.86 million TRs derived from 338,963 whole-genome sequencing (WGS) samples of diverse ancestries (39.5% non-European samples). TR-gnomAD offers critical insights into ancestry-specific disease prevalence using disparities in TR unit number frequencies among ancestries. Moreover, TR-gnomAD is able to differentiate between common, presumably benign TR expansions, which are prevalent in TR-gnomAD, from those potentially pathogenic TR expansions, which are found more frequently in disease groups than within TR-gnomAD. Together, TR-gnomAD is an invaluable resource for researchers and physicians to interpret TR expansions in individuals with genetic diseases.

Landscape of genomic structural variations in Indian population-based cohorts: Deeper insights into their prevalence and clinical relevance

Structural variations (SV) are large (> 50 bp) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) has been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2913 duplications, 8710 insertions, and 13 inversions. 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the under-represented Indian population provides valuable insights that extends beyond Euro-centric human genetic studies.

Abstract 6237: Large-scale imputation models for multi-ancestry proteome-wide association analysis

Abstract Proteome-wide association studies (PWAS) decode the intricate proteomic landscape of biological mechanisms for complex diseases. Traditional PWAS model training relies heavily on individual-level reference proteomes, thereby restricting its capacity to harness the emerging summary-level protein quantitative trait loci (pQTL) data in the public domain. Here we introduced a novel framework to train PWAS models directly from pQTL summary statistics. By leveraging extensive pQTL data from the UK Biobank, deCODE, and ARIC studies, we applied our approach to train large-scale European PWAS models (total n = 88,838 subjects). Furthermore, we developed PWAS models tailored for Asian and African ancestries by integrating multi-ancestry summary and individual-level data resources (total n = 914 for Asian and 3,042 for African ancestries). We validated the performance of our PWAS models through a systematic multi-ancestry analysis of over 700 phenotypes across five major genetic data resources. Specifically, we identified several novel and well-known genes for various cancers; we highlighted eight genes associated with six cancer traits across all three PWAS model cohorts, including CTSF, RSPO3, CRTAM, LAYN, CHRDL2, DPEP1, NFASC, and NAAA. Our results bridge the gap between genomics and proteomics for drug discovery, highlighting novel protein-phenotype links and their transferability across diverse ancestries. The developed PWAS models and data resources are freely available at www.gcbhub.org. Citation Format: Chong Wu, Zichen Zhang, Xiaochen Yang, Bingxin Zhao. Large-scale imputation models for multi-ancestry proteome-wide association analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6237.

Abstract 2948: Unveiling hidden genomic diversity: Exploring epigenetic potential and gene expression in African Pan Genome contig sequences

Abstract An important consideration when studying cancer in diverse populations is the representativeness of the reference genome. Cancer genomics findings are largely based upon alignments to GRCh37 and GRCh38 references, and with the recent release of the telomere-to-telomere (T2T) and the Human Pangenome Reference Consortium references, analyses of sequences distinct from previous references in the cancer context provide exciting opportunities to identify novel targets that may be linked to cancer outcomes. Because GRCh38 and T2T are overwhelmingly Eurocentric, the question remains if these references have applicability outside the ancestral populations that comprise them. Prior to T2T and pangenome, whole genome sequencing of 910 individuals of African descent revealed 296.5 million distinct base pairs, which were assembled into 125,715 African Pan Genome (APG) contigs. These unique sequences represent African ancestry novel genomic sequences whose function was unclear. Here we present provisional efforts to determine the function of APG contigs, and whether they are represented in newer references. To determine the epigenetic potential of the 125,715 APG contigs, we used Emboss Cpgplot to predict CpG islands. We identified 8,353 potential CpG islands, where 6,352 contigs had at least 1 predicted CpG island, and 1 contig had 9. There was weak correlation between contig length, GC content and number of predicted CpG islands suggesting that these sequences represented potentially functional regions. Using unmapped transcriptomic reads from our published African ancestry triple negative breast cancer cohort, we sought to determine the expression potential of these contigs. Unmapped reads mapped to ~9% of the contigs, where ~1100 APG contigs had both predicted CpG islands and alignment of the unmapped transcriptomic reads. This strongly suggests that these APG contigs contain African ancestry-specific regulatory regions and functional gene coding sequences. Preliminary BLASTn queries of contigs with regulatory potential revealed that these sequences may be present in T2T. Mapping to T2T and visualization of expression and CpG islands showed that our predictions matched novel T2T sequences. We anticipated some contigs would map to T2T given one- or two-end placement in GRCh38 and wanted to determine if any of the ~1100 contigs mapped to T2T. Initial analysis of this contig subset shows ~15% fail to map to T2T, indicating that T2T may still fail to capture diversity across ancestry groups. These sequences represent previously unstudied expression and epigenetic potential not captured in the reference genome, and we are working to evaluate all 125,715 sequences. Capturing the diversity across the genome remains extremely important to contextualize these findings and build resources to continue moving precision medicine approaches forward across diverse ancestry groups. Citation Format: Rachel Martini, Kyriaki Founta, Sebastian Maurice, Jason White, Onyinye Balogun, Nyasha Chambwe, Melissa Davis. Unveiling hidden genomic diversity: Exploring epigenetic potential and gene expression in African Pan Genome contig sequences [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2948.

Abstract B020: A clinically relevant orthotopic endometrial carcinosarcoma mouse model using human patient-derived organoids

Abstract Uterine carcinosarcoma (CS) is a rare but aggressive endometrial malignancy. The incidence of CS has been increasing and is projected to continue to rise. African American women in particular have an increased incidence of CS and overall increased mortality related to endometrial cancer, underscoring known disparities in cancer care across racial and ethnic groups. Compared to other histologic subtypes, CS remains rare and understudied on a molecular and cellular basis, and under-represented in clinical trials. Therefore, current treatment therapies available for CS have been extrapolated from treatments used in other histologies of endometrial cancer, highlighting a significant need for effective treatment targeted at this subtype. Due to this paucity of data surrounding targeted therapies for CS, patients who are diagnosed with this aggressive and lethal cancer tend to have worse outcomes. We have developed a clinically relevant CS murine model by injecting human CS patient-derived organoids (PDO) from diverse ancestries into the endometrium of immunocompromised mice. Tumor progression in the mice was monitored with physical examination, PET/CT scan, contrast enhanced CT scan, ultrasound, and bioluciferase imaging. The tumor was established after three months, and the mice were sacrificed following the experiment. The diagnosis of invasive CS was confirmed by macroscopic and histologic analyses in the orthotopic model. Our orthotopic CS PDO transplantation model has many potential applications for studying tumor biology of CS in the pre-clinical setting. Future directions include trialing the efficacy of standard of care chemotherapy in the orthotopic model. Using this model, we aim to identify targeted therapy for CS and potentially advance to Phase I human clinical trials. Citation Format: Megan Gorman, Divya Gowthaman, Arielle Katcher, Charlie Chung, Brian Yueh, Mali Barbi, Libia Garcia, Marina Frimer, Gary L. Goldberg, Semir Beyaz. A clinically relevant orthotopic endometrial carcinosarcoma mouse model using human patient-derived organoids [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr B020.

VEXAS-Defining UBA1 Somatic Variants in 245,368 Diverse Individuals in the NIH All Of Us Cohort.

Somatic variants in UBA1 cause VEXAS, a recently described, systemic autoinflammatory disease. Research on VEXAS has largely focused on highly symptomatic patients. We sought to determine the prevalence of canonical, VEXAS-associated somatic variants and their disease penetrance in a diverse, unselected population. We analyzed clinical-grade whole genome sequencing data from 245,368 participants in the All of Us Research Program. We compared persons carrying a canonical VEXAS-associated somatic variant to age, sex, and ancestry matched controls across the domains of diagnoses, medications, and laboratory values. 74 participants were identified who carry one VEXAS-defining somatic variant, UBA1 c.121A>C, p.Met41Leu. The variant allele fraction ranged from 4.5% to 33%. No other canonical VEXAS-associated variants were identified. Of the 74 carriers, 62 (84%) were women, 20 (27%) were African American, and 14 (19%) were American Admixed/Latino. There was no statistically significant association between case/control status and any VEXAS-associated diagnosis code, medication prescription, or laboratory value. We report the largest cohort to date of persons with the VEXAS-associated p.Met41Leu somatic variant. This cohort differed substantially from reported cohorts of patients with clinical VEXAS, having a higher proportion of persons who were young, female, and of diverse ancestry. Variant allele fractions were lower than reported in clinical VEXAS cohorts, and bioinformatic analysis detected no clinical manifestations of VEXAS. Thus, the UBA1 p.Met41Leu somatic variant displayed incomplete penetrance for VEXAS. Further study is needed to determine the natural history of VEXAS-associated somatic variants in the predisease phase.

The frequency of pathogenic variation in the All of Us cohort reveals ancestry-driven disparities

Disparities in data underlying clinical genomic interpretation is an acknowledged problem, but there is a paucity of data demonstrating it. The All of Us Research Program is collecting data including whole-genome sequences, health records, and surveys for at least a million participants with diverse ancestry and access to healthcare, representing one of the largest biomedical research repositories of its kind. Here, we examine pathogenic and likely pathogenic variants that were identified in the All of Us cohort. The European ancestry subgroup showed the highest overall rate of pathogenic variation, with 2.26% of participants having a pathogenic variant. Other ancestry groups had lower rates of pathogenic variation, including 1.62% for the African ancestry group and 1.32% in the Latino/Admixed American ancestry group. Pathogenic variants were most frequently observed in genes related to Breast/Ovarian Cancer or Hypercholesterolemia. Variant frequencies in many genes were consistent with the data from the public gnomAD database, with some notable exceptions resolved using gnomAD subsets. Differences in pathogenic variant frequency observed between ancestral groups generally indicate biases of ascertainment of knowledge about those variants, but some deviations may be indicative of differences in disease prevalence. This work will allow targeted precision medicine efforts at revealed disparities.