Diverse Ancestry Research Articles

Prequalification of genome-based newborn screening for severe childhood genetic diseases through federated training based on purifying hyperselection

Genome-sequence-based newborn screening (gNBS) has substantial potential to improve outcomes in hundreds of severe childhood genetic disorders (SCGDs). However, a major impediment to gNBS is imprecision due to variants classified as pathogenic (P)or likely pathogenic (LP) that are not SCGD causal. gNBS with 53,855 P/LP variants, 342 genes, 412 SCGDs, and 1,603 therapies was positive in 74% of UK Biobank (UKB470K) adults, suggesting 97% false positives. We used the phenomenon of purifying hyperselection, which acts to decrease the frequency of SCGD causal diplotypes, to reduce false positives. Training of gene-disease-inheritance mode-diplotype tetrads in 618,290 control and affected subjects identified 293 variants or haplotypes and seven genes with variable inheritance contributing higher positive diplotype counts than consistent with purifying hyperselection and with little or no evidence of SCGD causality. With these changes, 2.0% of UKB470K adults were positive. In contrast, gNBS was positive in 7.2% of 3,118 critically ill children with suspected SCGDs and 7.9% of 705 infant deaths. When compared with rapid diagnostic genome sequencing (RDGS), gNBS had 99.1% recall. In eight true-positive children, gNBS was projected to decrease time to diagnosis by a median of 121days and avoid life-threatening disease presentations in four children, organ damage in six children, ∼$1.25 million in healthcare cost, and ten (1.4%) infant deaths. Federated training predicated on purifying hyperselection provides a general framework to attain high precision in population screening. Federated training across many biobanks and clinical trials can provide a privacy-preserving mechanism for qualification of gNBS in diverse genetic ancestries.

Genomic insights for personalised care in lung cancer and smoking cessation: motivating at-risk individuals toward evidence-based health practices

Lung cancer and tobacco use pose significant global health challenges, necessitating a comprehensive translational roadmap for improved prevention strategies such as cancer screening and tobacco treatment, which are currently under-utilised. Polygenic risk scores (PRSs) may further motivate health behaviour change in primary care for lung cancer in diverse populations. In this work, we introduce the GREAT care paradigm, which integrates PRSs within comprehensive patient risk profiles to motivate positive health behaviour changes. We developed PRSs using large-scale multi-ancestry genome-wide association studies and standardised PRS distributions across all ancestries. We validated our PRSs in 561,776 individuals of diverse ancestry from the GISC Trial, UK Biobank (UKBB), and All of Us Research Program (AoU). Significant odds ratios (ORs) for lung cancer and difficulty quitting smoking were observed in both UKBB and AoU. For lung cancer, the ORs for individuals in the highest risk group (top 20% versus bottom 20%) were 1.85 (95% CI: 1.58-2.18) in UKBB and 2.39 (95% CI: 1.93-2.97) in AoU. For difficulty quitting smoking, the ORs (top 33% versus bottom 33%) were 1.36 (95% CI: 1.32-1.41) in UKBB and 1.32 (95% CI: 1.28-1.36) in AoU. Our PRS-based intervention model leverages large-scale genetic data for robust risk assessment across populations, which will be evaluated in two cluster-randomised clinical trials. This approach integrates genomic insights into primary care, promising improved outcomes in cancer prevention and tobacco treatment. National Institutes of Health, NIH Intramural Research Program, National Science Foundation.

Exome sequencing in Asian populations identifies low-frequency and rare coding variation influencing Parkinson's disease risk.

Parkinson's disease (PD) is an incurable, progressive and common movement disorder that is increasing in incidence globally because of population aging. We hypothesized that the landscape of rare, protein-altering variants could provide further insights into disease pathogenesis. Here we performed whole-exome sequencing followed by gene-based tests on 4,298 PD cases and 5,512 controls of Asian ancestry. We showed that GBA1 and SMPD1 were significantly associated with PD risk, with replication in a further 5,585 PD cases and 5,642 controls. We further refined variant classification using in vitro assays and showed that SMPD1 variants with reduced enzymatic activity display the strongest association (<44% activity, odds ratio (OR) = 2.24, P = 1.25 × 10-15) with PD risk. Moreover, 80.5% of SMPD1 carriers harbored the Asian-specific p.Pro332Arg variant (OR = 2.16; P = 4.47 × 10-8). Our findings highlight the utility of performing exome sequencing in diverse ancestry groups to identify rare protein-altering variants in genes previously unassociated with disease.

DNA Methylation Signatures of Cardiovascular Health Provide Insights into Diseases.

The association of overall cardiovascular health (CVH) with changes in DNA methylation (DNAm) has not been well characterized. We calculated the American Heart Association's Life's Essential 8 (LE8) score to reflect CVH in five cohorts with diverse ancestry backgrounds. Epigenome-wide association studies (EWAS) for LE8 score were conducted, followed by bioinformatic analyses. DNAm loci significantly associated with LE8 score were used to calculate a CVH DNAm score. We examined the association of the CVH DNAm score with incident CVD, CVD-specific mortality, and all-cause mortality. We identified 609 CpGs associated with LE8 score at false discovery rate (FDR) < 0.05 in the discovery analysis and at Bonferroni corrected P < 0.05 in the multi-cohort replication stage. Most had low-to-moderate heterogeneity (414 CpGs [68.0%] with I 2 < 0.2) in replication analysis. Pathway enrichment analyses and phenome-wide association study (PheWAS) search associated these CpGs with inflammatory or autoimmune phenotypes. We observed enrichment for phenotypes in the EWAS catalog, with 29-fold enrichment for stroke ( P = 2.4e-15) and 21-fold for ischemic heart disease ( P = 7.4e-38). Two-sample Mendelian randomization (MR) analysis showed significant association between 141 CpGs and ten phenotypes (261 CpG-phenotype pairs) at FDR < 0.05. For example, hypomethylation at cg20544516 ( MIR33B ; SREBF1 ) associated with lower risk of stroke ( P = 8.1e-6). In multivariable prospective analyses, the CVH DNAm score was consistently associated with clinical outcomes across participating cohorts, the reduction in risk of incident CVD, CVD mortality, and all-cause mortality per standard deviation increase in the DNAm score ranged from 19% to 32%, 28% to 40%, and 27% to 45%, respectively. We identified new DNAm signatures for CVH across diverse cohorts. Our analyses indicate that immune response-related pathways may be the key mechanism underpinning the association between CVH and clinical outcomes.

Leveraging diverse genomic data to guide equitable carrier screening: Insights from gnomAD v.4.1.0.

Analysis of exome data from the latest release of the Genome Aggregation Database (gnomAD v.4.1.0) revealed a significant carrier burden of pathogenic/likely pathogenic (P/LP) variants in genes associated with autosomal-recessive conditions across diverse ancestral populations. Carrier screening panels are routinely offered to reproductive partners to inform their risk of having an affected child. Current guidelines from the American College of Medical Genetics and Genomics (ACMG) recommend screening for genes with a carrier frequency of at least 1/200 and associated with moderate/severe conditions. Here, we systematically analyzed >700,000 gnomAD v.4.1.0 exomes spanning eight ancestries to estimate the carrier frequency of P/LP variants in 2,987 genes associated with autosomal-recessive conditions. After expert curation for clinical severity, we identified 286 genes meeting the criteria for carrier screening. The number of genes exceeding the 1/200 threshold varied across populations, with 40 in the South Asian ancestry and up to 119 in the Ashkenazi Jewish population. Simulations showed that pan-ethnic screening panels offer advantages for individuals of diverse or admixed ancestry, while ancestry-specific panels may be preferable for genetically homogeneous populations. This study leveraged the most comprehensive genomic dataset to date to provide an updated candidate gene list for equitable carrier screening across diverse populations. Our findings highlight the need for continued expansion of genomic resources to better understand rare disease risk and inform screening efforts in underrepresented groups.

Circulating blood circular RNA in Parkinson's Disease; from involvement in pathology to diagnostic tools in at-risk individuals.

To identify circRNAs associated with Parkinson's disease (PD) we leveraged two of the largest publicly available studies with longitudinal clinical and blood transcriptomic data. We performed a cross-sectional study utilizing the last visit of each participant (N = 1848), and a longitudinal analysis that included 1166 participants with at least two time points. We identified 192 differentially expressed circRNAs, with effects that were sustained during disease, in mutation carriers, and diverse ancestry. The 192 circRNAs were leveraged to distinguish between PD and healthy participants with a ROC AUC of 0.797. Further, 71 circRNAs were sufficient to distinguish between genetic PD (AUC71 = 0.954) and, at-risk participants (AUC71 = 0.929) and healthy controls, supporting that circRNAs have the potential to aid the diagnosis of PD. Finally, we identified five circRNAs highly correlated with symptom severity. Overall, we demonstrated that circRNAs play an important role in PD and can be clinically relevant to improve diagnostic and monitoring.

Biobank-scale characterization of Alzheimer's disease and related dementias identifies potential disease-causing variants, risk factors, and genetic modifiers across diverse ancestries.

Alzheimer's disease and related dementias (AD/ADRDs) pose a significant global public health challenge, underscored by the intricate interplay of genetic and environmental factors that differ across ancestries. To effectively implement equitable, personalized therapeutic interventions on a global scale, it is essential to identify disease-causing mutations and genetic risk and resilience factors across diverse ancestral backgrounds. Exploring genetic-phenotypic correlations across the globe enhances the generalizability of research findings, contributing to a more inclusive and universal understanding of disease. This study leveraged biobank-scale data to conduct the largest multi-ancestry whole-genome sequencing characterization of AD/ADRDs. We aimed to build a valuable catalog of potential disease-causing, genetic risk and resilience variants impacting the etiology of these conditions. We thoroughly characterized genetic variants from key genes associated with AD/ADRDs across 11 genetic ancestries, utilizing data from All of Us, UK Biobank, 100,000 Genomes Project, Alzheimer's Disease Sequencing Project, and the Accelerating Medicines Partnership in Parkinson's Disease, including a total of 25,001 cases and 93,542 controls. We prioritized 116 variants possibly linked to disease, including 18 known pathogenic and 98 novel variants. We detected previously described disease-causing variants among controls, leading us to question their pathogenicity. Notably, we showed a higher frequency of APOE ε4/ε4 carriers among individuals of African and African Admixed ancestry compared to other ancestries, confirming ancestry-driven modulation of APOE -associated AD/ADRDs. A thorough assessment of APOE revealed a disease-modifying effect conferred by the TOMM40 :rs11556505, APOE :rs449647, 19q13.31 :rs10423769, NOCT :rs13116075, CASS4 :rs6024870, and LRRC37A :rs2732703 variants among APOE ε4 carriers across different ancestries. In summary, we compiled the most extensive catalog of established and novel genetic variants in known genes increasing risk or conferring resistance to AD/ADRDs across diverse ancestries, providing clinical insights into their genetic-phenotypic correlations. The findings from this investigation hold significant implications for potential clinical trials and therapeutic interventions on a global scale. Finally, we present an accessible and user-friendly platform for the AD/ADRDs research community to help inform and support basic, translational, and clinical research on these debilitating conditions ( https://niacard.shinyapps.io/MAMBARD_browser/ ).

Benchmarking for genotyping and imputation using degraded DNA for forensic applications across diverse populations

Advancements in sequencing and laboratory technologies have enabled forensic genetic analysis on increasingly low quality and degraded DNA samples. However, existing computational methods applied to genotyping and imputation for generating DNA profiles from degraded DNA have not been tested for forensic applications. Here we simulated sequencing data of varying qualities–coverage, fragment lengths, and deamination patterns–from forty individuals of diverse genetic ancestries. We used this dataset to test the performance of commonly used genotype and imputation methods (SAMtools, GATK, ATLAS, Beagle, and GLIMPSE) on five different SNP panels (MPS-plex, FORCE, two extended kinship panels, and the Human Origins array) that are used for forensic and population genetics applications. For genome mapping and variant calling with degraded DNA, we find use of parameters and methods (such as ATLAS) developed for ancient DNA analysis provides a marked improvement over conventional standards used for next generation sequencing analysis. We find that ATLAS outperforms GATK and SAMtools, achieving over 90 % genotyping accuracy for the four largest SNP panels with coverages greater than 10X. For lower coverages, decreased concordance rates are correlated with increased rates of heterozygosity. Genotype refinement and imputation improve the accuracy at lower coverages by leveraging population reference data. For all five SNP panels, we find that using a population reference panel representative of worldwide populations (e.g., the 1000 Genomes Project) results in increased genotype accuracies across genetic ancestries, compared to ancestry-matched population reference panels. Importantly, we find that the low SNP density of commonly used forensics SNP panels can impact the reliability and performance of genotype refinement and imputation. This highlights a critical trade-off between enhancing privacy by using panels with fewer SNPs and maintaining the effectiveness of genomic tools. We provide benchmarks and recommendations for analyzing degraded DNA from diverse populations with widely used genomic methods in forensic casework.

Abstract 4120763: Predicting Disease Risk Among Variants in Cardiomyopathy-Associated Genes Across Diverse Genetic Ancestries

Background: Many cases of cardiomyopathy (CM) are genetically inherited, and the expansion of broad genomic sequencing has opened the door for predicting those at risk for developing disease. However, genetic tools that help determine variant pathogenicity employ genetic data from predominantly European genetic ancestries. Understanding the full diversity of genetic variants in cardiomyopathy genes is central to identifying which variants will cause disease. Hypothesis: Participants of non-European genetic ancestry will have a higher burden of cardiomyopathy gene variants with "VUS" designation in ClinVar but will have equivalent/less penetrance of clinical cardiomyopathy compared to a European ancestry group. Methods: Participants in the AllofUs database with exome sequencing (ES) were queried and a cohort of 230,013 participants were retained after sample quality control filters. Participant genetic ancestry was based on the designated ancestry group determined via AllofUs as previously described (1). Participants were queried for variants in genes with definitive or moderate evidence of hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), and arrhythmogenic cardiomyopathy (ACM) in ClinGen. Variants were filtered by ClinVar status (1* and above P/LP, 1* and above B/LB, and VUS). Participant CM disease status was determined via ICD-9/10 code. Results: For each ancestry group, prevalence of cardiomyopathy ranged from 0.34% in the Latino/admixed American ancestry group to 1.09% in the African group, with an average prevalence of 0.91% across all groups. The European group had a statistically significant lower percentage of ClinVar VUS variants at 26%, while all other non-European ancestry groups had a combined VUS prevalence rate of 35% (****p&lt;0.0001). The penetrance of CM in participants with CM VUS variants was lower in combined non-European ancestry groups (0.84%) than European ancestry (1.02%) (*p=0.0156). Conclusion: Prevalence of ClinVar VUS variants varies across different genetic ancestry groups, with European ancestry having a lower burden of VUS variants compared to non-European groups. However, non-European ancestry groups with increased burden of VUS variants have lower disease penetrance. Citations: (1) The All of Us Research Program Genomics Investigators. Genomic data in the All of Us Research Program. Nature 627 , 340–346 (2024). https://doi.org/10.1038/s41586-023-06957-x

Abstract 4121555: Integrated Polygenic Score Stratifies Risk of Peripheral Artery Disease and Major Adverse Limb Events

Background: Peripheral artery disease (PAD) is a heritable atherosclerotic condition. With growing knowledge of the genetic basis for PAD and related risk factors, there is opportunity to identify high-risk individuals for prevention and potentially intervention based on polygenic background. Aims: To develop and validate an integrated genome-wide polygenic score for PAD (GPS PAD ), evaluate association of polygenic risk with major adverse limb events (MALE), and compare predictive performance in diverse ancestral populations to previously published polygenic scores. Methods: We developed GPS PAD by integrating genetic association summary statistics for PAD and related traits stratified by ancestry. GPS PAD was trained in a sample of 96,239 European individuals from the UK Biobank, and validated in multi-ancestry cohorts, including a holdout validation UK Biobank dataset (N=304,294), and external All of Us (AoU; N=237,173) and Mass General Brigham Biobank datasets (N=37,017). GPS PAD performance was benchmarked against previously published polygenic scores and clinical risk factors. Results: GPS PAD was comprised of 603,595 variants with weights informed by association with PAD and ten PAD risk factors across five ancestry groups. GPS PAD had an OR-per SD of 1.63 in the holdout UK Biobank dataset (95% CI 1.60-1.68). GPS PAD outperformed previously published scores in non-European subgroups in the UK Biobank and achieved superior cross-population portability in external validation cohorts. GPS PAD was associated with incident PAD in the UK Biobank (HR 1.66; 95% CI 1.61-1.71) and achieved improvements in discrimination (ΔC-statistic 0.030) that were nearly equivalent to the additive performances of diabetes (ΔC-statistic 0.029) and smoking (ΔC-statistic 0.034) to the baseline model including age, sex, and 10 principal components of ancestry. Among individuals with prevalent PAD, GPS PAD was associated with incident MALE in the UK Biobank (HR 1.48; 95% CI 1.24-1.77). GPS PAD consistently identified individuals with PAD at high MALE-risk in the Mass General Brigham Biobank (HR 1.34; 95% CI 1.12-1.60), and AoU (HR 1.33; 95% CI 1.12-1.58). Conclusions: These findings contribute a polygenic score for PAD that predicts disease and MALE with cross-cohort performance and transferability to diverse ancestries. Integrated polygenic scores may be used to stratify PAD risk and target more aggressive management, lifestyle modification, and surveillance efforts.

Diverse ancestry GWAS for advanced age-related macular degeneration in TOPMed-imputed and Ophthalmologically-confirmed 16,108 cases and 18,038 controls.

Age-related macular degeneration (AMD) is a leading cause of blindness with $344 billion dollars global costs. In 2016, the International Age-related Macular Degeneration Genomics Consortium devised genomic data on ∼50,000 individuals (IAMDGC 1.0) and identified 52 variants across 34 loci associated with advanced AMD in European ancestry. We have now analyzed a more densely imputed version (IAMDGC 2.0) and performed cross-ancestry GWAS in 16,108 advanced AMD cases and 18,038 AMD-free controls. This identified 28 loci at P<5×10 -8 , including two additional AMD loci compared to IAMDGC 1.0 ( SERPINA1 and CPN1 ). Fine-mapping supported one ancestry-shared signal around HTRA1/ARMS2 and nine signals around CFH without African ancestry contribution. The 52-variant genetic risk score with and the 44-variant score without CFH -variants predicted advanced AMD not only in EUR, but also in AFR and ASN (AUC=0.80/0.75, 0.65/0.64, 0.80/0.79, respectively). Our results indicate that the genetic underpinning of advanced AMD is mostly shared between ancestries.

An atlas of genetic effects on the monocyte methylome across European and African populations.

Elucidating the genetic architecture of DNA methylation is crucial for decoding complex disease etiology. However, current epigenomic studies are often limited by incomplete methylation coverage and heterogeneous tissue samples. Here, we present the first comprehensive, multi-ancestry human methylome atlas of purified human monocytes, generated through integrated whole-genome bisulfite sequencing and whole-genome sequencing from 298 European Americans (EA) and 160 African Americans (AA). By analyzing over 25 million methylation sites, we identified 1,383,250 and 1,721,167 methylation quantitative trait loci (meQTLs) in cis- regions for EA and AA populations, respectively, revealing both shared (880,108 sites) and population-specific regulatory patterns. Furthermore, we developed population-specific DNAm imputation models, enabling methylome-wide association studies (MWAS) for 1,976,046 and 2,657,581 methylation sites in EA and AA, respectively. These models were validated through multi-ancestry analysis of 41 complex traits from the Million Veteran Program. The identified meQTLs, MWAS models, and data resources are freely available at www.gcbhub.org and https://osf.io/gct57/ .

Microsatellites explorer: A database of short tandem repeats across genomes

Short tandem repeats (STRs) are widespread, repetitive elements, with a number of biological functions and are among the most rapidly mutating regions in the genome. Their distribution varies significantly between taxonomic groups in the tree of life and are highly polymorphic within the human population. Advances in sequencing technologies coupled with decreasing costs have enabled the generation of an ever-growing number of complete genomes. Additionally, the arrival of accurate long reads has facilitated the generation of Telomere-to-Telomere (T2T) assemblies of complete genomes. Nevertheless, there is no comprehensive database that encompasses the STRs found per genome across different organisms and for different human genomes across diverse ancestries. Here we introduce Microsatellites Explorer, a database of STRs found in the genomes of 117,253 organisms across all major taxonomic groups, 15 T2T genome assemblies of different organisms, and 94 human haplotypes from the human pangenome. The database currently hosts 406,758,798 STR sequences, serving as a centralized user-friendly repository to perform searches, interactive visualizations, and download existing STR data for independent analysis. Microsatellites Explorer is implemented as a web-portal for browsing, analyzing and downloading STR data. Microsatellites Explorer is publicly available at https://www.microsatellitesexplorer.com.

The Black and African American Connections to Parkinson’s Disease (BLAAC PD) study protocol

Determining the genetic contributions to Parkinson’s disease (PD) across diverse ancestries is a high priority as this work can guide therapeutic development in a global setting. The genetics of PD spans the etiological risk spectrum, from rare, highly deleterious variants linked to monogenic forms with Mendelian patterns of inheritance, to common variation involved in sporadic disease. A major limitation in PD genomics research is lack of racial and ethnic diversity. Enrollment disparities have detrimental consequences on the generalizability of results and exacerbate existing inequities in care. The Black and African American Connections to Parkinson’s Disease (BLAAC PD) study is part of the Global Parkinson’s Genetics Program, supported by the Aligning Science Across Parkinson’s initiative. The goal of the study is to investigate the genetic architecture underlying PD risk and progression in the Black and/or African American populations. This cross-sectional multicenter study in the United States has a recruitment target of up to 2,000 individuals with PD and up to 2,000 controls, all of Black and/or African American ancestry. The study design incorporates several strategies to reduce barriers to research participation. The multifaceted recruitment strategy aims to involve individuals with and without PD in various settings, emphasizing community outreach and engagement. The BLAAC PD study is an important first step toward informing understanding of the genetics of PD in a more diverse population.

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Association of common and rare variants with Alzheimer's disease in more than 13,000 diverse individuals with whole-genome sequencing from the Alzheimer's Disease Sequencing Project.

Alzheimer's disease (AD) is a common disorder of the elderly that is both highly heritable and genetically heterogeneous. We investigated the association of AD with both common variants and aggregates of rare coding and non-coding variants in 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. Pooled-population analyses of all individuals identified genetic variants at apolipoprotein E (APOE) and BIN1 associated with AD (p<5×10-8). Subgroup-specific analyses identified a haplotype on chromosome 14 including PSEN1 associated with AD in Hispanics, further supported by aggregate testing of rare coding and non-coding variants in the region. Common variants in LINC00320 were observed associated with AD in Black individuals (p=1.9×10-9). Finally, we observed rare non-coding variants in the promoter of TOMM40 distinct of APOE in pooled-population analyses (p=7.2×10-8). We observed that complementary pooled-population and subgroup-specific analyses offered unique insights into the genetic architecture of AD. We determine the association of genetic variants with Alzheimer's disease (AD) using 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. We identified genetic variants at apolipoprotein E (APOE), BIN1, PSEN1, and LINC00320 associated with AD. We observed rare non-coding variants in the promoter of TOMM40 distinct of APOE.

6846 Rare Variants in SEMA3A in Individuals with Constitutional Delay of Puberty (CDP)

Abstract Disclosure: W. He: None. E.C. Schafer: None. R. Brauner: None. A. Delaney: None. L. Dunkel: None. R. Grinspon: None. J.E. Hall: None. J.N. Hirschhorn: None. S. Howard: None. A. Latronico: None. A.A. Jorge: None. K. McElreavey: None. V. Mericq: None. P.M. Merino: None. M.R. Palmert: None. R.A. Rey: None. R.C. Rezende: None. S.B. Seminara: None. N. Shaw: None. T. Delayed Puberty Genetics Consortium: None. Y. Chan: None. Background: Constitutional delay of puberty (CDP), also known as self-limited delayed puberty, refers to late onset of puberty with relatively normal progression afterward. In contrast, idiopathic hypogonadotropic hypogonadism (IHH) results in a long-lasting defect in reproductive endocrine activity. Both CDP and IHH are highly heritable and are sometimes observed in different family members in the same pedigree. Previous work by our group and others has suggested genetic overlap between the two conditions. In this study, we aimed to identify specific IHH-related genes that are also genetic causes of CDP. Methods: The Delayed Puberty Consortium assembled exome data for 233 individuals of diverse ancestries with CDP, with onset of puberty between 12 and 18 y in girls and between 13.5 and 18 y in boys. For control data, we used exome sequencing data from gnomAD v2.1.1 (n=125,748). After data harmonization and quality control, we used a modification of the “TRAPD” method to perform gene-based burden testing for 63 genes associated with IHH. We analyzed rare variants (minor allele frequency &amp;lt; 0.01) with high impact (premature stop, frameshift, start-lost, stop-lost) in all individuals across ancestries (n=233), as allele frequencies for high-impact variants are unlikely to vary widely across populations. We also analyzed rare variants with moderate impact (missense, inframe insertions/deletions) predicted to be deleterious by the Primate AI algorithm (score &amp;gt;0.6) in non-Finnish European (NFE) individuals with CDP (n=99), then meta-analyzed the results for high- and moderate-impact variants. We considered p-values &amp;lt; 7.9 x 10-4 (0.05 with Bonferroni adjustment for 63 genes) significant. Results: Of the 63 genes analyzed, SEMA3A (which encodes semaphorin-3A) exhibited significant enrichment for moderate-impact variants in the NFE CDP cohort compared to controls (variant frequency in CDP vs control: 0.064 vs 0.0076, p = 1.3 x 10-4) and in the meta-analysis of both high- and moderate-impact variants (p = 3.5 x 10-6). Novel SEMA3A variants identified exclusively in CDP individuals but not in controls were a frameshift variant, p.F546fsX2, and a missense variant, I252R. Also, three missense variants in SEMA3A were observed at a higher frequency in NFE CDP individuals compared with controls: p.R66T, p.V461A, and p.T717I. No other IHH genes showed significant enrichment of rare variants in the CDP cohort. Conclusion: Rare variants in SEMA3A contribute to both CDP and IHH. While functional studies are required to assess the effects of these specific variants on protein function, previous in vitro studies of similar SEMA3A variants demonstrated defects in secretion or signaling activity. Subsequent studies employing individual-level ancestry-matched controls and larger CDP cohorts are planned to identify additional genes that contribute to CDP. Presentation: 6/1/2024

6715 Short Adult Height in Childhood Cancer Survivors: Prevalence, Risk Factors, and Genetic Contribution

Abstract Disclosure: T. Yoshida: None. J. Baedke: None. F. Wang: None. W. Moon: None. Y. Sapkota: None. J. Miguel Martínez: None. T.E. Merchant: None. C.L. Wilson: None. K.K. Ness: None. M.M. Hudson: None. Y. Yasui: None. A. Delaney: None. Background: Survivors of childhood cancer are at elevated risk for short adult height (SAH) due to cancer and/or its treatment. In the general population, height is a highly polygenic trait; heritability is estimated to be 70-80%. However, the contribution of genetic factors to SAH among childhood cancer survivors is unknown. In addition, the contribution of chemotherapy agents to risk of SAH among survivors has not been established. We assessed: 1) prevalence of SAH; 2) contribution of genetic factors; and 3) impact of cancer therapy including chemotherapy, on SAH in a large cohort of childhood cancer survivors. Methods: Participants included 4461 childhood cancer survivors aged ≥18 years (female 47.5%, mean age 33.2 years old) with measured height information. SAH was defined as height &amp;lt;3rd percentile for age and sex based on the Centers for Disease Control growth charts. Cancer and treatment history were extracted from medical records. We calculated multi-ancestry height polygenic score (PGS) using the latest methodology developed from 5.4 million individuals of diverse ancestries with more than 1 million variants, where lower score associates with shorter height. With a random sample of 75% of survivors, we fit a multivariable logistic regression model for SAH with the PGS, chemotherapy exposures/doses, corticosteroid exposures/doses, and established risk factors for SAH (e.g., age at cancer diagnosis, radiotherapy exposure) as covariates (main model). The remaining 25% of survivors served for validation of the main model and for the calculation of the population attributable fractions (PAF) of the PGS and cancer treatments. Results: The prevalence of SAH was 8.9% among all survivors (9.3% in males; 8.5% in females) and differed widely by primary cancer diagnosis. SAH was associated with lower PGS [odds ratio (OR) 0.47, 95% confidence interval (CI) 0.40-0.55 for a one standard deviation increase], alkylating agent exposure of &amp;gt;12000 mg/m2 (OR 2.19, 95% CI 1.41-3.38, vs. non-exposure), and spinal radiotherapy (OR 3.65, 95% CI 2.23-6.00, vs. non-exposure). Radiotherapy exposure to the hypothalamic-pituitary region and younger age at cancer diagnosis was also associated with SAH in a dose-response manner. The area under the ROC curve of the main model in the validation dataset was 0.80 (95% CI 0.74-0.87), suggesting good predictive ability for SAH by the model. The PAF of SAH calculated from the multiplicative logistic regression model of SAH was 85.7% for cancer treatments and 30.2% and 60.2% for having PGS below the median and the 90th percentile, respectively. Conclusions: Cancer treatments are the primary contributor to SAH risk among survivors with a PAF of 85.7%. Exposure to high-dose alkylating agents contributes to this along with radiotherapy. Inherited genetic factors also affect SAH among survivors but to a much lesser degree than cancer treatments. Presentation: 6/3/2024

12330 Rare Variants in SEMA3A in Individuals with Constitutional Delay of Puberty (CDP)

Abstract Disclosure: W. He: None. E.C. Schafer: None. R. Brauner: None. A. Delaney: None. L. Dunkel: None. R. Grinspon: None. J.E. Hall: None. J.N. Hirschhorn: None. S. Howard: None. A. Latronico: None. A.A. Jorge: None. K. McElreavey: None. V. Mericq: None. P.M. Merino: None. M.R. Palmert: None. R.A. Rey: None. R.C. Rezende: None. S.B. Seminara: None. N. Shaw: None. T. Delayed Puberty Genetics Consortium: None. Y. Chan: None. Background: Constitutional delay of puberty (CDP), also known as self-limited delayed puberty, refers to late onset of puberty with relatively normal progression afterward. In contrast, idiopathic hypogonadotropic hypogonadism (IHH) results in a long-lasting defect in reproductive endocrine activity. Both CDP and IHH are highly heritable and are sometimes observed in different family members in the same pedigree. Previous work by our group and others has suggested genetic overlap between the two conditions. In this study, we aimed to identify specific IHH-related genes that are also genetic causes of CDP. Methods: The Delayed Puberty Consortium assembled exome data for 233 individuals of diverse ancestries with CDP, with onset of puberty between 12 and 18 y in girls and between 13.5 and 18 y in boys. For control data, we used exome sequencing data from gnomAD v2.1.1 (n=125,748). After data harmonization and quality control, we used a modification of the “TRAPD” method to perform gene-based burden testing for 63 genes associated with IHH. We analyzed rare variants (minor allele frequency &amp;lt; 0.01) with high impact (premature stop, frameshift, start-lost, stop-lost) in all individuals across ancestries (n=233), as allele frequencies for high-impact variants are unlikely to vary widely across populations. We also analyzed rare variants with moderate impact (missense, inframe insertions/deletions) predicted to be deleterious by the Primate AI algorithm (score &amp;gt;0.6) in non-Finnish European (NFE) individuals with CDP (n=99), then meta-analyzed the results for high- and moderate-impact variants. We considered p-values &amp;lt; 7.9 x 10-4 (0.05 with Bonferroni adjustment for 63 genes) significant. Results: Of the 63 genes analyzed, SEMA3A (which encodes semaphorin-3A) exhibited significant enrichment for moderate-impact variants in the NFE CDP cohort compared to controls (variant frequency in CDP vs control: 0.064 vs 0.0076, p = 1.3 x 10-4) and in the meta-analysis of both high- and moderate-impact variants (p = 3.5 x 10-6). Novel SEMA3A variants identified exclusively in CDP individuals but not in controls were a frameshift variant, p.F546fsX2, and a missense variant, I252R. Also, three missense variants in SEMA3A were observed at a higher frequency in NFE CDP individuals compared with controls: p.R66T, p.V461A, and p.T717I. No other IHH genes showed significant enrichment of rare variants in the CDP cohort. Conclusion: Rare variants in SEMA3A contribute to both CDP and IHH. While functional studies are required to assess the effects of these specific variants on protein function, previous in vitro studies of similar SEMA3A variants demonstrated defects in secretion or signaling activity. Subsequent studies employing individual-level ancestry-matched controls and larger CDP cohorts are planned to identify additional genes that contribute to CDP. Presentation: 6/1/2024

Hemoglobin A1c Genetics and Disparities in Risk of Diabetic Retinopathy in Individuals of Genetically Inferred African American/African British and European Ancestries.

Individuals with diabetes who carry genetic variants that lower hemoglobin A1c (HbA1c) independently of glycemia may have higher real, but undetected, hyperglycemia compared with those without these variants despite achieving similar HbA1c targets, potentially placing them at greater risk for diabetes-related complications. We sought to determine whether these genetic variants, aggregated in a polygenic score, and the large-effect African ancestry-specific missense variant in G6PD (rs1050828) that lower HbA1c were associated with higher retinopathy risk. Using data from 29,828 type 2 diabetes cases of genetically inferred African American/African British and European ancestries, we calculated ancestry-specific nonglycemic HbA1c polygenic scores (ngA1cPS) composed of 122 variants associated with HbA1c at genome-wide significance, but not with glucose. We tested the association of the ngA1cPS and the G6PD variant with retinopathy, adjusting for measured HbA1c and retinopathy risk factors. Participants in the bottom quintile of the ngA1cPS showed between 20% and 50% higher retinopathy prevalence, compared with those above this quintile, despite similar levels of measured HbA1c. The adjusted meta-analytic odds ratio for the bottom quintile was 1.31 (95% CI 1.0, 1.73; P = 0.05) in African ancestry and 1.31 (95% CI 1.15, 1.50; P = 6.5 × 10-5) in European ancestry. Among individuals of African ancestry with HbA1c below 7%, retinopathy prevalence was higher in individuals below, compared with above, the 50th percentile of the ngA1cPS regardless of sex or G6PD carrier status. Genetic effects need to be considered to personalize HbA1c targets and improve outcomes of people with diabetes from diverse ancestries.