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

Recent developments in population biobanks and the genetic architecture of complex disease

Population biobanks have radically transformed our understanding of complex disease genetics. Recent technological advances and the inclusion of diverse populations have accelerated the discovery and interpretation of variant associations. For instance, population-scale whole-genome sequencing now allows deep exploration of rare and structural variant associations, while multi-omics approaches integrating genome-wide association studies with proteomics, metabolomics, and advanced statistical methods like Mendelian randomization provide nuanced insights into genetic disease mechanisms. Additionally, cross-biobank collaborations and meta-analyses have been particularly impactful, dramatically increasing the statistical power for discovery. These efforts have identified novel genetic associations across numerous complex diseases, with significant contributions from non-European populations. However, data integration complexities, privacy concerns, and methodological limitations continue to constrain research. Here we review how recent advances have contributed to genetic discovery.

Empowering human research ethics committees to review genomics applications: evaluating the utility of a custom online education resource

Complex genomic technologies are increasingly utilised in research. However, human research ethics committee (HREC) members lack confidence reviewing genomics applications. This study developed and evaluated the acceptability and utility of an online educational resource on genomics and the ethical considerations for HREC members. Resource development and evaluation was theoretically informed. Qualitative semi-structured interviews with HREC members and subject experts were transcribed and deductively analysed. Participants (n = 29) found the content to be comprehensive, appropriately pitched, and optimal in quantity. Most reported the resource was easy to access and intuitive to navigate. HREC members reported improved confidence in reviewing genomics ethics applications and intentions to re-access as needed. Most (n = 28/29) would recommend to other HREC members, and some volunteered that they would recommend to researchers. Suggested navigation improvements included a progress bar, active learning elements, and a more clearly visible menu. Content suggestions included more detail on data storage/management and considerations when engaging diverse communities. This is the first study to develop and evaluate a genomic educational resource tailored to ethics committees. Following refinement and quantitative evaluation, it is hoped that this resource will increase HREC member confidence in reviewing genomics ethics applications and the quality of researchers' submissions.

The ethnic disparity in the diagnostic yield of high-throughput next-generation sequencing in inherited retinal diseases: a systematic review and meta-analysis

OBJECTIVE

Next-generation sequencing (NGS) is the state-of-the-art molecular diagnostics for genetic heterogenous inherited-retinal diseases (IRDs). However, the impact of ethnic discrepancy in NGS diagnostic yields for patients with IRD is unclear. Therefore, we performed a systemic review (SR) and meta-analysis (MA) to delineate this issue.

METHODS

MEDLINE and PubMed databases were searched on 30 January 2024. Original studies published between 2013 and 2024 that reported the IRD diagnostic yield of panel-based sequencing was eligible for inclusion. The diagnostic yield is defined as the proportion of patients with a molecular diagnosis after high-throughput panel screening. Studies were stratified by IRD enrollment phenotype and patient ancestry.

RESULTS

A total of 42 studies comprising 23,324 patients evaluated for diagnosis yield were included in the meta-analysis. The pooled diagnostic yield was 0.570 [0.530,0.610] across studies with IRD-related enrollment and 0.617 [0.568; 0.664] for those with IRD enrollment. The stratification of studies for ancestry produced a diagnostic yield of 0.629 [0.568; 0.688] in Europeans, and the diagnostic yield dropped to 0.549 [0.456; 0.641] for East Asians. There is a lack of available data for Latin American evidence meta-synthesis.

CONCLUSIONS

This review supports the existence of ethnic disparity in panel-based sequencing for IRDs. Specifically, a relatively lower diagnostic yield and a higher inconclusive diagnosis rate are present in East Asian populations compared to the European population. Consequently, our findings should prompt future reclassification of variants of unknown significance (VUS) in non-whites to improve the ethnic inequities of molecular diagnostic yields for IRDs.

Experience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories

Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings. This perspective piece is based on a decade of experience in a clinical genomics laboratory and provides insight into the relevance of conventional and ancestry-based population descriptors for clinical genetic testing, reporting, and clinical research on aggregated data. As clinicians, laboratory geneticists, genetic counselors, and researchers, we describe real-world experiences collecting conventional population descriptors in the course of clinical genetic testing and expose challenges in ensuring clarity and consistency in the use of population descriptors. Current practices in clinical genomics laboratories that are influenced by population descriptors are identified and discussed through case examples. In relation to this, we describe specific types of clinical research projects in which population descriptors were used and helped derive useful insights related to practicing and improving genomic medicine.

Strategies to Assess Risk for Hereditary Cancer in Primary Care Clinics: A Cluster Randomized Clinical Trial

Importance

Best practices for improving access to assessment of hereditary cancer risk in primary care are lacking.

Objective

To compare 2 population-based engagement strategies for identifying primary care patients with a family or personal history of cancer and offering eligible individuals genetic testing for cancer susceptibility.

Design, Setting, and Participants

The EDGE (Early Detection of Genetic Risk) clinical trial cluster-randomized 12 clinics from 2 health care systems in Montana, Wyoming, and Washington state to 1 of 2 engagement approaches for assessment of hereditary cancer risk in primary care. The study population included 95 623 English-speaking patients at least 25 years old with a primary care visit during the recruitment window between April 1, 2021, and March 31, 2022.

Intervention

The intervention comprised 2 risk assessment engagement approaches: (1) point of care (POC), conducted by staff immediately preceding clinical appointments, and (2) direct patient engagement (DPE), where letter and email outreach facilitated at-home completion. Patients who completed risk assessment and met prespecified criteria were offered genetic testing via a home-delivered saliva testing kit at no cost.

Main Outcomes and Measures

Primary outcomes were the proportion of patients with a visit who (1) completed the risk assessment and (2) completed genetic testing. Logistic regression models were used to compare the POC and DPE approaches, allowing for overdispersion and including clinic as a design factor. An intention-to-treat analysis was used to evaluate primary outcomes.

Results

Over a 12-month window, 95 623 patients had a primary care visit across the 12 clinics. Those who completed the risk assessment (n = 13 705) were predominately female (64.7%) and aged between 65 and 84 years (39.6%). The POC approach resulted in a higher proportion of patients completing risk assessment than the DPE approach (19.1% vs 8.7%; adjusted odds ratio [AOR], 2.68; 95% CI, 1.72-4.17; P < .001) but a similar proportion completing testing (1.5% vs 1.6%; AOR, 0.96; 95% CI, 0.64-1.46; P = .86). Among those eligible for testing, POC test completion was approximately half of that for the DPE approach (24.7% vs 44.7%; AOR, 0.49; 95% CI, 0.37-0.64; P < .001). The proportion of tested patients identified with an actionable pathogenic variant was significantly lower for the POC approach than the DPE approach (3.8% vs 6.6%; AOR, 0.61; 95% CI, 0.44-0.85; P = .003).

Conclusions and Relevance

In this cluster randomized clinical trial of risk assessment delivery, POC engagement resulted in a higher rate of assessment of hereditary cancer risk than the DPE approach but a similar rate of genetic testing completion. Using a combination of engagement strategies may be the optimal approach for greater reach and impact.

Trial Registration

ClinicalTrials.gov Identifier: NCT04746794.

Functional characterisation of missense ceruloplasmin variants and real-world prevalence assessment of Aceruloplasminemia using population data

BACKGROUND

Aceruloplasminemia (ACP) is a rare recessive disease caused by loss of ceruloplasmin activity due to pathogenic variants in the ceruloplasmin (CP) gene. ACP causes iron accumulation in various organs, leading to neurodegeneration, anaemia, and diabetes. Estimating ACP prevalence is challenging, particularly as missense variants are not readily identified as pathogenic.

METHODS

Heterozygous missense variants likely to impact function were mapped in gnomAD and representative examples analysed for effects on CP activity. This knowledge was complemented by prediction of destabilizing effects of potentially pathogenic missense variants and integrated with loss-of-function mutations. Global ACP prevalence was predicted and compared with a more traditional method.

FINDINGS

Several as yet uncharacterised missense CP variants of pathogenic interest were identified by structure-function in-silico analysis. A representative subset was functionally validated, together with known ACP missense variants. Insights on the relative importance of copper ions coordinating centres in CP and its substrate specificity were discovered. Overall, a destabilizing effect was predicted for 130 missense CP variants. This information, integrated with known ACP missense and loss-of-function CP variants in gnomAD, allowed an estimation of ACP prevalence of 12.6/106. An alternative analysis based on minor allele frequency ≤0.01 resulted in an ACP prevalence as high as 8/106.

INTERPRETATION

These prevalence estimates for ACP are 20-25-fold higher than previously estimated and underscore the applicability of structure-function based analyses of real-world genetic variability to provide an alternative method for representing the frequency of rare disease variants.

FUNDING

REACT-EU PON 2014-2021, Kedrion S.p.A.

Biobanking with genetics shapes precision medicine and global health

Precision medicine provides patients with access to personally tailored treatments based on individual-level data. However, developing personalized therapies requires analyses with substantial statistical power to map genetic and epidemiologic associations that ultimately create models informing clinical decisions. As one solution, biobanks have emerged as large-scale, longitudinal cohort studies with long-term storage of biological specimens and health information, including electronic health records and participant survey responses. By providing access to individual-level data for genotype-phenotype mapping efforts, pharmacogenomic studies, polygenic risk score assessments and rare variant analyses, biobanks support ongoing and future precision medicine research. Notably, due in part to the geographical enrichment of biobanks in Western Europe and North America, European ancestries have become disproportionately over-represented in precision medicine research. Herein, we provide a genetics-focused review of biobanks from around the world that are in pursuit of supporting precision medicine. We discuss the limitations of their designs, ongoing efforts to diversify genomics research and strategies to maximize the benefits of research leveraging biobanks for all.

Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves prediction across ancestry groups

We conducted a multiancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry, 58,236 African ancestry, 23,546 Hispanic/Latino and 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (P ≤ 5 × 10-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n = 95,768). Meta-analyzing discovery and replication (n = 392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our genome-wide polygenic risk scores ranged from 11.6% to 16.6% for European ancestry, 5.5% to 9.5% for African ancestry, 13.5% to 18.2% for Hispanic/Latino and 8.6% to 15.3% for Asian ancestry and decreased with increasing age. Midlife genetically adjusted PSA levels were more strongly associated with overall and aggressive prostate cancer than unadjusted PSA levels. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, offering potential to personalize prostate cancer screening.

Breaking barriers: fostering equitable access to pediatric genomics through innovative care models and technologies

The integration of genomic medicine into pediatric clinical practice is a critical need that remains largely unmet, especially in socioeconomically challenged and rural areas where healthcare disparities are most pronounced. This review seeks to summarize the barriers responsible for delayed diagnosis and treatment, and examines diverse care models, technological innovations, and strategies for dissemination and implementation aimed at addressing the evolving genomic needs of pediatric populations. Through a comprehensive review of the literature, we explore proposed methodologies to bridge this gap in pediatric healthcare, with a specific emphasis on understanding and speeding implementation approaches and technologies to mitigate disparities in underserved populations, including rural and marginalized communities. There are both external and internal factors to consider in demographic and social determinants when evaluating patient access. To address these barriers, potential solutions include telegenetic services, alternative care delivery models, pediatric subspecialist expansion, and non-genetic provider education. By improving access to pediatric genomic services, therapeutic interventions will also be more available to all pediatric patients. IMPACT STATEMENT: Genomic testing has clinical utility in pediatric populations but access for people from diverse demographic and social-economic groups is problematic. Understanding barriers responsible for delayed genetic diagnosis and treatment in pediatric populations will improve reach, adoption, implementation, and maintenance of genomic medicine in pediatric healthcare context. Innovative care models, adaptation of appropriate technologies, and strategies aimed at addressing pediatric genomic needs are needed.

Deleterious coding variation associated with autism is consistent across populations, as exemplified by admixed Latin American populations

The past decade has seen remarkable progress in identifying genes that, when impacted by deleterious coding variation, confer high risk for autism spectrum disorder (ASD), intellectual disability, and other developmental disorders. However, most underlying gene discovery efforts have focused on individuals of European ancestry, limiting insights into genetic risks across diverse populations. To help address this, the Genomics of Autism in Latin American Ancestries Consortium (GALA) was formed, presenting here the largest sequencing study of ASD in Latin American individuals (n>15,000). We identified 35 genome-wide significant (FDR < 0.05) ASD risk genes, with substantial overlap with findings from European cohorts, and highly constrained genes showing consistent signal across populations. The results provide support for emerging (e.g., MARK2, YWHAG, PACS1, RERE, SPEN, GSE1, GLS, TNPO3, ANKRD17) and established ASD genes, and for the utility of genetic testing approaches for deleterious variants in diverse populations, while also demonstrating the ongoing need for more inclusive genetic research and testing. We conclude that the biology of ASD is universal and not impacted to any detectable degree by ancestry.

Pharmacogenetics: Opportunities for the All of Us Research Program and Other Large Data Sets to Advance the Field

Pharmacogenetic variation is common and an established driver of response for many drugs. There has been tremendous progress in pharmacogenetics knowledge over the last 30 years and in clinical implementation of that knowledge over the last 15 years. But there have also been many examples where translation has stalled because of the lack of available data sets for discovery or validation research. The recent availability of data from very large cohorts with linked genetic, electronic health record, and other data promises new opportunities to advance pharmacogenetics research. This review presents the stages from pharmacogenetics discovery to widespread clinical adoption using prominent gene-drug pairs that have been implemented into clinical practice as examples. We discuss the opportunities that the All of Us Research Program and other large biorepositories with genomic and linked electronic health record data present in advancing and accelerating the translation of pharmacogenetics into clinical practice.

Using multiplexed functional data to reduce variant classification inequities in underrepresented populations

BACKGROUND

Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style functional data may help resolve variant classification disparities between populations, especially for Variants of Uncertain Significance (VUS).

METHODS

We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource's Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN.

RESULTS

Using two orthogonal statistical approaches, we show a higher prevalence (p ≤ 5.95e - 06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation (p ≤ 2.5e - 05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were increased in individuals of European-like genetic ancestry (p ≤ 2.5e - 05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry (p = 9.1e - 03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency (p = 7.47e - 06) and computational predictor (p = 6.92e - 05) evidence codes for individuals of non-European-like genetic ancestry.

CONCLUSIONS

Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.

Disparate Rates of Germline Variants in Cancer Predisposition Genes in African American/Black Compared With Non-Hispanic White Individuals Between 2015 and 2022

PURPOSE

African American/Black (AA/B) individuals are under-represented in genomic databases and thus less likely to receive definitive information from germline genetic testing (GGT) than non-Hispanic White (NHW) individuals. With nearly 500,000 AA/B and NHW individuals having undergone multigene panel testing (MGPT) for hereditary cancer risk at a single commercial laboratory, to our knowledge, we present the largest study to date investigating cancer GGT results in AA/B and NHW individuals.

METHODS

MGPT results from a retrospective cohort of AA/B (n = 48,684) and NHW (n = 444,831) patients were evaluated. Frequencies of pathogenic germline variants (PGVs) and variants of uncertain significance (VUS) were compared between AA/B and NHW individuals. Changes in frequency of VUS over time were determined. Pearson's chi-squared test was used to compare categorical variables among groups. All significance tests were two-tailed, and P < .05 was considered statistically significant.

RESULTS

Between 2015 and 2022, rates of VUS decreased 2.3-fold in AA/B and 1.8-fold in NHW individuals; however, frequencies of VUS and PGV remained significantly higher (46% v 32%; P < .0001) and lower (9% v 13%; P < .0001) in AA/B compared with NHW individuals. Rates of VUS in ATM, BRCA1, BRCA2, PALB2, and PMS2 were significantly higher in AA/B compared with NHW individuals, whereas rates of PGV in BRCA1, BRCA2, and PALB2 were higher in AA/B compared with NHW individuals (P < .001).

CONCLUSION

Despite reductions in VUS frequencies over time, disparities in definitive GGT results persist. Increasing inclusion of AA/B populations in both testing and research will further increase knowledge of genetic variants across these racial groups.

Genomic data in the All of Us Research Program

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1-4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme's genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.