Genomics is failing on diversity

Genomic structural variation: A complex but important driver of human evolution

Structural variants (SVs)-including duplications, deletions, and inversions of DNA-can have significant genomic and functional impacts but are technically difficult to identify and assay compared with single-nucleotide variants. With the aid of new genomic technologies, it has become clear that SVs account for significant differences across and within species. This phenomenon is particularly well-documented for humans and other primates due to the wealth of sequence data available. In great apes, SVs affect a larger number of nucleotides than single-nucleotide variants, with many identified SVs exhibiting population and species specificity. In this review, we highlight the importance of SVs in human evolution by (1) how they have shaped great ape genomes resulting in sensitized regions associated with traits and diseases, (2) their impact on gene functions and regulation, which subsequently has played a role in natural selection, and (3) the role of gene duplications in human brain evolution. We further discuss how to incorporate SVs in research, including the strengths and limitations of various genomic approaches. Finally, we propose future considerations in integrating existing data and biospecimens with the ever-expanding SV compendium propelled by biotechnology advancements.

Equitable machine learning counteracts ancestral bias in precision medicine, improving outcomes for all

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease [1-8]. Therapeutics and outcomes remain hidden because we lack insights that we could gain from analyzing ancestry-unbiased genomic data. To address this significant gap, we present PhyloFrame, the first-ever machine learning method for equitable genomic precision medicine. PhyloFrame corrects for ancestral bias by integrating big data tissue-specific functional interaction networks, global population variation data, and disease-relevant transcriptomic data. Application of PhyloFrame to breast, thyroid, and uterine cancers shows marked improvements in predictive power across all ancestries, less model overfitting, and a higher likelihood of identifying known cancer-related genes. The ability to provide accurate predictions for underrepresented groups, in particular, is substantially increased. These results demonstrate how AI can mitigate ancestral bias in training data and contribute to equitable representation in medical research.

Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study

BACKGROUND

The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants.

METHODS

In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey (aim one). Subsequently, we used a zero-inflated negative binomial regression to examine whether these factors were also related to participation in the COPING follow-up surveys (aim two).

RESULTS

For aim one, older age, female gender identity, non-binary or self-defined gender identities, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey, and current or ex-smoking were associated with a reduced odds. For aim two, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. Lower educational attainment, higher alcohol consumption at the GLAD Study sign-up, ex-smoking, and self-reported attention deficit hyperactivity disorder had negative relationships.

CONCLUSIONS

Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Factors associated with participation may vary depending on study design. Researchers should examine the barriers and mechanisms underlying participation bias in order to combat these issues and address recruitment biases in future studies.

Rethinking Benefit and Responsibility in the Context of Diversity: Perspectives from the Front Lines of Precision Medicine Research

INTRODUCTION

Federal agencies have instituted guidelines to prioritize the enrollment and retention of diverse participants in precision medicine research (PMR). Prior studies examining participation of minoritized communities have shown that potential benefits represent a key determinant. Human subject research guidance, however, conceptualizes potential benefits narrowly, emphasizing generalized advances in medical knowledge. Further, few studies have provided qualitative data that critically examine how the concept of "benefit" is interpreted or challenged in the context of research practice. This paper examines the experiences of PMR investigators and frontline research staff to understand how standard approaches to benefit are received, contested, and negotiated "on the ground."

METHODS

Findings are drawn from a qualitative project conducted across five US-based, federally funded PMR studies. Data collection included 125 in-depth interviews with a purposive sample of investigators, research staff, community advisory board members, and NIH program officers associated with these PMR studies.

RESULTS

Researchers report that the standard approach to benefit - which relies on the premise of altruism and the promise of incrementally advancing scientific knowledge - is frequently contested. Researchers experience moral distress over the unmet clinical, psychosocial, and material needs within the communities they are engaging. Many believe the broader research enterprise has a responsibility to better address these needs.

CONCLUSION

Researchers frequently take issue with and sometimes negotiate what is owed to participants and to their communities in exchange for the data they provide. These experiences of moral distress and these improvisations warrant systematic redress, not by individual researchers but by the broader research ethics infrastructure.

Bridging the diversity gap: Analytical and study design considerations for improving the accuracy of trans-ancestry genetic prediction

Genetic prediction of common complex disease risk is an essential component of precision medicine. Currently, genome-wide association studies (GWASs) are mostly composed of European-ancestry samples and resulting polygenic scores (PGSs) have been shown to poorly transfer to other ancestries partly due to heterogeneity of allelic effects between populations. Fixed-effects (FETA) and random-effects (RETA) trans-ancestry meta-analyses do not model such ancestry-related heterogeneity, while ancestry-specific (AS) scores may suffer from low power due to low sample sizes. In contrast, trans-ancestry meta-regression (TAMR) builds ancestry-aware PGS that account for more complex trans-ancestry architectures. Here, we examine the predictive performance of these four PGSs under multiple genetic architectures and ancestry configurations. We show that the predictive performance of FETA and RETA is strongly affected by cross-ancestry genetic heterogeneity, while AS PGS performance decreases in under-represented target populations. TAMR PGS is also impacted by heterogeneity but maintains good prediction performance in most situations, especially in ancestry-diverse scenarios. In simulations of human complex traits, TAMR scores currently explain 25% more phenotypic variance than AS in triglyceride levels and 33% more phenotypic variance than FETA in type 2 diabetes in most non-European populations. Importantly, a high proportion of non-European-ancestry individuals is needed to reach prediction levels that are comparable in those populations to the one observed in European-ancestry studies. Our results highlight the need to rebalance the ancestral composition of GWAS to enable accurate prediction in non-European-ancestry groups, and demonstrate the relevance of meta-regression approaches for compensating some of the current population biases in GWAS.

Admixture mapping implicates 13q33.3 as ancestry-of-origin locus for Alzheimer disease in Hispanic and Latino populations

Alzheimer disease (AD) is the most common form of senile dementia, with high incidence late in life in many populations including Caribbean Hispanic (CH) populations. Such admixed populations, descended from more than one ancestral population, can present challenges for genetic studies, including limited sample sizes and unique analytical constraints. Therefore, CH populations and other admixed populations have not been well represented in studies of AD, and much of the genetic variation contributing to AD risk in these populations remains unknown. Here, we conduct genome-wide analysis of AD in multiplex CH families from the Alzheimer Disease Sequencing Project (ADSP). We developed, validated, and applied an implementation of a logistic mixed model for admixture mapping with binary traits that leverages genetic ancestry to identify ancestry-of-origin loci contributing to AD. We identified three loci on chromosome 13q33.3 associated with reduced risk of AD, where associations were driven by Native American (NAM) ancestry. This AD admixture mapping signal spans the FAM155A, ABHD13, TNFSF13B, LIG4, and MYO16 genes and was supported by evidence for association in an independent sample from the Alzheimer's Genetics in Argentina-Alzheimer Argentina consortium (AGA-ALZAR) study with considerable NAM ancestry. We also provide evidence of NAM haplotypes and key variants within 13q33.3 that segregate with AD in the ADSP whole-genome sequencing data. Interestingly, the widely used genome-wide association study approach failed to identify associations in this region. Our findings underscore the potential of leveraging genetic ancestry diversity in recently admixed populations to improve genetic mapping, in this case for AD-relevant loci.

Human genetics: Rich genomic history of two isolated Indigenous peoples of South America

Genome-wide data from two Indigenous South American groups reveal their dynamic population history. The Mapuche from Southern Chile and the Ashaninka from Amazonian Peru remained largely isolated over time. Yet, both groups interacted with other South American peoples sporadically.

Optimal strategies for learning multi-ancestry polygenic scores vary across traits

Polygenic scores (PGSs) are individual-level measures that aggregate the genome-wide genetic predisposition to a given trait. As PGS have predominantly been developed using European-ancestry samples, trait prediction using such European ancestry-derived PGS is less accurate in non-European ancestry individuals. Although there has been recent progress in combining multiple PGS trained on distinct populations, the problem of how to maximize performance given a multiple-ancestry cohort is largely unexplored. Here, we investigate the effect of sample size and ancestry composition on PGS performance for fifteen traits in UK Biobank. For some traits, PGS estimated using a relatively small African-ancestry training set outperformed, on an African-ancestry test set, PGS estimated using a much larger European-ancestry only training set. We observe similar, but not identical, results when considering other minority-ancestry groups within UK Biobank. Our results emphasise the importance of targeted data collection from underrepresented groups in order to address existing disparities in PGS performance.

Polygenic Risk Score Associates with Atherosclerotic Plaque Characteristics at Autopsy

Background

Polygenic risk scores (PRS) for coronary artery disease (CAD) potentially improve cardiovascular risk prediction. However, their relationship with histopathologic features of CAD has never been examined systematically.

Methods

From 4,327 subjects referred to CVPath by the State of Maryland Office Chief Medical Examiner (OCME) for sudden death between 1994 and 2015, 2,455 cases were randomly selected for genotyping. We generated PRS from 291 known CAD risk loci. Detailed histopathologic examination of the coronary arteries was performed in all subjects. The primary study outcome measurements were histopathologic plaque features determining severity of atherosclerosis, including %stenosis, calcification, thin-cap fibroatheromas (TCFA), and thrombotic CAD.

Results

After exclusion of cases with insufficient DNA sample quality or with missing data, 954 cases (mean age 48.8±14.7; 75.7% men) remained in the final study cohort. Subjects in the highest PRS quintile exhibited more severe atherosclerosis compared to subjects in the lowest quintile, with greater %stenosis (80.3%±27.0% vs. 50.4%±38.7%; adjusted p<0.001) and a higher frequency of calcification (69.6% vs. 35.8%; adjusted p=0.004) and TCFAs (26.7% vs. 9.5%; adjusted p=0.007). Even after adjustment for traditional CAD risk factors subjects within the highest PRS quintile had higher odds of severe atherosclerosis (i.e., ≥75% stenosis; adjusted OR 3.77; 95%CI 2.10-6.78; p<0.001) and plaque rupture (adjusted OR 4.05; 95%CI 2.26-7.24; p<0.001). Moreover, subjects within the highest quintile had higher odds of CAD-associated cause of death, especially among those aged 50 years and younger (adjusted OR 4.08; 95%CI 2.01-8.30; p<0.001). No associations were observed with plaque erosion.

Conclusions

This is the first autopsy study investigating associations between PRS and atherosclerosis severity at the histopathologic level in subjects with sudden death. Our pathological analysis suggests PRS correlates with plaque burden and features of advanced atherosclerosis and may be useful as a method for CAD risk stratification, especially in younger subjects.

Highlights

In this autopsy study including 954 subjects within the CVPath Sudden Death Registry, high PRS correlated with plaque burden and atherosclerosis severity.The PRS showed differential associations with plaque rupture and plaque erosion, suggesting different etiologies to these two causes of thrombotic CAD.PRS may be useful for risk stratification, particularly in the young. Further examination of individual risk loci and their association with plaque morphology may help understand molecular mechanisms of atherosclerosis, potentially revealing new therapy targets of CAD.

Graphic Abstract

A polygenic risk score, generated from 291 known CAD risk loci, was assessed in 954 subjects within the CVPath Sudden Death Registry. Histopathologic examination of the coronary arteries was performed in all subjects. Subjects in the highest PRS quintile exhibited more severe atherosclerosis as compared to subjects in the lowest quintile, with a greater plaque burden, more calcification, and a higher frequency of plaque rupture.

A person-centered data analytic approach to dopaminergic polygenic moderation of child maltreatment exposure

The present study illustrates the utility of latent class analysis, a person-centered data analytic approach, as an innovative method for identifying naturally occurring patterns of polygenic risk, specifically within the dopaminergic system. Moreover, this study tests whether latent classes of polygenic variation moderate the effect of child maltreatment exposure on internalizing symptoms among African ancestry youth. African ancestry youth were selected for this study because youth of color are overrepresented in the child welfare system and because African ancestry individuals are significantly underrepresented in genomics research. Results identified three latent classes of dopaminergic gene variation. Class 1 was marked predominately by homozygous minor alleles, Class 2 was characterized by homozygous major and heterozygous presentations, and Class 3 was marked by heterozygous alleles on the DAT-1 single-nucleotide polymorphisms (SNPs) and a combination of homozygous major and minor alleles on the other SNPs. Results indicated that a greater number of maltreatment subtypes experienced were associated with higher internalizing symptoms only for children with the latent polygenic Class 2 pattern. This latent class was distinctly characterized by more homozygous major or heterozygous allelic presentations along all three DAT-1 SNPs. This significant latent polygenic class by environment interaction was replicated in an independent replication sample. Together, findings suggest that African ancestry children with a pattern of dopaminergic variation characterized by this specific combination of polygenic variation are more vulnerable to developing internalizing symptoms following maltreatment exposure, relative to their peers with other dopamine-related polygenic patterns.

Genome-wide Association Study for AKI

Key Points

Two genetic variants in the DISP1-TLR5 gene locus were associated with risk of AKI. DISP1 and TLR5 were differentially regulated in kidney biopsy tissue from patients with AKI compared with no AKI.

Background

Although common genetic risks for CKD are well established, genetic factors influencing risk for AKI in hospitalized patients are poorly understood.

Methods

We conducted a genome-wide association study in 1369 participants in the Assessment, Serial Evaluation, and Subsequent Sequelae of AKI Study; a multiethnic population of hospitalized participants with and without AKI matched on demographics, comorbidities, and kidney function before hospitalization. We then completed functional annotation of top-performing variants for AKI using single-cell RNA sequencing data from kidney biopsies in 12 patients with AKI and 18 healthy living donors from the Kidney Precision Medicine Project.

Results

No genome-wide significant associations with AKI risk were found in Assessment, Serial Evaluation, and Subsequent Sequelae of AKI (P < 5×10 −8 ). The top two variants with the strongest association with AKI mapped to the dispatched resistance-nodulation-division (RND) transporter family member 1 (DISP1) gene and toll-like receptor 5 (TLR5) gene locus, rs17538288 (odds ratio, 1.55; 95% confidence interval, 1.32 to 182; P = 9.47×10 −8 ) and rs7546189 (odds ratio, 1.53; 95% confidence interval, 1.30 to 1.81; P = 4.60×10 −7 ). In comparison with kidney tissue from healthy living donors, kidney biopsies in patients with AKI showed differential DISP1 expression in proximal tubular epithelial cells (adjusted P = 3.9× 10−2) and thick ascending limb of the loop of Henle (adjusted P = 8.7× 10−3) and differential TLR5 gene expression in thick ascending limb of the loop of Henle (adjusted P = 4.9× 10−30).

Conclusions

AKI is a heterogeneous clinical syndrome with various underlying risk factors, etiologies, and pathophysiology that may limit the identification of genetic variants. Although no variants reached genome-wide significance, we report two variants in the intergenic region between DISP1 and TLR5 , suggesting this region as a novel risk for AKI susceptibility.

Role of genomic medicine and implementing equitable access for critically ill infants in neonatal intensive care units

Genetic disorders are a leading cause of morbidity and mortality in infants admitted to neonatal intensive care units. This population has immense potential to benefit from genomic medicine, as early precision diagnosis is critical to early personalized management. However, the implementation of genomic medicine in neonatology thus far has arguably worsened health inequities, and strategies are urgently needed to achieve equitable access to genomics in neonatal care. In this perspective, we demonstrate the utility of genomic sequencing in critically ill infants and highlight three key recommendations to advance equitable access: recruitment of underrepresented populations, education of non-genetics providers to empower practice of genomic medicine, and development of innovative infrastructure to implement genomic medicine across diverse settings.

Alterations in the Epigenetic Machinery Associated with Prostate Cancer Health Disparities

Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry as a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Investigating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found that African-derived tumors present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63), including several putative therapeutic targets (CHD7, DPF3, POLR1B, SETD1B, UBTF, and VPS72). Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified the top genes in African- and European-derived tumors representing a multifunctional "generic machinery", the alteration of which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis, but African-derived tumors appear to achieve this state with greater diversity among such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African-tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.

Associations between polygenic risk score and covid-19 susceptibility and severity across ethnic groups: UK Biobank analysis

BACKGROUND

COVID-19 manifests with huge heterogeneity in susceptibility and severity outcomes. UK Black Asian and Minority Ethnic (BAME) groups have demonstrated disproportionate burdens. Some variability remains unexplained, suggesting potential genetic contribution. Polygenic Risk Scores (PRS) can determine genetic predisposition to disease based on Single Nucleotide Polymorphisms (SNPs) within the genome. COVID-19 PRS analyses within non-European samples are extremely limited. We applied a multi-ethnic PRS to a UK-based cohort to understand genetic contribution to COVID-19 variability.

METHODS

We constructed two PRS for susceptibility and severity outcomes based on leading risk-variants from the COVID-19 Host Genetics Initiative. Scores were applied to 447,382 participants from the UK-Biobank. Associations with COVID-19 outcomes were assessed using binary logistic regression and discriminative power was validated using incremental area under receiver operating curve (ΔAUC). Variance explained was compared between ethnic groups via incremental pseudo-R2 (ΔR2).

RESULTS

Compared to those at low genetic risk, those at high risk had a significantly greater risk of severe COVID-19 for White (odds ratio [OR] 1.57, 95% confidence interval [CI] 1.42-1.74), Asian (OR 2.88, 95% CI 1.63-5.09) and Black (OR 1.98, 95% CI 1.11-3.53) ethnic groups. Severity PRS performed best within Asian (ΔAUC 0.9%, ΔR2 0.98%) and Black (ΔAUC 0.6%, ΔR2 0.61%) cohorts. For susceptibility, higher genetic risk was significantly associated with COVID-19 infection risk for the White cohort (OR 1.31, 95% CI 1.26-1.36), but not for Black or Asian groups.

CONCLUSIONS

Significant associations between PRS and COVID-19 outcomes were elicited, establishing a genetic basis for variability in COVID-19. PRS showed utility in identifying high-risk individuals. The multi-ethnic approach allowed applicability of PRS to diverse populations, with the severity model performing well within Black and Asian cohorts. Further studies with larger sample sizes of non-White samples are required to increase statistical power and better assess impacts within BAME populations.

The DCM Project Portal: A direct-to-participant platform of The DCM Research Project

Study Objective

To develop a digital platform to conduct family-based, dilated cardiomyopathy (DCM) genetic research.

Design

Innovative approaches are needed to achieve large family enrollment targets. The DCM Project Portal, a direct-to-participant electronic recruitment, consent, and communication tool, was designed using prior experience with traditional enrollment methods, characteristics and feedback of current participants, and internet access of the US population.

Participants

DCM patients (probands) and their family members.

Results

The portal was designed as a self-guided, three module (registration, eligibility, and consent) process with internally created supporting informational and messaging resources integrated throughout. The experience can be tailored to user type and the format adapted with programmatic growth. Characteristics of participants of the recently completed DCM Precision Medicine Study were assessed as an exemplary user population. A majority of the diverse (34% non-Hispanic Black (NHE-B), 9.1% Hispanic; 53.6% female) proband (n=1223) and family members (n=1781) participants aged ≥18 years reported not at all or rarely having problems learning about their health from written information (81%) and a high confidence in completing medical forms (77.2% very much or often confident). A majority of participants across age and race-ethnicity groups reported internet access, with highest rates of no reported access in those ≥77 years, NHE-B, and Hispanic, which reflects patterns similar to rates reported by the US Census Bureau as of 2021.

Conclusions

Digital enrollment tools offer opportunity to improve access and efficiency. The portal is an example of a digital approach to family-based genetic research.

Leveraging trans-ethnic genetic risk scores to improve association power for complex traits in underrepresented populations

Trans-ethnic genome-wide association studies have revealed that many loci identified in European populations can be reproducible in non-European populations, indicating widespread trans-ethnic genetic similarity. However, how to leverage such shared information more efficiently in association analysis is less investigated for traits in underrepresented populations. We here propose a statistical framework, trans-ethnic genetic risk score informed gene-based association mixed model (GAMM), by hierarchically modeling single-nucleotide polymorphism effects in the target population as a function of effects of the same trait in well-studied populations. GAMM powerfully integrates genetic similarity across distinct ancestral groups to enhance power in understudied populations, as confirmed by extensive simulations. We illustrate the usefulness of GAMM via the application to 13 blood cell traits (i.e. basophil count, eosinophil count, hematocrit, hemoglobin concentration, lymphocyte count, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, mean corpuscular volume, monocyte count, neutrophil count, platelet count, red blood cell count and total white blood cell count) in Africans of the UK Biobank (n = 3204) while utilizing genetic overlap shared in Europeans (n = 746 667) and East Asians (n = 162 255). We discovered multiple new associated genes, which had otherwise been missed by existing methods, and revealed that the trans-ethnic information indirectly contributed much to the phenotypic variance. Overall, GAMM represents a flexible and powerful statistical framework of association analysis for complex traits in underrepresented populations by integrating trans-ethnic genetic similarity across well-studied populations, and helps attenuate health inequities in current genetics research for people of minority populations.

Polygenic risk scores in pharmacogenomics: opportunities and challenges-a mini review

Pharmacogenomics (PGx) aims at tailoring drug therapy by considering patient genetic makeup. While drug dosage guidelines have been extensively based on single gene mutations (single nucleotide polymorphisms) over the last decade, polygenic risk scores (PRS) have emerged in the past years as a promising tool to account for the complex interplay and polygenic nature of patients' genetic predisposition affecting drug response. Even though PRS research has demonstrated convincing evidence in disease risk prediction, the clinical utility and its implementation in daily care has yet to be demonstrated, and pharmacogenomics is no exception; usual endpoints include drug efficacy or toxicity. Here, we review the general pipeline in PRS calculation, and we discuss some of the remaining barriers and challenges that must be undertaken to bring PRS research in PGx closer to patient care. Besides the need in following reporting guidelines and larger PGx patient cohorts, PRS integration will require close collaboration between bioinformatician, treating physicians and genetic consultants to ensure a transparent, generalizable, and trustful implementation of PRS results in real-world medical decisions.

Evaluating significance of European-associated index SNPs in the East Asian population for 31 complex phenotypes

BACKGROUND

Genome-wide association studies (GWASs) have identified many single-nucleotide polymorphisms (SNPs) associated with complex phenotypes in the European (EUR) population; however, the extent to which EUR-associated SNPs can be generalized to other populations such as East Asian (EAS) is not clear.

RESULTS

By leveraging summary statistics of 31 phenotypes in the EUR and EAS populations, we first evaluated the difference in heritability between the two populations and calculated the trans-ethnic genetic correlation. We observed the heritability estimates of some phenotypes varied substantially across populations and 53.3% of trans-ethnic genetic correlations were significantly smaller than one. Next, we examined whether EUR-associated SNPs of these phenotypes could be identified in EAS using the trans-ethnic false discovery rate method while accounting for winner's curse for SNP effect in EUR and difference of sample sizes in EAS. We found on average 54.5% of EUR-associated SNPs were also significant in EAS. Furthermore, we discovered non-significant SNPs had higher effect heterogeneity, and significant SNPs showed more consistent linkage disequilibrium and allele frequency patterns between the two populations. We also demonstrated non-significant SNPs were more likely to undergo natural selection.

CONCLUSIONS

Our study revealed the extent to which EUR-associated SNPs could be significant in the EAS population and offered deep insights into the similarity and diversity of genetic architectures underlying phenotypes in distinct ancestral groups.

Evaluating Genomic Polygenic Risk Scores for Childhood Acute Lymphoblastic Leukemia in Latinos

The utility of polygenic risk score (PRS) models has not been comprehensively evaluated for childhood acute lymphoblastic leukemia (ALL), the most common type of cancer in children. Previous PRS models for ALL were based on significant loci observed in genome-wide association studies (GWAS), even though genomic PRS models have been shown to improve prediction performance for a number of complex diseases. In the United States, Latino (LAT) children have the highest risk of ALL, but the transferability of PRS models to LAT children has not been studied. In this study we constructed and evaluated genomic PRS models based on either non-Latino white (NLW) GWAS or a multi-ancestry GWAS. We found that the best PRS models performed similarly between held-out NLW and LAT samples (PseudoR 2 = 0.086 ± 0.023 in NLW vs. 0.060 ± 0.020 in LAT), and can be improved for LAT if we performed GWAS in LAT-only (PseudoR 2 = 0.116 ± 0.026) or multi-ancestry samples (PseudoR 2 = 0.131 ± 0.025). However, the best genomic models currently do not have better prediction accuracy than a conventional model using all known ALL-associated loci in the literature (PseudoR 2 = 0.166 ± 0.025), which includes loci from GWAS populations that we could not access to train genomic PRS models. Our results suggest that larger and more inclusive GWAS may be needed for genomic PRS to be useful for ALL. Moreover, the comparable performance between populations may suggest a more oligo-genic architecture for ALL, where some large effect loci may be shared between populations. Future PRS models that move away from the infinite causal loci assumption may further improve PRS for ALL.

Similarity and diversity of genetic architecture for complex traits between East Asian and European populations

BACKGROUND

Genome-wide association studies have detected a large number of single-nucleotide polymorphisms (SNPs) associated with complex traits in diverse ancestral groups. However, the trans-ethnic similarity and diversity of genetic architecture is not well understood currently.

RESULTS

By leveraging summary statistics of 37 traits from East Asian (N_max=254,373) or European (N_max=693,529) populations, we first evaluated the trans-ethnic genetic correlation (ρ_g) and found substantial evidence of shared genetic overlap underlying these traits between the two populations, with [Formula: see text] ranging from 0.53 (se = 0.11) for adult-onset asthma to 0.98 (se = 0.17) for hemoglobin A1c. However, 88.9% of the genetic correlation estimates were significantly less than one, indicating potential heterogeneity in genetic effect across populations. We next identified common associated SNPs using the conjunction conditional false discovery rate method and observed 21.7% of trait-associated SNPs can be identified simultaneously in both populations. Among these shared associated SNPs, 20.8% showed heterogeneous influence on traits between the two ancestral populations. Moreover, we demonstrated that population-common associated SNPs often exhibited more consistent linkage disequilibrium and allele frequency pattern across ancestral groups compared to population-specific or null ones. We also revealed population-specific associated SNPs were much likely to undergo natural selection compared to population-common associated SNPs.

CONCLUSIONS

Our study provides an in-depth understanding of similarity and diversity regarding genetic architecture for complex traits across diverse populations, and can assist in trans-ethnic association analysis, genetic risk prediction, and causal variant fine mapping.

Core issues, case studies, and the need for expanded Legacy African American genomics

Introduction: Genomic studies of Legacy African Americans have a tangled and convoluted history in western science. In this review paper, core issues affecting African American genomic studies are addressed and two case studies, the New York African Burial Ground and the Gullah Geechee peoples, are presented to highlight the current status of genomic research among Africa Americans. Methods: To investigate our target population's core issues, a metadatabase derived from 22 publicly accessible databases were reviewed, evaluated, and synthesized to identify the core bioethical issues prevalent during the centuries of the African American presence in North America. The sequence of metadatabase development included 5 steps: identification of information, record screening and retention of topic relevant information, identification of eligibility via synthesis for concept identifications, and inclusion of studies used for conceptual summaries and studies used for genetic and genomic summaries. To these data we added our emic perspectives and specific insights from our case studies. Results: Overall, there is a paucity of existing research on underrepresent African American genomic diversity. In every category of genomic testing (i.e., diagnostic, clinical predictive, pharmacogenomic, direct-to-consumer, and tumor testing), African Americans are disproportionately underrepresented compared to European Americans. The first of our case studies is from the New York African Burial Ground Project where genomic studies of grave soil derived aDNA yields insights into the causes of death of 17^th and 18^th Century African Americans. In the second of our case studies, research among the Gullah Geechee people of the Carolina Lowcountry reveals a connection between genomic studies and health disparities. Discussion: African Americans have historically borne the brunt of the earliest biomedical studies used to generate and refine primitive concepts in genetics. As exploited victims these investigations, African American men, women, and children were subjected to an ethics-free western science. Now that bioethical safeguards have been added, underrepresented and marginalized people who were once the convenient targets of western science, are now excluded from its health-related benefits. Recommendations to enhance the inclusion of African Americans in global genomic databases and clinical trials should include the following: emphasis on the connection of inclusion to advances in precision medicine, emphasis on the relevance of inclusion to fundamental questions in human evolutionary biology, emphasis on the historical relevance of inclusion for Legacy African Americans, emphasis on the ability of inclusion to foster expanded scientific expertise in the target population, ethical engagement with their descendants, and increase the number of science researchers from these communities.

Decoding the genetic relationship between Alzheimer's disease and type 2 diabetes: potential risk variants and future direction for North Africa

Introduction

Alzheimer's disease (AD) and Type 2 diabetes (T2D) are both age-associated diseases. Identification of shared genes could help develop early diagnosis and preventive strategies. Although genetic background plays a crucial role in these diseases, we noticed an underrepresentation tendency of North African populations in omics studies.

Materials and methods

First, we conducted a comprehensive review of genes and pathways shared between T2D and AD through PubMed. Then, the function of the identified genes and variants was investigated using annotation tools including PolyPhen2, RegulomeDB, and miRdSNP. Pathways enrichment analyses were performed with g:Profiler and EnrichmentMap. Next, we analyzed variant distributions in 16 worldwide populations using PLINK2, R, and STRUCTURE software. Finally, we performed an inter-ethnic comparison based on the minor allele frequency of T2D-AD common variants.

Results

A total of 59 eligible papers were included in our study. We found 231 variants and 363 genes shared between T2D and AD. Variant annotation revealed six single nucleotide polymorphisms (SNP) with a high pathogenic score, three SNPs with regulatory effects on the brain, and six SNPs with potential effects on miRNA-binding sites. The miRNAs affected were implicated in T2D, insulin signaling pathways, and AD. Moreover, replicated genes were significantly enriched in pathways related to plasma protein binding, positive regulation of amyloid fibril deposition, microglia activation, and cholesterol metabolism. Multidimensional screening performed based on the 363 shared genes showed that main North African populations are clustered together and are divergent from other worldwide populations. Interestingly, our results showed that 49 SNP associated with T2D and AD were present in North African populations. Among them, 11 variants located in DNM3, CFH, PPARG, ROHA, AGER, CLU, BDNF1, CST9, and PLCG1 genes display significant differences in risk allele frequencies between North African and other populations.

Conclusion

Our study highlighted the complexity and the unique molecular architecture of North African populations regarding T2D-AD shared genes. In conclusion, we emphasize the importance of T2D-AD shared genes and ethnicity-specific investigation studies for a better understanding of the link behind these diseases and to develop accurate diagnoses using personalized genetic biomarkers.

Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture

We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.

Emerging trends in gene and bipolar disorder research: a bibliometric analysis and network visualisation

This study aims to use a bibliometric technique to evaluate the scientific output of gene and bipolar disorder research. The search query related to gene and bipolar disorder from the Scopus database identified 1848 documents from 1951 to 2020. The growth in the publications increased since early 1990, peaked in 2011, and started to decline thereafter. High occurrence in author keywords suggests that some research topics, such as "polymorphism", "linkage" and "association study" have waned over time, whereas others, such as "DNA methylation," "circadian rhythm," "" and "meta-analysis," are now the emerging trends in gene and bipolar disorder research. The USA was the country with the highest production followed by the UK, Canada, Italy and Germany. The leading institutions were Cardiff University in the UK, the National Institute of Mental Health (NIMH) in the USA, King's College London in the UK and the University of California, San Diego in the USA. The leading journals publishing gene and bipolar literature were the American Journal of Medical Genetics Neuropsychiatric Genetics, Molecular Psychiatry and Psychiatric Genetics. The top authors in the number of publications were Craddock N, Serretti A and Rietschel M. According to the co-authorship network analysis of authors, the majority of the authors in the same clusters were closely linked together and originated from the same or neighbouring country. The findings of this study may be useful in identifying emerging topics for future research and promoting research collaboration in the field of genetic studies related to bipolar disorder.

Ethical Issues Associated With Direct-to-Consumer Genetic Testing

Direct-to-consumer genetic testing (DTC-GT) is becoming an increasingly profitable private enterprise that provides genetic testing kits directly to consumers. DTC-GT companies advertise themselves as a method for patients to take control of their own health and investigate their risk of diseases and conditions as well as look into their ancestry. The scope of practice of these companies continues to widen offering more services. Consumers may therefore have a relatively poor understanding of the services provided when purchasing these products. The testing methods utilised show some limitations, the consequences of which have the possibility of leading to harm to consumers. The result of the data gathered may instigate the formation of negative stereotypes from the public and reinforce existing ones towards a population that may have already been previously subjugated to unfair treatment. The controversy surrounding how data are utilised further impacts how many may engage in its use. This review aims to provide an overview of the services these companies purport to provide as well as highlight important ethical issues of the service such as quality of information, privacy concerns, negative psychosocial impact and the effect on clinical practice.

Diagnostic yield of pediatric and prenatal exome sequencing in a diverse population

The diagnostic yield of exome sequencing (ES) has primarily been evaluated in individuals of European ancestry, with less focus on underrepresented minority (URM) and underserved (US) patients. We evaluated the diagnostic yield of ES in a cohort of predominantly US and URM pediatric and prenatal patients suspected to have a genetic disorder. Eligible pediatric patients had multiple congenital anomalies and/or neurocognitive disabilities and prenatal patients had one or more structural anomalies, disorders of fetal growth, or fetal effusions. URM and US patients were prioritized for enrollment and underwent ES at a single academic center. We identified definitive positive or probable positive results in 201/845 (23.8%) patients, with a significantly higher diagnostic rate in pediatric (26.7%) compared to prenatal patients (19.0%) (P = 0.01). For both pediatric and prenatal patients, the diagnostic yield and frequency of inconclusive findings did not differ significantly between URM and non-URM patients or between patients with US status and those without US status. Our results demonstrate a similar diagnostic yield of ES between prenatal and pediatric URM/US patients and non-URM/US patients for positive and inconclusive results. These data support the use of ES to identify clinically relevant variants in patients from diverse populations.

Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

Humans coexisted and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here, we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,169 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 962 exonic splicing mutations that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than that in Neanderthals. Adaptively introgressed variants were enriched for moderate-effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a unique tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a unique Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide unique insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.

Epilepsy panels in clinical practice: Yield, variants of uncertain significance, and treatment implications

OBJECTIVE

There has been increasing utilization of genetic testing for pediatric epilepsy in recent years. Little systematic data is available examining how practice changes have impacted testing yields, diagnostic pace, incidence of variants of uncertain significance (VUSs), or therapeutic management.

METHODS

A retrospective chart review was performed at Children's Hospital Colorado from February 2016 through February 2020. All patients under 18 years for whom an epilepsy gene panel was sent were included.

RESULTS

A total of 761 epilepsy gene panels were sent over the study period. During the study period, there was a 292% increase in the average number of panels sent per month. The time from seizure onset to panel result decreased over the study period from a median of 2.9 years to 0.7 years. Despite the increase in testing, the percentage of panels yielding a disease-causing result remained stable at 11-13%. A total of 90 disease-causing results were identified, > 75% of which provided guidance in management. Children were more likely to have a disease-causing result if they were < 3 years old at seizure onset (OR 4.4, p < 0.001), had neurodevelopmental concerns (OR 2.2, p = 0.002), or had a developmentally abnormal MRI (OR 3.8, p < 0.001). A total of 1417 VUSs were identified, equating to 15.7 VUSs per disease-causing result. Non-Hispanic white patients had a lower average number of VUSs than patients of all other races/ethnicities (1.7 vs 2.1, p < 0.001).

SIGNIFICANCE

Expansion in the volume of genetic testing corresponded to a decrease in the time from seizure onset to testing result. Diagnostic yield remained stable, resulting in an increase in the absolute number of disease-causing results annually-most of which have implications for management. However, there has also been an increase in total VUSs, which likely resulted in additional clinical time spent on VUS resolution.

Characterization of pharmacogenomic variants in a Brazilian admixed cohort of elderly individuals based on whole-genome sequencing data

Introduction: Research in the field of pharmacogenomics (PGx) aims to identify genetic variants that modulate response to drugs, through alterations in their pharmacokinetics (PK) or pharmacodynamics (PD). The distribution of PGx variants differs considerably among populations, and whole-genome sequencing (WGS) plays a major role as a comprehensive approach to detect both common and rare variants. This study evaluated the frequency of PGx markers in the context of the Brazilian population, using data from a population-based admixed cohort from Sao Paulo, Brazil, which includes variants from WGS of 1,171 unrelated, elderly individuals. Methods: The Stargazer tool was used to call star alleles and structural variants (SVs) from 38 pharmacogenes. Clinically relevant variants were investigated, and the predicted drug response phenotype was analyzed in combination with the medication record to assess individuals potentially at high-risk of gene-drug interaction. Results: In total, 352 unique star alleles or haplotypes were observed, of which 255 and 199 had a frequency < 0.05 and < 0.01, respectively. For star alleles with frequency > 5% (n = 97), decreased, loss-of-function and unknown function accounted for 13.4%, 8.2% and 27.8% of alleles or haplotypes, respectively. Structural variants (SVs) were identified in 35 genes for at least one individual, and occurred with frequencies >5% for CYP2D6, CYP2A6, GSTM1, and UGT2B17. Overall 98.0% of the individuals carried at least one high risk genotype-predicted phenotype in pharmacogenes with PharmGKB level of evidence 1A for drug interaction. The Electronic Health Record (EHR) Priority Result Notation and the cohort medication registry were combined to assess high-risk gene-drug interactions. In general, 42.0% of the cohort used at least one PharmGKB evidence level 1A drug, and 18.9% of individuals who used PharmGKB evidence level 1A drugs had a genotype-predicted phenotype of high-risk gene-drug interaction. Conclusion: This study described the applicability of next-generation sequencing (NGS) techniques for translating PGx variants into clinically relevant phenotypes on a large scale in the Brazilian population and explores the feasibility of systematic adoption of PGx testing in Brazil.

Partnering with First Nations in Northern British Columbia Canada to Reduce Inequity in Access to Genomic Research

Indigenous-led, culturally safe health research and infrastructure are essential to address existing inequities and disparities for Indigenous Peoples globally. Biobanking, genomic research, and self-governance could reduce the existing divide and increase Indigenous participation in health research. While genomic research advances medicine, barriers persist for Indigenous patients to benefit. In northern BC, Canada, the Northern Biobank Initiative (NBI), with guidance from a Northern First Nations Biobank Advisory Committee (NFNBAC), has engaged in consultations with First Nations on biobanking and genomic research. Key informant interviews and focus groups conducted with First Nations leaders, Elders, Knowledge Keepers, and community members established culturally safe ways of biobanking and exploring genomic research. Strong support for a Northern British Columbia First Nations Biobank (NBCFNB) that will promote choice, inclusion, and access to health research opportunities emerged. The acceptance and enthusiasm for the development of this NBCFNB and its governance table highlight the shift towards Indigenous ownership and support of health research and its benefits. With engagement and partnership, community awareness, multigenerational involvement, and support from diverse and experienced healthcare leaders, the NBCFNB will establish this culturally safe, locally driven, and critically important research priority that may serve as an example for diverse Indigenous groups when designing their unique biobanking or genomic research opportunities.

Spectrum of genetic disorders and gene variants in the United Arab Emirates national population: insights from the CTGA database

Like many other Arab countries, the United Arab Emirates (UAE) has a relatively high prevalence of genetic disorders. Here we present the first review and analysis of all genetic disorders and gene variants reported in Emirati nationals and hosted on the Catalogue for Transmission Genetics in Arabs (CTGA), an open-access database hosting bibliographic data on human gene variants associated with inherited or heritable phenotypes in Arabs. To date, CTGA hosts 665 distinct genetic conditions that have been described in Emiratis, 621 of which follow a clear Mendelian inheritance. Strikingly, over half of these are extremely rare according to global prevalence rates, predominantly with an autosomal recessive mode of inheritance. This is likely due to the relatively high consanguinity rates within the Emirati population. The 665 conditions include disorders that are unique to the Emirati population, as well as clearly monogenic disorders that have not yet been mapped to a causal genetic locus. We also describe 1,365 gene variants reported in Emiratis, most of which are substitutions and over half are classified as likely pathogenic or pathogenic. Of these, 235 had not been reported on the international databases dbSNP and Clinvar, as of December 2022. Further analysis of this Emirati variant dataset allows a comparison of clinical significance as reported by Clinvar and CTGA, where the latter is derived from the study cited. A total of 307 pathogenic/likely pathogenic variants from CTGA's Emirati dataset, were classified as benign, variants of uncertain significance, or were missing a clinical significance or had not been reported by Clinvar. In conclusion, we present here the spectrum of genetic disorders and gene variants reported in Emiratis. This review emphasizes the importance of ethnic databases such as CTGA in addressing the underrepresentation of Arab variant data in international databases and documenting population-specific discrepancies in variant interpretation, reiterating the value of such repositories for clinicians and researchers, especially when dealing with rare disorders.

Demographic Characteristics Associated With Perceptions of Personal Utility in Genetic and Genomic Testing: A Systematic Review

Importance

The expansion of genetic and genomic testing in health care has led to recognition that these tests provide personal as well as clinical utility to patients and families. However, available systematic reviews on this topic have not reported the demographic backgrounds of participants in studies of personal utility, leaving generalizability unclear.

Objective

To determine the demographic characteristics of participants in studies examining the personal utility of genetic and genomic testing in health care.

Evidence Review

For this systematic review, we utilized and updated the results of a highly cited 2017 systematic review on the personal utility of genetics and genomics, which identified relevant articles published between January 1, 2003, and August 4, 2016. We also used the original methods to update this bibliography with literature published subsequently up to January 1, 2022. Studies were screened for eligibility by 2 independent reviewers. Eligible studies reported empirical data on the perspectives of patients, family members, and/or the general public in the US on the personal utility of any type of health-related genetic or genomic test. We utilized a standardized codebook to extract study and participant characteristics. We summarized demographic characteristics descriptively across all studies and by subgroup based on study and participant characteristics.

Findings

We included 52 studies with 13 251 eligible participants. Sex or gender was the most frequently reported demographic characteristic (48 studies [92.3%]), followed by race and ethnicity (40 studies [76.9%]), education (38 studies [73.1%]), and income (26 studies [50.0%]). Across studies, participants disproportionately were women or female (mean [SD], 70.8% [20.5%]), were White (mean [SD], 76.1% [22.0%]), had a college degree or higher (mean [SD], 64.5% [19.9%]), and reported income above the US median (mean [SD], 67.4% [19.2%]). Examination of subgroups of results by study and participant characteristics evidenced only small shifts in demographic characteristics.

Conclusions and Relevance

This systematic review examined the demographic characteristics of individual participants in studies of the personal utility of health-related genetic and genomic testing in the US. The results suggest that participants in these studies were disproportionately White, college-educated women with above-average income. Understanding the perspectives of more diverse individuals regarding the personal utility of genetic and genomic testing may inform barriers to research recruitment and uptake of clinical testing in currently underrepresented populations.

Community Engagement in Precision Medicine Research: Organizational Practices and Their Impacts for Equity

BACKGROUND

In the wake of mandates for biomedical research to increase participation by members of historically underrepresented populations, community engagement (CE) has emerged as a key intervention to help achieve this goal.

METHODS

Using interviews, observations, and document analysis, we examine how stakeholders in precision medicine research understand and seek to put into practice ideas about who to engage, how engagement should be conducted, and what engagement is for.

RESULTS

We find that ad hoc, opportunistic, and instrumental approaches to CE exacted significant consequences for the time and resources devoted to engagement and the ultimate impacts it has on research. Critical differences emerged when engagement and research decisionmaking were integrated with each other versus occurring in parallel, separate parts of the study organization, and whether community members had the ability to determine which issues would be brought to them for consideration or to revise or even veto proposals made upstream based on criteria that mattered to them. CE was understood to have a range of purposes, from instrumentally facilitating recruitment and data collection, to advancing community priorities and concerns, to furthering long-term investments in relationships with and changes in communities. These choices about who to engage, what engagement activities to support, how to solicit and integrate community input into the workflow of the study, and what CE was for were often conditioned upon preexisting perceptions and upstream decisions about study goals, competing priorities, and resource availability.

CONCLUSIONS

Upstream choices about CE and constraints of time and resources cascade into tradeoffs that often culminated in "pantomime community engagement." This approach can create downstream costs when engagement is experienced as improvised and sporadic. Transformations are needed for CE to be seen as a necessary scientific investment and part of the scientific process.

Future-oriented Emotions and Decisions to Receive Genomic Testing Results Among U.S. Adults of African Ancestry

BACKGROUND

Future-oriented emotions are associated with consequential health decision-making, including genomic testing decisions. However, little is known about the relative role of various future-oriented emotions in such decisions. Moreover, most research on predictors of decision making regarding genomic testing is conducted with white participants.

PURPOSE

This study examined the role of future-oriented emotions in decisions to receive genomic testing results in U.S. individuals of African descent.

METHODS

We analyzed cross-sectional survey data from a genomic sequencing cohort (N = 408). All participants identified as African, African-American, or Afro-Caribbean (Mage = 56.3, 74.7% female). Participants completed measures assessing anticipatory affect (worry about genetic testing results), anticipated distress (feeling devastated if genetic testing showed an increased risk for fatal disease), and anticipated regret (regretting a decision not to learn results). Outcomes were intentions for learning actionable, nonactionable, and carrier results.

RESULTS

Anticipated regret was robustly positively associated with intentions to receive actionable (b = 0.28, p < .001), nonactionable (b = 0.39, p < .001), and carrier (b = 0.30, p < .001) results. Anticipated distress was negatively associated with intentions to receive nonactionable results only (b = -0.16, p < .01). Anticipatory negative affect (worry) was not associated with intentions. At higher levels of anticipated regret, anticipated distress was less strongly associated with intentions to receive nonactionable results (b = 0.14, p = .02).

CONCLUSIONS

Our results highlight the role of future-oriented emotions in genomic testing among participants who are typically underrepresented in genomic testing studies and behavioral medicine broadly. Future work should examine whether interventions targeting future-oriented emotions such as anticipated regret may have clinically meaningful effects in genetic counseling in similar cohorts.

Managing re-identification risks while providing access to the All of Us research program

OBJECTIVE

The All of Us Research Program makes individual-level data available to researchers while protecting the participants' privacy. This article describes the protections embedded in the multistep access process, with a particular focus on how the data was transformed to meet generally accepted re-identification risk levels.

METHODS

At the time of the study, the resource consisted of 329 084 participants. Systematic amendments were applied to the data to mitigate re-identification risk (eg, generalization of geographic regions, suppression of public events, and randomization of dates). We computed the re-identification risk for each participant using a state-of-the-art adversarial model specifically assuming that it is known that someone is a participant in the program. We confirmed the expected risk is no greater than 0.09, a threshold that is consistent with guidelines from various US state and federal agencies. We further investigated how risk varied as a function of participant demographics.

RESULTS

The results indicated that 95th percentile of the re-identification risk of all the participants is below current thresholds. At the same time, we observed that risk levels were higher for certain race, ethnic, and genders.

CONCLUSIONS

While the re-identification risk was sufficiently low, this does not imply that the system is devoid of risk. Rather, All of Us uses a multipronged data protection strategy that includes strong authentication practices, active monitoring of data misuse, and penalization mechanisms for users who violate terms of service.

Evolving Science on Cardiovascular Disease Among Hispanic/Latino Adults: JACC International

The landmark, multicenter HCHS/SOL (Hispanic Community Health Study/Study of Latinos) is the largest, most comprehensive, longitudinal community-based cohort study to date of diverse Hispanic/Latino persons in the United States. The HCHS/SOL aimed to address the dearth of comprehensive data on risk factors for cardiovascular disease (CVD) and other chronic diseases in this population and has expanded considerably in scope since its inception. This paper describes the aims/objectives and data collection of the HCHS/SOL and its ancillary studies to date and highlights the critical and sizable contributions made by the study to understanding the prevalence of and changes in CVD risk/protective factors and the burden of CVD and related chronic conditions among adults of diverse Hispanic/Latino backgrounds. The continued follow-up of this cohort will allow in-depth investigations on cardiovascular and pulmonary outcomes in this population, and data from the ongoing ancillary studies will facilitate generation of new hypotheses and study questions.

Low and differential polygenic score generalizability among African populations due largely to genetic diversity

African populations are vastly underrepresented in genetic studies but have the most genetic variation and face wide-ranging environmental exposures globally. Because systematic evaluations of genetic prediction had not yet been conducted in ancestries that span African diversity, we calculated polygenic risk scores (PRSs) in simulations across Africa and in empirical data from South Africa, Uganda, and the United Kingdom to better understand the generalizability of genetic studies. PRS accuracy improves with ancestry-matched discovery cohorts more than from ancestry-mismatched studies. Within ancestrally and ethnically diverse South African individuals, we find that PRS accuracy is low for all traits but varies across groups. Differences in African ancestries contribute more to variability in PRS accuracy than other large cohort differences considered between individuals in the United Kingdom versus Uganda. We computed PRS in African ancestry populations using existing European-only versus ancestrally diverse genetic studies; the increased diversity produced the largest accuracy gains for hemoglobin concentration and white blood cell count, reflecting large-effect ancestry-enriched variants in genes known to influence sickle cell anemia and the allergic response, respectively. Differences in PRS accuracy across African ancestries originating from diverse regions are as large as across out-of-Africa continental ancestries, requiring commensurate nuance.

Polygenic Risk Score in African populations: progress and challenges

Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects  single nucleotide polymorphisms (SNPs) that  contribute to the disease with low effect size  making it more precise at individual level risk prediction. PRS  analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with  low effect size but play an indispensable role to the observed phenotypic/trait variance.  PRS analysis has  applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies  show   that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that  lack of sufficient GWAS data and tools is  the limiting factor of applying PRS analysis to sub-Saharan populations.   We recommend developing Africa-specific PRS methods and tools for estimating and analyzing  African population data   for clinical  evaluation of PRSs of interest and predicting  rare diseases.

Polygenic Risk Score in African populations: progress and challenges

Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects  single nucleotide polymorphisms (SNPs) that  contribute to the disease with low effect size  making it more precise at individual level risk prediction. PRS  analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with  low effect size but play an indispensable role to the observed phenotypic/trait variance.  PRS analysis has  applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies  show   that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that  lack of sufficient GWAS data and tools is  the limiting factor of applying PRS analysis to sub-Saharan populations.   We recommend developing Africa-specific PRS methods and tools for estimating and analyzing  African population data   for clinical  evaluation of PRSs of interest and predicting  rare diseases.

Dynamics of the personalities of PCSK9 on missense variants (rs505151 and rs562556) from elderly cohort studies in Brazil

The Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) promotes the degradation of the low-density lipoprotein receptors (LDLR). Gain-of-function (GOF) variants of PCSK9 significantly affects lipid metabolism leading to coronary artery disease (CAD), owing to the raising the plasma low-density lipoprotein (LDL). Considering the public health matter, large-scale genomic studies have been conducted worldwide to provide the genetic architecture of populations for the implementation of precision medicine actions. Nevertheless, despite the advances in genomic studies, non-European populations are still underrepresented in public genomic data banks. Despite this, we found two high-frequency variants (rs505151 and rs562556) in the ABraOM databank (Brazilian genomic variants) from a cohort SABE study conducted in the largest city of Brazil, São Paulo. Here, we assessed the structural and dynamical features of these variants against WT through a molecular dynamics study. We sought fundamental dynamical interdomain relations through Perturb Response Scanning (PRS) and we found an interesting change of dynamical relation between prodomain and Cysteine-Histidine-Rich-Domain (CHRD) in the variants. The results highlight the pivotal role of prodomain in the PCSK9 dynamic and the implications for the development of new drugs depending on patient group genotype.

Immunogenetics of HLA-B: SNP, allele, and haplotype diversity in populations from different continents and ancestry backgrounds

HLA-B is among the most variable gene in the human genome. This gene encodes a key molecule for antigen presentation to CD8+ T lymphocytes and NK cell modulation. Despite the myriad of studies evaluating its coding region (with an emphasis on exons 2 and 3), few studies evaluated introns and regulatory sequences in real population samples. Thus, HLA-B variability is probably underestimated. We applied a bioinformatics pipeline tailored for HLA genes on 5347 samples from 80 different populations, which includes more than 1000 admixed Brazilians, to evaluate the HLA-B variability (SNPs, indels, MNPs, alleles, and haplotypes) in exons, introns, and regulatory regions. We observed 610 variable sites throughout HLA-B; the most frequent variants are shared worldwide. However, the haplotype distribution is geographically structured. We detected 920 full-length haplotypes (exons, introns, and untranslated regions) encoding 239 different protein sequences. HLA-B gene diversity is higher in admixed populations and Europeans while lower in African ancestry individuals. Each HLA-B allele group is associated with specific promoter sequences. This HLA-B variation resource may improve HLA imputation accuracy and disease-association studies and provide evolutionary insights regarding HLA-B genetic diversity in human populations.

Attitudes and beliefs regarding race-targeted genetic testing of Black people: A systematic review

Geographical ancestry has been associated with an increased risk of various genetic conditions. Race and ethnicity often have been used as proxies for geographical ancestry. Despite numerous problems associated with the crude reliance on race and ethnicity as proxies for geographical ancestry, some genetic testing in the clinical, research, and employment settings has been and continues to be race- or ethnicity-based. Race-based or race-targeted genetic testing refers to genetic testing offered only or primarily to people of particular racial or ethnic groups because of presumed differences among groups. One current example is APOL1 testing of Black kidney donors. Race-based genetic testing raises numerous ethical and policy questions. Given the ongoing reliance on the Black race in genetic testing, it is important to understand the views of people who identify as Black or are identified as Black (including African American, Afro-Caribbean, and Hispanic Black) regarding race-based genetic testing that targets Black people because of their race. We conducted a systematic review of studies and reports of stakeholder-engaged projects that examined how people who identify as or are identified as Black perceive genetic testing that specifically presumes genetic differences exist among racial groups or uses race as a surrogate for ancestral genetic variation and targets Black people. Our review identified 14 studies that explicitly studied this question and another 13 that implicitly or tacitly studied this matter. We found four main factors that contribute to a positive attitude toward race-targeted genetic testing (facilitators) and eight main factors that are associated with concerns regarding race-targeted genetic testing (barriers). This review fills an important gap. These findings should inform future genetic research and the policies and practices developed in clinical, research, public health, or other settings regarding genetic testing.

Association of parental divorce, discord, and polygenic risk with children's alcohol initiation and lifetime risk for alcohol use disorder

BACKGROUND

Parental divorce and discord are associated with poorer alcohol-related outcomes for offspring. However, not all children exposed to these stressors develop alcohol problems. Our objective was to test gene-by-environment interaction effects whereby children's genetic risk for alcohol problems modifies the effects of parental divorce and discord to predict alcohol outcomes.

METHODS

The sample included European (EA; N = 5608, 47% male, Mage  ~ 36 years) and African (AA; N = 1714, 46% female, Mage  ~ 33 years) ancestry participants from the Collaborative Study on the Genetics of Alcoholism. Outcomes included age at initiation of regular drinking and lifetime DSM-5 alcohol use disorder (AUD). Predictors included parental divorce, parental relationship discord, and offspring alcohol problems polygenic risk scores (PRSALC ). Mixed effects Cox proportional hazard models were used to examine alcohol initiation and generalized linear mixed effects models were used to examine lifetime AUD. Tests of PRS moderation of the effects of parental divorce/relationship discord on alcohol outcomes were examined on multiplicative and additive scales.

RESULTS

Among EA participants, parental divorce, parental discord, and higher PRSALC were associated with earlier alcohol initiation and greater lifetime AUD risk. Among AA participants, parental divorce was associated with earlier alcohol initiation and discord was associated with earlier initiation and AUD. PRSALC was not associated with either. Parental divorce/discord and PRSALC interacted on an additive scale in the EA sample, but no interactions were found in AA participants.

CONCLUSIONS

Children's genetic risk for alcohol problems modifies the impact of parental divorce/discord, consistent with an additive model of diathesis-stress interaction, with some differences across ancestry.

A meta-analysis of genetic effects associated with neurodevelopmental disorders and co-occurring conditions

A systematic understanding of the aetiology of neurodevelopmental disorders (NDDs) and their co-occurrence with other conditions during childhood and adolescence remains incomplete. In the current meta-analysis, we synthesized the literature on (1) the contribution of genetic and environmental factors to NDDs, (2) the genetic and environmental overlap between different NDDs, and (3) the co-occurrence between NDDs and disruptive, impulse control and conduct disorders (DICCs). Searches were conducted across three platforms: Web of Science, Ovid Medline and Ovid Embase. Studies were included only if 75% or more of the sample consisted of children and/or adolescents and the studies had measured the aetiology of NDDs and DICCs using single-generation family designs or genomic methods. Studies that had selected participants on the basis of unrelated diagnoses or injuries were excluded. We performed multilevel, random-effects meta-analyses on 296 independent studies, including over four million (partly overlapping) individuals. We further explored developmental trajectories and the moderating roles of gender, measurement, geography and ancestry. We found all NDDs to be substantially heritable (family-based heritability, 0.66 (s.e. = 0.03); SNP heritability, 0.19 (s.e. = 0.03)). Meta-analytic genetic correlations between NDDs were moderate (grand family-based genetic correlation, 0.36 (s.e. = 0.12); grand SNP-based genetic correlation, 0.39 (s.e. = 0.19)) but differed substantially between pairs of disorders. The genetic overlap between NDDs and DICCs was strong (grand family-based genetic correlation, 0.62 (s.e. = 0.20)). While our work provides evidence to inform and potentially guide clinical and educational diagnostic procedures and practice, it also highlights the imbalance in the research effort that has characterized developmental genetics research.

Microsatellites used in forensics are located in regions unusually rich in trait-associated variants

The 20 short tandem repeat (STR) markers of the combined DNA index system (CODIS) are the basis of the vast majority of forensic genetics in the United States. One argument for permissive rules about the collection of CODIS genotypes is that the CODIS markers are thought to contain information relevant to identification only (such as a human fingerprint would), with little information about ancestry or traits. However, in the past 20 years, a quickly growing field has identified hundreds of thousands of genotype-trait associations. Here we conduct a survey of the landscape of such associations surrounding the CODIS loci as compared with non-CODIS STRs. We find that the regions around the CODIS markers are enriched for both known pathogenic variants (>90th percentile) and for SNPs identified as trait-associated in genome-wide association studies (GWAS) (≥95th percentile in 10kb and 100kb flanking regions), compared with other random sets of autosomal tetranucleotide-repeat STRs. Although it is not obvious how much phenotypic information CODIS would need to convey to strain the "DNA fingerprint" analogy, the CODIS markers, considered as a set, are in regions unusually dense with variants with known phenotypic associations.

Human microbiome variance is underestimated

Most of the variance in the human microbiome remains unexplained. Although an extensive list of individual lifestyles shaping the microbiome has been identified, important gaps in knowledge persist. Most human microbiome data are from individuals living in socioeconomically developed countries. This may have skewed the interpretation of microbiome variance and its relationship to health and disease. Moreover, striking under-representation of minority groups in microbiome studies is a missed opportunity to assess context, history and the changing nature of the microbiome in relation to the risk of disease. Therefore, we focus here on areas of recent progress - ageing and ethnicity - both of which contribute to microbiome variance with particular lessons for the promise of microbiome-based diagnostics and therapeutics.