Diversity and inclusion in genomic research: why the uneven progress?

Accuracy of Gene Expression Prediction From Genotype Data With PrediXcan Varies Across and Within Continental Populations

Using genetic data to predict gene expression has garnered significant attention in recent years. PrediXcan has become one of the most widely used gene-based methods for testing associations between predicted gene expression values and a phenotype, which has facilitated novel insights into the relationship between complex traits and the component of gene expression that can be attributed to genetic variation. The gene expression prediction models for PrediXcan were developed using supervised machine learning methods and training data from the Depression Genes and Networks (DGN) study and the Genotype-Tissue Expression (GTEx) project, where the majority of subjects are of European descent. Many genetic studies, however, include samples from multi-ethnic populations, and in this paper we evaluate the accuracy of PrediXcan for predicting gene expression in diverse populations. Using transcriptomic data from the GEUVADIS (Genetic European Variation in Disease) RNA sequencing project and whole genome sequencing data from the 1000 Genomes project, we evaluate and compare the predictive performance of PrediXcan in an African population (Yoruban) and four European ancestry populations for thousands of genes. We evaluate a range of models from the PrediXcan weight databases and use Pearson's correlation coefficient to assess gene expression prediction accuracy with PrediXcan. From our evaluation, we find that the predictive performance of PrediXcan varies substantially among populations from different continents (F-test p-value < 2.2 × 10-16), where prediction accuracy is lower in the Yoruban population from West Africa compared to the European-ancestry populations. Moreover, not only do we find differences in predictive performance between populations from different continents, we also find highly significant differences in prediction accuracy among the four European ancestry populations considered (F-test p-value < 2.2 × 10-16). Finally, while there is variability in prediction accuracy across different PrediXcan weight databases, we also find consistency in the qualitative performance of PrediXcan for the five populations considered, with the African ancestry population having the lowest accuracy across databases.

Association between polygenic risk for tobacco or alcohol consumption and liability to licit and illicit substance use in young Australian adults

BACKGROUND

Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods.

METHODS

Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together.

RESULTS

After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC.

CONCLUSIONS

To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.

Caring for trafficked and unidentified patients in the EHR shadows: Shining a light by sharing the data

OBJECTIVE

Healthcare providers have key roles in the prevention of, detection of, and interventions for human trafficking. Yet caring for trafficked persons is particularly challenging: patients whose identities are unknown, unreliable, or false could receive subpar care from providers delivering care in a vacuum of relevant information. The application of precision medicine principles and integration of biometric data (including genetic information) could facilitate patient identification, enable longitudinal medical records, and improve continuity and quality of care for this vulnerable patient population. Scant empirical data exist regarding healthcare system preparedness and care for the needs of this vulnerable population nor data on perspectives on the use and risks of biometrics or genetic information for trafficked patients.

METHODS

To address this gap, we conducted mixed-methods research involving semi-structured interviews with key informants, which informed a subsequent broad survey of physicians and registered nurses.

RESULTS

Our findings support the perception that trafficked persons obtain care yet remain unnoticed or undocumented in the electronic health record. Our survey findings further reveal that healthcare providers remain largely unaware of human trafficking issues and are inadequately prepared to provide patient-centered care for trafficked and unidentified patients.

CONCLUSION

Meaningful efforts to design and implement precision medicine initiatives in an inclusive way that optimizes impacts are unlikely to succeed without concurrent efforts to increase general awareness of and preparedness to care for trafficked persons. Additional research is needed to examine properly the potential utility for biometrics to improve the delivery of care for trafficked patients.

The Emergence of Genomic Research in Africa and New Frameworks for Equity in Biomedical Research

Individuals with African ancestry have the greatest genomic diversity in the world, yet they have been underrepresented in genomic research. To advance our understanding of human biology and our ability to trace human history, we must include more samples from Africans in genomic research. Additionally, inclusion of more samples from participants of recent African descent is imperative to provide equitable health care as genomics is increasingly used for diagnosis, treatment, and to understand disease risk. The Human Heredity and Health in Africa initiative (H3Africa) seeks to expand the number of Africans included in genomic research and to do so by expanding the research capacity on the continent. In this article, we discuss how H3Africa is endeavoring to achieve these goals while promoting equitable research collaborations.

Whole genome sequence association with E-selectin levels reveals loss-of-function variant in African Americans

E-selectin mediates the rolling of circulating leukocytes during inflammatory processes. Previous genome-wide association studies in European and Asian individuals have identified the ABO locus associated with E-selectin levels. Using Trans-Omics for Precision Medicine whole genome sequencing data in 2249 African Americans (AAs) from the Jackson Heart Study, we examined genome-wide associations with soluble E-selectin levels. In addition to replicating known signals at ABO, we identified a novel association of a common loss-of-function, missense variant in Fucosyltransferase 6 (FUT6; rs17855739,p.Glu274Lys, P = 9.02 × 10-24) with higher soluble E-selectin levels. This variant is considerably more common in populations of African ancestry compared to non-African ancestry populations. We replicated the association of FUT6 p.Glu274Lys with higher soluble E-selectin in an independent population of 748 AAs from the Women's Health Initiative and identified an additional pleiotropic association with vitamin B12 levels. Despite the broad role of both selectins and fucosyltransferases in various inflammatory, immune and cancer-related processes, we were unable to identify any additional disease associations of the FUT6 p.Glu274Lys variant in an electronic medical record-based phenome-wide association scan of over 9000 AAs.

Host and Microbiome Genome-Wide Association Studies: Current State and Challenges

The involvement of the microbiome in health and disease is well established. Microbiome genome-wide association studies (mGWAS) are used to elucidate the interaction of host genetic variation with the microbiome. The emergence of this relatively new field has been facilitated by the advent of next generation sequencing technologies that enable the investigation of the complex interaction between host genetics and microbial communities. In this paper, we review recent studies investigating host-microbiome interactions using mGWAS. Additionally, we highlight the marked disparity in the sampling population of mGWAS carried out to date and draw attention to the critical need for inclusion of diverse populations.

Ethnic identity and engagement with genome sequencing research

Purpose.

We examined the role of ethnic identity (which measures the degree to which individuals identify with their ethnic group) in beliefs about, and intentions to learn, genomic results.

Methods.

A longitudinal cohort was recruited to implement genome sequencing among healthy participants self-identifying as African, African-American, or Afro-Caribbean, 40–65 years old (n=408). Before receiving genomic results, participants completed a survey assessing social and behavioral constructs related to health, genomics, and ethnic identity.

Results.

Ethnic identity was positively correlated with perceived value of genomic results and expected benefits from genomic research participation. Among participants with stronger ethnic identity, cognitive beliefs [perceived value of results (b=0.63, 95% CI: 0.29, 0.98, p<0.001) and expected benefits from genomic research participation (b=0.32, 95% CI: 0.12, 0.53, p=0.002)] were associated with intentions to receive results. Among those with weaker ethnic identity, there was no such association.

Conclusion.

Individuals with stronger ethnic identity seem to attend more to cognitive beliefs such as the value of genomic results when deliberating receipt of results compared to those with weaker ethnic identity. Understanding ethnic identity variation and its influence on genome sequencing perceptions and intentions can inform future research opportunities using ethnic identity to explore specific practical, clinical questions.

Model framework for governance of genomic research and biobanking in Africa - a content description

Genomic research and biobanking are expanding globally, with a promise to fast-track the research needed to improve approaches to disease treatment and prevention through scientific collaborations such as the Human Heredity and Health in Africa (H3Africa) initiative. Integral to this type of research is the availability of samples and data for research. The need for broad access brings along a host of ethical concerns, including those related to privacy and confidentiality, as well as fairness and equity in access and capacity to utilise these samples between scientists from the high income and low income countries. Addressing these concerns while promoting genomic research, especially in Africa, requires the implementation of a sound governance framework. In this paper, we describe the contents of a Framework for Best Practice for Genomics Research and biobanking in Africa that was developed, under the auspices of the H3Africa initiative. This framework is broad enough to be used and adapted by African countries to facilitate the development of country-specific guidelines and to help improve the conduct and governance of genomics research.

Model framework for governance of genomic research and biobanking in Africa - a content description

Genomic research and biobanking are expanding globally, with a promise to fast-track the research needed to improve approaches to disease treatment and prevention through scientific collaborations such as the Human Heredity and Health in Africa (H3Africa) initiative. Integral to this type of research is the availability of samples and data for research. The need for broad access brings along a host of ethical concerns, including those related to privacy and confidentiality, as well as fairness and equity in access and capacity to utilise these samples between scientists from the high income and low income countries. Addressing these concerns while promoting genomic research, especially in Africa, requires the implementation of a sound governance framework. In this paper, we describe the contents of a Framework for Best Practice for Genomics Research and biobanking in Africa that was developed, under the auspices of the H3Africa initiative. This framework is broad enough to be used and adapted by African countries to facilitate the development of country-specific guidelines and to help improve the conduct and governance of genomics research.

Cultivating inclusivity in precision medicine research: disability, diversity, and cultural competence

Cultural competence is increasingly viewed as key for the inclusion of diverse populations in precision medicine research (PMR) in the USA. Precision medicine researchers and personnel are thus increasingly expected to undergo cultural competency trainings and to engage with relevant racial/ethnic communities to ensure that all research components are culturally and linguistically sensitive to these communities. However, the need for PMR enterprises to ensure competence with and understanding of disability rights, history, and needs (hereinafter disability culture competency) have not received attention. This article discusses the importance of disability inclusivity in PMR and the construct-and challenges-of disability as a cultural community. Reviewing and extrapolating from studies in healthcare settings, the article considers three interrelated issues that are likely to impact disability inclusivity in PMR: disability accessibility and accommodation; disability stigma and unconsious bias; and disability language and communication. Next, disability competency trainings that were developed in healthcare settings are surveyed and their applicability for PMR is discussed. The arguments advanced are that disability culture competency among precision medicine researchers, personnel, and oversight committees is essential to upholding the welfare and rights of human subjects with disabilities in PMR; that engagement with disability communities is imperative for this endeavor; and that such knowledge of disability culture is crucial for cultivating inclusivity of people with different (dis)abilities in PMR.

Genetics of Obesity in Diverse Populations

PURPOSE OF REVIEW

The prevalence of obesity continues to rise, fueling a global public health crisis characterized by dramatic increases in type 2 diabetes, cardiovascular disease, and many cancers. In the USA, several minority populations, who bear much of the obesity burden (47% in African Americans and Hispanic/Latinos, compared to 38% in European descent groups), are particularly at risk of downstream chronic disease. Compounding these disparities, most genome-wide association studies (GWAS)-including those of obesity-have largely been conducted in populations of European or East Asian ancestry. In fact, analysis of the GWAS Catalog found that while the proportion of participants of non-European or non-Asian descent had risen from 4% in 2009 to 19% in 2016, African-ancestry participants are still just 3% of GWAS, Hispanic/Latinos are < 0.5%, and other ancestries are < 0.3% or not represented at all. This review summarizes recent developments in obesity genomics in US minority populations, with the goal of reducing obesity health disparities and improving public health programs and access to precision medicine.

RECENT FINDINGS

GWAS of populations with the highest burden of obesity are essential to narrow candidate variants for functional follow-up, to identify additional ancestry-specific variants that contribute to individual genetic susceptibility, and to advance both public health and precision medicine approaches to obesity. Given the global public health burden posed by obesity and downstream chronic conditions which disproportionately affect non-European populations, GWAS of obesity-related traits in diverse populations is essential to (1) locate causal variants in GWAS-identified regions through fine mapping, (2) identify variants which influence obesity across ancestries through generalization, and (3) discover novel ancestry-specific variants which may be low frequency in European populations but common in other groups. Recent efforts to expand obesity genomic studies to understudied and underserved populations, including AAAGC, PAGE, and HISLA, are working to reduce obesity health disparities, improve public health, and bring the promise of precision medicine to all.

A Novel Pathogenic UGT1A1 Variant in a Sudanese Child with Type 1 Crigler-Najjar Syndrome

Uridine diphosphate glucuronosyltransferases (UGTs) are key enzymes responsible for the body's ability to process a variety of endogenous and exogenous compounds. Significant gains in understanding UGT function have come from the analysis of variants seen in patients. We cared for a Sudanese child who showed clinical features of type 1 Crigler-Najjar syndrome (CN-1), namely severe unconjugated hyperbilirubinemia leading to liver transplantation. CN-1 is an autosomal recessive disorder caused by damaging mutations in the gene for UGT1A1, the hepatic enzyme responsible for bilirubin conjugation in humans. Clinical genetic testing was unable to identify a known pathogenic UGT1A1 mutation in this child. Instead, a novel homozygous variant resulting in an in-frame deletion, p.Val275del, was noted. Sanger sequencing demonstrated that this variant segregated with the disease phenotype in this family. We further performed functional testing using recombinantly expressed UGT1A1 with and without the patient variant, demonstrating that p.Val275del results in a complete lack of glucuronidation activity, a hallmark of CN-1. Sequence analysis of this region shows a high degree of conservation across all known catalytically active human UGTs, further suggesting that it plays a key role in the enzymatic function of UGTs. Finally, we note that the patient's ethnicity likely played a role in his variant being previously undescribed and advocate for greater diversity and inclusion in genomic medicine.

The Clinical Sequencing Evidence-Generating Research Consortium: Integrating Genomic Sequencing in Diverse and Medically Underserved Populations

The Clinical Sequencing Evidence-Generating Research (CSER) consortium, now in its second funding cycle, is investigating the effectiveness of integrating genomic (exome or genome) sequencing into the clinical care of diverse and medically underserved individuals in a variety of healthcare settings and disease states. The consortium comprises a coordinating center, six funded extramural clinical projects, and an ongoing National Human Genome Research Institute (NHGRI) intramural project. Collectively, these projects aim to enroll and sequence over 6,100 participants in four years. At least 60% of participants will be of non-European ancestry or from underserved settings, with the goal of diversifying the populations that are providing an evidence base for genomic medicine. Five of the six clinical projects are enrolling pediatric patients with various phenotypes. One of these five projects is also enrolling couples whose fetus has a structural anomaly, and the sixth project is enrolling adults at risk for hereditary cancer. The ongoing NHGRI intramural project has enrolled primarily healthy adults. Goals of the consortium include assessing the clinical utility of genomic sequencing, exploring medical follow up and cascade testing of relatives, and evaluating patient-provider-laboratory level interactions that influence the use of this technology. The findings from the CSER consortium will offer patients, healthcare systems, and policymakers a clearer understanding of the opportunities and challenges of providing genomic medicine in diverse populations and settings, and contribute evidence toward developing best practices for the delivery of clinically useful and cost-effective genomic sequencing in diverse healthcare settings.

Equitable Participation in Biobanks: The Risks and Benefits of a "Dynamic Consent" Approach

Participation in biobanks tends to favor certain groups—white, middle-class, more highly-educated—often to the exclusion of others, such as indigenous people, the socially-disadvantaged and the culturally and linguistically diverse. Barriers to participation, which include age, location, cultural sensitivities around human tissue, and issues of literacy and language, can influence the diversity of samples found in biobanks. This has implications for the generalizability of research findings from biobanks being able to be translated into the clinic. Dynamic Consent, which is a digital decision-support tool, could improve participants' recruitment to, and engagement with, biobanks over time and help to overcome some of the barriers to participation. However, there are also risks that it may deepen the “digital divide” by favoring those with knowledge and access to digital technologies, with the potential to decrease participant engagement in research. When applying a Dynamic Consent approach in biobanking, researchers should give particular attention to adaptations that can improve participant inclusivity, and evaluate the tool empirically, with a focus on equity-relevant outcome measures. This may help biobanks to fulfill their promise of enabling translational research that is relevant to all.

Precision Medicine: Familiarity, Perceived Health Drivers, and Genetic Testing Considerations Across Health Literacy Levels in a Diverse Sample

A clear awareness of a patient's knowledge, values, and perspectives is an important component of effective genetic counseling. Advances in precision medicine, however, have outpaced our understanding of patient perceptions of this new approach. Patient views may differ across the three domains of precision medicine (genetics, behavioral, and environmental determinants of health), ethnic/racial groups, and health literacy levels. This study describes and compares group differences in familiarity, perceptions, and preferences for precision medicine in a diverse sample. Between 2016 and 2017, 252 participants completed a 10-15-min survey in three primary care clinics in Florida and Tennessee. The final sample was 42.5% African American/Black, 25.8% Hispanic/Latino, 25.0% White, and 6.7% other ethnicity/race. Less than a quarter of participants reported being familiar with the term "precision medicine," but were more familiar with basic genetic terms. Participants with higher health literacy reported greater familiarity with terms (p ≤ .003). African Americans/Black participants were more likely to identify ethnicity/race and discrimination as influencing their health (p ≤ .004). When deciding to get a genetic test, individuals across ethnic/racial groups shared similar considerations. Those with higher health literacy, however, gave significantly greater importance to provider trust (p ≤ .008). Given the recent emergence of precision medicine, at present there may be limited differences in patient perceptions across ethnic/racial groups. Culturally sensitive efforts, tailored to health literacy level, may aid equitable precision medicine uptake.

Stress-Related Biosocial Mechanisms of Discrimination and African American Health Inequities

This review describes stress-related biological mechanisms linking interpersonal racism to life course health trajectories among African Americans. Interpersonal racism, a form of social exclusion enacted via discrimination, remains a salient issue in the lives of African Americans, and it triggers a cascade of biological processes originating as perceived social exclusion and registering as social pain. Exposure to discrimination increases sympathetic nervous system activation and upregulates the HPA axis, increasing physiological wear and tear and elevating the risks of cardiometabolic conditions. Consequently, discrimination is associated with morbidities including low birth weight, hypertension, abdominal obesity, and cardiovascular disease. Biological measures can provide important analytic tools to study the interactions between social experiences such as racial discrimination and health outcomes over the life course. We make future recommendations for the study of discrimination and health outcomes, including the integration of neuroscience, genomics, and new health technologies; interdisciplinary engagement; and the diversification of scholars engaged in biosocial inequities research.

Prioritizing diversity in human genomics research

Recent studies have highlighted the imperatives of including diverse and under-represented individuals in human genomics research and the striking gaps in attaining that inclusion. With its multidecade experience in supporting research and policy efforts in human genomics, the National Human Genome Research Institute is committed to establishing foundational approaches to study the role of genomic variation in health and disease that include diverse populations. Large-scale efforts to understand biology and health have yielded key scientific findings, lessons and recommendations on how to increase diversity in genomic research studies and the genomic research workforce. Increased attention to diversity will increase the accuracy, utility and acceptability of using genomic information for clinical care.

Leveraging the Learning Health Care Model to Improve Equity in the Age of Genomic Medicine

To fully achieve the goals of a genomics-enabled learning health care system, purposeful efforts to understand and reduce health disparities and improve equity of care are essential. This paper highlights three major challenges facing genomics-enabled learning health care systems, as they pertain to ancestrally diverse populations: inequality in the utility of genomic medicine; lack of access to pharmacogenomics in clinical care; and inadequate incorporation of social and environmental data into the electronic health care record (EHR). We advance a framework that can not only be used to directly improve care for all within the learning health system, but can also be used to focus on the needs to address racial and ethnic health disparities and improve health equity.

Genomics for all in the 21st century?

As the field of genomics enters the second decade after the completion of the International Human Genome Project, human genomics research is still far from reflective of the ancestral diversity found in global populations. This special issue of the Journal of Community Genetics brings together a global perspective on the need for researchers and health care professionals to support achievable milestones that will enhance global ancestral diversity in genomic research for the 21st century, and integrate the resulting knowledge into health care that benefits everyone. As the publications in this special issue illustrate, this will require focused community engagement, including often overlooked isolated populations, as well as meaningful integration of genomics and health services across the global landscape. With the advancement of sequencing technology and reduction in the cost, the time has come to address critical barriers.