Has translational genomics come of age in Africa?

Are Hospital Pharmacists Ready for Precision Medicine in Nigerian Healthcare? Insights From a Multi-Center Study

Background

Precision medicine (PM) has taken center stage in healthcare since the completion of the genomic project. Developed countries have gradually integrated PM into mainstream patient management. However, Nigeria still grapples with wide acceptance, key translational research and implementation of PM. This study sought to explore the knowledge and attitude of PM among pharmacists as key stakeholders in the healthcare team.

Methods

A cross-sectional study was conducted in selected tertiary hospitals across the country. A 21-item semi-structured questionnaire was administered by hybrid online and physical methods and the results analyzed with Statistical Package for the Social Sciences Version 25. Descriptive statistics were used to summarize the data. A chi-square test was employed to determine the association of knowledge of PM and the sociodemographic characteristics of the study population.

Results

A total of 167 hospital pharmacists participated in the study. A high proportion of the participants are familiar with artificial intelligence (91.75%), Pharmacogenomics (84.5%), and precision medicine (61%). Overall, 38.9% of the pharmacists had a good knowledge while 13.2% had a poor knowledge of PM and associated terms. The level of knowledge did not correlate significantly with gender (X 2 = 3.21, p = 0.201), age (X 2 = 5, p = 0.27), marital status (X 2 = 3.21, p = 0.201), and professional level (X 2 = 6.85, p = 0.144). The most important value of precision medicine to hospital pharmacists is the ability to minimize the impact of disease through preventive medicine (49%) while a large portion are pursuing and or actively planning to pursue additional education in precision medicine.

Conclusions

There is a highly positive attitude toward the prospect of PM among hospital pharmacists in Nigeria. Education modules in this field are highly recommended as most do not have a holistic knowledge of terms used in PM. Also, more research aimed at translating PM knowledge into clinical practice is recommended.

Ancestry-aligned polygenic scores combined with conventional risk factors improve prediction of cardiometabolic outcomes in African populations

BACKGROUND

Cardiovascular diseases (CVD) are a major health concern in Africa. Improved identification and treatment of high-risk individuals can reduce adverse health outcomes. Current CVD risk calculators are largely unvalidated in African populations and overlook genetic factors. Polygenic scores (PGS) can enhance risk prediction by measuring genetic susceptibility to CVD, but their effectiveness in genetically diverse populations is limited by a European-ancestry bias. To address this, we developed models integrating genetic data and conventional risk factors to assess the risk of developing cardiometabolic outcomes in African populations.

METHODS

We used summary statistics from a genome-wide association meta-analysis (n = 14,126) in African populations to derive novel genome-wide PGS for 14 cardiometabolic traits in an independent African target sample (Africa Wits-INDEPTH Partnership for Genomic Research (AWI-Gen), n = 10,603). Regression analyses assessed relationships between each PGS and corresponding cardiometabolic trait, and seven CVD outcomes (CVD, heart attack, stroke, diabetes mellitus, dyslipidaemia, hypertension, and obesity). The predictive utility of the genetic data was evaluated using elastic net models containing multiple PGS (MultiPGS) and reference-projected principal components of ancestry (PPCs). An integrated risk prediction model incorporating genetic and conventional risk factors was developed. Nested cross-validation was used when deriving elastic net models to enhance generalisability.

RESULTS

Our African-specific PGS displayed significant but variable within- and cross- trait prediction (max.R2 = 6.8%, p = 1.86 × 10-173). Significantly associated PGS with dyslipidaemia included the PGS for total cholesterol (logOR = 0.210, SE = 0.022, p = 2.18 × 10-21) and low-density lipoprotein (logOR =  - 0.141, SE = 0.022, p = 1.30 × 10-20); with hypertension, the systolic blood pressure PGS (logOR = 0.150, SE = 0.045, p = 8.34 × 10-4); and multiple PGS associated with obesity: body mass index (max. logOR = 0.131, SE = 0.031, p = 2.22 × 10-5), hip circumference (logOR = 0.122, SE = 0.029, p = 2.28 × 10-5), waist circumference (logOR = 0.013, SE = 0.098, p = 8.13 × 10-4) and weight (logOR = 0.103, SE = 0.029, p = 4.89 × 10-5). Elastic net models incorporating MultiPGS and PPCs significantly improved prediction over MultiPGS alone. Models including genetic data and conventional risk factors were more predictive than conventional risk models alone (dyslipidaemia: R2 increase = 2.6%, p = 4.45 × 10-12; hypertension: R2 increase = 2.6%, p = 2.37 × 10-13; obesity: R2 increase = 5.5%, 1.33 × 10-34).

CONCLUSIONS

In African populations, CVD and associated cardiometabolic trait prediction models can be improved by incorporating ancestry-aligned PGS and accounting for ancestry. Combining PGS with conventional risk factors further enhances prediction over traditional models based on conventional factors. Incorporating data from target populations can improve the generalisability of international predictive models for CVD and associated traits in African populations.

The dawn of a cure for sickle cell disease through CRISPR-based treatment: A critical test of equity in public health genomics

Equity in access to genomic technologies, resources, and products remains a great challenge. This was evident especially during the coronavirus disease 2019 (COVID-19) pandemic when the majority of lower middle-income countries were unable to achieve at least 10% population vaccination coverage during initial COVID-19 vaccine rollouts, despite the rapid development of those vaccines. Sickle cell disease (SCD) is an inherited monogenic red blood cell disorder that affects hemoglobin, the protein that carries oxygen through the body. Globally, the African continent carries the highest burden of SCD with at least 240,000 children born each year with the disease. SCD has evolved from a treatable to a curable disease. Recently, the UK medical regulator approved its cure through clustered regularly interspaced short palindromic repeat (CRISPR)-based treatment, whereas the US Food and Drug Administration has equally approved two SCD gene therapies. This presents a remarkable opportunity to demonstrate equity in public health genomics. This CRISPR-based treatment is expensive and therefore, a need for an ambitious action to ensure that they are affordable and accessible where they are needed most and stand to save millions of lives.

A feasible molecular diagnostic strategy for rare genetic disorders within resource-constrained environments

Timely and accurate diagnosis of rare genetic disorders is critical, as it enables improved patient management and prognosis. In a resource-constrained environment such as the South African State healthcare system, the challenge is to design appropriate and cost-effective assays that will enable accurate genetic diagnostic services in patients of African ancestry across a broad disease spectrum. Next-generation sequencing (NGS) has transformed testing approaches for many Mendelian disorders, but this technology is still relatively new in our setting and requires cost-effective ways to implement. As a proof of concept, we describe a feasible diagnostic strategy for genetic disorders frequently seen in our genetics clinics (RASopathies, Cornelia de Lange syndrome, Treacher Collins syndrome, and CHARGE syndrome). The custom-designed targeted NGS gene panel enabled concurrent variant screening for these disorders. Samples were batched during sequencing and analyzed selectively based on the clinical phenotype. The strategy employed in the current study was cost-effective, with sequencing and analysis done at USD849.68 per sample and achieving an overall detection rate of 54.5%. The strategy employed is cost-effective as it allows batching of samples from patients with different diseases in a single run, an approach that can be utilized with rare and less frequently ordered molecular diagnostic tests. The subsequent selective analysis pipeline allowed for timeous reporting back of patients results. This is feasible with a reasonable yield and can be employed for the molecular diagnosis of a wide range of rare monogenic disorders in a resource-constrained environment.

Incorporating CNV analysis improves the yield of exome sequencing for rare monogenic disorders-an important consideration for resource-constrained settings

Exome sequencing (ES) is a recommended first-tier diagnostic test for many rare monogenic diseases. It allows for the detection of both single-nucleotide variants (SNVs) and copy number variants (CNVs) in coding exonic regions of the genome in a single test, and this dual analysis is a valuable approach, especially in limited resource settings. Single-nucleotide variants are well studied; however, the incorporation of copy number variant analysis tools into variant calling pipelines has not been implemented yet as a routine diagnostic test, and chromosomal microarray is still more widely used to detect copy number variants. Research shows that combined single and copy number variant analysis can lead to a diagnostic yield of up to 58%, increasing the yield with as much as 18% from the single-nucleotide variant only pipeline. Importantly, this is achieved with the consideration of computational costs only, without incurring any additional sequencing costs. This mini review provides an overview of copy number variant analysis from exome data and what the current recommendations are for this type of analysis. We also present an overview on rare monogenic disease research standard practices in resource-limited settings. We present evidence that integrating copy number variant detection tools into a standard exome sequencing analysis pipeline improves diagnostic yield and should be considered a significantly beneficial addition, with relatively low-cost implications. Routine implementation in underrepresented populations and limited resource settings will promote generation and sharing of CNV datasets and provide momentum to build core centers for this niche within genomic medicine.

An Assessment of the Knowledge and Perceptions of Precision Medicine (PM) in the Rwandan Healthcare Setting

INTRODUCTION

Precision medicine (PM) or personalized medicine is an innovative approach that aims to tailor disease prevention and treatment to consider the differences in people's genes, environments, and lifestyles. Although many efforts have been made to accelerate the universal adoption of PM, several challenges need to be addressed in order to advance PM in Africa. Therefore, our study aimed to establish baseline data on the knowledge and perceptions of the implementation of PM in the Rwandan healthcare setting.

METHOD

A descriptive qualitative study was conducted in five hospitals offering diagnostics and oncology services to cancer patients in Rwanda. To understand the existing policies regarding PM implementation in the country, two additional institutions were surveyed: the Ministry of Health (MOH), which creates and sets policies for the overall vision of the health sector, and the Rwanda Biomedical Center (RBC), which coordinates the implementation of health sector policies in the country. The researchers conducted 32 key informant interviews and assessed the functionality of available PM equipment in the 5 selected health facilities. The data were thematically categorized and analyzed.

RESULTS

The study revealed that PM is perceived as a complex and expensive program by most health managers and health providers. The most cited challenges to implementing PM included the following: the lack of policies and guidelines; the lack of supportive infrastructures and limited suppliers of required equipment and laboratory consumables; financial constraints; cultural, behavioral, and religious beliefs; and limited trained, motivated, and specialized healthcare providers. Regarding access to health services for cancer treatment, patients with health insurance pay 10% of their medical costs, which is still too expensive for Rwandans.

CONCLUSION

The study participants highlighted the importance of PM to enhance healthcare delivery if the identified barriers are addressed. For instance, Rwandan health sector leadership might consider the creation of specialized oncology centers in all or some referral hospitals with all the necessary genomic equipment and trained staff to serve the needs of the country and implement a PM program.

The implementation and utility of clinical exome sequencing in a South African infant cohort

Genetic disorders are significant contributors to infant hospitalization and mortality globally. The early diagnosis of these conditions in infants remains a considerable challenge. Clinical exome sequencing (CES) has shown to be a successful tool for the early diagnosis of genetic conditions, however, its utility in African infant populations has not been investigated. The impact of the under-representation of African genomic data, the cost of testing, and genomic workforce shortages, need to be investigated and evidence-based implementation strategies accounting for locally available genetics expertise and diagnostic infrastructure need to be developed. We evaluated the diagnostic utility of singleton CES in a cohort of 32 ill, South African infants from two State hospitals in Johannesburg, South Africa. We analysed the data using a series of filtering approaches, including a curated virtual gene panel consisting of genes implicated in neonatal-and early childhood-onset conditions and genes with known founder and common variants in African populations. We reported a diagnostic yield of 22% and identified seven pathogenic variants in the NPHS1, COL2A1, OCRL, SHOC2, TPRV4, MTM1 and STAC3 genes. This study demonstrates the utility value of CES in the South African State healthcare setting, providing a diagnosis to patients who would otherwise not receive one and allowing for directed management. We anticipate an increase in the diagnostic yield of our workflow with further refinement of the study inclusion criteria. This study highlights important considerations for the implementation of genomic medicine in under-resourced settings and in under-represented African populations where variant interpretation remains a challenge.

Identifying the genetic causes of developmental disorders and intellectual disability in Africa: a systematic literature review

Objective: Genetic variants cause a significant portion of developmental disorders and intellectual disabilities (DD/ID), but clinical and genetic heterogeneity makes identification challenging. Compounding the issue is a lack of ethnic diversity in studies into the genetic aetiology of DD/ID, with a dearth of data from Africa. This systematic review aimed to comprehensively describe the current knowledge from the African continent on this topic. Method: Applicable literature published up until July 2021 was retrieved from PubMed, Scopus and Web of Science databases, following PRISMA guidelines, focusing on original research reports on DD/ID where African patients were the focus of the study. The quality of the dataset was assessed using appraisal tools from the Joanna Briggs Institute, whereafter metadata was extracted for analysis. Results: A total of 3,803 publications were extracted and screened. After duplicate removal, title, abstract and full paper screening, 287 publications were deemed appropriate for inclusion. Of the papers analysed, a large disparity was seen between work emanating from North Africa compared to sub-Saharan Africa, with North Africa dominating the publications. Representation of African scientists on publications was poorly balanced, with most research being led by international researchers. There are very few systematic cohort studies, particularly using newer technologies, such as chromosomal microarray and next-generation sequencing. Most of the reports on new technology data were generated outside Africa. Conclusion: This review highlights how the molecular epidemiology of DD/ID in Africa is hampered by significant knowledge gaps. Efforts are needed to produce systematically obtained high quality data that can be used to inform appropriate strategies to implement genomic medicine for DD/ID on the African continent, and to successfully bridge healthcare inequalities.

Retrospective file review shows limited genetic services fails most patients - an argument for the implementation of exome sequencing as a first-tier test in resource-constraint settings

BACKGROUND

Exome sequencing is recommended as a first-line investigation for patients with a developmental delay or intellectual disability. This approach has not been implemented in most resource-constraint settings, including Africa, due to the high cost of implementation. Instead, patients have limited access to services and testing options. Here, we evaluate the effectiveness of a limited genetic testing strategy and contrast the findings to a conceivable outcome if exome sequencing were available instead.

RESULTS

A retrospective audit of 934 patient files presenting to a medical genetics clinic in South Africa showed that 83% of patients presented with developmental delay as a clinical feature. Patients could be divided into three groups, representing distinct diagnostic pathways. Patient Group A (18%; mean test cost $131) were confirmed with aneuploidies, following a simple, inexpensive test. Patient Group B (25%; mean test cost $140) presented with clinically recognizable conditions but only 39% received a genetic diagnostic confirmation due to limited testing options. Patient Group C - the largest group (57%; mean test cost $337) - presented with heterogenous conditions and DD, and 92% remained undiagnosed after limited available testing was performed.

CONCLUSIONS

Patients with DD are the largest group of patients seen in medical genetics clinics in South Africa. When clinical features are not distinct, limited testing options drastically restricts diagnostic yield. A cost- and time analysis shows most patients would benefit from first-line exome sequencing, reducing their individual diagnostic odysseys.

Clinicians' Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa

Cardiovascular diseases (CVDs) are a leading cause of mortality and morbidity in South Africa. Risk stratification is the preferred approach to disease prevention, but identifying patients at high risk for CVD remains challenging. Assessing genetic risk could improve stratification and inform a clinically relevant precision medicine (PM) approach. Clinicians are critical to PM adoption, thus, this study explores practicing clinicians’ perceptions of PM-based CVD risk stratification in South Africa’s public health setting. Practicing clinicians (n = 109) at four teaching hospitals in Johannesburg, South Africa, completed an electronic self-administered survey. The effect of demographic and professional characteristics on PM-based CVD risk stratification perceptions was assessed. Fewer than 25% of respondents used clinical genetic testing, and 14% had formal genetics training. 78% had a low mean knowledge score, with higher scores associated with genetic training (p < 0.0005) and research involvement (p < 0.05). Despite limited knowledge and resources, 84% perceived PM approaches positively. 57% felt confident in applying the PM-based approach, with those already undertaking CVD risk stratification more confident (p < 0.001). High cost and limited access to genetics services are key barriers. Integrating genetic information into established clinical tools will likely increase confidence in using PM approaches. Addressing the genetics training gap and investment into the country’s genomics capacity is needed to advance PM in South Africa.

Increasing African genomic data generation and sharing to resolve rare and undiagnosed diseases in Africa: a call-to-action by the H3Africa rare diseases working group

The rich and diverse genomics of African populations is significantly underrepresented in reference and in disease-associated databases. This renders interpreting the Next Generation Sequencing (NGS) data and reaching a diagnostic more difficult in Africa and for the African diaspora. It increases chances for false positives with variants being misclassified as pathogenic due to their novelty or rarity. We can increase African genomic data by (1) making consent for sharing aggregate frequency data an essential component of research toolkit; (2) encouraging investigators with African data to share available data through public resources such as gnomAD, AVGD, ClinVar, DECIPHER and to use MatchMaker Exchange; (3) educating African research participants on the meaning and value of sharing aggregate frequency data; and (4) increasing funding to scale-up the production of African genomic data that will be more representative of the geographical and ethno-linguistic variation on the continent. The RDWG of H3Africa is hereby calling to action because this underrepresentation accentuates the health disparities. Applying the NGS to shorten the diagnostic odyssey or to guide therapeutic options for rare diseases will fully work for Africans only when public repositories include sufficient data from African subjects.

African genomic data sharing and the struggle for equitable benefit

Genomic and related health data from Africa remain scarce and are extremely valuable, due to an abundance of variants often rare or absent in the rest of the world. Insights from such data will benefit global populations, but will Africa be neglected by limited access to affordable benefits resulting from research that uses their data?