Identifying genetic variants and pathways associated with extreme levels of fetal hemoglobin in sickle cell disease in Tanzania.

BACKGROUND: Sickle cell disease (SCD) is a blood disorder caused by a point mutation on the beta globin gene resulting in the synthesis of abnormal hemoglobin. Fetal hemoglobin (HbF) reduces disease severity, but the levels vary from one individual to another. Most research has focused on common genetic variants which differ across populations and hence do not fully account for HbF variation. METHODS: We investigated rare and common genetic variants that influence HbF levels in 14 SCD patients to elucidate variants and pathways in SCD patients with extreme HbF levels (≥7.7% for high HbF) and (≤2.5% for low HbF) in Tanzania. We performed targeted next generation sequencing (Illumina_Miseq) covering exonic and other significant fetal hemoglobin-associated loci, including BCL11A, MYB, HOXA9, HBB, HBG1, HBG2, CHD4, KLF1, MBD3, ZBTB7A and PGLYRP1. RESULTS: Results revealed a range of genetic variants, including bi-allelic and multi-allelic SNPs, frameshift insertions and deletions, some of which have functional importance. Notably, there were significantly more deletions in individuals with high HbF levels (11% vs 0.9%). We identified frameshift deletions in individuals with high HbF levels and frameshift insertions in individuals with low HbF. CHD4 and MBD3 genes, interacting in the same sub-network, were identified to have a significant number of pathogenic or non-synonymous mutations in individuals with low HbF levels, suggesting an important role of epigenetic pathways in the regulation of HbF synthesis. CONCLUSIONS: This study provides new insights in selecting essential variants and identifying potential biological pathways associated with extreme HbF levels in SCD interrogating multiple genomic variants associated with HbF in SCD.

Skills Capacity Building For Health Care Services and Research Through the Sickle Pan African Research Consortium.

Skills development, the building of human capacity, is key to any sustainable capacity building effort, however, such undertakings require adaptable and tailored strategies. The Sickle Pan-African Research Consortium (SPARCo) is building capacity in sickle cell disease (SCD) management and research in sub-Saharan Africa, including a multi-national SCD patient registry, this is underpinned by skills development activities in data, research, and SCD management. Method: The SPARCo Skills Working Group was set up with the mandate of coordinating skills development activities across the three SPARCo sites in Ghana, Nigeria and Tanzania. To tailor activities to the requirements of the consortium, a needs assessment was conducted at the start of the project which identified skills required for SCD management and research and catalogued existing external and internal training programmes. The needs assessment highlighted differences in skill levels between the sites and different organisational structures which required tailored skills development activities at individual, site and consortium levels. Strategy: Based on the needs and the resources available, different types of training activities were implemented: these included online, blended and face to face activities. In order to create a sustainable skills development programme, existing short, medium, long-term, on-job training activities were used wherever possible. World Sickle Cell Day (19th June) was leveraged for training and health education activities. Results: SPARCo has recorded 1,726 participants in skills development activities across the three sites. Skills have been enhanced in data management, SCD and research to underpin the core deliverables of SPARCo. Conclusion and Lessons Learned: The baseline needs assessments and continual review and adjustment were critical for development of an effective skill development strategy for the consortium. This adaptability was particularly valuable during the COVID-19 pandemic. The sustainability plan leveraged existing programmes and activities and has created a pool of people with required skills for health care and research in SCD. To be effective, skills development programmes need to take into account existing capacity, training opportunities and local conditions. The model was applied to SCD and is adaptable to other skills development in healthcare and research in low and middle- income countries.

Biomarkers of sickle cell nephropathy in Senegal.

Sickle cell anemia (SCA) is caused by a single point variation in the ß-globin gene (HBB): c.20A> T (p.Glu7Val), in homozygous state. SCA is characterized by sickling of red blood cells in small blood vessels which leads to a range of multiorgan complications, including kidney dysfunction. This case-control study aims at identifying sickle cell nephropathy biomarkers in a group of patients living with SCA from Senegal. A total of 163 patients living with SCA and 177 ethnic matched controls were investigated. Biological phenotyping included evaluation of glycemia, glucosuria, albuminuria, proteinuria, tubular proteinuria, serum creatinine, urine creatinine, urine specific gravity and glomerular filtration rate. Descriptive statistics of biomarkers were performed using the χ2 -test, with the significance level set at p<0.05. Patients living with SCA had a median age of 20 years (range 4 to 57) with a female sex frequency of 53.21%. The median age of the control participants was 29 years (range: 4-77) with a female sex frequency of 66.09%. The following proportions of abnormal biological indices were observed in SCA patients versus (vs.) controls, as follows: hyposthenuria: 35.3%vs.5.2% (p<0.001); glomerular hyperfiltration: 47.66%vs.19.75% (p<0.001), renal insufficiency: 5.47%vs.3.82% (p = 0.182); microalbuminuria: 42.38%vs.5.78% (p<0.001); proteinuria: 39.33%vs.4.62% (p<0.001); tubular proteinuria: 40.97%vs.4.73% (p<0.001) and microglucosuria: 22.5%vs.5.1% (p<0.001). This study shows a relatively high proportion of SCA nephropathy among patients living with SCA in Senegal. Microglucosuria, proteinuria, tubular proteinuria, microalbuminuria, hyposthenuria and glomerular hyperfiltration are the most prevalent biomarkers of nephropathy in this group of Senegalese patients with SCA.

Genetic Analysis of TB Susceptibility Variants in Ghana Reveals Candidate Protective Loci in SORBS2 and SCL11A1 Genes.

Despite advancements made toward diagnostics, tuberculosis caused by Mycobacterium africanum (Maf) and Mycobacterium tuberculosis sensu stricto (Mtbss) remains a major public health issue. Human host factors are key players in tuberculosis (TB) outcomes and treatment. Research is required to probe the interplay between host and bacterial genomes. Here, we explored the association between selected human/host genomic variants and TB disease in Ghana. Paired host genotype datum and infecting bacterial isolate information were analyzed for associations using a multinomial logistic regression. Mycobacterium tuberculosis complex (MTBC) isolates were obtained from 191 TB patients and genotyped into different phylogenetic lineages by standard methods. Two hundred and thirty-five (235) nondisease participants were used as healthy controls. A selection of 29 SNPs from TB disease-associated genes with high frequency among African populations was assayed using a TaqMan® SNP Genotyping Assay and iPLEX Gold Sequenom Mass Genotyping Array. Using 26 high-quality SNPs across 326 case-control samples in an association analysis, we found a protective variant, rs955263, in the SORBS2 gene against both Maf and Mtb infections (P BH  = 0.05; OR = 0.33; 95% CI = 0.32-0.34). A relatively uncommon variant, rs17235409 in the SLC11A1 gene was observed with an even stronger protective effect against Mtb infection (MAF = 0.06; PBH = 0.04; OR = 0.05; 95% CI = 0.04-0.05). These findings suggest SLC11A1 and SORBS2 as a potential protective gene of substantial interest for TB, which is an important pathogen in West Africa, and highlight the need for in-depth host-pathogen studies in West Africa.

Implementing Artificial Intelligence and Digital Health in Resource-Limited Settings? Top 10 Lessons We Learned in Congenital Heart Defects and Cardiology.

Artificial intelligence (AI) is one of the key drivers of digital health. Digital health and AI applications in medicine and biology are emerging worldwide, not only in resource-rich but also resource-limited regions. AI predates to the mid-20th century, but the current wave of AI builds in part on machine learning (ML), big data, and algorithms that can learn from massive amounts of online user data from patients or healthy persons. There are lessons to be learned from AI applications in different medical specialties and across developed and resource-limited contexts. A case in point is congenital heart defects (CHDs) that continue to plague sub-Saharan Africa, which calls for innovative approaches to improve risk prediction and performance of the available diagnostics. Beyond CHDs, AI in cardiology is a promising context as well. The current suite of digital health applications in CHD and cardiology include complementary technologies such as neural networks, ML, natural language processing and deep learning, not to mention embedded digital sensors. Algorithms that build on these advances are beginning to complement traditional medical expertise while inviting us to redefine the concepts and definitions of expertise in molecular diagnostics and precision medicine. We examine and share here the lessons learned in current attempts to implement AI and digital health in CHD for precision risk prediction and diagnosis in resource-limited settings. These top 10 lessons on AI and digital health summarized in this expert review are relevant broadly beyond CHD in cardiology and medical innovations. As with AI itself that calls for systems approaches to data capture, analysis, and interpretation, both developed and developing countries can usefully learn from their respective experiences as digital health continues to evolve worldwide.