Computational approaches for network-based integrative multi-omics analysis.

Advances in omics technologies allow for holistic studies into biological systems. These studies rely on integrative data analysis techniques to obtain a comprehensive view of the dynamics of cellular processes, and molecular mechanisms. Network-based integrative approaches have revolutionized multi-omics analysis by providing the framework to represent interactions between multiple different omics-layers in a graph, which may faithfully reflect the molecular wiring in a cell. Here we review network-based multi-omics/multi-modal integrative analytical approaches. We classify these approaches according to the type of omics data supported, the methods and/or algorithms implemented, their node and/or edge weighting components, and their ability to identify key nodes and subnetworks. We show how these approaches can be used to identify biomarkers, disease subtypes, crosstalk, causality, and molecular drivers of physiological and pathological mechanisms. We provide insight into the most appropriate methods and tools for research questions as showcased around the aetiology and treatment of COVID-19 that can be informed by multi-omics data integration. We conclude with an overview of challenges associated with multi-omics network-based analysis, such as reproducibility, heterogeneity, (biological) interpretability of the results, and we highlight some future directions for network-based integration.

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.

Establishing a database for sickle cell disease patient mapping and survival tracking: The sickle pan-african research consortium Nigeria example.

Background: The Sickle Pan-African Research Consortium (SPARCO) and Sickle Africa Data Coordinating Center (SADaCC) were set up with funding from the US National Institute of Health (NIH) for physicians, scientists, patients, support groups, and statisticians to collaborate to reduce the high disease burden and alleviate the impact of Sickle Cell Disease (SCD) in Africa. For 5 years, SPARCO and SADaCC have been collecting basic clinical and demographic data from Nigeria, Tanzania, and Ghana. The resulting database will support analyses to estimate significant clinical events and provide directions for targeting interventions and assessing their impacts. Method: The Nigerian study sited at Centre of Excellence for Sickle Cell Disease Research and Training (CESRTA), University of Abuja, adopted REDCap for online database management. The case report form (CRF) was adapted from 1,400 data elements adopted by SPARCO sites. It captures 215 data elements of interest across sub-sites, i.e., demographic, social, diagnostic, clinical, laboratory, imaging, and others. These were harmonized using the SADaCC data dictionary. REDCap was installed on University of Abuja cloud server at https://www.redcap.uniabuja.edu.ng. Data collected at the sites are sent to CESRTA for collation, cleaning and uploading to the database. Results: 7,767 people living with sickle cell disease were enrolled at 25 health institutions across the six zones in Nigeria with 5,295 having had at least one follow-up visit with their clinical data updated. They range from 44 to 1,180 from 3 centers from South East, 4 from South, 5 from South West, 8 from North Central, 4 in North West and 3 in the North East. North West has registered 1,383 patients, representing 17.8%; North East, 359 (4.6%); North Central, 2,947 (37.9%); South West, 1,609 (20.7%); South, 442 (5.7%) and South East, 1,027 patients (13.2%). Conclusion: The database is being used to support studies including analysis of clinical phenotypes of SCD in Nigeria, and evaluation of Hydroxyurea use in SCD. Reports undergoing review in journals have relied on the ease of data access in REDCap. The database is regularly updated by batch and individual record uploads while we are utilizing REDCap's in-built functions to generate simple statistic.

Clinical characteristics and risk factors of relative systemic hypertension and hypertension among sickle cell patients in Cameroon.

Increased blood pressure (BP) has been associated with higher risk of stroke and mortality in Sickle Cell Disease (SCD). We investigated risk factors associated with Relative Systemic Hypertension (RSH) or systemic hypertension in SCD patients in Cameroon. Using R, Multivariate multinomial logistic regression modeling was used to examine the effects of the demographic, anthropometric, clinical, and laboratory factors to determine risk factors. A total of 815 individuals with SCD, including 380 (46.6%) males were analyzed. At baseline, the median age [interquartile range] was 18.0 [12.0-25.0] years, ranging from 3 to 66 years. Approximately three-quarters of the patients (n = 645; 79.1%) had normal BP, 151 (18.5%) had RSH and 19 (2.3%) had hypertension. Age (P < 0.001) and gender (P = 0.022) were significantly different across the BP categories. Weight (P < 0.001), height (P < 0.001), BMI (P < 0.001), pulse pressure (P = 0.020), history of stroke (P = 0.012), hemoglobin level (P = 0.002), red blood cell count (P = 0.031), creatinine (P < 0.001), and (estimated glomerular filtration rate) eGFR (P = 0.002) was also significantly different across the three BP categories. After adjustment, the significantly associated factors of RSH in the SCD patients were age [OR = 1.03, (95% CI = 1.01-1.06), P < 0.010], male gender [OR = 1.54, (95% CI = 1.04-2.27), P = 0.029], BMI [OR = 1.10, (95% CI = 1.04-1.17), P = 0.001]. After adjustment, the independent variables significantly associated factors of Hypertension in the SCD patients were age [OR = 1.05, (95% CI = 1.01-1.10), P = 0.034], male gender [OR = 3.31, (95% CI = 1.04-10.52), P = 0.042], BMI [OR = 1.14, (95% CI = 1.01-1.29), P = 0.027]. Creatinine was significantly associated with RSH [OR =1.31 (1.05-1.63), P = 0.016]. SCD patients with RSH or hypertension maybe at increased risk of renal dysfunction. We found relatively high prevalence of RSH and hypertension (20.8%) in SCD patients in Cameroon. Tailored Interventions that consider major risk factors (age, gender, and BMI) may lower BP pressure and prevent severe complications.

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.

The Sickle Cell Disease Ontology: recent development and expansion of the universal sickle cell knowledge representation.

The Sickle Cell Disease (SCD) Ontology (SCDO, https://scdontology.h3abionet.org/) provides a comprehensive knowledge base of SCD management, systems and standardized human and machine-readable resources that unambiguously describe terminology and concepts about SCD for researchers, patients and clinicians. The SCDO was launched in 2016 and is continuously updated in quantity, as well as in quality, to effectively support the curation of SCD research, patient databasing and clinical informatics applications. SCD knowledge from the scientific literature is used to update existing SCDO terms and create new terms where necessary. Here, we report major updates to the SCDO, from December 2019 until April 2021, for promoting interoperability and facilitating SCD data harmonization, sharing and integration across different studies and for retrospective multi-site research collaborations. SCDO developers continue to collaborate with the SCD community, clinicians and researchers to improve specific ontology areas and expand standardized descriptions to conditions influencing SCD phenotypic expressions and clinical manifestations of the sickling process, e.g. thalassemias. Database URL: https://scdontology.h3abionet.org/.

Establishing a Sickle Cell Disease Registry in Africa: Experience From the Sickle Pan-African Research Consortium, Kumasi-Ghana.

Sickle cell disease (SCD) is the most common clinically significant hemoglobinopathy, characterized by painful episodes, anemia, high risk of infection, and other acute and chronic complications. In Africa, where the disease is most prevalent, large longitudinal data on patients and their outcomes are lacking. This article describes the experiences of the Kumasi Center for SCD at the Komfo Anokye Teaching Hospital (KCSCD-KATH), a Sickle Pan-African Research Consortium (SPARCO) site and a SickleInAfrica Consortium member, in establishing a SCD registry for the evaluation of the outcomes of patients. It also provides a report of a preliminary analysis of the data. The process of developing the registry database involved comprehensive review of the center's SCD patient medical records, incorporating data elements developed by the SickleInAfrica Consortium and obtaining ethical clearance from the local Institutional Review Board. From December 2017 to March 2020, 3,148 SCD patients were enrolled into the SCD registry. Enrollment was during the SCD outpatient clinic visits or through home visits. A significant proportion of the patients was from the newborn screening cohort (50.3%) and was males (52.9%). SCD-SS, SCD-SC, and Sß +thalassemia were seen in 67.2, 32.5, and 0.3% patients, respectively. The majority of the patients were in a steady state at enrollment; however, some were enrolled after discharge for an acute illness admission. The top two clinical diagnoses for SCD-SS patients were sickle cell painful events and acute anemia secondary to hyperhemolysis with incidence rates of 141.86 per 10,000 person months of observation (PMO) and 32.74 per 10,000 PMO, respectively. In SCD-SC patients, the top two diagnoses were sickle cell painful events and avascular necrosis with incidence rates of 203.09 per 10,000 PMO and 21.19 per 10,000 PMO, respectively. The SPARCO Kumasi site has developed skills and infrastructure to design, manage, and analyze data in the SCD registry. The newborn screening program and alternative recruitment methods such as radio announcement and home visits for defaulting patients were the key steps taken in enrolling patients into the registry. The registry will provide longitudinal data that will help improve knowledge of SCD in Ghana and Africa through research.

Factors associated with blood pressure variation in sickle cell disease patients: a systematic review and meta-analyses.

OBJECTIVES: Blood pressure (BP) values ≥120/70 mmHg considerably increase the risk of pulmonary hypertension and renal dysfunction in Sickle Cell Disease (CSD) patients and ultimately increased morbidity and mortality. This has led to the development of the term relative systemic hypertension (RSH). RSH was defined as Systolic BP 120-139 mm Hg or diastolic BP 70-89 mm Hg, whereas systemic hypertension is defined as Systolic BP ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg. Systematic identification of BP variations and risk factors in SCD patients could promote effective management. This review aimed to identify factors associated with BP variation among SCD patients. METHODS: We searched PubMed, Scopus, Web of Science, and Google Scholar up to December 2020 with no geographical or language restrictions. Two reviewers independently screened and summarized data from eligible studies. RESULTS: Advancing age, gender, higher body weight, hemoglobin, eGFR, triglycerides, greater hematocrit, higher blood viscosity, history of blood transfusion, and targeted variants in DRD2 and MIR4301 genes were independently associated with the risk of hypertension in SCD patients. CONCLUSION: Interventions that consider these risk factors may potentially contribute to lower BP pressure in SCD patients and prevent the development of severe complications.

Network-driven analysis of human-Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets.

BACKGROUND: The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery. METHODS: This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein-protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis. RESULTS: This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host-pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways subverted by P. falciparum to increase its within-host survival. CONCLUSIONS: Host-pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies.

Reviewing and assessing existing meta-analysis models and tools.

Over the past few years, meta-analysis has become popular among biomedical researchers for detecting biomarkers across multiple cohort studies with increased predictive power. Combining datasets from different sources increases sample size, thus overcoming the issue related to limited sample size from each individual study and boosting the predictive power. This leads to an increased likelihood of more accurately predicting differentially expressed genes/proteins or significant biomarkers underlying the biological condition of interest. Currently, several meta-analysis methods and tools exist, each having its own strengths and limitations. In this paper, we survey existing meta-analysis methods, and assess the performance of different methods based on results from different datasets as well as assessment from prior knowledge of each method. This provides a reference summary of meta-analysis models and tools, which helps to guide end-users on the choice of appropriate models or tools for given types of datasets and enables developers to consider current advances when planning the development of new meta-analysis models and more practical integrative tools.

Investigations of Kidney Dysfunction-Related Gene Variants in Sickle Cell Disease Patients in Cameroon (Sub-Saharan Africa).

BACKGROUND: Renal dysfunctions are associated with increased morbidity and mortality in sickle cell disease (SCD). Early detection and subsequent management of SCD patients at risk for renal failure and dysfunctions are essential, however, predictors that can identify patients at risk of developing renal dysfunction are not fully understood. METHODS: In this study, we have investigated the association of 31 known kidney dysfunctions-related variants detected in African Americans from multi-ethnic genome wide studies (GWAS) meta-analysis, to kidney-dysfunctions in a group of 413 Cameroonian patients with SCD. Systems level bioinformatics analyses were performed, employing protein-protein interaction networks to further interrogate the putative associations. RESULTS: Up to 61% of these patients had micro-albuminuria, 2.4% proteinuria, 71% glomerular hyperfiltration, and 5.9% had renal failure. Six variants are significantly associated with the two quantifiable phenotypes of kidney dysfunction (eGFR and crude-albuminuria): A1CF-rs10994860 (P = 0.02020), SYPL2-rs12136063 (P = 0.04208), and APOL1 (G1)-rs73885319 (P = 0.04610) are associated with eGFR; and WNT7A-rs6795744 (P = 0.03730), TMEM60-rs6465825 (P = 0.02340), and APOL1 (G2)-rs71785313 (P = 0.03803) observed to be protective against micro-albuminuria. We identified a protein-protein interaction sub-network containing three of these gene variants: APOL1, SYPL2, and WNT7A, connected to the Nuclear factor NF-kappa-B p105 subunit (NFKB1), revealed to be essential and might indirectly influence extreme phenotypes. Interestingly, clinical variables, including body mass index (BMI), systolic blood pressure, vaso-occlusive crisis (VOC), and haemoglobin (Hb), explain better the kidney phenotypic variations in this SCD population. CONCLUSION: This study highlights a strong contribution of haematological indices (Hb level), anthropometric variables (BMI, blood pressure), and clinical events (i.e., vaso-occlusive crisis) to kidney dysfunctions in SCD, rather than known genetic factors. Only 6/31 characterised gene-variants are associated with kidney dysfunction phenotypes in SCD samples from Cameroon. The data reveal and emphasise the urgent need to extend GWAS studies in populations of African ancestries living in Africa, and particularly for kidney dysfunctions in SCD.

Simulation of African and non-African low and high coverage whole genome sequence data to assess variant calling approaches.

Current variant calling (VC) approaches have been designed to leverage populations of long-range haplotypes and were benchmarked using populations of European descent, whereas most genetic diversity is found in non-European such as Africa populations. Working with these genetically diverse populations, VC tools may produce false positive and false negative results, which may produce misleading conclusions in prioritization of mutations, clinical relevancy and actionability of genes. The most prominent question is which tool or pipeline has a high rate of sensitivity and precision when analysing African data with either low or high sequence coverage, given the high genetic diversity and heterogeneity of this data. Here, a total of 100 synthetic Whole Genome Sequencing (WGS) samples, mimicking the genetics profile of African and European subjects for different specific coverage levels (high/low), have been generated to assess the performance of nine different VC tools on these contrasting datasets. The performances of these tools were assessed in false positive and false negative call rates by comparing the simulated golden variants to the variants identified by each VC tool. Combining our results on sensitivity and positive predictive value (PPV), VarDict [PPV = 0.999 and Matthews correlation coefficient (MCC) = 0.832] and BCFtools (PPV = 0.999 and MCC = 0.813) perform best when using African population data on high and low coverage data. Overall, current VC tools produce high false positive and false negative rates when analysing African compared with European data. This highlights the need for development of VC approaches with high sensitivity and precision tailored for populations characterized by high genetic variations and low linkage disequilibrium.

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.

IHP-PING-generating integrated human protein-protein interaction networks on-the-fly.

Advances in high-throughput sequencing technologies have resulted in an exponential growth of publicly accessible biological datasets. In the 'big data' driven 'post-genomic' context, much work is being done to explore human protein-protein interactions (PPIs) for a systems level based analysis to uncover useful signals and gain more insights to advance current knowledge and answer specific biological and health questions. These PPIs are experimentally or computationally predicted, stored in different online databases and some of PPI resources are updated regularly. As with many biological datasets, such regular updates continuously render older PPI datasets potentially outdated. Moreover, while many of these interactions are shared between these online resources, each resource includes its own identified PPIs and none of these databases exhaustively contains all existing human PPI maps. In this context, it is essential to enable the integration of or combining interaction datasets from different resources, to generate a PPI map with increased coverage and confidence. To allow researchers to produce an integrated human PPI datasets in real-time, we introduce the integrated human protein-protein interaction network generator (IHP-PING) tool. IHP-PING is a flexible python package which generates a human PPI network from freely available online resources. This tool extracts and integrates heterogeneous PPI datasets to generate a unified PPI network, which is stored locally for further applications.

The Sickle Cell Disease Ontology: Enabling Collaborative Research and Co-Designing of New Planetary Health Applications.

Sickle cell disease (SCD) is one of the most common blood disorders impacting planetary health. Over 300,000 newborns are diagnosed with SCD each year globally, with an increasing trend. The sickle cell disease ontology (SCDO) is the most comprehensive multidisciplinary SCD knowledge portal. The SCDO was collaboratively developed by the SCDO working group, which includes experts in SCD and data standards from across the globe. This expert review presents highlights and lessons learned from the fourth SCDO workshop that marked the beginning of applications toward planetary health impact, and with an eye to empower and cultivate multisite SCD collaborative research. The workshop was organized by the Sickle Africa Data Coordinating Center (SADaCC) and attended by 44 participants from 14 countries, with 2 participants connecting remotely. Notably, from the standpoint of democratizing and innovating scientific meeting design, an SCD patient advocate also presented at the workshop, giving a broader real-life perspective on patients' aspirations, needs, and challenges. A major component of the workshop was new approaches to harness SCDO to harmonize data elements used by different studies. This was facilitated by a web-based platform onto which participants uploaded data elements from previous or ongoing SCD-relevant research studies before the workshop, making multisite collaborative research studies based on existing SCD data possible, including multisite cohort, SCD global clinical trials, and SCD community engagement approaches. Trainees presented proposals for systematic literature reviews in key SCD research areas. This expert review emphasizes potential and prospects of SCDO-enabled data standards and harmonization to facilitate large-scale global SCD collaborative initiatives. As the fields of public and global health continue to broaden toward planetary health, the SCDO is well poised to play a prominent role to decipher SCD pathophysiology further, and co-design diagnostics and therapeutics innovation in the field.

High-depth African genomes inform human migration and health.

The African continent is regarded as the cradle of modern humans and African genomes contain more genetic variation than those from any other continent, yet only a fraction of the genetic diversity among African individuals has been surveyed1. Here we performed whole-genome sequencing analyses of 426 individuals-comprising 50 ethnolinguistic groups, including previously unsampled populations-to explore the breadth of genomic diversity across Africa. We uncovered more than 3 million previously undescribed variants, most of which were found among individuals from newly sampled ethnolinguistic groups, as well as 62 previously unreported loci that are under strong selection, which were predominantly found in genes that are involved in viral immunity, DNA repair and metabolism. We observed complex patterns of ancestral admixture and putative-damaging and novel variation, both within and between populations, alongside evidence that Zambia was a likely intermediate site along the routes of expansion of Bantu-speaking populations. Pathogenic variants in genes that are currently characterized as medically relevant were uncommon-but in other genes, variants denoted as 'likely pathogenic' in the ClinVar database were commonly observed. Collectively, these findings refine our current understanding of continental migration, identify gene flow and the response to human disease as strong drivers of genome-level population variation, and underscore the scientific imperative for a broader characterization of the genomic diversity of African individuals to understand human ancestry and improve health.

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.