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To accelerate the impact of African genomics on human health, data science skills and awareness of Africa's rich genetic diversity must be strengthened globally. We describe the first African genomics data science workshop, implemented by the African Society of Human Genetics (AfSHG) and international partners, providing a framework for future workshops., Competing Interests: Declaration of interests None declared., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The 11th Congress of the African Society of Human Genetics (AfSHG) was held from September 16, 2018 to September 21, 2018, in conjunction with the 12th Human Heredity and Health in Africa (H3Africa) Consortium meeting in Kigali, Rwanda. The event was organized by the AfSHG in partnership with the Rwanda Society of Human Genetics and the University of Rwanda. A 2-day workshop on the application of next-generation sequencing technologies for analyzing monogenic disease in African populations was organized as part of the conference (September 22, 2018-September 23, 2018, Kigali, Rwanda). The theme of the conference was "Building skills and resources for genomics, epigenetics and bioinformatics research for Africa." The conference served as a platform to bring together members from country-specific Societies of Human Genetics, including Rwanda, Cameroon, Democratic Republic of Congo, Egypt, Mali, Senegal, and South Africa, and included 435 delegates from 38 countries, including 29 African countries that attended the conference. A major topic of discussion was how to bridge the gap between the emerging knowledge on genomics and Omics in African populations. The importance of understanding the role of genetic variation in disease causation and susceptibility among Africans was a constant theme during the meeting, as was the need to develop research infrastructure and resources to enhance healthcare systems, so that they are not left behind in the genomic revolution. It was concluded that there is a need to inspire more African scientists to train and work as investigators, clinicians, and genetic counselors in the field of human genetics in Africa. Local investments, and South-South and South-North collaboration were identified as the key drivers for the successful implementation of research and development on the continent.

The tenth conference of the African Society of Human Genetics was held in Egypt with the theme "Human Genetics and Genomics in Africa: Challenges for Both Rare and Common Genetic Disorders." Current research was presented, and we discussed visions for the future of genomic research on the African continent. In this report, we summarize the presented scientific research within and relevant to Africa as presented by both African and non-African scientists. We also discuss the current situation concerning genomic medicine and genomic research within the continent, difficulties in implementing genetic services and genomic medicine in Africa, and a road map to overcome those difficulties and meet the needs of the African researchers and patients.

We present a comprehensive assessment of genomic diversity in the African-American population by studying three genotyped cohorts comprising 3,726 African-Americans from across the United States that provide a representative description of the population across all US states and socioeconomic status. An estimated 82.1% of ancestors to African-Americans lived in Africa prior to the advent of transatlantic travel, 16.7% in Europe, and 1.2% in the Americas, with increased African ancestry in the southern United States compared to the North and West. Combining demographic models of ancestry and those of relatedness suggests that admixture occurred predominantly in the South prior to the Civil War and that ancestry-biased migration is responsible for regional differences in ancestry. We find that recent migrations also caused a strong increase in genetic relatedness among geographically distant African-Americans. Long-range relatedness among African-Americans and between African-Americans and European-Americans thus track north- and west-bound migration routes followed during the Great Migration of the twentieth century. By contrast, short-range relatedness patterns suggest comparable mobility of ∼15-16km per generation for African-Americans and European-Americans, as estimated using a novel analytical model of isolation-by-distance.

Genome-wide association studies have become a reality in the study of the genetics of complex disease. This technology provides a wealth of genomic information on patient samples, from which we hope to learn novel biology and detect important genetic and environmental factors for disease processes. Because strategies for analyzing these data have not kept pace with the laboratory methods that generate the data it is unlikely that these advances will immediately lead to an improved understanding of the genetic contribution to common human disease and drug response. Currently, no single analytical method will allow us to extract all information from a whole-genome association study. Thus, many novel methods are being proposed and developed. It will be vital for the success of these new methods, to have the ability to simulate datasets consisting of polymorphisms throughout the genome with realistic linkage disequilibrium patterns. Within these datasets, we can embed genetic models of disease whereby we can evaluate the ability of novel methods to detect these simulated effects. This paper describes a new software package, genomeSIM, for the simulation of large-scale genomic data in population based case-control samples. It allows for single SNP, as well as gene-gene interaction models to be associated with disease risk. We describe the algorithm and demonstrate its utility for future genetic studies of whole-genome association.

Purpose: To present evidence of genetic and environmental interactions as they relate to nutrition, diabetes, and obesity., Methods: A review of seminal literature related to genetics, obesity, and diabetes., Findings: Multifactorial interactions are important in the development of nutrition-related disorders, but the challenge remains to explain how these interactions are expressed. Treating subpopulations of people might be important and useful to some extent at present, but in the future treating people of given genetic predispositions and other personal and environmental factors will have greater effects on quality-of-life indicators and life expectancies., Conclusions: Individualization coupled with multifactorial interactions will lead to new and more effective preventive and treatment modalities of nutrition-related disorders. With obesity and diabetes, genomics will bridge the traditional use of diet, exercise, and weight reduction with other environmental factors, ultimately leading to healthier lives.

Background: Tuberculosis (TB) is the most deadly infectious disease globally and is highly prevalent in the developing world. For individuals infected with both Mycobacterium tuberculosis (Mtb) and human immunodeficiency virus (HIV), the risk of active TB is 10% or more annually. Previously, we identified in a genome-wide association study (GWAS) a region on chromosome 5 associated with resistance to TB, which included epigenetic marks that could influence gene regulation. We hypothesized that HIV-infected individuals exposed to Mtb who remain disease free carry epigenetic changes that strongly protect them from active TB.Methods: We conducted a methylome-wide study in HIV-infected, TB-exposed cohorts from Uganda and Tanzania and integrated data from our GWAS.Results: We identified 3 regions of interest that included markers that were differentially methylated between TB cases and controls with latent TB infection: chromosome 1 (RNF220, P = 4 × 10-5), chromosome 2 (between COPS8 and COL6A3, P = 2.7 × 10-5), and chromosome 5 (CEP72, P = 1.3 × 10-5). These methylation results co-localized with associated single-nucleotide polymorphisms (SNPs), methylation QTLs, and methylation × SNP interaction effects. These markers were in regions with regulatory markers for cells involved in TB immunity and/or lung.Conclusions: Epigenetic regulation is a potential biologic factor underlying resistance to TB in immunocompromised individuals that can act in conjunction with genetic variants. [ABSTRACT FROM AUTHOR]

The article focuses on the initiative "Up For A Challenge (U4C)—Stimulating Innovation in Breast Cancer Genetic Epidemiology" by the American organization National Cancer Institute (NCI). Topics discussed include understanding the role of disease risk through genome-wide association studies (GWAS) of the genetic variants of breast cancer, review by National Institutes of Health (NIH) of entries, and chart on U4C entries received.

We present an extension of the two-class multifactor dimensionality reduction (MDR) algorithm that enables detection and characterization of epistatic SNP-SNP interactions in the context of a quantitative trait. The proposed Quantitative MDR (QMDR) method handles continuous data by modifying MDR’s constructive induction algorithm to use a T-test. QMDR replaces the balanced accuracy metric with a T-test statistic as the score to determine the best interaction model. We used a simulation to identify the empirical distribution of QMDR’s testing score. We then applied QMDR to genetic data from the ongoing prospective Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. [ABSTRACT FROM AUTHOR]

Motivation: The sequencing of the human genome has made it possible to identify an informative set of >1 million single nucleotide polymorphisms (SNPs) across the genome that can be used to carry out genome-wide association studies (GWASs). The availability of massive amounts of GWAS data has necessitated the development of new biostatistical methods for quality control, imputation and analysis issues including multiple testing. This work has been successful and has enabled the discovery of new associations that have been replicated in multiple studies. However, it is now recognized that most SNPs discovered via GWAS have small effects on disease susceptibility and thus may not be suitable for improving health care through genetic testing. One likely explanation for the mixed results of GWAS is that the current biostatistical analysis paradigm is by design agnostic or unbiased in that it ignores all prior knowledge about disease pathobiology. Further, the linear modeling framework that is employed in GWAS often considers only one SNP at a time thus ignoring their genomic and environmental context. There is now a shift away from the biostatistical approach toward a more holistic approach that recognizes the complexity of the genotype–phenotype relationship that is characterized by significant heterogeneity and gene–gene and gene–environment interaction. We argue here that bioinformatics has an important role to play in addressing the complexity of the underlying genetic basis of common human diseases. The goal of this review is to identify and discuss those GWAS challenges that will require computational methods. [ABSTRACT FROM PUBLISHER]

Spontaneous preterm birth (<37 weeks gestation-PTB) occurs in ∼12% of pregnancies in the United States, and is the largest contributor to neonatal morbidity and mortality. PTB is a complex disease, potentially induced by several etiologic factors from multiple pathophysiologic pathways. To dissect the genetic risk factors of PTB a large-scale high-throughput candidate gene association study was performed examining 1536 SNP in 130 candidate genes from hypothesized PTB pathways. Maternal and fetal DNA from 370 US Caucasian birth-events (172 cases and 198 controls) was examined. Single locus, haplotype, and multi-locus association analyses were performed separately on maternal and fetal data. For maternal data the strongest associations were found in genes in the complement-coagulation pathway related to decidual hemorrhage in PTB. In this pathway 3 of 6 genes examined had SNPs significantly associated with PTB. These include factor V (FV) that was previously associated with PTB, factor VII (FVII), and tissue plasminogen activator (tPA). The single strongest effect was observed in tPA marker rs879293 with a significant allelic (p = 2.30x10-3) and genotypic association (p = 2.0x10-6) with PTB. The odds ratio (OR) for this SNP was 2.80 [CI 1.77-4.44] for a recessive model. Given that 6 of 8 markers in tPA were statistically significant, sliding window haplotype analyses were performed and revealed an associating 4 marker haplotype in tPA (p = 6.00x10-3). The single strongest effect in fetal DNA was observed in the inflammatory pathway at rs17121510 in the interleukin-10 receptor antagonist (IL-10RA) gene for allele (p = 0.01) and genotype (p = 3.34x10-4). The OR for the IL-10RA genotypic additive model was 1.92 [CI 1.15-3.19] (p = 2.00x10-3). Finally, exploratory multi-locus analyses in the complement and coagulation pathway were performed and revealed a potentially significant interaction between a marker in FV (rs2187952) and FVII (rs3211719) (p<0.001). These results support a role for genes in both the coagulation and inflammation pathways, and potentially different maternal and fetal genetic risks for PTB. [ABSTRACT FROM AUTHOR]

Background and Objectives: The α2A-adrenergic receptor (ADRA2A) plays a central role in the regulation of systemic sympathetic activity and hence cardiovascular responses such as heart rate and blood pressure. The objectives of this study were to systematically search for variants in the ADRA2A gene, to define the gene's haplotype structure, and to examine potential functional effects of these variants.Methods: We examined 5957 base pairs of contiguous sequence of ADRA2A (promoter, exonic, and 3′-flanking region) using polymerase chain reaction to amplify the genomic target, followed by bidirectional sequencing, in 135 healthy subjects (85 white and 50 black subjects). Haplotypes were inferred by use of an expectation-maximization algorithm. Primary (plasma norepinephrine concentration) and secondary (resting heart rate and blood pressure) phenotypes were compared among subjects grouped by individual polymorphisms and haplotypes.Results: We identified 41 variants, including 24 novel variants. On the basis of 9 optimally selected markers, 11 haplotypes in 5 haplotype groups were inferred, representing approximately 99% of the cohort. Two uncommon variants in complete linkage disequilibrium (G>C at −1903 and C>G at −1607, identified in 3 black subjects) were associated with significantly increased plasma norepinephrine concentrations (376.7 ± 6.1 pg/mL versus 218.4 ± 95.0 pg/mL, P = .011). There was no other significant association between genetic variants or any of the haplotypes with phenotypes.Conclusion: We describe novel variants and the haplotype structure of the ADRA2A gene. Common genetic ADRA2A variants are not important determinants of baseline cardiovascular measures (plasma norepinephrine, heart rate, and blood pressure) in healthy volunteers.Clinical Pharmacology & Therapeutics (2006) 79, 173–185; doi: 10.1016/j.clpt.2005.10.006 [ABSTRACT FROM AUTHOR]

An editorial is presented which discusses on the studies of monozygotic twins. in forensic settings. It expresses concern on the potential risks of personally identifying the subjects in the studies, the autonomy, and vulnerability of those whom the framework in the manuscript was applied. It also emphasizes the reason behind presenting the studies after the proof-of-principle cases had been removed.

The article offers information on professor Muntaser Ibrahim of the University of Khartoum in Sudan. Topics include a leading Sudanese geneticist, is internationally recognized for his work on important medical genetics problems, from infectious diseases to cancer; mentions he has been a leader in high profile in Great Britain-funded research initiatives on malaria, tuberculosis and leishmaniasis; and also mentions a dedicated educator with profound impact on the careers of Sudanese students.

Background Recent advances in genotyping techniques and genomic knowledge via the Hap Map and Human Genome projects allow for true Genome-Wide Association (GWA) analysis for common complex diseases such as heart disease, diabetes, and Alzheimer's. A major obstacle in GWA analysis is the prohibitively high cost of genotyping the possibly thousands of individuals necessary to achieve statistical significance of results. One potential solution is to pool the DNA of case and control populations and to determine the genotype allele frequency differences in these populations by pooled allelotyping. While pooling can dramatically save time and money, it also adds sources of error. Our work has created a system process that allows for direct evaluation and comparison of pooled allelotyping to individual genotyping for GWA association analysis of complex disease. Materials and methods Complex disease penetrance functions were calculated for a 3 locus bi-allelic model with additive or multiplicative allelic spectrums using GenomeSIM software [1]. Penetrance probabilities were calculated for genotypes having from 0 to 6 disease-associated alleles. All probability functions used a base penetrance probability of 10% disease risk to account for environmental influences on disease risk. A total of 25,000 individual genotype files were created, each comprised of 10,000 SNPs with 3 disease-associated loci imbedded within. Custom MATLAB scripts were used to make in silico "pseudo-pools" for pooled allelotyping from the individual genotype files. HAPLOVIEW software was used to conduct individual genotyping association analysis [2]. A modified version of the Pooled DNA Analyzer (PDA) program was used for pooled association analysis [3]. Conclusion Power analysis was conducted for individual genotyping and pooled allelotyping with allele frequency estimation error from levels from 1% to 5% (see Figure 1). Our results show that pooling errors have a very large effect on the overall statistical significance of a pooled GWA study. Even a pooling error of 1% shifted the minimum resolvable relative risk (RR) with 80% power from (1.33-1.5) in individual genotyping to (1.5-1.67) in pooling. Pooling with 2% error had a minimum resolvable RR of (1.67-1.83). Pooling with 3% error resolved at RR (2.0-2.33). Further, pooling with 4% and 5% error of was not able to achieve 80% power at any of the levels of relative risk tested. Thus, pooled GWA studies may be limited to resolving complex disease associated variants with medium to high relative risks ratios. [ABSTRACT FROM AUTHOR]

Background & Aims: Germline variations in allele-specific expression (ASE) are associated with highly penetrant familial cancers, but their role in common sporadic cancers is unclear. ASE of adenomatous polyposis coli (APC) is associated with pathogenesis of familial adenomatous polyposis. We investigated whether moderate variations in ASE of APC contribute to common forms of colorectal cancer (CRC). Methods: Denaturing high-performance liquid chromatography was used to analyze germline ASE of APC in blood samples from patients with CRC (cases, n = 53) and controls (n = 68). Means, medians, and variances of ASE were compared. Variants in the APC gene region also were analyzed. Results: The distribution of ASE differed significantly between groups; cases had significantly larger amounts of variance than controls (P = .0004). Risk for CRC increased proportionally with the degree of deviation from the mean. The odds ratio for individuals with levels of ASE that deviated more than 1 standard deviation from the mean was 3.97 (95% confidence interval, 1.71–9.24; P = .001); for those with levels greater than 1.645 standard deviations, the odds ratio was 13.46 (95% confidence interval, 1.76–609.40; P = .005). Sequence analysis revealed that a patient with a high level of ASE who did not have a family history of CRC carried a nonsense mutation in APC (p.Arg216X). Genotype analysis of APC associated multiple single-nucleotide polymorphisms with ASE values and/or variance among cases, but not controls. Cis variants, therefore, might account for some of the variance in ASE of APC. Conclusions: Patients with CRC have a larger variance in germline levels of ASE in APC than controls; large distances from the mean ASE were associated with risk for common forms of CRC. [Copyright &y& Elsevier]

A letter to the editor is presented in response to the article "Race and Genomics" in the March 20, 2003 issue.