A computational approach to candidate gene prioritization for X-linked mental retardation using annotation-based binary filtering and motif-based linear discriminatory analysis

<p>Abstract</p> <p>Background</p> <p>Several computational candidate gene selection and prioritization methods have recently been developed. These <it>in silico </it>selection and prioritization techniques are usually based on two central approaches - the examination of similarities to known disease genes and/or the evaluation of functional annotation of genes. Each of these approaches has its own caveats. Here we employ a previously described method of candidate gene prioritization based mainly on gene annotation, in accompaniment with a technique based on the evaluation of pertinent sequence motifs or signatures, in an attempt to refine the gene prioritization approach. We apply this approach to X-linked mental retardation (XLMR), a group of heterogeneous disorders for which some of the underlying genetics is known.</p> <p>Results</p> <p>The gene annotation-based binary filtering method yielded a ranked list of putative XLMR candidate genes with good plausibility of being associated with the development of mental retardation. In parallel, a motif finding approach based on linear discriminatory analysis (LDA) was employed to identify short sequence patterns that may discriminate XLMR from non-XLMR genes. High rates (>80%) of correct classification was achieved, suggesting that the identification of these motifs effectively captures genomic signals associated with XLMR vs. non-XLMR genes. The computational tools developed for the motif-based LDA is integrated into the freely available genomic analysis portal Galaxy (<url>http://main.g2.bx.psu.edu/</url>). Nine genes (<it>APLN</it>, <it>ZC4H2</it>, <it>MAGED4</it>, <it>MAGED4B</it>, <it>RAP2C</it>, <it>FAM156A</it>, <it>FAM156B</it>, <it>TBL1X</it>, and <it>UXT</it>) were highlighted as highly-ranked XLMR methods.</p> <p>Conclusions</p> <p>The combination of gene annotation information and sequence motif-orientated computational candidate gene prediction methods highlight an added benefit in generating a list of plausible candidate genes, as has been demonstrated for XLMR.</p> <p><it>Reviewers: This article was reviewed by Dr Barbara Bardoni (nominated by Prof Juergen Brosius); Prof Neil Smalheiser and Dr Dustin Holloway (nominated by Prof Charles DeLisi).</it></p

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$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

Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome

<p>Abstract</p> <p>Background</p> <p>Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although <it>in utero </it>alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach.</p> <p>Results</p> <p>10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes.</p> <p>Conclusion</p> <p>This analysis highlighted a list of strong candidate genes from the TGF-β, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis.</p

Appetite regulation genes are associated with body mass index in black South African adolescents: a genetic association study

PMID: 22614171 PMCID: PMC3358621BACKGROUND: Obesity is a complex trait with both environmental and genetic contributors. Genome-wide association studies have identified several variants that are robustly associated with obesity and body mass index (BMI), many of which are found within genes involved in appetite regulation. Currently, genetic association data for obesity are lacking in Africans-a single genome-wide association study and a few replication studies have been published in West Africa, but none have been performed in a South African population. OBJECTIVE: To assess the association of candidate loci with BMI in black South Africans. The authors focused on single nucleotide polymorphisms (SNPs) in the FTO, LEP, LEPR, MC4R, NPY2R and POMC genes. DESIGN: A genetic association study. PARTICIPANTS: 990 randomly selected individuals from the larger Birth to Twenty cohort (a longitudinal birth cohort study of health and development in Africans). MEASURES: The authors genotyped 44 SNPs within the six candidate genes that included known BMI-associated SNPs and tagSNPs based on linkage disequilibrium in an African population for FTO, LEP and NPY2R. To assess population substructure, the authors included 18 ancestry informative markers. Weight, height, sex, sex-specific pubertal stage and exact age collected during adolescence (13 years) were used to identify loci that predispose to obesity early in life. RESULTS: Sex, sex-specific pubertal stage and exact age together explain 14.3% of the variation in log(BMI) at age 13. After adjustment for these factors, four SNPs were individually significantly associated with BMI: FTO rs17817449 (p=0.022), LEP rs10954174 (p=0.0004), LEP rs6966536 (p=0.012) and MC4R rs17782313 (p=0.045). Together the four SNPs account for 2.1% of the variation in log(BMI). Each risk allele was associated with an estimated average increase of 2.5% in BMI. CONCLUSIONS: The study highlighted SNPs in FTO and MC4R as potential genetic markers of obesity risk in South Africans. The association with two SNPs in the 3' untranslated region of the LEP gene is novel

Genetic risk score for adult body mass index associations with childhood and adolescent weight gain in an African population

Abstract Background Ninety-seven independent single nucleotide polymorphisms (SNPs) are robustly associated with adult body mass index (BMI kg/m2) in Caucasian populations. The relevance of such variants in African populations at different stages of the life course (such as childhood) is unclear. We tested whether a genetic risk score composed of the aforementioned SNPs was associated with BMI from infancy to early adulthood. We further tested whether this genetic effect was mediated by conditional weight gain at different growth periods. We used data from the Birth to Twenty Plus Cohort (Bt20+), for 971 urban South African black children from birth to 18 years. DNA was collected at 13 years old and was genotyped using the Metabochip (Illumina) array. The weighted genetic risk score (wGRS) for BMI was constructed based on 71 of the 97 previously reported SNPs. Results The cross-sectional association between the wGRS and BMI strengthened with age from 5 to 18 years. The significant associations were observed from 11 to 18 years, and peak effect sizes were observed at 13 and 14 years of age. Results from the linear mixed effects models showed significant interactions between the wGRS and age on longitudinal BMI but no such interactions were observed in sex and the wGRS. A higher wGRS was associated with an increased relative risk of belonging to the early onset obese longitudinal BMI trajectory (relative risk = 1.88; 95%CI 1.28 to 2.76) compared to belonging to a normal longitudinal BMI trajectory. Adolescent conditional relative weight gain had a suggestive mediation effect of 56% on the association between wGRS and obesity risk at 18 years. Conclusions The results suggest that genetic susceptibility to higher adult BMI can be tracked from childhood in this African population. This supports the notion that prevention of adult obesity should begin early in life. The genetic risk score combined with other non-genetic risk factors, such as BMI trajectory membership in our case, has the potential to be used to screen for early identification of individuals at increased risk of obesity and other related NCD risk factors in order to reduce the adverse health risk outcomes later

Glucocorticoids associate with cardiometabolic risk factors in black South Africans

Circulating glucocorticoids are associated with metabolic syndrome and related cardiometabolic risk factors in non-Africans. This study investigated these associations in Africans, whose metabolic phenotype reportedly differs from Europeans. Adiposity, blood pressure, glycaemia, insulin resistance, and lipid profile, were measured in 316 African men and 788 African women living in Soweto, Johannesburg. The 2009 harmonized criteria were used to define metabolic syndrome. Serum glucocorticoids were measured using liquid chromatography-mass spectrometry. Cortisol was associated with greater odds presenting with metabolic syndrome (odds ratio (95% CI) =1.50 (1.04, 2.17) and higher systolic (beta coefficient, β (95% CI) =0.04 (0.01, 0.08)) and diastolic (0.05 (0.02, 0.09)) blood pressure, but higher HDL (0.10 (0.02, 0.19)) and lower LDL (−0.14 (−0.24, −0.03)) cholesterol concentrations, in the combined sample of men and women. In contrast, corticosterone was only associated with higher insulin sensitivity (Matsuda index; 0.22 (0.03, 0.41)), but this was not independent of BMI. Sex-specific associations were observed, such that both cortisol and corticosterone were associated with higher fasting glucose (standardized β (95% CI): 0.24 (0.12, 0.36) for cortisol and 0.12 (0.01, 0.23) for corticosterone) and HbA1c (0.13 (0.01, 0.25) for cortisol and 0.12 (0.01, 0.24) for corticosterone) in men only, but lower HbA1c (0.10 (−0.20, −0.01) for cortisol and −0.09 (−0.18, −0.03) for corticosterone) in women only. Our study reports for the first time that associations between circulating glucocorticoid concentrations and key cardiometabolic risk factors exhibit both glucocorticoid- and sex-specificity in Africans

Implications of direct-to-consumer whole-exome sequencing in South Africa

This editorial examines a number of vitally important ethical, legal and scientific concerns that have to be addressed to ensure proper and ethical implementation of direct-to-consumer whole-exome sequencing in South Africa. Individuals taking part in this endeavour must be fully informed of the positive and negative sequelae

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

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

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