Prediction of HLA class II alleles using SNPs in an African population

BACKGROUND: Despite the importance of the human leukocyte antigen (HLA) gene locus in research and clinical practice, direct HLA typing is laborious and expensive. Furthermore, the analysis requires specialized software and expertise which are unavailable in most developing country settings. Recently, in silico methods have been developed for predicting HLA alleles using single nucleotide polymorphisms (SNPs). However, the utility of these methods in African populations has not been systematically evaluated. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we investigate prediction of HLA class II (HLA-DRB1 and HLA-DQB1) alleles using SNPs in the Wolaita population, southern Ethiopia. The subjects comprised 297 Ethiopians with genome-wide SNP data, of whom 188 had also been HLA typed and were used for training and testing the model. The 109 subjects with SNP data alone were used for empirical prediction using the multi-allelic gene prediction method. We evaluated accuracy of the prediction, agreement between predicted and HLA typed alleles, and discriminative ability of the prediction probability supplied by the model. We found that the model predicted intermediate (two-digit) resolution for HLA-DRB1 and HLA-DQB1 alleles at accuracy levels of 96% and 87%, respectively. All measures of performance showed high accuracy and reliability for prediction. The distribution of the majority of HLA alleles in the study was similar to that previously reported for the Oromo and Amhara ethnic groups from Ethiopia. CONCLUSIONS/SIGNIFICANCE: We demonstrate that HLA class II alleles can be predicted from SNP genotype data with a high level of accuracy at intermediate (two-digit) resolution in an African population. This finding offers new opportunities for HLA studies of disease epidemiology and population genetics in developing countrie

Influence of Fetal and Maternal Genetic Susceptibility to Obesity on Birthweight in African Ancestry Populations

Fetal and maternal genetic propensity to obesity can influence birthweight. We investigated the effects of fetal and maternal genetic risk of obesity on birthweight and evaluated whether these genetic influences modify the well-known association between maternal pre-pregnancy body mass index (BMI) and birthweight. In 950 mother-baby pairs of African ancestry, a genetic risk score for adulthood obesity was generated for mothers (mGRS) and their babies (bGRS) as the weighted sum of BMI-increasing alleles of 97 single nucleotide polymorphisms known to be associated with BMI. The median GRS value was used as a cut-off to define high or low bGRS and mGRS. High bGRS was significantly associated with 70 g lower birthweight (95% Confidence Interval [CI] = −127.4 to −12.4) compared to low bGRS. mGRS was positively correlated with birthweight but the association was not significant. mGRS modified the significant birthweight-increasing effect of maternal pre-pregnancy BMI (P-for-interaction = 0.03); among mothers with low mGRS, those who were overweight or obese had 127.7 g heavier babies (95% CI = 27.1 to 228.2) compared to those who had normal weight. In summary, fetal obesity genetic risk loci exert direct influence on birthweight, and maternal loci modify the effect of pre-pregnancy BMI on birthweight

DNA methylation loci in placenta associated with birthweight and expression of genes relevant for early development and adult diseases

Background Birthweight marks an important milestone of health across the lifespan, including cardiometabolic disease risk in later life. The placenta, a transient organ at the maternal-fetal interface, regulates fetal growth. Identifying genetic loci where DNA methylation in placenta is associated with birthweight can unravel genomic pathways that are dysregulated in aberrant fetal growth and cardiometabolic diseases in later life. Results We performed placental epigenome-wide association study (EWAS) of birthweight in an ethnic diverse cohort of pregnant women (n = 301). Methylation at 15 cytosine-(phosphate)-guanine sites (CpGs) was associated with birthweight (false discovery rate (FDR) < 0.05). Methylation at four (26.7%) CpG sites was associated with placental transcript levels of 15 genes (FDR < 0.05), including genes known to be associated with adult lipid traits, inflammation and oxidative stress. Increased methylation at cg06155341 was associated with higher birthweight and lower FOSL1 expression, and lower FOSL1 expression was correlated with higher birthweight. Given the role of the FOSL1 transcription factor in regulating developmental processes at the maternal-fetal interface, epigenetic mechanisms at this locus may regulate fetal development. We demonstrated trans-tissue portability of methylation at four genes (MLLT1, PDE9A, ASAP2, and SLC20A2) implicated in birthweight by a previous study in cord blood. We also found that methylation changes known to be related to maternal underweight, preeclampsia and adult type 2 diabetes were associated with lower birthweight in placenta. Conclusion We identified novel placental DNA methylation changes associated with birthweight. Placental epigenetic mechanisms may underlie dysregulated fetal development and early origins of adult cardiometabolic diseases. Clinical trial registration ClinicalTrials.gov, NCT0091213

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations

Burden of podoconiosis in poor rural communities in Guliso woreda, western Ethiopia

Background. Podoconiosis is an environmental lymphoedema affecting people living and working barefoot on irritant red clay soil. Podoconiosis is relatively well described in southern Ethiopia, but remains neglected in other parts of the Ethiopian highlands. This study aimed to assess the burden of podoconiosis in rural communities in western Ethiopia. Methodology/Principal Findings. A cross-sectional study was conducted in Gulliso woreda (district), west Ethiopia. A household survey in the 26 rural kebeles (villages) of this district was conducted to identify podoconiosis patients and to measure disease prevalence. A more detailed study was done in six randomly selected kebeles to describe clinical features of the disease, patients’ experiences of foot hygiene, and shoe wearing practice. 1,935 cases of podoconiosis were registered, giving a prevalence of 2.8%. The prevalence was higher in those aged 15 – 64 years (5.2%) and in females than males (prevalence ratio 2.6:1). 90.3% of patients were in the 15 – 64 year age group. In the detailed study, 335 cases were interviewed and their feet assessed. The majority of patients were farmers, uneducated, and poor. Two-third of patients developed the disease before the age of thirty. Almost all patients (97.0%) had experienced adenolymphangitis (ALA - red, hot legs, swollen and painful groin) at least once during the previous year. Patients experienced an average of 5.5 ALA episodes annually, each of average 4.4 days, thus 24 working days were lost annually. The incidence of ALA in podoconiosis patients was higher than that reported for filariasis in other countries. Shoe wearing was limited mainly due to financial problems. Conclusions. We have documented high podoconiosis prevalence, frequent adenolymphangitis and high disease-related morbidity in west Ethiopia. Interventions must be developed to prevent, treat and control podoconiosis, one of the core neglected tropical diseases in Ethiopia

Detecting and staging podoconiosis cases in North West Cameroon: positive predictive value of clinical screening of patients by community health workers and researchers

Background The suitability of using clinical assessment to identify patients with podoconiosis in endemic communities has previously been demonstrated. In this study, we explored the feasibility and accuracy of using Community Health Implementers (CHIs) for the large scale clinical screening of the population for podoconiosis in North-west Cameroon. Methods Before a regional podoconiosis mapping, 193 CHIs and 50 health personnel selected from 6 health districts were trained in the clinical diagnosis of the disease. After training, CHIs undertook community screening for podoconiosis patients under health personnel supervision. Identified cases were later re-examined by a research team with experience in the clinical identification of podoconiosis. Results Cases were identified by CHIs with an overall positive predictive value (PPV) of 48.5% [34.1–70%]. They were more accurate in detecting advanced stages of the disease compared to early stages; OR 2.07, 95% CI = 1.15–3.73, p = 0.015 for all advanced stages). Accuracy of detecting cases showed statistically significant differences among health districts (χ2 = 25.30, p = 0.0001). Conclusion Podoconiosis being a stigmatized disease, the use of CHIs who are familiar to the community appears appropriate for identifying cases through clinical diagnosis. However, to improve their effectiveness and accuracy, more training, supervision and support are required. More emphasis must be given in identifying early clinical stages and in health districts with relatively lower PPVs

The African Genome Variation Project shapes medical genetics in Africa.

Given the importance of Africa to studies of human origins and disease susceptibility, detailed characterization of African genetic diversity is needed. The African Genome Variation Project provides a resource with which to design, implement and interpret genomic studies in sub-Saharan Africa and worldwide. The African Genome Variation Project represents dense genotypes from 1,481 individuals and whole-genome sequences from 320 individuals across sub-Saharan Africa. Using this resource, we find novel evidence of complex, regionally distinct hunter-gatherer and Eurasian admixture across sub-Saharan Africa. We identify new loci under selection, including loci related to malaria susceptibility and hypertension. We show that modern imputation panels (sets of reference genotypes from which unobserved or missing genotypes in study sets can be inferred) can identify association signals at highly differentiated loci across populations in sub-Saharan Africa. Using whole-genome sequencing, we demonstrate further improvements in imputation accuracy, strengthening the case for large-scale sequencing efforts of diverse African haplotypes. Finally, we present an efficient genotype array design capturing common genetic variation in Africa

Pleiotropic genes for metabolic syndrome and inflammation

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18–2.01) and European sample: OR = 1.75 (95% CI: 1.30–2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61–4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD