Complimentary Methods for Multivariate Genome-Wide Association Study Identify New Susceptibility Genes for Blood Cell Traits.

Genome-wide association studies (GWAS) have found hundreds of novel loci associated with full blood count (FBC) phenotypes. However, most of these studies were performed in a single phenotype framework without putting into consideration the clinical relatedness among traits. In this work, in addition to the standard univariate GWAS, we also use two different multivariate methods to perform the first multiple traits GWAS of FBC traits in ∼7000 individuals from the Ugandan General Population Cohort (GPC). We started by performing the standard univariate GWAS approach. We then performed our first multivariate method, in this approach, we tested for marker associations with 15 FBC traits simultaneously in a multivariate mixed model implemented in GEMMA while accounting for the relatedness of individuals and pedigree structures, as well as population substructure. In this analysis, we provide a framework for the combination of multiple phenotypes in multivariate GWAS analysis and show evidence of multi-collinearity whenever the correlation between traits exceeds the correlation coefficient threshold of r 2 >=0.75. This approach identifies two known and one novel loci. In the second multivariate method, we applied principal component analysis (PCA) to the same 15 correlated FBC traits. We then tested for marker associations with each PC in univariate linear mixed models implemented in GEMMA. We show that the FBC composite phenotype as assessed by each PC expresses information that is not completely encapsulated by the individual FBC traits, as this approach identifies three known and five novel loci that were not identified using both the standard univariate and multivariate GWAS methods. Across both multivariate methods, we identified six novel loci. As a proof of concept, both multivariate methods also identified known loci, HBB and ITFG3. The two multivariate methods show that multivariate genotype-phenotype methods increase power and identify novel genotype-phenotype associations not found with the standard univariate GWAS in the same dataset

Genome-Wide Association Study of Cryptosporidiosis in Infants Implicates PRKCA.

Diarrhea is a major cause of both morbidity and mortality worldwide, especially among young children. Cryptosporidiosis is a leading cause of diarrhea in children, particularly in South Asia and sub-Saharan Africa, where it is responsible for over 200,000 deaths per year. Beyond the initial clinical presentation of diarrhea, it is associated with long-term sequelae such as malnutrition and neurocognitive developmental deficits. Risk factors include poverty and overcrowding, and yet not all children with these risk factors and exposure are infected, nor do all infected children develop symptomatic disease. One potential risk factor to explain these differences is their human genome. To identify genetic variants associated with symptomatic cryptosporidiosis, we conducted a genome-wide association study (GWAS) examining 6.5 million single nucleotide polymorphisms (SNPs) in 873 children from three independent cohorts in Dhaka, Bangladesh, namely, the Dhaka Birth Cohort (DBC), the Performance of Rotavirus and Oral Polio Vaccines in Developing Countries (PROVIDE) study, and the Cryptosporidiosis Birth Cohort (CBC). Associations were estimated separately for each cohort under an additive model, adjusting for length-for-age Z-score at 12 months of age, the first two principal components to account for population substructure, and genotyping batch. The strongest meta-analytic association was with rs58296998 (P = 3.73 × 10-8), an intronic SNP and expression quantitative trait locus (eQTL) of protein kinase C alpha (PRKCA). Each additional risk allele conferred 2.4 times the odds of Cryptosporidium-associated diarrhea in the first year of life. This genetic association suggests a role for protein kinase C alpha in pediatric cryptosporidiosis and warrants further investigation.IMPORTANCE Globally, diarrhea remains one of the major causes of pediatric morbidity and mortality. The initial symptoms of diarrhea can often lead to long-term consequences for the health of young children, such as malnutrition and neurocognitive developmental deficits. Despite many children having similar exposures to infectious causes of diarrhea, not all develop symptomatic disease, indicating a possible role for human genetic variation. Here, we conducted a genetic study of susceptibility to symptomatic disease associated with Cryptosporidium infection (a leading cause of diarrhea) in three independent cohorts of infants from Dhaka, Bangladesh. We identified a genetic variant within protein kinase C alpha (PRKCA) associated with higher risk of cryptosporidiosis in the first year of life. These results indicate a role for human genetics in susceptibility to cryptosporidiosis and warrant further research to elucidate the mechanism

Progress in the Prediction of pKa Values in Proteins

The pKa-cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pKa values and protein electrostatics in general. The first round of the pKa-cooperative, which challenged computational labs to carry out blind predictions against pKas experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6–10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pKa calculations, emphasizing methods that were used by the participants in calculating the blind pKa values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pKa calculations

Genome-wide association study of type 2 diabetes in Africa

Abstract: Aims/hypothesis: Genome-wide association studies (GWAS) for type 2 diabetes have uncovered >400 risk loci, primarily in populations of European and Asian ancestry. Here, we aimed to discover additional type 2 diabetes risk loci (including African-specific variants) and fine-map association signals by performing genetic analysis in African populations. Methods: We conducted two type 2 diabetes genome-wide association studies in 4347 Africans from South Africa, Nigeria, Ghana and Kenya and meta-analysed both studies together. Likely causal variants were identified using fine-mapping approaches. Results: The most significantly associated variants mapped to the widely replicated type 2 diabetes risk locus near TCF7L2 (p = 5.3 × 10−13). Fine-mapping of the TCF7L2 locus suggested one type 2 diabetes association signal shared between Europeans and Africans (indexed by rs7903146) and a distinct African-specific signal (indexed by rs17746147). We also detected one novel signal, rs73284431, near AGMO (p = 5.2 × 10−9, minor allele frequency [MAF] = 0.095; monomorphic in most non-African populations), distinct from previously reported signals in the region. In analyses focused on 100 published type 2 diabetes risk loci, we identified 21 with shared causal variants in African and non-African populations. Conclusions/interpretation: These results demonstrate the value of performing GWAS in Africans, provide a resource to larger consortia for further discovery and fine-mapping and indicate that additional large-scale efforts in Africa are warranted to gain further insight in to the genetic architecture of type 2 diabetes

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

ZRANB3 is an African-specific type 2 diabetes locus associated with beta-cell mass and insulin response

Abstract: Genome analysis of diverse human populations has contributed to the identification of novel genomic loci for diseases of major clinical and public health impact. Here, we report a genome-wide analysis of type 2 diabetes (T2D) in sub-Saharan Africans, an understudied ancestral group. We analyze ~18 million autosomal SNPs in 5,231 individuals from Nigeria, Ghana and Kenya. We identify a previously-unreported genome-wide significant locus: ZRANB3 (Zinc Finger RANBP2-Type Containing 3, lead SNP p = 2.831 × 10−9). Knockdown or genomic knockout of the zebrafish ortholog results in reduction in pancreatic β-cell number which we demonstrate to be due to increased apoptosis in islets. siRNA transfection of murine Zranb3 in MIN6 β-cells results in impaired insulin secretion in response to high glucose, implicating Zranb3 in β-cell functional response to high glucose conditions. We also show transferability in our study of 32 established T2D loci. Our findings advance understanding of the genetics of T2D in non-European ancestry populations

Distinct genetic architectures and environmental factors associate with host response to the γ 2-herpesvirus infections

Abstract: Kaposi’s sarcoma-associated herpesvirus (KSHV) and Epstein-Barr Virus (EBV) establish life-long infections and are associated with malignancies. Striking geographic variation in incidence and the fact that virus alone is insufficient to cause disease, suggests other co-factors are involved. Here we present epidemiological analysis and genome-wide association study (GWAS) in 4365 individuals from an African population cohort, to assess the influence of host genetic and non-genetic factors on virus antibody responses. EBV/KSHV co-infection (OR = 5.71(1.58–7.12)), HIV positivity (OR = 2.22(1.32–3.73)) and living in a more rural area (OR = 1.38(1.01–1.89)) are strongly associated with immunogenicity. GWAS reveals associations with KSHV antibody response in the HLA-B/C region (p = 6.64 × 10−09). For EBV, associations are identified for VCA (rs71542439, p = 1.15 × 10−12). Human leucocyte antigen (HLA) and trans-ancestry fine-mapping substantiate that distinct variants in HLA-DQA1 (p = 5.24 × 10−44) are driving associations for EBNA-1 in Africa. This study highlights complex interactions between KSHV and EBV, in addition to distinct genetic architectures resulting in important differences in pathogenesis and transmission

Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa.

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.Main funding: This work was funded by the Wellcome Trust, The Wellcome Sanger Institute (WT098051), the U.K. Medical Research Council (G0901213-92157, G0801566, and MR/K013491/1), and the Medical Research Council/Uganda Virus Research Institute Uganda Research Unit on AIDS core funding

Copyright: Elsevier

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Is Ocean Acidification an Open-Ocean Syndrome? Understanding Anthropogenic Impacts on Seawater pH

Ocean acidification due to anthropogenic CO2 emissions is a dominant driver of long-term changes in pH in the open ocean, raising concern for the future of calcifying organisms, many of which are present in coastal habitats. However, changes in pH in coastal ecosystems result from a multitude of drivers, including impacts from watershed processes, nutrient inputs, and changes in ecosystem structure and metabolism. Interaction between ocean acidification due to anthropogenic CO2 emissions and the dynamic regional to local drivers of coastal ecosystems have resulted in complex regulation of pH in coastal waters. Changes in the watershed can, for example, lead to changes in alkalinity and CO2 fluxes that, together with metabolic processes and oceanic dynamics, yield high-magnitude decadal changes of up to 0.5 units in coastal pH. Metabolism results in strong diel to seasonal fluctuations in pH, with characteristic ranges of 0.3 pH units, with metabolically intense habitats exceeding this range on a daily basis. The intense variability and multiple, complex controls on pH implies that the concept of ocean acidification due to anthropogenic CO2 emissions cannot be transposed to coastal ecosystems directly. Furthermore, in coastal ecosystems, the detection of trends towards acidification is not trivial and the attribution of these changes to anthropogenic CO2 emissions is even more problematic. Coastal ecosystems may show acidification or basification, depending on the balance between the invasion of coastal waters by anthropogenic CO2, watershed export of alkalinity, organic matter and CO2, and changes in the balance between primary production, respiration and calcification rates in response to changes in nutrient inputs and losses of ecosystem components. Hence, we contend that ocean acidification from anthropogenic CO2 is largely an open-ocean syndrome and that a concept of anthropogenic impacts on marine pH, which is applicable across the entire ocean, from coastal to open-ocean environments, provides a superior framework to consider the multiple components of the anthropogenic perturbation of marine pH trajectories. The concept of anthropogenic impacts on seawater pH acknowledges that a regional focus is necessary to predict future trajectories in the pH of coastal waters and points at opportunities to manage these trajectories locally to conserve coastal organisms vulnerable to ocean acidification. © 2013 Coastal and Estuarine Research Federation.This document results from contributions from MEDEICG projects funded by the Spanish Ministry of Economy and Competitiveness (CTM2009-07013), MedSEA of the FP7 of the EU (contract no. FP7-ENV-2010-265103), TEMSPATH Marie Curie Intra European Fellowship of the FP7 of the EU (254297: FP7-PEOPLE-2009-IEF), the CSIRO Marine and Coastal Carbon Biogeochemistry Flagship Cluster, and the Baltic Nest InstitutePeer Reviewe