368 results for ""10.37717"+DELTAS+Africa+SFA+Foundation+grant+DOI"

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• InterPregGen-GWAS-KAZ-2

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. This dataset includes OmniExpress genotyping of maternal and fetal PE cases and controls from Kazakhstan. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator).

  Dataset EGAD00010001947

• InterPregGen-GWAS-KAZ-3

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. This dataset includes Infinium GSA genotyping of maternal, paternal and fetal PE cases and controls from Kazakhstan. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator).

  Dataset EGAD00010001949

• Gabriella Miller Kids First Pediatric Research Program in Whole Genome Sequencing of African and Asian Orofacial Clefts Case-Parent Triads

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. The focus of this study is to identify novel risk variants for OFC in Africa and Asian OFC case-parent triads through analysis of Whole Genome Sequencing data.

  Study phs001997

• Papuan Genomes: whole genome sequencing

  The genomes of 25 individuals from Papua New Guinea was sequenced to high depth (30x) to address population genetic questions relating to the spread of humans outside of Africa and the peopling of Sahul (the continent of Greater Australia). The study design of this project was to sequence small numbers of genomes from several geographically distinct Papuan groups, focusing on the highland regions that are thought to have been more isolated, to enable comparisons between populations within Papua New Guinea and with Australian Aboriginal populations. Data from this project feed directly into on-going projects on the genetic history of Australia and also serve as a first look at the population genomics of the Papuan highlands.

  Study EGAS00001001247

• Genome Diversity in Africa Project - GemCode libraries (2017-07-05)

  High depth whole genome sequencing from GemCode (10x Genomics) DNA libraries containing long range linkage information for one Baganda trio and one Baganda child (parent already sequenced at high depth). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-07-05.

  Dataset EGAD00001003426

• WGS of liver cancer in the Japanese population

  Hepatocellular carcinoma (HCC) is the third leading cancer-related cause of death and the seventh most common form of cancer worldwide, with an estimate of more than 700,000 new cases each year. The most established risk factors of HCC are chronic HBV and HCV infection. HBV infection is responsible for over 50% of the worldwide attributable risk of HCC, especially in East Asia and Africa, while in Japan and several Western countries HCV infection is the most common risk factor for HCC. To gain insights into the molecular alterations of virus-associated HCC, we performed whole genome sequencing (WGS) of 321 HCC tumors from 159 patients. This work was performed as a part of the ICGC (International Cancer Genome Consortium) project.

  Study EGAS00001000678

• Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR and PEAR-2)

  The primary aim of the Pharmacogenomic Evaluation of Antihypertensive Responses grant (funded by NIH Pharmacogenomic Research Network grant U01 GM074492) was to identify genetic determinants of blood pressure response and adverse events after antihypertensive treatments. Two different clinical trials with genomic information available were included: PEAR-1 and PEAR-2 studies. The PEAR-1 study (clinicaltrials.gov identifier NCT00246519) was a randomized controlled clinical trial evaluating genetic determinants of BP responses and adverse metabolic responses to atenolol and hydrochlorothiazide (HCTZ) monotherapy and in combination (PMID: 19249413). Briefly, PEAR-1 recruited 768 hypertension individuals with uncomplicated hypertension who were randomized to either monotherapy of atenolol 50 mg daily or HCTZ 12.5 mg daily for 3 weeks, followed by dose titration to 100 mg and 25 mg daily, then the combination therapy. BP and metabolic responses to monotherapy and combination therapy were assessed after an average of 9 weeks of antihypertensive treatment. BP was measured using three different methods: home, office and ambulatory. For the BP analysis, a composite weighted average of the office, home, ambulatory daytime and nighttime BP responses was calculated based on the row sums of the inverse of the inter-method covariance matrices. Genomic DNA from PEAR-1 participants was genotyped using the Illumina Human Omni1MQuad BeadChip (Illumina, San Diego, CA, USA). The PEAR-2 study was a multicenter sequential monotherapy clinical trial (clinicaltrials.gov identifier NCT01203852) evaluating genetic determinants of BP response to metoprolol monotherapy and chlorthalidone monotherapy. After a washout period (if necessary), eligible hypertensive patients with uncomplicated hypertension received metoprolol tartrate 50 mg twice daily for 3 weeks and the dose was increased to 100 mg twice daily for an additional six weeks if an inadequate response was observed (>120/70 mm Hg and heart rate >55 beats/min). After second washout period, patients received chlorthalidone monotherapy. Home and office BP measurements were collected in PEAR-2 study. We have previously demonstrated that home BP is the more informative single BP measurement compared to the office BP measurement. Therefore, home BP is the phenotype used for the genome-wide association analysis for PEAR-2. PEAR-2 samples were genotyped using the Illumina Human Omni2.5S Beadchip (Illumina, San Diego, CA, USA).

  Study phs000649

• Genome-Wide Association of Type 2 Diabetes in Africans: The AADM Study

  The Africa America Diabetes Mellitus (AADM) study is a genetic epidemiological study of type 2 diabetes in Sub-Saharan Africa. Study participants were enrolled through university medical centers in Nigeria, Ghana, and Kenya. Ethical approval for the study was obtained from the Institutional Review Board (IRB) of each participating institution. All subjects provided written informed consent for the collection of samples and subsequent analysis. The case definition of type 2 diabetes was based on the American Diabetes Association (ADA) criteria. After providing informed consent, participants underwent the same enrollment procedures, which included collection of demographic information, medical history, clinical examination and a blood draw. Genome-wide SNP genotyping was done on either the Axiom™ PanAFR SNP array (n=1,808) or the Multi-Ethnic Global Array (MEGA) (n=3,423). After appropriate quality control, in silico imputation was done using the African Genome Resources Haplotype Reference Panel (at the Sanger Imputation Service). Imputed genotypes were filtered for variants with minor allele frequency (MAF)≥ 0.01 and information score (info) ≥ 0.3 for genetic association analysis. Genome-wide association analysis between type 2 diabetes and the imputed genotype dosages was done using a generalized linear mixed model, which adjusted for age, gender, body mass index, the genetic relatedness matrix and the first three principal components (PCs) of the genotypes.Metabolomics profiling of plasma samples of type 2 diabetes (T2D) cases and controls in Nigerians (West Africa) was done in the AADM Study. Plasma metabolites were measured in a total of 580 individuals (N=310 for the discovery phase and N=270 for the replication stage) using the global/untargeted approach on the Metabolon platform and following the manufacturer's standard operation protocols. The analytic methods are described in detail in Doumatey et al. [Genome Med 2024]. The measured metabolites level represented by peak areas are relative values. The peak area data were batch-normalized to remove the instrument batch effects (batch variability) and the batch-normalized data correspond to the median-scaled raw data. For each identified metabolite, the minimum value across all batches in the batch-normalized was imputed for the missing values. The batch-normalized and imputed data are natural log-transformed and consist of 1116 metabolites for the discovery cohort and 1071 metabolites for the replication. Welch's two-sample t-test on the log-transformed data was used to identify metabolites differentially expressed between T2D cases and controls . All other statistical analyses conducted on both the replication and discovery cohorts used the log-transformed data. To merge the discovery and replication, the same quality control samples (bridge samples) were run with each batch of the experimental samples in both cohorts and used to correct for additional variability and uniformize the procedures. The resulting merged data is the QC-normalized and imputed data that contains only metabolites that were common to both cohorts and successfully bridged for all batches (n= 891 metabolites).

  Study phs001844

• The Etiological Bases of Giftedness: Epidemiological Study of Cognitive Ability in Children in Saudi Arabia

  Recent studies of genetic foundations of cognitive ability rely on large samples (hundreds of thousands) of individuals from relatively outbred populations of mostly European ancestry. Hypothesizing that the genetic foundation of cognitive ability depends on the broader population-specific genetic context, we performed a genome-wide association study and homozygosity mapping of cognitive ability estimates obtained through latent variable modeling in a sample of 354 children from the consanguineous population of Saudi Arabia. Approximately half of the sample demonstrated significantly elevated homozygosity levels indicative of inbreeding, and among those with elevated homozygosity, it was negatively associated with cognitive ability. Further homozygosity mapping identified a specific run, inclusive of the GRIA4 gene, that survived corrections for multiple testing for association with cognitive ability. The results suggest that in a consanguineous population, a notable proportion of the variance in cognitive ability in the normal range in children might be regulated by population-specific mechanisms such as patterns of elevated autozygosity.

  Study phs001884

• Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution

  Dissecting human neurobiology at high resolution and with mechanistic precision requires a major leap in scalability, given the need for experimental designs to multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we have implemented and benchmarked complementary strategies to multiplex brain organoids by pooling cells from different pluripotent stem cell lines (PSC) either during organoid generation (mosaic models) or before single cell-RNAseq library preparation (downstream multiplexing). We have also developed a new computational method, SCanSNP, and a consensus call to deconvolve cell identities, overcoming current criticalities in doublets prediction and low quality cells identification. We validated both multiplexing methods for charting neurodevelopmental trajectories at high resolution, thus linking specificity to genetic variation. Finally, we modelled their scalability across different multiplexing combinations and showed that mosaic organoids represent an enabling method for high-throughput settings. Together, this multiplexing suite of experimental and computational methods provides a highly scalable resource for disease modelling.

  Study EGAS50000000698