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• Longitudinal RNA-seq in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Dataset EGAD00001002068

• 5hmC enrichment in human monocyte differentiation

  This dataset consists of 5hmC capture-seq data from human monocytes, monocyte-derived dendritic cells. It includes two biological replicates and three time points. Including controls, the dataset comprises 10 samples in total.

  Dataset EGAD00001006603

• Longitudinal Transcriptomic Profiling of Endothelial Progenitor Cells in Post-COVID-19 Patients: Insights at 3 and 6-Months Post-SARS-CoV-2 Infection

  Bulk RNA-sequencing analysis of endothelial cells isolated from post-COVID patients at 3 and 6 months post-infection, alongside healthy controls. This study aims to identify differentially expressed genes in endothelial cells from post-COVID patients—at both 3- and 6-month time points—compared to those from healthy individuals. The objective is to uncover upregulated and downregulated pathways potentially associated with long-term consequences of SARS-CoV-2 infection.

  Study EGAS50000000993

• The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk.

  The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk and explore the mechanisms underlying the associations between perinatal characteristics and the development of risk for adult chronic disease. In other words, the cohort has enabled the examination of associations between maternal and paternal characteristics with cardiometabolic risk variables in offspring at various points in the life course, as well as the effect of longitudinal changes in characteristics in both parents and offspring.

  Study EGAS00001004075

• Impact of allogeneic umbilical-cord derived mesenchymal stromal cells on B-cell scRNAseq in patients with systemic lupus erythematosus

  The impact of MSC(UC) on peripheral B cells from Systemic Lupus Erythematosus (SLE) patients was studied by 10X scRNAseq. This scRNAseq study encompassed 3 SLE patients at 3 time points: before or after (1 month, and 3 months) MSC injection in order to analyze B cell subsets and their DEG. The aim of this study was to observe the potential changes of B cell subsets after MSC(UC) injection in SLE patients.

  Study EGAS50000000325

• COVID_19_Challenge_Project_Single_Cell_Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection

  Study EGAS00001005696

• Exome sequencing of samples taken at multipl time points to monitor therapy response in AML

  As part of our individualized systems medicine program, personalized treatment options are identified and administered to chemorefractory AML patients based on exome sequencing and ex-vivo drug sensitivity and resistance testing data. In this study, we developed this approach further to take into account clonal heterogeneity and analyzed responses of 13 AML patients to chemotherapy and six patients to targeted treatments by using exome and ultra-deep amplicon resequencing. The data submitted includes fastq files from exome sequencing of multiple time-point samples collected from the 13 patients. In this study we identified rare subclonal variants present at diagnosis or later relapse samples and developed a correlation-based method to compare subclonal responses in serial samples across multiple time-points. Significant subclone-specific responses were observed subsequent to chemotherapy and specifically to targeted therapy in five patients.

  Study EGAS00001001948

• First genome-wide association study in an Australian Aboriginal population provides insights into genetic risk factors for Body Mass Index and Type 2 Diabetes

  A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,355,133 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped=1.50x10-6; rs11140653 Pimputed_1000G=2.90x10-7) for BMI lies 5’ of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped=8.06x10-6; rs10841048 Pimputed_1000G=6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped=4.65x10-5; rs13225016 Pimputed_1000G=6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped=5.59x10-6, Pimputed_1000G=5.73x10-6) for T2D lies 5’ of BCL9 that, along with TCFL2, promotes beta-catenin’s transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped=4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G=2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.

  Study EGAS00001001004

• Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

  In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases. (Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research)

  Study phs001659

• Massachusetts General Hospital (MGH) Atrial Fibrillation Study

  The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" box located on the right hand side of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study. phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing

  Study phs001001