Search Results - EGA European Genome-Phenome Archive

Idiopathic Pulmonary Fibrosis Network (IPFnet) Prednisone, Azathioprine, and N-Acetylcysteine: A Study That Evaluates Response in Idiopathic Pulmonary Fibrosis (IPFNet-Panther-IPF-BioLINCC)

Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: The initial objective of the PANTHER-IPF study was to evaluate the effectiveness of a drug combination of prednisone, azathioprine, and N-acetylcysteine in the treatment of mild-to-moderate idiopathic pulmonary fibrosis (IPF) compared to N-acetylcysteine alone or placebo. After interim analysis presented safety concerns regarding the three drug regimen, the protocol was modified to evaluate only N-acetylcysteine effectiveness. Background: IPF is a chronic, progressive lung disease of unknown cause that is characterized by the histopathological or radiologic patterns of usual interstitial pneumonia in a typical clinical setting. The median survival of participants with idiopathic pulmonary fibrosis after diagnosis is 2 to 5 years. To date, no pharmacologic therapies have been shown to improve survival. Acetylcysteine has been suggested as a beneficial treatment for idiopathic pulmonary fibrosis, although data from placebo-controlled studies are lacking.Design: Patients with mild-to-moderate impairment in pulmonary function were randomly assigned to receive a three-drug regimen (prednisone, azathioprine, and acetylcysteine), acetylcysteine alone (plus matched placebos for prednisone and azathioprine), or matched placebos for each of the active therapies. After the planned midpoint interim analysis, the data and safety monitoring board recommended discontinuation of the three-drug regimen because of an excess in the number of deaths, hospitalizations, and serious adverse events among patients in the combination-therapy group, as compared with the placebo group. After NHLBI accepted this recommendation on October 14, 2011, the three-drug regimen was discontinued and patients were recruited for only the acetylcysteine group and the placebo group. Patients were seen at the clinical centers for screening, at baseline, and at 4, 15, 30, 45, and 60 weeks. The primary outcome measure was change in FVC over 60 weeks.Conclusions: As compared with placebo, acetylcysteine offered no significant benefit with respect to the preservation of FVC in patients with idiopathic pulmonary fibrosis with mild-to-moderate impairment in lung function. In addition, there were no significant differences between the acetylcysteine group and the placebo group in the rates of death or acute exacerbation.

Study phs004071

A Case Controlled Etiologic Study of Sarcoidosis (ACCESS-BioLINCC)

Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from (ACCESS) include Bronchial Lavage, DNA, Peripheral Blood Mononuclear Cells, and Plasma. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: To determine the etiology of sarcoidosis by establishing a case control, multi-center study. In addition to etiology, this study also sought to examine socioeconomic variables and the clinical course of patients with sarcoidosis, including quality of life.Background: Sarcoidosis is a chronic granulomatous disorder of unknown cause that is characterized by activation of T-lymphocytes and macrophages. For many years, sarcoidosis was presumed to be an atypical manifestation of tuberculosis because of the similarity between the inflammatory responses of the two diseases. However, as culture techniques became more widely employed to diagnose tuberculosis and it became less common, it became clear that sarcoidosis was not simply a variation of tuberculosis. Data on the etiology of sarcoidosis have come from diverse sources: in clinical investigations, alveolitis has been found to precede granulomatous inflammation; in case control studies, familial aggregation has been identified; and in case reports, recurrence of granulomatous inflammation has been observed after lung transplantation. The cause may not prove to be a single, known exposure. Interactions of exposures with genetic dispositions could have important implications for our understanding of immune responses as well as the pathogenesis of sarcoidosis.Participants: 736 participants with sarcoidosis enrolled within 6 months of diagnosis from 10 clinical centers in the U.S. Using the ACCESS sarcoidosis assessment system, organ involvement was determined for the whole group and for subgroups differentiated by sex, race, and age (Conclusions: The initial presentation of sarcoidosis is related to sex, race and age, and it tends to remain stable over two years in the majority of patients. The etiology is probably multifactoral with both genetic and environmental factors contributing.Specimen Details: The PBMC for this study are pelleted and suspended in guanidinium-based solution and are nonviable.

Study phs004276

Molecular_characterization_of_invasive_lobular_carcinoma

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

Study EGAS00001000292

UK10K_OBESITY_SCOOP

In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The SCOOP samples are part of the Obesity group and will undergo exome sequencing. Severe Childhood Onset Obesity Project (SCOOP) is a sub-cohort of the Genetics Of Obesity Study (GOOS) cohort established by Sadaf Farooqi and Steve O’Rahilly at the University of Cambridge over the last 12 years. The GOOS cohort contains >4,000 patients of diverse geographic origin, many of whom have monogenic and syndromic forms of obesity, and includes patients that are offspring of consanguineous union. SCOOP is a subset of >1500 UK Caucasian patients with severe, early onset obesity (all patients have a BMI Standard Deviation Score (SDS) > 3 and obesity onset before the age of 10 years), in whom all known monogenic causes of obesity have been excluded. GWAS data on the SCOOP cohort will be available (WTCCC2 independent study) at the time of the start of this study. Data from this cohort has demonstrated that the prevalence of the common obesity risk alleles in FTO, MC4R and NEGR1 are amongst the highest within SCOOP, demonstrating its value also in the study of genetic variants with an impact on more common obesity. For further information with regard to this cohort please contact Sadaf Farooqi (isf20@medschl.cam.ac.uk).

Study EGAS00001000124

RNA_Seq_in_Patients_with_Primordial_Dwarfism

Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.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/

Study EGAS00001000283

Sensitive and robust liquid biopsy-based detection of PIK3CA mutations

Over the last years, the treatment of hormone receptor-positive metastatic breast cancer patients has dramatically changed. Combination strategies attempting to overcome resistance to endocrine therapy such as targeting the PI3 kinase pathway are gaining importance. The phase III SOLAR-1 trial demonstrated the benefit of the addition of alpelisib to fulvestrant, thereby providing further clinical evidence of the increasing importance of PIK3CA testing. Here, we performed a comparison of liquid biopsy and tissue-based detection of PIK3CA mutations in HR-positive metastatic breast cancer patients. Plasma samples and the latest available tumor tissue from 69 patients with metastatic hormone-receptor positive breast cancer were analyzed for PIK3CA hotspot mutations. A high-resolution NGS assay (SiMSen-Seq) was used for plasma samples covering 11 recurrent PIK3CA mutations, used for stratification in SOLAR-1. Additionally, mFAST-SeqS was used to estimate the tumor fractions in the plasma samples. For tumor tissue samples, targeted Ion Torrent NGS was employed. Matched tissue and plasma samples were available from 63 patients. PIK3CA mutations were detected in 46.1% of the tissue samples and in 50.7% of the plasma samples. The variant allele frequency (VAF) ranged from 4.36% to 72.93% with a median of 28.60% in tissue samples, and from 0.28% to 49.85% with a median of 1.17% in plasma samples. The most frequent variants in tissue and plasma were H1047R, E545K, and E542K. We detected at least one of 11 PIK3CA mutations from the SOLAR-1 trial in 51/63 patients, both in tissue and plasma. In 7 patients, such mutations were found only in plasma. In 5 patients, PIK3CA mutations found in tissue were not detectable in ctDNA, 2 of which had a low tumor fraction.Together, in 33/67 plasma samples without detectable PIK3CA mutations, 18 samples had elevated tumor fraction, implicating true negative results. In the remaining 15 patients with low tumor fraction, additional tissue analysis was needed. SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted, mutation-independent approach for detecting ctDNA fractions may confirm a negative PIK3CA result and thereby enhance the performance of the SiMSen-Seq test. This combinatory approach for selecting suitable patients for alpelisib treatment should be validated in larger patient cohorts.

Study EGAS00001004940

eMERGE Network Imputed GWAS for 41 Phenotypes

The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites (Cincinnati Children's Hospital Medical Center/Boston Children's Hospital, Children's Hospital of Philadelphia, Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University, Geisinger Clinic, Group Health Cooperative/University of Washington, Mayo Clinic, Icahn School of Medicine at Mount Sinai, Northwestern University, Vanderbilt University Medical Center) funded by the NHGRI to investigate the use of electronic medical record (EMR) systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 55,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of over forty phenotypes, including Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection, as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. Sites and participants include: Children's Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic medical records (EMRs). EMRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): Cincinnati Children's Hospital Medical Center (CCHMC) and Boston Children's Hospital (BCH) are pediatric institutions dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. The CCHMC/BCH site has been built on a five-year history of collaboration, particularly in patient electronic record (ERM)-related informatics, the basis of much of eMERGE II. CCHMC and BCH together bring an extraordinary faculty to eMERGE II who are committed to diseases that afflict children, specifically phenotypes that focus upon diseases of children in ways that will leverage the available eMERGE adult GWAS and EMRs to discover meaningful use results. CCHMC/BCH plans to demonstrate real-time execution of phenotypic selection across their two distinct pediatric institutions as a model for ensuring phenotypic standardization and for national scalability. They will also look carefully at parents' responses to results and use of their children's research results and better understand the factors that influence their decisions about learning incidental findings. In addition to patient and parent perceptions CCHMC/BCH will also explore clinician perceptions of pharmacogenetic research results after EMR integration. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Group Health(GH)/University of Washington (UW): GH participants for the PGx project were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~6300.) Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in GH's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at Group Health: 1. Demographics - participants with self-reported race as Asian or African ancestry were prioritized and selected to enrich for non-European ancestry; 2. Diagnosis and procedure codes - participants were selected if found to have a history of hypertension, atrial fibrillation (AF), or congestive heart failure (CHF). Participants with a history of arrhythmia were added if the entire selection algorithm did not generate 900 individuals. We also enriched for participants with EHR evidence of actionable indications related to PGRNSeq genes. Participants were selected if found to have an ICD9 code for malignant hyperthermia, hypertension, atrial fibrillation, congestive heart failure or long QT syndrome (LQTS); 3. Laboratory values - if participants had any laboratory event of creatine kinase (CK) >1000, and were dispensed statins within 6 months of the event, then they were selected; and 4. Medications - participants were excluded if ever on carbamazepine or had a current regimen of warfarin. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations.

Study phs000888

Data upcycling, powered by EGA

In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

Blog data-upcycling-powered-by-ega

Hyperdiploidy impairs fetal hematopoietic progenitor cell fitness and differentiation enabling persistence of rare preleukemic aneuploid clones

Cells previously cryopreserved in FBS-10%DMSO were thawed and resuspended in 1mL of cold lysis buffer (10 mM Tris-HCl pH 7.4, 154 mM NaCl, 0.2% BSA, 0.1% NP-40, 1 mM CaCl₂, 0.5 mM MgCl₂ in ultra-pure water) to lyse the cell membrane and release intact nuclei. The nuclei were stained with propidium iodide (10 µg/mL) and Hoechst 33258 (10µg/mL) to facilitate sorting based on cell cycle state and viability. Single nuclei from 48 cells per sample were isolated into 96-well plates containing 5µL of freeze buffer (1X PBS, 7.5% DMSO, and 40% ProFreeze freezing medium (Lonza)) using a MoFlo Astrios cell sorter (Beckman Coulter) at the Flow Cytometry Unit of the University Medical Center Groningen (UMCG), Netherlands. The plates were centrifuged at 500 g and stored at -80°C until library preparation. Single-nuclei libraries were prepared using a Bravo Automated Liquid Handling Platform (Agilent Technologies). Nuclei were lysed, and DNA was labelled with unique 10 bp dual barcodes and amplified as previously described. Sequencing was performed on an Illumina NextSeq 2000 platform with 77bp single end reads. The generated data were subsequently demultiplexed using sample-specific barcodes and converted to FASTQ files with bcl2fastq. Sequencing reads were aligned to the GRCh38/hg38 human reference genome using Bowtie2 (v2.2.4), and duplicate reads were marked with BamUtil (v1.0.3). Single-cell karyotypes were determined by performing copy number analysis using AneuFinder (v4.3.3) (https://github.com/ataudt/aneufinder). The analysis included GC-content correction and blacklisting of artifact regions identified from euploid controls. Copy number calling was conducted with the dnacopy and edivisive algorithms, employing a bin size of 1 Mb and a step size of 500 Kb. Libraries with an average of fewer than 10 reads per chromosome copy per bin or less than 95% concordance between the two algorithms were excluded from analysis. Whole-chromosome aneuploidies were identified when over 95% of bins exhibited deviation from the disomic state. Aneuploidy scores were calculated as weighted averages of absolute copy number deviations from the euploid state.

Dataset EGAD50000002314

Assessment of genetic and epigenetic variation in human IPS cells-RNA

In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The transcriptomes of these iPS cells will be compared. Protocol: primary cultures of cells were reprogrammed to iPS cells. RNA was extracted using a standard column extraction kit.

Dataset EGAD00001000604

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