6365 results for "11+1双色球多少钱一注"

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• Genomic analysis reveals novel secondary drivers and progression pathways in skin basal cell carcinoma

  Basal cell carcinoma of the skin (BCC) is the most common malignant neoplasm in humans. BCC is primarily driven by the aberrant activation of the Sonic Hedgehog (Hh) pathway. However, its extensive phenotypical variation remains to be explained. The genetic profiling of 293 BCCs revealed the highest mutation rate observed in cancer (65 Mutations/Mb), with strong prevalence of UV-light signature mutations. 85% of BCCs harbored mutations in Hh pathway genes: mutually exclusive PTCH1 (73%) and SMO (20%) (P=6.6x10-8), SUFU (8%), and in TP53 (61%). 85% of BCCs also harbored secondary driver mutations in other genes implicated in BCC tumorigenesis. Recurrent secondary driver mutations were observed in MYCN (30%), PPP6C (15%), STK19 (10%), LATS1 (8%), ERBB2 (4%), PIK3CA (2%), RAC1 (1%) and N/K/H-RAS (2%). Loss of function (LoF) and deleterious missense mutations were observed in PTPN14 (23%), RB1 (8%) and FBXW7 (5%). In line with the mutational profiles detected by RNAseq, we observed activation of the Hh pathway as well as upregulation of target genes of the Hippo-YAP pathway and activation of MYCN target genes. The functional analysis of the novel tumorigenic driver mutations in MYCN, PTPN14 and LATS1 demonstrates their relevance in BCC tumorigenesis and provides an expanded molecular understanding of BCC.

  Study EGAS00001001540

• Comprehensive analysis of atypical teratoid rhabdoid tumour (ATRT) using genomic, epigenomic and transcriptomic techniques.

  ATRTs (Atypical teratoid rhabdoid tumours) represent one of the most aggressive pediatric brain cancers, but intriguingly exhibit few other recurrently mutated loci except for SMARCB1/hSNF5. We integrated whole genome (n=15), exome, copy number, gene expression and methylation analyses to comprehensively interrogate 64 ATRTs and observed that structural events were relatively frequent in the ATRT genome (~3 tumour). In addition to SMARCB1, which was targeted by structural events in a majority (49/64) of tumours, recurrent structural alterations targeting the LRP1B, CDH13, BCR and MKL1 loci were observed. We observed novel translocation events, including 2 targeting SMARCB1 which were detected only by NGS analyses. Significantly, integration of gene expression and methylation profiles with genomic analyses revealed ATRT comprise two sub-groups with distinct clinical and genetic features. Group 1 tumours were characterized by supra-tentorial brain location, focal intragenic alterations of SMARCB1 and a pro-neural gene expression signature with evidence of NOTCH pathway activation. While Group 2 ATRTs were characterized by infra-tentorial brain location, broad SMARCB1 alterations and an activation of the BMP signalling pathway. Our findings highlight epigenetic mechanisms as important determinants of ATRT tumour phenotypes, and demonstrate for the first time that ATRTs arising in different anatomical compartments comprise distinct molecular and therapeutic sub-groups.

  Study EGAS00001000506

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Background: Glioblastoma (GBM) is a complex disease with extensive molecular and transcriptional heterogeneity. GBM can be subcategorized into four distinct subtypes; tumors that shift towards the mesenchymal phenotype upon recurrence are generally associated with treatment resistance, unfavorable prognosis, and the infiltration of pro-tumorigenic macrophages. Results: We explore the transcriptional regulatory networks of mesenchymal-associated tumor-associated macrophages (MA-TAMs), which drive the malignant phenotypic state of GBM, and identify macrophage receptor with collagenous structure (MARCO) as the most highly differentially expressed gene. MARCOhigh TAMs induce a phenotypic shift towards mesenchymal cellular state of glioma stem cells, promoting both invasive and proliferative activities, as well as therapeutic resistance to irradiation. MARCOhigh TAMs also significantly accelerate tumor engraftment and growth in vivo. Moreover, both MA-TAM master regulators and their target genes are significantly correlated with poor clinical outcomes, and are often associated with genomic aberrations in neurofibromin 1 (NF1) and phosphoinositide 3-kinases/mammalian target of rapamycin/Akt pathway (PI3K-mTOR-AKT)-related genes. We further demonstrate origination of MA-TAMs from peripheral blood, as well as their potential association with tumor-induced polarization states and immunosuppressive environments. Conclusions: Collectively, our study characterizes the global transcriptional profile of TAMs driving mesenchymal GBM pathogenesis, providing potential therapeutic targets for improving the effectiveness of GBM immunotherapy.

  Study EGAS00001002443

• Coding and small non-coding transcriptional landscape of tuberous sclerosis complex cortical tubers: implications for pathophysiology and treatment

  Tuberous Sclerosis Complex (TSC) is a rare genetic disorder that results from a mutation in the TSC1 or TSC2 genes leading to constitutive activation of the mechanistic target of rapamycin complex 1 (mTORC1). TSC is associated with autism, intellectual disability and severe epilepsy. Cortical tubers are believed to represent the neuropathological substrates of these disabling manifestations in TSC. In the presented study we used high-throughput RNA sequencing in combination with systems-based computational approaches to investigate the complexity of the TSC molecular network. Overall we detected 438 differentially expressed genes and 991 differentially expressed small non-coding RNAs in cortical tubers compared to autopsy control brain tissue. We observed increased expression of genes associated with inflammatory, innate and adaptive immune responses. In contrast, we observed a down-regulation of genes associated with neurogenesis and glutamate receptor signaling. MicroRNAs represented the largest class of over-expressed small non-coding RNA species in tubers. In particular, our analysis revealed that the miR-34 family (including miR-34a, miR-34b and miR-34c) was significantly over-expressed. Functional studies demonstrated the ability of miR-34b to modulate neurite outgrowth in mouse primary hippocampal neuronal cultures. This study provides new insights into the TSC transcriptomic network along with the identification of potential new treatment targets.

  Study EGAS00001002485

• Analysis_of_genomic_integrity_of_disease_corrected_human_induced_pluripotent_stem_cells_by_exome_sequencing

  Induced pluripotent stem (iPS) cells hold great promise for autologous cell transplantation. In order to apply this therapy to monogenic disorder, disease-causing mutations must be corrected prior to transplantation. We generated iPS cells from patients with alpha-1 antitrypsin deficiency, which is caused by homozygous non-synonymous mutation in the SERPINA1 gene. In vitro differentiation of patient-derived iPS cells to hepatocytes showed recapitulation of the disease phenotype. We corrected the mutations by gene targeting using zinc finger nuclease (ZFN) and piggyBac transposon technologies. Our mutation correction is highly accurate. There is no exogenous sequence left behind at the targeted site. The corrected iPS cell-derived hepatocytes were indistinguishable from healthy hepatocyte, suggesting that the corrected gene was fully functional. The genomic integrity was also analyzed by CGH and SNP array, showing no genomic alterations. These are important points to ensure clinical safety as well as functional restoration of the corrected gene. One remaining question is if these corrected iPS cells are clinically safe at the single base-pair level. Recent publications suggested that cancer-related mutations are significantly accumulated during iPS cell propagation. We aim to assess the clinical safety of the corrected iPS cells by using exome sequencing. Outcome from this project would bring iPS cell technology one step closer to clinical applications.

  Study EGAS00001000055

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Transcriptional and DNA binding profiling of CEBPE in REH acute lymphoblastic leukaemia cells using shRNA RNA-Seq and ChIP-Seq

  ChIP-Seq - CEBPE - REH. The ETV6/RUNX1 translocated acute lymphoblastic leukaemia cell line REH was used to perform ChIP-Seq using a CEBPE antibody. Cells were fixed in 1% formaldehyde for 10mins, prior to preparation of chromatin using Active Motif Express ChIP-IT. 2ug of antibody (anti CEBPE Atlas Antibodies HPA002928)was added to 25ug of chromatin O/N at 4C with rotation. Duplicate reactions were pooled and purified. 10ng of ChIPd and input DNA used for Illumina NGS preparation (NEBNext ChIP-Seq Library kit; New England Biolabs), CEBPE and Input DNA ChIP samples were sequenced on a MiSeq using 150bp Kit v3 paired end and a HiSeq 2500 using 2x101 version 4 paired end (Illumina) respectively. Reactions performed in duplicate. shCEBPE RNA-Seq - REH. REH cells were lentivirally transduced with a pTRIPZ shRNA vector for transcriptional profiling of CEBPE. Two controls (empty and non-targeting) and two CEBPE shRNAs (V3THS_150517(A13), V3THS_404312(G3) Dharmacon, GE) were transduced into REH cells. Cells were treated with 1ug/ml doxycyclin for 144hrs and total RNA purified. Libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kit and sequenced on an Illuimna HiSeq 2500 using 2x101 version 4 paired end chemistry. 3 biological replicates of each samples were prepared.

  Study EGAS00001002877

• Spatial concordance of DNA methylation classification in diffuse glioma

  Background: Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence. Methods: We used neuronavigation to acquire 133 image-guided and spatially-separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast enhanced T1 weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a three-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites. Results: Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account. Conclusion: Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.

  Study EGAS00001005434

• scRNA-seq of HGSC tumor and ascites

  Immune regulatory metabolites are key features of the tumor microenvironment (TME), yet with a few notable exceptions, their identities remain largely unknown. We uncovered the immune regulatory metabolic states and metabolomes of sorted tumor and stromal, CD4+, and CD8+ cells from the tumor and ascites of patients with high-grade serous ovarian cancer (HGSC) using high-dimensional flow cytometry and metabolomics supplemented with single cell RNA sequencing. Flow cytometry revealed that tumor cells show a consistently greater uptake of glucose than T cells, but similar mitochondrial activity. Cells within the ascites and tumor had pervasive metabolite differences, with a striking enrichment in 1-methylnicotinamide (MNA) in T cells infiltrating the tumor compared to ascites. Despite the elevated levels of MNA in T cells, the expression of nicotinamide N-methyltransferase, the gene encoding the enzyme that catalyses the transfer of a methyl group from S-adenosylmethionine to nicotinamide, was restricted to fibroblasts and tumor cells. Treatment of T cells with MNA resulted in an increase in T cell-mediated secretion of the tumor promoting cytokine tumor necrosis factor alpha. Thus, the TME-derived metabolite MNA contributes to an alternative and non-cell autonomous mechanism of immune modulation of T cells in HGSC. Collectively, uncovering the tumor-T cell metabolome may reveal metabolic vulnerabilities that can be exploited using T cell-based immunotherapies to treat human cancer.

  Study EGAS00001004829

• Genetic insights into the biological mechanisms governing human ovarian ageing

  Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ~200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

  Study EGAS00001004947

• Ultrasensitive detection of minor allele fractions in maternal samples based on microhaplotype analysis

  Background: Tools for quantifying and studying genetic variation in heterogeneous cell populations have a limited sensitivity. However, many biological problems require ultrasensitive genetic deconvolution of cell mixtures. The detection of fetal cells in cervical samples from pregnant women presents such a challenge. Methods: Using deep sequencing of microhaplotype loci and analysis of the error profiles in genetically pure and mixed samples, we increase the sensitivity for minor allele detection and demonstrate the potential for paternal allele detection in cervical samples from pregnant women. Results: Using artificial DNA mixtures, we show that unique alleles can be readily identified in mixtures with a ratio of 1 in 10,000 (0.01%). By applying this method on ten non-invasive cervical samples from pregnant women we could identify the presence of paternal alleles in half of the samples. Unexpectedly, we demonstrate those alleles not to be of fetal origin but of sperm. Conclusions: We developed a novel method that can deconvolute genetic mixtures to at least 0.01%, which can be applied to study minor allele fractions in genetic mixtures and, for example, could aid in trophoblast cell detection in maternal blood or cervix. Our results demonstrate the importance of discriminating fetal and paternal alleles when analyzing cervical fetal cells and may pinpoint a potential cause of erroneous results in previous trophoblast isolation studies.

  Study EGAS00001007057

• Germline whole genome sequencing of patients with Li-Fraumeni syndrome

  Five hundred ng to 1 ug of genomic DNA was submitted to The Centre for Applied Genomics (TCAG) at The Hospital for Sick Children for genomic library preparation and whole genome sequencing. DNA samples were quantified using the Qubit High Sensitivity Assay and purity was assessed using the Nanodrop OD 260/280 ratio. Approximately 500-700 ng of DNA was used as input material for library preparation using the Illumina TruSeq PCR-free DNA Library Prep Kit following the manufacturer’s recommended protocol. In brief, DNA was fragmented to 400 bp on average using sonication on a Covaris LE220 instrument. Fragmented DNA was end-repaired, A-tailed and indexed TruSeq Illumina adapters with overhang-T were added to the DNA. Libraries were then validated on a Bioanalyzer DNA High Sensitivity chip to check for size and absence of primer dimers and quantified by qPCR using Kapa Library Quantification Illumina/ABI Prism Kit protocol (KAPA Biosystems). Validated libraries were pooled in equimolar quantities and paired-end sequenced on an Illumina HiSeq X platform following Illumina’s recommended protocol to generate paired-end reads of 150-bases in length and an average depth of 40X. FASTQ files were aligned to the hg19 reference genome using BWA-mem v0.78. PCR duplicates were marked with Picard MarkDuplicates v1.1.08, and base recalibration and realignment was performed using GATK v2.8.1.

  Study EGAS00001007061

• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  A growing number of druggable targets and national initiatives for precision oncology necessitate broader genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a sensitivity between 91-95% and a positive predictive value (PPV) of 82-95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Deviations were observed for cases with low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

  Study EGAS00001007363

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Implementation, Adoption, and Utility of Family History in Diverse Care Settings

  The purpose of this study is to address the key question of whether and how family health history (FHH) is adopted as a tool to more efficiently manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as well as thrombophilia and coronary heart disease (CHD) and to provide evidence supporting clinical utility -- improved health behaviors in patients and physician screening recommendations. Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, University of North Texas. Duke will serve as a coordinating center for this project (Pro00043372) as well as a site. Healthcare Effectiveness Data and Information Set (HEDIS) measures as intermediate clinical effectiveness measures for Coronary Heart Disease (CHD) and selected cancers as well as survey/formative data and electronic medical record (EMR) data will be used as outcomes measures. The research model is purposely designed to mimic clinical delivery as an important step toward widespread implementation and sustainability. In addition, a cost-effectiveness analysis comparing usual care to the FHH guided preventive health model will be used. The completion of this project will result in an optimal strategy for integration of FHH data collection and clinical decision support (CDS) tools into an EMR and demonstrate the utility of the FHH intervention among diverse primary care patients, their settings, their providers, and the health systems that deliver their care. Specific Aim 1: To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) platform and return CDS results to providers and patients (and to EMRs where relevant). To explore the integration of genetic risk and FHH data at selected sites. Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system. Specific Aim 4: To take a leadership role in the dissemination of guidelines for a FHH intervention across in diverse practice settings. AAA Hypertension Lupus Multiple sclerosis Obesity Osteoporosis Thyroid disease Rheumatoid arthritis Blood clotting (6): Blood Clot (high risk features) Factor V PT mutation AT III deficiency Protein S deficiency Protein C deficiency Brain Disorders (5): Dementia Hemorrhagic stroke Ischemic stroke Macrocephaly Seizure Cancer/Adenomas (32): Bone cancer Brain cancer Breast cancer Colon cancer Adrenal cortex tumor Neuroendocrine tumor Paraganglioma Pheochromoctyoma Pituitary adenoma Medullary thyroid cancer Non-medullary (follicular or papillary) thyroid cancer Don't know type of thyroid cancer Thyroid nodule Other type of endocrine cancer Esophageal cancer Kidney cancer Leukemia Lipoma Liver cancer Muscle cancer Ovarian cancer Pancreatic cancer Prostate cancer Rectal cancer Retinoblastoma Melanoma Non-melanoma skin cancer Do not know type of skin cancer Small bowel cancer Stomach cancer Uterine cancer Other type of cancer Cardiovascular/heart/artery disease (5): Atrial fibrillation Carotid stenosis Heart attack/coronary artery disease Peripheral arterial disease Other heart disease Diabetes (3): Gestational diabetes Diabetes type I Diabetes type 2 Digestive Disorders (5): Colon polyp Crohn's disease Irritable bowel syndrome Ulcerative colitis Other digestive disorder Eye Disorder (3): Blindness Glaucoma Macular degeneration Hereditary Cancer Syndromes (22): Birt-Hogg-Dube syndrome Cowden syndrome Familial adenomatous polyposis Hereditary breast and ovarian cancer syndrome Hereditary diffuse gastric cancer Hereditary leiomyomatosis and renal cell carcinoma syndrome Hereditary melenoma Hereditary papillary renal cancer syndrome Hereditary paraganglioma-pheochromocytoma syndrome Hereditary retinoblastoma Juvenile polyposis Li-Fraumeni syndrome Lynch syndrome Mutyh-associated polyposis Malignant hyperthermia susceptibility Multiple endocrine neoplasia type 1 Multiple endocrine neoplasia type 2 Nevoid basal cell carcinoma syndrome Peutz-Jeghers syndrome Tuberous Sclerosis complex Von-Hippel Lindau syndrome Other hereditary cancer Hereditary Cardiovascular syndromes (10): Long qt Brugada Catecholaminergic polymorphic ventricular tachycardia Hypertrophic cardiomyopathy Dilated cardiomyopathy Left ventricular non-compaction syndrome Arrhythmogenic right ventricular dysplasia Ehlers-Danlos syndrome Marfan syndrome Other hereditary cardiovascular syndrome High cholesterol (2): Hyperlipidemia Familial hypercholesterolemia Kidney Disease (6): Cystic kidney disease Diabetic kidney disease Kidney nephrosis Nephritis Nephrotic syndrome Other kidney disease Liver Disease (6): Alpha 1 antitrypsinase deficiency Auto-immune hepatitis Hereditary hemochromatosis Primary biliary cirrhosis Sclerosing cholangitis Wilson's disease Lung Disease (3): Asthma COPD/chronic bronchitis/emphysema Other lung disease Psychological disorder (14): Addiction ADHD Autism Bipolar Depression Eating disorder Intellectual disability Obsessive compulsive disorder Panic disorder Personality disorder PTSD Schizophrenia Social phobia Sickle cell/thalassemia (3): Sickle cell disease Sickle cell trait Thalassemia

  Study phs001641

• The African American Breast Cancer Epidemiology and Risk (AMBER) Consortium Study

  The AMBER Consortium Study was formed to pool interview data, questionnaire data, and biological samples from epidemiological studies of breast cancer in African-American women to discover the potential causes of early-onset and aggressive breast cancer in African-American women. AMBER is funded through a Program Project grant from the National Cancer Institute. Genetic data submitted to dbGaP come from participants in the Carolina Breast Cancer Study, Women's Circle of Health Study, and Black Women's Health Study. The P01 consists of four scientific projects; the aims include follow-up on previous GWAS findings for breast cancer susceptibility in AA women as well as investigation of SNPs in candidate genes in biologically plausible pathways. These SNPs were genotyped using DNA from 3130 African-American women with breast cancer and 3700 controls. Descriptions of the original studies that provided the data and samples for this collaborative study are given below. The Carolina Breast Cancer Study (CBCS): a North Carolina population-based case-control study of breast cancer, conducted in three phases. The current study phase, phase 3 (years 2008-2014), includes women residents in 44 counties. CBCS phases 1 and 2 were conducted in 24 counties. Breast cancer cases are identified using Rapid Case Ascertainment in cooperation with the NC Central Cancer Registry. Controls were identified for phases 1 and 2 only (1993-1996 and 1996-2001), using Division of Motor Vehicles lists for women under age 65 and Health Care Financing Administration lists for women 65 and older. Randomized recruitment was used to oversample AA women and women under age 50. In-depth interviews are conducted by study nurses in participants' homes to obtain information on potential risk factors for breast cancer. DNA samples have been obtained from most participants. Overall response rates for Phases 1 and 2 were 74% for AA cases and 54% for AA controls. Phase 3, conducted in 44 counties from 2008-2014, includes cases only. The response rate for AA cases in Phase 3 was 70.5%. The Women's Circle of Health Study (WCHS): a multi-site case-control study in New York City (NYC) and New Jersey (NJ) aimed at evaluating risk factors for early and aggressive breast cancer in women of AA and EA ancestry. Recruitment in NYC took place between January 2002 and December 2008 and involved hospital-based ascertainment of cases, while controls were identified through random digit dialing (RDD). Recruitment at the NJ site started in March 2006 and is ongoing. Phase I of the study ended in April 2012 and covered seven counties in NJ. WCHS2 includes two additional counties. Cases in NJ were identified from 2006 to 2012 by the NJ State Cancer Registry using rapid case ascertainment. Controls were initially recruited though RDD (2006 to 2010) and later through community-based efforts (2009-2012). In-person interviews ascertained data on established and suspected risk factors for breast cancer. DNA samples were obtained. Among eligible AA women, 75% in NY and 54% in NJ completed an interview and provided a biologic specimen. Black Women's Health Study (BWHS): an ongoing prospective cohort study of health and illness among U.S. black women, with a focus on cancer. The study began in 1995 when 59,000 AA women 21-69 years of age from across the United States completed a 14-page postal health questionnaire. The median age at entry was 38, and participants were residents of 17 states in mainland U.S.: Northeast, 28%; South, 30%; Midwest, 23%; West, 19%. The baseline questionnaire elicited information on a wide range of variables, including demographic factors, use of medical care, family history of breast cancer, reproductive and medical history, cigarette and alcohol use, weight, height, waist and hip circumference, medication use, diet, and exercise. Biennial follow-up questionnaires ascertain new cases of breast cancer and other illnesses and update covariate information. Medical record and cancer registry data are sought for all participants who report a diagnosis of breast cancer. As of 2014, approximately 80% of the baseline cohort have completed follow-up. DNA samples were obtained from about 50% of participants. BWHS data for the AMBER consortium were prepared as a nested case-control study, with controls frequency-matched to cases on year of birth, geographic region, and most recent questionnaire completed prior to the end of the at-risk period.

  Study phs000669

• Identification of the underlying causal variant in a multi-generational family with autosomal dominant common variable immunodeficiency

  Common variable immunodeficiency (CVID) is the most common form of primary immunodeficiency with an estimated incidence of 1:10,000. It has been apparent for many years that CVID has a genetic component, occurs frequently in families and can have both a recessive or dominant mode of inheritance. In recent years, 4 genes underlying CVID have been identified; however, mutations within in them are estimated to account for no more than 10% of all cases of CVID. We have identified a multi-generational family with autosomal dominant CVID. Genome-wide linkage analysis has mapped the locus underlying CVID in this family to an approximately 9.2 Mb interval on chromosome 3q27.3-q29, between the markers D3S3570 and D3S1265. This locus is distinct from any of the previously mapped susceptibility loci suggesting a novel genetic variant is responsible for disease in this family. The aim of this study is to use exome sequencing of affected (n = 4) and unaffected (n = 4) individuals, in tandem with the available genetic mapping data, to identify the causal variant underlying CVID in this family.

  Dataset EGAD00001000363

• Gut 16S rRNA/FINRISK 2002

  Gut microbiome 16S rRNA raw data for N=7174 FINRISK 2002 participants. FINRISK fecal samples were mailed to the Knight laboratory at the University of California (San Diego, CA), for microbiota sequencing using the standard Earth Microbiome Project protocols (https://earthmicrobiome.org/protocols-and-standards/). DNA was extracted using a magnetic bead-based DNA extraction protocol. Amplicon sequence data for the V4 region of the 16S rRNA gene was generated using 515F (Parada) and 806R (Apprill) primers. For a total of 25μl reaction volume, 13 µl PCR-grade water was combined with 10 µl PCR master mix (Platinum Hot Start PCR Master Mix, 2x, ThermoFisher), 0.5 µl forward primer (10 µM), 0.5 µl reverse primer (10 µM), and 1 µl template DNA. Amplification was performed in triplicate reactions, and triplicate PCR reactions were pooled afterwards. Expected products were visualized on agarose gels (300–350 bp) and quantified with Quant-iT PicoGreen dsDNA kit (Invitrogen). Equal amounts (240 ng) of amplicon were combined for each sample and cleaned (MoBio UltraClean PCR Clean-Up Kit). Cleaned amplicon pools were sequenced with 515F and 806R primers.

  Dataset EGAD50000000287

• Fecal microbiome of T2D patients undergoing semaglutide or empagliflozin treatment

  The gut microbiome has been shown to be affected by the use of many human-targeted medications, and the interaction can be bidirectional. This has been clearly demonstrated for type 2 diabetes medications that have been in clinical use for several decades. However, the bidirectional effects of novel type 2 diabetes drugs semaglutide, empagliflozin, and the gut microbiome have yet to be clearly described. We investigated the effect of semaglutide and empagliflozin initiation on the gut microbiome of type 2 diabetes patients. In addition, we analyzed whether the pre-treatment gut microbiome can predict the treatment efficacy. Twenty subjects (10 women and 10 men) were enrolled in the study between November 2019 and January 2023 from the University of Tartu Hospital, Tartu, Estonia. All participants had been diagnosed with type 2 diabetes. The study group taking semaglutide included 6 women and 4 men, and the group prescribed empagliflozin included 4 women and 6 men. Gut microbiome fecal samples donated at four timepoints (Baseline, Month 1, Month 3; Month 12) were studied using 16S ribosomal RNA gene sequencing and analysis.

  Dataset EGAD50000000756

• Psoriasis Patient PBMC scRNA-seq data

  This dataset contains raw and processed data of four scRNA-seq PBMC samples from four Psoriasis patients (Pso3 = male, Pso4 = female, Pso7 = female, Pso8 = male). Raw sample libraries were prepared with 10x 5'-kit v2 multiplexing the individual samples using TrueSeq barcoded antibodies to stain the cells. Resulting sequencing data consists of four FASTQs (2 x antibody multiplex to demultiplex the samples + 2 x transcriptome data containing the typical cell x UMI barcode data for count matrix generation). The raw sequencing data was processed with cellranger 6.0.1 with the GRCh38 3.0.0 reference and cell to sample assignment was subsequently done with couhto 1.1.0 (https://github.com/dmalzl/counhto) employing the same algorithm as cellranger multi (couldn't be used here though as multi does not handle 5'-chemistry data). Processed data contains all main outputs of cellranger count in raw text format or in h5 formats including the used feature reference for (i.e. antibody barcode to sample assignment) as well as the computed cell to sample assignment computed by counhto. For further details including all used code in the analysis of the data please consult https://doi.org/10.5281/zenodo.13846873

  Dataset EGAD50000001102

• scRNA seq and scTCR seq data from 5 melanoma patients

  The Chromium Controller and Chromium X platfor of 10X Genomics were used for single cell partitioning and barcoding. Each cell's transcriptome was barcoded during reverse transcription, pooled cDNA was amplified and Single Cell 5' Gene Expression (GEX), V(D)J and Feature Barcode (FB) Libraries were prepared according to the manufacturer's protocols (CG000330 and CG000331, 10X Genomics). All libraries were quantified and normalized on library QC data generated on the Bioanalyzer system according to manufacturer's protocols (G2938-90321 and G2938-90024, Agilent Technologies). Based on the expected target cell counts, a balanced library sub-pool of samples was compsed for SC5'GEX, V(D)J and FB libraries. Library sub-pools were quantified by qPCR, accodring to the KAPA Library Quantification Kit Illumina(R) Platforms protocol (KR0405, KAPA Biosystems). Based on qPCR results a final sequencing pool was composed. Paired end sequencing was performed on a NovaSeq 6000 Instrument (Illumina) using NovaSeq 6000 Reagent Kits v1.5 100 cycles (cat. no. 20028401, 20028319, 20028316 Illumina), using 28 cycles for Read 1, 10 cycles for Read i7, 10 cycles for Read i5 and 90 cycles for Read 2.

  Dataset EGAD50000001155

• M116 scRNA-seq

  scRNA-seq was performed using Chromium Next GEM Single Cell 3’ Kit v3.1 (10X Genomics) according to the manufacturer’s instructions. Briefly, M116's PBMCs were thawed and quantified in order to calculate the number of cells to be loaded. Then, barcoded Single Cell 3ʹ Gel Beads, a master mix containing PBMCs, and Partitioning Oil were combined onto the Chromium Next GEM Chip G to generate Gel Beads-In-Emulsion (GEMs), where polyadenylated mRNAs were reverse transcribed. This way, all generated cDNAs from the same cell shared a common 10X Barcode. Following the reverse transcription, GEMs were broken and cDNAs were amplified and cleaned up with SPRIselect beads (Beckman Coulter®). Next, a portion of these cDNAs were enzymatically fragmented and subjected to adaptor ligation before using them as a PCR template for the incorporation of i5/i7 indexes. Finally, libraries were purified with SPRIselect beads, quantified and quality checked by using the 2200 TapeStation (Agilent®), and subjected to paired-end 150-bp sequencing (Novaseq systems, Illumina®) following standard practices at external facilities (Novogene®). Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001289

• PD-associated regulatory variants in human dopaminergic neurons reveals modulators of SCARB2 and BAG3 expression

  SNPs have been associated with the risk of Parkinson’s disease but not in regulatory regions. While those potentially disrupt TFBS altering gene expression and contributing to cis-regulatory variation. To study changes in A and B compartment interactions and in topologically associated domains (TADs), we sequenced: - 3D chromatin contact using LowC, 6 samples. 3 replicates for each condition: smNPC (controls) cells and differentiated neurons after 30 days. Resulting paired-end are provided as BAM files. In order to confirm the predicted impact of the PD-associated allele of rs144814361 on BAG3 promoter, we proceeded with genome editing of the TH-REP1 cell line by using prime editing to insert the “T” allele at the position chr10:119651405 in the BAG3 promoter. - Chromatin accessibility using ATAC-seq, 9 samples of derived cell line TH-REP1. 3 replicates for each condition: 1) iPSC Wild Type 2) SNP-BAG3 variant in iPSC 3) SNP-BAG3 variant in smNPC. BAG3 variant: heterozygous for the SNP variant: rs144814361 (chr10 119651405) Resulting sequencing are provided as paired-end FASTQ files.

  Dataset EGAD50000002258

• Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

  Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

  Dataset EGAD00001006013