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• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Prematurity and Respiratory Outcomes Program (PROP) Core Database Protocol (PROP-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 Prematurity and Respiratory Outcomes Program (PROP) was performed to identify suitable predictors of respiratory outcomes that may serve as surrogate endpoints in future trials of prevention and therapy of respiratory diseases in preterm infants.Background: Acute and chronic respiratory morbidities are common in premature births, and can pose significant risk to the infant's health, particularly during the first two years of life. One such condition is bronchopulmonary dysplasia (BPD) where infants require oxygen therapy due to abnormal repair and impaired lung development after acute lung injury. BPD poses a high mortality risk, even in infants that survive the initial hospitalization. Regardless of BPD diagnosis, preterm infants frequently return for medical care due to symptoms of post-prematurity respiratory disease (PRD), which includes intermittent or chronic wheezing, cough without cold, poor growth, apnea and cyanosis, and lower respiratory tract infections. Impaired lung function can persist into adulthood, contributing to chronic respiratory diseases including asthma and emphysema.However, at the time of the PROP study, there were no objective measures to predict which preterm infants would have persistent respiratory problems after discharge from the hospital. Furthermore, improved survival rates of premature infants and the high prevalence of lasting respiratory morbidities highlight the need for more comprehensive strategies to address both short-term and long-term respiratory complications. Thus, the Prematurity and Respiratory Outcomes Program (PROP) was formed to investigate multiple research hypotheses on the molecular mechanisms that contribute to respiratory disease risk of premature neonates over the first year of life. Specifically, PROP investigators hypothesized that in survivors of extreme prematurity to 36 weeks postmenstrual age (PMA), specific biologic, physiologic and clinical data obtained during the initial hospitalization will predict respiratory morbidity between discharge and 1 year corrected age. Participants: A total of 835 infants were enrolled.Design: PROP was a collaboratively developed multicenter prospective cohort study of very preterm infants from birth through the time of discharge from the NICU and up to one year corrected age.Clinical data included maternal and infant demographics, co-morbidities, and daily infant respiratory, nutritional, and medication data until discharge. These were prospectively collected from birth using medical record review and family interviews. After discharge, phone interviews were conducted with the infant's main caregiver at 3, 6, 9 and 12 months corrected age to assess domains of respiratory morbidity. At 6 and 12 months corrected age, a survey of environmental respiratory irritant exposures and an assessment for gastroesophageal reflux disease were also completed. A standardized physical exam was performed at 36-40 weeks PMA and again at one year corrected age. The exam focused on anthropometrics, vital signs, and respiratory system signs. At 34-41 weeks PMA and within one week of anticipated discharge based on physiologic stability, a set of non-invasive respiratory assessments were performed to assess physiologic biomarkers in infants that were not mechanically ventilated or receiving non-invasive positive pressure ventilation. Respiratory inductance plethysmography (RIP) was performed before and after inhaled albuterol to assess potential airway reactivity. During the RIP study, continuous pulse oximetry was performed during quiet sleep in order to analyze oxygen desaturations and apneas. Standardized oxygen requirement challenge tests were performed at about 36 weeks PMA, and at about 40 weeks PMA if the infant was still hospitalized and was not eligible for, or failed, the previous challenge. Failure was defined as SpO2 20 seconds at any point in the testing. Infants breathing ambient air or that passed the 36 week challenge test underwent a hypoxia challenge consisting of a 15-minute trial of FiO2 of 0.15. Failure was defined as SpO2 The primary outcome was respiratory morbidity, as measured by the presence or absence of substantial post-prematurity respiratory disease (PRD) up to one year corrected age. PRD was classified as a positive response in at least one of four morbidity domains during at least two separate parental interviews. The domains were respiratory medications, hospitalizations for cardiopulmonary cause, respiratory symptoms, and home technology dependence (oxygen, ventilator, or CPAP/BiPAP). Mortality from a respiratory cause was also incorporated.

  Study phs004117

• 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

• Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  While endometrioid and mucinous ovarian cancers represent nearly a quarter of ovarian cancers, their molecular characteristics and pathologic origins are poorly understood. To characterize the genomic and epigenomic alterations of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed sequence, copy number, mutation signature, rearrangement, and methylation analyses from tumor samples and matched normal tissues of 133 patients. These analyses included patients with ovarian endometrioid (n=44), ovarian mucinous (n=43), uterine endometrial (n=15), and gastrointestinal mucinous cancers (n=31). In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4 and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous cancers. Whole genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid tumors, and NF1 and MED1 in ovarian mucinous cancers. The number of alterations and affected genes in ovarian and uterine endometrioid cancers were similar as were genome-wide methylation profiles, suggesting that these tumors may have a similar tissue of origin. By contrast, methylation patterns in ovarian mucinous cancers were more similar to other gastrointestinal mucinous cancers, including mucinous cancers of the stomach, colon, and pancreas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers.

  Study EGAS50000000523

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049

• National Institute on Alcohol Abuse and Alcoholism (NIAAA) Postmortem Prefrontal Cortex eQTL and mQTL Study

  Mapping expression and methylation quantitative trait loci (eQTLs and mQTLs) using genome-wide genotype, transcriptome, and DNA methylome data can provide an unbiased approach to identify novel functional variants. One critical issue of the eQTL/mQTL analysis is that the role of genetic variants in regulating gene expression (or DNA methylation) can be tissue- or cell-specific. To unravel causal variants from disease-associated loci, it would be necessary to map eQTLs and mQTLs in both patients and controls. Those eQTLs and mQTLs in patients are more likely to be causal variants for the disease. Identification of disease- and tissue-specific eQTLs and mQTLs will help disentangle the role of the specific tissue in disease development as well. In the present study, we mapped eQTLs and mQTLs in postmortem prefrontal cortex of patients with alcoholism or alcohol use disorder (AUD) and matched control subjects by integrative analyses of genome-wide SNP genotype, mRNA transcriptome, and DNA methylome data. As AUD is comorbid with schizophrenia (SCZ), bipolar disorder (BIP), major depressive disorder (MDD), and attention deficit/hyperactivity disorder (ADHD), we further examined the co-localization of PFC eQTLs/mQTLs and GWAS-identified SNPs (mainly noncoding SNPs) that were associated with AUD as well as comorbid SCZ, BIP, MDD, and ADHD. Our study demonstrated the enrichment of PFC eQTLs/mQTLs in the above psychiatric disorder-associated genetic variants identified by genome-wide association studies (GWAS).

  Study phs001981

• scRNA-seq dataset for AD and Pso patients

  This dataset contains scRNA-seq fastq files to the paper entitled "Single-cell profiles reveal distinctive immune response in atopic dermatitis in contrast to psoriasis". The details of experiment setup was described in the paper.

  Dataset EGAD00001010106

• Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing

  Chromosomal translocations with immunoglobin (IG) loci are the classic drivers in a large subset of B-cell lymphomas. Detection of these translocations is important for confirmation of diagnosis and for prognosis and therapy decisions. Currently, molecular diagnosis of translocations in lymphomas is not addressed well by Next Generation Sequencing (NGS). The standard method for detection of translocations is Fluorescence In Situ Hybridization (FISH), which is labor-intensive, and can be difficult to interpret. There is a need for a robust technology that can be standardized. Targeted Locus Capture (TLC) selectively enriches and sequences entire genes based on the crosslinking of physically proximal sequences, and thereby enables complete sequencing of genes of interest, including detection of large structural variants. Because the technology is based on the crosslinking and fragmenting of DNA, it has particular advantages in the analysis of Formalin-Fixed, Paraffin-Embedded (FFPE) samples, in which DNA is inherently crosslinked and fragmented. In order to validate the FFPE-TLC technology as a novel approach for translocation detection in lymphoma samples, we have developed a panel assay containing genes with frequent translocations (MYC, BCL2, BCL6, IG loci). With this assay we have analyzed >140 lymphoma and control FFPE samples of variable input amounts and qualities that had previously been analyzed with FISH, and a subset also with standard targeted NGS. Good concordance with FISH results was observed for both translocation positive and negative samples. In 10 cases for which FFPE-TLC detected a relevant fusion and FISH had been called negative, discordance could be explained by higher sensitivity of FFPE-TLC or by inconclusive FISH results. In a specific case, FFPE-TLC detected a small-distance rearrangement on chromosome 3 that caused a BCL6 fusion but led to insufficient and therefore undetectable break-apart with FISH. Secondly, the FFPE-TLC approach was tested on a set of 19 B-cell lymphoma FFPE samples that had previously been analyzed using standard targeted NGS and FISH and was enriched for discordant results between these methods. FFPE-TLC-based NGS enables more robust translocation calling as the detection relies on broad sequencing coverage across the translocation partner rather than on breakpoint sequences only. In 3 cases, FFPE-TLC could proof false negative calls in standard targeted NGS due to breakpoints located in regions difficult to capture or to sequence. In 1 case, standard targeted NGS had made a false positive call on a breakpoint sequence that was shown to be caused by a small insertion rather than a genuine translocation. This study shows that FFPE-TLC promises to be a robust alternative for FISH analysis and standard targeted NGS procedures in lymphoma diagnostics and possibly in other cancers with frequent structural variants. The FFPE-TLC approach enables a single, DNA-based NGS test detecting both small mutations and translocations.

  Study EGAS00001004760

• Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer

  Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers – either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions.Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array.

  Study EGAS00001002763

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002