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• NHLBI GO-ESP: Family Studies (Thoracic aortic aneurysms leading to acute aortic dissections)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Acute aortic dissections are a common cause of premature death in the United States, ranking as high as the 15th leading cause of death. The goal of the Familial Thoracic Aortic Aneurysm and Dissection (TAAD) study at the University of Texas Health Science Center at Houston is to identify the genes causing thoracic aortic disease, and prevent premature deaths due to aortic dissections by identifying individuals who are genetically predisposed to the disease and initiating medical and surgical therapies to prevent dissections. In this study ("NHLBI GO-ESP Family Studies: Aortic Disease"), we have selected a series of families from the TAAD study, and are performing exome sequencing of 2 to 3 individuals per family.

  Study phs000347

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: SPARK Simons Foundation Powering Autism Research for Knowledge

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002511

• Molecular Evolution of Cancer

  Recently developed methods that utilize partitioning of long genomic DNA fragments, and barcoding of shorter fragments derived from them, have succeeded in retaining long-range information in short sequencing reads. These so-called read cloud approaches represent a powerful, accurate, and cost-effective alternative to single-molecule long-read sequencing. We developed software, GROC-SVs, that takes advantage of read clouds for structural variant detection and assembly. We apply the method to two 10x Genomics data sets, one chromothriptic sarcoma with several spatially separated samples, and one breast cancer cell line, all Illumina-sequenced to high coverage. Comparison to short-fragment data from the same samples, and validation by mate-pair data from a subset of the sarcoma samples, demonstrate substantial improvement in specificity of breakpoint detection compared to short-fragment sequencing, at comparable sensitivity, and vice versa. The embedded long-range information also facilitates sequence assembly of a large fraction of the breakpoints; importantly, consecutive breakpoints that are closer than the average length of the input DNA molecules can be assembled together and their order and arrangement reconstructed, with some events exhibiting remarkable complexity. These features facilitated an analysis of the structural evolution of the sarcoma. In the chromothripsis, rearrangements occurred before copy number amplifications, and using the phylogenetic tree built from point mutation data, we show that single nucleotide variants and structural variants are not correlated. We predict significant future advances in structural variant science using 10x data analyzed with GROC-SVs and other read cloud-specific methods.

  Study phs001255

• University of Washington Cerebrospinal Fluid Biomarker Study for Parkinson disease

  There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

  Study phs000901

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Victorian Collaborative AuTism Study (CATS): Family and Community Study of the Genetics of Autism Spectrum Disorder

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002044

• Center for Craniofacial and Dental Genetics: Exome Sequencing of Orofacial Cleft Families

  Orofacial Clefts (OFCs) are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans. Affect about 1 in 800 newborns, OFCs are also one of the most common structural birth defects worldwide. OFCs can impose a substantial personal cost resulting from the associated emotional and financial burden. On average a child undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Individuals born with an OFC have higher infant mortality (especially in developing countries with limited access to care), higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genetic studies have focused on the contribution of common genetic variants through genome-wide linkage and association studies. These studies have revealed a significant etiologic heterogeneity. One promising approach to dissect the etiology of OFCs into focus on subclinical phenotypic features present in the non-cleft family members of affected individuals. These subclinical features are subtle phenotypic features that may represent mild manifestations of the same risk genes; thus, their inclusion in family-based studies may clarify the inheritance patterns in OFC families. In this project, we conducted whole exome sequencing in multiplex families with both overt OFCs and subclinical phenotypes to identify high-impact genes causing OFCs.

  Study phs001675

• High-Resolution Clonal Mapping of Multi-Organ Metastasis, and Resistance to Neoadjuvant Chemotherapy, in Triple Negative Breast Cancer

  Clonal dynamics during metastasis were studied in two patient-derived xenograft (PDX) models established from treatment-naive primary breast tumors from TNBC patients diagnosed with concurrent metastatic disease. Genomic sequencing and barcode-mediated clonal tracking revealed robust alterations in clonal architecture between primary tumors and metastases. Polyclonal seeding and maintenance of low-abundance subclones was observed in each metastatic lesion examined. Lung, liver, and brain metastases were enriched for an identical population of subclones. Clones dominating multi-organ metastases shared a genomic lineage. Thus, properties of rare mammary tumor subclones enabled the seeding and colonization of metastases in multiple secondary organ sites. In this study, patient-derived xenograft (PDX) models of treatment-naive TNBC and serial biopsies from TNBC patients undergoing NACT were used to elucidate mechanisms of chemoresistance in the neoadjuvant setting. Barcode-mediated clonal tracking and genomic sequencing of PDX tumors revealed that residual tumors remaining after chemotherapy maintained the subclonal architecture of untreated tumors yet their transcriptomes, proteomes, and histologic features were distinct from those of untreated tumors. Once treatment was halted, residual tumors gave rise to chemotherapy-sensitive tumors with similar transcriptomes, proteomes, and histological features to those of untreated tumors. Taken together, these results demonstrated that tumors can adopt a reversible drug-tolerant state that does not involve clonal selection as a chemotherapy resistance mechanism. Serial biopsies obtained from patients with TNBC undergoing NACT revealed similar histologic changes as well as maintenance of stable subclonal architecture, demonstrating that PDXs capture molecular features characteristic of human TNBC chemoresistance.

  Study phs001742

• National Heart Lung and Blood Institute Exome sequencing in SCID

  Analysis of the molecular etiologies of severe combined immunodeficiency (SCID) has led to important insights into the control of immune cell development. Most cases of SCID result from either X-linked or autosomal recessive inheritance of mutations in a known causative gene. However, in some cases, the molecular etiology remains unclear. To identify the cause of SCID in a patient known to lack the protein tyrosine phosphatase CD45, we utilized single nucleotide polymorphisms (SNP) arrays and whole exome sequencing. The patient's mother was heterozygous for an inactivating mutation in CD45, while the paternal alleles lacked mutations. The patient exhibited a single CD45 mutation identical to the maternal allele. Patient SNP array analysis revealed no change in copy number but loss of heterozygosity for the entire length of chromosome 1 (Chr1), indicating that disease was caused by uniparental disomy (UPD) with isodisomy of the entire maternal Chr1 bearing the CD45 mutation. Non-lymphoid blood cells and other mesoderm and ectoderm-derived tissues retained UPD of the entire maternal Chr1 in this patient who had undergone successful bone marrow transplantation. Exome sequencing revealed mutations in 7 additional genes bearing nonsynonymous SNPs predicted to have deleterious effects. These findings represent the first reported case of SCID caused by UPD and suggest UPD should be considered in SCID and other recessive disorders, especially when the patient appears homozygous for an abnormal gene found in only one parent. Evaluation for alterations in other genes affected by UPD should also be considered in such cases.

  Study phs000479

• Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI)

  (Excerpted/paraphrased from original grant application): FOCI seeks to expand our understanding of epithelial ovarian cancer through a coordinated and comprehensive approach. Project 1 will focus on discovery, expansion, and replication. By pooling GWAS, we expect to identify new associations and achieve independent replication, explore whether there are risk variants specific for histologic subtypes, and evaluate structural polymorphisms - copy number variants - as risk factors. Finally, Project 1 will leverage the GWAS data to correlate DNA variants with a new endpoint - survival. Project 2 will focus on biological studies designed to help inform interpretation of findings from Project 1. This will include efforts to identify the functional consequences of variants and improve understanding of biological mechanisms. Project 3 will include epidemiologic studies of gene by gene interaction, gene by environment interaction, and development of risk prediction models. The collective effort builds upon the strengths and history of collaboration inherent in the Ovarian Cancer Association Consortium (OCAC), a multidisciplinary group comprised of epidemiologists, genetic epidemiologists, statistical geneticists, molecular and cell biologists and clinicians that was formed in 2005. The FOCI Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs001133 FOCI Cohort. phs001131 Affymetrix Exome Chip phs001132 GWAS Meta Analysis phs001142 Mayo Omni Express phs001150 Mayo 2 5M

  Study phs001133

• Global Endometrial DNA Methylation Analysis Reveals Insights into mQTL Regulation and Associated Endometriosis Disease Risk and Endometrial Function

  Endometriosis is a common gynecological disorder affecting 11% of reproductive aged women and is a leading cause of pain and infertility. We investigated global DNA methylation (DNAm) profiles in endometrium associated with endometriosis, menstruation, and genetic variation. Endometrial samples were collected from 984 patients with confirmed endometriosis (n=637) and women without endometriosis (n=347). Patients were recruited through the University of California San Francisco, USA, University of Melbourne, Australia, Endometriosis CaRe Centre in Oxford, UK, and EXPPECT Centre, The University of Edinburgh, UK, using the World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project (WERF EPHect) standardized protocols for tissue collection and processing, and participant characteristics and clinical annotation. DNA was extracted from samples and was use to generate DNAm data using the Illumina Infinium MethylationEPIC Beadchip and genotype data using the Axiom Precision Medicine Research array. Estimates from this study suggest that 15.4% of the variation in endometriosis is captured by DNAm. DNAm analysis identified significant differences in DNAm profiles and DNAm networks, associated with endometriosis, endometriosis sub-phenotypes, and menstrual cycle phases. Integration of DNAm and genetic data in a DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis highlighting target genes contributing to disease risk. This study identified novel factors affecting epigenetic regulation in endometrium associated with endometriosis risk and disease heterogeneity and provides an important data resource for reproductive medicine. Genotype data generated as part of this study are available on dbGaP and methylation data are available on GEO.

  Study phs003307