Search Results - EGA European Genome-Phenome Archive

Cell-Free, Methylated DNA in Blood Samples Reveals Tissue-Specific, Cellular Damage from Radiation Treatment

Radiation therapy is an effective cancer treatment, although damage to surrounding healthy tissues can also occur. Cell-type specific DNA methylation patterns can be used to decode the cellular origins of cell-free DNA fragments, allowing for minimally-invasive monitoring of tissue damage. To evaluate whether changes in cell-free DNA methylation can indicate damages to tissues in patients treated with radiation, we collected serum samples from 15 breast cancer patients at three timepoints during their standard-of-care radiation therapy after surgery. A baseline sample was taken for each patient before onset of radiation therapy and a second End-Of-Treatment (EOT) sample was taken 30 minutes after the last treatment fraction. Finally, a recovery sample was taken one month after completion of radiation therapy. From serum samples, cell-free DNA was isolated and bisulfite capture-sequencing DNA methylation data were generated. Bisulfite capture-sequencing DNA methylation data were also generated from buffy coat and tissue-specific endothelial gDNA samples as well as from serum/plasma samples of healthy controls. The analysis of serum samples from breast cancer patients undergoing radiation treatment revealed distinct tissue-specific epithelial and endothelial responses to radiation across multiple organs. In conclusion, as a proof of concept we show that cell-type specific methylation signatures can be applied to detect cellular injury from radiation treatment using minimally invasive cell-free DNA in blood samples.

Study phs003290

NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Lung Health Study of Chronic Obstructive Pulmonary Disease)

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. The Lung Health Study I was a randomized multicenter clinical trial with 5887 participants carried out from October 1986 to April 1994, designed to test the effectiveness of smoking cessation and bronchodilator administration in smokers aged 35 to 60 with mild lung function impairment. Participants were randomly assigned to one of three groups: usual care, who received no intervention smoking intervention with the inhaled bronchodilator ipratroprium bromide smoking intervention with an inhaled placebo The effect of intervention was evaluated by the rate of decline of forced expiratory volume in one second (FEV1).

Study phs000291

NIMH (National Institute of Mental Health) De Novo Mutation Identification in Taiwanese Schizophrenia Trios

The substantial reproductive impact of schizophrenia, for which affected individuals have fewer than half as many offspring as unaffected individuals do, implies that mutations of largest effect will frequently be de novo mutations. Ascertaining exome sequence variation in father-mother-offspring trios allows such mutations to be identified and distinguished from the far-larger amount of rare variation that is inherited by each individual. The pursuit of this approach in a large, well-powered cohort of trios can also provide lessons that inform the development of such gene discovery strategies more generally in human genetics. Schizophrenia trios from the Taiwanese population are being collected by Dr. Ming Tsuang (PI, UC San Diego, California) and investigators in Taiwan (PI, Dr. Hai Gwo Hwu; both funded by NIMH grant 1R01MH085560; Expanding Rapid Ascertainment Networks of Schizophrenia Families in Taiwan). A total of 3800 trios are anticipated to be collected by May 2013. This represents a highly homogenous national sample from the same ancestral population. DNA samples will be obtained from the NIMH Repository, Rutgers University Cell and DNA Repository (described below) and stored at the Broad Institute. Genetic and data analyses will be performed at the Broad Institute. We propose to sequence the whole exome of trios by hybrid capture and Illumina next generation sequencing and perform targeted genotyping and validation of variants (SNPs, indels and CNVs) using several molecular methods, to include emulsion-based PCR and Sanger sequencing.

Study phs001196

National Cancer Institute (NCI) Genome-Wide Association Study (GWAS) of Renal Cell Carcinoma in African Americans

The NCI GWAS of renal cell carcinoma (RCC) in African Americans was undertaken to provide insight into genetic loci affecting susceptibility to this malignancy in a racial group known to be at elevated risk. We genotyped 1,136,723 single-nucleotide polymorphisms (SNPs) among 255 cases and 375 controls of African ancestry from the NCI Kidney Cancer Study, and further investigated 16 SNPs in a replication set consisting of 140 cases and 543 controls from a case-control study conducted at the University of Texas MD Anderson Cancer Center. The variant rs10771279 located on 12p11, 77kb from a European-ancestry RCC risk marker, was associated with RCC risk in the GWAS (P=1.2 x 10-7) but did not replicate (P=0.99). The variant 7105934 on 11q13.3, previously associated with RCC in a GWAS using European-ancestry samples, was associated with risk in both studies [meta-analysis odds ratio (OR)=0.76, 95% confidence interval (CI)=0.64-0.91; P=0.0022]. The frequency of this allele was higher than that observed in the European-ancestry GWAS (0.56 and 0.07 respectively among controls). The rs7105934 association was stronger for clear cell RCC (ccRCC: OR=0.56; P=7.4 x 10-7) and absent for cases of other or unknown histology (OR=1.02; P=0.86). In conclusion, this study provides evidence that rs7105934 is a susceptibility locus for RCC, and clear-cell RCC in particular, among African Americans.

Study phs000863

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

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 phs002043

MAITS in HCC

Hepatocellular Carcinoma (HCC) is a leading cause of cancer-related death and can be considered a prototype of inflammation-derived cancer arising from chronic liver injury. The cell composition of the HCC tumor immune microenvironment (TiME) has a major impact on cancer biology as the TiME can have divergent capacities on tumor initiation, progress, and response to therapy. Recent development of multi-omics and single-cell technologies help us to comprehensively quantify the cellular heterogeneity and spatial organization of the TiME and to further our understanding of antitumor immunity. We investigated the cellular composition of liver cancer patient samples (n=8) using single-cell RNA-seq. For this purpose, mononuclear cells were isolated from human liver cancer samples. Three locations within the tumor-bearing liver were used: adjacent liver, rim and tumor core. Then, cells were FACS sorted (either CD45+ cells or MAIT cells) and subjected to 10X Chromium-based scRNA-seq. We investigated immune cell changes and the cellular heterogeneity of the HCC TiME with a focus on MAIT cells. Annotated H5 files are provided. Clinical metadata including TMN stage, sex, gender, ethnicity, pretreatment, and histopathological reports are available for all patient samples. Further details on the study can be obtained in our paper once it’s published.A complementary dataset derived from ultrahighplex CO-Detection by indEXing (CODEX) from paired patient samples can be accessed through The Cancer Imaging Archives (TCIA) under DOI: https://doi.org/10.7937/bh0r-y074.

Study phs003279

Systems genetics in human endothelial cells identifies non-coding variants modifying enhancers, expression, and complex disease traits

Identification of causal variants and mechanisms underlying complex disease traits in humans requires strategies to locate and fine-map functional regulatory variants in disease-relevant cell types. To discover functional regulatory variants in primary aortic endothelial cells (ECs) from humans, we collected genetic, transcriptomic, and four epigenomic phenotypes in a population of 153 human donors representing individuals of both sexes and three major ancestries. We found thousands of EC eQTLs that were not present in GTEx at all ranges of effect sizes, indicating novel functional variants not observable from tissue data. We performed several epigenetic assays across 53 donors' EC to enable molecular QTL mapping, which included chromatin accessibility, histone modification, and transcription factor binding of proteins ERG and NF-kB/p65 in two activation states. We discovered over 3000 regulatory elements where cis-regulatory variants associated to significant differences in epigenetic marks. Co-localization with our eQTLs, TF motif mutations, and 3D confirmation capture data in ECs enabled our discovery of hundreds of high-confidence functional regulatory elements that perturb endothelial molecular phenotypes. Furthermore, this set of variants is enriched at GWAS loci for Coronary Artery disease and other disease traits, with some SNPs demonstrating pleiotropic effects. Together, our dataset and analytical approach provide the genetics and vascular biology communities with specific variants affecting EC biology and serves as a proof-of-principle for how to detect functional regulatory variants in human cells with relevance to complex traits.

Study phs002057

International Consortium on the Genetics of Systemic Lupus Erythematosus (SLEGEN)

The genetic makeup of an individual strongly influences the risk of developing systemic lupus erythematosus (SLE). The identification of genes that predispose an individual to SLE will lead to earlier and better diagnosis, better treatments, and possibly prevention. To this end, the International Consortium on the Genetics of Systemic Lupus Erythematosus (SLEGEN) was formed in 2005 and is composed of lupus researchers who agreed to pool their knowledge and resources to search for genes that predispose to lupus. Eight laboratories contributed DNA samples for genotyping at the Broad Institute and association with SLE was performed by the Data Coordinating Center (Wake Forest University), as part of a four stage study design. Stages one and two of this design were graciously funded by the Alliance for Lupus Research (www.lupusresearch.org). In this stage of the study, approximately 767 SLE patients (cases) were compared to approximately 383 non-SLE patients (controls) for differences among the Illumina HumanHap300. The affected individuals are all females of European decent. 82% of the cases are the index case from multiplex pedigrees for SLE and the remaining 18% have self-reported first degree relatives with SLE. A detailed summary of the methods and results can be found in the manuscript in Nature Genetics February 2008 by SLEGEN "Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants ITGAM, PXK, KIAA1542 and other loci". (Please see also Study Accession: phs000202.v1.p1)

Study phs000216

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

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 phs002509

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Homozygosity Mapping Consortium for Autism (HMCA)

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 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 phs001894

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Simons Searchlight

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 phs002512

Indexing Genes Impacted by Copy Number Variation in Developmental Disorders

A challenge in clinical genomics is to predict whether copy number variation (CNV) affecting a gene or multiple genes will manifest as disease. Increasing recognition of gene dosage effects in neurodevelopmental disorders prompted us to develop a computational approach based on critical-exon (highly expressed in brain, highly conserved) examination for potential etiologic effects. Using a large CNV dataset, our updated analyses revealed significant (P < 1.64 x 10-15) enrichment of critical-exons within rare CNVs in cases compared to controls. Separately, we used a weighted gene co-expression network analysis (WGCNA) to construct an unbiased protein module from prenatal and adult tissues and found it significantly enriched for critical exons in prenatal (P < 1.15 x 10-50, OR = 2.11) and adult (P < 6.03 x 10-18, OR = 1.55) development. WGCNA yielded 1,206 proteins for which we prioritized the corresponding genes as likely to have a role in neurodevelopmental disorders. We compared the gene lists obtained from critical-exon and WGCNA analysis and found 438 candidate genes associated with CNVs annotated as pathogenic, or variants of uncertain significance (VOUS), from among 10,619 developmental delay cases. We identified genes containing CNVs previously considered to be VOUS, to be new candidate genes for neurodevelopmental disorders (GIT1, MVB12B and PPP1R9A) demonstrating the utility of this strategy to index the clinical effects of CNVs. Reprinted from Uddin et al, 2016, with permission from Scientific Reports.

Study phs001154

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Center of Excellence (ACE II)

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 phs002042

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Study of Autism Genetics Exploration (SAGE)

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 phs001740

Genomic Architecture of Progression and Treatment Response in AMD

Numerous studies have identified common and rare genetic variation associated with risk of advanced age-related macular degeneration (AMD). However, risk is just one facet of AMD disease architecture. Both disease progression and response to treatment are two critical elements that may also be influenced by genetic variation. The primary aim of this study was to identify genetic variation influencing progression and response to treatment for AMD, with a secondary aim of further elucidating the genetic etiology of AMD risk. We ascertained AMD cases and controls of European ancestry from Vanderbilt Eye Institute (VEI) and the Bascom Palmer Eye Institute (BPEI) and obtained blood samples from all participants. Eyes were examined using standard ophthalmological methods, and graded according the modified Age-Related Eye Disease Study scale (AREDS grades 1-5) using fundus photography. Individuals were re-examined in follow-up exams at regular intervals to assess any change in AMD grade. Eyes with advanced neovascular AMD that were examined using ocular coherence tomography imaging (OCT), treated with anti-angiogenesis therapy and monitored for response to treatment. All individuals ascertained for the study were exome-chipped for genome-wide single nucleotide variation coverage. To target rare genetic variation, whole exome sequencing was performed on individuals at the phenotypic extremes based on 1) AMD grade, 2) rate of progression from intermediate to advanced AMD and 3) response to anti-VEGF treatment for eyes with advanced neovascular AMD.

Study phs001046

Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

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 phs002004

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Genetic Resource Exchange

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 phs001766

Detection and Targeting of Splicing Deregulation in Pediatric Acute Myeloid Leukemia Stem Cells

This study evaluates the gene expression and splicing changes between pediatric patients with and without Acute Myeloid Leukemia (AML) and pediatric and adult patients with AML. We obtained bone marrow or peripheral blood from patients and isolated CD34+ stem and/or progenitor cells from pediatric patients with AML (10) or without AML (6) and adult patients with AML (5). In parallel, a targeted analysis for known, deleterious, genetic mutations in the KRAS, NRAS, and KMT2C genes identified 2, 5, and 6 AML patients with alterations, respectively. Additionally, Tapestri analysis further identified a mutation in the intronic region of the SF3B1 gene in multiple pediatric AML patients. RNA-Seq was performed on the purified cell populations at The Scripps Research Institute Next Generation Core on an Illumina NextSeq 500 sequencer with 150bp paired-end reads.These datasets revealed that, similar to adult AML, pediatric AML samples were enriched for Leukemia Stem Cells (LSC) markers. A deeper analysis showed widespread dysregulation of splicing in pediatric AML samples compared to age-matched non-leukemic samples. In addition, the splicing regulator RBFOX2 was downregulated with an accompanying increase in specific CD47 splice isoforms in the pediatric AML samples. Thus, the increased presence of LSCs in pediatric AML is possibly driven by global splicing deregulation, and the treatment with splicing modulators like Rebecsinib has a potential therapeutic value for eradicating LSCs in these patients.

Study phs003196

Tumor Mutation Burden, Expressed Neoantigen and Immune Microenvironment in Diffuse Gliomas

A consistent correlation between tumor mutation burden (TMB) and tumor immune microenvironment has not been observed in gliomas as in other cancers. Driver germline and somatic mutations, TMB, neoantigen, and immune cell signatures were analyzed using whole exome sequencing (WES) and transcriptome sequencing of tumor and WES of matched germline DNA in a cohort of 66 glioma samples (44 IDH-mutant and 22 IDH-wildtype). Fourteen samples revealed a hypermutator phenotype (HMP). Eight pathogenic (P) or likely pathogenic (LP) germline variants were detected in 9 (19%) patients. Six of these 8 genes were DNA damage repair genes. P/LP germline variants were found in 22% of IDH-mutant gliomas and 12.5%of IDH-wildtype gliomas (p= 0.7). TMB was correlated with expressed neoantigen but showed an inverse correlation with immune score (R =−0.46, p= 0.03) in IDH-wildtype tumors and no correlation in IDH-mutant tumors. Antigen Processing and Presentation (APP) score correlates with immune score. The APP is higher in non-hypermutator phenotype (NHMP) samples versus HMP samples in the IDH-wildtype gliomas, but higher in HMP samples versus NHMP samples in the IDH-mutant gliomas. Conclusion: TMB was inversely correlated with the immune score in the IDH-wildtype gliomas, and showed no correlation in the IDH-mutant tumors. The APP was correlated with the immune score, and may be further investigated as a biomarker for response to immunotherapy in gliomas. Studies of germline variants in a large glioma cohort are warranted.

Study phs002653

Expression of Activation Induced Cytidine Deaminase and Risk of Transformation in Follicular Lymphoma

It is currently unclear how to identify follicular lymphoma (FL) patients with low disease burden but high risk for early progression. Building on a prior study demonstrating early transformation in FLs with high variant allele frequency (VAF) BCL2 mutations at activation-induced cytidine deaminase (AICDA) sites, we examined 11 AICDA mutational targets, including BCL2, BCL6, PAX5, PIM1, RHOH, SOCS1, and MYC, in a more contemporary cohort of 199 newly diagnosed grade 1 and grade 2 FLs using targeted capture and massively parallel sequencing. BCL2 mutations with VAF >20% occurred in 52% of cases. Among 97 FLs that did not initially receive rituximab-containing therapy, nonsynonymous BCL2 mutations at VAF >20% were associated with shorter, event-free survival (EFS, median 1.4 years with these mutations versus 4.5 years without, p = 0.048), and increased risk of transformation (HR 3.01, 95% CI 1.03-8.77, p = 0.04). Other sequenced genes were less frequently mutated and did not significantly increase the prognostic value of the panel. Across the entire population, BCL2 mutations at VAF >20% were associated with decreased EFS (HR 1.58, 95% CI 1.03-2.40, p = 0.034 after correction for FLIPI and treatment) and decreased overall survival after median 14-year follow-up (HR 1.86, 95% CI 1.07-3.23, p = 0.029). Thus, high VAF BCL2 mutations remain a prognostic factor for FL even in the chemoimmunotherapy era and might need to be considered in future study design.

Study phs002845

Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

Study phs001041

Center for Common Disease Genomics (CCDG) Neuropsychiatric: The Autism Simplex Collection (TASC)

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 phs001741

NIAID Centralized Sequencing Program

Investigators at the National Institute of Allergy and Infectious Diseases (NIAID) use next-generation sequencing technologies to help determine genetic contributions to immune diseases. These efforts have increased rates of molecular diagnosis for a subset of NIAID participants as well as uncovered fundamental insights into the cellular and signaling pathways in host defense and immune regulation. Despite these successes, analysis and interpretation of genomic data remain a substantial challenge. Simply, researchers do not understand the functional and clinical consequences of most human genetic variation. Making progress in this area requires a coordinated, systematic, and transparent approach to clinical genomics research. This protocol is specific to genetic testing and explicitly aims to both strengthen clinical care and enhance research. Probands provide biological specimens for genetic testing and primary clinical and research evaluations are completed via a research protocol at NIAID. This protocol serves as a vehicle for a programmatic effort that includes standardized phenotyping, test ordering through the Clinical Research Information System (CRIS) at the National Institutes of Health Clinical Center, sample collection and isolation, nucleic acid analysis, bioinformatics, clinical interpretation, reporting in CRIS, genetic counseling, and supporting effective use of genomics as a research tool throughout the institute. Overall, increased process standardization will support data integrity and efficiency while still accommodating the need for investigator flexibility. This study aims to generate and analyze evidence regarding the genetic contribution to diverse immune diseases studied by the NIAID intramural research program.

Study phs001899

Medulloblastoma exome sequence analysis

Medulloblastomas are the most common malignant brain tumors in children. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles. Here, we utilized whole exome hybrid capture and Illumina sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, to our knowledge novel findings in medulloblastoma and all cancer. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma. "Reprinted from 'MEDULLOBLASTOMA EXOME SEQUENCING UNCOVERS SUBTYPE-SPECIFIC SOMATIC MUTATION', with permission from Nature"

Study phs000504

Utility of Capillary Blood in Gene Expression Studies

The FAA Functional Genomics Team examined the feasibility of analyzing gene expression profiles using capillary blood collected by fingerstick, with the goal of developing practical fingerstick blood collections to expand blood collection capabilities and allow large-scale or field-based collections. We compared the RNA sequencing results obtained from two different capillary blood collection and RNA extraction methods with the results obtained from a standard venous blood collection and RNA extraction protocol. We also compared capillary blood processing methods, as well as fingerstick locations, within one capillary collection/extraction method. Within each method we sought to distinguish male from female participants to assess the capacity of each collection/extraction method for gene expression profiling. The study population included 40 participants aged 18-60 who were free from any acute illness or any illness that would preclude blood collection. We determined that capillary blood possesses large-scale significant differences from venous blood and that the two capillary methods produced similar gene expression profiles. We further determined that all methods were useful for detecting gene expression differences between assessed groups (male and female participants in this case). We conclude that capillary blood is suitable for gene expression profiling in quantities as low as 100 μL whole blood, but recommend that researchers should rely on a single blood collection method if they desire to compare results between individual studies. Raw sequencing files (.fastq) from this study are available in dbGaP.

Study phs003496

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