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• Impact of DIS3 Aso on BCR repertoir in human buffy coat purified B-Cells

  The aim is to identify difference in the BCR of Aso DIS3 treated cells compared to Control Aso. Using extracted DNA from human B-cells

  Study EGAS50000001107

• Investigation of molecular diagnosis by molecular biological analysis using next-generation sequencer for actionable endocrine diseases (including neoplastic diseases)

  Fructose-1,6-bisphosphatase (FBPase) deficiency, caused by an FBP1 mutation, is an autosomal recessive disorder characterized by hypoglycemic lactic acidosis. Due to the rarity of FBPase deficiency, the mechanism by which the mutations cause enzyme activity loss still remains unclear. Here we identify compound heterozygous missense mutations of FBP1, c.491G>A (p.G164D) and c.581T>C (p.F194S), in an adult patient with hypoglycemic lactic acidosis. The G164D and F194S FBP1 mutants exhibit decreased FBP1 protein expression and a loss of FBPase enzyme activity. The biochemical phenotypes of all previously reported FBP1 missense mutations in addition to G164D and F194S are classified into three functional categories. Type 1 mutations are located at pivotal residues in enzyme activity motifs and have no effects on protein expression. Type 2 mutations structurally cluster around the substrate binding pocket and are associated with decreased protein expression due to protein misfolding. Type 3 mutations are likely nonpathogenic. These findings demonstrate a key role of protein misfolding in mediating the pathogenesis of FBPase deficiency, particularly for Type 2 mutations. This study provides important insights that certain patients with Type 2 mutations may respond to chaperone molecules.

  Study JGAS000625

• A somatic reference standard for cancer genome sequencing with COLO829

  Identification of somatic alterations in cancer has become feasible with the massive adoption of next generation sequencing. However, due to variability in sequencing and informatics pipelines, a common somatic reference is needed. We thus performed paired whole genome sequencing of a metastatic melanoma cell line (COLO829) and a matched lymphoblastoid line (COLO829BL) across three institutions (TGen, Illumina, Genome Sciences Centre at the British Columbia Cancer Agency). We performed a meta-analysis of all data, in combination with the originally reported analysis of these cell lines by Pleasance et al (PMID: 20016485), and report a somatic reference standard based on consensus events. DNA extractions, library preparation, sequencing, and analysis were separately performed at each site. Results were compiled with sequence data previously generated for the cell lines to identify true positive variants, collectively representing a somatic reference standard. Overall, common somatic events include point mutations, small insertion/deletions, and genes affected by concurrent copy number changes. We additionally show divergence of somatic mutations in COLO829 associated with differences in cell line lineage. We present this reference to the community as a standard for enabling interpretation and identification of somatic mutations across institutions and analytical pipelines.

  Study EGAS00001001385

• Whole genome sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia

  TCF3::PBX1 leukemia is a rare subtype of B-cell acute lymphoblastic leukemia (B-ALL), occurring in approximately 3–5% of pediatric cases. It results from a chromosomal translocation t(1;19)(q23;p13), generating the TCF3::PBX1 fusion gene, which disrupts normal transcriptional regulation and contributes to leukemogenesis. Although historically associated with poor prognosis, contemporary risk stratification and intensified therapy have significantly improved outcomes, and both 5-years DFS and OS are nowadays ≥ 0.96.

  Study EGAS50000001257

• Panel sequencing of endocrine-resistant breast cancer

  Patients with endocrine-resistant breast cancer in Stockholm Sweden. DNA obtained from patients primary and relapse tumors, and tumor-free lymph nodes used as germline control. DNA was extracted from formalin-fixed paraffin-embedded tissue and sequenced by 370-gene panel-based sequencing with Kapa HyperPlus library preparation and Twist Bioscience hybrid capture. Custom bait sets (panels) from Twist Bioscience. Paired end 2x150 bp using NovaSeq X. The data is presented as fastq-files.

  Study EGAS50000000236

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia

  TCF3::PBX1 leukemia is a rare subtype of B-cell acute lymphoblastic leukemia (B-ALL), occurring in approximately 3–5% of pediatric cases. It results from a chromosomal translocation t(1;19)(q23;p13), generating the TCF3::PBX1 fusion gene, which disrupts normal transcriptional regulation and contributes to leukemogenesis. Although historically associated with poor prognosis, contemporary risk stratification and intensified therapy have significantly improved outcomes, and both 5-years DFS and OS are nowadays ≥ 0.96.

  Study EGAS50000001797

• Sporadic Parathyroid Carcinoma

  This dataset is compromised of 5 sequencing experiments from a single patient with sporadic and recurring parathyroid carcinoma. The samples include whole genome sequence of the primary tumor, the first recurrent tumor and peripheral blood. Whole transcriptome sequence of the first and second recurrent tumors are also included.

  Dataset EGAD00001000370

• Integrative genomic and transcriptomic analysis of adult leiomyosarcoma (HIPO-028, HIPO-018, HIPO-021)

  Leiomyosarcoma (LMS) is an aggressive mesenchmyal malignancy with few therapeutic options. The mechanisms underlying LMS development, including clinically actionable genetic vulnerabilities, are largely unknown. We performed genomic and transcriptomic profiling of a large cohort of LMS tumors and identified substantial mutational heterogeneity, near-universal inactivation of TP53 and RB1, widespread DNA copy number alterations, chromothripsis, and frequent whole-genome duplication. Furthermore, we discovered recurrent alterations in telomere maintenance genes such as ATRX, RBL2, and RPA1, resulting in alternative lengthening of telomeres in 78% of cases. Finally, most tumors displayed hallmarks of “BRCAness”, including alterations in various homologous recombination DNA repair genes, multiple structural rearrangements, and enrichment of specific mutational signatures, and cultured LMS cells were sensitive towards olaparib and cisplatin treatment. This first comprehensive study of genetic alterations in LMS has uncovered key biological features that may inform future experimental research and enable the design of novel therapeutic strategies for this disease.

  Study EGAS00001002437

• Comparing nodal versus bony metastatic spread using tumour phylogenies

  The role of lymph node metastases in distant prostate cancer dissemination and lethality is ill defined. Patients with metastases restricted to lymph nodes have a better prognosis than those with distant metastatic spread, suggesting the possibility of distinct aetiologies. To explore this, we traced patterns of cancer dissemination using tumour phylogenies inferred from genome-wide copy-number profiling of 48 samples across 3 patients with lymph node metastatic disease and 3 patients with osseous metastatic disease. Our results show that metastatic cells in regional lymph nodes originate from evolutionary advanced extra-prostatic tumour cells rather than less advanced central tumour cell populations. In contrast, osseous metastases do not exhibit such a constrained developmental lineage, arising from either intra or extra-prostatic tumour cell populations, at early and late stages in the evolution of the primary. Collectively, this comparison suggests that lymph node metastases may not be an intermediate developmental step for distant osseous metastases, but rather represent a distinct metastatic lineage.

  Study EGAS00001001801

• Whole genome sequencing delineates regulatory, structural, and cryptic splice variants in early onset cardiomyopathy

  Cardiomyopathy (CMP) is a heritable disorder. Over 50% cases are gene-elusive on clinical gene panel testing. The contribution of variants in non-coding DNA elements that result in cryptic splicing and regulate gene expression has not been explored. We analyzed whole genome sequencing (WGS) data in a discovery cohort of 209 pediatric CMP patients and 1,953 independent replication genomes and exomes. We searched for protein-coding variants, and non-coding variants predicted to affect the function or expression of genes. Thirty-nine % cases harbored pathogenic coding variants in known CMP genes, and 5% harbored high-risk loss-of-function (LoF) variants in additional candidate CMP genes. Fifteen % harbored high-risk regulatory variants in promoters and enhancers of CMP genes (Odds ratio 2.25, p=6.70×10-7 versus controls). Genes involved in α-dystroglycan glycosylation (FKTN, DTNA) and desmosomal signaling (DSC2, DSG2) were most highly enriched for regulatory variants (Odds ratio 6.7-58.1). Functional effects were confirmed in patient myocardium and reporter assays in human cardiomyocytes, and in zebrafish CRISPR knockouts. We provide strong evidence for the genomic contribution of functionally active variants in new genes and in regulatory elements of known CMP genes to early-onset CMP.

  Study EGAS00001004929

• A GWAS meta-analysis on severe acne on a European population of 26,722 individuals

  Acne vulgaris is a highly heritable common, chronic inflammatory disease of the skin. We performed a genome-wide association study of 3,823 cases and 16,144 controls followed by meta-analysis with summary statistics from a previous study, with a total sample size of 26,722. We identified 20 independent association signals at 15 risk loci, 12 of which have not been previously implicated in the disease.

  Study EGAS00001003278

• Somatic L1 retrotranspositions in normal human cells

  Genomic mutations accumulate in normal cells during lifetime; however, somatic mosaicism generated by mobilization of transposable elements is not well understood. Here, we explored whole-genome sequences of single-cell expanded clones to illustrate the mutational landscape produced by L1. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 and read-through RNA expression profiles to investigate the epigenetic regulation of L1 activity.

  Study EGAS00001006213

• Atypical teratoid/rhabdoid tumors (ATRT) are comprised of three epigenetic subgroups with distinct enhancer landscapes

  Atypical teratoid/rhabdoid tumor (ATRT) is one of the most common brain tumors in infants and young children. Although the prognosis of ATRT patients is poor, some patients respond very well to current treatments, suggesting inter-tumor molecular heterogeneity. To investigate this further, we genetically and epigenetically analyzed a large cohort of ATRTs (n = 170). Three distinct molecular subgroups of ATRTs, associated with differences in demographics, tumor location and type of SMARCB1 alterations, were identified using DNA-methylation or gene expression analyses. Whole genome DNA- and RNA-sequencing found no other recurrent mutations explaining the differences between subgroups. However, whole genome bisulfite-sequencing and H3K27Ac ChIP-sequencing of primary tumors revealed clear differences in methylation patterns and enhancer landscapes, leading to the identification of subgroup-specific regulatory networks.

  Dataset EGAD00001001444

• The landscape of chromothripsis across adult cancer types

  Chromothripsis is a recently identified mutational phenomenon, by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosome(s). Considered as an early event in tumour development, this form of genome instability plays a prominent role in tumour onset. Chromothripsis prevalence might have been underestimated when using low-resolution methods, and pan-cancer studies based on sequencing are rare. We analysed chromothripsis in 28 tumour types covering all major adult cancers (634 tumours, 316 whole-genome and 318 whole-exome sequences). We show that chromothripsis affects a substantial proportion of human cancers, with a prevalence of 49% across all cases. Chromothripsis generates entity-specific genomic alterations driving tumour development, including clinically relevant druggable fusions. Chromothripsis is linked with specific telomere patterns and univocal mutational signatures in distinct tumour entities. Longitudinal analysis of chromothriptic patterns in 24 matched tumour pairs reveals novel insights in the clonal evolution of tumours with chromothripsis. (H021)

  Study EGAS00001004250

• Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

  The study is a retrospective transcriptomic profiling of oropharyngeal squamous cell carcinoma. The pathologic database was queried for squamous cell carcinoma tumors originating from the anatomic oropharynx (tonsil or tongue base) with available samples from surgical archives. This retrospective RNA sequencing cohort included cases dating prior to the routine implementation of p16 immunohistochemistry (IHC) testing at our institution, therefore, p16 status was not required for inclusion in this study. Formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center (LCCC) Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer's protocol (Promega 9FB167). After a pathology review of a hematoxylin and eosin (H&E) stained slides to identify tumor area, RNA was extracted from unstained slides using macrodissection. Total RNA quality was measured using a NanoDrop spectrophotometer (Thermo Scientific ND-2000C) and a TapeStation 4200 (Agilent G2991AA). Total RNA concentration was quantified using a Qubit 3.0 fluorometer (Life Technologies Q33216). Libraries were prepared with Illumina TruSeq Stranded Total RNA with Ribo-Zero protocol. Libraries were sequenced on an Illumina HiSeq2500 sequencer. Paired end read data, with read lengths of 75 were collected.

  Study phs002935

• Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

  In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

  Study EGAS50000000701

• International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

  The incidence of invasive breast cancer is rapidly increasing in East Asia, enriching in younger patients and luminal disease. We presented a deep proteogenomic landscape of a prospectively enrolled early-stage cohort in Taiwan to uncover the etiology, age-related subtype and oncogenic vulnerabilities underlying the heterogeneous disease. Multilayer proteogenomic architecture revealed distinct endogenous and environmental carcinogen-associated mutagenesis, linking APOBEC (apolipoprotein-B mRNA editing enzyme, catalytic polypeptide-like) cytidine deaminase and DBAC (dibenz[a,j] acridine) signatures to significantly elevated hormone biosynthesis and chemical carcinogenesis in younger patients, and identifying a novel subset of high mutation burden and immune escape potentially beneficial from combined epigenetic therapy and immunotherapy. A proteomics-informed classification resolves luminal heterogeneity, defines high-risk recurrent luminal disease and nominates biomarkers and actionable druggable pathways. Furthermore, proteogenomics profile distinguished a young luminal population susceptible to exogenous carcinogen and having DNA repair deficiency. This study illuminates the age-related molecular subtypes and oncogenic vulnerabilities, providing a proteogenomics-transformative guide for patient stratification and precision therapeutics beyond clinical staging.

  Study phs003150

• Whole genome sequencing of multiple myeloma identifies novel structural and non-coding mutations.

  The coding region of the myeloma genome is well understood with key mutations having been identified. However, the non-coding regions of the myeloma genome are yet to be analyzed. Here we have performed whole genome sequencing of myeloma patient samples to identify structural abnormalities including chromothripsis and chromoplexy, as well as gene dysregulation through super-enhancer juxtaposition with key oncogenes. We have also identified non-coding region hotspots of mutation, especially in promoter regions, that affect gene expression.

  Study EGAS00001003164

• The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

  Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

  Study EGAS00001004518

• Whole Genome Sequencing of 317 individuals from the Pacific region

  Although genetic studies of modern Oceanians have revealed varying levels of admixture with populations of East Asian ancestry, attributed to the Austronesian expansion, the early peopling history of Oceania remains poorly characterized. Additionally, it is currently unknown whether and how the settlement of the Pacific was accompanied by genetic adaptation to island environments, and if archaic introgression facilitated this process in Oceanians, who present the highest worldwide levels of combined Neanderthal and Denisovan ancestry. This study reports the first whole genome-based survey that addresses a wide range of questions related to the demographic and adaptive history of Pacific populations.

  Study EGAS00001004540

• Patient Registry for Primary Pulmonary Hypertension (PPH Registry-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 Establish a patient registry to evaluate the natural history, etiology, pathogenesis and treatment of primary pulmonary hypertension. Specific aims included the characterization of the demographic, medical history, family history, physical and laboratory findings of patients at time of diagnosis, and to characterize the survival duration of patients by traits evaluated at diagnosis and by medical interventions. Background There are several known causes of pulmonary hypertension: chronic obstructive pulmonary disease, congenital heart disease, mitral stenosis, left ventricular dysfunction and recurrent pulmonary emboli. Primary Pulmonary Hypertension is a disorder of unknown etiology which is diagnosed only after the known causes of pulmonary hypertension have been eliminated. Prior to the PPH registry, little was known regarding the epidemiology, etiology, natural history or ultimate survival among patients with PPH. In 1973, the WHO met to review the current state of knowledge on PPH and proposed the establishment of a multicenter collaborative study. The NHLBI PPH registry enrolled patients in the registry from 1981 to 1985. Participants Participants were enrolled into the registry from 32 medical centers throughout the US. Pulmonary hypertension was defined as a mean pulmonary arterial pressure of >25 mmHg at rest or 30 mmHg with exercise at catheterization. The diagnosis of primary pulmonary hypertension was only accepted after the following secondary causes of pulmonary hypertension had been excluded: pulmonary hypertension within the first year of life, congenital abnormalities of the heart, lungs, or diaphragm, pulmonary thromboembolic disease, diagnosis of sickle cell anemia, history of intravenous drug abuse, obstructive lung disease, interstitial lung disease, arterial hypoxemia, collagen vascular disease, parasitic disease affecting the lungs, pulmonary artery or valve stenosis, or pulmonary venous hypertension. Baseline and follow-up data collected on participants include demographic characteristics, chest radiograph, pulmonary function tests, lung perfusion scan or pulmonary angiogram, intracardiac left-to-right shunt, pulmonary hemodynamics, as well as a history, physical findings and other laboratory measurements. Participants were followed for approximately 5 years. Conclusions There were 1.7 females for each male in the registry, and females tended to present with more severe symptoms. The mean time from onset of symptoms to diagnosis was 2 years. Right ventricular hypertrophy was found in 87% of participants and right atrial pressure was elevated in 72% of participants. The estimated median survival was 2.8 years with single year survival rates of: 1 year, 68%; 3 years, 48%; and 5 years, 34%. (Ann Intern Med, 1987; 107:216-23, Ann Intern Med, 1991; 115:343-49).

  Study phs004275

• Drug screening and whole genome sequencing of primary cells and cell lines from ovarian cancer patients to associate genomic aberrations with in vitro drug sensitivities

  Identifying drugs for cancers with poor prognosis like ovarian cancer (OC) is hindered by inappropriate cell models and the limitations of current viability assays. We developed an automated confocal microscopy-based live cell assay (DeathPro) that robustly de-convolves cell death and proliferation over time by employing a specific image processing strategy. Using DeathPro, we screened nine OC patient-derived cell lines and one normal cell line (HOSEpiC) with 22 drugs or combinations. Whole genome was performed to analyze if the cell lines harbor OC-typical genomic aberrations and to relate genomic features to drug sensitivities. Commonly observed alterations in OC patients like TP53 mutations and MYC or PI3KCA amplifications were absent in the normal cell line but frequently detected in the OC cell lines. Moreover, genome-derived homologous recombination deficiency (HRD) scores of the OC cell lines correlated with their responses to carboplatin, olaparib and DNA demethylation drugs. Overall, we propose an imaging-based platform to guide drug development and genome-drug sensitivity analysis.

  Study EGAS00001002239

• Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy

  Anti-PD-(L)1 therapy is routinely used in metastatic NSCLC. However, response rates vary and biomarkers predicting treatment efficacy are lacking. Liquid biopsies allow monitoring of residual disease during therapy. Residual circulating tumor DNA (ctDNA) after therapy represents a predictive marker for adverse outcome. Here, we assessed copy number variations (CNVs) in serial plasma samples of NSCLC patients receiving PD-(L)1 blockade. We profiled CNV and fragmentation features in 118 plasma samples of advanced NSCLC patients by low-coverage whole genome sequencing taken at baseline, after four therapy cycles and at disease progression. CNVs and fragment features (i.e., fragment length, end motifs, position) were significantly altered in patients compared to healthy donors. Furthermore, fragment length changes at baseline and residual CNVs after four therapy cycles correlated with short progression-free survival. Our results highlight the suitability of plasma-based CNV and fragment analysis for disease monitoring and as a predictive marker for response duration in NSCLC patients under anti-PD-(L)1 therapy.

  Study EGAS50000000441

• UK10K NEURO ASD GALLAGHER

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This is an Irish sample set of individuals with ASD (approximately 50% with comorbid intellectual disability). Individuals have been diagnosed with ADI/ ADOS, measures of cognition/ adaptive function. They represent a more severe, narrowly defined cohort of ASD subjects. Family histories are available for some with measures of broader phenotype. For further information on this cohort please contact Nadia Bolshakova (bolshakn@tcd.ie).

  Study EGAS00001000112

• 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: 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

• Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Study EGAS00001007650

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• Multi-Omics Study of Lung Cancer in Smokers From EAGLE

  EAGLE (Environment And Genetics in Lung cancer Etiology) is a population-based case-control study examining the full spectrum of lung cancer etiology from smoking initiation, smoking dependency to lung cancer development and outcome. It combines a traditional molecular epidemiology design with more integrative approaches by examining epidemiological, molecular, and clinical data together. To comprehensively investigate the effect of tobacco smoking behaviors on genomic or epigenomic alterations, we performed a multi-omics study including whole-genomic, transcriptomic, and epigenomic profiles in a total of 221 individuals from the EAGLE study.

  Study phs002992

• The Haemgen RBC study

  Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size. Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size.

  Study EGAS00000000132

• Sexual dimorphism in human immune system aging

  We isolated peripheral blood mononuclear cells (PBMCs) from 172 community-dwelling healthy volunteers (91 women, 81 men) ages spanning adult lifespan: 54 young (ages 22-40: 23 men, 31 women), 59 middle-aged (ages 41-64: 31 men, 28 women), and 59 older subjects (65+: 27 men, 32 women). PBMCs were profiled using ATAC-seq (54 men, 66 women), RNA-seq (41 men, 34 women), and flow cytometry (62 men, 67 women). Flow cytometry data is publicly available, genomic data for 121 individuals are provided here. These datasets revealed immune system aging signatures in men and women and showed in which ways aging differentially affects the immune systems of men and women. A subset of these samples have been generated and analyzed previously and can be found at EGA (EGAS00001002605). This dataset on dbGaP include EGA samples as well.

  Study phs001934

• PETAL trial Whole Exome Sequencing (WES) from Normal Samples

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 55 Normal Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000002507

• PETAL trial Whole Exome Sequencing (WES) from Tumor Samples

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Tumor Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000001172

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• 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

• 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: 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

• 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

• 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

• NCI COVID-19 in Cancer Patients Study (NCCAPS): A Longitudinal Natural History Study

  NCCAPS is a longitudinal prospective cohort study designed to assess patient, disease and treatment factors associated with short- and long-term outcomes in patients with cancer who develop COVID-19. We also aimed to describe COVID-19 symptoms and treatments, and to describe disruptions in cancer treatment due to COVID-19. The study enrolled patients with cancer on active treatment or with a history of stem cell transplant or CAR-T cell therapy with new, active COVID-19, defined as being within 14 days of their first positive SARS-CoV-2 test. The study found that receipt of chemotherapy and baseline history of stroke, atrial fibrillation or pulmonary embolism were associated with a higher risk of hospitalization for COVID-19. Vaccination for SARS-CoV-2 was associated with a lower risk of hospitalization. Death due to COVID-19 was highest in patients with lymphoma, intermediate in those with acute leukemia and lung cancer, and lowest in those with other solid tumors and other hematologic cancers. Disruptions of cancer treatment were frequent in the first 30 days after SARS-CoV-2 infection.

  Study phs004178

• Interferon lambda 4 impairs viral antigen presentation and attenuates T cell responses

  Genetic variants of the interferon lambda (IFNL) gene locus are strongly associated with spontaneous and IFN treatment induced clearance of hepatitis C virus (HCV) infections. Individuals with the ancestral IFNL4-dG allele are not able to clear HCV in the acute phase and develop chronic hepatitis C (CHC) with more than 90% probability. Paradoxically, the IFNL4-dG allele encodes a fully functional IFNλ4 protein with antiviral activity against HCV and coronavirus. Here we describe a hitherto unknown effect of IFNλ4 on HCV antigen presentation. Only minor amounts of IFNλ4 are secreted, because the protein is largely retained in the endoplasmic reticulum (ER) where it induces ER stress. Stressed cells were significantly weaker activators of HCV specific CD8+ T cells. This was not due to reduced MHC I surface presentation or extracellular IFNλ4 effects, since T cell responses could be restored by exogenous loading of MHC with HCV antigens. Rather, IFNλ4 induced ER stress impaired HCV antigen processing and/or loading onto the MHC I complex. Our results provide a potential explanation for the IFNλ4 – HCV paradox.

  Study EGAS00001005396

• Genetics of Disorders Affecting Tooth Structure, Number, Morphology and Eruption

  The long-term objective of this research project is to discover the complete spectrum of genes that contribute to the etiologies of genetic disorders of dentition. Inherited tooth defects can be isolated (the only symptom) or syndromic (having additional symptoms), and can be caused by mutations in many different genes. Clinically, it can be difficult to distinguish among the diverse forms. Making an accurate diagnosis would be greatly improved if reliable tests could identify the specific genetic defect that causes the disease in each case. Current technology can identify the numerous sequence variations throughout a patient's exome, but the disease-causing variation among them cannot be identified unless it is already on the list of genes that potentially cause the disease. A diagnosis based upon the genetic defect that causes the disorder distinguishes between isolated and syndromic tooth defects. A precise diagnosis permits formulation of a more accurate prognosis, which informs treatment decisions. The benefits of accomplishing our aims are to 1) enable genetic testing to achieve a precise and accurate diagnosis, and thereby optimize treatment, and 2) improve our understanding of normal and pathological tooth formation, leading to future improvements in treatment and eventually cures. Our short-term objectives are to 1) recruit kindreds with inherited disorders affecting their dentition, characterize their dental phenotype (and non-dental phenotypes when applicable) and the distribution of the disorder throughout the family, and 2) determine the genetic etiology of their disorders.

  Study phs001491

• Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss

  The Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss, which constitute the Epidemiology of the Weiss Cohort Projects, consist of a series of inter-connected projects, building upon a set of cohort projects of various groups, mainly drug users from medication-assisted treatment programs, that Dr. Stanley H. Weiss first developed in the 1980&#8217;s plus several newer initiatives, each with an array of collaborators. Beginning in the 1980&#8217;s, Dr. Stanley H. Weiss started several long-term studies of persons who inject drugs (PWID) across the United States, ultimately enrolling over 10,000 participants through the early 1990&#8217;s with an average age then in their 30&#8217;s. About a quarter were enrolled from sites in New Jersey (NJ). These studies included the first testing of PWID for the human immunodeficiency virus (HIV) and the human T-cell lymphotropic viruses (HTLV I and HTLV II). Cumulative past support (initiation thru ~ 1999) for these cohort studies included ~ $20 million from intramural resources from the National Cancer Institute (NCI) and the National Institute on Drug Abuse (NIDA), plus multiple grants and in-kind support from the New Jersey Department of Health (NJDOH) totaling ~ $1 million. The Weiss Cohort Projects include the first large AIDS-era cohorts to include women at high risk for HIV. A high percentage of subjects in these studies are black or Latino. Thus, this is an ethnically diverse US cohort, with a high proportion of women included. These subjects are at high risk of parenteral and sexual infection from both drug use and sexual practices. Samples from other studies conducted by Dr. Weiss, in which detailed interviews were conducted, are included as controls (persons documented by us not to have a history of opioid drug use). As one of our groups of subjects have many persons of Haitian ancestry, we specifically included some Haitians who had never used opioids as controls. Our documentation includes such ancestry. These cohorts demonstrated high rates of HIV and HTLV-II infection in PWIDs, including one study initiated in 1981 with confirmation in the later cohorts. In the first two decades of these studies, among numerous publications was the first study showing a very high rate of hepatitis C infection among PWIDs. An example of how the studies&#8217; long-time horizon proved essential was that it first became possible to test whether a person had ever been infected with hepatitis C virus (HCV), as well as how much HCV was in each person&#8217;s blood, many years after the specimens were collected. This allowed HCV amounts in blood to be compared for subjects who had died of liver disease early in the study versus those who survived. Then a sequence of published papers culminated in demonstrating, using a nested case-control design, that a high baseline HCV titer was predictive of early progression to death from end-stage liver failure. Outcomes related to HCV (end stage liver disease and hepatocellular carcinoma) remain under study. In the original cohort studies, the mean age at enrollment was ~ 33 years old, so that those still alive in 2022 are mainly now ~ 60 - 75 years old. Many participants have already died. The tincture of time has led to subjects reaching ages when many more are dying from a wide array of outcomes, including from many chronic diseases (including cancer) as well as from infectious agents (especially HIV, HCV) or drug overdose. Renewed collaboration with local drug treatment programs has led to new field-based studies, including examination of some currently evolving problems among drug users. Dr. Weiss joined the National Institute on Drug Abuse (NIDA) Genetics Consortium (NGC) in 2017, and through the NIDA project officer has had access to NGC contract resources (see below). NIH Certificate of Confidentiality, CC-DA-16-214 (attached) protects these studies. Past arrangements related to data on our subjects leads to restrictions on the use of data emanating from our study, such as potential commercialization and restrictions on whom may access and use these data. NIDA Genetics Consortium (NGC) resources further support these endeavors and will be used as part of the NGC analyses studying the genetics of substance use. Study participants signed informed consent for the information collected from them to be used with no time limit and for biologic specimens collected from them to be used without restriction in future research. Serum samples were collected from participants, and from many also plasma, white blood cells and/or urine samples. About 100,000 vials were stored. All specimens have been continuously preserved at sufficiently cold temperatures to prevent deterioration, and many subjects separated white blood cells were processed and frozen in such a way as to maintain viability. Detailed data from the participants has been accumulated over time, and in general, linkage has been retained in each sub-study in accordance with the consent forms and protocols. For some participants, specimens were collected at multiple times (that is, sequential specimens). Multiple specimens from a single person exist in this database, and efforts at de-duplication remain ongoing. Dr. Weiss should be contacted if an investigator requires unique individuals since: &#8226; Multiple phases of enrollment occurred, and as our prospective follow-up continues; Dr. Weiss may identify new instances of multiple enrollment. &#8226; Some persons are related to each other. &#8226; In general, in this dataset for dbGaP, only a single specimen/record form a given person is included. Advances in laboratory testing techniques now permit innovative new uses for our linked research biospecimen repository. The ongoing focus of an interdisciplinary research program based on these cohorts relates subjects&#8217; diseases, behaviors, medical history, and outcomes with biological and exposure markers. Participants&#8217; use of various substances was ascertained on study enrollments, many serially over time. Quantitative frequency of use data, also sometimes sequential over time, were ascertained. Active ascertainment of outcomes is being conducted, including matching to mortality and cancer databases. Investigators interested in collaborations on specific outcomes (which is not part of this dbGaP dataset) or in the use of our stored specimens are encouraged to contact the principal investigator, Dr. Weiss. The processing of the genomic data was done in conjunction with NIDA, and in accordance with some longstanding data cleaning steps used by NIDA in the NIDA Genetics Consortium (NGC), a group to which we shall be contributing these data for collaborative analyses. Since there is the potential for these steps to introduce certain types of potential biases, we summarize these here. Under contract from NIDA, cryopreserved sera or plasma (-80 C) or cells (in liquid nitrogen) were used, with most stored having been stored for 30 to 40 years in our biorepository. In the case of serum or plasma, in which only (largely) cell-free DNA fragments were available, DNA was extracted and restored prior to amplification. Industry standard DNA amplification techniques were done on all samples prior to genotyping in accord with established protocols of the NIDA Genetics Consortium. Our genotype data were run and processed on the Illumina Infinium OmniExpress_v_1.3 array. This array has 714,238 SNPs, and was designed many years ago. There were 628 SNPs on the array that do not correspond to any chromosome position, and these were removed. Genotype data were submitted by NIDA&#8217;s contracted genotyping laboratory in six batches over time to NIDA&#8217;s contracted dbGaP data management group, which conducted quality control (QC) analyses. QC analysis included an assessment of batch effects on for five of the six batches. (One of the batches, with only 12 samples, was too small for QC analysis of batch effects.) Standard NIDA Genetic Consortium cleaning was performed. Samples with a call rate &lt;.85 were removed. Only one sample per person was retained. When more than one specimen was genotyped from one subject, only the sample with the higher call rate was retained (provided, of course, that that call rate was &#8805; 0.85). We have retained some people we know are related, including some found to have been related through genotyping; the pedigree file describes those relationships. In summary, key cleaning steps include: 1. Using PLINK to check gender discrepancy. 2. Using PREST-PLUS and KING (Kinship-based Inference for GWAS) to check relatedness. 3. Using PEDCHECK and PLINK to check/zero-out Mendelian error. 4. Using PLINK to perform sample QC, SNP QC, along with KING to perform chromosome X and chromosome Y QC. 5. SNP-QC: Batch-effect: 5 Batches were compared (one batch, with few samples, was not). These five batches were compared to each other in all ten possible pairs, one batch vs. another batch, examining SNP allele frequency discrepancies by population (from GRAF), Fisher Exact Allelic test, with the criterion of p&lt;5e-8 for removal. 6. SNP-QC: discordant SNPs in QC duplicates. Compared 25 QC duplicated samples with call rate &gt; 0.95, removed SNPs with 3+ discordance. 7. There were 1,056 SNPs that were monomorphic; these have been retained so they can be included in analyses in which our dbGaP data are combined with those from other cohorts (in the latter of which those SNPs may not be monomorphic). The final cleaned dataset submitted has 8,898 samples and 606,793 SNPs.

  Study phs002140

• Neuroblastoma patient WGS data

  Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008123

• Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Despite maximal therapy with surgery, chemotherapy and radiotherapy, glioblastoma multiforme (GBM) patients have a median survival of only 15 months. Almost all patients inevitably experience symptomatic tumor recurrence. A hallmark of this tumor type is the large heterogeneity between patients and within tumors itself which relate to failure of standardized tumor treatment. In this study, tissue samples of paired primary and recurrent GBM tumors were investigated to identify individual factors related to tumor progression.

  Study EGAS00001004345

• Integration of genomics and metabolomics in acute myeloid leukemia

  Although targeting of cell metabolism is a promising therapeutic strategy in acute myeloid leukemia (AML), metabolic dependencies are largely unexplored. We aimed to classify AML patients based on their metabolic landscape and map connections between metabolic and genomic profiles. The intracellular metabolome distinguished three AML clusters, correlating with distinct genomic profiles: NPM1-mutated(mut), chromatin/spliceosome-mut and TP53-mut/aneuploid AML that were confirmed by biofluid analysis.

  Study EGAS00001005422

• Single-Cell Analysis of Somatic Mutations in Human Bronchial Epithelial Cells in Relation to Aging and Smoking

  While lung cancer risk among smokers is dependent on smoking dose, it remains unknown if this increased risk reflects an increased rate of somatic mutation accumulation in normal lung cells. Here we applied single-cell whole genome sequencing of proximal bronchial basal cells from 33 subjects, aged between 11 and 86 years, with smoking histories varying from never smoking to 116 pack years. We found an increase in the frequency of single-nucleotide variants and small insertions and deletions with chronological age in never-smokers, with mutation frequencies significantly elevated among smokers. However, when plotted against smoking pack-years, mutations were found to follow the linear increase in cancer risk only until about 23 pack years, after which no further increase in mutation frequency was observed, pointing towards individual selection for mutation avoidance. Known lung cancer-defined global mutation signatures tracked with both age and smoking. Within study power limits, no significant enrichment for somatic mutations in lung cancer driver genes was observed.

  Study phs002758

• Genomic and Genetic Analysis of Brain Tumors and Analysis of Their Clinicopathological Significance

  The treatment outcome of glioma patients remains disappointing, and more studies are needed to improve therapeutic strategies. In particular, it is crucial to understand the mechanisms underlying resistance to treatment and malignant transformation, as well as the intratumoral heterogeneity and interaction of tumor cells and host immunity. Recent advances in omics analysis techniques, such as next-generation sequencing (NGS), have enabled us to obtain omics data more easily and accelerated our ability to integrate this information and precisely characterize cases. In our project, we have already collected more than 100 pairs of human glioma/normal tissue samples, of which some are multiple specimens collected from initial and recurrent tumors, and some include multiple specimens collected from different regions within a single tumor. We used our in-house algorithms, composed of alignment and variant calling programs, to analyze omics data from multiple platforms, such as whole-exome sequencing (WES), RNA sequencing (RNA-seq), and methylation array, with our original cohort of glioma patients. Using several informatics tools, the information about genetic and epigenetic status and expression signatures were analyzed. Those data are expected to provide key information for investigating the mechanisms discussed above. Through this project, we hope to improve strategies for personalized therapy based on comprehensive omics data.

  Study JGAS000004

• Allele Balance Bias Identifies Systematic Genotyping Errors and False Disease Associations

  In recent years, Next Generation Sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the allele balance distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies (RVAS).

  Study EGAS00001003027