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• 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

• Genome Wide Association for Asthma and Lung Function

  The SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic (STAMPEED) asthma project includes subjects with asthma and controls from the Chicago Asthma Genetics Study (CAG), NHLBI multicenter Severe Asthma Research Program (SARP) and NHLBI Collaborative Studies on the Genetics of Asthma CSGA (Wake Forest). All studies included European American and African American children and adults with asthma ranging from mild to severe and adult controls. CAG participants were collected at the University of Chicago. SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al, Am J Respir Crit Care Med, 2010, PMID: 19892860). CSGA cases and controls collected by the Wake Forest investigators were also included. Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. Genotyping was performed on the Illumina 1Mv1 platform, with individual genotypes called using clustering algorithms as implemented in the BeadStudio software by Illumina. The total number of markers following standard QC was 1,025,129. Imputation was performed using the HapMap phase 2, release 21 SNPs using MACH with the phased HapMap CEU and YRI haplotypes as a reference. Case/control association tests for asthma status were performed using logistic regression in R (http://CRAN.R-project.org/) on genotype dosages, and adjusting for the first principal component from EIGENSTRAT.

  Study phs000355

• 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: 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

• 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

• Center for Sub-Cellular Genomics

  A cell is a highly complex system with distributed molecular physiologies in structured sub-cellular compartments whose interplay with the nuclear genome determine the functional characteristics of the cell. A classic example of distributed genomic processes is found in neurons. Learning and memory require modulation of individual synapses through RNA localization, localized translation, and localized metabolites, such as those from dendritic mitochondria. Dendrites of neurons integrate distributed synaptic signals into both electrical and nuclear transcriptional response. Dysfunction of these distributed genomic functions in neurons can result in a broad spectrum of neuropsychiatric diseases such as bipolar and depressive disorders, autism, among others. The Center for Sub-Cellular Genomics' (CSG) mission is to develop new technologies to enable the dissection of complex genomic interactions within a single cell. New technologies include methods to target DNA and RNA sampling at sub-cellular resolution in live cells; high-throughput isolation and microfluidics chemistry for sub-cellular fractions; sub-cellular resolution mass-spectrometry; and computational tools for analysis of sub-cellular genomics data. The new technologies developed by CSG will enable the broader genomics community to associate sub-cellular processes to cell function and dysfunction. These technologies will be utilized in the center to generate a comprehensive atlas of genomic signatures of sub-cellular compartments in the mammalian neuron system. The technologies and neuron-focused data obtained here will be relevant to neurodegenerative and neuropsychiatric diseases including schizophrenia, depression, autism spectrum disorder, traumatic brain injury, and Alzheimer's.

  Study phs002120

• Sequencing component for the whole genome methylation analysis in PBMCs and cell subset pilot study DAC

  Dac EGAC00001000096

• The EMC-NICHE DAC considers appeals for hematopoietic/niche-related data sets.

  Dac EGAC00001000537

• Data access policy for PDTX Breast Cancer data from Bruna et al (2016), Cell.

  Dac EGAC00001000540

• CIR-RIMLS committee on data access to Immunological mechanisms for celiac disease database

  Dac EGAC00001000557

• Data access committee for the pseudomyxoma peritonei exome sequencing vcf-files

  Dac EGAC00001000649

• DAC for "A Functional Network of Gastric-Cancer-Associated Splicing Events Controlled by Dysregulated Splicing Factors"

  Dac EGAC00001000675

• DAC for Hungarian human exome team (Department of Medical Biology, University of Szeged, Hungary)

  Dac EGAC00001000838

• Data access committee handling data access requests for biomarker data from the clinical trial IMvigor210.

  Dac EGAC00001000945

• DAC for study: "Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer"

  Dac EGAC00001001099

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee (part II)

  Dac EGAC00001001332

• DAC Therapeutic vulnerabilities in the DNA damage response for the treatment of ATRX mutant neuroblastoma

  Dac EGAC00001001675

• The data access committee for Detection and characterization of lung cancer using cell-free DNA fragmentomes

  Dac EGAC00001002184

• Data Access Committee for the MAXOMOD Consortium - E-Rare / European Joint Programme on Rare Diseases

  Dac EGAC00001003287

• Integration of intra-sample contextual error modeling for improved detection of somatic mutations

  Study EGAS00001003806

• The WID-EC test for the detection and risk prediction of endometrial cancer

  Study EGAS00001005033

• Evaluating CRISPR-based Prime Editing for cancer modeling and CFTR repair in organoids

  Study EGAS00001005358

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Study EGAS00001006820

• MPIMG DAC

  DAC of the Max Planck Institute for Molecular Genetics

  Dac EGAC50000000149

• Stage-1 GWAS

  Summary statistics from Stage-1 GWAS for blood pressure phenotypes

  Dataset EGAD00010001569

• Quad samples for study EGAS00001001023

  Dataset EGAD00001001126

• Cancer Alliance WGS

  Whole genome sequencing for individualized cancer interpretation

  Dataset EGAD00001006233

• TRAIP patients

  BAM files for two WES TRAIP patients

  Dataset EGAD00001001633

• Predicting Chemotherapy-Induced Mucositis with Genetic and Clinical Factors

  We hypothesized that genetic variability in the enzymes/proteins involved in drug metabolism, inflammation, and immune function is a major underlying contributor to mucositis incidence and progression and that, based on this variability we can identify variants that influence risk, and develop a mucositis progression prediction model that improves on existing models by incorporating genetic variability along with clinical factors. Using genome wide association study (GWAS) combined with a pathway candidate gene approach and a modified case-control study method, we investigated the hypothesis in a sample of 1092 patients who received a myeloablative dose of melphalan (MEL) followed by autologous hematopoietic stem cell (ASCT) transplantation as treatment for multiple myeloma and for whom banked blood stem cell samples and clinical data were available.

  Study phs000545

• SNP array analysis of spondylocostal dysostosis patient iPSCs and gene edited isogenic controls

  This study, "SNP Array Analysis of Gene Edited SDV Patient iPSCs" is part of a larger study where we applied our recently established experimental in vitro model system of the human segmentation clock, for the analysis of human segmentation defects of the vertebrae (SDV) including spondylocostal dysostosis (SCD). To this end we generated patient-derived iPSC lines, identified putative disease-causing mutations and corrected these mutations using CRISPR/Cas9-based genome editing technology. We identified in the patient-sample originally obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research (#: GM13539) heterozygous compound mutations in MESP2. These mutations were corrected accordingly and the resulting clones were genotyped by SNP array analysis.

  Study phs001975

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

  Study phs003066

• Episodic Ataxia Syndrome: Longitudinal Study

  Individuals with episodic ataxia experience recurrent attacks of dizziness and incoordination; between attacks patients are typically normal. The majority of cases are likely caused by an inherited genetic mutation. However, in some patients we are unable to identify the mutation. So far, 2 genes have been identified which cause different types of episodic ataxia. Ultimately, when the actual mutation is identified the protein product of the gene can be studied and specific medications can be designed. During this study, we will clinically evaluate patients with EA and follow them over time to help us better characterize the disease. We will also obtain blood samples to test for the known genetic mutations. In the future, we plan to coordinate trials of medications for the treatment of these disorders.

  Study phs000521

• Pharmacogenomics of Metformin Dose Response in T2DM Patients

  Type 2 Diabetes Mellitus (T2DM) is a chronic and sometimes debilitating disease that affects millions of adults in the USA. Metformin is commonly prescribed for T2DM; yet some T2DM patients do not tolerate it or respond well. This pharmacogenomics study will examine response, as both change in T2DM patients' weight and hemoglobin A1c (HbA1c) levels, to different doses of metformin, by extracting this data from the electronic health record (EHR), for T2DM subjects taking metformin found by prescription orders in the EHR, and identified as cases with the EHR phenotype algorithm published by Kho et. al. in 2012 (PMID: 22101970 as part of the eMERGE (electronic Medical Records and Genomics; dbGaP phs000237, phs000297, phs000360, phs000368, phs000888, and phs000948) project.

  Study phs000984

• Genetic Basis of Pulmonary Non-tuberculous Mycobacterial Infections

  This project aims at characterizing the human host susceptibility to pulmonary non-tuberculous mycobacterial (PNTM) infections. PNTM infections occur in patients with chronic lung disease, but also in a distinct group of elderly women without lung defects but who share a common body morphology: tall and lean with scoliosis, pectus excavatum, and mitral valve prolapse. We performed whole exome and genome sequencing in extended families of patients with active PNTM. This unique collection of familial cohorts in PNTM represents an important opportunity for a high yield search for genes that regulate mucosal immunity. We also sequenced the genome of mycobacterial isolates from PNTM patients to integrate host PNTM susceptibility with mycobacterial genotypes and gain insights into the key factors involved in this devastating disease.

  Study phs000719

• The mutational characterization of adenoid cystic carcinoma

  Adenoid cystic carcinoma (ACC) typically emanate from the major and minor salivary glands of the head and neck. ACCs have high rates of perineural invasion, locoregional recurrence, and distant metastasis. Here we report sequencing of 60 tumor/normal pairs and find substantial mutational diversity. On pathway analysis, a significant percentage of mutations involved chromatin remodeling, DNA damage, protein kinase A signaling, and FGF/IGF/PI3K signaling. Whole genome sequencing and FISH confirmed the MYB-NFIB translocation as the main structural variant in ACC. Evaluation of potential driver mutations KDM6A and PIK3CA reveal that specific, observed alterations impart functional consequences. Collectively, our data delineate the ACC mutational landscape and establish a molecular foundation for investigating new therapies for this disease.

  Study phs000612

• Identification of Genomic Markers of Cervical Dystonia and Subtypes

  As the third most common movement disorder, dystonias collectively affect more than 2 million people worldwide. Despite their high prevalence, their biological roots are largely unknown. Genetic influences are suggested in familial studies, however, no specific genetic variants are responsible for a significant proportion of identified cases. Previous genome-wide association studies of the dystonias were limited by smaller sample size and lack of coverage of rare variants. In this study, we use a high-throughput genomic approach to effectively investigate relationships between over genome-wide genetic variations and dystonias. We conduct targeted analyses of candidate genes, as well as agnostic searches for any genomic with the dystonias and subtypes in a large sample of dystonia patients available.

  Study phs001803

• Natural Genetic Variation in the Human Genome

  In this study, we used existing whole genome sequencing data from the TOPMed Amish and Jackson Heart Study, as well as the GTEx study, to identify mobile element insertions in the genomes of these individuals.  A total of 1112 TOPMed Amish, 3331 TOPMed Jackson Heart Study, and 698 GTEx individuals were examined.  We used the Mobile Element Locator Tool (MELT) developed previously by our lab, along with a Cloud-based version of MELT (CloudMELT), to discover non-reference mobile element insertions (MEIs) in these genomes.  We discovered Alu, L1, SVA, and HERV-K MEIs and produced genotypes in individual genomes.  Build hg19 bams were used for the TOPMed samples, and build GRCh37 bams were used for the GTEx samples in this study.

  Study phs002463

• Lifestyle, Infertility, Fertility, and Evaluation (LIFE) Study

  The purpose of this study is to provide a reference profile of small extracellular RNAs in body fluids. These samples were originally obtained in a study that had a different purpose. The purpose of the original study was to establish a data and biological specimen repository to advance future research into male reproductive health and urologic health. Semen from semen analyses, as part of standard of care at the Center for Reproductive Health, was collected and stored in a tissue bank for future research purposes. These samples and associated clinical data (including age, race, education level, medical history and diet, environmental exposures and laboratory values, fertility diagnosis and infertility treatments) will help researchers understand any urological disorders and male reproductive health issues.

  Study phs001692

• Drug Resistant Hypertension in African Americans' Exome

  Resistant hypertension is defined as blood pressure that remains above goal in spite of the concurrent use of 3 antihypertensive agents of different classes or the concurrent use of 4 or more antihypertensive agents regardless of control. Its diagnosis is important for the identification of patients who are at high risk of having reversible causes of hypertension and/or patients who, because of persistently high blood pressure levels, may benefit from special diagnostic and therapeutic considerations. Resistant hypertension represents an extreme phenotype, thus, it has been predicted that genetic factors could play a larger role than for the general hypertensive population. Genetic assessments of patients with resistant hypertension have been limited. The current study assayed the exome of 91 African American patients with treatment resistant hypertension.

  Study phs000442

• NPC Genome Project

  Niemann-Pick disease, type C1 (NPC1) is neurodegenerative disorder due to pathological variants of NPC1. NPC1 is predominately a pediatric/adolescent disorder, although adult onset cases have been described. The NPC1 protein functions to move unesterified cholesterol from the endolysosomal lumen to make it bioavailable for cellular function. Impaired NPC1 function results in endolysosomal accumulation of unesterified cholesterol and other lipids. The NPC1 phenotype is extremely heterogeneous, both with respect to age of onset and sign/symptom complex. Comparison of individuals homozygous for the common p.I1061T variant and affected siblings suggests that other genes can significantly modify the clinical phenotype. The goal of this project is to obtain genome sequencing on ~200 individuals with NPC1 in order to facilitate identifying potential genetic modifiers.

  Study phs003214

• DAC for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• DirectHRD Enables Sensitive Scar-Based Classification of Homologous Recombination Deficiency (HRD)

  Homologous recombination deficiency (HRD)-induced genomic scars are an FDA-approved biomarker for identifying cancers likely to respond to PARP inhibitors. However, detecting HRD scars from blood biopsies has been challenging due to the low tumor content in blood samples. To address this limitation, we developed DirectHRD, a genomic scar-based HRD classifier leveraging whole-genome sequencing (WGS) data for non-invasive blood biopsy testing. DirectHRD was applied to 90 cell-free DNA (cfDNA) samples across four cancer types: breast, ovarian, prostate, and pancreatic. The method achieved an AUC of 0.87 and demonstrated the ability to detect HRD at tumor fractions as low as 1%, offering a tenfold increase in sensitivity compared to state-of-the-art methods.

  Study phs003760

• C-MACH reduced-representation bisulfite sequencing (RRBS)

  Umbilical cord blood (CB) has been commonly used as an epigenetic surrogate of fetuses. Here, we propose umbilical cord tissue (UC) as an alternative surrogate for epigenetic studies on fetuses. To explore the feasibility to examine UC epigenome by deep sequencing, we determined CpG methylation profiles of human postnatal UC by reduced representation bisulfite sequencing. We compared DNA methylomes between UC and CB. To investigate the effect of folate during pregnancy on fetal DNA methylation, we compared fetal UC DNA methylation between low and high levels of maternal plasma folate. Our study suggests that UC is useful as an alternative surrogate for studying environmental effects on DNA methylation in human fetuses, compensating CB by providing additional information about epigenetic regulation of genes.

  Study JGAS000171

• Germline variants in UHRF1 are associated with multi-locus imprinting disturbance in humans and mice

  Genomic imprinting provides is an epigenetic process crucial for normal development and is disrupted in congenital imprinting disorders(CIDs). There is great interest in the clinical consequences and aetiology of multilocus imprinting disturbance(MLID) which occurs in some individuals with CID, though the cause of MLID is unknown in most cases. We investigated a kindred with a CID and MLID and identified a rare genetic variant in the UHRF1 gene which has a critical role in the establishment and maintenance of DNA methylation. We generated a mouse model and found that the equivalent Uhrf1 variant was associated with prenatal lethality and disruption of normal imprinting mechanisms. These findings support UHRF1 as a novel candidate gene for CIDs with MLID.

  Study EGAS50000001179

• Ultrasensitive Detection and Monitoring of Circulating Tumor DNA using Structural Variants in Early-Stage Breast Cancer

  Circulating tumor DNA (ctDNA) detection has an emerging role in the management of breast cancer, offering a non-invasive means to monitor disease status and detect recurrence. This study demonstrates that longitudinal monitoring of tumor-specific structural variants - frequent alterations observed across many tumor types including all subtypes of breast cancer derived from Whole Genome Sequencing data - allows for ctDNA detection in nearly all participants in this cohort with untreated early breast cancer prior to starting neoadjuvant therapy. On-treatment ctDNA monitoring enabled the early identification of patients at high risk of recurrence and ctDNA was detected prior to relapse in participants across all receptor subtypes. These findings demonstrate the clinical validity of this assay approach for ultrasensitive ctDNA monitoring.

  Study EGAS50000000799

• WES samples of patients with anti-PD-1 resistant HNSCC from a non-randomized, open-label phase 1b clinical trial

  Immune checkpoint blockade (ICB) is an effective treatment for a subset of patients with head and neck squamous cell carcinoma (HNSCC); however, the majority remain refractory. In a nonrandomized, open-label Phase 1b clinical trial, participants with recurrent and/or metastatic (R/M) HNSCC who had progressed on ICB were treated with low-dose 5-azacytidine (5-aza) daily for either 5 or 10 days, in combination with durvalumab and tremelimumab. The primary objective was to determine the biologically effective dose of 5-aza. In this study, whole exome sequencing (WES) was performed on baseline samples from 12 participants, and genomic alterations were analyzed to access the genetic background of these participants.

  Study EGAS50000000729

• Single cell transcriptomics to characterize the tumor microenvironment of prostate cancer fusion biopsies

  The primary objective of this study was to characterize the tumor microenvironment in fusion-guided transperineal biopsy samples from patients undergoing PC diagnosis. For each patient, one biopsy was taken from a suspected tumor region and another from a non-suspicious area, which were later classified as high- or low-tumorigenicity based on anatomopathological analysis. Using scRNA-seq data, we performed cancer-oriented cell annotation, differential expression analysis, and functional pathway enrichment studies across key cellular subpopulations. Additionally, differential abundance analysis was conducted to identify cell groups representative of different tumorigenicity levels. Finally, classification models were developed using gene expression data to differentiate high- vs. low-tumorigenicity samples, with the long-term goal of establishing a diagnostic classifier for PC stratification.

  Study EGAS50000000888

• Association studies using the Metabochip array - Samples analysed by the WTCCC (1958 British Birth Cohort (58BC), Hypertension cohort (HT), Type 2 Diabetes Cohort (T2D) and Coronary Artery Disease (CAD) cohort)

  Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Metabochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for genetic studies of metabolic, cardiovascular and anthropometric traits (Voight et al., in press PLoS Genetics).

  Study EGAS00000000115