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

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

  Study phs001981

• SEQCAP_Internation_1q_Type_2_Consortium - Agilent SureSelec

  The aim of this project is to identify rare variants in the 1q region associated with type 2 diabetes. To this end 651 case samples and 651 control samples from six populations have been pooled (pool sizes range from 27-33 individuals), and are being sequenced. The hybridization solution being used captures the exons and UTRs of genes in the 1q region.

  Dataset EGAD00001000421

• Single cell RNA-seq mapping of nasal and tracheobronchial airways in human healthy volunteers

  The respiratory tract constitutes an elaborated line of defense based on a unique cellular ecosystem. Single-cell profiling methods enable the investigation of cell population distributions and transcriptional changes along the airways. We have explored cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12th division of the airway tree. The resulting atlas is composed of a high percentage of epithelial cells (89.1%), but also immune (6.2%) and stromal (4.7%) cells with peculiar cellular proportions in different sites of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type specific gene expression was stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuro-endocrine (PNEC) and brush cells, which are likely derived from a common population of precursor cells. We also report a population of KRT13 positive cells with a high percentage of dividing cells which are reminiscent of “hillock” cells previously described in mouse. Robust characterization of this unprecedented large single-cell cohort establishes an important resource for future investigations. The precise description of the continuum existing from nasal epithelium to successive divisions of lung airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

  Study EGAS00001004082

• HNF1B induced three-dimentional genome analysis of patient-derived pancreas neoplasm organoids

  Three-dimensional (3D) genome structures are organized in a hierarchy of various module layers, including chromosome compartment, topologically associating domain, and enhancer-promoter loop. These modules are important in regulating cell type specific gene expression. Here, we aimed to elucidate how 3D genome organization is related to regulating subtype specific genes in pancreatic neoplasms.

  Study JGAS000514

• Development of New Diagnostics, Therapeutics, and Prevention Methods for Personalized Medicine Based on Comprehensive Cancer-Related Gene Exome Analysis and Information Analysis Using Cancer Specimens Stored in TMDU Biobank.

  Biobanked tumor samples are a valuable resource in real-world solid tumor research. Panel-based genomic profiling enables the identification of clinically significant alterations that inform personalized diagnostic and treatment decisions. This study aimed to characterize the genomic landscape of solid tumors collected through the TMDU Biobank by summarizing mutational, copy number, and gene fusion alterations in a large and diverse patient cohort. This dataset contains summary-level genomic information from 1,996 tumor samples analyzed by ACT Genomics and ACT med using the ACTOnco Comprehensive 440-Gene Cancer Panel. Data provided includes (1) gene-level mutation counts, (2) a summary of copy number alterations, and (3) a summary of detected fusion events. Clinical attributes such as ICD-10 codes, age group, sex, tumor mutational burden (TMB), and microsatellite instability (MSI) status were included at the aggregate level. Summary statistics were generated from three source tables (gene, sample, and copy number data) using standardized processing rules. Due to contractual and ethical considerations, individual-level mutation locations and raw sequence data are not included; only summary-level information is provided. This dataset will support future research in tumor-type-specific genomic patterns, molecular characterization of solid malignancies, and precision oncology.

  Study JGAS000863

• Determination of cell specific regulatory enhancers in hematopoetic models

  The BLUEPRINT project is a large-scale project investigating epigenetic mechanisms involved in blood formation, in health and disease. The human variation workpackage (WP10, led by NS) of the project seeks to characterize the effect of common sequence variation on the epigenome status of a cell. To do this, the project will use highly purified blood cells to minimise "experimental noise" and therefore enhance the power to discover modest effects. Two peripheral blood cell types, the CD14+CD16- monocyte (an important central orchestrator of adaptive immunity and a bridge between innate and adaptive immunity) and the CD65+CD9- neutrophilic granulocyte (the frontline cell for innate immunity) have been selected for this purpose. The two types of cells will be obtained at high purity from adult blood (AB) of 200 healthy males and females, respectively. Cells will be purified by using already validated and fully operational protocols that are based on density gradient centrifugation of the buffy coat obtained from whole blood, followed by magnetic bead-based purification using monoclonal antibodies against Cluster of Differentiation (CD) lineage-specific cell surface markers. Units of 475 ml of AB will be obtained from consenting volunteers of the Cambridge BioResource (CBR), a panel of 10,000 healthy volunteers local to Cambridge who have already consented to participate in biomedical research and of whom biological samples (DNA, plasma, serum) and lifestyle data have been deposited in a repository and database, respectively. We are requesting funding from the Human Diversity project to sequence the genomes of the 200 CBR volunteers at low pass (6x coverage). Nuclei, DNA and RNA will be recovered from the purified cells and made available for RNA-seq, DNA-seq and ChIP-seq and genomic DNA for entire genome sequencing will be recovered from the DNA repository.

  Dataset EGAD00001002205

• 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

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• 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

• Prognostic factors in prostate cancer: deep sequencing pilot project TAPG

  This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

  Dataset EGAD00001001237