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• Identification_of_rare_variants_associated_with_cardiovascular_traits_in_Cilento_isolates

  The aim of this project is to identify rare genetic variants of large effect implicated in complex diseases by focusing on the study of cardiovascular diseases and related quantitative traits in a well characterized isolated population in Cilento area, Italy.The reference panel has been selected carefully in order to maximize the imputation coverage and quality on the all population samples. The selected individuals should meet three criteria: selected individuals should be chip-genotyped and closely related to the maximum number of chip-genotyped individuals so as to maximize imputation coverage; relatedness between selected individuals should be minimal, so as to minimize redundancy in genetic information of the reference panel.We perform exome sequencing on samples from 250 individuals from the Campora and Gioi-Cardile populations.

  Study EGAS00001000620

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• Temporal stability of circulating microRNAs in human serum

  Circulating microRNA biomarkers for disease have been subject to extensive research. However, insufficient consideration of variability in the healthy population has led to few markers achieving the performance necessary in independent follow-up studies to be taken forward to clinical practice. To investigate the natural variation of circulating microRNA over time, we performed small RNA sequencing in a longitudinal study of 66 women with no history of cancer, and determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2-5 years. We also investigate abundances in circulation, as well as the impact of normalization, age, BMI, and other sample collection factors on microRNA measurements from small RNA sequencing.

  Study EGAS00001003221

• Clonal dominance defines metastatic dissemination in pancreatic cancer

  Using patient-derived cells from a pancreatic ductal adenocarcinoma, we created orthotopic clonal replica tumors to trace in an unbiased fashion clonal lineage dynamics of unperturbed tumor expansion and dissemination over time. The model revealed the complex multifaced nature of tumor clonal expansion and uncovered brisk changes in fitness that lead to a continuous reshuffling of tumor clonal architecture and alternating clonal dominance as a distinct feature of cancer growth. Paired analysis of clonal lineages in primary and secondary sites revealed fitness in the primary tumor as a major contributor to dissemination, although other clonal intrinsic and extrinsic factors may contribute to metastatic process. Molecular characterization of lineages with differential metastatic potential identified actionable strategy to suppress dissemination at the subclonal level.

  Study EGAS00001006358

• Reconstruction of the personal information from human genome reads in gut metagenome sequencing data

  Human DNA present in fecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is currently unclear how much personal information can be reconstructed from such reads and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable the efficient use of human genetic information in stool samples, such as for research and forensics. Here, we used genomic approaches to reconstruct personal information from fecal metagenomes of 343 Japanese individuals with associated human genotype data. Our approach can be used to quantify the personal information contained within gut metagenome data.

  Study EGAS00001007027

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Dataset EGAD00001007872

• Access to shallow whole genome sequencing data from DETECT

  Access to this dataset is subject to aceptance of the terms and conditions. Please summarise your project and sign the following document:

  Dac EGAC50000000553

• Primary T-cell differentiation to T helper subtypes

  human CD4+ T cells differentiated to diverse T helper subtypes

  Study EGAS50000000818

• Submitter Portal

  Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submission. To start a new submission click on “Create a Submission”.In this phase you have the option to add any collaborator(s) as well as their permissions (“Read only” or “Read & Write”). If you want to invite all the collaborators from a previous submission, you can add them by selecting said submission.In the event that the submission has been closed, you will need to reopen it. To do this, you will need to modify one of the objects in the submission, for example, copy and paste the title. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv and the sample will be created.Add single sample: complete the mandatory fields with the metadata information of your sample.  Further information can be found in the Submission Tour5. Create Experiment Register an experiment with ​information about the sequencing methods, protocols and machines. Experiments generate the connection between samples and study. Further information can be found in the Submission Tour6. Create Run Samples, experiments and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batch by using a template. Batch upload: download the template and complete it with the sample - file linkage. Upload the run.csv and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh. Add single run: select the file format, sample and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded in your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF and phenotype linkage to samples. The analysis is an EGA specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested please delete them from your SFTP INBOX before finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button, and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more file to a closed submission, you will need to re-open the submission where the dataset was registered. Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission id (EGA0XXX).  Reopen the submission where the dataset is located: to reopen a submission, you must edit any object within the submission. For example, you can copy and paste the title. Take The Tour The Submitter Portal Take The Tour is a visual guidance of all the steps described previously about how to start a submission. Tutorial In this tutorial we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

• Determination of Cross-Reactive Immunological Material (CRIM) status and longitudinal follow-up of individuals with Pompe disease

  Infantile-onset Pompe disease is an inherited disorder that is normally diagnosed within the first months of life. It is caused by lack of or defect in an enzyme (a special protein that carries out normal chemical reactions within the body) called acid alpha-glucosidase (GAA). GAA normally breaks down glycogen (stored sugar) in lysosomes (the part of the cell that digests food and other chemicals). Pompe disease is one of many lysosomal storage diseases (LSDs). LSDs are diseases caused by the malfunction of the lysosome or one of their digestive enzymes. Patients with Pompe disease cannot break down lysosomal glycogen. This causes glycogen to build up and damage cells throughout the body, especially in the heart and muscles. Current treatment for Pompe disease involves enzyme replacement therapy (ERT). In this treatment, the drug alglucosidase alfa (Myozyme) is put into your blood. The drug provides a form of the GAA enzyme to replace the enzyme that is missing or not working properly in the patient's blood. This treatment has allowed babies to live longer and achieve developmental milestones. In this study, researchers will learn about the patient's ability to tolerate ERT. Cross-Reactive Immunological Material (CRIM) is a measurement of natural GAA production. A patient's CRIM status (either positive or negative) is an important factor that affects how he or she responds to ERT with Myozyme. Children who produce some natural GAA are classified as CRIM+, while children who do not produce any natural GAA are classified as CRIM-. Children who are CRIM+ generally tolerate ERT well. But, children who are CRIM-, and some children classified as CRIM+, have a poor response to ERT. Patients who have a poor response to ERT have complications because their body sees Myozyme as "foreign" and triggers an immune response to try to remove it from the body. Treatments are currently being developed to stop this immune response and prevent complications from ERT. We will enroll patients with Infantile Pompe disease in this longitudinal natural history (observational) study. The specific aims of this study are: To determine and correlate Cross-Reactive Immunological Material (CRIM) status with the GAA gene mutations found on these patients To validate an approach for determining CRIM status from whole blood sample, with the gold standard determination of CRIM status by skin fibroblasts and mutation analysis To explore the clinical treatment response and natural history of CRIM-positive and CRIM-negative Pompe disease patients with and without immune modulation To investigate the role of immune response to treatment

  Study phs001555

• Study of Adaptation to Hypoxia in Ethiopian Highlanders via Whole Genome Sequencing

  Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome (either exons or a subset of SNPs) or a group of candidate genes, interpretation of the results was limited. We focused our study on Ethiopian highlander populations, which have been found to be well adapted to high altitudes (~3500m). We sequenced and analyze the genomes of 13 high altitude native Ethiopians: 6 individuals of Oromo heritage living on Bale Plateau (labeled "Oromos"), and 7 individuals residing on the Chennek field in the Simien Mountains (labeled "Amhara"). Our study revealed evolutionarily conserved genes that modulate hypoxia tolerance.

  Study phs000647

• Genomic Predictors of Response to Immune Checkpoint Therapy

  Immune checkpoint therapies, including monoclonal antibodies to programmed cell death-1 (PD-1) and cytotoxic % lymphocyte associated protein-4 (CTLA-4), yield durable clinical responses across many tumor types, including metastatic melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). However, predictors of response to these therapies in RCC are still unknown. Genomic characterization of large clinical cohorts of patients treated with anti-CTLA-4 and anti-PD-1 agents in melanoma and NSCLC have suggested that high mutational burden, high neoantigen burden, and high expression of certain genes in pre-treatment tumors may be associated with patient response to these therapies. In this study, we sought to investigate genomic predictors of response to anti-PD1 therapy in metastatic RCC in two independent clinical cohorts using whole exome and whole transcriptome sequencing.

  Study phs001493

• Transgenerational Transmission of Post-Zygotic Mutations Suggests Symmetric Contribution of First Two Blastomeres to Human Germline

  Skin and blood samples were collected from four phenotypically normal individuals (mother, father, and children) from a randomly selected family. Whole genomes of the samples from these individuals were sequenced to a depth of 30X-200X. Sequencing data for the mother was previously analyzed and is available at NDA collection #2961. Sequenced reads from the children and father were aligned to the human reference genome (hg19) generating BAM files for each individual. We used post-zygotic mutations in the mother to trace cell lineages across human generations. Analysis of this family demonstrated that different cell lineages were transmitted to offspring. Coupled with analysis of publicly available data, this result revealed a fundamental difference between soma and germline in lineage allocation and suggested a 50:50 contribution of the first two blastomeres to the germline.

  Study phs003781

• Spatiotemporal immune atlas of the first clinical-grade gene-edited pig-to-human kidney xenotransplant

  Pig-to-human xenotransplantation is rapidly approaching the clinical arena; however, it is unclear which immunomodulatory regimens will effectively control human immune responses to pig xenografts. We transplanted a gene-edited pig kidney into a brain-dead human recipient on pharmacologic immunosuppression and studied the human immune response to the xenograft using spatial transcriptomics and single-cell RNA sequencing. Human immune cells were uncommon in the porcine kidney cortex early after xenotransplantation and consisted of primarily myeloid cells. Both the porcine resident macrophages and human infiltrating macrophages expressed genes consistent with an alternatively activated, anti-inflammatory phenotype. No significant infiltration of human B or T cells into the porcine kidney xenograft was detected. Altogether, these findings provide proof of concept that conventional pharmacologic immunosuppression is sufficient to restrict infiltration of human immune cells into the xenograft early after compatible pig-to-human kidney xenotransplantation.

  Study EGAS50000000244

• Recapitulation of genetic predisposition to medulloblastoma in human neuroepithelial stem cells

  Human neural stem cell cultures provide progenitor cells that are potential cells of origin for brain cancers. However, the extent to which genetic predisposition to tumor formation can be faithfully captured in stem cell lines is uncertain. Here we evaluated neuroepithelial stem (NES) cells, representative of cerebellar progenitors. We transduced NES cells with MYCN, observing medulloblastoma upon orthotopic implantation in mice. Significantly, transcriptomes and patterns of DNA methylation from xenograft tumors were globally more representative of human medulloblastoma compared to a MYCN-driven genetically engineered mouse model. Orthotopic transplantation of NES cells generated from Gorlin syndrome, patients predisposed to medulloblastoma due to germline mutated PTCH1, also generated medulloblastoma. We engineered candidate cooperating mutations in Gorlin NES cells, with mutation of DDX3X or loss of GSE1 both accelerating tumorigenesis. These findings demonstrate that human NES cells provide a potent experimental resource for dissecting genetic causation in medulloblastoma.

  Study EGAS00001003620

• Conserved interferon-gamma signaling and decreased immune exclusion programs in responses to immune checkpoint blockade therapy

  We analyzed baseline and on-therapy tumor biopsies from 101 patients with advanced melanoma treated with nivolumab (anti-PD-1) alone or combined with ipilimumab (anti-CTLA-4). Analysis of whole transcriptome data showed that T cell infiltration and interferon-gamma signaling signatures corresponded most highly with clinical response to therapy, with a reciprocal decrease in cell cycle and WNT signaling pathways in responding biopsies. Clinical outcome differences were likely not due to differential melanoma cell responses to interferon-gamma, as 57 human melanoma cell lines exposed in vitro to this cytokine showed a conserved interferon-gamma transcriptome response unless they had mutations that precluded signaling from the interferon-gamma receptor. Therefore, the magnitude of the antitumor T cell response and the corresponding downstream interferon-gamma signaling are the main drivers of clinical response or resistance to immune checkpoint blockade therapy.

  Study EGAS00001004545

• Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

  Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized. Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

  Study EGAS00001007767

• FHS-Net Social Networks

  Note: Data Use Restrictions: The data must only be used for genetic research projects solely in the area of health-related social-network research. This study compiles detailed information on family and social ties linked to participants in the offspring cohort of the Framingham Heart Study. The investigators took computerized information from self-report data used by the FHS for over 30 years to facilitate health exam scheduling. These tracking sheets asked participants to identify people close to them, which were assumed by the investigators to indicate a social tie. Individuals are listed as "egos" (if the ties are from their perspective) and/or "alters" (if they are linked as a friend or family members to one of the other participants). All egos were FHS offspring participants while alters could be FHS participants in any cohort or non-participants. This information was combined with internal FHS pedigree data on family ties to list family member alters (as well as the nature of their relationship). The resultant dataset therefore includes each ego-alter tie, the nature of their relationship and the start and end dates for their ties for each of seven waves for the offspring study. Due to privacy concerns, all exam dates for individuals are listed relative to the initial FHS exam date. The study investigators chose a random, confidential date, to which all initial exam dates are linked (by number of months from random date to initial exam date). With this information, researchers can have access to the temporal relationships among participants' exam dates while remaining unaware of the actual exam dates for individual participants. During each clinic exam cycle, the participants undergo a detailed examination including physical examination, medical history, laboratory testing, and electrocardiogram. Over the years, other tests (that may not be performed at every exam cycle) have included pulmonary function, lifestyle, physical function, cognitive function questionnaires, and various noninvasive cardiovascular tests including echocardiograms. This study involves phenotypic data from these exams including (when available) basic body measurements (height, weight, blood pressure), laboratory values (blood sugar levels, LDL levels), information on smoking and alcohol use, and tests of depression and cognitive functioning. Important links to apply for individual-level data Data Use Certification Requirements (DUC) Instructions to Request Authorized Access Apply here for controlled access to individual level data Participant Protection Policy FAQ In 1948, researchers recruited men and women from the town of Framingham, Massachusetts, beginning the first round of extensive physical examinations and lifestyle interviews that would later be analyzed for common patterns related to CVD development. Initially, the Framingham Heart Study enrolled 5,209 men and women from the Framingham area who were between the ages of 28 and 62 years. Beginning in 1971, the Framingham Heart Study enrolled 5,124 men and women, who were either offspring of the original cohort or spouses of those offspring. In 2002, 4,095 third generation participants (men and women) were enrolled.

  Study phs000153

• Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial

  Summary of the Design and Aims: The Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial (CAF-PINT) is an ancillary study to the HALF PINT (NCT01565941) randomized, controlled trial that was originally designed to study changes in inflammatory and thrombosis pathways in the setting of an interventional trial. The parent HALF PINT study was designed to study the impact of tight glycemic control (TGC) using an explicit insulin titration algorithm to safely achieve a normal glucose in target range of 80-110 mg/dL versus 150-180mg/dL on clinical outcomes among critically ill hyperglycemic children with Heart and Lung Failure. The CAF PINT study collected blood samples pre randomization and at 2 and 4 days after randomization. Blood samples collected in EDTA tubes were centrifuged at local sites to separate the plasma from cell pellets and frozen prior to shipment. In addition, 0.5 mL of whole blood collected in PAXgene tubes modified for use in pediatrics frozen 24 hours after collection prior to shipment.Population Information: Setting: Twenty-one academic children's hospitals (HALF-PINT) and 1 academic children's hospital (IIT-SBPP). Participants: Critically ill hyperglycemic children requiring mechanical ventilation/vasoactive support (n=293).Interventions and Exposures: Patients in HALF PINT were randomized to achieve a low target glucose (80-110 mg/dL) vs. a higher target (150-180 mg/dL). The primary trial was stopped early due to low likelihood of achieving a statistically significant difference in the primary outcomes. Molecular Technologies Employed: Plasma biomarkers were assayed on thawed plasma using a Luminex panel. RNA was extracted from PAXgene Blood RNA Kits modified for pediatric use. Extracted RNA was sequenced with the Novaseq S4 system (Illumina) to generate 2 x 150 base paired end reads to a target depth of 50 million read-pairs per sample.Principal Findings of the Study: We tested for heterogeneity of treatment effects according to baseline blood inflammatory proteins using logistic regression with individual biomarkers as interaction terms and Cox regression analysis using biomarker-derived latent classes. Children with higher inflammatory proteins including TNFR-1, IL-6, IL-8, and IL-10 had lower mortality when treated with insulin to a target glucose of 80-110 mg/dL as compared to 150-180 mg/dL (interaction p<0.05). Causal forest estimates ranged from a 40% mortality reduction to a 15% mortality increase with TGC, depending on each patient’s individual biomarker profile. Latent class categorization strongly interacted with TGC with respect to mortality (Cox regression interaction p=0.005). Specifically, patients with higher inflammation benefited from TGC (6% mortality with TGC vs. 48% mortality, p=0.004) whereas hypoinflamed patients showed a trend towards harm (14% mortality with TGC vs. 7% mortality, p=0.055).Data available through dbGaP: Transcriptomic (Gene Counts) and phenotype data

  Study phs003016

• Feasibility and Clinical Utility of Whole Genome Profiling in Pediatric and Young Adult Cancers

  Comprehensive Whole Genome Sequencing and Whole Transcriptome (RNASeq) analyses from 114 pediatric patients at Memorial Sloan Kettering. This dataset was used as a prospective clinical utility and feasibility study. By using our Isabl infrastructure for precision medicine, we developed a 2-week end-to-end pipeline to analyze cfDNA, WGS and WTS, which we refer to as cWGTS.

  Study phs002620

• Biomarkers for Noise-Induced Sleep Disruption

  This project aims to investigate gene expression biomarkers for noise-induced sleep disruption and cognitive changes. The project is a sub-study, part of the larger ASCENT COE project 86 designed to test the ability of broadband pink noise to serve as a countermeasure for sleep loss from simulated aircraft noise. Gene expression research was sponsored by the Federal Aviation Administration.

  Study phs003932

• Elucidating the development of cervical cancer and identifying therapeutic targets based on cancer genome analysis.

  The objective of this project is to analyze genomic aberrations and gene expression changes, such as mutations, deletions, and amplifications, in human cervical cancer cells at the somatic cell level, and to contrast these with clinicopathological information to elucidate the molecular mechanisms and characteristics of lcervical cancer development and progression at the genetic level.

  Study JGAS000803

• Reference Panel for Imputation Analysis Based on Whole Genome Sequencing Data of 3,256 Japanese Individuals(BioBank Japan genotype data)

  This reference panel was constructed using whole genome sequencing data from 3,256 Japanese individuals and the 1000 Genomes Project. It provides high accuracy and utility in analyzing genetic polymorphisms, while also reflecting the genetic diversity specific to the Japanese population. This dataset is expected to contribute to the advancement of genetic research and personalized medicine.

  Study JGAS000746

• Spatial transcriptome analysis of aging of healthy skin samples

  Previous studies have revealed that skin T cells accumulate and maintain immune responses in the elderly. However, we questioned why these functional T cells fail to recognize and eliminate malignant cells, making elderly skin more prone to developing malignant tumors. To address this question, we examined the overall skin microenvironment in aging using Xenium digital spatial RNA sequencing.

  Study JGAS000771

• Cancer genomics for elucidation of molecular mechanisms of carcinogenecis and progression in lung cancer

  The objective of this project is to analyze genomic aberrations and gene expression changes such as mutations, deletions, amplifications, and hypermethylation in human lung cancer cells at the somatic cell level, and to contrast these with clinicopathological information to elucidate the molecular mechanisms and characteristics of lung cancer development and progression at the genetic level.

  Study JGAS000756