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• Small variants in mtDNA Canary Islands - WES Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005678

• Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005679

• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• Bladder cancer subtyping study across 4 atezo clinical trials

  Checkpoint inhibitors targeting the PD-1/PD-L1 interaction have revolutionized cancer therapy across many indications. In urothelial carcinoma (UC), several PD-1/PD-L1 inhibitors have been approved for treatment in localized and metastatic disease. While these agents provide durable clinical benefit in a number of patients, the majority do not respond. A better understanding of the molecular mechanisms underlying response and resistance is needed to tailor existing treatments and develop new therapeutics in UC. We profiled tumors from 2803 patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab in metastatic UC and muscle-invasive bladder cancer by RNA-seq, a targeted DNA panel, immunohistochemistry, and digital pathology. A machine learning algorithm identified four UC transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care was observed in immune and basal tumors (45% of patients). Digital pathology showed enrichment of human interpretable features in specific molecular subtypes, and a self-supervised approach could classify molecular subtypes from H&E slides with high accuracy, suggesting that machine-based image interpretation could accelerate tumor molecular profiling. Somatic alterations showed limited capacity to identify responders. Finally, mechanisms of benefit with PD-L1 blockade appeared different in immune and basal tumors, with immune tumors benefiting from B/plasma cell enrichment, while basal tumors benefited from granulocyte enrichment. This study represents the largest integration of UC molecular and curated clinical data in randomized clinical trials to date, paving the way for prospective clinical studies tailoring treatment regimens to specific tumor molecular subtypes in UC and other indications.

  Study EGAS50000000497

• A reference map of potential determinants for the human serum metabolome

  The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.

  Study EGAS00001004512

• All you need to know about our new DAC Portal v2

  An updated version to boost the management of DACs (Data Access Committees), policies, and data access requests. In September of 2023, we launched new services for all EGA users, including a DAC Portal. Since then, our team has been working to refine it and improve the user experience. The version 2 of our DAC Portal is now ready, with a range of new features aimed at streamlining your workflow and boosting productivity. If you are interested in learning more about the latest version of our DAC Portal, then you are in the right place! In this post, you will find information about the implemented features and more. The full documentation is available on our website. Moreover, we highly recommend exploring the DAC Portal through the Take the Tour. This said, let's get cracking! Customise your data access requests table This table offers the possibility to tailor information about the data access requests by making visible or hiding different columns regarding the Dataset Persistent Identifier, the Organisation or the requestor's name s, among others. You can choose which columns to see, depending on your needs and interests. Additionally, we have implemented two new features columns with two new functionalities, DAC Comment and Expiration Date. You can find more details in the following sections! In this table, all data access requests are displayed by default. With the latest version of the Portal, you can now apply filters, combine them, and save them for future use. Leave internal comments on pending requests and visible to all the DAC Members We understand that many Data Access Committees (DACs) cannot instantly approve or deny data access requests. Often, there's an intermediary phase where discussions and the signing of legal documents are necessary. To facilitate this process, we've introduced the DAC comment feature! When you navigate to the DAC column, you'll find two tabs: "User" and "DAC". Under "User", you'll see the message provided by the requester at the time of requesting access to the data. As a DAC member/admin, you can then add an internal comment in the "DAC" tab. These comments are visible only to DAC members/admins, ensuring confidentiality. Requesters won't have access to DAC comments. By adding a DAC comment to a pending request, we'll know that you've begun reviewing it. This allows you to filter pending requests without DAC comments to focus on genuinely new requests, and it prevents you from receiving email notifications about ongoing data requests. Set expiration dates for permissions and revoke them automatically The latest update to the DAC Portal introduces a new feature allowing you to set expiration dates for new access requests. For instance, if you anticipate approving a data access request but only wish to grant access for a limited time, you can now specify an expiration date for the granted permissions. Once this date is reached, the permissions will automatically be revoked. By default, permissions are granted indefinitely without an expiration date. However, if you ever need to revoke permissions, you can easily do so from the History page. Audit your metadata objects Managing and auditing your metadata objects will be easier from now on as the new DAC Portal enhances and facilitates your role as a Data Controller. This is possible thanks to the tables available in each of the primary tabs visible on the homepage: DACs, Policies and Datasets. Starting with DACs, this section allows to check the policies linked to a specific DAC. In Policies, you can obtain a list of the datasets connected to a particular policy. In the Dataset tab, it is possible to group datasets by either DAC or Policy, as well as the release status. Now you have the option of deprecating metadata objects that you don’t want to use anymore, or that were created by mistake. You will find the deprecate button on the EDIT page of the DAC, as well as for registered policies. You can find more information here. What's neat about this feature is that once a DAC or policy is deprecated, it becomes hidden within the DAC Portal. This ensures that you only see information that is consistently up to date! Define your preferences regarding email notifications For pending requests, you will be able to decide how often you want to get the notifications: daily, weekly or fortnightly. Remember, you will not receive email notifications for pending requests with a DAC comment! Furthermore, you have the flexibility to decide which notifications you wish to receive, such as invitations to join a new DAC or notifications regarding DAC acceptance by the Helpdesk, among other options. Check the User preference to see the complete list of available notification settings! What’s next: incoming DAC Portal API In addition to the new DAC Portal, we are excited to announce the release of the DAC API! This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can consult the DAC API specification. This post was written by Aina Jené and Ana T. Alonso.

  Blog new-dac-portal-v2

• Butyrate producers as potential next-generation probiotics: safety assessment of the administration of Butyricicoccus pullicaecorum to healthy volunteers

  Advances in gut microbiota research have triggered interest in developing colon butyrate producers as niche-specific next-generation probiotics, targeted at increasing colon butyrate production and countering disease-associated microbiota alterations. Crucial steps in the development of next-generation probiotics are the design of formulations with a reasonable shelf life as well as the safety demonstration of an intervention in healthy volunteers. One such potential next-generation butyrate-producing probiotic is Butyricicoccus pullicaecorum 25-3T, with demonstrated safety in in vitro as well as in animal models. Here, we examined the strain's safety, tolerability, and impact on microbiota composition and metabolic activity in healthy volunteers in a randomized, double blind, placebo-controlled, crossover study in 30 healthy volunteers. Study design consisted of two four-week intervention periods (108 CFU B. pullicaecorum [treatment] or maltodextrin [placebo] per day) with a three-week washout in between. We assessed adverse events, blood parameters (primary endpoints), and fecal microbiota composition and metabolite profiles (secondary endpoints).The number of reported adverse events during the B. pullicaecorum treatment was similar to placebo intervention, as were observed changes in blood chemistry parameters, bowel habits, and fecal calprotectin concentrations. Administration of the strain did not induce any disruptive effect in microbiota composition or metabolic activity. In this first human intervention trial with a butyrate-producing Clostridium cluster IV isolate, we demonstrated B. pullicaecorum 25-3T administration to be both safe and well tolerated by healthy participants. This safety study paves the way for the further development of the strain as a next-generation probiotic.

  Study EGAS00001003276

• NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate

  The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.

  Study phs001359

• Whole genome sequencing of core-binding factor leukemia

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study phs000414

• The Genomic Landscape of Core-Binding Factor Acute Myeloid Leukemias

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study EGAS00001000349

• Multi-omics profiling identifies two epithelioid sarcoma molecular subtypes with distinct signaling and immune characteristics

  Epithelioid sarcoma (EpS) is an aggressive sarcoma, characterized by the loss of SMARCB1 expression. EpS is traditionally classified as distal or proximal according to clinicopathological features, but its molecular characteristics remain largely unknown. To establish an EpS molecular classification and uncover determinants of inter- and intra-patient heterogeneity in EpS, we used multi-omics profiling and integrated the genomic, transcriptional and methylome landscapes with single-cell RNA sequencing on fresh samples as well as spatial transcriptomics. We identified two molecular subtypes of EpS: “distal-like” and “proximal-like”, which were distinct from the histological subtypes. Distal-like tumors include all morphological distal subtypes and a subset of proximal and hybrid EpS. They express a specific molecular single-cell derived epithelial-to-mesenchymal transition signature, which associates with improved patient survival and includes Desmoglein 2 (DSG2), which we identify as a potential routine immunohistochemical biomarker to improve diagnosis. Distal-like EpS also display increased peri-tumoral CD8+ T cell infiltrates and specific tumor-immune cell interactions. Conversely, proximal-like EpS harbor a higher inter-tumoral molecular heterogeneity with some cases resembling other SMARCB1-deficient tumors by DNA methylation profiling, and increased intra-tumoral pro-tumoral macrophage infiltrates. Our study introduces a novel molecular classification of EpS with prognostic value, associated diagnostic biomarkers and distinct tumor immune microenvironments, which extends beyond traditional clinicopathological classification. This paves the way for precision medicine-based therapeutic strategies for patients with EpS.

  Dac EGAC50000000552

• Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals.

  Study phs001238

• NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238.

  Study phs001345

• The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

  The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

  Study EGAS00001008040

• TSO500 STJAN33, BRAF mutated CUP

  The data set contains FASTQ files (filetype) of a NEXTSEQ550DX run (instrument). De FASTQ files are from DNA and RNA sample. The Library prep is a NGS TSO500 library prep (Illumina) (technology). A Study to Examine the Clinical Value of Comprehensive Genomic Profiling Performed by Belgian NGS Laboratories: a Belgian Precision Study of the BSMO in Collaboration With the Cancer Centre (BALLETT) This 2-year study involves the consortium of 9 cooperating Belgian NGS laboratories and will enroll 936 metastatic or locally advanced cancer patients coming from 13 different Belgian hospitals and cancer centers. Upon inclusion, all cancer patients will be offered 'comprehensive genomic profiling' (CGP) using Illumina's TSO500 NGS panel. This targeted NGS panel of 523 genes allows for the detection of single nucleotide variants, small indels, copy number variations and fusions, as well as for the determination of the 'tumor mutational burden' (TMB) and the 'microsatellite-instability' status (MSI). Both the wet lab execution of the CGP as well as the biological and clinical classification of the variants will be performed in a fully standardized way among the 9 participating Belgian local NGS laboratories.

  Dataset EGAD50000000689

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Epilepsy: Epi25 Consortium

  Epilepsy genetics research is at an exciting stage where it is now feasible, with the power of a large cohort, to understand the more complex genetic components of epilepsy. The driving principle behind the Epi25 Consortium is collaboration and synergy - it is only possible to achieve this type of research by working together. The Epi25 Consortium was formed by the unification of various consortia, including Epi4K, EPIGEN, EuroEPINOMICS, the Epilepsy Phenome/Genome Project, EpiPGX, SANAD, and EpiCURE, and individual epilepsy investigators. The consortium's sample collection is the best resource in the world for this disease, both in terms of numbers of patients and quality of phenotypic information. As part of the NHGRI Centers for Common Disease Genomics (2016-2020), we aggregated a global sample collection from the various repositories for whole genome genotyping and whole exome sequencing (WES) at the Broad Institute (Cambridge, MA), initiating the largest and most ethnically diverse genetic study of epilepsy to date. The primary epilepsy phenotypes for Epi25 are based on strict standards agreed upon by the epilepsy community. The epilepsy cases contributed by Epi25 sites can be broadly defined as genetic generalized epilepsy (GGE), non-acquired focal epilepsy (NAFE), epileptic encephalopathies (EE), and lesional focal epilepsies. More information about eligibility criteria and phenotyping forms for Epi25, as well as the contributing centers, can be found here: epi-25.org The genomic data will be analyzed iteratively to identify genes and variants that explain these types of epilepsy. Summary clinical data compiled in the Epi25 clinical database will allow retrospective phenotypic analyses of groups of subjects with common genomic variant(s).

  Study phs001489

• Longitudinal Studies of Patients with Familial Platelet Disorder with Associated Myeloid Malignancy (FPDMM)

  FPDMM (OMIM #601399) is a rare autosomal dominant disease characterized by defective megakaryocytic development, thrombocytopenia, platelet functional defects, and a life-long risk of developing hematological malignancies. FPDMM is caused by germline mutations in the RUNX1 gene, which encodes a master regulator of hematopoiesis. The overall lifetime risk of hematological malignancies in FPDMM patients is 35 - 45%. It is hypothesized that mutations in other genes cooperate with the germline RUNX1 mutations for leukemia development. However, it is not clear which genes need to be mutated for leukemia to develop and which biomarkers or clinical tests can be used to predict which patients will progress to leukemia. Likewise, there are no treatments and/or preventative measures that can reduce or stop disease progression except for stem cell transplantation, which is not available for all patients and may be associated with significant complications. To address these questions, we launched a longitudinal natural history study of patients associated with RUNX1 germline mutations at the NIH Clinical Center in early 2019 (Trial Registration ID: NCT03854318). The goals of this study are to: (1) perform comprehensive longitudinal phenotyping of FPDMM patients to document the full spectrum of both hematopoietic and non-hematopoietic manifestations of the disease; and (2) perform extensive genomic analyses of FPDMM patient samples to identify cooperating genomic variants, which may confer growth advantage that leads to clonal expansion of affected hematopoietic cells that may serve as the precursor to malignancies. The data available through dbGaP include exome sequencing and RNA-seq data from these patients. Diverse germline mutation types were identified in the RUNX1 gene, including splice site mutations and large deletions, in addition to nucleotide substitutions and small indels. Somatic mutations, especially in genes associated with clonal hematopoiesis of indeterminate potential (CHIP), were found in a substantial proportion of FPDMM patients who were leukemia-free. The findings suggest that the genomes in these patients are prone to somatic mutations and monitoring the dynamic changes of these somatic mutations prospectively may provide a way to predict progression to malignancies.

  Study phs003075

• Hepatitis C Antiviral Long-term Treatment Against Cirrhosis (HALT-C)

  Reprinted from http://www.haltctrial.org/ Purpose The Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) Trial is a randomized controlled trial designed to evaluate the safety and efficacy of long-term use of pegylated interferon for the treatment of chronic hepatitis C in patients who failed to respond to previous interferon therapy. The HALT-C Trial was developed to determine whether prolonged interferon therapy altered histological and clinical outcomes in a group of patients who had failed to eradicate hepatitis C virus with previous interferon treatment. Study Hypotheses In patients with chronic hepatitis C and bridging fibrosis who failed to eradicate the virus with previous interferon therapy, long-term treatment with interferon is safe and can prevent progression to cirrhosis. In patients with cirrhosis secondary to chronic hepatitis C who failed to eradicate the virus with previous interferon therapy, long-term treatment with interferon is safe and can reduce the risks of hepatic decompensation or of hepatocellular carcinoma. Study Design 1145 patients with chronic HCV and advanced hepatic fibrosis (Ishak stage 3-6) who failed to respond to previous treatment with interferon were enrolled at 10 clinical centers and entered into a Lead-in phase. They were treated with a combination of pegylated interferon (Pegasys®, Hoffmann-La Roche) 180 µg/week and ribavirin (1000-1200 mg/day) for 24 weeks. Patients who had no detectable HCV-RNA at week 20 continued on combination therapy until week 48. 662 patients who did not clear virus were randomly assigned at week 24 to either continue treatment with pegylated interferon alone (90 µg/week) for an additional 42 months, or to have treatment discontinued. All patients were followed at 3-month intervals following randomization. Liver biopsy was performed at baseline and after 1.5 and 3.5 years of treatment. Because of slower than expected enrollment and the approval by the FDA of peginterferon alfa-2b after the start of the trial, we modified the study protocol in three ways. First, criteria for admission to the trial were liberalized to allow patients to enter the trial with lower platelet and white blood cell counts than had been initially considered safe or tolerable. Second, 151 Lead-in patients and those continuing on therapy after 24 weeks who demonstrated return of viremia during or after their 48-week treatment period (called "Breakthrough" or "Relapse" patients, respectively) were allowed to return to enter the randomized trial. Third, 237 patients treated with peginterferon alfa-2b (or with peginterferon alfa-2a in licensing trials) outside the HALT-C Trial who in other respects met all study criteria, having received the equivalent of Trial Lead-in period therapy, were allowed to enter the long-term trial as "Express" patients. A total 1050 patients were randomized. Those patients who completed Month 48 were offered an "extended follow-up (observation only)" until October 2009. These visits will primarily be to identify outcome events, and to provide information to patients concerning the current status of the trial. Some questionnaires, blood tests, and an ultrasonogram will be performed. Quarterly (every 3 months) Interval history of complications, adverse events Current medications Brief physical examination Laboratory tests: liver panel, CBC, INR, AFP Child-Pugh Score Stored serum Annual Complete physical examination Ultrasound of liver 1.5 years (M24 visit, middle of study) Liver biopsy: formalin fixed histology, frozen liver tissue (subset of patients) 3.5 years (M48, end of study) Liver biopsy: formalin fixed histology, frozen liver tissue (subset of patients) Endoscopy: evaluate esophageal varices and portal hypertension After Month 48 Observation only (no treatment) to determine clinical outcomes Clinic visit every 6 months with current medications, brief PE, liver panel, CBC, AFP, stored Serum Ultrasound of liver every 6 months Outcome Variables Primary outcome variables to be assessed in the two groups of patients include: Development of cirrhosis on liver biopsy (progression of Ishak fibrosis score by 2 points or more) Development of hepatic decompensation, as shown by: Sustained increase in the Child-Turcotte-Pugh score to 7 points or higher Variceal hemorrhage Ascites Spontaneous bacterial peritonitis Hepatic encephalopathy Development of hepatocellular carcinoma Death Secondary outcomes include quality of life, serious adverse events, events requiring dose reductions, and development of presumed hepatocellular carcinoma.

  Study phs000430

• GEnomics and Transcriptomics of Human INsulinoma (GETHIN)

  The Genomics and Transcriptomics of Human Insulinoma (GETHIN) The common forms of diabetes - Types 1 and 2 - ultimately result from a deficiency of insulin-producing pancreatic beta cells. The Genomics and Transcriptomics of Human Insulinoma (GETHIN) study was performed in order to identify novel approaches to inducing human pancreatic beta cells to replicate and regenerate. As a corollary, developing drugs that are able to expand human beta cell mass in people with diabetes should reverse diabetes. Unfortunately, identifying druggable pathways that can enhance human beta cell replication has been a major challenge. In 2017, there is only one class of drugs - the harmine analogues - that can induce human beta cells to replicate, and in this case, higher replication rates are desirable. Thus, identifying additional drugs and druggable pathways is a priority in diabetes research. Insulinomas are rare, benign adenomas of the pancreatic beta cell that cause excess insulin production and hypoglycemia: exactly the opposite of Types 1 and 2 diabetes. Beta cell proliferation rates in insulinomas are abnormally high. Thus, the premise for The Genomics and Transcriptomics of Human Insulinoma study is that benign human insulinomas hold the genomic and transcriptomic "recipe", and the repertoire of druggable pathways, that can be exploited to induce regeneration or replication of human beta cells in diabetes. Because, insulinomas are so rare, are almost always benign (non-malignant), and are easily resected by laparoscopic surgery, little attention has been paid to understanding the genomics or transcriptomics of insulinoma. There are at present only three published studies employing next-gen sequencing in insulinoma (PMID:24326773; PMID:25787250; and PMID:25763608). These studies contained 10, 7 and 8 insulinomas, respectively, and highlighted likely mutations in YY1 and MEN1. Our goal was to markedly expand the database and to add RNAseq to these earlier studies. The GETHIN study reports next-gen sequencing on 38 insulinomas, by far the largest series of human insulinomas subjected to next-gen sequencing (see the Selected publications section for reference). This includes paired (genomic plus tumor) whole exome sequencing on 26 human insulinomas (22 sequenced at Mount Sinai, 4 downloaded from Cao et al, PMID:24326773), and 25 sets of RNAseq from insulinomas, some of which also had paired whole exome sequencing, and some of which did not. The insulinoma RNAseq was compared to RNAseq from 22 sets of FACS-sorted normal human beta cells. Since insulinomas are so rare, the 38 insulinomas were collected by several investigators at several institutions over several decades, but most (22 whole exome sets, and all RNAseq) were sequenced at the Icahn School of Medicine at Mount Sinai in New York. The current dataset contains whole exome sequencing and RNAseq on the 11 insulinomas harvested at Mount Sinai. The four from Cao et al can be retrieved from Cao et al PMID:24326773. Fastq files from the remaining 23 insulinomas will be added as the local IRBs and Institutional Certifications are acquired. Complete patient data are provided in our Nature Communications report. Going forward, our intention is to expand this series, with the goal of sequencing 100 human insulinomas. These will be added to dbGaP as they accrue. Paired-end whole exome sequencing (mean usable sequencing depth 79X and 105X for blood and insulinoma, respectively) was performed using an Illumina HiSeq 2500. Insulinoma and sorted normal beta cell RNAseq was performed on Ribozero and polyA paired end libraries using the Illumina HiSeq 2500. Complete sequencing and bioinformatic details are provided in our Nature Communications report. The principal findings from the study are that although each insulinoma has a different set of presumptive driver mutations, the majority converge on genes that are members of the Polycomb Complex, Trithorax Complex and other epigenetic modifying enzymes. In addition, 20% of insulinomas have copy number loss or loss of heterozygosity of all or most of chromosome 11, and the majority display abnormalities in CpG methylation and imprinting control on the imprinted Chr 11 p15.5-15.4 region that contains INS, IGF2, CDKN1C, KCNQ1, and other genes involved in beta cell specification and proliferation.

  Study phs001422

• Lessons learned from the exome sequencing of nine cases of infertility and the way forward

  This study investigated the role of exome sequencing in the diagnosis of male and female infertility. Nine unrelated cases referred between 2019 and 2024 were analysed using exome sequencing, with segregation confirmed by Sanger sequencing and functional assays for splicing variants. We identified nine causative variants in genes including TUBB8, PATL2, CCDC39, STAG3, KIAA0319, FBXO43, AGBL5/BBS7, PLCZ1, and HS6ST1, six of which were novel. The findings highlight diverse reproductive phenotypes such as oocyte maturation arrest, early embryonic arrest, spermatogenic failure, and syndromic infertility. This work demonstrates the value of combining genetic, functional, and clinical approaches to improve diagnostic yield and patient care in reproductive failure.

  Study EGAS50000001320

• TRanscriptomic ANalySis of left ventriCulaR gene Expression (TRANSCRibE)

  Myocardial ischemia occurs when there is a mismatch between coronary oxygen delivery and metabolic requirements of the myocardium, which may be clinically manifested during angina, coronary angioplasty or cardiopulmonary bypass (CPB). Myocardial ischemia may lead to a spectrum of myocardial stunning, hibernating myocardium, and ultimately cell death if the ischemic insult is severe. In the human heart, irreversible damage begins after approximately 20 to 40 minutes of oxygen deprivation. Observed molecular and cellular changes of myocardial ischemia are characteristic of an inflammatory response, but the exact mechanisms that underlie this pathological process are unclear and may not be full emulated by animal models of ischemia or infarction. Thus, we felt it valuable to investigate a human ischemia model. During cardiac surgery, CPB with aortic cross-clamping (AoXC) and cardioplegic arrest is associated with excellent clinical outcomes and suitable operative conditions. However, despite the use of cardioprotective strategies, AoXc during CPB is accompanied by a variable, yet obligate ischemic period lasting 1 to 3 hours, resulting in hypoxia, metabolic substrate depletion, reperfusion injury, apoptosis, and necrosis. Cardiac specific biomarkers of ischemia and infarction, including troponin, are elevated even after routine coronary artery bypass graft surgery and correlate with the duration of ischemia from AoXc.This process of CPB provides us with the ability to examine the transcriptional profile before and after an expected, consistent, and reproducible human ischemic event, albeit induced by cold cardioplegic arrest and not coronary occlusion. In addition, the absence of reperfusion in this time period allows us to examine the transcriptomic response to intermittent ischemia, without having to account for the perturbations of reperfusion injury. Although various animal models have been used to examine the effects of ischemia on cardiac function, no human data exist which examine the early transcriptomic response to a left ventricular (LV) ischemic insult. We therefore characterized the effect of cold cardioplegia induced acute ischemia on the transcriptional profile of the LV by performing whole transcriptome next-generation RNA-sequencing (RNA-seq) in patients undergoing cardiac surgery by sampling human LV tissue prior to, and after, the obligate ischemia during AoXC. We hypothesized that the cold cardioplegia induced ischemic injury will dramatically alter transcription in the human myocardium, and that we would identify genes and pathways, which will identify interventional targets for pharmacological therapy. Methods:We have collected left ventricle tissue samples and blood sample from patients undergoing heart surgery. We obtained punch biopsies (~3-5μg total RNA content) from the site of a routinely placed surgical vent in the anterolateral apical left ventricular wall of patients undergoing elective aortic valve replacement surgery with cardiopulmonary bypass. After an average of 79 minutes of aortic cross-clamping with intermittent cold blood cardioplegia for myocardial protection every 20 minutes, a second biopsy was obtained in the same manner. Tissue samples were immediately placed in RNAlater® (Ambion, ThermoFisher Scientific, Waltham, MA), and after 48 hours at +4°C were stored at -80°C until RNA extraction. Total RNA was isolated with Trizol and RNA quality was assessed using the Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA). Libraries were prepared by poly(A) mRNA isolation and reverse transcription Polymerase Chain Reaction (RT-PCR), then sequenced on the Illumina HiSeq2000 or HiSeq2500 (Illumina, San Diego, CA). As samples were analyzed at different times, different read lengths were employed, initially using single-end reads (n=20) and then transitioning to paired end reads (n=216), ranging from 36 - 100 base pairs. Raw sequencing files were processed using Sickle, Skewer, and STAR software, and aligned to GrCh37 or UCSC Hg19. DNA was isolated from whole blood using standard methods. SNP genotyping was performed using the Illumina Omni2.5Exome-8 BeadChip array with additional exome content (Illumina, San Diego, CA) chip, version 1.1. We first phased and imputed 93 subjects using a phasing tool called SHAPEIT and an imputation tool called MINIMAC, with 1000 Genomes phase 1 version 3 for the reference panel. We then phased and imputed 26 more subjects using SHAPEIT, an imputation tool called IMPUTE2, and 1000 Genomes phase 3 version 5.

  Study phs001679

• Genetic Basis of Early Onset Bicuspid Aortic Valve Disease

  The study protocol was approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston (HSC-MS-11-0185). Study recruitment began on July 1, 2017, and concluded on March 30, 2022. After written informed consent, we enrolled probands with early onset BAV disease (EBAV), which we defined as individuals with BAV who were under the age of 30 at the time of first clinical event. Clinical events were defined as aortic replacement, aortic valve surgery, aortic dissection, moderate or severe aortic stenosis or aortic regurgitation, large aneurysm (Z > 4.5), or intervention for BAV-related conditions. Those with hypoplastic left heart, known genetic mutations, genetic syndromes, or complex congenital heart disease were excluded. Samples were collected and genotyped as previously reported. For comparison, we analyzed a cohort of older individuals of European ancestry with sporadic BAV disease selected from the International BAV Consortium (BAVGWAS). Phenotypes were derived from record review with confirmation of image data whenever possible [25-26]. The computational pipeline for CNV analysis of Illumina single nucleotide polymorphism (SNP) array data included three independent CNV detection algorithms.GenomeStudio was used to exclude samples with indeterminate sex or more than 5% missing genotypes, and single nucleotide polymorphisms (SNPs) with GenTrain = 0. Principal component analysis was used to remove outliers that did not cluster with European ancestry. Prior to CNV analysis, each dataset was trimmed by selecting a common set of 650,000 SNPs that were genotyped on each of the microarrays used in this study.Three independent algorithms (PennCNV, cnvPartition, and QuantiSNP) were used to generate CNV calls and sample-level quality statistics from SNP intensity data. PennCNV and QuantiSNP were run on Unix clusters and cnvPartition data were exported from GenomeStudio. The analysis was run using default configurations. PennCNV was used to generate QC data and remove CNV calls that intersect with polymorphic genomic regions. Samples that met any of the following criteria were excluded, standard deviation of the LogR ratio (obtained from PennCNV) > 0.35 or number of CNVs > 2 standard deviations above the mean for each data set. CNV calls less than 20 Kilobases in length and/or spanned by fewer than 6 probes were excluded. The overlap function for rare CNVs in PLINK was used to construct CNV regions (CNVRs) after adjacent regions were merged using PennCNV. LogR ratio (LRR) and B allele frequency (BAF) data at CNVRs and calls of interest were visualized in GenomeStudio for validation. For segregation analysis, GenomeStudio was used to determine the presence of CNVs in relatives.A total of 22,014 unselected control Illumina Genotypes obtained from the Database of Genotypes and Phenotypes were analyzed using identical methods (S1 Table). The Wisconsin Longitudinal Study (WLS) includes data on a cohort of 10,300 individuals who graduated from Wisconsin high schools in 1957. The Health and Retirement Study (HRS) includes data on 37,000 individuals aged 50 above from 23,000 households across the United States. Principal component analysis was used to select European ancestry genotypes from these datasets for analysis. Datasets were paired for case-control analysis based on the concordance of log-transformed sample-level quality control statistics (number of CNV calls and standard deviation of logR ratios). Chi-squared or Fisher exact tests were used to compare CNV frequencies in cases and controls.Rare CNV functions in PLINK (v1.7) were used to perform permutation-based burden tests or gene set-based enrichment tests. Case control burden tests were restricted to CNVs that were longer than 110 Kb and less than 0.1% in frequency. CNV overlap functions in PLINK were used to identify rare CNVs that intersect between datasets or involve specific BAV or CHD genes . The list of candidate genes included 190 CHD genes that have strong cumulative evidence to cause BAV or related congenital malformations from human or animal model data. Genome Reference Consortium Human Build 37 was used for CNV annotation [34].

  Study phs003705

• Cell-free DNA sequencing data of healthy control, atrophic gastritis, and gastric cancer patients’ blood

  Sample cohort (n=48) is consisted of healthy, atrophic gastritis and gastric cancer patients. Some of the gastric cancer patients samples are collected at the separate time points: -1 before the operation; -2 after the operation; -3 during the control visit. For the hybridisation capture of the genes unique 15 gastric cancer-related gene panel was developed and very deep sequencing using TruSight Oncology Unique Molecular Identifier (UMI) Reagents (Illumina) was used.

  Dataset EGAD00001011153

• INSIGHT (Intervention Nurses Start Infants Growing on Healthy Trajectories) Cohort

  This is a study of the biological risk factors for children enrolled in the INSIGHT (Intervention Nurses Start Infants Growing on Healthy Trajectories) study. INSIGHT is a randomized, controlled trial testing a responsive parenting intervention designed for the primary prevention of childhood obesity against a safety control. These first-born children were deeply studied in this time period with data collected on a wide variety of variables including mode of delivery, gender, weight and height (collected at 7 time points), medication usage, diet information, and maternal health information (gestational weight gain, gestational diabetes, smoking during pregnancy). This study includes a survey of the oral and gut microbiota from 226 mother-child dyads. It was designed to investigate the relationship between a cross-sectional view of the child's microbiome (at two years of age) and the patterns of growth between birth and 2 years. Microbiome samples from children (buccal swab and stool sample) and their mothers (buccal swab) are collected at the children's 2-year clinical research visit. Stool metabolites have also been assayed for a subset of the 226 children using 1H-NMR. Additionally, we genotyped the same individuals for SNPs across the genome. For a subset of 48 individuals we have added second-born siblings. For these additional 48 children, we characterized the methylation pattern across the genome using cord blood and placenta samples.

  Study phs001498