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• UK10K NEURO FSZ

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. These Finnish schizophrenia samples have been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder, each family having at least two affected siblings. 170 families originate from an internal isolate (Kuusamo) with a three-fold lifetime risk for the trait. The genealogy of the internal isolate is well documented and the individuals form a “megapedigree” reaching to the 17th Century. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data. For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

  Study EGAS00001000118

• METABRIC

  Solid tumors are complex tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Normal cell contamination can dilute cancer cell information and tissue architecture is generally not reflected in molecular assays. To address these challenges, we developed a computational approach based on standard Haematoxylin and Eosin-stained sections and demonstrated its power in a discovery cohort of 323 breast tumors and an independent validation cohort of 241 tumors. First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.

  Study EGAS00000000098

• THAP11 mutations in a patient with a cblX-like phenotype implicates THAP11 in the regulation of cobalamin metabolism and early vertebrate development

  Mutations in HCFC1 are associated with cblX (MIM309541), an X-linked recessive disorder, characterized by defects in cobalamin metabolism and other developmental defects. HCFC1 is a transcriptional co-regulator, which interacts with transcription factors to regulate the expression of a myriad of genes. Notably, HCFC1 regulates cobalamin metabolism via the regulation of MMACHC expression through its interaction with THAP11, a THAP domain-containing transcription factor. In addition, the HCFC1/THAP11 complex potentially regulates genes involved in diverse cellular functions including cell cycle, proliferation, and transcription. Thus, it is likely that mutations in THAP11 may also result in biochemical and other phenotypes similar to those observed in patients with cblX. We report a patient who presented with phenotypic features that overlap cblX, but did not have any mutations in either MMACHC or HCFC1. We sequenced THAP11 by Sanger sequencing and discovered a potentially pathogenic, homozygous variant in THAP11, c.240C>G (p.Phe80Leu). Functional analysis in the developing zebrafish embryo, demonstrate that both THAP11 and HCFC1 regulate the proliferation and differentiation of neural precursors, suggesting important roles in normal brain development. Further, the loss of THAP11 in zebrafish embryos, results in craniofacial abnormalities including the complete loss of Meckel’s cartilage, the ceratohyal, and all of the ceratobranchial cartilages. These data are consistent with our previous work which demonstrated a role for HCFC1 in vertebrate craniofacial development. Furthermore, our high throughput RNA-sequencing analysis reveals several overlapping gene targets of HCFC1 and THAP11 that likely contribute to the phenotypes associated with cblX and related disorders. Thus, both HCFC1 and THAP11 play important roles in the regulation of cobalamin metabolism as well as other pathways involved in early vertebrate development.

  Study EGAS00001002201

• Whole exome sequencing of cell-free DNA reveals temporo-spatial heterogeneity and identifies treatment-resistant clones in neuroblastoma

  Background: Neuroblastoma (NB) displays important clinical and genetic heterogeneity, with emergence of new mutations at tumor progression. Patients and Methods: To study clonal evolution during treatment and follow-up, an innovative method based on circulating cell-free DNA (cfDNA) analysis by whole exome sequencing (WES) paired with target sequencing was realized in sequential liquid biopsy samples of 19 NB patients. Results: WES of the primary tumor and cfDNA at diagnosis showed overlap of Single Nucleotide Variants (SNVs) and Copy Number Alterations (CNAs), with 41% and 93% of all detected alterations common to the primary NB and cfDNA. CfDNA WES at a second time point indicated a mean of 22 new SNVs for patients with progressive disease. Relapse-specific alterations included genes of the MAPK pathway and targeted the protein kinase A signaling pathway. Deep coverage target sequencing of intermediate timepoints during treatment and follow-up identified distinct subclones. For 17 seemingly relapse-specific SNVs detected by sequencing detected these alterations in minor subclones, with relapse-emerging SNVs targeting genes of neuritogenesis and cell cycle. Furthermore a persisting, resistant clone with concomitant disappearance of other clones was identified by a mutation in the ubiquitin protein ligase HERC2. Conclusion: Modelisation of mutated allele fractions in cfDNA indicated distinct patterns of clonal evolution, with either a minor, treatment-resistant clone expanding to a major clone at relapse, or minor clones collaborating towards tumor progression. Identification of treatment-resistant clones will enable development of more efficient treatment strategies.cfDNA WES at relapse but not tumor or cfDNA WES at diagnosis, deep coverage target.

  Study EGAS00001002705

• UK10K NEURO UKSCZ

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. These samples have been collected from throughout the UK and Ireland. The samples fall into two main categories, approximately 500 have a full diagnostic work up. A proportion of these are cases with a positive family history of schizophrenia, either collected as sib-pairs or from multiplex kindred's. The second group consist mainly of >300 samples that have been systematically collected within South Wales and in addition to full diagnostic work up have undergone detailed cognitive testing. All samples have obtained a DSM IV diagnosis of schizophrenia or schizoaffective disorder.For further information on this cohort please contact Michael Owen (OwenMJ@cardiff.ac.uk).

  Study EGAS00001000123

• Breast cancer women lack normal lifelong immune response after full-term pregnancies

  Immunological tolerance during pregnancy is necessary for women’s bodies to accept the semi-allogenic fetus. Interestingly, “immune evasion”, which consists of some similar immunological changes, was recently proposed as a hallmark of cancer. Looking at these results, it seems paradoxical that increasing number of full-term pregnancies (FTP) reduces the risk of breast cancer in women. Our aim was to use a systems epidemiology approach to investigate this paradox by modelling breast cancer incidence as a function of parity in the Norwegian Women and Cancer (NOWAC) cohort, then testing the mathematical model using gene expression from blood in a subcohort of these women: the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis for immunological gene sets. A linear trend nicely fitted the dataset showing an 8% decrease in risk for each FTP, independent of stratification on other risk factors and lasting for decades after a woman’s last FTP. However, when we looked at gene expression we found that hundreds of genes showed linear trends in cancer-free controls, but this was not the case in /any/ of the samples from breast cancer cases. In the gene set enrichment analysis, samples consisted of human blood or cord blood and mouse bone marrow or spleen. We found more adaptive gene sets than expected in humans and more innate gene sets than expected in mice. None of the gene sets provided information about the long-term effects of immunological tolerance during pregnancy, but the lack of relevant reductionist experiments hampers our interpretation. We suggest that, after resolution at birth, the immunological tolerance induced by pregnancy augments immune response to cancer development.

  Study EGAS00001002616

• Proteom characterization in primary colorectal cancer and corresponding liver metastasis

  Colorectal adenocarcinomas (CRC) are one of the most commonly diagnosed tumors worldwide. Colorectal adenocarcinomas primarily metastasize into the liver and (less often) into the peritoneum. Patients suffering from CRC-liver metastasis (CRC-LM) typically present with a dismal overall survival compared to non-metastasized CRC patients. The metastasis process and metastasis promoting factors in patients with CRC are under intensive debate. However, CRC studies investigating the proteome biology are lacking. Formalin-fixed paraffin-embedded (FFPE) tissue specimens provide a valuable resource for comprehensive proteomic studies of a broad variety of clinical malignancies. The presented pilot study compares the proteome of primary CRC and patient-matched CRC-LM. The applied protocol allows a reproducible and straightforward identification and quantification of over 2,600 proteins within the dissected tumorous tissue. Subsequent unsupervised clustering reveals distinct proteome biologies of the primary CRC and the corresponding CRC-LM. Statistical analysis yields multiple differentially abundant proteins in either primary CRC or their corresponding liver metastases. A more detailed analysis of dysregulated biological processes suggests an active immune response in the liver metastases, including several proteins of the complement system. Proteins with structural roles, e.g. cytoskeleton organization or cell junction assembly appear to be less prominent in liver metastases as compared to primary CRC. Immunohistochemistry corroborates proteomic high expression levels of metabolic proteins in CRC-LM. We further assessed how the in vitro inhibition of two in CRC-LM enriched metabolic proteins affected cell proliferation and chemosensitivity. The presented proteomic investigation in a small clinical cohort promotes a more comprehensive understanding of the distinct proteome biology of primary CRC and their corresponding liver metastases.

  Study EGAS00001005641

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• Exome sequencing from cfDNA blood samples. 159 samples at 2x101bp Illumina reads in Fastq format.

  Differential presence of exons (DPE) by next generation sequencing (NGS) is a method of interpretation of whole exome sequencing. This method has been proposed to design a predictive and diagnostic algorithm with clinical value in plasma from patients bearing colorectal cancer (CRC). The aim of the present study was to determine a common exonic signature to discriminate between different clinical pictures, such as non-metastatic, metastatic and non-disease (healthy), using a sustainable and novel technology in liquid biopsy. Through DPE analysis, we determined the differences in DNA exon levels circulating in plasma between patients bearing CRC vs. healthy, patients bearing CRC metastasis vs. non-metastatic and patients bearing CRC metastasis vs. healthy comparisons. We identified a set of 510 exons (469 up and 41 down) whose differential presence in plasma allowed us to group and classify between the three cohorts. Random forest classification (machine learning) was performed and an estimated out-of-bag (OOB) error rate of 35.9% was obtained and the predictive model had an accuracy of 75% with a confidence interval (CI) of 56.6-88.5. In conclusion, the DPE analysis allowed us to discriminate between different patho-physiological status such as metastatic, non-metastatic and healthy donors. In addition, this analysis allowed us to obtain very significant values with respect to previous published results, since we increased the number of samples in our study. These results suggest that circulating DNA in patient’s plasma may be actively released by cells and may be involved in intercellular communication and, therefore, may play a pivotal role in malignant transformation (genometastasis).

  Study EGAS00001006656

• Transcriptomics-driven classification of ALAL

  Acute leukemia of ambiguous lineage (ALAL) is a rare, poor-prognosis subtype of acute leukemia that cannot be assigned to a single hematopoietic lineage. Although ALAL patients are typically treated with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL) regimens, optimal treatment choice is hindered by their lineage ambiguity. Therefore, we investigated the added value of transcriptomics for improving lineage assignment, currently based mainly on surface markers. First, we used an in-house pipeline to comprehensively detect genetic lesions in RNA-sequencing data (n=23) with a sensitivity >90%, as confirmed by targeted DNA sequencing. Second, we compared ALAL gene expression profiles (GEPs) with representative AML (n=145), B-ALL (n=223) and T-ALL (n=85) cases. In a principal component analysis, ALALs did not form a separate group, but clustered with AML, B-ALL or T-ALL. Accordingly, a machine learning classifier trained with GEPs of acute leukemias segregated 20/23 ALALs into myeloid-, B- or T-lymphoid leukemia. These 20 cases harbored genetic abnormalities consistent with the classifier-assigned leukemia. Furthermore, ALAL GEPs were deconvoluted with single-cell transcriptional profiles of normal hematopoietic cells using CIBERSORTx, revealing enrichment for signatures of lineages corresponding to the leukemic type predicted by our algorithm. The classifier was validated on an external ALAL cohort (n=24), assigning 75% of the patients to a lineage matching their immunophenotypic and methylation profiles. In conclusion, integrative analysis of RNA-sequencing data can accurately classify most ALAL cases. The pipeline and classifier developed in our study are valuable tools to improve ALAL diagnosis and guide therapeutic decisions.

  Study EGAS00001007967

• European BestAgeing Study on microRNA candidates for cardiovascular disease

  Background: Circulating miRNAs have emerged as promising biomarker candidates due to their stability and their role in regulating key pathological pathways in cardiovascular disease (CVD). Yet, large-scale, multicenter studies examining their diagnostic and prognostic potential are scarce. This study evaluates the potential of miRNA expression profiles to inform disease classification and risk stratification across major CVD phenotypes, including acute coronary syndrome (ACS), chronic coronary artery disease (CAD), dilated cardiomyopathy (DCM), and ischemic cardiomyopathy (ICM), in a large, multicenter European cohort. Methods: We assessed genome-wide miRNA expression profiles in a total of 1,209 cardiovascular patients and 848 controls in a uniform, standardized fashion, which renders this study one of the largest prospective miRNA studies. To focus on only the most biologically plausible miRNAs for clinical translation, we mined all original studies of miRNA candidates in CVD and performed differential miRNA expression and enrichment analysis. We then trained disease-specific binary classification models to evaluate the diagnostic potential of miRNA signatures. Finally, we evaluated prognosis and disease severity based on distinct miRNA levels. Results: 634 original abstracts were identified, detailing 166 ACS, 181 CAD, 56 DCM, and 182 ICM miRNAs. Without further optimization, the signatures of a priori miRNAs already yielded very good diagnostic performance with ROC AUC of 0.83 – 0.95. There was an improvement when considering additional miRNAs in a discovery setting. Interestingly, in ACS, CAD and DCM we observed a significantly worse prognosis in probands with higher scores in the miRNA signatures, indicating additional prognostic information. Conclusions: The European BestAgeing miRNA study reveals emerging associations of several miRNA signatures with cardiovascular disease discrimination and prognostication, providing a foundation for future external validation and potential clinical translation of this class of markers.

  Study EGAS00001008346

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• 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

• Whole exome sequencing of a cold agglutinin disease patient

  We performed whole exome sequencing of bone marrow monoclear cells derived from a cold agglutinin disease patient. Aim of our study is to elucidate the pathogenesis of hemolytic anemia.

  Study JGAS000612

• Whole exome sequencing of a cold agglutinin disease patient

  We performed whole exome sequencing of bone marrow monoclear cells derived from a cold agglutinin disease patient. Aim of our study is to elucidate the pathogenesis of hemolytic anemia.

  Study JGAS000583

• A mathematical model of cell-free DNA fragment size reveals cancer-specific fragmentomic patterns

  This study aim to test a mathematical model of cfDNA length distribution across multiple biodiy flulids. It try to investigate biological mechanisms of cfDNA fragmentation and release.

  Study EGAS50000001560

• A comprehensive genetic map of cytokine responses in Lyme borreliosis

  A study on the genetic determinants of immune response in patients diagnosed with Lyme borreliosis. Examining the link between genetic variants and cytokine response in more than 1,000 patients.

  Study EGAS50000000024

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Exome sequencing of a novel cervical cancer cell line

  In this work, we establish and characterized a low-passage cervix cancer cell line from a Brazilian patient with squamous cell carcinoma. The dataset contains three samples from the same patient (blood, tumor tissue and the primary cell line). The technology used was exome sequencing and the file type available is fastq files.

  Dataset EGAD00001004480

• Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma

  Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma (2 samples). One sequencing was done on GridION, the other one on a P2 Solo. In both cases the SQK LSK-109 Kit was used for preparation.

  Dataset EGAD00001009490

• Germline genome sequencing samples from the Hereditary Cancer Syndromes (ICCon) Cancer Flagship

  A prospective study of individuals with suspicion of a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or was not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing and a comprehensive cancer virtual gene panel analysis were undertaken.

  Dataset EGAD00001011260

• Single-Cell Mitochondrial Variant Profiling via TAMITO-seq

  This dataset focuses on mitochondrial variant detection using the TAMITO-seq protocol. A pre-designed mitochondrial panel (https://designer.missionbio.com/catalogpanels/Virtual-mtDNA) was spiked into the scTAMseq workflow targeting 200 CpGs and 167 genotyping loci. Data were generated from a peripheral blood sample of a healthy donor, donor X.2, multiplexed with data from another donor.

  Dataset EGAD00001015494

• A method for multiplexed full-length single-molecule sequencing of the human mitochondrial genome

  Here we describe a method to target, multiplex and sequence full-length, native single-molecule the human mitochondrial genome utilizing the RNA-guided DNA endonuclease Cas9.

  Study EGAS00001006203

• Epidemiological study comparing rates and risk factors for dementia in African Americans in Indianapolis and Yoruba living in Ibadan, Nigeria

  In 1991 collaboration between researchers at Indiana University School of Medicine and the University of Ibadan, Ibadan, Nigeria established the Indianapolis-Ibadan Dementia Project. It is a longitudinal, prospective population-based comparative epidemiological study of the prevalence and incidence rates and risk factors of Alzheimer's disease and other age associated dementias. The project compares samples of community-dwelling elderly (age > 70 years) African Americans living in Indianapolis to Yoruba living in Ibadan, Nigeria, employing the same research design, methods, and investigators. It initially reported significantly lower prevalence rates of disorders in the Yoruba compared to the African Americans. In subsequent waves of the study (1994-1995, 1997-1998) incidence rates, rates of newly diagnosed cases, were also found to be significantly lower in the Yoruba. In genetic studies, the frequency of the APOE 4 allele was about the same in the two groups. APOE 4 was a significant risk factor for Alzheimer's disease and dementia in the Americans, while no association was found for the Yoruba. The APOE 2 allele appears to be protective in the Americans, but not the Yoruba. A constellation of factors often associated with vascular risk including a history of hypertension, diabetes, and high cholesterol levels is less common in the Yoruba than in the American group. An interaction was observed between cholesterol, APOE genotype and Alzheimer's disease in both study groups. In 2001-2002 survivors of the original cohort were once again evaluated (N~800 in each site) and 2,000 additional individuals age 70 years and older were enrolled in each site. Blood samples were collected from approximately 1,500 study participants in each site for genetic studies and analysis of biochemical risk factors for vascular disease. Subsequent waves of field work were conducted in 2004, 2007, 2009, and 2011. This fieldwork followed the classic two-stage study design. The study design involves an in-home screening interview with the study participant, which includes a cognitive assessment, medical history and current medications, brief neurological examination, height and weight, blood pressure measurement and assessment of social involvement. There is also a screening interview with a close relative of the study participant to assess activities of daily living, personality change, and medical history of the study participant. On the basis of the screening interview a sample of study participants (N~500 in each site) is selected for a full clinical diagnostic dementia work up which includes a neurological test battery, extensive interview with a family member and examination by a clinician. Diagnoses are made in a consensus diagnosis conference using the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition (DSM-III R) and International Classification of Diseases 10th Revision (ICD-10) for dementia. The criteria of the National Institute for Neurological and Communicative Disease and Stroke-Alzheimer's Disease and Related Disorders Association were used to diagnose possible and probable Alzheimer's disease. The focus of the study is risk factors for dementia and Alzheimer's disease, but also of particular importance is the question of mild cognitive impairment. This refers to the condition of having some decline in cognition but the decline is not sufficient to meet the criteria for dementia. We have studied this over the course of this project. In follow up studies of individuals who have this diagnosis about one third of them are better at follow up, about a third are about the same, and about a third decline more to meet the criteria for dementia. This is a very important issue for researchers because the ultimate goal of the research is to figure out how to identify the individuals who will definitely progress to dementia. If there are clear identifiers, it would be possible to make interventions, while individuals still function well, and possibly prevent the development of dementia altogether or delay the onset significantly. This is crucial because at the moment individuals usually do not enter into the medical care system until the dementia symptoms are quite severe, and the pathological damage to the brain cannot be undone.

  Study phs000378

• Prevention and Early Treatment of Acute Lung Injury (PETAL) Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis (CLOVERS) (PETAL CLOVERS-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL CLOVERS include plasma, and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Available Data: The data available for request now include Long Term Outcome data.Objectives: To compare the effects of a restrictive fluid strategy (with early use of vasopressors) to a liberal fluid strategy in participants with sepsis-induced hypotension.Background: Intravenous fluid resuscitation is a common therapy used in the initial treatment of participants with septic shock and sepsis-induced hypotension. The goal of initial fluid therapy is to increase depleted or functionally reduced intravascular volume that occurs in sepsis due to a vasodilated vascular network. However, intravenous fluid resuscitation can create dilutional coagulopathy, fluid overload, and pathogenic edema in the lungs and other organs. Vasopressor agents are also commonly used to treat hypoperfusion by inducing constriction of arterioles and venules and increasing cardiac contractility. Vasopressor therapy also comes with risks that include vasoconstriction resulting in tissue ischemia, increased cardiac workload, and arrhythmias. Clinicians have used these strategies, typically in combination, to provide supportive care for participants with sepsis-induced hypoperfusion. However, at the time of the CLOVERS study, there was limited data to guide specific use of these therapies, including fluid volumes, in the early care of participants with sepsis-induced hypotension. The CLOVERS study hypothesized that a restrictive fluid strategy used during the first 24-hours of resuscitation for sepsis-induced hypotension would lead to lower mortality before discharge home by day 90 than a liberal fluid strategy.Participants: A total of 1,563 participants, from 60 medical centers, of the planned 2,230 participants were enrolled, with 782 assigned to the restrictive fluid group and 781 to the liberal fluid group. Enrollment in the trial was ended after the second interim analysis due to a lack of significant difference observed between the two 24-hour strategies.Design: This study was a multi-center, prospective, phase 3 randomized non-blinded interventional trial of fluid treatment strategies in the first 24 hours for participants with sepsis-induced hypotension. Participants were randomly assigned in a 1:1 ratio to either a restrictive fluid strategy (with early vasopressor use) or a liberal fluid strategy. In each group, the assigned protocol was followed for a period of 24 hours. The restrictive fluid protocol prioritized vasopressors as the primary treatment for sepsis-induced hypotension, with 'rescue fluids' being permitted for prespecified indications that suggested severe intravascular volume depletion. The liberal fluid protocol consisted of a recommended initial 2000-ml intravenous infusion of isotonic crystalloid, followed by fluid boluses administered on the basis of clinical triggers (e.g., tachycardia) with 'rescue vasopressors' permitted for prespecified indications. A protocol amendment implemented in October, 2019, allowed for limiting the initial infusion to 1,000 ml if the participant's blood pressure and heart rate had stabilized and the clinical assessment was that the participant was unlikely to benefit from additional intravenous fluid administration. The clinical team could override the protocol-specified care instructions at any time if it was judged to be in the best interest of the participant.The primary outcome was death from any cause before discharge home by day 90. Secondary outcomes included 28-day measures of the number of days free from ventilator use, days free from renal-replacement therapy, days free from vasopressor use, days out of the ICU, and days out of the hospital. Conclusions: Among participants with sepsis-induced hypotension, the restrictive fluid strategy that was used in this trial did not result in significantly lower (or higher) mortality, or other measures of recovery such as length of hospital stay, before discharge home by day 90 than the liberal fluid strategy.

  Study phs004080