12401 results for ""statistically+reactive"+taxa+in+microbial+community"

in 23.46 milliseconds.

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• Gabriella Miller Kids First Pediatric Research Program: An Integrated Clinical and Genomic Analysis of Treatment Failure in Pediatric Osteosarcoma

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in childhood cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Although the survival of children with relapsed osteosarcoma is very poor, little is known about the etiology of treatment failure in this disease. The purpose of this project is to perform whole genome sequencing on serial samples from patients with osteosarcoma obtained before treatment, after treatment, and at relapse/metastasis in order to identify the mutations and pathways that are drivers of drug resistance. If successful, our results may help identify patients at high risk for treatment failure and may yield new treatments for children who cannot currently be cured.

  Study phs001714

• GWAS for Genetic Determinants of Bone Fragility in European-American Premenopausal Women

  Osteoporotic fractures are largely due to an increased propensity to fall with aging and a reduction in bone strength. Although skeletal architecture contributes to fracture risk, bone mineral density (BMD) is the most important determinant of bone strength and fracture risk. Between 60 and 80% of the variance of BMD of adult Caucasian women is due to heritable factors. Final BMD is a function of peak bone mass attained during young adulthood and the subsequent rate of bone loss, which occurs as a result of both post-menopausal estrogen loss and aging. The evidence for a genetic contribution to rate of loss in BMD is substantially weaker than that for peak BMD. Therefore, we have focused our sample collection on the recruitment of premenopausal women, in whom we have sought to identify the genes influencing peak BMD at the spine and hip, the two major skeletal sites of osteoporotic fracture. The primary goal of this study is to identify genes that affect peak BMD in premenopausal women. Identification of these genes may: 1) lead to molecular tests that predict risk of osteoporosis and allow institution of early preventive measures; 2) provide insight into basic bone cell biology and other factors that affect peak BMD; and 3) provide molecular targets for therapeutic agents to increase BMD.

  Study phs000138

• Molecular Determinants of Tumor Behavior in Early Lung Adenocarcinoma

  Lung adenocarcinoma is the leading cause of cancer death worldwide and a heterogeneous disease with poor survival in the advanced stage. Given that the frequency of early diagnosis is increasing, the investigation of the molecular determinants of disease progression is paramount. Prediction of whether the tumor is indolent or aggressive has been the subject of recent investigations. Yet, the molecular underpinnings explaining the difference in tumor behavior remains largely unknown and is directly relevant to the efficacy and cost-effectiveness of lung cancer screening, including the risks of over-diagnosis and overtreatment. To gain insights into the molecular pathogenesis and the underlying molecular determinants of clinical behavior of early adenocarcinoma, we investigated genetic alterations in 102 surgically resected early adenocarcinomas. We hypothesized that the behavior of early adenocarcinoma can be predicted based on genomic underpinnings. To identify the type of genomic alterations associated with resected indolent and aggressive early lung ADC, the DNA samples from 21 adenocarcinoma in situ (AIS), 27 minimally invasive adenocarcinoma (MIA) and 54 fully invasive adenocarcinoma were collected and subjected to a deep next generation sequencing, targeting a custom 347 cancer gene panel. Our study provides new insights into cancer genomic evolution, helps to elucidate the interplay of somatic mutation and the adaptation of clones, and brings new insights into the key distinction between indolent and aggressive tumor behavior.

  Study phs001811

• PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

  Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

  Study phs000963

• Identification of Cancer Predisposition Genes in Breast Cancer Families

  Breast cancer has a significant genetic component. The strongest epidemiologic risk factor is family history of the disease. Familial studies have identified a number of genes contributing to increased risk. Of these, the highly penetrant BRCA1 and BRCA2 genes account for the majority of families in whom disease-causal mutations have been identified. However, mutations in other genes have been associated with predisposition to breast or breast and ovarian cancer including (CHEK2, ATM, PALB2, RAD51C, RAD51D). Together these genes account for less than 20% of excess familial breast cancer risk and do not explain ~50% of high-risk families referred for genetic testing. This significant gap in our understanding of the genetic basis of breast cancer poses a significant barrier to our ability to identify women at increased risk, who would benefit greatly from appropriate clinical management. To identify additional breast cancer predisposition genes whole exome sequencing of familial high-risk breast cancer patients was undertaken. DNA samples from 50 pairs of breast cancer patients from high-risk breast cancer families with no pathogenic mutations in the BRCA1 or BRCA2 breast cancer predisposition genes were subjected to whole exome sequencing. The goal was to select candidate predisposition genes for further validation studies based on sharing of putative protein inactivating mutations among both members of each family and/or the frequency of inactivating mutations among the 50 families.

  Study phs000480

• MAESTRO-Pool Enables Highly Parallel and Specific Mutation-Enrichment Sequencing for Minimal Residual Disease Detection in Cohort Studies

  MAESTRO-Pool builds upon the technology MAESTRO (Minor Allele Enriched Sequencing Through Recognition Oligonucleotides) by pooling tumor-specific MAESTRO probes from multiple patients and applying these to all samples from all patients. In this study, MAESTRO-Pool was applied to a cohort of 9 melanoma patients where 98 plasma samples were screened for 22,333 mutations. Additionally, a new dynamic minimal residual disease (MRD) caller was used to estimate the likelihood of MRD detection based on the number mutations and cell-free DNA molecules interrogated which allowed each bespoke MRD test to be properly calibrated against false detection. These developments led to sensitive detection in patient-matched samples down to 0.78 parts per million (ppm) while limiting false detection in negative controls to 1/784 (tumor fraction=2.7 ppm). MAESTRO-Pool and the dynamic MRD caller enable a unique blend of sensitivity, specificity, and efficiency, which will improve the ability to detect MRD.The data contained in this repository consists of:Tumor and normal whole genome sequencing data used to call patient-specific tumor mutations and design the MRD Tracker and MAESTRO-Pool fingerprintsMAESTRO-Pool data (enriched duplex sequencing via hybrid capture) of tumor gDNA, normal gDNA and cfDNA MRD Tracker data (duplex sequencing via hybrid capture) of tumor gDNA, normal gDNA and cfDNA

  Study phs003447

• NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study

  The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 participants and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Also available are aptamer proteomic profiling, RNAseq and 850K array DNA methylation data that predominantly overlap with participants with WGS data. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007.

  Study phs000974

• Rituximab-treated lymphoma patients show correlated deficiency in serological and T cell Spike-specific response after SARS-CoV-2 vaccination: insights from the CORSA Study.

  This study is part of the CORSA trial (NCT04345315), a prospective multicentric research project conducted by the Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori” to investigate the immunologic response to mRNA SARS-CoV-2 vaccines in patients with hematologic malignancies (HM) and healthy individuals as controls (HC). The data in this repository refer to two subcohorts: 7 healthy controls and 10 lymphoma patients, randomly selected. Whole blood samples were collected to characterize T cell receptor (TCR) repertoire specificity against SARS-CoV-2 proteins before and after two BNT162b2 vaccination cycles, at baseline (before vaccination), 50 days after the first dose (V1), and 6 months after the first dose (V3). All participants were vaccinated under the Italian national campaign and provided informed consent following the Declaration of Helsinki. We investigated SARS-CoV-2-specific T cell responses through TCR repertoire profiling and examined correlations between serological and cellular responses in both patient and control groups. Using Next-Generation Sequencing (NGS) to characterize the CDR3 sequences of TCR β-chains from peripheral blood, we assessed clonal expansion (depth) and diversification (breadth) of SARS-CoV-2-specific T cell clonotypes over time, aiming to understand how cancer and its treatment influence vaccine-induced immunity in immunocompromised individuals.

  Study EGAS50000001205

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes using low pass whole genome sequencing and high density SNP genotyping in 2,657 individuals.

  The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome, and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in EGA will include all the Swedish, Finnish, UK, and German samples.

  Study EGAS00001001459