3311 results for "*geneti*"

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• Role of Tobacco Smoke in Clear Cell Renal Cell Carcinoma

  Background. Clear cell renal cell carcinoma (ccRCC) is the most common histologically defined renal cancer. However, it is not a uniform disease and includes several genetic subtypes with different prognoses. ccRCC is also characterized by distinguished metabolic reprogramming. Tobacco smoking (TS) is an established risk factor for ccRCC with unknown effects on tumor pathobiology.Methods. We investigated the landscape of ccRCCs and paired normal kidney tissues (NKTs) using integrated transcriptomic, metabolomic and metallomic approaches in a cohort of never smokers (NS) and long-term current smokers (LTS) Caucasian males. Results. All three Omics domains consistently identified a distinct metabolic subtype of ccRCCs in LTS, characterized by activation of oxidative phosphorylation (OxPhos) coupled with reprogramming of the malate-aspartate shuttle and metabolism of aspartate, glutamate, glutamine and histidine. Cadmium, copper and inorganic arsenic accumulated in LTS tumors showing redistribution among intracellular pools, including relocation of copper into the cytochrome c oxidase complex. Gene expression signature based on the LTS metabolic subtype provided prognostic stratification of The Cancer Genome Atlas (TCGA) ccRCC tumors that was independent from genomic alterations.Conclusions. The work identified the TS related metabolic subtype of ccRCC with vulnerabilities that can be exploited for precision medicine approaches targeting metabolic pathways. The results provided rationale for the development of metabolic biomarkers with diagnostic and prognostic applications using evaluation of OxPhos status. The metallomic analysis revealed the role of disrupted metal homeostasis in ccRCC highlighting the importance of studying effects of metals from e-cigarettes and environmental exposures.

  Study phs002083

• Bone Microarchitecture

  Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.    

  Study phs002102

• Gabriella Miller Kids First Pediatric Research Program in Craniofacial Microsomia

  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 pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). 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. Craniofacial microsomia (CFM), also termed hemifacial microsomia or oculo-auricular-vertebral spectrum, is the third most common congenital craniofacial condition. CFM comprises a variable phenotype and the most common features include malformations of the ear (i.e. microtia) and lower jaw (i.e. mandibular hypoplasia) on one or both sides. Microtia in the absence of other anomalies is believed to represent the mildest form of CFM. The cause of CFM is unknown for most affected individuals. We have established a cohort through previous studies and collected DNA to identify the genetic contributions to CFM, which could facilitate diagnosis, tailored treatments and guide prevention strategies. Successful completion of this proposal will advance knowledge in the genetic architecture of susceptibility to CFM and will provide insight about the biological mechanisms underlying craniofacial development. The results from this study have the potential to further research on the etiology of other craniofacial conditions, and the pathogenesis of typical and atypical craniofacial development.

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• Genomics of Opioid Pharmacogenomics and Acute/Chronic Postsurgical Pain after Major Surgery in Children

  Pain management after surgery is not optimal, partly due to great interindividual variability in pain perception and coping. This can lead to persistent pain beyond the healing period and disability. Up to two-thirds of the inter-individual variability results from genetic variations in pain perception as well as response to the pain medicine. The investigators aim to identify genomic (genetic/epigenetic), psychological and drug profiles contributing to this variability. Opioids are the mainstay for treatment of postoperative pain in children. Experience dictates that opioids have narrow therapeutic indices and large inter-patient variability in response. This leads to serious side effects like respiratory depression in up to 50% of children undergoing invasive surgery, which can be fatal. It is evident that there are particular children who are more susceptible to suffering side effects and having inadequate pain relief from opioids.It is hypothesized that much of the genetic variability can be explained by gene function which is modulated by a) Single Nucleotide Polymorphisms (SNPs) in genes that encode proteins involved in pain perception, opioid transport/metabolism (pharmacokinetics), and opioid receptor signaling (pharmacodynamics); b) epigenetics which modify gene expression without structural changes to the DNA, and c) genes that influence psychological factors.The purpose of this research study is to identify factors and genes that may be associated with acute and chronic post-surgical pain, and to develop pharmacometric models for response to opioids, like morphine and hydromorphone. While children undergoing different surgeries will be recruited for acute outcomes, children undergoing spine fusion will be followed for 10-12 months for evaluation of psychological and genomic factors affecting chronic post-surgical pain, with a goal of identifying genetic and epigenetic risk models for prediction of acute and chronic post-surgical pain. Although opioids are used every day, some children have bad reactions from their use, like breathing problems, sedation, etc. The investigators want to study factors that may be associated with pain sensitivity, opioid requirements after surgery, their metabolism, efficacy and their side-effects. The investigators expect that the information obtained in this research study will help to develop effective, safer, and tailored treatment options in the future.

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• Epigenetic Mechanisms of Inflammation and Fatigue in Head and Neck Cancer

  This was a longitudinal observational study to examine the association between fatigue and DNA methylation as well as gene expression among patients with head and neck cancer. Demographic and clinical variables were collected before chemoradiotherapy and/or at follow-up visits as appropriate. Fatigue was assessed and biosamples (for DNA methylation and gene expression) were collected before, immediately after, and at six- and twelve-months post-chemoradiotherapy.

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• Unraveling the Genetic Architecture of Diabetic Retinopathy in South India

  This study aims to understand the genetic architecture of diabetic retinopathy in the South Indian population by examining participants with South Indian ancestry and type 2 diabetes (T2D) from two sources: the Sankara Nethralaya-Diabetic Retinopathy Epidemiology and Molecular Genetic Study (SN-DREAMS) and prospective recruitment at Sankara Nethralaya affiliates. A total of 2393 patients were recruited and included in the genetic analysis, with 1588 patients having no diabetic retinopathy (DR) serving as the controls and 805 patients with any level of DR serving as the cases. Enrolled individuals had genome-wide genotyping from DNA extracted from blood samples. In addition, whole genome sequencing (WGS) was performed on 31 members from 2 families. Clinical data, such as age, duration of diabetes, and hemoglobin A1C (HbA1c) were recorded for study participants. Diabetic retinopathy was assessed by clinical exam and/or fundus photography. The grading of diabetic retinopathy followed the International Clinical Diabetic Retinopathy Severity Scale.

  Study phs002116

• Integrated Clinical and Transcriptomic Profiling to Characterize Disease Phenotype

  Personalized medicine requires that we first address the challenge of genetic heterogeneity, prominent in rare cancers to common disease. While current clinical DNA sequence data successfully identify novel genetic variants, the genomic data alone are insufficient biomarkers of clinical phenotype. There is an unmet need for systematic integration of specific functional genomic data with patient genetic data, in order to bridge the knowledge gap between genetic variation and clinical phenotype. This specific study is focused on functional genomic data from platelets as disease-specific cells that are also ideal for proof-of-principle transcriptomic investigation (being anucleate), and highly-relevant to multiple disease processes.

  Study phs002121

• Environmental Arsenic and Diabetes Mellitus (Chihuahua Cohort)

  The Chihuahua Cohort was established as part of a larger NIEHS-funded project that used laboratory models (tissue culture and mice) and human subjects to examine the association between exposure to arsenic and diabetes, including identification of mechanisms underlying this association. All procedures involving human subjects were approved by institutional review boards at the University of North Carolina at Chapel Hill and Cinvestav-IPN (Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional, Mexico City, Mexico). All participants provided signed informed consent. A total of 1,160 adults (≥ 18 years old) with a minimum 5-year uninterrupted residency in the Chihuahua study area were recruited between 2008 and 2012. Samples of drinking water were obtained from the participants' households. Data on residency, occupation, drinking-water sources and use, smoking, alcohol consumption, and medical history were recorded by a study questionnaire. Spot urine and fasting venous blood were collected during medical examination that included an oral glucose tolerance test (OGTT) with blood drawn 2 hr after a 75-g glucose dose. Plasma from both fasting and 2-hr blood samples was collected. Body mass index (BMI) of each participant was calculated from body weight and height. BMI cutoffs of ≥ 25.0, ≥ 30, and < 18.5 kg/m2 were used to define overweight, obese, and underweight individuals, respectively. Participants' waist circumference was also measured. Blood pressure was assessed using a manual sphygmomanometer. Three measurements were taken at intervals of at least 1 min, with a 5-min rest before obtaining the first reading; the mean of the last two measurements was used. The concentrations of arsenic in drinking water and arsenic species in urine were measured by hydride generation-atomic absorption spectrometry. The limit of detection for As in water as well as for As species in urine was 0.01 µg As/L. Creatinine concentration in urine was determined using an established colorimetric assay. DNA was isolated from blood for genotyping analysis.The following measures were taken: glucose concentration in fasting blood (FBG) and in blood collected 2 hours into OGTT (2HBG); concentrations of triglycerides, HDL and total cholesterol (TC) in fasting plasma; and LDL was calculated using the Friedewald equation. Diabetes was classified by FPG ≥ 126 mg/dL, 2HPG ≥ 200 mg/dL, or self-reported diabetes diagnosis or medication use (WHO/International Diabetes Federation 2006). Prediabetes was defined as the absence of diabetes with FPG ≥ 110 mg/ dL or 2HPG ≥ 140 mg/dL. Elevated fasting levels of each lipid were defined as plasma TG ≥ 150 mg/dL, TC ≥ 200 mg/dL, and LDL ≥ 130 mg/dL. Fasting HDL < 40 mg/dL in men and < 50 mg/dL in women were designated as low. Hypertension was defined by systolic blood pressure (SBP) > 140 mm Hg, diastolic blood pressure (DBP) > 90 mmHg, or self-reported use of anti-hypertensive medication. Genotyping analysis, which will be available in version 2 of this study, was carried out in a subset of ~600 subjects with focus on enzymes involved in the metabolism of arsenic, including AS3MT, GSTs.All data collected during the medical exams or generated by the above-described chemical and biochemical analysis of water, urine and blood/plasma, as well as results of the genotyping analysis are included in dbGaP. Data generated by metabolomics and epigenetic analyses in small subsets of the Chihuahua cohort are not included, but are available in published articles.

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• Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss

  The Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss, which constitute the Epidemiology of the Weiss Cohort Projects, consist of a series of inter-connected projects, building upon a set of cohort projects of various groups, mainly drug users from medication-assisted treatment programs, that Dr. Stanley H. Weiss first developed in the 1980’s plus several newer initiatives, each with an array of collaborators. Beginning in the 1980’s, Dr. Stanley H. Weiss started several long-term studies of persons who inject drugs (PWID) across the United States, ultimately enrolling over 10,000 participants through the early 1990’s with an average age then in their 30’s. About a quarter were enrolled from sites in New Jersey (NJ). These studies included the first testing of PWID for the human immunodeficiency virus (HIV) and the human T-cell lymphotropic viruses (HTLV I and HTLV II). Cumulative past support (initiation thru ~ 1999) for these cohort studies included ~ $20 million from intramural resources from the National Cancer Institute (NCI) and the National Institute on Drug Abuse (NIDA), plus multiple grants and in-kind support from the New Jersey Department of Health (NJDOH) totaling ~ $1 million. The Weiss Cohort Projects include the first large AIDS-era cohorts to include women at high risk for HIV. A high percentage of subjects in these studies are black or Latino. Thus, this is an ethnically diverse US cohort, with a high proportion of women included. These subjects are at high risk of parenteral and sexual infection from both drug use and sexual practices. Samples from other studies conducted by Dr. Weiss, in which detailed interviews were conducted, are included as controls (persons documented by us not to have a history of opioid drug use). As one of our groups of subjects have many persons of Haitian ancestry, we specifically included some Haitians who had never used opioids as controls. Our documentation includes such ancestry. These cohorts demonstrated high rates of HIV and HTLV-II infection in PWIDs, including one study initiated in 1981 with confirmation in the later cohorts. In the first two decades of these studies, among numerous publications was the first study showing a very high rate of hepatitis C infection among PWIDs. An example of how the studies’ long-time horizon proved essential was that it first became possible to test whether a person had ever been infected with hepatitis C virus (HCV), as well as how much HCV was in each person’s blood, many years after the specimens were collected. This allowed HCV amounts in blood to be compared for subjects who had died of liver disease early in the study versus those who survived. Then a sequence of published papers culminated in demonstrating, using a nested case-control design, that a high baseline HCV titer was predictive of early progression to death from end-stage liver failure. Outcomes related to HCV (end stage liver disease and hepatocellular carcinoma) remain under study. In the original cohort studies, the mean age at enrollment was ~ 33 years old, so that those still alive in 2022 are mainly now ~ 60 - 75 years old. Many participants have already died. The tincture of time has led to subjects reaching ages when many more are dying from a wide array of outcomes, including from many chronic diseases (including cancer) as well as from infectious agents (especially HIV, HCV) or drug overdose. Renewed collaboration with local drug treatment programs has led to new field-based studies, including examination of some currently evolving problems among drug users. Dr. Weiss joined the National Institute on Drug Abuse (NIDA) Genetics Consortium (NGC) in 2017, and through the NIDA project officer has had access to NGC contract resources (see below). NIH Certificate of Confidentiality, CC-DA-16-214 (attached) protects these studies. Past arrangements related to data on our subjects leads to restrictions on the use of data emanating from our study, such as potential commercialization and restrictions on whom may access and use these data. NIDA Genetics Consortium (NGC) resources further support these endeavors and will be used as part of the NGC analyses studying the genetics of substance use. Study participants signed informed consent for the information collected from them to be used with no time limit and for biologic specimens collected from them to be used without restriction in future research. Serum samples were collected from participants, and from many also plasma, white blood cells and/or urine samples. About 100,000 vials were stored. All specimens have been continuously preserved at sufficiently cold temperatures to prevent deterioration, and many subjects separated white blood cells were processed and frozen in such a way as to maintain viability. Detailed data from the participants has been accumulated over time, and in general, linkage has been retained in each sub-study in accordance with the consent forms and protocols. For some participants, specimens were collected at multiple times (that is, sequential specimens). Multiple specimens from a single person exist in this database, and efforts at de-duplication remain ongoing. Dr. Weiss should be contacted if an investigator requires unique individuals since: • Multiple phases of enrollment occurred, and as our prospective follow-up continues; Dr. Weiss may identify new instances of multiple enrollment. • Some persons are related to each other. • In general, in this dataset for dbGaP, only a single specimen/record form a given person is included. Advances in laboratory testing techniques now permit innovative new uses for our linked research biospecimen repository. The ongoing focus of an interdisciplinary research program based on these cohorts relates subjects’ diseases, behaviors, medical history, and outcomes with biological and exposure markers. Participants’ use of various substances was ascertained on study enrollments, many serially over time. Quantitative frequency of use data, also sometimes sequential over time, were ascertained. Active ascertainment of outcomes is being conducted, including matching to mortality and cancer databases. Investigators interested in collaborations on specific outcomes (which is not part of this dbGaP dataset) or in the use of our stored specimens are encouraged to contact the principal investigator, Dr. Weiss. The processing of the genomic data was done in conjunction with NIDA, and in accordance with some longstanding data cleaning steps used by NIDA in the NIDA Genetics Consortium (NGC), a group to which we shall be contributing these data for collaborative analyses. Since there is the potential for these steps to introduce certain types of potential biases, we summarize these here. Under contract from NIDA, cryopreserved sera or plasma (-80 C) or cells (in liquid nitrogen) were used, with most stored having been stored for 30 to 40 years in our biorepository. In the case of serum or plasma, in which only (largely) cell-free DNA fragments were available, DNA was extracted and restored prior to amplification. Industry standard DNA amplification techniques were done on all samples prior to genotyping in accord with established protocols of the NIDA Genetics Consortium. Our genotype data were run and processed on the Illumina Infinium OmniExpress_v_1.3 array. This array has 714,238 SNPs, and was designed many years ago. There were 628 SNPs on the array that do not correspond to any chromosome position, and these were removed. Genotype data were submitted by NIDA’s contracted genotyping laboratory in six batches over time to NIDA’s contracted dbGaP data management group, which conducted quality control (QC) analyses. QC analysis included an assessment of batch effects on for five of the six batches. (One of the batches, with only 12 samples, was too small for QC analysis of batch effects.) Standard NIDA Genetic Consortium cleaning was performed. Samples with a call rate <.85 were removed. Only one sample per person was retained. When more than one specimen was genotyped from one subject, only the sample with the higher call rate was retained (provided, of course, that that call rate was ≥ 0.85). We have retained some people we know are related, including some found to have been related through genotyping; the pedigree file describes those relationships. In summary, key cleaning steps include: 1. Using PLINK to check gender discrepancy. 2. Using PREST-PLUS and KING (Kinship-based Inference for GWAS) to check relatedness. 3. Using PEDCHECK and PLINK to check/zero-out Mendelian error. 4. Using PLINK to perform sample QC, SNP QC, along with KING to perform chromosome X and chromosome Y QC. 5. SNP-QC: Batch-effect: 5 Batches were compared (one batch, with few samples, was not). These five batches were compared to each other in all ten possible pairs, one batch vs. another batch, examining SNP allele frequency discrepancies by population (from GRAF), Fisher Exact Allelic test, with the criterion of p<5e-8 for removal. 6. SNP-QC: discordant SNPs in QC duplicates. Compared 25 QC duplicated samples with call rate > 0.95, removed SNPs with 3+ discordance. 7. There were 1,056 SNPs that were monomorphic; these have been retained so they can be included in analyses in which our dbGaP data are combined with those from other cohorts (in the latter of which those SNPs may not be monomorphic). The final cleaned dataset submitted has 8,898 samples and 606,793 SNPs.

  Study phs002140

• Molecular Characterization of Hemimegalencephaly

  Somatic mutations, in which a fraction of the cells in the body have a deleterious mutation, are well recognized in cancer but only recently appreciated in neurological disease. Given a somatic mutation in a population of progenitor cells, all daughter cells inherit the mutation and are able to express the resultant phenotype as a function of the differentiation program. We recently identified the first de novo somatic mutations in the developing brain in the condition hemimegalencephaly (HME), a catastrophic focal epilepsy condition associated with a malformation of cerebral cortical development (MCD). HME is one of the most severe MCD syndromes, characterized by massive hamartomatous overgrowth of either of the two cerebral hemispheres. Cerebral hemispherectomy is a frequent treatment for refractory epilepsy, allowing the sampling of diseased tissue. By comparing DNA from a diseased brain with DNA from blood/saliva, we identified de novo somatic mutations in PIK3CA, AKT3 or MTOR, part of the mTOR pathway. Mutations were present in 8-40% of sequenced alleles in various brain regions sampled during surgery and in some codons known to activate proteins.• Population informationPatient samples were collected from multiple centers. The population is Caucasian and Hispanic• Molecular technologies employedWhole-exome sequencing• Principal findings of the studyWe were the first to describe mTOR-related and non-mTOR mutations causing hemimegalencephaly, and we described two-hit mutational models to explain the genetic pathogenesis of hemimegalencephaly

  Study phs002156