3335 results for "*geneti*"

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• Clinical Resistance to Crenolanib in Acute Myeloid Leukemia Due to Diverse Molecular Mechanisms

  FLT3 mutations are commonly detected in Acute Myeloid Leukemia (AML) patients and are associated with poor prognosis. Crenolanib, a potent type I pan-FLT3 (GeneID:2322) inhibitor, is effective against both internal tandem duplications (ITD) and resistance-conferring tyrosine kinase domain (TKD) mutations. While crenolanib monotherapy has demonstrated significant clinical benefit in heavily pretreated relapsed/refractory AML patients, responses are transient and relapse eventually occurs. To investigate the mechanisms of crenolanib resistance, we performed whole exome sequencing of AML patient samples before and after crenolanib treatment (122 samples from 59 patients). Unlike other FLT3 inhibitors, crenolanib did not induce FLT3 activation loop mutations, and mutations of the FLT3 "gatekeeper" residue were infrequent. Instead, mutations of NRAS (GeneID:4893) and IDH2 (GeneID:3418) arose, mostly as FLT3-independent subclones, while TET2 (GeneID:54790) and IDH1 (GeneID:3417) predominantly co-occurred with the FLT3-mutant clone and were enriched in crenolanib poor-responders. The remaining patients exhibited post-crenolanib expansion of mutations associated with epigenetic regulators, transcription factors, and cohesion factors, suggesting diverse non-FLT3 genetic/epigenetic mechanisms of crenolanib resistance. Drug combinations in experimental models restored crenolanib sensitivity.

  Study phs001628

• The Immunogenetics of Measles Immunity - Measles (MMR) vaccination (NIAID/NIH)

  To examine the role of gene polymorphisms (including functional studies of SNPs) on variations in vaccine-induced immune responses, in approximately 3,000 healthy school-age children, adolescents and young adults/adults, who were vaccinated with measles-containing vaccine (MMR). To achieve greatest power to detect SNPs associated with measles-specific immune response phenotypes, we pooled our data across three genotyping platforms and three cohorts (US cohort, San Diego cohort and Rochester cohort).

  Study phs001630

• Genetics of Mood Disorders: Aging and Emotion Regulation Brain Circuitry in Bipolar

  This single-site study is designed to investigate age-related changes in structure and function of a ventral prefrontal cortex (VPFC) neural system, that subserves emotion processing and regulation, during mid to later adulthood in individuals with bipolar disorder (BD), compared to healthy controls (HC). It is a 5-year study of age-related changes in mood, emotion regulation and related symptoms and behaviors using multimodality imaging measures [structural magnetic resonance imaging (MRI) of gray matter, diffusion tensor imaging (DTI) of white matter, and functional MRI measures of functional connectivity and of brain responses during implicit and explicit emotion regulation] comparing BD and HC groups ages 40-79 years, 50% female; a subgroup will be reassessed and rescanned after 2 years to study brain and associated behavioral changes over time. We will explore relationships between brain aging with risk factors implicated in progression. This will include genes, as well as adverse outcomes of progression such as suicide ideation and behavior. As there has been little study of effects of aging of the VPFC emotional circuitry in healthy individuals, findings could provide new insights into brain circuitry and emotional regulation in older adults. In addition to the importance of contributing to understanding BD, as BD is unique in having both elevated and depressive episodes, its study can provide a model for understanding progressive emotion dysregulation to both intervention and prevention that can be better targeted specifically for older individuals with BD. A de-identified blood sample will be sent to the Repository and Genomics Resource.

  Study phs001631

• Prospective Analysis of Genotypes in Adults Undergoing Therapy for Lung Cancer (Paclitaxel Cohort)

  Lung cancer is frequently treated with paclitaxel in combination with several other agents; however, paclitaxel treatment is often ineffective or limited by treatment-related toxicities. Heritable variants in genes associated with absorption, distribution, metabolism, and elimination may predict paclitaxel clinical outcome and toxicity. We designed a prospective multi-institutional study that recruited 546 patients receiving therapy with a 5-year follow up. All patients were genotyped using the Drug Metabolizing Enzymes and Transporters (DMET) platform, which ascertains 1931 genotypes in 235 genes. Genotypes were compared to the progression-free survival of paclitaxel therapy and clinically-significant paclitaxel toxicities. Seven genetic variants were associated with paclitaxel PFS (in ABCB11, ABCC3, ABCG1, CYP8B1, NR3C1, FMO6P, and GSTM3), whereas four genetic variants (in VKORC1, SLC22A14, GSTA2, and DCK) were associated with paclitaxel toxicities. The present SNPs have limited clinical utility but suggest that certain genes are related to important paclitaxel pathways in lung cancer.

  Study phs001660

• Center for Craniofacial and Dental Genetics: Exome Sequencing of Orofacial Cleft Families

  Orofacial Clefts (OFCs) are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans. Affect about 1 in 800 newborns, OFCs are also one of the most common structural birth defects worldwide. OFCs can impose a substantial personal cost resulting from the associated emotional and financial burden. On average a child undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Individuals born with an OFC have higher infant mortality (especially in developing countries with limited access to care), higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genetic studies have focused on the contribution of common genetic variants through genome-wide linkage and association studies. These studies have revealed a significant etiologic heterogeneity. One promising approach to dissect the etiology of OFCs into focus on subclinical phenotypic features present in the non-cleft family members of affected individuals. These subclinical features are subtle phenotypic features that may represent mild manifestations of the same risk genes; thus, their inclusion in family-based studies may clarify the inheritance patterns in OFC families. In this project, we conducted whole exome sequencing in multiplex families with both overt OFCs and subclinical phenotypes to identify high-impact genes causing OFCs.

  Study phs001675

• African American Multiple Myeloma GWAS

  The case set is from a case-control study designed to identify common genetic risk factors for multiple myeloma in African Americans, the population with the highest risk for this cancer. We conducted two GWAS and combined each of these with convenience controls consisting of unaffected African American participants in cohorts with existing GWAS data. We then conducted a meta-analysis of the two sets. Cases were persons of African ancestry with smoldering or active multiple myeloma identified at participating oncology clinics or through SEER registries, as part of the African American Multiple Myeloma Study (AAMMS) diagnosed from Jan 1, 1988 through July 31, 2016. The majority of the samples were collected from incident and prevalent cases diagnosed since Jan 1, 2008 (80.9%), with a minority obtained from biobanks from cases diagnosed prior to 2008 (19.1%). Additional samples were obtained from the Multiethnic Cohort (USC and University of Hawaii) (n=40), the University of California at San Francisco Multiple Myeloma Study (n=27), and from the Multiple Myeloma Research Consortium for secondary analysis (samples originally provided to MMRC by 8 additional sites (n=84)). We have identified the phenotype (smoldering myeloma, plasma cell multiple myeloma, or myeloma not otherwise specified (myeloma NOS) when myeloma phenotype was not known), sex and age at diagnosis in this data set. The initial GWAS set consisted of 1308 (1,305 passed QC) cases with DNA samples, with a GWAS performed on the Illumina Human Core. Controls consisted of 7,078 unaffected African American subjects who were participants in the African American Prostate and Breast Consortium, with existing GWAS data from the Illumina1M Duo BeadChip. The second GWAS set consisted of 529 African American multiple myeloma patients with samples (406 from University of Arkansas, results not contained in this dataset because NCI funds were not used for the collection and genotyping) with GWAS data resulting from the Illumina Mega-BeadChip v1.1. Controls were 2,390 unaffected African American participants in the Multiethnic Cohort with existing GWAS data from the same array. After QC and removal of duplicates within sets, sex mismatches, and removal of plasmacytoma cases (ICD-0 code 9731), this deposited data set contains the typed GWAS data for the Illumina Human Core (set 1) (n=1298), and for the MegaBead Chip v1.1 (set 2) (n=123), with the University of Arkansas samples removed, for a total of 1,421 case genotypes. Note that 13 samples that overlap set 1 and set 2 were included.

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• Implementation, Adoption, and Utility of Family History in Diverse Care Settings

  The purpose of this study is to address the key question of whether and how family health history (FHH) is adopted as a tool to more efficiently manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as well as thrombophilia and coronary heart disease (CHD) and to provide evidence supporting clinical utility -- improved health behaviors in patients and physician screening recommendations. Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, University of North Texas. Duke will serve as a coordinating center for this project (Pro00043372) as well as a site. Healthcare Effectiveness Data and Information Set (HEDIS) measures as intermediate clinical effectiveness measures for Coronary Heart Disease (CHD) and selected cancers as well as survey/formative data and electronic medical record (EMR) data will be used as outcomes measures. The research model is purposely designed to mimic clinical delivery as an important step toward widespread implementation and sustainability. In addition, a cost-effectiveness analysis comparing usual care to the FHH guided preventive health model will be used. The completion of this project will result in an optimal strategy for integration of FHH data collection and clinical decision support (CDS) tools into an EMR and demonstrate the utility of the FHH intervention among diverse primary care patients, their settings, their providers, and the health systems that deliver their care. Specific Aim 1: To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) platform and return CDS results to providers and patients (and to EMRs where relevant). To explore the integration of genetic risk and FHH data at selected sites. Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system. Specific Aim 4: To take a leadership role in the dissemination of guidelines for a FHH intervention across in diverse practice settings. AAA Hypertension Lupus Multiple sclerosis Obesity Osteoporosis Thyroid disease Rheumatoid arthritis Blood clotting (6): Blood Clot (high risk features) Factor V PT mutation AT III deficiency Protein S deficiency Protein C deficiency Brain Disorders (5): Dementia Hemorrhagic stroke Ischemic stroke Macrocephaly Seizure Cancer/Adenomas (32): Bone cancer Brain cancer Breast cancer Colon cancer Adrenal cortex tumor Neuroendocrine tumor Paraganglioma Pheochromoctyoma Pituitary adenoma Medullary thyroid cancer Non-medullary (follicular or papillary) thyroid cancer Don't know type of thyroid cancer Thyroid nodule Other type of endocrine cancer Esophageal cancer Kidney cancer Leukemia Lipoma Liver cancer Muscle cancer Ovarian cancer Pancreatic cancer Prostate cancer Rectal cancer Retinoblastoma Melanoma Non-melanoma skin cancer Do not know type of skin cancer Small bowel cancer Stomach cancer Uterine cancer Other type of cancer Cardiovascular/heart/artery disease (5): Atrial fibrillation Carotid stenosis Heart attack/coronary artery disease Peripheral arterial disease Other heart disease Diabetes (3): Gestational diabetes Diabetes type I Diabetes type 2 Digestive Disorders (5): Colon polyp Crohn's disease Irritable bowel syndrome Ulcerative colitis Other digestive disorder Eye Disorder (3): Blindness Glaucoma Macular degeneration Hereditary Cancer Syndromes (22): Birt-Hogg-Dube syndrome Cowden syndrome Familial adenomatous polyposis Hereditary breast and ovarian cancer syndrome Hereditary diffuse gastric cancer Hereditary leiomyomatosis and renal cell carcinoma syndrome Hereditary melenoma Hereditary papillary renal cancer syndrome Hereditary paraganglioma-pheochromocytoma syndrome Hereditary retinoblastoma Juvenile polyposis Li-Fraumeni syndrome Lynch syndrome Mutyh-associated polyposis Malignant hyperthermia susceptibility Multiple endocrine neoplasia type 1 Multiple endocrine neoplasia type 2 Nevoid basal cell carcinoma syndrome Peutz-Jeghers syndrome Tuberous Sclerosis complex Von-Hippel Lindau syndrome Other hereditary cancer Hereditary Cardiovascular syndromes (10): Long qt Brugada Catecholaminergic polymorphic ventricular tachycardia Hypertrophic cardiomyopathy Dilated cardiomyopathy Left ventricular non-compaction syndrome Arrhythmogenic right ventricular dysplasia Ehlers-Danlos syndrome Marfan syndrome Other hereditary cardiovascular syndrome High cholesterol (2): Hyperlipidemia Familial hypercholesterolemia Kidney Disease (6): Cystic kidney disease Diabetic kidney disease Kidney nephrosis Nephritis Nephrotic syndrome Other kidney disease Liver Disease (6): Alpha 1 antitrypsinase deficiency Auto-immune hepatitis Hereditary hemochromatosis Primary biliary cirrhosis Sclerosing cholangitis Wilson's disease Lung Disease (3): Asthma COPD/chronic bronchitis/emphysema Other lung disease Psychological disorder (14): Addiction ADHD Autism Bipolar Depression Eating disorder Intellectual disability Obsessive compulsive disorder Panic disorder Personality disorder PTSD Schizophrenia Social phobia Sickle cell/thalassemia (3): Sickle cell disease Sickle cell trait Thalassemia

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• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

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• Genomic Landscape of Cutaneous Diffuse Large B Cell Lymphoma

  Cutaneous diffuse large B cell lymphomas (DLBCL) are aggressive lymphomas with a poor prognosis. To elucidate their genetic bases, we performed whole exome capture and massively parallel sequencing on 19 tumor samples of diffuse large B cell lymphoma, leg type (DLBCL-LT) and 6 samples of secondary cutaneous diffuse large B cell lymphoma, not otherwise specified (DLBCL-NOS). Tumor specimens and their associated sequencing data were from multiple institutions, including Northwestern University (Chicago, IL), Massachusetts General Hospital (Boston, MA), and Medical University of Graz (Graz, Austria).

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• NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A)

  The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response.

  Study phs001661

• Varieties of Impulsivity in Opiate and Stimulant Users

  The study was conducted in Bulgaria as a collaboration between Virginia Commonwealth University (Richmond, VA, USA), the Bulgarian Addictions Institute (Sofia, Bulgaria), the Molecular Medicine Center/Medical University (Sofia, Bulgaria), and Indiana University (Bloomington, IN, USA). The overall aim of this study is to investigate the role of impulsivity as an endophenotype for drug addiction. Although impulsivity is considered one of the strongest candidate endophenotypes for addiction, progress in the field is hampered by the heterogeneity of impulsivity, characterized by multiple personality, psychiatric, and neurocognitive dimensions, rarely examined concurrently in the same population; and the heterogeneity of addiction phenotypes, due in part to the high rates of polysubstance dependence among substance users. To address these challenges, we have developed a program of addiction research in Bulgaria, a key transit country for heroin trafficking due to its strategic geographical location on the "Balkan Drug Route" and a major European center for production of synthetic amphetamine-type stimulants. This has allowed us to access rare populations of predominantly mono-substance dependent heroin and amphetamine users, many in protracted abstinence. Our preliminary results reveal a complex relationship between trait and neurocognitive (state) dimensions of impulsivity, often manifested in opposite directions in heroin and amphetamine dependent individuals. Pilot computational modeling analyses of decision-making, a central neurocognitive aspect of impulsivity, have proved particularly informative by indicating that different mechanisms may underlie the impaired decision-making of opiate and stimulant users. A different modeling approach, i.e. phenotypic modeling, holds significant promise to address the pervasive "missing heritability" problem in genetic studies. While genetic heterogeneity is often invoked as an explanation, the manner in which complex phenotypic traits are measured and modeled is equally important contributor to the missing heritability problem but has received much less attention in the literature. Despite the multidimensionality of traits measured by psychometric, diagnostic, and neurocognitive instruments, most GWAS studies typically use aggregate sum scores that do not reflect the underlying phenotypic multidimensionality. Therefore, at least part of the missing heritability problem may originate in misspecification of the phenotypic models. Consequently, sample sizes requirements may increase from ~800 subjects in correctly specified models to 6,000-16,000 subjects in incorrectly specified models. The current study aims to increase our understanding of the complex relationship between multiple putative impulsivity endophenotypes to help redefine endophenotypes as multi-level combination of measures that could inform multivariate multilevel models of complex phenotypes. The specific aims of the study are to: (1) Assess the utility of various personality, psychiatric, and neurocognitive indices of impulsivity (either individually or in combination) as candidate endophenotype(s) for drug addiction in general and for opiate and stimulant addictions in particular; (2) Evaluate the viability of computational model parameters modeling various neurocognitive dimensions of impulsivity as novel endophenotype(s) for addiction; and (3) Test the external validity of the optimal endophenotype(s) by evaluating their associations with HIV and other risk behaviors in opiate and stimulant users in protracted abstinence, a question of critical importance for prevention and intervention efforts in this much less-well understood stage of the addiction cycle.

  Study phs001647

• Center for Education and Drug Abuse Research (CEDAR)

  Under its programmatic name, the Center for Education and Drug Abuse research (CEDAR), this Center of Excellence project was completed in 2015. The CEDAR sample consists of 775 nuclear families comprising an adult male (proband), his spouse/mate, and their biological child who is 10-12 years of age at recruitment. This child is designated as index child (IC), and is followed through age 30. Minimal exclusionary criteria were applied to maximize the sample's representativeness. Follow-up evaluations on ICs were conducted at ages 14, 16, 19, 22, 25, 27 and 30. Interim questionnaires were mailed annually beginning at age 20. CEDAR utilizes the family/high-risk paradigm. The offspring thus comprise high average risk (HAR) and low average risk (LAR) groups, constituting the majority of the CEDAR children sample: 250 HAR males, 100 HAR females, 250 LAR males and 94 LAR females. The remainder of the IC sample, 50 males and 31 females, are the offspring of fathers who have a lifetime non-SUD psychiatric dis-order. The follow-up rate from baseline to the final assessment is ~65%. The cohort of children is 76% White and 22% Black. The representation of females among ICs is lower than males, due to the later start of recruit-ment (2nd funding cycle; the study originally focused on males). The CEDAR genetic study has been augmented by the inclusion of its sample into the whole-genome genotyping effort conducted under the Genes, Environment and Development Initiative (GEDI). DNA from the blood samples of target children (index cases) and their siblings submitted to the NIDA Genetics Depository a Rutgers University was obtained and genotyped on Illumina Human660W-Quad Beadchips, with a high average genotyping rate of 99.8%. The sample comprised 158 females and 271 males (37 and 63 %), ~70:30 European- and African- American, with approximately 1:1 ratio of children of affected fathers and normal controls.

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• Genetic and Genomic Stability Across Lymphoblastoid Cell Line Expansions

  This study was focused on exploring genetic and genomic stability across cell line expansions. We used DNA and cell lines sampled from six apparently healthy research participants. We assayed genome-wide genetic variants and inferred structural variants for DNA extracted from blood, from transformed cell cultures, and from three generations of expansions.

  Study phs001650

• Whole Exome Characterization of Squamous Cell Lung Cancers (Lung SQCC) from Appalachian Kentucky (APPKY)

  This is a pilot study of squamous cell lung cancer and matched normal tissue pairs collected (convenience sample) from patients from Central Appalachia, in Southeastern Kentucky. This study performed whole exome sequencing on tumor and matched normal DNA samples from 51 lung squamous cell carcinoma (SQCC) subjects from Appalachian Kentucky (AppKY). Somatic genomic alteration profiles were compared between the AppKY and TCGA SQCC cohorts. We found that IDH1 and PCMTD1 had higher mutation rates in AppKY versus TCGA. These findings suggest population differences in the genetics of lung SQCC between AppKY and US populations that have implications for personalized treatment for this disease.

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• Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

  In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases. (Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research)

  Study phs001659

• Genetic Etiology of Heterotaxy

  To understand the genetic etiology of heterotaxy, patients with heterotaxy were consented and recruited, with blood drawn for DNA extraction and exome sequencing. Using the exome sequencing dataset obtained, rare coding sequence variants were identified.

  Study phs001691

• NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

  Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

  Study phs001662

• Parkinson's Disease Cognitive Genetics Consortium (PDCGC) Stage I, NeuroX Dataset

  Cognitive impairment is a common and disabling problem in Parkinson's disease (PD). Identification of genetic variants that influence the presence or severity of cognitive deficits in PD might provide a clearer understanding of the pathophysiology underlying this important nonmotor feature. We are presently undertaking a large-scale, two-stage study designed to identify genetic risk factors for cognitive impairment in PD. The study population is divided into a discovery (Stage I) and a validation (Stage II) sample of patients enrolled in the PD Cognitive Genetics Consortium (PDCGC). Each patient has undergone a detailed neurological evaluation and cognitive testing. Clinical and genetic data for the project are stored and managed at the Coordinating Center at the University of Washington and VA Puget Sound Health Care System in Seattle. Stage I of the project is now complete; 1,219 PD patients were genotyped for 249,336 variants using the NeuroX array. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised [HVLT-R]), working memory/executive function (Letter-Number Sequencing and Trail Making Test [TMT] A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation [JoLO]), and global cognitive function (Montreal Cognitive Assessment). We excluded individuals who were of non-European ancestry, failed genotyping, were missing data for one or more covariates, were related to another participant in the cohort, or failed to complete at least half of the cognitive tests. After these quality control measures were implemented, 1,105 participants remained and were included in all subsequent analyses. For common variants we used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates. Rare variants were analyzed using the optimal unified sequence kernel association test. The significance threshold was defined as a false discovery rate corrected P-value (PFDR) of 0.05. Eighteen common variants in 13 genomic regions exceeded the significance threshold for one of the cognitive tests. These included GBA rs2230288 (E326K; PFDR = 2.7 x 10-4) for JoLO, PARP4 rs9318600 (PFDR = 0.006) and rs9581094 (PFDR = 0.006) for HVLT-R total recall, and MTCL1 rs34877994 (PFDR = 0.01) for TMT B-A. Analysis of rare variants did not yield any significant gene regions. We have conducted the first large-scale PD cognitive genetics analysis and nominated several new putative susceptibility genes for cognitive impairment in PD. These results will require replication in independent PD cohorts, and efforts to validate the findings in PDCGC Stage II are in progress.

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• Genomics of Kidney Transplantation

  We have an established consortium consisting of 5 clinical centers which do a total of >800 kidney transplants/year. We have developed a quality-controlled multicenter database with high quality data, and obtained DNA samples and clinical data on 962 recipients and 442 donors. Using our developed infrastructure, we propose to study whether genetic variants are, in part, responsible for the differing outcomes of transplant recipients treated with contemporary immunosuppressive protocols. Our central hypotheses are that the genetic variation is associated with a) kidney transplant outcome, and b) immunosuppressive drug disposition and toxicity. Our long-term goals are to determine whether it is possible to individualize immunosuppressive therapy, based on genetics. At the same time, our studies may elicit new information on pathways important in the immune response or in immunosuppressive drug efficacy, disposition, and toxicity.Our application consists of 3 cores (Genetics Core, Clinical Core, and Administrative Core). We will do a genome wide association study (GWAS). Significant single nucleotide polymorphisms (SNPs) will be identified using the GWAS.Project 1 has 2 specific aims.Aim 1: To identify recipient SNPs that are associated with kidney allograft outcomes, including acute rejection, chronic graft dysfunction, and graft failure. Aim 2: To identify living donor SNPs that are associated with kidney allograft outcomes. Project 2 has 4 specific aims. Aim 1: To identify SNPs that are associated with tacrolimus blood levels.Aim 2: To identify SNPs that are associated with early tacrolimus-related nephrotoxicity and immune suppressant-related new onset diabetes.Aim 3: To identify SNPs that are associated with mycophenolate-related toxicity. Aim 4: To establish the relationships between candidate recipient SNPs, enzyme activity and mRNA expression of the pharmacologic targets of mycophenolate and calcineurin inhibitors. The projects use the genotyping data, which were provided by the Genetics Core, and clinical information, which were collected and entered into the multicenter database by the Clinical Core. Further, biostatistical support (Clinical Core) and administrative oversight and support (Administrative Core) will facilitate data collection, data entry, and data analyses for both projects. The Administrative Core will also facilitate interaction between Sites, Cores, and Projects.Technical note: Regarding to the study design, all transplant recipients should be unrelated. Given the nature of transplantation, some donors may be related to recipients. The donor-recipient relationships are reported in the demographic file under the "related" column. As we did not collect full pedigree information for the related donor-recipient pairs, we have included a IBD file (calculated using PLINK) with the genotype data.

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• Veterans Administration (VA) Million Veteran Program (MVP) Summary Results from Omics Studies

  MVP is an ongoing prospective cohort study and mega-biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans.

  Study phs001672

• ADAGESIII: Contribution of genotype to glaucoma phenotype in African Americans

  Glaucoma results in vision loss due to damage of the optic nerve that is irreversible if undetected or untreated. The most common form of glaucoma is primary open angle glaucoma (POAG). While glaucoma affects all races, persons of African descent are disproportionately affected; studies show African-Americans (AAs) are about four to five times more likely than Caucasian Americans to develop the disease. Glaucoma is the leading cause of irreversible blindness in Americans of African descent, and the second leading cause in all Americans. The lack of understanding about the etiology of POAG impedes our ability to identify and treat it early in its development. Evidence of genetic contribution in the pathogenesis of POAG is well established. Since POAG tends to run in families, it is critical to identify the genetic basis of the disease in order to develop effective therapies for early intervention. While genome wide association studies (GWAS) for glaucoma have been completed for Caucasian populations, evidence from other studies suggests that a GWAS of glaucoma specific genes to the African-American population will yield unique and important findings for both this population and for glaucoma in general. A better understanding of the relationship among the stage of disease, the rate of change, ancestry, and other important risk factors being tracked in the ongoing African Descent and Glaucoma Study (ADAGES) will allow us to evaluate the relationship between genetics, visual loss and structural damage in this high-risk cohort. The scientific plan for this new study focuses on glaucoma in ∼2058 African-Americans by detailed phenotyping of new subjects, acquisition of samples from both new and established previously phenotyped study subjects for a repository, establishment of a data coordinating center, and genome wide association studies. The recruitment, enrollment, and phenotyping of both established and new subjects occurs at five clinical centers, University of California (UCSD), New York Eye and Ear Infirmary (Mt Sinai) and Columbia University Medical Center, a private practice in the Atlanta area, the University of Alabama at Birmingham, and the Robert Cizik Eye Clinic in Houston, TX. UCSD is also the location for the Data Coordinating Center and the Repository with Robert N. Weinreb as Principal Investigator. LA BioMed at Harbor-UCLA did the genotyping with a GWAS panel of ∼1 million single nucleotide polymorphisms (SNPs) using the Illumina MEGA array under the direction of Jerome Rotter, Ida Chen, and Kent Taylor.

  Study phs001673

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Adolescent Idiopathic Scoliosis (AIS) 1000 Exomes Study

  Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Although the Bracing in AIS Trial (BrAIST) recently demonstrated the effectiveness of bracing for preventing scoliosis progression in some patients, more than 20,000 children undergo major spinal fusion surgery at an annual cost of $3 billion. Spinal fusion surgery is a major operation with considerable risks and complications. Accurate methods of predicting curve progression are needed to develop personalized prevention strategies for those at high risk and to eliminate screening and treatment of those at low risk of progression. Previously identified risk factors for scoliosis curve progression include sex, age of onset, curve type, and presence of an underlying disorder. However, currently available algorithms for predicting AIS curve progression are inaccurate, possibly because the role of genetic factors has been largely unexplored. Because there is little a priori knowledge of the genetic variants involved in AIS pathology, an unbiased genome-wide approach is likely to provide the best opportunity to comprehensively identify disease-associated genes. This is a multicenter exome sequencing study of extreme cases with severe scoliosis.

  Study phs001677

• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

  Study phs001680

• Prediction of DNA Repair Inhibitor Response in Short Term Patient-Derived Ovarian Cancer Organoids

  In this study, 34 ovarian tumor organoids generated from 23 patients underwent paired DNA damage repair defect functional analyses and whole exome sequencing analysis to compare genetic mutational status to DNA repair functional capacity. 22 of the patients had high grade serous cancer and 1 of the patients had low grade serous cancer. A normal control, fresh parent tumor, and cells from the organoid culture generated from the parent tumor underwent whole exome sequencing analysis and the data from the sequencing analysis is provided here.

  Study phs001685