Search Results - EGA European Genome-Phenome Archive

Separation, characterization, and identification of individuals from multi-person blood mixtures with single cell ATAC-seq

We report a deconvolution and identification strategy of scATAC-seq datasets using mixed PMBCs data. After sequencing the data were processed with the de-goulash pipeline and analyzed with aim to identify and acquire biogeogrpahical ancestry of the involved individuals. The study includes samples of biological mixtures and in silico mixtures in different mixed ration and cell volumes.

Study EGAS00001007380

Whole-exome-sequencing and Whole-genome-sequencing and RNA-sequencing in Familial amyotrophic lateral sclerosis (ALS)

To identify the genetic cause and modifiers of Familial amyotrophic lateral sclerosis (ALS), we performed Whole-exome-sequencing and Whole-genome-sequencing and RNA-sequencing of Familial amyotrophic lateral sclerosis (ALS) patients.

Study JGAS000358

Shared and distinct features of immune checkpoint therapy-induced myocarditis and myositis

Immune checkpoint therapies (ICTs) can induce life-threatening immune-related adverse events including myocarditis and myositis, which are rare and often concurrent. The molecular pathways and immune subsets underlying these toxicities remain poorly understood.

Study EGAS00001007511

Transcriptional profiling and clonality analysis of peripheral blood B cells and small intestinal plasma cells in celiac disease

Single-cell RNA-seq and BCR sequencing and/or inference of sorted IgA+ peripheral blood B-lineage cells and small intestinal plasma cells of untreated celiac disease patients.

Study EGAS50000000229

InsPIRE islets

We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

Study EGAS00001003997

INDIA

We collected PBMCs from 10 Indian and 10 Dutch individuals before BCG vaccination and 10-12 post-vaccination. We assessed the open chromatin profiles under baseline conditions, and the transcriptomic profiles upon stimulation with Influenza and SARS-CoV-2.

Study EGAS00001006417

Kids First Pediatric Research Study in Familial Predisposition to Hematopoietic Malignancies (SJFAMILY-HM)

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. Acute lymphoblastic leukemia (ALL) is the commonest childhood tumor and a leading cause of cancer death in children, adolescents and young adults. Hodgkin and non-Hodgkin lymphoma are also important hematologic malignancies (HM) that occur in children. Each are genetic diseases with growing evidence for a germline predisposition of both familial and sporadic cases, however the inherited genetic basis of ALL/lymphoma are poorly understood. Such knowledge is essential to gain mechanistic insight into the basis of tumor formation, and to guide genetic counseling and genetic management. Here we have assembled a large collection of familial HM kindreds, and extended recurrence cohorts of ALL and HL which will be used to identify the genetic basis of familial HM, examine the frequency of germline variants in sporadic ALL and HL, and to integrate inherited and somatic genomic data. These studies have high potential to provide fundamental new insights into the inherited genetic basis of HM, to provide important information to guide clinical management, and to provide an invaluable public resource of genomic data.

Study phs001738

Integration of Genomics and Transcriptomics in unselected Twins and in Major Depression

Our goals are to develop a comprehensive understanding of the genomics of transcription in a population based unselected sample and to discover DNA and RNA biomarkers for major depressive disorder (MDD). This work is essential to developing a more complete understanding of the biological basis of MDD, a common complex trait associated with considerable morbidity, mortality, and personal/societal cost. All biological samples have been collected from well-defined populations, and are now available. First, we conduct a "genetical genomics" or eQTL study of ~800 MZ and ~800DZ twin pairs. Each subject has been assayed for genome-wide SNPs and CNVs and gene expression from peripheral blood sampled under standardized conditions. We determine the genetic architecture (genetic and non-genetic proportions of variance via twin analyses) for every transcript, and the genome-wide associations (i.e., SNP-transcript eQTL pairs). These analyses will be expanded to consider transcriptional modules. The key deliverable is a detailed catalogue of the general and specific architecture of transcription plus raw intensity files. Second, we seek to discover DNA and RNA biomarkers relevant to MDD, capitalizing on the results of a large MDD study with repeated clinical and biological assessments; we have previously shown that PB is a reasonable proxy for CNS expression and employ an advanced modelling framework: (a) Using baseline data, we identify biomarkers for MDD by comparing ~1000 controls with ~1400 MDD cases via comparisons of SNP, CNV, expression transcripts, and transcriptional modules. (b) Using longitudinal data, we contrast gene expression signatures assessed at baseline and two years later in ~200 controls and ~500 MDD cases.

Study phs000486

Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study - Maternal Glycemia and Birthweight GEI Study

Low and high birth weight are not only major causes of neonatal morbidity and mortality, but epidemiological data have established an association between birth weight and later life risk of adult metabolic diseases. Fetal growth is determined by complex interactions between fetal genes and the maternal uterine environment. Subtle or overt variation in maternal glucose tolerance, which is, in part, genetically determined, is related to fetal size at birth. Moreover, new emerging data suggest that genetic variation in the fetus can impact maternal metabolism (e.g., blood pressure and glucose tolerance). Given the above, we are addressing the hypothesis that, during pregnancy, gene-environment interactions in the context of the maternal-fetal unit impact fetal size at birth and maternal metabolism. Genes that control fetal growth or maternal metabolism during pregnancy are largely unknown, so the first step to address our hypothesis will be to identify genetic variation that impacts fetal growth and maternal metabolism and to determine the interaction of that variation with the intrauterine and fetal environment. To accomplish this, we are performing genome wide association (GWA) mapping on a subset of ~37,000 DNA samples that were collected from mothers and their offspring as part of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. HAPO is a multicenter, international study in which high quality phenotypic data related to fetal growth and maternal glucose metabolism has been collected from 25,000 pregnant women of varied racial and socio-demographic backgrounds using standardized protocols that were uniform across centers. For these studies, we are genotyping 1,500 infants and their mothers of European descent, 1,250 Afro-Caribbean infants and mothers, 800 Hispanic (Mexican-American) infants and mothers, and 1200 Thai infants and mothers. Genotyping is being performed using the Illumina Human610 Quad (European ancestry participants), Human1M Duo (Afro-Caribbean and Hispanic participants), and Omni1-Quad_v1-0_B (Thai participants). The specific aims for the project are as follows: (1) To apply analytic approaches for conducting GWA mapping studies on quantitative phenotypes related to offspring size at birth (birth weight, ponderal index, head circumference and adiposity) allowing for other known influences such as gestational age, parity, and maternal weight gain. (2) To apply the above approaches to identify genetic variation that impacts maternal glucose tolerance at ~28 weeks of gestation (fasting glucose, glucose during an oral glucose tolerance test, and insulin sensitivity expressed as quantitative traits) allowing for other known influences such as maternal weight gain, parity and age. (3) To examine the interaction between maternal genes, the intrauterine environment, and fetal genes to identify interactions that modulate genetic regulation of size at birth and fetal genetic variation that impacts on maternal glucose tolerance. GWA mapping will provide initial evidence for association of specific SNPs with the quantitative traits outlined above. As low and high birth weight are not only major causes of neonatal morbidity and mortality but have also been associated with increased risk of metabolic diseases in adults, identification of genes that regulate fetal growth and maternal metabolism will provide novel information about the pathways that regulate these processes as well as important insight into susceptibility genes for chronic diseases like type 2 diabetes. The Version 1 (v1) dbGaP release will include data only from the Hispanic study participants. The Version 2 (v2) dbGaP release will include data from the Hispanic and European ancestry study participants. The Version 3 (v3) dbGaP release will include data from the Afro-Caribbean, Hispanic and European ancestry participants. The Version 4 (v4) dbGaP release will include data from all participants (i.e., Afro-Caribbean, Hispanic, European ancestry, and Thai participants). This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to maternal metabolism and birthweight through large-scale genome-wide association studies of infants and their mothers at multiple international sites. Genotyping was performed at the Broad Institute of MIT and Harvard, and at CIDR of Johns Hopkins University, GENEVA genotyping centers. Data cleaning and harmonization was performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

Study phs000096

NHLBI GO-ESP: Family Studies (Familial Atrial Fibrillation)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Large epidemiological studies have demonstrated a significant heritable component in atrial fibrillation (AF), especially the Lone forms, suggesting a monogenic syndrome. Although substantial genetic contribution has been made to the etiology of AF, the specific genes have not yet been identified. The familial form of this disease remains poorly characterized and largely undetermined. Here we seek to identify, characterize and determine the natural course of AF in our clinical practice. We identified four large multi-generation families (FAF 1-4). In FAF 1-2, most family members have symptomatic paroxysmal Atrial Fibrillation (AF) and were adequately treated with a combination of rate and rhythm therapies. By contrast, the AF substrate in FAF 3 and 4 was resistant to anti-arrhythmic drugs and ablation therapies.

Study phs000362

Cancer Moonshot Biobank

The National Cancer Institute initiated the Cancer Moonshot Biobank to accelerate research through the collection and distribution of biospecimens for key research efforts. The Biobank will engage with over one thousand cancer patients, being treated with standard-of-care therapies, for longitudinal biospecimen and data collection. Cancer patients will be enrolled into the study from a diverse participant population engaged at medical institutions throughout the U.S. The biospecimens will be distributed to qualified scientists to accelerate research progress. The Biobank program, working closely with Leidos Biomedical, Inc. (LBR), will partner with community hospitals and other medical institutions, designated as Biospecimen Source Sites (BSS), to engage and consent eligible participants and collect biospecimens and associated clinical data; work with a central Biospecimen Core Resource (BCR) to support biospecimen collection, processing and storage activities and perform pathology quality control; work with LBR's Molecular Characterization (MoCha) lab to perform clinical tumor molecular characterization assays and return results to patients and their physicians; and make the biospecimens and associated data available to researchers to accelerate cancer research progress. Return of clinical results, a dedicated Patient and Provider Engagement (PPE) website, electronic informed consent, local participant engagement projects, and an embedded ethical, legal and social issues sub-study will together support patient and provider engagement in the program. Cancer Moonshot Biobank imaging data is being made available in The Cancer Imaging Archive (TCIA) on a release schedule that is coordinated with the program releases of data to dbGaP. The imaging data can be found at the following link: Cancer Moonshot Biobank Imaging

Study phs002192

Intervention with Micronutrients and Long-Term Impact in Brazil-RECODISA

Intervention with Micronutrients and Long-Term Impact in Brazil, a partnership between the Federal University of Ceará, Brazil and the University of Virginia, USA, enrolled infants in the age group of 2-36 months to investigate trends in gastrointestinal infections and their effects on growth and development and to identify genetic factors contributing to these diseases.A total of 1044 children from six urban communities in Brazil's semiarid region, were enrolled during active surveillance; those with diarrhea (three or more liquid stools in the last 24 hours at enrollment) were defined as a cases and matched with controls having no diarrhea during the past two weeks (at enrollment) to evaluate their growth and development. A subset of 664 children with their genetic and associated phenotypic data is included in this submission. More information on this project and its related projects can be found here: Studies of diarrheal susceptibility, growth, and development, in pediatric populations in Northeastern Brazil

Study phs003174

Whole Genome, Exome, Transcriptome and Validation Sequencing of an Acute Lymphoblastic Leukemia

We used massively parallel sequencing technology to profile the genomic DNA and RNA of tumor cells (leukemic bone marrow) and normal cells (skin biopsy) obtained from a single patient with Acute Lymphoblastic Leukemia (ALL), referred to throughout this study as 'ALL1'. Included in this study are samples obtained from a primary tumor, first relapse, second relapse and several intermediate timepoints. We identified somatic mutations present in each tumor by analysis of whole genome (WGS) and exome sequence data. Single nucleotide variants (SNVs) and small insertions and deletions were identified in both the exome and WGS data. Large copy number variations (CNVs) and structural variants (SVs) were identified in the WGS data. A custom capture reagent was designed to target most variants and used to generate deep validation sequence data. The expression status of all somatic variants was assessed by RNA-seq. The RNA-seq data was also used for gene expression analysis and gene fusion detection.

Study phs001066

Genomics and Methylation of Neuroendocrine Prostate Cancer from cfDNA (Cornell/Trento 2019)

A subset of castration resistant prostate cancers develop small cell neuroendocrine prostate cancer (NEPC) as a mechanism of treatment resistance. Metastatic tissue biopsies to evaluate for NEPC transformation are invasive and challenging to perform serially. We performed whole exome and whole genome bisulfite sequencing of plasma cfDNA and matched tumor biopsy samples from 62 patients with metastatic prostate cancer along the disease spectrum to evaluate for NEPC associated genomic and epigenomic features. Multiple tissue biopsies and/or plasma time points were included for a subset of patients to characterize disease heterogeneity and dynamic changes. Computational analysis of clonality and allele specific quantification allowed for detailed comparison of matched tumor tissue and cfDNA data (CLONET v2). Methylation profiles detected from tissue and plasma data were compared and NEPC specific alterations were evaluated in cfDNA. The study supports the feasibility of a plasma based assay for the detection of NEPC.

Study phs001752

Healthy and FPD Bone Marrow Single Cell Sequencing

Familial platelet disorder (FPD) is caused by germline RUNX1 mutations. Families inheriting the disease suffer from platelet dysfunction and consequently various bleeding disorders. The life long risk of developing leukemia increases in FPD individuals by 40% and the onset is at 29 years old. In order to understand the mechanism behind disease transformation, we performed single cell sequencing on mononuclear bone marrow cells from 10 FPD and 4 healthy control individuals. The participants were between 6 and 72 years of age at time of bone marrow collection and were not diagnosed with any leukemia. Following the established Ficoll paque assay, the mononuclear cells were used to perform 10x chromium single cell, the data was analyzed through Seruat packages, and further analysis was done to access differences between FPD and healthy. The most distinguished feature between FPD and healthy was the upregulation of inflammation and inflammatory related disease. These findings were further validated and used to design an inhibitory assay for reversal of FPD phenotype.

Study phs003508

Geographical structure and differential natural selection among North European populations

European populations and epidemiological cohorts are of special significance in the current era of genomic research aiming to characterize the background of common human diseases. The genome sequence, detailed information of genetic variations between individuals, high-throughput molecular technologies and novel statistical strategies create new possibilities to define genetic and life-style risk factors behind common health problems. Studies of large population cohorts are needed to transform the genetic information to detailed understanding of the predisposing factors in diseases affecting most human populations. European twin cohorts provide a unique competitive advantage for investigations of the role of genetics and environment or life style in the etiology of common diseases. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterise the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide.

Study EGAS00000000033

Integrated genetic and epigenetic analysis defines novel molecular clusters in rhabdomyosarcoma

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in childhood. To unravel the genetic/epigenetic basis of RMS, we studied 60 RMS cases using whole exome/transcriptome sequencing, copy number (CN) profiling, and DNA methylome analysis. Based on DNA methylation patterns, RMS was clustered into 4 distinct subtypes, which exhibited remarkable correlation with mutation/CN profiles, histological phenotypes, and clinical behaviors. A1 and A2 subtypes, especially A1, largely corresponded to alveolar histology with frequent PAX3/7 fusions and alterations in cell cycle regulators. In contrast, mostly showing embryonal histology, both E1 and E2 subtypes were characterized by high frequency of CN alterations and/or allelic imbalances, FGFR4/RAS/AKT pathway mutations and PTEN mutations/methylation and in E2, also by p53 inactivation. Despite generally poor prognosis in RMS, patients in E1 cluster exceptionally showed excellent prognosis. Our results highlight the close relationship between DNA methylation status and gene mutations and biological behavior in RMS.

Study EGAS00001000884

The biology of cell-free DNA fragmentation and the roles ofDNASE1, DNASE1L3 and DFFB

The biology of cell-free DNA fragmentation and the roles of DNASE1, DNASE1L3 and DFFB

Study EGAS00001003514

Genomic characterization of a patient with AGS and CdLS transcriptomic comparison of his monocytes against healthy and disease control samples

In this study, we describe an extreme genetic phenotype of two simultaneous genetic lesions, leading to broad alterations in immunophenotype and transcriptome. Whole Exome Sequencing and RNA-Sequencing of CD14+ monocytes was performed on the case patient, and RNA-sequencing was also performed on disease (Systemic Lupus Erythematosus) and healthy controls.

Study EGAS00001007829

TIGER-LC High-Throughput Sequencing

Intrahepatic cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) are clinically disparate primary liver cancers with etiological and biological heterogeneity. We performed sequencing on multiple data levels of Thai CCA and HCC among the Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC) cohort using targeted OncoVar platform, whole exome, whole transcriptome, and whole genome metagenomic sequencing.

Study phs001199

Gene expression in brain (Schizophrenia) study

The study included post-mortem brain tissue samples from 68 schizophrenia patients and 44 age and sex matched control subjects. Whole transcriptome poly-A selected paired-end RNA sequencing was performed on tissue from prefrontal cortex and orbitofrontal cortex. RNA expression differences were detected between case and control individuals, focusing both on single genes and pathways.

Study EGAS00001004199

Drug Signatures for Prediction and Mitigation of Toxicity

The overall goal of the drug signatures for prediction and mitigation of toxicity study is to use genomic and proteomic high-throughput measurements as the basis for computational analysis that integrates network analyses with structural constraints and dynamical models in multiple cell types to identify signatures that predict toxicity induced by 55 FDA-approved chemotherapeutic drugs and potential mitigation of this toxicity. Specifically, we have recruited and pre-screened healthy individuals to be included in our study. Ninety six male and female individuals that satisfied the initial pre-screening for the study and their sex, age, race/ethnicity recorded through an enrollment questionnaire were consented. Eighty five underwent a formal and thorough medical health screening. The evaluation involved assessment of all inclusion and exclusion criteria, a full medical history, measurement of weight, height, waist and hip circumference, heart rate, blood pressure, respiratory rate, and oxygen saturation, a physical exam and an electrocardiograph (ECG). Blood was drawn for analysis of clinical relevant parameters. A pregnancy test was included for female participants. All blood draws and pregnancy tests were sent to a certified clinical laboratory for clinical analysis. Of the 85 subjects that were screened 42 (48.3%) were deemed eligible for final inclusion. Of these 42, one declined to undergo skin biopsy and/or venesection and one subject didn’t show up for the scheduled biopsy, leaving 40 clinically healthy subjects on which a skin biopsy and venesection was performed. Fibroblast lines were established from the skin biopsies. Induced pluripotent cells (iPSC) were generated from the established fibroblast lines of these 40 clinically healthy racially diverse male and female study participants who ranged in age from 22 and 61 years through reprogramming using either the mRNA or Sendai-virus methods. One clone from each of the 40 iPSC line was fully characterized for normal karyotype, short-tandem repeat matching to the original fibroblast line (authentication), pluripotency by select pluripotent marker expression via immunocytochemistry and by mRNAseq-based PluriTest analysis, and whole-genome sequencing.

Study phs002088

Childhood Cancer Data Initiative (CCDI): Molecular Characterization across Pediatric Brain Tumors and Other Solid and Hematologic Malignancies for Research, Diagnostic, and Precision Medicine

This study contains tumor and germline WGS, RNA-Seq, Clinical Panel Sequencing, and other omics and molecular data for patients with pediatric brain tumors and other solid and hematologic malignancies. This data has been collected from multiple organizations including the multi-institute Children's Brain Tumor Network (CBTN), the Pacific Pediatric Neuro-Oncology Consortium (PNOC), and the Children's Hospital of Philadelphia Division for Genomic Diagnostics (CHOP DGD). In addition to being available pre-publication and without embargo via dbGaP and the NCI Cancer Research Data Commons, this data is made available via Cavatica, PedcBioPortal and the Kids First Data Resource Portal. Collectively, this availability strives to accelerate the research process and enable members of the scientific and patient communities to partner and make discoveries faster than ever before.In 2019, the CBTN launched the Pediatric Brain Tumor Atlas, which now comprises the largest collection of childhood brain tumor data in the world. This resource is helping accelerate not only brain tumor research, but is also empowering discovery for other rare childhood conditions. Brain tumors are the most common form of cancer in children aged 0-19 in the United States, and are the largest cause of cancer-related deaths. The estimated number of new cases in 2019 is nearly 3,800, and thus brain tumors are a rare disease. Despite their relative rarity, the years of potential life lost due to brain tumors in 2009 was estimated at 47,631 years for children and adolescents aged 0-19 in the United States; this is a disproportionate amount of life lost compared to adult cancers and represents an unrecognized societal threat. There is an urgent need to improve therapies for these children. This sequencing cohort defines the largest, clinically annotated pediatric brain tumor cohort study to date and seeks to define the intersection of germline and somatic underpinnings of pediatric brain tumors across a shared developmental context of cancer and structural birth defects.

Study phs002517

Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

The National Human Genome Research Institute and the NIH Clinical Center established the intramural Undiagnosed Diseases Program (UDP) in 2008 to make progress in uncovering, understanding, and treating rare disorders. Based on the success of the UDP, the NIH Common Fund established the Undiagnosed Diseases Network (UDN) in FY 2013 (Phase I, 9/16/2015-8/31/2018) to achieve this type of cross-disciplinary approach to disease diagnosis in academic medical centers around the United States. The NIH Common Fund expanded the network in 2018 (Phase II, 9/1/2018-6/20/2023) to increase the availability of diagnostic services, foster opportunities for collaboration between laboratory and clinical investigators, provide resulting data and protocols to the broader community, and assess development of a sustainable national resource after Common Fund support ends. The UDN transitioned from Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) will oversee the Network in Phase III, which launched in July 2023, with help from 17 different NIH Institutes and Centers along with the NIH Office of the Director. With help from patients, family members, patient advocacy groups, a Data Management and Coordinating Center (DMCC), several Clinical Sites, and other stakeholders, the NIH envisions the UDN evolving into a larger, diverse, and self-sustained network that fosters scientific discovery and provides expert diagnostic services for undiagnosed patients across the nation. The overarching goals of the UDN in Phase III include: Continuing the proven success of the UDN in improving the clinical evaluation of difficult-to-diagnose patients using a collaborative team approach and investigating and validating promising new diagnostic technologies. Facilitating research into the etiology of undiagnosed diseases by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and documentation of environmental exposures. Promoting a broader integrated and collaborative community across multiple Clinical Sites and among laboratory and clinical investigators prepared to investigate the genetic, pathophysiologic, cell biologic, and molecular mechanisms underpinning these difficult-to-diagnose conditions.

Study phs001232

National Institute on Alcohol Abuse and Alcoholism (NIAAA) Postmortem Prefrontal Cortex eQTL and mQTL Study

Mapping expression and methylation quantitative trait loci (eQTLs and mQTLs) using genome-wide genotype, transcriptome, and DNA methylome data can provide an unbiased approach to identify novel functional variants. One critical issue of the eQTL/mQTL analysis is that the role of genetic variants in regulating gene expression (or DNA methylation) can be tissue- or cell-specific. To unravel causal variants from disease-associated loci, it would be necessary to map eQTLs and mQTLs in both patients and controls. Those eQTLs and mQTLs in patients are more likely to be causal variants for the disease. Identification of disease- and tissue-specific eQTLs and mQTLs will help disentangle the role of the specific tissue in disease development as well. In the present study, we mapped eQTLs and mQTLs in postmortem prefrontal cortex of patients with alcoholism or alcohol use disorder (AUD) and matched control subjects by integrative analyses of genome-wide SNP genotype, mRNA transcriptome, and DNA methylome data. As AUD is comorbid with schizophrenia (SCZ), bipolar disorder (BIP), major depressive disorder (MDD), and attention deficit/hyperactivity disorder (ADHD), we further examined the co-localization of PFC eQTLs/mQTLs and GWAS-identified SNPs (mainly noncoding SNPs) that were associated with AUD as well as comorbid SCZ, BIP, MDD, and ADHD. Our study demonstrated the enrichment of PFC eQTLs/mQTLs in the above psychiatric disorder-associated genetic variants identified by genome-wide association studies (GWAS).

Study phs001981

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