Candidate Gene and Genome-Wide Association Studies for Circulating
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Genetic Analysis of Retinopathy in Type 1 Diabetes
Genetic Analysis of Retinopathy in Type 1 Diabetes by Sayed Mohsen Hosseini A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Institute of Medical Science University of Toronto © Copyright by S. Mohsen Hosseini 2014 Genetic Analysis of Retinopathy in Type 1 Diabetes Sayed Mohsen Hosseini Doctor of Philosophy Institute of Medical Science University of Toronto 2014 Abstract Diabetic retinopathy (DR) is a leading cause of blindness worldwide. Several lines of evidence suggest a genetic contribution to the risk of DR; however, no genetic variant has shown convincing association with DR in genome-wide association studies (GWAS). To identify common polymorphisms associated with DR, meta-GWAS were performed in three type 1 diabetes cohorts of White subjects: Diabetes Complications and Control Trial (DCCT, n=1304), Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR, n=603) and Renin-Angiotensin System Study (RASS, n=239). Severe (SDR) and mild (MDR) retinopathy outcomes were defined based on repeated fundus photographs in each study graded for retinopathy severity on the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. Multivariable models accounted for glycemia (measured by A1C), diabetes duration and other relevant covariates in the association analyses of additive genotypes with SDR and MDR. Fixed-effects meta- analysis was used to combine the results of GWAS performed separately in WESDR, ii RASS and subgroups of DCCT, defined by cohort and treatment group. Top association signals were prioritized for replication, based on previous supporting knowledge from the literature, followed by replication in three independent white T1D studies: Genesis-GeneDiab (n=502), Steno (n=936) and FinnDiane (n=2194). -
The Global Architecture Shaping the Heterogeneity and Tissue-Dependency of the MHC Class I Immunopeptidome Is Evolutionarily Conserved
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.28.317750; this version posted September 29, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The Global Architecture Shaping the Heterogeneity and Tissue-Dependency of the MHC Class I Immunopeptidome is Evolutionarily Conserved Authors Peter Kubiniok†1, Ana Marcu†2,3, Leon Bichmann†2,4, Leon Kuchenbecker4, Heiko Schuster1,5, David Hamelin1, Jérome Despault1, Kevin Kovalchik1, Laura Wessling1, Oliver Kohlbacher4,7,8,9,10 Stefan Stevanovic2,3,6, Hans-Georg Rammensee2,3,6, Marian C. Neidert11, Isabelle Sirois1, Etienne Caron1,12* Affiliations *Corresponding and Leading author: Etienne Caron ([email protected]) †Equal contribution to this work 1CHU Sainte-Justine Research Center, Montreal, QC H3T 1C5, Canada 2Department of Immunology, Interfaculty Institute for Cell Biology, University of Tübingen, Tübingen, Baden-Württemberg, 72076, Germany. 3Cluster of Excellence iFIT (EXC 2180) "Image-Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Baden-Württemberg, 72076, Germany. 4Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Baden- Württemberg, 72074, Germany. 5Immatics Biotechnologies GmbH, Tübingen, 72076, Baden-Württemberg, Germany. 6DKFZ Partner Site Tübingen, German Cancer Consortium (DKTK), Tübingen, Baden- Württemberg, 72076, Germany. 7Institute for Bioinformatics and Medical Informatics, -
Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma
Anatomy and Pathology Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma Sarah L. Lake,1 Sarah E. Coupland,1 Azzam F. G. Taktak,2 and Bertil E. Damato3 PURPOSE. To detect deletions and loss of heterozygosity of disease is fatal in 92% of patients within 2 years of diagnosis. chromosome 3 in a rare subset of fatal, disomy 3 uveal mela- Clinical and histopathologic risk factors for UM metastasis noma (UM), undetectable by fluorescence in situ hybridization include large basal tumor diameter (LBD), ciliary body involve- (FISH). ment, epithelioid cytomorphology, extracellular matrix peri- ϩ ETHODS odic acid-Schiff-positive (PAS ) loops, and high mitotic M . Multiplex ligation-dependent probe amplification 3,4 5 (MLPA) with the P027 UM assay was performed on formalin- count. Prescher et al. showed that a nonrandom genetic fixed, paraffin-embedded (FFPE) whole tumor sections from 19 change, monosomy 3, correlates strongly with metastatic death, and the correlation has since been confirmed by several disomy 3 metastasizing UMs. Whole-genome microarray analy- 3,6–10 ses using a single-nucleotide polymorphism microarray (aSNP) groups. Consequently, fluorescence in situ hybridization were performed on frozen tissue samples from four fatal dis- (FISH) detection of chromosome 3 using a centromeric probe omy 3 metastasizing UMs and three disomy 3 tumors with Ͼ5 became routine practice for UM prognostication; however, 5% years’ metastasis-free survival. to 20% of disomy 3 UM patients unexpectedly develop metas- tases.11 Attempts have therefore been made to identify the RESULTS. Two metastasizing UMs that had been classified as minimal region(s) of deletion on chromosome 3.12–15 Despite disomy 3 by FISH analysis of a small tumor sample were found these studies, little progress has been made in defining the key on MLPA analysis to show monosomy 3. -
Genome-Wide Association Identifies Candidate Genes That Influence The
Genome-wide association identifies candidate genes that influence the human electroencephalogram Colin A. Hodgkinsona,1, Mary-Anne Enocha, Vibhuti Srivastavaa, Justine S. Cummins-Omana, Cherisse Ferriera, Polina Iarikovaa, Sriram Sankararamanb, Goli Yaminia, Qiaoping Yuana, Zhifeng Zhoua, Bernard Albaughc, Kenneth V. Whitea, Pei-Hong Shena, and David Goldmana aLaboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, Rockville, MD 20852; bComputer Science Department, University of California, Berkeley, CA 94720; and cCenter for Human Behavior Studies, Weatherford, OK 73096 Edited* by Raymond L. White, University of California, Emeryville, CA, and approved March 31, 2010 (received for review July 23, 2009) Complex psychiatric disorders are resistant to whole-genome reflects rhythmic electrical activity of the brain. EEG patterns analysis due to genetic and etiological heterogeneity. Variation in dynamically and quantitatively index cortical activation, cognitive resting electroencephalogram (EEG) is associated with common, function, and state of consciousness. EEG traits were among the complex psychiatric diseases including alcoholism, schizophrenia, original intermediate phenotypes in neuropsychiatry, having been and anxiety disorders, although not diagnostic for any of them. EEG first recorded in humans in 1924 by Hans Berger, who documented traits for an individual are stable, variable between individuals, and the α rhythm, seen maximally during states of relaxation with eyes moderately to highly heritable. Such intermediate phenotypes closed, and supplanted by faster β waves during mental activity. appear to be closer to underlying molecular processes than are EEG can be used clinically for the evaluation and differential di- clinical symptoms, and represent an alternative approach for the agnosis of epilepsy and sleep disorders, differentiation of en- identification of genetic variation that underlies complex psychiat- cephalopathy from catatonia, assessment of depth of anesthesia, ric disorders. -
Expression Quantitative Trait Loci and the Phenogen
TECHNOLOGIES FROM THE FIELD EXPRESSION QUANTITATIVE TRAIT LOCI AND Like experimental technologies, techniques for analyz THE PHENOGEN DATABASE ing the data generated from the microarray technologies continue to evolve. Initially, researchers obtained data for several thousand genes but on a relatively small number of Laura Saba, Ph.D.; Paula L. Hoffman, Ph.D.; subjects. After applying the appropriate statistics and multi Cheryl Hornbaker; Sanjiv V. Bhave, Ph.D.; and ple comparison adjustment, the investigators would com Boris Tabakoff, Ph.D. pile from these a list of potential candidates that could contribute to the phenotype under investigation. In many KEY WORDS: Genetic theory of alcohol and other drug use; cases, this list would contain several hundred genes. For a microarray technologies; microarray analysis; phenotype; researcher who is looking to take a few candidate genes to candidate gene; qualitative trait locus (QTL); expression qualitative the next step of testing, such a long list was problematic. trait locus (eQTL); gene expression; gene transcription; genetics; With only limited resources and time available, the researcher genomics; transcriptomics; high-throughput analysis; messenger was forced to pick some “favorites” from the list for further RNA (mRNA); brain; laboratory mice; laboratory rats; PhenoGen testing. More recently, however, techniques have been Database developed to systematically narrow these lists. These approaches incorporate biological reasoning to avoid a subjective choice of candidate genes. The following section describes esearchers from a wide variety of backgrounds and one of these strategies. with a broad range of goals have utilized high- R throughput screening technologies (i.e., microarray technologies) to identify candidate genes that may be associ Behavioral and Expression Quantitative ated with an observable characteristic or behavior (i.e., phe Trait Loci for Selecting Candidate Genes notype) of interest. -
The Role of Haplotypes in Candidate Gene Studies
Genetic Epidemiology 27: 321–333 (2004) The Role of Haplotypes in Candidate Gene Studies Andrew G. Clarkn Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York Human geneticists working on systems for which it is possible to make a strong case for a set of candidate genes face the problem of whether it is necessary to consider the variation in those genes as phased haplotypes, or whether the one-SNP- at-a-time approach might perform as well. There are three reasons why the phased haplotype route should be an improvement. First, the protein products of the candidate genes occur in polypeptide chains whose folding and other properties may depend on particular combinations of amino acids. Second, population genetic principles show us that variation in populations is inherently structured into haplotypes. Third, the statistical power of association tests with phased data is likely to be improved because of the reduction in dimension. However, in reality it takes a great deal of extra work to obtain valid haplotype phase information, and inferred phase information may simply compound the errors. In addition, if the causal connection between SNPs and a phenotype is truly driven by just a single SNP, then the haplotype- based approach may perform worse than the one-SNP-at-a-time approach. Here we examine some of the factors that affect haplotype patterns in genes, how haplotypes may be inferred, and how haplotypes have been useful in the context of testing association between candidate genes and complex traits. Genet. Epidemiol. & 2004 Wiley-Liss, Inc. Key words: haplotype inference; haplotype association testing; candidate genes; linkage equilibrium Grant sponsor: NIH; Grant numbers: GM65509, HL072904. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
CCNL1 (NM 020307) Human Untagged Clone – SC113160 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC113160 CCNL1 (NM_020307) Human Untagged Clone Product data: Product Type: Expression Plasmids Product Name: CCNL1 (NM_020307) Human Untagged Clone Tag: Tag Free Symbol: CCNL1 Synonyms: ania-6a; ANIA6A; BM-001; PRO1073 Vector: pCMV6-XL5 E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: None Fully Sequenced ORF: >NCBI ORF sequence for NM_020307, the custom clone sequence may differ by one or more nucleotides ATGGCGTCCGGGCCTCATTCGACAGCTACTGCTGCCGCAGCCGCCTCATCGGCCGCCCCAAGCGCGGGCG GCTCCAGCTCCGGGACGACGACCACGACGACGACCACGACGGGAGGGATCCTGATCGGCGATCGCCTGTA CTCGGAAGTTTCACTTACCATCGACCACTCTCTGATTCCGGAGGAGAGGCTCTCGCCCACCCCATCCATG CAGGATGGGCTCGACCTGCCCAGTGAGACGGACTTACGCATCCTGGGCTGCGAGCTCATCCAGGCCGCCG GCATTCTCCTCCGGCTGCCGCAGGTGGCGATGGCAACGGGGCAGGTGTTGTTTCATCGTTTTTTCTACTC CAAATCTTTCGTCAAACACAGTTTCGAGATTGTTGCTATGGCTTGTATTAATCTTGCATCAAAAATCGAA GAAGCACCTAGAAGAATAAGAGATGTGATTAATGTATTCCACCACCTCCGCCAGTTAAGAGGAAAAAGGA CTCCAAGCCCCCTGATCCTTGATCAGAACTACATTAACACCAAAAATCAAGTTATCAAAGCAGAGAGGAG GGTGCTAAAGGAGTTGGGATTTTGTGTTCATGTCAAGCATCCTCATAAGATCATTGTTATGTATTTACAA GTCTTAGAATGTGAACGTAATCAAACCCTGGTTCAAACTGCCTGGAATTACATGAATGACAGTCTTCGAA CCAATGTGTTTGTTCGATTTCAACCAGAGACTATAGCATGTGCTTGCATCTACCTTGCAGCTAGAGCACT TCAGATTCCGTTGCCAACTCGTCCCCATTGGTTTCTTCTTTTTGGTACTACAGAAGAGGAAATCCAGGAA ATCTGCATAGAAACACTTAGGCTTTATACCAGAAAAAAGCCAAACTATGAATTACTGGAAAAAGAAGTAG AAAAAAGAAAAGTAGCCTTACAAGAAGCCAAATTAAAAGCAAAGGGATTGAATCCGGATGGAACTCCAGC -
Epigenome-Wide Study Identified Methylation Sites Associated With
nutrients Article Epigenome-Wide Study Identified Methylation Sites Associated with the Risk of Obesity Majid Nikpay 1,*, Sepehr Ravati 2, Robert Dent 3 and Ruth McPherson 1,4,* 1 Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, 40 Ruskin St–H4208, Ottawa, ON K1Y 4W7, Canada 2 Plastenor Technologies Company, Montreal, QC H2P 2G4, Canada; [email protected] 3 Department of Medicine, Division of Endocrinology, University of Ottawa, the Ottawa Hospital, Ottawa, ON K1Y 4E9, Canada; [email protected] 4 Atherogenomics Laboratory, University of Ottawa Heart Institute, Ottawa, ON K1Y 4W7, Canada * Correspondence: [email protected] (M.N.); [email protected] (R.M.) Abstract: Here, we performed a genome-wide search for methylation sites that contribute to the risk of obesity. We integrated methylation quantitative trait locus (mQTL) data with BMI GWAS information through a SNP-based multiomics approach to identify genomic regions where mQTLs for a methylation site co-localize with obesity risk SNPs. We then tested whether the identified site contributed to BMI through Mendelian randomization. We identified multiple methylation sites causally contributing to the risk of obesity. We validated these findings through a replication stage. By integrating expression quantitative trait locus (eQTL) data, we noted that lower methylation at cg21178254 site upstream of CCNL1 contributes to obesity by increasing the expression of this gene. Higher methylation at cg02814054 increases the risk of obesity by lowering the expression of MAST3, whereas lower methylation at cg06028605 contributes to obesity by decreasing the expression of SLC5A11. Finally, we noted that rare variants within 2p23.3 impact obesity by making the cg01884057 Citation: Nikpay, M.; Ravati, S.; Dent, R.; McPherson, R. -
A Mouse Model of Heritable Cerebrovascular Disease
A Mouse Model of Heritable Cerebrovascular Disease Thomas J. Sproule1, John G. Sled2, Jill Wentzell1, Bing Wang1, R. Mark Henkelman2, Derry C. Roopenian1, Robert W. Burgess1* 1 The Jackson Laboratory, Bar Harbor, Maine, United States of America, 2 Hospital for Sick Children, University of Toronto, Toronto, Canada Abstract The study of animal models of heritable cerebrovascular diseases can improve our understanding of disease mechanisms, identify candidate genes for related human disorders, and provide experimental models for preclinical trials. Here we describe a spontaneous mouse mutation that results in reproducible, adult-onset, progressive, focal ischemia in the brain. The pathology is not the result of hemorrhage, embolism, or an anatomical abnormality in the cerebral vasculature. The mutation maps as a single site recessive locus to mouse Chromosome 9 at 105 Mb, a region of shared synteny with human chromosome 3q22. The genetic interval, defined by recombination mapping, contains seven protein-coding genes and one processed transcript, none of which are changed in their expression level, splicing, or sequence in affected mice. Targeted resequencing of the entire interval did not reveal any provocative changes; thus, the causative molecular lesion has not been identified. Citation: Sproule TJ, Sled JG, Wentzell J, Wang B, Henkelman RM, et al. (2010) A Mouse Model of Heritable Cerebrovascular Disease. PLoS ONE 5(12): e15327. doi:10.1371/journal.pone.0015327 Editor: Takeo Yoshikawa, RIKEN Brain Science Institute, Japan Received September 8, 2010; Accepted November 8, 2010; Published December 31, 2010 Copyright: ß 2010 Sproule et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. -
Candidate-Gene Criteria for Clinical Reporting: Diagnostic Exome Sequencing Identifies Altered Candidate Genes Among 8% of Patients with Undiagnosed Diseases
ORIGINAL RESEARCH ARTICLE Official journal of the American College of Medical Genetics and Genomics Open Candidate-gene criteria for clinical reporting: diagnostic exome sequencing identifies altered candidate genes among 8% of patients with undiagnosed diseases Kelly D. Farwell Hagman, MS, CGC1, Deepali N. Shinde, PhD1, Cameron Mroske, MS1, Erica Smith, PhD1, Kelly Radtke, PhD1, Layla Shahmirzadi, MS, CGC1, Dima El-Khechen, MS, CGC1, Zöe Powis, MS, CGC1, Elizabeth C. Chao, MD, FACMG1,2, Wendy A. Alcaraz, PhD, DABMG1, Katherine L. Helbig, MS, CGC1, Samin A. Sajan, PhD1, Mari Rossi, MS, PhL1, Hsiao-Mei Lu, PhD1, Robert Huether, PhD1, Shuwei Li, PhD1, Sitao Wu, PhD1, Mark E. Nuñes, MD3 and Sha Tang, PhD, FACMG1 Purpose: Diagnostic exome sequencing (DES) is now a commonly corroborated in the peer-reviewed literature. This rate of corrobo- ordered test for individuals with undiagnosed genetic disorders. In ration increased to 51.9% (27/52) among patients whose gene was addition to providing a diagnosis for characterized diseases, exome reported at least 12 months previously. sequencing has the capacity to uncover novel candidate genes for Conclusions: Herein, we provide transparent, comprehensive, and disease. standardized scoring criteria for the clinical reporting of candidate Methods: Family-based DES included analysis of both characterized genes. These results demonstrate that DES is an integral tool for and novel genetic etiologies. To evaluate candidate genes for disease genetic diagnosis, especially for elucidating the molecular basis for in the clinical setting, we developed a systematic, rule-based classifi- both characterized and novel candidate genetic etiologies. Gene dis- cation schema. coveries also advance the understanding of normal human biology and more common diseases. -
Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened.