Genome-Wide Genetic Study in Autoimmune Disease-Prone Mice

2014 ◽  
pp. 111-141
Author(s):  
Masaomi Obata ◽  
Mareki Ohtsuji ◽  
Yukiyasu Iida ◽  
Toshikazu Shirai ◽  
Sachiko Hirose ◽  
...  
Keyword(s):  
Autoimmune Disease ◽  
Genetic Study ◽  
Genome Wide

scholarly journals The genomics of autoimmune disease in the era of genome-wide association studies and beyond

2012 ◽  
Vol 11 (4) ◽  
pp. 267-275 ◽  
Author(s):  
Christopher J. Lessard ◽  
John A. Ice ◽  
Indra Adrianto ◽  
Graham B. Wiley ◽  
Jennifer A. Kelly ◽  
...  
Keyword(s):  
Autoimmune Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Multi-ancestry genetic study in 5,876 patients identifies an association between excitotoxic genes and early outcomes after acute ischemic stroke

2020 ◽  
Author(s):  
Laura Ibanez ◽  
Laura Heitsch ◽  
Caty Carrera ◽  
Fabiana H.G. Farias ◽  
Rajat Dhar ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Genetic Study ◽  
Genetic Architecture ◽  
Stroke Onset ◽  
Neurological Deficits ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Synaptic Protein ◽  
Genome Wide

ABSTRACTDuring the first hours after stroke onset neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between NIH stroke scale (NIHSS) within six hours of stroke onset and NIHSS at 24h (ΔNIHSS). A total of 5,876 individuals from seven countries (Spain, Finland, Poland, United States, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of ΔNIHSS variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture than that of stroke risk. Seven loci (2p25.1, 2q31.2, 2q33.3, 4q34.3, 5q33.2, 6q26 and 7p21.1) were genome-wide significant and explained 2.1% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each loci. eQTL mapping and SMR indicate that ADAM23 (log Bayes Factor (LBF)=6.34) was driving the association for 2q33.3. Gene based analyses suggested that GRIA1 (LBF=5.26), which is predominantly expressed in brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated PARK2 (LBF=5.30) and ABCB5 (LBF=5.70) for the 6q26 and 7p21.1 loci. Human brain single nuclei RNA-seq indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a pre-synaptic protein, and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provides the first evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischemic stroke.RESEARCH INTO CONTEXTEvidence before this studyNo previous genome-wide association studies have investigated the genetic architecture of early outcomes after ischemic stroke.Added Value of this studyThis is the first study that investigated genetic influences on early outcomes after ischemic stroke using a genome-wide approach, revealing seven genome-wide significant loci. A unique aspect of this genetic study is the inclusion of all of the major ethnicities by recruiting from participants throughout the world. Most genetic studies to date have been limited to populations of European ancestry.Implications of all available evidenceThe findings provide the first evidence that genes implicating excitotoxicity contribute to human acute ischemic stroke, and demonstrates proof of principle that GWAS of acute ischemic stroke patients can reveal mechanisms involved in ischemic brain injury.

scholarly journals Using eQTL weights to improve power for genome-wide association studies: a genetic study of childhood asthma

2013 ◽  
Vol 4 ◽  
Author(s):  
Lin Li ◽  
Michael Kabesch ◽  
Emmanuelle Bouzigon ◽  
Florence Demenais ◽  
Martin Farrall ◽  
...  
Keyword(s):  
Genetic Study ◽  
Childhood Asthma ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Evidence for a potential role of miR-1908-5p and miR-3614-5p in autoimmune disease risk using genome-wide analyses

2018 ◽  
Author(s):  
Inken Wohlers ◽  
Lars Bertram ◽  
Christina M. Lill
Keyword(s):  
Autoimmune Disease ◽  
Autoimmune Diseases ◽  
Disease Risk ◽  
Association Studies ◽  
Microrna Expression ◽  
Next Generation Sequencing Data ◽  
Genome Wide Association Studies ◽  
Functional Variants ◽  
Genome Wide

AbstractGenome-wide association studies (GWAS) have identified a large number of genetic risk loci for autoimmune diseases. However, the functional variants underlying these disease associations remain largely unknown. There is evidence that microRNA-mediated regulation may play an important role in this context. Therefore, we assessed whether autoimmune disease loci unfold their effects via altering microRNA expression in relevant immune cells.To this end, we performed microRNA expression quantitative trait loci (eQTL) analyses across 115 GWAS regions associated with 12 autoimmune diseases using next-generation sequencing data of 345 lymphoblastoid cell lines. Statistical analyses included the application and extension of a recently proposed framework (joint likelihood mapping), to microRNA expression data and microRNA target gene enrichment analyses of relevant GWAS data.Overall, only a minority of autoimmune disease risk loci may exert their pathophysiologic effects by altering miRNA expression based on JLIM. However, detailed functional fine-mapping revealed two independent GWAS regions harboring autoimmune disease risk SNPs with significant effects on microRNA expression. These relate to SNPs associated with Crohn’s disease (CD; rs102275) and rheumatoid arthritis (RA; rs968567), which affect the expression of miR-1908-5p (prs102275=1.44e-20, prs968567=2.54e-14). In addition, an independent CD risk SNP, rs3853824, was found to alter the expression of miR-3614-5p (p=5.70e-7). To support these findings, we demonstrate that GWAS signals for RA and CD were enriched in genes predicted to be targeted by both miRNAs (all with p<0.05).In summary, our study points towards a pathophysiological role of miR-1908-5p and miR- 3614-5p in autoimmunity.

scholarly journals Validating Online Measures of Cognitive Ability in Genes for Good, a Genetic Study of Health and Behavior

Assessment ◽  
2017 ◽  
Vol 27 (1) ◽  
pp. 136-148 ◽  
Author(s):  
MengZhen Liu ◽  
Gianna Rea-Sandin ◽  
Johanna Foerster ◽  
Lars Fritsche ◽  
Katharine Brieger ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Cognitive Ability ◽  
Genetic Study ◽  
Fluid Intelligence ◽  
Five Factor Model ◽  
Association Studies ◽  
Cognitive Measures ◽  
Polygenic Score ◽  
Genome Wide ◽  
A Genome

Genetic association studies routinely require many thousands of participants to achieve sufficient power, yet accumulation of large well-assessed samples is costly. We describe here an effort to efficiently measure cognitive ability and personality in an online genetic study, Genes for Good. We report on the first 21,550 participants with relevant phenotypic data, 7,458 of whom have been genotyped genome-wide. Measures of crystallized and fluid intelligence reflected a two-dimensional latent ability space, with items demonstrating adequate item-level characteristics. The Big Five Inventory questionnaire revealed the expected five-factor model of personality. Cognitive measures predicted educational attainment over and above personality characteristics, as expected. We found that a genome-wide polygenic score of educational attainment predicted educational level, accounting for 4%, 4%, and 2.7% of the variance in educational attainment, verbal reasoning, and spatial reasoning, respectively. In summary, the online cognitive measures in Genes for Good appear to perform adequately and demonstrate expected associations with personality, education, and an education-based polygenic score. Results indicate that online cognitive assessment is one avenue to accumulate large samples of individuals for genetic research of cognitive ability.

scholarly journals POS0350 EPIONE APPLICATION: AN INTEGRATED GENOTYPE ANALYSIS WEB SERVER FOR CLINICAL GENOMICS IN SYSTEMIC LUPUS ERYTHEMATOSUS (SLE)

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 405-405
Author(s):  
L. Papageorgiou ◽  
H. Alkenaris ◽  
M. Zervou ◽  
D. Vlachakis ◽  
G. Goulielmos ◽  
...  
Keyword(s):  
Data Mining ◽  
Autoimmune Disease ◽  
Association Studies ◽  
Genomic Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Gene Variants ◽  
Clinical Genomics ◽  
Patient Profile ◽  
Genome Wide

Background:Genome wide association studies (GWAS) have successfully identified novel autoimmune disease-associated loci, with many of them shared by multiple disease-associated pathways but much of the genetics and pathophysiological mechanisms remain still obscure [1-3]. SLE is a chronic, highly heterogeneous autoimmune disease, characterized by differences in autoantibody profile, serum cytokines, and a multi-system involvement [4]. Epione Application is an integrated bioinformatics web-tool designed to assist medical experts and researchers in the process of diagnosing SLE [5].Objectives:To identify the most credible gene variants and single nucleotide polymorphisms (SNPs), causing SLE using the genomic data provided for the patient and aid the medical expert in SLE diagnosis [5].Methods:In the present study, we have analyzed more than 70.000 SLE-related publications using data mining and semantic techniques towards extracting the SLE -related genes and SNPs [6]. The extracted knowledge has been filtered, evaluated, annotated, classified, and stored in the Epione Application Database (EAD) (Figure 1). Moreover, an updated gene regulatory network with the genes implements in SLE has been estimated [7]. This was followed by the design and development of the Epione application, in which the generated datasets and results were included. The application has been tested and presented here with WES data from several related patients with SLE [8].Results:SLE-related SNPs and variants identified in genome-wide association studies (GWAS), whole-genome (WGS), whole-exome (WES), or targeted sequencing information are classified, annotated, and analyzed in an integrated patient profile with clinical significance information. Probable genes associated with the patient’s genomic profile are visualized with several graphs, including chromosome ideograms, statistic bars, and regulatory networks through data mining studies with relative publications, to obtain a representative number of the most credible candidate genes and biological pathways associated with the SLE. An evaluation study was performed on 7 patients from a three-generation family with SLE [9]. All the recognized gene variants that were previously considered SLE-associated were properly identified in the output profile per patient, and by comparing the results, new findings have emerged.Conclusion:The Epione application was designed to assist medical doctor diagnosis from the early stages by using the patients’ genomic data [5, 8, 10]. Its diagnosis-oriented output presents the patient profile through which the user is provided with a structured set of results in various categories, which are generated based on the list of the most predictable candidate gene variants related to SLE. This novel and accessible webserver tool of SLE to assist medical experts in the clinical genomics and precision medicine procedure is available at http://143.233.188.162/epione/.References:[1]Molineros JE et al. (2017). Hum Mol Genet 26:1205-1216.[2]Sciascia S et al. (2018). F1000 Res, 2018:1-17.[3]Gonzalez-Serna D et al. (2020). Sci Rep 10:1862.[4]Harley JB et al. (2006). Springer Semin Immun 28:119–130.[5]Goulielmos GN et al. (2018). Gene 668:59-72.[6]Zhao Y et al. (2020). Front Genet 11:400.[7]Song YL and Chen S (2009). Interdiscip Sci 1:179-186.[8]Koile D et al. (2018). BMC Bioinformatics 19:25.[9]Albertsen HM et al. (2019). Mol Med Rep 19:1716-1720.[10]Ebrahimiyan H et al. (2018). Meta Gene 16:241-247.Figure 1.The Epione application database (EAD) for SLE.Disclosure of Interests:None declared

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