Follow up of schizophrenia gwas based on cognitive performance, high density eeg, and structural brain imaging

2011 ◽  
Vol 26 (S2) ◽  
pp. 2083-2083
Author(s):  
G. Donohoe ◽  
E. Rose ◽  
D. Morris ◽  
A. Hargreaves ◽  
M. Gill ◽  
...  
Keyword(s):  
Cognitive Deficits ◽  
Association Studies ◽  
Structure And Function ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Brain Structure And Function ◽  
And Function ◽  
Healthy Participants

The advent of genome wide association studies have resulted in the identification of a number of novel genetic loci for schizophrenia and related disorders. Understanding the functional impact of these variants on brain structure and function is crucial to understand their role in disease pathology. We presents data based on our genetic and neuropsychological assessment of almost 700 patients and healthy participants for a number of these variants and replication of our findings in independent samples of almost 1500 cases and controls. Specifically, we will use this data to suggest that the risk associated with some genetics variants (e.g. NOS1) is being mediated by an influence on variation in intelligence and other cognitive phenotypes, while other risk variants (e.g. ZNF804A) delineate illness subtypes in which cognitive deficits are a less prominent feature.

scholarly journals Genome-wide association studies of brain structure and function in the UK Biobank

2017 ◽  
Author(s):  
Lloyd T. Elliott ◽  
Kevin Sharp ◽  
Fidel Alfaro-Almagro ◽  
Sinan Shi ◽  
Karla Miller ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Brain Structure ◽  
Association Studies ◽  
Structure And Function ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Brain Structure And Function ◽  
And Function

SummaryThe genetic basis of brain structure and function is largely unknown. We carried out genome-wide association studies of 3,144 distinct functional and structural brain imaging derived phenotypes in UK Biobank (discovery dataset 8,428 subjects). We show that many of these phenotypes are heritable. We identify 148 clusters of SNP-imaging associations with lead SNPs that replicate at p<0.05, when we would expect 21 to replicate by chance. Notable significant and interpretable associations include: iron transport and storage genes, related to changes in T2* in subcortical regions; extracellular matrix and the epidermal growth factor genes, associated with white matter micro-structure and lesion volume; genes regulating mid-line axon guidance development associated with pontine crossing tract organisation; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide new insight into the genetic architecture of the brain with relevance to complex neurological and psychiatric disorders, as well as brain development and aging. The full set of results is available on the interactive Oxford Brain Imaging Genetics (BIG) web browser.

What is the impact of genome-wide supported risk variants for schizophrenia and bipolar disorder on brain structure and function? A systematic review

2015 ◽  
Vol 45 (12) ◽  
pp. 2461-2480 ◽  
Author(s):  
R. Gurung ◽  
D. P. Prata
Keyword(s):  
Bipolar Disorder ◽  
Brain Structure ◽  
Association Studies ◽  
Structure And Function ◽  
Future Research ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Brain Structure And Function ◽  
And Function ◽  
The Impact

The powerful genome-wide association studies (GWAS) revealed common mutations that increase susceptibility for schizophrenia (SZ) and bipolar disorder (BD), but the vast majority were not known to be functional or associated with these illnesses. To help fill this gap, their impact on human brain structure and function has been examined. We systematically discuss this output to facilitate its timely integration in the psychosis research field; and encourage reflection for future research. Irrespective of imaging modality, studies addressing the effect of SZ/BD GWAS risk genes (ANK3, CACNA1C, MHC, TCF4, NRGN, DGKH, PBRM1, NCANandZNF804A) were included. Most GWAS risk variations were reported to affect neuroimaging phenotypes implicated in SZ/BD: white-matter integrity (ANK3andZNF804A), volume (CACNA1CandZNF804A) and density (ZNF804A); grey-matter (CACNA1C, NRGN, TCF4andZNF804A) and ventricular (TCF4) volume; cortical folding (NCAN) and thickness (ZNF804A); regional activation during executive tasks (ANK3, CACNA1C, DGKH, NRGNandZNF804A) and functional connectivity during executive tasks (CACNA1CandZNF804A), facial affect recognition (CACNA1CandZNF804A) and theory-of-mind (ZNF804A); but inconsistencies and non-replications also exist. Further efforts such as standardizing reporting and exploring complementary designs, are warranted to test the reproducibility of these early findings.

scholarly journals The Impact of Genome-Wide Supported Schizophrenia Risk Variants in the Neurogranin Gene on Brain Structure and Function

PLoS ONE ◽  
2013 ◽  
Vol 8 (10) ◽  
pp. e76815 ◽  
Author(s):  
Esther Walton ◽  
Daniel Geisler ◽  
Johanna Hass ◽  
Jingyu Liu ◽  
Jessica Turner ◽  
...  
Keyword(s):  
Brain Structure ◽  
Structure And Function ◽  
Risk Variants ◽  
Genome Wide ◽  
Brain Structure And Function ◽  
And Function ◽  
The Impact

scholarly journals The Parkinson’s Disease GWAS Locus Browser

2020 ◽  
Author(s):  
Francis P. Grenn ◽  
Jonggeol J. Kim ◽  
Mary B. Makarious ◽  
Hirotaka Iwaki ◽  
Anastasia Illarionova ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Large Scale ◽  
Association Studies ◽  
Age At Onset ◽  
Genome Wide Association Studies ◽  
Functional Studies ◽  
Risk Variants ◽  
Genome Wide

AbstractParkinson’s disease (PD) is a neurodegenerative disease with an often complex genetic component identifiable by genome-wide association studies (GWAS). The most recent large scale PD GWASes have identified more than 90 independent risk variants for PD risk and progression across 80 loci. One major challenge in current genomics is identifying the causal gene(s) and variant(s) from each GWAS locus. Here we present a GWAS locus browser application that combines data from multiple databases to aid in the prioritization of genes associated with PD GWAS loci. We included 92 independent genome-wide significant signals from multiple recent PD GWAS studies including the PD risk GWAS, age-at-onset GWAS and progression GWAS. We gathered data for all 2336 genes within 1Mb up and downstream of each variant to allow users to assess which gene(s) are most associated with the variant of interest based on a set of self-ranked criteria. Our aim is that the information contained in this browser (https://pdgenetics.shinyapps.io/GWASBrowser/) will assist the PD research community with the prioritization of genes for follow-up functional studies and as potential therapeutic targets.

scholarly journals The Genetic Basis of Hypertriglyceridemia

2021 ◽  
Vol 23 (8) ◽  
Author(s):  
Germán D. Carrasquilla ◽  
Malene Revsbech Christiansen ◽  
Tuomas O. Kilpeläinen
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Cumulative Effect ◽  
Genome Wide Association Studies ◽  
Genetic Loci ◽  
Risk Variants ◽  
Genome Wide ◽  
Severe Hypertriglyceridemia ◽  
Increased Risk ◽  
Polygenic Scores

Abstract Purpose of Review Hypertriglyceridemia is a common dyslipidemia associated with an increased risk of cardiovascular disease and pancreatitis. Severe hypertriglyceridemia may sometimes be a monogenic condition. However, in the vast majority of patients, hypertriglyceridemia is due to the cumulative effect of multiple genetic risk variants along with lifestyle factors, medications, and disease conditions that elevate triglyceride levels. In this review, we will summarize recent progress in the understanding of the genetic basis of hypertriglyceridemia. Recent Findings More than 300 genetic loci have been identified for association with triglyceride levels in large genome-wide association studies. Studies combining the loci into polygenic scores have demonstrated that some hypertriglyceridemia phenotypes previously attributed to monogenic inheritance have a polygenic basis. The new genetic discoveries have opened avenues for the development of more effective triglyceride-lowering treatments and raised interest towards genetic screening and tailored treatments against hypertriglyceridemia. Summary The discovery of multiple genetic loci associated with elevated triglyceride levels has led to improved understanding of the genetic basis of hypertriglyceridemia and opened new translational opportunities.

scholarly journals Functional genomics of autoimmune diseases

2021 ◽  
pp. annrheumdis-2019-216794
Author(s):  
Akari Suzuki ◽  
Matteo Maurizio Guerrini ◽  
Kazuhiko Yamamoto
Keyword(s):  
Autoimmune Diseases ◽  
Association Studies ◽  
Linkage Disequilibrium Block ◽  
Causal Variant ◽  
Genome Wide Association Studies ◽  
Coding Region ◽  
Risk Variants ◽  
Non Coding Rna ◽  
Genome Wide ◽  
Long Non Coding Rna

For more than a decade, genome-wide association studies have been applied to autoimmune diseases and have expanded our understanding on the pathogeneses. Genetic risk factors associated with diseases and traits are essentially causative. However, elucidation of the biological mechanism of disease from genetic factors is challenging. In fact, it is difficult to identify the causal variant among multiple variants located on the same haplotype or linkage disequilibrium block and thus the responsible biological genes remain elusive. Recently, multiple studies have revealed that the majority of risk variants locate in the non-coding region of the genome and they are the most likely to regulate gene expression such as quantitative trait loci. Enhancer, promoter and long non-coding RNA appear to be the main target mechanisms of the risk variants. In this review, we discuss functional genetics to challenge these puzzles.

scholarly journals Polygenic Susceptibility of Aortic Aneurysms Associates to the Diameter of the Aneurysm Sac: the Aneurysm-Express Biobank Cohort

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Constance J. H. C. M. van Laarhoven ◽  
Jessica van Setten ◽  
Joost A. van Herwaarden ◽  
Gerard Pasterkamp ◽  
Dominique P. V. de Kleijn ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Association Studies ◽  
Significant Risk ◽  
Aortic Aneurysms ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Best Fit ◽  
Genetic Risk Variants

AbstractRecent genome-wide association studies (GWAS) have discovered ten genetic risk variants for abdominal aortic aneurysms (AAA). To what extent these genetic variants contribute to the pathology of aneurysms is yet unknown. The present study aims to investigate whether genetic risk variants are associated with three clinical features: diameter of aneurysm sac, type of artery and aneurysm related-symptoms in aortic and peripheral aneurysm patients. Aneurysm tissue of 415 patients included in the Aneurysm-Express biobank was used. A best-fit polygenic risk score (PRS) based on previous GWAS effect estimates was modeled for each clinical phenotype. The best-fit PRS (including 272 variants at PT = 0.01015) showed a significant correlation with aneurysm diameter (R2 = 0.019, p = 0.001). No polygenic association was found with clinical symptoms or artery type. In addition, the ten genome-wide significant risk variants for AAA were tested individually, but no associations were observed with any of the clinical phenotypes. All models were corrected for confounders and data was normalized. In conclusion, a weighted PRS of AAA susceptibility explained 1.9% of the phenotypic variation (p = 0.001) in diameter in aneurysm patients. Given our limited sample size, future biobank collaborations need to confirm a potential causal role of susceptibility variants on aneurysmal disease initiation and progression.

scholarly journals Genome-wide association studies of cardiac electrical phenotypes

2020 ◽  
Vol 116 (9) ◽  
pp. 1620-1634
Author(s):  
Charlotte Glinge ◽  
Najim Lahrouchi ◽  
Reza Jabbari ◽  
Jacob Tfelt-Hansen ◽  
Connie R Bezzina
Keyword(s):  
Genetic Basis ◽  
Association Studies ◽  
Individual Variability ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
Challenges And Opportunities ◽  
Electrocardiographic Parameters

Abstract The genetic basis of cardiac electrical phenotypes has in the last 25 years been the subject of intense investigation. While in the first years, such efforts were dominated by the study of familial arrhythmia syndromes, in recent years, large consortia of investigators have successfully pursued genome-wide association studies (GWAS) for the identification of single-nucleotide polymorphisms that govern inter-individual variability in electrocardiographic parameters in the general population. We here provide a review of GWAS conducted on cardiac electrical phenotypes in the last 14 years and discuss the implications of these discoveries for our understanding of the genetic basis of disease susceptibility and variability in disease severity. Furthermore, we review functional follow-up studies that have been conducted on GWAS loci associated with cardiac electrical phenotypes and highlight the challenges and opportunities offered by such studies.

Efficient estimation of disease odds ratios for follow-up genetic association studies

2017 ◽  
Vol 28 (7) ◽  
pp. 1927-1941
Author(s):  
Jiyuan Hu ◽  
Wei Zhang ◽  
Xinmin Li ◽  
Dongdong Pan ◽  
Qizhai Li
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Efficient Estimation ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Odds Ratios ◽  
Genome Wide ◽  
Follow Up Studies

In the past decade, genome-wide association studies have identified thousands of susceptible variants associated with complex human diseases and traits. Conducting follow-up genetic association studies has become a standard approach to validate the findings of genome-wide association studies. One problem of high interest in genetic association studies is to accurately estimate the strength of the association, which is often quantified by odds ratios in case-control studies. However, estimating the association directly by follow-up studies is inefficient since this approach ignores information from the genome-wide association studies. In this article, an estimator called GFcom, which integrates information from genome-wide association studies and follow-up studies, is proposed. The estimator includes both the point estimate and corresponding confidence interval. GFcom is more efficient than competing estimators regarding MSE and the length of confidence intervals. The superiority of GFcom is particularly evident when the genome-wide association study suffers from severe selection bias. Comprehensive simulation studies and applications to three real follow-up studies demonstrate the performance of the proposed estimator. An R package, “GFcom”, implementing our method is publicly available at https://github.com/JiyuanHu/GFcom .

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