scholarly journals The length of the expressed 3’ UTR is an intermediate molecular phenotype linking genetic variants to complex diseases

2019 ◽  
Author(s):  
Elisa Mariella ◽  
Federico Marotta ◽  
Elena Grassi ◽  
Stefano Gilotto ◽  
Paolo Provero
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Alternative Polyadenylation ◽  
Complex Diseases ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Transcriptional Regulatory Mechanism ◽  
Transcriptional Regulatory ◽  
Common Genetic Variants ◽  
Molecular Phenotypes

AbstractIn the last decades, genome wide association studies (GWAS) have uncovered tens of thousands of associations between common genetic variants and complex diseases. However, these statistical associations can rarely be interpreted functionally and mechanistically. As the majority of the disease-associated variants are located far from coding sequences, even the relevant gene is often unclear. A way to gain insight into the relevant mechanisms is to study the genetic determinants of intermediate molecular phenotypes, such as gene expression and transcript structure. We propose a computational strategy to discover genetic variants affecting the relative expression of alternative 3’ untranslated region (UTR) isoforms, generated through alternative polyadenylation, a widespread post-transcriptional regulatory mechanism known to have relevant functional consequences. When applied to a large dataset in which whole genome and RNA sequencing data are available for 373 European individuals, 2,530 genes with alternative polyadenylation quantitative trait loci (apaQTL) were identified. We analyze and discuss possible mechanisms of action of these variants, and we show that they are significantly enriched in GWAS hits, in particular those concerning immune-related and neurological disorders. Our results point to an important role for genetically determined alternative polyadenylation in affecting predisposition to complex diseases, and suggest new ways to extract functional information from GWAS data.

scholarly journals Association of common genetic variants with brain microbleeds

Neurology ◽  
2020 ◽  
Vol 95 (24) ◽  
pp. e3331-e3343 ◽  
Author(s):  
Maria J. Knol ◽  
Dongwei Lu ◽  
Matthew Traylor ◽  
Hieab H.H. Adams ◽  
José Rafael J. Romero ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Small Vessel Disease ◽  
Association Studies ◽  
Cerebral Small Vessel Disease ◽  
Small Vessel ◽  
White Matter Hyperintensity ◽  
Genome Wide Association Studies ◽  
Vessel Disease ◽  
Genome Wide ◽  
Common Genetic Variants

ObjectiveTo identify common genetic variants associated with the presence of brain microbleeds (BMBs).MethodsWe performed genome-wide association studies in 11 population-based cohort studies and 3 case–control or case-only stroke cohorts. Genotypes were imputed to the Haplotype Reference Consortium or 1000 Genomes reference panel. BMBs were rated on susceptibility-weighted or T2*-weighted gradient echo MRI sequences, and further classified as lobar or mixed (including strictly deep and infratentorial, possibly with lobar BMB). In a subset, we assessed the effects of APOE ε2 and ε4 alleles on BMB counts. We also related previously identified cerebral small vessel disease variants to BMBs.ResultsBMBs were detected in 3,556 of the 25,862 participants, of which 2,179 were strictly lobar and 1,293 mixed. One locus in the APOE region reached genome-wide significance for its association with BMB (lead single nucleotide polymorphism rs769449; odds ratio [OR]any BMB [95% confidence interval (CI)] 1.33 [1.21–1.45]; p = 2.5 × 10−10). APOE ε4 alleles were associated with strictly lobar (OR [95% CI] 1.34 [1.19–1.50]; p = 1.0 × 10−6) but not with mixed BMB counts (OR [95% CI] 1.04 [0.86–1.25]; p = 0.68). APOE ε2 alleles did not show associations with BMB counts. Variants previously related to deep intracerebral hemorrhage and lacunar stroke, and a risk score of cerebral white matter hyperintensity variants, were associated with BMB.ConclusionsGenetic variants in the APOE region are associated with the presence of BMB, most likely due to the APOE ε4 allele count related to a higher number of strictly lobar BMBs. Genetic predisposition to small vessel disease confers risk of BMB, indicating genetic overlap with other cerebral small vessel disease markers.

scholarly journals Contributions of common genetic variants to risk of schizophrenia among individuals of African and Latino ancestry

2019 ◽  
Vol 25 (10) ◽  
pp. 2455-2467 ◽  
Author(s):  
Tim B. Bigdeli ◽  
◽  
Giulio Genovese ◽  
Penelope Georgakopoulos ◽  
Jacquelyn L. Meyers ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Large Fraction ◽  
African Ancestry ◽  
Common Variant ◽  
Human Populations ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Common Genetic Variants

Abstract Schizophrenia is a common, chronic and debilitating neuropsychiatric syndrome affecting tens of millions of individuals worldwide. While rare genetic variants play a role in the etiology of schizophrenia, most of the currently explained liability is within common variation, suggesting that variation predating the human diaspora out of Africa harbors a large fraction of the common variant attributable heritability. However, common variant association studies in schizophrenia have concentrated mainly on cohorts of European descent. We describe genome-wide association studies of 6152 cases and 3918 controls of admixed African ancestry, and of 1234 cases and 3090 controls of Latino ancestry, representing the largest such study in these populations to date. Combining results from the samples with African ancestry with summary statistics from the Psychiatric Genomics Consortium (PGC) study of schizophrenia yielded seven newly genome-wide significant loci, and we identified an additional eight loci by incorporating the results from samples with Latino ancestry. Leveraging population differences in patterns of linkage disequilibrium, we achieve improved fine-mapping resolution at 22 previously reported and 4 newly significant loci. Polygenic risk score profiling revealed improved prediction based on trans-ancestry meta-analysis results for admixed African (Nagelkerke’s R2 = 0.032; liability R2 = 0.017; P < 10−52), Latino (Nagelkerke’s R2 = 0.089; liability R2 = 0.021; P < 10−58), and European individuals (Nagelkerke’s R2 = 0.089; liability R2 = 0.037; P < 10−113), further highlighting the advantages of incorporating data from diverse human populations.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals Lipid associated polygenic enrichment in Alzheimer’s disease

2018 ◽  
Author(s):  
Iris J. Broce ◽  
Chin Hong Tan ◽  
Chun Chieh Fan ◽  
Aree Witoelar ◽  
Natalie Wen ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Variants ◽  
Plasma Lipids ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Genetic Pleiotropy ◽  
Common Genetic Variants

ABSTRACTCardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimer’s disease (AD) pathogenesis. Beyond the ∊4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimer’s risk.

scholarly journals The genetic architecture of medication-use

2020 ◽  
Author(s):  
Palle Duun Rohde ◽  
Peter Sørensen ◽  
Mette Nyegaard
Keyword(s):  
Medical Treatment ◽  
Allele Frequency ◽  
Minor Allele Frequency ◽  
Genetic Variants ◽  
Genetic Architecture ◽  
Association Studies ◽  
Medication Use ◽  
Minor Allele ◽  
Genome Wide Association Studies ◽  
Common Genetic Variants

AbstractGenomics has been forecasted to revolutionise human health by improving medical treatment through a better understanding of the molecular mechanisms of human diseases. Despite great successes of the last decade’s genome-wide association studies (GWAS), the results have to a limited extent been translated to genomic medicine. We propose, that one route to get closer to improved medical treatment is by understanding the genetics of medication-use. Here we obtained entire medication profiles from 335,744 individuals from the UK Biobank and performed a GWAS to identify which common genetic variants are major drivers of medication-use. We analysed 9 million imputed genetic variants, estimated SNP heritability, partitioned the genomic variance across functional categories, and constructed genetic scores for medication-use. In total, 59 independent loci were identified for medication-use and approximately 18% of the total variation was attributable to common genetic (minor allele frequency >0.01) variants. The largest fraction of variance was captured by variants with low to medium minor allele frequency. In particular coding and conserved regions, as well as transcription start sites, displayed significantly enrichment of heritability. The average correlation between medication-use and predicted genetic scores was 0.14. These results demonstrate that medication-use per se is a highly polygenic complex trait and that individuals with higher genetic liability are on average more diseased and have a higher risk for adverse drug reactions. These results provide an insight into the genetic architecture of medication use and pave the way for developments of multicomponent genetic risk models that includes the genetically informed medication-use.

scholarly journals Schizophrenia risk from locus-specific human endogenous retroviruses

2019 ◽  
Author(s):  
Rodrigo R.R. Duarte ◽  
Matthew L. Bendall ◽  
Miguel de Mulder ◽  
Christopher E. Ormsby ◽  
Greta A. Beckerle ◽  
...  
Keyword(s):  
Association Studies ◽  
Endogenous Retroviruses ◽  
Substantial Contribution ◽  
Genome Wide Association Studies ◽  
Sequencing Data ◽  
Human Endogenous Retroviruses ◽  
Risk Variants ◽  
Repetitive Nature ◽  
Common Genetic Variants ◽  
Dorsolateral Prefrontal

AbstractSchizophrenia genome-wide association studies highlight the substantial contribution of risk attributed to the non-coding genome where human endogenous retroviruses (HERVs) are encoded. These ancient viral elements have previously been overlooked in genetic and transcriptomic studies due to their poor annotation and repetitive nature. Using a new, comprehensive HERV annotation, we found that the fraction of the genome where HERVs are located (the ‘retrogenome’) is enriched for schizophrenia risk variants, and that there are 148 disparate HERVs involved in susceptibility. Analysis of RNA-sequencing data from the dorsolateral prefrontal cortex of 259 schizophrenia cases and 279 controls from the CommonMind Consortium showed that HERVs are actively expressed in the brain (n = 3,979), regulated in cis by common genetic variants (n = 1,759), and differentially expressed in patients (n = 81). Convergent analyses implicate LTR25_6q21 and ERVLE_8q24.3h as HERVs of etiological relevance to schizophrenia, which are co-regulated with genes involved in neuronal and mitochondrial function, respectively. Our findings provide a strong rationale for exploring the retrogenome and the expression of these locus-specific HERVs as novel risk factors for schizophrenia and potential diagnostic biomarkers and treatment targets.

scholarly journals An integrated platform to systematically identify causal variants and genes for polygenic human traits

2019 ◽  
Author(s):  
Damien J. Downes ◽  
Ron Schwessinger ◽  
Stephanie J. Hill ◽  
Lea Nussbaum ◽  
Caroline Scott ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Significant Proportion ◽  
Genome Wide Association Studies ◽  
Effector Genes ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Integrated Platform ◽  
Causal Variants

ABSTRACTGenome-wide association studies (GWAS) have identified over 150,000 links between common genetic variants and human traits or complex diseases. Over 80% of these associations map to polymorphisms in non-coding DNA. Therefore, the challenge is to identify disease-causing variants, the genes they affect, and the cells in which these effects occur. We have developed a platform using ATAC-seq, DNaseI footprints, NG Capture-C and machine learning to address this challenge. Applying this approach to red blood cell traits identifies a significant proportion of known causative variants and their effector genes, which we show can be validated by direct in vivo modelling.

scholarly journals The Effect of Alterations of Schizophrenia-Associated Genes on Gamma Band Oscillations

2020 ◽  
Author(s):  
Christoph Metzner ◽  
Tuomo Mäki-Marttunen ◽  
Gili Karni ◽  
Hana McMahon-Cole ◽  
Volker Steuber
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Primary Auditory Cortex ◽  
Gamma Band ◽  
Oscillatory Activity ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Common Genetic Variants ◽  
Gamma Power ◽  
Response Task

Abnormalities in the synchronized oscillatory activity of neurons in general and, specifically in the gamma band, might play a crucial role in the pathophysiology of schizophrenia. While these changes in oscillatory activity have traditionally been linked to alterations at the synaptic level, we demonstrate here, using computational modeling, that common genetic variants of ion channels can contribute strongly to this effect. Our model of primary auditory cortex highlights multiple schizophrenia-associated genetic variants that reduce gamma power in an auditory steady-state response task. Furthermore, we show that combinations of several of these schizophrenia-associated variants can produce similar effects as the more traditionally considered synaptic changes. Overall, our study provides a mechanistic link between schizophrenia-associated common genetic variants, as identified by genome-wide association studies, and one of the most robust neurophysiological endophenotypes of schizophrenia.

scholarly journals Gene-Based Association Tests Using GWAS Summary Statistics and Incorporating eQTL

2021 ◽  
Author(s):  
Xuewei Cao ◽  
Xuexia Wang ◽  
Shuanglin Zhang ◽  
Qiuying Sha
Keyword(s):  
Genetic Variants ◽  
Association Studies ◽  
Complex Diseases ◽  
Gaussian Copula ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Association Tests ◽  
Aggregate Information ◽  
Alternative Approach

Abstract Although genome-wide association studies (GWAS) have been successfully applied to a variety of complex diseases and identified many genetic variants underlying complex diseases, there is still a considerable heritability of complex diseases that could not be explained by GWAS. One alternative approach to overcome the missing heritability caused by the genetic heterogeneity is gene-based analysis, which considers the aggregate effects of multiple genetic variants in a single test. Another alternative approach is transcriptome-wide association study (TWAS). TWAS aggregates genomic information into functionally relevant units that map to genes and their expression. TWAS is not only powerful, but can also increase the interpretability in biological mechanisms of identified trait associated genes. In this study, we propose two powerful and computationally efficient gene-based association tests, Overall and Copula. These two tests aggregate information from three traditional types of gene-based association tests and also incorporate expression quantitative trait locus (eQTL) data into GWAS using GWAS summary statistics. Overall utilizes the extended Simes procedure and Copula utilizes the Gaussian copula approximation-based method. We show that after a small number of replications to estimate the correlation among the integrated gene-based tests, the P values of these two methods can be calculated analytically. Simulation studies show that these two tests can control type I error rate very well and have higher power than the tests that we compared. We also apply these two methods to two schizophrenia GWAS summary datasets and two lipids GWAS summary datasets. The results show that these two newly developed methods can identify more significant genes than other methods we compared with.

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