scholarly journals Ischemic Stroke Genetics: What Is New and How to Apply It in Clinical Practice?

Genes ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 48
Author(s):  
Aleksandra Ekkert ◽  
Aleksandra Šliachtenko ◽  
Julija Grigaitė ◽  
Birutė Burnytė ◽  
Algirdas Utkus ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Association Studies ◽  
Clinical Manifestations ◽  
Clinical Information ◽  
Clinical Work ◽  
Classification Systems ◽  
Risk Scores ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Genetic Causes

The etiology of ischemic stroke is multifactorial. Although receiving less emphasis, genetic causes make a significant contribution to ischemic stroke genesis, especially in early-onset stroke. Several stroke classification systems based on genetic information corresponding to various stroke phenotypes were proposed. Twin and family history studies, as well as candidate gene approach, are common methods to discover genetic causes of stroke, however, both have their own limitations. Genome-wide association studies and next generation sequencing are more efficient, promising and increasingly used for daily diagnostics. Some monogenic disorders, despite covering only about 7% of stroke etiology, may cause well-known clinical manifestations that include stroke. Polygenic disorders are more frequent, causing about 38% of all ischemic strokes, and their identification is a rapidly developing field of modern stroke genetics. Current advances in human genetics provide opportunity for personalized prevention of stroke and novel treatment possibilities. Genetic risk scores (GRS) and extended polygenic risk scores (PRS) estimate cumulative contribution of known genetic factors to a specific outcome of stroke. Combining those scores with clinical information and risk factor profiles might result in better primary stroke prevention. Some authors encourage the use of stroke gene panels for stroke risk evaluation and further stroke research. Moreover, new biomarkers for stroke genetic causes and novel targets for gene therapy are on the horizon. In this article, we summarize the latest evidence and perspectives of ischemic stroke genetics that could be of interest to the practitioner and useful for day-to-day clinical work.

scholarly journals Stroke genetics informs drug discovery and risk prediction across ancestries

2022 ◽  
Author(s):  
Stéphanie Debette ◽  
Aniket Mishra ◽  
Rainer Malik ◽  
Tsuyoshi Hachiya ◽  
Tuuli Jürgenson ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Risk Prediction ◽  
Genetic Risk ◽  
Association Studies ◽  
European Ancestry ◽  
Risk Scores ◽  
Targeted Prevention ◽  
Genome Wide Association Studies ◽  
East Asians ◽  
Better Than

Abstract Previous genome-wide association studies (GWAS) of stroke, the second leading cause of death, have been conducted in populations of predominantly European ancestry.1,2 We undertook cross-ancestry GWAS meta-analyses of stroke and its subtypes in 110,182 stroke patients (33% non-European) and 1,503,898 control individuals of five ancestries from population- and clinic-based studies, nearly doubling the number of cases in previous stroke GWAS. We identified association signals at 89 independent loci, of which 61 were novel. Effect sizes were overall highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis using a novel machine-learning approach,3 transcriptome and proteome-wide association analyses revealed putative causal genes (e.g. SH3PXD2A and FURIN) and variants (e.g. at GRK5 and NOS3). Using a novel three-pronged approach,4 we provided genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWAS with vascular risk factor GWAS (iPGS) showed strong prediction of ischemic stroke risk in European and, for the first time, East-Asian populations.5,6 The iPGS performed better than stroke PGS alone and better than previous best iPGS, in Europeans and East-Asians. Transferability of European-specific iPGS to East-Asians was limited. Stroke genetic risk scores were predictive of ischemic stroke independent of clinical risk factors in 52,600 clinical trial participants with cardiometabolic disease and performed considerably better than previous scores, both in Europeans and East-Asians. Altogether our results provide critical insight to inform biology, reveal potential drug targets for intervention, and provide genetic risk prediction tools across ancestries for targeted prevention.

scholarly journals Genetic architecture of schizophrenia: a review of major advancements

2021 ◽  
pp. 1-10
Author(s):  
Sophie E. Legge ◽  
Marcos L. Santoro ◽  
Sathish Periyasamy ◽  
Adeniran Okewole ◽  
Arsalan Arsalan ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Association Studies ◽  
Copy Number Variants ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Genetic Loci ◽  
Significant Enrichment ◽  
High Heritability ◽  
Coding Variants

Abstract Schizophrenia is a severe psychiatric disorder with high heritability. Consortia efforts and technological advancements have led to a substantial increase in knowledge of the genetic architecture of schizophrenia over the past decade. In this article, we provide an overview of the current understanding of the genetics of schizophrenia, outline remaining challenges, and summarise future directions of research. World-wide collaborations have resulted in genome-wide association studies (GWAS) in over 56 000 schizophrenia cases and 78 000 controls, which identified 176 distinct genetic loci. The latest GWAS from the Psychiatric Genetics Consortium, available as a pre-print, indicates that 270 distinct common genetic loci have now been associated with schizophrenia. Polygenic risk scores can currently explain around 7.7% of the variance in schizophrenia case-control status. Rare variant studies have implicated eight rare copy-number variants, and an increased burden of loss-of-function variants in SETD1A, as increasing the risk of schizophrenia. The latest exome sequencing study, available as a pre-print, implicates a burden of rare coding variants in a further nine genes. Gene-set analyses have demonstrated significant enrichment of both common and rare genetic variants associated with schizophrenia in synaptic pathways. To address current challenges, future genetic studies of schizophrenia need increased sample sizes from more diverse populations. Continued expansion of international collaboration will likely identify new genetic regions, improve fine-mapping to identify causal variants, and increase our understanding of the biology and mechanisms of schizophrenia.

scholarly journals Polygenic Risk Score of Longevity Predicts Longer Survival Across an Age Continuum

2020 ◽  
Author(s):  
Niccolo’ Tesi ◽  
Sven J van der Lee ◽  
Marc Hulsman ◽  
Iris E Jansen ◽  
Najada Stringa ◽  
...  
Keyword(s):  
Older Adults ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Risk Scores ◽  
Human Longevity ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Age Related

Abstract Studying the genome of centenarians may give insights into the molecular mechanisms underlying extreme human longevity and the escape of age-related diseases. Here, we set out to construct polygenic risk scores (PRSs) for longevity and to investigate the functions of longevity-associated variants. Using a cohort of centenarians with maintained cognitive health (N = 343), a population-matched cohort of older adults from 5 cohorts (N = 2905), and summary statistics data from genome-wide association studies on parental longevity, we constructed a PRS including 330 variants that significantly discriminated between centenarians and older adults. This PRS was also associated with longer survival in an independent sample of younger individuals (p = .02), leading up to a 4-year difference in survival based on common genetic factors only. We show that this PRS was, in part, able to compensate for the deleterious effect of the APOE-ε4 allele. Using an integrative framework, we annotated the 330 variants included in this PRS by the genes they associate with. We find that they are enriched with genes associated with cellular differentiation, developmental processes, and cellular response to stress. Together, our results indicate that an extended human life span is, in part, the result of a constellation of variants each exerting small advantageous effects on aging-related biological mechanisms that maintain overall health and decrease the risk of age-related diseases.

scholarly journals Genetic Basis of Mastitis Resistance in Dairy Cattle – A Review / Podstawy Genetyczne Odporności Krów Mlecznych Na Zapalenie Wymienia – Artykuł Przeglądowy

2013 ◽  
Vol 13 (4) ◽  
pp. 663-673 ◽  
Author(s):  
Grażyna Sender ◽  
Agnieszka Korwin-Kossakowska ◽  
Adrianna Pawlik ◽  
Karima Galal Abdel Hameed ◽  
Jolanta Oprządek
Keyword(s):  
Dairy Cattle ◽  
Association Studies ◽  
Genetic Resistance ◽  
Clinical Mastitis ◽  
Future Research ◽  
Complex Nature ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Polygenic Control ◽  
Breeding Programmes

Abstract Mastitis is one of the most important mammary gland diseases impacting lactating animals. Resistance to this disease could be improved by breeding. There are several selection methods for mastitis resistance. To improve the natural genetic resistance of cows in succeeding generations, current breeding programmes use somatic cell count and clinical mastitis cases as resistance traits. However, these methods of selection have met with limited success. This is partly due to the complex nature of the disease. The limited progress in improving udder health by conventional selection procedures requires applying information on molecular markers of mastitis susceptibility in marker-assisted selection schemes. Mastitis is under polygenic control, so there are many genes that control this trait in many loci. This review briefly describes genome-wide association studies which have been carried out to identify quantitative trait loci associated with mastitis resistance in dairy cattle worldwide. It also characterizes the candidate gene approach focus on identifying genes that are strong candidates for the mastitis resistance trait. In the conclusion of the paper we focus our attention on future research which should be conducted in the field of the resistance to mastitis.

scholarly journals Challenges of Adjusting Single-Nucleotide Polymorphism Effect Sizes for Linkage Disequilibrium

2021 ◽  
pp. 1-11
Author(s):  
Valentina Escott-Price ◽  
Karl Michael Schmidt
Keyword(s):  
Linkage Disequilibrium ◽  
Association Studies ◽  
Statistical Significance ◽  
Ordinary Least Squares ◽  
Effect Sizes ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Tikhonov Regularisation

<b><i>Background:</i></b> Genome-wide association studies (GWAS) were successful in identifying SNPs showing association with disease, but their individual effect sizes are small and require large sample sizes to achieve statistical significance. Methods of post-GWAS analysis, including gene-based, gene-set and polygenic risk scores, combine the SNP effect sizes in an attempt to boost the power of the analyses. To avoid giving undue weight to SNPs in linkage disequilibrium (LD), the LD needs to be taken into account in these analyses. <b><i>Objectives:</i></b> We review methods that attempt to adjust the effect sizes (β<i>-</i>coefficients) of summary statistics, instead of simple LD pruning. <b><i>Methods:</i></b> We subject LD adjustment approaches to a mathematical analysis, recognising Tikhonov regularisation as a framework for comparison. <b><i>Results:</i></b> Observing the similarity of the processes involved with the more straightforward Tikhonov-regularised ordinary least squares estimate for multivariate regression coefficients, we note that current methods based on a Bayesian model for the effect sizes effectively provide an implicit choice of the regularisation parameter, which is convenient, but at the price of reduced transparency and, especially in smaller LD blocks, a risk of incomplete LD correction. <b><i>Conclusions:</i></b> There is no simple answer to the question which method is best, but where interpretability of the LD adjustment is essential, as in research aiming at identifying the genomic aetiology of disorders, our study suggests that a more direct choice of mild regularisation in the correction of effect sizes may be preferable.

Stroke Genetics: Turning Discoveries into Clinical Applications

Stroke ◽  
2021 ◽  
Author(s):  
Martin Dichgans ◽  
Nathalie Beaufort ◽  
Stephanie Debette ◽  
Christopher D. Anderson
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Clinical Applications ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Neuroprotective Agents ◽  
Experimental Systems ◽  
Genome Wide ◽  
Rapid Pace

The field of medical and population genetics in stroke is moving at a rapid pace and has led to unanticipated opportunities for discovery and clinical applications. Genome-wide association studies have highlighted the role of specific pathways relevant to etiologically defined subtypes of stroke and to stroke as a whole. They have further offered starting points for the exploration of novel pathways and pharmacological strategies in experimental systems. Mendelian randomization studies continue to provide insights in the causal relationships between exposures and outcomes and have become a useful tool for predicting the efficacy and side effects of drugs. Additional applications that have emerged from recent discoveries include risk prediction based on polygenic risk scores and pharmacogenomics. Among the topics currently moving into focus is the genetics of stroke outcome. While still at its infancy, this field is expected to boost the development of neuroprotective agents. We provide a brief overview on recent progress in these areas.

scholarly journals The migraine–stroke connection: A genetic perspective

Cephalalgia ◽  
2015 ◽  
Vol 36 (7) ◽  
pp. 658-668 ◽  
Author(s):  
Rainer Malik ◽  
Bendik Winsvold ◽  
Eva Auffenberg ◽  
Martin Dichgans ◽  
Tobias Freilinger
Keyword(s):  
Ischemic Stroke ◽  
Vascular Disease ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Familial Hemiplegic Migraine ◽  
Artery Dissection ◽  
Cervical Artery Dissection ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Disease Manifestation

Background A complex relationship between migraine and vascular disease has long been recognized. The pathophysiological basis underlying this correlation is incompletely understood. Aim The aim of this review is to focus on the migraine–vascular disorders connection from a genetic perspective, illustrating potentially shared (molecular) mechanisms. Results We first summarize the clinical presentation and genetic basis of CADASIL and other monogenic vascular syndromes with migraine as a prominent disease manifestation. Based on data from transgenic mouse models for familial hemiplegic migraine, we then discuss cortical spreading depression as a potential mechanistic link between migraine and ischemic stroke. Finally, we review data from genome-wide association studies, with a focus on overlapping findings with cervical artery dissection, ischemic stroke in general and cardiovascular disease. Conclusion A wealth of data supports a genetic link between migraine and vascular disease. Based on growing high-throughput data-sets, new genotyping techniques and in-depth phenotyping, further insights are expected for the future.

scholarly journals An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

2018 ◽  
Author(s):  
Tom G. Richardson ◽  
Sean Harrison ◽  
Gibran Hemani ◽  
George Davey Smith
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Polygenic Risk ◽  
The Uk

AbstractThe age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5×l0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

scholarly journals Polygenic influences associated with adolescent cognitive skills

2021 ◽  
Author(s):  
Brittany L Mitchell ◽  
Narelle K Hansell ◽  
Kerrie McAloney ◽  
Nicholas G. Martin ◽  
Margaret J. Wright ◽  
...  
Keyword(s):  
Mental Health ◽  
Genetic Predisposition ◽  
Prediction Models ◽  
Association Studies ◽  
Developmental Trajectory ◽  
Cognitive Outcomes ◽  
Cognitive Domain ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Negatively Associated

Genes play an important role in children’s cognitive ability through puberty and into adolescence. Recent advances in genomics has enabled us to test the effect of various genetic predispositions on measured cognitive outcomes. Here, we leveraged summary statistics from the most recent genome-wide association studies of eleven cognitive and mental health traits to build polygenic prediction models of measured intelligence and academic achievement in a cohort of Australian adolescent twins (N=2,335, 57% female). Additionally, we tested the association of these polygenic risk scores (PRS) with core academic skills such as the ability to comprehend, structure and sequence, evaluate and assess, communicate, and apply techniques and procedures. We show that PRSs for educational attainment, intelligence and cognitive factors explained up to 10% of the variance in educational achievement and 7% in intelligence test scores in our cohort. Additionally, we found that a genetic predisposition for ADHD was negatively associated with all cognitive outcomes and skills and a genetic predisposition for schizophrenia was negatively associated with performance IQ but no other cognitive domain. In this study, we show the potential value of genotypic data for predicting pupil achievement and cognitive developmental trajectory through puberty and into adolescence. We provide evidence that a genetic vulnerability to some mental health disorders is associated with poorer cognitive and educational outcomes, regardless of whether the individual has developed the disorder.

scholarly journals Fine-tuning Polygenic Risk Scores with GWAS Summary Statistics

2019 ◽  
Author(s):  
Zijie Zhao ◽  
Yanyao Yi ◽  
Yuchang Wu ◽  
Xiaoyuan Zhong ◽  
Yupei Lin ◽  
...  
Keyword(s):  
Association Studies ◽  
Fine Tuning ◽  
Risk Scores ◽  
Training Dataset ◽  
Validation Dataset ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Polygenic Risk ◽  
Model Tuning

AbstractPolygenic risk scores (PRSs) have wide applications in human genetics research. Notably, most PRS models include tuning parameters which improve predictive performance when properly selected. However, existing model-tuning methods require individual-level genetic data as the training dataset or as a validation dataset independent from both training and testing samples. These data rarely exist in practice, creating a significant gap between PRS methodology and applications. Here, we introduce PUMAS (Parameter-tuning Using Marginal Association Statistics), a novel method to fine-tune PRS models using summary statistics from genome-wide association studies (GWASs). Through extensive simulations, external validations, and analysis of 65 traits, we demonstrate that PUMAS can perform a variety of model-tuning procedures (e.g. cross-validation) using GWAS summary statistics and can effectively benchmark and optimize PRS models under diverse genetic architecture. On average, PUMAS improves the predictive R2 by 205.6% and 62.5% compared to PRSs with arbitrary p-value cutoffs of 0.01 and 1, respectively. Applied to 211 neuroimaging traits and Alzheimer’s disease, we show that fine-tuned PRSs will significantly improve statistical power in downstream association analysis. We believe our method resolves a fundamental problem without a current solution and will greatly benefit genetic prediction applications.

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