Using Human Genetics to Understand Mechanisms in Ischemic Stroke Outcome: From Early Brain Injury to Long-Term Recovery

Stroke ◽  
2021 ◽  
Author(s):  
Jin-Moo Lee ◽  
Israel Fernandez-Cadenas ◽  
Arne G. Lindgren

There is a critical need to elucidate molecular mechanisms underlying brain injury, repair, and recovery following ischemic stroke—a global health problem with major social and economic impact. Despite 5 decades of intensive research, there are no widely accepted neuroprotective drugs that mitigate ischemic brain injury, or neuroreparative drugs, or personalized approaches that guide therapies to enhance recovery. We here explore novel reverse translational approaches that will complement traditional forward translational methods in identifying mechanisms relevant to human stroke outcome. Although genome-wide association studies have yielded over 30 genetic loci that influence ischemic stroke risk, only a few genome-wide association studies have been performed for stroke outcome. We discuss important considerations for genetic studies of ischemic stroke outcome—including carefully designed phenotypes that capture injury/recovery mechanisms, anchored in time to stroke onset. We also address recent genome-wide association studies that provide insight into mechanisms underlying brain injury and repair. There are several ongoing initiatives exploring genomic associations with novel phenotypes related to stroke outcome. To improve the understanding of the genetic architecture of ischemic stroke outcome, larger studies using standardized phenotypes, preferably embedded in standard-of-care measures, are needed. Novel techniques beyond genome-wide association studies—including exploiting informatics, multi-omics, and novel analytics—promise to uncover genetic and molecular pathways from which drug targets and other new interventions may be identified.

2017 ◽  
Vol 242 (13) ◽  
pp. 1325-1334 ◽  
Author(s):  
Yizhou Zhu ◽  
Cagdas Tazearslan ◽  
Yousin Suh

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.


2021 ◽  
Author(s):  
Chun Chieh Fan ◽  
Robert Loughnan ◽  
Diliana Pechva ◽  
Chi-Hua Chen ◽  
Donald Hagler ◽  
...  

It is important to understand the molecular determinants for microstructures of human brain. However, past genome-wide association studies (GWAS) on microstructures of human brain have had limited results due to methodological constraints. Here, we adopt advanced imaging processing methods and multivariate GWAS on two large scale imaging genetic datasets (UK Biobank and Adolescent Brain Cognitive Development study) to identify and validate key genetic association signals. We discovered 503 unique genetic loci that explained more than 50% of the average heritability across imaging features sensitive to tissue compartments. The genome-wide signals are strongly overlapped with neuropsychiatric diseases, cognitive functions, risk tolerance, and immune responses. Our results implicate the shared molecular mechanisms between tissue microstructures of brain and neuropsychiatric outcomes with astrocyte involvement in the early developmental stage.


Stroke ◽  
2020 ◽  
Vol 51 (12) ◽  
pp. 3751-3755
Author(s):  
Jiang Li ◽  
Vida Abedi ◽  
Ramin Zand ◽  
Christoph J. Griessenauer ◽  

Background and Purpose: The purpose of this study was to replicate the top loci associated with white matter hyperintensity (WMH) phenotypes identified by large genome-wide association studies and the loci identified from the previous candidate gene studies. Methods: A total of 946 Geisinger MyCode patients with acute ischemic stroke with validated European ancestry and magnetic resonance imaging data were included in this study. Log-transformed WMH volume, as a quantitative trait, was calculated by a fully automated quantification process. The genome-wide association studies was carried out by a linear mixed regression model (GEMMA). A candidate-single nucleotide polymorphism analysis by including known single nucleotide polymorphisms, reported from a meta-analysis and several large GWAS for WMH, was conducted in all cases and binary converted extreme cases. Results: No genome-wide significantly associated variants were identified. In a candidate-single nucleotide polymorphism study, rs9515201 ( COL4A2 ) and rs3744028 ( TRIM65 ), 2 known genetic loci, showed nominal or trend of association with the WMH volume (β=0.13 and P =0.001 for rs9515201; β=0.094 and P =0.094 for rs3744028), and replicated in a subset of extreme cases versus controls (odds ratio=1.78, P =7.74×10 − 4 for rs9515201; odds ratio=1.53, P =0.047 for rs3744028, respectively). MTHFR677 cytosine/thymine (rs1801133) also showed an association with the binary WMH with odds ratio=1.47 for T allele ( P =0.019). Conclusions: Replication of COL4A1/2 associated with WMH reassures that the genetic risk factors for monogenic and polygenic ischemic stroke are shared at gene level.


Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 440
Author(s):  
Carina Mauersberger ◽  
Heribert Schunkert ◽  
Hendrik B. Sager

Although the importance of inflammation in atherosclerosis is now well established, the exact molecular processes linking inflammation to the development and course of the disease are not sufficiently understood. In this context, modern genetics—as applied by genome-wide association studies (GWAS)—can serve as a comprehensive and unbiased tool for the screening of potentially involved pathways. Indeed, a considerable proportion of loci discovered by GWAS is assumed to affect inflammatory processes. Despite many well-replicated association findings, however, translating genomic hits to specific molecular mechanisms remains challenging. This review provides an overview of the currently most relevant inflammation-related GWAS findings in coronary artery disease and explores their potential clinical perspectives.


2021 ◽  
Author(s):  
Ying Xiong ◽  
Susanna Kullberg ◽  
Lori Garman ◽  
Nathan Pezant ◽  
David Ellinghaus ◽  
...  

Abstract Background: Sex differences in the susceptibility of sarcoidosis are unknown. The study aims to identify sex-dependent genetic variations in two sarcoidosis clinical phenotypes: Löfgren's syndrome (LS) and non- Löfgren's syndrome (non-LS).Methods: A meta-analysis of genome-wide association studies was conducted in Europeans and African Americans, totaling 10,103 individuals from three population-based cohorts, Sweden (n = 3,843), Germany (n = 3,342), and the United States (n = 2,918), followed by replication look-up in the UK Biobank (n = 387,945). A genome-wide association study based on Immunochip data consisting of 141,000 single nucleotide polymorphisms (SNPs) was conducted in males and females in each cohort, respectively. The association test was based on logistic regression using the additive model in LS and non-LS independently. Additionally, gene-based analysis, expression quantitative trait loci (eQTL) assessments, and enrichment analysis were performed to discover functionally relevant mechanisms related to biological sex. Results: In LS sarcoidosis, we identified various sex-dependent genetic variations (798 SNPs in males and 703 SNPs in females). Genetic findings in sex groups were explicitly located in the extended major histocompatibility complex. In non-LS, we detected 16 SNPs in males and 38 in females, primarily localized to the MHC class II region. Additionally, the ANXA11 gene, a well-documented locus in sarcoidosis, was associated exclusively with non-LS males. Gene-based, eQTL assessment and enrichment analyses revealed distinct sex-dependent genomic loci and gene expression variation in the sex groups. Conclusions: Our findings provide new evidence of the existence of sex-dependent genetic variations underlying sarcoidosis genetic architecture. These findings suggest a sex bias in molecular mechanisms of sarcoidosis.


2016 ◽  
Author(s):  
Robert A. Power ◽  
Julian Parkhill ◽  
Tulio de Oliveira

AbstractThe reduced costs of sequencing have led to the availability of whole genome sequences for a large number of microorganisms, enabling the application of microbial genome wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS is likely to further advance our understanding of infectious diseases. By building on the success of GWAS, microbial GWAS have the potential to rapidly provide important insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this review, we outline the methodologies of GWAS, the state of the field of microbial GWAS today, and how lessons from GWAS can direct the future of the field.


2015 ◽  
Author(s):  
Christian Benner ◽  
Chris C.A. Spencer ◽  
Samuli Ripatti ◽  
Matti Pirinen

Motivation: The goal of fine-mapping in genomic regions associated with complex diseases and traits is to identify causal variants that point to molecular mechanisms behind the associations. Recent fine-mapping methods using summary data from genome-wide association studies rely on exhaustive search through all possible causal configurations, which is computationally expensive. Results: We introduce FINEMAP, a software package to efficiently explore a set of the most important causal configurations of the region via a shotgun stochastic search algorithm. We show that FINEMAP produces accurate results in a fraction of processing time of existing approaches and is therefore a promising tool for analyzing growing amounts of data produced in genome-wide association studies. Availability: FINEMAP v1.0 is freely available for Mac OS X and Linux at http://www.christianbenner.com.


2020 ◽  
Vol 21 (9) ◽  
pp. 615-625
Author(s):  
Jacqueline Zayas ◽  
Sisi Qin ◽  
Jia Yu ◽  
James N Ingle ◽  
Liewei Wang

Breast cancer is the most common invasive cancer in women worldwide. Functional follow-up of breast cancer genome-wide association studies has led to the discovery of genes that regulate endocrine therapy response in a SNP- and drug-dependent manner. Here, we will present four examples in which functional genomic studies from breast cancer clinical trials led to novel pharmacogenomic insights and molecular mechanisms of selective estrogen receptor modulators and aromatase inhibitors. The approach utilized for studying genetic variability described in this review offers substantial potential for meaningful discoveries that move the field toward precision medicine for patients.


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