Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk

Abstract Alzheimer’s disease (AD) is the most common type of dementia, affecting millions of people worldwide; however, no disease-modifying treatments are currently available. Genome-wide association studies (GWASs) have identified more than 40 loci associated with AD risk. However, most of the dis...

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Main Authors: Gloriia Novikova, Shea J. Andrews, Alan E. Renton, Edoardo Marcora
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Molecular Neurodegeneration
Subjects:
Online Access:https://doi.org/10.1186/s13024-021-00449-0
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spelling doaj-5e01f228869c40fe8c9360db728db89c2021-04-25T11:28:13ZengBMCMolecular Neurodegeneration1750-13262021-04-0116111310.1186/s13024-021-00449-0Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease riskGloriia Novikova0Shea J. Andrews1Alan E. Renton2Edoardo Marcora3Ronald M. Loeb Center for Alzheimer’s Disease, Department of Neuroscience, Icahn School of Medicine at Mount SinaiRonald M. Loeb Center for Alzheimer’s Disease, Department of Neuroscience, Icahn School of Medicine at Mount SinaiRonald M. Loeb Center for Alzheimer’s Disease, Department of Neuroscience, Icahn School of Medicine at Mount SinaiRonald M. Loeb Center for Alzheimer’s Disease, Department of Neuroscience, Icahn School of Medicine at Mount SinaiAbstract Alzheimer’s disease (AD) is the most common type of dementia, affecting millions of people worldwide; however, no disease-modifying treatments are currently available. Genome-wide association studies (GWASs) have identified more than 40 loci associated with AD risk. However, most of the disease-associated variants reside in non-coding regions of the genome, making it difficult to elucidate how they affect disease susceptibility. Nonetheless, identification of the regulatory elements, genes, pathways and cell type/tissue(s) impacted by these variants to modulate AD risk is critical to our understanding of disease pathogenesis and ability to develop effective therapeutics. In this review, we provide an overview of the methods and approaches used in the field to identify the functional effects of AD risk variants in the causal path to disease risk modification as well as describe the most recent findings. We first discuss efforts in cell type/tissue prioritization followed by recent progress in candidate causal variant and gene nomination. We discuss statistical methods for fine-mapping as well as approaches that integrate multiple levels of evidence, such as epigenomic and transcriptomic data, to identify causal variants and risk mechanisms of AD-associated loci. Additionally, we discuss experimental approaches and data resources that will be needed to validate and further elucidate the effects of these variants and genes on biological pathways, cellular phenotypes and disease risk. Finally, we discuss future steps that need to be taken to ensure that AD GWAS functional mapping efforts lead to novel findings and bring us closer to finding effective treatments for this devastating disease.https://doi.org/10.1186/s13024-021-00449-0Alzheimer’s diseaseMyeloid cellsFunctional genomicsFine-mapping methodsNon-coding variantsGene prioritization
collection DOAJ
language English
format Article
sources DOAJ
author Gloriia Novikova
Shea J. Andrews
Alan E. Renton
Edoardo Marcora
spellingShingle Gloriia Novikova
Shea J. Andrews
Alan E. Renton
Edoardo Marcora
Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk
Molecular Neurodegeneration
Alzheimer’s disease
Myeloid cells
Functional genomics
Fine-mapping methods
Non-coding variants
Gene prioritization
author_facet Gloriia Novikova
Shea J. Andrews
Alan E. Renton
Edoardo Marcora
author_sort Gloriia Novikova
title Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk
title_short Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk
title_full Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk
title_fullStr Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk
title_full_unstemmed Beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate Alzheimer’s disease risk
title_sort beyond association: successes and challenges in linking non-coding genetic variation to functional consequences that modulate alzheimer’s disease risk
publisher BMC
series Molecular Neurodegeneration
issn 1750-1326
publishDate 2021-04-01
description Abstract Alzheimer’s disease (AD) is the most common type of dementia, affecting millions of people worldwide; however, no disease-modifying treatments are currently available. Genome-wide association studies (GWASs) have identified more than 40 loci associated with AD risk. However, most of the disease-associated variants reside in non-coding regions of the genome, making it difficult to elucidate how they affect disease susceptibility. Nonetheless, identification of the regulatory elements, genes, pathways and cell type/tissue(s) impacted by these variants to modulate AD risk is critical to our understanding of disease pathogenesis and ability to develop effective therapeutics. In this review, we provide an overview of the methods and approaches used in the field to identify the functional effects of AD risk variants in the causal path to disease risk modification as well as describe the most recent findings. We first discuss efforts in cell type/tissue prioritization followed by recent progress in candidate causal variant and gene nomination. We discuss statistical methods for fine-mapping as well as approaches that integrate multiple levels of evidence, such as epigenomic and transcriptomic data, to identify causal variants and risk mechanisms of AD-associated loci. Additionally, we discuss experimental approaches and data resources that will be needed to validate and further elucidate the effects of these variants and genes on biological pathways, cellular phenotypes and disease risk. Finally, we discuss future steps that need to be taken to ensure that AD GWAS functional mapping efforts lead to novel findings and bring us closer to finding effective treatments for this devastating disease.
topic Alzheimer’s disease
Myeloid cells
Functional genomics
Fine-mapping methods
Non-coding variants
Gene prioritization
url https://doi.org/10.1186/s13024-021-00449-0
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