Genetics of Alzheimer’s Disease

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: closed (20 May 2021) | Viewed by 37349

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Guest Editor
1. Department of Psychiatry, Washington University in Saint Louis School of Medicine, 4444 Forest Park, Campus Box 8134, Saint Louis, MO, 63110, USA
2. NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, 63110, USA
3. Department of Neurology, Washington University in Saint Louis School of Medicine, Saint Louis, MO, 63110, USA
Interests: biomarkers; dementia; genetics; stroke; bioinformatics
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Guest Editor
1. Department of Pathology and Laboratory Medicine, University of Kentucky, Lexington, KY, 40536 USA
2. Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY 40536, USA
3. Division of Biomedical Informatics, Department of Internal Medicine, University of Kentucky, Lexington, KY, 40536, USA
4. Department of Microbiology, Immunology, and Molecular Genetics, University of Kentucky, Lexington, KY, 40536 USA
Interests: bioinformatics; Alzheimer’s disease; genetics; evolution; machine learning; algorithms; pedigree analysis; rare variant analysis; codon usage bias; synonymous variation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Alzheimer’s disease is the most common form of dementia, and often has devastating effects on affected individuals, their families, and caregivers. Although recent large-scale genetic analyses have revealed the genetic landscape of Alzheimer's disease, most of the phenotypic variance attributed to genetics remains unexplained. Moreover, the gene driving the association or the implications for disease progression for most of the identified loci remain largely unknown.

This Special Issue entitled “Genetics of Alzheimer’s Disease” is intended to provide a platform for a wide range of reviews, research articles, communications, and technical notes related to the genetics of either late-onset or early-onset Alzheimer’s disease. We encourage manuscripts to have a strong genetic component that may include, but is not limited to: machine learning of genetic markers associated with Alzheimer’s disease, genome-wide association studies, functional studies for Alzheimer’ disease-related genes or variants, personalized genetics, gene expression analyses, clinical trials with a genetic component, rare variant analyses, and other bioinformatics analyses of Alzheimer’s disease using DNA or RNA sequencing data. Please contact the Guest Editors with questions related to the scope of this Special Issue.

Dr. Laura Ibanez
Dr. Justin Miller
Guest Editors

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Keywords

  • Alzheimer’s disease
  • Genetics
  • Early-onset Alzheimer’s disease
  • Machine learning
  • Bioinformatics
  • Sequencing
  • Dementia
  • Clinical trial
  • Rare variant
  • Gene expression

Published Papers (10 papers)

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Editorial

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3 pages, 174 KiB  
Editorial
Editorial for the Genetics of Alzheimer’s Disease Special Issue: October 2021
by Laura Ibanez and Justin B. Miller
Genes 2021, 12(11), 1794; https://doi.org/10.3390/genes12111794 - 14 Nov 2021
Viewed by 2720
Abstract
Alzheimer’s disease is a complex and multifactorial condition regulated by both genetics and lifestyle, which ultimately results in the accumulation of β-amyloid (Aβ) and tau proteins in the brain, loss of gray matter, and neuronal death [...] Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)

Research

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12 pages, 452 KiB  
Article
Pairwise Correlation Analysis of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Dataset Reveals Significant Feature Correlation
by Erik D. Huckvale, Matthew W. Hodgman, Brianna B. Greenwood, Devorah O. Stucki, Katrisa M. Ward, Mark T. W. Ebbert, John S. K. Kauwe, The Alzheimer’s Disease Neuroimaging Initiative, The Alzheimer’s Disease Metabolomics Consortium and Justin B. Miller
Genes 2021, 12(11), 1661; https://doi.org/10.3390/genes12111661 - 21 Oct 2021
Cited by 7 | Viewed by 3920
Abstract
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using [...] Read more.
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) contains extensive patient measurements (e.g., magnetic resonance imaging [MRI], biometrics, RNA expression, etc.) from Alzheimer’s disease (AD) cases and controls that have recently been used by machine learning algorithms to evaluate AD onset and progression. While using a variety of biomarkers is essential to AD research, highly correlated input features can significantly decrease machine learning model generalizability and performance. Additionally, redundant features unnecessarily increase computational time and resources necessary to train predictive models. Therefore, we used 49,288 biomarkers and 793,600 extracted MRI features to assess feature correlation within the ADNI dataset to determine the extent to which this issue might impact large scale analyses using these data. We found that 93.457% of biomarkers, 92.549% of the gene expression values, and 100% of MRI features were strongly correlated with at least one other feature in ADNI based on our Bonferroni corrected α (p-value ≤ 1.40754 × 10−13). We provide a comprehensive mapping of all ADNI biomarkers to highly correlated features within the dataset. Additionally, we show that significant correlation within the ADNI dataset should be resolved before performing bulk data analyses, and we provide recommendations to address these issues. We anticipate that these recommendations and resources will help guide researchers utilizing the ADNI dataset to increase model performance and reduce the cost and complexity of their analyses. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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11 pages, 1101 KiB  
Article
Analysis of Genetic Variants Associated with Levels of Immune Modulating Proteins for Impact on Alzheimer’s Disease Risk Reveal a Potential Role for SIGLEC14
by Benjamin C. Shaw, Yuriko Katsumata, James F. Simpson, David W. Fardo and Steven Estus
Genes 2021, 12(7), 1008; https://doi.org/10.3390/genes12071008 - 30 Jun 2021
Cited by 8 | Viewed by 2799
Abstract
Genome-wide association studies (GWAS) have identified immune-related genes as risk factors for Alzheimer’s disease (AD), including TREM2 and CD33, frequently passing a stringent false-discovery rate. These genes either encode or signal through immunomodulatory tyrosine-phosphorylated inhibitory motifs (ITIMs) or activation motifs (ITAMs) and [...] Read more.
Genome-wide association studies (GWAS) have identified immune-related genes as risk factors for Alzheimer’s disease (AD), including TREM2 and CD33, frequently passing a stringent false-discovery rate. These genes either encode or signal through immunomodulatory tyrosine-phosphorylated inhibitory motifs (ITIMs) or activation motifs (ITAMs) and govern processes critical to AD pathology, such as inflammation and amyloid phagocytosis. To investigate whether additional ITIM and ITAM-containing family members may contribute to AD risk and be overlooked due to the stringent multiple testing in GWAS, we combined protein quantitative trait loci (pQTL) data from a recent plasma proteomics study with AD associations in a recent GWAS. We found that pQTLs for genes encoding ITIM/ITAM family members were more frequently associated with AD than those for non-ITIM/ITAM genes. Further testing of one family member, SIGLEC14 which encodes an ITAM, uncovered substantial copy number variations, identified an SNP as a proxy for gene deletion, and found that gene expression correlates significantly with gene deletion. We also found that SIGLEC14 deletion increases the expression of SIGLEC5, an ITIM. We conclude that many genes in this ITIM/ITAM family likely impact AD risk, and that complex genetics including copy number variation, opposing function of encoded proteins, and coupled gene expression may mask these AD risk associations at the genome-wide level. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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19 pages, 1695 KiB  
Article
TOMM40 RNA Transcription in Alzheimer’s Disease Brain and Its Implication in Mitochondrial Dysfunction
by Eun-Gyung Lee, Sunny Chen, Lesley Leong, Jessica Tulloch and Chang-En Yu
Genes 2021, 12(6), 871; https://doi.org/10.3390/genes12060871 - 6 Jun 2021
Cited by 20 | Viewed by 4505
Abstract
Increasing evidence suggests that the Translocase of Outer Mitochondria Membrane 40 (TOMM40) gene may contribute to the risk of Alzheimer’s disease (AD). Currently, there is no consensus as to whether TOMM40 expression is up- or down-regulated in AD brains, hindering a [...] Read more.
Increasing evidence suggests that the Translocase of Outer Mitochondria Membrane 40 (TOMM40) gene may contribute to the risk of Alzheimer’s disease (AD). Currently, there is no consensus as to whether TOMM40 expression is up- or down-regulated in AD brains, hindering a clear interpretation of TOMM40’s role in this disease. The aim of this study was to determine if TOMM40 RNA levels differ between AD and control brains. We applied RT-qPCR to study TOMM40 transcription in human postmortem brain (PMB) and assessed associations of these RNA levels with genetic variants in APOE and TOMM40. We also compared TOMM40 RNA levels with mitochondrial functions in human cell lines. Initially, we found that the human genome carries multiple TOMM40 pseudogenes capable of producing highly homologous RNAs that can obscure precise TOMM40 RNA measurements. To circumvent this obstacle, we developed a novel RNA expression assay targeting the primary transcript of TOMM40. Using this assay, we showed that TOMM40 RNA was upregulated in AD PMB. Additionally, elevated TOMM40 RNA levels were associated with decreases in mitochondrial DNA copy number and mitochondrial membrane potential in oxidative stress-challenged cells. Overall, differential transcription of TOMM40 RNA in the brain is associated with AD and could be an indicator of mitochondrial dysfunction. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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9 pages, 247 KiB  
Article
Shared Genetic Etiology between Alzheimer’s Disease and Blood Levels of Specific Cytokines and Growth Factors
by Robert J. van der Linden, Ward De Witte and Geert Poelmans
Genes 2021, 12(6), 865; https://doi.org/10.3390/genes12060865 - 5 Jun 2021
Cited by 2 | Viewed by 2325
Abstract
Late-onset Alzheimer’s disease (AD) has a significant genetic and immunological component, but the molecular mechanisms through which genetic and immunity-related risk factors and their interplay contribute to AD pathogenesis are unclear. Therefore, we screened for genetic sharing between AD and the blood levels [...] Read more.
Late-onset Alzheimer’s disease (AD) has a significant genetic and immunological component, but the molecular mechanisms through which genetic and immunity-related risk factors and their interplay contribute to AD pathogenesis are unclear. Therefore, we screened for genetic sharing between AD and the blood levels of a set of cytokines and growth factors to elucidate how the polygenic architecture of AD affects immune marker profiles. For this, we retrieved summary statistics from Finnish genome-wide association studies of AD and 41 immune marker blood levels and assessed for shared genetic etiology, using a polygenic risk score-based approach. For the blood levels of 15 cytokines and growth factors, we identified genetic sharing with AD. We also found positive and negative genetic concordances—implying that genetic risk factors for AD are associated with higher and lower blood levels—for several immune markers and were able to relate some of these results to the literature. Our results imply that genetic risk factors for AD also affect specific immune marker levels, which may be leveraged to develop novel treatment strategies for AD. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
12 pages, 275 KiB  
Article
The Impact of Complement Genes on the Risk of Late-Onset Alzheimer’s Disease
by Sarah M. Carpanini, Janet C. Harwood, Emily Baker, Megan Torvell, The GERAD1 Consortium, Rebecca Sims, Julie Williams and B. Paul Morgan
Genes 2021, 12(3), 443; https://doi.org/10.3390/genes12030443 - 20 Mar 2021
Cited by 15 | Viewed by 3555
Abstract
Late-onset Alzheimer’s disease (LOAD), the most common cause of dementia, and a huge global health challenge, is a neurodegenerative disease of uncertain aetiology. To deliver effective diagnostics and therapeutics, understanding the molecular basis of the disease is essential. Contemporary large genome-wide association studies [...] Read more.
Late-onset Alzheimer’s disease (LOAD), the most common cause of dementia, and a huge global health challenge, is a neurodegenerative disease of uncertain aetiology. To deliver effective diagnostics and therapeutics, understanding the molecular basis of the disease is essential. Contemporary large genome-wide association studies (GWAS) have identified over seventy novel genetic susceptibility loci for LOAD. Most are implicated in microglial or inflammatory pathways, bringing inflammation to the fore as a candidate pathological pathway. Among the most significant GWAS hits are three complement genes: CLU, encoding the fluid-phase complement inhibitor clusterin; CR1 encoding complement receptor 1 (CR1); and recently, C1S encoding the complement enzyme C1s. Complement activation is a critical driver of inflammation; changes in complement genes may impact risk by altering the inflammatory status in the brain. To assess complement gene association with LOAD risk, we manually created a comprehensive complement gene list and tested these in gene-set analysis with LOAD summary statistics. We confirmed associations of CLU and CR1 genes with LOAD but showed no significant associations for the complement gene-set when excluding CLU and CR1. No significant association with other complement genes, including C1S, was seen in the IGAP dataset; however, these may emerge from larger datasets. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
16 pages, 848 KiB  
Article
Set-Based Rare Variant Expression Quantitative Trait Loci in Blood and Brain from Alzheimer Disease Study Participants
by Devanshi Patel, Xiaoling Zhang, John J. Farrell, Kathryn L. Lunetta and Lindsay A. Farrer
Genes 2021, 12(3), 419; https://doi.org/10.3390/genes12030419 - 15 Mar 2021
Cited by 6 | Viewed by 3407
Abstract
Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived [...] Read more.
Because studies of rare variant effects on gene expression have limited power, we investigated set-based methods to identify rare expression quantitative trait loci (eQTL) related to Alzheimer disease (AD). Gene-level and pathway-level cis rare-eQTL mapping was performed genome-wide using gene expression data derived from blood donated by 713 Alzheimer’s Disease Neuroimaging Initiative participants and from brain tissues donated by 475 Religious Orders Study/Memory and Aging Project participants. The association of gene or pathway expression with a set of all cis potentially regulatory low-frequency and rare variants within 1 Mb of genes was evaluated using SKAT-O. A total of 65 genes expressed in the brain were significant targets for rare expression single nucleotide polymorphisms (eSNPs) among which 17% (11/65) included established AD genes HLA-DRB1 and HLA-DRB5. In the blood, 307 genes were significant targets for rare eSNPs. In the blood and the brain, GNMT, LDHC, RBPMS2, DUS2, and HP were targets for significant eSNPs. Pathway enrichment analysis revealed significant pathways in the brain (n = 9) and blood (n = 16). Pathways for apoptosis signaling, cholecystokinin receptor (CCKR) signaling, and inflammation mediated by chemokine and cytokine signaling were common to both tissues. Significant rare eQTLs in inflammation pathways included five genes in the blood (ALOX5AP, CXCR2, FPR2, GRB2, IFNAR1) that were previously linked to AD. This study identified several significant gene- and pathway-level rare eQTLs, which further confirmed the importance of the immune system and inflammation in AD and highlighted the advantages of using a set-based eQTL approach for evaluating the effect of low-frequency and rare variants on gene expression. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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Review

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15 pages, 1422 KiB  
Review
Genetic Insights into the Impact of Complement in Alzheimer’s Disease
by Megan Torvell, Sarah M. Carpanini, Nikoleta Daskoulidou, Robert A. J. Byrne, Rebecca Sims and B. Paul Morgan
Genes 2021, 12(12), 1990; https://doi.org/10.3390/genes12121990 - 15 Dec 2021
Cited by 11 | Viewed by 4311
Abstract
The presence of complement activation products at sites of pathology in post-mortem Alzheimer’s disease (AD) brains is well known. Recent evidence from genome-wide association studies (GWAS), combined with the demonstration that complement activation is pivotal in synapse loss in AD, strongly implicates complement [...] Read more.
The presence of complement activation products at sites of pathology in post-mortem Alzheimer’s disease (AD) brains is well known. Recent evidence from genome-wide association studies (GWAS), combined with the demonstration that complement activation is pivotal in synapse loss in AD, strongly implicates complement in disease aetiology. Genetic variations in complement genes are widespread. While most variants individually have only minor effects on complement homeostasis, the combined effects of variants in multiple complement genes, referred to as the “complotype”, can have major effects. In some diseases, the complotype highlights specific parts of the complement pathway involved in disease, thereby pointing towards a mechanism; however, this is not the case with AD. Here we review the complement GWAS hits; CR1 encoding complement receptor 1 (CR1), CLU encoding clusterin, and a suggestive association of C1S encoding the enzyme C1s, and discuss difficulties in attributing the AD association in these genes to complement function. A better understanding of complement genetics in AD might facilitate predictive genetic screening tests and enable the development of simple diagnostic tools and guide the future use of anti-complement drugs, of which several are currently in development for central nervous system disorders. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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25 pages, 1089 KiB  
Review
Advances in Genetic and Molecular Understanding of Alzheimer’s Disease
by Laura Ibanez, Carlos Cruchaga and Maria Victoria Fernández
Genes 2021, 12(8), 1247; https://doi.org/10.3390/genes12081247 - 15 Aug 2021
Cited by 10 | Viewed by 5827
Abstract
Alzheimer’s disease (AD) has become a common disease of the elderly for which no cure currently exists. After over 30 years of intensive research, we have gained extensive knowledge of the genetic and molecular factors involved and their interplay in disease. These findings [...] Read more.
Alzheimer’s disease (AD) has become a common disease of the elderly for which no cure currently exists. After over 30 years of intensive research, we have gained extensive knowledge of the genetic and molecular factors involved and their interplay in disease. These findings suggest that different subgroups of AD may exist. Not only are we starting to treat autosomal dominant cases differently from sporadic cases, but we could be observing different underlying pathological mechanisms related to the amyloid cascade hypothesis, immune dysfunction, and a tau-dependent pathology. Genetic, molecular, and, more recently, multi-omic evidence support each of these scenarios, which are highly interconnected but can also point to the different subgroups of AD. The identification of the pathologic triggers and order of events in the disease processes are key to the design of treatments and therapies. Prevention and treatment of AD cannot be attempted using a single approach; different therapeutic strategies at specific disease stages may be appropriate. For successful prevention and treatment, biomarker assays must be designed so that patients can be more accurately monitored at specific points during the course of the disease and potential treatment. In addition, to advance the development of therapeutic drugs, models that better mimic the complexity of the human brain are needed; there have been several advances in this arena. Here, we review significant, recent developments in genetics, omics, and molecular studies that have contributed to the understanding of this disease. We also discuss the implications that these contributions have on medicine. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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7 pages, 244 KiB  
Review
Advances with Long Non-Coding RNAs in Alzheimer’s Disease as Peripheral Biomarker
by Maria Garofalo, Cecilia Pandini, Daisy Sproviero, Orietta Pansarasa, Cristina Cereda and Stella Gagliardi
Genes 2021, 12(8), 1124; https://doi.org/10.3390/genes12081124 - 24 Jul 2021
Cited by 16 | Viewed by 2240
Abstract
One of the most compelling needs in the study of Alzheimer’s disease (AD) is the characterization of cognitive decline peripheral biomarkers. In this context, the theme of altered RNA processing has emerged as a contributing factor to AD. In particular, the significant role [...] Read more.
One of the most compelling needs in the study of Alzheimer’s disease (AD) is the characterization of cognitive decline peripheral biomarkers. In this context, the theme of altered RNA processing has emerged as a contributing factor to AD. In particular, the significant role of long non-coding RNAs (lncRNAs) associated to AD is opening new perspectives in AD research. This class of RNAs may offer numerous starting points for new investigations about pathogenic mechanisms and, in particular, about peripheral biomarkers. Indeed, altered lncRNA signatures are emerging as potential diagnostic biomarkers. In this review, we have collected and fully explored all the presented data about lncRNAs and AD in the peripheral system to offer an overview about this class of non-coding RNAs and their possible role in AD. Full article
(This article belongs to the Special Issue Genetics of Alzheimer’s Disease)
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