Genetics of Late-Onset Alzheimer's Disease: Update from the Alzgene Database and Analysis of Shared Pathways

The genetics of late-onset Alzheimer's disease (LOAD) has taken impressive steps forwards in the last few years. To date, more than six-hundred genes have been linked to the disorder. However, only a minority of them are supported by a sufficient level of evidence. This review focused on such genes and analyzed shared biological pathways. Genetic markers were selected from a web-based collection (Alzgene). For each SNP in the database, it was possible to perform a meta-analysis. The quality of studies was assessed using criteria such as size of research samples, heterogeneity across studies, and protection from publication bias. This produced a list of 15 top-rated genes:APOE, CLU, PICALM, EXOC3L2, BIN1, CR1, SORL1, TNK1, IL8, LDLR, CST3, CHRNB2, SORCS1, TNF,andCCR2.A systematic analysis of gene ontology terms associated with each marker showed that most genes were implicated in cholesterol metabolism, intracellular transport of beta-amyloid precursor, and autophagy of damaged organelles. Moreover, the impact of these genes on complement cascade and cytokine production highlights the role of inflammatory response in AD pathogenesis. Gene-gene and gene-environment interactions are prominent issues in AD genetics, but they are not specifically featured in the Alzgene database.

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Race-Related Association between APOE Genotype and Alzheimer’s Disease: A Systematic Review and Meta-Analysis

Journal of Alzheimer s Disease ◽

10.3233/jad-210549 ◽

2021 ◽

pp. 1-10

Author(s):

Wei Qin ◽

Wenwen Li ◽

Qi Wang ◽

Min Gong ◽

Tingting Li ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Black People ◽

Late Onset ◽

Meta Analysis ◽

Group Analysis ◽

Apoe Genotype ◽

Cochrane Library ◽

Data Sets ◽

Apoe Genotypes

Background: The global race-dependent association of Alzheimer’s disease (AD) and apolipoprotein E (APOE) genotype is not well understood. Transethnic analysis of APOE could clarify the role of genetics in AD risk across populations. Objective: This study aims to determine how race and APOE genotype affect the risks for AD. Methods: We performed a systematic search of PubMed, Embase, Web of Science, and the Cochrane Library since 1993 to Aug 25, 2020. A total of 10,395 reports were identified, and 133 were eligible for analysis with data on 77,402 participants. Studies contained AD clinical diagnostic and APOE genotype data. Homogeneous data sets were pooled in case-control analyses. Odds ratios and 95% confidence intervals for developing AD were calculated for populations of different races and APOE genotypes. Results: The proportion of APOE genotypes and alleles differed between populations of different races. Results showed that APOE ɛ4 was a risk factor for AD, whereas APOE ɛ2 protected against it. The effects of APOE ɛ4 and ɛ2 on AD risk were distinct in various races, they were substantially attenuated among Black people. Sub-group analysis found a higher frequency of APOE ɛ4/ɛ4 and lower frequency of APOE ɛ3/ɛ3 among early-onset AD than late-onset AD in a combined group and different races. Conclusion: Our meta-analysis suggests that the association of APOE genotypes and AD differ between races. These results enhance our understanding of APOE-related risk for AD across race backgrounds and provide new insights into precision medicine for AD.

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RECRUITMENT INTO THE ALZHEIMER PREVENTION TRIALS (APT) WEBSTUDY FOR A TRIAL-READY COHORT FOR PRECLINICAL AND PRODROMAL ALZHEIMER’S DISEASE (TRCPAD)

Journal of Prevention of Alzheimer's Disease ◽

10.14283/jpad.2020.46 ◽

2020 ◽

pp. 1-7

Author(s):

S. Walter ◽

T.B. Clanton ◽

O.G. Langford ◽

M.S. Rafii ◽

E.J. Shaffer ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Effective Means ◽

Web Based ◽

The Us ◽

Study Team ◽

Prodromal Alzheimer’S Disease ◽

Prevention Trials ◽

Study Participants ◽

The Impact

BACKGROUND: The Alzheimer Prevention Trials (APT) Webstudy is the first stage in establishing a Trial-ready Cohort for Preclinical and Prodromal Alzheimer’s disease (TRC-PAD). This paper describes recruitment approaches for the APT Webstudy. Objectives: To remotely enroll a cohort of individuals into a web-based longitudinal observational study. Participants are followed quarterly with brief cognitive and functional assessments, and referred to Sites for in-clinic testing and biomarker confirmation prior to enrolling in the Trial-ready Cohort (TRC). Design: Participants are referred to the APT Webstudy from existing registries of individuals interested in brain health and Alzheimer’s disease research, as well as through central and site recruitment efforts. The study team utilizes Urchin Tracking Modules (UTM) codes to better understand the impact of electronic recruitment methods. Setting: A remotely enrolled online study. Participants: Volunteers who are at least 50 years old and interested in Alzheimer’s research. Measurements: Demographics and recruitment source of participant where measured by UTM. Results: 30,650 participants consented to the APT Webstudy as of April 2020, with 69.7% resulting from referrals from online registries. Emails sent by the registry to participants were the most effective means of recruitment. Participants are distributed across the US, and the demographics of the APT Webstudy reflect the referral registries, with 73.1% female, 85.0% highly educated, and 92.5% Caucasian. Conclusions: We have demonstrated the feasibility of enrolling a remote web-based study utilizing existing registries as a primary referral source. The next priority of the study team is to engage in recruitment initiatives that will improve the diversity of the cohort, towards the goal of clinical trials that better represent the US population.

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Genome-Wide Meta-Analysis of Late-Onset Alzheimer's Disease Using Rare Variant Imputation in 324,809 Subjects Identifies Novel Rare Variant Locus NCK2: The International Genomics of Alzheimer's Project (IGAP)

10.1101/2021.03.14.21253553 ◽

2021 ◽

Author(s):

Adam C. Naj ◽

Ganna Leonenko ◽

Xueqiu Jian ◽

Benjamin Grenier-Boley ◽

Maria Carolina Dalmasso ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variant ◽

Late Onset ◽

Sequence Data ◽

Association Studies ◽

Meta Analysis ◽

Genome Wide Association Studies ◽

Genome Wide ◽

The Uk

Risk for late-onset Alzheimer's disease (LOAD) is driven by multiple loci primarily identified by genome-wide association studies, many of which are common variants with minor allele frequencies (MAF)>0.01. To identify additional common and rare LOAD risk variants, we performed a GWAS on 25,170 LOAD subjects and 41,052 cognitively normal controls in 44 datasets from the International Genomics of Alzheimer's Project (IGAP). Existing genotype data were imputed using the dense, high-resolution Haplotype Reference Consortium (HRC) r1.1 reference panel. Stage 1 associations of P<10-5 were meta-analyzed with the European Alzheimer's Disease Biobank (EADB) (n=20,301 cases; 21,839 controls) (stage 2 combined IGAP and EADB). An expanded meta-analysis was performed using a GWAS of parental AD/dementia history in the UK Biobank (UKBB) (n=35,214 cases; 180,791 controls) (stage 3 combined IGAP, EADB, and UKBB). Common variant (MAF≥0.01) associations were identified for 29 loci in stage 2, including novel genome-wide significant associations at TSPAN14 (P=2.33×10-12), SHARPIN (P=1.56×10-9), and ATF5/SIGLEC11 (P=1.03[mult]10-8), and newly significant associations without using AD proxy cases in MTSS1L/IL34 (P=1.80×10-8), APH1B (P=2.10×10-13), and CLNK (P=2.24×10-10). Rare variant (MAF<0.01) associations with genome-wide significance in stage 2 included multiple variants in APOE and TREM2, and a novel association of a rare variant (rs143080277; MAF=0.0054; P=2.69×10-9) in NCK2, further strengthened with the inclusion of UKBB data in stage 3 (P=7.17×10-13). Single-nucleus sequence data shows that NCK2 is highly expressed in amyloid-responsive microglial cells, suggesting a role in LOAD pathology.

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Genetically regulated expression in late-onset Alzheimer’s disease implicates risk genes within known and novel loci

Translational Psychiatry ◽

10.1038/s41398-021-01677-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hung-Hsin Chen ◽

Lauren E. Petty ◽

Jin Sha ◽

Yi Zhao ◽

Amanda Kuzma ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Late Onset ◽

Meta Analysis ◽

Data Sets ◽

Phenotypic Variance ◽

Risk Variants ◽

Genome Wide ◽

Regulated Expression ◽

Genetic Mechanisms

AbstractLate-onset Alzheimer disease (LOAD) is highly polygenic, with a heritability estimated between 40 and 80%, yet risk variants identified in genome-wide studies explain only ~8% of phenotypic variance. Due to its increased power and interpretability, genetically regulated expression (GReX) analysis is an emerging approach to investigate the genetic mechanisms of complex diseases. Here, we conducted GReX analysis within and across 51 tissues on 39 LOAD GWAS data sets comprising 58,713 cases and controls from the Alzheimer’s Disease Genetics Consortium (ADGC) and the International Genomics of Alzheimer’s Project (IGAP). Meta-analysis across studies identified 216 unique significant genes, including 72 with no previously reported LOAD GWAS associations. Cross-brain-tissue and cross-GTEx models revealed eight additional genes significantly associated with LOAD. Conditional analysis of previously reported loci using established LOAD-risk variants identified eight genes reaching genome-wide significance independent of known signals. Moreover, the proportion of SNP-based heritability is highly enriched in genes identified by GReX analysis. In summary, GReX-based meta-analysis in LOAD identifies 216 genes (including 72 novel genes), illuminating the role of gene regulatory models in LOAD.

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Meta-analysis of genetic association with diagnosed Alzheimer’s disease identifies novel risk loci and implicates Abeta, Tau, immunity and lipid processing

10.1101/294629 ◽

2018 ◽

Cited By ~ 9

Author(s):

BW Kunkle ◽

B Grenier-Boley ◽

R Sims ◽

JC Bis ◽

AC Naj ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variants ◽

Late Onset ◽

Association Studies ◽

Meta Analysis ◽

The Elderly ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Load Risk

IntroductionLate-onset Alzheimer’s disease (LOAD, onset age > 60 years) is the most prevalent dementia in the elderly1, and risk is partially driven by genetics2. Many of the loci responsible for this genetic risk were identified by genome-wide association studies (GWAS)3–8. To identify additional LOAD risk loci, the we performed the largest GWAS to date (89,769 individuals), analyzing both common and rare variants. We confirm 20 previous LOAD risk loci and identify four new genome-wide loci (IQCK, ACE, ADAM10, and ADAMTS1). Pathway analysis of these data implicates the immune system and lipid metabolism, and for the first time tau binding proteins and APP metabolism. These findings show that genetic variants affecting APP and Aβ processing are not only associated with early-onset autosomal dominant AD but also with LOAD. Analysis of AD risk genes and pathways show enrichment for rare variants (P = 1.32 × 10−7) indicating that additional rare variants remain to be identified.

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Cholesterol and Alzheimer’s Disease; From Risk Genes to Pathological Effects

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2021.690372 ◽

2021 ◽

Vol 13 ◽

Author(s):

Femke M. Feringa ◽

Rik van der Kant

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cholesterol Metabolism ◽

Late Onset ◽

Induced Pluripotent Stem Cell ◽

Risk Genes ◽

Cholesterol Levels ◽

Technical Advances ◽

The Central Nervous System ◽

Induced Pluripotent

While the central nervous system compromises 2% of our body weight, it harbors up to 25% of the body’s cholesterol. Cholesterol levels in the brain are tightly regulated for physiological brain function, but mounting evidence indicates that excessive cholesterol accumulates in Alzheimer’s disease (AD), where it may drive AD-associated pathological changes. This seems especially relevant for late-onset AD, as several of the major genetic risk factors are functionally associated with cholesterol metabolism. In this review we discuss the different systems that maintain brain cholesterol metabolism in the healthy brain, and how dysregulation of these processes can lead, or contribute to, Alzheimer’s disease. We will also discuss how AD-risk genes might impact cholesterol metabolism and downstream AD pathology. Finally, we will address the major outstanding questions in the field and how recent technical advances in CRISPR/Cas9-gene editing and induced pluripotent stem cell (iPSC)-technology can aid to study these problems.

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Genome Wide Meta-Analysis identifies common genetic signatures shared by heart function and Alzheimer’s disease

Scientific Reports ◽

10.1038/s41598-019-52724-2 ◽

2019 ◽

Vol 9 (1) ◽

Author(s):

M. E. Sáez ◽

A. González-Pérez ◽

B. Hernández-Olasagarre ◽

A. Beà ◽

S. Moreno-Grau ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cardiac Function ◽

Heart Development ◽

Heart Function ◽

Meta Analysis ◽

Genome Wide ◽

Study Results ◽

Apoptotic Genes ◽

The Impact

Abstract Echocardiography has become an indispensable tool for the study of heart performance, improving the monitoring of individuals with cardiac diseases. Diverse genetic factors associated with echocardiographic measures have been previously reported. The impact of several apoptotic genes in heart development identified in experimental models prompted us to assess their potential association with human cardiac function. This study aimed at investigating the possible association of variants of apoptotic genes with echocardiographic traits and to identify new genetic markers associated with cardiac function. Genome wide data from different studies were obtained from public repositories. After quality control and imputation, a meta-analysis of individual association study results was performed. Our results confirmed the role of caspases and other apoptosis related genes with cardiac phenotypes. Moreover, enrichment analysis showed an over-representation of genes, including some apoptotic regulators, associated with Alzheimer’s disease. We further explored this unexpected observation which was confirmed by genetic correlation analyses. Our findings show the association of apoptotic gene variants with echocardiographic indicators of heart function and reveal a novel potential genetic link between echocardiographic measures in healthy populations and cognitive decline later on in life. These findings may have important implications for preventative strategies combating Alzheimer’s disease.

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O3-03-06: CROSS-TISSUE TRANSCRIPTOME-WIDE ASSOCIATION META-ANALYSIS IDENTIFIES NOVEL RISK GENES FOR LATE-ONSET ALZHEIMER'S DISEASE

Alzheimer s & Dementia ◽

10.1016/j.jalz.2018.06.2787 ◽

2006 ◽

Vol 14 (7S_Part_19) ◽

pp. P1017-P1018

Author(s):

Qiongshi Lu ◽

Yiming Hu ◽

Mo Li ◽

Haoyi Weng ◽

Jiawei Wang ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Late Onset ◽

Meta Analysis ◽

Risk Genes

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The role of APOE4 in Alzheimer’s disease: strategies for future therapeutic interventions

Neuronal Signaling ◽

10.1042/ns20180203 ◽

2019 ◽

Vol 3 (2) ◽

Cited By ~ 2

Author(s):

Holly C. Hunsberger ◽

Priyanka D. Pinky ◽

Warren Smith ◽

Vishnu Suppiramaniam ◽

Miranda N. Reed

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Synapse Formation ◽

Late Onset ◽

Therapeutic Interventions ◽

Memory Decline ◽

Current Therapies ◽

Ε4 Allele ◽

The Impact

Abstract Alzheimer’s disease (AD) is the leading cause of dementia affecting almost 50 million people worldwide. The ε4 allele of Apolipoprotein E (APOE) is the strongest known genetic risk factor for late-onset AD cases, with homozygous APOE4 carriers being approximately 15-times more likely to develop the disease. With 25% of the population being APOE4 carriers, understanding the role of this allele in AD pathogenesis and pathophysiology is crucial. Though the exact mechanism by which ε4 allele increases the risk for AD is unknown, the processes mediated by APOE, including cholesterol transport, synapse formation, modulation of neurite outgrowth, synaptic plasticity, destabilization of microtubules, and β-amyloid clearance, suggest potential therapeutic targets. This review will summarize the impact of APOE on neurons and neuronal signaling, the interactions between APOE and AD pathology, and the association with memory decline. We will then describe current treatments targeting APOE4, complications associated with the current therapies, and suggestions for future areas of research and treatment.

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The Association between TREM2 Gene and Late-Onset Alzheimer’s Disease in Chinese Han Population

Gerontology ◽

10.1159/000517284 ◽

2021 ◽

pp. 1-7

Author(s):

Yan Sun ◽

Yun-Ke Zhang ◽

Hai Chen ◽

Ren-Shou Chen

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Logistic Regression ◽

Regression Analysis ◽

Environmental Factors ◽

Logistic Regression Analysis ◽

Late Onset ◽

Increased Risk ◽

The Impact ◽

Load Risk

Objective: : The objective of this study was to evaluate the impact of single nucleotide polymorphisms (SNPs) in triggering receptor expressed on the myeloid cells 2 protein (TREM2) gene and their interaction with environmental factors and haplotypes on late-onset Alzheimer’s disease (LOAD). Methods: DNA was extracted from the whole blood of the participants and genotyped using PCR and followed by restriction fragment length polymorphism. The Hardy-Weinberg equilibrium test was used in the control group. Multivariate logistic regression analysis was used to determine the relationship between the 4 SNPs of the TREM2 gene and the risk of LOAD. Generalized multifactor dimensionality reduction was used to test the best interaction combination between SNPs and environmental factors. Results: Logistic regression analysis showed that the T allele of rs75932628 and the T allele of rs2234253 were independently associated with increased risk of LOAD, and adjusted odds ratios (ORs) were 1.81 (1.271–2.35) and 1.59 (1.15–2.03), respectively. However, there was no significant association with LOAD for rs142232675 and rs143332484. We found a best model significantly associated with LOAD risk that consisted of rs75932628 and smoking, which scored 10/10 for both the sign test and cross-validation consistency (p = 0.012). Stratified analysis indicated that current smokers with rs75932628-CT/TT genotype have the highest LOAD risk compared to never smokers with rs75932628 – CC genotype, OR (95% confidence interval) = 2.73 (1.72–3.79). Haplotypes of rs75932628 and rs2234253 were analyzed using the SHEsis online software. However, no haplotype was found to be significantly associated with the risk of LOAD. Conclusions: The T allele of rs75932628 and the T allele of rs2234253 and interaction between rs75932628 and smoking were all correlated with increased risk of LOAD.

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