Weighted burden analysis of exome-sequenced late onset Alzheimer’s cases and controls provides further evidence for a role for PSEN1 and suggests involvement of the PI3K/Akt/GSK-3β and WNT signalling pathways

SummaryPrevious studies have implicated common and rare genetic variants as risk factors for late onset Alzheimer’s disease (AD, LOAD). Here, weighted burden analysis was applied to over 10,000 exome sequenced subjects from the Alzheimer’s Disease Sequencing Project. Analyses were carried out to investigate whether rare variants predicted to have a functional effect within a gene were more commonly seen in cases or in controls. Confirmatory results were obtained for TREM2, ABCA7 and SORL1. Additional support was provided for PSEN1 (p = 0.0002), which previously had been only weakly implicated in LOAD. There was suggestive evidence that functional variants in PIK3R1, WNT7A, C1R and EXOC5 might increase risk and that variants in TIAF1 and/or NDRG2 might have a protective effect. Overall, there was strong evidence (p = 5 × 10−6) that variants in tyrosine phosphatase genes reduce the risk of developing LOAD. Since PIK3R1 variants are expected to impair PI3K/Akt/GSK-3β signalling while variants in tyrosine phosphatase genes would enhance it, these findings are in line with those from animal models suggesting that this pathway is protective against AD.

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Rare Variants in APP, PSEN1 and PSEN2 Increase Risk for AD in Late-Onset Alzheimer's Disease Families

PLoS ONE ◽

10.1371/journal.pone.0031039 ◽

2012 ◽

Vol 7 (2) ◽

pp. e31039 ◽

Cited By ~ 158

Author(s):

Carlos Cruchaga ◽

Sumitra Chakraverty ◽

Kevin Mayo ◽

Francesco L. M. Vallania ◽

Robi D. Mitra ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variants ◽

Late Onset ◽

Increase Risk

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Correction: Rare Variants in APP, PSEN1 and PSEN2 Increase Risk for AD in Late-Onset Alzheimer's Disease Families

PLoS ONE ◽

10.1371/annotation/c92e16da-7733-421d-b063-1db19488daa6 ◽

2012 ◽

Vol 7 (5) ◽

Cited By ~ 18

Author(s):

Carlos Cruchaga ◽

Sumitra Chakraverty ◽

Kevin Mayo ◽

Francesco L. M. Vallania ◽

Robi D. Mitra ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variants ◽

Late Onset ◽

Increase Risk

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Genetic Analysis of TREM2 Variants in Tunisian Patients with Alzheimer's Disease

Medical Principles and Practice ◽

10.1159/000489779 ◽

2018 ◽

Vol 27 (4) ◽

pp. 317-322 ◽

Cited By ~ 1

Author(s):

Zied Landoulsi ◽

Mouna Ben Djebara ◽

Imen Kacem ◽

Youssef Sidhom ◽

Rym Kefi ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variants ◽

Late Onset ◽

Tunisian Population ◽

Fisher Exact Test ◽

Exon 2 ◽

Exact Test ◽

Tunisian Patients ◽

Synonymous Variant

Objective: Rare variants in the TREM2 gene have been reported to significantly increase the risk of Alzheimer’s disease in Caucasian populations. Hitherto, this association was not studied in North African populations. In this work, we aimed to study the association between TREM2 exon 2 variants and the risk of late-onset Alzheimer’s disease (LOAD) in a Tunisian population. Subjects and Methods: We sequenced exon 2 of TREM2 in a Tunisian cohort of 172 LOAD patients and 158 control subjects. We used the Fisher exact test to compare the distribution of allelic frequencies between the two groups. Results: We identified 4 previously reported nonsynonymous variants (p.Asp39Glu, p.Arg62His, p.Thr96Lys, and p.Val126Gly) and 1 novel synonymous variant (p.Gln109Gln), none of which was significantly associated with the risk of Alzheimer’s disease. Moreover, the rare TREM2 variant (p.Arg47His), which was considered to be a risk factor for Alzheimer’s disease in European descent populations, was not detected in our cohort. Conclusion: These findings do not support a major role for TREM2 in the pathogenesis of LOAD in the Tunisian population.

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Rare Variants in PLD3 Increase Risk for Alzheimer’s Disease in Han Chinese

Journal of Alzheimer s Disease ◽

10.3233/jad-180205 ◽

2018 ◽

Vol 64 (1) ◽

pp. 55-59 ◽

Cited By ~ 6

Author(s):

Meng-Shan Tan ◽

Jun-Xia Zhu ◽

Xi-Peng Cao ◽

Jin-Tai Yu ◽

Lan Tan

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variants ◽

Han Chinese ◽

Increase Risk

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P1-018: Rare Deleterious And Loss-of-Function Variants in OPRL1 and GAS2L2 Contribute to the Risk of Late-Onset Alzheimer’s Disease: Alzheimer’s Disease Sequencing Project Case-Control Study

Alzheimer s & Dementia ◽

10.1016/j.jalz.2016.06.765 ◽

2016 ◽

Vol 12 ◽

pp. P406-P406

Author(s):

Xueqiu Jian ◽

Joshua C. Bis ◽

Brian W. Kunkle ◽

Kara L. Hamilton ◽

Gary W. Beecham ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Case Control Study ◽

Late Onset ◽

Case Control ◽

Loss Of Function ◽

Sequencing Project ◽

Control Study

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Network propagation of rare variants in Alzheimer’s disease reveals tissue-specific hub genes and communities

PLoS Computational Biology ◽

10.1371/journal.pcbi.1008517 ◽

2021 ◽

Vol 17 (1) ◽

pp. e1008517

Author(s):

Marzia Antonella Scelsi ◽

Valerio Napolioni ◽

Michael D. Greicius ◽

Andre Altmann ◽

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variants ◽

Late Onset ◽

Integrative Approach ◽

Specific Gene ◽

Tissue Specific ◽

Association Testing ◽

Wide Range ◽

Network Propagation

State-of-the-art rare variant association testing methods aggregate the contribution of rare variants in biologically relevant genomic regions to boost statistical power. However, testing single genes separately does not consider the complex interaction landscape of genes, nor the downstream effects of non-synonymous variants on protein structure and function. Here we present the NETwork Propagation-based Assessment of Genetic Events (NETPAGE), an integrative approach aimed at investigating the biological pathways through which rare variation results in complex disease phenotypes. We applied NETPAGE to sporadic, late-onset Alzheimer’s disease (AD), using whole-genome sequencing from the AD Neuroimaging Initiative (ADNI) cohort, as well as whole-exome sequencing from the AD Sequencing Project (ADSP). NETPAGE is based on network propagation, a framework that models information flow on a graph and simulates the percolation of genetic variation through tissue-specific gene interaction networks. The result of network propagation is a set of smoothed gene scores that can be tested for association with disease status through sparse regression. The application of NETPAGE to AD enabled the identification of a set of connected genes whose smoothed variation profile was robustly associated to case-control status, based on gene interactions in the hippocampus. Additionally, smoothed scores significantly correlated with risk of conversion to AD in Mild Cognitive Impairment (MCI) subjects. Lastly, we investigated tissue-specific transcriptional dysregulation of the core genes in two independent RNA-seq datasets, as well as significant enrichments in terms of gene sets with known connections to AD. We present a framework that enables enhanced genetic association testing for a wide range of traits, diseases, and sample sizes.

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Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer’s Disease

Frontiers in Genetics ◽

10.3389/fgene.2020.629373 ◽

2021 ◽

Vol 11 ◽

Author(s):

Valerio Napolioni ◽

Marzia A. Scelsi ◽

Raiyan R. Khan ◽

Andre Altmann ◽

Michael D. Greicius

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Ethnic Groups ◽

Late Onset ◽

Population Increase ◽

Outbred Population ◽

Genotype Relative Risk ◽

Subsequent Work ◽

Sequencing Project ◽

Increased Risk

Prior work in late-onset Alzheimer’s disease (LOAD) has resulted in discrepant findings as to whether recent consanguinity and outbred autozygosity are associated with LOAD risk. In the current study, we tested the association between consanguinity and outbred autozygosity with LOAD in the largest such analysis to date, in which 20 LOAD GWAS datasets were retrieved through public databases. Our analyses were restricted to eight distinct ethnic groups: African–Caribbean, Ashkenazi–Jewish European, European–Caribbean, French–Canadian, Finnish European, North-Western European, South-Eastern European, and Yoruba African for a total of 21,492 unrelated subjects (11,196 LOAD and 10,296 controls). Recent consanguinity determination was performed using FSuite v1.0.3, according to subjects’ ancestral background. The level of autozygosity in the outbred population was assessed by calculating inbreeding estimates based on the proportion (FROH) and the number (NROH) of runs of homozygosity (ROHs). We analyzed all eight ethnic groups using a fixed-effect meta-analysis, which showed a significant association of recent consanguinity with LOAD (N = 21,481; OR = 1.262, P = 3.6 × 10–4), independently of APOE∗4 (N = 21,468, OR = 1.237, P = 0.002), and years of education (N = 9,257; OR = 1.274, P = 0.020). Autozygosity in the outbred population was also associated with an increased risk of LOAD, both for FROH (N = 20,237; OR = 1.204, P = 0.030) and NROH metrics (N = 20,237; OR = 1.019, P = 0.006), independently of APOE∗4 [(FROH, N = 20,225; OR = 1.222, P = 0.029) (NROH, N = 20,225; OR = 1.019, P = 0.007)]. By leveraging the Alzheimer’s Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data, we determined that LOAD subjects do not show an enrichment of rare, risk-enhancing minor homozygote variants compared to the control population. A two-stage recessive GWAS using ADSP data from 201 consanguineous subjects in the discovery phase followed by validation in 10,469 subjects led to the identification of RPH3AL p.A303V (rs117190076) as a rare minor homozygote variant increasing the risk of LOAD [discovery: Genotype Relative Risk (GRR) = 46, P = 2.16 × 10–6; validation: GRR = 1.9, P = 8.0 × 10–4]. These results confirm that recent consanguinity and autozygosity in the outbred population increase risk for LOAD. Subsequent work, with increased samples sizes of consanguineous subjects, should accelerate the discovery of non-additive genetic effects in LOAD.

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An Association Test of the Spatial Distribution of Rare Missense Variants within Protein Structures Improves Statistical Power of Sequencing Studies

10.1101/2021.08.09.455695 ◽

2021 ◽

Author(s):

Bowen Jin ◽

John A Capra ◽

Penelope Benchek ◽

Nicholas R Wheeler ◽

Adam C Naj ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Spatial Distribution ◽

Protein Structure ◽

Statistical Power ◽

Rare Variants ◽

Protein Structures ◽

Sequencing Project ◽

Missense Variants ◽

Risk Variants

Over 90% of variants are rare, and 50% of them are singletons in the Alzheimer's Disease Sequencing Project Whole Exome Sequencing (ADSP WES) data. However, either single variant tests or unit-based tests are limited in the statistical power to detect the association between rare variants and phenotypes. To best utilize rare variants and investigate their biological effect, we exam their association with phenotypes in the context of protein. We developed a protein structure-based approach, POKEMON (Protein Optimized Kernel Evaluation of Missense Nucleotides), which evaluates rare missense variants based on their spatial distribution on the protein rather than allele frequency. The hypothesis behind this is that the three-dimensional spatial distribution of variants within a protein structure provides functional context and improves the power of association tests. POKEMON identified four candidate genes from the ADSP WES data, namely two known Alzheimer's disease (AD) genes (TREM2 and SORL) and two novel genes (DUSP18 and CSF1R). For known AD genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low frequency risk variants within these genes. DUSP18 has a cluster of variants primarily shared by case subjects around the ligand-binding domain, and this cluster is further validated in a replication dataset with a larger sample size. POKEMON is an open-source tool available at https://github.com/bushlab-genomics/POKEMON.

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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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