Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

paper Cited Public

Authors: Desikan, R S; Schork, A J; Wang, Y; Witoelar, A; Sharma, M; McEvoy, L K; Holland, D; Brewer, J B; Chen, C-H; Thompson, W K; Harold, D; Williams, J; Owen, M J; O'Donovan, M C; Pericak-Vance, M A; Mayeux, R; Haines, J L; Farrer, L A; Schellenberg, G D; Heutink, P; Singleton, A B; Brice, A; Wood, N W; Hardy, J; Martinez, M; Choi, S H; DeStefano, A; Ikram, M A; Bis, J C; Smith, A; Fitzpatrick, A L; Launer, L; van Duijn, C; Seshadri, S; Ulstein, I D; Aarsland, D; Fladby, T; Djurovic, S; Hyman, B T; Snaedal, J; Stefansson, H; Stefansson, K; Gasser, T; Andreassen, O A; Dale, A M; ADNI, ADGC, GERAD, CHARGE and IPDGC Investigators
Year: 2015
Journal: Molecular psychiatry
PMID: 25687773
DOI: 10.1038/mp.2015.6
PMCID: PMC4539304

Figure 1

Forest plot for rs393152. Since rs393152 was not available within the Oslo cohort (*), we used a proxy SNP (rs17690703; r2 = .765, D'=1 in Hapmap2).

LLM interpretation

This is a forest plot showing the odds ratios (OR) and 95% confidence intervals (CI) for the SNP rs393152 across five individual studies (ADGC, GERAD, DeCODE, Oslo, and CHARGE) and a joint analysis. The x-axis represents the Odds Ratio, with a vertical dashed line at 1.0 indicating no effect. The joint analysis result, represented by a red diamond, shows a statistically significant decrease in odds (OR = 0.91, p = 1.65e-07) as the diamond and its CI are entirely to the left of the null line.

Figure 2

(a) Regional linkage disequilibrium (LD) plot demonstrating the relationship between rs393152 on chromosome 17 and loci greater than and less than 1 MB. The bottom panel indicates the location of genes in the region. Linkage Disequilibrium measured in the 1000 genomes European Populations using plink v1.07.(b) Regional association plot illustrating the association signal within the MAPT region on chromosome 17. The bottom panel indicates the location of genes in the region. Linkage Disequilibrium measured in the 1000 genomes European Populations using plink v1.07.

LLM interpretation

This is a regional association plot (Manhattan plot) showing the association signal within the MAPT region on chromosome 17. The y-axis represents $-\log_{10}(p)$ values and the x-axis represents the base pair position in kilobases (kB), with a cluster of highly significant SNPs (red dots, $r^2=1$) centered around the reference SNP rs393152. A bottom panel maps the locations of genes in this region, with the MAPT gene highlighted by a grey shaded vertical bar.

Figure 3

Box plots illustrating the relationship between rs393152 alleles (x-axis) and gene expression levels of MAPT, SYP, and SNCA (y-axis). For each plot, thick black lines show the median value. Regions above and below the black line show the upper and lower quartiles, respectively. The dashed lines extend to the minimum and maximum values with outliers shown as open circles. For MAPT, a proxy SNP was used (please see Results for additional details). As illustrated, the A allele of rs393152 demonstrated a selective dose-dependent effect on the level of intracranial MAPT transcript.

LLM interpretation

This figure consists of three box plots showing the relationship between rs393152 alleles (AA, AG, GG) and the mRNA expression levels of *MAPT*, *SYP*, and *SNCA*. For *MAPT*, there is a visible dose-dependent decrease in expression levels from the AA to the GG genotype. In contrast, *SYP* and *SNCA* expression levels remain relatively stable across the three genotype groups.

Figure 4

Regional association plot demonstrating the relationship between MAPT transcript expression levels (y-axis) and SNPs in LD with rs393152 on chromosome 17. The bottom panel indicates the location of genes in the region. Linkage Disequilibrium measured in the 1000 genomes European Populations using plink v1.07. As illustrated, SNPs in r2 LD =1 with rs393152 constituted the peak of the association signal with MAPT transcript expression levels.

LLM interpretation

This figure is a regional association plot (Manhattan plot) showing the relationship between SNPs on chromosome 17 and *MAPT* transcript expression levels. The top panel plots $-\log_{10}(p)$ against base pair position (kB), with points color-coded by linkage disequilibrium ($r^2$) relative to rs393152, showing a peak of highly significant associations (red dots, $r^2=1$) centered around the *MAPT* gene. The bottom panel provides a genomic map of genes in the region, with the *MAPT* gene location highlighted by a gray shaded vertical bar.

Figure 5

Bar plots demonstrating the relationship between rs393152 alleles (x-axis) and volume loss (annualized percent change – y-axis) of the hippocampus (blue) and entorhinal cortex (gray) among APOE ε4 carriers (left panel) and APOE ε4 non-carriers (right panel). As illustrated, the A allele of rs393152 demonstrated a selective dose-dependent relationship with medial temporal lobe atrophy only among APOE ε4 non-carriers.

LLM interpretation

This figure consists of two side-by-side bar plots showing the annualized percent change in volume for the hippocampus (blue) and entorhinal cortex (gray) across rs393152 genotypes (AA, AG, GG). The left panel represents APOE ε4 carriers, where volume loss remains relatively consistent across genotypes, while the right panel represents APOE ε4 non-carriers. In the non-carrier group, there is a visible dose-dependent trend where the GG genotype is associated with less volume loss compared to the AA genotype.

#	Section	Preview
0	INTRODUCTION	Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the two most common neurodegenerative…
1	INTRODUCTION	Combining GWAS from two disorders provides insights into genetic pleiotropy (defined as a single…
2	METHODS — Participant Samples	We obtained complete GWAS results in the form of summary statistics from the PD International…
3	METHODS — Participant Samples	To test for replication, we also assessed the p-values of the PD genome-wide significant SNPs in…
4	METHODS — Participant Samples	statistic data drawn from the Icelandic population (deCODE) included 3,759 AD cases (65.8 % female)…
5	METHODS — Participant Samples	These studies addressed potential concerns of population stratification by limiting analysis to…
6	METHODS — Participant Samples	For the gene expression analyses, we used publicly available, genotyping (performed on the…
7	METHODS — Statistical analyses	We used stepwise gatekeeper hypothesis testing 17 to identify SNPs associating with both PD and AD.…
8	RESULTS — Genetic overlap between AD and PD at the A allele of rs393152	We found 8 SNPs on 4 chromosomes that were genome-wide significant in PD, thus requiring a…
9	RESULTS — Genetic overlap between AD and PD at the A allele of rs393152	and Oslo cohorts (one-tailed p-value = 0.047, OR for the minor allele = 0.85, 95% CI = 0.71–1.02).…
10	RESULTS — Genetic overlap between AD and PD at the A allele of rs393152	We evaluated the statistical power for detecting an association of rs393152 with AD across the…
11	RESULTS — Genetic overlap between AD and PD at the A allele of rs393152	PD-significant SNPs results in considerable increase in statistical power for AD gene discovery. We…
12	RESULTS — Genetic overlap between AD and PD at the A allele of rs393152	Based on the 1000 Genomes Project LD structure, we found that rs393152 was in r2 LD > 0.8 with a…
13	RESULTS — Genetic overlap between AD and PD at the A allele of rs393152	demonstrated a similar meta-analysis p-value to rs393152 (two-tailed meta-analysis p-value of 1.29…
14	RESULTS — Non-polygenic pleiotropy between AD and PD	We further investigated whether the observed genetic overlap between AD and PD was polygenic and…
15	RESULTS — AD-PD pleiotropic locus correlates with MAPT transcript levels	We assessed the relationship between the AD-PD pleiotropic locus on chromosome 17 and MAPT…
16	RESULTS — AD-PD pleiotropic locus correlates with MAPT transcript levels	vs. controls), brain tissue region (frontal, parietal, temporal, or cerebellar), postmortem…
17	RESULTS — AD-PD pleiotropic locus correlates with MAPT transcript levels	performed a ‘locus wide association study’ testing all SNPs in the MAPT region for association…
18	RESULTS — AD-PD pleiotropic locus correlates with longitudinal brain atrophy	Using linear mixed effects models, we assessed the relationship of rs393152 with longitudinal brain…
19	RESULTS — AD-PD pleiotropic locus demonstrates larger effect among APOE ε4 non-carriers	We further assessed the relationship between rs393152, MAPT transcript expression levels, and medial…

Citation	PMID	DOI	Status
Abraham, R et al., Am J Med Genet B Neuropsychiatr Genet, An association study of common variation at the MAPT locus with late-onset Alzheimer's disease	19308965	10.1002/ajmg.b.30951	Cited
Allen, M et al., Alzheimers Res Ther, 2014, Association of MAPT haplotypes with Alzheimer's disease risk and MAPT brain gene expression levels	25324900	10.1186/alzrt268	Cited
Andreassen, OA et al., Am J Hum Genet, 2013, Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors	23375658	10.1016/j.ajhg.2013.01.001	Cited
Andreassen, OA et al., Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: implications for immune related disease mechanisms, Molecular Psychiatry, 2014, Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate	—	—	—
Andreassen, OA et al., PLoS Genet, 2013, Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate	23637625	10.1371/journal.pgen.1003455	Cited
Braak, H et al., Acta Neuropathol, 1991, Neuropathological stageing of Alzheimer-related changes	1759558	10.1007/BF00308809	Cited
Canu, E et al., Eur J Hum Genet, 2009, H1 haplotype of the MAPT gene is associated with lower regional gray matter volume in healthy carriers	18854867	10.1038/ejhg.2008.185	Cited
Charlesworth, G et al., Neurobiol Aging, 2012, Tau acts as an independent genetic risk factor in pathologically proven PD	22221882	10.1016/j.neurobiolaging.2011.11.001	Cited
Coppola, G et al., Hum Mol Genet, 2012, Evidence for a role of the rare p.A152T variant in MAPT in increasing the risk for FTD-spectrum and Alzheimer's diseases	22556362	10.1093/hmg/dds161	Cited
Desikan, RS et al., AJNR Am J Neuroradiol, 2013, Apolipoprotein E {varepsilon}4 Does Not Modulate Amyloid-β-Associated Neurodegeneration in Preclinical Alzheimer Disease	22976236	10.3174/ajnr.A3267	Cited
Desikan, RS et al., Ann Neurol, 2011, Amyloid-β associated volume loss occurs only in the presence of p-tau	22002658	10.1002/ana.22509	Cited
Desikan, RS et al., Arch Neurol, 2012, Amyloid-β--associated clinical decline occurs only in the presence of elevated P-tau	22529247	10.1001/archneurol.2011.3354	Cited
Dmitrienko, A et al., Statistics in Medicine, 2007, Tree-structured gatekeeping tests in clinical trials with hierarchically ordered multiple objectives	17054103	10.1002/sim.2716	Cited
Fagan, AM et al., Arch Neurol, 2007, Cerebrospinal fluid tau/beta-amyloid(42) ratio as a prediction of cognitive decline in nondemented older adults	17210801	10.1001/archneur.64.3.noc60123	Cited
Gerrish, A et al., J Alzheimers Dis, 2012, The role of variation at AβPP, PSEN1, PSEN2, and MAPT in late onset Alzheimer's disease	22027014	10.3233/JAD-2011-110824	Cited
Goñi, J et al., J Alzheimer's Dis, 2013, Selective brain gray matter atrophy associated with APOE ε4 and MAPT H1 in subjects with mild cognitive impairment	23064258	10.3233/JAD-2012-121174	Cited
Harold, D et al., Nat Genet, 2009, Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease	19734902	10.1038/ng.440	Cited
Huang, Y et al., Cell, 2012, Alzheimer mechanisms and therapeutic strategies	22424230	10.1016/j.cell.2012.02.040	Cited
Jonsson, T et al., N Engl J Med, 2013, Variant of TREM2 associated with the risk of Alzheimer's disease	23150908	10.1056/NEJMoa1211103	Cited
Jonsson, T et al., Nature, 2012, A mutation in APP protects against Alzheimer's disease and age-related cognitive decline	22801501	10.1038/nature11283	Cited
Lambert, JC et al., Nat Genet, 2009, Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease	19734903	10.1038/ng.439	Cited
Lambert, JC et al., Nat Genet, 2013, Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease	24162737	10.1038/ng.2802	Cited
Li, G et al., Neurology, 2007, CSF tau/Abeta42 ratio for increased risk of mild cognitive impairment: a follow-up study	17698783	10.1212/01.wnl.0000267428.62582.aa	Cited
Liu, JZ et al., Nat Genet, 2013, Dense genotyping of immune-related disease regions identifies nine new risk loci for primary sclerosing cholangitis	23603763	10.1038/ng.2616	Cited
Mann, DM et al., Neurosci Lett, 1990, Deposition of amyloid (A4) protein within the brains of persons with dementing disorders other than Alzheimer's disease and Down's syndrome	2138261	10.1016/0304-3940(90)90539-l	Cited
Moskvina, V et al., JAMA Neurol, 2013, Analysis of Genome-Wide Association Studies of Alzheimer Disease and of Parkinson Disease to Determine If These 2 Diseases Share a Common Genetic Risk	23921447	10.1001/jamaneurol.2013.448	Cited
Mukherjee, O et al., BMC Genet, 2007, Haplotype-based association analysis of the MAPT locus in late onset Alzheimer's disease	17266761	10.1186/1471-2156-8-3	Cited
Myers, AJ et al., Hum Mol Genet, 2005, The H1c haplotype at the MAPT locus is associated with Alzheimer's disease	16000317	10.1093/hmg/ddi241	Cited
Myers, AJ et al., Neurobiol Dis, 2007, The MAPT H1c risk haplotype is associated with increased expression of tau and especially of 4 repeat containing transcripts	17174556	10.1016/j.nbd.2006.10.018	Cited
Naj, AC et al., Nat Genet, 2011, Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease	21460841	10.1038/ng.801	Cited
Nalls, MA et al., Lancet, 2011, Imputation of sequence variants for identification of genetic risks for Parkinson's disease: a meta-analysis of genome-wide association studies	21292315	10.1016/S0140-6736(10)62345-8	Cited
Nussbaum, RL et al., N Engl J Med, 2003, Alzheimer's disease and Parkinson's disease	12672864	10.1056/NEJM2003ra020003	Cited
Pittman, AM et al., Hum Mol Genet, 2006, Untangling the tau gene association with neurodegenerative disorders	16987883	10.1093/hmg/ddl190	Cited
Rietveld, CA et al., Proc Natl Acad Sci U S A, 2014, Common genetic variants associated with cognitive performance identified using the proxy-phenotype method	25201988	10.1073/pnas.1404623111	Cited
Satake, W et al., Nat Genet, 2009, Genome-wide association study identifies common variants at four loci as genetic risk factors for Parkinson's disease	19915576	10.1038/ng.485	Cited
Seshadri, S et al., JAMA, 2010, Genome-wide analysis of genetic loci associated with Alzheimer disease	20460622	10.1001/jama.2010.574	Cited
Shulman, JM et al., Nat Genet, 2009, Evidence for a common pathway linking neurodegenerative diseases	19935760	10.1038/ng1209-1261	Cited
Simón-Sánchez, J et al., Nat Genet, 2009, Genome-wide association study reveals genetic risk underlying Parkinson's disease	19915575	10.1038/ng.487	Cited
Spillantini, MG et al., Lancet Neurol, 2013, Tau pathology and neurodegeneration	23684085	10.1016/S1474-4422(13)70090-5	Cited
Sutherland, GT et al., J Alzheimers Dis, 2011, 2011 Knowing me, knowing you: can a knowledge of risk factors for Alzheimer's disease prove useful in understanding the pathogenesis of Parkinson's disease?	21441655	10.3233/JAD-2011-110026	Cited
Trabzuni, D et al., Hum Mol Genet, 2012, MAPT expression and splicing is differentially regulated by brain region: relation to genotype and implication for tauopathies	22723018	10.1093/hmg/dds238	Cited
Uchikado, H et al., J Neuropathol Exp Neurol, 2006, Lewy bodies in progressive supranuclear palsy represent an independent disease process	16691119	10.1097/01.jnen.0000218449.17073.43	Cited
Webster, JA et al., Am J Hum Genet, 2009, Genetic control of human brain transcript expression in Alzheimer disease	19361613	10.1016/j.ajhg.2009.03.011	Cited
Wijsman, EM et al., PLoS Genet, 2011, Genome-wide association of familial late-onset Alzheimer's disease replicates BIN1 and CLU and nominates CUGBP2 in interaction with APOE	21379329	10.1371/journal.pgen.1001308	Cited
Willer, CJ et al., Bioinformatics, 2010, METAL: fast and efficient meta-analysis of genomewide association scans	20616382	10.1093/bioinformatics/btq340	Cited
Zou, F et al., PLoS Genet, 2012, Brain expression genome-wide association study (eGWAS) identifies human disease-associated variants	22685416	10.1371/journal.pgen.1002707	Cited

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Genetic correlation and gene-based pleiotropy analysis for four major neurodegenerative diseases with summary statistics.	Qiao J et al.	—	2023	→
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Clinicopathological overlap of neurodegenerative diseases: A comprehensive review.	Das S et al.	—	2020	→
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Extracellular vesicle-associated proteins as potential biomarkers.	Schou AS et al.	—	2020	→
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Identification of Conserved Proteomic Networks in Neurodegenerative Dementia.	Swarup V et al.	—	2020	→
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Translational research on reserve against neurodegenerative disease: consensus report of the International Conference on Cognitive Reserve in the Dementias and the Alzheimer's Association Reserve, Resilience and Protective Factors Professional Interest Area working groups.	Perneczky R et al.	—	2019	→
Widespread Tau-Specific CD4 T Cell Reactivity in the General Population.	Lindestam Arlehamn CS et al.	—	2019	→
Are dementia with Lewy bodies and Parkinson's disease dementia the same disease?	Jellinger KA et al.	—	2018	→
Association of microtubule-associated protein tau gene polymorphisms with the risk of sporadic Alzheimer's disease: a meta-analysis.	Yuan H et al.	—	2018	→
Deconstructing and targeting the genomic architecture of human neurodegeneration.	De Jager PL et al.	—	2018	→
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Immune-related genetic enrichment in frontotemporal dementia: An analysis of genome-wide association studies.	Broce I et al.	—	2018	→
<i>NeuroArray</i>: A Customized aCGH for the Analysis of Copy Number Variations in Neurological Disorders.	La Cognata V et al.	—	2018	→
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A152T tau allele causes neurodegeneration that can be ameliorated in a zebrafish model by autophagy induction.	Lopez A et al.	—	2017	→
Analysis of neurodegenerative Mendelian genes in clinically diagnosed Alzheimer Disease.	Fernández MV et al.	—	2017	→
A new tool to identify patients with Parkinson's disease at increased risk of dementia.	Aarsland D et al.	—	2017	→
Association of IGF1 gene polymorphism with Parkinson's disease in a Han Chinese population.	Xiao Y et al.	—	2017	→
Cognitive decline in Parkinson disease.	Aarsland D et al.	—	2017	→
Dissecting the Molecular Mechanisms of Neurodegenerative Diseases through Network Biology.	Santiago JA et al.	—	2017	→
Genetic architecture of sporadic frontotemporal dementia and overlap with Alzheimer's and Parkinson's diseases.	Ferrari R et al.	—	2017	→
Genetic Comparison of Symptomatic and Asymptomatic Persons With Alzheimer Disease Neuropathology.	Monsell SE et al.	—	2017	→
Genetic evidence for role of integration of fast and slow neurotransmission in schizophrenia.	Devor A et al.	—	2017	→
Genome-wide interaction study of brain beta-amyloid burden and cognitive impairment in Alzheimer's disease.	Roostaei T et al.	—	2017	→
Genome-wide Pleiotropy Between Parkinson Disease and Autoimmune Diseases.	Witoelar A et al.	—	2017	→
MAPT mutation associated with frontotemporal dementia and parkinsonism (FTDP-17).	Haussmann R et al.	—	2017	→
Modeling tau pathology in human stem cell derived neurons.	Wray S	—	2017	→
Multimodal characterization of older APOE2 carriers reveals selective reduction of amyloid load.	Grothe MJ et al.	—	2017	→
Shared genetic risk between corticobasal degeneration, progressive supranuclear palsy, and frontotemporal dementia.	Yokoyama JS et al.	—	2017	→
Simple Test of Manual Dexterity Can Help to Identify Persons at High Risk for Neurodegenerative Diseases in the Community.	Darweesh SK et al.	—	2017	→
Tau reduction prevents neuronal loss and reverses pathological tau deposition and seeding in mice with tauopathy.	DeVos SL et al.	—	2017	→
The psychosis spectrum in Parkinson disease.	Ffytche DH et al.	—	2017	→
A convex optimization approach for identification of human tissue-specific interactomes.	Mohammadi S et al.	—	2016	→
A customized high-resolution array-comparative genomic hybridization to explore copy number variations in Parkinson's disease.	La Cognata V et al.	—	2016	→
Copy number variation analysis of the 17q21.31 region and its role in neurodegenerative diseases.	Cervera-Carles L et al.	—	2016	→
Drivers: A Biologically Contextualized, Cross-Inferential View of the Epidemiology of Neurodegenerative Disorders.	de Pedro-Cuesta J et al.	—	2016	→
Expression of A152T human tau causes age-dependent neuronal dysfunction and loss in transgenic mice.	Maeda S et al.	—	2016	→
Gene expression, methylation and neuropathology correlations at progressive supranuclear palsy risk loci.	Allen M et al.	—	2016	→
Genetic overlap between multiple sclerosis and several cardiovascular disease risk factors.	Wang Y et al.	—	2016	→
Overlap between Parkinson disease and Alzheimer disease in ABCA7 functional variants.	Nuytemans K et al.	—	2016	→
The effect of MAPT haplotype on neocortical Lewy body pathology in Parkinson disease.	Robakis D et al.	—	2016	→
Trans-pQTL study identifies immune crosstalk between Parkinson and Alzheimer loci.	Chan G et al.	—	2016	→
Variants in GBA, SNCA, and MAPT influence Parkinson disease risk, age at onset, and progression.	Davis AA et al.	—	2016	→
Genetic perspective on the role of the autophagy-lysosome pathway in Parkinson disease.	Gan-Or Z et al.	—	2015	→
Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans.	Saykin AJ et al.	—	2015	→
Genome-wide Meta-analysis on the Sense of Smell Among US Older Adults.	Dong J et al.	—	2015	→
Regulation of human MAPT gene expression.	Caillet-Boudin ML et al.	—	2015	→