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Record W1963919142 · doi:10.1186/alzrt268

Association of MAPT haplotypes with Alzheimer’s disease risk and MAPT brain gene expression levels

2014· article· en· W1963919142 on OpenAlexfundno aff
Mariet Allen, Michaela Kachadoorian, Zachary Quicksall, Fanggeng Zou, High Seng Chai, Curtis Younkin, Julia E. Crook, V. Shane Pankratz, Minerva M. Carrasquillo, Siddharth Krishnan, Thuy Nguyen, Li Ma, Kimberly G. Malphrus, Sarah Lincoln, Gina Bisceglio, Christopher P. Kolbert, Jin Jen, Shubhabrata Mukherjee, John Kauwe, Paul K. Crane, Jonathan L. Haines, Richard Mayeux, Margaret A. Pericak‐Vance, Lindsay A. Farrer, Gerard D. Schellenberg, Joseph E. Parisi, Ronald Petersen, Neill R. Graff‐Radford, Dennis W. Dickson, Steven G. Younkin, Nilüfer Ertekin‐Taner

Bibliographic record

VenueAlzheimer s Research & Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersNational Institute of Mental HealthNational Institute on AgingNational Center for Advancing Translational SciencesMedical Research CouncilUniversity of California, IrvineUniversity of California, San FranciscoUniversity of California, San DiegoUniversity of California, DavisUniversity of California, Los AngelesNational Institutes of HealthRush UniversityNational Institute of Neurological Disorders and StrokeUniversity of PittsburghUniversity of WashingtonJohns Hopkins UniversityUniversity of MiamiYork UniversityNorthwestern UniversityGHR FoundationEmory UniversityNewcastle UniversityUniversity of PennsylvaniaVanderbilt UniversityInstitute on Aging, University of PennsylvaniaUniversity of Southern CaliforniaMassachusetts General Hospital
KeywordsHaplotypeDiseaseNeurologyTau proteinAssociation (psychology)Genetic associationAlzheimer's diseaseMedicineNeuroscienceGeneGeneticsAllelePsychologyPsychiatryBiologySingle-nucleotide polymorphismInternal medicineGenotype

Abstract

fetched live from OpenAlex

INTRODUCTION: MAPT encodes for tau, the predominant component of neurofibrillary tangles that are neuropathological hallmarks of Alzheimer's disease (AD). Genetic association of MAPT variants with late-onset AD (LOAD) risk has been inconsistent, although insufficient power and incomplete assessment of MAPT haplotypes may account for this. METHODS: We examined the association of MAPT haplotypes with LOAD risk in more than 20,000 subjects (n-cases = 9,814, n-controls = 11,550) from Mayo Clinic (n-cases = 2,052, n-controls = 3,406) and the Alzheimer's Disease Genetics Consortium (ADGC, n-cases = 7,762, n-controls = 8,144). We also assessed associations with brain MAPT gene expression levels measured in the cerebellum (n = 197) and temporal cortex (n = 202) of LOAD subjects. Six single nucleotide polymorphisms (SNPs) which tag MAPT haplotypes with frequencies greater than 1% were evaluated. RESULTS: H2-haplotype tagging rs8070723-G allele associated with reduced risk of LOAD (odds ratio, OR = 0.90, 95% confidence interval, CI = 0.85-0.95, p = 5.2E-05) with consistent results in the Mayo (OR = 0.81, p = 7.0E-04) and ADGC (OR = 0.89, p = 1.26E-04) cohorts. rs3785883-A allele was also nominally significantly associated with LOAD risk (OR = 1.06, 95% CI = 1.01-1.13, p = 0.034). Haplotype analysis revealed significant global association with LOAD risk in the combined cohort (p = 0.033), with significant association of the H2 haplotype with reduced risk of LOAD as expected (p = 1.53E-04) and suggestive association with additional haplotypes. MAPT SNPs and haplotypes also associated with brain MAPT levels in the cerebellum and temporal cortex of AD subjects with the strongest associations observed for the H2 haplotype and reduced brain MAPT levels (β = -0.16 to -0.20, p = 1.0E-03 to 3.0E-03). CONCLUSIONS: These results confirm the previously reported MAPT H2 associations with LOAD risk in two large series, that this haplotype has the strongest effect on brain MAPT expression amongst those tested and identify additional haplotypes with suggestive associations, which require replication in independent series. These biologically congruent results provide compelling evidence to screen the MAPT region for regulatory variants which confer LOAD risk by influencing its brain gene expression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.080
GPT teacher head0.370
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations160
Published2014
Admission routes1
Has abstractyes

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