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Record W2947271916

Genetic Contributions to Alzheimer’s Disease: The Role of Immune Modulatory Regions

2017· article· en· W2947271916 on OpenAlexfundno aff
Jessie S. Carr

Bibliographic record

VenueeScholarship (California Digital Library) · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersNational Institute on AgingCanadian Institutes of Health ResearchGenentechNational Institutes of HealthIXICOStichting MS ResearchServierMedical Research CouncilMeso Scale DiagnosticsHersenstichtingBristol-Myers SquibbNorth Bristol NHS TrustEisaiNewcastle UniversityU.S. Department of DefenseEli Lilly and CompanyAlzheimer's Research TrustNorthern California Institute for Research and EducationPfizerBiogenBioClinicaNovartis Pharmaceuticals CorporationUniversitat de BarcelonaUniversity of California, San DiegoU.S. Department of Veterans AffairsOffice of Research and DevelopmentAlzheimer's AssociationWellcome TrustUniversity of Southern CaliforniaH. Lundbeck A/S
KeywordsHaplotypeOdds ratioCohortImputation (statistics)DiseaseAllelePsychologyMedicineGeneticsInternal medicineBiologyGene
DOInot available

Abstract

fetched live from OpenAlex

We used a robust imputation method on two case–control cohorts (a small UCSF cohort and a large cohort from the Alzheimer’s Disease Genetics Consortium [ADGC]) to identify HLA haplotypes associated with Alzheimer’s disease and followed up these studies with direct sequencing of the HLA region in AD cases and controls, including both typical amnestic and atypical clinical forms of disease. In our imputed study, we found the haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08–1.37]) was associated with increased risk of AD in the combined UCSF + ADGC cohort (n = 11,690). Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for APOE-ε4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01–1.23]) and class II haplotype DRB1*15:01~DQA1*01:02~DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01–1.15]) as risk factors for AD. We followed up these genetic associations in a separate clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels. We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline on two different assessments. \tWe also directly sequenced the HLA region in an expanded cohort of AD cases, controls, and atypical AD cases seen at UCSF. We corroborated the accuracy of HLA imputation via direct sequencing of 308 overlapping samples and confirmed the association of the haplotype previously associated with AD risk in the UCSF cohort. We also found that the A*03:01~B*07:02~C*07:02~DRB1*15:01~DQB1*06:02~DPB1*04:01 haplotype was associated with decreased risk of atypical AD in our cohort (p = 0.01, OR = 0.18 [0.02-0.74]). Taken together, our findings corroborate a role of the HLA in AD risk and suggest a differential role of HLA variation in amnestic versus atypical AD.

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)0.016
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.024
GPT teacher head0.251
Teacher spread0.227 · 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 designBench or experimental
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

Citations0
Published2017
Admission routes1
Has abstractyes

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