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Record W4243520659 · doi:10.1016/j.jalz.2016.06.526

O3‐04‐03: Age‐Related Neuropathology Helps Distinguish Autosomal Dominant from Late‐Onset Alzheimer's Disease

2016· article· en· W4243520659 on OpenAlexaboutno aff
Nigel J. Cairns, Richard J. Perrin, Erin Franklin, Benjamin Vincent, Michael R. N. Baxter, John C. Morris

Bibliographic record

VenueAlzheimer s & Dementia · 2016
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNeuropathologyLewy bodyPathologyHippocampal sclerosisDementiaClinical Dementia RatingCohortMedicineAlzheimer's diseasePsychologyDiseaseNeuroscienceTemporal lobe

Abstract

fetched live from OpenAlex

Although autosomal dominant Alzheimer disease (ADAD) accounts for a small proportion (approximately 1%) of cases of AD, there is evidence to suggest that it overlaps both clinically and neuropathologically with spofradic late-onset AD (LOAD). However, there have been few studies comparing the neuropathology of these two groups. The Neuropathology Core of the Dominantly Inherited Alzheimer Network (DIAN) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) has undertaken standardized neuropathologic assessments of all participants (n=48) who came to autopsy at ADNI sites in the USA and Canada and participants (n=9) and family members (n=15) at DIAN sites in the USA and Australia. In fifteen brain areas, histology included hematoxylin and eosin and a modified Bielschowsky silver impregnation; immunohistochemistry was performed to detect four frequent molecular pathologies: Aβ (10D5; Eli Lilly, Indianapolis, IN, USA), phospho-tau (PHF1; gift of P. Davies, Feinstein Institute for Medical Research, Manhasset, NY, USA), phospho-α-synuclein (Phospho-α-synuclein (Ser129), Cell Applications, Inc., San Diego, CA, USA), and phospho-TDP-43 (pTDP-43, Cosmo Bio USA, Inc., Carlsbad, CA, USA). Of 48 ADNI participants with dementia of the Alzheimer type at expiration, 96% cases had AD neuropathologic change (ADNC); two cases had argyrophilic grain disease. All 24 DIAN cases had ADNC at expiration. Twelve of 24 DIAN cases had diffuse Lewy body disease or amygdala-predominant Lewy body disease. In the ADNI cohort, 42.4% had Lewy body disease. Other comorbidities in LOAD (ADNI cohort) included: TDP-43 proteinopathy (21.2%), AGD (18.2%), hippocampal sclerosis (6.1%), age-related tau astroglopathy (3%) and infarcts (3%). These comorbidities were absent from the ADAD (DIAN cohort) cases. Both ADAD and LOAD have significant α-synucleinopathy (Lewy bodies) in up to one half of cases. LOAD cases are distinguished from ADAD by additional age-related comorbidities including: TDP-43 proteinopathy, hippocampal sclerosis, AGD, age-related tau astrogliopathy, and small vessel disease with infarcts. Comorbid pathology may contribute to the variance in ADNI and DIAN biomarker data. These findings also suggest sophisticated diagnostic and therapeutic approaches for comorbid pathologies, in addition to ADNC, will be required to optimize treatment for dementing diseases. *For listing of ADNI and DIAN investigators see: http://www.adni-info.org/ and http://dian-info.org/.

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)0.001
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 score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0130.004

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 head0.027
GPT teacher head0.291
Teacher spread0.265 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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