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Record W4390194933 · doi:10.1002/alz.078419

Plasma biomarkers across the spectrum of Alzheimer’s and Parkinson’s disease: Association with cortical thickness and cognitive dysfunction

2023· article· en· W4390194933 on OpenAlexaffabout
Gillian Coughlan, Peter Zhukovsky, Erlan Sanchez, Cheryl Grady, Douglas P. Munoz, Sandra E. Black, Rachel F. Buckley, Mario Masellis

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsSunnybrook Health Science CentreQueen's UniversityBaycrest HospitalUniversity of TorontoSunnybrook Hospital
Fundersnot available
KeywordsDementiaNeuropsychologyAtrophyCognitionCognitive declineClinical Dementia RatingMedicinePathologicalNeurosciencePsychologyInternal medicineDiseasePathologyAudiology

Abstract

fetched live from OpenAlex

Abstract Background Plasma biomarkers of phosphorylated‐tau(p‐tau), astrocytosis and axonal damage offer a reliable means of identifying and measuring multiple pathological processes in‐vivo. How these biomarkers are associated with cortical brain structure and cognition within, and across, disorders is unclear. Leveraging the Ontario Neurodegenerative Disease Research Initiative, we examined the cross‐sectional association between plasma biomarkers, cortical thickness, and multi‐domain cognition. Method 290 participants diagnosed with AD or PD (in accordance with clinical guidelines) and healthy controls (HC) were included (MeanAge = 68.96;[41% women; 35% APOE4carriers]). Four groups were formed: i)AD with mild cognitive impairment or dementia(ADMCI/ADD;N = 121), ii)PD with MCI or dementia(PDMCI/PDD;N = 78), iii)PD with normal cognition(PD‐NC;N = 43) and HC(N = 44; Table1). Plasma measures of p‐tau181‐UGOT, Neurofilament light chain (NfL) and GFAP, alongside FreeSurfer‐derived cortical thickness were included. A neuropsychological battery was administered. All models were adjusted for age, sex, and education. Result There was an effect of diagnostic group on global cortical thickness, with PD‐NC, ADMCI/ADD and PDMCI/ADD exhibiting a significant reduction relative to HC(Fig1A). Regional patterns of brain atrophy were significantly associated in ADMCI/ADD and PDMCI/ADD(Fig1B). Across groups, p‐tau181, GFAP and to a lesser extent NfL, were associated with cortical thinning, particularly in lateral temporal and medial parietal regions (Fig2A). Unlike global thickness, ADMCI/ADD and PDMCI/PDD, but not PD‐NC, showed reduced thickness in the regions associated with p‐tau181, GFAP and NfL (Fig2B). Diagnostic group*GFAP/NfL/ptau181 interactions were not significant. Mediation analysis showed the cortical thinning in lateral temporal and medial parietal regions mediated between 33% to 40% of association between p‐tau181 and delayed memory. Similarly, thinning in these areas mediated 22% to 33% of the relationship between GFAP and executive function(Fig2C). Conclusion We conclude that there is a similar pattern of gray matter loss in MCI/Dementia due to AD and PD. Higher concentrations of plasma p‐tau181 and GFAP are associated with poorer memory and executive function, in part through cortical thinning in lateral temporal and medial parietal regions. In conclusion, pathological processes related to the deposition of amyloid and tau, as well as astrogliosis, may co‐exist across cognitively impaired individuals with AD and PD. This is consistent with autopsy findings showing that AD pathology is present in 33‐60% of PD patients.

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)0.002
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 score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.023
GPT teacher head0.303
Teacher spread0.280 · 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
Published2023
Admission routes2
Has abstractyes

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