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Record W3113027002 · doi:10.1002/alz.044114

Hypercholesterolemia accelerates Aβ deposition in regions associated with early amyloidosis

2020· article· en· W3113027002 on OpenAlexaff
João Pedro Ferrari‐Souza, Guilherme Povala, Wagner S. Brum, Marco Antônio De Bastiani, Tharick A. Pascoal, Andréa Lessa Benedet, Joseph Therriault, Lucas U. das Ros, Andrei Bieger, Pedro Rosa‐Neto, Eduardo R. Zimmer

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsCholesterolMedicinePittsburgh compound BAlzheimer's Disease Neuroimaging InitiativeAmyloid (mycology)NeuroimagingInternal medicineApolipoprotein EAmyloidosisEpidemiologyRisk factorDementiaEndocrinologyDiseaseGastroenterologyPathologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Hypercholesterolemia is a well‐established risk factor for developing Alzheimer's disease (AD). Mechanisms underlying this relationship, however, are still unclear. Recent experiments have reported conflicting findings regarding the relationship between amyloid‐beta (Aβ) and cholesterol. While in vitro studies have shown that cholesterol accelerates Aβ aggregation, an epidemiological investigation demonstrated that total serum cholesterol is not associated with Aβ load. Nevertheless, it is still unclear whether total serum cholesterol affects Aβ deposition in the human brain. Here, we aimed to assess whether high levels of total serum cholesterol are associated with the rate of Aβ aggregation in the brain. We hypothesized that high total serum cholesterol levels could accelerate cerebral amyloidosis of non‐demented subjects. Method We selected 207 non‐demented – cognitively unimpaired and mild cognitive impairment – participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) who had available data for baseline cholesterol and longitudinal amyloid PET scans with [18F]AV45. Subjects were divided into two groups regarding their total serum cholesterol levels, being classified as normal (<200mg/dL; n=158) or abnormal (>200mg/dL; n=107). We performed a voxel‐wise general linear modelling to assess Aβ load differences between groups at baseline. Then, a longitudinal comparison was carried out to evaluate the rate of Aβ deposition in 4 years, calculated as "(IMAGE4_YEARS ‐ IMAGEBASELINE)x100/IMAGEBASELINE". Age, gender, APOEε4, cholesterol treatment and diagnostic group were used as covariates. Result No differences were found in Aβ load at baseline. By contrast, we observed a significantly higher rate of Aβ accumulation for the abnormal group in brain regions associated to early amyloidosis, including lateral temporal (peak t(200) = 4.498, p<0.0001) and parietal (peak t(200) = 4.504, p<0.0001) lobes, over a 4‐year period when compared to the normal group (Figure 1). Conclusion Our findings suggest that serum cholesterol dysmetabolism could influence cerebral Aβ aggregation. In addition, our analysis points to a potential communication between central and peripheral cholesterol compartments (perhaps intensified by hypercholesterolemia‐related inflammation). Also, it corroborates with the hypothesis that higher serum cholesterol levels accelerate the process of brain amyloidosis, stressing the need for further investigation on the mechanisms involved in this process.

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)0.000
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.051
GPT teacher head0.292
Teacher spread0.241 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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