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Record W2897397401 · doi:10.1016/j.jalz.2018.06.2747

F3‐02‐04: SERUM INDICES OF ETHANOLAMINE PLASMALOGENS AND PHOSPHATIDE METABOLISM IN THE COMBINED ADNI‐1/GO/2 COHORT: DOES THE LIVER CONTRIBUTE TO AD RISK BY FAILING TO SUPPLY KEY LIPIDS TO THE BRAIN?

2018· article· en· W2897397401 on OpenAlexaff
Mitchel A. Kling, Dayan B. Goodenowe, Vijitha Senanayake, Siamak MahmoudianDehkordi, Rebecca Baillie, Xianlin Han, Alexandra Kueider‐Paisley, Rima Kaddurah‐Daouk

Bibliographic record

VenueAlzheimer s & Dementia · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsSaskatchewan Health Authority
Fundersnot available
KeywordsPlasmalogenPhosphatidylethanolamineInternal medicineEthanolamineLipid metabolismChemistryEndocrinologyBiochemistryBiologyMedicinePhospholipidMembrane

Abstract

fetched live from OpenAlex

Altered lipid metabolism is linked to Alzheimer's disease (AD) risk; the underlying mechanisms are incompletely understood. The liver synthesizes many circulating lipids and lipoproteins; some are critical for supporting neuronal and brain functions. For example, the ether lipid plasmalogens promote vesicle fusion and thus synaptic function, are membrane antioxidants, and affect other AD-relevant processes. The liver is a key site for plasmalogen synthesis, remodeling, and incorporation into circulating lipoproteins, some of which can enter the brain. Liver peroxisomal activity is crucial for plasmalogen synthesis; a deficiency can limit delivery to brain, disrupt synaptic function, and impair cognition. Our consortium is engaged in further exploration of these and other lipids and their relation to liver-related genes and proteins that may influence brain function via circulating lipoproteins. We measured 8 phosphoethanolamines (PEs), including 4 ethanolamine plasmalogens and 4 closely-related phosphatidylethanolamines, in >1500 baseline serum specimens from Alzheimer's Disease Neuroimaging Initiative (ADNI)-1,-GO, and -2 cohorts. We derived 4 indices: PL-PX (ethanolamine plasmalogen remodeling); PE-PX (phosphatidylethanolamine remodeling); PL/PE (ethanolamine plasmalogen/phosphatide ratios); and PBV (a composite index). We tested for cross-sectional associations of these indices with cognition by ADAS-Cog13 (in ADNI) and MMSE, and diagnosis (AD vs. (L)MCI vs. cognitively normal (CN)). We observed significant negative associations of baseline ADAS-Cog13 score with PL-PX (coeff.= -0.135/p=3.24E-6/q=1.94E-5) and overall PBV (coeff.= -0.130/p=6.92E-5), and for MMSE with PL-PX (coeff.= 0.040/p=1.28E-9) and PBV (coeff.= 0.038/p=6.50E-9). Logistic regression models showed statistically-significant negative relationships of AD vs. CN diagnosis with PL-PX (coeff.= -0.244/p=0.007) and overall PBV (coeff.= -0.255/p=0.005), i.e., lower values of these indices associated with a higher likelihood of AD, and a similar pattern of LMCI vs. CN diagnosis associations with PL-PX (coeff.= -0.330/p=2.89E-5) and PBV (coeff.= -0.294, p=1.99E-4). These data provide further evidence that altered ethanolamine plasmalogen metabolism contribute to the risk of cognitive impairment in AD and MCI. Failure of plasmalogen synthesis involving liver peroxisomes may adversely affect CNS synaptic and antioxidant functions and contribute to cognitive decline in AD. We are now further examining the connections between plasmalogens and other lipids vs. cognition, associations with gene expression in liver and brain, and network modeling approaches.

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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.231
Teacher spread0.225 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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