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Record W4221033220 · doi:10.3389/fnagi.2022.838223

Association Between Plasma Apolipoprotein M With Alzheimer’s Disease: A Cross-Sectional Pilot Study From China

2022· article· en· W4221033220 on OpenAlexaboutno aff
Jiayan Xin, Xiao Huang, Ying Sun, Haisong Jiang, Fan Jin, Nengwei Yu, Fuqiang Guo, Fang Ye, Jun Xiao, Weidong Le, Shaojie Yang, Yang Xiang

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2022
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsInternal medicineApolipoprotein ECross-sectional studyMedicineLogistic regressionApolipoprotein BMontreal Cognitive AssessmentAlzheimer's diseaseCognitive declineGastroenterologyEndocrinologyDiseasePsychologyDementiaCholesterolPathology

Abstract

fetched live from OpenAlex

Background Recent evidence of genetics and metabonomics indicated a potential role of apolipoprotein M (ApoM) in the pathogenesis of Alzheimer’s disease (AD). Here, we aimed to investigate the association between plasma ApoM with AD. Methods A multicenter, cross-sectional study recruited patients with AD (n = 67), age- and sex-matched cognitively normal (CN) controls (n = 73). After the data collection of demographic characteristics, lifestyle risk factors, and medical history, we examined and compared the plasma levels of ApoM, tau phosphorylated at threonine 217 (p-tau217) and neurofilament light (NfL). Multivariate logistic regression analysis was applied to determine the association of plasma ApoM with the presence of AD. The correlation analysis was used to explore the correlations between plasma ApoM with cognitive function [Mini–Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA)], activities of daily living (ADL), and the representative blood-based biomarkers (plasma p-tau217 and NfL). Receiver operating characteristic (ROC) analysis and Delong’s test were used to determine the diagnostic power of plasma ApoM. Results Plasma ApoM and its derived indicators (ratios of ApoM/TC, ApoM/TG, ApoM/HDL-C, and ApoM/LDL-C) were significantly higher in AD group than those in CN group (each p < 0.0001). After adjusted for the risk factors of AD, the plasma ApoM and its derived indicators were significantly associated with the presence of AD, respectively. ApoM (OR = 1.058, 95% CI: 1.027–1.090, p < 0.0001), ApoM/TC ratio (OR = 1.239, 95% CI: 1.120–1.372, p < 0.0001), ApoM/TG ratio (OR = 1.064, 95% CI: 1.035–1.095, p < 0.0001), ApoM/HDL-C ratio (OR = 1.069, 95% CI: 1.037–1.102, p < 0.0001), and ApoM/LDL-C ratio (OR = 1.064, 95% CI:1.023–1.106, p = 0.002). In total participants, plasma ApoM was significantly positively correlated with plasma p-tau217, plasma NfL, and ADL (each p < 0.0001) and significantly negatively correlated with MMSE and MoCA (each p < 0.0001), respectively. In further subgroup analyses, these associations remained in different APOEϵ 4 status participants and sex subgroups. ApoM/TC ratio (ΔAUC = 0.056, p = 0.044) and ApoM/TG ratio (ΔAUC = 0.097, p = 0.011) had a statistically remarkably larger AUC than ApoM, respectively. The independent addition of ApoM and its derived indicators to the basic model [combining age, sex, APOEϵ 4, and body mass index (BMI)] led to the significant improvement in diagnostic power, respectively (each p < 0.05). Conclusion All the findings preliminarily uncovered the association between plasma ApoM and AD and provided more evidence of the potential of ApoM as a candidate biomarker of 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)0.001
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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.044
GPT teacher head0.320
Teacher spread0.276 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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