New approach for early and specific Alzheimer disease diagnosis from different plasma biomarkers.

Fecha de publicación: Fecha Ahead of Print:

Autores de IIS La Fe

Participantes ajenos a IIS La Fe

  • Forte, Anabel
  • Lara, Sergio

Grupos

Abstract

BACKGROUND: Alzheimer Disease (AD) is a complex pathology, in which several biochemical pathways could be involved. Therefore, the development of clinical studies combining different nature biomarkers in an AD diagnosis approach is required. Specifically, the present study evaluated blood biomarkers from different molecular pathways (epigenomics, lipid metabolism, lipid peroxidation), to obtain an early and specific AD diagnosis approach. METHODS: The participants were classified into early AD (n=53), and non-AD (healthy controls, other dementias) (n=83). Blood samples were collected and biochemical determinations (microRNAs, lipids, lipid peroxidation compounds) were carried out by quantitative PCR and liquid chromatography coupled to mass spectrometry, respectively. Then, a logistic regression model with a Bayesian variable selection procedure was developed. RESULTS: The Bayesian variable selection procedure for microRNAs did not show any relevant variable. Therefore, microRNA biomarkers were excluded. So, the developed model considered only lipids and lipid peroxidation compounds. The corresponding selected variables were age, 18:0 LPC, PGE2, isoprostanes and, isofurans. The validated model (by leave-one-out cross-validation) provided satisfactory diagnosis indexes (AUC 0.83, Sensitivity 87 %, Specificity 79 %). CONCLUSION: The developed model included biomarkers from different pathways (lipid metabolism, oxidative stress), achieving a promising approach to early, specific and, minimally invasive AD diagnosis. Nevertheless, further work to validate clinically these preliminary results with an external cohort is required. Also, the integration of different compounds coming from several biochemical pathways could constitute a relevant research field for the development of AD therapeutic targets.

Copyright © 2024 Elsevier B.V. All rights reserved.

Datos de la publicación

ISSN/ISSNe:
0009-8981, 1873-3492

CLINICA CHIMICA ACTA  ELSEVIER

Tipo:
Article
Páginas:
117842-117842
PubMed:
38417780
Factor de Impacto:
1,086 SCImago
Cuartil:
Q1 SCImago

Citas Recibidas en Web of Science: 5

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Keywords

  • Alzheimer disease; Bayesian statistics; Biomarker; Diagnosis model; Lipid; Lipid peroxidation; Plasma; microRNA

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