Evidence map›Paper›PMID 36362077›Full record

ArticleInternational journal of molecular sciences2022

Blood Analytes as Biomarkers of Mechanisms Involved in Alzheimer's Disease Progression.

Andrea Baldini, Alberto Greco, Mirko Lomi, Roberta Giannelli, Paola Canale, Andrea Diana, Cristina Dolciotti, Renata Del Carratore, Paolo Bongioanni

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 1 country.

Andrea BaldiniDepartment of Information Engineering, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy.ORCID 0000-0003-2003-7604
Alberto GrecoDepartment of Information Engineering, Faculty of Engineering, University of Pisa, 56122 Pisa, Italy.ORCID 0000-0002-4822-5562
Mirko LomiInstitute of Clinical Physiology, National Research Council, 56124 Pisa, Italy.
Roberta GiannelliInstitute of Clinical Physiology, National Research Council, 56124 Pisa, Italy.
Paola CanaleInstitute of Clinical Physiology, National Research Council, 56124 Pisa, Italy.
Andrea DianaDepartment of Biomedical Sciences, University of Cagliari, 09042 Cagliari, Italy.ORCID 0000-0002-7247-6994
Cristina DolciottiMedical Specialties Department, Azienda Ospedaliero-Universitaria Pisana, 56126 Pisa, Italy.
Renata Del CarratoreInstitute of Clinical Physiology, National Research Council, 56124 Pisa, Italy.
Paolo BongioanniMedical Specialties Department, Azienda Ospedaliero-Universitaria Pisana, 56126 Pisa, Italy.
Istituto di Fisiologia Clinica · ITAssociazione Italiana Vulvodinia Onlus · ITUniversity of Pisa · ITUniversity of Cagliari · IT

Funding

Regione Toscana (Italy) DSB.AD006.289-NEWDEM
6 · The paper itself

Abstract

Alzheimer's disease (AD) is the leading cause of dementia, but the pathogenetic factors are not yet well known, and the relationships between brain and systemic biochemical derangements and disease onset and progression are unclear. We aim to focus on blood biomarkers for an accurate prognosis of the disease. We used a dataset characterized by longitudinal findings collected over the past 10 years from 90 AD patients. The dataset included 277 observations (both clinical and biochemical ones, encompassing blood analytes encompassing routine profiles for different organs, together with immunoinflammatory and oxidative markers). Subjects were grouped into four severity classes according to the Clinical Dementia Rating (CDR) Scale: mild (CDR = 0.5 and CDR = 1), moderate (CDR = 2), severe (CDR = 3) and very severe (CDR = 4 and CDR = 5). Statistical models were used for the identification of potential blood markers of AD progression. Moreover, we employed the Pathfinder tool of the Reactome database to investigate the biological pathways in which the analytes of interest could be involved. Statistical results reveal an inverse significant relation between four analytes (high-density cholesterol, total cholesterol, iron and ferritin) with AD severity. In addition, the Reactome database suggests that such analytes could be involved in pathways that are altered in AD progression. Indeed, the identified blood markers include molecules that reflect the heterogeneous pathogenetic mechanisms of AD. The combination of such blood analytes might be an early indicator of AD progression and constitute useful therapeutic targets.

Indexed as

Alzheimer DiseaseBiomarkersCholesterolDisease ProgressionHumansNeuropsychological TestsSeverity of Illness IndexBiomarkersCholesterolAlzheimer’s diseaseblood neurodegenerative biomarkersgeneralized linear mixed-effects modelspathways

Identifiers

PMID36362077
PMCPMC9657599
OpenAlexW4308125669

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.