Evidence map›Paper›PMID 38660510›Full record

ArticleFrontiers in endocrinology2024

Blood-based biological ageing and red cell distribution width are associated with prevalent Parkinson's disease: findings from a large Italian population cohort.

Alessandro Gialluisi, Alfonsina Tirozzi, Simona Costanzo, Maria Ilenia De Bartolo, Daniele Belvisi, Sara Magnacca, Amalia De Curtis, Stefania Falciglia, Moreno Ricci, Chiara Cerletti and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 6 citations in OpenAlex.

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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

14 authors at 3 institutions in 1 country.

Alessandro Gialluisi *Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Alfonsina Tirozzi *Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Simona CostanzoDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Maria Ilenia De BartoloIRCCS NEUROMED, Pozzilli, Italy.
Daniele BelvisiIRCCS NEUROMED, Pozzilli, Italy.
Sara MagnaccaDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Amalia De CurtisDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Stefania FalcigliaUOC Governance del Farmaco, Azienda Sanitaria Regionale del Molise -ASREM, Campobasso, Italy.
Moreno RicciUOC Governance del Farmaco, Azienda Sanitaria Regionale del Molise -ASREM, Campobasso, Italy.
Chiara CerlettiDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Maria Benedetta DonatiDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Alfredo BerardelliIRCCS NEUROMED, Pozzilli, Italy.
Giovanni de GaetanoDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Licia IacovielloDepartment of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, Italy.
Istituto Neurologico Mediterraneo · ITLibera Università Maria SS. Assunta · ITUniversity of Molise · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Aging clocks tag the actual underlying age of an organism and its discrepancy with chronological age and have been reported to predict incident disease risk in the general population. However, the relationship with neurodegenerative risk and in particular with Parkinson's Disease (PD) remains unclear, with few discordant findings reporting associations with both incident and prevalent PD risk. Objective: To clarify this relationship, we computed a common aging clock based on blood markers and tested the resulting discrepancy with chronological age (ΔPhenoAge) for association with both incident and prevalent PD risk. Methods: In a large Italian population cohort - the Moli-sani study (N=23,437; age ≥ 35 years; 52% women) - we carried out both Cox Proportional Hazards regressions modelling ΔPhenoAge as exposure and incident PD as outcome, and linear models testing prevalent PD as exposure and ΔPhenoAge as outcome. All models were incrementally adjusted for age, sex, education level completed and other risk/protective factors previously associated with PD risk in the same cohort (prevalent dysthyroidism, hypertension, diabetes, use of oral contraceptives, exposure to paints, daily coffee intake and cigarette smoking). Results: No significant association between incident PD risk (209 cases, median (IQR) follow-up time 11.19 (2.03) years) and PhenoAging was observed (Hazard Ratio [95% Confidence Interval] = 0.98 [0.71; 1.37]). However, a small but significant increase of ΔPhenoAge was observed in prevalent PD cases vs healthy subjects (β (Standard Error) = 1.39 (0.70)). An analysis of each component biomarker of PhenoAge revealed a significant positive association of prevalent PD status with red cell distribution width (RDW; β (SE) = 0.46 (0.18)). All the remaining markers did not show any significant evidence of association. Conclusion: The reported evidence highlights systemic effects of prevalent PD status on biological aging and red cell distribution width. Further cohort and functional studies may help shedding a light on the related pathways altered at the organism level in prevalent PD, like red cells variability, inflammatory and oxidative stress mechanisms.

Indexed as

AgingErythrocyte IndicesParkinson DiseaseAdultAgedBiomarkersCohort StudiesFemaleHumansIncidenceItalyMaleMiddle AgedPrevalenceRisk FactorsBiomarkersbiological aginginflammationoxidative stressParkinson’s diseasePhenoAgered cell distribution width

Identifiers

PMID38660510
PMCPMC11041016
OpenAlexW4394678634

What OpenQuestion holds

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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.