Evidence map›Paper›PMID 38517924›Full record

ArticlePloS one2024

INFLAMMATION's cognitive impact revealed by a novel "Line of Identity" approach.

Donald R Royall, Raymond F Palmer

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

3 citing papers in PubMed, 1 citations in OpenAlex.

  1. Article
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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

2 authors at 1 institution in 1 country.

Donald R RoyallDepartment of Psychiatry and Behavioral Science, The University of Texas Health Science Center, San Antonio, Texas, United States of America.ORCID 0000-0001-6475-0300
Raymond F PalmerDepartment of Family and Community Medicine, The University of Texas Health Science Center, San Antonio, Texas, United States of America.
The University of Texas Health Science Center at San Antonio · US

Funding

South Texas Alzheimer's Disease Research CenterP30AG066546 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Mohamad Habes · 2021 to 2026
$24.0M
NIA NIH HHS P30 AG066546
6 · The paper itself

Abstract

importanceDementia is an "overdetermined" syndrome. Few individuals are demented by any single biomarker, while several may independently explain small fractions of dementia severity. It may be advantageous to identify individuals afflicted by a specific biomarker to guide individualized treatment.

objectiveWe aim to validate a psychometric classifier to identify persons adversely impacted by inflammation and replicate it in a second cohort.

designSecondary analyses of data collected by the Texas Alzheimer's Research and Care Consortium (TARCC) (N = 3497) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N = 1737).

settingTwo large, well-characterized multi-center convenience samples.

participantsVolunteers with normal cognition (NC), Mild Cognitive Impairment (MCI) or clinical "Alzheimer's Disease (AD)". EXPOSURE: Participants were assigned to "Afflicted" or "Resilient" classes on the basis of a psychometric classifier derived by confirmatory factor analysis. MAIN OUTCOME(S) AND MEASURE(S): The groups were contrasted on multiple assessments and biomarkers. The groups were also contrasted regarding 4-year prospective conversions to "AD" from non-demented baseline diagnoses (controls and MCI). The Afflicted groups were predicted to have adverse levels of inflammation-related blood-based biomarkers, greater dementia severity and greater risk of prospective conversion.

resultsIn ADNI /plasma, 47.1% of subjects were assigned to the Afflicted class. 44.6% of TARCC's subjects were afflicted, 49.5% of non-Hispanic Whites (NHW) and 37.2% of Mexican Americans (MA). There was greater dementia severity in the Afflicted class [by ANOVA: ADNI /F(1) = 686.99, p <0.001; TARCC /F(1) = 1544.01, p <0.001]. "INFLAMMATION" factor composite scores were significantly higher (adverse) in Afflicted subjects [by ANOVA in ADNI /plasma F(1) = 1642.64, p <0.001 and in TARCC /serum F(1) = 3059.96, p <0.001]. Afflicted cases were more likely to convert to AD in the next four years [by Cox's F, ADNI /plasma: F (252, 268) = 3.74 p < 0.001; TARCC /serum: F (160, 134) = 3.03, p < 0.001 (in TARCC's entire sample), F (110, 90) = 4.92, p <0.001 in NHW, and F(50, 44) = 2.13, p = 0.006 in MA]. The proportions converting were similar among afflicted NHW in both cohorts /biofluids but MA exhibited a lower risk (7% in TARCC /serum at 48 months). CONCLUSIONS AND RELEVANCE: Our inflammation-specific psychometric classifier selects individuals with pre-specified biomarker profiles and predicts conversion to "AD" across cohorts, biofluids, and ethnicities. This algorithm might be applied to any dementia-related biomarker making the psychometric estimation of individual biomarker effects feasible without biomarker assessment. Our approach also distinguishes individuals resilient to individual biomarker effects allowing for more accurate prediction and precision intervention.

Indexed as

Alzheimer DiseaseCognitive DysfunctionBiomarkersCognitionHumansInflammationProspective StudiesBiomarkers

Identifiers

PMID38517924
PMCPMC10959355
OpenAlexW4393079696

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.