{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T03:25:13Z","timestamp":1782357913950,"version":"3.54.5"},"reference-count":51,"publisher":"Public Library of Science (PLoS)","issue":"3","license":[{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Importance<\/jats:title>\n<jats:p>Dementia is an \u201coverdetermined\u201d 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Objective<\/jats:title>\n<jats:p>We aim to validate a psychometric classifier to identify persons adversely impacted by inflammation and replicate it in a second cohort.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Design<\/jats:title>\n<jats:p>Secondary analyses of data collected by the Texas Alzheimer\u2019s Research and Care Consortium (TARCC) (N = 3497) and the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) (N = 1737).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Setting<\/jats:title>\n<jats:p>Two large, well-characterized multi-center convenience samples.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec005\">\n<jats:title>Participants<\/jats:title>\n<jats:p>Volunteers with normal cognition (NC), Mild Cognitive Impairment (MCI) or clinical \u201cAlzheimer\u2019s Disease (AD)\u201d.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec006\">\n<jats:title>Exposure<\/jats:title>\n<jats:p>Participants were assigned to \u201cAfflicted\u201d or \u201cResilient\u201d classes on the basis of a psychometric classifier derived by confirmatory factor analysis.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec007\">\n<jats:title>Main outcome(s) and measure(s)<\/jats:title>\n<jats:p>The groups were contrasted on multiple assessments and biomarkers. The groups were also contrasted regarding 4-year prospective conversions to \u201cAD\u201d 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.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec008\">\n<jats:title>Results<\/jats:title>\n<jats:p>In ADNI \/plasma, 47.1% of subjects were assigned to the Afflicted class. 44.6% of TARCC\u2019s 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 &lt;0.001; TARCC \/F(1) = 1544.01, p &lt;0.001]. \u201cINFLAMMATION\u201d factor composite scores were significantly higher (adverse) in Afflicted subjects [by ANOVA in ADNI \/plasma F(1) = 1642.64, p &lt;0.001 and in TARCC \/serum F(1) = 3059.96, p &lt;0.001]. Afflicted cases were more likely to convert to AD in the next four years [by Cox\u2019s F, ADNI \/plasma: F (252, 268) = 3.74 p &lt; 0.001; TARCC \/serum: F (160, 134) = 3.03, p &lt; 0.001 (in TARCC\u2019s entire sample), F (110, 90) = 4.92, p &lt;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).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec009\">\n<jats:title>Conclusions and relevance<\/jats:title>\n<jats:p>Our inflammation-specific psychometric classifier selects individuals with pre-specified biomarker profiles and predicts conversion to \u201cAD\u201d 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.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0295386","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T17:32:11Z","timestamp":1711128731000},"page":"e0295386","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["INFLAMMATION\u2019s cognitive impact revealed by a novel \u201cLine of Identity\u201d approach"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6475-0300","authenticated-orcid":true,"given":"Donald R.","family":"Royall","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raymond 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