Evidence map›Paper›PMID 42060990›Full record

ArticleThe journal of prevention of Alzheimer's disease2026

Amyloid pathology and modifiable risk factors in cognitive decline among cognitively unimpaired older adults.

Ying-Hsin Hsu, Chih-Kuang Liang, Ming-Yueh Chou, Jaysón Davidson, Yu-Chun Wang, Mike A Nalls, Luigi Ferrucci, Mark Cookson, Hirotaka Iwaki

Abstract readMulticenter Study
In one paragraph

Article in The journal of prevention of Alzheimer's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ying-Hsin HsuCenter for Geriatrics and Gerontology, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan; Shu-Zen Junior College of Medicine and Management, Kaohsiung, 821004, Taiwan; Division of Neurology, Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan; Mei-Ho University, Pingtung, 912009, Taiwan.
Chih-Kuang LiangCenter for Geriatrics and Gerontology, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan; Division of Neurology, Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan; Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, 112304, Taiwan; Department of Geriatric Medicine, National Yang Ming Chiao Tung University, Taipei, 112304, Taiwan.
Ming-Yueh ChouCenter for Geriatrics and Gerontology, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan; Mei-Ho University, Pingtung, 912009, Taiwan; Center for Healthy Longevity and Aging Sciences, National Yang Ming Chiao Tung University, Taipei, 112304, Taiwan; Department of Geriatric Medicine, National Yang Ming Chiao Tung University, Taipei, 112304, Taiwan.
Jaysón DavidsonCenter for Alzheimer's and Related Dementias, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA; DataTecnica LLC, Washington, DC, 20037, USA.
Yu-Chun WangCenter for Geriatrics and Gerontology, Kaohsiung Veterans General Hospital, Kaohsiung, 81362, Taiwan; Shu-Zen Junior College of Medicine and Management, Kaohsiung, 821004, Taiwan; Mei-Ho University, Pingtung, 912009, Taiwan; Chia Nan University of Pharmacy & Science, Tainan, 717301, Taiwan.
Mike A NallsCenter for Alzheimer's and Related Dementias, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA; DataTecnica LLC, Washington, DC, 20037, USA.
Luigi FerrucciCenter for Alzheimer's and Related Dementias, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA.
Mark CooksonCenter for Alzheimer's and Related Dementias, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA.
Hirotaka IwakiCenter for Alzheimer's and Related Dementias, National Institute on Aging, National Institutes of Health, Bethesda, MD, 20892, USA; DataTecnica LLC, Washington, DC, 20037, USA. Electronic address: hirotaka.iwaki@nih.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) pathology, particularly amyloid-β (Aβ) deposition, occurs years before clinical symptoms. Modifiable risk factors may influence cognitive trajectories during this preclinical stage, but whether amyloid status alters their effects remains unclear.

objectivesTo investigate interactions between amyloid pathology and modifiable risk factors in predicting longitudinal cognitive decline among cognitively unimpaired older adults. DESIGN AND

settingThis study was a secondary analysis of data derived from two large multicenter longitudinal cohort studies, the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease (A4) Study and the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) Study.

participantsA total of 1707 cognitively unimpaired adults aged 65-85 years were included, comprising 1169 amyloid-positive participants from the A4 Study (Aβ+) and 538 amyloid-negative participants from the LEARN Study (Aβ-). MEASUREMENTS: Cognitive function was assessed every six months using the Preclinical Alzheimer's Cognitive Composite (PACC) over a mean follow-up of 4.9 years. Eight established modifiable risk factors-low education, alcohol use, diabetes, high cholesterol, high blood pressure, obesity, depressive symptoms, and physical inactivity-were evaluated. Linear mixed-effects models were applied to examine associations between each risk factor and longitudinal PACC decline, and to test interactions with amyloid status, adjusting for demographic and genetic covariates.

resultsSignificant interactions between amyloid status and modifiable risk factors were observed for diabetes (adjusted β = -0.206, p = 0.032), high cholesterol (adjusted β = -0.155, p < 0.001), and physical inactivity (adjusted β = -0.161, p = 0.046), indicating combined effects rather than additive effects on cognitive decline among Aβ+ individuals. In the A4 study (Aβ+), low education, diabetes, high cholesterol, and physical inactivity were independently associated with accelerated cognitive decline, whereas obesity was linked to slower decline. In contrast, in the LEARN study (Aβ-), these associations were not statistically significant.

conclusionsIn conclusion, the significant interactions with amyloid status were observed for diabetes, high cholesterol, and physical inactivity, indicating that these risk factors were associated with faster cognitive decline specifically in Aβ+ individuals. The results suggest that consideration of amyloid status may be important when evaluating the potential role of metabolic and lifestyle risk factors in preclinical cognitive decline. In Aβ+ individuals, obesity was associated with slower cognitive decline, while low education was linked to lower baseline cognition or a reduced symptom threshold, without a significant interaction with amyloid status. Future studies should incorporate amyloid status and longitudinal biomarkers to assess whether modifying these factors can slow preclinical cognitive decline.

Indexed as

Alzheimer DiseaseAmyloid beta-PeptidesCognitive DysfunctionAgedAged, 80 and overCognitionFemaleHumansLongitudinal StudiesMaleRisk FactorsAmyloid beta-PeptidesAmyloid pathologyCognitive declineCognitively unimpaired older adultsModifiable risk factors

Identifiers

PMID42060990
PMCPMC13140026

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LicenceCC BY-NC-ND
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Registered trials

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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.