Evidence map›Paper›PMID 41966600›Full record

ArticleThe journal of prevention of Alzheimer's disease2026

Multidimensional modeling of biological aging: integrating gait, eye movement, rest-state functional connectivity, and plasma biomarkers in non-dementia older adults.

Jingyi Lin, Yiliang Liu, Ziyu Ouyang, Xuan Yang, Sizhe Zhang, Tianyan Xu, Qijie Yang, Yuan Zhu, Meidan Wan, Xuewen Xiao and 5 more

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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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0citing papers 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

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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

15 authors.

Jingyi LinHunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha 410008, China; Department of Biology, Emory University, Atlanta, Georgia 30301, USA.
Yiliang LiuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Ziyu OuyangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Xuan YangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Sizhe ZhangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Tianyan XuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Qijie YangDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Yuan ZhuDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Meidan WanDepartment of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China.
Xuewen XiaoHunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China; Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha 410008, China.
Xiangmin FanInstitute of Software, Chinese Academy of Sciences, Beijing 100000, China.
Beisha TangHunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China; Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha 410008, China.
Lu ShenHunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China; Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha 410008, China.
Bin JiaoHunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China; Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha 410008, China.
Shilin LuoHunan International Scientific and Technological Cooperation Base of Neurodegenerative and Neurogenetic Diseases, Xiangya Hospital, Central South University, Changsha 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha 410008, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha 410008, China; Engineering Research Center of Hunan Province in Cognitive Impairment Disorders, Central South University, Changsha 410008, China. Electronic address: shilin_luo@csu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate modeling of biological age has clinical value for risk stratification, personalized prevention, and intervention planning, promoting proactive healthcare for aging and age-related diseases. Because aging is multidimensional, robust and interpretable multimodal approaches are needed. We studied 908 non-dementia older adults (> 60 years), collecting data on gait, eye movements, resting-state functional connectivity (rs-FC), and plasma biomarkers (neurofilament light chain, NfL, and glial fibrillary acidic protein, GFAP). Fourteen gait features, two eye movement features, 19 rs-FC features, and plasma GFAP levels were significantly correlated with age (p < 0.05). Among single-domain models, eye movement features showed the strongest predictive performance (R

Indexed as

AgingBrainEye MovementsGaitAgedAged, 80 and overBiomarkersFemaleGlial Fibrillary Acidic ProteinHumansMagnetic Resonance ImagingMaleMiddle AgedRestBiomarkersGlial Fibrillary Acidic ProteinBiological agingEye movementGait analysisPlasma biomarkersResting-state functional connectivity

Identifiers

PMID41966600
PMCPMC13091995

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.