Evidence map›Paper›PMID 35023051›Full record

ArticleAging clinical and experimental research2022

Longitudinal resting-state functional connectivity and regional brain atrophy-based biomarkers of preclinical cognitive impairment in healthy old adults.

Jean de Dieu Uwisengeyimana, Benedictor Alexander Nguchu, Yaming Wang, Du Zhang, Yanpeng Liu, Zhoufan Jiang, Xiaoxiao Wang, Bensheng Qiu

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in Aging clinical and experimental research, 2022. 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
0.6field-weighted citation impact, top 38% 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, 5 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

8 authors at 1 institution in 2 countries.

Jean de Dieu UwisengeyimanaHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Benedictor Alexander NguchuHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Yaming WangHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Du ZhangHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Yanpeng LiuHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Zhoufan JiangHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Xiaoxiao WangHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China. wang506@ustc.edu.cn.ORCID http://orcid.org/0000-0002-8498-7388
Bensheng QiuHefei National Lab for Physical Sciences at the Microscale and Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, 230026, Anhui, China. bqiu@ustc.edu.cn.
University of Science and Technology of China · CN

Funding

chinese academy of sciences (cas) block grantsnational natural science foundation of china 81701665world academy of sciences (twas) block grants
6 · The paper itself

Abstract

backgroundIntervention against age-related neurodegenerative diseases may be difficult once extensive structural and functional deteriorations have already occurred in the brain.

aimInvestigating 6-year longitudinal changes and implications of regional brain atrophy and functional connectivity in the triple-network model as biomarkers of preclinical cognitive impairment in healthy aging.

methodsWe acquired longitudinal cognitive scores and magnetic resonance imaging (MRI) data from 74 healthy old adults. Resting-state functional MRI (rs-fMRI) analysis was conducted using FSL6.0.1 to examine functional connectivity changes and regional brain morphometries were quantified using FreeSurfer5.3. Finally, we cross-validated and compared two support vector machine (SVM) regression models to predict future 6-year cognition score from the baseline regional brain atrophy and resting-state functional connectivity (rs-FC) measures.

resultsAfter a 6-year follow-up, our results (P < 0.05-corrected) indicated significant connectivity reduction within all the three brain networks, significant differences in regional brain volumes and cortical thickness. We also observed significant improvement in episodic memory and significant decline in executive functions. Finally, comparing the two models, we observed that regional brain atrophy predictors were more efficient in approximating future 6-year cognitive scores (R = 0.756, P < 0.0001) than rs-FC predictors (R = 0.6, P < 0.0001).

conclusionThis study used longitudinal data to keep subject variability low and to increase the validity of the results. We demonstrated significant changes in structural and functional MRI over 6 years. Our findings present a potential neuroimaging-based biomarker to detect cognitive impairment and prevent risks of neurodegenerative diseases in healthy old adults.

Indexed as

Cognitive DysfunctionNeurodegenerative DiseasesAtrophyBiomarkersBrainHumansMagnetic Resonance ImagingBiomarkersCognitive functionFunctional connectivityLongitudinal studyNormal agingRegional brain atrophy

Identifiers

PMID35023051
OpenAlexW4206642041

What OpenQuestion holds

Textmetadata
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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.