Evidence map›Paper›PMID 31111980›Full record

ArticleHuman brain mapping2019

Brain biomarkers and cognition across adulthood.

Angeliki Tsapanou, Christian Habeck, Yunglin Gazes, Qolamreza Razlighi, Jayant Sakhardande, Yaakov Stern, Timothy A Salthouse

Abstract read
In one paragraph

Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

19 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  11. Neurovascular coupling dysfunction in end-stage renal disease patients related to cognitive impairment.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2021
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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

7 authors.

Angeliki TsapanouCognitive Neuroscience Division, Department of Neurology and the Taub Institute, Columbia University, New York, New York.ORCID 0000-0003-0471-5786
Christian HabeckCognitive Neuroscience Division, Department of Neurology and the Taub Institute, Columbia University, New York, New York.ORCID 0000-0001-9961-7446
Yunglin GazesCognitive Neuroscience Division, Department of Neurology and the Taub Institute, Columbia University, New York, New York.
Qolamreza RazlighiCognitive Neuroscience Division, Department of Neurology and the Taub Institute, Columbia University, New York, New York.ORCID 0000-0001-9588-8062
Jayant SakhardandeCognitive Neuroscience Division, Department of Neurology and the Taub Institute, Columbia University, New York, New York.
Yaakov SternCognitive Neuroscience Division, Department of Neurology and the Taub Institute, Columbia University, New York, New York.
Timothy A SalthouseDepartment of Psychology, University of Virginia, Charlottesville, Virginia.

Funding

Exploring Cognitive Aging Using Reference Ability Neural NetworksR01AG038465 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HABECK, CHRISTIAN GEORG, STERN, YAAKOV · 2011 to 2025
$17.0M
Imaging of Cognition, Learning and Memory in AgingR01AG026158 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI STERN, YAAKOV · 2004 to 2021
$10.9M
Exploring Cognitive Aging Using Refernce Ability Neural NetworksRF1AG038465 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HABECK, CHRISTIAN GEORG, STERN, YAAKOV · 2016 to 2018
$7.6M
Longitudinal changes in white matter integrity predicting cognitive changes in reasoning and vocabulary abilitiesK01AG051777 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GAZES, YUNGLIN · 2016 to 2020
$623k
NIA NIH HHS K01 AG051777NIA NIH HHS R01 AG026158NIA NIH HHS R01 AG038465NIA NIH HHS RF1 AG038465
6 · The paper itself

Abstract

Understanding the associations between brain biomarkers (BMs) and cognition across age is of paramount importance. Five hundred and sixty-two participants (19-80 years old, 16 mean years of education) were studied. Data from structural T1, diffusion tensor imaging, fluid-attenuated inversion recovery, and resting-state functional magnetic resonance imaging scans combined with a neuropsychological evaluation were used. More specifically, the measures of cortical, entorhinal, and parahippocampal thickness, hippocampal and striatal volume, default-mode network and fronto-parietal control network, fractional anisotropy (FA), and white matter hyperintensity (WMH) were assessed. z-Scores for three cognitive domains measuring episodic memory, executive function, and speed of processing were computed. Multiple linear regressions and interaction effects between each of the BMs and age on cognition were examined. Adjustments were made for age, sex, education, intracranial volume, and then, further, for general cognition and motion. BMs were significantly associated with cognition. Across the adult lifespan, slow speed was associated with low striatal volume, low FA, and high WMH burden. Poor executive function was associated with low FA, while poor memory was associated with high WMH burden. After adjustments, results were significant for the associations: speed-FA and WMH, memory-entorhinal thickness. There was also a significant interaction between hippocampal volume and age in memory. In age-stratified analyses, the most significant associations for the young group occurred between FA and executive function, WMH, and memory, while for the old group, between entorhinal thickness and speed, and WMH and speed, executive function. Unique sets of BMs can explain variation in specific cognitive domains across adulthood. Such results provide essential information about the neurobiology of aging.

Indexed as

CerebrumConnectomeGray MatterWhite MatterAdultAgedAged, 80 and overAgingBiomarkersCognitionFemaleHumansMaleMiddle AgedPsychomotor PerformanceYoung AdultBiomarkersagingbrain biomarkerscognition

Identifiers

PMID31111980
PMCPMC6689657

What OpenQuestion holds

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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.