Evidence map›Paper›PMID 37461451›Full record

ArticlebioRxiv : the preprint server for biology2023

Defining Dementia Subtypes Through Neuropsychiatric Symptom-Linked Brain Connectivity Patterns.

Kanhao Zhao, Hua Xie, Gregory A Fonzo, Nancy Carlisle, Ricardo S Osorio, Yu Zhang

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Kanhao ZhaoDepartment of Bioengineering, Lehigh University, Bethlehem, PA, USA.
Hua XieCenter for Neuroscience Research, Children's National Hospital, Washington, DC, USA.
Gregory A FonzoCenter for Psychedelic Research and Therapy, Department of Psychiatry and Behavioral Sciences, Dell Medical School, The University of Texas at Austin, TX, USA.
Nancy CarlisleDepartment of Psychology, Lehigh University, Bethlehem, PA, USA.
Ricardo S OsorioDepartment of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA.
Yu ZhangDepartment of Bioengineering, Lehigh University, Bethlehem, PA, USA.

Funding

Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Arline Faustin · 2020 to 2026
$28.4M
1/2 Neurodevelopmental and clinical trajectories of youth at risk for bipolar I disorderR01MH125886 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI ALMEIDA, JORGE R C, STRAKOWSKI, STEPHEN M · 2021 to 2025
$4.3M
Establishing Multimodal Brain Biomarkers Using Data-driven Analyticsfor Treatment Selection in DepressionR01MH129694 · NIMH · STANFORD UNIVERSITY · PI Yu Zhang · 2023 to 2026
$2.8M
Computational neuroimaging of reward in post-trauma psychopathologyK23MH114023 · NIMH · UNIVERSITY OF TEXAS AT AUSTIN · PI FONZO, GREGORY · 2018 to 2022
$957k
Identifying Transdiagnostic Functional Connectivity Biomarkers for Cognitive Health and PsychopathologyR21MH130956 · NIMH · LEHIGH UNIVERSITY · PI BERDICHEVSKY, YEVGENY · 2023 to 2024
$409k
NIA NIH HHS P30 AG066512NIMH NIH HHS K23 MH114023NIMH NIH HHS R01 MH125886NIMH NIH HHS R01 MH129694NIMH NIH HHS R21 MH130956
6 · The paper itself

Abstract

backgroundDementia is highly heterogeneous, with pronounced individual differences in neuropsychiatric symptoms (NPS) and neuroimaging findings. Understanding the heterogeneity of NPS and associated brain abnormalities is essential for effective management and treatment of dementia.

methodsUsing large-scale neuroimaging data from the Open Access Series of Imaging Studies (OASIS-3), we conducted a multivariate sparse canonical correlation analysis to identify functional connectivity-informed symptom dimensions. Subsequently, we performed a clustering analysis on the obtained latent connectivity profiles to reveal neurophysiological subtypes and examined differences in abnormal connectivity and phenotypic profiles between subtypes.

resultsWe identified two reliable neuropsychiatric subsyndromes - behavioral and anxiety in the connectivity-NPS linked latent space. The behavioral subsyndrome was characterized by the connections predominantly involving the default mode and somatomotor networks and neuropsychiatric symptoms involving nighttime behavior disturbance, agitation, and apathy. The anxiety subsyndrome was mainly contributed by connections involving the visual network and the anxiety neuropsychiatric symptom. By clustering individuals along these two subsyndromes-linked connectivity latent features, we uncovered three subtypes encompassing both dementia patients and healthy controls. Dementia in one subtype exhibited similar brain connectivity and cognitive-behavior patterns to healthy individuals. However, dementia in the other two subtypes showed different dysfunctional connectivity profiles involving the default mode, frontoparietal control, somatomotor, and ventral attention networks, compared to healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity and longitudinal progression of cognitive impairment and behavioral dysfunction.

conclusionsOur findings shed valuable insights into disentangling the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the development of timely and targeted interventions for dementia patients.

Indexed as

Dementia subtypesDisease heterogeneityFunctional connectivityFunctional magnetic resonance imagingNeuropsychiatric symptoms

Identifiers

PMID37461451
PMCPMC10349933

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.