Evidence map›Paper›PMID 39294332›Full record

ArticleCommunications biology2024

Fingerprints of brain disease: connectome identifiability in Alzheimer's disease.

Sara Stampacchia, Saina Asadi, Szymon Tomczyk, Federica Ribaldi, Max Scheffler, Karl-Olof Lövblad, Michela Pievani, Aïda B Fall, Maria Giulia Preti, Paul G Unschuld and 5 more

Abstract read
In one paragraph

Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Neural manifold connectomics reveals multiregime functional connectivity.bioRxiv : the preprint server for biology · 2026
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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

15 authors.

Sara StampacchiaNeuro-X Institute and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. sara.stampacchia@epfl.ch.ORCID 0000-0001-9545-3376
Saina AsadiDepartment of Radiology and Medical Informatics, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.
Szymon TomczykLaboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
Federica RibaldiLaboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
Max SchefflerDivision of Radiology, Geneva University Hospitals, Geneva, Switzerland.
Karl-Olof LövbladDepartment of Radiology and Medical Informatics, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.
Michela PievaniLab of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Aïda B FallFaculty of Medicine, University of Geneva, Geneva, Switzerland.
Maria Giulia PretiNeuro-X Institute and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.ORCID 0000-0002-5323-5327
Paul G UnschuldDivision of Geriatric Psychiatry, University Hospitals of Geneva (HUG), 1226, Thônex, Switzerland.ORCID 0000-0002-6116-3386
Dimitri Van De VilleNeuro-X Institute and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.ORCID 0000-0002-2879-3861
Olaf BlankeNeuro-X Institute and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.ORCID 0000-0002-9745-3983
Giovanni B FrisoniLaboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
Valentina Garibotto *Department of Radiology and Medical Informatics, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland.
Enrico Amico *Neuro-X Institute and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. e.amico@bham.ac.uk.ORCID 0000-0001-6705-9689

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
NIA NIH HHS U01 AG024904
6 · The paper itself

Abstract

Functional connectivity patterns in the human brain, like the friction ridges of a fingerprint, can uniquely identify individuals. Does this "brain fingerprint" remain distinct even during Alzheimer's disease (AD)? Using fMRI data from healthy and pathologically ageing subjects, we find that individual functional connectivity profiles remain unique and highly heterogeneous during mild cognitive impairment and AD. However, the patterns that make individuals identifiable change with disease progression, revealing a reconfiguration of the brain fingerprint. Notably, connectivity shifts towards functional system connections in AD and lower-order cognitive functions in early disease stages. These findings emphasize the importance of focusing on individual variability rather than group differences in AD studies. Individual functional connectomes could be instrumental in creating personalized models of AD progression, predicting disease course, and optimizing treatments, paving the way for personalized medicine in AD management.

Indexed as

Alzheimer DiseaseBrainConnectomeMagnetic Resonance ImagingAgedAged, 80 and overCognitive DysfunctionDisease ProgressionFemaleHumansMaleMiddle Aged

Identifiers

PMID39294332
PMCPMC11411139

What OpenQuestion holds

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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.