Evidence map›Paper›PMID 37981178›Full record

ArticleBiological psychiatry2024

Mapping the Relationship of White Matter Lesions to Depression in Multiple Sclerosis.

Erica B Baller, Elizabeth M Sweeney, Matthew Cieslak, Timothy Robert-Fitzgerald, Sydney C Covitz, Melissa L Martin, Matthew K Schindler, Amit Bar-Or, Ameena Elahi, Bart S Larsen and 9 more

Open access · hybridAbstract read
In one paragraph

Article in Biological psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
7.9field-weighted citation impact, top 2% 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

23 citing papers in PubMed, 31 citations in OpenAlex.

  1. Review
  2. Presence and Impact of Fatigue in Patients With Multiple Sclerosis.Medical science monitor : international medical journal of experimental and clinical research · 2026
    Observational
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Affective reserve in multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025
    Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Association of Anxiety with Uncinate Fasciculus Lesion Burden in Multiple Sclerosis.medRxiv : the preprint server for health sciences · 2024
    Article
  19. Article
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 3 institutions in 1 country.

Erica B BallerPenn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
Elizabeth M SweeneyPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
Matthew CieslakPenn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
Timothy Robert-FitzgeraldPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
Sydney C CovitzPenn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
Melissa L MartinPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
Matthew K SchindlerDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Neuroinflammation and Neurotherapeutics, University of Pennsylvania, Philadelphia, Pennsylvania.
Amit Bar-OrDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Neuroinflammation and Neurotherapeutics, University of Pennsylvania, Philadelphia, Pennsylvania.
Ameena ElahiDepartment of Information Services, University of Pennsylvania, Philadelphia, Pennsylvania.
Bart S LarsenPenn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
Abigail R ManningPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
Clyde E MarkowitzDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Neuroinflammation and Neurotherapeutics, University of Pennsylvania, Philadelphia, Pennsylvania.
Christopher M PerroneDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Neuroinflammation and Neurotherapeutics, University of Pennsylvania, Philadelphia, Pennsylvania.
Victoria RautmanDepartment of Information Services, University of Pennsylvania, Philadelphia, Pennsylvania.
Madeleine M SeitzPenn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
John A DetreDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.
Michael D FoxCenter for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Russell T ShinoharaPenn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.
Theodore D SatterthwaitePenn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania. Electronic address: sattertt@pennmedicine.upenn.edu.
Penn Center for AIDS Research · USUniversity of Pennsylvania · USBrigham and Women's Hospital · US

Funding

Longitudinal Mapping of Network Development Underlying Executive Dysfunction in AdolescenceR01MH113550 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Danielle Smith Bassett, Theodore Satterthwaite · 2018 to 2026
$6.9M
SCHIZOPHRENIA: A NEUROPSYCHIATRIC PERSPECTIVET32MH019112 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GUR, RAQUEL E · 1990 to 2024
$6.2M
Personalized Functional Network Modeling to Characterize and Predict Psychopathology in YouthR01EB022573 · NIBIB · UNIVERSITY OF PENNSYLVANIA · PI Yong Fan, Theodore Satterthwaite · 2016 to 2026
$6.0M
Inter-modal Coupling Image AnalyticsR01MH112847 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI Theodore Satterthwaite, Russell Takeshi Shinohara · 2017 to 2026
$5.9M
Precision mapping of individualized executive networks in youthR37MH125829 · NIMH · UNIVERSITY OF MINNESOTA · PI Damien A Fair, Theodore Satterthwaite · 2021 to 2026
$4.7M
Harmonization of Multi-Site Neuroimaging Data from Complex Study DesignsR01MH123550 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2025
$4.0M
The Neuroimaging Brain Chart Software SuiteU24NS130411 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI Christos Davatzikos, Yong Fan · 2023 to 2026
$3.7M
Reproducible imaging-based brain growth charts for psychiatryR01MH120482 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI MILHAM, MICHAEL PETER, SATTERTHWAITE, THEODORE · 2019 to 2023
$3.5M
Advanced Statistical Analytics of MRI in MSR01NS112274 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2020 to 2024
$2.8M
Network Control and Functional Context: Mechanisms for TMS ResponseRF1MH116920 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI BASSETT, DANIELLE SMITH, OATHES, DESMOND · 2018 to 2018
$2.8M
Statistical methods for large and complex databases of ultra-high-dimensionalR01NS085211 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI SHINOHARA, RUSSELL TAKESHI · 2013 to 2017
$1.8M
Brain iron as a neurodevelopmental mechanism for transdianostic executive dysfunctionR00MH127293 · NIMH · UNIVERSITY OF MINNESOTA · PI Bart Larsen · 2023 to 2026
$821k
NIA NIH HHS R21 AG070434NIBIB NIH HHS R01 EB022573NIMH NIH HHS K23 MH133118NIMH NIH HHS K99 MH127293NIMH NIH HHS L30 MH127652NIMH NIH HHS R00 MH127293NIMH NIH HHS R01 MH112847NIMH NIH HHS R01 MH113550NIMH NIH HHS R01 MH120482NIMH NIH HHS R01 MH123550NIMH NIH HHS R37 MH125829NIMH NIH HHS RF1 MH116920NIMH NIH HHS T32 MH019112NINDS NIH HHS R01 NS085211NINDS NIH HHS R01 NS112274NINDS NIH HHS U24 NS130411
6 · The paper itself

Abstract

backgroundMultiple sclerosis (MS) is an immune-mediated neurological disorder, and up to 50% of patients experience depression. We investigated how white matter network disruption is related to depression in MS.

methodsUsing electronic health records, 380 participants with MS were identified. Depressed individuals (MS+Depression group; n = 232) included persons who had an ICD-10 depression diagnosis, had a prescription for antidepressant medication, or screened positive via Patient Health Questionnaire (PHQ)-2 or PHQ-9. Age- and sex-matched nondepressed individuals with MS (MS-Depression group; n = 148) included persons who had no prior depression diagnosis, had no psychiatric medication prescriptions, and were asymptomatic on PHQ-2 or PHQ-9. Research-quality 3T structural magnetic resonance imaging was obtained as part of routine care. We first evaluated whether lesions were preferentially located within the depression network compared with other brain regions. Next, we examined if MS+Depression patients had greater lesion burden and if this was driven by lesions in the depression network. Primary outcome measures were the burden of lesions (e.g., impacted fascicles) within a network and across the brain.

resultsMS lesions preferentially affected fascicles within versus outside the depression network (β = 0.09, 95% CI = 0.08 to 0.10, p < .001). MS+Depression patients had more lesion burden (β = 0.06, 95% CI = 0.01 to 0.10, p = .015); this was driven by lesions within the depression network (β = 0.02, 95% CI = 0.003 to 0.040, p = .020).

conclusionsWe demonstrated that lesion location and burden may contribute to depression comorbidity in MS. MS lesions disproportionately impacted fascicles in the depression network. MS+Depression patients had more disease than MS-Depression patients, which was driven by disease within the depression network. Future studies relating lesion location to personalized depression interventions are warranted.

Indexed as

Magnetic Resonance ImagingMultiple SclerosisWhite MatterAdultBrainDepressionFemaleHumansMaleMiddle AgedDepressionLesion network mappingMRIMultiple sclerosisNetworksWhite matter

Identifiers

PMID37981178
PMCPMC11101593
OpenAlexW4388799114

What OpenQuestion holds

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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.