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; Abigail R Manning; Clyde E Markowitz; Christopher M Perrone; Victoria Rautman; Madeleine M Seitz; John A Detre; Michael D Fox; Russell T Shinohara; Theodore D Satterthwaite

doi:10.1016/j.biopsych.2023.11.010

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

Biol Psychiatry. 2023 Nov 18:S0006-3223(23)01722-5. doi: 10.1016/j.biopsych.2023.11.010. Online ahead of print.

Authors

Erica B Baller¹, Elizabeth M Sweeney², Matthew Cieslak¹, Timothy Robert-Fitzgerald², Sydney C Covitz¹, Melissa L Martin², Matthew K Schindler³, Amit Bar-Or³, Ameena Elahi⁴, Bart S Larsen¹, Abigail R Manning², Clyde E Markowitz³, Christopher M Perrone³, Victoria Rautman⁴, Madeleine M Seitz⁵, John A Detre⁶, Michael D Fox⁷, Russell T Shinohara⁸, Theodore D Satterthwaite⁹

Affiliations

¹ Penn Lifespan Informatics and Neuroimaging Center, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
² Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
³ Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Neuroinflammation and Neurotherapeutics, University of Pennsylvania, Philadelphia, Pennsylvania.
⁴ Department of Information Services, University of Pennsylvania, Philadelphia, Pennsylvania.
⁵ Penn 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.
⁶ Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania.
⁷ Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
⁸ Penn 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.
⁹ Penn 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.

PMID: 37981178
PMCID: PMC11101593 (available on 2025-05-18)
DOI: 10.1016/j.biopsych.2023.11.010

Abstract

Background: Multiple 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.

Methods: Using 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.

Results: MS 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).

Conclusions: We 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.

Keywords: Depression; Lesion network mapping; MRI; Multiple sclerosis; Networks; White matter.

Abstract

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