Data-Driven Subgroups in Depression Derived from Directed Functional Connectivity Paths at Rest
Open accessAbstract
Depressed patients show abnormalities in brain connectivity at rest, including hyperconnectivity within the default mode network (DMN). However, there is well-known heterogeneity in the clinical presentation of depression that is overlooked when averaging connectivity data. We used data-driven parsing of neural connectivity to reveal subgroups among 80 depressed patients completing resting state fMRI. Directed functional connectivity paths (eg, region A influences region B) within a depression-relevant network were characterized using Group Iterative Multiple Model Estimation, a method shown to accurately recover the direction and presence of connectivity paths in individual participants. Individuals were clustered using community detection on neural connectivity estimates. Subgroups were compared on network features and on clinical and biological/demographic characteristics that influence depression prognosis. Two subgroups emerged. Subgroup A, containing 71% of the patients, showed a typical pattern of connectivity across DMN nodes, as previously reported in depressed patients on average. Subgroup B exhibited an atypical connectivity profile lacking DMN connectivity, with increased dorsal anterior cingulate-driven connectivity paths. Subgroup B members had an over-representation of females (87% of Subgroup B vs 65% of Subgroup A; χ 2=3.89, p=0.049), comorbid anxiety diagnoses (42.9% of Subgroup B vs 17.5% of Subgroup A; χ 2=5.34, p=.02), and highly recurrent depression (63.2% of Subgroup B vs 31.8% of Subgroup A; χ 2=5.38, p=.02). Neural connectivity-based categorization revealed an atypical pattern of connectivity in a depressed patient subset that would be overlooked in group comparisons of depressed and healthy participants, and tracks with clinically relevant phenotypes including anxious depression and episodic recurrence. Data-driven parsing suggests heterogeneous substrates of depression; ideally, future work building on these findings will inform personalized treatment.
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Marked heterogeneity of depressed patients is evident at the neural network, cognitive, information processing, and clinical levels.
“Equally noteworthy, however, is the marked heterogeneity of depressed patients, which is evident at the neural network 143,144 , cognitive 145 , information processing 145,146 , and clinical 147 levels, and may help to explain the fact that no known intervention strategy is effective for all depressed patients.”
From Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model (2020) · cites this paper as [143]
FCS alterations in these regions have been proven to be related to regulation of widespread cognitive, emotional, and executive control functions in MDD.
“The FCS alterations in these regions have been proven to be related to the regulation of widespread cognitive, emotional, and executive control functions in patients with MDD [6, 42-50].”
From Mapping neurophysiological subtypes of major depressive disorder using normative models of the functional connectome (2023) · cites this paper as [46]
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Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model
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“Equally noteworthy, however, is the marked heterogeneity of depressed patients, which is evident at the neural network [143, 144], cognitive [145], information processing [145, 146], and clinical [147] levels, and may help to explain the fact that no known intervention strategy is effective for all depressed”
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- Authors
- Price, R. B., Gates, K., Kraynak, T. E., Thase, M. E., & Siegle, G. J.
- Affiliations
- University of Pittsburgh (US)
- University of North Carolina at Chapel Hill (US)
- Philadelphia VA Medical Center (US)
- Corresponding author
- Price, Rebecca B
- Venue
- Neuropsychopharmacology
- Published
- 2017-05-12
- Volume
- 42
- Issue
- 13
- Pages
- 2623-2632
- ISSN
- 0893-133X (ISSN-L)
- 1740-634X
- PMC
- PMC5686504
- OpenAlex
- W2613978285
- Cited by
- 98
- References
- 61
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 12 · 2023: 8 · 2022: 13 · 2021: 12 · 2020: 13 · 2019: 12 · 2018: 5 · 2017: 1
- FWCI
- 4.86
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Neuropsychopharmacology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Funders
- Pittsburgh Foundation
- Bristol-Myers Squibb
- Eli Lilly and Company
- Pfizer
- AstraZeneca
- Sunovion
- Cerecor
- H. Lundbeck A/S
- National Institutes of Health (MH082998)
- Allergan
- National Heart, Lung, and Blood Institute (T32HL007560)
- National Institute of Mental Health (K23MH100259)
- National Institute of Biomedical Imaging and Bioengineering (R01EB022904)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Keywords
- depression, directed functional connectivity, resting-state fMRI, default mode network, group iterative multiple model estimation, community detection, dorsal anterior cingulate cortex, anxious depression, recurrent depression, sex differences, clinical heterogeneity, personalized treatment
- MeSH terms
- Adult, Anxiety Disorders, Brain, Brain Mapping, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Neural Pathways, Psychiatric Status Rating Scales, Recurrence, Rest, Severity of Illness Index, Comorbidity
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