Dopaminergic dysfunction in the left putamen of patients with major depressive disorder

D'Onofrio, Antonio Maria; Pizzuto, Daniele Antonio; Batir, Rana; Perrone, Elisabetta; Cocciolillo, Fabrizio; Cavallo, Federica; Kotzalidis, Georgios Demetrios; Simonetti, Alessio; d'Andrea, Giacomo; Pettorruso, Mauro; Sani, Gabriele; Di Giuda, Daniela; Camardese, Giovanni

doi:10.1016/j.jad.2024.04.044

Cited by 2 publications

(2 citation statements)

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“…The neural functioning of the left putamen has also been implicated in the risk of bipolar disorder onset, suggesting a potential marker of vulnerability [ 99 ], as well as suicidality in bipolar II disorder [ 100 ]. Our results are consistent with decreased putamen regional homogeneity reported in adult patients with MDD [ 101 , 102 ], and with a recent SPECT study that showed negative correlation between levels of depression, anxiety, anhedonia and psychomotor retardation and DAT availability in the left putamen [ 103 ]. The same study showed lower left putamen DAT availability in seriously depressed patients and in patients with significant psychomotor retardation [ 103 ].…”

Section: Discussionsupporting

confidence: 93%

Neural Functioning in Late-Life Depression: An Activation Likelihood Estimation Meta-Analysis

Del Casale,

Mancino,

Arena

et al. 2024

Geriatrics

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Late-life depression (LLD) is a relatively common and debilitating mental disorder, also associated with cognitive dysfunctions and an increased risk of mortality. Considering the growing elderly population worldwide, LLD is increasingly emerging as a significant public health issue, also due to the rise in direct and indirect costs borne by healthcare systems. Understanding the neuroanatomical and neurofunctional correlates of LLD is crucial for developing more targeted and effective interventions, both from a preventive and therapeutic standpoint. This ALE meta-analysis aims to evaluate the involvement of specific neurofunctional changes in the neurophysiopathology of LLD by analysing functional neuroimaging studies conducted on patients with LLD compared to healthy subjects (HCs). We included 19 studies conducted on 844 subjects, divided into 439 patients with LLD and 405 HCs. Patients with LLD, compared to HCs, showed significant hypoactivation of the right superior and medial frontal gyri (Brodmann areas (Bas) 8, 9), left cingulate cortex (BA 24), left putamen, and left caudate body. The same patients exhibited significant hyperactivation of the left superior temporal gyrus (BA 42), left inferior frontal gyrus (BA 45), right anterior cingulate cortex (BA 24), right cerebellar culmen, and left cerebellar declive. In summary, we found significant changes in activation patterns and brain functioning in areas encompassed in the cortico–limbic–striatal network in LLD. Furthermore, our results suggest a potential role for areas within the cortico–striatal–cerebellar network in the neurophysiopathology of LLD.

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Section: Discussionsupporting

confidence: 93%

Neural Functioning in Late-Life Depression: An Activation Likelihood Estimation Meta-Analysis

Del Casale,

Mancino,

Arena

et al. 2024

Geriatrics

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“…Addressing the “treatment-selection” problem requires a deeper understanding of biomarkers in depression: objectively measurable characteristics reflecting underlying biological processes that contribute to heterogeneity of the MDD subtype and predict the therapeutic response ( 11 – 13 ). Resting-state electroencephalography (EEG), a neuroimaging technique known for its high temporal resolution, appears to be a promising approach for response prediction in depressive illness ( 14 ).…”

Section: Introductionmentioning

confidence: 99%

Overcoming treatment-resistant depression with machine-learning based tools: a study protocol combining EEG and clinical data to personalize glutamatergic and brain stimulation interventions (SelecTool Project)

Pettorruso,

Di Lorenzo,

Benatti

et al. 2024

Front. Psychiatry

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Treatment-Resistant Depression (TRD) poses a substantial health and economic challenge, persisting as a major concern despite decades of extensive research into novel treatment modalities. The considerable heterogeneity in TRD’s clinical manifestations and neurobiological bases has complicated efforts toward effective interventions. Recognizing the need for precise biomarkers to guide treatment choices in TRD, herein we introduce the SelecTool Project. This initiative focuses on developing (WorkPlane 1/WP1) and conducting preliminary validation (WorkPlane 2/WP2) of a computational tool (SelecTool) that integrates clinical data, neurophysiological (EEG) and peripheral (blood sample) biomarkers through a machine-learning framework designed to optimize TRD treatment protocols. The SelecTool project aims to enhance clinical decision-making by enabling the selection of personalized interventions. It leverages multi-modal data analysis to navigate treatment choices towards two validated therapeutic options for TRD: esketamine nasal spray (ESK-NS) and accelerated repetitive Transcranial Magnetic Stimulation (arTMS). In WP1, 100 subjects with TRD will be randomized to receive either ESK-NS or arTMS, with comprehensive evaluations encompassing neurophysiological (EEG), clinical (psychometric scales), and peripheral (blood samples) assessments both at baseline (T0) and one month post-treatment initiation (T1). WP2 will utilize the data collected in WP1 to train the SelecTool algorithm, followed by its application in a second, out-of-sample cohort of 20 TRD subjects, assigning treatments based on the tool’s recommendations. Ultimately, this research seeks to revolutionize the treatment of TRD by employing advanced machine learning strategies and thorough data analysis, aimed at unraveling the complex neurobiological landscape of depression. This effort is expected to provide pivotal insights that will promote the development of more effective and individually tailored treatment strategies, thus addressing a significant void in current TRD management and potentially reducing its profound societal and economic burdens.

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Dopaminergic dysfunction in the left putamen of patients with major depressive disorder

Cited by 2 publications

References 69 publications

Neural Functioning in Late-Life Depression: An Activation Likelihood Estimation Meta-Analysis

Neural Functioning in Late-Life Depression: An Activation Likelihood Estimation Meta-Analysis

Overcoming treatment-resistant depression with machine-learning based tools: a study protocol combining EEG and clinical data to personalize glutamatergic and brain stimulation interventions (SelecTool Project)

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