Exercise Ameliorates Depressive Status through the Interaction between Motor and Reward Regions

635 

Abstract Submission 

Shiqi Di^1,2, Na Luo¹, Weiyang Shi¹, Tianzi Jiang^1,2,3,4,5

¹Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China, ²School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China, ³Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China, ⁴Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou, China, ⁵Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou, China

Shiqi Di  
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences|School of Artificial Intelligence, University of Chinese Academy of Sciences
Beijing, China|Beijing, China

Na Luo  
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences
Beijing, China

Weiyang Shi  
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences
Beijing, China

Tianzi Jiang  
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences|School of Artificial Intelligence, University of Chinese Academy of Sciences|Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences|Research Center for Augmented Intelligence, Zhejiang Lab|Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital
Beijing, China|Beijing, China|Beijing, China|Hangzhou, China|Yongzhou, China

Major depressive disorder (MDD) is a widespread mental disorder globally (Smith 2014), characterized by persistent feelings of low mood and anhedonia. Physical activity has been demonstrated as an effective non-pharmacological intervention for depression (D'Angelantonio et al. 2022). However, little attention has been paid to the underlying neuroimaging mechanisms linking exercise and depression, as well as the microscale molecular basis underlying the macroscale imaging mechanisms. In this study, we therefore conduct a multiscale analysis to systematically investigate how physical activity modulates brain structure and its biological influence, thus leaving a positive impact on improving depressive status.

The MDD-1 dataset was obtained from the UK Biobank (https://www.ukbiobank.ac.uk/), including 1,027 subjects with 492 MDDs and 535 healthy controls (HCs). The dMRI preprocessing was conducted by the UK Biobank team (Miller et al. 2016). After that, we performed PROBTRACKx and established structural connectivity (SC) at the brain region level based on the Brainnetome Atlas (Fan et al. 2016). Partial least squares (PLS) regression was utilized to explore the significant link between SC pattern and physical activity score. The identified imaging pattern was then generalized to three independent datasets also with depressive symptoms (MDD-2, bipolar disorder (BD) and schizophrenia (SCZ) datasets) to explore the stability and specificity of the findings (Luo et al. 2018). Afterwards, the neuromaps toolbox (Markello et al. 2022) was applied to interpret the biological ontologies of the identified SC pattern. Finally, the Allen Human Brain Atlas dataset (Arnatkeviciute et al. 2019) and other genome databases (Zhou et al. 2019, Seidlitz et al. 2020) were adopted to explore its underlying genetic basis, pathways and cell types. The analysis pipeline was depicted in Figure 1.

1. A linked imaging-exercise pattern (r = 0.67, p = 1.2e-134) was identified to be both significantly correlated with depressive mood (p= 6.0e-18) and group discriminative (p = 2.1e-4) between MDDs and HCs. The structural connections with significant contributions were primarily located between the motor-related regions and reward-related regions (Figure 2).
2. When generalizing the SC pattern to three independent datasets, all datasets except for schizophrenia with positive symptoms presented a significant group difference (p = 1.5e-2 for another MDD dataset, p = 7.4e-4 for bipolar disorder, p = 1.6e-4 for schizophrenia with negative symptoms), suggesting that the identified SC pattern is generalizable to mental disorders involving depressive mood.
3. Based on the neurotransmitter receptor maps parcellated with the Brainnetome Atlas, the SC pattern exhibited spatial correlations with distributions of several neurotransmitter receptors, such as serotonin receptor 5-HT1a, 5-HT2a, and GABA receptor GABAa (FDR-corrected p < 0.01).
4. A further imaging-genetic analysis revealed a gene list involving a total of 2,385 significant genes (|Z|>3), which decodes many depression-related genes like CRY1, VAMP2, ADCY9, and PTX3. These genes further enriched pathways like synaptic signaling, ion transport and astrocytes cell type, and diseases including "mood disorders".

In conclusion, our findings emphasized the pivotal role of the interaction between the motor-related and reward-related networks underlying the ameliorative influence of physical activity on depressive mood. The interaction is further linked with serotonin and GABA receptors, and regulated through synaptic signaling, ion transport and astrocytes cell type. These findings engender a comprehensive comprehension of the multifaceted mechanisms behind the ameliorative effects, and concurrently furnish potential targets for therapeutic interventions of depression.

Psychiatric (eg. Depression, Anxiety, Schizophrenia) ¹

Genetic Association Studies

Connectivity (eg. functional, effective, structural)

Multivariate Approaches ²

ADULTS

Data analysis

Emotions

Motor

MRI

Psychiatric Disorders