The anhedonia is differently modulated by structural covariance network of NAc in bipolar disorder and major depressive disorder
Introduction
As a core feature of depression, the anhedonia is a multi-faceted symptom that includes deficits in the experience of pleasure, reduced approach-related motivated behavior, and impaired learning about rewards(Treadway and Zald, 2011b). Depressed BD or MDD patients have indistinguishable symptoms including the anhedonia, leading to high misdiagnosis of BD(Hirschfeld et al., 2003; Phillips and Kupfer, 2013).Investigating the anhedonia(Harvey et al., 2007) of depression helps to understand distinct physiological characterizations of BD and MDD patients (Leboyer et al., 1998).However, whether the neural correlates of the anhedonia is different between BD and MDD remains unclear.
The anhedonia in depression is related to aberrant rewarding processes(Keedwell et al., 2005), reinforcement learning (Schultz, 1998) and motivated responding (Dichter et al., 2009; Niv et al., 2007; Pizzagalli et al., 2009a; Treadway and Zald, 2011a) in the brain. The neural system underlying reward is well defined in humans including nucleus accumbens (NAc)(Haber and Knutson, 2009), orbitofrontal cortex(OFC), amygdala, anterior insula (AIC)and anterior cingulate cortex (ACC) (Avery et al., 2014; DerAvakian and Markou, 2012a; Heshmati and Russo, 2015; Wacker et al., 2009). As a integral hub in the reward circuit(Heshmati and Russo, 2015; Hikosaka et al., 2008), the NAc integrates different excitatory and inhibitory inputs to signal the salience of rewarding stimuli (Smith et al., 2011).Studies have consistently found structural and functional aberrance in reward system across BD and MDD. For example, the activity of the NAc is consistently found decreased in depression (Drevets et al., 1992; Mayberg et al., 2000),this reduced activity of the NAc is related to altered reward function driving the anhedonia(Russo and Nestler, 2013).In addition, patients with depression present smaller gray matter volume in OFC and ACC (Caetano et al., 2006; Drevets et al., 1997; Lai et al., 2000) and smaller BOLD signal changes during a reversal-learning task(Taylor Tavares et al., 2008).BD patients display greater ventral striatum, OFC activation during reward anticipation (Caseras et al., 2013; Robin Nusslock et al., 2012).Although common dimensional reward deficits in functional connectome are found across BD and MDD (Sharma et al., 2017a), recent findings suggest that the neural correlates underlying the anhedonia in BD and MDD might be different (Alloy et al., 2016; Whitton et al., 2015).
Recent findings suggest reward processes are differently altered between BD and MDD. The abnormally elevated activity of ventrolateral prefrontal cortex during a guessing task distinguishes depressed BD patients from MDD patients (Chase et al., 2013a). Ronny et al. find BD patients present a lower activation in reward-related regions including NAc, thalamus compared with MDD patients during a card-guess paradigm (Redlich et al., 2015).BD patients have significantly higher self-report of reward and punishment sensitivity when compared with MDD patients (Weinstock et al., 2018).The differential abnormal activity of ACC distinguishes BD from MDD in emotional faces matching task (Bürger et al., 2017).Apart from these findings, depression severity presents different relationship with social reward response in BD and MDD (Sharma et al., 2016).Mounts of studies also find that structure and function of key regions in reward system are distinctly altered in BD and MDD (Han et al., 2019a; Versace et al., 2010).The gray matter volume of amygdala is reduced in MDD while that in BD is increased (Konarski et al., 2010).Amplitude of low-frequency fluctuations (ALFF) of insula is higher in BD than that in MDD(Liu et al., 2012). MDD patients present reduced nodal connectivity strength within reward system in ventral striatum, AIC and thalamus compared with MDD patients and HCs(Satterthwaite et al., 2015).Taken together, these results suggest the neural correlates underlying the anhedonia in BD and MDD might be different. The anhedonia in BD is hypothesized to arise due to elevated activity in ventral striatum and prefrontal cortex, reflecting heighted reward sensitivity(Depue and Iacono, 2003), while that in MDD is related to altered incentive salience, incentive motivation and reinforcement learning in MDD (Alloy et al., 2016; Whitton et al., 2015). However, there is no direct evidence to prove these hypotheses.
This study, to our knowledge, was the first time to directly explore distinct neural correlates underlying the anhedonia in BD and MDD. Focusing on the NAc, a region plays a vital role in the anhedonia of depression(Cooper et al., 2018; DerAvakian and Markou, 2012a; Gabbay et al., 2013; Heshmati and Russo, 2015; Philip, 2008), the structural covariance network of NAc was constructed. Then, we explored altered structural covariance network of NAc and its interaction with the anhedonia severity in BD and MDD. Based on current literature, two main hypotheses were proposed. First, BD and MDD patients presented commonly and distinctly altered structural covariance network of NAc. Second, the interaction between the structural covariance network of NAc and the anhedonia severity in BD and MDD would present different dimensional distribution. The anhedonia in MDD might be mainly located in regions in salience network and responding for reinforcement learning, while that in BD might be mainly located in striatum and frontal gyrus.
Section snippets
Participants
Thirty six BD patients and 40 MDD patients were recruited from the Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China. Each patient was interviewed by two experienced psychiatrists using the Structured Clinical Interview for DSM-IV-TR-Patient Edition (SCID-P, 2/2001 revision), and was finally diagnosed to BD or MDD according to DSM-IV.The 24-items Hamilton Depression scale (HAMD) was used to evaluate the clinical depressive states of
Clinical effects
Demographic and clinical characteristics of subjects were shown in Table 1. Sociodemographic characteristics including age, gender, years of education presented no significant difference among three groups (Table 1).There was no significant difference of HAMD between BD and MDD. Both BD (p < .01)and MDD (p < .01) presented higher SHAPS score than HCs, while there was no significant difference of SHAPS score between BD and MDD patients (p > .99).
Structural covariance network of NAc was differently altered in BD and MDD patients
The structural covariance of NAc connected to the
Discussion
To our knowledge, it was the first time to directly explore the different neural basis underlying the anhedonia in BD and MDD patients. There were two main findings in this study. First, structural covariance network of NAc was differently altered between BD and MDD. Especially, the structural covariance of NAc connected to regions including left hippocampus and thalamus, presented opposite differences in BD and MDD. Second, the interaction between structural covariance network of NAc and the
Conclusion
This was the first study to explore the different neural basis underlying the anhedonia in patients with BD and MDD. BD and MDD patients not only presented commonly and distinctly abnormal structural covariance network of NAc, the interaction between the structural covariance network of NAc and the anhedonia severity presented different dimensional distribution in BD and MDD. Our results provided direct evidences that the neural correlates underlying the anhedonia in BD and MDD was different.
Financial disclosures
All authors declared no conflict of interest.
Ethical statement
The study was approved by the research ethical committee of University of Electronic Science and Technology of China.
Authors contributions
Shaoqiang Han mainly write the paper. Shaoqiang Han, Xiao Wang, Liang Li, Wei Sheng are charge of designing the method. Yuyan Chen, Di Li, Zongling He, Xiaonan Guo, Yun-Shuang Fan, Jing Guo are in charge of data acquisition. Qian Cui and Huafu Chen design all study. The manuscript is revised by all authors and the final version of manuscript is approved by all authors.
Disclosure statement
This is an original manuscript and no parts of this manuscript are being considered for publication elsewhere. All authors have approved this manuscript. No author has financial or other contractual agreements that might cause conflicts of interest.
Acknowledgments
This work was supported by the Natural Science Foundation of China (61533006, U1808204,81771919), Key Project of Research and Development of Ministry of Science and Technology (2018AAA0100705),the Scientific research project of Sichuan Medical Association (S15012), the Youth Innovation Project of Sichuan Provincial Medical Association (Q14014),China Postdoctoral Science Foundation Grant (Grant No. 2019M653383).
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2022, Neurobiology of StressCitation Excerpt :The NAc has two components, the core and the shell. The core of NAc receives dopaminergic projections from VTA and glutamatergic projections from BLA, prefrontal cortex, and hippocampus (Han et al., 2020; Li et al., 2018). Besides the local effects on the soma and non-neural tissue, NAc-DBS entrains the action potentials propagating through the efferent axons to the target brain regions, and through the afferent axons antidromically to the cell body in BLA, prefrontal cortex, and hippocampus (Jakobs et al., 2019).
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2021, NeuroImage: ClinicalCitation Excerpt :Aforementioned results provided evidence of subcortical trait and state-dependent markers of MDD. Although previous studies have shown alteration in structural covariance (Han et al., 2020; Wu et al., 2017; Zuo et al., 2018) and in cortical networks (Wang et al., 2016) in MDD, our study was the first, to our knowledge, to investigate the sophisticated relationship of subcortical trait and state-dependent markers with SCN alterations over different stages of depression. The SCN represents structural inter-relationships among different neuronal substrates, including both morphometric correlations and anatomical connectivities (Lim et al., 2013), that could be used to elucidate eloquent neurobiological mechanisms underlying structural neural networks (Bassett et al., 2008; Bernhardt et al., 2011).
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2020, Journal of Affective DisordersCitation Excerpt :Although researchers considered that BD is closely related to genetic and environmental factors(Rathje et al., 2019; Segura et al., 2019; Stapp et al., 2019), its underlying neuropathophysiological mechanism remains largely unknown. At present, numerous scholars have investigated the prefrontal cortex and limbic system in kinds of mental disorders and the results are promising (Han et al., 2020; Qiu et al., 2020; Wang et al., 2019b), but have ignored the role of cerebellum in these disorders. The cerebellum had been considered for almost 200 years to be devoted exclusively to motor control such as coordination of voluntary movement, gait, posture and motor function (Schmahmann et al., 2019).