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Investigation of habenula volume in mood disorders: A meta-analytic study

Published online by Cambridge University Press:  30 March 2026

Jean-Simon Fortin Open the ORCID record for Jean-Simon Fortin [Opens in a new window] ,
Sébastien Hétu Open the ORCID record for Sébastien Hétu [Opens in a new window] ,
Charles Parisien Open the ORCID record for Charles Parisien [Opens in a new window]  and
Catherine Parent
Jean-Simon Fortin*
Affiliation:
Department of Psychology, Université de Montréal, Montreal, QC, Canada
Sébastien Hétu
Affiliation:
Department of Psychology, Université de Montréal, Montreal, QC, Canada
Charles Parisien
Affiliation:
Department of Psychology, Université de Montréal, Montreal, QC, Canada
Catherine Parent
Affiliation:
Department of Psychology, Université de Montréal, Montreal, QC, Canada
*
Corresponding author: Jean-Simon Fortin; Email: jean-simon.fortin@umontreal.ca
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Abstract

The habenula, a small brain structure involved in processing aversive stimuli, has been strongly implicated in the pathophysiology of mood disorders. While diminutions in hippocampal and medial prefrontal cortex volume have been demonstrated in individuals with a mood disorder, evidence for structural alterations in the habenula remains inconsistent. This set of meta-analyses examines whether individuals with a mood disorder show alterations in habenula volume compared to healthy controls. We conducted six meta-analyses. Two global analyses compared left and right habenula volumes between individuals with a mood disorder (MDD or BD) and healthy controls (HCs), each including 15 samples (left: 1,230 participants; right: 1,236). Four additional analyses compared MDD versus HCs and BD versus HCs for left and right volumes separately. Subgroup and meta-regression analyses tested the habenula segmentation method, medication status, and MRI resolution as moderators. The global meta-analyses pooling MDD and BD data showed small but significant volume reductions in the left (g = −0.1367, p = .0344) and right (g = −0.1562, p = .0409) habenula in mood disorder patients compared to controls. However, these effects did not survive correction for multiple comparisons. After correction, no significant group differences were found in the diagnosis-specific meta-analyses (MDD versus controls; BD versus controls), and no moderator analyses were significant. Current evidence points toward small habenula volume reductions in mood disorders, though findings did not withstand correction for multiple comparisons. Further high-resolution neuroimaging studies are needed to clarify habenula volume alterations in mood disorders.

Keywords

bipolar disorderdepressionhabenulameta-analysismood disordersvolumeMRIatrophyneurotrophic theory of depression

Information

Type
Review Article
Information
Psychological Medicine , Volume 56 , 2026 , e82
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press

Mood disorders – including major depressive disorder (MDD) and bipolar disorder (BD) – collectively rank among the leading contributors to the global burden of disease. Within the category of mental disorders, they account for the highest proportion of disability-adjusted life years (DALYs), a metric that captures both premature mortality and years lived with disability (GBD, 2019 Mental Disorders Collaborators, 2022). Worldwide, MDD affects an estimated 280 million people, and BD about 40 million (World Health Organization, 2022). Despite their impact, their underlying pathophysiology remains poorly understood (Jesulola, Micalos, & Baguley, Reference Jesulola, Micalos and Baguley2018; Marcolongo-Pereira et al., Reference Marcolongo-Pereira, Castro, Barcelos, Chiepe, Rossoni Junior, Ambrosio, Chiarelli-Neto and Pesarico2022). In recent years, the habenula – a pair of small epithalamic nuclei located in the dorsal thalamus – has emerged as one of the most intensively studied brain structures in preclinical research on mood disorders (Spreen, Alkhoury, Walter, & Müller, Reference Spreen, Alkhoury, Walter and Müller2024), and is receiving increasing attention in human studies (Cameron, Weston-Green, & Newell, Reference Cameron, Weston-Green and Newell2024; Chen, Sun, Zhang, Mu, & Su, Reference Chen, Sun, Zhang, Mu and Su2022). As a key node within the brain’s reward circuitry (Namboodiri, Rodriguez-Romaguera, & Stuber, Reference Namboodiri, Rodriguez-Romaguera and Stuber2016), the habenula plays a crucial role in processing aversive stimuli and is often referred to as the brain’s ‘anti-reward center’ (Hu, Cui, & Yang, Reference Hu, Cui and Yang2020). It comprises two distinct subdivisions: the medial habenula (MHb) and the lateral habenula (LHb), with the LHb believed to account for a substantially greater proportion of total habenula volume in humans (Ahumada-Galleguillos et al., Reference Ahumada-Galleguillos, Lemus, Díaz, Osorio-Reich, Härtel and Concha2017; Groos & Helmchen, Reference Groos and Helmchen2024).

The growing interest in the habenula’s role in mood disorders stems from animal studies implicating it as a key hub in their pathophysiology (Hikosaka, Reference Hikosaka2010; Hu et al., Reference Hu, Cui and Yang2020; Yang, Wang, Hu, & Hu, Reference Yang, Wang, Hu and Hu2018). Notably, one of the most influential discoveries has been the identification of elevated baseline activity in the LHb – a phenomenon consistently observed across diverse animal models of depression (Caldecott-Hazard, Mazziotta, & Phelps, Reference Caldecott-Hazard, Mazziotta and Phelps1988; Cerniauskas et al., Reference Cerniauskas, Winterer, de Jong, Lukacsovich, Yang, Khan, Peck, Obayashi, Lilascharoen, Lim, Földy and Lammel2019; Tchenio, Lecca, Valentinova, & Mameli, Reference Tchenio, Lecca, Valentinova and Mameli2017) – which appears to play a critical role in the expression of depressive-like behaviors. Caldecott-Hazard et al. (Reference Caldecott-Hazard, Mazziotta and Phelps1988) first reported elevated LHb glucose metabolism in three rodent depression models, identifying it as the only brain region consistently hyperactive in all three models. Since then, multiple lines of evidence have supported LHb hyperactivity as a key contributor to depression pathophysiology. For example, optogenetic stimulation of LHb projections to the rostromedial tegmental nucleus (RMTg) was shown to induce depressive-like symptoms in rodents (Proulx et al., Reference Proulx, Aronson, Milivojevic, Molina, Loi, Monk, Shabel and Malinow2018), while LHb inhibition produced antidepressant-like effects (Winter, Vollmayr, Djodari-Irani, Klein, & Sartorius, Reference Winter, Vollmayr, Djodari-Irani, Klein and Sartorius2011). Additional studies have shown that lesioning the LHb reduces depressive-like behaviors following chronic stress (Yang, Hu, Xia, Zhang, & Zhao, Reference Yang, Hu, Xia, Zhang and Zhao2008) or prevents their emergence when performed prior to exposure to inescapable shocks (Amat et al., Reference Amat, Sparks, Matus-Amat, Griggs, Watkins and Maier2001). Furthermore, the rapid antidepressant effects of ketamine have been linked to its ability to normalize the increased burst firing of LHb neurons observed in animal models of depression (Yang et al., Reference Yang, Cui, Sang, Dong, Ni, Ma and Hu2018). Collectively, these findings strongly implicate excessive LHb activity as a central mechanism in the pathophysiology of depression. Given the habenula’s well-documented functional abnormalities in mood disorders, it is plausible that it may also exhibit structural alterations. This notion is supported by animal studies showing reduced habenula volume in depression models (Jacinto, Mata, Novais, Marques, & Sousa, Reference Jacinto, Mata, Novais, Marques and Sousa2017; Yang et al., Reference Yang, Kim, Yang, Lee, Sun, Lee and Kim2019), as well as longitudinal human studies reporting volume increases following treatments such as antidepressants (Elias et al., Reference Elias, Germann, Loh, Boutet, Pancholi, Beyn, Bhat, Woodside, Giacobbe, Kennedy and Lozano2022; Etienne et al., Reference Etienne, Boutigny, David, Deflesselle, Gressier, Becquemont, Corruble and Colle2024; Sartorius et al., Reference Sartorius, Demirakca, Böhringer, Clemm von Hohenberg, Aksay, Bumb, Kranaster and Ende2016). Such findings have spurred growing interest in habenula anatomy, reflected in a growing number of studies examining habenula volume in individuals with a mood disorder (Cameron et al., Reference Cameron, Weston-Green and Newell2024).

More generally, human structural neuroimaging has been instrumental in advancing our understanding of mood disorders. Among the most consistently observed brain alterations in MDD are reductions in hippocampal and medial prefrontal cortex (mPFC) volume (Belleau, Treadway, & Pizzagalli, Reference Belleau, Treadway and Pizzagalli2019; Campbell, Marriott, Nahmias, & MacQueen, Reference Campbell, Marriott, Nahmias and MacQueen2004; Koolschijn, van Haren, Lensvelt-Mulders, Hulshoff Pol, & Kahn, Reference Koolschijn, van Haren, Lensvelt-Mulders, Hulshoff Pol and Kahn2009; Schmaal et al., Reference Schmaal, Veltman, van Erp, Sämann, Frodl, Jahanshad, Loehrer, Tiemeier, Hofman and Niessen2016), with similar reductions reported in BD (Angelescu, Brugger, Borgan, Kaar, & Howes, Reference Angelescu, Brugger, Borgan, Kaar and Howes2021; Cao et al., Reference Cao, Passos, Mwangi, Amaral-Silva, Tannous, Wu, Zunta-Soares and Soares2017; Hajek, Kopecek, Höschl, & Alda, Reference Hajek, Kopecek, Höschl and Alda2012; Haukvik et al., Reference Haukvik, Gurholt, Nerland, Elvsåshagen, Akudjedu, Alda, Alnaes, Alonso-Lana, Bauer, Baune, Benedetti, Berk, Bettella, Bøen, Bonnín, Brambilla, Canales-Rodríguez, Cannon, Caseras and Agartz2022; Qi et al., Reference Qi, Wang, Gong, Su, Fu, Huang and Wang2022; Savitz, Price, & Drevets, Reference Savitz, Price and Drevets2014; Wise et al., Reference Wise, Radua, Via, Cardoner, Abe, Adams, Amico, Cheng, Cole, de Azevedo Marques Périco, Dickstein, Farrow, Frodl, Wagner, Gotlib, Gruber, Ham, Job, Kempton and Arnone2017). Findings of volume reductions in these stress-sensitive brain regions have been instrumental in the development of the neurotrophic hypothesis of depression, a leading alternative to the monoaminergic theory (Ferrari & Villa, Reference Ferrari and Villa2017; Liu, Liu, Wang, Zhang, & Li, Reference Liu, Liu, Wang, Zhang and Li2017; Page, Epperson, Novick, Duffy, & Thompson, Reference Page, Epperson, Novick, Duffy and Thompson2024). According to this hypothesis, stress reduces the expression of neurotrophic factors – particularly brain-derived neurotrophic factor (BDNF) – in key limbic regions. This reduction in BDNF is thought to drive structural degeneration, most notably in the hippocampus and mPFC (Duman & Monteggia, Reference Duman and Monteggia2006). In both regions, structural abnormalities co-occur with well-documented functional impairments (Liu et al., Reference Liu, Liu, Wang, Zhang and Li2017; Page et al., Reference Page, Epperson, Novick, Duffy and Thompson2024). Recent evidence shows that stress also reduces BDNF levels in the habenula (Sachs & Caron, Reference Sachs and Caron2015; Tong et al., Reference Tong, Chen, Hao, Shen, Chen, Cheng, Yan, Li, Li, Gulizhaerkezi, Zeng and Meng2023; Zhang et al., Reference Zhang, Lyu, Wang, Shi, Wang, Yang, Huang, Wei, Chen, Xu and Hong2022) – a change that, as in the hippocampus and mPFC (Björkholm & Monteggia, Reference Björkholm and Monteggia2016; Duman, Deyama, & Fogaça, Reference Duman, Deyama and Fogaça2021), can be reversed by antidepressant treatment. These findings raise the possibility that neurotrophic mechanisms contributing to structural alterations in the hippocampus and mPFC may likewise affect the habenula, another key region involved in mood regulation. Such mechanisms could potentially lead to volume reductions in the habenula in mood disorders.

Evidence of volumetric alterations in the habenula could have wide-ranging implications, potentially prompting research aimed at integrating the habenula into the neurotrophic theory of depression and at exploring its relationship with the hypothalamic–pituitary–adrenal (HPA) axis. Moreover, these findings could establish the habenula as a crucial node in research seeking to bridge reward-based and neurotrophic models of depression, aiming to provide a more unified framework for understanding its pathophysiology. Existing studies on habenula volume in mood disorders show mixed results: some report reduced habenula volume in mood disorders (Cho et al., Reference Cho, Park, Na, Chung, Ma, Kang and Kang2021; Ranft et al., Reference Ranft, Dobrowolny, Krell, Bielau, Bogerts and Bernstein2010), while others observe no differences (Aftanas et al., Reference Aftanas, Filimonova, Anisimenko, Berdyugina, Rezakova, Simutkin, Bokhan, Ivanova, Danilenko and Lipina2023; Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023; Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017) or even increased volume (Liu, Valton, Wang, Zhu, & Roiser, Reference Liu, Liu, Wang, Zhang and Li2017). Therefore, to clarify whether habenula volume is reliably altered in mood disorders, we conducted six meta-analyses comparing patients and healthy controls (HCs). Specifically, we examined left and right habenula volume separately, comparing individuals with MDD and BD – both pooled and as distinct groups – to HCs. Given the habenula’s small size (~30 mm3), current imaging lacks the resolution to distinguish its lateral and medial subdivisions; therefore, our meta-analyses focused on total habenula volume.

Methods and materials

This meta-analysis followed the PRISMA guidelines (Page et al., Reference Page, McKenzie, Bossuyt, Boutron, Hoffmann, Mulrow, Shamseer, Tetzlaff, Akl, Brennan, Chou, Glanville, Grimshaw, Hróbjartsson, Lalu, Li, Loder, Mayo-Wilson, McDonald and Moher2021) and was registered on OSF (https://osf.io/atxvj/).

Literature search

We searched Ovid (Embase, Medline, PsycINFO), Web of Science, and Google Scholar in April 2025 (see Supplemental Information for full strategies).

Inclusion and exclusion criteria

To be included, studies had to report habenula volumes (MRI or post-mortem) in humans and include: (1) a mood disorder group (MDD or BD), (2) a HC group, and (3) separate data for left and right habenula. Only studies reporting whole habenula volume were included; those with only gray/white matter measures were excluded. Left and right volumes were analyzed separately based on evidence of lateralized habenula function (Concha & Ahumada-Galleguillos, Reference Concha and Ahumada-Galleguillos2016; Hétu et al., Reference Hétu, Luo, Saez, D’Ardenne, Lohrenz and Montague2016). Studies were eligible regardless of publication date or format (e.g. preprints, theses, conference proceedings). Non-English articles and conference abstracts were excluded, though authors would have been contacted to obtain the data if conference abstracts seemed to be relevant (none identified). Only studies on MDD or BD were included; those on other conditions (e.g. PTSD) or subclinical depression (e.g. elevated symptoms without a clinical diagnosis) were excluded.

Study selection

The study selection process is shown in the PRISMA diagram (Figure 1) (Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia. Available at www.covidence.org.). One reviewer (J.S.F) conducted the initial database search and imported results into Covidence, where both title/abstract and full-text screening were performed. Two reviewers (J.S.F and C.P2) independently screened all titles/abstracts and full texts, resolving discrepancies through discussion. The initial search yielded 732 studies across five databases, with one additional preprint identified independently after the search. Duplicates were removed using Covidence’s automated tool and manual checks, leaving 384 unique records. Of these, 33 were assessed at the full-text level. In total, 14 studies (15 samples) met the inclusion criteria and were incorporated into the global meta-analyses, pooling data across both MDD and BD.

Figure 1.

PRISMA flow diagram of the study selection process.

Data extraction

We extracted data required for effect size calculations: sample size, mean, and standard deviation of left and right habenula volumes for clinical and control groups. Two reviewers (J.S.F and C.P2) independently extracted these values for all datasets and cross-checked results to resolve discrepancies. Data were recorded in Excel. We used absolute habenula volumes (in mm3) rather than relative measures (e.g. based on total intracranial volume (TIV) or total brain volume (TBV)), as absolute values were more consistently reported across studies.

Quality assessment

Study quality was assessed by one reviewer (J.S.F) using the NIH tool for observational studies (National Heart Lung and Blood Institute (NHLBI), 2021).

Data analysis

We conducted six meta-analyses. First, we performed two meta-analyses comparing left and right habenula volumes between individuals with a mood disorder (MDD or BD) and HCs; these are referred to as the global meta-analyses throughout the paper. Two additional meta-analyses focused on MDD, and two on BD, each comparing patients to controls for left and right volumes. To control for multiple comparisons across our six meta-analyses, a 5% false discovery rate (FDR) correction (Benjamini–Hochberg procedure (Benjamini & Hochberg, Reference Benjamini and Hochberg1995) was applied. Unless otherwise noted, p-values reported in the article are uncorrected. A random-effects model with inverse-variance weighting was used, and Hedges’ g was chosen as the effect size metric to correct for small-sample bias (Hedges & Olkin, Reference Hedges and Olkin1985).

We conducted secondary subgroup analyses by habenula segmentation method and medication status within each of the six meta-analyses. Automatic and semi-automatic habenula segmentation methods were combined and compared to manual segmentation. Groups were classified as unmedicated only if none of the participants used psychotropic medication at the time of scanning; otherwise, they were considered medicated. Prior medication history did not affect classification. Sex-based subgroup analyses were not conducted, as only one study reported habenula volumes by sex. We performed subgroup analyses in all meta-analyses regardless of the number of samples. However, subgroup comparisons with fewer than 10 studies (k < 10) should be interpreted cautiously due to low power and greater uncertainty in effect size estimates. When k ≥ 10, meta-regressions tested MRI resolution (mean-centered in mm3) as a moderator. A 5% FDR correction controlled for multiple comparisons across all secondary analyses.

Results

Sample characteristics

Fourteen articles (15 samples, as one study contained two samples) were included in the global meta-analyses pooling MDD and BD. Detailed sample characteristics are reported in Table 1. Fourteen samples used structural MRI, and one used post-mortem data (Ranft et al., Reference Ranft, Dobrowolny, Krell, Bielau, Bogerts and Bernstein2010). Among MRI studies, two used 7 T scanners (Cho et al., Reference Cho, Park, Na, Chung, Ma, Kang and Kang2021; Schmidt et al., Reference Schmidt, Schindler, Adamidis, Strauß, Tränkner, Trampel, Walter, Hegerl, Turner, Geyer and Schönknecht2017), ten used 3 T (Aftanas et al., Reference Aftanas, Filimonova, Anisimenko, Berdyugina, Rezakova, Simutkin, Bokhan, Ivanova, Danilenko and Lipina2023; Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023; Furman & Gotlib, Reference Furman and Gotlib2016; Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Kyuragi et al., Reference Kyuragi, Oishi, Hatakoshi, Hirano, Noda, Yoshihara, Ito, Igarashi, Miyata, Takahashi, Kamiya, Matsumoto, Okada, Fushimi, Nakagome, Mimura, Murai and Suwa2024; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017; Liu, Valton, et al, Reference Liu, Liu, Wang, Zhang and Li2017; Luan, Zhang, Wang, Zhao, & Liu, Reference Luan, Zhang, Wang, Zhao and Liu2019; Savitz et al., Reference Savitz, Nugent, Bogers, Roiser, Bain, Neumeister, Zarate, Manji, Cannon, Marrett, Henn, Charney and Drevets2011; Schafer et al., Reference Schafer, Kim, Joseph, Xu, Frangou and Doucet2018), and two used 1.5 T (Germann et al., Reference Germann, Gouveia, Martinez, Zanetti, de Souza Duran, Chaim-Avancini, Serpa, Chakravarty and Devenyi2020). Manual habenula segmentation was applied in nine MRI samples (Aftanas et al., Reference Aftanas, Filimonova, Anisimenko, Berdyugina, Rezakova, Simutkin, Bokhan, Ivanova, Danilenko and Lipina2023; Cho et al., Reference Cho, Park, Na, Chung, Ma, Kang and Kang2021; Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023; Furman & Gotlib, Reference Furman and Gotlib2016; Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017; Liu, Valton, et al., Reference Liu, Liu, Wang, Zhang and Li2017; Luan et al., Reference Luan, Zhang, Wang, Zhao and Liu2019; Savitz et al., Reference Savitz, Nugent, Bogers, Roiser, Bain, Neumeister, Zarate, Manji, Cannon, Marrett, Henn, Charney and Drevets2011) and one post-mortem sample (Ranft et al., Reference Ranft, Dobrowolny, Krell, Bielau, Bogerts and Bernstein2010). Three samples used fully automated segmentation (Germann et al., Reference Germann, Gouveia, Martinez, Zanetti, de Souza Duran, Chaim-Avancini, Serpa, Chakravarty and Devenyi2020; Kyuragi et al., Reference Kyuragi, Oishi, Hatakoshi, Hirano, Noda, Yoshihara, Ito, Igarashi, Miyata, Takahashi, Kamiya, Matsumoto, Okada, Fushimi, Nakagome, Mimura, Murai and Suwa2024, and two used semi-automated methods (Schafer et al., Reference Schafer, Kim, Joseph, Xu, Frangou and Doucet2018; Schmidt et al., Reference Schmidt, Schindler, Adamidis, Strauß, Tränkner, Trampel, Walter, Hegerl, Turner, Geyer and Schönknecht2017). MRI voxel resolution ranged from 0.125 to 2.028 mm3 (mean = 0.591 ± 0.505 mm3). Four samples did not report medication status (Germann et al., Reference Germann, Gouveia, Martinez, Zanetti, de Souza Duran, Chaim-Avancini, Serpa, Chakravarty and Devenyi2020; Kyuragi et al., Reference Kyuragi, Oishi, Hatakoshi, Hirano, Noda, Yoshihara, Ito, Igarashi, Miyata, Takahashi, Kamiya, Matsumoto, Okada, Fushimi, Nakagome, Mimura, Murai and Suwa2024; Luan et al., Reference Luan, Zhang, Wang, Zhao and Liu2019). In four other samples, all patients were medication-free at the time of scanning (Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023; Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017; Liu, Valton, et al., Reference Liu, Liu, Wang, Zhang and Li2017). Of these, one study reported that 27 of 64 MDD participants had prior antidepressant use (Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023); others did not report treatment history (Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017; Liu, Valton, et al., Reference Liu, Liu, Wang, Zhang and Li2017). One study provided separate data for medicated and unmedicated MDD patients (Schmidt et al., Reference Schmidt, Schindler, Adamidis, Strauß, Tränkner, Trampel, Walter, Hegerl, Turner, Geyer and Schönknecht2017), and six samples included some medicated participants (Aftanas et al., Reference Aftanas, Filimonova, Anisimenko, Berdyugina, Rezakova, Simutkin, Bokhan, Ivanova, Danilenko and Lipina2023; Cho et al., Reference Cho, Park, Na, Chung, Ma, Kang and Kang2021; Furman & Gotlib, Reference Furman and Gotlib2016; Ranft et al., Reference Ranft, Dobrowolny, Krell, Bielau, Bogerts and Bernstein2010; Savitz et al., Reference Savitz, Nugent, Bogers, Roiser, Bain, Neumeister, Zarate, Manji, Cannon, Marrett, Henn, Charney and Drevets2011; Schafer et al., Reference Schafer, Kim, Joseph, Xu, Frangou and Doucet2018). Based on the NIH Quality Assessment Tool, three samples were rated good, ten fair, and two poor (Supplementary Table S1).

Table 1.

Summary of characteristics of included samples

Note: BD, bipolar disorder; FED, first-episode depression; HC, healthy control; MDD, major depressive disorder; MRI, magnetic resonance imaging; NA, not available; TRD, treatment-resistant depression.

a The sample size reported corresponds to the number of participants that could be accurately extracted from the available graphical data.

Meta-analyses

For the left habenula volume, the global meta-analysis included 15 samples (1,230 participants: 686 with a mood disorder, 544 HCs) (Figure 2). A random-effects model showed a small but significant volume reduction in mood disorders (g = −0.1367, 95% CI [−0.2618, −0.0116], p = .0344). The effect size ranged from −0.1654 to −0.1205 in the leave-one-out analysis (Supplementary Figure S19). In six (Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023; Germann et al., Reference Germann, Gouveia, Martinez, Zanetti, de Souza Duran, Chaim-Avancini, Serpa, Chakravarty and Devenyi2020; Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Kyuragi et al., Reference Kyuragi, Oishi, Hatakoshi, Hirano, Noda, Yoshihara, Ito, Igarashi, Miyata, Takahashi, Kamiya, Matsumoto, Okada, Fushimi, Nakagome, Mimura, Murai and Suwa2024; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017; Savitz et al., Reference Savitz, Nugent, Bogers, Roiser, Bain, Neumeister, Zarate, Manji, Cannon, Marrett, Henn, Charney and Drevets2011) out of the 15 samples, removal of the individual sample rendered the meta-analytic effect non-significant, indicating limited robustness of the observed effect. Moreover, after applying a 5% FDR correction, the adjusted p-value was 0.0992, rendering the effect non-significant. Between-study heterogeneity was low (τ 2 < 0.0001, 95% CI [0.0000, 0.1311]), with an I 2 value of 0.0% (95% CI [0.0%, 53.6%]), indicating low heterogeneity and suggesting consistency across studies. The Q-test did not indicate significant heterogeneity (Q = 13.74, df = 14, p = .4689). The 95% prediction intervals ranged from −0.2630 to −0.0104, suggesting that future studies are also likely to observe a negative effect. Neither Egger’s test nor the funnel plot (Supplementary Figure S25) showed evidence of publication bias (t = 0.51, p = 0.6176), and trim-and-fill analysis suggested no missing studies.

Figure 2.

Forest plot for the meta-analysis comparing the volume of the left habenula in patients with a mood disorder versus healthy controls (HCs).

For the right habenula volume, the global meta-analysis included 15 samples (1,236 participants: 689 with a mood disorder, 547 HCs) (Figure 3). A random-effects model showed a small but significant volume reduction in mood disorders (g = −0.1562, 95% CI [−0.3049, −0.0074], p = .0409). The effect size ranged from −0.1804 to −0.1296 in the leave-one-out analysis (Supplementary Figure S20). In seven (Cho et al., Reference Cho, Park, Na, Chung, Ma, Kang and Kang2021; Etienne et al., Reference Etienne, Boutigny, Minh Ngoc Thien, Ducreux, Deflesselle, Chappell, Gressier, Becquemont, Corruble and Colle2023; Germann et al., Reference Germann, Gouveia, Martinez, Zanetti, de Souza Duran, Chaim-Avancini, Serpa, Chakravarty and Devenyi2020; Hou et al., Reference Hou, Bian, Luan, Pan, Li, Xue, Zhang and Zhang2025; Kyuragi et al., Reference Kyuragi, Oishi, Hatakoshi, Hirano, Noda, Yoshihara, Ito, Igarashi, Miyata, Takahashi, Kamiya, Matsumoto, Okada, Fushimi, Nakagome, Mimura, Murai and Suwa2024; Lawson et al., Reference Lawson, Nord, Seymour, Thomas, Dayan, Pilling and Roiser2017; Savitz et al., Reference Savitz, Nugent, Bogers, Roiser, Bain, Neumeister, Zarate, Manji, Cannon, Marrett, Henn, Charney and Drevets2011) out of the 15 samples, removing that individual sample rendered the meta-analytic effect non-significant, indicating limited robustness of the observed effect. After FDR correction, the adjusted p-value was 0.0992, rendering the result non-significant. Between-study heterogeneity was low (τ 2 < 0.0001, 95% CI [0.0000, 0.2584]), with an I 2 value of 28.2% (95% CI [0.0%, 61.4%]), indicating low to moderate heterogeneity. The Q-test did not indicate significant heterogeneity (Q = 19.50, df = 14, p = .1466). The 95% prediction interval ranged from −0.2823 to −0.0301, suggesting that future studies are also likely to observe a negative effect. Neither Egger’s test nor the funnel plot (Supplementary Figure S26) showed evidence of publication bias (t = 0.03, p = 0.9735). Trim-and-fill analysis indicated three potentially missing studies. After imputing these studies, the adjusted meta-analytic effect size remained statistically significant and even shifted slightly toward a more negative value (g = −0.2247, 95% CI [−0.3958, −0.0535], p = 0.0131). However, after FDR correction, the p-value rose to 0.0786, rendering the result non-significant.

Figure 3.

Forest plot for the meta-analysis comparing the volume of the right habenula in patients with a mood disorder versus healthy controls (HCs).

Separate meta-analyses for MDD and BD showed no significant effects for either habenula (Supplementary Figures S3–S6).

Secondary analyses

We conducted separate meta-analyses to examine left and right habenula volumes in individuals with a mood disorder (i.e. MDD or BD), MDD, and BD, stratified by segmentation method (automatic versus manual). Additionally, we carried out six tests of subgroup differences based on the segmentation method for each diagnostic group (mood disorder, MDD, and BD) and hemisphere (left and right) (Supplementary Figures S7–S12). None of the separate meta-analyses or tests of subgroup differences remained statistically significant after FDR correction. We then repeated the same set of analyses for medication status (medicated versus unmedicated) (Supplementary Figures S13–S18), and observed a similar pattern, with no statistically significant results following correction. Meta-regressions tested MRI resolution as a moderator; it was not significant for either habenula in mood disorders (left: β = −0.1201, p = .3317; right: β = 0.0571, p = .6556) or in MDD-only analyses (left: β = −0.4551, p = .2600; right: β = −0.0443, p = .9179).

Discussion

Our meta-analyses offer the first comprehensive synthesis of evidence on habenula volume in mood disorders. In our global meta-analyses – pooling data from MDD and BD – we found small reductions in both left and right habenula volume, though these did not survive FDR correction. Separate analyses of MDD and BD showed no significant group differences, but all four subgroup meta-analyses revealed nonsignificant volume reductions, with effect sizes ranging from −0.09 (left) to −0.15 (right) in MDD, and − 0.13 (left) to −0.23 (right) in BD. Although the results from our six meta-analyses do not provide conclusive evidence for reduced habenula volume in mood disorders, they consistently point toward a possible small reduction, as all analyses showed effects in the same direction – albeit non-significant – and the two global meta-analyses reached statistical significance prior to FDR correction.

To assess publication bias, we used Egger’s test, funnel plots, and the trim-and-fill method. Egger’s test showed no evidence of bias in the global meta-analyses. The trim-and-fill procedure identified no missing studies for left habenula volume but suggested possible bias for the right. After imputing studies, the adjusted effect size for right habenula volume remained statistically significant and shifted slightly toward a more negative value (g = −0.2247), further supporting the possibility of a small volumetric reduction in mood disorders. Overall, our findings raise no major concerns about publication bias and may even suggest a bias toward reporting increased volume in mood disorders.

As registered, we conducted subgroup analyses by segmentation method and medication status, as well as meta-regressions with MRI resolution as a moderator. No comparisons between automatic and manual segmentation were significant, nor were any meta-analyses based on subgroups after FDR correction. MRI resolution was not a significant moderator. Overall, results from the subgroup analyses and meta-regressions should be interpreted cautiously due to limited power – no analysis included more than 14 samples.

Although our findings did not survive FDR correction, reduced habenula volume in mood disorders would align with emerging evidence from animal models. Two studies have examined habenula volume in depression models: Yang et al. (Reference Yang, Kim, Yang, Lee, Sun, Lee and Kim2019) reported reduced total volume in a lipopolysaccharide model of depression, while Jacinto et al. (Reference Jacinto, Mata, Novais, Marques and Sousa2017) found bilateral volume reductions following chronic stress, along with a decreased number of neurons in the right MHb and a decreased number of glial cells bilaterally in the LHb. Human studies also suggest that effective treatment may increase habenula volume. Etienne et al. (Reference Etienne, Boutigny, David, Deflesselle, Gressier, Becquemont, Corruble and Colle2024) observed significant volume increases after 3 months of venlafaxine in MDD patients, and Elias et al. (Reference Elias, Germann, Loh, Boutet, Pancholi, Beyn, Bhat, Woodside, Giacobbe, Kennedy and Lozano2022) reported bilateral volume increases in responders to subcallosal cingulate deep brain stimulation, with clinical response linked to volume change. Sartorius et al. (Reference Sartorius, Demirakca, Böhringer, Clemm von Hohenberg, Aksay, Bumb, Kranaster and Ende2016) found increased gray matter volume in both habenulae after electroconvulsive therapy in treatment-resistant depression, though interpretation is limited by the lack of correlation with clinical scores. In contrast, Anand et al. (Reference Anand, Nakamura, Spielberg, Cha, Karne and Hu2020) reported reduced habenula volume after lithium treatment in BD. Overall, our findings align with several lines of evidence – both in humans and animals – suggesting reduced habenula volume in mood disorders.

The neurotrophic hypothesis of depression may offer a framework for understanding the putative link between habenula volume and mood disorders (Duman & Monteggia, Reference Duman and Monteggia2006). It posits that stress – and the resulting elevation of glucocorticoids – reduces expression of neurotrophic factors, particularly BDNF, in key limbic regions (Duman & Monteggia, Reference Duman and Monteggia2006). The resulting BDNF deficiency is thought to drive structural atrophy and neuronal and glial loss, particularly in the hippocampus and mPFC (Duman, Aghajanian, Sanacora, & Krystal, Reference Duman, Aghajanian, Sanacora and Krystal2016; Duman & Monteggia, Reference Duman and Monteggia2006; Pittenger & Duman, Reference Pittenger and Duman2008). Similar mechanisms could plausibly affect the habenula as well, with elevated glucocorticoids and reduced BDNF signaling contributing to its structural alterations.

In both animal models and human studies, increased glucocorticoid exposure is associated with hippocampal (Lupien et al., Reference Lupien, De Leon, De Santi, Convit, Tarshish, Nair, Thakur, McEwen, Hauger and Meaney1998; Zhang, Zhao, & Wang, Reference Zhang, Zhao and Wang2015) and mPFC (Kim et al., Reference Kim, Yi, Choi, Hong, Shin and Kang2014; Stomby et al., Reference Stomby, Boraxbekk, Lundquist, Nordin, Nilsson, Adolfsson, Nyberg and Olsson2016) atrophy. Supporting a similar pattern in the habenula, Jacinto et al. (Reference Jacinto, Mata, Novais, Marques and Sousa2017) found strong negative correlations between systemic glucocorticoid levels and bilateral habenula volume. However, it remains unclear whether this reflects a direct effect, as glucocorticoid receptors have not been identified in the habenula (Aronsson et al., Reference Aronsson, Fuxe, Dong, Agnati, Okret and Gustafsson1988). Another possible contributor to stress-related habenula atrophy is corticotropin-releasing hormone (CRH), a key regulator of the stress response (Sukhareva, Reference Sukhareva2021), with known receptor expression in the habenula (Authement et al., Reference Authement, Langlois, Shepard, Browne, Lucki, Kassis and Nugent2018; Justice, Yuan, Sawchenko, & Vale, Reference Justice, Yuan, Sawchenko and Vale2008). In the hippocampus, CRH signaling via CRH receptor 1 (CRHR1) has been implicated in stress-induced atrophy (Maras & Baram, Reference Maras and Baram2012), with evidence suggesting that hippocampal neurons themselves are a primary source of CRH acting locally on CRHR1 receptors, contributing to structural degradation (Chen, Andres, Frotscher, & Baram, Reference Chen, Andres, Frotscher and Baram2012). A similar mechanism may operate in the habenula. The rodent LHb has been shown to be highly responsive to CRH (Authement et al., Reference Authement, Langlois, Shepard, Browne, Lucki, Kassis and Nugent2018), and CRHR1 expression has been identified in this region (Justice et al., Reference Justice, Yuan, Sawchenko and Vale2008). Strikingly, retrograde tracing in CRH-Cre mice has shown that the LHb itself is a major source of CRH projections to the LHb (Flerlage et al., Reference Flerlage, Gouty, Thomas, Simmons, Tsuda, Rujan, Iyer, Petrus, Cox and Wu2025), as is the case for the hippocampus. These parallels raise the possibility that locally driven CRH–CRHR1 signaling within the habenula may also contribute to stress-related atrophy.

Further supporting the notion that the neurotrophic hypothesis of depression may also apply to the habenula, several studies show that stress and antidepressant treatments modulate BDNF expression in this region. Zhang et al. (Reference Zhang, Lyu, Wang, Shi, Wang, Yang, Huang, Wei, Chen, Xu and Hong2022) reported significantly reduced BDNF levels in the habenula of rats exposed to chronic restraint stress, with ketamine treatment increasing habenula BDNF levels. Similarly, Tong et al. (Reference Tong, Chen, Hao, Shen, Chen, Cheng, Yan, Li, Li, Gulizhaerkezi, Zeng and Meng2023) found decreased LHb BDNF expression in rats subjected to chronic unpredictable mild stress, reversed by acupuncture or fluoxetine treatment. Consistent with this, Sachs et al. (Reference Sachs and Caron2015) observed elevated levels of BDNF mRNA in the habenula of mice after fluoxetine administration. In contrast, however, Lei et al. (Reference Lei, Dong, Song, Sun, Liu and Zhao2020) reported that the antidepressant effects of Rislenemdaz may involve downregulation of BDNF in the LHb, suggesting that the relationship between BDNF and antidepressant mechanisms in the habenula may be complex and context-dependent.

Lastly, inflammation represents another potential mechanism hypothesized to contribute to structural alterations in the hippocampus and mPFC (Belleau et al., Reference Belleau, Treadway and Pizzagalli2019), and may similarly impact the habenula. Chronic unpredictable stress has been shown to increase the production of pro-inflammatory cytokines in both the hippocampus (Iwata et al., Reference Iwata, Ota, Li, Sakaue, Li, Dutheil, Banasr, Duric, Yamanashi and Kaneko2016) and the mPFC (Pan, Chen, Zhang, & Kong, Reference Pan, Chen, Zhang and Kong2014). Notably, similar stress paradigms also upregulate inflammatory cytokine expression in the habenula (Wang et al., Reference Wang, Qu, Sun, Li, Liu and Yang2022), pointing to inflammation as a common downstream consequence of stress exposure that may contribute to structural changes across multiple mood-related brain regions.

While our discussion highlights several neurobiological mechanisms that could plausibly underlie structural changes in the habenula, we must emphasize that our findings did not survive correction for multiple comparisons. These explanations should therefore be considered preliminary and hypothesis-generating, as future studies are needed to confirm whether habenula volume reductions are reliably observed in mood disorders.

Limitations and future directions

One limitation of our study is that research on habenula volume in mood disorders is still relatively nascent, resulting in a limited number of eligible studies. Notably, the effect sizes observed in our global analyses – g = −0.14 for the left habenula and −0.16 for the right – were similar in magnitude to those reported for hippocampal volume in a large meta-analysis of 1,728 MDD patients and 7,199 HCs (d = −0.14) (Schmaal et al., Reference Schmaal, Veltman, van Erp, Sämann, Frodl, Jahanshad, Loehrer, Tiemeier, Hofman and Niessen2016). However, our small number of samples likely limited statistical power, preventing effects from surviving FDR correction. As more data accumulate, future meta-analyses may be positioned to detect reliable effects. Additionally, our subgroup analyses and meta-regression were underpowered, limiting our ability to draw conclusions about potential moderators of effect size. While we attempted to examine the impact of medication status, our analysis was limited both by the small number of available samples and by the fact that most studies did not report data stratified by medication status. As a result, we were only able to compare unmedicated samples to those that included at least some medicated participants. Existing evidence suggests that habenula volume may increase following antidepressant treatment, indicating that medication exposure may have influenced our results (Elias et al., Reference Elias, Germann, Loh, Boutet, Pancholi, Beyn, Bhat, Woodside, Giacobbe, Kennedy and Lozano2022; Etienne et al., Reference Etienne, Boutigny, David, Deflesselle, Gressier, Becquemont, Corruble and Colle2024; Sartorius et al., Reference Sartorius, Demirakca, Böhringer, Clemm von Hohenberg, Aksay, Bumb, Kranaster and Ende2016). To enhance the ability of future meta-analyses to detect medication-related effects, it is crucial that primary studies systematically report findings separately for medicated and unmedicated participants. Another important factor likely affecting the magnitude of volume reductions is illness severity. Indeed, volume reductions in the hippocampus and mPFC have been consistently linked to markers of illness progression, including recurrent episodes, longer illness duration, and treatment resistance (Schmaal et al., Reference Schmaal, Veltman, van Erp, Sämann, Frodl, Jahanshad, Loehrer, Tiemeier, Hofman and Niessen2016). Unfortunately, very few studies in our dataset reported sufficient detail on illness severity, precluding us from examining its role in habenula volume. Future research should prioritize the collection of such clinical variables to better understand their impact.

Finally, a broader methodological limitation in the field is the difficulty of accurately segmenting the habenula due to its small size and poor contrast with adjacent structures (Strotmann et al., Reference Strotmann, Kögler, Bazin, Weiss, Villringer and Turner2013), which may limit measurement precision. To address this, future studies should prioritize the use of ultra-high-field MRI (e.g. 7 T) to improve spatial resolution and contrast (Calabro et al., Reference Calabro, Parr, Sydnor, Hetherington, Prasad, Ibrahim, Sarpal, Famalette, Verma and Luna2024; Sclocco, Beissner, Bianciardi, Polimeni, & Napadow, Reference Sclocco, Beissner, Bianciardi, Polimeni and Napadow2018). Only two included samples employed 7 T imaging, underscoring the need for wider adoption of this technology. Another limitation of the field is the reliance on manual habenula segmentation, which may be prone to imprecision due to the small size of the structure and the requirement for detailed anatomical expertise. A promising avenue for future research is the application of automated habenula segmentation methods (e.g. Kim & Xu, Reference Kim and Xu2022; Kyuragi et al., Reference Kyuragi, Oishi, Hatakoshi, Hirano, Noda, Yoshihara, Ito, Igarashi, Miyata, Takahashi, Kamiya, Matsumoto, Okada, Fushimi, Nakagome, Mimura, Murai and Suwa2024) to large databases of patients with a mood disorder, as this approach would enable the analysis of larger samples by overcoming the time constraints of manual segmentation, thereby increasing statistical power.

Conclusion

In conclusion, although small reductions in left and right habenula volumes were observed in mood disorders, these did not survive FDR correction. Furthermore, separate analyses for BD and MDD showed no significant group differences in habenula volumes for either hemisphere. Interestingly, the effect sizes observed were similar in magnitude to those reported for hippocampal volume reductions in depression, suggesting that our meta-analyses may have lacked sufficient power to detect statistically significant effects. Nonetheless, the consistent direction of effects across analyses hints at a true diminution in habenula volume in mood disorders. Future studies with ultra-high-field MRI, automated segmentation, and larger samples are needed.

Supplementary material

The supplementary material for this article can be found at http://doi.org/10.1017/S0033291726103730.

Data availability statement

Raw data and analysis scripts are available at: https://osf.io/fc95y/overview.

Funding statement

This study was funded by a Discovery Grant (S.H), a doctoral scholarship (J.S.F), and a master’s scholarship (C.P) from the Natural Sciences and Engineering Research Council of Canada. The funding body was not involved in the study design, collection, analysis, or interpretation of data, nor in the writing of the manuscript and the decision to submit the article for publication.

Competing interests

Competing interests: The author(s) declare none.

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Figure 0

Figure 1. PRISMA flow diagram of the study selection process.

Figure 1

Table 1. Summary of characteristics of included samples

Figure 2

Figure 2. Forest plot for the meta-analysis comparing the volume of the left habenula in patients with a mood disorder versus healthy controls (HCs).

Figure 3

Figure 3. Forest plot for the meta-analysis comparing the volume of the right habenula in patients with a mood disorder versus healthy controls (HCs).

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