Skip to main content
Download PDF

Gender differences in major depressive disorder at different ages: a REST-meta-MDD project-based study

BMC Psychiatry volume 24, Article number: 575 (2024) Cite this article

Abstract

Background

Major depressive disorder (MDD) is a highly heterogeneous disease, with differences in clinical manifestations among depression patients based on onset ages and genders. The neural mechanisms underlying these differences remain unclear. In this study, we utilized resting state functional imaging data from a large sample database and adopted the ReHo method to investigate gender differences in local brain function in MDD patients across different onset age groups.

Methods

The study included 364 MDD patients and 695 healthy participants who were part of the REST-meta-MDD project. Regional homogeneity (ReHo) assessed gender disparities in MDD and healthy individuals within groups delineated by gender and onset age (young group: 18–29 years; middle-aged group: 30–45 years).

Results

Among the young MDD groups, there were significant gender differences in the right superior frontal gyrus, right inferior frontal gyrus, left superior temporal gyrus, and right superior parietal lobule, with male MDD patients having higher ReHo values compared to females. When compared to healthy males, male MDD patients exhibited elevated ReHo values in the right superior parietal lobule. In the middle-aged groups, a marked ReHo difference was observed in the bilateral cerebellum posterior lobe, with female MDD patients showing higher ReHo values.

Conclusions

The functional mechanisms of MDD differ between genders and show distinct variations across different onset age groups. These findings underscore the importance of developing personalized interventions that address the unique needs of MDD patients, tailored to their gender and age, and necessitate the development of antidepressant medications targeted at each gender-age subgroup.

Peer Review reports

Background

Major depressive disorder (MDD) is a neuropsychiatric disease characterized by core symptoms such as emotional dissonance, depressed mood, guilt, anhedonia, and cognitive and behavioral symptoms [1]. It affects over 300 million people globally [2], with a lifetime prevalence rate exceeding 20% [3].

Depression is a highly heterogeneous condition, with gender differences contributing to its variability.Significant gender disparities exist in MDD’s morbidity, symptom presentation, and response to antidepressant treatment. Women exhibit twice the morbidity of singular MDD episodes and four times that of recurrent MDD compared to men [4, 5]. Moreover, female MDD patients tend to experience more severe symptoms and higher subjective distress than their male counterparts [6, 7]. Women are more prone to comorbid anxiety [8], while men are more susceptible to comorbid substance use disorders [9]. Additionally, the onset age significantly contributes to the heterogeneity observed in MDD. Literature suggests variances in heritability, illness severity, and chronicity of MDD symptoms between early-onset MDD (age < 30) and late-onset MDD (age > 30) [10, 11]. Furthermore, MDD onset in middle-aged patients (age > 45) may be influenced more by vascular factors [12]. There are notable differences in MDD across genders and onset ages, presenting challenges in objective diagnosis and precise treatment of the disorder.

Resting State fMRI (rs-fMRI) is a prevalent technique in the study of mental disorders due to its non-invasive and radiation-free nature.Rs-fMRI does not necessitate any specific tasks or external stimuli, facilitating easier cooperation from patients. This method is crucial in researching the pathological mechanisms underlying emotional and cognitive disorders. Recent studies using rs-fMRI have highlighted gender disparities in regional cerebral activity and brain structure in MDD. Tu et al. [13] employed ReHo and the ALFF method to investigate gender differences in MDD, determining that the occipital lobe, calcarine, dorsolateral prefrontal cortex (DLPFC), median cingulate and paracingulate gyri (DCG) are pivotal in explaining these differences. In MDD females compared to males, the ALFF values decreased in the right superior occipital gyrus, while the ReHo values in the left calcarine and left dorsolateral superior frontal gyrus diminished. In a separate study, Sun et al. [14] used the ReHo method to discern gender differences in brain activity among recurrent depression (RDE) patients. They identified significant disparities in the right middle temporal gyrus, right thalamus, and left posterior cerebellar lobe. Furthermore, interactions between gender and depression diagnosis were evident in the left middle frontal gyrus, left precentral gyrus, and right insula.

Numerous studies have investigated the mechanisms underlying gender differences in depression from various angles. However, these studies often report inconsistent brain regions exhibiting gender disparities, which might be attributed to their limited sample sizes (with fewer than 50 patients) and other sources of heterogeneity, such as the onset age of MDD. Shen et al. [15, 16] discovered that, compared to early-onset depression in adults (EOD, 18–29 years old) and late-onset depression in adults (LOD, 30–44 years old), the grey matter volume (GMV) in the right posterior cingulate cortex was reduced in the EOD group. This group also exhibited a significant increase in ReHo in the left precuneus and a decrease in the right fusiform, suggesting varying pathological mechanisms in adult depression patients of different age groups. Previous studies utilized age as a covariate to examine gender disparities in local brain activity associated with MDD. However, these studies failed to independently assess the influence of gender and onset age, compromising the consistency and accuracy of their findings.

In contrast, the present study utilized extensive data samples from MDD patients sourced from the REST-meta-MDD project, mitigating the potential overestimation bias associated with smaller samples [17, 18]. Drawing from prior research, our study selected MDD patients with a course of less than 12 months in the database and divided them into a young group (18–29 years old) and a middle-aged group (30–45 years old) of MDD patients (young group representing early- onset depression, middle-aged group representing late-onset depression), and selected a healthy control (HC) group of corresponding ages. This study used the ReHo method to analyze the differences in MDD patients of different genders at different onset ages, minimizing potential confounding factors such as sample size, onset age, gender, and vascular diseases in older populations. This aids in providing beneficial assistance for the precise identification and treatment of MDD.

Methods

Clinical materials and groups

The study data were from the open, multisite dataset provided by the REST-meta-MDD project (http://rfmri.org/REST-meta-MDD) [19], encompassing 25 datasets from 2,428 individuals (1,300 MDD patients and 1,128 HCs) across 17 hospitals in China. All participants underwent T1-weighted structural MRI and fMRI. Data collection received approval from the respective local ethics committees, ensuring all REST-meta-MDD project data were de-identified and anonymized to maintain participant privacy.To minimize site effects on the results, we applied several techniques and statistical methods. In the data preprocessing phase, we normalized the imaging data across different sites to ensure uniformity. During statistical analysis, site was included as a covariate to account for any potential site-specific biases. We also evaluated the sample size and data quality from each site to ensure compliance with study standards. These steps were taken to enhance the reliability and accuracy of the results.

Participants were excluded based on the following criteria: (1) overlapping data records; (2) age < 18 or > 45 years; (3) MDD diagnosis with an HDRS score < 17; (4) illness duration exceeding 12 months; (5) incomplete data on gender, years of education, or HDRS for MDD patients; (6) incomplete gender and education information for HC; (7) subpar image quality; or (8) study centers with fewer than 10 participants in any given group.

According to the onset age, Drawing from prior research [15, 16], patients were categorized into two groups: the young group (18–29 years) and the middle-aged group (30–45 years). HCs were similarly segmented by their age during fMRI scanning. Subsequently, the young group consisted of 71 young male MDD, 109 young female MDD, 203 young male HC, and 243 young female HC. The middle-aged group was divided into: 49 middle-aged male MDD, 135 middle-aged female MDD, 108 middle-aged male HC, and 141 middle-aged female HC.

Data preprocessing and definition

R-fMRI data were preprocessed at each site using the same DPARSF protocol [20] (Supplementary material) and ReHo values were calculated. ReHo, defined as the rank-based Kendall Consistency Coefficient (KCC), assessed the synchronization among adjacent voxel time patterns (27 voxels).

Statistical analysis

Demographic data were analyzed using SPSS 26.0. Continuous data were represented as means ± standard deviations (SD). One-way ANOVA compared the age and education distribution across the four youth and middle-aged patient groups. A two-factor ANOVA, considering gender (male and female) and diagnosis (MDD and HC), contrasted the demographic parameters. Comparison of the illness duration and HDRS scorese between two patient groups use two sample t-tests.Significance was ascertained at p < 0.05.

The SPM 12 two-way ANOVA, focusing on the youth and middle-aged groups, integrated gender and diagnosis as inter-group factors; age and education level functioned as concomitant variables to identify cerebral regions with ReHo discrepancies. Resultant values underwent Gaussian random field (GRF) correction using Data Processing and Analysis for Brain Imaging (DPABI) software, establishing statistical significance at a voxel threshold level p < 0.001 and a cluster size p < 0.05. ReHo values highlighting gender-related cerebral region differences were extracted and subjected to a post hoc test (Bonferroni correction, p < 0.05). Spearman analysis examined the correlation between ReHo values and HAMA scores in each MDD group.

Results

Demographic data

Within the young groups, significant disparities in age and education years were evident among male MDD, female MDD, HC males, and HC females. Gender significantly influenced age, yet neither diagnosis nor the interaction between gender and diagnosis significantly impacted age. Diagnosis significantly affected education years, whereas gender and its interaction with diagnosis did not. HDRS scores and illness duration were not statistically significant differences between the young male MDD group and the young female MDD group (Table 1).

Table 1 Demographic and clinical characteristics of the young group
Full size table

In the middle-aged groups, age and education years varied significantly among male MDD, female MDD, HC males, and HC females. The interaction between gender and diagnosis significantly influenced age, but neither gender nor diagnosis alone did. Diagnosis significantly impacted education years, while gender and its interaction with diagnosis did not. HDRS scores and illness duration between middle-aged male and middle-aged female MDD patients showed no significant differences (Table 2).

Table 2 Characteristics of the middle-aged group
Full size table

ReHo values in all MDD and HCs

Pronounced differences in ReHo appeared in bilateral regions such as the superior parietal lobules, posterior central gyrus, lateral occipital, anterior cuneiform lobe, lingual gyrus, temporal lobe, and cerebellar regions(SI).

ReHo values in young groups

In terms of diagnosis’s main effects, ReHo differences were evident among the young groups in the left and right cerebellum posterior lobe (GRF correction, p < 0.05). Young male MDD patients had elevated ReHo values in the right cerebellum posterior lobe compared to young male HCs. Both young male HCs and female MDD demonstrated significantly higher ReHo values in the left cerebellum posterior lobe than young female HCs (Bonferroni correction, p < 0.05) (Table 3; Fig. 1).

Table 3 Differential cerebral regions in ReHo values for groups of young group
Full size table
Fig. 1
figure 1

Statistical maps showing main effects of diagnosis in ReHo among the four young groups (GRF correction, p < 0.05). Regions included (A) Right superior frontal gyrus; (B) Left cerebellum posterior lobe.The graph shows the ReHo values extracted from regions with the main effect of diagnosis group.*Represents a significant difference detected (p < 0.05)

Full size image

Regarding gender’s main effects, significant ReHo differences existed among the young groups in the right superior frontal gyrus, right inferior frontal gyrus, left superior temporal gyrus and right superior parietal lobule (GRF correction, p < 0.05). Young male MDD patients exhibited increased ReHo values in these regions compared to young female MDD patients (Bonferroni correction, p < 0.05). The young male MDD also showed a heightened ReHo value in the right superior parietal lobe when contrasted with young male HCs. Young male HCs displayed a higher ReHo in the right superior frontal gyrus and right inferior frontal gyrus than young female HCs (Bonferroni correction, p < 0.05) (Table 3; Fig. 2).

Fig. 2
figure 2

Statistical maps showing main effects of gender in ReHo among the four young groups (GRF correction, p < 0.05). Regions included (A) Right superior frontal gyrus; (B) Right inferior frontal gyrus; (C)Left superior temporal gyrus; (D) Right superior parietal lobule. The graph shows the ReHo values extracted from regions with the main effect of gender group.*Represents a significant difference detected (p < 0.05)

Full size image

Regarding the main effects of the gender-by-diagnosis interaction, no significant ReHo differences were observed among the four groups. Furthermore, no correlations were observed between ReHo values and HDRS scores in each differential cerebral region for MDD.

ReHo values in middle-aged groups

In terms of diagnosis’s main effects, significant ReHo disparities were found among the middle-aged groups in the bilateral posterior central gyrus, the bilateral lingual gyrus, the left anterior cuneiform lobe, the right superior temporal gyrus, the right insula lobe, the rihgt frontal orbital cortex and the bilateral cerebellum (GRF correction, p < 0.05). In these regions, the ReHo values for middle-aged MDD patients were notably lower than those for middle-aged HCs of the same sex (Bonferroni correction, p < 0.05). (Table 4; Fig. 3).

Table 4 Differential cerebral regions in ReHo values for groups of middle-aged group
Full size table
Fig. 3
figure 3

Statistical maps showing main effects of diagnosis in ReHo among the four middle-aged groups (GRF correction, p < 0.05). Regions included (A) Left anterior cuneiform lobe, bilateral cerebellum and bilateral posterior central gyrus; (B)Right superior temporal gyrus, right insula lobe and right frontal orbital cortex. The graph shows the ReHo values extracted from regions with the main effect of diagnosis group.*Represents a significant difference detected (p < 0.05)

Full size image

Regarding gender’s main effects, significant ReHo differences were observed among the four middle-aged groups in the bilateral cerebellum posterior lobe (GRF correction, p < 0.05). Middle-aged male MDD patients displayed a marked decrease in ReHo values of the bilateral cerebellum posterior lobe compared to their female counterparts (Bonferroni correction,p < 0.05) (Table 4; Fig. 4).

Fig. 4
figure 4

Statistical maps showing main effects of gender in ReHo among the four middle-aged groups (GRF correction, p < 0.05). Regions included bilateral cerebellum posterior lobe. The graph shows the ReHo values extracted from regions with the main effect of gender group.*Represents a significant difference detected (p < 0.05)

Full size image

Considering the main effects of the gender-by-diagnosis interaction, no significant ReHo differences were identified among the four groups. Additionally, there was no correlation between ReHo values and HDRS scores in each differential cerebral region for MDD.

Discussion

This study utilized a comprehensive multi-site sample from the REST-meta-MDD project, and used the ReHo method to discern gender variances in local brain function within different onset aged MDD patients. One possible reason for the observed gender differences across age groups is the varying impact of hormones on brain structure and function during development and adulthood. Hormonal changes, particularly those related to estrogen and testosterone, are known to influence brain activity and connectivity. This hormonal impact could contribute to the gender-specific ReHo value variations seen in both young and middle-aged MDD patients [21]. Additionally, socio-cultural factors, such as societal roles and stressors, might lead to different neural pathways developing in males and females, further driving gender disparities in brain activity. These variations underscore the importance of considering gender-specific treatment approaches for MDD [22].We ascertained that among young MDD groups, the brain regions with gender differences are the right superior frontal gyrus, right inferior frontal gyrus, left superior temporal gyrus and right superior parietal lobule, the ReHo values of male MDD in these regions are significantly exceeded those in female MDD.In contrast with healthy males, male MDD patients exhibited elevated ReHo values in the right superior parietal lobule. For the middle-aged groups, a pronounced ReHo value discrepancy in the bilateral cerebellum posterior lobe existed between male and female MDD patients, with females presenting higher values. Our findings robustly indicate that MDD’s functional mechanisms diverge between genders. Moreover, the functional intricacies of gender differences in MDD also fluctuate across age brackets. This research elucidates novel perspectives on the neuropathological mechanisms driving gender discrepancies in MDD.

In this study, discernible gender-related differences in brain activity were identified among young MDD patients. Notably, distinct activity patterns emerged in the right superior frontal gyrus, right inferior frontal gyrus, left superior temporal gyrus and right superior parietal lobule. Nonetheless, these variations bore no correlation to MDD severity. The temporal lobe, responsible for processing negative emotions and fear, exhibits heightened activity that can impede cognitive function and conflict resolution in adult MDD patients [23, 24]. The lack of correlation between these brain activity variations and MDD severity suggests that gender-based differences may reflect underlying biological processes rather than symptom intensity. The heightened activity in the temporal lobe could be attributed to its role in emotion processing, which might be influenced by gender-specific factors such as socialization patterns and coping mechanisms. Given that MDD is a multifaceted disorder, these gender-based discrepancies may represent different paths of disease progression or coping strategies, indicating that gender might play a role in how MDD manifests at the neural level. Both genders demonstrate enhanced activation in the left temporal lobe during the object recognition phase of vocabulary extraction, underlining gender disparities in temporal lobe-mediated situational language memory [25]. Certain studies posit gender-based volume variations in the left temporal lobe among the youth, potentially providing the structural foundation for distinct cognitive functions [26]. The frontal orbital cortex, vital for diverse cognitive and emotional tasks, has associations with MDD [27,28,29]. A dysfunction in the prefrontal region of the frontoparietal network augments MDD and suicide risk [30, 31]. Moreover, glutamate-related gene expression varies between male and female MDD patients [32], with diminished gray matter volume in the prefrontal cortex increasing susceptibility in male MDD patients [33]. Previous research indicates that heightened information complexity amplifies bilateral posterior parietal lobe blood flow [34]. However, for MDD patients, this results in decreased flow [35]. Such parietal cortex impairment can stifle new information absorption and learning [36]. The superior parietal lobule, a pivotal segment of the frontal parietal network, plays a role in attentional cognitive control and emotional regulation [36, 37]. Ultimately, the observed gender-specific brain activity variances might align more with MDD-related youth suicide incidence and risk than with symptom severity.

For middle-aged MDD patients, ReHo showcases gender differences. Contrary to the young MDD cohort, middle-aged participants exhibited ReHo value variations in distinct cerebral regions, especially the bilateral cerebellum posterior lobe (specifically regions VII, VIII, and Crus II of the posterior cerebellar lobe). Yet, these cerebellar ReHo values held no significant relation with MDD scores. With its role in mood regulation and cognitive function, cerebellar ReHo values might differentiate subclinical from MDD, and refractory from non-refractory depressive disorders [38,39,40]. The cerebellum’s receipt of data from cortical and limbic systems, crucial for emotional regulation, underscores that cerebellar malfunctions might escalate mental strain in patients [41]. Furthermore, diminished 5-hydroxytryptamine receptor binding (5-HTT) in the cerebellar hemisphere correlates with heightened impulsivity in suicide-attempting MDD patients [42]. These observations suggest that the bilateral posterior cerebellar lobe’s regional cerebral activity disparities in middle-aged MDD patients might relate to augmented impulsivity and a heightened rate of successful suicide attempts, especially in males. Nonetheless, no correlation emerged between ReHo values and HAMD scores in this study.

The findings indicate that MDD’s pathophysiological mechanisms exhibit gender-based differences and onset age-related variations. While regional cerebral activity differences appear in both healthy subjects and MDD patients, specific regions differ. Notably, ReHo values did not denote MDD severity, given the absence of correlation with depression scores. Additionally, compared to male HCs, young male MDD patients exhibit elevated ReHo values in the right superior parietal lobule. This suggests that this region might be pivotal in diagnosing and treating early ontset male MDD. Hence, shifts in ReHo values could offer diagnostic cues for this demographic, warranting further exploration.

Significant gender-related variations in brain activity were observed between healthy males and females. Male youths demonstrated enhanced activity in the right frontal orbital cortex relative to their female counterparts, whereas middle-aged females displayed heightened cerebellar activity. These observations are consistent with prior research on gender disparities in brain structure and function [43,44,45]. However, the extent to which these differences influence gender disparities in MDD, as documented in previous literature [46], remains inconclusive. The findings suggest that gender-related variations in MDD mirror typical disparities in brain development across genders at different life stages, hinting at a possible connection between gender-related MDD mechanisms and standard brain maturation.

The present study acknowledges certain limitations. The database provided incomplete information regarding patient medication, disease progression, and recurrence. Given that participants were sourced from this database, the analysis was constrained to the available data, thus excluding certain indicators from the study.

Conclusions

This study confirms the presence of gender-specific differences in regional cerebral neurological activity among MDD patients across various age groups. Our findings suggest that gender disparities in MDD-related brain function are influenced by age at onset, with distinct patterns emerging in different age brackets. In young MDD patients, the key regions of gender disparity were the right superior frontal gyrus, right inferior frontal gyrus, left superior temporal gyrus, and right superior parietal lobule. For middle-aged MDD patients, significant gender-based differences were primarily observed in the bilateral cerebellum posterior lobe.These results highlight the need for continued research to uncover the underlying mechanisms driving these gender disparities in cerebral activity. Future studies should aim to explore how these gender-based differences in brain function influence MDD’s clinical presentation, treatment response, and long-term outcomes. A deeper understanding of these differences could inform the development of gender-specific treatment strategies and provide a basis for the development of antidepressant medications targeted at each gender-age subgroup.

Data availability

All data generated or analysed during this study are included in this published article.

Abbreviations

MDD:

Major depressive disorder

fmri:

Functional magnetic resonance imaging

reho:

Regional homogeneity

rs-fmri:

Resting State fmri

RDE:

Recurrent depression

GMV:

Grey matter volume

SD:

Standard deviations

GRF:

Gaussian random field

References

  1. Seney ML, Glausier J, Sibille E. Large-scale Transcriptomics studies provide insight into sex differences in Depression. Biol Psychiatry. 2022;91:14–24.

    Article  CAS  PubMed  Google Scholar 

  2. Herrman H, Kieling C, McGorry P, Horton R, Sargent J, Patel V. Reducing the global burden of depression: a Lancet-World Psychiatric Association Commission. Lancet. 2019;393:e42–3.

    Article  PubMed  Google Scholar 

  3. Hasin DS, Sarvet AL, Meyers JL, Saha TD, Ruan WJ, Stohl M, et al. Epidemiology of adult DSM-5 major depressive disorder and its Specifiers in the United States. JAMA Psychiatry. 2018;75:336–46.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Kornstein SG, Schatzberg AF, Thase ME, Yonkers KA, McCullough JP, Keitner GI, et al. Gender differences in chronic major and double depression. J Affect Disord. 2000;60:1–11.

    Article  CAS  PubMed  Google Scholar 

  5. Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005;62:593–602.

    Article  PubMed  Google Scholar 

  6. Angst J, Dobler-Mikola A. Do the diagnostic criteria determine the sex ratio in depression? J Affect Disord. 1984;7:189–98.

    Article  CAS  PubMed  Google Scholar 

  7. Frank E, Carpenter LL, Kupfer DJ. Sex differences in recurrent depression: are there any that are significant? Am J Psychiatry. 1988;145:41–5.

    Article  CAS  PubMed  Google Scholar 

  8. Silverstein B. Gender difference in the prevalence of clinical depression: the role played by depression associated with somatic symptoms. Am J Psychiatry. 1999;156:480–2.

    Article  CAS  PubMed  Google Scholar 

  9. Najt P, Fusar-Poli P, Brambilla P. Co-occurring mental and substance abuse disorders: a review on the potential predictors and clinical outcomes. Psychiatry Res. 2011;186:159–64.

    Article  PubMed  Google Scholar 

  10. Lyons MJ, Eisen SA, Goldberg J, True W, Lin N, Meyer JM, et al. A registry-based twin study of depression in men. Arch Gen Psychiatry. 1998;55:468–72.

    Article  CAS  PubMed  Google Scholar 

  11. Mondimore FM, Zandi PP, Mackinnon DF, McInnis MG, Miller EB, Crowe RP, et al. Familial aggregation of illness chronicity in recurrent, early-onset major depression pedigrees. Am J Psychiatry. 2006;163:1554–60.

    Article  PubMed  Google Scholar 

  12. Kendler KS, Fiske A, Gardner CO, Gatz M. Delineation of two genetic pathways to major depression. Biol Psychiatry. 2009;65:808–11.

    Article  CAS  PubMed  Google Scholar 

  13. Tu Z, Wu F, Jiang X, Kong L, Tang Y. Gender differences in major depressive disorders: a resting state fMRI study. Front Psychiatry. 2022;13:1025531.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Sun J, Gao S, Ma Y, Guo C, Du Z, Luo Y et al. A study of Differential resting-state brain functional activity in males and females with recurrent depressive disorder. Brain Sci. 2022;12.

  15. Shen Z, Jiang L, Yang S, Ye J, Dai N, Liu X, et al. Identify changes of brain regional homogeneity in early and later adult onset patients with first-episode depression using resting-state fMRI. PLoS ONE. 2017;12:e0184712.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Shen Z, Cheng Y, Yang S, Dai N, Ye J, Liu X, et al. Changes of grey matter volume in first-episode drug-naive adult major depressive disorder patients with different age-onset. Neuroimage Clin. 2016;12:492–8.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Ioannidis JP. Why most published research findings are false. PLoS Med. 2005;2:e124.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Zuo XN, Xu T, Milham MP. Harnessing reliability for neuroscience research. Nat Hum Behav. 2019;3:768–71.

    Article  PubMed  Google Scholar 

  19. Yan CG, Chen X, Li L, Castellanos FX, Bai TJ, Bo QJ, et al. Reduced default mode network functional connectivity in patients with recurrent major depressive disorder. Proc Natl Acad Sci U S A. 2019;116:9078–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chao-Gan Y, Yu-Feng Z. DPARSF: a MATLAB Toolbox for Pipeline Data Analysis of resting-state fMRI. Front Syst Neurosci. 2010;4:13.

    PubMed  PubMed Central  Google Scholar 

  21. McHenry J, Carrier N, Hull E, et al. Sex differences in anxiety and depression: role of testosterone. Front Neuroendocr. 2013;35(1):42–57.

    Article  Google Scholar 

  22. Rubinow DR, Schmidt PJ. Sex differences and the neurobiology of affective disorders. Neuropsychopharmacology. 2018;44(1):111–28.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Surguladze SA, El-Hage W, Dalgleish T, Radua J, Gohier B, Phillips ML. Depression is associated with increased sensitivity to signals of disgust: a functional magnetic resonance imaging study. J Psychiatr Res. 2010;44:894–902.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lai CH, Wu YT. The alterations in regional homogeneity of parieto-cingulate and temporo-cerebellum regions of first-episode medication-naïve depression patients. Brain Imaging Behav. 2016;10:187–94.

    Article  PubMed  Google Scholar 

  25. Wu T, Zang Y, Wang L, Long X, Li K, Chan P. Normal aging decreases regional homogeneity of the motor areas in the resting state. Neurosci Lett. 2007;423:189–93.

    Article  CAS  PubMed  Google Scholar 

  26. Lenroot RK, Giedd JN. Sex differences in the adolescent brain. Brain Cogn. 2010;72:46–55.

    Article  PubMed  Google Scholar 

  27. Sun J, Chen L, He J, Du Z, Ma Y, Wang Z, et al. Altered brain function in First-Episode and Recurrent Depression: a resting-state functional magnetic resonance imaging study. Front Neurosci. 2022;16:876121.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Brosch K, Stein F, Meller T, Schmitt S, Yuksel D, Ringwald KG, et al. DLPFC volume is a neural correlate of resilience in healthy high-risk individuals with both childhood maltreatment and familial risk for depression. Psychol Med. 2021;52:1–7.

    PubMed  Google Scholar 

  29. Nejati V, Majidinezhad M, Nitsche M. The role of the dorsolateral and ventromedial prefrontal cortex in emotion regulation in females with major depressive disorder (MDD): a tDCS study. J Psychiatr Res. 2022;148:149–58.

    Article  PubMed  Google Scholar 

  30. Kolb B, Mychasiuk R, Muhammad A, Li Y, Frost DO, Gibb R. Experience and the developing prefrontal cortex. Proc Natl Acad Sci U S A. 2012;109(Suppl 2):17186–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Petrides M, Pandya DN. Efferent association pathways from the rostral prefrontal cortex in the macaque monkey. J Neurosci. 2007;27:11573–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Gray AL, Hyde TM, Deep-Soboslay A, Kleinman JE, Sodhi MS. Sex differences in glutamate receptor gene expression in major depression and suicide. Mol Psychiatry. 2015;20:1057–68.

    Article  CAS  PubMed  Google Scholar 

  33. Carlson JM, Depetro E, Maxwell J, Harmon-Jones E, Hajcak G. Gender moderates the association between dorsal medial prefrontal cortex volume and depressive symptoms in a subclinical sample. Psychiatry Res. 2015;233:285–8.

    Article  PubMed  Google Scholar 

  34. Grafton ST, Mazziotta JC, Presty S, Friston KJ, Frackowiak RS, Phelps ME. Functional anatomy of human procedural learning determined with regional cerebral blood flow and PET. J Neurosci. 1992;12:2542–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Deiber MP, Passingham RE, Colebatch JG, Friston KJ, Nixon PD, Frackowiak RS. Cortical areas and the selection of movement: a study with positron emission tomography. Exp Brain Res. 1991;84:393–402.

    Article  CAS  PubMed  Google Scholar 

  36. Liang MJ, Zhou Q, Yang KR, Yang XL, Fang J, Chen WL, et al. Identify changes of brain regional homogeneity in bipolar disorder and unipolar depression using resting-state FMRI. PLoS ONE. 2013;8:e79999.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Qin J, Wei M, Liu H, Yan R, Luo G, Yao Z, et al. Abnormal brain anatomical topological organization of the cognitive-emotional and the frontoparietal circuitry in major depressive disorder. Magn Reson Med. 2014;72:1397–407.

    Article  PubMed  Google Scholar 

  38. Wolf U, Rapoport MJ, Schweizer TA. Evaluating the affective component of the cerebellar cognitive affective syndrome. J Neuropsychiatry Clin Neurosci. 2009;21:245–53.

    Article  PubMed  Google Scholar 

  39. Zhang B, Liu S, Chen S, Yan F, Ke Y, Chen L, et al. Common and unique neural activities in subclinical depression and major depressive disorder indicate the development of brain impairments in different depressive stages. J Affect Disord. 2022;317:278–86.

    Article  PubMed  Google Scholar 

  40. Guo WB, Liu F, Chen JD, Gao K, Xue ZM, Xu XJ, et al. Abnormal neural activity of brain regions in treatment-resistant and treatment-sensitive major depressive disorder: a resting-state fMRI study. J Psychiatr Res. 2012;46:1366–73.

    Article  PubMed  Google Scholar 

  41. Hilber P. The role of the cerebellar and vestibular networks in anxiety disorders and Depression: the Internal Model Hypothesis. Cerebellum. 2022;21:791–800.

    Article  PubMed  Google Scholar 

  42. Ryding E, Ahnlide JA, Lindström M, Rosén I, Träskman-Bendz L. Regional brain serotonin and dopamine transporter binding capacity in suicide attempters relate to impulsiveness and mental energy. Psychiatry Res. 2006;148:195–203.

    Article  CAS  PubMed  Google Scholar 

  43. Filippi M, Valsasina P, Misci P, Falini A, Comi G, Rocca MA. The organization of intrinsic brain activity differs between genders: a resting-state fMRI study in a large cohort of young healthy subjects. Hum Brain Mapp. 2013;34:1330–43.

    Article  PubMed  Google Scholar 

  44. Luders E, Gaser C, Narr KL, Toga AW. Why sex matters: brain size independent differences in gray matter distributions between men and women. J Neurosci. 2009;29:14265–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Luders E, Narr KL, Thompson PM, Woods RP, Rex DE, Jancke L, et al. Mapping cortical gray matter in the young adult brain: effects of gender. NeuroImage. 2005;26:493–501.

    Article  CAS  PubMed  Google Scholar 

  46. Yang X, Peng Z, Ma X, Meng Y, Li M, Zhang J, et al. Sex differences in the clinical characteristics and brain gray matter volume alterations in unmedicated patients with major depressive disorder. Sci Rep. 2017;7:2515.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

The study was supported by the National High Technology Research and Development Program of China (no.2019YFA0706201), National Natural Science Foundation of China (no.82271543).

Author information

Authors and Affiliations

  1. NHC Key Laboratory of Mental Health (Peking University), and National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University Sixth Hospital, Peking University Institute of Mental Health, Peking University, 51 Huayuanbei Road, Beijing, 100191, China

    Xi Tian, Na Hu, Lin Lu & Peng Li

  2. Department of Radiology, Beijing University of Chinese Medicine Third Affiliated Hospital, Beijing, 100029, China

    Lili Tan

Authors
  1. Xi Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Na Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lin Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lili Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Peng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

P.L. designed the experiments and revised the manuscript. X.T collected and analyzed the data and wrote the manuscript. L.L., N.H. and L.T. participated in the discussion and offered some good ideas. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Peng Li.

Ethics declarations

Ethics approval and consent to participate

Data collection received approval from the respective local ethics committees, ensuring all REST-meta-MDD project data were de-identified and anonymized to maintain participant privacy. I confirm that all methods were performed in accordance with the relevant guidelines. All procedures were performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, X., Hu, N., Lu, L. et al. Gender differences in major depressive disorder at different ages: a REST-meta-MDD project-based study. BMC Psychiatry 24, 575 (2024). https://doi.org/10.1186/s12888-024-06021-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12888-024-06021-6

Keywords

BMC Psychiatry

ISSN: 1471-244X

Contact us