Centre for Youth Mental Health - Research Publications
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ItemAssociations of depression and regional brain structure across the adult lifespan: Pooled analyses of six population-based and two clinical cohort studies in the European Lifebrain consortium(ELSEVIER SCI LTD, 2022)OBJECTIVE: Major depressive disorder has been associated with lower prefrontal thickness and hippocampal volume, but it is unknown whether this association also holds for depressive symptoms in the general population. We investigated associations of depressive symptoms and depression status with brain structures across population-based and patient-control cohorts, and explored whether these associations are similar over the lifespan and across sexes. METHODS: We included 3,447 participants aged 18-89 years from six population-based and two clinical patient-control cohorts of the European Lifebrain consortium. Cross-sectional meta-analyses using individual person data were performed for associations of depressive symptoms and depression status with FreeSurfer-derived thickness of bilateral rostral anterior cingulate cortex (rACC) and medial orbitofrontal cortex (mOFC), and hippocampal and total grey matter volume (GMV), separately for population-based and clinical cohorts. RESULTS: Across patient-control cohorts, depressive symptoms and presence of mild-to-severe depression were associated with lower mOFC thickness (rsymptoms = -0.15/ rstatus = -0.22), rACC thickness (rsymptoms = -0.20/ rstatus = -0.25), hippocampal volume (rsymptoms = -0.13/ rstatus = 0.13) and total GMV (rsymptoms = -0.21/ rstatus = -0.25). Effect sizes were slightly larger for presence of moderate-to-severe depression. Associations were similar across age groups and sex. Across population-based cohorts, no associations between depression and brain structures were observed. CONCLUSIONS: Fitting with previous meta-analyses, depressive symptoms and depression status were associated with lower mOFC, rACC thickness, and hippocampal and total grey matter volume in clinical patient-control cohorts, although effect sizes were small. The absence of consistent associations in population-based cohorts with mostly mild depressive symptoms, suggests that significantly lower thickness and volume of the studied brain structures are only detectable in clinical populations with more severe depressive symptoms.
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ItemThe association between clinical and biological characteristics of depression and structural brain alterations(ELSEVIER, 2022-09-01)BACKGROUND: Structural brain alterations are observed in major depressive disorder (MDD). However, MDD is a highly heterogeneous disorder and specific clinical or biological characteristics of depression might relate to specific structural brain alterations. Clinical symptom subtypes of depression, as well as immuno-metabolic dysregulation associated with subtypes of depression, have been associated with brain alterations. Therefore, we examined if specific clinical and biological characteristics of depression show different brain alterations compared to overall depression. METHOD: Individuals with and without depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA) (328 participants from three timepoints leading to 541 observations) and the Mood Treatment with Antidepressants or Running (MOTAR) study (123 baseline participants) were included. Symptom profiles (atypical energy-related profile, melancholic profile and depression severity) and biological indices (inflammatory, metabolic syndrome, and immuno-metabolic indices) were created. The associations of the clinical and biological profiles with depression-related structural brain measures (anterior cingulate cortex [ACC], orbitofrontal cortex, insula, and nucleus accumbens) were examined dimensionally in both studies and meta-analysed. RESULTS: Depression severity was negatively associated with rostral ACC thickness (B = -0.55, pFDR = 0.03), and melancholic symptoms were negatively associated with caudal ACC thickness (B = -0.42, pFDR = 0.03). The atypical energy-related symptom profile and immuno-metabolic indices did not show a consistent association with structural brain measures across studies. CONCLUSION: Overall depression- and melancholic symptom severity showed a dose-response relationship with reduced ACC thickness. No associations between immuno-metabolic dysregulation and structural brain alterations were found, suggesting that although both are associated with depression, distinct mechanisms may be involved.
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ItemA large-scale ENIGMA multisite replication study of brain age in depression(Elsevier BV, 2022-12)Background: Several studies have evaluated whether depressed persons have older appearing brains than their nondepressed peers. However, the estimated neuroimaging-derived “brain age gap” has varied from study to study, likely driven by differences in training and testing sample (size), age range, and used modality/features. To validate our previously developed ENIGMA brain age model and the identified brain age gap, we aim to replicate the presence and effect size estimate previously found in the largest study in depression to date (N = 2126 controls & N = 2675 cases; +1.08 years [SE 0.22], Cohen’s d = 0.14, 95% CI: 0.08–0.20), in independent cohorts that were not part of the original study. Methods: A previously trained brain age model (www.photon-ai.com/enigma_brainage) based on 77 FreeSurfer brain regions of interest was used to obtain unbiased brain age predictions in 751 controls and 766 persons with depression (18–75 years) from 13 new cohorts collected from 20 different scanners. Meta-regressions were used to examine potential moderating effects of basic cohort characteristics (e.g., clinical and scan technical) on the brain age gap. Results: Our ENIGMA MDD brain age model generalized reasonably well to controls from the new cohorts (predicted age vs. age: r = 0.73, R2 = 0.47, MAE = 7.50 years), although the performance varied from cohort to cohort. In these new cohorts, on average, depressed persons showed a significantly higher brain age gap of +1 year (SE 0.35) (Cohen’s d = 0.15, 95% CI: 0.05–0.25) compared with controls, highly similar to our previous finding. Significant moderating effects of FreeSurfer version 6.0 (d = 0.41, p = 0.007) and Philips scanner vendor (d = 0.50, p < 0.0001) were found, leading to more positive effect size estimates. Conclusions: This study further validates our previously developed ENIGMA brain age algorithm. Importantly, we replicated the brain age gap in depression with a comparable effect size. Thus, two large-scale independent mega-analyses across in total 32 cohorts and >3400 patients and >2800 controls worldwide show reliable but subtle effects of brain aging in adult depression. Future studies are needed to identify factors that may further explain the brain age gap variance between cohorts.
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ItemBrain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium(SPRINGERNATURE, 2023-03)Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.
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ItemAdvanced brain age correlates with greater rumination and less mindfulness in schizophrenia(ELSEVIER SCI LTD, 2023)BACKGROUND: Individual variation in brain aging trajectories is linked with several physical and mental health outcomes. Greater stress levels, worry, and rumination correspond with advanced brain age, while other individual characteristics, like mindfulness, may be protective of brain health. Multiple lines of evidence point to advanced brain aging in schizophrenia (i.e., neural age estimate > chronological age). Whether psychological dimensions such as mindfulness, rumination, and perceived stress contribute to brain aging in schizophrenia is unknown. METHODS: We estimated brain age from high-resolution anatomical scans in 54 healthy controls (HC) and 52 individuals with schizophrenia (SZ) and computed the brain predicted age difference (BrainAGE-diff), i.e., the delta between estimated brain age and chronological age. Emotional well-being summary scores were empirically derived to reflect individual differences in trait mindfulness, rumination, and perceived stress. Core analyses evaluated relationships between BrainAGE-diff and emotional well-being, testing for slopes differences across groups. RESULTS: HC showed higher emotional well-being (greater mindfulness and less rumination/stress), relative to SZ. We observed a significant group difference in the relationship between BrainAge-diff and emotional well-being, explained by BrainAGE-diff negatively correlating with emotional well-being scores in SZ, and not in HC. That is, SZ with younger appearing brains (predicted age < chronological age) had emotional summary scores that were more like HC, a relationship that endured after accounting for several demographic and clinical variables. CONCLUSIONS: These data reveal clinically relevant aspects of brain age heterogeneity among SZ and point to case-control differences in the relationship between advanced brain aging and emotional well-being.
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ItemeLife's new model and its impact on science communication(eLIFE SCIENCES PUBL LTD, 2022-12-08)The eLife Early-Career Advisory Group discusses eLife's new peer review and publishing model, and how the whole process of scientific communication could be improved for the benefit of early-career researchers and the entire scientific community.
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ItemNo Preview AvailableLongitudinal associations between depression, lifestyle and brain structure: a nine-year follow-up MRI study(ELSEVIER, 2020-02-01)Background: Major depressive disorder (MDD) has been associated with smaller regional grey matter brain volumes. However, the longitudinal nature of these abnormalities is still largely unknown as longitudinal studies in MDD are scarce and findings inconsistent. Also, MDD is known to be associated with an unhealthy lifestyle including physical inactivity, short or long sleep, high BMI, smoking and high alcohol consumption, which have also been associated with lower grey matter volume and therefore could partly explain brain structural changes in MDD. Aim: Investigate the relation between depression, lifestyle and brain structure cross-sectionally and longitudinally over up to 9 years. Methods: We included persons with MDD and/or anxiety and healthy controls (605 observations from 344 participants) of the Netherlands Study of Depression and Anxiety (NESDA). Hippocampal volume, and rostral anterior cingulate cortex (rACC) and medial orbitofrontal cortex (mOFC) thickness were derived from T1 structural MRI scans using Freesurfer. Generalized Estimating Equations analyses were used to investigate multi-wave cross-sectional associations between depression, lifestyle (BMI, smoking, alcohol consumption, physical activity and sleep duration) and brain structure. Multiple regression analyses were used to investigate associations between baseline depression or lifestyle, or change of these measures, with change in brain structure over 2 (n=178) or 9 years (n=84), and between percentage of time with MDD or anxiety disorders over 9 years to change in brain structure over time. Results: Cross-sectional analyses across waves show a negative association between depression severity and mOFC (p=0.020) and rACC (p=0.002) thickness, which remained significant when correcting for BMI and other lifestyle factors. BMI, but no other lifestyle indicators, was negatively associated with mOFC (p<0.001) and rACC (p=0.004) thickness, also when correcting for depression. Longitudinal analyses show that thickness of mOFC, rACC and hippocampal volume decreased over time (all p<0.001). Longitudinally, no associations between baseline depression severity, or lifestyle, or change of these measures over time, were observed with change in brain structure over 2 or 9 years. The percentage of time with MDD or anxiety over 9 years was also not related to change in brain structure over time. Conclusions: Depression severity and BMI were both negatively associated with medial prefrontal brain structure (lower mOFC and rACC thickness), independent of each other and other lifestyle indicators. Associations with hippocampal volume and between brain regions and other lifestyle factors were not significant. As expected, grey matter volume decreased over time. However, this change over time was not significantly associated with (change in) depression or lifestyle. The observed associations with cross-sectional brain structure but not with longitudinal change might suggest that lower prefrontal brain thickness could be a long-term consequence or be related to vulnerability for depression and BMI, however, the limited sample size of longitudinal analyses warrants careful interpretation. We will aim to replicate these findings and further delineate potential associations with lifestyle over the whole lifespan in community-based samples of 3500 persons within the European Lifebrain longitudinal neuroimaging consortium.
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ItemA methylation study of long-term depression risk(NATURE PUBLISHING GROUP, 2020-06)Recurrent and chronic major depressive disorder (MDD) accounts for a substantial part of the disease burden because this course is most prevalent and typically requires long-term treatment. We associated blood DNA methylation profiles from 581 MDD patients at baseline with MDD status 6 years later. A resampling approach showed a highly significant association between methylation profiles in blood at baseline and future disease status (P = 2.0 × 10-16). Top MWAS results were enriched specific pathways, overlapped with genes found in GWAS of MDD disease status, autoimmune disease and inflammation, and co-localized with eQTLS and (genic enhancers of) of transcription sites in brain and blood. Many of these findings remained significant after correction for multiple testing. The major themes emerging were cellular responses to stress and signaling mechanisms linked to immune cell migration and inflammation. This suggests that an immune signature of treatment-resistant depression is already present at baseline. We also created a methylation risk score (MRS) to predict MDD status 6 years later. The AUC of our MRS was 0.724 and higher than risk scores created using a set of five putative MDD biomarkers, genome-wide SNP data, and 27 clinical, demographic and lifestyle variables. Although further studies are needed to examine the generalizability to different patient populations, these results suggest that methylation profiles in blood may present a promising avenue to support clinical decision making by providing empirical information about the likelihood MDD is chronic or will recur in the future.
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ItemAn integrative study of five biological clocks in somatic and mental health(eLIFE SCIENCES PUBL LTD, 2021-02-09)Biological clocks have been developed at different molecular levels and were found to be more advanced in the presence of somatic illness and mental disorders. However, it is unclear whether different biological clocks reflect similar aging processes and determinants. In ~3000 subjects, we examined whether five biological clocks (telomere length, epigenetic, transcriptomic, proteomic, and metabolomic clocks) were interrelated and associated to somatic and mental health determinants. Correlations between biological aging indicators were small (all r < 0.2), indicating little overlap. The most consistent associations of advanced biological aging were found for male sex, higher body mass index (BMI), metabolic syndrome, smoking, and depression. As compared to the individual clocks, a composite index of all five clocks showed most pronounced associations with health determinants. The large effect sizes of the composite index and the low correlation between biological aging indicators suggest that one's biological age is best reflected by combining aging measures from multiple cellular levels.
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ItemContributing factors to advanced brain aging in depression and anxiety disorders(SPRINGERNATURE, 2021-07-21)Depression and anxiety are common and often comorbid mental health disorders that represent risk factors for aging-related conditions. Brain aging has shown to be more advanced in patients with major depressive disorder (MDD). Here, we extend prior work by investigating multivariate brain aging in patients with MDD, anxiety disorders, or both, and examine which factors contribute to older-appearing brains. Adults aged 18-57 years from the Netherlands Study of Depression and Anxiety underwent structural MRI. A pretrained brain-age prediction model based on >2000 samples from the ENIGMA consortium was applied to obtain brain-predicted age differences (brain PAD, predicted brain age minus chronological age) in 65 controls and 220 patients with current MDD and/or anxiety. Brain-PAD estimates were associated with clinical, somatic, lifestyle, and biological factors. After correcting for antidepressant use, brain PAD was significantly higher in MDD (+2.78 years, Cohen's d = 0.25, 95% CI -0.10-0.60) and anxiety patients (+2.91 years, Cohen's d = 0.27, 95% CI -0.08-0.61), compared with controls. There were no significant associations with lifestyle or biological stress systems. A multivariable model indicated unique contributions of higher severity of somatic depression symptoms (b = 4.21 years per unit increase on average sum score) and antidepressant use (-2.53 years) to brain PAD. Advanced brain aging in patients with MDD and anxiety was most strongly associated with somatic depressive symptomatology. We also present clinically relevant evidence for a potential neuroprotective antidepressant effect on the brain-PAD metric that requires follow-up in future research.