ORCID Profile
0000-0003-1379-9491
Current Organisation
University Hospital Frankfurt
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Publisher: Elsevier BV
Date: 03-2022
DOI: 10.1016/J.BIOPSYCH.2021.09.008
Abstract: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and erse international s le with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippoc al cortex (0.18 <d < 0.22). More (hypo)manic episodes were associated with faster cortical thinning, primarily in the prefrontal cortex. In the hitherto largest longitudinal MRI study on BD, we did not detect accelerated cortical thinning but noted faster ventricular enlargements in BD. However, abnormal frontocortical thinning was observed in association with frequent manic episodes. Our study yields insights into disease progression in BD and highlights the importance of mania prevention in BD treatment.
Publisher: American Medical Association (AMA)
Date: 2021
Publisher: Elsevier BV
Date: 05-2018
DOI: 10.1016/J.PSYCHRES.2018.02.046
Abstract: To understand how cognitive dysfunction contributes to social cognitive deficits in depression, we investigated the relationship between executive function and social cognitive performance in adolescents and young adults during current and remitted depression, compared to healthy controls. Social cognition and executive function were measured in 179 students (61 healthy controls and 118 patients with depression M
Publisher: Springer Science and Business Media LLC
Date: 22-09-2020
DOI: 10.1038/S41467-020-18367-Y
Abstract: Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery s le comprises 22,824 in iduals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
Publisher: Springer Science and Business Media LLC
Date: 04-2022
DOI: 10.1038/S41593-022-01042-4
Abstract: Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 in iduals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
Publisher: Springer Science and Business Media LLC
Date: 16-04-2021
DOI: 10.1038/S41380-021-01098-X
Abstract: In iduals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control in iduals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, in iduals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippoc us, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI ( Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some in iduals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.
Publisher: Wiley
Date: 19-10-2020
DOI: 10.1002/HBM.25249
Abstract: The hippoc us consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippoc al subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 in iduals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippoc al subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippoc us (Cohen's d = −0.20), cornu ammonis (CA)1 ( d = −0.18), CA2/3 ( d = −0.11), CA4 ( d = −0.19), molecular layer ( d = −0.21), granule cell layer of dentate gyrus ( d = −0.21), hippoc al tail ( d = −0.10), subiculum ( d = −0.15), presubiculum ( d = −0.18), and hippoc al amygdala transition area ( d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippoc al subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.
Publisher: Wiley
Date: 04-10-2016
DOI: 10.1111/GBB.12318
Abstract: Tumour necrosis factor alpha (TNFα) has been implicated in the pathophysiology of neurodegenerative and neuropsychiatric disease, with research highlighting a role for TNFα in hippoc al and striatal regulation. TNFα signals are primarily transduced by TNF receptors 1 and 2 (TNFR1 and TNFR2), encoded by TNFRSF1A and TNFRSF1B, which exert opposing effects on cell survival (TNFR1, neurodegenerative TNFR2, neuroprotective). We therefore sought to explore the respective roles of TNFR1 and TNFR2 in the regulation of hippoc al and striatal morphology in an imaging genetics study. Voxel-based morphometry was used to analyse the associations between TNFRSF1A (rs4149576 and rs4149577) and TNFRSF1B (rs1061624) genotypes and grey matter structure. The final s les comprised a total of 505 subjects (mean age = 33.29, SD = 11.55 years 285 females and 220 males) for morphometric analyses of rs1061624 and rs4149576, and 493 subjects for rs4149577 (mean age = 33.20, SD = 11.56 years 281 females and 212 males). Analyses of TNFRSF1A single nucleotide polymorphisms (SNPs) rs4149576 and rs4149577 showed highly significant genotypic associations with striatal volume but not the hippoc us. Specifically, for rs4149576, G homozygotes were associated with reduced caudate nucleus volumes relative to A homozygotes and heterozygotes, whereas for rs4149577, reduced caudate volumes were observed in C homozygotes relative to T homozygotes and heterozygotes. Analysis of the TNFRSF1B SNP rs1061624 yielded a significant association with hippoc al but not with striatal volume, whereby G homozygotes were associated with increased volumes relative to A homozygotes and heterozygotes. Our findings indicate a role for TNFR1 in regulating striatal but not hippoc al morphology, as well as a complementary role for TNFR2 in hippoc al but not in striatal morphology.
Publisher: Springer Science and Business Media LLC
Date: 15-11-2021
Publisher: Elsevier BV
Date: 03-2022
Publisher: Springer Science and Business Media LLC
Date: 21-08-2019
Publisher: Springer Science and Business Media LLC
Date: 30-08-2019
Publisher: Wiley
Date: 16-12-2021
DOI: 10.1111/BDI.13172
Abstract: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under‐researched in psychiatry. We obtained body mass index (BMI) and magnetic resonance imaging‐derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control in iduals from 14 sites within the ENIGMA‐BD Working Group. We identified regionally specific profiles of cortical thickness using K‐means clustering and studied clinical characteristics associated with in idual cortical profiles. We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the s le) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD in iduals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in in iduals with higher BMI, which was additive and similar to the BD‐associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.
Publisher: Royal College of Psychiatrists
Date: 25-08-2021
DOI: 10.1192/BJP.2021.102
Abstract: Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO ( n = 12 977) and PAO ( n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication s le ( n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. AAO and PAO are associated with indicators of bipolar disorder severity. In iduals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Publisher: Cold Spring Harbor Laboratory
Date: 16-01-2019
DOI: 10.1101/509554
Abstract: We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.
Publisher: Springer Science and Business Media LLC
Date: 08-07-2019
Publisher: CMA Joule Inc.
Date: 07-2021
DOI: 10.1503/JPN.200176
Publisher: Springer Science and Business Media LLC
Date: 08-12-2020
DOI: 10.1038/S41398-020-01109-5
Abstract: It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent s les comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD.
Publisher: American Psychological Association (APA)
Date: 08-2022
DOI: 10.1037/ABN0000738
Abstract: Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite s le of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-s le split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in in iduals with low educational attainment, but less likely to predict MDD in in iduals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Publisher: Frontiers Media SA
Date: 09-05-2019
Publisher: Springer Science and Business Media LLC
Date: 18-05-2020
DOI: 10.1038/S41380-020-0754-0
Abstract: Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 s les worldwide. Healthy brain aging was estimated by predicting chronological age (18–75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen’s d = 0.14, 95% CI: 0.08–0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
Publisher: Springer Science and Business Media LLC
Date: 16-09-2019
DOI: 10.1038/S41386-019-0521-6
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Publisher: Springer Science and Business Media LLC
Date: 05-09-2018
DOI: 10.1038/S41380-018-0236-9
Abstract: Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery s le of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication s le (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery s le. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication s le. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.PSYNEUEN.2018.09.027
Abstract: Obesity is a clinically relevant and highly prevalent somatic comorbidity of major depression (MDD). Genetic predisposition and history of childhood trauma have both independently been demonstrated to act as risk factors for obesity and to be associated with alterations in reward related brain structure and function. We therefore aimed to investigate the influence of childhood maltreatment and genetic risk for obesity on structural and functional imaging correlates associated with reward processing in MDD. 161 MDD patients underwent structural and functional MRI during a frequently used card guessing paradigm. Main and interaction effects of a polygenic risk score for obesity (PRS) and childhood maltreatment experiences as assessed using the Childhood Trauma Questionnaire (CTQ) were investigated. We found that maltreatment experiences and polygenic risk for obesity significantly interacted on a) body mass index b) gray matter volume of the orbitofrontal cortex as well as on c) BOLD response in the right insula during reward processing. While polygenic risk for obesity was associated with elevated BMI as well as with decreased OFC gray matter and increased insular BOLD response in non-maltreated patients, these associations were absent in patients with a history of childhood trauma. No significant main effect of PRS or maltreatment on gray matter or BOLD response could be detected at the applied thresholds. The present study suggests that childhood maltreatment moderates the influence of genetic load for obesity on BMI as well as on altered brain structure and function in reward related brain circuits in MDD.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 20-03-2020
Abstract: The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 in iduals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. We identified 369 nominally genome-wide significant loci ( P 5 × 10 −8 ) associated with cortical structure in a discovery s le of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P 8.3 × 10 −10 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain s les, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on in idual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY (C) M. R. GLASS
Publisher: Elsevier BV
Date: 08-2021
Publisher: Cold Spring Harbor Laboratory
Date: 19-01-2023
DOI: 10.1101/2023.01.16.524331
Abstract: Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing s le sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 in iduals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each in idual’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences. We present a global effort to devise harmonization procedures necessary to meaningfully leverage big data.
Publisher: Cold Spring Harbor Laboratory
Date: 26-02-2019
DOI: 10.1101/560623
Abstract: Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 s les worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohen’s d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004). This highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates. This work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.
No related grants have been discovered for Jonathan Repple.