Browsing by Author "Groenewold, Nynke"

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    Open Access
    A functional magnetic resonance imaging study of cognitive emotion regulation in relation to individual differences in self-esteem
    (2020) Swan, Freda Zoë; Groenewold, Nynke; Uhlmann, Anne; Stein, Dan
    Objectives Self-esteem may affect the processing and regulation of emotion. However, it is unclear whether differences in self-esteem are associated with changes in initial emotional appraisal or engagement of emotion regulation. I investigated whether individual differences in self-esteem predicted brain responses to negative emotional stimuli: 1) when they were viewed without intentional regulation; and 2) during downregulation using cognitive reappraisal. Thirdly, I investigated whether self-esteem predicted reappraisal success. Method Twenty-nine healthy adults (age M=47, SD=15; 16 female) performed a cognitive reappraisal emotion regulation task during fMRI scanning. Participants viewed and subsequently reappraised or attended to negative and neutral images. Trait self-esteem (Rosenberg Self-Esteem Scale) was included as a predictor in a whole-brain multiple regression analysis. Analyses were thresholded at p<.005, k>p20, p<.05 family-wise error (FWE)-corrected at cluster-level. The anterior cingulate cortex (ACC; BA32) and the dorsal prefrontal cortex (PFC; BA6) were a priori regions of interest (ROI), since both have previously been reported in fMRI studies of self-esteem and cognitive reappraisal. A post-hoc ROI analysis tested the correspondence of self-esteem-related ACC activation with findings from a meta-analysis of emotion regulation. Ratings of negative emotional intensity following reappraisal trials were subtracted from ratings following attend-negative trials to index reappraisal success. Results Self-esteem was associated with potentiated ACC ROI activation during viewing of negative, compared to neutral, images (MNI x, y, z = -6, 17, 38, k=43, punc=.001 at peak, pFWE=.368 at cluster-level). For reappraisal compared to attended negative images, self-esteem was positively associated with activation in the left posterior insula (MNI x, y, z = -30, -10, 17, k=30, punc<.001 at peak, pFWE=.959 at cluster-level) and negatively associated with activation in the mid cingulate cortex (MNI x, y, z = 3, -34, 35, k=50, punc=.001 at peak, pFWE=.805 at clusterlevel). However, only the post-hoc ACC ROI analysis was significant after multiple comparison correction (MNI x, y, z = -6, 23, 38, k=22, punc=.001 at peak, pFWE=.021 at clusterlevel). For reappraisal, self-esteem was not related to activation in the ACC or dorsal PFC ROIs. Trait self-esteem did not correlate with reappraisal success, r =.16, p =.208. Conclusion Trait self-esteem may affect recruitment of the ACC during initial emotional appraisal. This may reflect successful automatic emotion regulation for high self-esteem, consistent with the demonstrated spatial overlap with a meta-analytic emotion regulation cluster. While selfesteem may affect brain responsivity during cognitive reappraisal, the observed trends must be interpreted carefully, since the findings do not survive correction for multiple comparisons, and emotional outcomes of applying reappraisal do not differ as a function of self-esteem. Taken together, these findings suggest that high trait self-esteem may be advantageous for rapid automatic emotion regulation, but not deliberate cognitive reappraisal.
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    Open Access
    An investigation of amygdala and hippocampal subregions and their relation to ageing in anxiety and related disorders
    (2024) Ntwatwa, Ziphozihle; Ipser, Jonathan; Groenewold, Nynke; Stein, Dan; van Honk, Jack
    Background Obsessive-compulsive disorder (OCD) and social anxiety disorder (SAD) are debilitating disorders that are associated with (inconsistent) evidence of hippocampal and amygdala volumetric abnormalities. In addition, both OCD and SAD are associated with accentuated biological aging, as indexed by cellular and molecular markers. Nevertheless, little is known about brain aging in OCD and SAD, or the extent to which inconsistencies in hippocampal and amygdala volume findings in these disorders may be due to the differential effect of age on the subfields from which these structures are composed. Accordingly, this dissertation set out to characterise differences in hippocampal and amygdala subfield volumes between healthy controls (HCs) and participants with OCD and SAD in large-scale MRI datasets and relate these to whole and regional brain aging. Methods Hippocampal and amygdala subfield volumes and brain age estimates were derived from T1 weighted MRI images from the OCD Brain Imaging Consortium (De Wit et al., 2014) and the European and South African Research Network in Anxiety Disorders (Bas-Hoogendam et al., 2017). Subfield volumes were segmented using an automated segmentation algorithm from Freesurfer (v6.0). The brain age analysis was performed by using a previously trained machine learning algorithm that provides brain age estimates for the whole brain, as well as for regions of interest (occipital, frontal, temporal, parietal, cingulate, insula, or cerebellar–subcortical features) (Kaufmann et al., 2019). Differences in relative brain age (brain predicted age difference; brain-PAD) were calculated by subtracting chronological age from the predicted brain age. Between-group differences (diagnosis vs HCs) in volumetric and brain-PAD estimates were assessed using a mixed-effects (d) model adjusted for several covariates. Subgroup analyses were performed to determine the association of the main findings with clinical characteristics. Finally, unique associations between subfield volumes and whole brain age were estimated using partial correlation analysis. Results There was no evidence for a difference in subfield volumes between individuals with OCD and HCs. However, we found that psychotropic medication use was associated with significantly smaller hippocampal dentate gyrus (d=-0.26, pFDR=0.042), molecular layer (d=-0.29, pFDR=0.042) and larger lateral (d=0.23, pFDR=0.049) and basal (d=0.25, pFDR=0.049) amygdala subfields than HCs. Individuals with OCD without psychotropic medication use had significantly smaller hippocampal CA1 (d=-0.28, pFDR=0.016) compared to HCs. No association was found for symptom severity. In contrast to the findings for OCD, individuals with SAD demonstrated significantly smaller basal (d= 0.32, pFDR=0.022), accessory basal (d=-0.42, pFDR=0.005) and corticoamygdaloid transition area (d=0.37, pFDR=0.014) amygdala subfields overall compared to HCs, and larger hippocampal CA3 (d=0.34, pFDR=0.024), CA4 (d=0.44, pFDR= 0.007), dentate gyrus (d=0.35, pFDR= 0.022) and molecular layer (d=0.28, pFDR=0.033). In addition, individuals with SAD without comorbid anxiety disorder had smaller lateral amygdala and hippocampal amygdala transition area, compared to HCs. No association was found for psychotropic medication use and symptom severity. Individuals with OCD (n=375) had significantly higher whole brain-PAD (+1.6 years, pFDR=0.006, d=0.20) compared to HCs (n=335), but no differences were observed in the regional models. The effect on whole brain brain-PAD estimates was largely driven by psychotropic medication use as higher relative brain age was evident in individuals with OCD with psychotropic medication use (+2.98 years, d=0.38, p <0.001) compared to HCs, but not in individuals without psychotropic medication use (+0.57 years, d=0.07, p =0.374) compared to HCs. No association was found for symptom severity. Partial correlation analysis found a significant negative association between hippocampal and amygdala volume and whole brain PAD in the OCD group (R=-0.224, p=0.00001), but not in the HC group (R=0.081, p=0.138), specifically the lateral nucleus (R=-0.18), CAT(R=-0.13), hippocampal fimbria (R=0.17), and hippocampal fissure (R=0.17) were significant in OCD. Individuals with SAD (n=107) had significantly higher whole brain-PAD (+2.5 years, d=0.33, pFDR=0.010) compared to HCs (n=137), and significantly higher regional brain-PAD in the temporal (+3.80 years, d=0.37, pFDR=0.008,), parietal (+3.57 years, d=0.38, pFDR=0.008), occipital (+3.26 years, d = 0.33, pFDR=0.010), and frontal regions (+2.97 years, d=0.33, pFDR=0.010,) compared to HCs. Brain PAD was higher in SAD without comorbid anxiety disorder, without MDD, and without psychotropic medication use. No association was found for symptom severity. There was no partial correlation between subfields and brain age. Discussion & Conclusion The evidence presented in the thesis suggests that 1) differences in subfield volumes between OCD and HCs were influenced by psychotropic medication use, which is consistent with previous studies that suggest that psychotropic medication status is a strong confounder for subcortical brain volumes observed in OCD, 2) differences in subfield volumes between SAD and HCs were observed in the areas associated with sensory information processing and these differences were partially influenced by psychiatric comorbidity, 3) both OCD and SAD were associated with accentuated brain aging with differential patterns in the whole and regional brain, dependent on clinical characteristics, and 4) only OCD relative brain age was associated with subfield volumes. It is unclear whether our findings in OCD and SAD reflect an adaptive response or are a pre-existing risk factor to these disorders, or both. Future longitudinal analysis is required to investigate whether the observed differences in subfield volume and brain age remain over time.
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    Open Access
    Are maternal symptoms of depression/PTSD and Child Genetic risk scores for depression/PTSD associated with childhood subcortical brain volumes?
    (2025) Grobler, Anje-Lore; Mufford, Mary; Groenewold, Nynke; Stein, Dan
    The antenatal period is a critical window for genetic and environmental factors to influence a child's brain development. While previous research in East Asian and European populations has linked child polygenic risk scores (PRSs) for depression and maternal antenatal symptoms (E) to child subcortical brain volumes, these associations remain unexplored in African populations. Moreover, PRSs for post-traumatic stress disorder (PTSD) have not been investigated in relation to child subcortical brain volumes. This study examined: 1) the effects of child genetic risk for depression and PTSD (G), including the interaction with maternal antenatal symptoms of depression and PTSD (G+E or GxE), on child subcortical brain volumes at two years of age; and 2) the genetic architecture of these brain volumes. Using PRS-CSx, PRSs were derived from Psychiatric Genomics Consortium summary statistics, with the Drakenstein Child Health Study (N = 128) as the target dataset. Associations between child genetic risk, maternal antenatal symptoms and child subcortical brain volumes were tested using linear regression. A genome-wide association study (GWAS; N = 163) was used to investigate genetic associations with these subcortical volumes, and trans-ancestry genetic correlations between African and European cohorts were estimated using Popcorn. For depression, model G was associated with larger total thalamus, left thalamus, and left hippocampus volumes, and smaller right thalamus, bilateral putamen and total pallidum volumes. Model GxE was associated with larger bilateral caudate volume. For PTSD, model G was associated with larger total and right putamen and right pallidum volume, and with smaller left putamen and left hippocampus volume. Model G+E was associated with larger total thalamus and right thalamus volumes, and model GxE with larger bilateral caudate volumes. No SNPs reached genome-wide significance, but three SNPs showed trending associations: rs6052713 (left caudate), rs11771415, and rs7317597 (right hippocampus). No significant cross-population genetic correlations were identified. This study provides preliminary evidence of gene-environment interactions influencing child subcortical brain volumes in a South African population. Findings partially align with prior research and highlight the need for larger studies to clarify the mechanisms linking maternal mental health, child genetics, and brain development.
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    The brain age gap in social anxiety disorder
    (2021) Blake, Kimberly Vanessa; Groenewold, Nynke; Ipser, Jonathan; Stein, Dan
    Background: When an individual's brain appears ‘older' than expected based upon their chronological age, they may be at an increased risk for developing brain-related diseases and cognitive decline. There is growing evidence of advanced brain ageing in neuropsychiatric diseases. Social anxiety disorder (SAD) is a disabling mental illness, which has been associated with both structural brain deficits and advanced biological ageing. However, brain age research has yet to be conducted in adults diagnosed with SAD. The present study investigated whether adults with SAD showed an advanced brain ageing process, compared to healthy controls (HCs), and whether brain ageing in SAD patients is associated with clinical characteristics. Method: A systematic review of the literature was conducted to identify knowledge gaps in brain age research in psychiatric disorders before commencing with the present dissertation. Hereafter, a secondary data analysis of a large multi-site dataset was performed. T1-weighted structural MRI scans of 387 participants (SAD n=174, HC n=213) between the ages 18 and 60 years were included. These structural scans were segmented using both FreeSurfer and SPM12, after which they underwent quality control procedures. Brain age was estimated by two different machine learning models – Tobias Kaufmann's brain age model and James Cole's BrainageR. The primary outcome for analysis was the brain age gap (BAG), calculated by subtracting a participants' chronological age from their estimated brain age. General linear models were run to determine whether there was a significantly larger positive BAG in the SAD group (Kaufmann model n=100, Cole model n=155) compared to the HC group (Kaufmann model n=138, Cole model n=197) after adjusting for age, mean centred age2 and sex. The association between BAG and comorbid depression and anxiety, as well as medication use and symptom severity, was also assessed. Results: In the present study sample, predicted age was more strongly associated with chronological age for the Cole model estimates than the Kaufmann model estimates (Cole: Pearson correlation = 0.828, MAE = 4.78, SD = 3.96, versus Kaufmann: Pearson correlation = 0.576, MAE = 11.93, SD = 6.93). With the Kaufmann model, the SAD group had a significantly larger BAG than the HC group of almost one year (mean difference = 0.943 year, SE = 0.40, p = .019). In addition, with the Kaufmann model, patients without psychiatric comorbidities had a significantly larger BAG than HCs, of more than one year (mean difference = 1.242 year, SE = 0.49, p = .038). No difference was observed in BAG between patients with comorbidities and HCs (mean difference = 0.983 year, SE = 0.85, p = .749). In contrast, with the Cole model, the SAD group did not have a significantly larger BAG than the HC group (mean difference = 0.513 year, SE = 0.49, p = .383). Moreover, the Cole model found no significant difference in BAG between SAD patients with and without comorbidities, or between each of these groups and HCs (all p > .708). Finally, no significant associations were observed between the BAG and symptom severity and the BAG and medication use in SAD patients in the Cole or Kaufmann models. Conclusion: This study observed contradictory evidence for a larger BAG between patients with SAD than HCs. The differences observed between the Cole model and the Kaufmann model may be a result of the different information used to estimate brain age (voxel-based volumetric data, compared to cortical thickness/surface area and subcortical/cerebellar volumes, respectively). The models demonstrated largely overlapping confidence intervals for group mean difference in BAG, suggesting that if there is a positive BAG in adults diagnosed with SAD, it is likely to be small. This should be verified in future research by using multiple different machine learning models based on different feature sets, to obtain more reliable and robust brain age estimates.