Positive affect training to reduce mental health problems during the COVID-19 pandemic: a proof-of-concept randomised clinical trial.

BACKGROUND: The social restrictions occurring during the pandemic contributed to loss of many sources of reward, which contributes to poor mental health. OBJECTIVE: This trial evaluated a brief positive affect training programme to reduce anxiety, depression and suicidality during the pandemic. METHODS: In this single-blind, parallel, randomised controlled trial, adults who screened positive for COVID-19-related psychological distress across Australia were randomly allocated to either a 6-session group-based programme based on positive affect training (n=87) or enhanced usual care (EUC, n=87). Primary outcome was total score on the Hospital Anxiety and Depression Scale-anxiety and depression subscales assessed at baseline, 1-week post-treatment, 3 months (primary outcome time point) as well as secondary outcome measures of suicidality, generalised anxiety disorder, sleep impairment, positive and negative mood and COVID-19-related stress. FINDINGS: Between 20 September 2020 and 16 September 2021, 174 participants were enrolled into the trial. Relative to EUC, at 3-month follow-up the intervention led to greater reduction on depression (mean difference 1.2 (95% CI 0.4 to 1.9)), p=0.003), with a moderate effect size (0.5 (95% CI 0.2 to 0.9)). There were also greater reduction of suicidality and improvement in quality of life. There were no differences in anxiety, generalised anxiety, anhedonia, sleep impairment, positive or negative mood or COVID-19 concerns. CONCLUSIONS: This intervention was able to reduce depression and suicidality during adverse experiences when rewarding events were diminished, such as pandemics. CLINICAL IMPLICATIONS: Strategies to improve positive affect may be useful to reduce mental health issues. TRIAL REGISTRATION NUMBER: ACTRN12620000811909.

A comparison of methods to harmonize cortical thickness measurements across scanners and sites.

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results From the ENIGMA-PGC Posttraumatic Stress Disorder Consortium.

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1300 PTSD cases and >2000 trauma-exposed control subjects (ages 6.2-85.2 years) by the ENIGMA-PGC (Enhancing Neuro Imaging Genetics through Meta Analysis-Psychiatric Genomics Consortium) PTSD working group. Cortical regions in the network were rank ordered by the effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2-148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared with the mean SC of 5000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD control subjects, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex, and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The SC networks that are perturbed in PTSD comport with converging evidence from resting-state functional connectivity networks and networks affected by inflammatory processes and stress hormones in PTSD.

Trauma and posttraumatic stress disorder modulate polygenic predictors of hippocampal and amygdala volume.

The volume of subcortical structures represents a reliable, quantitative, and objective phenotype that captures genetic effects, environmental effects such as trauma, and disease effects such as posttraumatic stress disorder (PTSD). Trauma and PTSD represent potent exposures that may interact with genetic markers to influence brain structure and function. Genetic variants, associated with subcortical volumes in two large normative discovery samples, were used to compute polygenic scores (PGS) for the volume of seven subcortical structures. These were applied to a target sample enriched for childhood trauma and PTSD. Subcortical volume PGS from the discovery sample were strongly associated in our trauma/PTSD enriched sample (n = 7580) with respective subcortical volumes of the hippocampus (p = 1.10 × 10-20), thalamus (p = 7.46 × 10-10), caudate (p = 1.97 × 10-18), putamen (p = 1.7 × 10-12), and nucleus accumbens (p = 1.99 × 10-7). We found a significant association between the hippocampal volume PGS and hippocampal volume in control subjects from our sample, but was absent in individuals with PTSD (GxE; (beta = -0.10, p = 0.027)). This significant GxE (PGS × PTSD) relationship persisted (p < 1 × 10-19) in four out of five threshold peaks (0.024, 0.133, 0.487, 0.730, and 0.889) used to calculate hippocampal volume PGSs. We detected similar GxE (G × ChildTrauma) relationships in the amygdala for exposure to childhood trauma (rs4702973; p = 2.16 × 10-7) or PTSD (rs10861272; p = 1.78 × 10-6) in the CHST11 gene. The hippocampus and amygdala are pivotal brain structures in mediating PTSD symptomatology. Trauma exposure and PTSD modulate the effect of polygenic markers on hippocampal volume (GxE) and the amygdala volume PGS is associated with PTSD risk, which supports the role of amygdala volume as a risk factor for PTSD.

Distinct neural mechanisms of emotional processing in prolonged grief disorder.

BACKGROUND: Prolonged grief disorder (PGD) has recently been recognized as a separate psychiatric diagnosis, despite controversy over the extent to which it is distinctive from posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). METHODS: This study investigated distinctive neural processes underpinning emotion processing in participants with PGD, PTSD, and MDD with functional magnetic resonance study of 117 participants that included PGD (n = 21), PTSD (n = 45), MDD (n = 26), and bereaved controls (BC) (n = 25). Neural responses were measured across the brain while sad, happy, or neutral faces were presented at both supraliminal and subliminal levels. RESULTS: PGD had greater activation in the pregenual anterior cingulate cortex (pgACC), bilateral insula, bilateral dorsolateral prefrontal cortices and right caudate and also greater pgACC-right pallidum connectivity relative to BC during subliminal processing of happy faces. PGD was distinct relative to both PTSD and MDD groups with greater recruitment of the medial orbitofrontal cortex during supraliminal processing of sad faces. PGD were also distinct relative to MDD (but not PTSD) with greater activation in the left amygdala, caudate, and putamen during subliminal presentation of sad faces. There was no distinction between PGD, PTSD, and MDD during processing of happy faces. CONCLUSIONS: These results provide initial evidence of distinct neural profiles of PGD relative to related psychopathological conditions, and highlight activation of neural regions implicated in reward networks. This pattern of findings validates current models of PGD that emphasize the roles of yearning and appetitive processes in PGD.

The distinctive neural circuitry of complex posttraumatic stress disorder during threat processing.

BACKGROUND: There is controversy over the extent to which the new International Classification of Diseases (ICD-11) diagnosis of complex posttraumatic stress disorder (CPTSD) is distinct from posttraumatic stress disorder (PTSD). This study aimed to conduct the first investigation of distinctive neural processes during threat processing in CPTSD relative to PTSD. METHOD: This cross-sectional functional magnetic resonance study included 99 participants who met criteria for PTSD (PTSD = 32, CPTSD = 28) and 39 trauma-exposed controls. PTSD was assessed with the Clinician-Administered PTSD Scale (CAPS). CPTSD was assessed with an adapted version of the International Trauma Questionnaire. Neural responses were measured across the brain while threat or neutral faces were presented at both supraliminal and subliminal levels. RESULTS: During supraliminal presentations of threat stimuli, there was greater bilateral insula and right amygdala activation in CPTSD participants relative to PTSD. Reduced supraliminal right dorsolateral prefrontal cortex activation and increased subliminal amygdala and insula activation were observed as common dysfunction for both CPTSD and PTSD groups relative to trauma controls. There were no significant differences in terms of subliminal presentations and no differences in functional connectivity. Dissociative responses were positively associated with right insula activation (r = 0.347, p < 0.01). CONCLUSIONS: These results provide the first evidence of distinct neural profiles of CPTSD and PTSD during threat processing. The observation of increased insula and right amygdala activation in CPTSD accords with the proposal that CPTSD is distinguished from PTSD by disturbances in emotion regulation and self-concept.

Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis.

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values < 0.039) and were significantly negatively correlated with PTSS severity. After adjusting for depression symptoms, the PTSD findings in left and right LOFG remained significant. These findings indicate that cortical volumes in PTSD patients are smaller in prefrontal regulatory regions, as well as in broader emotion and sensory processing cortical regions.

The conditions that regulate formation of a false fear memory in rats.

People and animals sometimes associate events that never occurred together. These false memories can have disastrous consequences, yet little is known about the conditions under which they form. In four experiments, we investigated how rats learn to fear a context in which they have never experienced danger (i.e., how they form a false context fear memory). In each experiment, rats were pre-exposed to a context on day 1, shocked in a similar-but-different context on day 2, and tested in the pre-exposed or explicitly-conditioned context on day 3. The results revealed that: (1) the true memory of the explicitly-conditioned context and false memory of the pre-exposed context develop simultaneously and independently; and (2) the conditions of pre-exposure on day 1 and time of shock exposure on day 2 interact to determine the strength of the false memory. These findings are anticipated by a recent computational model, the Bayesian Context Fear Algorithm/Automaton (BACON; Krasne, Cushman, & Fanselow, 2015). They are discussed in relation to this model and more general theories of context learning.