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Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
The COVID-19 pandemic and resulting measures can be regarded as a global stressor. Cross-sectional studies showed rather negative impacts on people’s mental health, while longitudinal studies considering pre-lockdown data are still scarce. The present study investigated the impact of COVID-19 related lockdown measures in a longitudinal German sample, assessed since 2017. During lockdown, 523 participants completed additional weekly online questionnaires on e.g., mental health, COVID-19-related and general stressor exposure. Predictors for and distinct trajectories of mental health outcomes were determined, using multilevel models and latent growth mixture models, respectively. Positive pandemic appraisal, social support, and adaptive cognitive emotion regulation were positively, whereas perceived stress, daily hassles, and feeling lonely negatively related to mental health outcomes in the entire sample. Three subgroups (“recovered,” 9.0%; “resilient,” 82.6%; “delayed dysfunction,” 8.4%) with different mental health responses to initial lockdown measures were identified. Subgroups differed in perceived stress and COVID-19-specific positive appraisal. Although most participants remained mentally healthy, as observed in the resilient group, we also observed inter-individual differences. Participants’ psychological state deteriorated over time in the delayed dysfunction group, putting them at risk for mental disorder development. Consequently, health services should especially identify and allocate resources to vulnerable individuals.
Lifestyle factors—such as diet, physical activity (PA), smoking, and alcohol consumption—have a significant impact on mortality as well as healthcare costs. Moreover, they play a crucial role in the development of type 2 diabetes mellitus (DM2). There also seems to be a link between lifestyle behaviours and insulin resistance, which is often a precursor of DM2. This study uses an enhanced Healthy Living Index (HLI) integrating accelerometric data and an Ecological Momentary Assessment (EMA) to explore differences in lifestyle between insulin-sensitive (IS) and insulin-resistant (IR) individuals. Moreover, it explores the association between lifestyle behaviours and inflammation. Analysing data from 99 participants of the mPRIME study (57 women and 42 men; mean age 49.8 years), we calculated HLI scores—ranging from 0 to 4— based on adherence to specific low-risk lifestyle behaviours, including non-smoking, adhering to a healthy diet, maximally moderate alcohol consumption, and meeting World Health Organization (WHO) PA guidelines. Insulin sensitivity was assessed using a Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and C-reactive protein (CRP) levels were used as a proxy for inflammation. Lifestyle behaviours, represented by HLI scores, were significantly different between IS and IR individuals (U = 1529.0; p = 0.023). The difference in the HLI score between IR and IS individuals was mainly driven by lower adherence to PA recommendations in the IR group. Moreover, reduced PA was linked to increased CRP levels in the IR group (r = −0.368, p = 0.014). Our findings suggest that enhancing PA, especially among individuals with impaired insulin resistance, holds significant promise as a preventive strategy.
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N = 53,293, N = 681,275, and N = 98,697, respectively). We then conducted genome-wide ADHD–BMI and ADHD–obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD–BMI overlapping genes with brain volumes (primary GWAS data N = 10,720–10,928; replication data N = 9428). The dopaminergic gene set was associated with both ADHD (P = 5.81 × 10−3) and BMI (P = 1.63 × 10−5); the circadian rhythm was associated with BMI (P = 1.28 × 10−3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD–BMI and ADHD–obesity results. The ADHD–BMI overlapping genes were associated with putamen volume (P = 7.7 × 10−3; replication data P = 3.9 × 10−2)—a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD–obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
Highlights
• Up-to-date overview on developing new medications including candidates with novel bioloigical targets for the treatment of anxiety disorders and PTSD.
• Targeting glutamatergic, cholinergic and neurosteroid mechanisms can produce acute anxiolytic effects.
• Drugs, including psychedelics, are hypothesized to produce neuroplasticity to cause enduring clinical effects.
• Combining medication with psychological approaches may augment therapeutic efficacy.
• Advances in circuit neuroscience can be leveraged to inform the design of rationale drug targets.
Abstract
Psychiatric disorders associated with psychological trauma, stress and anxiety are a highly prevalent and increasing cause of morbidity worldwide. Current therapeutic approaches, including medication, are effective in alleviating symptoms of anxiety disorders and posttraumatic stress disorder (PTSD), at least in some individuals, but have unwanted side-effects and do not resolve underlying pathophysiology. After a period of stagnation, there is renewed enthusiasm from public, academic and commercial parties in designing and developing drug treatments for these disorders. Here, we aim to provide a snapshot of the current state of this field that is written for neuropharmacologists, but also practicing clinicians and the interested lay-reader. After introducing currently available drug treatments, we summarize recent/ongoing clinical assessment of novel medicines for anxiety and PTSD, grouped according to primary neurochemical targets and their potential to produce acute and/or enduring therapeutic effects. The evaluation of putative treatments targeting monoamine (including psychedelics), GABA, glutamate, cannabinoid, cholinergic and neuropeptide systems, amongst others, are discussed. We emphasize the importance of designing and clinically assessing new medications based on a firm understanding of the underlying neurobiology stemming from the rapid advances being made in neuroscience. This includes harnessing neuroplasticity to bring about lasting beneficial changes in the brain rather than – as many current medications do – produce a transient attenuation of symptoms, as exemplified by combining psychotropic/cognitive enhancing drugs with psychotherapeutic approaches. We conclude by noting some of the other emerging trends in this promising new phase of drug development.
Purpose: Collaborative care is effective in improving symptoms of patients with depression. The aims of this study were to characterize symptom trajectories in patients with major depression during one year of collaborative care and to explore associations between baseline characteristics and symptom trajectories.
Methods: We conducted a cluster-randomized controlled trial in primary care. The collaborative care intervention comprised case management and behavioral activation. We used the Patient Health Questionnaire-9 (PHQ-9) to assess symptom severity as the primary outcome. Statistical analyses comprised latent growth mixture modeling and a hierarchical binary logistic regression model.
Results: We included 74 practices and 626 patients (310 intervention and 316 control recipients) at baseline. Based on a minimum of 12 measurement points for each intervention recipient, we identified two latent trajectories, which we labeled "fast improvers" (60.5%) and "slow improvers" (39.5%). At all measurements after baseline, "fast improvers" presented higher PHQ mean values than "slow improvers". At baseline, "fast improvers" presented fewer physical conditions, higher health-related quality of life, and had made fewer suicide attempts in their history.
Conclusions: A notable proportion of 39.5% of patients improved only "slowly" and probably needed more intense treatment. The third follow-up in month two could well be a sensible time to adjust treatment to support "slow improvers".
Structural brain morphometry as classifier and predictor of ADHD and reward-related comorbidities
(2022)
Attention deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, and around two-thirds of affected children report persisting problems in adulthood. This negative trajectory is associated with high comorbidity with disorders like obesity, depression, or substance use disorder (SUD). Decreases in cortical volume and thickness have also been reported in depression, SUD, and obesity, but it is unclear whether structural brain alterations represent unique disorder-specific profiles. A transdiagnostic exploration of ADHD and typical comorbid disorders could help to understand whether specific morphometric brain changes are due to ADHD or, alternatively, to the comorbid disorders. In the current study, we studied the brain morphometry of 136 subjects with ADHD with and without comorbid depression, SUD, and obesity to test whether there are unique or common brain alterations. We employed a machine-learning-algorithm trained to classify subjects with ADHD in the large ENIGMA-ADHD dataset and used it to predict the diagnostic status of subjects with ADHD and/or comorbidities. The parcellation analysis demonstrated decreased cortical thickness in medial prefrontal areas that was associated with presence of any comorbidity. However, these results did not survive correction for multiple comparisons. Similarly, the machine learning analysis indicated that the predictive algorithm grouped most of our ADHD participants as belonging to the ADHD-group, but no systematic differences between comorbidity status came up. In sum, neither a classical comparison of segmented structural brain metrics nor an ML model based on the ADHD ENIGMA data differentiate between ADHD with and without comorbidities. As the ML model is based in part on adolescent brains, this might indicate that comorbid disorders and their brain changes are not captured by the ML model because it represents a different developmental brain trajectory.
Depressive symptoms in youth with ADHD: the role of impairments in cognitive emotion regulation
(2022)
Youth with attention-deficit/hyperactivity disorder (ADHD) are at increased risk to develop co-morbid depression. Identifying factors that contribute to depression risk may allow early intervention and prevention. Poor emotion regulation, which is common in adolescents, is a candidate risk factor. Impaired cognitive emotion regulation is a fundamental characteristic of depression and depression risk in the general population. However, little is known about cognitive emotion regulation in youth with ADHD and its link to depression and depression risk. Using explicit and implicit measures, this study assessed cognitive emotion regulation in youth with ADHD (N = 40) compared to demographically matched healthy controls (N = 40) and determined the association with depressive symptomatology. As explicit measure, we assessed the use of cognitive emotion regulation strategies via self-report. As implicit measure, performance in an ambiguous cue-conditioning task was assessed as indicator of affective bias in the processing of information. Compared to controls, patients reported more frequent use of maladaptive (i.e., self-blame, catastrophizing, and rumination) and less frequent use of adaptive (i.e., positive reappraisal) emotion regulation strategies. This pattern was associated with the severity of current depressive symptoms in patients. In the implicit measure of cognitive bias, there was no significant difference in response of patients and controls and no association with depression. Our findings point to depression-related alterations in the use of cognitive emotion regulation strategies in youth with ADHD. The study suggests those alterations as a candidate risk factor for ADHD-depression comorbidity that may be used for risk assessment and prevention strategies.
Beyond well-established difficulties with working memory in individuals with attention deficit hyperactivity disorder (ADHD), evidence is emerging that other memory processes may also be affected. We investigated, first, which memory processes show differences in adults and adolescents with ADHD in comparison to control participants, focusing on working and short-term memory, initial learning, interference, delayed and recognition memory. Second, we investigated whether ADHD severity, co-occurring depressive symptoms, IQ and physical fitness are associated with the memory performance in the individuals with ADHD.
We assessed 205 participants with ADHD (mean age 25.8 years, SD 7.99) and 50 control participants (mean age 21.1 years, SD 5.07) on cognitive tasks including the digit span forward (DSF) and backward (DSB), the Rey Auditory Verbal Learning Test (RAVLT), and the vocabulary and matrix reasoning subtests of the Wechsler Abbreviated Scale of Intelligence. Participants with ADHD were additionally assessed on ADHD severity, depression symptoms and cardiorespiratory fitness. A series of regressions were run, with sensitivity analyses performed when variables were skewed.
ADHD-control comparisons were significant for DSF, DSB, delayed and recognition memory, with people with ADHD performing less well than the control participants. The result for recognition memory was no longer significant in sensitivity analysis. Memory performance was not associated with greater ADHD or depression symptoms severity. IQ was positively associated with all memory variables except DSF. Cardiorespiratory fitness was negatively associated with the majority of RAVLT variables.
Individuals with ADHD showed difficulties with working memory, short-term memory and delayed memory, as well as a potential difficulty with recognition memory, despite preserved initial learning.
Epigenetic signatures such as methylation of the monoamine oxidase A (MAOA) gene have been found to be altered in panic disorder (PD). Hypothesizing temporal plasticity of epigenetic processes as a mechanism of successful fear extinction, the present psychotherapy-epigenetic study for we believe the first time investigated MAOA methylation changes during the course of exposure-based cognitive behavioral therapy (CBT) in PD. MAOA methylation was compared between N=28 female Caucasian PD patients (discovery sample) and N=28 age- and sex-matched healthy controls via direct sequencing of sodium bisulfite-treated DNA extracted from blood cells. MAOA methylation was furthermore analyzed at baseline (T0) and after a 6-week CBT (T1) in the discovery sample parallelized by a waiting time in healthy controls, as well as in an independent sample of female PD patients (N=20). Patients exhibited lower MAOA methylation than healthy controls (P<0.001), and baseline PD severity correlated negatively with MAOA methylation (P=0.01). In the discovery sample, MAOA methylation increased up to the level of healthy controls along with CBT response (number of panic attacks; T0–T1: +3.37±2.17%), while non-responders further decreased in methylation (−2.00±1.28%; P=0.001). In the replication sample, increases in MAOA methylation correlated with agoraphobic symptom reduction after CBT (P=0.02–0.03). The present results support previous evidence for MAOA hypomethylation as a PD risk marker and suggest reversibility of MAOA hypomethylation as a potential epigenetic correlate of response to CBT. The emerging notion of epigenetic signatures as a mechanism of action of psychotherapeutic interventions may promote epigenetic patterns as biomarkers of lasting extinction effects.