Translational Psychiatry最新文献

Amnestic mild cognitive impairment (aMCI) is a risk factor for Alzheimer's disease (AD). Multi-domain cognitive training (CT) may slow cognitive decline and delay AD onset. However, most work involves short interventions, targeting single cognitive domains or lacking active controls. We conducted a single-blind randomized controlled trial to investigate the effect of a 6-month, multi-domain CT on Fluid Cognition, functional connectivity in memory and executive functioning networks (primary outcomes), and white matter microstructural properties (secondary outcome) in aMCI. Sixty participants were randomly assigned to either a multi-domain CT or crossword training (CW) group, and thirty-four participants completed the intervention. We found a significant group-by-time interaction in Fluid Cognition (p = 0.007, F (1,28) = 8.26, Cohen's d = 0.38, 95% confidence interval [CI]: 2.45-14.4), with 90% of CT patients showing post-intervention improvements (p < 0.01, Cohen's d = 0.7). The CT group also showed better post-intervention Fluid Cognition than healthy controls (HCs, N = 45, p = 0.045). Functional connectivity analyses showed a significant group-by-time interaction (Cohen's d ≥ 0.8) in the dorsolateral prefrontal cortex (DLPFC) and inferior parietal cortex (IPC) networks. Specifically, CT displayed post-intervention increases whereas CW displayed decreases in functional connectivity. Moreover, increased connectivity strength between the left DLPFC and medial PFC was associated with improved Fluid Cognition. At a microstructural level, we observed a decline in fiber density (FD) for both groups, but the CT group declined less steeply (1.3 vs. 2%). The slower decline in FD for the CT group in several tracts, including the cingulum-hippocampus tract, was associated with better working memory. Finally, we identified regions in cognitive control and memory networks for which baseline functional connectivity and microstructural properties were associated with changes in Fluid Cognition. Long-term, multi-domain CT improves cognitive functioning and functional connectivity and delays structural brain decline in aMCI (ClinicalTrials.gov number: NCT03883308).

Maternal stress and depression during pregnancy and the first year of the infant's life affect a large percentage of mothers. Maternal stress and depression have been associated with adverse fetal and childhood outcomes as well as differential child DNA methylation (DNAm). However, the biological mechanisms connecting maternal stress and depression to poor health outcomes in children are still largely unknown. Here we aim to determine whether prenatal stress and depression are associated with differences in cord blood mononuclear cell DNAm (CBMC-DNAm) in newborns (n = 119) and whether postnatal stress and depression are associated with differences in peripheral blood mononuclear cell DNAm (PBMC-DNAm) in children of 12 months of age (n = 113) from the Canadian Healthy Infant Longitudinal Development (CHILD) cohort. Stress was measured using the 10-item Perceived Stress Scale (PSS) and depression was measured using the 20-item Center for Epidemiologic Studies Depression Questionnaire (CESD). Both stress and depression were measured longitudinally at 18 weeks and 36 weeks of pregnancy and six months and 12 months postpartum. We conducted epigenome-wide association studies (EWAS) using robust linear regression followed by a sensitivity analysis in which we bias-adjusted for inflation and unmeasured confounding using the bacon and cate methods. To quantify the cumulative effect of maternal stress and depression, we created composite prenatal and postnatal adversity scores. We identified a significant association between prenatal stress and differential CBMC-DNAm at 8 CpG sites and between prenatal depression and differential CBMC-DNAm at 2 CpG sites. Additionally, we identified a significant association between postnatal stress and differential PBMC-DNAm at 8 CpG sites and between postnatal depression and differential PBMC-DNAm at 11 CpG sites. Using our composite scores, we further identified 2 CpG sites significantly associated with prenatal adversity and 7 CpG sites significantly associated with postnatal adversity. Several of the associated genes, including PLAGL1, HYMAI, BRD2, and ERC2 have been implicated in adverse fetal outcomes and neuropsychiatric disorders. These data further support the finding that differential DNAm may play a role in the relationship between maternal mental health and child health.

The "Sign-tracker/Goal-tracker" (ST/GT) is an animal model of individual differences in learning and motivational processes attributable to distinctive conditioned responses to environmental cues. While GT rats value the reward-predictive cue as a mere predictor, ST rats attribute it with incentive salience, engaging in aberrant reward-seeking behaviors that mirror those of impulse control disorders. Given its potential clinical value, the present study aimed to map such model onto humans and investigated resting state functional magnetic resonance imaging correlates of individuals categorized as more disposed to sign-tracking or goal-tracking behavior. To do so, eye-tracking was used during a translationally informed Pavlovian paradigm to classify humans as STs (n = 36) GTs (n = 35) or as Intermediates (n = 33), depending on their eye-gaze towards the reward-predictive cue or the reward location. Using connectivity and network-based approach, measures of resting state functional connectivity and centrality (role of a node as a hub) replicated preclinical findings, suggesting a major involvement of subcortical areas in STs, and dominant cortical involvement in GTs. Overall, the study strengthens the translational value of the ST/GT model, with important implications for the early identification of vulnerable phenotypes for psychopathological conditions such as substance use disorder.

Oxidative stress (OS) is strongly implicated in the pathophysiology of major depressive disorder (MDD) but the molecular mechanisms remain largely unknown. The purpose of this study is to identify genes related to both OS and MDD, and further to evaluate the utility of these genes as diagnostic markers and potential treatment targets. We searched datasets related to MDD from the Gene Expression Omnibus (GEO) database for differentially expressed genes (DEGs) also related to OS according to GeneCards. Bioinformatics analyses and machine learning algorithms were used to identify hub genes mediating OS-MDD interactions. A summary data-based Mendelian randomization (SMR) approach was employed to identify possible causal genes for MDD from blood tissue eQLT data. These investigations identified 32 genes mediating OS-MDD interactions, while SMR analysis identified KCNE1 (OR = 1.057, 95%CI = 1.013-1.102, P value = 0.010), MAPK3 (OR = 1.023, 95%CI = 1.004-1.043, P value = 0.020), and STIP1 (OR = 0.792, 95%CI = 0.641-0.979, P value = 0.031) as OS-related causal genes for MDD. These genes may thus serve as useful diagnostic markers and potential therapeutic targets.

Longitudinal associations of homocysteine (HCY) with depressive symptoms scores among urban adults remain under-studied, especially across sex, race and levels of anxiety. We examined longitudinal associations of homocysteine (HCY) with depressive symptoms scores among urban adults, before and after stratifying by sex, race and anxiety level, using data from 1460 Healthy Aging in Neighborhoods of Diversity across the Lifespan Study (HANDLS) participants aged 30-64 y at v₁ (2004-2009), followed across 3 visits up to 2017. In addition to LnHcy_v1, we used group-based trajectory models predicting z-transformed likelihood of greater LnHcy with age (Hcy_traj). Total and domain-specific depression symptoms were scored using Center for Epidemiologic Studies Depression (CES-D) scale. Mixed-effects linear regression models and Cox proportional hazards models were utilized. A positive association was found between baseline LnHcy_v1 and CES-D total scores in reduced socio-demographic- adjusted Model 1 (β (standard error [SE]) = + 2.337 (0.902), P = 0.010), a relationship slightly attenuated in fully adjusted Model 2 (Model 1 adjusting for lifestyle and health factors) with a β (SE) = + 1.825 (0.883), P = 0.039. Individuals with lower anxiety levels experienced faster CES-D domain 2 score annualized increase over time (interpersonal problems) with higher LnHcy_v1 (β (SE) = 0.041 (0.018), P = 0.024). Hcy_traj was linked to incident elevated depressive symptoms (CES-D total score ≥16) overall (fully adjusted model: HR = 1.09, 95% CI: 1.03-1.14, P = 0.001), particularly among women and those living in poverty. Baseline and "high trajectory" of LnHcy were positively associated with depressive symptoms and elevated depressive symptom incidence, in a sex-, race-, poverty status- and anxiety-level specific manner.

Body image disturbance is a key symptom of anorexia nervosa (AN). AN patients report body dissatisfaction and overestimate their own body size in several tasks. This study aimed to clarify whether this overestimation arises from deficits in visual perception. To this end, 36 adolescent restrictive-type AN patients and 42 matched healthy controls performed metric and depictive body size estimation (BSE) tasks. Magneto- and electroencephalography were measured during the size estimation of 66 computer-generated body pictures varying in size from underweight to overweight. AN patients versus controls showed overestimation across self-referential metric and depictive BSE tasks, but similar performance in a depictive BSE task without self-reference and similar early neurophysiological responses. Starting mid-latency (200 ms), AN patients showed relatively more neural activity in response to underweight body pictures and less neural activity in response to higher-weight body pictures in distributed brain regions. A secondary comparison of AN patients with slight vs. distinct overestimation during self-referential BSE uncovered relatively stronger neural responses to body pictures corresponding to the estimated body mass index. These results suggest that body image disturbances in adolescent restrictive-type AN patients depend on self-reference and do not represent a deficit of visual perception, but rather biased emotional attention.

Substance use disorders (SUDs) imposes profound physical, psychological, and socioeconomic burdens on individuals, families, communities, and society as a whole, but the available treatment options remain limited. Deep brain-machine interfaces (DBMIs) provide an innovative approach by facilitating efficient interactions between external devices and deep brain structures, thereby enabling the meticulous monitoring and precise modulation of neural activity in these regions. This pioneering paradigm holds significant promise for revolutionizing the treatment landscape of addictive disorders. In this review, we carefully examine the potential of closed-loop DBMIs for addressing SUDs, with a specific emphasis on three fundamental aspects: addictive behaviors-related biomarkers, neuromodulation techniques, and control policies. Although direct empirical evidence is still somewhat limited, rapid advancements in cutting-edge technologies such as electrophysiological and neurochemical recordings, deep brain stimulation, optogenetics, microfluidics, and control theory offer fertile ground for exploring the transformative potential of closed-loop DBMIs for ameliorating symptoms and enhancing the overall well-being of individuals struggling with SUDs.

Stress contributes to transdiagnostic morbidity and mortality across a wide range of physical and mental health problems. VR tasks have been validated as stressors with robust effect sizes for VR-based stressors to evoke stress across the most common autonomic and adrenocortical stress biomarkers. However, meta-analytic validation of VR stressors have resulted in inconsistent logic: why should something that isn't real evoke a very real suite of stress responses? This review posits that conceptually addressing this question requires differentiating a cause, "stressor", from effects, "stress". Stress comprises a series of well-delineated perturbations in biological systems, such as autonomic and adrenocortical biomarkers in response to stressors. Despite their ubiquity, decades of literature have back-calculated stressor intensity based on the magnitude of a stress response. This causal directionality is not logical, yet remains pervasive because seemingly objective stress indices have generated a wealth of findings showing how stress gets under the skin and skull. This has created challenges for providing clear guidance and strategies to measure acute stressor intensity. Binary thinking about whether something is (not) real has stifled advances in understanding how to measure the dosage of a stressful environment. As a function of being programmed, individualizable, and titrated, virtual reality (VR) based stressors offer the field a platform for quantifying the dose of a stressor and generating reliable dose-response curves. This also raises the possibility to safely and ethically integrate psychosocial stressor administration into clinical and therapeutic settings. For example, Social Evaluative Threat experiments effectively trigger a stress response both in a laboratory setting and in built environments, while also upholding hard-fought trust and rapport with care providers. By focusing attention on the measurement of the stressor, VR paradigms can advance tangible understanding of stressors themselves and the pathways to the stress response.

There is increasing interest in the pathophysiological role of arginine metabolism in schizophrenia, particularly in relation to the modulation of the endogenous messenger nitric oxide (NO). The assessment of specific arginine metabolites that, unlike NO, are stable can provide useful insights into NO regulatory enzymes such as isoform 1 of dimethylarginine dimethylaminohydrolase (DDAH1) and arginase. We investigated the role of arginine metabolomics in schizophrenia by conducting a systematic review and meta-analysis of the circulating concentrations of arginine metabolites associated with DDAH1, arginase, and NO synthesis [arginine, citrulline, asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), dimethylamine, and ornithine] in this patient group. We searched PubMed, Scopus, and Web of Science from inception to the 31^st of May 2023 for studies investigating arginine metabolites in patients with schizophrenia and healthy controls. The JBI Critical Appraisal Checklist for analytical studies and GRADE were used to assess the risk of bias and the certainty of evidence, respectively (PROSPERO registration number: CRD42023433000). Twenty-one studies were identified for analysis. There were no significant between-group differences in arginine, citrulline, and SDMA. By contrast, patients with schizophrenia had significantly higher ADMA (DDAH1 substrate, standard mean difference, SMD = 1.23, 95% CI 0.86-1.61, p < 0.001; moderate certainty of evidence), dimethylamine (DDAH1 product, SMD = 0.47, 95% CI 0.24-0.70, p < 0.001; very low certainty of evidence), and ornithine concentrations (arginase product, SMD = 0.32, 95% CI 0.16-0.49, p < 0.001; low certainty of evidence). In subgroup analysis, the pooled SMD for ornithine was significantly different in studies of untreated, but not treated, patients. Our study suggests that DDAH1 and arginase are dysregulated in schizophrenia. Further studies are warranted to investigate the expression/activity of these enzymes in the brain of patients with schizophrenia and the effects of targeted treatments.

Background: Recent evidence indicates that the risk of death by suicide in teenagers has increased significantly worldwide. Consequently, different therapeutic interventions have been proposed for suicidal behavior in this particular population. Therefore, the main objective of this study is to provide an updated review of the existing psychological interventions for the treatment of suicide attempts (SA) in adolescents and to analyze the efficacy of such interventions.

Methods: A systematic review was conducted following PRISMA guidelines. The studies were identified by searching PubMed, PsychINFO, Web of Science, and Scopus databases from 2016 to 2022. According to the inclusion criteria, a total of 40 studies that tested the efficacy of different psychological interventions were selected.

Results: Various psychological interventions for adolescents with suicidal behaviors were identified. Most of those present promising results. However, to summarize results from recent years, dialectical behavior therapy (DBT) was the most common and the only treatment shown to be effective for adolescents at high risk of suicide and SA. In contrast, empirical evidence for other psychological interventions focusing on deliberate self-harm (SH) is inconclusive.

Conclusions: Interventions specifically designed to reduce suicidal risk in adolescents have multiplied significantly in recent years. There are a few promising interventions for reducing suicidal behaviors in adolescents evaluated by independent research groups. However, replication and dismantling studies are needed to identify the effects of these interventions and their specific components. An important future challenge is to develop brief and effective interventions to reduce the risk of death by suicide among the adolescent population.