Translational Psychiatry最新文献

Treatment strategies that are efficient against established Alzheimer's disease (AD) are needed. BRICHOS is a molecular chaperone domain that prevents amyloid fibril formation and associated cellular toxicity. In this study, we treated an AD mouse model seven months after pathology onset, using intravenous administration of recombinant human (rh) Bri2 BRICHOS R221E. Two injections of rh Bri2 BRICHOS R221E per week for three months in AD mice reduced amyloid β (Aβ) burden, and mitigated astro- and microgliosis, as determined by glial fibrillary acidic protein (GFAP) and ionized calcium-binding adaptor molecule 1 (Iba1) immunohistochemistry. Sequencing of RNA from cortical microglia cells showed that BRICHOS treatment normalized the expression of identified plaque-induced genes in mice and humans, including clusterin and GFAP. Rh Bri2 BRICHOS R221E passed the blood-brain barrier (BBB) in age-matched wild-type mice as efficiently as in the AD mice, but then had no effect on measures of AD-like pathology, and mainly affected the expression of genes that affect cellular shape and movement. These results indicate a potential of rh Bri2 BRICHOS against advanced AD and underscore the ability of BRICHOS to target amyloid-induced pathology.

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs, although sensitivity analyses indicated that other structures were plausible. The multivariate GWASs of the GIBNs identified 74 genome-wide significant (GWS) loci (p < 5 × 10^-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed between attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). CT GIBNs displayed a negative genetic correlation with alcohol dependence. Even though we observed model instability in our application of genomic SEM to high-dimensional data, jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across neuroimaging phenotypes offers new insights into the genetics of cortical structure and relationships to psychopathology.

Autism Spectrum Disorder (ASD) is a developmental disorder characterized by impaired social communication and repetitive behaviors. In recent years, a pharmacological mouse model of ASD involving maternal administration of valproic acid (VPA) has become widely used. Newborn pups in this model show an abnormal balance between excitatory and inhibitory (E/I) signaling in neurons and exhibit ASD-like behavior. However, the molecular basis of this model and its implications for the pathogenesis of ASD in humans remain unknown. Using quantitative secretome analysis, we found that the level of leucine-rich repeat and immunoglobulin domain-containing protein 2 (Lingo2) was upregulated in the conditioned medium of VPA model neurons. This upregulation was associated with excitatory synaptic organizer activity. The secreted form of the extracellular domain of Lingo2 (sLingo2) is produced by the transmembrane metalloprotease ADAM10 through proteolytic processing. sLingo2 was found to induce the formation of excitatory synapses in both mouse and human neurons, and treatment with sLingo2 resulted in an increased frequency of miniature excitatory postsynaptic currents in human neurons. These findings suggest that sLingo2 is an excitatory synapse organizer involved in ASD, and further understanding of the mechanisms by which sLingo2 induces excitatory synaptogenesis is expected to advance our understanding of the pathogenesis of ASD.

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.