Biological Psychiatry最新文献

Although the precise underlying cause(s) of autism spectrum disorder remain unclear, more than 1000 rare genetic variations are associated with the condition. For many people living with profound autism, this genetic heterogeneity has impeded the identification of common biological targets for therapy development for core and comorbid traits that include significant impairments in social communication and repetitive and restricted behaviors. A substantial number of genes associated with autism encode proteins involved in signal transduction and synaptic transmission that are critical for brain development and function. CAMK4 is an emerging risk gene for autism spectrum disorder that encodes the CaMK4 (calcium/calmodulin-dependent protein kinase 4) enzyme. CaMK4 is a key component of a Ca²⁺-activated signaling pathway that regulates neurodevelopment and synaptic plasticity. In this review, we discuss 3 genetic variants of CAMK4 found in individuals with hyperkinetic movement disorder and comorbid neurological symptoms including autism spectrum disorder that are likely pathogenic with monogenic effect. We also comment on 4 other genetic variations in CAMK4 that show associations with autism spectrum disorder, as well as 12 examples of autism-associated variations in other genes that impact CaMK4 signaling pathways. Finally, we highlight 3 environmental risk factors that impact CaMK4 signaling based on studies of preclinical models of autism and/or clinical cohorts. Overall, we review molecular, genetic, physiological, and environmental evidence that suggest that defects in the CaMK4 signaling pathway may play an important role in a common autism pathogenesis network across numerous patient groups, and we propose CaMK4 as a potential therapeutic target.

Background: Simultaneous interoceptive, emotional, and social cognition deficits are observed across neurodegenerative diseases. Indirect evidence suggests shared neurobiological bases underlying these impairments, termed the allostatic-interoceptive network (AIN). However, no study has yet explored the convergence of these deficits in neurodegenerative diseases or examined how structural and functional changes contribute to cross-domain impairments.

Methods: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) activated likelihood estimate meta-analysis encompassed studies that met the following inclusion criteria: interoception, emotion, or social cognition tasks; neurodegenerative diseases (behavioral variant frontotemporal dementia, primary progressive aphasias, Alzheimer's disease, Parkinson's disease, multiple sclerosis); and neuroimaging (structural: magnetic resonance imaging voxel-based morphometry; functional: magnetic resonance imaging and fluorodeoxyglucose-positron emission tomography).

Results: Of 20,593 studies, 170 met inclusion criteria (58 interoception, 65 emotion, and 47 social cognition) involving 7032 participants (4963 patients and 2069 healthy control participants). In all participants combined, conjunction analyses revealed AIN involvement of the insula, amygdala, orbitofrontal cortex, anterior cingulate, striatum, thalamus, and hippocampus across domains. In behavioral variant frontotemporal dementia, this conjunction was replicated across domains, with further involvement of the temporal pole, temporal fusiform cortex, and angular gyrus. A convergence of interoception and emotion in the striatum, thalamus, and hippocampus in Parkinson's disease and the posterior insula in primary progressive aphasias was also observed. In Alzheimer's disease and multiple sclerosis, disruptions in the AIN were observed during interoception, but no convergence with emotion was identified.

Conclusions: Neurodegeneration induces dysfunctional AIN across atrophy, connectivity, and metabolism, more accentuated in behavioral variant frontotemporal dementia. Findings bolster the predictive coding theories of large-scale AIN, calling for more synergistic approaches to understanding interoception, emotion, and social cognition impairments in neurodegeneration.

Background: The high heterogeneity of neuropsychiatric symptoms (NPSs) hinders further exploration of their role in neurobiological mechanisms and Alzheimer's disease (AD). We aimed to delineate NPS patterns based on brain macroscale connectomics to understand the biological mechanisms of NPSs on the AD continuum.

Methods: We constructed regional radiomics similarity networks for 550 participants (AD with NPSs [n = 376], AD without NPSs [n = 111], and normal control participants [n = 63]) from the CIBL (Chinese Imaging, Biomarkers, and Lifestyle) study. We identified regional radiomics similarity network connections associated with NPSs and then clustered distinct subtypes of AD with NPSs. An independent dataset (n = 189) and internal validation were performed to assess the robustness of the NPS subtypes. Subsequent multiomics analysis was performed to assess the distinct clinical phenotype and biological mechanisms in each NPS subtype.

Results: AD patients with NPSs were clustered into severe (n = 187), moderate (n = 87), and mild (n = 102) NPS subtypes, each exhibiting distinct brain network dysfunction patterns. A high level of consistency in clustering NPSs was internally and externally validated. Severe and moderate NPS subtypes were associated with significant cognitive impairment, increased plasma p-tau181 (tau phosphorylated at threonine 181) levels, extensive decreased brain volume and cortical thickness, and accelerated cognitive decline. Gene set enrichment analysis revealed enrichment of differentially expressed genes in ion transport and synaptic transmission with variations for each NPS subtype. Genome-wide association study analysis defined the specific gene loci for each subtype of AD with NPSs (e.g., logical memory), consistent with clinical manifestations and progression patterns.

Conclusions: This study identified and validated 3 distinct NPS subtypes, underscoring the role of NPSs in neurobiological mechanisms and progression of the AD continuum.

Background: Neuropsychiatric and neurodegenerative disorders involve diverse changes in brain functional connectivity. As an alternative to approaches that search for specific mosaic patterns of affected connections and networks, we used polyconnectomic scoring to quantify disorder-related whole-brain connectivity signatures into interpretable, personalized scores.

Methods: The polyconnectomic score (PCS) measures the extent to which an individual's functional connectivity mirrors the whole-brain circuitry characteristics of a trait. We computed PCSs for 8 neuropsychiatric conditions (attention-deficit/hyperactivity disorder, anxiety-related disorders, autism spectrum disorder, obsessive-compulsive disorder, bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) and 3 neurodegenerative conditions (Alzheimer's disease, frontotemporal dementia, and Parkinson's disease) across 22 datasets with resting-state functional magnetic resonance imaging data from 10,667 individuals (5325 patients, 5342 control participants). We also examined PCSs in 26,673 individuals from the population-based UK Biobank cohort.

Results: PCSs were consistently higher in out-of-sample patients across 6 of the 8 neuropsychiatric and across all 3 investigated neurodegenerative disorders ([minimum, maximum]: area under the receiver operating characteristic curve = [0.55, 0.73], false discovery rate-corrected p [p_FDR] = [1.8 × 10^-16, 4.5 × 10^-2]). Individuals with elevated PCS levels for neuropsychiatric conditions exhibited higher neuroticism (p_FDR < 9.7 × 10^-5), lower cognitive performance (p_FDR < 5.3 × 10^-5), and lower general well-being (p_FDR < 9.7 × 10^-4).

Conclusions: Our findings reveal generalizable whole-brain connectivity alterations in brain disorders. Polyconnectomic scoring effectively aggregates disorder-related signatures across the entire brain into an interpretable, participant-specific metric. A toolbox is provided for PCS computation.

Genome-wide studies are yielding a growing catalog of common and rare variants that confer risk for psychopathology. However, despite representing unprecedented progress, emerging data also indicate that the full promise of psychiatric genetics-including understanding pathophysiology and improving personalized care-will not be fully realized by targeting traditional dichotomous diagnostic categories. The current article provides reflections on themes that emerged from a 2021 National Institute of Mental Health-sponsored conference convened to address strategies for the evolving field of psychiatric genetics. As anticipated by the National Institute of Mental Health's Research Domain Criteria framework, multilevel investigations of dimensional and transdiagnostic phenotypes, particularly when integrated with biobanks and big data, will be critical to advancing knowledge. The path forward will also require more diverse representation in source studies. Additionally, progress will be catalyzed by a range of converging approaches, including capitalizing on computational methods, pursuing biological insights, working within a developmental framework, and engaging health care systems and patient communities.

Background: Aging is a multilevel process of gradual decline that predicts morbidity and mortality. Independent investigations have implicated senescence of brain and peripheral physiology in psychiatric risk, but it is unclear whether these effects stem from unique or shared mechanisms.

Methods: To address this question, we analyzed clinical, blood chemistry, and resting-state functional neuroimaging data in a healthy aging cohort (n = 427; ages 36-100 years) and 2 disorder-specific samples including patients with early psychosis (100 patients, 16-35 years) and major depressive disorder (MDD) (104 patients, 20-76 years).

Results: We identified sex-dependent coupling between blood chemistry markers of metabolic senescence (i.e., homeostatic dysregulation), functional brain network aging, and psychiatric risk. In females, premature aging of frontoparietal and somatomotor networks was linked to greater homeostatic dysregulation. It also predicted the severity and treatment resistance of mood symptoms (depression/anxiety [all 3 samples], anhedonia [MDD]) and social withdrawal/behavioral inhibition (avoidant personality disorder [healthy aging], negative symptoms [early psychosis]). In males, premature aging of the default mode, cingulo-opercular, and visual networks was linked to reduced homeostatic dysregulation and predicted the severity and treatment resistance of symptoms relevant to hostility/aggression (antisocial personality disorder [healthy aging], mania/positive symptoms [early psychosis]), impaired thought processes (early psychosis, MDD), and somatic problems (healthy aging, MDD).

Conclusions: Our findings identify sexually dimorphic relationships between brain dynamics, peripheral physiology, and risk for psychiatric illness, suggesting that the specificity of putative risk biomarkers and precision therapeutics may be improved by considering sex and other relevant personal characteristics.

Background: Sleep and arousal disorders are common, but the underlying physiology of wakefulness is not fully understood. The locus coeruleus promotes arousal via alpha-1 adrenergic receptor (α₁AR) driven recruitment of wake-promoting dopamine (DA) neurons in the ventral periaqueductal gray (vPAG^DA neurons). α₁AR expression is enriched on vPAG astrocytes, and chemogenetic activation of astrocytic G_q signaling promotes wakefulness. Astrocytes can release extracellular "gliotransmitters," such as ATP and adenosine, but the mechanism underlying how vPAG astrocytic α₁ARs influence sleep/wake behavior and vPAG^DA neuron physiology is unknown.

Methods: In this study, we utilized genetic manipulations with ex vivo calcium imaging in vPAG^DA neurons and astrocytes, patch-clamp electrophysiology, and behavioral experiments in mice to probe our hypothesis that astrocytic α₁ARs mediate noradrenergic modulation of wake-promoting vPAG^DA neurons via adenosine signaling.

Results: Activation of α₁ARs with phenylephrine increased calcium transients in vPAG^DA neurons and vPAG astrocytes, and increased vPAG^DA neuron excitability ex vivo. Chemogenetic Gq-DREADD activation of vPAG astrocytes similarly increased vPAG^DA neuron calcium activity and intrinsic excitability. Conversely, shRNA knockdown of vPAG astrocytic α₁ARs reduced the excitatory effect of phenylephrine on vPAG^DA neurons and blunted arousal during the wake phase. Pharmacological blockade of adenosine 2A (A_2A) receptors precludes the α₁AR-induced increase in vPAG^DA calcium activity and excitability in brain slices, as well as the wake-promoting effects of vPAG α₁AR activation in vivo.

Conclusions: We have identified a crucial role for vPAG astrocytic α₁AR receptors in sustaining arousal through heightened excitability and activity of vPAG^DA neurons mediated by local A_2A receptors.