AMPK signaling linked to the schizophrenia-associated 1q21.1 deletion is required for neuronal and sleep maintenance

Akt and AMPK activators rescue hyperexcitability in neurons from patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is a multifactorial psychiatric illness affecting ∼1% of the global adult population. Lithium (Li), is the most effective mood stabilizer for BD but works only for a subset of patients and its mechanism of action remains largely elusive.

METHODS

In the present study, we used iPSC-derived neurons from patients with BD who are responsive (LR) or not (LNR) to lithium. Combined electrophysiology, calcium imaging, biochemistry, transcriptomics, and phosphoproteomics were employed to provide mechanistic insights into neuronal hyperactivity in BD, investigate Li's mode of action, and identify alternative treatment strategies.

FINDINGS

We show a selective rescue of the neuronal hyperactivity phenotype by Li in LR neurons, correlated with changes to Na+ conductance. Whole transcriptome sequencing in BD neurons revealed altered gene expression pathways related to glutamate transmission, alterations in cell signalling and ion transport/channel activity. We found altered Akt signalling as a potential therapeutic effect of Li in LR neurons from patients with BD, and that Akt activation mimics Li effect in LR neurons. Furthermore, the increased neural network activity observed in both LR & LNR neurons from patients with BD were reversed by AMP-activated protein kinase (AMPK) activation.

INTERPRETATION

These results suggest potential for new treatment strategies in BD, such as Akt activators in LR cases, and the use of AMPK activators for LNR patients with BD.

FUNDING

Supported by funding from ERA PerMed, Bell Brain Canada Mental Research Program and Brain & Behavior Research Foundation.

The copy number variant architecture of psychopathology and cognitive development in the ABCD® study

Importance

Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored.

Objective

Investigating CNV associations with dimensions of child psychopathology and cognitive functions.

Design Setting and Participants

ABCD® study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024.

Main Outcomes and Measures

In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development® study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes.

Results

In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains.

Conclusions and Relevance

In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology.

Mechanistic insight on the role of iRhom2-TNF-α-BAFF signaling pathway in various autoimmune disorders

iRhom2 is a crucial cofactor involved in upregulation of TNF receptors (TNFRs) and the pro-inflammatory cytokine tumor necrosis factor (TNF-) from the cell surface by ADAM17. Tumor necrosis factor- α converting enzyme (TACE) is another name given to ADAM17. Many membrane attached biologically active molecules are cleaved by this enzyme which includes TNFRs and the pro-inflammatory cytokine tumor necrosis factor- α. The TNF receptors are of two types TNFR1 and TNFR2. iRhom2 belongs to the pseudo-protease class of rhomboid family, its abundance is observed in the immune cells. Biological activity of ADAM17 is affected in multiple levels by the iRhom2. ADAM17 is trafficked into the Golgi apparatus by the action of iRhom2, where it gets matured proteolytically and is stimulated to perform its function on the cell surface. This process of activation of ADAM17 results in the protection of the organism from the cascade of inflammatory reactions, as this activation blocks the TNF- α mediated secretion responsible for inflammatory responses produced. Present paper illustrates about the iRhom2-TNF-α-BAFF signaling pathway and its correlation with several autoimmune disorders such as Rheumatoid Arthritis, Systemic Lupus Erythematosus, Hemophilia Arthropathy, Alzheimer's disease and Tylosis with esophageal cancer etc.

Lifestyle effects on aging and CVD: A spotlight on the nutrient-sensing network

Aging is widespread worldwide and a significant risk factor for cardiovascular disease (CVD). Mechanisms underlying aging have attracted considerable attention in recent years. Remarkably, aging and CVD overlap in numerous ways, with deregulated nutrient sensing as a common mechanism and lifestyle as a communal modifier. Interestingly, lifestyle triggers or suppresses multiple nutrient-related signaling pathways. In this review, we first present the composition of the nutrient-sensing network (NSN) and its metabolic impact on aging and CVD. Secondly, we review how risk factors closely associated with CVD, including adverse life states such as sedentary behavior, sleep disorders, high-fat diet, and psychosocial stress, contribute to aging and CVD, with a focus on the bridging role of the NSN. Finally, we focus on the positive effects of beneficial dietary interventions, specifically dietary restriction and the Mediterranean diet, on the regulation of nutrient metabolism and the delayed effects of aging and CVD that depend on the balance of the NSN. In summary, we expound on the interaction between lifestyle, NSN, aging, and CVD.

Potential Schizophrenia Disease-Related Genes Prediction Using Metagraph Representations Based on a Protein-Protein Interaction Keyword Network: Framework Development and Validation

BACKGROUND

Schizophrenia is a serious mental disease. With increased research funding for this disease, schizophrenia has become one of the key areas of focus in the medical field. Searching for associations between diseases and genes is an effective approach to study complex diseases, which may enhance research on schizophrenia pathology and lead to the identification of new treatment targets.

OBJECTIVE

The aim of this study was to identify potential schizophrenia risk genes by employing machine learning methods to extract topological characteristics of proteins and their functional roles in a protein-protein interaction (PPI)-keywords (PPIK) network and understand the complex disease-causing property. Consequently, a PPIK-based metagraph representation approach is proposed.

METHODS

To enrich the PPI network, we integrated keywords describing protein properties and constructed a PPIK network. We extracted features that describe the topology of this network through metagraphs. We further transformed these metagraphs into vectors and represented proteins with a series of vectors. We then trained and optimized our model using random forest (RF), extreme gradient boosting, light gradient boosting machine, and logistic regression models.

RESULTS

Comprehensive experiments demonstrated the good performance of our proposed method with an area under the receiver operating characteristic curve (AUC) value between 0.72 and 0.76. Our model also outperformed baseline methods for overall disease protein prediction, including the random walk with restart, average commute time, and Katz models. Compared with the PPI network constructed from the baseline models, complementation of keywords in the PPIK network improved the performance (AUC) by 0.08 on average, and the metagraph-based method improved the AUC by 0.30 on average compared with that of the baseline methods. According to the comprehensive performance of the four models, RF was selected as the best model for disease protein prediction, with precision, recall, F1-score, and AUC values of 0.76, 0.73, 0.72, and 0.76, respectively. We transformed these proteins to their encoding gene IDs and identified the top 20 genes as the most probable schizophrenia-risk genes, including the EYA3, CNTN4, HSPA8, LRRK2, and AFP genes. We further validated these outcomes against metagraph features and evidence from the literature, performed a features analysis, and exploited evidence from the literature to interpret the correlation between the predicted genes and diseases.

CONCLUSIONS

The metagraph representation based on the PPIK network framework was found to be effective for potential schizophrenia risk genes identification. The results are quite reliable as evidence can be found in the literature to support our prediction. Our approach can provide more biological insights into the pathogenesis of schizophrenia.

A New Concept of Associations between Gut Microbiota, Immunity and Central Nervous System for the Innovative Treatment of Neurodegenerative Disorders

Nerve cell death accounts for various neurodegenerative disorders, in which altered immunity to the integrated central nervous system (CNS) might have destructive consequences. This undesirable immune response often affects the progressive neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, schizophrenia and/or amyotrophic lateral sclerosis (ALS). It has been shown that commensal gut microbiota could influence the brain and/or several machineries of immune function. In other words, neurodegenerative disorders may be connected to the gut-brain-immune correlational system. The engrams in the brain could retain the information of a certain inflammation in the body which might be involved in the pathogenesis of neurodegenerative disorders. Tactics involving the use of probiotics and/or fecal microbiota transplantation (FMT) are now evolving as the most promising and/or valuable for the modification of the gut-brain-immune axis. More deliberation of this concept and the roles of gut microbiota would lead to the development of stupendous treatments for the prevention of, and/or therapeutics for, various intractable diseases including several neurodegenerative disorders.

A gut-derived hormone suppresses sugar appetite and regulates food choice in Drosophila

Animals must adapt their dietary choices to meet their nutritional needs. How these needs are detected and translated into nutrient-specific appetites that drive food-choice behaviours is poorly understood. Here we show that enteroendocrine cells of the adult female Drosophila midgut sense nutrients and in response release neuropeptide F (NPF), which is an ortholog of mammalian neuropeptide Y-family gut-brain hormones. Gut-derived NPF acts on glucagon-like adipokinetic hormone (AKH) signalling to induce sugar satiety and increase consumption of protein-rich food, and on adipose tissue to promote storage of ingested nutrients. Suppression of NPF-mediated gut signalling leads to overconsumption of dietary sugar while simultaneously decreasing intake of protein-rich yeast. Furthermore, gut-derived NPF has a female-specific function in promoting consumption of protein-containing food in mated females. Together, our findings suggest that gut NPF-to-AKH signalling modulates specific appetites and regulates food choice to ensure homeostatic consumption of nutrients, providing insight into the hormonal mechanisms that underlie nutrient-specific hungers.

The molecular mechanism of natural short sleep: A path towards understanding why we need to sleep

Sleep constitutes a third of human life and it is increasingly recognized as important for health. Over the past several decades, numerous genes have been identified to be involved in sleep regulation in animal models, but most of these genes when disturbed impair not only sleep but also health and physiological functions. Human natural short sleepers are individuals with lifelong short sleep and no obvious adverse outcomes associated with the lack of sleep. These traits appear to be heritable, and thus characterization of the genetic basis of natural short sleep provides an opportunity to study not only the genetic mechanism of human sleep but also the relationship between sleep and physiological function. This review focuses on the current understanding of mutations associated with the natural short sleep trait and the mechanisms by which they contribute to this trait.

LKB1 Is Physiologically Required for Sleep from Drosophila melanogaster to the Mus musculus

Liver Kinase B1 (LKB1) is known as a master kinase for 14 kinases related to the adenosine monophosphate (AMP)-activated protein kinase (AMPK). Two of them salt inducible kinase 3 (SIK3) and AMPKα have previously been implicated in sleep regulation. We generated loss-of-function (LOF) mutants for Lkb1 in both Drosophila and mice. Sleep, but not circadian rhythms, was reduced in Lkb1-mutant flies and in flies with neuronal deletion of Lkb1. Genetic interactions between Lkb1 and Threonine to Alanine mutation at residue 184 of AMPK in Drosophila sleep or those between Lkb1 and Threonine to Glutamic Acid mutation at residue 196 of SIK3 in Drosophila viability have been observed. Sleep was reduced in mice after virally mediated reduction of Lkb1 in the brain. Electroencephalography (EEG) analysis showed that non-rapid eye movement (NREM) sleep and sleep need were both reduced in Lkb1-mutant mice. These results indicate that LKB1 plays a physiological role in sleep regulation conserved from flies to mice.

Identify specific gene pairs for subarachnoid hemorrhage based on wavelet analysis and genetic algorithm

Subarachnoid hemorrhage (SAH) is a fatal stroke caused by bleeding in the brain. SAH can be caused by a ruptured aneurysm or head injury. One-third of patients will survive and recover. One-third will survive with disability; one-third will die. The focus of treatment is to stop bleeding, restore normal blood flow, and prevent vasospasm. Treatment for SAH varies, depending on the bleeding’s underlying cause and the extent of damage to the brain. Treatment may include lifesaving measures, symptom relief, repair of the bleeding vessel, and complication prevention. However, the useful diagnostic biomarkers of SAH are still limited due to the instability of gene marker expression. To overcome this limitation, we developed a new protocol pairing genes and screened significant gene pairs based on the feature selection algorithm. A classifier was constructed with the selected gene pairs and achieved a high performance.

Dissecting Molecular Genetic Mechanisms of 1q21.1 CNV in Neuropsychiatric Disorders

Pathogenic copy number variations (CNVs) contribute to the etiology of neurodevelopmental/neuropsychiatric disorders (NDs). Increased CNV burden has been found to be critically involved in NDs compared with controls in clinical studies. The 1q21.1 CNVs, rare and large chromosomal microduplications and microdeletions, are detected in many patients with NDs. Phenotypes of duplication and deletion appear at the two ends of the spectrum. Microdeletions are predominant in individuals with schizophrenia (SCZ) and microcephaly, whereas microduplications are predominant in individuals with autism spectrum disorder (ASD) and macrocephaly. However, its complexity hinders the discovery of molecular pathways and phenotypic networks. In this review, we summarize the recent genome-wide association studies (GWASs) that have identified candidate genes positively correlated with 1q21.1 CNVs, which are likely to contribute to abnormal phenotypes in carriers. We discuss the clinical data implicated in the 1q21.1 genetic structure that is strongly associated with neurodevelopmental dysfunctions like cognitive impairment and reduced synaptic plasticity. We further present variations reported in the phenotypic severity, genomic penetrance and inheritance.

Dissecting the complexity of CNV pathogenicity: insights from Drosophila and zebrafish models

Genetic architecture predisposes regions of the human genome to copy-number variants, which confer substantial disease risk, most prominently towards neurodevelopmental disorders. These variants typically contain multiple genes and are often associated with extensive pleiotropy and variable phenotypic expressivity. Despite the expansion of the fidelity of CNV detection, and the study of such lesions at the population level, understanding causal mechanisms for CNV phenotypes will require biological testing of constituent genes and their interactions. In this regard, model systems amenable to high-throughput phenotypic analysis of dosage-sensitive genes (and combinations thereof) are beginning to offer improved granularity of CNV-driven pathology. Here, we review the utility of Drosophila and zebrafish models for pathogenic CNV regions, highlight the advances made in discovery of single gene drivers and genetic interactions that determine specific CNV phenotypes, and argue for their validity in dissecting conserved developmental mechanisms associated with CNVs.

Time-Varying Gene Network Analysis of Human Prefrontal Cortex Development

The prefrontal cortex (PFC) constitutes a large part of the human central nervous system and is essential for the normal social affection and executive function of humans and other primates. Despite ongoing research in this region, the development of interactions between PFC genes over the lifespan is still unknown. To investigate the conversion of PFC gene interaction networks and further identify hub genes, we obtained time-series gene expression data of human PFC tissues from the Gene Expression Omnibus (GEO) database. A statistical model, loggle, was used to construct time-varying networks and several common network attributes were used to explore the development of PFC gene networks with age. Network similarity analysis showed that the development of human PFC is divided into three stages, namely, fast development period, deceleration to stationary period, and recession period. We identified some genes related to PFC development at these different stages, including genes involved in neuronal differentiation or synapse formation, genes involved in nerve impulse transmission, and genes involved in the development of myelin around neurons. Some of these genes are consistent with findings in previous reports. At the same time, we explored the development of several known KEGG pathways in PFC and corresponding hub genes. This study clarified the development trajectory of the interaction between PFC genes, and proposed a set of candidate genes related to PFC development, which helps further study of human brain development at the genomic level supplemental to regular anatomical analyses. The analytical process used in this study, involving the loggle model, similarity analysis, and central analysis, provides a comprehensive strategy to gain novel insights into the evolution and development of brain networks in other organisms.

AMPK and the Need to Breathe and Feed: What's the Matter with Oxygen?

We live and to do so we must breathe and eat, so are we a combination of what we eat and breathe? Here, we will consider this question, and the role in this respect of the AMP-activated protein kinase (AMPK). Emerging evidence suggests that AMPK facilitates central and peripheral reflexes that coordinate breathing and oxygen supply, and contributes to the central regulation of feeding and food choice. We propose, therefore, that oxygen supply to the body is aligned with not only the quantity we eat, but also nutrient-based diet selection, and that the cell-specific expression pattern of AMPK subunit isoforms is critical to appropriate system alignment in this respect. Currently available information on how oxygen supply may be aligned with feeding and food choice, or vice versa, through our motivation to breathe and select particular nutrients is sparse, fragmented and lacks any integrated understanding. By addressing this, we aim to provide the foundations for a clinical perspective that reveals untapped potential, by highlighting how aberrant cell-specific changes in the expression of AMPK subunit isoforms could give rise, in part, to known associations between metabolic disease, such as obesity and type 2 diabetes, sleep-disordered breathing, pulmonary hypertension and acute respiratory distress syndrome.

Analysis of genes within the schizophrenia-linked 22q11.2 deletion identifies interaction of night owl/LZTR1 and NF1 in GABAergic sleep control

The human 22q11.2 chromosomal deletion is one of the strongest identified genetic risk factors for schizophrenia. Although the deletion spans a number of known genes, the contribution of each of these to the 22q11.2 deletion syndrome (DS) is not known. To investigate the effect of individual genes within this interval on the pathophysiology associated with the deletion, we analyzed their role in sleep, a behavior affected in virtually all psychiatric disorders, including the 22q11.2 DS. We identified the gene LZTR1 (night owl, nowl) as a regulator of night-time sleep in Drosophila. In humans, LZTR1 has been associated with Ras-dependent neurological diseases also caused by Neurofibromin-1 (Nf1) deficiency. We show that Nf1 loss leads to a night-time sleep phenotype nearly identical to that of nowl loss and that nowl negatively regulates Ras and interacts with Nf1 in sleep regulation. Furthermore, nowl is required for metabolic homeostasis, suggesting that LZTR1 may contribute to the genetic susceptibility to obesity associated with the 22q11.2 DS. Knockdown of nowl or Nf1 in GABA-responsive sleep-promoting neurons elicits the sleep phenotype, and this defect can be rescued by increased GABA_A receptor signaling, indicating that Nowl regulates sleep through modulation of GABA signaling. Our results suggest that nowl/LZTR1 may be a conserved regulator of GABA signaling important for normal sleep that contributes to the 22q11.2 DS.

Schizophrenia is a devastating mental disorder with a large genetic component to disease predisposition. One of the strongest genetic risk factors for this disorder is a relatively small genetic deletion of 43 genes on the 22^nd chromosome, called 22q11.2, which confers about a 25% risk of schizophrenia development. However, it is likely that only some of these deleted genes affect disease risk, so we tested most of them individually. One of the main symptoms of schizophrenia is disturbed sleep. Sleep is an evolutionarily conserved behavior that can be easily studied in the fruit fly Drosophila melanogaster, so we investigated the effect on sleep of blocking expression of the fly homologs of most of the 22q11.2 genes and identified the gene LZTR1 (night owl, nowl) as an important sleep regulator. We found that Nowl/LZTR1 is required for inhibition of the Ras pathway and interacts genetically with the Ras inhibitor NF1. Nowl/LZTR1 appears to function in sleep by modulating inhibitory GABA signaling, which is affected in schizophrenia. Thus, this gene may underlie some of the phenotypes of the human schizophrenia-risk deletion.