Biology subjects

Alda, M.

Publications and source records attributed to Alda, M..

13 recordsLinked to original sources

bioRxiv2026

Neuronal secretome from bipolar patient-derived neurons alters network function and contains candidate biomarkers for diagnosis and lithium response

Delayed diagnosis and treatment are a major burden to patients with bipolar disorder. While lithium is the most effective treatment against mania, depressive episodes, and suicide, only 30% of patients respond to it fully. Currently there are no reliable methods to predict lithium responsiveness. To address these challenges, we aimed to identify potential diagnostic and treatment response biomarkers for BD, in addition furthering understanding of BD pathophysiology. Here, we leveraged human induced pluripotent stem cell (hiPSC) derived neurons from lithium responsive (LR), lithium non-responsive (LNR), and healthy age-matched controls (CTL). We found extracellular vesicle (EV) cargos from hiPSC-derived neurons are indicative of disease state and treatment-response. Unbiased proteomic and miRNA profiling identified 10 proteins and 13 miRNAs that were differentially expressed in BD EVs relative to CTL, as well as distinct molecular signatures separating LR ad LNR groups. These differences converged on pathways related to synaptic function, neurotrophic signalling, and cellular stress responses. Additionally, we found the BD neuronal secretome alters activity in non-BD neuronal networks. Chronic treatment of CTL cultures with BD neuron-conditioned media modified the proportion of active neurons and the frequency and amplitude of calcium transients in individual neurons. We demonstrate that neuronal EVs contain molecular signatures of disease state and treatment response in BD and identify the BD secretome as an active regulator of neuronal network homeostasis. This study provides novel insights into the pathophysiology of BD and candidate biomarkers for personalized BD diagnosis and treatment selection.

neuroscience↗

bioRxiv2025

Divergent Excitability of GABAergic Neurons Derived from Bipolar Disorder Patients Shapes Energy Shifts of Network Dynamics, possibly mimicking mania and depression

Bipolar disorder (BD) is characterized by fluctuating mood states, yet the cellular and circuit-level mechanisms distinguishing lithium-responsive (LR) from non-responsive (NR) patients remain elusive. We derived dentate gyrus granule neurons and GABAergic interneurons from induced pluripotent stem cells (iPSCs) of BD patients stratified by lithium response, and from healthy controls. Using patch-clamp electrophysiology, we assessed intrinsic excitability. We further developed a computational model simulating large-scale neuronal networks based on patient-derived electrophysiological properties and ion channel conductance distributions. Granule neurons from both LR and NR patients exhibited hyperexcitability compared to controls. However, GABAergic neurons showed a striking divergence: LR neurons were hyperexcitable, while NR neurons were hypoexcitable. Transcriptomic profiling revealed distinct molecular signatures between NR and LR neurons, including dysregulation of GABA receptor genes (GABRR1). Computational simulations over 10,000 iterations, mimicking long-term network activity, revealed that dentate granule neuron changes alone failed to recapitulate netwrok shifts between global hyperexcitability and global hypoexcitability. Networks incorporating only granule neuron phenotypes entered persistent hyper- or hypoactive states, depending on lithium response. Remarkably, when GABAergic neuron phenotypes were added to the model, both LR and NR networks exhibited spontaneous transitions between high and low activity states, that may be associated with the mood episodes that the patients exhibit. Control networks did not show such bistability. We, therefore, conclude that GABAergic neuronal excitability is a key determinant of lithium responsiveness in BD and critically shapes the emergence of state-shift dynamics in neural networks. These findings suggest that restoring excitatory/inhibitory (E/I) balance via targeted modulation of interneuron function may offer novel therapeutic avenues for BD.

neuroscience↗

bioRxiv2025

Lithium partially rescues gene expression and enhancer activity from heterozygous knockout of AKAP11 while inducing novel differential changes

Bipolar disorder (BD) is a complex psychiatric condition usually requiring long-term treatment. Lithium (Li) remains the most effective mood stabilizer for BD, yet it benefits only a subset of patients, and its precise mechanism of action remains elusive. Exome sequencing has identified AKAP11 (A-kinase anchoring protein 11) as a shared risk gene for BD and schizophrenia (SCZ). Given that both the AKAP11-Protein Kinase A (PKA) complex and Li target and inhibit Glycogen Synthase Kinase-3 beta (GSK3{beta}), we hypothesize that Li may partially normalize the transcriptomic and/or epigenomic alterations observed in heterozygous AKAP11-knockout (Het-AKAP11-KO) iPSC-derived neurons. In this study, we employed genome-wide approaches to assess the effects of Li on the transcriptome and epigenome of human iPSC-derived Het-AKAP11-KO neuronal culture. We show that chronic Li treatment in this cellular model upregulates key pathways that were initially downregulated by Het-AKAP11-KO, several of which have also been reported as downregulated in synapses of BD and SCZ post-mortem brain tissues. Moreover, we demonstrated that Li treatment partially rescues certain transcriptomic alterations resulting from Het-AKAP11-KO, bringing them closer to the WT state. We suggest two possible mechanisms underlying these transcriptomic effects: (1) Li modulates histone H3K27ac levels at intergenic and intronic enhancers, influencing enhancer activity and transcription factor binding, and (2) Li enhances GSK3{beta} serine 9 phosphorylation, impacting WNT/{beta}-catenin signaling and downstream transcription. These findings underscore Lis potential as a therapeutic agent for BD and SCZ patients carrying AKAP11 loss-of-function variants or exhibiting similar pathway alterations to those observed in Het-AKAP11-KO models.

genomics↗

bioRxiv2024

Predicting Suicide Risk in Bipolar Disorder patients from Lymphoblastoid Cell Lines genetic signatures

This research investigates the genetic signatures associated with a high risk of suicide in Bipolar disorder (BD) patients through RNA sequencing analysis of lymphoblastoid cell lines (LCLs). By identifying differentially expressed genes (DEGs) and their enrichment in pathways and disease associations, we uncover insights into the molecular mechanisms underlying suicidal behavior. LCL gene expression analysis reveals significant enrichment in pathways related to primary immunodeficiency, ion channel, and cardiovascular defects. Notably, genes such as LCK, KCNN2, and GRIA1 emerged as pivotal in these pathways, suggesting their potential roles as biomarkers. Machine learning models trained on a subset of the patients and then tested on other patients demonstrate high accuracy in distinguishing low and high-risk of suicide in BD patients. Moreover, the study explores the genetic overlap between suicide-related genes and several psychiatric disorders. This comprehensive approach enhances our understanding of the complex interplay between genetics and suicidal behavior, laying the groundwork for future prevention strategies.

neuroscience↗

bioRxiv2024

The Effects of Bipolar Disorder Granule Cell Hyperexcitability and Lithium Therapy on Pattern Separation in a Computational Model of the Dentate Gyrus

Induced pluripotent stem cell (iPSC) derived hippocampal dentate granule cell-like neurons from individuals with bipolar disorder (BD) are hyperexcitable and more spontaneously active relative to healthy control (HC) neurons. These abnormalities are normalised after the application of lithium in neurons derived from lithium responders (LR) only. How these abnormalities impact hippocampal microcircuit computation is not understood. We aimed to investigate the impacts of BD-associated abnormal granule cell (GC) activity on pattern separation (PS) using a computational model of the dentate gyrus (DG). We used parameter optimization to fit the parameters of biophysically realistic granule cell (GC) models to electrophysiological data from iPSC GCs from patients with BD. These cellular models were incorporated into DG networks to assess impacts on PS using an adapted spatiotemporal task. Relationships between BD, lithium and spontaneous activity were analysed using linear mixed effects modelling. Lithium and BD negatively impacted PS, consistent with clinical reports of cognitive slowing and memory impairment during lithium therapy. By normalising spontaneous activity levels, lithium improved PS performance in LRs only. Improvements in PS after lithium therapy in LRs may therefore be attributable to the normalisation of spontaneous activity levels, rather than reductions in GC intrinsic excitability as we hypothesised. Our results agree with a hypothesised relationship between behavioural mnemonic discrimination and DG PS, as previous research has suggested that mnemonic discrimination improves after lithium therapy in lithium responders only. Our work can be expanded on in the future by simulating the effects of lithium-induced neurogenesis on PS.

neuroscience↗

bioRxiv2024

Transcriptomic and epigenomic consequences of heterozygous loss of function mutations in AKAP11, the first large-effect shared risk gene for bipolar disorder and schizophrenia

The gene A-kinase anchoring protein 11 (AKAP11) recently emerged as a shared risk factor between bipolar disorder and schizophrenia, driven by large-effect loss-of-function (LoF) variants. Recent research has uncovered the neurophysiological characteristics and synapse proteomics profile of Akap11-mutant mouse models. Considering the role of AKAP11 in binding cAMP-dependent protein kinase A (PKA) and mediating phosphorylation of numerous substrates, such as transcription factors and epigenetic regulators, and given that chromatin alterations have been implicated in the brains of patients with bipolar disorder and schizophrenia, it is crucial to uncover the transcriptomic and chromatin dysregulations following the heterozygous knockout of AKAP11, particularly in human neurons. In this study, we use genome-wide approaches to investigate such aberrations in human induced pluripotent stem cell (iPSC)-derived neurons. We show the impact of heterozygous AKAP11 LoF mutations on the gene expression landscape and profile the methylomic and acetylomic modifications. Altogether we highlight the involvement of aberrant activity of intergenic and intronic enhancers, which are enriched in PBX homeobox 2 (PBX2) and Nuclear Factor-1 (NF1) known binding motifs, respectively, in transcription dysregulations of genes functioning as DNA-binding transcription factors, actin and cytoskeleton regulators, and cytokine receptors, as well as genes involved in G-protein-coupled receptors (GPCRs) binding and signaling. A better understanding of the dysregulations resulting from haploinsufficiency in AKAP11 improves our knowledge of the biological roots and pathophysiology of BD and SCZ, paving the way for better therapeutic approaches.

genomics↗

bioRxiv2023

The Impact of Electrophysiological Diversity on Pattern Completion in Lithium Nonresponsive Bipolar Disorder: A Computational Modelling Approach

Patients with bipolar disorder (BD) demonstrate episodic memory deficits, which may be hippocampal-dependent and may be attenuated in lithium responders. Induced pluripotent stem-cell derived CA3 pyramidal cell-like neurons show significant hyperexcitability in lithium responsive BD patients, while lithium nonresponders show marked variance in hyperexcitability. We hypothesize that this variable excitability will impair episodic memory recall, as assessed by cued retrieval (pattern completion) within a computational model of the hippocampal CA3. We simulated pattern completion tasks using a computational model of the CA3 with different degrees of pyramidal cell excitability variance. Since pyramidal cell excitability variance naturally leads to a mix of hyperexcitability and hypoexcitability, we also examined what fraction (hyper-vs. hypoexcitable) was predominantly responsible for pattern completion errors in our model. Pyramidal cell excitability variance impaired pattern completion (linear model {beta}=-1.94, SE=0.01, p<0.001). The effect was invariant to the number of patterns stored in the network, as well as general inhibitory tone and pyramidal cell sparsity in the network. Excitability variance, and more specifically hyperexcitability, increased the number of spuriously active neurons, increasing false alarm rates and producing pattern completion deficits. Excessive inhibition also induces pattern completion deficits by limiting the number of correctly active neurons during pattern retrieval. Excitability variance in CA3 pyramidal cell-like neurons observed in lithium nonresponders may predict pattern completion deficits in these patients. These cognitive deficits may not be fully corrected by medications that minimize excitability. Future studies should test our predictions by examining behavioural correlates of pattern completion in lithium responsive and nonresponsive BD patients. Author summaryPatients with bipolar disorder experience debilitating cognitive impairments whose mechanisms are unknown, and these deficits may be greater in patients who do not respond to the mood stabilizer lithium. Studies using induced pluripotent stem cell (iPSC) derived neurons have suggested that CA3 pyramidal cells in lithium nonresponders may have wide diversity of excitability. Our study examines how this diversity of neuronal excitability would impact the computation of pattern completion in the CA3. In a computational model of the CA3, we found that variance in pyramidal cell excitability reliably impaired pattern completion abilities. Furthermore, we found that both the hyperexcitable and hypoexcitable fractions of cells were each responsible for distinct pattern completion errors, depending on the overall level of network inhibition. These results suggest that lithium nonresponsive patients with bipolar disorder will have worse performance on behavioural tasks that are sensitive to pattern completion, potentially including cued recall paradigms. Our results also suggest that mood stabilizers that simply reduce cellular hyperexcitability may not be sufficient to correct micro-circuit level computations in lithium nonresponsive bipolar disorder. Rather, these patients may require development of mood stabilizers that normalize the distribution of neuronal hyperexcitability among CA3 pyramidal cells.

neuroscience↗

bioRxiv2023

Molecular signatures of hyperexcitability and lithium responsiveness in bipolar disorder patient neurons provide alternative therapeutic strategies.

Bipolar disorder (BD) is a multifactorial psychiatric illness affecting about 1% of the world population. The first line treatment, lithium (Li), is effective in only a subset of patients and its mechanism of action remains largely elusive. In the present study, we used iPSC-derived neurons from BD patients responsive (LR) or not (LNR) to lithium and combined electrophysiology, calcium imaging, biochemistry, transcriptomics, and phosphoproteomics to report mechanistic insights into neuronal hyperactivity in BD, and Lis mode of action. We show a selective rescue of neuronal hyperactivity by Li in BD LR neurons through changes in Na+ currents. The whole transcriptome sequencing revealed altered gene expression in BD neurons in pathways related to glutamatergic transmission, and Li selectively altered those involved in cell signaling and ion transport/channel activity. We found the therapeutic effect of Li in BD LR patients was associated with Akt signaling and confirmed that an Akt activator mimics Li effect in BD LR neurons. Further, we showed that AMP-activated protein kinase (AMPK) reduces neural network activity and sodium currents in BD LNR patients. These findings suggest the potential for novel treatment strategies in BD, such as Akt activators in BD LR cases, and the use of AMPK activators for BD LNR patients.

neuroscience↗

bioRxiv2023

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individuals latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences. TeaserWe present a global effort to devise harmonization procedures necessary to meaningfully leverage big data.

neuroscience↗

bioRxiv2022

Information theory characteristics improve the prediction of lithium response in bipolar disorder patients using an SVM classifier

Bipolar disorder (BD) is a mood disorder with a high morbidity and death rate. Lithium (Li), a prominent mood stabilizer, is fully effective in roughly 30% of BD patients. The remaining patients respond partially or do not respond at all. Another drug used to treat BD patients is valproate (VPA). Plenty of efforts has been made to understand how these drugs affect the patients neurons. We have performed electrophysiological recordings in patient-derived dentate gyrus (DG) granule neurons for three groups: control individuals, BD patients who respond to Li treatment (LR), and BD patients who do not respond to Li treatment (NR). The recordings were analyzed by the statistical tools of modern information theory, which enabled us to recognize new relationships between the electrophysiological features. These added features included the entropy of several electrophysiological measurements and the mutual information between different types of electrophysiological measurements. Information theory features provided further knowledge about the distribution of the electrophysiological entities, which improved basic classification schemes. These newly added features enabled a significant improvement in our ability to distinguish the BD patients from the control individuals (an improvement from 60% accuracy to 74% accuracy) and the Li responders from the non-responders in the BD population using Support Vector Machine (SVM) classification algorithms (an improvement from 81% accuracy to 99% accuracy). These new tools showed that LR neurons are less distinguishable from control neurons after Li treatment but not after VPA treatment, whereas NR neurons become more distinguishable from control neurons after Li treatment.

neuroscience↗

bioRxiv2020

Circadian rhythms in bipolar disorder patient-derived neurons predict lithium response

Bipolar disorder (BD) is a neuropsychiatric disorder with genetic risk factors defined by recurrent episodes of mania/hypomania, depression and circadian rhythm abnormalities. While lithium is an effective drug for BD, 30-40% of patients fail to respond adequately to treatment. Previous work has demonstrated that lithium affects the expression of "clock genes" and that lithium responders (Li-R) can be distinguished from non-responders (Li-NR) by differences in circadian rhythms. However, rhythm abnormalities in BD have not been evaluated in neurons and it is unknown if neuronal rhythms differ between Li-R and Li-NR. We used induced pluripotent stem cells (iPSCs) to culture neuronal precursor cells (NPC) and glutamatergic neurons from BD patients and controls. We identified strong circadian rhythms in Per2-luc expression in NPCs and neurons from controls and Li-R. NPC rhythms in Li-R had a shorter circadian period. Li-NR rhythms were low-amplitude and profoundly weakened. In NPCs and neurons, expression of PER2 was higher in both BD groups compared to controls. In neurons, PER2 protein expression was higher in BD than controls, especially in Li-NR samples. In single cells, NPC and neuron rhythms in both BD groups were desynchronized compared to controls. Lithium lengthened period in Li-R and control neurons but failed to alter rhythms in Li-NR. In contrast, temperature entrainment increased amplitude across all groups, and partly restored rhythms in Li-NR neurons. We conclude that neuronal circadian rhythm abnormalities are present in BD and most pronounced in Li-NR. Rhythm deficits in BD may be partly reversible through stimulation of entrainment pathways.

neuroscience↗

bioRxiv2020

Chronic lithium treatment alters the excitatory/inhibitory balance of synaptic networks and reduces mGluR5-PKC signaling

Bipolar disorder (BD) is characterized by cyclical alternations between mania and depression, often comorbid with psychosis, and suicide. The mood stabilizer lithium, compared to other medications, is the most efficient treatment for prevention of manic and depressive episodes. The pathophysiology of BD, and lithiums mode of action, are yet to be fully understood. Evidence suggests a change in the balance of excitatory/inhibitory activity, favouring excitation in BD. Here, we sought to establish a holistic appreciation of the neuronal consequences of lithium exposure in mouse cortical neurons and identify underlying mechanisms. We found that chronic (but not acute) lithium treatment significantly reduced intracellular calcium flux, specifically through the activation of the metabotropic glutamatergic receptor mGluR5. This was associated with altered phosphorylation of PKC and GSK3 kinases, reduced neuronal excitability, and several alterations to synapse function. Consequently, lithium treatment shifts the excitatory/inhibitory balance in the network toward inhibition. Together, the results revealed how lithium dampens neuronal excitability and glutamatergic network activity, which are predicted to be overactive in the manic phase of BD. Our working model of lithium action enables the development of targeted strategies to restore the balance of overactive networks, mimicking the therapeutic benefits of lithium, but with reduced toxicity.

neuroscience↗

bioRxiv2019

Asymmetrical reliability of the Alda Score favours a dichotomous representation of lithium responsiveness

The Alda score is commonly used to quantify lithium responsiveness in bipolar disorder. Most often, this score is dichotomized into "responder" and "non-responder" categories, respectively. This practice is often criticized as inappropriate, since continuous variables are thought to invariably be "more informative" than their dichotomizations. We therefore investigated the degree of informativeness across raw and dichotomized versions of the Alda score, using data from a published study of the scales inter-rater reliability (n=59 raters of 12 standardized vignettes each). After learning a generative model for the relationship between observed and ground truth scores (the latter defined by a consensus rating of the 12 vignettes), we show that the dichotomized scale is more robust to inter-rater disagreement than the raw 0-10 scale. Further theoretical analysis shows that when a measures reliability is stronger at one extreme of the continuum--a scenario which has received little-to-no statistical attention, but which likely occurs for the Alda score [≥] 7--dichotomization of a continuous variable may be more informative concerning its ground truth value, particularly in the presence of noise. Our study suggests that research employing the Alda score of lithium responsiveness should continue using the dichotomous definition, particularly when data are sampled across multiple raters.

pharmacology and toxicology↗