Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks.
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ABSTRACT:
SUBMITTER: Puppo F
PROVIDER: S-EPMC8323822 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We systematically compare strengths and weaknesses of two methods that can be used to quantify causal links between time series: Granger-causality and Bivariate Phase Rectified Signal Averaging (BPRSA). While a statistical test method for Granger-causality has already been established, we show that BPRSA causality can also be probed with existing statistical tests. Our results indicate that more data or stronger interactions are required for the BPRSA method than for the Granger-causality method to detect an existing link. Furthermore, the Granger-causality method can distinguish direct causal links from indirect links as well as links that arise from a common source, while BPRSA cannot. However, in contrast to Granger-causality, BPRSA is suited for the analysis of non-stationary data. We demonstrate the practicability of the Granger-causality method by applying it to polysomnography data from sleep laboratories. An algorithm is presented, which addresses the stationarity condition of Granger-causality by splitting non-stationary data into shorter segments until they pass a stationarity test. We reconstruct causal networks of heart rate, breathing rate, and EEG amplitude from young healthy subjects, elderly healthy subjects, and subjects with obstructive sleep apnea, a condition that leads to disruption of normal respiration during sleep. These networks exhibit differences not only between different sleep stages, but also between young and elderly healthy subjects on the one hand and subjects with sleep apnea on the other hand. Among these differences are 1) weaker interactions in all groups between heart rate, breathing rate and EEG amplitude during deep sleep, compared to light and REM sleep, 2) a stronger causal link from heart rate to breathing rate but disturbances in respiratory sinus arrhythmia (breathing to heart rate coupling) in subjects with sleep apnea, 3) a stronger causal link from EEG amplitude to breathing rate during REM sleep in subjects with sleep apnea. The Granger-causality method, although initially developed for econometric purposes, can provide a quantitative, testable measure for causality in physiological networks.
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Project description:BackgroundTuberous sclerosis complex (TSC) is a rare genetic multisystemic disorder resulting from autosomal dominant mutations in the TSC1 or TSC2 genes. It is characterised by hyperactivation of the mechanistic target of rapamycin complex 1 (mTORC1) pathway and has severe neurodevelopmental and neurological components including autism, intellectual disability and epilepsy. In human and rodent models, loss of the TSC proteins causes neuronal hyperexcitability and synaptic dysfunction, although the consequences of these changes for the developing central nervous system are currently unclear.MethodsHere we apply multi-electrode array-based assays to study the effects of TSC2 loss on neuronal network activity using autism spectrum disorder (ASD) patient-derived iPSCs. We examine both temporal synchronisation of neuronal bursting and spatial connectivity between electrodes across the network.ResultsWe find that ASD patient-derived neurons with a functional loss of TSC2, in addition to possessing neuronal hyperactivity, develop a dysfunctional neuronal network with reduced synchronisation of neuronal bursting and lower spatial connectivity. These deficits of network function are associated with elevated expression of genes for inhibitory GABA signalling and glutamate signalling, indicating a potential abnormality of synaptic inhibitory-excitatory signalling. mTORC1 activity functions within a homeostatic triad of protein kinases, mTOR, AMP-dependent protein Kinase 1 (AMPK) and Unc-51 like Autophagy Activating Kinase 1 (ULK1) that orchestrate the interplay of anabolic cell growth and catabolic autophagy while balancing energy and nutrient homeostasis. The mTOR inhibitor rapamycin suppresses neuronal hyperactivity, but does not increase synchronised network activity, whereas activation of AMPK restores some aspects of network activity. In contrast, the ULK1 activator, LYN-1604, increases the network behaviour, shortens the network burst lengths and reduces the number of uncorrelated spikes.LimitationsAlthough a robust and consistent phenotype is observed across multiple independent iPSC cultures, the results are based on one patient. There may be more subtle differences between patients with different TSC2 mutations or differences of polygenic background within their genomes. This may affect the severity of the network deficit or the pharmacological response between TSC2 patients.ConclusionsOur observations suggest that there is a reduction in the network connectivity of the in vitro neuronal network associated with ASD patients with TSC2 mutation, which may arise via an excitatory/inhibitory imbalance due to increased GABA-signalling at inhibitory synapses. This abnormality can be effectively suppressed via activation of ULK1.
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