Pinpointing the locus of GABAergic vulnerability in Alzheimer's disease

Parvalbumin Interneuron Dysfunction in Neurological Disorders: Focus on Epilepsy and Alzheimer's Disease

Parvalbumin expressing (PV+) GABAergic interneurons are fast spiking neurons that provide powerful but relatively short-lived inhibition to principal excitatory cells in the brain. They play a vital role in feedforward and feedback synaptic inhibition, preventing run away excitation in neural networks. Hence, their dysfunction can lead to hyperexcitability and increased susceptibility to seizures. PV+ interneurons are also key players in generating gamma oscillations, which are synchronized neural oscillations associated with various cognitive functions. PV+ interneuron are particularly vulnerable to aging and their degeneration has been associated with cognitive decline and memory impairment in dementia and Alzheimer's disease (AD). Overall, dysfunction of PV+ interneurons disrupts the normal excitatory/inhibitory balance within specific neurocircuits in the brain and thus has been linked to a wide range of neurodevelopmental and neuropsychiatric disorders. This review focuses on the role of dysfunctional PV+ inhibitory interneurons in the generation of epileptic seizures and cognitive impairment and their potential as targets in the design of future therapeutic strategies to treat these disorders. Recent research using cutting-edge optogenetic and chemogenetic technologies has demonstrated that they can be selectively manipulated to control seizures and restore the balance of neural activity in the brains of animal models. This suggests that PV+ interneurons could be important targets in developing future treatments for patients with epilepsy and comorbid disorders, such as AD, where seizures and cognitive decline are directly linked to specific PV+ interneuron deficits.

Gene-expression profiling of individuals resilient to Alzheimer's disease reveals higher expression of genes related to metallothionein and mitochondrial processes and no changes in the unfolded protein response

Some individuals show a discrepancy between cognition and the amount of neuropathological changes characteristic for Alzheimer's disease (AD). This phenomenon has been referred to as 'resilience'. The molecular and cellular underpinnings of resilience remain poorly understood. To obtain an unbiased understanding of the molecular changes underlying resilience, we investigated global changes in gene expression in the superior frontal gyrus of a cohort of cognitively and pathologically well-defined AD patients, resilient individuals and age-matched controls (n = 11-12 per group). 897 genes were significantly altered between AD and control, 1121 between resilient and control and 6 between resilient and AD. Gene set enrichment analysis (GSEA) revealed that the expression of metallothionein (MT) and of genes related to mitochondrial processes was higher in the resilient donors. Weighted gene co-expression network analysis (WGCNA) identified gene modules related to the unfolded protein response, mitochondrial processes and synaptic signaling to be differentially associated with resilience or dementia. As changes in MT, mitochondria, heat shock proteins and the unfolded protein response (UPR) were the most pronounced changes in the GSEA and/or WGCNA, immunohistochemistry was used to further validate these processes. MT was significantly increased in astrocytes in resilient individuals. A higher proportion of the mitochondrial gene MT-CO1 was detected outside the cell body versus inside the cell body in the resilient compared to the control group and there were higher levels of heat shock protein 70 (HSP70) and X-box-binding protein 1 spliced (XBP1s), two proteins related to heat shock proteins and the UPR, in the AD donors. Finally, we show evidence for putative sex-specific alterations in resilience, including gene expression differences related to autophagy in females compared to males. Taken together, these results show possible mechanisms involving MTs, mitochondrial processes and the UPR by which individuals might maintain cognition despite the presence of AD pathology.

Amyloid Pathology Impairs Experience-Dependent Inhibitory Synaptic Plasticity

Alzheimer's disease patients and mouse models exhibit aberrant neuronal activity and altered excitatory-to-inhibitory synaptic ratio. Using multicolor two-photon microscopy, we test how amyloid pathology alters the structural dynamics of excitatory and inhibitory synapses and their adaptation to altered visual experience in vivo in the visual cortex. We show that the baseline dynamics of mature excitatory synapses and their adaptation to visual deprivation are not altered in amyloidosis. Likewise, the baseline dynamics of inhibitory synapses are not affected. In contrast, visual deprivation fails to induce inhibitory synapse loss in amyloidosis, a phenomenon observed in nonpathological conditions. Intriguingly, inhibitory synapse loss associated with visual deprivation in nonpathological mice is accompanied by subtle broadening of spontaneous but not visually evoked calcium transients. However, such broadening does not manifest in the context of amyloidosis. We also show that excitatory and inhibitory synapse loss is locally clustered under the nonpathological state. In contrast, a fraction of synapse loss is not locally clustered in amyloidosis, indicating an impairment in inhibitory synapse adaptation to changes in excitatory synaptic activity.

Fast-spiking parvalbumin-positive interneurons in brain physiology and Alzheimer's disease

Fast-spiking parvalbumin (PV) interneurons are inhibitory interneurons with unique morphological and functional properties that allow them to precisely control local circuitry, brain networks and memory processing. Since the discovery in 1987 that PV is expressed in a subset of fast-spiking GABAergic inhibitory neurons, our knowledge of the complex molecular and physiological properties of these cells has been expanding. In this review, we highlight the specific properties of PV neurons that allow them to fire at high frequency and with high reliability, enabling them to control network oscillations and shape the encoding, consolidation and retrieval of memories. We next discuss multiple studies reporting PV neuron impairment as a critical step in neuronal network dysfunction and cognitive decline in mouse models of Alzheimer's disease (AD). Finally, we propose potential mechanisms underlying PV neuron dysfunction in AD and we argue that early changes in PV neuron activity could be a causal step in AD-associated network and memory impairment and a significant contributor to disease pathogenesis.

Amyloid pathology impairs experience-dependent inhibitory synaptic plasticity

Alzheimer's disease patients and mouse models exhibit aberrant neuronal activity and altered excitatory-to-inhibitory synaptic ratio. Using multicolor two-photon microscopy, we test how amyloid pathology alters the structural dynamics of excitatory and inhibitory synapses and their adaptation to altered visual experience in vivo in the visual cortex. We show that the baseline dynamics of mature excitatory synapses and their adaptation to visual deprivation are not altered in amyloidosis. Likewise, the baseline dynamics of inhibitory synapses are not affected. In contrast, visual deprivation fails to induce inhibitory synapse loss in amyloidosis, a phenomenon observed in nonpathological conditions. Intriguingly, inhibitory synapse loss associated with visual deprivation in nonpathological mice is accompanied by the broadening of spontaneous but not visually evoked calcium transients. However, such broadening does not manifest in the context of amyloidosis. We also show that excitatory and inhibitory synapse loss is locally clustered under the nonpathological state. In contrast, a fraction of synapse loss is not locally clustered in amyloidosis, indicating an impairment in inhibitory synapse adaptation to changes in excitatory synaptic activity.

Single-cell sequencing of entorhinal cortex reveals widespread disruption of neuropeptide networks in Alzheimer's disease

INTRODUCTION

Abnormalities of neuropeptides (NPs) that play important roles in modulating neuronal activities are commonly observed in Alzheimer's disease (AD). We hypothesize that NP network disruption is widespread in AD brains.

METHODS

Single-cell transcriptomic data from the entorhinal cortex (EC) were used to investigate the NP network disruption in AD. Bulk RNA-sequencing data generated from the temporal cortex by independent groups and machine learning were employed to identify key NPs involved in AD. The relationship between aging and AD-associated NP (ADNP) expression was studied using GTEx data.

RESULTS

The proportion of cells expressing NPs but not their receptors decreased significantly in AD. Neurons expressing higher level and greater diversity of NPs were disproportionately absent in AD. Increased age coincides with decreased ADNP expression in the hippocampus.

DISCUSSION

NP network disruption is widespread in AD EC. Neurons expressing more NPs may be selectively vulnerable to AD. Decreased expression of NPs participates in early AD pathogenesis. We predict that the NP network can be harnessed for treatment and/or early diagnosis of AD.

Alzheimer's Disease: Insights from Large-Scale Brain Dynamics Models

Alzheimer's disease (AD) is a degenerative brain disease, and the condition is difficult to assess. In the past, numerous brain dynamics models have made remarkable contributions to neuroscience and the brain from the microcosmic to the macroscopic scale. Recently, large-scale brain dynamics models have been developed based on dual-driven multimodal neuroimaging data and neurodynamics theory. These models bridge the gap between anatomical structure and functional dynamics and have played an important role in assisting the understanding of the brain mechanism. Large-scale brain dynamics have been widely used to explain how macroscale neuroimaging biomarkers emerge from potential neuronal population level disturbances associated with AD. In this review, we describe this emerging approach to studying AD that utilizes a biophysically large-scale brain dynamics model. In particular, we focus on the application of the model to AD and discuss important directions for the future development and analysis of AD models. This will facilitate the development of virtual brain models in the field of AD diagnosis and treatment and add new opportunities for advancing clinical neuroscience.