Understanding Systems-Level Mechanisms of Age-Related Cognitive Decline
The number of Americans over age 65 exceeds 54 million with a large proportion of these older adults experiencing cognitive decline that interferes with their quality of life. The current estimated costs for patient care involving Alzheimer’s disease and related dementias that impact older adults in the United States is $277 billion and predicted to exceed $1 trillion by 2050. Thus, developing new strategies for improving late life cognition is vital. Both changes in the activity properties of individual neurons in the medial temporal lobe and prefrontal cortex, as well as aberrant organization and dynamics of functional connectivity across the brain have been linked to cognitive decline in old age and early Alzheimer’s disease. Notably, however, differences in individual neurons that are the building blocks of network functional connectivity have not been linked to largescale changes in the distributed brain networks that support cognition. Bridging spatial and temporal scales to understand the mechanisms of cognitive aging is critical for developing targeted interventions to improve cognitive function in aging and Alzheimer’s disease. This is highlighted by the well-documented observation that aging is associated with a host of regionally-specific neurobiological alterations that do not correlate across different brain regions. For example, the aged brain is characterized by both decreased neuronal excitability in the prefrontal (Wang et al., 2011; Banuelos et al., 2014) and perirhinal cortices (Burke et al., 2014), and increased neuronal excitability in subregions of the hippocampus (Wilson et al., 2005; Yassa et al., 2010). Thus, targeted interventions that restore normal activity in one brain region may exacerbate aberrant activity in another, hindering the restoration of function at the behavioral level. As such, interventions that target the optimization of memory networks rather than discrete brain regions may be more effective for improving cognitive outcomes in older adults. The long-term goal of this area of research in the Brain Organization and Aging Laboratory is to determine the mechanisms of altered network-level interactions that underlie cognitive dysfunction in advanced age and Alzheimer’s disease. To do this we use multi-modal imaging techniques that include, immediate-early gene expression analysis in anatomical defined circuits, fluorescence microscopy, MRI and 3D light sheet imaging, as well as in vivo neurophysiology.
Metabolic Interventions for Enhancing Cognitive Resilience in Aging and Alzheimer’s Disease.
While the effects of old age on activity dynamics, receptor distribution, synapse number and morphology, and gene expression are not consistent across different brain regions, the ability to use glucose for energy production ubiquitously declines across the brain in old age and in Alzheimer’s disease. Moreover, diet is a modifiable lifestyle factor that could be leveraged as an accessible intervention to our rapidly expanding population of older adults. Thus, a number of ongoing projects in the lab are aimed at investigating the mechanisms by which ketogenic diets, exogenous ketone supplementation, or intermittent fasting alter energy metabolism across the brain and testing if these interventions can improve cognition in pre-clinical models of aging and Alzheimer’s disease. The rationale for these experiments is that improving brain energy metabolism may be a mechanism for globally optimizing brain circuits to alleviate cognitive aging.
Reverse Translating Neuropsychological Evaluation To Rodent Models To Evaluate Cognitive Aging, Brain Injury, And Neurodegeneration.
While current cognitive assessments used to diagnose Alzheimer’s disease and other causes of cognitive impairment are fairly reliable (nearing ~80% accuracy), this reliability is largely attributable to the fact that diagnosis typically occurs after individuals experience marked, life-altering cognitive decline. In contrast, there is a growing appreciation that effective treatments for progressive diseases will require the ability to intervene before widespread brain pathology develops. Additionally, sensitive cognitive assessments can inform treatment efficacy for enhancing cognitive functioning in neurological conditions such as epilepsy, traumatic brain injury and mental health disorders. Hence, there is a critical need for improved diagnostic tools that detect the earliest manifestations of disease and other forms of cognitive impairment. To this end, several projects in the BOA lab are focused on developing, validating, and testing novel behavioral assays that are sensitive to detecting deficits associated with advanced age and various pathological conditions. Recently, a battery of these tests have been adapted to be carried out in rodent touchscreen chambers, offering a close parallel to neuropsychological assessment in humans, and an expansive ability to update task parameters and test stimuli.
Preclinical Assays of Hippocampal-Prefrontal Cortical Circuit Engagement for Application in Therapeutic Development.
The high failure rate of translating discovery science to positive clinical outcomes in the treatment of psychiatric diseases demonstrates the necessity of improving the efficiency and rigor of the therapeutic development pipeline. To this end, the critical importance of advancing the discovery of in vivo physiological and behavioral measures of the engagement of specific circuits for normal cognitive function has been acknowledged across funding initiatives. The hippocampus (HPC)-prefrontal cortical (PFC) circuit is critical for affective processing as well as higher cognitive functions and vulnerable in a number of mental health disorders. Although disrupted functional connectivity in the HPC-PFC circuit is a common feature of anxiety, bipolar disorder, schizophrenia, and autism, how local cellular interactions within this circuit manifest as large-scale temporal coordination to support higher cognitive functions remains unknown. Addressing this fundamental gap in our knowledge will establish a foundation for using circuit-based models for therapeutic target discovery and screening tools of novel drug efficacy. We hope to enhance the therapeutic development pipeline for mental illness treatment by optimizing, evaluating, and mechanistically testing neurophysiological and behavioral measures of HPC-PFC circuit engagement using behavior, neurophysiology, pharmacology, and AAV-mediated targeted manipulation.