Roberta Diaz Brinton, PhD

Director & Regents Professor

Alzheimer’s Disease (AD) is the leading age-associated neurodegenerative disorder, affecting more than 50 million people around the world. The hallmark pathologies of AD are a decline in brain glucose metabolism and mitochondrial function, beta amyloid plaques, neurofibrillary tangles, inflammation and brain atrophy. The Alzheimer’s risk gene, ApoE4, can accelerate and exacerbate the course of the disease.

By focusing on women, who are most affected by the disease, we discovered that the brain undergoes a series of transitions starting early in the aging process that spans years or the pre-clinical or prodromal stage of AD. The long road to age-associated Alzheimer’s starts with a rise in brain inflammation and concomitant decline in glucose metabolism, followed by a development of the hallmark pathologies of Alzheimer’s.

Advancing our precision approach to Alzheimer’s, we use health informatics combined with insights from basic disease biology to identify clinically relevant strategies to detect high-risk phenotypes and develop precision therapeutics that target identified causal mechanisms. Using a big data approach, we are identifying a common bioenergetic dysregulation across diseases, suggesting a common initiating mechanism for age-associated neurodegenerative disease.

Kathleen Rodgers, Ph.D.

Associate Director, Translational Neuroscience

Multiple Sclerosis (MS) affects 2.3 million persons globally, diagnosis after age 50 means rapid deterioration and few treatments to slow the disease progression. A chronic demyelinating disease, MS is marked by progressive loss of neuronal function and arise from attacks of the immune system on myelin sheaths responsible for the conduction of neuronal impulses. The pathology of MS is driven by chronic inflammation and oxidative stress; features common to all age-related neurodegenerative disorders in the CIBS portfolio.

Current MS therapeutics target the immune system to reduce injury to the myelin sheath but have side effects due to their non-specific modulation of immune function.

We have developed a suite of compounds that target both inflammation and oxidative stress, while simultaneously stimulating the brain’s own regenerative mechanisms.

In preclinical animal studies, our peptides were able to reduce inflammation, lesion size and clinical symptoms of MS. Building on our legacy of translation with A(1-7) and Nle3 (1-7) that includes the preclinical characterization, manufacturing, preclinical safety through to Phase 2 and Phase 3 clinical trials, we are expecting to launch a clinical trial in less than three (3) years.

In parallel, together with other CIBS faculty, we are pioneering the developments of patient-specific nucleic acid aptamers capable of neutralizing pathological antibodies and T cells in MS. Targeting common initiating mechanism across diseases showcases how the power of systems-level thinking inherent to the CIBS mission is allowing us to broaden the therapeutic horizon of these drugs.

Fei Yin, Ph.D.

Assistant Director, Translational Neuroscience

By weight, the brain is the body’s most energetically expensive organ, accounting for nearly a quarter of all oxygen and glucose consumption. This demand for fuel renders the brain particularly vulnerable to even a modest decline in its bioenergetic capacity. New research is now suggesting that changes in energy metabolism may be a common initiating factor in the emergence of age-associated neurodegenerative disorders.

Mitochondria, the cellular power generators, are unique in that they harbor their own genome, which encodes the most essential components to perform bioenergetic transduction — making them a natural target for intervention. Through deep mitochondrial genotyping and phenotyping of aged and Alzheimer’s disease models, we discovered that the integrity of the mitochondrial genome is critical in maintaining the brain bioenergetic function.

Bioenergetic dysregulation often occurs in parallel with widespread neuroinflammation: how these processes interact is unclear. We are delineating the crosstalk between brain energy metabolism and chronic neuroinflammation, focusing on cellular redox dysregulation and lipid dyshomeostasis as candidate-bridging factors and potential therapeutic targets for age-associated neurodegenerative disorders.

We are leveraging these fundamental insights into the pathophysiology of disease to develop animal and cellular models that combine targeted disruptions of the mitochondrial genome with genetic risk factors for Alzheimer’s, Parkinson’s, ALS and MS. By more closely mirroring human disease, we are able to improve the predictive translational validity of drug development assays based on these models.

Rui Chang, Ph.D.

Associate Director, Computational Systems Biology

Neurodegenerative diseases show a striking phenotypic diversity driven by a complex array of factors, including genetics, aging, gender, environment and disease stage. To capture this complexity, we use predictive computational systems biology network models that hybridize novel causality inference (bottom-up) algorithms with conventional, top-down Bayesian networks. Through these models, we are able to integrate pan-omics, including genetics, genomics, proteomics, metabolomics, phenotypic, clinical and longitudinal data, allowing us to discover causal relationships hidden in the diseases’ multifactorial etiology.

When applied to data from Alzheimer’s patients stratified by genetic risk factors, gender and disease stage, our approach identified sex-specific metabolic markers of disease progression. In males, these metabolic networks emerged as dysregulation of brain-chain amino acids, while females showed decreases in a network of phosphatidylcholines.

Moving from the patient level to the single cell level, we were able to use our models to integrate multi-scale omics data from specific cell types in central nerve systems. Insights derived from these analyses are allowing us to identify and validate key driver therapeutics in a cell type-specific way across the spectrum of age-associated neurodegenerative disorders.

Gerson Hernandez, MD, MPH

Senior Director, Clinical Operations

99.6% of clinical trials for age-associated neurodegenerative diseases result in failure. Across the hundreds of clinical trials, only a few therapies aimed at symptomatic relief have demonstrated efficacy and none have resulted in a cure. Historically, clinical trials that have used a one-size-fits-all approach, ignoring both disease complexity and their progressive nature.

A challenge to finding a cure for Alzheimer’s, Parkinson’s, Multiple Sclerosis and ALS requires clinical trials with large numbers of patients to ensure that even small therapeutic effects can be detected. Partnering with Critical Path Institute, we are leveraging biomarker data to power computational simulations of disease progression rates, allowing us to identify patient-specific transition states to refine windows of therapeutic opportunity and drive clinical trial recruitment.

Traditional clinical trials proceed linearly, from design to conduct to analysis. At CIBS, we are implementing adaptive trial designs that use interim data reports to add a “review-adapt” loop to the trials structure. Through careful a priori contingency mapping, we are able to implement changes to our designs based on the analyses of the recorded data, ensuring our trials produce the best possible data.

Adam Raikes, Ph.D.

Adam Raikes, Ph.D. is an Assistant Scientific Investigator at the Center for Innovation in Brain Science (CIBS) at the University of Arizona. With a background in sports medicine, mild traumatic brain injuries, neuroimaging, and sleep, he oversees neuroimaging projects for human and animal models of neurodegeneration. He is combining high resolution MRI, PET imaging, and emerging imaging technologies with cutting edge software tools to provide unique insights into brain structure and function in healthy and disease states.

Education: Ph.D. in Disability Disciplines from Utah State University

Francesca Vitali, Ph.D.

Francesca Vitali, Ph.D. is a Research Assistant Professor and Director of Bioinformatics in the Center for Innovation in Brain Science.

She is focused on the development of computational methods to support precision medicine, drug repurposing and poly-pharmacology. Her background includes data mining, statistics, graph theory, machine learning, artificial intelligence and data integration techniques. She has a long record of working in multi­disciplinary collaborative teams, including collaborations with international laboratories and pharmaceutical companies.

Education: Ph.D. in Bioinformatics and Biomedical Engineering from the University of Pavia, Italy.

Jean-Paul Wiegand, Ph.D.

Jean-Paul Wiegand, Ph.D. is the Preclinical Program Manager at the Center for Innovation in Brain Science. With a background in sleep and memory electrophysiology, high-throughput behavioral research, and Lean Six Sigma project management, he oversees the CIBS Behavioral Core. He is combining cutting edge genetics with inducible lifestyle factors to develop more accurate disease models.

Education: Ph.D. in Neuroscience from the University of Arizona.