Focus areas

Dr. Grinberg's Neurodegeneration and Sleep Pathology Lab at Mayo Clinic leads and collaborates on innovative research projects to advance the understanding, diagnosis and treatment of neurodegenerative diseases, especially Alzheimer's disease, frontotemporal dementia (FTD) and related tauopathies. Our work integrates advanced molecular, genetic and imaging techniques to uncover the mechanisms driving these diseases and to translate discoveries into better patient care.

Sleep, circadian rhythms and neurodegeneration

Our team explores how sleep and circadian rhythm disruptions are linked to neurodegenerative diseases, particularly tauopathies such as Alzheimer's disease and progressive supranuclear palsy. We use spatial transcriptomics and proteomics to map selective vulnerability in sleep-regulating brain regions.

Addressing sleep and circadian dysfunction may reduce symptom burden, delay institutionalization, and improve overall well-being for patients and caregivers.

Goals

  • Identify molecular pathways that make specific sleep or circadian nuclei vulnerable to tau pathology.
  • Understand how these changes contribute to sleep disturbances and disease progression.
  • Inform new strategies for improving sleep and quality of life in patients with dementia.

Principal investigator

Funding

  • National Institute on Aging
  • Rainwater Charitable Foundation

Leveraging atypical Alzheimer's disease to understand selective neuronal vulnerability

Research in this area focuses on why some brain regions and cell types are more vulnerable to tau pathology in young-onset Alzheimer's disease, which affects people age 65 and younger without known genetic mutations. We combine advanced neuropathology, single-cell transcriptomics and digital spatial profiling to map tau accumulation and microglial activation across different clinical syndromes, including people with typical amnestic presentations and atypical presentations.

By pinpointing the cells and pathways most affected in early-onset and atypical AD, we aim to enable earlier diagnosis, more accurate prognosis and the development of targeted therapies for patients with nonclassical forms of Alzheimer's disease.

Goals

  • Identify molecular and cellular signatures of vulnerability and resilience to tau pathology.
  • Understand how demographic factors such as age and sex, traumatic brain injury, and genetic risk modify disease patterns.
  • Reveal how microglial activation contributes to disease progression and clinical symptoms.

Principal investigators

Funding

  • National Institute on Aging

High-resolution histology to validate novel neuroimaging methods

Our lab is advancing imaging-based diagnostics for Alzheimer's disease and related tauopathies by validating neuroimaging signals against histological gold standards. We develop and apply high-resolution pipelines to coregister in vivo and ex vivo MRI and PET scans with histological data — including digital pathology quantification powered by the lab's proprietary convolution neural network, IHCNet. This enables voxel-by-voxel comparisons at unprecedented spatial resolution.

Through these efforts, we aim to enhance early detection, differential diagnosis and monitoring of disease progression, ultimately supporting more-personalized and more-effective treatment strategies for patients.

Goals

  • Improve the accuracy and specificity of imaging biomarkers for tau and amyloid pathology.
  • Evaluate the performance of tau PET tracers such as [18F]-AV-1451 across different tauopathies.
  • Inform the development and application of MRI-based techniques — for example, DECOMPOSE-QSM — to distinguish iron from protein aggregates in the brain.
  • Build a comprehensive imaging-histology database to support biomarker validation and discovery.

Outcomes

  • Created a histology-to-imaging pipeline with 0.1x0.1x0.1 mm resolution, overcoming prior limitations in tissue distortion and registration.
  • Demonstrated that tau PET tracers may have limited specificity in non-Alzheimer's tauopathies, guiding future tracer development.
  • Guided the development of DECOMPOSE-QSM, an MRI technique that separates diamagnetic and paramagnetic sources, improving the specificity of imaging signals for tau and iron.
  • Published foundational work on the mislocalization of acetylated tau and its impact on neuronal structure.

Principal investigators

Collaborations

  • Brazilian Biobank for Aging Studies
  • Mayo Clinic Brain Bank
  • The laboratories of William Jagust, M.D., and Gil Rabinovici, M.D., at the University of California, San Francisco
  • University of California, San Francisco Edward and Pearl Fein Memory and Aging Center longitudinal cohort

Funding

  • Avid Radiopharmaceuticals
  • Lilly Research Award Program
  • U54 Tau Centers Without Walls, National Institute on Aging

Alternative biomarkers for Alzheimer's disease

The Neurodegeneration and Sleep Pathology Lab is developing and validating a cerebrospinal fluid assay for detecting caspase-6–truncated tau (D13 tr-tau), a novel biomarker that may enable earlier and more accurate diagnosis of Alzheimer's disease and help distinguish it from other tauopathies.

Earlier and more precise diagnosis can improve patient outcomes, guide treatment decisions and accelerate the development of new therapies.

Goals

  • Optimize and validate the D13 tr-tau assay for clinical and research use.
  • Test its ability to differentiate samples of Alzheimer's disease from control samples and samples of other dementias.
  • Support clinical trials by providing a sensitive marker for disease progression and treatment response.

Principal investigator

Mayo Clinic Brain Bank modernization

This initiative aims to digitize and modernize the Mayo Clinic Brain Bank, which houses over 240,000 scanned and stained slide images from approximately 11,000 autopsied patients across the United States. Our goal is to make these images searchable, link them to clinical and pathological data, and enable advanced computational analysis to support research in neurodegenerative diseases.

By transforming the brain bank into a digital, searchable resource, we will accelerate research into Alzheimer's disease, frontotemporal dementia, Lewy body dementia and other neurodegenerative conditions. The initiative also will improve access to high-quality tissue data for researchers and clinicians, supporting biomarker development and precision diagnostics.

The potential of this platform will only grow, as we are incorporating multiple imaging analytical algorithms powered by artificial intelligence to provide pathological data with efficiency and accuracy. For example, two pilot methods are already deployable for large-scale pathological data collection from brain slide images: ICHNet — our lab's histological quantification algorithm — as well as the anatomical segmentation algorithm developed by the Translational Neuropathology Laboratory of Melissa E. Murray, Ph.D.

Goals

  • Digitize and organize all slide images, linking them to patient metadata stored in a relational database.
  • Apply computational tools — including convolutional neural networks and voxel-to-voxel matching algorithms — to extract meaningful data from histological images.
  • Create a searchable inventory and dashboard for all samples and associated data in the brain bank.
  • Enable integration with clinical diagnosis, Braak staging, and other neuropathological findings to support research and diagnostics.
  • Expand the depth of data collection with AI-powered imagining analysis tools.

Outcomes

  • Successfully preprocessed hundreds of slides, with automated pipelines now in place for metadata extraction and stain classification.
  • Developed scripts to categorize slides by label quality, stain type and brain region.
  • Initiated schema design for database integration and inventory tracking.
  • Collaborated with quantitative and information technology teams to implement scalable infrastructure and automation tools.