Seminars

By using artificial intelligence and machine learning (AI/ML) to analyze complex, high-dimensional biomedical data, we aim to better understand human aging and disease by examining data from multiple organs and omics. We believe AI/ML can reveal patterns and insights that may be invisible to humans, providing valuable and complementary information to clinicians. This talk highlights two main topics: how AI/ML can provide low-dimensional signatures to digitize i) biological aging and ii) disease heterogeneity in the context of multi-organ and multi-omics modeling. These use cases are powered by the MULTI consortium, which consolidates and harmonizes large-scale multiorgan and multi-omics biomedical data across the human lifespan. The integration of AI-driven decision support systems into clinical settings can help identify potential biomarkers for genetic, proteomic, metabolomic, and imaging data, which may inform future therapeutic interventions.

The dorsolateral prefrontal cortex (dlPFC) and its complex connectivity are critical for maintaining executive functions such as working memory, planning and maintaining attention. dlPFC function progressively declines with age, evidenced by worsened performance in tasks assessing key executive functions among older adults. A potential driver of this decline is cellular senescence, a central hallmark of aging. Senescence encompasses heterogeneous cellular states triggered by prolonged cellular stress resulting in the irreversible arrest of cell proliferation and permanent changes to cell function in vivo. Identifying senescent cells poses challenges due to their rarity, heterogeneity, and the absence of a definitive marker. In this study, we performed Visium Spatial Transcriptomics (ST) and single nucleus RNA sequencing (snRNA-seq) on a cohort of non-pathological human tissue to identify signatures of aging and senescence in the dorsolateral prefrontal cortex (dlPFC) with both spatial and single-cell resolution. We identified markers characteristic of aging dlPFC cortical layers and cell types. Additionally, the cellular composition of the dlPFC changed with age, with an increase in astrocyte abundance and a decrease in somatostatin (SST) expressing inhibitory neurons. Overall, the observed senescence profile in the dlPFC was highly heterogeneous and heavily influenced by cell type identity and cortical layer. Combined unbiased analysis of ST and snRNA-seq datasets revealed gene expression modules encoding communities of microglia and endothelial cells in the white matter and regional astrocyte programs that were strongly enriched with age and for senescence-related genes. These findings provide new insights into how senescence-associated gene signatures present in the brain and will help facilitate future studies exploring the function of senescent cell subpopulations in the aging dlPFC.

The prevailing hypothesis about the pathogenesis of Alzheimer’s disease (AD) suggests a cascade of biological events initiated by abnormal beta-amyloid processing that leads to tau-related neuronal dysfunction, neurodegeneration, and dementia. This conceptualization has directly informed current diagnostic schemes, which evolved from diagnosing AD based on the characterization of a clinical syndrome to diagnosing AD based on the presence of biological markers of amyloid and tau alone. Our research over the past several years challenges this conceptualization and argues that AD comprises mixed pathologies that includes the contributions of cerebrovascular disease. Within the context of community-based research, clinical samples, populations with genetically-deterministic AD, and animal models, our findings suggest that cerebrovascular disease is a core feature that both contributes to the clinical emergence of AD and to its putative pathology.

Brain arterial aging consists of several sometimes overlapping phenotypes such as atherosclerosis, calcifications and dilatation. Non-atherosclerotic brain arterial aging consists of elastin loss, disruption of the internal elastic lamina, luminal dilatation and concentric intima thickening. Non-atherosclerotic aging is associated with a higher risk of incident dementia, especially Alzheimer’s disease, in several populations. Possible mechanisms relating non-atherosclerotic brain arterial aging with neurodegeneration include disruption of the brain-blood barrier via altered hemodynamics, increased neuroinflammation and/or disruption of the lymphatic system.

Humans have the most complex emotional repertoire in the animal kingdom, but it takes a very long time to reach full adult functioning. This prolonged development maximizes its chances of being influenced by social environments. Variations in early species-typical experiences, such as parental caregiving, reveal the profound effects of such influences on the development of neurobiology involved in emotional learning and regulation (e.g., amygdala, hippocampus, medial prefrontal cortex). This talk will focus on both typical development as well as development following caregiving-related stress showing that early life environments may influence development through learning and modification of developmental trajectories. These age-related changes will be discussed in terms of potential developmental sensitive periods for environmental influence.

We hypothesize that age- and pathology-related reduction in neurogenesis might be a culprit of the etiology of Alzheimer’s disease. Since neurogenesis relates to the brain resilience, restoring healthy levels of neurogenesis could have beneficial effects healthy aging. Using zebrafish, mouse, and novel 3D human neurogenesis assay systems as models to investigate the vertebrate neural stem cells, which we believe pose a unique hope to bring back lost neurons or strengthen brain wiring, we aim to find ways to restore brain function in AD through enhancing neurogenesis and neural regeneration.