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Eskaros, A.

Publications and source records attributed to Eskaros, A..

2 recordsLinked to original sources

Integrative Spatial Omics for Systems-Level Mapping of Pathological Niches

Spatial omics technologies are a powerful tool for mapping the relationship between cellular organization and molecular distributions in healthy and diseased tissue microenvironments. Here, we describe a novel multimodal pipeline that represents experimental and computational advances for spatiomolecular analysis of tissue samples across molecular classes. This adaptable method integrates matrix-assisted laser desorption/ionization imaging mass spectrometry spatial lipidomics, spatial transcriptomics, protein imaging via multiplexed immunofluorescence microscopy, and histopathological staining to uncover spatiomolecular profiles associated with unique cellular niches and pathological features. We demonstrate the power of this approach using two different complex human disease systems: Alzheimers disease in human brain tissue and type 2 diabetes mellitus in the human pancreas. This work establishes and demonstrates a generalizable framework for multimodal spatial integration, enabling precise mapping of molecular mechanisms that underlie complex tissue pathologies.

systems biology↗

Heterogeneous endocrine cell composition defines human islet functional phenotypes

Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While and {beta} cell composition influenced insulin and glucagon secretory traits, the abundance of {delta} cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and {beta} cell replacement therapy.

physiology↗