# Improvement and standardization of a bioinformatic software suite for multiplexed imaging > **NIH NIH R01** · STANFORD UNIVERSITY · 2022 · $218,717 ## Abstract PROJECT SUMMARY Sarcopenia, or age-related muscle atrophy, afflicts 15% of the elderly, severely diminishing quality of life and increasing morbidity and mortality. Our overarching goal is to elucidate novel causal mechanisms of sarcopenia and use this knowledge to improve aged muscle function. We propose to capitalize on our discovery that a reduction in the prostaglandins PGE2 and PGD2 in aged muscle results from catabolism by 15-hydroxyprosta- glandin dehydrogenase (15-PGDH), the prostaglandin degrading enzyme, the subject of the parent grant of this application. As described in the grant, we made the unexpected finding that 15-PGDH expression is significantly increased in aged mouse and human muscles. Additionally, our data show that overexpressing 15-PGDH in young muscles induces an aging phenotype accompanied by a marked decrease in muscle mass and function, mimicking sarcopenia. The central hypothesis of the parent grant is that during aging, senescent and inflamma- tory cells accumulate in the muscle microenvironment and express 15-PGDH, which degrades PGE2 and PGD2, and causes muscle wasting. Therefore, inhibition of 15-PGDH in aged muscles will increase PGE2 and PGD2 lipid metabolites and augment muscle mass and strength. Our aims are to (i) elucidate the roles of PGE2 and PGD2 in skeletal muscle homeostasis, (ii) identify the cell source of 15-PGDH and prostaglandin dysregulation in aged muscle, and (iii) restore aged muscle function and mass by inhibiting 15-PGDH. Parent grant Aim 2 employs a cutting-edge single cell multiplexed imaging technology called CODEX (CO-Detection by indEXing). CODEX allows us to resolve up to 60 markers simultaneously in single tissue sections. This breakthrough meth- odology will enable a determination of whether senescent cells comprise a cell source of 15-PGDH and allow us to resolve the spatial relationships among the diverse cell types present in aged muscles. Each CODEX experi- ment produces terabytes of high-resolution images that must be deconvolved and stitched together. We have developed 3 software packages (CRISP, HFCluster, and SpaCE) to deconvolve, stitch, cluster, and annotate our CODEX data and computationally identify signaling among cell types. Our goal for this supplement is to fund a skilled and dedicated lab associate for the continued improvement and maintenance of this software, specifi- cally to improve user interface, standardize data input formats, and provide compatibility for a range of multi- plexed imaging workflows. These improvements will not only help us achieve the second aim of our grant, but they will also make the software we develop far more user-friendly and readily accessible to the muscle biology and aging communities, as well as to all users of CODEX and other multiplexed imaging modalities. ## Key facts - **NIH application ID:** 10609313 - **Project number:** 3R01AG069858-03S1 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** Helen M Blau - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $218,717 - **Award type:** 3 - **Project period:** 2020-09-15 → 2024-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10609313 ## Citation > US National Institutes of Health, RePORTER application 10609313, Improvement and standardization of a bioinformatic software suite for multiplexed imaging (3R01AG069858-03S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10609313. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*