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  • Profiling senescent cells in human brains reveals neurons with CDKN2D/p19 and tau neuropathology.

Profiling senescent cells in human brains reveals neurons with CDKN2D/p19 and tau neuropathology.

Nature aging (2022-05-10)
Shiva Kazempour Dehkordi, Jamie Walker, Eric Sah, Emma Bennett, Farzaneh Atrian, Bess Frost, Benjamin Woost, Rachel E Bennett, Timothy C Orr, Yingyue Zhou, Prabhakar S Andhey, Marco Colonna, Peter H Sudmant, Peng Xu, Minghui Wang, Bin Zhang, Habil Zare, Miranda E Orr
ABSTRACT

Senescent cells contribute to pathology and dysfunction in animal models1. Their sparse distribution and heterogenous phenotype have presented challenges for detecting them in human tissues. We developed a senescence eigengene approach to identify these rare cells within large, diverse populations of postmortem human brain cells. Eigengenes are useful when no single gene reliably captures a phenotype, like senescence; they also help to reduce noise, which is important in large transcriptomic datasets where subtle signals from low-expressing genes can be lost. Each of our eigengenes detected ~2% senescent cells from a population of ~140,000 single nuclei derived from 76 postmortem human brains with various levels of Alzheimer's disease (AD) pathology. More than 97% of the senescent cells were excitatory neurons and overlapped with tau-containing neurofibrillary tangles (NFTs). Cyclin dependent kinase inhibitor 2D (CDKN2D/p19) was predicted as the most significant contributor to the primary senescence eigengene. RNAscope and immunofluorescence confirmed its elevated expression in AD brain tissue whereby p19-expressing neurons had 1.8-fold larger nuclei and significantly more cells with lipofuscin than p19-negative neurons. These hallmark senescence phenotypes were further elevated in the presence of NFTs. Collectively, CDKN2D/p19-expressing neurons with NFTs represent a unique cellular population in human AD with a senescence phenotype. The eigengenes developed may be useful in future senescence profiling studies as they accurately identified senescent cells in snRNASeq datasets and predicted biomarkers for histological investigation.