Aging cell

2022 Nov 17

Xu, Q;Rydz, C;Nguyen Huu, VA;Rocha, L;Palomino La Torre, C;Lee, I;Cho, W;Jabari, M;Donello, J;Lyon, DC;Brooke, RT;Horvath, S;Weinreb, RN;Ju, WK;Foik, A;Skowronska-Krawczyk, D;
PMID: 36397653 | DOI: 10.1111/acel.13737

Aging, a universal process that affects all cells in an organism, is a major risk factor for a group of neuropathies called glaucoma, where elevated intraocular pressure is one of the known stresses affecting the tissue. Our understanding of molecular impact of aging on response to stress in retina is very limited; therefore, we developed a new mouse model to approach this question experimentally. Here we show that susceptibility to response to stress increases with age and is primed on chromatin level. We demonstrate that ocular hypertension activates a stress response that is similar to natural aging and involves activation of inflammation and senescence. We show that multiple instances of pressure elevation cause aging of young retina as measured on transcriptional and DNA methylation level and are accompanied by local histone modification changes. Our data show that repeated stress accelerates appearance of aging features in tissues and suggest chromatin modifications as the key molecular components of aging. Lastly, our work further emphasizes the importance of early diagnosis and prevention as well as age-specific management of age-related diseases, including glaucoma.

The Major Risk Factors for Alzheimer’s Disease: Age, Sex, and Genes Modulate the Microglia Response to Ab Plaques.

Cell Rep.

2019 Apr 23

Sala Frigerio C, Wolfs L, Fattorelli N, Thrupp N, Voytyuk I, Schmidt I, Mancuso R, Chen WT, Woodbury ME, Srivastava G, Möller T, Hudry E, Das S, Saido T, Karran E, Hyman B, Perry VH, Fiers M, De Strooper B.
PMID: 31018141 | DOI: 10.1016/j.celrep.2019.03.099

Gene expression profiles of more than 10,000 individual microglial cells isolated from cortex and hippocampus of male and female AppNL-G-Fmice over time demonstrate that progressive amyloid-β accumulation accelerates two main activated microglia states that are also present during normal aging. Activated response microglia (ARMs) are composed of specialized subgroups overexpressing MHC type II and putative tissue repair genes (Dkk2, Gpnmb, and Spp1) and are strongly enriched with Alzheimer's disease (AD) risk genes. Microglia from female mice progress faster in this activation trajectory. Similar activated states are also found in a second AD model and in human brain. Apoe, the major genetic risk factor for AD, regulates the ARMs but not the interferon response microglia (IRMs). Thus, the ARMs response is the converging point for aging, sex, and genetic AD risk factors.

Single-cell transcriptomes of the human skin reveal age-related loss of fibroblast priming.

Commun Biol

2020 Apr 23

Sol�-Boldo L, Raddatz G, Sch�tz S, Mallm JP, Rippe K, Lonsdorf AS, Rodr�guez-Paredes M, Lyko F
PMID: 32327715 | DOI: 10.1038/s42003-020-0922-4

Fibroblasts are an essential cell population for human skin architecture and function. While fibroblast heterogeneity is well established, this phenomenon has not been analyzed systematically yet. We have used single-cell RNA sequencing to analyze the transcriptomes of more than 5,000 fibroblasts from a sun-protected area in healthy human donors. Our results define four main subpopulations that can be spatially localized and show differential secretory, mesenchymal and pro-inflammatory functional annotations. Importantly, we found that this fibroblast 'priming' becomes reduced with age. We also show that aging causes a substantial reduction in the predicted interactions between dermal fibroblasts and other skin cells, including undifferentiated keratinocytes at the dermal-epidermal junction. Our work thus provides evidence for a functional specialization of human dermal fibroblasts and identifies the partial loss of cellular identity as an important age-related change in the human dermis. These findings have important implications for understanding human skin aging and its associated phenotypes.

Microglia response following acute demyelination is heterogeneous and limits infiltrating macrophage dispersion.

Sci Adv

2020 Jan 15

Plemel JR, Stratton JA, Michaels NJ, Rawji KS, Zhang E, Sinha S, Baaklini CS, Dong Y, Ho M, Thorburn K, Friedman TN, Jawad S, Silva C, Caprariello AV, Hoghooghi V, Yue J, Jaffer A, Lee K, Kerr BJ, Midha R, Stys PK, Biernaskie J, Yong VW
PMID: 31998844 | DOI: 10.1126/sciadv.aay6324

Microglia and infiltrating macrophages are thought to orchestrate the central nervous system (CNS) response to injury; however, the similarities between these cells make it challenging to distinguish their relative contributions. We genetically labeled microglia and CNS-associated macrophages to distinguish them from infiltrating macrophages. Using single-cell RNA sequencing, we describe multiple microglia activation states, one of which was enriched for interferon associated signaling. Although blood-derived macrophages acutely infiltrated the demyelinated lesion, microglia progressively monopolized the lesion environment where they surrounded infiltrating macrophages. In the microglia-devoid sciatic nerve, the infiltrating macrophage response was sustained. In the CNS, the preferential proliferation of microglia and sparse microglia death contributed to microglia dominating the lesion. Microglia ablation reversed the spatial restriction of macrophages with the demyelinated spinal cord, highlighting an unrealized macrophages-microglia interaction. The restriction of peripheral inflammation by microglia may be a previously unidentified mechanism by which the CNS maintains its "immune privileged" status.

Severe COVID-19 infection is associated with aberrant cytokine production by infected lung epithelial cells rather than by systemic immune dysfunction

Research square

2021 Nov 24

Gajewski, T;Rouhani, S;Trujillo, J;Pyzer, A;Yu, J;Fessler, J;Cabanov, A;Higgs, E;Cron, K;Zha, Y;Lu, Y;Bloodworth, J;Abasiyanik, M;Okrah, S;Flood, B;Hatogai, K;Leung, M;Pezeshk, A;Kozloff, L;Reschke, R;Strohbehn, G;Chervin, CS;Kumar, M;Schrantz, S;Madariaga, ML;Beavis, K;Yeo, KT;Sweis, R;Segal, J;Tay, S;Izumchenko, E;Mueller, J;Chen, L;
PMID: 34845442 | DOI: 10.21203/rs.3.rs-1083825/v1

The mechanisms explaining progression to severe COVID-19 remain poorly understood. It has been proposed that immune system dysregulation/over-stimulation may be implicated, but it is not clear how such processes would lead to respiratory failure. We performed comprehensive multiparameter immune monitoring in a tightly controlled cohort of 128 COVID-19 patients, and used the ratio of oxygen saturation to fraction of inspired oxygen (SpO2 / FiO2) as a physiologic measure of disease severity. Machine learning algorithms integrating 139 parameters identified IL-6 and CCL2 as two factors predictive of severe disease, consistent with the therapeutic benefit observed with anti-IL6-R antibody treatment. However, transcripts encoding these cytokines were not detected among circulating immune cells. Rather, in situ analysis of lung specimens using RNAscope and immunofluorescent staining revealed that elevated IL-6 and CCL2 were dominantly produced by infected lung type II pneumocytes. Severe disease was not associated with higher viral load, deficient antibody responses, or dysfunctional T cell responses. These results refine our understanding of severe COVID-19 pathophysiology, indicating that aberrant cytokine production by infected lung epithelial cells is a major driver of immunopathology. We propose that these factors cause local immune regulation towards the benefit of the virus.

The Presence of Interleukin-13 at Pancreatic ADM/PanIN Lesions Alters Macrophage Populations and Mediates Pancreatic Tumorigenesis.

Cell Rep.

2017 May 16

Liou GY, Bastea L, Fleming A, Döppler H, Edenfield BH, Dawson DW, Zhang L, Bardeesy N, Storz P.
PMID: 28514653 | DOI: 10.1016/j.celrep.2017.04.052

The contributions of the innate immune system to the development of pancreatic cancer are still ill defined. Inflammatory macrophages can initiate metaplasia of pancreatic acinar cells to a duct-like phenotype (acinar-to-ductal metaplasia [ADM]), which then gives rise to pancreatic intraepithelial neoplasia (PanIN) when oncogenic KRas is present. However, it remains unclear when and how this inflammatory macrophage population is replaced by tumor-promoting macrophages. Here, we demonstrate the presence of interleukin-13 (IL-13), which can convert inflammatory into Ym1+ alternatively activated macrophages, at ADM/PanIN lesions. We further show that Ym1+ macrophages release factors, such as IL-1ra and CCL2, to drive pancreatic fibrogenesis and tumorigenesis. Treatment of mice expressing oncogenic KRas under an acinar cell-specific promoter with a neutralizing antibody for IL-13 significantly decreased the accumulation of alternatively activated macrophages at these lesions, resulting in decreased fibrosis and lesion growth.

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	Description
sense Example: Hs-LAG3-sense	Standard probes for RNA detection are in antisense. Sense probe is reverse complent to the corresponding antisense probe.
Intron# Example: Mm-Htt-intron2	Probe targets the indicated intron in the target gene, commonly used for pre-mRNA detection
Pool/Pan Example: Hs-CD3-pool (Hs-CD3D, Hs-CD3E, Hs-CD3G)	A mixture of multiple probe sets targeting multiple genes or transcripts
No-XSp Example: Hs-PDGFB-No-XMm	Does not cross detect with the species (Sp)
XSp Example: Rn-Pde9a-XMm	designed to cross detect with the species (Sp)
O# Example: Mm-Islr-O1	Alternative design targeting different regions of the same transcript or isoforms
CDS Example: Hs-SLC31A-CDS	Probe targets the protein-coding sequence only
EnEm	Probe targets exons n and m
En-Em	Probe targets region from exon n to exon m
Retired Nomenclature
tvn Example: Hs-LEPR-tv1	Designed to target transcript variant n
ORF Example: Hs-ACVRL1-ORF	Probe targets open reading frame
UTR Example: Hs-HTT-UTR-C3	Probe targets the untranslated region (non-protein-coding region) only
5UTR Example: Hs-GNRHR-5UTR	Probe targets the 5' untranslated region only
3UTR Example: Rn-Npy1r-3UTR	Probe targets the 3' untranslated region only
Pan Example: Pool	A mixture of multiple probe sets targeting multiple genes or transcripts

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