Heterochronic parabiosis alters the transcriptomic landscape to combat aging and aging-related diseases in aging-accelerated mice

Abstract

Aging is a multifactorial process involving a gradual decline in cellular and tissue functions, making it a major risk factor for aging-related degenerative diseases. In this study, we utilized the senescence-accelerated mouse prone 8 mice model, which mimics pathological characteristics of Alzheimer's disease, fatty liver disease, and cardiac fibrosis, to construct a heterochronic parabiosis model and systematically investigate the rejuvenating effects of heterochronic parabiosis on the brain, liver, and heart. Our findings revealed that heterochronic parabiosis promotes synaptic plasticity and neuronal communication, restores hepatocyte metabolic functions, and reduces chronic inflammation and fibrosis in the heart. Notably, heterochronic parabiosis significantly downregulates the expression of age-related disease risk genes. In addition, endothelial cells, as cell types directly exposed to the circulatory environment, demonstrated the highest sensitivity to heterochronic parabiosis across three organs, and exhibited significantly reduced inflammation after intervention, suggesting that they may play an early and central role in the rejuvenation process. Overall, our study increases the understanding of the molecular and cellular mechanisms of aging and its related diseases, highlights the multiorgan and multitarget potential of heterochronic parabiosis in delaying aging and mitigating aging-related diseases, and provides new therapeutic targets for achieving healthy aging.

Keywords

heterochronic parabiosis / snRNA-seq / aging / aging-related diseases

References

[1] López-Otín C , Blasco MA , Partridge L , et al. Hallmarks of aging: an expanding universe. Cell 2023; 186: 243- 78.

[2] Cai Y , Song W , Li J , et al. The landscape of aging. Sci China Life Sci 2022; 65: 2354- 454.

[3] Guo J , Huang X , Dou L , et al. Aging and aging-related diseases:from molecular mechanisms to interventions and treatments. Signal Transduct Target Ther 2022; 7: 391.

[4] Cortes-Canteli M , Iadecola C . Alzheimer's disease and vascular aging:JACC focus seminar. J Am Coll Cardiol 2020; 75: 942- 51.

[5] Ungvari A , Gulej R , Patai R , et al. Sex-specific mechanisms in vascular aging: exploring cellular and molecular pathways in the pathogenesis of age-related cardiovascular and cerebrovascular diseases. Geroscience 2025; 47: 301- 37.

[6] Zheng R , Zhang Y , Zhang K , et al. The complement system, aging, and aging-related diseases. Int J Mol Sci 2022; 23: 8689.

[7] Yang J , Luo J , Tian X , et al. Progress in understanding oxidative stress, aging, and aging-related diseases. Antioxidants (Basel) 2024; 13: 394.

[8] Li Z , Zhang Z , Ren Y , et al. Aging and age-related diseases:from mechanisms to therapeutic strategies. Biogerontology 2021; 22: 165- 87.

[9] Dayan IE , Arga KY , Ulgen KO . Multiomics approach to novel therapeutic targets for cancer and aging-related diseases:role of Sld7 in yeast aging network. OMICS 2017; 21: 100- 13.

[10] Conboy MJ , Conboy IM , Rando TA . Heterochronic parabiosis:historical perspective and methodological considerations for studies of aging and longevity. Aging Cell 2013; 12: 525- 30.

[11] Lagunas-Rangel FA . Aging insights from heterochronic parabiosis models. NPJ Aging 2024; 10: 38.

[12] Yang C , Liu Z-L , Wang J , et al. Parabiosis modeling: protocol, application and perspectives. Zool Res 2021; 42: 253- 61.

[13] Palovics R , Keller A , Schaum N , et al.; Tabula Muris Consortium. Molecular hallmarks of heterochronic parabiosis at single-cell resolution. Nature 2022; 603: 309- 14.

[14] Ma S , Wang S , Ye Y , et al. Heterochronic parabiosis induces stem cell revitalization and systemic rejuvenation across aged tissues. Cell Stem Cell 2022; 29: 990- 1005.e10.

[15] Ximerakis M , Holton KM , Giadone RM , et al. Heterochronic parabiosis reprograms the mouse brain transcriptome by shifting aging signatures in multiple cell types. Nature Aging 2023; 3: 327- 45.

[16] Ashapkin VV , Kutueva LI , Vanyushin BF . The effects of parabiosis on aging and age-related diseases. Adv Exp Med Biol 2020; 1260: 107- 22.

[17] Miyamoto M . Characteristics of age-related behavioral changes in senescence-accelerated mouse SAMP8 and SAMP10. Exp Gerontol 1997; 32: 139- 48.

[18] Cai N , Wu Y , Huang Y . Induction of accelerated aging in a mouse model. Cells 2022; 11: 1418.

[19] Morley JE , Farr SA , Kumar VB , et al. The SAMP8 mouse: a model to develop therapeutic interventions for Alzheimer's disease. Curr Pharm Des 2012; 18: 1123- 30.

[20] Liu B , Liu J , Shi JS . SAMP8 mice as a model of age-related cognition decline with underlying mechanisms in Alzheimer's disease. J Alzheimers Dis 2020; 75: 385- 95.

[21] Xie QY , Shu X , Liu T , et al. Ethanol extract of propolis attenuates liver lipid metabolism disorder in high-fat diet-fed SAMP8 mice. Mol Nutr Food Res 2024; 68: e2400297.

[22] Altenburg HM , Kamm DR , Schaller ML , et al. The effects of sex differences and diet on the development of non-alcoholic fatty liver disease in SAMP8 mice. FASEB J 2019; 33: 582.

[23] Karuppagounder V , Arumugam S , Babu SS , et al. The senescence accelerated mouse prone 8 (SAMP8): a novel murine model for cardiac aging. Ageing Res Rev 2017; 35: 291- 6.

[24] Takeda T , Matsushita T , Kurozumi M , et al. Pathobiology of the senescence-accelerated mouse (SAM). Exp Gerontol 1997; 32: 117- 27.

[25] Kamran P , Sereti K-I , Zhao P , et al. Parabiosis in mice: a detailed protocol. J Vis Exp 2013; 80: 50556.

[26] Tabula Muris C . A single-cell transcriptomic atlas characterizes ageing tissues in the mouse. Nature 2020; 583: 590- 5.

[27] Han X , Wang R , Zhou Y , et al. Mapping the mouse cell atlas by Microwell-Seq. Cell 2018; 172: 1091- 107.e17.

[28] Ortiz C , Navarro JF , Jurek A , et al. Molecular atlas of the adult mouse brain. Sci Adv 2020; 6: eabb3446.

[29] Li YE , Preissl S , Hou X , et al. An atlas of gene regulatory elements in adult mouse cerebrum. Nature 2021; 598: 129- 36.

[30] Xu J , Guo P , Hao S , et al. A spatiotemporal atlas of mouse liver homeostasis and regeneration. Nat Genet 2024; 56: 953- 69.

[31] Su Q , Kim SY , Adewale F , et al. Single-cell RNA transcriptome landscape of hepatocytes and non-parenchymal cells in healthy and NAFLD mouse liver. iScience 2021; 24: 103233.

[32] Feng W , Bais A , He H , et al. Single-cell transcriptomic analysis identifies murine heart molecular features at embryonic and neonatal stages. Nat Commun 2022; 13: 7960.

[33] Yin Q , Chu Q , Jiang H , et al. Single-cell RNA sequencing profiling of mouse cardiac cells in response to retinoic acid. Heliyon 2024; 10: e38301.

[34] Buckley MT , Sun ED , George BM , et al. Cell-type-specific aging clocks to quantify aging and rejuvenation in neurogenic regions of the brain. Nat Aging 2023; 3: 121- 37.

[35] Wang S , Zheng Y , Li J , et al. Single-cell transcriptomic atlas of primate ovarian aging. Cell 2020; 180: 585- 600.e19.

[36] Yang S , Liu C , Jiang M , et al. A single-nucleus transcriptomic atlas of primate liver aging uncovers the pro-senescence role of SREBP2 in hepatocytes. Protein Cell 2024; 15: 98- 120.

[37] Ma S , Skarica M , Li Q , et al. Molecular and cellular evolution of the primate dorsolateral prefrontal cortex. Science 2022; 377: eabo7257.

[38] Gomez-Oliva R , Martínez-Ortega S , Atienza-Navarro I , et al. Rescue of neurogenesis and age-associated cognitive decline in SAMP8 mouse:role of transforming growth factor-alpha. Aging Cell 2023; 22: e13829.

[39] Zhang S , Zhu D , Li H , et al. Characterization of circRNAassociated-ceRNA networks in a senescence-accelerated mouse prone 8 brain. Mol Ther 2017; 25: 2053- 61.

[40] Kumar N , Mishra B , Athar M , et al. Inference of gene regulatory network from single-cell transcriptomic data using pySCENIC. Methods Mol Biol 2021; 2328: 171- 82.

[41] Scobie KN , Hall BJ , Wilke SA , et al. Kruppel-Like factor 9 is necessary for late-phase neuronal maturation in the developing dentate gyrus and during adult hippocampal neurogenesis. J Neurosci 2009; 29: 9875- 87.

[42] Avila-Mendoza J , Subramani A , Sifuentes CJ , et al. Molecular mechanisms for Kruppel-like factor 13 actions in hippocampal neurons. Mol Neurobiol 2020; 57: 3785- 802.

[43] Du SQ , Zheng H . Role of FoxO transcription factors in aging and age-related metabolic and neurodegenerative diseases. Cell Biosci 2021; 11: 188.

[44] Hoyt KR , Obrietan K . Circadian clocks, cognition, and Alzheimer's disease:synaptic mechanisms, signaling effectors, and chronotherapeutics. Mol Neurodegener 2022; 17: 35.

[45] Frank MG . Circadian regulation of synaptic plasticity. Biology (Basel) 2016; 5: 31.

[46] Koopmans F , van Nierop P , Andres-Alonso M , et al. SynGO: an evidence-based, expert-curated knowledge base for the synapse. Neuron 2019; 103: 217- 34.e4.

[47] Choquet D , Triller A . The dynamic synapse. Neuron 2013; 80: 691- 703.

[48] Dejanovic B , Sheng M , Hanson JE . Targeting synapse function and loss for treatment of neurodegenerative diseases. Nat Rev Drug Discov 2024; 23: 23- 42.

[49] Jin S , Guerrero-Juarez CF , Zhang L et al. Inference and analysis of cell-cell communication using CellChat. Nat Commun 2021; 12: 1088.

[50] Jin S , Plikus MV , Nie Q . CellChat for systematic analysis of cellcell communication from single-cell transcriptomics. Nat Protoc 2024; 20: 180- 219.

[51] Ledonne A , Mercuri NB . On the modulatory roles of Neuregulins/ErbB signaling on synaptic plasticity. Int J Mol Sci 2019; 21: 275.

[52] Sasi M , Vignoli B , Canossa M , et al. Neurobiology of local and intercellular BDNF signaling. Pflugers Arch 2017; 469: 593- 610.

[53] Garcia-Dominguez M . Enkephalins and pain modulation: mechanisms of action and therapeutic perspectives. Biomolecules 2024; 14: 926.

[54] Zhou Z , Pan Y , Zhou S , et al. Single-cell analysis reveals specific neuronal transition during mouse corticogenesis. Front Cell Dev Biol 2023; 11: 1209320.

[55] Li H , Xu Li , Jiang W , et al. Pleiotrophin ameliorates age-induced adult hippocampal neurogenesis decline and cognitive dysfunction. Cell Rep 2023; 42: 113022.

[56] Ye X , Meeker HC , Kozlowski PB , et al. Pathological changes in the liver of a senescence accelerated mouse strain (SAMP8): a mouse model for the study of liver diseases. Histol Histopathol 2004; 19: 1141- 51.

[57] Wei Y , Wang YG , Jia Y , et al. Liver homeostasis is maintained by midlobular zone 2 hepatocytes (vol 371, eabb1625, 2021). Science 2021; 371: eabb1625.

[58] Oishi Y , Manabe I . Kruppel-like factors in metabolic homeostasis and cardiometabolic disease. Front Cardiovasc Med 2018; 5: 69.

[59] Hiraike Y , Waki H , Miyake K , et al. NFIA differentially controls adipogenic and myogenic gene program through distinct pathways to ensure brown and beige adipocyte differentiation. PLoS Genet 2020; 16: e1009044.

[60] Hliwa A , Ramos-Molina B , Laski D , et al. The role of fatty acids in non-alcoholic fatty liver disease progression: an update. Int J Mol Sci 2021; 22: 6900.

[61] Houten SM , Denis S , Argmann CA , et al. Peroxisomal L-bifunctional enzyme (Ehhadh) is essential for the production of medium-chain dicarboxylic acids.J Lipid Res 2012; 53: 1296- 303.

[62] Elmansi AM , Miller RA . Oxidative phosphorylation and fatty acid oxidation in slow-aging mice. Free Radic Biol Med 2024; 224: 246- 55.

[63] Zhang Z , Wang Y , Chen X , et al. The aging heart in focus: the advanced understanding of heart failure with preserved ejection fraction. Ageing Res Rev 2024; 101: 102542.

[64] Papaconstantinou J . The role of signaling pathways of inflammation and oxidative stress in development of senescence and aging phenotypes in cardiovascular disease. Cells 2019; 8: 1383.

[65] Patrick R , Janbandhu V , Tallapragada V , et al. Integration mapping of cardiac fibroblast single-cell transcriptomes elucidates cellular principles of fibrosis in diverse pathologies. Sci Adv 2024; 10: eadk8501.

[66] Augustin HG , Koh GY . A systems view of the vascular endothelium in health and disease. Cell 2024; 187: 4833- 58.

[67] Skinnider MA , Squair JW , Kathe C , et al. Cell type prioritization in single-cell data. Nat Biotechnol 2021; 39: 30- 4.

[68] Qiu X , Hill A , Packer J , et al. Single-cell mRNA quantification and differential analysis with Census. Nat Methods 2017; 14: 309- 15.

[69] Bieri G , Schroer AB , Villeda SA . Blood-to-brain communication in aging and rejuvenation. Nat Neurosci 2023; 26: 379- 93.

[70] He J , Duan M , Zhuang H . ICAM1 and VCAM1 are associated with outcome in patients with sepsis: a systematic review and meta-analysis. Heliyon 2024; 10: e40003.

[71] Koga K , Wang B , Kaneko S . Current status and future perspectives of HLA-edited induced pluripotent stem cells. Inflamm Regen 2020; 40: 23.

[72] Pinero J , Ramírez-Anguita JM , Saüch-Pitarch J , et al. The DisGeNET knowledge platform for disease genomics:2019 update. Nucleic Acids Res 2020; 48: D845- 55.

[73] Soldano A , Hassan BA . Beyond pathology: APP, brain development and Alzheimer's disease. Curr Opin Neurobiol 2014; 27: 61- 7.

[74] Bagyinszky E , Giau VV , Youn YC , et al. Characterization of mutations in (prion) gene and their possible roles in neurodegenerative diseases. Neuropsych Dis Treat 2018; 14: 2067- 85.

[75] Bayer TA , Cappai R , Masters CL , et al. It all sticks together- the APP-related family of proteins and Alzheimer's disease. Mol Psychiatr 1999; 4: 524- 8.

[76] Sorci G , Bianchi R , Riuzzi F , et al. S100B protein, a damageassociated molecular pattern protein in the brain and heart, and beyond. Cardiovasc Psychiatry Neurol 2010; 2010: 1- 13.

[77] Li N , Li X , Ding Y , et al. SREBP regulation of lipid metabolism in liver disease, and therapeutic strategies. Biomedicines 2023; 11: 3280.

[78] Ding Z , Wei Y , Peng J , et al. The potential role of C-reactive protein in metabolic-dysfunction-associated fatty liver disease and aging. Biomedicines 2023; 11: 2711.

[79] Ghanbari M , Momen Maragheh S , Aghazadeh A , et al. Interleukin-1 in obesity-related low-grade inflammation:from molecular mechanisms to therapeutic strategies. Int Immunopharmacol 2021; 96: 107765.

[80] Song W , Wang H , Wu Q . Atrial natriuretic peptide in cardiovascular biology and disease (NPPA). Gene 2015; 569: 1- 6.

[81] Abumrad NA , Goldberg IJ . CD36 actions in the heart: lipids, calcium, inflammation, repair and more? Biochim Biophys Acta 2016; 1861: 1442- 9.

[82] Lopez-Otin C , Blasco MA , Partridge L , et al. The hallmarks of aging. Cell 2013; 153: 1194- 217.

[83] Sun S , Ma S , Cai Y , et al. A single-cell transcriptomic atlas of exercise-induced anti-inflammatory and geroprotective effects across the body. Innovation (Camb) 2023; 4: 100380.

[84] Ma S , Sun S , Geng L , et al. Caloric restriction reprograms the single-cell transcriptional landscape of rattus norvegicus aging. Cell 2020; 180: 984- 1001.e22.

[85] Bakken TE , Hodge RD , Miller JA , et al. Single-nucleus and single-cell transcriptomes compared in matched cortical cell types. PLoS One 2018; 13: e0209648.

[86] Han L , Wei X , Liu C , et al. Cell transcriptomic atlas of the nonhuman primate Macaca fascicularis. Nature 2022; 604: 723- 31.

[87] Hao Y , Hao S , Andersen-Nissen E , et al. Integrated analysis of multimodal single-cell data. Cell 2021; 184: 3573- 87.e29.

[88] McGinnis CS , Murrow LM , Gartner ZJ . DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors. Cell Syst 2019; 8: 329- 37.e4.

[89] Yang S , Corbett SE , Koga Y , et al. Decontamination of ambient RNA in single-cell RNA-seq with DecontX. Genome Biol 2020; 21: 57.

[90] Korsunsky I , Millard N , Fan J , et al. Fast, sensitive and accurate integration of single-cell data with harmony. Nat Methods 2019; 16: 1289- 96.

[91] Wu T , Hu E , Xu S , et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation (Camb) 2021; 2: 100141.

[92] Zhou Y , Zhou B , Pache L , et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019; 10: 1523.

[93] Van de Sande B , Flerin C , Davie K , et al. A scalable SCENIC workflow for single-cell gene regulatory network analysis. Nat Protoc 2020; 15: 2247- 76.

[94] Kotliar D , Veres A , Nagy MA , et al. Identifying gene expression programs of cell-type identity and cellular activity with single-cell RNA-Seq. Elife 2019; 8: e43803.

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