Categories: Lifestyle

Lifestyle change accelerates epigenetic ageing in King penguins

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  • Tam, B. T., Morais, J. A. & Santosa, S. Obesity and ageing: two sides of the identical coin. Obes. Rev. 21, e12991 (2020).


    Google Scholar
     

  • de Rezende, L. F., Rey-López, J. P., Matsudo, V. Ok. & do Carmo Luiz, O. Sedentary habits and well being outcomes amongst older adults: a scientific evaluation. BMC Public Health 14, 333 (2014).


    Google Scholar
     

  • López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. The hallmarks of growing old. Cell 153, 1194–1217 (2013).


    Google Scholar
     

  • Horvath, S. et al. Obesity accelerates epigenetic growing old of human liver. Proc. Natl. Acad. Sci. USA 111, 15538–15543 (2014).


    Google Scholar
     

  • Maegawa, S. et al. Caloric restriction delays age-related methylation drift. Nat. Commun. 8, 539 (2017).


    Google Scholar
     

  • Kankaanpää, A. et al. Leisure-time and occupational bodily exercise associates otherwise with epigenetic growing old. Med. Sci. Sports Exerc. 53, 487–495 (2021).


    Google Scholar
     

  • Booth, F. W., Laye, M. J. & Roberts, M. D. Lifetime sedentary residing accelerates some points of secondary growing old. J. Appl. Physiol. 111, 1497–1504 (2011).


    Google Scholar
     

  • Kehler, D. S. & Theou, O. The impression of bodily exercise and sedentary behaviors on frailty ranges. Mech. Ageing Dev. 180, 29–41 (2019).


    Google Scholar
     

  • Gale, C. R. et al. The epigenetic clock and objectively measured sedentary and strolling habits in older adults: the Lothian Birth Cohort 1936. Clin. Epigenetics 10, 4 (2018).


    Google Scholar
     

  • de Cabo, R. & Mattson, M. P. Effects of intermittent fasting on well being, growing old, and illness. N. Engl. J. Med. 381, 2541–2551 (2019).


    Google Scholar
     

  • Pak, H. H. et al. Fasting drives the metabolic, molecular and geroprotective results of a calorie-restricted weight loss plan in mice. Nat. Metab. 3, 1327–1341 (2021).


    Google Scholar
     

  • Fitzgerald, Ok. N. et al. Potential reversal of epigenetic age utilizing a weight loss plan and way of life intervention: a pilot randomized scientific trial. Aging 13, 9419–9432 (2021).


    Google Scholar
     

  • Ekelund, U. et al. Does bodily exercise attenuate, and even get rid of, the detrimental affiliation of sitting time with mortality? A harmonised meta-analysis of knowledge from greater than 1 million women and men. Lancet 388, 1302–1310 (2016).


    Google Scholar
     

  • Madeo, F., Pietrocola, F., Eisenberg, T. & Kroemer, G. Caloric restriction mimetics: in direction of a molecular definition. Nat. Rev. Drug Discov. 13, 727–740 (2014).


    Google Scholar
     

  • Fahy, G. M. et al. Reversal of epigenetic growing old and immunosenescent tendencies in people. Aging Cell 18, e13028 (2019).


    Google Scholar
     

  • Moatt, J. P., Savola, E., Regan, J. C., Nussey, D. H. & Walling, C. A. Lifespan extension through dietary restriction: time to rethink the evolutionary mechanisms?. BioEssays 42, 1900241 (2020).


    Google Scholar
     

  • Briga, M. & Verhulst, S. What can long-lived mutants inform us about mechanisms inflicting growing old and lifespan variation in pure environments?. Exp. Gerontol. 71, 21–26 (2015).


    Google Scholar
     

  • McCracken, A. W., Adams, G., Hartshorne, L., Tatar, M. & Simons, M. J. P. The hidden prices of dietary restriction: Implications for its evolutionary and mechanistic origins. Sci. Adv. 6, eaay3047 (2020).


    Google Scholar
     

  • Valenzano, D. R., Aboobaker, A., Seluanov, A. & Gorbunova, V. Non-canonical growing old mannequin methods and why we want them. EMBO J 36, 959–963 (2017).


    Google Scholar
     

  • Phelan, J. P. & Rose, M. R. Why dietary restriction considerably will increase longevity in animal fashions however gained’t in people. Ageing Res. Rev. 4, 339–350 (2005).


    Google Scholar
     

  • Caccialanza, R., Aprile, G., Cereda, E. & Pedrazzoli, P. Fasting in oncology: a phrase of warning. Nat. Rev. Cancer 19, 177–177 (2019).


    Google Scholar
     

  • Most, J., Tosti, V., Redman, L. M. & Fontana, L. Calorie restriction in people: an replace. Ageing Res. Rev. 39, 36–45 (2017).


    Google Scholar
     

  • Mariath, A. B., Machado, A. D., Ferreira, L., do & Ribeiro, N. M. S. M. L. The attainable position of elevated consumption of ultra-processed meals merchandise within the growth of frailty: a menace for wholesome ageing?. Br. J. Nutr. 128, 461–466 (2022).


    Google Scholar
     

  • Nencioni, A., Caffa, I., Cortellino, S. & Longo, V. D. Fasting and most cancers: molecular mechanisms and scientific utility. Nat. Rev. Cancer 18, 707–719 (2018).


    Google Scholar
     

  • Groscolas, R. & Robin, J.-P. Long-term fasting and re-feeding in penguins. Comp. Biochem. Physiol. A. Mol. Integr. Physiol. 128, 643–653 (2001).


    Google Scholar
     

  • Bost, C. A. et al. Large-scale climatic anomalies have an effect on marine predator foraging behaviour and demography. Nat. Commun. 6, 8220 (2015).


    Google Scholar
     

  • Tidière, M. et al. Comparative analyses of longevity and senescence reveal variable survival advantages of residing in zoos throughout mammals. Sci. Rep. 6, 36361 (2016).


    Google Scholar
     

  • Lecorps, B., Weary, D. M. & von Keyserlingk, M. A. G. Captivity-induced despair in animals. Trends Cogn. Sci. 25, 539–541 (2021).


    Google Scholar
     

  • Fens, A. & Clauss, M. Nutrition as an integral a part of behavioural administration of zoo animals. J. Zoo Aquar. Res. 12, 196–204 (2024).


    Google Scholar
     

  • Tangili, M. et al. DNA methylation markers of age(ing) in non-model animals. Mol. Ecol. 32, 4725–4741 (2023).


    Google Scholar
     

  • Bell, C. G. et al. DNA methylation growing old clocks: challenges and suggestions. Genome Biol. 20, 249 (2019).


    Google Scholar
     

  • Vaisvila, R. et al. Enzymatic methyl sequencing detects DNA methylation at single-base decision from picograms of DNA. Genome Res. 31, 1280–1289 (2021).


    Google Scholar
     

  • Higgins-Chen, A. T. et al. A computational resolution for bolstering reliability of epigenetic clocks: implications for scientific trials and longitudinal monitoring. Nat. Aging 2, 644–661 (2022).


    Google Scholar
     

  • Snir, S., Farrell, C. & Pellegrini, M. Human epigenetic ageing is logarithmic with time throughout the whole lifespan. Epigenetics 14, 912–926 (2019).


    Google Scholar
     

  • Kaprio, J. et al. The Older Finnish Twin Cohort − 45 Years of Follow-up. Twin Res. Hum. Genet. Off. J. Int. Soc. Twin Stud. 22, 240–254 (2019).


    Google Scholar
     

  • Klopack, E. T., Carroll, J. E., Cole, S. W., Seeman, T. E. & Crimmins, E. M. Lifetime publicity to smoking, epigenetic growing old, and morbidity and mortality in older adults. Clin. Epigenetics 14, 72 (2022).


    Google Scholar
     

  • Perrier, F. et al. Identifying and correcting epigenetics measurements for systematic sources of variation. Clin. Epigenetics 10, 38 (2018).


    Google Scholar
     

  • Fabregat, A. et al. The Reactome Pathway Knowledgebase. Nucleic Acids Res. 46, D649–D655 (2018).


    Google Scholar
     

  • Liu, G. Y. & Sabatini, D. M. mTOR on the nexus of vitamin, progress, ageing and illness. Nat. Rev. Mol. Cell Biol. 21, 183–203 (2020).


    Google Scholar
     

  • Saxton, R. A. & Sabatini, D. M. mTOR signaling in progress, metabolism, and illness. Cell 168, 960–976 (2017).


    Google Scholar
     

  • Laplante, M. & Sabatini, D. M. mTOR signaling in progress management and illness. Cell 149, 274–293 (2012).


    Google Scholar
     

  • Green, C. L., Lamming, D. W. & Fontana, L. Molecular mechanisms of dietary restriction selling well being and longevity. Nat. Rev. Mol. Cell Biol. 23, 56–73 (2022).


    Google Scholar
     

  • Kaur, N. et al. Multi-organ FGF21-FGFR1 signaling in metabolic well being and illness. Front. Cardiovasc. Med. 9, 962561 (2022).


    Google Scholar
     

  • Zhang, M. et al. INPP4B protects from metabolic syndrome and related issues. Commun. Biol. 4, 1–15 (2021).


    Google Scholar
     

  • Newberry, M., Stec, D. E., Hildebrandt, E., Stec, D. F. & Drummond, H. A. Mice missing ASIC2 and βENaC are shielded from excessive fats dietinduced metabolic syndrome. Front. Endocrinol. 15, 1449344 (2024).

  • Lee, C. F., Nizami, H., Gu, H. & Light, C. SARM1 NAD hydrolase deficiency normalizes fibrosis and ameliorates cardiac dysfunction in diabetic hearts. FASEB J. 36, S1 (2022).

  • Pan, Z.-G. & An, X.-S. SARM1 deletion restrains NAFLD induced by excessive fats weight loss plan (HFD) by decreasing irritation, oxidative stress and lipid accumulation. Biochem. Biophys. Res. Commun. 498, 416–423 (2018).


    Google Scholar
     

  • Fox, F. A. U., Liu, D., Breteler, M. M. B. & Aziz, N. A. Physical exercise is related to slower epigenetic ageing—Findings from the Rhineland examine. Aging Cell 22, e13828 (2023).


    Google Scholar
     

  • Verweij, N., van de Vegte, Y. J. & van der Harst, P. Genetic examine hyperlinks parts of the autonomous nervous system to heart-rate profile throughout train. Nat. Commun. 9, 898 (2018).


    Google Scholar
     

  • Lu, A. T. et al. Universal DNA methylation age throughout mammalian tissues. Nat. Aging 3, 1144–1166 (2023).

  • Raclot, T., Groscolas, R. & Cherel, Y. Fatty acid proof for the significance of myctophid fishes within the weight loss plan of king penguins, Aptenodytes patagonicus. Mar. Biol. 132, 523–533 (1998).


    Google Scholar
     

  • Watkeys, O. J., Kremerskothen, Ok., Quidé, Y., Fullerton, J. M. & Green, M. J. Glucocorticoid receptor gene (NR3C1) DNA methylation in affiliation with trauma, psychopathology, transcript expression, or genotypic variation: a scientific evaluation. Neurosci. Biobehav. Rev. 95, 85–122 (2018).


    Google Scholar
     

  • Ruiz-Raya, F., Noguera, J. C. & Velando, A. Covariation between glucocorticoid ranges and receptor expression modulates embryo growth and postnatal phenotypes in gulls. Horm. Behav. 149, 105316 (2023).


    Google Scholar
     

  • Michael, A. Ok. et al. Cancer/testis antigen PASD1 silences the circadian clock. Mol. Cell 58, 743–754 (2015).


    Google Scholar
     

  • Bishehsari, F., Voigt, R. M. & Keshavarzian, A. Circadian rhythms and the intestine microbiota: from the metabolic syndrome to most cancers. Nat. Rev. Endocrinol. 16, 731–739 (2020).


    Google Scholar
     

  • Lindner, M. et al. Temporal modifications in DNA methylation and RNA expression in a small track fowl: within- and between-tissue comparisons. BMC Genomics 22, 36 (2021).


    Google Scholar
     

  • Bardon, G. et al. RFIDeep: unfolding the potential of deep studying for radio-frequency identification. Methods Ecol. Evol. 14, 2814–2826 (2023).


    Google Scholar
     

  • Schweizer, S., Stoll, P., Houwald, F. von & Baur, B. King penguins in zoos: relating breeding success to husbandry practices. J. Zoo Aquar. Res. 4, 91–98 (2016).


    Google Scholar
     

  • Grover, S. A. et al. Years of life misplaced and wholesome life-years misplaced from diabetes and heart problems in obese and overweight individuals: a modelling examine. Lancet Diabetes Endocrinol. 3, 114–122 (2015).


    Google Scholar
     

  • Zhou, J. et al. BCREval: a computational technique to estimate the bisulfite conversion ratio in WGBS. BMC Bioinformatics 21, 38 (2020).


    Google Scholar
     

  • Farrell, C., Thompson, M., Tosevska, A., Oyetunde, A. & Pellegrini, M. BiSulfite bolt: a bisulfite sequencing evaluation platform. GigaScience 10, giab033 (2021).

  • Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).


    Google Scholar
     

  • Laurent, L. et al. Dynamic modifications within the human methylome throughout differentiation. Genome Res. 20, 320–331 (2010).


    Google Scholar
     

  • Hoff, Ok., Lomsadze, A., Borodovsky, M. & Stanke, M. Whole-genome annotation with BRAKER. Methods Mol. Biol. Clifton NJ 1962, 65–95 (2019).


    Google Scholar
     

  • Paris, J. R. et al. Gene Expression Shifts in Emperor Penguin Adaptation to the Extreme Antarctic Environment. Mol. Ecol. 34, e17552 (2025).


    Google Scholar
     

  • Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).


    Google Scholar
     

  • Kuznetsov, D. et al. OrthoDB v11: annotation of orthologs within the widest sampling of organismal variety. Nucleic Acids Res. 51, D445–D451 (2023).


    Google Scholar
     

  • Hackenberg, M. et al. CpGcluster: a distance-based algorithm for CpG-island detection. BMC Bioinformatics 7, 446 (2006).


    Google Scholar
     

  • Camacho, C. et al. BLAST+: structure and purposes. BMC Bioinformatics 10, 421 (2009).


    Google Scholar
     

  • Akalin, A. et al. methylKit: a complete R bundle for the evaluation of genome-wide DNA methylation profiles. Genome Biol. 13, R87 (2012).


    Google Scholar
     

  • Friedman, J. H., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear fashions through coordinate descent. J. Stat. Softw. 33, 1–22 (2010).


    Google Scholar
     

  • Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects fashions utilizing lme4. J. Stat. Softw. 67, 1–48 (2015).


    Google Scholar
     

  • Jühling, F. et al. metilene: quick and delicate calling of differentially methylated areas from bisulfite sequencing knowledge. Genome Res. 26, 256 (2016).


    Google Scholar
     

  • Piao, Y., Xu, W., Park, Ok. H., Ryu, Ok. H. & Xiang, R. Comprehensive analysis of differential methylation evaluation strategies for bisulfite sequencing knowledge. Int. J. Environ. Res. Public. Health 18, 7975 (2021).


    Google Scholar
     

  • Brooks, M. E. et al. glmmTMB balances pace and suppleness amongst packages for zero-inflated generalized linear combined modeling. R J 9, 378–400 (2017).


    Google Scholar
     

  • Ben-Ari Fuchs, S. et al. GeneAnalytics: an integrative gene set evaluation software for subsequent technology sequencing, RNAseq and microarray knowledge. Omics J. Integr. Biol. 20, 139–151 (2016).


    Google Scholar
     


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