Discrete Changes in Glucose Metabolism Define Aging
Aging is a physiological process in which multifactorial processes determine a progressive decline. Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked...
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| Veröffentlicht in: | Scientific reports 2019-07, Vol.9 (1), p.10347-8, Article 10347 |
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| description | Aging is a physiological process in which multifactorial processes determine a progressive decline. Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked with the aging process that it is possible predict the age of a person on the basis of the modification of one specific pathway, as proposed by Horwath and his aging clock based on DNA methylation. Because the energy metabolism changes are involved in the aging process, in this work, we propose a new aging clock based on the modifications of glucose catabolism. The biochemical analyses were performed on mononuclear cells isolated from peripheral blood, obtained from a healthy population with an age between 5 and 106 years. In particular, we have evaluated the oxidative phosphorylation function and efficiency, the ATP/AMP ratio, the lactate dehydrogenase activity and the malondialdehyde content. Further, based on these biochemical markers, we developed a machine learning-based mathematical model able to predict the age of an individual with a mean absolute error of approximately 9.7 years. This mathematical model represents a new non-invasive tool to evaluate and define the age of individuals and could be used to evaluate the effects of drugs or other treatments on the early aging or the rejuvenation. |
| doi_str_mv | 10.1038/s41598-019-46749-w |
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Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked with the aging process that it is possible predict the age of a person on the basis of the modification of one specific pathway, as proposed by Horwath and his aging clock based on DNA methylation. Because the energy metabolism changes are involved in the aging process, in this work, we propose a new aging clock based on the modifications of glucose catabolism. The biochemical analyses were performed on mononuclear cells isolated from peripheral blood, obtained from a healthy population with an age between 5 and 106 years. In particular, we have evaluated the oxidative phosphorylation function and efficiency, the ATP/AMP ratio, the lactate dehydrogenase activity and the malondialdehyde content. Further, based on these biochemical markers, we developed a machine learning-based mathematical model able to predict the age of an individual with a mean absolute error of approximately 9.7 years. This mathematical model represents a new non-invasive tool to evaluate and define the age of individuals and could be used to evaluate the effects of drugs or other treatments on the early aging or the rejuvenation.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/s41598-019-46749-w</identifier><identifier>PMID: 31316102</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>13/95 ; 631/45/47 ; 692/53/2423 ; Adenosine Triphosphate - metabolism ; Adolescent ; Adult ; Age ; Aged ; Aged, 80 and over ; Aging ; Aging - metabolism ; AMP ; Autophagy ; Biochemical markers ; Biomarkers - metabolism ; Child ; Child, Preschool ; DNA methylation ; Energy Metabolism ; Epigenetics ; Female ; Glucose - metabolism ; Humanities and Social Sciences ; Humans ; L-Lactate dehydrogenase ; Lactic acid ; Learning algorithms ; Leukocytes (mononuclear) ; Leukocytes, Mononuclear - metabolism ; Machine Learning ; Male ; Malondialdehyde ; Malondialdehyde - metabolism ; Mathematical models ; Metabolism ; Middle Aged ; Mitochondria - metabolism ; Models, Biological ; multidisciplinary ; Oxidative Phosphorylation ; Oxidative stress ; Peripheral blood mononuclear cells ; Phagocytosis ; Phosphorylation ; Science ; Science (multidisciplinary) ; Young Adult</subject><ispartof>Scientific reports, 2019-07, Vol.9 (1), p.10347-8, Article 10347</ispartof><rights>The Author(s) 2019</rights><rights>2019. 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Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked with the aging process that it is possible predict the age of a person on the basis of the modification of one specific pathway, as proposed by Horwath and his aging clock based on DNA methylation. Because the energy metabolism changes are involved in the aging process, in this work, we propose a new aging clock based on the modifications of glucose catabolism. The biochemical analyses were performed on mononuclear cells isolated from peripheral blood, obtained from a healthy population with an age between 5 and 106 years. In particular, we have evaluated the oxidative phosphorylation function and efficiency, the ATP/AMP ratio, the lactate dehydrogenase activity and the malondialdehyde content. Further, based on these biochemical markers, we developed a machine learning-based mathematical model able to predict the age of an individual with a mean absolute error of approximately 9.7 years. This mathematical model represents a new non-invasive tool to evaluate and define the age of individuals and could be used to evaluate the effects of drugs or other treatments on the early aging or the rejuvenation.</description><subject>13/95</subject><subject>631/45/47</subject><subject>692/53/2423</subject><subject>Adenosine Triphosphate - metabolism</subject><subject>Adolescent</subject><subject>Adult</subject><subject>Age</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging</subject><subject>Aging - metabolism</subject><subject>AMP</subject><subject>Autophagy</subject><subject>Biochemical markers</subject><subject>Biomarkers - metabolism</subject><subject>Child</subject><subject>Child, Preschool</subject><subject>DNA methylation</subject><subject>Energy Metabolism</subject><subject>Epigenetics</subject><subject>Female</subject><subject>Glucose - metabolism</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>L-Lactate dehydrogenase</subject><subject>Lactic acid</subject><subject>Learning algorithms</subject><subject>Leukocytes (mononuclear)</subject><subject>Leukocytes, Mononuclear - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ravera, Silvia</au><au>Podestà, Marina</au><au>Sabatini, Federica</au><au>Dagnino, Monica</au><au>Cilloni, Daniela</au><au>Fiorini, Samuele</au><au>Barla, Annalisa</au><au>Frassoni, Francesco</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discrete Changes in Glucose Metabolism Define Aging</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2019-07-17</date><risdate>2019</risdate><volume>9</volume><issue>1</issue><spage>10347</spage><epage>8</epage><pages>10347-8</pages><artnum>10347</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Aging is a physiological process in which multifactorial processes determine a progressive decline. Several alterations contribute to the aging process, including telomere shortening, oxidative stress, deregulated autophagy and epigenetic modifications. In some cases, these alterations are so linked with the aging process that it is possible predict the age of a person on the basis of the modification of one specific pathway, as proposed by Horwath and his aging clock based on DNA methylation. Because the energy metabolism changes are involved in the aging process, in this work, we propose a new aging clock based on the modifications of glucose catabolism. The biochemical analyses were performed on mononuclear cells isolated from peripheral blood, obtained from a healthy population with an age between 5 and 106 years. In particular, we have evaluated the oxidative phosphorylation function and efficiency, the ATP/AMP ratio, the lactate dehydrogenase activity and the malondialdehyde content. Further, based on these biochemical markers, we developed a machine learning-based mathematical model able to predict the age of an individual with a mean absolute error of approximately 9.7 years. This mathematical model represents a new non-invasive tool to evaluate and define the age of individuals and could be used to evaluate the effects of drugs or other treatments on the early aging or the rejuvenation.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>31316102</pmid><doi>10.1038/s41598-019-46749-w</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0002-3436-035X</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | 13/95 631/45/47 692/53/2423 Adenosine Triphosphate - metabolism Adolescent Adult Age Aged Aged, 80 and over Aging Aging - metabolism AMP Autophagy Biochemical markers Biomarkers - metabolism Child Child, Preschool DNA methylation Energy Metabolism Epigenetics Female Glucose - metabolism Humanities and Social Sciences Humans L-Lactate dehydrogenase Lactic acid Learning algorithms Leukocytes (mononuclear) Leukocytes, Mononuclear - metabolism Machine Learning Male Malondialdehyde Malondialdehyde - metabolism Mathematical models Metabolism Middle Aged Mitochondria - metabolism Models, Biological multidisciplinary Oxidative Phosphorylation Oxidative stress Peripheral blood mononuclear cells Phagocytosis Phosphorylation Science Science (multidisciplinary) Young Adult |
| title | Discrete Changes in Glucose Metabolism Define Aging |
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