Journals of : BIOLOGICAL SCIENCES © The Author 2013. Published by Oxford University Press on behalf of The Gerontological Society of America. Cite journal as: J Gerontol A Biol Sci Med Sci 2014 July;69(7):777–778 All rights reserved. For permissions, please e-mail: [email protected]. doi:10.1093/gerona/glt202 Advance Access publication December 10, 2013

Guest Editorial Are Glycans the Holy Grail for Biomarkers of Aging? (Comment on: Glycans Are a Novel Biomarker of Chronological and Biological Age by Kristic et al.)

David G. Le Couteur,1,2,3 Stephen J. Simpson,3,4 and Rafael de Cabo5 Downloaded from https://academic.oup.com/biomedgerontology/article/69/7/777/662886 by guest on 24 September 2021

1Centre for Education and Research on and 2ANZAC Research Institute, University of Sydney and Concord Repatriation General Hospital, New South Wales, Australia. 3The Charles Perkins Centre and 4School of Biological Sciences, University of Sydney, Australia. 5Translational Gerontology Branch, National Institute on Ageing, Baltimore.

Address correspondence to David Le Couteur, PhD, Centre for Education and Research on Ageing, University of Sydney and Concord Repatriation General Hospital, Hospital Rd, Concord, Sydney, NSW 2139, Australia. Email: [email protected]

Posttranslational modifications of circulating proteins such as immunoglobulins may prove to be important biomarkers of aging.

Key Words: Biomarkers of aging—Glycans.

Received November 11, 2013; Accepted November 12, 2013

Decision Editor: Rafael de Cabo, PhD

valuating the effect of any intervention that influ- •• It must monitor a basic process that underlies the aging Eences aging requires some sort of endpoint to be meas- process, not the effects of ured, ideally span. Maximum life span is the key outcome •• It must be able to be tested repeatedly without harming influenced primarily by interventions that act on aging and the person or animal is the gold standard. Median life span can also be influenced •• It must be something that works in and in labora- by interventions that prevent disease, thereby squaring popu- tory animals (3) lation survival curves without necessarily extending maxi- From a pragmatic perspective, biomarkers of aging mum life span. Measurement of either median or maximum should also be easy to measure (eg, blood tests) and change life span requires the study of large over their over a relatively short period of time (4). lifetime, which, in long-lived , is an insurmountable In human clinical trials of , surrogate mark- barrier. Thus clinical trials in are unlikely to use life ers and composite outcomes are well-established, if span as an initial primary outcome, and some sort of surrogate sometimes controversial, endpoints that are used to outcome or biomarker of aging is essential. Consequently, facilitate and speed up the development and testing of the discovery of robust and accurate biomarkers of aging has new pharmaceutical agents. Surrogate outcomes such as become a holy grail for aging research. As yet, there is no blood pressure, , and hemoglobin A1c are accepted established set of biological or clinical biomarkers of aging in outcomes for vascular disease and diabetes mellitus, animals or humans, although many have been proposed (1–6). whereas composite outcomes combining , hospi- Various criteria for biomarkers of aging have been put talization, acute coronary syndrome, and angioplasty forward (4,6). The underlying assumption is that any inter- are frequent in cardiovascular prevention trials. We vention that alters a biomarker of aging will, by extrapola- need similar approaches to study aging interventions, tion, also alter the aging process and maximum life span. although this will be much more complex than for For example the American Federation for Aging Research disease-based interventions (4). In 1988, the National concluded that any useful biomarker of aging should fulfill Institute of Aging established an extensive program to a variety of criteria, including the following: develop biomarkers of aging based on studies of mice, •• It must predict the rate of aging and be a better predictor but biomarkers of aging that could be used as surrogates of life span than chronological age alone for aging were not forthcoming (4).

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Some of the biomarkers of aging based on our under- age could be predicted by a combination of glycans, sys- standing of aging biology include inflammatory mark- tolic blood pressure, and FEV1. ers (interleukin 6, tumor necrosis factor alpha, C-reactive As well as being a strong statistical marker of aging, gly- protein), DNA changes (mitochondrial DNA, ), cans are of particular interest because they regulate pro- and and markers of and advanced glycation anti-inflammatory IgG responses by influencing the bind- endproducts (4,6,7). Panels of clinical biomarkers (com- ing of IgG to its various receptors. For example, the age- posite outcomes) that predict age and risk of death have related reduction in IgG galactosylation will increase the been developed from longitudinal human studies, includ- proinflammatory function of IgG. This is of importance, ing anthropometry, muscle strength, serum albumin, blood given the key association of inflammation with aging, a pressure, forced expiratory volume (FEV1), lipoproteins, process termed inflammaging by Franceschi and colleagues Downloaded from https://academic.oup.com/biomedgerontology/article/69/7/777/662886 by guest on 24 September 2021 and cognitive and functional status. Such parameters might (13). The authors conclude with the appropriate epidemio- predict chronological age and risk of death, but many over- logical caveat that the direction of causality between aging lap with typical definitions of disease or disease risk factors. and altered IgG glycosylation is uncertain. Even so, IgG The -omics technologies are promising to generate novel glycans might prove to be significant biomarkers of aging but complicated biomarkers based on patterns of change because of both their strong statistical link with age and in tissue or blood transcriptome, proteasome, metabolome, their plausible mechanistic link with age-related changes in microRNAs, and DNA methylation (7,8). Detailed profiling inflammatory responses. of posttranslational modification of circulating proteins (eg, N-glycans on circulating glycoproteins such as immuno- References globulins) has also generated new biomarkers of aging (9), 1. Ingram DK, Nakamura E, Smucny D, Roth GS, Lane MA. Strategy for and this approach has been promoted for future research on identifying biomarkers of aging in long-lived species. Exp Gerontol. aging and biomarkers (8,10). 2001;36:1025–1034. In this issue of the Journal of Gerontology, a new study 2. Le Couteur DG, McLachlan AJ, Quinn RJ, Simpson SJ, de Cabo R. Aging biology and novel targets for drug discovery. J Gerontol A Biol of the relationship between aging and posttranslational Sci Med Sci. 2012;67:169–174. glycosylation of IgG is reported (11). This study might 3. Johnson TE. Recent results: biomarkers of aging. Exp Gerontol. prove to be a significant advance because of the strong 2006;41:1243–1246. statistical association with chronological age and plau- 4. Sprott RL. Biomarkers of aging and disease: introduction and defini- sible mechanistic contribution to age-related changes in tions. Exp Gerontol. 2010;45:2–4. 5. Butler RN, Sprott RL. Biomarkers of aging: From primitive organisms inflammation. Krištić and colleagues (11) studied 5,117 to man. New York: International Center; 2000. participants ranging in age from 16 to 100 years from four 6. Simm A, Johnson TE. Biomarkers of ageing: A challenge for the different European cohorts—the Croatian island of Vis, the future. Exp Gerontol. 2010;45:731–732. Croatian island of Korcula, Scottish Orkney Islands, and 7. Holly AC, Melzer D, Pilling LC, et al. Towards a gene expression bio- the TwinsUK cohort. There were complicated but strong marker set for human biological age. Aging . 2013;12:324–326. 8. valdes AM, Glass D, Spector TD. Omics technologies and the study relationships between changes in IgG glycosylation and of human ageing. Nat Rev Genet. 2013;14:601–607. age. The greatest impact of age was a reduction of about 9. vanhooren V, Dewaele S, Libert C, et al. Serum N-glycan profile shift 50% in galactosylation. This finding had stood the test of during human ageing. Exp Gerontol. 2010;45:738–743. time, having been reported in 1988 by Parekh and col- 10. Dall’Olio F, Vanhooren V, Chen CC, Slagboom PE, Wuhrer M, leagues (12). They developed an index called GlycanAge, Franceschi C. N-glycomic biomarkers of biological aging and longev- ity: a link with inflammaging.Ageing Res Rev. 2013;12:685–698. which combined three of the IgG glycans and explained 11. Krištić J, Vučković F, Menni C, et al. Glycans are a novel biomarker nearly 60% of chronological age. Then they studied the of chronological and biological age. J Gerontol A Biol Sci Med Sci. In relationship between, age, IgG glycans, and other clini- press. cal biomarkers of aging such as anthropometric measure- 12. Parekh R, Roitt I, Isenberg D, Dwek R, Rademacher T. Age-related ments, lipids, blood pressure, and FEV1. Once again, the galactosylation of the N-linked oligosaccharides of human serum IgG. J Exp Med. 1988;167:1731–1736. IgG glycans proved to be strongly associated with age 13. Franceschi C, Capri M, Monti D, et al. Inflammaging and anti-inflam- when these other markers were taken into account. From maging: a systemic perspective on aging and longevity emerged from about 50 years of age, 71% of variance in chronological studies in humans. Mech Ageing Dev. 2007;128:92–105.