Aging, frailty and complex networks

When people age their mortality rate increases exponentially, following Gompertz’s law. Even so, individuals do not die from old age. Instead, they accumulate age-related illnesses and conditions and so become increasingly vulnerable to death from various external and internal stressors. As a measure of such vulnerability, frailty can be quantified using the frailty index (FI). Larger values of the FI are strongly associated with mortality and other adverse health outcomes. This association, and the insensitivity of the FI to the particular health variables that are included in its construction, makes it a powerful, convenient, and increasingly popular integrative health measure. Still, little is known about why the FI works so well. Our group has recently developed a theoretical network model of health deficits to better understand how changes in health are captured by the FI. In our model, health-related variables are represented by the nodes of a complex network. The network has a scale-free shape or “topology”: a few nodes have many connections with other nodes, whereas most nodes have few connections. These nodes can be in two states, either damaged or undamaged. Transitions between damaged and non-damaged states are governed by the stochastic environment of individual nodes. Changes in the degree of damage of connected nodes change the local environment and make further damage more likely. Our model shows how age-dependent acceleration of the FI and of mortality emerges, even without specifying an age-damage relationship or any other time-dependent parameter. We have also used our model to assess how informative individual deficits are with respect to mortality. We find that the information is larger for nodes that are well connected than for nodes that are not. The model supports the idea that aging occurs as an emergent phenomenon, and not as a result of age-specific programming. Instead, aging reflects how damage propagates through a complex network of interconnected elements.

[1]  Kenneth Rockwood,et al.  Changes with age in the distribution of a frailty index , 2004, Mechanisms of Ageing and Development.

[2]  Thomas B. L. Kirkwood,et al.  Deciphering death: a commentary on Gompertz (1825) ‘On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies’ , 2015, Philosophical Transactions of the Royal Society B: Biological Sciences.

[3]  M. Woodbury,et al.  Time-varying covariates in models of human mortality and aging: multidimensional generalizations of the Gompertz. , 1994, Journal of gerontology.

[4]  I. Rubinfeld,et al.  Accumulating deficits model of frailty and postoperative mortality and morbidity: its application to a national database. , 2013, The Journal of surgical research.

[5]  T. Strandberg,et al.  Frailty in elderly people , 2007, The Lancet.

[6]  A. Mitnitski,et al.  Going from bad to worse: A stochastic model of transitions in deficit accumulation, in relation to mortality , 2006, Mechanisms of Ageing and Development.

[7]  A. Mitnitski,et al.  Mortality in Relation to Frailty in Patients Admitted to a Specialized Geriatric Intensive Care Unit , 2015, The journals of gerontology. Series A, Biological sciences and medical sciences.

[8]  Konstantin G Arbeev,et al.  Resilience Versus Robustness in Aging. , 2016, The journals of gerontology. Series A, Biological sciences and medical sciences.

[9]  A. Mitnitski,et al.  A limit to frailty in very old, community-dwelling people: a secondary analysis of the Chinese longitudinal health and longevity study. , 2013, Age and ageing.

[10]  Ross T Tsuyuki,et al.  Validity and reliability of the Edmonton Frail Scale , 2006, Age and ageing.

[11]  A. Mitnitski,et al.  Standard laboratory tests to identify older adults at increased risk of death , 2014, BMC Medicine.

[12]  Kenneth Rockwood,et al.  Heterogeneity of Human Aging and Its Assessment , 2016, The journals of gerontology. Series A, Biological sciences and medical sciences.

[13]  A. Mitnitski,et al.  Age-related deficit accumulation and the risk of late-life dementia , 2014, Alzheimer's Research & Therapy.

[14]  David Steinsaltz,et al.  Markov models of aging: Theory and practice , 2012, Experimental Gerontology.

[15]  A. Mitnitski,et al.  Limits to deficit accumulation in elderly people , 2006, Mechanisms of Ageing and Development.

[16]  M. Wolfson,et al.  The signaling hubs at the crossroad of longevity and age-related disease networks. , 2009, The international journal of biochemistry & cell biology.

[17]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[18]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[19]  Robi Tacutu,et al.  The NetAge database: a compendium of networks for longevity, age-related diseases and associated processes , 2010, Biogerontology.

[20]  B. Frey,et al.  Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing , 2008, Nature Genetics.

[21]  Kenneth Rockwood,et al.  Changes in relative fitness and frailty across the adult lifespan: evidence from the Canadian National Population Health Survey , 2011, Canadian Medical Association Journal.

[22]  L. Gavrilov,et al.  The reliability theory of aging and longevity. , 2001, Journal of theoretical biology.

[23]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[24]  K. Rockwood,et al.  A procedure for creating a frailty index based on deficit accumulation in aging mice. , 2012, The journals of gerontology. Series A, Biological sciences and medical sciences.

[25]  Konstantin G. Arbeev,et al.  Age trajectories of physiological indices in relation to healthy life course , 2011, Mechanisms of Ageing and Development.

[26]  A. Mitnitski,et al.  Aging as a process of deficit accumulation: its utility and origin. , 2015, Interdisciplinary topics in gerontology.

[27]  Sara A Rafferty,et al.  The impacts of age and frailty on heart rate and sinoatrial node function , 2016, The Journal of physiology.

[28]  Kenneth Rockwood,et al.  Accumulation of Deficits as a Proxy Measure of Aging , 2001, TheScientificWorldJournal.

[29]  A. Budovsky,et al.  Longevity network: Construction and implications , 2007, Mechanisms of Ageing and Development.

[30]  Albert-László Barabási,et al.  A Dynamic Network Approach for the Study of Human Phenotypes , 2009, PLoS Comput. Biol..

[31]  A. Yashin,et al.  Biodemographic trajectories of longevity. , 1998, Science.

[32]  James Waterman Glover United States Life Tables , 2013 .

[33]  David P. Smith,et al.  On the Nature of the Function Expressive of the Law of Human Mortality , 2013 .

[34]  J. P. Magalhães,et al.  A mathematical model of mortality dynamics across the lifespan combining heterogeneity and stochastic effects , 2013, Experimental Gerontology.

[35]  I. Rubinfeld,et al.  Use of a simplified frailty index to predict Clavien 4 complications and mortality after hepatectomy: analysis of the National Surgical Quality Improvement Project database. , 2016, American journal of surgery.

[36]  Leonid A. Gavrilov,et al.  Evolutionary Theories of Aging and Longevity , 2002, TheScientificWorldJournal.

[37]  R. Buckner,et al.  Parcellating Cortical Functional Networks in Individuals , 2015, Nature Neuroscience.

[38]  D. Promislow Protein networks, pleiotropy and the evolution of senescence , 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[39]  Kenneth Rockwood,et al.  Exploring the relationship between national economic indicators and relative fitness and frailty in middle-aged and older Europeans. , 2013, Age and ageing.

[40]  A. Mitnitski,et al.  Frailty in relation to the accumulation of deficits. , 2007, The journals of gerontology. Series A, Biological sciences and medical sciences.

[41]  Robert A. Rose,et al.  A Clinical Frailty Index in Aging Mice: Comparisons With Frailty Index Data in Humans , 2013, The journals of gerontology. Series A, Biological sciences and medical sciences.

[42]  C. Mussi,et al.  A frailty index predicts survival and incident multimorbidity independent of markers of HIV disease severity , 2015, AIDS.

[43]  M. Echteld,et al.  Predicting disabilities in daily functioning in older people with intellectual disabilities using a frailty index. , 2014, Research in developmental disabilities.

[44]  A. Yashin,et al.  Accelerated accumulation of health deficits as a characteristic of aging , 2007, Experimental Gerontology.

[45]  B. Gompertz,et al.  On the Nature of the Function Expressive of the Law of Human Mortality , 1825 .

[46]  Joseph A Hill United States Life Tables , 2013 .

[47]  Benjamin Gompertz,et al.  XXIV. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. In a letter to Francis Baily, Esq. F. R. S. &c , 1825, Philosophical Transactions of the Royal Society of London.

[48]  L Mahadevan,et al.  Aging in complex interdependency networks. , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[49]  Kenneth Rockwood,et al.  Long‐Term Risks of Death and Institutionalization of Elderly People in Relation to Deficit Accumulation at Age 70 , 2006, Journal of the American Geriatrics Society.

[50]  A. Budovsky,et al.  Tissue repair genes: the TiRe database and its implication for skin wound healing , 2016, Oncotarget.

[51]  M. Baron,et al.  Frailty Index to Measure Health Status in People with Systemic Sclerosis , 2014, The Journal of Rheumatology.

[52]  J. Sautter,et al.  Frailty and mortality among Chinese at advanced ages. , 2009, The journals of gerontology. Series B, Psychological sciences and social sciences.

[53]  T. Gill,et al.  A standard procedure for creating a frailty index , 2008, BMC geriatrics.

[54]  Ilia Stambler,et al.  The application of information theory for the research of aging and aging-related diseases , 2017, Progress in Neurobiology.

[55]  Albert-László Barabási,et al.  Endophenotype Network Models: Common Core of Complex Diseases , 2016, Scientific Reports.

[56]  L Mahadevan,et al.  The organization and control of an evolving interdependent population , 2015, Journal of The Royal Society Interface.

[57]  A. Yashin,et al.  Mortality and aging in a heterogeneous population: a stochastic process model with observed and unobserved variables. , 1985, Theoretical population biology.

[58]  T. Kirkwood,et al.  Can aging be programmed? A critical literature review , 2016, Aging cell.

[59]  A. Mitnitski,et al.  A comparison of two approaches to measuring frailty in elderly people. , 2007, The journals of gerontology. Series A, Biological sciences and medical sciences.

[60]  Cole Trapnell,et al.  Targeted RNA sequencing reveals the deep complexity of the human transcriptome , 2011, Nature Biotechnology.

[61]  David W. Johnson,et al.  Feasibility and construct validity of a Frailty index for patients with chronic kidney disease , 2015, Australasian journal on ageing.

[62]  Dynamical network model for age-related health deficits and mortality. , 2016, Physical review. E.

[63]  J. Vaupel,et al.  The impact of heterogeneity in individual frailty on the dynamics of mortality , 1979, Demography.

[64]  T. Spector,et al.  The Identification of Hereditary and Environmental Determinants of Frailty in a Cohort of UK Twins , 2016, Twin Research and Human Genetics.

[65]  E. Milne The natural distribution of survival. , 2008, Journal of theoretical biology.

[66]  Katrien G Luijkx,et al.  The Tilburg Frailty Indicator: psychometric properties. , 2010, Journal of the American Medical Directors Association.

[67]  Kenneth Rockwood,et al.  Age-related frailty and its association with biological markers of ageing , 2015, BMC Medicine.

[68]  A. Yashin,et al.  The quadratic hazard model for analyzing longitudinal data on aging, health, and the life span. , 2012, Physics of life reviews.

[69]  A. Mitnitski,et al.  The rate of aging: the rate of deficit accumulation does not change over the adult life span , 2015, Biogerontology.

[70]  A. Mitnitski,et al.  Network model of human aging: Frailty limits and information measures. , 2016, Physical review. E.

[71]  Suresh I. S. Rattan,et al.  Healthy ageing, but what is health? , 2013, Biogerontology.

[72]  A. Mitnitski,et al.  Assessing biological aging: the origin of deficit accumulation , 2013, Biogerontology.

[73]  A. Mitnitski,et al.  Trajectories of changes over twelve years in the health status of Canadians from late middle age , 2012, Experimental Gerontology.

[74]  M. Loeb,et al.  Aging, frailty and age-related diseases , 2010, Biogerontology.

[75]  E. Arias United States life tables, 2010. , 2014, National vital statistics reports : from the Centers for Disease Control and Prevention, National Center for Health Statistics, National Vital Statistics System.

[76]  B. Strehler,et al.  General theory of mortality and aging. , 1960, Science.

[77]  Kenneth Rockwood,et al.  Operationalization of Frailty Using Eight Commonly Used Scales and Comparison of Their Ability to Predict All‐Cause Mortality , 2013, Journal of the American Geriatrics Society.

[78]  Kenneth Rockwood,et al.  Comparison of alternate scoring of variables on the performance of the frailty index , 2014, BMC Geriatrics.

[79]  A. Yashin,et al.  Uncoupling associations of risk alleles with endophenotypes and phenotypes: insights from the ApoB locus and heart‐related traits , 2016, Aging cell.

[80]  L. Fried,et al.  Frailty in older adults: evidence for a phenotype. , 2001, The journals of gerontology. Series A, Biological sciences and medical sciences.

[81]  Kenneth Rockwood,et al.  Identifying Common Characteristics of Frailty Across Seven Scales , 2014, Journal of the American Geriatrics Society.

[82]  A. Mitnitski,et al.  Socioeconomic gradient in health in Canada: Is the gap widening or narrowing? , 2016, Health policy.