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Current Opinion in HIV & AIDS:
doi: 10.1097/COH.0000000000000070
HIV AND AGING: Edited by Amy C. Justice and Julian Falutz

Biologic aging, frailty, and age-related disease in chronic HIV infection

Brothers, Thomas D.a,b; Rockwood, Kennetha,c

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aGeriatric Medicine Research

bFaculty of Medicine, Dalhousie University

cCentre for Healthcare of the Elderly, QEII Health Sciences Centre, Capital District Health Authority, Halifax, Nova Scotia, Canada

Correspondence to Kenneth Rockwood, Geriatric Medicine Research, Dalhousie University, 1421-5955 Veterans’ Memorial Lane, Halifax, NS, Canada B3H 2E1. Tel: +1 902 473 8631; fax: +1 902 473 4908; e-mail:

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Purpose of review: Effective therapies have transformed HIV infection into a chronic disease, and new problems are arising related to aging. This article reviews the aging process, age-related deficit accumulation and frailty, and how these might be affected by chronic HIV infection.

Recent findings: Aging is characterized by acceleration in the rate of unrepaired physiologic damage an organism accumulates. HIV infection is associated with many factors that might affect the aging process, including extrinsic behavioral risk factors and co-infections, and multiple intrinsic factors, including intercellular communication, inflammation, and coagulation pathways. Whether each factor affects the aging process, they likely result in an increase in the risk of adverse health outcomes, and so give rise to frailty, likely with several clinical manifestations.

Summary: Age-related deficit accumulation is influenced by both the background or environmental rate of insults an organism sustains and the efficacy of intrinsic damage control and repair mechanisms. Both processes are likely affected in people living with HIV infection.

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Effective therapies have transformed HIV infection into a chronic disease, and many HIV-positive people with access to treatment are living to near-normal life expectancies [1,2▪]. With this success, new challenges arise related to aging with HIV and its lifelong treatment. People living with HIV exhibit higher rates of many age-related health problems, including cardiovascular disease, certain cancers, cognitive and renal impairment, bone demineralization, and age-related immune dysregulation [3]. In consequence, a contested theory has emerged that this might represent a form of ‘accelerated’ or ‘premature’ aging [4]. The purpose of this review is to discuss what aging is, its relationship with health, disease, and frailty, and how these might be affected by chronic HIV infection.

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On average, as people grow older they are more likely to die. They also become more and more likely to experience health problems, including disease, mobility and functional limitations, and cognitive impairment. This trend can be described as acceleration in the rate of unrepaired damage an organism sustains, which characterizes aging and helps differentiate it from the concept of chronological age. This is classically described by the Gompertz law of mortality [5]: that is, the key to distinguishing age from aging is that the latter results in an increase in the hazard rate – which occurs, for example, each year after age 15 but which falls from the perinatal months to the early teenage years. Accelerating hazard rates have been observed across species [6].

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Hallmarks of aging

Aging happens, even among the fittest and healthiest of us. This damage is largely intrinsic, representing the byproducts of lifelong metabolic processes at cellular and subcellular levels. Current understanding describes various ‘hallmarks’ of aging, which have been reviewed elsewhere [7▪▪]. These processes are complex, but in general terms, a well accepted view is that aging is characterized by an accumulation of near-random damage throughout the life course, which appears to also occur consistently within telomeres [8,9], dysfunction in the mechanisms that stabilize and guide protein folding [10], and DNA and posttranslational epigenetic changes [11]. Compensatory mechanisms initially repair or mitigate this damage, but can cause further damage when they are chronically activated or engaged; these include mitochondrial dysfunction, leading to accumulation of reactive oxygen species (ROS) and less efficient ATP generation [12], and cellular senescence, arresting cellular growth after a finite number of divisions [7▪▪]. Both primary and compensatory mechanisms contribute to the exhaustion of stem cells and regenerative potential of tissue with age, and also alter intercellular communication, leading to a progressive proinflammatory state at older ages [7▪▪].

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The observation of this chronic proinflammatory state has given rise to the ‘inflammaging’ hypothesis of aging [7▪▪,13]. Like other characteristic processes of aging, inflammaging has multiple potential contributory sources, including the tissue damage and accompanying inflammatory response, pathogens and problematic host cells not fully cleared by the immune system, and senescent cells with a propensity to secrete proinflammatory cytokines [13,14]. Chronic inflammation causes or is exacerbated by multiple age-related diseases, including obesity, type II diabetes, and atherosclerosis, which in turn might lead to the more rapid accumulation of further deficits [13].

Inflammation and age-related immune system dysfunction have been particularly implicated in the greater prevalence of age-related health problems observed in people aging with treated HIV infection [14]. Higher levels of biomarkers of inflammation (IL-6), altered coagulation (D-dimer), and monocyte activation (sCD14) have been observed among HIV-positive individuals with CD4 depletion and ongoing virus replication, compared with HIV-negative individuals [15]. Data from the Strategies for Management of Antiretroviral Therapy (SMART) trial showed significantly greater IL-6 and D-dimer increases among people randomized to receive interrupted, CD4-guided antiretroviral therapy (ART) compared with those randomized to receive continuous ART, and that IL-6 and D-dimer were strongly associated with all-cause mortality [16]. Further SMART data identified higher rates of cardiovascular, renal, and hepatic disease in the interrupted-treatment group [17]. Proposed mechanisms between chronic inflammation and the greater risk for specific age-associated diseases observed in HIV infection have been reviewed in detail elsewhere [14,18–20].

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Age-related damage and repair

As damage goes unrepaired and accumulates with aging, further damage becomes more likely. The dominant view of cellular aging is that subcellular, cellular, and intercellular damage progress to deficits at the level of tissue and organs (which might be identified by laboratory or imaging tests before they become clinically apparent), and eventually at higher level functions, including functional dependence, falls, immobility, and cognitive impairment [21▪▪]. The mechanisms of this scaling process are complex and not yet fully understood, but the notion that health problems make an individual more likely to develop further health problems is a plausible one [22]. Problems in one physiological system also contribute to vulnerability in others, and though the individual effects of a deficit can be small their cumulative effects can be large [23,24▪]. This is characteristic of the ‘atypical’ disease presentation often seen in frail older adults. In a common example, a frail older adult with bacterial pneumonia might present with falls and without the cough, fever, or elevated leukocytes seen in younger, fitter adults with bacterial pneumonia [25].

It is important to recall this damage is largely intrinsic, and as a byproduct of living it is experienced throughout the life course. For this damage to become a deficit, it must go unrepaired. The involvement of maintenance and repair mechanisms throughout the aging process has been noted [7▪▪,26,27]. Such repair mechanisms contribute to the complex and stochastic nature of damage and deficit accumulation [28▪▪]. They also suggest that change with aging is not always deteriorative, improvement is also possible [29,30].

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Alternative accounts of cellular aging

More recent work on aging has revealed processes other than widespread age-related deficit accumulation in cells. A great body of evidence points to an important role for cellular senescence, in which cells undergo irreversible growth arrest. Senescent cells exhibit features notable in the deficit accumulation account: extensive gene-expression changes, increased cell size and protein content, and changes in cell and organelle shape [31]. Originally understood as a protective response to potentially oncogenic events, such as telomere shortening, DNA damage and mutations, protein aggregation, and increased ROS, senescent cells instead have a ‘senescence-associated secretory phenotype’ (SASP) that elaborates a variety of factors that promote not only low-level chronic inflammatory damage, but also cancer [31]. Importantly, then, the accumulation of senescent cells might be implicated in tissue damage associated with aging (sometimes otherwise viewed as too little cellular activity) and with cancer (being too much cellular activity) [32].

One account of how cellular aging comes about sees it not as a matter of accumulated random damage, but rather the result of cell programs gone awry. The mammalian target of rapamycin pathway in particular is implicated: it responds to a variety of nutrients, so that aging is a byproduct of specific metabolic processes in a so-called hyperfunction theory of aging [33,34].

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Heterogeneity in aging processes

No matter what the mechanism, how individuals age is influenced by the background or environmental rate of insults, the efficacy of their intrinsic damage control and recovery mechanisms, and interactions between the two [28▪▪]. These processes are also influenced by extrinsic factors experienced throughout the life course. For example, in Canadian [35] and Chinese [36] cohorts, smokers accumulated more deficits at a given age than nonsmokers. European residents who were born in low-income or middle-income countries accumulated more deficits than native-born Europeans of the same age [37].

People living with HIV infection often experience high rates of such environmental insults, including smoking, alcohol and drug use, co-infections, and psychosocial stressors, as well as the cumulative toxic effects of long-term antiretroviral use [3,15,38]. These same factors likely also influence damage control and repair mechanisms, as might the natural history of the virus itself. This is illustrated in part by altered intercell communication observed in HIV infection, characterized by the chronic inflammatory and hypercoagulable state described above, as well as mitochondrial dysfunction [39]. Emerging data further reinforce the importance of this interaction between the rate of insults and the efficacy of damage repair mechanisms in chronic viral infection [19]. Cytomegalovirus (CMV) infection, for example, remodels the immune system, but its effects on poor health (and its role as an independent risk factor for mortality) are not demonstrable until older ages when other deficits accumulate [40]. CMV co-infection has also been implicated in the hyperinflammatory state observed in HIV-positive individuals who respond to antiretroviral treatment [41,42].

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Although aging happens to everyone, not everyone ages the same way. Indeed, two people of the same age might experience very different levels of health. This variable risk of poor health in people of the same age is known as ‘frailty’ [21▪▪]. Frailty is recognized as a condition of increased vulnerability to stressors, associated with an impaired homeostatic response and increased likelihood of multiple adverse health outcomes, including falls, delirium, disability, and death [21▪▪]. Homeostatic mechanisms normally decline with aging, so that the notion of greater decline relative to other people of the same age is key; even so, it is the case that at some static, uncommonly high age (notionally in the 10th decade) all older adults are frail, in the sense of being at some very high risk of adverse health outcomes. This is commonly manifested when a relatively small insult can result in a disproportionately negative response [21▪▪]. In consequence, a great deal of effort has gone into identifying who is in the risk state before adverse consequences occur. Counting deficits is one useful way to quantify frailty [25,43▪]. As people accumulate health deficits and become frailer, they are both more likely to accumulate further health deficits (i.e. an acceleration in the hazard rate) and more likely to experience changes in health state (e.g. from independent to dependent, mobile to immobile, lucid to delirious, or alive to dead) [21▪▪].

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Frailty as a syndrome or a state

Many tools exist to assess frailty, and these different tools count different groups of health deficits [43▪]. They differ especially in being informed by two contrasting conceptual models: the frailty phenotype and the frailty index [21▪▪]. The frailty phenotype views frailty as a clinical syndrome, originating in a ‘cycle of frailty’ comprised of undernutrition, sarcopenia, and weakness and impaired exercise tolerance [44]. To operationalize this, the frailty phenotype in effect counts five specific health deficits: unintentional weight loss, impaired grip strength and walking speed, fatigue, and decreased activity levels [45]. An individual is frail if they exhibit three of these five health deficits. This approach suggests that the pathophysiology of frailty is distinct from aging or other disease processes.

The frailty index (first proposed by members of our group) views frailty as a state, rather than a specific syndrome, representing the cumulative effects of multiple nonspecific health deficits that might arise through the aging process [46]. The approach is very robust, and remarkably, as long as enough items are counted, appears to lead to comparable results even when different items are included in different versions of the frailty index. In other words, a frailty index can include any variable measuring an age-related health deficit, as long as at least around 30 are selected which cover a range of physiological systems [47]. Each deficit should be associated with adverse health outcomes and with age, have a prevalence of at least 1%, and not become universal with age. For each selected variable, an individual should be assigned 1 if a deficit is fully expressed and 0 if a deficit is absent. For intermediate values (e.g. ‘good’ or ‘fair’ self-rated health), individuals can be assigned relevant fractions (e.g. 0.33, 0.66, etc.) although it is not necessary to do more than dichotomize [48]. By calculating the proportion of deficits an individual has accumulated out of the total number of items measured, this assesses the severity of frailty. Other scales often include more health variables those specified by the frailty phenotype, and fewer than the generally 30 or more used in the frailty index approach [49▪].

Many frailty scales demonstrate ability to grade vulnerability and to do so better than chronological age alone. Even so, different scales vary in their prognostic abilities and operational feasibility [49▪]. The frailty phenotype has been extensively studied and widely validated for multiple adverse health outcomes. It appears to be insensitive to changes in frailty severity and relatively nonspecific (especially in relation to comorbidities, such as cancer, parkinsonism, or musculoskeletal disorders, which might influence the presence or absence of the specific criteria). Additional items have been proposed to make up an expanded frailty phenotype, including affect and cognition [50,51]; on the other hand, some have proposed removing items so as to simplify the phenotype [52].

The frailty index has been widely applied across different populations, using different sets and different numbers of variables [29]. Consistent findings include that frailty index values increase nonlinearly with age after age 50 (by 3% with each year of age, on a log scale), and there appears to be an upper limit to deficit accumulation (around about 0.7) beyond which survival is not possible. Because at least 30 health variables are required, this might make it less convenient to apply in some settings. Clinically, frailty indexes have been created using electronic medical records [53] and comprehensive geriatric assessments (CGAs) [54,55▪,56,57].

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Frailty in people aging with HIV infection

Data on frailty in people with HIV are rapidly emerging from cohort and clinical studies. Reports to date use frailty scales that count a limited number of age-related health deficits; most are based on the frailty phenotype [58,59▪▪,60]. Although methodological differences in the frailty scales used limit meaningful comparisons of frailty prevalence estimates between studies, some consistent findings reinforce the notion of frailty quantifying heterogeneity in the aging process. Similar to findings in HIV-negative individuals, frailty levels are higher in HIV-positive individuals with less formal education [61,62▪,63▪▪], who are unemployed or who have lower incomes [61,64], or who have comorbidities not included in the frailty scale, including diabetes [63▪▪], kidney disease [63▪▪], depressive symptoms [61,62▪,63▪▪], hepatitis C co-infection [65], and markers of chronic inflammation (IL-6, D-dimer, and sCD14) [66].

Frailty is positively associated with traditional markers of HIV disease and vulnerability, including current and nadir CD4 count [61,62▪,63▪▪,65,67–69], and presence of a detectable viral load [62▪,63▪▪]. Among a cohort of people who inject drugs, HIV-positive participants with advanced HIV disease (defined as CD4 <350 cells/μl and detectable viral load) were more likely to be frail than HIV-negative participants, whereas HIV-positive participants without advanced HIV disease were not more likely to be frail [62▪]. One longitudinal analysis of the Multicenter AIDS Cohort Study (MACS) from 2007 to 2011 found that HIV-positive participants with a history of AIDS were more likely to become frail than HIV-negative participants, whereas HIV-positive participants with no history of AIDS were not [63▪▪].

Limited data exist on frailty in relation to outcomes in HIV infection, and further work is needed. In a cohort of people who inject drugs, being HIV-positive or being frail was each associated with three times higher odds of death, whereas being both HIV-positive and frail was associated with seven times higher odds [62▪]. In the MACS, participants who were frail before starting ART had shorter time to AIDS or death [70].

Of particular interest is the widely investigated Veterans Ageing Cohort Study (VACS) index. The VACS index was originally developed to assess health status and predict death in people with chronic HIV infection, and has recently been proposed as a frailty measure in this population [59▪▪]. The index includes traditional HIV-related measures, including CD4 count and viral load, other deficits including hepatitis C virus co-infection, liver fibrosis, hemoglobin, kidney function, as well as race and age.

Data from studies employing the VACS index can help illustrate the association between deficit accumulation, frailty, and the emergence of age-related disease across multiple physiological systems. VACS index scores are associated with multiple health problems common with aging and frailty: inflammation (IL-6, D-dimer, and sCD14) [66], distal muscle weakness [71], fragility fractures [59▪▪], cognitive impairment [72▪], coronary heart disease-related mortality [73], and all-cause mortality [66,74▪].

Notwithstanding these points of similarity, the VACS index differs from frailty measures developed in HIV-negative populations, as it includes chronological age and race [74▪]. Most frailty scales do not include age as a variable, as they intend to describe the cumulative effects of multiple biological age-related health changes, including the possibility of improvement [75]. Most frailty scales also do not include race, which obviously does not change with age. Although it can reasonably be argued that as a measure of vulnerability, frailty scales could include all variables which improve the prediction of adverse outcomes, different patterns have been observed between the accumulation of social deficits [76] and general health deficits [43▪,76]. The VACS index also includes variable weightings derived from the VACS study to optimize its prognostic abilities. Weighting of deficits is uncommon in frailty scales, as variable weights derived from one sample can limit generalizability to other populations [49▪]. Even so, as described above, the VACS index has identified vulnerability for outcomes in addition to death, including many collinear with frailty, and its variable weightings have demonstrated notable stability in validation datasets [74▪].

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How best to measure frailty in people living with HIV?

In the current highly active antiretroviral treatment era, in which most HIV-positive people with access to therapy experience long-term immune reconstitution and suppression of viral load below detectable levels, which frailty scale is best or most informative has not been established [58]. This is not surprising, as there is also no consensus on which frailty scale is best to use in geriatric practice in general [49▪]. The best frailty scale to use might also depend on the setting in which it is used, whether as a convenient screening tool to signal a need for follow-up or as a more comprehensive evaluation.

Special considerations might apply to those aging with HIV infection, however, as HIV-positive and HIV-negative people might experience characteristically different risk profiles with age. Perhaps scales measuring frailty in people aging with HIV should include measures of behavioral risk factors for illness, of chronic viral co-infections, or of surrogate laboratory measures known to be influenced by HIV infection. Although these factors might contribute to vulnerability in people aging with HIV, this might represent something else in addition to the frailty that has been identified in HIV-negative older adult populations in geriatric medicine. Here, the frailty index approach might prove useful. As noted, a frailty index can be comprised of many different variables that assess age-related health, and deficits can be included or excluded as long as there are at least around 30 included that meet the few stated criteria. No published studies have yet evaluated the frailty index among people aging with HIV.

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Aging, characterized by acceleration in the accumulation of unrepaired health deficits over time, is influenced by both the rate of insults an organism sustains and the efficacy of damage maintenance and repair mechanisms. Both of these processes are likely affected in complex and heterogeneous ways among people aging with HIV infection. Differences in aging can be assessed and quantified by counting these deficits, through the concept of frailty. Patterns of aging, deficit accumulation, and frailty are not yet well understood in HIV infection, and this perspective may add to understanding about aging and age-related disease in this population.

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Conflicts of interest

K.R. assigned copyright of a frailty instrument called the Clinical Frailty Scale to Dalhousie University. Several prior publications indicated that K.R. intended to commercialize two frailty measures, but this is no longer the case. When people write to ask for permission to use the scale, they are asked not to modify and commercialize the instruments. If they are doing it for a commercial research organization, Dalhousie has a fee schedule that they follow for any such instrument. T.D.B. reports no conflicts of interest.

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Papers of particular interest, published within the annual period of review, have been highlighted as:

▪ of special interest

▪▪ of outstanding interest

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1. Sabin CA. Do people with HIV infection have a normal life expectancy in the era of combination antiretroviral therapy? BMC Med 2013; 11:251.

2▪. Guaraldi G, Cossarizza A, Franceschi C, et al. Life expectancy in the immune recovery era: the evolving scenario of the HIV epidemic in northern Italy. J Acquir Immune Defic Syndr 2014; 65:175–181.

This study of a large Italian HIV-positive cohort described increasing rates of immune reconstitution over time, and a positive association between immune reconstitution and life expectancy.

3. Deeks SG, Lewin SR, Havlir DV. The end of AIDS: HIV infection as a chronic disease. Lancet 2013; 382:1525–1533.

4. Pathai S, Bajillan H, Landay AL, High KP. Is HIV a model of accelerated or accentuated aging? J Gerontol A Biol Sci Med Sci 2013; . [Epub ahead of print].

5. Gompertz B. 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. Philos Trans R Soc Lond 1825; 115:513–583.

6. Strulik H, Vollmer S. Long-run trends of human aging and longevity. J Popul Econ 2013; 26:1303–1323.

7▪▪. López-Otín C, Blasco MA, Partridge L, et al. The hallmarks of aging. Cell 2013; 153:1194–1217.

This review paper outlines current understanding of ‘hallmarks’ that characterize the aging process.

8. Moskalev AA, Shaposhnikov MV, Plyusnina EN, et al. The role of DNA damage and repair in aging through the prism of Koch-like criteria. Ageing Res Rev 2013; 12:661–684.

9. Armanios M. Telomeres and age-related disease: how telomere biology informs clinical paradigms. J Clin Invest 2013; 123:996–1002.

10. Powers ET, Morimoto RI, Dillin A, et al. Biological and chemical approaches to diseases of proteostasis deficiency. Annu Rev Biochem 2009; 78:959–991.

11. Talens RP, Christensen K, Putter H, et al. Epigenetic variation during the adult lifespan: cross-sectional and longitudinal data on monozygotic twin pairs. Aging Cell 2012; 11:694–703.

12. Green DR, Galluzzi L, Kroemer G. Mitochondria and the autophagy–inflammation–cell death axis in organismal aging. Science 2011; 333:1109–1112.

13. Salminen A, Kaarniranta K, Kauppinen A. Inflammaging: disturbed interplay between autophagy and inflammasomes. Aging (Albany NY) 2012; 4:166- L 175.

14. Deeks SG. HIV infection, inflammation, immunosenescence, and aging. Annu Rev Med 2011; 62:141–155.

15. Armah KA, McGinnis K, Baker J, et al. HIV status, burden of comorbid disease, and biomarkers of inflammation, altered coagulation, and monocyte activation. Clin Infect Dis 2012; 55:126–136.

16. Kuller LH, Tracy R, Belloso W, et al. Inflammatory and coagulation biomarkers and mortality in patients with HIV infection. PLoS Med 2008; 5:e203.

17. Strategies for Management of Antiretroviral Therapy (SMART) Study Group. CD4+ count-guided interruption of antiretroviral treatment. N Engl J Med 2006; 355:2283–2296.

18. Hearps AC, Martin GE, Rajasuriar R, Crowe SM. Inflammatory co-morbidities in HIV+ individuals: learning lessons from healthy ageing. Curr HIV/AIDS Rep 2014; 11:20–34.

19. Deeks SG, Tracy R, Douek DC. Systemic effects of inflammation on health during chronic HIV infection. Immunity 2013; 39:633–645.

20. Plaeger SF, Collins BS, Musib R, et al. Immune activation in the pathogenesis of treated chronic HIV disease: a workshop summary. AIDS Res Hum Retroviruses 2012; 28:469–477.

21▪▪. Clegg A, Young J, Iliffe S, et al. Frailty in elderly people. Lancet 2013; 381:752–762.

This review explains the current understanding and evidence regarding frailty to a general medical audience.

22. Howlett SE, Rockwood K. New horizons in frailty: ageing and the deficit-scaling problem. Age Ageing 2013; 42:416–423.

23. Song X, Mitnitski A, Rockwood K. Nontraditional risk factors combine to predict Alzheimer disease and dementia. Neurology 2011; 77:227–234.

24▪. Wallace LMK, Theou O, Kirkland SA, et al. Accumulation of nontraditional risk factors for coronary heart disease is associated with incident coronary heart disease hospitalization and death. PLoS One 2014; 9:e90475.

This study shows an association between the accumulation of general health deficits and incident coronary-heart-disease-specific outcomes.

25. Moorhouse P, Rockwood K. Frailty and its quantitative clinical evaluation. J R Coll Physicians Edinb 2011; 42:333–340.

26. Kirkwood TB. Understanding the odd science of aging. Cell 2005; 120:437–447.

27. Kirkwood TBL. Systems biology of ageing and longevity. Philos Trans R Soc Lond B Biol Sci 2011; 366:64–70.

28▪▪. Mitnitski A, Song X, Rockwood K. Assessing biological aging: the origin of deficit accumulation. Biogerontology 2013; 14:709–717.

This study presents and tests a model for the interacting effects on deficit accumulation of background insult rates and repair mechanism efficacy.

29. Rockwood K, Mitnitski A. Frailty defined by deficit accumulation and geriatric medicine defined by frailty. Clin Geriatr Med 2011; 27:17–26.

30. Steinsaltz D, Mohan G, Kolb M. Markov models of aging: theory and practice. Exp Gerontol 2012; 47:792–802.

31. Tchkonia T, Zhu Y, van Deursen J, et al. Cellular senescence and the senescent secretory phenotype: therapeutic opportunities. J Clin Invest 2013; 123:966–972.

32. Ohtani N, Hara E. Roles and mechanisms of cellular senescence in regulation of tissue homeostasis. Cancer Sci 2013; 104:525–530.

33. Blagosklonny MV. Prospective treatment of age-related diseases by slowing down aging. Am J Pathol 2012; 181:1142–1146.

34. Blagosklonny MV. Hormesis does not make sense except in the light of TOR-driven aging. Aging (Albany NY) 2011; 3:1051–1062.

35. Hubbard RE, Searle SD, Mitnitski A, Rockwood K. Effect of smoking on the accumulation of deficits, frailty and survival in older adults: a secondary analysis from the Canadian Study of Health and Aging. J Nutr Health Aging 2009; 13:468–472.

36. Wang C, Song X, Mitnitski A, et al. Gender differences in the relationship between smoking and frailty: results from the Beijing Longitudinal Study of Aging. J Gerontol A Biol Sci Med Sci 2013; 68:338–346.

37. Brothers TD, Theou O, Rockwood K. Frailty and migration in middle-aged and older Europeans. Arch Gerontol Geriatr 2014; 58:63–68.

38. Armah KA, Quinn EK, Cheng DM, et al. Human immunodeficiency virus, hepatitis C, and inflammatory biomarkers in individuals with alcohol problems: a cross-sectional study. BMC Infect Dis 2013; 13:399.

39. Pérez-Matute P, Pérez-Martínez L, Blanco JR, Oteo JA. Role of mitochondria in HIV infection and associated metabolic disorders: focus on nonalcoholic fatty liver disease and lipodystrophy syndrome. Oxid Med Cell Longev 2013; 2013:493413.

40. Koch S, Solana R, Dela Rosa O, Pawelec G. Human cytomegalovirus infection and T cell immunosenescence: a mini review. Mech Aging Dev 2006; 127:538–543.

41. Naeger DM, Martin JN, Sinclair E, et al. Cytomegalovirus-specific T cells persist at very high levels during long-term antiretroviral treatment of HIV disease. PLoS One 2010; 5:e8886.

42. Hunt PW, Martin JN, Sinclair E, et al. Valganciclovir reduces T cell activation in HIV-infected individuals with incomplete CD4+ T cell recovery on antiretroviral therapy. J Infect Dis 2011; 203:1474–1483.

43▪. Theou O, Brothers TD, Peña FG, Mitnitski A, Rockwood K. Identifying common characteristics of frailty across seven scales. J Am Geriatr Soc 2014; . [Epub ahead of print].

This study found that different frailty scales exhibit common characteristics of general, age-related deficit accumulation, even though they are based on different conceptual models and include different groups of specific deficits.

44. Walston J. Frailty: the search for underlying causes. Sci Aging Knowledge Environ 2004; 2004:e4.

45. Fried L, Tangen C, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001; 56:M146–M156.

46. Mitnitski AB, Mogilner AJ, Rockwood K. Accumulation of deficits as a proxy measure of aging. ScientificWorldJournal 2001; 1:323–336.

47. Searle SD, Mitnitski A, Gahbauer EA, et al. A standard procedure for creating a frailty index. BMC Geriatr 2008; 8:24.

48. Pena F, Theou O, Wallace L, et al. Comparison of alternate scoring of variables on the performance of the frailty index. BMC Geriatr 2014; 14:25.

49▪. Theou O, Brothers TD, Mitnitski A, Rockwood K. Operationalization of frailty using eight scales and comparison of their ability to predict all-cause mortality. J Am Geriatr Soc 2013; 61:1537–1551.

This study found differences in the feasibility, predictive ability, and frailty prevalence estimates among eight commonly used frailty scales when operationalized in the large Survey or Health, Ageing, and Retirement in Europe (SHARE) longitudinal cohort study.

50. Sourial N, Bergman H, Karunananthan S, et al. Contribution of frailty markers in explaining differences among individuals in five samples of older persons. J Gerontol A Biol Sci Med Sci 2012; 67:1197–1204.

51. Sternberg SA, Schwartz AW, Karunananthan S, et al. The identification of frailty: a systematic literature review. J Am Geriatr Soc 2011; 59:2129–2138.

52. Rothman MD, Leo-Summers L, Gill TM. Prognostic significance of potential frailty criteria. J Am Geriatr Soc 2008; 56:2211–2216.

53. Drubbel I, de Wit NJ, Bleijenberg N, et al. Prediction of adverse health outcomes in older people using a frailty index based on routine primary care data. J Gerontol A Biol Sci Med Sci 2013; 68:301–308.

54. Evans SJ, Sayers M, Mitnitski A, Rockwood K. The risk of adverse outcomes in hospitalized older patients in relation to a frailty index based on a comprehensive geriatric assessment. Age Ageing 2014; 43:127–132.

55▪. Krishnan M, Beck S, Havelock W, et al. Predicting outcome after hip fracture: using a frailty index to integrate comprehensive geriatric assessment results. Age Ageing 2014; 43:122–126.

This study found that a frailty index, automatically calculated from routine CGA, predicted mortality, length of stay, and failure to return to own home among a sample of older adults hospitalized with hip fracture.

56. Singh I, Gallacher J, Davis K, et al. Predictors of adverse outcomes on an acute geriatric rehabilitation ward. Age Ageing 2012; 41:242–246.

57. Jones D, Song X, Mitnitski A, Rockwood K. Evaluation of a frailty index based on a comprehensive geriatric assessment in a population based study of elderly Canadians. Aging Clin Exp Res 2005; 17:465–471.

58. Brothers TD, Kirkland S, Guaraldi G, et al. Frailty in people aging with human immunodeficiency virus (HIV) infection. J Infect Dis 2014 [In press].

59▪▪. Womack JA, Goulet JL, Gibert C, et al. Physiologic frailty and fragility fracture in HIV-infected male veterans. Clin Infect Dis 2013; 56:1498–1504.

This study proposed the VACS index to be a measure of frailty, as VACS index scores significantly predicted fragility fracture risk in a sample of more than 40 000 HIV-positive, largely middle-aged male veterans. In a model including VACS index score, other factors also predicting fragility fractures which might reasonably be incorporated into a frailty index included low BMI, alcohol-related diagnoses, proton pump inhibitor use, corticosteroid use, and cardiovascular disease.

60. Erlandson KM, Allshouse AA, Jankowski CM, et al. Risk factors for falls in HIV-infected persons. J Acquir Immune Defic Syndr 2012; 61:484–489.

61. Onen NF, Agbebi A, Shacham E, et al. Frailty among HIV-infected persons in an urban outpatient care setting. J Infect 2009; 59:346–352.

62▪. Piggott DA, Muzaale AD, Mehta SH, et al. Frailty, HIV infection, and mortality in an aging cohort of injection drug users. PLoS One 2013; 8:e54910.

This is one of the few published studies assessing outcomes in relation to frailty among HIV-positive individuals and also comparing this to an HIV-negative group. The data showed that being both HIV-positive and frail more than doubled the risk of death compared with either being HIV-positive or frail. The study used a modified version of the frailty phenotype.

63▪▪. Althoff KN, Jacobson LP, Cranston RD, et al. Age, comorbidities, and AIDS predict a frailty phenotype in men who have sex with men. J Gerontol A Biol Sci Med Sci 2014; 69:189–198.

This is a longitudinal analysis of data from 2007 to 2011 in the MACS study, assessing a modified frailty phenotype at each study visit. It found that many HIV-positive and HIV-negative men who were frail at one study visit were not frail at visits before and after. Most HIV-positive and HIV-negative men who were frail had two or more comorbidities.

64. Erlandson KM, Allshouse AA, Jankowski CM, et al. Comparison of functional status instruments in HIV-infected adults on effective antiretroviral therapy. HIV Clin Trials 2012; 13:324–334.

65. Ianas V, Berg E, Mohler MJ, et al. Antiretroviral therapy protects against frailty in HIV-1 infection. J Int Assoc Provid AIDS Care 2012; 12:62–66.

66. Justice AC, Freiberg MS, Tracy R, et al. Does an index composed of clinical data reflect effects of inflammation, coagulation, and monocyte activation on mortality among those aging with HIV? Clin Infect Dis 2012; 54:984–994.

67. Terzian AS, Holman S, Nathwani N, et al. Factors associated with preclinical disability and frailty among HIV-infected and HIV-uninfected women in the era of cART. J Womens Health (Larchmt) 2009; 18:1965–1974.

68. Pathai S, Gilbert C, Weiss HA, et al. Frailty in HIV-infected adults in South Africa. J Acquir Immune Defic Syndr 2012; 62:43–51.

69. Adeyemi O, Livak B. Higher Veterans Aging Cohort Study (VACS) index scores in HIV-positive adults with CD4 counts < 200 cells/mm3 despite viral suppression. J Acquir Immune Defic Syndr 2013; 63:e78–e81.

70. Desquilbet L, Jacobson LP, Fried LP, et al. A frailty-related phenotype before HAART initiation as an independent risk factor for AIDS or death after HAART among HIV-infected men. J Gerontol A Biol Sci Med Sci 2011; 66:1030–1038.

71. Oursler K, Tate J, Gill TM, et al. Association of the VACS index with exercise capacity in HIV-infected adults. AIDS Res Hum Retroviruses 2013; 29:1218–1223.

72▪. Marquine MJ, Umlauf A, Rooney AS, et al. The Veterans Aging Cohort Study index is associated with concurrent risk for neurocognitive impairment. J Acquir Immune Defic Syndr 2014; 65:190–197.

This study identified an association between VACS index scores and neurocognitive impairment, among a sample comprised mostly of middle-aged people with CD4 count greater than 350 and HIV viral load less than 500.

73. Justice AC, Tate JP, Freiberg MS, et al. Reply to Chow et al. Clin Infect Dis 2012; 55:751–752.

74▪. Tate JP, Justice AC, Hughes MD, et al. An internationally generalizable risk index for mortality after one year of antiretroviral therapy. AIDS 2013; 27:563–572.

This study presents a validation of the VACS index in the ART Cohort Collaboration. The Harrell's c statistic for 5-year mortality prediction was notably stable between the validation cohort and the development VACS cohort, suggesting the scale is generalizable to other groups.

75. Mitnitski A, Song X, Rockwood K. Trajectories of changes over twelve years in the health status of Canadians from late middle age. Exp Gerontol 2012; 47:893–899.

76. Andrew MK, Mitnitski AB, Rockwood K. Social vulnerability, frailty and mortality in elderly people. PLoS One 2008; 3:e2232.


aging; frailty; health status; HIV; older adults

© 2014 Lippincott Williams & Wilkins, Inc.


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