biomarkers of aging in epidemiological research biomarkers of aging workshop university of...
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Biomarkers of Aging in Biomarkers of Aging in Epidemiological Research Epidemiological Research
Biomarkers of Aging WorkshopBiomarkers of Aging WorkshopUniversity of Pittsburgh Mind Body CenterUniversity of Pittsburgh Mind Body Center
Anne B. Newman, MD, MPHAnne B. Newman, MD, MPHProfessor of Epidemiology and MedicineProfessor of Epidemiology and Medicine
11/07/0611/07/06
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OverviewOverview
IntroductionIntroduction– Definitions of biomarkers of agingDefinitions of biomarkers of aging– Models for determining markers in human studiesModels for determining markers in human studies
Example of biomarkers at basic and system levelExample of biomarkers at basic and system level– Serum markers that change with ageSerum markers that change with age– Muscle strength as a physiologic markerMuscle strength as a physiologic marker– Relationship of serum markers to physiologic markers – DHEAS Relationship of serum markers to physiologic markers – DHEAS
and muscle strengthand muscle strength
Physiologic markers of age related diseasePhysiologic markers of age related disease– Cardiovascular agingCardiovascular aging– Multisystem physiologic indexMultisystem physiologic index– FrailtyFrailty
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DefinitionsDefinitions
What is a biomarker?What is a biomarker?– Surrogate measure to track a physiologic Surrogate measure to track a physiologic
processprocess
Biomarker of agingBiomarker of aging– Marker of physiologic rather than chronologic Marker of physiologic rather than chronologic
ageage
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How would a biomarker of aging How would a biomarker of aging useful?useful?
Risk stratificationRisk stratification– Complement or substitute for chronological Complement or substitute for chronological
age.age.
Intervention targetsIntervention targets– that could delay age-related loss of physical that could delay age-related loss of physical
or cognitive functioning (loss of strength, or cognitive functioning (loss of strength, speed)speed)
– That could delay age-related chronic disease.That could delay age-related chronic disease.
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Some commonly, but loosely used Some commonly, but loosely used definitions of biomarkers of agingdefinitions of biomarkers of aging
Anything that is correlated with age.Anything that is correlated with age.
Anything that predicts mortality in older Anything that predicts mortality in older adults.adults.
Correlated with age and predictive of Correlated with age and predictive of mortality.mortality.
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More specific criteria proposed for More specific criteria proposed for defining aging biomarkersdefining aging biomarkers
An aspect of the fundamental process of aging*An aspect of the fundamental process of aging*
Demonstrated cross-sectional and longitudinal Demonstrated cross-sectional and longitudinal change agingchange aging
Consistently ranks a person across the life span Consistently ranks a person across the life span (not just in old age)(not just in old age)
Consistently ranks one species relative to Consistently ranks one species relative to anotheranother
Changes with interventions that modify the rate Changes with interventions that modify the rate of agingof aging
* Need to define aging* Need to define aging
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What is Aging?What is Aging?
The The processprocess that converts healthy adults that converts healthy adults into frail onesinto frail ones– With diminished physiologic reservesWith diminished physiologic reserves– With decreased homeostatic control With decreased homeostatic control – With exponentially increased vulnerability to With exponentially increased vulnerability to
diseases and death.diseases and death.– Usually referring to processes that are Usually referring to processes that are
universal, deleterious, and irreversible.universal, deleterious, and irreversible.
But these are aspects of risk that imply need to stress an individual to determine vulnerability
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Are there external standards for Are there external standards for definition of aging ?definition of aging ?
Increasing risk of mortality Increasing risk of mortality – After the fact standard – useful for fruit flies, worms After the fact standard – useful for fruit flies, worms
and miceand mice
Increasing high risk of age-related chronic Increasing high risk of age-related chronic diseasesdiseases– DementiaDementia– Cardiovascular diseaseCardiovascular disease– CancerCancer– OsteoporosisOsteoporosis– DiabetesDiabetes
Increasing risk of age-related disabilityIncreasing risk of age-related disability
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Caloric restriction model for Caloric restriction model for identifying biomarkersidentifying biomarkers
Examine the change in potential Examine the change in potential biomarkers in long lived animal modelsbiomarkers in long lived animal models
Evaluate the parameters that change as Evaluate the parameters that change as predictors of mortality in humanspredictors of mortality in humans
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body centerPublished by AAAS
Biomarkers of Caloric Restriction May Predict Longevity in Humans
Roth GS, Lane MA, Ingram DK, Mattison JA, Elahi D, Tobin JD, Muller D, Metter EJ. Science. 2002;297(5582):811.
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Successful aging model of Successful aging model of identifying biomarkersidentifying biomarkers
Examine the change in biomarkers in an Examine the change in biomarkers in an elite subgroup of humans with minimal elite subgroup of humans with minimal diseasedisease
Define aging biomarkers as the changes Define aging biomarkers as the changes seen in this subgroup that by the selection, seen in this subgroup that by the selection, are related to aging and not disease. are related to aging and not disease.
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body centerCopyright ©2005 American Heart Association
Fleg, J. L. et al. Circulation 2005;112:674-682
Longitudinal and cross-sectional changes in peak VO2 per kg FFM by quartile of age-adjusted high-intensity LTPA
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Biomarkers of agingBiomarkers of agingLevels of assessmentLevels of assessment
Molecular Cellular Organ System Organism
age, disease, ionizing radiation, injury, behavior, toxins
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Some candidate biomarkers of Some candidate biomarkers of aging in humansaging in humans
DHEASDHEAS
GH/IGF-1GH/IGF-1
Interleukin-6Interleukin-6
Telomere lengthTelomere length
Oxidative damage markersOxidative damage markers
Mitochondrial DNA mutationsMitochondrial DNA mutations
Less evidence but under study in epidemiologic studies
Have been demonstrated as important in epidemiologic studies of aging
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DHEAS – DHEAS – Dihydroepiandrostendione sulfateDihydroepiandrostendione sulfate
Major component of adrenal androgen Major component of adrenal androgen productionproduction
No known disease stateNo known disease state
Strongly declines with ageStrongly declines with age
Predicts mortality more so in menPredicts mortality more so in men
Modified by caloric restriction in animalsModified by caloric restriction in animals
Rate of decline correlates with life span Rate of decline correlates with life span across speciesacross species
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DHEAS - Adrenal Androgens and DHEAS - Adrenal Androgens and AgingAging
Nafziger AN, Bowlin SJ, Jenkins PL, Pearson TA. Longitudinal changes in dehydroepinadrosterone concentrations in men and women. J Clin Lab Med. 1998;131:316-323.
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body centerCopyright ©2001 The Endocrine Society
Trivedi DP,Khaw KT. Dehydroepiandrsterone sulfate and mortality in elderly men and women. J Clin Endocrinol Metab 2001;86:4171-4177.
DHEAS predicts mortalityDHEAS predicts mortality
Survival curve according to quartile of DHEAS in men (age adjusted).
Survival curve according to quartile of DHEAS in women (age adjusted).
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Growth Hormone and IGF-1Growth Hormone and IGF-1
Essential for growth in development but not lifeEssential for growth in development but not lifeStrong decline with ageStrong decline with ageLower levels of GH and IGF-1 have been studied as Lower levels of GH and IGF-1 have been studied as predictors of loss of lean mass, increased body fat,– predictors of loss of lean mass, increased body fat,– inconsistent, generally negative findings inconsistent, generally negative findings May be related to low strength and low physical May be related to low strength and low physical functioning , also diabetes.functioning , also diabetes.Higher levels of GH/IGF may predict cancerHigher levels of GH/IGF may predict cancerManipulations that reduce IGF Manipulations that reduce IGF increaseincrease lifespan in lifespan in animal modelsanimal modelsGrowth hormone supplements widely advertised as anti-Growth hormone supplements widely advertised as anti-aging supplementaging supplement
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From O’Connor et al, J Geron Med Sci, 1998
Decline in IGF-1 with ageDecline in IGF-1 with age
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IGF-1 may be related to disability IGF-1 may be related to disability outcomesoutcomes
Women’s Health and Aging StudyWomen’s Health and Aging Study
617 women aged 70-79617 women aged 70-79
Low IGF-1 was related to Low IGF-1 was related to – Lower extremity strengthLower extremity strength– Walking speedWalking speed– Self reported difficulty in walking tasksSelf reported difficulty in walking tasks
Cappola AR, et al Journal of Clinical Endocrinology and Metabolism 86; 4136-4146, 2001
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Interleukin 6 (IL-6)Interleukin 6 (IL-6)
Cytokine that modulates the immune Cytokine that modulates the immune responseresponse
Goes up with ageGoes up with age
More closely related to disease status in More closely related to disease status in that it may not change until later in lifethat it may not change until later in life
Predicts all cause mortality and disability Predicts all cause mortality and disability in older adultsin older adults
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IL-6 goes up with ageIL-6 goes up with age
0.50.55
0.60.65
0.70.75
0.80.85
0.90.95
1
71-72(reference)
73-74 75-76 77-80 >=80
Lo
g p
g/m
l
Age (years)
Harris TB, Ferrucci L, Tracy RP, Corti MC, Wacholder S, Ettinger WH Jr, Heimovitz H, Cohen HJ, Wallace R. Associations of elevated interleukin-6 and c-reactive protein levels with mortality in the elderly. Am J Med. 1999;106:506-512.
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Il-6 is a robust predictor of all- cause mortalityIl-6 is a robust predictor of all- cause mortality
Harris TB, Ferrucci L, Tracy RP, Corti MC, Wacholder S, Ettinger WH Jr, Heimovitz H, Cohen HJ, Wallace R. Associations of elevated interleukin-6 and c-reactive protein levels with mortality in the elderly. Am J Med. 1999;106:506-512.
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Inflammatory markers are related to Inflammatory markers are related to Incident Mobility LimitationIncident Mobility Limitation
*Based on chi-square statistics for categorical variables and t test or nonparametric Mann-Whitney statistics for continuous variables. IL=interleukin; TNF=tumor necrosis factor; IQR=interquartile range.
Penninx BWJH, Kritchevsky SB, Newman AB, Nicklas BJ, Simonsick EM, Rubin S, Nevitt M, Penninx BWJH, Kritchevsky SB, Newman AB, Nicklas BJ, Simonsick EM, Rubin S, Nevitt M, Visser M, Harris T, Pahor M. Inflammatory Markers and Incident Mobility Limitation in the Visser M, Harris T, Pahor M. Inflammatory Markers and Incident Mobility Limitation in the Elderly. Elderly. J Am Geriatr Soc.J Am Geriatr Soc. 2004;52: 1105-1113. 2004;52: 1105-1113.
00.5
11.5
22.5
33.5
44.5
5
C-reactive protein,mg/L, median (IQR)
IL-6, pg/ml, median(IQR)
TNF-alpha, pg/ml,median (IQR)
No incident mobility limitation n=2,081
Incident mobility limitation n=898
p=<.001*
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Biomarkers of agingBiomarkers of agingLevels of assessmentLevels of assessment
Molecular Cellular Organ System Organism
age, disease, ionizing radiation, injury, behavior, toxins
Oxidative damage
Mitochondrial function
Muscle strength
Functional ability
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Muscle strength might be a good Muscle strength might be a good biomarker of agingbiomarker of aging
Declines across the age span Declines across the age span
Predicts mortalityPredicts mortality
Predicts from middle agePredicts from middle age
Loss of strength and other metabolic Loss of strength and other metabolic functions seems to be a fundamental functions seems to be a fundamental aging process – few age-related muscle aging process – few age-related muscle diseasesdiseases
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body centerLarsson et al. J. Appl. Physiol.,1978
Muscle strength across the lifespanMuscle strength across the lifespan
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Lower quadriceps muscle strength Lower quadriceps muscle strength predicts mortality in Health ABCpredicts mortality in Health ABC
Men Women
Newman AB, Kupelian V, Visser M, Simonsick EM, Goodpaster BH, Kritchevsky SB, Tylavsky Newman AB, Kupelian V, Visser M, Simonsick EM, Goodpaster BH, Kritchevsky SB, Tylavsky FA, Rubin SM, Harris TB, The Health, Aging and Body Composition Investigators.FA, Rubin SM, Harris TB, The Health, Aging and Body Composition Investigators.Strength, but not muscle mass is associated with mortality in the Health, Aging and Body Strength, but not muscle mass is associated with mortality in the Health, Aging and Body Composition Study Cohort. J Gerontol A Biol Sci Med Sci. 2006;61A:M72-M77.Composition Study Cohort. J Gerontol A Biol Sci Med Sci. 2006;61A:M72-M77.
Su
rviv
al
months
0 6 12 18 24 30 36 42 48 54 60 66 72
.65
.7
.75
.8
.85
.9
.95
1
<90
90-130 130-170
>170
Su
rviv
al
months
0 6 12 18 24 30 36 42 48 54 60 66 72
.85
.9
.95
1
<60
60-80
80-100
>100
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Grip strength in middle age predicts Grip strength in middle age predicts mortality in the Honolulu Heart Studymortality in the Honolulu Heart Study
Rantanen T, Harris T, Leveille SG, Visser M, Foley D, Masaki K, Guralnik JM. Muscle Rantanen T, Harris T, Leveille SG, Visser M, Foley D, Masaki K, Guralnik JM. Muscle strength and body mass index as long-term predictors of mortality in initially healthy men. J strength and body mass index as long-term predictors of mortality in initially healthy men. J Gerontol A Biol Sci Med Sci. 2000;55A:M168-M173.Gerontol A Biol Sci Med Sci. 2000;55A:M168-M173.
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-15
-10
-5
0
% l
oss
of
stre
ng
th
Percent loss of leg strength
White Black White BlackMen Men Women Women
-15
-10
-5
0
-3.4% -4.1% -2.7% -3.0% *
% l
oss
of
l ean
ma s
s
and leg lean mass
* Annualized rates for strength declineGoodpaster B, J Gerontol 2006
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Skeletal Muscle fat
Less More Most
CT Scans of the mid thigh from actual Health ABC participants showing muscle area, subcutaneous fat and intermuscular fat (highlighted in pink) variability in thighs of similar cross-sectional area
Scatter plots of log[DHEAS] and lower Scatter plots of log[DHEAS] and lower extremity muscle strength according to ageextremity muscle strength according to age
Valenti G, Denti L, Maggio M, Ceda GP, Volpato S, Bandinelli S, Ceresini G, Cappola A, Valenti G, Denti L, Maggio M, Ceda GP, Volpato S, Bandinelli S, Ceresini G, Cappola A, Guralnik JM, Ferrucci. Effect of DHEAS on skeletal muscle over the life span: the InCHIANTI Guralnik JM, Ferrucci. Effect of DHEAS on skeletal muscle over the life span: the InCHIANTI Study. J Gerontol A Biol Sci Med Sci. 2004;59A:M466-M72.Study. J Gerontol A Biol Sci Med Sci. 2004;59A:M466-M72.
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Physiologic functions that decline Physiologic functions that decline with agewith age
EyesEyes– Lens accommodationLens accommodation
EarsEars– High frequency hearingHigh frequency hearing
SkinSkin– ElasticityElasticity
Nervous systemNervous system– Central nervous system Central nervous system
processing speedprocessing speed– Peripheral nerve functionPeripheral nerve function
HormonesHormones– Sex steroids, growth hormone, Sex steroids, growth hormone,
insulin sensitivity, cortisol insulin sensitivity, cortisol regulationregulation
Immune functionImmune function– depletion of naive memory depletion of naive memory
cells,cells,– increase in markers of increase in markers of
inflammationinflammation
BoneBone– Loss of mass and dilation of Loss of mass and dilation of
cross-sectional areacross-sectional area
JointsJoints– Cartilage stiffeningCartilage stiffening
Muscle functionMuscle function– loss of strength and oxidative loss of strength and oxidative
capacitycapacity
LungsLungs– loss of forced vital capacity and loss of forced vital capacity and
lung elasticitylung elasticity
Heart and blood vesselsHeart and blood vessels– vascular stiffening, dilation and vascular stiffening, dilation and
loss of recoilloss of recoil
Physiologic measures can Physiologic measures can capture very early chronic capture very early chronic disease and age related disease and age related
changeschanges
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Age DiseaseAge Disease
AgeAge Grey ZoneGrey Zone DiseaseDisease
Vascular StiffnessVascular Stiffness High BPHigh BP AtherosclerosisAtherosclerosis
Bone lossBone loss OsteopeniaOsteopenia OsteoporosisOsteoporosis
Decline in glucose Decline in glucose tolerancetolerance
Pre-diabetesPre-diabetes DiabetesDiabetes
Loss of neuronsLoss of neurons MCIMCI Alzheimer’s and other Alzheimer’s and other neurodegenerative neurodegenerative
diseasesdiseases
Loss of visual Loss of visual accommodation (lens accommodation (lens
stiffening)stiffening)
PresbyopiaPresbyopia CataractCataract
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Age vs. disease - Grey zone issuesAge vs. disease - Grey zone issues
Age-related biological changes are risk Age-related biological changes are risk factors for chronic disease factors for chronic disease (example - stiffening (example - stiffening of vasculature increases risk of plaque deposition) of vasculature increases risk of plaque deposition)
Similar biologic changes lead to both age-Similar biologic changes lead to both age-related physiologic declines and to age-related physiologic declines and to age-related chronic disease – related chronic disease – (example - oxidative (example - oxidative stress hypothesized in almost every chronic disease and stress hypothesized in almost every chronic disease and in the aging process) in the aging process)
It may be the same biology underlying It may be the same biology underlying physiologic decline and diseasephysiologic decline and disease . .
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Which comes first?Which comes first?The vicious cycleThe vicious cycle
Age change
Age-related chronic disease change
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Biomarkers of agingBiomarkers of agingLevels of assessmentLevels of assessment
Molecular Cellular Organism
InflammationMuscle hypertrophy and fibrosis
Atherosclerosis
Function – heart attack or stroke
Vascular stiffening
Organ System
Aging vs. Age-Related Chronic Disease
Are you as old as your arteries?Are you as old as your arteries?
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Initiation, Progression and Complication Initiation, Progression and Complication of Atherosclerotic Plaqueof Atherosclerotic Plaque
Libby P, et al. Current Concepts 2001;104:365-372
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CCA Progression - Participant 2CCA Progression - Participant 2
Baseline Follow-up
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Prevalence of CVD by Race and Prevalence of CVD by Race and Gender,Gender,CHS N=5843CHS N=5843
25
35.4
26.2
41.3
32.5
39.737.2
41.9
20.8
37.2
43.7
19.2
05
101520253035404550
None Subclinical Clinical
Per
cen
tage
(%
)
White Women n=2791 Black Women n=577White Men n=2136 Black Men n=339
Kuller L et al; Arterioscler Thromb Vasc Biol 1998;18:283-293
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Coronary Artery Calcification Scoring
HounsfieldHounsfield(Agatston Scoring)(Agatston Scoring)
130-199 1130-199 1
200-299 2200-299 2
300-399 3300-399 3
>400 4>400 4
Area = 15 mmArea = 15 mm22
Peak CT = 450Peak CT = 450
Score = 15 x 4 = 60Score = 15 x 4 = 60
Area = 8 mmArea = 8 mm22
Peak CT = 290Peak CT = 290
Score = 8 x 2 = 16Score = 8 x 2 = 16
Total Score = Total Score = all areas thisall areas thisSubject >400Subject >400
LAD RCA
Rumberger, Mayo Clinic Proc 1999;74:243-252
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00 0 0 4118
24
539
1064
0 00 3 16 41
151167
126120
725
328
542
0
200
400
600
800
1000
1200
Women, n=367 Men, n=247
Med
ian
Cor
onar
y ar
tery
cal
cific
atio
n sc
ore
Raggi 35-39 40-44 45-49 50-54 55-59
60-64 65-70 CHS 67-74 80-84 85-100
Median CAC Scores for two populations: EBT Nashville* and ACE-CHS by age in men and women
*Raggi, et al, Circulation 2000;101:850-855.
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Total Mortality by CVD and CAC Score Quartile – Total Mortality by CVD and CAC Score Quartile – ACE-CHS ACE-CHS (N=614, 40% men, 23% black, Mean age 80 yrs.)(N=614, 40% men, 23% black, Mean age 80 yrs.)
p=.0086
CAC CAC ScoreScore
Events Events
NN
Rate/100 Rate/100 p-yrp-yr
Age-CVD Age-CVD Adjusted HRAdjusted HR
(95% CI)(95% CI)
0-560-56 1111 2.142.14 1.0 (ref)1.0 (ref)
57-33257-332 1616 3.063.06 1.41 (0.65-1.41 (0.65-3.03)3.03)
333-333-917917
2222 4.474.47 1.91 (0.92-1.91 (0.92-3.96)3.96)
918-918-54595459
3434 7.597.59 2.78 (1.37-2.78 (1.37-5.64)5.64)
Newman AB, AHA 2004
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Incident CVD by level of coronary artery calcium in Incident CVD by level of coronary artery calcium in men and women age 80-100 in the Cardiovascular men and women age 80-100 in the Cardiovascular
Health Study, N= 559Health Study, N= 559
Quartiles of CAC Quartiles of CAC (Agatson Units)(Agatson Units)
Events per 100 p-yEvents per 100 p-y Adjusted HR* (95% CI)Adjusted HR* (95% CI)
Q1 (0-56)Q1 (0-56) 1.91.9 ReferentReferent
Q2 (57-332)Q2 (57-332) 5.45.4 3.0 (1.2, 7.3)3.0 (1.2, 7.3)
Q3 (333-917)Q3 (333-917) 6.36.3 4.1 (1.7, 10.2)4.1 (1.7, 10.2)
Q4 (>917)Q4 (>917) 6.96.9 4.6 (1.7, 12.3)4.6 (1.7, 12.3)
* Adjusted for age, sex, race, hypertension, diabetes, SBP, smoking status, cholesterol and LDL cholesterol Newman AB, AHA Epi Council 2005
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Newman AB, Arnold AM, Naydeck BL, et al. Successful aging: effect of subclinical cardiovascular disease. Arch Intern Med. 2003;163:2315-2322 .
Years of successful lifeYears of successful lifeby age, sex and CVD riskby age, sex and CVD risk
0
2
4
6
8
10
12
14
16
18
Women Men
Succ
essf
ul Y
ears
Women All High Risk Median All Low RiskMen All High Risk Median All Low Risk
16.4
9.0
2.6
14.0
8.1
2.2
10.8
6.3
1.7
7.8
4.31.3
4.51.90.7
14.7
8.9
2.4
12.5
7.4
2
9.7
4.8
1.5
7.03.8
1.1
4.02.30.6
Average effect of subclinical CVD –
Women - 6.5 years
Men - 5.6 years
Women Men
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Epidemiologic model for defining Epidemiologic model for defining “biomarkers” that explain chronologic aging“biomarkers” that explain chronologic aging
Marker or measures should be strongly related Marker or measures should be strongly related to age-related outcomes – such as disease, to age-related outcomes – such as disease, injury and death.injury and death.
Should explain a large component of the effect Should explain a large component of the effect of chronologic age on these outcomes.of chronologic age on these outcomes.
Holy Grail – factor (s) that have stronger Holy Grail – factor (s) that have stronger relationship to outcomes than age itself and relationship to outcomes than age itself and even explain away the effect of age altogether.even explain away the effect of age altogether.
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Risk Factors for 5 Year Mortality in CHSRisk Factors for 5 Year Mortality in CHS
Fried LP. Kronmal RA. Newman AB. Bild DE. Mittelmark MB. Polak JF. Robbins JA. Gardin JM. Risk factors for 5-year mortality in older adults: the Cardiovascular Health Study. JAMA. 279(8):585-92, 1998
Substantial age attenuation achieved - 27 risk factors explained 40% of age effect
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Construction of aConstruction of a“Physiologic Index”“Physiologic Index”
Index of “physiologic integrity” (0-10) from 5 non-Index of “physiologic integrity” (0-10) from 5 non-invasive tests including invasive tests including – internal carotid artery wall thickness (vascular internal carotid artery wall thickness (vascular
disease), disease), – fasting glucose (diabetes), fasting glucose (diabetes), – cystatin C (kidney disease), cystatin C (kidney disease), – white matter grade on brain magnetic resonance white matter grade on brain magnetic resonance
imaging (cerebrovascular disease), and imaging (cerebrovascular disease), and – forced vital capacity (lung disease). forced vital capacity (lung disease).
Best tertile for all measures =10Best tertile for all measures =10
Newman AB. AGS Annual Meeting, 2006
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Physiologic Index - Frequency DistributionPhysiologic Index - Frequency DistributionThe Cardiovascular Health Study 1992-1993, n=2928The Cardiovascular Health Study 1992-1993, n=2928
0
5
10
15
20
0 1 2 3 4 5 6 7 8 9 10
Physiologic Index
%
Worst Best
Newman AB. AGS Annual Meeting, 2006
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body center
155.5
80.5
33.826.5
20.1 16.8
50.7
109.4
69.1
9.1 70
20406080
100120140160180
0 1 2 3 4 5 6 7 8 9 10
Physiologic index
Mo
rtal
ity
rate
per
100
0 p
erso
n y
ears
Number of deaths
10 52 87 152 162 119 105 72 43 13 3
Worst Best
Total mortality rates by physiologic Total mortality rates by physiologic indexindex
Newman AB. AGS Annual Meeting, 2006
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Survival by physiologic indexSurvival by physiologic index
Physiologic IndexPhysiologic Index Mortality Rate per 1000 P-YMortality Rate per 1000 P-Y HR *HR *
0 - 30 - 3
4 - 54 - 5
6 – 76 – 7
8 - 108 - 10
72.172.1
37.237.2
21.021.0
12.612.6
6.316.31
3.063.06
1.701.70
(ref)(ref)
Newman AB. AGS Annual Meeting, 2006
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body center
Predictive Models for MortalityPredictive Models for MortalityPhysiologic Index vs. Continuous VariablesPhysiologic Index vs. Continuous Variables
Age onlyAge only Index Index onlyonly
IndexIndex
AdjustedAdjusted**
Continuous Continuous VariablesVariables††
Continuous Continuous variables plus variables plus Interactions Interactions
between between systemssystems††
AUCAUC .673.673 0.7060.706 0.7580.758 0.7750.775 0.7780.778
Model FitModel Fit
(SBC)(SBC)
1249412494 1241212412 1220712207 12194*12194* 1221612216
* Adjusted for age, sex, race, physical activity, smoking, BMI, clinical comorbidity index† Continuous variables for ICA, FVC, white matter grade, fasting glucose, cystatin C
Newman AB. AGS Annual Meeting, 2006
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Mortality - Attenuation of the hazards ratios Mortality - Attenuation of the hazards ratios for age with adjustment for physiologic index for age with adjustment for physiologic index
7.7
4.4
2.51.0 1.6
4.7
2.8
2.01.0 1.5
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
65-69 70-74 75-79 80-84 85+
Haz
ard
rat
io Sex, Race Adj.
Multivariate
11.04
Newman AB. AGS Annual Meeting, 2006
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FrailtyFrailty
Summarizes deficits at the organism levelSummarizes deficits at the organism levelOperational definition:Operational definition:– Multiple (3-5/5) criteria present:Multiple (3-5/5) criteria present:
Weight loss Weight loss WeaknessWeaknessExhaustionExhaustionSlowed walking speedSlowed walking speedLow activityLow activity
Fried et al. J. Gerontol: Medical Science, 2001Fried et al. J. Gerontol: Medical Science, 2001
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body center
Fried et al. J. Gerontol: Medical Science, 2001Fried et al. J. Gerontol: Medical Science, 2001
11/7/0/711/7/0/7 Biomarkers of Aging - Pittsburgh Mind Body centerBiomarkers of Aging - Pittsburgh Mind Body center
Biomarkers of agingBiomarkers of agingLevels of assessmentLevels of assessment
Molecular Cellular Organism
Inflammation, Hormones, Genes
Sarcopenia, Anemia
Frailty
Decreased physiologic reserve in multiple systems
Organ System
disease, ionizing radiation, injury, behavior, toxins
Age
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Frailty vs. Robust AgingFrailty vs. Robust Aging
N
Frail Robust
<10%3/5
Frail
45% 0/545%
1-2/5
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SummarySummary
No one marker of age or disease appears No one marker of age or disease appears to adequately describe aging. to adequately describe aging.
Some important systems include brain, Some important systems include brain, vascular, muscle strength, lung function, vascular, muscle strength, lung function, metabolismmetabolism
Challenges remain to put these togetherChallenges remain to put these together– Across the life span longitudinallyAcross the life span longitudinally– Across systemsAcross systems
Physiologic Changes Related to AgingOperational Definitions for Studies on Aging
35 100
• The aging process described decline of physiological parameters(The Nathan Shock Model)
Few examplesCognitive StatusNerve Conduction VelocityMuscle StrengthVisual AcuityVascular stiffeningInsulin SensitivityTestosteroneEstrogensIGF-1CytokinesROS / Antioxidants
Age
Ph
ys
iolo
gic
al
Pa
ram
ete
r
35 100
• Information on patterns of functional decline in multiple physiological systems with age is scant
Age
Ph
ys
iolo
gic
al
Pa
ram
ete
rPhysiologic Changes Related to Aging
Operational Definitions for Studies on Aging
35 100
• Aging manifest as decline in anatomical integrity and function across multiple physiological systems.
• Relationship between systems across the lifespan not fully understood.
Age
Ph
ys
iolo
gic
al
Pa
ram
ete
rPhysiologic Changes Related to Aging
Operational Definitions for Studies on Aging
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For discussionFor discussion
What are the best criteria for defining a What are the best criteria for defining a biomarker of aging?biomarker of aging?– Do we have an adequate framework?Do we have an adequate framework?
Biomarkers of aging vs. biomarker of age Biomarkers of aging vs. biomarker of age related diseaserelated disease– Is glucose sensitivity an aging biomarker?Is glucose sensitivity an aging biomarker?
How will biomarkers lead to improving our How will biomarkers lead to improving our understanding of aging and age related understanding of aging and age related chronic disease?chronic disease?