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5
An Overview of Biomarker Research from Community and Population-Based Studies on Aging

Jennifer R. Harris, Tara L. Gruenewald, and Teresa Seeman


The goal of this chapter is to provide an overview of findings from community-based studies that have profitably incorporated biomarkers along with more traditional interview data to address important questions regarding factors that affect health risks at older ages. The focus on older age stems from a series of activities (National Research Council, 1997, 2001a) funded by the National Institute on Aging that promoted a new era of population aging research predicated on the importance of integrating biomarkers into survey research.

Prior efforts to include biomarkers in community and population studies have yielded a wealth of knowledge regarding the role of biological systems and processes in cognitive and physical functioning, mental and physical disease development, and mortality outcomes. The biomarker initiative under the National Institute on Aging was particularly concerned with identifying biomarkers of physiological age (Butler et al., 2004). In contrast, biomarker research in the social and behavioral sciences has emphasized elucidating the interplay of biological systems with sociodemographic, behavioral, psychosocial, pharmacological, and genetic factors in health outcomes (Institute of Medicine, 2006; National Research Council, 2001b).

This chapter highlights research contributions from a selected group of community and population studies that include various biomarker measurements in study assessments. It is not intended to review completely, catalogue, or present in-depth results, but rather to provide an overview of the range of biomarker research conducted in these studies



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5 An Overview of Biomarker Research from Community and Population-Based Studies on Aging Jennifer R. Harris, Tara L. Gruenewald, and Teresa Seeman T he goal of this chapter is to provide an overview of findings from community-based studies that have profitably incorporated bio- markers along with more traditional interview data to address important questions regarding factors that affect health risks at older ages. The focus on older age stems from a series of activities (National Research Council, 1997, 2001a) funded by the National Institute on Aging that promoted a new era of population aging research predicated on the importance of integrating biomarkers into survey research. Prior efforts to include biomarkers in community and population studies have yielded a wealth of knowledge regarding the role of biologi- cal systems and processes in cognitive and physical functioning, mental and physical disease development, and mortality outcomes. The bio- marker initiative under the National Institute on Aging was particularly concerned with identifying biomarkers of physiological age (Butler et al., 2004). In contrast, biomarker research in the social and behavioral sciences has emphasized elucidating the interplay of biological systems with sociodemographic, behavioral, psychosocial, pharmacological, and genetic factors in health outcomes (Institute of Medicine, 2006; National Research Council, 2001b). This chapter highlights research contributions from a selected group of community and population studies that include various biomarker measurements in study assessments. It is not intended to review com- pletely, catalogue, or present in-depth results, but rather to provide an overview of the range of biomarker research conducted in these studies 

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 JENNIFER R. HARRIS, TARA L. GRUENEWALD, AND TERESA SEEMAN and highlight some key findings and research directions stemming from this integrative research. For the purposes of this review, we have limited our consideration of biomarkers mainly to DNA and physiological biomarkers collected from blood (e.g., glycosylated hemoglobin, cholesterol), saliva (cortisol) or urine (cortisol and catecholamines); not included are more functional parameters that are also considered to be biomarkers, such as hand grip strength, mea- sures of vision or hearing, and assessments of cognitive or physical func- tioning. This chapter highlights the types of questions that can be addressed when social and behavioral studies are supplemented with biomarker data, and therefore we also exclude descriptions of biomarker research derived from postmortem studies of brain tissue. It is important to note, however, the value of postmortem biomarkers for elucidating biological pathways and mechanisms, including those linking social and behavioral measures with disease outcomes. This is illustrated by research from, for example, the Nun’s Study (Snowdon, Kemper, Mortimer, Wekstein, and Markesbery, 1996), the Religious Order Study (Wilson, Bienias, and Evans, 2004), and the Memory and Aging Project (Bennett et al., 2005). Our decision to focus on physiological parameters and genes was driven in large part by a central goal of the current volume, namely, to help inform social scientists about the potential value of incorporating biomarkers into their projects through exposition of prior research in which analyses of such biomarkers or candidate genes have provided insights into processes and mechanisms affecting healthy aging. In that context, the focus taken herein seems warranted, as such biomarkers have generally not been included in social surveys (whereas assessments of functioning have), so that evidence based on physiological biomarkers is much less well known to the social science community. Much of the information presented in this chapter derives from the studies summarized in Table 5-1. These were selected to represent a sam- pling of ongoing community or population-based studies on aging that have collected DNA or other biological or physiological biomarkers and that are not reviewed elsewhere in this volume. We have organized the wide range of findings generated from the studies reviewed according to a number of critical thematic areas that emerged during our review. These include biomarkers and aging, genetic and environmental influences on risk factors for cardiovascular disease (CVD), social and psychological factors, behavior genetics, biomarkers of cognitive aging, biomarkers of physical function and aging, indices of cumulative biological risk, and the relationship between biomarkers and genetic pleiotropy.

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 TABLE 5-1 Description of Selected Community and Population-Based Studies Conducting Biomarker Research Specimen Type and Study Name Design and How (year started) Sample General Purpose Collected Biomarkers Ascertained MacArthur Study 1,189 men and Longitudinal Biomarker Total/HDL cholesterol, glycosylated of Successful Aging women, ages 70- cohort study to data were hemoglobin, albumin, IL-6, C-reactive (Berkman et al., 79 at baseline. elucidate the factors collected protein, fibrinogen, complete blood 1993) Selection criteria (sociodemographic, at baseline count (CBC), blood chemistry tests employed to behavior, and three- (SMAC-24), DHEAS, antioxidants, enroll a cohort psychosocial, year follow- homocysteine, vitamin B and folate, representing biological) up. Home urinary norepinephrine, epinephrine, the top third associated with more specimen cortisol and dopamine, resting and of this age successful aging collections— postural blood pressure, waist/hip group in terms (i.e., maintenance phlebotomist ratio, peak flow rate (Mini-Wright of physical of higher cognitive collected meter), ApoE genotyping. and cognitive and physical blood and functioning. functioning). Data 12-hour collected at baseline (overnight) and 3- and 7-year urine sample. follow-up exams via in-person and phone assessments.

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Normative Aging Sample of 2,280 Longitudinal Clinical CBC, creatinine, albumin, fasting Study (1963) (Bell, initially healthy cohort study to examinations glucose, insulin, 2-hour glucose Rose, and Damon, men, ages 21-80 examine biomedical every 3-5 tolerance test, lipid profiles 1972) at enrollment. and psychosocial years with (LDL, HDL, triglycerides), serum Study characteristics collection of glutamic-oxaloacetic transaminase conducted of aging and blood and 24- (SGOT), calcium, blood urea through development of hour urines. nitrogen (BUN), blood lead levels, Department of disease. urinary catecholamines, blood Veteran Affairs pressure, heart rate, EKG reading, in Boston (96% pulmonary function, anthropometry, of participants homocysteine, vitamin B and folate. are veterans). Cardiovascular Representative Longitudinal cohort Clinic-based Resting and postural blood pressure, Health Study (CHS, sample of 5,000 study of risk factors collection ankle-arm index, fasting glucose, 1989; Fried et al., adults, ages for coronary heart of blood for insulin, 2-hour oral glucose tolerance 2001) 65+, sampled disease and stroke wide array of test, lipid profile (LDL, HDL, from Medicare in older adults. biomarkers, triclycerides), albumin, CBC, left listings for 4 Assessments at EBCT, ventricular ejection fraction, markers communities baseline and one-, ultrasound, of inflammation and coagulation, (N = 1,250 two-, and three-year and MRI. ApoE, body fat (bioelectric each; Forsyth follow-ups. impedance), height, weight, waist/ County, ND; hip ratio, 12-lead ECGs (24-hour Sacramento, ambulatory ECGs on subset of CA; Washington 600), forced vital capacity, forced County, MD; expiratory volume, grip strength, Pittsburgh, PA). ultrasonography of carotid arteries, m- mode, Doppler echocardiography (for left ventricular mass, ejection fraction, stroke volume and end-systolic stress, regional and segmental wall motion, % fractional shortening).  Continued

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TABLE 5-1 Continued 00 Specimen Type and Study Name Design and How (year started) Sample General Purpose Collected Biomarkers Ascertained Later Life Resilience 135 older All participants Biological Blood pressure, heart rate, urinary Study (Ryff, Singer, women, ages took part in a prior data collected norepinephrine, epinephrine, and and Dienberg Love, 61-91, recruited 4-wave longitudinal through cortisol, glycosylated hemoglobin, 2004) from a prior study of community overnight visit total/HDL cholesterol, DHEAS, longitudinal relocation. to General salivary cortisol, waist/hip ratio, BMI. investigation Participants in the Clinical of move to biomarker study Research an assisted participated in a Center, living facility fifth wave of data including from personal collection, including blood, 12 hour residence in assessment of (overnight) Madison or biomarkers. urines and Milwaukee, WI saliva. (approximately half of the larger sample participated in biomarker substudy).

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Women’s Health WHAS I: cohort Longitudinal Home-based Fasted glucose, markers of and Aging Studies of women (n cohorts, followed specimen inflammation, growth factors (IGF- (WHAS) I and II. = 1,002) ages to elucidate factors collection. 1), genetic information (e.g., IL-6 WHAS I (Simonsick 65+ sampled associated with haplotype), antioxidants, ambulatory et al., 1997); WHAS to represent trajectories of ECG, resting 12-lead ECG, BP (resting, II (Fried et al., 2000) the one-third functional decline or ankle-arm), height, weight, grip most disabled lack thereof. strength, spirometry. Medicare enrollees from the Baltimore, MD, area (based on 12 zip code areas in eastern Baltimore and parts of Baltimore County). WHAS II = cohort of women, age s65+, sampled to represent the remaining two-thirds least disabled women in that age range. Continued 0

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TABLE 5-1 Continued 0 Specimen Type and Study Name Design and How (year started) Sample General Purpose Collected Biomarkers Ascertained Swedish Adoption Population- Longitudinal, Blood samples Serum lipoproteins: total cholesterol, Twin Study of based subset currently in 7th were drawn total triglycerides, HDL cholesterol, Aging (SATSA) of 958 twin wave, questionnaires during in- LDL cholesterol, apolipoproteins 1984-present pairs from the on all and in- person testing A-1 and B, MaoB H pylori, metals, (Pedersen et al., Swedish Twin person testing (12-hour creatinine, gamma-glutamyltransferase 1991) Registry. The on a subsample. fasting) drawn (gamma-GT), potassium, sodium, urea sample includes Combines twin and on subsample and uric acid, creatinine, electrolytes, twins reared adoption design of twins at telomere length. Whole blood for DNA apart and a to study genetic central testing bank. Plasma at in-person testing matched sample and environmental sites or in occasion 3 for evaluation of a variety of twins reared influences affecting home. of coagulation factors. together. variation in normal aging. Origins of Variance Swedish 5-wave longitudinal Blood samples Albumin, calcium, total cholesterol, in the Oldest-Old: twins ages study, measurements for clinical HDL cholesterol, creatinine, gamma- Octogenarian Twins 80 and older. conducted at 2-year assessment glutamyltransferase (gamma-GT), (OCTO-Twin) 1991- Original sample intervals, to explore and DNA potassium, sodium, urea and uric acid, 2002 (McClearn et identified 351 the origins of extraction for creatinine, electrolytes, cobalamin, free al., 1997) pairs for the individuality in the molecular thyroxin, folic acid, prostate-specific first wave of in- oldest-old. genetic antigen (PSA), and thyroid-stimulating person testing. analyses. hormone (TSH), homocysteine. Collected in home.

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Screening Across Pilot included Computer-assisted Blood samples Biological samples only collected the Lifespan Study a random telephone interview. collected at in pilot project include clinical (SALT) 1998-2002 sample of 2,000 Multidimensional local clinics. biochemistries, zygosity plus blood twins ages health, demography, stored for future analyses. Through 5-85. Followed health behaviors, recent efforts, DNA, serum, TG, HDL, by full-scale disease identification LDL, apoliproteins, glucose, HbA1C, screening of diagnostic items. and DNA collected on all pairs alive all twins born (goal 16,000 individuals, current at 1958 or earlier, 12,000). population- based. Men and Women’s 486 unlike- 3 wave longitudinal Collected Whole blood, serum, DNA, lipids, Aging (GENDER) sexed twins study with measures during in- clinical panel. born 1906-1925, 1995-1997, 1999-2001, person testing population- and 2001-2005. in home. based. Study of Dementia Twins born in Cross-sectional, Collected in Whole blood, serum, plasma, DNA, in Swedish Twins or before 1935, 1998-2001. Genetic home. lipids, clinical panel. (HARMONY) (Gatz population- and environmental et al., 1997) based. factors for Alzheimer disease and other dementias. Diagnostic assessments for dementia, cognitive testing, and risk factor information. Three-year follow up for small subsample. NOTES: HDL = high-density lipoprotein; IL-6 = interleukin 6; DHEAS = dehydroepiandrosterone sulfate; ApoE = apolipoprotein E; LDL = low- density lipoprotein; ECG or EKG = electrocardiogram; EBCT = electron beam computed tomography; MRI = magnetic resonance imaging. 0

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0 BIOSOCIAL SURVEYS BIOMARkERS IN COMMUNITy- OR POPULATION-BASED STUDIES Scientists have long been interested in obtaining measures of biomark- ers to understand the role of biological systems in functioning and disease processes. Much of this work has been conducted via well-controlled experiments in the laboratory with nonhuman animals or in small-scale human studies focused on specific physiological processes in the lab (e.g., physiological responses to a specific challenge or interaction of specific physiological systems). More recently, the value of collecting biomarker measurements in large-scale community and population studies has been recognized (National Research Council, 2001a) and greater emphasis is being placed, by researchers and by funding agencies, on banking bio- logical samples. The impetus for the collection of biomarkers is to gain a better under- standing of the role of specific biological systems in health conditions, including an understanding of the role of biological systems in associa- tion with other sociodemographic, behavioral, pharmacological, psycho- social, and genetic contributions to health outcomes. There is a growing literature in the behavioral sciences literature linking social and behav- ioral factors (ranging from sociocultural and neighborhood influences to interpersonal relations) to biomarkers and health (Berkman and Kawachi, 2000; Cacioppo, Hughes, Waite, Hawkley, and Thisted, 2006; Hawkley, Masi, Berry, and Cacioppo, 2006; House, Landis, and Umberson, 1988; Kiecolt-Glaser et al., 2005; Ryff and Singer, 2001; Uchino, Cacioppo, and Kiecolt-Glaser, 1996; Wen, Hawkley, and Cacioppo, 2006). These findings, in conjunction with methodological advances, are fostering integrative lines of research to study health and pathways to disease. For example, the recent Institute of Medicine report Genes, Behavior, and the Social Envi� ronment (2006) focuses on social environments in the study of gene by environment interactions and health. A wide variety of biomarkers have been assessed in community- or population-based studies. Biomarkers of cardiovascular, metabolic, endo- crine, and immune systems or processes are most commonly assessed. However, other types of biomarker measurements have also been obtained, including exposure indices (e.g., bone and blood lead levels or pesticide blood levels to assess environmental exposure), measurements of vitamin or antioxidant levels, anthropometric measures (e.g., bone length, height, weight), bone density scans, measurements of brain activity (e.g., func- tional magnetic resonance imaging, fMRI, or electroencephalogram, EEG), as well as markers of the functional status of a bodily system (e.g., forced expiratory volume to assess lung function). Biomarker values are typically assessed for biological systems at a

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0 JENNIFER R. HARRIS, TARA L. GRUENEWALD, AND TERESA SEEMAN resting state (e.g., resting blood pressure, blood levels of glucose), but values are also sometimes assessed under conditions of challenge to a system (e.g., blood pressure levels after standing, levels of glucose after a glucose challenge test). Blood, urine, and saliva samples are typical sources for biomarker assessments, although for some of the biomarkers described above, mechanical or electrical devices (e.g., MRI machine) are also used to obtain measurements. The measurement of biomarkers in community- or population-based studies presents a methodological chal- lenge for researchers, as they must determine how and where to obtain biomarker measurements on a large number of people. Most studies have used home-based or clinic-based protocols for the collection of biological specimens, with some investigations utilizing both approaches. The primary advantage of clinic-based specimen collection is the ability to implement protocols requiring greater temperature control (e.g., samples must be kept cold or iced) as well as meeting more restricted processing requirements (e.g., within minutes or several hours at most). However, sample representativeness can sometimes suffer as certain sub- groups are less able or willing to come to a clinic for reasons related to health, transportation, or unfamiliarity with the location. Examples of studies that have used clinic-based protocols successfully include the Women’s Health and Aging Studies I and II, the Cardiovascular Health Study, and the Health, Aging and Body Composition Study. Studies using home-based protocols include the MacArthur Study of Successful Aging (Berkman et al., 1993), the Later Life Resilience Study (Ryff, Singer, and Dienberg Love, 2004), and the Swedish Twin Studies (Lichtenstein et al., 2002). BIOMARkERS AND AgINg Most established biomarkers indices reflect age norms in disease- free samples from which individuals with known risks and diseases are excluded from study. This poses a challenge for aging studies because these criteria make it difficult to define “normal” values among groups of elderly individuals for whom morbidity is common. Furthermore, this approach could mask age changes in many biomarkers and values of routine bio- chemical blood tests. A study of clinical biochemical values in a popula- tion-based sample of twins ages 82 and older from the Swedish study of Origins of Variance in the Oldest-Old: Octogenarian Twins (OCTO-Twin) found few participants without clinical diagnoses; therefore, subsequent survival for six years was used as a marker of overall health in late life. Results revealed an association between mortality and higher serum levels of urea, urate, gamma-glutamyltransferase (gamma-GT), free thyroxin, and plasma homocysteine. In women, increased mortality was associated with

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0 BIOSOCIAL SURVEYS low serum values for albumin and total cholesterol. The authors propose that these results could provide guidelines for clinical practice and general health examinations (Nilsson et al., 2003a, 2003b). Further study of the association of biochemical values with morbidity, drug therapy, and anthropometry was examined. In addition to expected findings showing that biochemical values deviate under disease states common among the elderly, a number of biological risk factors exhibit patterns of increasing risk with age, including blood pressure, glucose, and markers of inflammation and homocysteine, each of which is associ- ated with risks for one or more common diseases of aging, such as car- diovascular disease, osteoporosis, hip fracture, depression, and dementia (Nilsson et al., 2003a, 2003b). These findings indicate that morbidity and health-related factors common in aging populations substantially influ- ence routine biochemical values. Analyses of community-based studies, such as the MacArthur Study of Successful Aging, also point to potentially important age-related reduc- tions in risks associated with some biological factors (e.g., a reduction in the apparent risks associated with elevated total cholesterol—Karlamangla, Singer, Reuben, and Seeman, 2004), although other major risk factors continue to exhibit strong effects with respect to risks for major outcomes, such as physical function (Reuben et al., 2002), cognitive function (Weaver et al., 2002), and longevity (Hu et al., 2005). Analyses of biomarker data from the Cardiovascular Health Study (CHS) have confirmed that lipid profiles (specifically total and low-density lipoprotein [LDL], cholesterol) are not significant predictors of myocardial infarction (MI), stroke, or mortality among older adults (Psaty et al., 2004). CHS data also point to the continued importance of such biomark- ers as high blood pressure, fasted glucose, low albumin, elevated creati- nine, and low forced vital capacity as significant, independent risk fac- tors for mortality, along with additional measures of subclinical disease, including aortic stenosis, abnormal left ventricular ejection fraction, major electrocardiographic abnormalities, and stenosis of the internal carotid artery (Fried et al., 1998) and markers of inflammation (Jenny et al., 2006). Analyses from the Health, Aging and Body Composition Study (Health ABC) (another cohort study of adults ages 70 and older) suggest that the presence of metabolic syndrome (based on a complex of risk factors, including cholesterol, blood pressure, and glucose) in older adults does continue to predict subsequent coronary events, heart failure, myocardial infarctions, and cardiovascular-related mortality (Butler et al., 2006). Like the MacArthur and other studies of aging, Health ABC data indicate that inflammatory markers such as interleukin-6 (IL-6) and tumor necrosis factor (TNF)-α are associated cross-sectionally with the presence of sub- clinical or clinical cardiovascular disease (Cesari et al., 2003a), and the

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 JENNIFER R. HARRIS, TARA L. GRUENEWALD, AND TERESA SEEMAN the logistical constraints imposed by time and handling requirements for obtaining many biological measurements. Examples include (1) the need for phlebotomy to collect venous blood (e.g., when dried blood spots can- not be used), (2) the need for fasted blood samples, which can constrain collection to morning hours, (3) the need for sample collection at specific times due to diurnal rhythms of parameters such as cortisol, necessitating collection at the same time of day for everyone and collection of multiple samples over time, (4) the need for blood or urine samples to be processed within a limited time frame (usually within a couple of hours). The selec- tion of biomarkers for inclusion in a given study will thus necessarily be heavily influenced by what is possible in the context of specific study designs and logistical parameters. For example, the national scope of the HRS study precludes collection of venous blood so dried blood spots are being collected. Selection of biomarkers is thus restricted to those for which assays are available that can use dried blood spots rather than venous blood. By contrast, the MIDUS study is collecting a wide array of biomarkers because participants are being brought to regional clinical research centers (each in a hospital setting) where venous blood can be drawn first thing in the morning (allowing for fasted samples) and where these samples can be processed immediately. Thus, the final set of biomarkers included in any studies will reflect both the underlying scientific questions investigators seek to address and what is possible given their logistical and financial constraints. Despite the demands and challenges inherent in incorporating biomarkers into social science surveys, continued research development and efforts in the directions presented herein are critical to understanding better the factors that affect patterns of biological aging and trajectories of health at older ages. REFERENCES Antonelli-Incalzi, R., Pedone, C., McDermott, M.M., Bandinelli, S., Miniati, B., Lova, R.M., Lauretani, F., and Ferrucci, L. (2006). Association between nutrient intake and peripher- al artery disease: Results from the InCHIANTI study. Atherosclerosis, (1), 200-206. Bandeen-Roche, K., Xue, Q.L., Ferrucci, L., Walston, J., Guralnik, J.M., Chaves, P., Zeger, S.L., and Fried, L.P. (2006). Phenotype of frailty: Characterization in the Women’s Health and Aging Studies. Journals of Gerontology Series A: Biological Sciences and Medical Sciences, (3), 262-266. Bassuk, S.S., Glass, T.A., and Berkman, L.F. (1999). Social disengagement and incident cogni- tive decline in community-dwelling elderly persons. Annals of Internal Medicine, , 165-173. Bell, B., Rose, C.L., and Damon, A. (1972). The normative aging study: An interdisciplinary and longitudinal study of health and aging. Aging and Human Development, (1), 5-17.

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