Index

A

Accidents, 117, 150, 263

ACE gene, 98

Activities of daily living (ADLs), 67, 163, 168, 174, 339

Activities of Daily Vision Scale, 168

Adams, Julian, 80

Addictive behaviors, 45, 50, 78n.11, 86, 102, 116

Adematous colon polyps, 237

Administrative data linkages, 3, 13, 236, 251, 252, 256, 258, 271, 330

Adoption studies

bias in, 44

with biological offspring of adoptive parents, 119

designs, 118–119

of familiality, 118–119, 234–235

of genetic factors, 43–44

of mental illness, 234–235

representativeness of sample, 119

Adrenocorticotropic hormone (ACTH), 26

Advanced activities of daily living (AADLs), 163, 168

Advanced intercross, 222

Advocacy and support groups, 320

Affected sib-pair linkage analysis, 121

Affective status, 166, 167

Affinity chromatography, 29

Affymetrix, 135, 136

African Americans, 94, 102, 143, 282.

See also Race/ethnicity

Age/aging.

See also Biomarkers of aging;

Life span;

Longevity;

Mortality;

Mouse models of aging

actuarial quantification approach, 183– 184

and antioxidant levels, 24

biological, indices of, 184–185, 231–232

caloric restriction and, 182, 187–188, 204, 206–207, 232

definition, 181, 232

and disease processes, 231, 232

“elite” vs. “successful,” 144

energy resource allocation and, 232–233

environmental factors in, 182, 187–188, 204, 206–207, 232

and gene expression changes, 133, 134– 138, 182, 206–207

and genetics of disease risk, 73–74, 93, 97–98, 133, 232–233

homocysteine and, 21

intercellular signaling systems and, 161

interindividual differences in, 184–185

interpopulation differences in rate, 194

major surveys on, 2

and mortality patterns, 76, 81–83, 93



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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Index A Accidents, 117, 150, 263 ACE gene, 98 Activities of daily living (ADLs), 67, 163, 168, 174, 339 Activities of Daily Vision Scale, 168 Adams, Julian, 80 Addictive behaviors, 45, 50, 78n.11, 86, 102, 116 Adematous colon polyps, 237 Administrative data linkages, 3, 13, 236, 251, 252, 256, 258, 271, 330 Adoption studies bias in, 44 with biological offspring of adoptive parents, 119 designs, 118–119 of familiality, 118–119, 234–235 of genetic factors, 43–44 of mental illness, 234–235 representativeness of sample, 119 Adrenocorticotropic hormone (ACTH), 26 Advanced activities of daily living (AADLs), 163, 168 Advanced intercross, 222 Advocacy and support groups, 320 Affected sib-pair linkage analysis, 121 Affective status, 166, 167 Affinity chromatography, 29 Affymetrix, 135, 136 African Americans, 94, 102, 143, 282. See also Race/ethnicity Age/aging. See also Biomarkers of aging; Life span; Longevity; Mortality; Mouse models of aging actuarial quantification approach, 183– 184 and antioxidant levels, 24 biological, indices of, 184–185, 231–232 caloric restriction and, 182, 187–188, 204, 206–207, 232 definition, 181, 232 and disease processes, 231, 232 “elite” vs. “successful,” 144 energy resource allocation and, 232–233 environmental factors in, 182, 187–188, 204, 206–207, 232 and gene expression changes, 133, 134– 138, 182, 206–207 and genetics of disease risk, 73–74, 93, 97–98, 133, 232–233 homocysteine and, 21 intercellular signaling systems and, 161 interindividual differences in, 184–185 interpopulation differences in rate, 194 major surveys on, 2 and mortality patterns, 76, 81–83, 93

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? multiple-clocks model, 181–182 and onset of disease, 48, 76, 94, 140, 141, 143, 234, 238, 263, 314 paternal, and mutations in offspring, 139 pathobiology of, 15, 146 and physiological function, 143–144, 159–176, 182 sample collection considerations, 243, 246, 265, 267, 297 single-clock model, 182–183 and societal functioning, 162–163 and stereotypic expectations, 162–163 and telomere shortening, 232 Aging Research Center, 53 Albumin, 20, 21, 22, 25 Alcohol/alcoholism, 45, 50, 78n.11, 86, 218, 224, 282 Allele-sharing methods for QTL mapping, 121–122 Alleles APOE, 50, 52, 73, 74, 78, 83, 88, 90, 93– 94, 102, 143, 225, 340 BRCA, 84, 92–93 candidate, 69n.5, 70 common, 71 defined, 67, 339 825T for GNB3 gene, 79, 95 frequencies, 139, 239 geographic distribution of, 72, 141, 148, 238, 239 HPC, 241 rare, 67, 73, 84, 91, 92–93 risky, 84n.17, 85 SNPs, 67 Alliance of Genetic Support Groups, 320 Allostatic load, 3, 25–26, 334–335, 339 Alpha secretases, 141 Alzheimer’s disease APOE genes and, 50, 71, 73, 74, 90, 91– 92, 93, 94, 101, 143, 145, 241, 263, 264, 314, 340 autopsy studies of, 137, 140 complex-trait models, 114 data collection issues, 236, 298 early-onset, 140 environmental considerations, 93, 94 gender differences, 93 late-onset, 263 population studies, 4–5, 237 race/ethnicity and, 94, 142–143 twin studies, 45 American Academy of Pediatrics, 297 American College of Medical Genetics, 297 American College of Pathology, 148 American Society of Human Genetics, 293, 297, 311 Amino acids, 151, 339 Amyloidosis, 197 Anemia, 271 Animal model research advanced intercross groups, 222 advantages, 180, 208–209, 225 backcross groups, 223 of biomarkers of aging, 187–192, 193 of cognition, 216, 226 comparison with human studies, 188 of diabetes, 222 dogs, 204–205 environmental variables in, 215–217, 223 fruit flies, 184, 215, 222, 224 gene mapping, 222 genetic variables in, 217–223 genetically heterogeneous stocks, 219– 223 genotype constraint, 217–219 genotypic selective breeding, 225 IL-6-stress relationship, 22 inbred strains, 217–219, 221, 222, 223 manipulation of genes in, 223–225 mice, 215, 216, 222, 225; See also Mouse models of aging microarray analyses, 138 model systems, 214–223 nematode worms, 182, 205, 217, 222 phenotypic selective breeding, 224–225 QTL, 222, 223, 225, 226 quantitative genetic model, 113, 226 rationale for, 214 recombinant strains, 223 relevance for human populations, 213– 227 replicability, 218, 219–220 representativeness of strain, 218, 219– 220 Rhesus monkeys, 200 species choice, 214–215 statistical power, 219 transgenic and knock-out preparations, 225 validity for humans, 225–227 wild-trapped animals, 220 yeast, 222

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Antagonistic pleiotropy, 97, 340, 342 Anthropometric measurements, 54, 254, 271 Antibody production, 201 Anticlotting agents, 23 Antioxidants, 20, 24, 30, 209 Antisocial and criminal behavior, 87 APOB gene, 98 Apolipoprotein E (APOE) genes, 150, 331 and Alzheimer’s disease, 50, 71, 73, 74, 90, 91–92, 93, 94, 101, 143, 145, 241, 263, 264, 314, 340 animal model, 225 BRCA genes compared, 91–94 and cardiovascular disease, 50, 73, 74, 78–79, 83, 91, 92–93, 94, 96, 143, 145, 264, 340 case-control studies, 75 and cholesterol, 50, 85, 340 and cognitive function, 18, 50 cohort studies, 88 defined, 340 and demographic modeling, 18, 73–74, 90, 91–94, 99 and diabetes, 50 e2 allele, 143 e3 allele, 225 e4 allele, 50, 52, 73, 74, 78, 83, 88, 90, 93– 94, 102, 143, 263, 265, 340 environmental interactions, 50, 94 gender differences, 18, 93 genotype/genotyping, 30, 50, 60, 73, 74– 75, 92, 145, 254 and head trauma recovery, 52 and health outcomes, 18, 85 and mortality risk, 74–75, 78–79, 83, 88, 91–92, 93, 102 population frequencies, 92–93 polymorphisms and rare alleles, 73, 91, 92–93 race/ethnicity and 18, 79, 85, 92–93, 102, 143 Apoptosis, 194, 340 Arnold, Matthew, 334, 336 Arteriosclerosis, 142 Arthritis, 11, 17. See also Osteoarthritis; Rheumatoid arthritis Ashkenazim, 93, 319 Assets and Dynamics Among the Oldest Old (AHEAD), 251 Association studies, 78, 122 biological samples and, 236 with candidate genes, 69–70, 86, 97, 123– 124, 240 case-control design, 87, 123, 133, 142– 143, 239–240 of dementia, 142–143 elements of, 214 environment-disease, 240 founder effects, 123 genetic drift and, 123 of inheritance patterns, 69–70, 78 limitations of, 70, 142–143 linkage methods integrated with, 121, 125 pedigree-based, 143, 240–241 population-based, 239–241 of psychiatric disorders, 86 race/ethnicity and, 70, 123, 142–143 with siblings, 124–125, 143 spurious associations in, 123–124 with tightly linked markers to functional genes, 123–124 transmission/disequilibrium tests, 124– 125 with twins, 45, 241 Assortive mating, 95, 117, 118, 340 Asthma, 114–115, 239, 260 Atherosclerosis, 24, 50, 162, 233 Atherosclerosis Risk in Communities study, 27 Attention/attentiveness, 166 Attributable risk, 90, 93, 99 Attrition, biological sample collection and, 29, 30, 55–56, 59, 242–243, 270 Autism, 45 Autoimmune diseases, 260 Autopsies of accident victims, 150 costs, 149 dementia studies, 137, 140 genetic analysis of samples, 150 hospital, 150 population-based studies of geriatric populations, 4–5, 134, 150 rates, 148–149 sources of materials from, 149–150 Autosomal dominant mutations, 140, 141 Autosomal recessive disorders, 49, 140, 151

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? B Baby-boom cohorts, 252 Backcross groups, 223 Bacterial artificial chromosomes (BACs), 139, 340 Balance, 18 Baltimore Longitudinal Study of Aging, 162 Bangladesh, 271 Base pairs, 137, 139, 340 Base sequence, 340 Basic activities of daily living (BADLs), 168, 258 Behavioral genetics in addictions, 45, 50, 78n.11, 86, 102, 116 association studies, 86 community-based studies, 241–242 and demographic analysis, 76, 78n.11, 85–87, 100 generalizability of findings, 100 psychiatric disorders, 86 research opportunities, 330–331 twin studies, 45, 48, 68, 86 Beta amyloid precursor protein, 140–141, 150 Beta secretases, 141 Between-population differences, in gene—environment interactions, 85, 90, 95 Bias in adoption studies, 44 in case-control studies, 142, 240 environment-disease association studies, 237–238 in genetic epidemiology, 235 in linear regression, 77–78 in logistic regression, 78 population stratification, 239 in risk assessment, 255 sampling, 86, 98, 111, 150, 239, 253 selection, 246, 267 in twin studies, 44, 117–118 type I errors, 237 Biodemography, 340 Bioindicators. See also Biomarkers advantages in social surveys, 4–6, 254–265 allostatic load, 25–26, 339 antioxidant profiles, 20, 24 appropriateness, 9 blood samples as, 171–172, 254 of cardiovascular system, 18, 19, 20, 21, 22 changes over time, 256 cholesterol as, 15, 19, 22, 25, 254 cognitive function, 21, 22, 23, 24, 25 collaborative research opportunities, 272 defined, 340 in demographic approach, 14–16, 94 environment-health linkages from, 259– 263 fertility, 15 gene expression data and, 207, 208 height and weight as, 329–330 historical context, 329 HPA axis, 20, 22–23, 25, 29 for inclusion in household surveys, 17– 26, 31, 254 liabilities in social surveys, 265–266 lung function, 19, 20, 24, 28, 54, 161–162, 174 of metabolic processes, 19–21, 161 physiological, 18–19, 21 renal function, 19, 20, 24, 159, 161, 170, 172 and representativeness of nonclinical data, 254–256 risk factors, 15, 19 self-report calibration with, 256–259 SNS activity, 19, 20, 23, 25, 29 symptoms, 15 value of, 330–336 Biological determinism, 320 Biological pathways, 16 Biological specimens. See also Blood samples; Collection of biological specimens; DNA samples/sampling; Pathology samples; Repository specimens; Urine samples and association studies, 236 from autopsies, 149–150 genetic specimen sources, 149–150, 245– 246, 276 for hypothesis testing, 208 transport and storage, 244–245, 268 uses of data from, 9, 276 Biomarkers. See also Bioindicators of coagulation processes, 20, 21–22, 161 defined, 184, 340 of diabetes, 172, 184–185 in epidemiologic studies, 17 of inflammation processes, 19, 20, 21–22, 25 of neuronal cells, 137

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Biomarkers of aging, 17 animal model research, 187–192, 193 criteria for, 185–186 defined, 185, 340 gender and, 188–189, 191–192, 193 hormonal/reproductive history, 191–192 indices of biological age and, 184–185, 231–232 life expectancy correlated with, 186 molecular, 134 mouse studies of, 187–192, 193 muscle strength and, 189, 190 physiological reserve and, 186 secondary evaluation criteria, 187 T-cell subsets, 187–192, 193, 200–201, 206 validation of, 185–186 Biomedical assessments, 28 Biometric models, 44 Blood pressure. See also Hypertension alcohol and, 50 BMI and, 96 diurnal fluctuations, 161 heritability of, 94, 95–96 measurement, 19, 20, 25, 28, 161, 290 race/ethnicity and, 256 Blood samples, 19 collection, 29–30, 55, 57, 58, 243, 254, 271, 279 indicators of function, 171–172 interpretation considerations, 172 Body mass index, 15 and blood pressure, 96 and cardiovascular disease, 96 heritability of, 44, 94, 95 measurement of, 20 Bone density, 74, 96–97, 189, 201, 237 Bone fractures, 23, 89, 96–97, 237 Bone marrow function, 161 Bone matrix turnover, 203 Boston University, 312 Brain gene expression in, 85–86, 137 GFAP levels, 203 BRCA genes APOE gene compared, 91–94 defined, 341 as demogenes, 91–94 and mortality risk, 91–92 polymorphisms and rare alleles, 84, 92– 93 testing for, 101, 294 Breast cancer, 46, 74, 84, 91–94, 101, 237, 294, 319, 320, 341 Brown, Pat, 135 C C-reactive protein (CRP), 20, 21, 22, 25, 30 Caloric restriction and aging, 182, 187–188, 204 and gene expression, 206–207 Cancer. See also individual sites cultural practices and, 84 heritability of, 68, 90–91, 139, 142 and longevity in mice, 196–197, 198 repository-sample issues, 293, 294 self-reports of, 17 stress and, 260 telomere shortening and, 232 tumor suppressor genes, 138–139, 142 Cancer Genetic Studies Consortium (CGSC), 320 Candidate genes. See also Demogenes association studies with, 69–70, 86, 97, 123–124, 240 confirmatory role of social surveys, 321 defined, 341 Human Genome Project and, 72 for longevity, 87–88, 97–98, 141–142, 182, 203, 342, 344 for psychiatric disorders, 86 Capron, Alexander, 294 CARDIA, 27 Cardiac arrhythmias, 161 Cardiovascular disease. See also Heart disease; individual disorders and diseases allostatic load and, 25 APOE gene and, 50, 73, 74, 78–79, 83, 91, 92–93, 94, 96, 143, 145, 264, 340 bioindicators of, 18, 21, 23, 24 BMI and, 96 cholesterol and, 96 cortisol and, 23 environmental influences, 116 gender differences in outcomes, 93 gene-environment interactions, 12, 94, 233 genetic factors, 48, 50, 73, 74, 78–79, 83, 91, 92–93, 94, 96, 143, 145, 340 Syndrome X, 18, 25 Cardiovascular Health Study, 27

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Cardiovascular system bioindicators of health, 18, 19, 20, 21, 22 functional assessment, 161, 162 and self-efficacy and control, 23 Case-control studies of APOE mortality risk, 75 demographic analyses used with, 77 of environment-health interactions, 240 of gene-disease associations, 87, 123, 133, 142–143, 239–240 of gene-environment interactions, 241 limitations of, 74, 142–143, 240 nested, 51, 240 point estimates, 77 for qualitative traits, 123 Cataracts, 142, 189 Catecholamines, 23, 26, 207, 267 Causation, 90n.21 Cause-of-death associations, 189, 196–200, 238 cDNA, 135, 136, 341 Center for Epidemiological Studies Depression Scale, 261 Centers for Disease Control, 277, 286, 297 Cerebrovascular disease, 21, 166 Challenge, and health, 23, 260–262 Chemtech, 136 Children genetic testing of, 296–298, 314 health issues, 11, 14, 15 Chinese populations, 27, 92, 95n.22, 251, 253–256, 261, 264, 271 Cholesterol, serum APOE gene and, 50, 85, 340 as bioindicator of health status, 15, 19, 22, 25, 254 and cardiovascular disease, 96 components, 19–20 and functional status, 22 HDL, 19–20, 22, 29, 256 measurement of, 20, 29, 254, 288, 290 race/ethnicity and, 85 synthesis errors, 49 Chromosomes, human (4), 64 (6), 87 (12), 49 (19), 71 Chromosomes, mouse (6), 195 (9), 195 (12), 195, 197, 201, 209 Chronic fatigue, 263 Chronic obstructive pulmonary disease, 46 Clinical Laboratory Improvement Amendments, 289 Clinical samples and tests, 27, 150–152, 160, 161, 170, 173, 243, 289 Clones/cloning BAC, 139, 340 positional, 64, 70, 71, 194, 345 Cluster analysis algorithms, 135 Coagulation processes, 19, 20, 21–22, 161 Cognate DNA sequences, 139 Cognate genes, 135 Cognitive function animal model of, 216, 226 APOE gene and, 18, 50 assessment, 3, 28, 54–55, 144, 167, 258 bioindicators of, 21, 22, 23, 24, 25 dimensions of, 166 heritability of, 47, 86, 87, 234 and informed consent, 270, 298 integrative, 167 lung function and, 24 and physical function, 163 population studies, 11, 150, 237, 258 and self-reports, 258 stress and, 260 Cohort studies. See also Population-based research and surveys; individual studies of APOE genes, 88 collection of biological materials in, 54– 55 disease risk trends, 74 of gene-disease relationships, 239–240 of gene-environment interactions, 50–51, 54–55, 238, 240 in genetic epidemiology, 88–89, 235 temporal associations in, 238 COLIA genes, 70 Collagen, 70, 182, 201 Collection of biological specimens. See also Biological specimens; Measurement of function; Sampling strategies age considerations, 243, 246, 265, 267 benefit to study participants, 269, 282 biopsy tissues, 160, 173, 243 blood, 29–30, 55, 57, 58, 243 clinic-based protocols, 27, 160, 173, 243, 254 in cohort studies, 54–55

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? and compromise of research objectives, 265, 268–269, 341 costs, 6–7, 56, 59, 207, 251, 254, 265–266, 267–268, 271 cytological/cellular samples, 148, 161, 172–173, 245 Danish 1995–1999 experience, 3, 53–55, 56 DNA, 56–60, 208, 243, 263 ethical issues, 31, 246, 251 in family studies, 208 feasibility of, 53–60, 251 for gene mapping, 208 for genetic epidemiology, 42–43, 51–53 informed consent for, 270, 279–280 in-home, 6, 243, 254, 258, 267 logistical issues, 26, 243–244, 254, 267– 268 in MacArthur Study, 26–30, 31 noninvasive, 31, 170 pilot studies of, 28–29, 243, 253, 264, 266 in population surveys, 16–17, 26–30, 53– 60, 207, 236, 242–246, 263, 265–269 prospective, 277, 279 quality control, 60, 244, 251, 268 from repositories, 246 respondent burden, 6, 266–267, 297–298 semen and ova, 243, 246 staff training for, 7, 243, 268 and study participation rate, 6, 29, 30, 55–56, 59, 242–243, 251, 266 Collection of data anthropometric measurements, 54, 254, 271 family structure and disease data, 236 in household surveys, 12–13, 16–17, 53– 60, 161–162, 236 proxy interviews, 12, 59, 173, 175, 236, 252, 253, 256, 270 self-reports, 12, 16–17, 26, 30, 174, 175– 176, 256–259, 262 College of American Pathologists Ad Hoc Committee on Stored Tissue, 286, 294, 295 Collins, Francis, 320 Colon/colorectal cancers, 115, 146–148, 237 Communication of research results, 265, 268–269, 288–290, 297, 341 Community-based behavioral studies, 241– 242 Comparison disparate studies, 74–75 Complex quantitative traits defined, 67 demography and, 72–75, 239 in disease, 114, 233, 240 in founder populations, 239 models of, 112, 121 Confidentiality issues, 255 Certificate of Confidentiality, 309 importance of, 270–271 informed-consent protections, 280–281, 291, 292–293, 297 Congenital hypothyroidism, 151 Congestive heart failure, 159, 170, 197 Consanguineous matings/marriages, 140 Consumer rights movement, 278 Contamination effects, 265, 268–269, 341 Controls. See also Case-control studies in demographic studies, 77–78 in family studies, 111, 124–125, 126 genes as, 77–78, 263, 264 in nested case-control studies, 51 in population studies, 239, 263 racial/ethnic considerations, 51 twins as, 65, 68 Coronary artery disease, 95, 96, 100, 170, 237 Coronary heart disease, 22 Cortisol, 20, 22–23, 25, 29, 172, 254, 267 Cost considerations in autopsies, 149 in biological specimen collection, 56, 59, 207, 251, 265–266, 267–268, 271 laboratory assays, 136, 137, 267 Covariation, among relatives in family studies, 113, 115, 118 Cox regression analysis, 51, 88 Creatinine clearance, 20, 24, 29 Cross-cultural studies, 255–256 Cross-national comparisons, 76 Cross-sectional analysis, 238, 255 Crossover effect, 201, 221, 341 Crow, James, 139 Cryopreservation of surgical tissues, 145, 146 Cultural considerations, in genetic research, 282–283, 317–319 Cultural practices, and cancer, 84 Cultural transmission effects, 113, 117, 118, 140 Cystic fibrosis, 43, 49, 99, 238, 314 Cytokines, 161, 186

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Cytological/cellular samples and tests collection of, 148, 161, 172–173, 245 gene expression screening by cell type, 206–207 D Danish Center for Demographic Research, 53 Danish 1905-Cohort Study, 53, 54–56, 59 Danish Twin Registry, 54 Death certificate data, 134, 148, 150 deCODE Genetics, 311–312, 313 Dehydroepiandrosterone sulfate (DHEAS), 20, 22, 23, 25, 29, 254, 256 Delayed paragraph recall test, 144 Dementias, 137. See also Alzheimer’s disease association studies of, 142–143, 239 autopsy data, 137, 140 background rates, 142 early-onset, 48, 140, 141 genetic factors, 48, 239 and language function, 166 late-onset, 48, 143 and physical functioning, 163 population studies of, 258 and proxy interviews, 59, 236 Demogenes APOE as, 18, 73–74, 90, 91–94, 99 for body mass index, 95 BRCA as, 91–94 for coronary artery disease, 96 criteria for, 89–94, 99 defined, 76, 89 evidence from genetic epidemiology, 94–99 gene-environment interactions, 90, 94, 95 for hypertension, 95–96 identification of, 89–94 for longevity, 97–98 for osteoporosis, 96–97 prospects for, 98–99 Demographic approaches/models of age pattern of mortality, 81–83 of APOE gene, 18, 73–74, 90, 91–94 behavioral genetics in, 76, 78n.11, 85–87, 100 bioindicators in, 7, 14–16, 94 case-control data combined with, 77 common mechanisms, 9 comparing disparate studies, 74–75 complex quantitative traits and, 72–75, 239 controlling for genotype in, 77–78 of fertility, 11 of gene-environment interactions, 90, 94, 95 genetic epidemiologic surveys and, 88– 89, 94–100, 101–102, 242 genetic marker distributions, 238–239 in genetic research, 65, 66, 72–75, 100–101 genotyping for, 73, 75, 77–78 health outcome models, 13–14, 76–81, 84–85 of individual differences in outcomes, 76–81 and informed consent, 279 longevity genes and, 76, 87–88 of major genes for common diseases, 73–74, 89, 242 multistate, 75, 80 of population differences in outcomes, 84–85 scope of, 7, 10 time considerations, 101 variables of interest, 67 Depression, 48, 260, 261 Diabetes mellitus animal models, 222 APOE gene and, 50 biomarkers for, 172, 184–185 clinical test, 160, 170 environment and, 5–6, 260 insulin-dependent, 48, 124 juvenile type 1, 314 race/ethnicity and, 16, 21, 319 self-reports of, 17, 257 TDT for, 124 type 2, 142 Dimensionality reduction, 6, 335 Disease and disease processes. See also Health outcomes; individual diseases and disorders age-at-onset considerations, 48, 76, 94, 140, 141, 143, 234, 238 age-related rates of change in, 231 aging distinguished from, 232 cohort studies of risk trends, 74 dimensions of, 231 family studies of, 234–235, 236 gene-environment interactions, 12, 44, 49, 79, 84, 94, 95, 114–115, 146, 233, 263

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? genes for, 64, 65, 73–74, 79, 97 genetic variance in, 49–50 misclassification of conditions, 234 registries, 239 single-gene, 140, 238 twin studies of, 45, 48, 234 Divorce, 48 Dizygotic (fraternal) twins, 44, 54, 68, 117, 234 DNA adducts, 244 cognate, 139 damage, 24, 185 defined, 341 genomic, 139 junk, 342 mitochondrial, 98, 239, 344 recombinant, 346 repair, 232 sequencing, 135, 139, 341 variants, 72 DNA samples/sampling age considerations, 246 alternative sources, 245–246 cheek brushes, 54, 57–59, 173, 208, 243, 263, 265 finger prick, 54, 56–57, 58, 173, 208 for gene mapping, 208 in genetic epidemiology, 43 in-home collection, 243 mouth lavage, 56 participation rates, 59 quality control, 60 size of, 208 sources, 149–150, 245–246 storage, 60, 244–245 urine, 56 Dogs, height-life span nexus, 204–205 Dominant gain-of-function mutations, 140 Dopamine, 21, 29 Drosophila, 215, 224 Dyslexia, 45, 86–87 E Economic models of health, 10, 14, 260 Economic returns to education, 68 Educational attainment, and outcomes, 333 Effect modifiers, genes as, 78–79, 139 Effect size, 18 Egypt, 271 Empirical results, 10 Endocrine function, 23, 161, 171, 194 Endometriosis, 197 Endorphins, 207 Environment-health interactions. See also Gene-environment interactions and age-related physiological change and disease, 182, 187–188, 204, 206– 207, 232 in Alzheimer’s disease, 93, 94 in animal model research, 215–217, 223 bioindicators of, 259–263 biological factors, 5 candidate agents, 125 and cardiovascular disease, 116 case-control studies, 240 chemical factors, 5 compromise approach, 116 in family studies, 117 and genetic variance, 48 latent effects, 116, 126 major qualitative exposure to risk factors, 112, 115 “mapping,” 5, 125–126 measurable effects, 3–4, 116–117, 126 migration studies, 235 monitoring systems, 3–4 physical factors, 5 polyenvironmental influences, 115–116 in quantitative genetic models, 115–117, 125, 127 shared environmental effects, 117, 118 twin studies, 45, 117 Enzymes, 140–141, 160, 341 Eosin, 144 Epidemiological models, 10–11, 12–13. See also Genetic epidemiology biomarkers in, 17 Epigenetic changes, 146–147, 341 Epinephrine, 20, 23, 25, 29, 254 Epistatic effects, 114, 222, 341 Equal environment assumption, 45, 117 Established Populations for Epidemiologic Studies of the Elderly (EPESE), 27, 89, 256, 341 Estrogen receptor gene, 146–147 Ethical issues, 31, 59. See also Confidentiality issues; Informed consent; Privacy of genetic information in collection of biological specimens, 31, 246, 251

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? communication of research results, 288– 290 in genetic marker research, 264–265 in genetic testing, 281–283, 291–292, 297, 317–319 group-related harms, 282–283, 304, 317– 319 HGP budget for, 304 historical reports, 304–305 ownership of repository specimens, 245, 295, 311–315 paternity misattributions, 236, 292, 307, 316 psychological risks, 315–317 research agenda on, 7, 322–323 responding to change in genetic research, 321 in social surveys, 255, 264–265 Ethical, Legal and Social Implications Program, 322–323 Ethnohistorical distance between populations, and cancer mortality, 84 Eugenics, 281 Evolutionary theory, 110 Executive function, 167 Exons, 135, 342 Extraversion, 47 Eye tumor retinoblastoma, 239 F F1 generation, 220–221, 222, 223, 342 Familiality adoption studies, 118–119, 234–235 information sources, 236 nuclear family studies, 118 sibling studies, 119, 234–235 in twins reared apart, 68, 119 twin studies, 117–118 in unrelated children, 235 Family studies. See also Adoption studies; Twin studies biological samples, 208 controls, 111, 124–125, 126 covariation among relatives in, 113, 115, 118 cultural transmission model in, 118 design of, 111–112 of diseases and disorders, 234–235, 236 environmental considerations, 117 gene-environment interactions, 42, 118 in genetic epidemiology, 68 of genetic markers, 240–241 generalizability and representativeness of, 118 of heritability of traits, 68, 120, 254 limitations of, 111–112, 118, 124–125, 236 nuclear, 118, 240–241 parent-offspring pairs, 119, 125, 208 Fatty acid oxidation, 151 Fertility, 11, 15, 46–47. See also Reproduction Fibrinogen, 20, 22, 30 Fibroblast growth patterns, 203 Fibromyalgia, 263 Fibrosarcoma, 189, 196, 197, 198 “Fight or flight” responses, 23 Fine mapping, 70, 71 Finland, 22, 70, 92, 93, 149 Folic acid, 21, 30 Founder effects/populations, 85, 90, 93, 123, 141, 239, 342 Frailty, heterogeneity in, 75 Framingham Genomic Medicine, Inc. (FGM), 312 Framingham Heart Study, 10, 27, 89, 312 Framingham Offspring Study, 89 Free radicals, 24 Fruit flies, 184, 215, 222, 224 Function. See also Physiological functions assessment of, 158; see also Measurement of function integrated, 3, 162, 168–169, 174, 175 levels of, 160–163 societal, 162–163, 175 types of, 163–169 Functional reserve, 170, 171, 186 G G-protein $3 subunit, 79, 95 Gamete, 342 Gamma secretases, 141 Gender/sex and addictive behavior, 45 and Alzheimer’s disease, 93 and antioxidant levels, 24 APOE gene and, 18, 93 and biomarkers of aging, 188–189, 191–192, 193 and cardiovascular disease outcomes, 93

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? and fertility, 47 and health behavior, 254 and heritability of traits, 45, 47 and intelligence, 87 and life expectancy, 15 Gene chips, 120, 135, 136. See also Microarray analysis Gene-environment interactions. See also Genetic epidemiology aging-related, 5 APOE gene, 50, 94 assessment of, 51, 150 and between-population differences, 85, 90, 95 challenges in studies, 42, 51–53, 87, 114 case-control studies, 51, 241 cohort studies, 50–51, 54–55, 238 community-based behavioral studies, 241–242 and demographic studies, 90, 94, 95 design of studies, 50–51, 79, 150 in diseases and disorders, 12, 44, 49, 79, 84, 94, 95, 114–115, 146, 233, 263 family studies, 42, 118 height as expression of, 329–330 and longevity, 98 in mental illness/disorders, 44, 86, 241– 242 multiple comparison problem, 52–53, 70 relationships in, 48–49, 234 sample size considerations, 237 and segregation analysis, 69 toxicant metabolism, 241 twin studies, 44–45 Gene expression aging-related changes in, 133, 134–138, 182, 206–207 and bioindicators of clinical states, 207, 208 in the brain, 85–86, 137 caloric restriction and, 206–207 epigenetic changes in, 146–147, 341 microarray methodologies, 120, 133, 135–139, 145, 150, 344 in peripheral blood samples, 145 protein modulation of, 146 quantitative analysis of, 139 screening by cell type, 206–207 suppression, 341 technology, 127 transcription factors and, 134 Gene-gene interactions, 85, 87, 225 Gene mapping in affected sib-pairs, 121 in animal models, 222 with BAG clones, 139, 340 biological sample collection for, 208 defined, 342 linkage analysis, 120–121 of Mendelian major factors for disease loci, 120 multipoint, 121 pedigree data and, 120–121 positional cloning, 64, 70, 71, 194, 345 QTL studies, 86, 121–122, 125, 194–195, 201, 203, 222 in quantitative genetic model, 113, 119 sib-pair allele-sharing methods, 121–122 sibling studies, 119, 121–122 tandem repeats, 346 Gene promoters, 146 Gene therapy, 242, 306 Generalizability of findings in behavioral genetics, 100 in family studies, 118 Genes. See also Apolipoprotein E; Demogenes; Major genes ACE, 98 and age patterns of mortality, 81–83 for Alzheimer’s disease, 50, 71, 73, 74, 90, 91–92, 93, 94, 101, 143, 145, 340 APOB, 98 asthma susceptibility, 239 and behavior, 85–87 BRCA, 84, 91–94, 101, 294, 319, 341 cognate, 135 COLIA, 70 for common diseases, 73–74 as controls, 77–78 defined, 342 demographic models for, 73–74, 89, 242 as effect modifiers, 78–79, 139 estrogen receptor, 146–147 FAP, 294 functional, 123 and heterogeneity in survival analysis, 80–81 for Huntington’s chorea, 64, 65 as instrumental variables, 79, 333–334 isoforms, 137, 343 longevity, 76, 87–88, 97–98, 141–142, 182, 203, 342, 344

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Likelihood of adds (LOD) score, 120, 344 Linear regression analysis, genetic information in, 76, 77–78 Linkage analysis, 78 affected sib-pair, 121, 240–241 association methods integrated with, 121, 125 gene mapping with, 120–121 in genetic epidemiology, 70–71, 78 LOD score, 120 longevity studies, 140–142 of pedigree data, 120–121, 140–142, 240– 241 principles, 70–71, 72, 140 for psychiatric disorders, 86 twin studies, 44–45 Linkage disequilibrium, 71, 98, 120, 123, 139, 222 Liver function, 161 Locus/loci defined, 69, 343 identical-by-descent, 121, 139 LOD score, 344 quantitative trait, 69, 86, 114, 346 of small effect, 114 SNPs as, 70 Logistic regression analysis, genetic information in, 76, 78 Longevity, 233 antioxidants and, 24 cause-of-death associations, 189, 196– 200, 238 CD8M T-cells and, 187, 191, 192, 193 demographic considerations, 76, 87–88 gene-environment interactions and, 98 genes, 76, 87–88, 97–98, 141–142, 182, 203, 342, 344 natural selection and, 182, 183 in nonhuman species, 182, 183, 184, 196– 197, 198 and reproductive performance, 182–183, 194 segregation analysis, 77 Longitudinal Danish Centenarian Study, 53, 55, 56 Longitudinal Study of Aging (LSOA), 27 Longitudinal Study of Aging Danish Twins (LSADT), 53–54, 55, 56, 59 Longitudinal Study of Middle-Aged Twins, 53, 54, 56, 59 Low-density lipoproteins, 19–20, 24 Lung cancer, 73–74, 241 Lung function, 19, 20 and cognitive function, 24 health behavior and, 24 measurement, 3, 28, 54, 161–162, 174 Lymphoma, 189, 196, 197, 198 M Mac Arthur Study of Successful Aging, 10 biomarker correlates in, 21, 22, 24, 25 biomedical assessments, 28 cholesterol risk stratification, 20 collection of biological information in, 26–30, 31 cross-cultural comparisons, 255–256 description of, 27–28, 30–31, 262 LSOA compared, 27 physiological measures from blood and urine, 28–30 Macular degeneration, 234 Major affective disorder, 45, 86 Major genes and age-related risks, 73–74 for blood pressure, 95–96 for BMI, 95 defined, 67 demographic models for, 73–74, 89 disease registries, 239 and genetic variance, 113 interactions in diseases, 74 life-span modulating, 140–142 with multiple disease associations, 74 Mammary carcinoma, 189 Masoro, Edward, 182 Measurable effects environmental, 116–117 genotypic, 114–115, 126 Measurement of allostatic load, 25 of BMI, 20 of cholesterol, 20, 29 error, 26 of gene-environment interactions, 51, 150 Measurement of function ADLs, 67, 163, 168, 339 auditory, 168 biological samples, 169, 171–173 blood pressure, 19, 20, 25, 28, 161 cardiovascular system, 161, 162 clinical-level, 159, 161, 169

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? cognitive assessment, 28, 54–55, 144, 167 conditions for testing and, 176 criteria for method selection, 175 and diagnosis of disease, 159 in-home methods, 161–162 individual’s role in, 175–176 instruments for, 167, 168–169 molecular-level, 160 neuropsychological, 167 observer rating, 175 performance-based, 3, 12–13, 163, 173, 174–175, 176 physiological stress testing, 170 qualitative vs. quantitative, 169–170, 175 respondent burden, 173–174, 297–298 resting vs. challenge, 170–171 self-reports, 163, 173, 174 at total-organism level, 173–174 types of measures, 171–175 vision, 168 Medical Outcomes Study SF-36, 167 Medical records, 3, 13, 17, 263 Medicare claims records, 3, 13, 149, 251, 252, 258 Mediterranean fruit flies, 184 Meiosis, 120, 140, 344 Memory, 47, 144, 166, 260 Mendelian major factors for disease loci, 120 models of inheritance, 68, 71, 99, 112, 113, 222, 263 Mental health/illness, 11. See also specific disorders adoption studies, 234–235 data collection issues, 236 gene-environment interactions and, 44, 86, 241–242 performance testing of, 12 stress and, 260 Mental Health Index, 167 Mental retardation, 49 Messenger RNA (mRNA), 134, 341, 344 and functional capability, 160 microarray screening, 135, 137–138 quantitation, 160 transcription of genes into, 146 Metabolic processes and allostatic load concept, 25 indicators of health status of, 19–21, 161 Methylation, of gene promoters, 146–147 Mexican Americans, 96 Mice, longevity, 182 Microarray analysis animal studies, 138 BAC clones, 139 cDNA screening, 135, 136 costs, 136, 137 defined, 344 fluorescence-labeled, 136 of gene expression, 120, 133, 135–139, 145, 150, 344 genomic DNA hybridization, 139 human studies, 138, 139, 150 for inborn alterations in gene dosage, 138–139 informatics software, 135 oligonucleotide, 135, 136, 139 of pathology tissues, 145, 150 of polymorphisms, 139 resources, 135–137 for special-interest genes, 137 Microelectromechanical systems (MEMS), 3–4 Microsatellites, 120, 346 Middle-age populations advantages of studying, 134, 143–144, 185 Werner syndrome in, 194 Middle East, 140 Midlife in the United States survey (MIDUS), 271 Migraine headaches, 263 Migrations, population, 123, 124, 235, 238 Ming-Cheng, Chang, 268 Mini-Mental State Examination, 54, 167 Mini-Wright meter, 28 Mitochondrial DNA (MtDNA), 98, 239, 344 Mitochondrial protease, 138 Model, defined, 213–214 Molecular biology, advances in, 64, 66–67 Molecular biomarkers, 134 Molecular screening, 160 Monoclonal antibodies, 145 Monogenic diseases, 43, 344 Monozygotic (identical) twins, 44, 54, 68, 117, 234, 344 Moore v. Regents of the University of California , 295 Morphogens, 344 Mortality age-related patterns, 76, 81–83, 93 allostatic load and, 25

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? APOE gene and risk of, 74–75, 78–79, 83, 88, 91–92, 93, 102 BCRA genes and, 91–92 cancer, 84n.15 case-control studies, 75 catecholamine excretion and, 23 coagulation markers, 22 demographic research on, 99 DHEAS and, 23 genetic component, 18, 44, 67, 82 IHD, 93 inflammation markers and, 21–22 initial risks, 200 lung function and, 24 premature death, 44 race/ethnicity and, 102 risk factors for, 19, 21, 22 summary biologic risk scores and, 25 Mortality rate, doubling time, 183, 200 Motion detectors, 161 Motivation, and fertility, 47 Mouse models of aging advantages over human studies, 209 APOE gene, 225 biochemical mediators of genetic effects, 201, 203 biomarkers in, 187–192, 193 caloric restriction, 187–188, 204, 206–207 cause-of-death associations, 189, 196– 200, 205 CD4M T-cell biomarker, 187–192, 200– 201, 202 CD8M T-cell biomarker, 193 chromosomes, see Chromosomes, mouse gender covariate, 188–189, 191–192, 195 gene expression screening, 206–207 genetic control of age-sensitive traits, 200–206 height-life span nexus, 204–206 hormonal exposure/reproductive history correlation, 191–192 human genome correspondence to, 209 incidence and timing of lethal conditions, 198–200 longevity mutations, 194–200 methionine restriction, 204 muscle strength correlation, 189, 190 obesity, 205 P-glycoprotein expression, 191, 201, 202 QTL mapping, 194–195, 201, 203 selection pressures on laboratory stocks, 203–204, 205, 207 UM-HET3 population, 195, 200–201 urinary syndrome in, 192, 193, 199, 200 MRFIT study, 89 Multifactorial variance, 69, 126 Multiple comparison problem, 52–53, 70 Multipoint gene mapping, 121 Multistate demographic models, 75, 80 Multivariate logistic regression analysis, 51 Muscle strength, 189, 190 Muslims, 140 Mutations, 67, 70, 72, 85 autosomal dominant, 140, 141, 314 autosomal recessive, 49, 140, 151 at beta amyloid precursor protein locus, 140 of colon cancer cells, 146–147 of cystic fibrosis gene, 99, 314 dominant gain-of-function, 140 frequency, 139, 239 heterozygous carriers, 151–152 homozygous, 240 linkage disequilibrium and, 123 in mitochondrial DNA, 239 paternal age and, 139 p53, 294 population age of, 238 protein-truncating, 92 rare, nonrecurrent, 238 sampling strategies, 146 single-gene, 140, 182 somatic, 90–91, 142, 146, 232 Myocardial infarction, 260 N National Bioethics Advisory Commission (NBAC), 276, 284, 286, 293, 297, 298, 303, 305 National Breast Cancer Coalition, 320 National Cancer Institute, 148 National Death Index, 13, 236, 251, 252 National Eye Institute Visual Functioning Questionnaire, 168 National Health and Nutrition Examination Survey (NHANES), 10, 27, 89, 168, 257, 271, 277, 289, 332, 344 National Health Insurance exam, 254

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? National Health Survey of Pakistan, 257, 267 National Heart, Lung and Blood Institute, 299, 312 National Institute on Aging, 2, 27, 162 National Institutes of Health, 284, 286, 297, 320 National Long Term Care Survey (NLTCS), 263, 265 National Medical Expenditure Survey, 174 National Research Council, 304, 305, 318 National Survey of Family Growth, 271 Native Americans, 282, 319 Natural selection, 90, 143, 182, 183. See also Selective pressures Nature-nurture debate, 43 Needle biopsy, 173 Nematode worms, 182, 205, 217, 222 Nested case-control studies, 51, 240 Neural network model, 122 Neuroendocrine function, 23 Neuronal cells, 137 Neuroticism, 47 Nicotine, 78n.11 Nigeria, 92, 94 Norepinephrine, 20, 23, 25, 29, 254 Nuclear family studies, 118, 240–241 Nucleic acid probes, 145 Nucleotides, 345 Nun Study, 4–5 O Obesity, 19, 44, 79, 95, 205 Observer rating, 175 Occupational exposures to toxic substances, 15 Odense University Hospital, 59 Office for Protection from Research Risks (OPRR), 284, 286, 297, 304, 310–311 Office of Technology Assessment, 304 Oligogenes, 67, 69, 89, 345 Oligonucleotides, 135, 139, 345 Online Mendelian Inheritance in Man, 113 Onset of disease, age factors in, 48, 76, 94, 140, 141, 143, 234, 238, 263, 314 Opossum longevity, 182 Organ damage aging and, 182 detection of, 170 Organ/organoid cultures, 145 Organic acid metabolism, 151 Orofacial birth defects, 236 Osteoarthritis, 74 Osteoporosis, 70, 74, 94–95, 96–97, 142 Ovarian cancer, 91, 92, 93, 237, 320 P P-glycoprotein, 191, 201 PAH gene, 69n.4 Pakistan, 257, 267 Panic disorder, 86 Parent-offspring pairs, 119, 125, 208 Parent-offspring transmission-based TDT, 125 Parkinson’s disease, 46, 48, 234, 237 Participants, survey/study benefits of, 269, 282, 290 for children, 296–298 communication of research results to, 265, 268–269, 288–290, 297, 313–314, 341 familial coercion, 316 family contact, 296 mentally impaired, 270, 298 obligations to, 269–271 ownership of specimens, 295–296, 313– 315 partnership role, 320–321 psychological risks to, 315–317 recontacting tissue sources, 276–277, 290, 293–294 risk information, 291–292 vulnerable, 296–298 withdrawal from protocol, 295 Paternal age, and mutations in offspring, 139 Paternalism in medicine, 278 Paternity issues, 236, 292 Pathobiology of aging, 15, 146 Pathology samples autopsy, 148–150 clinical, 150–152, 245 colorectal, 146–147 costs related to, 146 cryopreservation, 145, 146 cytological materials, 148 genetic analysis of archived samples, 145–148 organ/organoid cultures from, 145 sample handling, 144–145, 146 surgical, 144–148, 245

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Peak-flow rate (pulmonary), 20, 24 Pedigree data/studies blood pressure heritability, 95 confidentiality issues, 309, 313 defined, 71, 345 and gene mapping, 120–121 of genetic association, 143 limitations of, 112 linkage analysis, 120–121, 140–142, 240– 241 for longevity genes, 140–142 population studies and, 235, 236, 240– 241 Peer review, 279 Penetrance rates, 68, 92, 94 Peptic ulcer, 46 Performance testing, 3, 12–13, 163, 173, 174– 175, 176 Peripheral blood samples, analysis of, 139, 145, 152 Peripheral vascular disease, 21, 50 Personality characteristics and health outcomes, 14 heritability, 48, 86, 117 Phenotypes defined, 66, 345 selective breeding of animal models, 224–225 senescent, 140–142 Phenylalanine hydroxylase, 49 Phenylketonuria, 49, 69n.4, 151 Phyletic descent, 345 Physical functioning allostatic load and, 25 antioxidants and, 24 assessment, 28, 163, 168–169 bioindicators of, 18–19, 21 capacity/performance discrepancies, 174 catecholamine excretion and, 23 cognitive function and, 163 components and integration levels, 165– 166 CRP and, 21 defined, 163 DHEAS and, 23 genetic factors, 48 hierarchical framework, 163–165 homocysteine and, 21 IL-6 and, 21 lung function and, 24 performance testing of, 12–13, 54–55, 163, 174–175 self-reports of, 163, 174 summary biologic risk scores and, 25 Physiological functions. See also Cognitive function aging and, 143–144, 159–176, 182 cellular, 161 challenge and, 260–262 cholesterol and, 22 differential rates of change, 143–144, 161 home monitoring/assessment of, 161 molecular, 160 neuropsychological, 23, 166–167, 173 organ, 161–162 sensory, 167–168, 174 total organism/integrated, 162, 163–169, 173–174 Physiological measures APOE genes, 18 from blood and urine, 19, 28–30 in MacArthur Study, 28–30 Pituitary adenoma, 205 Pleiotropic effects, 97, 200, 205, 331, 345 antagonistic, 97, 340, 342 Point estimates, 77 Poisson regression, 77 Polyenvironmental influences, 115–116 Polygenes, 69, 90, 95, 222 Polygenic variance, 69, 86, 113, 222, 223, 345 Polymerase chain reaction (PCR), 137, 345 inter-simple sequence repeat, 146 quantitative reverse transcription-competitive, 137 tissue analysis, 139 Polymorphisms, 67, 70, 72, 84, 85 APOE, 73, 91, 92–93 BCRA, 84, 92–93 defined, 345 for longevity, 195 microarray analysis of, 139 single-nucleotide, 67, 70, 72, 99, 100, 120, 139, 346 Population admixture, 70, 123–124 aging-rate differences within, 194 allele frequencies, 239 bottlenecks, 123 differences, gene studies of, 84–85, 238 ethnohistorical distance between, 84

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? migrations, 123, 124, 238 origins, 72 size, and mutation frequency, 93 stratification, 120, 124, 126, 239 Population-based research and surveys. See also Cohort studies; Genetic epidemiology; Household surveys; individual studies and surveys administrative data linked to, 3, 13, 236, 251, 252, 256, 258, 271, 330 animal model research compared, 188 association studies, 239–241 attrition rates, 29, 30, 55–56, 59, 242–243, 270 from autopsies, 134, 150 bioindicator liabilities in, 265–269 bioindicator value in, 254–265 biological specimen collection in, 12–13, 16–17, 26–30, 53–60, 161–162, 207, 236, 242–246, 251 of cognitive function, 11, 150, 237 confidentiality, 255, 270–271 contamination effects, 265, 268–269, 341 controls, 239 crosswalks in, 271 design challenges, 229, 236–242, 251 of environmental exposures, 230–231, 235, 237–238 familiality and heritability assessment in, 234–236 founder effects/populations, 85, 90, 93, 123, 141, 239, 342 gene-environment interactions, 230, 241–242, 263 gene expression screening in, 207 gene frequencies and disease occurrence, 92–93, 239–241 gene markers in demographically defined populations, 18, 229, 238–239 genetic bioindicator applications in, 17– 26, 31, 229, 236–242, 263–265 incident vs. prevalent outcomes, 237–238 large-scale, 2, 100–101, 111, 114, 123, 141, 262–263 longitudinal design advantages, 255 methodological issues, 237–238 participation issues, 6, 29, 30, 55–56, 59, 242–243, 251 pathology samples, 134, 150, 151–152 pedigree data from, 235, 236, 240–241 phenotypic outcomes specified in, 231– 234 proxy reports/interviews, 12, 59, 173, 175, 236, 252, 253, 270 public health and clinical applications, 241, 242 representativeness of nonclinical data in, 254–256 respondent burden, 6, 266–267 sample size considerations, 42, 51, 52, 77, 122, 234, 237, 238, 251 self-reports, 12, 16–17, 26, 30, 174, 175–176, 256–259, 262 spurious associations in, 123–124, 237– 238 value of, 30, 141, 235 Positional cloning, 64, 70, 71, 194, 345 Postal surveys, 235 Power simulation results, 126 Premature death, 44 Preparative cell sorting, 139 Presenilin genes, 101, 140, 141 Privacy of genetic information. See also Confidentiality issues Certificate of Confidentiality, 309 on databases, 310–312 discrimination and social stigma considerations, 264–265, 276, 281, 291–292, 297, 307–310 individual, within families, 310–311 informed-consent protections, 280–281, 291, 292–293, 308–309 medical information distinguish from, 306–307 publication of results and, 309–310 sample identification issues, 283–287, 292–294, 297 Probands, 113, 121, 345 Processing speed, 47 Prospective epidemiologic surveys genetic information in, 88–89 sample size considerations, 237 Prostate cancer, 139, 237, 241 Proteins age-dependent changes in, 203 beta amyloid precursor, 140–141, 150 C-reactive, 20, 21, 22, 25, 30 cross-linking, 182, 201 eye lens, 201 gene expression modulators, 146 isoforms, 343

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? oxidation, 189, 203 physiological modulation role, 134, 146 Proteomics, 134, 346 Proxy reports/interviews, 12, 59, 173, 175, 236, 252, 253, 270 PS-1 gene, 74 PS-2 gene, 74 Psychology and health outcomes, 14 twin studies, 48 Pubescence, 134 Pulmonary adenosarcoma, 198 Pure-tone audiometry, 168 Q Qualitative traits case-control studies for, 123 defined, 66 TDTs for, 124 variability, 110 Quality control, 60, 244, 268 Quantitative analysis, of gene expression, 139 Quantitative genetic models animal studies, 113, 226 basis of, 113 compromise approaches, 114, 116 covariation among relatives in, 113, 115 environmental variance components, 115–117, 125, 127 gene mapping in, 113, 119 genetic variance components, 113–115, 127 latent components, 113, 116, 119, 127 major-gene effects, 113 measurable effects, 114–115, 116–117, 127 polyenvironmental influences, 115–116 QTL effects in, 113 sib-pair tests, 125 of variance decomposition, 119 Quantitative reverse transcription-competitive PCR, 137 Quantitative trait loci (QTLs) allele-sharing methods, 121–122 in animal models, 222, 223, 225 for behavior, 86 defined, 69, 346 for latent genetic effect, 114 mapping, 86, 121–122, 125, 194–195, 201, 203, 222, 322 in mouse longevity studies, 194–195, 201, 203 polygenic influences and, 113, 222 Quantitative traits continuously distributed, 124 defined, 66, 346 multifactorial variance, 69, 126 oligogenes for, 67, 69 polygenic influences, 69, 222 variability sources, 110, 112–117 variance component models applied to, 68 Questionnaires, 53–54, 173, 174 R Race/ethnicity, 76 and Alzheimer’s disease, 94, 142–143 and antioxidant levels, 24 APOE gene and, 18, 79, 85, 92–93, 102, 143 and association studies, 70, 123, 142–143 and blood pressure, 256 and cholesterol, 85 and control selection, 51 and cortisol, 22–23 and diabetes, 16, 21, 319 genetic testing issues, 282–283 and glucose metabolism, 16, 21 GNB3 gene and, 79 and health outcomes, 15–16 and homocysteine metabolism, 21 and mutations, 140, 141 and SNS activity, 23 Reading disability, 45, 86–87 Recombinant inbred strains, 223 Recombination, 71, 123, 341, 346 Regression analysis, 51, 88, 122, 124, 188, 191 Reliability of laboratory assays, 26 of self-reports, 16–17, 26, 257 Religious activities, 22 Renal function, 19, 20, 24, 159, 161, 170, 172, 237, 288 Replicability of studies, 218, 219–220 Repository specimens, 60 commercial use of, 295–296, 311–312 cryopreservation of, 145, 146, 245 defined, 283 identification/labeling issues, 283–287, 288, 292–293

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? informed consent for use of, 270, 276– 277, 279–280, 283, 284, 288 from MacArthur Study of Successful Aging, 29–30, 31 ownership issues, 245, 295, 311–315 recontacting tissue sources, 276–277 risks of genetic testing on, 281–283 samples distinguished from, 283 semen and ova, 243, 246 value of, 31, 208 Representativeness of samples, 55, 118, 119, 218, 219–220, 252 in family studies, 118 self-selection and, 271 Reproduction. See also Fertility assortive mating, 95, 117, 118, 340 and biomarkers of aging, 191–192 consanguineous matings, 140 longevity and, 182–183, 191–192, 194 postponement of, 138–139 twin studies, 46–47 Resiliency/susceptibility, biological indicators, 18 Restriction fragment length polymorphisms, 120 Reverse causation, 14 Reverse transcriptase, 135, 137 Rhesus monkeys, 200 Rheumatoid arthritis, 46 Risk factors, for poor health outcomes, 15, 19 Risk-taking behavior, 117 Risks, of genetic testing on tissue samples, 281–283 RNA, defined, 346 Rosetta Inpharmatics, 135 Rosow-Breslau scale, 169 Rotterdam Study, 89 S Samples coded/linked, 284, 285, 287, 292–293, 297 in genetic epidemiology, 42, 51, 52 identified, 285, 297 of repository specimens, 283 representativeness, 55, 118, 119 size considerations, 42, 51, 52, 77, 122, 208, 237, 238 unidentified, 284, 285 unlinked, 284, 286, 293, 294, 309 Sampling strategies bias in, 86, 111, 119, 150, 239, 253 for complex traits, 114 for major-gene effects, 113 mutations in surgical tissues, 146 for sib-pair methods, 122 stratified, 126 surgical pathology tissues, 144–145 Schizophrenia, 44, 45, 48, 86, 234–235 Scholastic achievement in adolescence, 47, 48 Secretary’s Advisory Committee on Genetic Testing, 321 Segregation analysis applications, 68–69 for demogenes, 95, 97, 98 gene-environment interactions and, 69 in gentic epidemiology, 68–69, 77 of lung cancer risk, 73–74 in mouse models of aging, 194–195 polygenes in, 90 of variance in health outcomes, 77 Selective pressures on laboratory animal stocks, 203–204, 205 Selective sampling, 122 Self-efficacy and control, 23 Self-reports, 12, 330 calibration of, 256–259, 262, 332–333 cognitive status and, 258 of disease, 17, 257 of function, 174, 175–176, 258, 332–333 gender differences in, 258 of health behavior, 17 methods, 30 reliability, 16–17, 26, 257 Self-selection, 267, 271 Senescence defined, 346 immune, 206 phenotypes, 140–142 Sensory function, 167–168, 174 Serum glutamic-oxaloacetic transaminase (SGOT), 29 Sex steroids, 207 Sexuality, 68 Shapiro, Harold, 294 Shared effects environmental, 117, 118 genetic, 115, 118 Short tandem repeats (STRs), 120, 346

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Sib-pair allele-sharing methods for QTL mapping, 121–122 association studies, 124–125, 143 biological samples, 208 linkage analysis, 121, 240–241 Sibling studies discordant-sib-pair design, 125 of environmental influences, 126 extension of large-scale surveys, 122 of familiality, 119, 234–235 in gene mapping investigations, 119, 121–122 with middle-age cohorts, 144 TDT, 124–125 usefulness of, 112 Sickle-cell anemia, 65, 84, 160, 281 Single-gene diseases, 121, 141 Single-nucleotide polymorphisms (SNPs), 67, 70, 72, 99, 100, 120, 139, 346 Skin biopsy, 160, 173, 243 Sleep monitoring equipment, 161 Small effect, genes of, 122, 127 Smith, John Maynard, 182 Smith-Lemli-Optiz syndrome (SLOS), 49 Smoking behavior, 116 Snellen Eye Chart, 168 Social integration, 22 Social networks, and health outcomes, 14, 261 Social-psychological characteristics indicators of, 14, 19 inflammation markers and, 22 Social Security Administration, 3, 236, 251, 252 Social status variables, heritability of, 86 Social stigma, 297 Social surveys, 238. See also Population-based research and surveys advantages of, 250–251, 255 biomarker advantages in, 254–265 biomarker liabilities in, 265–266 confirmatory role of, 321 future directions, 271–272 obligations to participants, 269–271 statistical power, 250 Societal functioning, 162–163, 175 Socioeconomic status (SES) bioindicators of health status related to, 21, 22–23, 24, 25 and fertility, 47 genetic influences, 116 and health outcomes, 14, 15, 22, 47, 260 Somatic cells, 346 Somatic mutations, 90–91, 142, 146, 232 Somatic symptoms of illness, 167 Spatial reasoning, 47 Speech function, 166 Spontaneous activity, 189, 201 Spurious correlations/associations, 70, 98, 100, 126, 222 in genetic association studies, 123–124 Stanford University, 135 Statistical analysis development of techniques, 64–65, 114 of microarray results, 135, 137 Statistical power, 51, 52, 144, 219, 250 Stereotypes expectations of aging, 162–163 genetic basis for, 282–283 Stochastic events, 142, 218, 346 Strategene, 136 Strength, 3, 18, 48, 189, 190 Stress, 3, 22, 23, 207, 260–262 Stroke, 16, 21, 24, 163, 166 Study of Health and Living Status of the Elderly in Taiwan. See Taiwan Study Study of Women’s Health Across the Nation (SWAN), 27, 271 Summary biologic risk scores, 25–26 Supplement on Aging, 174 Surgical samples, 144–148 Survival analysis in gene-environment interaction studies, 51 genetic information in, 76, 80–81 heterogeneity in frailty, 76, 80–81 Sweden, 75, 89 Sympathetic nervous system (SNS) activity, 19, 20, 23, 25, 29 Symptoms of disease, 15 Syndrome X, 18, 25 Syntenic linkage, 346 T T-cell CD4M, 187–192, 193, 200–201, 206 CD4P, 191, 201 CD4V, 187 CD8M, 187, 191, 192, 193 cytokine production, 186

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? defined, 347 proliferation, 186 Taiwan National Health Insurance Program, 266 Provincial Institute of Family Planning, 253, 268 Taiwan Study of Health and Living Status of the Elderly, 27 APOE genotyping in, 264 benefit to participants, 269 biological specimen collection, 253–254, 265, 266–268 cross-cultural comparisons, 255–256 environment-health correlations, 261 informed consent for, 270 overview, 251, 253–254 self-reports of disease, 257, 262 Tandem mass spectrometry, 151 Tandem repeats, 346 Task Force on Genetic Testing, 304, 305 Tay-Sachs screening, 319 Telomeres, 203, 232, 347 Test of mean differences, 123 Thyroid function/hormone, 161, 194 Tightly linked markers, genetic association using, 123–124 Tissue atrophy, 142 Tissue differentiation during development, 134 Toxicant metabolism, 241 Toxoplasma gondii infection, 151 Transcription factors, 134, 146 Transgenerational environment, 6 Transmission/disequilibrium tests (TDT), 124–125 Tremin Trust, 271 Tumor suppressor genes, 138–139, 142 Tuskegee syphilis experiments, 278 Twin studies of Alzheimer’s disease, 45 barriers to use of, 65 basis in, 44, 117–118 of behavioral genetics, 45, 48, 68, 86 biases and error sources, 117–118 collection of biological material in, 53–54 concordance rates, 44, 45, 46 controls in, 65, 68 of diseases and disorders, 45, 46, 48, 234 equal environment assumption, 45, 117 of familiality, 117–118 of gene-environment interactions, 44–45 generalizability and representativeness of, 118 in genetic epidemiology, 45, 68 of heritability of traits, 44–48, 68, 95, 235 intraclass correlations, 44, 47 of life-span variation, 46, 142 limitations, 112 with offspring, 119 with parents, 119 of reproduction, 46–47 sample size considerations, 234 variance decomposition models, 117 weaknesses in, 45, 117 Twins reared apart, and heritability, 68, 119 registries, 54 types of, 44 Two-dimensional electrophoresis, 134 U Ultrasound, portable, 162 University of Michigan, 251 University of Southern Denmark, 53 University of Washington, 149 Urinary catecholamine excretion, 23 Urine samples, 19 analytical considerations, 172 collection procedures, 28–30, 254 DNA from, 56 U.S. Department of Defense, 320 U.S. Panel Study on Income Dynamics, 2 V Validation/validity of biomarkers of aging, 185–186 of laboratory assays, 26 of self-reports, 257 Variability, in quantitative traits, 112–117 Variable number of tandem repeats (VNTRs), 120, 347 Variance component models, 68, 117, 121– 122, 125 Variance decomposition models, 114, 117, 119 Verbal reasoning, 47 Virginia Commonwealth University, 310–311 Visual function, 167 Visual spatial function, 166–167

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Cells and Surveys: Should Biological Measures be Included in Social Science Research? Vitamin B12, 21, 30 Vitamin D receptor (VDR) gene, 70, 74, 96 Vitamin supplements, 24 Vocational interests in adolescence, 47, 48 X chromosome, 87, 139 W Waist/hip ratio, 20, 25, 28, 256 Weibull functions, 82n.13 Weight, 15, 19, 205 Welch Allyn Audioscope™, 168 Wellcome Trust, 72 Werner syndrome, 142, 194 Whispered voice test, 168 Whole-genome scan, 70, 72 Willis, Robert, 333–334 Wisconsin Longitudinal Study, 271 Within-population variation, 80–81 Y Yeast, 222 Yi-Li, Chuang, 268 Yu-Hsuan, Lin, 268 Z Zimbabwe, 95n.22 Zygosity misclassification, 118 Zygotes, 347 Zygotic twins, 347