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Pilgrim MJD, Beam CR, Nygaard M, Finkel D. Prospective Effects of Self-Rated Health on Dementia Risk in Two Twin Studies of Aging. Behav Genet 2024; 54:307-320. [PMID: 38822218 PMCID: PMC11196327 DOI: 10.1007/s10519-024-10182-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 04/13/2024] [Indexed: 06/02/2024]
Abstract
Subjective health ratings are associated with dementia risk such that those who rate their health more poorly have increased risk for dementia. The genetic and environmental mechanisms underlying this association are unclear, as prior research cannot rule out whether the association is due to genetic confounds. The current study addresses this gap in two samples of twins, one from Sweden (N = 548) and one from Denmark (N = 4,373). Using genetically-informed, bivariate regression models, we assessed whether additive genetic effects explained the association between subjective health and dementia risk as indexed by a latent variable proxy measure. Age at intake, sex, education, depressive symptomatology, and follow-up time between subjective health and dementia risk assessments were included as covariates. Results indicate that genetic variance and other sources of confounding accounted for the majority of the effect of subjective health ratings on dementia risk. After adjusting for genetic confounding and other covariates, a small correlation was observed between subjective health and latent dementia risk in the Danish sample (rE = - .09, p < .05). The results provide further support for the genetic association between subjective health and dementia risk, and also suggest that subjective ratings of health measures may be useful for predicting dementia risk.
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Affiliation(s)
- Matthew J D Pilgrim
- Department of Psychology, University of Southern California, Los Angeles, USA.
| | - Christopher R Beam
- Department of Psychology, University of Southern California, Los Angeles, USA
- Davis School of Gerontology, Universitty of Southern California, Los Angeles, USA
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Deborah Finkel
- Center for Economic and Social Research, University of Southern California, Los Angeles, USA
- Institute for Gerontology, School of Health and Welfare, Jönköping University, Jönköping, Sweden
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Finkel D, Gatz M, Franz CE, Catts VS, Christensen K, Kremen W, Nygaard M, Plassman BL, Sachdev PS, Whitfield K, Pedersen NL. Age and Sex Differences in the Genetic Architecture of Measures of Subjective Health: Relationships With Physical Health, Depressive Symptoms, and Episodic Memory. J Gerontol B Psychol Sci Soc Sci 2024; 79:gbae062. [PMID: 38632885 PMCID: PMC11127482 DOI: 10.1093/geronb/gbae062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Indexed: 04/19/2024] Open
Abstract
OBJECTIVES Subjective health (SH) is not just an indicator of physical health, but also reflects active cognitive processing of information about one's own health and has been associated with emotional health measures, such as neuroticism and depression. Behavior genetic approaches investigate the genetic architecture of SH, that is, genetic and environmental influences on individual differences in SH and associations with potential components such as physical, cognitive, and emotional health. Previous twin analyses have been limited by sex, sample size, age range, and focus on single covariates. METHODS The current analysis used data from 24,173 adults ranging in age from 40 to 90 years from the international Interplay of Genes and Environment across Multiple Studies consortium to investigate the genetic architecture of 3 measures of SH: self-rated health, health compared to others, and impact of health on activities. Independent pathways model of SH included physical health, depressive symptoms, and episodic memory, with age, sex, and country included as covariates. RESULTS Most or all of the genetic variance for SH measures were shared with physical health, depressive symptoms, and episodic memory. Genetic architecture of SH differed across measures, age groups (40-65, 66-90), and sexes. Age comparisons indicated stronger correlations with all 3 covariates in older adults, often resulting from greater shared genetic variance. DISCUSSION The predictive value of SH has been amply demonstrated. The higher genetic contributions to associations between SH and its components in older adults support the increasing conceptualization with age of SH as an intuitive summation of one's vital reserve.
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Affiliation(s)
- Deborah Finkel
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
- Institute for Gerontology, College of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego, San Diego, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, California, USA
| | - Vibeke S Catts
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
| | - Kaare Christensen
- Danish Aging Research Center, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - William Kremen
- Department of Psychiatry, University of California, San Diego, San Diego, California, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, San Diego, California, USA
| | - Marianne Nygaard
- The Danish Twin Registry, University of Southern Denmark, Odense, Denmark
| | - Brenda L Plassman
- Departments of Psychiatry and Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, School of Clinical Medicine, UNSW, Sydney, Australia
| | - Keith Whitfield
- Department of Psychology and Brain and Health, University of Nevada, Las Vegas, Las Vegas, Nevada, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Jang JY, Beam CR, Karlsson IK, Pedersen NL, Gatz M. Dementia and mortality in older adults: A twin study. Alzheimers Dement 2024; 20:1682-1692. [PMID: 38078564 PMCID: PMC10947969 DOI: 10.1002/alz.13553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/28/2023] [Accepted: 10/22/2023] [Indexed: 12/17/2023]
Abstract
INTRODUCTION Dementia predicts increased mortality. We used case-control and co-twin control models to investigate genetic and shared environmental influences on this association. METHODS Case-control design, including 987 twins with dementia and 2938 age- and sex-matched controls in the Swedish Twin Registry. Co-twin control design, including 90 monozygotic (MZ) and 288 dizygotic (DZ) twin pairs discordant for dementia. To test for genetic and environmental confounding, differences were examined in mortality risk between twins with dementia and their matched or co-twin controls. RESULTS Twins with dementia showed greater mortality risk than age- and sex-matched controls (HR = 2.02 [1.86, 2.18]). Mortality risk is significantly elevated but attenuated substantially in discordant twin pairs, for example, comparing MZ twins with dementia to their co-twin controls (HR = 1.48 [1.08, 2.04]). DISCUSSION Findings suggest that genetic factors partially confound the association between dementia and mortality and provide an alternative hypothesis to increased mortality due to dementia itself. Highlights We studied dementia and mortality in twin pairs discordant for dementia. People without dementia outlived people with dementia. Identical twins with dementia and their co-twin controls had similar survival time. Findings suggest genotype may explain the link between dementia and mortality.
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Affiliation(s)
- Jung Yun Jang
- Institute for Memory Impairments and Neurological DisordersUniversity of California IrvineIrvineCaliforniaUSA
| | - Christopher R. Beam
- Department of PsychologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Davis School of GerontologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Ida K. Karlsson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Nancy L. Pedersen
- Department of PsychologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Margaret Gatz
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Center for Economic and Social ResearchUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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Fellinghauer C, Debelak R, Strobl C. What Affects the Quality of Score Transformations? Potential Issues in True-Score Equating Using the Partial Credit Model. EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT 2023; 83:1249-1290. [PMID: 37970488 PMCID: PMC10638984 DOI: 10.1177/00131644221143051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
This simulation study investigated to what extent departures from construct similarity as well as differences in the difficulty and targeting of scales impact the score transformation when scales are equated by means of concurrent calibration using the partial credit model with a common person design. Practical implications of the simulation results are discussed with a focus on scale equating in health-related research settings. The study simulated data for two scales, varying the number of items and the sample sizes. The factor correlation between scales was used to operationalize construct similarity. Targeting of the scales was operationalized through increasing departure from equal difficulty and by varying the dispersion of the item and person parameters in each scale. The results show that low similarity between scales goes along with lower transformation precision. In cases with equal levels of similarity, precision improves in settings where the range of the item parameters is encompassing the person parameters range. With decreasing similarity, score transformation precision benefits more from good targeting. Difficulty shifts up to two logits somewhat increased the estimation bias but without affecting the transformation precision. The observed robustness against difficulty shifts supports the advantage of applying a true-score equating methods over identity equating, which was used as a naive baseline method for comparison. Finally, larger sample size did not improve the transformation precision in this study, longer scales improved only marginally the quality of the equating. The insights from the simulation study are used in a real-data example.
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Phillips DM, Finkel D, Petkus AJ, Muñoz E, Pahlen S, Johnson W, Reynolds CA, Pedersen N. Longitudinal analyses indicate bidirectional associations between loneliness and health. Aging Ment Health 2023; 27:1217-1225. [PMID: 35699236 PMCID: PMC11039305 DOI: 10.1080/13607863.2022.2087210] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 05/28/2022] [Indexed: 11/01/2022]
Abstract
OBJECTIVES To evaluate temporal dynamics between loneliness and both objective and subjective health (i.e. functional impairment and self-rated health) in mid- to late-adulthood. METHOD We applied bivariate dual-change-score models to longitudinal data from 3 Swedish twin studies (N = 1,939) to explore dynamic associations between loneliness and health across 3 age ranges (50-69, 70-81, and 82+ years) to investigate whether associations between loneliness and health change with age due to increasing incidence of chronic health conditions and bereavement. RESULTS Results showed bidirectional associations between loneliness and both objective and subjective health, with adverse impacts of loneliness observed on subsequent subjective and objective health beginning at age 70. Associations between health and subsequent loneliness were observed after age 82 and varied for subjective and objective health, with subjective health associated with less loneliness and objective health associated with greater loneliness. CONCLUSIONS Our results indicate dynamic associations between loneliness and health with age in mid- to late-adulthood, with earlier impacts of loneliness on health and later impacts of health on loneliness that vary for objective and subjective measures of health. These findings suggest impacts of health on loneliness may arise later in life when worsening health or mobility interfere with social interaction.
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Affiliation(s)
- Dianna M Phillips
- Department of Psychology, University of California, Riverside, CA, USA
| | - Deborah Finkel
- Department of Psychology, Indiana University Southeast, New Albany, IN, USA
- Institute for Gerontology, Jönköping University, Jönköping, Sweden
| | - Andrew J Petkus
- Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Elizabeth Muñoz
- Department of Psychology, University of California, Riverside, CA, USA
- Department of Human Development and Family Sciences, The University of Texas at Austin, Austin, TX, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, CA, USA
| | - Wendy Johnson
- Department of Psychology, University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh
| | | | - Nancy Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Mukherjee S, Choi SE, Lee ML, Scollard P, Trittschuh EH, Mez J, Saykin AJ, Gibbons LE, Sanders RE, Zaman AF, Teylan MA, Kukull WA, Barnes LL, Bennett DA, Lacroix AZ, Larson EB, Cuccaro M, Mercado S, Dumitrescu L, Hohman TJ, Crane PK. Cognitive domain harmonization and cocalibration in studies of older adults. Neuropsychology 2023; 37:409-423. [PMID: 35925737 PMCID: PMC9898463 DOI: 10.1037/neu0000835] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
OBJECTIVE Studies use different instruments to measure cognitirating cognitive tests permit direct comparisons of individuals across studies and pooling data for joint analyses. METHOD We began our legacy item bank with data from the Adult Changes in Thought study (n = 5,546), the Alzheimer's Disease Neuroimaging Initiative (n = 3,016), the Rush Memory and Aging Project (n = 2,163), and the Religious on such as the Mini-Mental State Examination, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, the Wechsler Memory Scale, and the Boston Naming Test. CocalibOrders Study (n = 1,456). Our workflow begins with categorizing items administered in each study as indicators of memory, executive functioning, language, visuospatial functioning, or none of these domains. We use confirmatory factor analysis models with data from the most recent visit on the pooled sample across these four studies for cocalibration and derive item parameters for all items. Using these item parameters, we then estimate factor scores along with corresponding standard errors for each domain for each study. We added additional studies to our pipeline as available and focused on thorough consideration of candidate anchor items with identical content and administration methods across studies. RESULTS Prestatistical harmonization steps such qualitative and quantitative assessment of granular cognitive items and evaluating factor structure are important steps when trying to cocalibrate cognitive scores across studies. We have cocalibrated cognitive data and derived scores for four domains for 76,723 individuals across 10 studies. CONCLUSIONS We have implemented a large-scale effort to harmonize and cocalibrate cognitive domain scores across multiple studies of cognitive aging. Scores on the same metric facilitate meta-analyses of cognitive outcomes across studies or the joint analysis of individual data across studies. Our systematic approach allows for cocalibration of additional studies as they become available and our growing item bank enables robust investigation of cognition in the context of aging and dementia. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
| | - Seo-Eun Choi
- Department of Medicine, The University of Washington
| | | | | | - Emily H. Trittschuh
- Department of Psychiatry and Behavioral Sciences, The University of Washington
- VA Puget Sound Health Care System, Seattle, Washington, United States
| | - Jesse Mez
- Department of Neurology, Boston University School of Medicine
| | - Andrew J. Saykin
- Department of Radiology and Imaging Services, Indiana Alzheimer’s Disease Research Center, Indiana University
| | | | | | - Andrew F. Zaman
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine
| | - Merilee A. Teylan
- National Alzheimer’s Coordinating Center, Department of Epidemiology, University of Washington
| | - Walter A. Kukull
- National Alzheimer’s Coordinating Center, Department of Epidemiology, University of Washington
- Department of Epidemiology, The University of Washington
| | - Lisa L. Barnes
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, United States
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, United States
| | | | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, United States
| | - Michael Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine
| | - Shannon Mercado
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Paul K. Crane
- Department of Medicine, The University of Washington
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Vo TT, Pahlen S, Kremen WS, McGue M, Dahl Aslan A, Nygaard M, Christensen K, Reynolds CA. Does sleep duration moderate genetic and environmental contributions to cognitive performance? Sleep 2022; 45:zsac140. [PMID: 35727734 PMCID: PMC9548666 DOI: 10.1093/sleep/zsac140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/06/2022] [Indexed: 01/27/2023] Open
Abstract
While prior research has demonstrated a relationship between sleep and cognitive performance, how sleep relates to underlying genetic and environmental etiologies contributing to cognitive functioning, regardless of the level of cognitive function, is unclear. The present study assessed whether the importance of genetic and environmental contributions to cognition vary depending on an individual's aging-related sleep characteristics. The large sample consisted of twins from six studies within the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium spanning mid- to late-life (Average age [Mage] = 57.6, range = 27-91 years, N = 7052, Female = 43.70%, 1525 complete monozygotic [MZ] pairs, 2001 complete dizygotic [DZ] pairs). Quantitative genetic twin models considered sleep duration as a primary moderator of genetic and environmental contributions to cognitive performance in four cognitive abilities (Semantic Fluency, Spatial-Visual Reasoning, Processing Speed, and Episodic Memory), while accounting for age moderation. Results suggested genetic and both shared and nonshared environmental contributions for Semantic Fluency and genetic and shared environmental contributions for Episodic Memory vary by sleep duration, while no significant moderation was observed for Spatial-Visual Reasoning or Processing Speed. Results for Semantic Fluency and Episodic Memory illustrated patterns of higher genetic influences on cognitive function at shorter sleep durations (i.e. 4 hours) and higher shared environmental contributions to cognitive function at longer sleep durations (i.e. 10 hours). Overall, these findings may align with associations of upregulation of neuroinflammatory processes and ineffective beta-amyloid clearance in short sleep contexts and common reporting of mental fatigue in long sleep contexts, both associated with poorer cognitive functioning.
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Affiliation(s)
- Tina T Vo
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California, San Diego, San Diego, CA, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Anna Dahl Aslan
- School of Health Sciences, University of Skövde, Skövde, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Marianne Nygaard
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Kaare Christensen
- The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Chandra A Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, USA
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Rico-Uribe LA, Morillo-Cuadrado D, Rodríguez-Laso Á, Vorstenbosch E, Weser AJ, Fincias L, Marcon Y, Rodriguez-Mañas L, Haro JM, Ayuso-Mateos JL. Worldwide mapping of initiatives that integrate population cohorts. Front Public Health 2022; 10:964086. [PMID: 36262229 PMCID: PMC9574101 DOI: 10.3389/fpubh.2022.964086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/14/2022] [Indexed: 11/29/2022] Open
Affiliation(s)
- Laura Alejandra Rico-Uribe
- CIBERSAM (Network-Based Biomedical Research Consortium, Area of Mental Health), Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Madrid, Spain
- School of Health Sciences, Universidad Internacional de La Rioja, Logroño, Spain
| | - Daniel Morillo-Cuadrado
- CIBERSAM (Network-Based Biomedical Research Consortium, Area of Mental Health), Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Madrid, Spain
- Instituto de Investigación Sanitaria La Princesa (IIS-LP), Hospital Universitario de La Princesa, Madrid, Spain
- *Correspondence: Daniel Morillo-Cuadrado
| | - Ángel Rodríguez-Laso
- CIBERFES (Network-Based Biomedical Research Consortium, Area of Frailty and Healthy Ageing), Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Madrid, Spain
| | - Ellen Vorstenbosch
- CIBERSAM (Network-Based Biomedical Research Consortium, Area of Mental Health), Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Madrid, Spain
- Parc Sanitari Sant Joan de Déu, Barcelona, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - Andreas J. Weser
- HUNT (The Trøndelag Health Study) Research Centre, Norwegian University of Science and Technology, Trondheim, Norway
| | | | | | - Leocadio Rodriguez-Mañas
- CIBERFES (Network-Based Biomedical Research Consortium, Area of Frailty and Healthy Ageing), Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Madrid, Spain
| | - Josep María Haro
- Parc Sanitari Sant Joan de Déu, Barcelona, Spain
- Department of Medicine, Universitat de Barcelona, Barcelona, Spain
| | - José Luis Ayuso-Mateos
- CIBERSAM (Network-Based Biomedical Research Consortium, Area of Mental Health), Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, Madrid, Spain
- Instituto de Investigación Sanitaria La Princesa (IIS-LP), Hospital Universitario de La Princesa, Madrid, Spain
- Department of Psychiatry, Universidad Autónoma de Madrid, Madrid, Spain
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O'Connor M, Spry E, Patton G, Moreno-Betancur M, Arnup S, Downes M, Goldfeld S, Burgner D, Olsson CA. Better together: Advancing life course research through multi-cohort analytic approaches. ADVANCES IN LIFE COURSE RESEARCH 2022; 53:100499. [PMID: 36652217 DOI: 10.1016/j.alcr.2022.100499] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Revised: 06/22/2022] [Accepted: 07/15/2022] [Indexed: 06/17/2023]
Abstract
Longitudinal cohorts can provide timely and cost-efficient evidence about the best points of health service and preventive interventions over the life course. Working systematically across cohorts has the potential to further exploit these valuable data assets, such as by improving the precision of estimates, enhancing (or appropriately reducing) confidence in the replicability of findings, and investigating interrelated questions within a broader theoretical model. In this conceptual review, we explore the opportunities and challenges presented by multi-cohort approaches in life course research. Specifically, we: 1) describe key motivations for multi-cohort work and the analytic approaches that are commonly used in each case; 2) flag some of the scientific and pragmatic challenges that arise when adopting these approaches; and 3) outline emerging directions for multi-cohort work in life course research. Harnessing their potential while thoughtfully considering limitations of multi-cohort approaches can contribute to the robust and granular evidence base needed to promote health and wellbeing over the life span.
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Affiliation(s)
- Meredith O'Connor
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia.
| | - Elizabeth Spry
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia; Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Australia
| | - George Patton
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia
| | - Margarita Moreno-Betancur
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia
| | - Sarah Arnup
- Murdoch Children's Research Institute, Parkville, Australia
| | - Marnie Downes
- Murdoch Children's Research Institute, Parkville, Australia
| | - Sharon Goldfeld
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia; Royal Children's Hospital, Centre for Community Child Health, Parkville, Australia
| | - David Burgner
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia; Royal Children's Hospital, Department of General Medicine, Parkville, Australia; Monash University, Department of Pediatrics, Clayton, Australia
| | - Craig A Olsson
- Murdoch Children's Research Institute, Parkville, Australia; University of Melbourne, Department of Paediatrics, Parkville, Australia; Deakin University, Centre for Social and Early Emotional Development, School of Psychology, Faculty of Health, Geelong, Australia
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Finkel D, Zavala C, Franz CE, Pahlen S, Gatz M, Pedersen NL, Finch BK, Dahl Aslan A, Catts VS, Ericsson M, Krueger RF, Martin NG, Mohan A, Mosing MA, Prescott CA, Whitfield KE. Financial strain moderates genetic influences on self-rated health: support for diathesis-stress model of gene-environment interplay. BIODEMOGRAPHY AND SOCIAL BIOLOGY 2022; 67:58-70. [PMID: 35156881 PMCID: PMC9038652 DOI: 10.1080/19485565.2022.2037069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Data from the Interplay of Genes and Environment across Multiple Studies (IGEMS) consortium were used to examine predictions of different models of gene-by-environment interaction to understand how genetic variance in self-rated health (SRH) varies at different levels of financial strain. A total of 11,359 individuals from 10 twin studies in Australia, Sweden, and the United States contributed relevant data, including 2,074 monozygotic and 2,623 dizygotic twin pairs. Age ranged from 22 to 98 years, with a mean age of 61.05 (SD = 13.24). A factor model was used to create a harmonized measure of financial strain across studies and items. Twin analyses of genetic and environmental variance for SRH incorporating age, age2, sex, and financial strain moderators indicated significant financial strain moderation of genetic influences on self-rated health. Moderation results did not differ across sex or country. Genetic variance for SRH increased as financial strain increased, matching the predictions of the diathesis-stress and social comparison models for components of variance. Under these models, environmental improvements would be expected to reduce genetically based health disparities.
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Affiliation(s)
- Deborah Finkel
- Department of Psychology, Indiana University Southeast, New Albany, Indiana
- Institute of Gerontology and Aging Research Network-Jönköping (ARN-J), Jönköping University, Jönköping, Sweden
| | - Catalina Zavala
- Department of Psychology, University of Southern California, Los Angeles, California
| | - Carol E Franz
- Department of Psychology, University of California, San Diego, California
| | - Shandell Pahlen
- Department of Psychology, University of California, Riverside, California
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, California
| | - Nancy L Pedersen
- Department of Psychology, University of Southern California, Los Angeles, California
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Brian K Finch
- Department of Sociology and Spatial Sciences, University of Southern California, Los Angeles, California
| | - Anna Dahl Aslan
- Institute of Gerontology and Aging Research Network-Jönköping (ARN-J), Jönköping University, Jönköping, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Vibeke S Catts
- Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, UNSW Sydney, Kensington, Australia
| | - Malin Ericsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
| | - Robert F Krueger
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota
| | - Nicholas G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Adith Mohan
- Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, UNSW Sydney, Kensington, Australia
| | - Miriam A Mosing
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia
| | - Carol A Prescott
- Department of Psychology, University of Southern California, Los Angeles, California
| | - Keith E Whitfield
- Department of Psychology, University of Nevada Las Vegas, Las Vegas, Nevada
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11
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Röhr S, Pabst A, Riedel-Heller SG, Jessen F, Turana Y, Handajani YS, Brayne C, Matthews FE, Stephan BCM, Lipton RB, Katz MJ, Wang C, Guerchet M, Preux PM, Mbelesso P, Ritchie K, Ancelin ML, Carrière I, Guaita A, Davin A, Vaccaro R, Kim KW, Han JW, Suh SW, Shahar S, Din NC, Vanoh D, van Boxtel M, Köhler S, Ganguli M, Jacobsen EP, Snitz BE, Anstey KJ, Cherbuin N, Kumagai S, Chen S, Narazaki K, Ng TP, Gao Q, Gwee X, Brodaty H, Kochan NA, Trollor J, Lobo A, López-Antón R, Santabárbara J, Crawford JD, Lipnicki DM, Sachdev PS. Estimating prevalence of subjective cognitive decline in and across international cohort studies of aging: a COSMIC study. ALZHEIMERS RESEARCH & THERAPY 2020; 12:167. [PMID: 33339532 PMCID: PMC7749505 DOI: 10.1186/s13195-020-00734-y] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 11/26/2020] [Indexed: 12/20/2022]
Abstract
Background Subjective cognitive decline (SCD) is recognized as a risk stage for Alzheimer’s disease (AD) and other dementias, but its prevalence is not well known. We aimed to use uniform criteria to better estimate SCD prevalence across international cohorts. Methods We combined individual participant data for 16 cohorts from 15 countries (members of the COSMIC consortium) and used qualitative and quantitative (Item Response Theory/IRT) harmonization techniques to estimate SCD prevalence. Results The sample comprised 39,387 cognitively unimpaired individuals above age 60. The prevalence of SCD across studies was around one quarter with both qualitative harmonization/QH (23.8%, 95%CI = 23.3–24.4%) and IRT (25.6%, 95%CI = 25.1–26.1%); however, prevalence estimates varied largely between studies (QH 6.1%, 95%CI = 5.1–7.0%, to 52.7%, 95%CI = 47.4–58.0%; IRT: 7.8%, 95%CI = 6.8–8.9%, to 52.7%, 95%CI = 47.4–58.0%). Across studies, SCD prevalence was higher in men than women, in lower levels of education, in Asian and Black African people compared to White people, in lower- and middle-income countries compared to high-income countries, and in studies conducted in later decades. Conclusions SCD is frequent in old age. Having a quarter of older individuals with SCD warrants further investigation of its significance, as a risk stage for AD and other dementias, and of ways to help individuals with SCD who seek medical advice. Moreover, a standardized instrument to measure SCD is needed to overcome the measurement variability currently dominant in the field.
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Affiliation(s)
- Susanne Röhr
- Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Philipp-Rosenthal-Straße 55, 04103, Leipzig, Germany. .,Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland.
| | - Alexander Pabst
- Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Philipp-Rosenthal-Straße 55, 04103, Leipzig, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health (ISAP), Medical Faculty, University of Leipzig, Philipp-Rosenthal-Straße 55, 04103, Leipzig, Germany
| | - Frank Jessen
- Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, Germany.,German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Yuda Turana
- Department of Neurology, School of Medicine, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Yvonne S Handajani
- Center for Health Research, School of Medicine, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Carol Brayne
- Cambridge Public Health, Cambridge University, Cambridge, UK
| | - Fiona E Matthews
- MRC Biostatistics Unit, Institute of Public Health, Cambridge University, Cambridge, UK.,Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Blossom C M Stephan
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Richard B Lipton
- Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Yeshiva University, New York, NY, USA.,Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Yeshiva University, New York, NY, USA.,Department of Psychiatry and Behavioral Medicine, Albert Einstein College of Medicine, Yeshiva University, New York, NY, USA
| | - Mindy J Katz
- Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, Yeshiva University, New York, NY, USA
| | - Cuiling Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Yeshiva University, New York, NY, USA
| | - Maëlenn Guerchet
- INSERM, U1094, Tropical Neuroepidemiology, Limoges, France.,Univ. Limoges, U1094, Tropical Neuroepidemiology, Institute of Epidemiology and Tropical Neurology, GEIST, Limoges, France.,IRD, Associated Unit, Tropical Neuroepidemiology, Limoges, France
| | - Pierre-Marie Preux
- INSERM, U1094, Tropical Neuroepidemiology, Limoges, France.,Univ. Limoges, U1094, Tropical Neuroepidemiology, Institute of Epidemiology and Tropical Neurology, GEIST, Limoges, France.,CHU, Department of Medical Information & Evaluation, Clinical Research and Biostatistic Unit, Limoges, France
| | - Pascal Mbelesso
- INSERM, U1094, Tropical Neuroepidemiology, Limoges, France.,Univ. Limoges, U1094, Tropical Neuroepidemiology, Institute of Epidemiology and Tropical Neurology, GEIST, Limoges, France.,Department of Neurology, Amitié Hospital, Bangui, Central African Republic
| | - Karen Ritchie
- INSERM U1061 Neuropsychiatry: Epidemiological and Clinical Research, La Colombière Hospital, Montpellier Cedex 5, Université de Montpellier, Montpellier, France.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Marie-Laure Ancelin
- INSERM U1061 Neuropsychiatry: Epidemiological and Clinical Research, La Colombière Hospital, Montpellier Cedex 5, Université de Montpellier, Montpellier, France
| | - Isabelle Carrière
- INSERM U1061 Neuropsychiatry: Epidemiological and Clinical Research, La Colombière Hospital, Montpellier Cedex 5, Université de Montpellier, Montpellier, France
| | - Antonio Guaita
- Golgi Cenci Foundation, Corso San Martino 10, 20081, Abbiategrasso, Italy
| | - Annalisa Davin
- Golgi Cenci Foundation, Corso San Martino 10, 20081, Abbiategrasso, Italy
| | - Roberta Vaccaro
- Golgi Cenci Foundation, Corso San Martino 10, 20081, Abbiategrasso, Italy
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Seung Wan Suh
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Suzana Shahar
- Centre of Healthy Aging and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Normah C Din
- Centre for Rehabilitation Science and Special Needs, Faculty of Health Science, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Divya Vanoh
- School of Health Science, Universiti Sains Malaysia, Kota Bharu, Kelantan, Malaysia
| | - Martin van Boxtel
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University Medical Center (MUMC), Maastricht, The Netherlands
| | - Sebastian Köhler
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University Medical Center (MUMC), Maastricht, The Netherlands
| | - Mary Ganguli
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.,Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA
| | - Erin P Jacobsen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kaarin J Anstey
- Ageing Futures Institute, University of New South Wales, Sydney, NSW, Australia.,Neuroscience Research Australia, Sydney, NSW, Australia.,Centre for Research on Ageing, Health and Wellbeing, College of Health and Medicine, Australian National University, Canberra, ACT, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, College of Health and Medicine, Australian National University, Canberra, ACT, Australia
| | - Shuzo Kumagai
- Center for Health Science and Counseling, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka, 819-0395, Japan
| | - Sanmei Chen
- Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan
| | - Kenji Narazaki
- Faculty of Socio-Environmental Studies, Department of Socio-Environmental Studies, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka, 811-0295, Japan
| | - Tze Pin Ng
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qi Gao
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Xinyi Gwee
- Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia.,Dementia Collaborative Research Centre, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia
| | - Nicole A Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia
| | - Julian Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia.,Department of Developmental Disability Neuropsychiatry, University of New South Wales Sydney, Sydney, Australia
| | - Antonio Lobo
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid, Spain.,Department of Medicine and Psychiatry, Universidad de Zaragoza and Instituto de Investigación Sanitaria Aragón, Zaragoza, Spain
| | - Raúl López-Antón
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid, Spain.,Department of Psychology and Sociology, Universidad de Zaragoza, Zaragoza, Spain
| | - Javier Santabárbara
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Ministry of Science and Innovation, Madrid, Spain.,Department of Microbiology, Preventive Medicine and Public Health, University of Zaragoza, Zaragoza, Spain
| | - John D Crawford
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia
| | - Darren M Lipnicki
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia.,Dementia Collaborative Research Centre, School of Psychiatry, University of New South Wales Sydney, Sydney, Australia
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12
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Luningham JM, Hendriks AM, Krapohl E, Ip HF, van Beijsterveldt CE, Lundström S, Vuoksimaa E, Korhonen T, Lichtenstein P, Plomin R, Pulkkinen L, Rose RJ, Kaprio J, Bartels M, Boomsma DI, Lubke GH. Harmonizing behavioral outcomes across studies, raters, and countries: application to the genetic analysis of aggression in the ACTION Consortium. J Child Psychol Psychiatry 2020; 61:807-817. [PMID: 31950512 PMCID: PMC7363537 DOI: 10.1111/jcpp.13188] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/25/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Aggression in children has genetic and environmental causes. Studies of aggression can pool existing datasets to include more complex models of social effects. Such analyses require large datasets with harmonized outcome measures. Here, we made use of a reference panel for phenotype data to harmonize multiple aggression measures in school-aged children to jointly analyze data from five large twin cohorts. METHODS Individual level aggression data on 86,559 children (42,468 twin pairs) were available in five European twin cohorts measured by different instruments. A phenotypic reference panel was collected which enabled a model-based phenotype harmonization approach. A bi-factor integration model in the integrative data analysis framework was developed to model aggression across studies while adjusting for rater, age, and sex. Finally, harmonized aggression scores were analyzed to estimate contributions of genes, environment, and social interaction to aggression. The large sample size allowed adequate power to test for sibling interaction effects, with unique dynamics permitted for opposite-sex twins. RESULTS The best-fitting model found a high level of overall heritability of aggression (~60%). Different heritability rates of aggression across sex were marginally significant, with heritability estimates in boys of ~64% and ~58% in girls. Sibling interaction effects were only significant in the opposite-sex twin pairs: the interaction effect of males on their female co-twin differed from the effect of females on their male co-twin. An aggressive female had a positive effect on male co-twin aggression, whereas more aggression in males had a negative influence on a female co-twin. CONCLUSIONS Opposite-sex twins displayed unique social dynamics of aggressive behaviors in a joint analysis of a large, multinational dataset. The integrative data analysis framework, applied in combination with a reference panel, has the potential to elucidate broad, generalizable results in the investigation of common psychological traits in children.
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Affiliation(s)
- Justin M. Luningham
- Department of Psychology, University of Notre Dame, Notre
Dame, IN;,Department of Population Health Sciences, School of Public
Health, Georgia State University, Atlanta, GA, USA
| | - Anne M. Hendriks
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Eva Krapohl
- Medical Research Council Social, Genetic, and Developmental
Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, UK
| | - Hill Fung Ip
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Catharina E.M. van Beijsterveldt
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, University of Gothenburg,
Gothenburg;,Centre for Ethics, Law and Mental Health (CELAM),
University of Gothenburg, Gothenburg, Sweden
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics,
Karolinska Institutet, Stockholm, Sweden
| | - Robert Plomin
- Medical Research Council Social, Genetic, and Developmental
Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, UK
| | - Lea Pulkkinen
- Department of Psychology, University of Jyvaskyla,
Jyvaskyla, Finland
| | - Richard J. Rose
- Department of Psychological and Brain Sciences, Indiana
University, Bloomington, IN, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of
Helsinki, Helsinki, Finland;,Department of Public Health, University of Helsinki,
Helsinki, Finland
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands;,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological
Psychology, Vrije Universiteit Amsterdam, Amsterdam;,Amsterdam Public Health research institute, Faculty of
Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The
Netherlands;,Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Gitta H. Lubke
- Department of Psychology, University of Notre Dame, Notre
Dame, IN
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13
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Luningham JM, McArtor DB, Hendriks AM, van Beijsterveldt CEM, Lichtenstein P, Lundström S, Larsson H, Bartels M, Boomsma DI, Lubke GH. Data Integration Methods for Phenotype Harmonization in Multi-Cohort Genome-Wide Association Studies With Behavioral Outcomes. Front Genet 2020; 10:1227. [PMID: 31921287 PMCID: PMC6914843 DOI: 10.3389/fgene.2019.01227] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 11/05/2019] [Indexed: 01/03/2023] Open
Abstract
Parallel meta-analysis is a popular approach for increasing the power to detect genetic effects in genome-wide association studies across multiple cohorts. Consortia studying the genetics of behavioral phenotypes are oftentimes faced with systematic differences in phenotype measurement across cohorts, introducing heterogeneity into the meta-analysis and reducing statistical power. This study investigated integrative data analysis (IDA) as an approach for jointly modeling the phenotype across multiple datasets. We put forth a bi-factor integration model (BFIM) that provides a single common phenotype score and accounts for sources of study-specific variability in the phenotype. In order to capitalize on this modeling strategy, a phenotype reference panel was utilized as a supplemental sample with complete data on all behavioral measures. A simulation study showed that a mega-analysis of genetic variant effects in a BFIM were more powerful than meta-analysis of genetic effects on a cohort-specific sum score of items. Saving the factor scores from the BFIM and using those as the outcome in meta-analysis was also more powerful than the sum score in most simulation conditions, but a small degree of bias was introduced by this approach. The reference panel was necessary to realize these power gains. An empirical demonstration used the BFIM to harmonize aggression scores in 9-year old children across the Netherlands Twin Register and the Child and Adolescent Twin Study in Sweden, providing a template for application of the BFIM to a range of different phenotypes. A supplemental data collection in the Netherlands Twin Register served as a reference panel for phenotype modeling across both cohorts. Our results indicate that model-based harmonization for the study of complex traits is a useful step within genetic consortia.
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Affiliation(s)
- Justin M Luningham
- Department of Psychology, University of Notre Dame, Notre Dame, IN, United States
| | - Daniel B McArtor
- Department of Psychology, University of Notre Dame, Notre Dame, IN, United States
| | - Anne M Hendriks
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Catharina E M van Beijsterveldt
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Paul Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sebastian Lundström
- Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Larsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Meike Bartels
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Dorret I Boomsma
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Faculty of Behavioural and Movement Sciences, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.,Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Gitta H Lubke
- Department of Psychology, University of Notre Dame, Notre Dame, IN, United States
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14
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Finkel D, Franz CE, Christensen K, Reynolds CA, Pedersen NL. Longitudinal Twin Study of Subjective Health: Differences in Genetic and Environmental Components of Variance Across Age and Sex. J Gerontol B Psychol Sci Soc Sci 2020; 75:1-10. [PMID: 29590493 PMCID: PMC6909438 DOI: 10.1093/geronb/gby030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2017] [Accepted: 03/22/2018] [Indexed: 01/30/2023] Open
Abstract
OBJECTIVE The current analysis examines sex differences in longitudinal changes in genetic and environmental influences on three measures of subjective health (SH). METHOD Sample includes 7,372 twins (mean intake age = 73.22) with up to 8 waves of measurement (mean = 3.1). Three SH items were included: general self-rated health (SRH), health compared to age peers (COMP), and impact of health on activities (ACT) which previous research shows capture different frames of reference. RESULTS Latent growth curve modeling indicated significant differences across gender and frame of reference in trajectories of change with age and in genetic and environmental contributions to change. Men have higher mean scores on all three SH measures, indicating better SH, but there were no sex differences in pattern of change with age. Accelerating declines with age were found for SRH and ACT, whereas COMP improved with age. Results indicated more genetic variance for women than men, but declining genetic variance for both after age 70. Increasing shared environmental variance with increasing age was also found for both sexes. DISCUSSION As aging triggers a re-evaluation of the meaning of "good health," physical aspects of health may become less important and shared cultural conceptions of health may become more relevant. This change in conceptions of good health may reflect both aging and the change in composition of the elderly population as a result of selective survival.
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Affiliation(s)
- Deborah Finkel
- Department of Psychology, Indiana University Southeast, New Albany
- Institute for Gerontology, Jönköping University, Sweden
- Address correspondence to: Deborah Finkel, PhD, Department of Psychology, Indiana University Southeast, New Albany, Crestview Hall 019, 4201 Grant Line Road, New Albany, IN 47150. E-mail:
| | - Carol E Franz
- Department of Psychiatry, University of California, San Diego
| | | | | | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychology, University of Southern California, Los Angeles
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15
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Pedersen NL, Gatz M, Finch BK, Finkel D, Butler DA, Dahl Aslan A, Franz CE, Kaprio J, Lapham S, McGue M, Mosing MA, Neiderhiser J, Nygaard M, Panizzon M, Prescott CA, Reynolds CA, Sachdev P, Whitfield KE. IGEMS: The Consortium on Interplay of Genes and Environment Across Multiple Studies - An Update. Twin Res Hum Genet 2019; 22:809-816. [PMID: 31544729 PMCID: PMC7056501 DOI: 10.1017/thg.2019.76] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
The Interplay of Genes and Environment across Multiple Studies (IGEMS) is a consortium of 18 twin studies from 5 different countries (Sweden, Denmark, Finland, United States, and Australia) established to explore the nature of gene-environment (GE) interplay in functioning across the adult lifespan. Fifteen of the studies are longitudinal, with follow-up as long as 59 years after baseline. The combined data from over 76,000 participants aged 14-103 at intake (including over 10,000 monozygotic and over 17,000 dizygotic twin pairs) support two primary research emphases: (1) investigation of models of GE interplay of early life adversity, and social factors at micro and macro environmental levels and with diverse outcomes, including mortality, physical functioning and psychological functioning; and (2) improved understanding of risk and protective factors for dementia by incorporating unmeasured and measured genetic factors with a wide range of exposures measured in young adulthood, midlife and later life.
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Affiliation(s)
- Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Margaret Gatz
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Brian K Finch
- Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Deborah Finkel
- Department of Psychology, Indiana University Southeast, New Albany, IN, USA
| | - David A Butler
- Office of Military and Veterans Health, Health and Medicine Division, The National Academies of Sciences, Engineering, and Medicine, Washington, DC, USA
| | - Anna Dahl Aslan
- Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jaakko Kaprio
- Department of Public Health, Faculty of Medicine & Institute for Molecular Medicine FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Susan Lapham
- Research and Evaluation, American Institutes for Research, Washington, DC, USA
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
- Department of Epidemiology, Biostatistics and Biodemography, University of Southern Denmark, Odense, Denmark
| | - Miriam A Mosing
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Jenae Neiderhiser
- Department of Psychology, Penn State University, University Park, PA, USA
| | - Marianne Nygaard
- The Danish Twin Registry, University of Southern Denmark, Odense C, Denmark
| | - Matthew Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Carol A Prescott
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California - Riverside, Riverside, CA, USA
| | - Perminder Sachdev
- Centre for Healthy Brain Ageing (CHeBA), University of New South Wales, Sydney, New South Wales, Australia
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16
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Hussong AM, Gottfredson NC, Bauer DJ, Curran PJ, Haroon M, Chandler R, Kahana SY, Delaney JAC, Altice FL, Beckwith CG, Feaster DJ, Flynn PM, Gordon MS, Knight K, Kuo I, Ouellet LJ, Quan VM, Seal DW, Springer SA. Approaches for creating comparable measures of alcohol use symptoms: Harmonization with eight studies of criminal justice populations. Drug Alcohol Depend 2019; 194:59-68. [PMID: 30412898 PMCID: PMC6312501 DOI: 10.1016/j.drugalcdep.2018.10.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 10/16/2018] [Accepted: 10/17/2018] [Indexed: 11/28/2022]
Abstract
BACKGROUND With increasing data archives comprised of studies with similar measurement, optimal methods for data harmonization and measurement scoring are a pressing need. We compare three methods for harmonizing and scoring the AUDIT as administered with minimal variation across 11 samples from eight study sites within the STTR (Seek-Test-Treat-Retain) Research Harmonization Initiative. Descriptive statistics and predictive validity results for cut-scores, sum scores, and Moderated Nonlinear Factor Analysis scores (MNLFA; a psychometric harmonization method) are presented. METHODS Across the eight study sites, sample sizes ranged from 50 to 2405 and target populations varied based on sampling frame, location, and inclusion/exclusion criteria. The pooled sample included 4667 participants (82% male, 52% Black, 24% White, 13% Hispanic, and 8% Asian/ Pacific Islander; mean age of 38.9 years). Participants completed the AUDIT at baseline in all studies. RESULTS After logical harmonization of items, we scored the AUDIT using three methods: published cut-scores, sum scores, and MNLFA. We found greater variation, fewer floor effects, and the ability to directly address missing data in MNLFA scores as compared to cut-scores and sum scores. MNLFA scores showed stronger associations with binge drinking and clearer study differences than did other scores. CONCLUSIONS MNLFA scores are a promising tool for data harmonization and scoring in pooled data analysis. Model complexity with large multi-study applications, however, may require new statistical advances to fully realize the benefits of this approach.
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Affiliation(s)
| | | | - Dan J Bauer
- University of North Carolina at Chapel Hill, United States.
| | | | - Maleeha Haroon
- University of North Carolina at Chapel Hill, United States.
| | - Redonna Chandler
- National Institute on Drug Abuse/National Institutes of Health, United States
| | - Shoshana Y Kahana
- National Institute on Drug Abuse/National Institutes of Health, United States.
| | | | | | | | | | | | | | | | - Irene Kuo
- The George Washington University, United States.
| | | | - Vu M Quan
- Johns Hopkins University, United States.
| | - David W Seal
- Tulane University School of Public Health and Tropical Medicine, United States.
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17
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Gross AL, Tommet D, D’Aquila M, Schmitt E, Marcantonio ER, Helfand B, Inouye SK, Jones RN. Harmonization of delirium severity instruments: a comparison of the DRS-R-98, MDAS, and CAM-S using item response theory. BMC Med Res Methodol 2018; 18:92. [PMID: 30200896 PMCID: PMC6131747 DOI: 10.1186/s12874-018-0552-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Accepted: 08/30/2018] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND This study aimed to describe the level of agreement of three commonly used delirium instruments: the Delirium Rating Scale-Revised-98 (DRS-R-98), Memorial Delirium Assessment Scale (MDAS), and Confusion Assessment Method-Severity (CAM-S). METHODS We used data from a prospective clinical research study, in which a team of trained lay interviewers administered each instrument along with supporting interview and cognitive assessments in the same group of patients daily while in the hospital (N = 352). We used item response theory methods to co-calibrate the instruments. RESULTS The latent traits underlying the three measures, capturing the severity of a delirium assessment, had a high degree of correlation (r's > .82). Unidimensional factor models fit well, facilitating co-calibration of the instruments. Across instruments, the less intense symptoms were generally items reflecting cognitive impairment. Although the intensity of delirium severity for most in the sample was relatively low, many of the item thresholds for the delirium severity scales are high (i.e., in the more severe range of the latent ability distribution). This indicates that even people with severe delirium may have a low probability of endorsing the highest severity categories for many items. Co-calibration enabled us to derive crosswalks to map delirium severity scores among the delirium instruments. CONCLUSION These delirium instruments measure the same underlying construct of delirium severity. Relative locations of items may inform design of refined measurement instruments. Mapping of overall delirium severity scores across the delirium severity instruments enabled us to derive crosswalks, which allow scores to be translated across instruments, facilitating comparison and combination of delirium studies for integrative analysis.
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Affiliation(s)
- Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 2024 E. Monument Street, Baltimore, MD 21205 USA
- Johns Hopkins University Center on Aging and Health, Baltimore, MD USA
| | - Doug Tommet
- Departments of Psychiatry and Human Behavior and Neurology, Warren Alpert Medical School, Brown University, Providence, RI USA
| | - Madeline D’Aquila
- Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, Boston, MA USA
| | - Eva Schmitt
- Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, Boston, MA USA
| | - Edward R. Marcantonio
- Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, Boston, MA USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
| | - Benjamin Helfand
- Departments of Psychiatry and Human Behavior and Neurology, Warren Alpert Medical School, Brown University, Providence, RI USA
- Department of Emergency Medicine, University of Massachusetts Medical School, Worcester, MA USA
| | - Sharon K. Inouye
- Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, Boston, MA USA
- Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
| | - Richard N. Jones
- Departments of Psychiatry and Human Behavior and Neurology, Warren Alpert Medical School, Brown University, Providence, RI USA
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18
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Petkus AJ, Beam CR, Johnson W, Kaprio J, Korhonen T, McGue M, Neiderhiser JM, Pedersen NL, Reynolds CA, Gatz M. Gene-environment interplay in depressive symptoms: moderation by age, sex, and physical illness. Psychol Med 2017; 47:1836-1847. [PMID: 28202098 PMCID: PMC5706656 DOI: 10.1017/s0033291717000290] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Numerous factors influence late-life depressive symptoms in adults, many not thoroughly characterized. We addressed whether genetic and environmental influences on depressive symptoms differed by age, sex, and physical illness. METHOD The analysis sample included 24 436 twins aged 40-90 years drawn from the Interplay of Genes and Environment across Multiple Studies (IGEMS) Consortium. Biometric analyses tested age, sex, and physical illness moderation of genetic and environmental variance in depressive symptoms. RESULTS Women reported greater depressive symptoms than men. After age 60, there was an accelerating increase in depressive symptom scores with age, but this did not appreciably affect genetic and environmental variances. Overlap in genetic influences between physical illness and depressive symptoms was greater in men than in women. Additionally, in men extent of overlap was greater with worse physical illness (the genetic correlation ranged from near 0.00 for the least physical illness to nearly 0.60 with physical illness 2 s.d. above the mean). For men and women, the same environmental factors that influenced depressive symptoms also influenced physical illness. CONCLUSIONS Findings suggested that genetic factors play a larger part in the association between depressive symptoms and physical illness for men than for women. For both sexes, across all ages, physical illness may similarly trigger social and health limitations that contribute to depressive symptoms.
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Affiliation(s)
- A J Petkus
- Department of Neurology,University of Southern California,Los Angeles, CA,USA
| | - C R Beam
- Department of Psychology & Davis School of Gerontology,University of Southern California,Los Angeles, CAUSA
| | - W Johnson
- Department of Psychology,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh,Edinburgh,UK
| | - J Kaprio
- Department of Public Health,University of Helsinki,Helsinki,Finland
| | - T Korhonen
- Department of Public Health,University of Helsinki,Helsinki,Finland
| | - M McGue
- Department of Psychology,University of Minnesota,Minneapolis, MN,USA
| | - J M Neiderhiser
- Department of Psychology,Penn State University,University Park,PA,USA
| | - N L Pedersen
- Department of Medical Epidemiology and Biostatistics,Karolinska Institutet,Stockholm,Sweden
| | - C A Reynolds
- Department of Psychology,University of California Riverside,Riverside, CA,USA
| | - M Gatz
- Department of Medical Epidemiology and Biostatistics,Karolinska Institutet,Stockholm,Sweden
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19
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Franz CE, Finkel D, Panizzon MS, Spoon K, Christensen K, Gatz M, Kremen WS, Krueger R, Neiderhiser J, Reynolds C, Pedersen NL. Facets of Subjective Health From Early Adulthood to Old Age. J Aging Health 2016; 29:149-171. [PMID: 26832851 DOI: 10.1177/0898264315625488] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
OBJECTIVE Subjective health is a complex indicator predicting longevity independent of objective health. Few studies examine genetic and environmental mechanisms underlying different facets of subjective health across the life course. METHOD Three subjective health measures were examined in 12,900 twins ( Mage = 63.38, range = 25-102) from nine studies in the Interplay of Genes and Environment across Multiple Studies Consortium: self-rated health (SRH), health compared with others (COMP), and health interfering with activities (ACT). RESULTS Analyses indicated age and sex differences in mean scores depending on the measure. SRH and ACT showed significant linear and non-linear moderation by age for individual differences in both genetic and environmental variance. Significant sex differences in components of variance were found for SRH and ACT, but not COMP. DISCUSSION Subjective health appears to be dependent on frame of reference and reflect different aspects of health. Results suggest different genetic and environmental mechanisms underlie each facet.
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Affiliation(s)
- Carol E Franz
- 1 University of California, San Diego, La Jolla, USA
| | | | | | - Kelly Spoon
- 1 University of California, San Diego, La Jolla, USA
| | | | - Margaret Gatz
- 4 University of Southern California, Los Angeles, USA
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20
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Finkel D, Franz CE, Horwitz B, Christensen K, Gatz M, Johnson W, Kaprio J, Korhonen T, Niederheiser J, Petersen I, Rose RJ, Silventoinen K. Gender Differences in Marital Status Moderation of Genetic and Environmental Influences on Subjective Health. Behav Genet 2016; 46:114-123. [PMID: 26468112 PMCID: PMC4833715 DOI: 10.1007/s10519-015-9758-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2015] [Accepted: 10/07/2015] [Indexed: 10/22/2022]
Abstract
From the IGEMS Consortium, data were available from 26,579 individuals aged 23 to 102 years on 3 subjective health items: self-rated health (SRH), health compared to others (COMP), and impact of health on activities (ACT). Marital status was a marker of environmental resources that may moderate genetic and environmental influences on subjective health. Results differed for the 3 subjective health items, indicating that they do not tap the same construct. Although there was little impact of marital status on variance components for women, marital status was a significant modifier of variance in all 3 subjective health measures for men. For both SRH and ACT, single men demonstrated greater shared and nonshared environmental variance than married men. For the COMP variable, genetic variance was greater for single men vs. married men. Results suggest gender differences in the role of marriage as a source of resources that are associated with subjective health.
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Affiliation(s)
| | - Carol E Franz
- University of California, San Diego, San Diego, CA, USA
| | - Briana Horwitz
- California State University, Fullerton, Fullerton, CA, USA
| | | | - Margaret Gatz
- University of Southern California, Los Angeles, CA, USA
| | | | - Jaako Kaprio
- University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Tellervo Korhonen
- University of Helsinki, Helsinki, Finland
- National Institute for Health and Welfare, Helsinki, Finland
- University of Eastern Finland, Kuopio, Finland
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21
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Reynolds CA, Gatz M, Christensen K, Christiansen L, Dahl Aslan AK, Kaprio J, Korhonen T, Kremen WS, Krueger R, McGue M, Neiderhiser JM, Pedersen NL. Gene-Environment Interplay in Physical, Psychological, and Cognitive Domains in Mid to Late Adulthood: Is APOE a Variability Gene? Behav Genet 2016; 46:4-19. [PMID: 26538244 PMCID: PMC4858319 DOI: 10.1007/s10519-015-9761-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 10/14/2015] [Indexed: 10/22/2022]
Abstract
Despite emerging interest in gene-environment interaction (GxE) effects, there is a dearth of studies evaluating its potential relevance apart from specific hypothesized environments and biometrical variance trends. Using a monozygotic within-pair approach, we evaluated evidence of G×E for body mass index (BMI), depressive symptoms, and cognition (verbal, spatial, attention, working memory, perceptual speed) in twin studies from four countries. We also evaluated whether APOE is a 'variability gene' across these measures and whether it partly represents the 'G' in G×E effects. In all three domains, G×E effects were pervasive across country and gender, with small-to-moderate effects. Age-cohort trends were generally stable for BMI and depressive symptoms; however, they were variable-with both increasing and decreasing age-cohort trends-for different cognitive measures. Results also suggested that APOE may represent a 'variability gene' for depressive symptoms and spatial reasoning, but not for BMI or other cognitive measures. Hence, additional genes are salient beyond APOE.
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Affiliation(s)
- Chandra A Reynolds
- Department of Psychology, University of California Riverside, 900 University Ave., Riverside, CA, 92521, USA.
| | - Margaret Gatz
- Department of Psychology, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177, Stockholm, Sweden
| | - Kaare Christensen
- Epidemiology, Biostatistics and Bio-demography, Institute of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
- Department of Clinical Genetics and Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark
| | - Lene Christiansen
- Epidemiology, Biostatistics and Bio-demography, Institute of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
| | - Anna K Dahl Aslan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177, Stockholm, Sweden
- Institute of Gerontology, School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Jaakko Kaprio
- Department of Public Health & Institute for Molecular Medicine FIMM, University of Helsinki, 00014, Helsinki, Finland
| | - Tellervo Korhonen
- Department of Public Health, University of Helsinki, 00014, Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211, Kuopio, Finland
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Robert Krueger
- Department of Psychology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Matt McGue
- Epidemiology, Biostatistics and Bio-demography, Institute of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
- Department of Psychology, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Jenae M Neiderhiser
- Department of Psychology, The Pennsylvania State University, University Park, PA, USA
| | - Nancy L Pedersen
- Department of Psychology, University of Southern California, Los Angeles, CA, 90089, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177, Stockholm, Sweden
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