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Vuoksimaa E, Saari TT, Aaltonen A, Aaltonen S, Herukka SK, Iso-Markku P, Kokkola T, Kyttälä A, Kärkkäinen S, Liedes H, Ollikainen M, Palviainen T, Ruotsalainen I, Toivola A, Urjansson M, Vasankari T, Vähä-Ypyä H, Forsberg MM, Hiltunen M, Jalanko A, Kälviäinen R, Kuopio T, Lähteenmäki J, Nyberg P, Männikkö M, Serpi R, Siltanen S, Palotie A, Kaprio J, Runz H, Julkunen V. TWINGEN: protocol for an observational clinical biobank recall and biomarker cohort study to identify Finnish individuals with high risk of Alzheimer's disease. BMJ Open 2024; 14:e081947. [PMID: 38866570 PMCID: PMC11177688 DOI: 10.1136/bmjopen-2023-081947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 05/09/2024] [Indexed: 06/14/2024] Open
Abstract
INTRODUCTION A better understanding of the earliest stages of Alzheimer's disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among THL Biobank donors according to TWINGEN study criteria. METHODS AND ANALYSIS A multi-centre study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behaviour and sleep. A subcohort is being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. The data collected in TWINGEN will be returned to THL Biobank from where it can later be requested for other biobank studies such as FinnGen that supported TWINGEN. ETHICS AND DISSEMINATION This recall study consists of FTC/THL Biobank/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.
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Affiliation(s)
- Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Toni T Saari
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Aino Aaltonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Sari Aaltonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Sanna-Kaisa Herukka
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - Paula Iso-Markku
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Tarja Kokkola
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Aija Kyttälä
- THL Biobank, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Sari Kärkkäinen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Hilkka Liedes
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- VTT Technical Research Centre of Finland Ltd, Oulu, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ilona Ruotsalainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- VTT Technical Research Centre of Finland Ltd, Espoo, Finland
| | - Auli Toivola
- THL Biobank, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Mia Urjansson
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Tommi Vasankari
- UKK Institute for Health Promotion Research, Tampere, Pirkanmaa, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Henri Vähä-Ypyä
- UKK Institute for Health Promotion Research, Tampere, Pirkanmaa, Finland
| | - Markus M Forsberg
- School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- VTT Technical Research Centre of Finland Ltd, Kuopio, Finland
| | - Mikko Hiltunen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Anu Jalanko
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Reetta Kälviäinen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, NeuroCenter, Kuopio University Hospital, Kuopio, Finland
| | - Teijo Kuopio
- Central Finland Biobank, Wellbeing Services County of Central Finland and University of Jyväskylä, Jyväskylä, Finland
| | | | - Pia Nyberg
- Biobank Borealis of Northern Finland, Oulu University Hospital, Wellbeing Services County of North Ostrobothnia, Oulu, Finland
- Translational Medicine Research Unit, University of Oulu, Oulu, Finland
| | - Minna Männikkö
- Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Raisa Serpi
- Biobank Borealis of Northern Finland, Oulu University Hospital, Wellbeing Services County of North Ostrobothnia, Oulu, Finland
| | - Sanna Siltanen
- Finnish Clinical Biobank Tampere, Tampere University Hospital, Wellbeing Services County of Pirkanmaa, Tampere, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Heiko Runz
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Translational Sciences, Biogen Inc, Cambridge, Massachusetts, USA
| | - Valtteri Julkunen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, NeuroCenter, Kuopio University Hospital, Kuopio, Finland
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Föhr T, Hendrix A, Kankaanpää A, Laakkonen EK, Kujala U, Pietiläinen KH, Lehtimäki T, Kähönen M, Raitakari O, Wang X, Kaprio J, Ollikainen M, Sillanpää E. Metabolic syndrome and epigenetic aging: a twin study. Int J Obes (Lond) 2024; 48:778-787. [PMID: 38273034 PMCID: PMC11129944 DOI: 10.1038/s41366-024-01466-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 12/13/2023] [Accepted: 01/10/2024] [Indexed: 01/27/2024]
Abstract
BACKGROUND Metabolic syndrome (MetS) is associated with premature aging, but whether this association is driven by genetic or lifestyle factors remains unclear. METHODS Two independent discovery cohorts, consisting of twins and unrelated individuals, were examined (N = 268, aged 23-69 years). The findings were replicated in two cohorts from the same base population. One consisted of unrelated individuals (N = 1 564), and the other of twins (N = 293). Participants' epigenetic age, estimated using blood DNA methylation data, was determined using the epigenetic clocks GrimAge and DunedinPACE. The individual-level linear regression models for investigating the associations of MetS and its components with epigenetic aging were followed by within-twin-pair analyses using fixed-effects regression models to account for genetic factors. RESULTS In individual-level analyses, GrimAge age acceleration was higher among participants with MetS (N = 56) compared to participants without MetS (N = 212) (mean 2.078 [95% CI = 0.996,3.160] years vs. -0.549 [-1.053,-0.045] years, between-group p = 3.5E-5). Likewise, the DunedinPACE estimate was higher among the participants with MetS compared to the participants without MetS (1.032 [1.002,1.063] years/calendar year vs. 0.911 [0.896,0.927] years/calendar year, p = 4.8E-11). An adverse profile in terms of specific MetS components was associated with accelerated aging. However, adjustments for lifestyle attenuated these associations; nevertheless, for DunedinPACE, they remained statistically significant. The within-twin-pair analyses suggested that genetics explains these associations fully for GrimAge and partly for DunedinPACE. The replication analyses provided additional evidence that the association between MetS components and accelerated aging is independent of the lifestyle factors considered in this study, however, suggesting that genetics is a significant confounder in this association. CONCLUSIONS The results of this study suggests that MetS is associated with accelerated epigenetic aging, independent of physical activity, smoking or alcohol consumption, and that the association may be explained by genetics.
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Affiliation(s)
- Tiina Föhr
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland.
| | - Arne Hendrix
- Physical Activity, Sport & Health Research Group, Department of Movement Sciences, KU Leuven - University of Leuven, Leuven, Belgium
| | - Anna Kankaanpää
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
| | - Eija K Laakkonen
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
| | - Urho Kujala
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Healthy Weight Hub, Endocrinology, Abdominal Center, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Xiaoling Wang
- Georgia Prevention Institute (GPI), Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Elina Sillanpää
- Faculty of Sport and Health Sciences, Gerontology Research Center, University of Jyväskylä, Jyväskylä, Finland
- The Wellbeing Services County of Central Finland, Jyväskylä, Finland
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Drouard G, Mykkänen J, Heiskanen J, Pohjonen J, Ruohonen S, Pahkala K, Lehtimäki T, Wang X, Ollikainen M, Ripatti S, Pirinen M, Raitakari O, Kaprio J. Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data. BMC Med Inform Decis Mak 2024; 24:116. [PMID: 38698395 PMCID: PMC11064347 DOI: 10.1186/s12911-024-02521-3] [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: 11/04/2022] [Accepted: 04/29/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios. METHODS We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning. RESULTS Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively. CONCLUSIONS By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Juha Mykkänen
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Jarkko Heiskanen
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Joona Pohjonen
- Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland
| | - Saku Ruohonen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Katja Pahkala
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Paavo Nurmi Centre & Unit for Health and Physical Activity, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Xiaoling Wang
- Georgia Prevention Institute, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
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Berntzen BJ, Tolvanen A, Kujala UM, Silventoinen K, Vuoksimaa E, Kaprio J, Aaltonen S. Longitudinal leisure-time physical activity profiles throughout adulthood and related characteristics: a 36-year follow-up study of the older Finnish Twin Cohort. Int J Behav Nutr Phys Act 2024; 21:47. [PMID: 38671483 PMCID: PMC11046842 DOI: 10.1186/s12966-024-01600-y] [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: 12/11/2023] [Accepted: 04/19/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Personalized interventions aiming to increase physical activity in individuals are effective. However, from a public health perspective, it would be important to stimulate physical activity in larger groups of people who share the vulnerability to be physically inactive throughout adulthood. To find these high-risk groups, we identified 36-year leisure-time physical activity profiles from young adulthood to late midlife in females and males. Moreover, we uncovered which anthropometric-, demographic-, lifestyle-, and health-related characteristics were associated with these physical activity profiles. METHODS We included 2,778 females and 1,938 males from the population-based older Finnish Twin Cohort Study, who responded to health and behavior surveys at the mean ages of 24, 30, 40 and 60. Latent profile analysis was used to identify longitudinal leisure-time physical activity profiles. RESULTS We found five longitudinal leisure-time physical activity profiles for both females and males. Females' profiles were: 1) Low increasing moderate (29%), 2) Moderate stable (23%), 3) Very low increasing low (20%), 4) Low stable (20%) and 5) High increasing high (9%). Males' profiles were: 1) Low increasing moderate (29%), 2) Low stable very low (26%), 3) Moderate decreasing low (21%), 4) High fluctuating high (17%) and 5) Very low stable (8%). In both females and males, lower leisure-time physical activity profiles were associated with lower education, higher body mass index, smoking, poorer perceived health, higher sedentary time, high blood pressure, and a higher risk for type 2 diabetes. Furthermore, lower leisure-time physical activity was linked to a higher risk of depression in females. CONCLUSIONS We found several longitudinal leisure-time physical activity profiles with unique changes in both sexes. Fewer profiles in females than in males remained or became low physically active during the 36-year follow-up. We observed that lower education, higher body mass index, and more smoking already in young adulthood were associated with low leisure-time physical activity profiles. However, the fact that several longitudinal profiles demonstrated a change in their physical activity behavior over time implies the potential for public health interventions to improve leisure-time physical activity levels.
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Affiliation(s)
- Bram J Berntzen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, P.O. Box 20, FI-00014, Helsinki, Finland
| | - Asko Tolvanen
- Methodology Centre for Human Sciences, University of Jyväskylä, P.O. Box 35, FI-40014, Jyväskylä, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35, FI-40014, Jyväskylä, Finland
| | - Karri Silventoinen
- Helsinki Institute for Demography and Population Health, University of Helsinki, P.O. Box 42, FI-00014, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, P.O. Box 20, FI-00014, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, P.O. Box 20, FI-00014, Helsinki, Finland
| | - Sari Aaltonen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, P.O. Box 20, FI-00014, Helsinki, Finland.
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Romero Villela PN, Evans LM, Palviainen T, Border R, Kaprio J, Palmer RHC, Keller MC, Ehringer MA. Loci on chromosome 20 interact with rs16969968 to influence cigarettes per day in European ancestry individuals. Drug Alcohol Depend 2024; 257:111126. [PMID: 38387257 PMCID: PMC11062023 DOI: 10.1016/j.drugalcdep.2024.111126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/12/2024] [Accepted: 02/07/2024] [Indexed: 02/24/2024]
Abstract
BACKGROUND The understanding of the molecular genetic contributions to smoking is largely limited to the additive effects of individual single nucleotide polymorphisms (SNPs), but the underlying genetic risk is likely to also include dominance, epistatic, and gene-environment interactions. METHODS To begin to address this complexity, we attempted to identify genetic interactions between rs16969968, the most replicated SNP associated with smoking quantity, and all SNPs and genes across the genome. RESULTS Using the UK Biobank European subsample, we found one SNP, rs1892967, and two genes, PCNA and TMEM230, that showed a significant genome-wide interaction with rs16969968 for log10 CPD and raw CPD, respectively, in a sample of 116 442 individuals who self-reported currently or previously smoking. We extended these analyses to individuals of South Asian descent and meta-analyzed the combined sample of 117 212 individuals of European and South Asian ancestry. We replicated the gene findings in a meta-analysis of five Finnish samples (N=40 140): FinHealth, FINRISK, Finnish Twin Cohort, GeneRISK, and Health-2000-2011. CONCLUSIONS To our knowledge, this represents the first reliable epistatic association between single nucleotide polymorphisms for smoking behaviors and provides a novel direction for possible future functional studies related to this interaction. Furthermore, this work demonstrates the feasibility of these analyses by pooling multiple datasets across various ancestries, which may be applied to other top SNPs for smoking and/or other phenotypes.
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Affiliation(s)
- Pamela N Romero Villela
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Department of Psychology and Neuroscience, University of Colorado, Boulder, USA
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, USA
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, USA
| | - Richard Border
- Departments of Neurology and Computer Science, University of California, Los Angeles, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, USA
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, Atlanta, GA, USA
| | - Matthew C Keller
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Department of Psychology and Neuroscience, University of Colorado, Boulder, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado, Boulder, USA; Departments of Neurology and Computer Science, University of California, Los Angeles, USA; Department of Integrative Physiology, University of Colorado, Boulder, USA.
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Kananen F, Kaprio J, Immonen I. Age-related macular degeneration discordance in monozygotic twin pairs. Acta Ophthalmol 2024. [PMID: 38528623 DOI: 10.1111/aos.16671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 02/16/2024] [Accepted: 03/12/2024] [Indexed: 03/27/2024]
Abstract
PURPOSE To examine age-related macular degeneration (AMD) and retinal pigment epithelium (RPE)-Bruch's membrane (BrM) complex volume associations in monozygotic twin pairs. METHODS In this study, 106 elderly twins (53 twin pairs) from the Finnish Twin Cohort study were recruited. Each participant underwent dilated 35-degree digital colour fundus photography (CFP), and spectral domain optical coherence tomography (OCT) and replied to a structured study questionnaire. The CFPs were graded according to the Age-Related Eye Disease Study (AREDS) classification. The OCT images were segmented and volumetric data of the RPE-BrM complex volume was calculated with the Orion™ software. The worse eye according to AREDS classification was used for the analysis. RESULTS Twenty-nine (55%) of the twin pairs were discordant with regard to AREDS classification. Fourteen (26%) pairs were discordant with one twin participant having AMD (AREDS 2-4) and the other being unaffected (AREDS 1). Four (8%) pairs had one twin participant with intermediate or late AMD (AREDS 3-4) versus the other being unaffected (AREDS 1). The within-pair polychoric correlation for AREDS was 0.605 (95% confidence interval 0.418-0.792). In multivariate analysis intermediate and late AMD as well as age associated with RPE-BrM complex volume. RPE-BrM complex volume showed a within twin pair correlation, r = 0.430 (95% confidence interval 0.172-0.688, p < 0.01). CONCLUSION A substantial proportion of monozygotic twin pairs are discordant with regard to age-related macular degeneration phenotype. RPE-BrM complex volume associated with age and intermediate and late AMD.
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Affiliation(s)
- Fabian Kananen
- Department of Ophthalmology, Örebro University Hospital, Örebro, Sweden
- Department of Ophthalmology, Helsinki University Hospital, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Ilkka Immonen
- Department of Ophthalmology, Helsinki University Hospital, Helsinki, Finland
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7
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Ollila HM, Sinnott-Armstrong N, Kantojärvi K, Broberg M, Palviainen T, Jones S, Ripatti V, Pandit A, Rong R, Kristiansson K, Sandman N, Valli K, Hublin C, Ripatti S, Widen E, Kaprio J, Saxena R, Paunio T. Nightmares share genetic risk factors with sleep and psychiatric traits. Transl Psychiatry 2024; 14:123. [PMID: 38413574 PMCID: PMC10899618 DOI: 10.1038/s41398-023-02637-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 08/08/2023] [Accepted: 10/23/2023] [Indexed: 02/29/2024] Open
Abstract
Nightmares are vivid, extended, and emotionally negative or negative dreams that awaken the dreamer. While sporadic nightmares and bad dreams are common and generally harmless, frequent nightmares often reflect underlying pathologies of emotional regulation. Indeed, insomnia, depression, anxiety, or alcohol use have been associated with nightmares in epidemiological and clinical studies. However, the connection between nightmares and their comorbidities are poorly understood. Our goal was to examine the genetic risk factors for nightmares and estimate correlation or causality between nightmares and comorbidities. We performed a genome-wide association study (GWAS) in 45,255 individuals using a questionnaire-based assessment on the frequency of nightmares during the past month and genome-wide genotyping data. While the GWAS did not reveal individual risk variants, heritability was estimated at 5%. In addition, the genetic correlation analysis showed a robust correlation (rg > 0.4) of nightmares with anxiety (rg = 0.671, p = 7.507e-06), depressive (rg = 0.562, p = 1.282e-07) and posttraumatic stress disorders (rg = 0.4083, p = 0.0152), and personality trait neuroticism (rg = 0.667, p = 4.516e-07). Furthermore, Mendelian randomization suggested causality from insomnia to nightmares (beta = 0.027, p = 0.0002). Our findings suggest that nightmares share genetic background with psychiatric traits and that insomnia may increase an individual's liability to experience frequent nightmares. Given the significant correlations with psychiatric and psychological traits, it is essential to grow awareness of how nightmares affect health and disease and systematically collect information about nightmares, especially from clinical samples and larger cohorts.
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Affiliation(s)
- Hanna M Ollila
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Katri Kantojärvi
- Population Health, Finnish Institute for Health and Welfare, Helsinki, Finland
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Martin Broberg
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Samuel Jones
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Vili Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Anita Pandit
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Robin Rong
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Kati Kristiansson
- Population Health, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Nils Sandman
- Department of Psychology and Speech-Language Pathology, and Turku Brain and Mind Center, University of Turku, Turku, Finland
| | - Katja Valli
- Department of Psychology and Speech-Language Pathology, and Turku Brain and Mind Center, University of Turku, Turku, Finland
- Department of Cognitive Neuroscience and Philosophy, University of Skövde, Skövde, Sweden
| | | | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Tiina Paunio
- Population Health, Finnish Institute for Health and Welfare, Helsinki, Finland.
- Department of Psychiatry and SleepWell Research Program, Faculty of Medicine, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland.
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8
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Kar A, Alvarez M, Garske KM, Huang H, Lee SHT, Deal M, Das SS, Koka A, Jamal Z, Mohlke KL, Laakso M, Heinonen S, Pietiläinen KH, Pajukanta P. Age-dependent genes in adipose stem and precursor cells affect regulation of fat cell differentiation and link aging to obesity via cellular and genetic interactions. Genome Med 2024; 16:19. [PMID: 38297378 PMCID: PMC10829214 DOI: 10.1186/s13073-024-01291-x] [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: 09/11/2023] [Accepted: 01/19/2024] [Indexed: 02/02/2024] Open
Abstract
BACKGROUND Age and obesity are dominant risk factors for several common cardiometabolic disorders, and both are known to impair adipose tissue function. However, the underlying cellular and genetic factors linking aging and obesity on adipose tissue function have remained elusive. Adipose stem and precursor cells (ASPCs) are an understudied, yet crucial adipose cell type due to their deterministic adipocyte differentiation potential, which impacts the capacity to store fat in a metabolically healthy manner. METHODS We integrated subcutaneous adipose tissue (SAT) bulk (n=435) and large single-nucleus RNA sequencing (n=105) data with the UK Biobank (UKB) (n=391,701) data to study age-obesity interactions originating from ASPCs by performing cell-type decomposition, differential expression testing, cell-cell communication analyses, and construction of polygenic risk scores for body mass index (BMI). RESULTS We found that the SAT ASPC proportions significantly decrease with age in an obesity-dependent way consistently in two independent cohorts, both showing that the age dependency of ASPC proportions is abolished by obesity. We further identified 76 genes (72 SAT ASPC marker genes and 4 transcription factors regulating ASPC marker genes) that are differentially expressed by age in SAT and functionally enriched for developmental processes and adipocyte differentiation (i.e., adipogenesis). The 76 age-perturbed ASPC genes include multiple negative regulators of adipogenesis, such as RORA, SMAD3, TWIST2, and ZNF521, form tight clusters of longitudinally co-expressed genes during human adipogenesis, and show age-based differences in cellular interactions between ASPCs and adipose cell types. Finally, our genetic data demonstrate that cis-regional variants of these genes interact with age as predictors of BMI in an obesity-dependent way in the large UKB, while no such gene-age interaction on BMI is observed with non-age-dependent ASPC marker genes, thus independently confirming our cellular ASPC results at the biobank level. CONCLUSIONS Overall, we discover that obesity prematurely induces a decrease in ASPC proportions and identify 76 developmentally important ASPC genes that implicate altered negative regulation of fat cell differentiation as a mechanism for aging and directly link aging to obesity via significant cellular and genetic interactions.
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Affiliation(s)
- Asha Kar
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Kristina M Garske
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Huiling Huang
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA
| | - Seung Hyuk T Lee
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Milena Deal
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Sankha Subhra Das
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Amogha Koka
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Zoeb Jamal
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Sini Heinonen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- HealthyWeightHub, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles (UCLA), Gonda Center, Room 6357B, 695 Charles E. Young Drive South, Los Angeles, CA, 90095-7088, USA.
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, USA.
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, USA.
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9
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Mbarek H, Gordon SD, Duffy DL, Hubers N, Mortlock S, Beck JJ, Hottenga JJ, Pool R, Dolan CV, Actkins KV, Gerring ZF, Van Dongen J, Ehli EA, Iacono WG, Mcgue M, Chasman DI, Gallagher CS, Schilit SLP, Morton CC, Paré G, Willemsen G, Whiteman DC, Olsen CM, Derom C, Vlietinck R, Gudbjartsson D, Cannon-Albright L, Krapohl E, Plomin R, Magnusson PKE, Pedersen NL, Hysi P, Mangino M, Spector TD, Palviainen T, Milaneschi Y, Penninnx BW, Campos AI, Ong KK, Perry JRB, Lambalk CB, Kaprio J, Ólafsson Í, Duroure K, Revenu C, Rentería ME, Yengo L, Davis L, Derks EM, Medland SE, Stefansson H, Stefansson K, Del Bene F, Reversade B, Montgomery GW, Boomsma DI, Martin NG. Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity. Hum Reprod 2024; 39:240-257. [PMID: 38052102 PMCID: PMC10767824 DOI: 10.1093/humrep/dead247] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 09/14/2023] [Indexed: 12/07/2023] Open
Abstract
STUDY QUESTION Which genetic factors regulate female propensity for giving birth to spontaneous dizygotic (DZ) twins? SUMMARY ANSWER We identified four new loci, GNRH1, FSHR, ZFPM1, and IPO8, in addition to previously identified loci, FSHB and SMAD3. WHAT IS KNOWN ALREADY The propensity to give birth to DZ twins runs in families. Earlier, we reported that FSHB and SMAD3 as associated with DZ twinning and female fertility measures. STUDY DESIGN, SIZE, DURATION We conducted a genome-wide association meta-analysis (GWAMA) of mothers of spontaneous dizygotic (DZ) twins (8265 cases, 264 567 controls) and of independent DZ twin offspring (26 252 cases, 417 433 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS Over 700 000 mothers of DZ twins, twin individuals and singletons from large cohorts in Australia/New Zealand, Europe, and the USA were carefully screened to exclude twins born after use of ARTs. Genetic association analyses by cohort were followed by meta-analysis, phenome wide association studies (PheWAS), in silico and in vivo annotations, and Zebrafish functional validation. MAIN RESULTS AND THE ROLE OF CHANCE This study enlarges the sample size considerably from previous efforts, finding four genome-wide significant loci, including two novel signals and a further two novel genes that are implicated by gene level enrichment analyses. The novel loci, GNRH1 and FSHR, have well-established roles in female reproduction whereas ZFPM1 and IPO8 have not previously been implicated in female fertility. We found significant genetic correlations with multiple aspects of female reproduction and body size as well as evidence for significant selection against DZ twinning during human evolution. The 26 top single nucleotide polymorphisms (SNPs) from our GWAMA in European-origin participants weakly predicted the crude twinning rates in 47 non-European populations (r = 0.23 between risk score and population prevalence, s.e. 0.11, 1-tail P = 0.058) indicating that genome-wide association studies (GWAS) are needed in African and Asian populations to explore the causes of their respectively high and low DZ twinning rates. In vivo functional tests in zebrafish for IPO8 validated its essential role in female, but not male, fertility. In most regions, risk SNPs linked to known expression quantitative trait loci (eQTLs). Top SNPs were associated with in vivo reproductive hormone levels with the top pathways including hormone ligand binding receptors and the ovulation cycle. LARGE SCALE DATA The full DZT GWAS summary statistics will made available after publication through the GWAS catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION Our study only included European ancestry cohorts. Inclusion of data from Africa (with the highest twining rate) and Asia (with the lowest rate) would illuminate further the biology of twinning and female fertility. WIDER IMPLICATIONS OF THE FINDINGS About one in 40 babies born in the world is a twin and there is much speculation on why twinning runs in families. We hope our results will inform investigations of ovarian response in new and existing ARTs and the causes of female infertility. STUDY FUNDING/COMPETING INTEREST(S) Support for the Netherlands Twin Register came from the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organization for Health Research and Development (ZonMW) grants, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, 911-09-032, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI.NL, 184.021.007), Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB, European Research Council (ERC-230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1) and the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health and Grand Opportunity grants 1RC2 MH089951. The QIMR Berghofer Medical Research Institute (QIMR) study was supported by grants from the National Health and Medical Research Council (NHMRC) of Australia (241944, 339462, 389927, 389875, 389891, 389892, 389938, 443036, 442915, 442981, 496610, 496739, 552485, 552498, 1050208, 1075175). L.Y. is funded by Australian Research Council (Grant number DE200100425). The Minnesota Center for Twin and Family Research (MCTFR) was supported in part by USPHS Grants from the National Institute on Alcohol Abuse and Alcoholism (AA09367 and AA11886) and the National Institute on Drug Abuse (DA05147, DA13240, and DA024417). The Women's Genome Health Study (WGHS) was funded by the National Heart, Lung, and Blood Institute (HL043851 and HL080467) and the National Cancer Institute (CA047988 and UM1CA182913), with support for genotyping provided by Amgen. Data collection in the Finnish Twin Registry has been supported by the Wellcome Trust Sanger Institute, the Broad Institute, ENGAGE-European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, AA-09203, AA15416, and K02AA018755) and the Academy of Finland (grants 100499, 205585, 118555, 141054, 264146, 308248, 312073 and 336823 to J. Kaprio). TwinsUK is funded by the Wellcome Trust, Medical Research Council, Versus Arthritis, European Union Horizon 2020, Chronic Disease Research Foundation (CDRF), Zoe Ltd and the National Institute for Health Research (NIHR) Clinical Research Network (CRN) and Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust in partnership with King's College London. For NESDA, funding was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10000-1002), the Center for Medical Systems Biology (CSMB, NVVO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University's Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, ROI D0042157-01A, MH081802, Grand Opportunity grants 1 RC2 Ml-1089951 and IRC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. Work in the Del Bene lab was supported by the Programme Investissements d'Avenir IHU FOReSIGHT (ANR-18-IAHU-01). C.R. was supported by an EU Horizon 2020 Marie Skłodowska-Curie Action fellowship (H2020-MSCA-IF-2014 #661527). H.S. and K.S. are employees of deCODE Genetics/Amgen. The other authors declare no competing financial interests. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Hamdi Mbarek
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Qatar Genome Program, Qatar Foundation, Doha, Qatar
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Scott D Gordon
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - David L Duffy
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nikki Hubers
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Sally Mortlock
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Jeffrey J Beck
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD, USA
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - René Pool
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - Conor V Dolan
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | - Ky’Era V Actkins
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | | | - Jenny Van Dongen
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Erik A Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital and University Health Center, Sioux Falls, SD, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Matt Mcgue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Daniel I Chasman
- Harvard Medical School, Harvard University, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | | | - Samantha L P Schilit
- Harvard Medical School, Harvard University, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Cynthia C Morton
- Harvard Medical School, Harvard University, Boston, MA, USA
- Brigham and Women’s Hospital, Boston, MA, USA
| | - Guillaume Paré
- Population Health Research Institute, McMaster University, Hamilton, ON, Canada
| | - Gonneke Willemsen
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
| | | | | | | | | | | | | | - Eva Krapohl
- Medical Research Council Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Statistical Sciences & Innovation, UCB Biosciences GmbH, Monheim, Germany
| | - Robert Plomin
- Medical Research Council Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Pirro Hysi
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
| | - Massimo Mangino
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London, UK
| | - Timothy D Spector
- Department of Twin Research & Genetic Epidemiology, King’s College London, London, UK
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Yuri Milaneschi
- Department of Psychiatry, EMGO Institute for Health and Care Research, Vrije Universiteit, Amsterdam, The Netherlands
| | - Brenda W Penninnx
- Department of Psychiatry, EMGO Institute for Health and Care Research, Vrije Universiteit, Amsterdam, The Netherlands
| | - Adrian I Campos
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
| | - Cornelis B Lambalk
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
- Amsterdam University Medical Centers Location VU Medical Center, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Ísleifur Ólafsson
- Department of Clinical Biochemistry, National University Hospital of Iceland, Reykjavik, Iceland
| | - Karine Duroure
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Céline Revenu
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | | | - Loic Yengo
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Lea Davis
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Eske M Derks
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | | | - Filippo Del Bene
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Bruno Reversade
- Genome Institute of Singapore, Laboratory of Human Genetics & Therapeutics, A*STAR, Singapore, Singapore
- Smart-Health Initiative, BESE, KAUST, Thuwal, Saudi Arabia
| | - Grant W Montgomery
- Institute of Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
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10
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Ahlberg J, Lobbezoo F, Hublin C, Piirtola M, Kaprio J. Self-reported sleep bruxism in 1990 and 2011 in a nationwide twin cohort: Evidence of trait persistence and genetic liability. J Oral Rehabil 2024; 51:119-124. [PMID: 36062358 DOI: 10.1111/joor.13368] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 07/17/2022] [Accepted: 08/09/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Due to different assessment modes employed, a clear picture of the prevalence of sleep bruxism across time cannot be formed. Moreover, studies on the persistent or fluctuating nature of sleep bruxism have yielded divergent and even contradictory results. The aim of the present study was to evaluate in a nationwide twin cohort whether self-reported sleep bruxism was correlated longitudinally, pairwise and cross-twin over a 20-year period. OBJECTIVES Self-reported bruxism was assessed in 1990 and 2011 by mailed questionnaires in the Finnish Twin Cohort study of same-sex twins born 1945-1957. METHODS We assessed the phenotypic stability over time for all participating individuals (n = 4992). Among zygosity verified pairs (n = 516 MZ and n = 837 DZ), we estimated the cross-sectional zygosity correlations and the zygosity-specific cross-twin cross-time correlations. RESULTS Reported bruxism appeared rather persistent over time without significant difference regarding zygosity. The overall phenotypic longitudinal correlation was 0.540 and somewhat higher in men (0.596) than in women (0.507). Pairwise trait correlations in 1990 and 2011 were higher in MZ than in DZ pairs. The cross-twin cross-time correlations were higher in MZ twins than in DZ twins, but less than the cross-sectional MZ and DZ pairwise correlations. CONCLUSIONS The higher correlation of reported sleep bruxism in the cross-twin cross-time analyses in MZ than in DZ pairs implies a genetic background for bruxism persistence. Also, bruxism over time in individual twins appears to be fairly persistent and somewhat higher in men than women.
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Affiliation(s)
- Jari Ahlberg
- Department of Oral and Maxillofacial Diseases, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
| | - Frank Lobbezoo
- Department of Orofacial pain and Dysfunction, Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Maarit Piirtola
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- UKK Institute for Health Promotion Research, Tampere, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
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11
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Ojala R, Hentilä J, Lietzén MS, Arponen M, Heiskanen MA, Honkala SM, Virtanen H, Koskensalo K, Lautamäki R, Löyttyniemi E, Parkkola R, Heinonen OJ, Malm T, Lahti L, Rinne J, Eskola O, Rajander J, Pietiläinen KH, Kaprio J, Ivaska KK, Hannukainen JC. Bone marrow metabolism is affected by body weight and response to exercise training varies according to anatomical location. Diabetes Obes Metab 2024; 26:251-261. [PMID: 37818602 DOI: 10.1111/dom.15311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/09/2023] [Accepted: 09/19/2023] [Indexed: 10/12/2023]
Abstract
AIM High body weight is a protective factor against osteoporosis, but obesity also suppresses bone metabolism and whole-body insulin sensitivity. However, the impact of body weight and regular training on bone marrow (BM) glucose metabolism is unclear. We studied the effects of regular exercise training on bone and BM metabolism in monozygotic twin pairs discordant for body weight. METHODS We recruited 12 monozygotic twin pairs (mean ± SD age 40.4 ± 4.5 years; body mass index 32.9 ± 7.6, mean difference between co-twins 7.6 kg/m2 ; eight female pairs). Ten pairs completed the 6-month long training intervention. We measured lumbar vertebral and femoral BM insulin-stimulated glucose uptake (GU) using 18 F-FDG positron emission tomography, lumbar spine bone mineral density and bone turnover markers. RESULTS At baseline, heavier co-twins had higher lumbar vertebral BM GU (p < .001) and lower bone turnover markers (all p < .01) compared with leaner co-twins but there was no significant difference in femoral BM GU, or bone mineral density. Training improved whole-body insulin sensitivity, aerobic capacity (both p < .05) and femoral BM GU (p = .008). The training response in lumbar vertebral BM GU was different between the groups (time × group, p = .02), as GU tended to decrease in heavier co-twins (p = .06) while there was no change in leaner co-twins. CONCLUSIONS In this study, regular exercise training increases femoral BM GU regardless of weight and genetics. Interestingly, lumbar vertebral BM GU is higher in participants with higher body weight, and training counteracts this effect in heavier co-twins even without reduction in weight. These data suggest that BM metabolism is altered by physical activity.
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Affiliation(s)
- Ronja Ojala
- Turku PET Centre, University of Turku, Turku, Finland
| | | | | | - Milja Arponen
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Marja A Heiskanen
- Turku PET Centre, University of Turku, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | | | | | - Kalle Koskensalo
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | | | | | - Riitta Parkkola
- Department of Radiology, University of Turku, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Olli J Heinonen
- Paavo Nurmi Centre, Department of Health and Physical Activity, University of Turku, Turku, Finland
| | - Tarja Malm
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Leo Lahti
- Department of Computing, University of Turku, Turku, Finland
| | - Juha Rinne
- Turku PET Centre, University of Turku, Turku, Finland
- Turku PET Centre, Turku University Hospital, Turku, Finland
| | - Olli Eskola
- Radiopharmaceutical Chemistry Laboratory, Turku PET Centre, University of Turku, Turku, Finland
| | - Johan Rajander
- Turku PET Centre, Accelerator Laboratory, Åbo Akademi University, Turku, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Healthy Weight Hub, Abdominal Center, Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kaisa K Ivaska
- Institute of Biomedicine, University of Turku, Turku, Finland
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12
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Helaakoski V, Zellers S, Hublin C, Ollila HM, Latvala A. Associations between sleep medication use and alcohol consumption over 36 years in Finnish twins. Alcohol 2023:S0741-8329(23)00344-0. [PMID: 38101525 DOI: 10.1016/j.alcohol.2023.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 11/23/2023] [Accepted: 12/12/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Sleep medication use is an indicator of underlying sleep problems that might be induced by various factors such as alcohol use. However, the longitudinal relationship between drinking and sleep problems remains poorly understood. We investigated associations between sleep medication and alcohol use throughout adulthood, and examined the role of familial and potential confounding factors contributing to these associations. METHODS We used information of zygosity and self-report questionnaire data over a follow-up period of 36 years from the Older Finnish Twin Cohort (N=13,851). RESULTS Logistic regression analyses suggested consistent associations between sleep medication use and heavy/binge drinking at all four time points (OR range =1.36-3.18, P <0.05), implying that increased drinking is associated with increased sleep medication use over time. Cross-lagged path analyses suggested that moderate/heavy and binge drinking predict sleep medication use at most time points (OR range = 1.15-1.94, P <0.05), whilst sleep medication use predicts subsequent abstaining from alcohol (OR range =2.26-2.47, P <0.05). Within-pair analyses implied that familial factors play a role, and quantitative genetic modelling estimated genetic factors to explain approximately 80% of the lifetime association of sleep medication use with moderate/heavy and binge drinking. CONCLUSIONS Drinking is associated with sleep medication use throughout adulthood. Further, our results suggest that drinking is likely to predict sleep medication use, thereby potentially constituting a risk factor for sleep problems, and that genetic factors contribute to the association. These findings are important in terms of better understanding the development of sleep and alcohol use disorders.
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Affiliation(s)
- Viola Helaakoski
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Stephanie Zellers
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Christer Hublin
- Finnish Institute of Occupational Health, Helsinki, Finland; Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Hanna M Ollila
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, USA; Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Antti Latvala
- Institute of Criminology and Legal Policy, University of Helsinki, Helsinki, Finland
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13
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Aaltonen S, Urjansson M, Varjonen A, Vähä-Ypyä H, Iso-Markku P, Kaartinen S, Vasankari T, Kujala UM, Silventoinen K, Kaprio J, Vuoksimaa E. Accelerometer-measured physical activity and sedentary behavior in nonagenarians: Associations with self-reported physical activity, anthropometric, sociodemographic, health and cognitive characteristics. PLoS One 2023; 18:e0294817. [PMID: 38055660 DOI: 10.1371/journal.pone.0294817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Accepted: 11/09/2023] [Indexed: 12/08/2023] Open
Abstract
BACKGROUND Research on device-based physical activity in the oldest-old adults is scarce. We examined accelerometer-measured physical activity and sedentary behavior in nonagenarians. We also investigated how the accelerometer characteristics associate with nonagenarians' self-reported physical activity, anthropometric, sociodemographic, health and cognitive characteristics. METHODS Nonagenarians from a population-based cohort study (N = 38, mean age 91.2) used accelerometers during the waking hours for seven days. They also participated in a health survey and cognitive telephone interview. The Wald test and Pearson and polyserial correlations were used to analyze the data. RESULTS The participants' average day consisted of 2931 steps, 11 minutes of moderate-to-vigorous physical activity and 13.6 hours of sedentary time. Physical activity bouts less than 3 minutes per day and sedentary time bouts of 20-60 minutes per day were the most common. No sex differences were found. Many accelerometer-measured and self-reported physical activity characteristics correlated positively (correlations ≥0.34, p-values <0.05). The low levels of many accelerometer-measured physical activity characteristics associated with low education (correlations ≥0.25, p-values <0.05), dizziness (correlations ≤-0.42, p-values <0.01) and fear of falling (correlations ≤-0.45, p-values <0.01). Fear of falling was also associated with accelerometer-measured sedentary behavior characteristics (correlations -0.42 or ≥0.43). CONCLUSIONS Nonagenarians were mostly sedentary and low in physical activity, but individual variability existed. Accelerometer-measured and self-reported physical activity had a good consistency. Education, dizziness and fear of falling were consistently related to accelerometer-measured characteristics in nonagenarians.
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Affiliation(s)
- Sari Aaltonen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Mia Urjansson
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Anni Varjonen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Henri Vähä-Ypyä
- UKK Institute for Health Promotion Research, Tampere, Finland
| | - Paula Iso-Markku
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, Clinical Physiology and Nuclear Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Sara Kaartinen
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Department of Physical Medicine and Rehabilitation, HUS Hyvinkää Hospital, Hyvinkää, Finland
| | - Tommi Vasankari
- UKK Institute for Health Promotion Research, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | | | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
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14
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Berntzen BJ, Palviainen T, Silventoinen K, Pietiläinen KH, Kaprio J. Polygenic risk of obesity and BMI trajectories over 36 years: A longitudinal study of adult Finnish twins. Obesity (Silver Spring) 2023; 31:3086-3094. [PMID: 37987187 PMCID: PMC10947257 DOI: 10.1002/oby.23906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/04/2023] [Accepted: 08/06/2023] [Indexed: 11/22/2023]
Abstract
OBJECTIVE This study investigated 36-year BMI trajectories in twins whose BMI in young adulthood was below, within, or above their genetically predicted BMI, with a focus on twin pairs with large intrapair BMI differences (within-pair ΔBMI ≥ 3 kg/m2 ). METHODS Together, 3227 like-sexed twin pairs (34% monozygotic) were examined at age ~30 years in 1975 and followed up in 1981, 1990, and 2011. An individual's observed BMI in 1975 was considered within (±2.0), below (<-2.0), or above (>+2.0) genetically predicted BMI, measured by a polygenic risk score of 996,919 single nucleotide polymorphisms. RESULTS In monozygotic and dizygotic twin pairs with large intrapair BMI differences, the co-twin with a higher observed BMI in 1975 deviated above predicted BMI more frequently (~2/3) than the co-twin with a lower BMI deviated below prediction (~1/3). Individuals below, within, and above prediction in 1975 reached, respectively, normal weight, overweight, and obesity by 2011, with a mean BMI increase of 4.5 (95% CI: 4.3-4.8). CONCLUSIONS Categorizing BMI as below, within, or above polygenic risk score-predicted BMI helps identifying individuals who have been resistant or susceptible to weight gain. This may provide new insights into determinants and consequences of obesity.
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Affiliation(s)
- Bram J. Berntzen
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
| | - Karri Silventoinen
- Faculty of Social Sciences, Population Research UnitUniversity of HelsinkiHelsinkiFinland
| | - Kirsi H. Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of MedicineUniversity of HelsinkiHelsinkiFinland
- HealthyWeightHub, Endocrinology, Abdominal CenterHelsinki University Hospital and University of HelsinkiHelsinkiFinland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
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15
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Vuoksimaa E, Saari TT, Aaltonen A, Aaltonen S, Herukka SK, Iso-Markku P, Kokkola T, Kyttälä A, Kärkkäinen S, Liedes H, Ollikainen M, Palviainen T, Ruotsalainen I, Toivola A, Urjansson M, Vasankari T, Vähä-Ypyä H, Forsberg MM, Hiltunen M, Jalanko A, Kälviäinen R, Kuopio T, Lähteenmäki J, Nyberg P, Männikkö M, Serpi R, Siltanen S, Palotie A, Kaprio J, Runz H, Julkunen V. TWINGEN - protocol for an observational clinical biobank recall and biomarker study to identify individuals with high risk of Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.03.23298018. [PMID: 37965200 PMCID: PMC10635260 DOI: 10.1101/2023.11.03.23298018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2023]
Abstract
Introduction A better understanding of the earliest stages of Alzheimer's disease (AD) could expedite the development or administration of treatments. Large population biobanks hold the promise to identify individuals at an elevated risk of AD and related dementias based on health registry information. Here, we establish the protocol for an observational clinical recall and biomarker study called TWINGEN with the aim to identify individuals at high risk of AD by assessing cognition, health and AD-related biomarkers. Suitable candidates were identified and invited to participate in the new study among Finnish biobank donors according to TWINGEN study criteria. Methods and analysis A multi-center study (n=800) to obtain blood-based biomarkers, telephone-administered and web-based memory and cognitive parameters, questionnaire information on lifestyle, health and psychological factors, and accelerometer data for measures of physical activity, sedentary behavior and sleep. A sub-cohort are being asked to participate in an in-person neuropsychological assessment (n=200) and wear an Oura ring (n=50). All participants in the TWINGEN study have genome-wide genotyping data and up to 48 years of follow-up data from the population-based older Finnish Twin Cohort (FTC) study of the University of Helsinki. TWINGEN data will be transferred to Finnish Institute of Health and Welfare (THL) biobank and we aim to further to transfer it to the FinnGen study where it will be combined with health registry data for prediction of AD. Ethics and dissemination This recall study consists of FTC/THL/FinnGen participants whose data were acquired in accordance with the Finnish Biobank Act. The recruitment protocols followed the biobank protocols approved by Finnish Medicines Agency. The TWINGEN study plan was approved by the Ethics Committee of Hospital District of Helsinki and Uusimaa (number 16831/2022). THL Biobank approved the research plan with the permission no: THLBB2022_83.
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Affiliation(s)
- Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Toni T Saari
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Aino Aaltonen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sari Aaltonen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sanna-Kaisa Herukka
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, Neurocenter, Kuopio University Hospital, Kuopio, Finland
| | - Paula Iso-Markku
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Tarja Kokkola
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Aija Kyttälä
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Sari Kärkkäinen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Hilkka Liedes
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- VTT Technical Research Centre of Finland Ltd., Oulu, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Teemu Palviainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Ilona Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- VTT Technical Research Centre of Finland Ltd., Espoo, Finland
| | - Auli Toivola
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Mia Urjansson
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Tommi Vasankari
- UKK Institute for Health Promotion Research, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Henri Vähä-Ypyä
- UKK Institute for Health Promotion Research, Tampere, Finland
| | - Markus M Forsberg
- School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland
- VTT Technical Research Centre of Finland Ltd., Kuopio, Finland
| | - Mikko Hiltunen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Anu Jalanko
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Reetta Kälviäinen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, Neurocenter, Kuopio University Hospital, Kuopio, Finland
| | - Teijo Kuopio
- Central Finland Biobank, Central Finland Health Care District, Jyväskylä, Finland
| | | | - Pia Nyberg
- Biobank Borealis of Northern Finland, Oulu University Hospital, Wellbeing Services county of North Ostrobothnia, Oulu, Finland
- Translational Medicine Research Unit, University of Oulu, Oulu, Finland
| | - Minna Männikkö
- Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Raisa Serpi
- Biobank Borealis of Northern Finland, Oulu University Hospital, Wellbeing Services county of North Ostrobothnia, Oulu, Finland
| | - Sanna Siltanen
- Finnish Clinical Biobank Tampere, Tampere University Hospital, Wellbeing Services County of Pirkanmaa, Tampere, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Analytic and Translational Genetics Unit, Department of Medicine, Department of Neurology and Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- The Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Heiko Runz
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Translational Sciences, Biogen, Cambridge, MA, USA
| | - Valtteri Julkunen
- Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Neurology, Neurocenter, Kuopio University Hospital, Kuopio, Finland
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16
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Howe LJ, Rasheed H, Jones PR, Boomsma DI, Evans DM, Giannelis A, Hayward C, Hopper JL, Hughes A, Lahtinen H, Li S, Lind PA, Martin NG, Martikainen P, Medland SE, Morris TT, Nivard MG, Pingault JB, Silventoinen K, Smith JA, Willoughby EA, Wilson JF. Educational attainment, health outcomes and mortality: a within-sibship Mendelian randomization study. Int J Epidemiol 2023; 52:1579-1591. [PMID: 37295953 PMCID: PMC10555788 DOI: 10.1093/ije/dyad079] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 05/12/2023] [Indexed: 06/12/2023] Open
Abstract
BACKGROUND Previous Mendelian randomization (MR) studies using population samples (population MR) have provided evidence for beneficial effects of educational attainment on health outcomes in adulthood. However, estimates from these studies may have been susceptible to bias from population stratification, assortative mating and indirect genetic effects due to unadjusted parental genotypes. MR using genetic association estimates derived from within-sibship models (within-sibship MR) can avoid these potential biases because genetic differences between siblings are due to random segregation at meiosis. METHODS Applying both population and within-sibship MR, we estimated the effects of genetic liability to educational attainment on body mass index (BMI), cigarette smoking, systolic blood pressure (SBP) and all-cause mortality. MR analyses used individual-level data on 72 932 siblings from UK Biobank and the Norwegian HUNT study, and summary-level data from a within-sibship Genome-wide Association Study including >140 000 individuals. RESULTS Both population and within-sibship MR estimates provided evidence that educational attainment decreased BMI, cigarette smoking and SBP. Genetic variant-outcome associations attenuated in the within-sibship model, but genetic variant-educational attainment associations also attenuated to a similar extent. Thus, within-sibship and population MR estimates were largely consistent. The within-sibship MR estimate of education on mortality was imprecise but consistent with a putative effect. CONCLUSIONS These results provide evidence of beneficial individual-level effects of education (or liability to education) on adulthood health, independently of potential demographic and family-level confounders.
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Affiliation(s)
- Laurence J Howe
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Humaira Rasheed
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
| | - Paul R Jones
- Department of Community Medicine and Global Health, Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Registry, Vrije Universiteit, Amsterdam, Netherlands
- Amsterdam Public Health (APH) and Amsterdam Reproduction and Development (AR&D)
| | - David M Evans
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- University of Queensland Diamantina Institute, University of Queensland, Brisbane, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | | | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Amanda Hughes
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hannu Lahtinen
- Population Research Unit, University of Helsinki, Helsinki, Finland
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Penelope A Lind
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Pekka Martikainen
- Population Research Unit, University of Helsinki, Helsinki, Finland
- The Max Planck Institute for Demographic Research, Germany
- Department of Public Health Sciences, Stockholm University, Sweden
| | - Sarah E Medland
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Faculty of Medicine, University of Queensland, Brisbane, Australia
- School of Psychology, University of Queensland, Brisbane, Australia
| | - Tim T Morris
- Medical Research Council Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Michel G Nivard
- Department of Biological Psychology, Netherlands Twin Registry, Vrije Universiteit, Amsterdam, Netherlands
| | - Jean-Baptiste Pingault
- Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | | | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | | | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Teviot Place, Edinburgh, UK
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17
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Garske KM, Kar A, Comenho C, Balliu B, Pan DZ, Bhagat YV, Rosenberg G, Koka A, Das SS, Miao Z, Sinsheimer JS, Kaprio J, Pietiläinen KH, Pajukanta P. Increased body mass index is linked to systemic inflammation through altered chromatin co-accessibility in human preadipocytes. Nat Commun 2023; 14:4214. [PMID: 37452040 PMCID: PMC10349101 DOI: 10.1038/s41467-023-39919-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 07/04/2023] [Indexed: 07/18/2023] Open
Abstract
Obesity-induced adipose tissue dysfunction can cause low-grade inflammation and downstream obesity comorbidities. Although preadipocytes may contribute to this pro-inflammatory environment, the underlying mechanisms are unclear. We used human primary preadipocytes from body mass index (BMI) -discordant monozygotic (MZ) twin pairs to generate epigenetic (ATAC-sequence) and transcriptomic (RNA-sequence) data for testing whether increased BMI alters the subnuclear compartmentalization of open chromatin in the twins' preadipocytes, causing downstream inflammation. Here we show that the co-accessibility of open chromatin, i.e. compartmentalization of chromatin activity, is altered in the higher vs lower BMI MZ siblings for a large subset ( ~ 88.5 Mb) of the active subnuclear compartments. Using the UK Biobank we show that variants within these regions contribute to systemic inflammation through interactions with BMI on C-reactive protein. In summary, open chromatin co-accessibility in human preadipocytes is disrupted among the higher BMI siblings, suggesting a mechanism how obesity may lead to inflammation via gene-environment interactions.
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Affiliation(s)
- Kristina M Garske
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Asha Kar
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Caroline Comenho
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Brunilda Balliu
- Department of Computational Medicine, UCLA, Los Angeles, CA, 90095, USA
| | - David Z Pan
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, 90095, USA
| | - Yash V Bhagat
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Gregory Rosenberg
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Amogha Koka
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Sankha Subhra Das
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Zong Miao
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, 90095, USA
| | - Janet S Sinsheimer
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
- Department of Computational Medicine, UCLA, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, 90095, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, 00014, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00014, Finland
- Obesity Center, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, 00014, Finland
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
- Department of Computational Medicine, UCLA, Los Angeles, CA, 90095, USA.
- Institute for Precision Heath, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA.
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18
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Hublin C, Kaprio J. Chronotype and mortality - a 37-year follow-up study in Finnish adults. Chronobiol Int 2023; 40:841-849. [PMID: 37322846 DOI: 10.1080/07420528.2023.2215342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 05/03/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023]
Abstract
The UK Biobank study on chronotype and mortality suggested small increases of all-cause and cardiovascular mortality in a 6.5-year follow-up. Our aim was to constructively replicate findings from it in a longer follow-up. A questionnaire was administered to the population-based adult Finnish Twin Cohort in 1981 (response rate 84%). The study population included 23 854 participants who replied to the question: "Try to assess to what extent you are a morning person or an evening person," with four response alternatives (anchored from "clearly a morning person" to "clearly an evening person"). Vital status and cause of death data were provided by nationwide registers up to the end of 2018. Hazard ratios for mortality were computed based on 8728 deaths. Adjustments were made for education, alcohol, smoking, BMI, and sleep duration. The covariate adjusted model showed a 9% increase of all-cause mortality for the evening-type group (HR = 1.09, 95% CI 1.01-1.18), with attenuation mainly due to smoking and alcohol. Their importance was highlighted by observing no increased mortality among non-smokers who were at most light drinkers. There was no increase in any cause-specific mortality. Our results suggest that there is little or no independent contribution of chronotype to mortality.
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Affiliation(s)
- Christer Hublin
- Working Ability and Working Careers, Finnish Institute of Occupational Health, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
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19
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Kankaanpää A, Tolvanen A, Joensuu L, Waller K, Heikkinen A, Kaprio J, Ollikainen M, Sillanpää E. The associations of long-term physical activity in adulthood with later biological ageing and all-cause mortality - a prospective twin study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.02.23290916. [PMID: 37333101 PMCID: PMC10274991 DOI: 10.1101/2023.06.02.23290916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Objectives The association between leisure-time physical activity (LTPA) and a lower risk of mortality is susceptible to bias from multiple sources. We investigated the potential of biological ageing to mediate the association between long-term LTPA and mortality and whether the methods used to account for reverse causality affect the interpretation of this association. Methods Study participants were twins from the older Finnish Twin Cohort (n=22,750; 18-50 years at baseline). LTPA was assessed using questionnaires in 1975, 1981 and 1990. The mortality follow-up lasted until 2020 and biological ageing was assessed using epigenetic clocks in a subsample (n=1,153) with blood samples taken during the follow-up. Using latent profile analysis, we identified classes with distinct longitudinal LTPA patterns and studied differences in biological ageing between these classes. We employed survival models to examine differences in total, short-term and long-term all-cause mortality, and multilevel models for twin data to control for familial factors. Results We identified four classes of long-term LTPA: sedentary, moderately active, active and highly active. Although biological ageing was accelerated in sedentary and highly active classes, after adjusting for other lifestyle-related factors, the associations mainly attenuated. Physically active classes had a maximum 7% lower risk of total mortality over the sedentary class, but this association was consistent only in the short term and could largely be accounted for by familial factors. LTPA exhibited less favourable associations when prevalent diseases were exclusion criteria rather than covariate. Conclusion Being active may reflect a healthy phenotype instead of causally reducing mortality.
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Affiliation(s)
- Anna Kankaanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Asko Tolvanen
- Methodology Center for Human Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Laura Joensuu
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Elina Sillanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
- Wellbeing services county of Central Finland, Jyväskylä, Finland
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20
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Richards G, Segal NL. Handedness in twins reared apart: A review of the literature and new data. Neuropsychologia 2023; 184:108523. [PMID: 37059260 DOI: 10.1016/j.neuropsychologia.2023.108523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 02/14/2023] [Accepted: 02/20/2023] [Indexed: 04/16/2023]
Abstract
Reared-apart twin studies are a powerful means for identifying the relative contributions of heredity and environment to variation in human physical and behavioural traits. One such characteristic is handedness, for which it has long been noted that approximately 20% of twin pairs are comprised of one right-handed cotwin and one left-handed cotwin. Reared-together twin studies suggest a slightly greater concordance in monozygotic (MZT) than dizygotic (DZT) twins, implying that genetics influences hand preference. We report here two studies of handedness in reared-apart twins. Study 1 synthesizes the available data and estimates that at least N = 560 same-sex reared-apart twin pairs (for which zygosity is known with reasonable confidence) have been identified. Of these, handedness data are available for both members of n = 415 pairs. We observed similar levels of concordance/discordance for reared-apart monozygotic (MZA) and dizygotic (DZA) twins. However, although direction of handedness (right or left) has frequently been examined, strength of handedness (strong or weak) has not. Study 2 examined strength of hand preference and relative hand skill, as well as right- and left-hand speed, information available for participants in the Minnesota Study of Twins Reared Apart (MISTRA). We provide evidence of heritability for right-hand and left-hand speed. We also found hand preference strength was more alike than chance in DZA, but not MZA, twins. Findings are discussed in relation to genetic and environmental influences on human handedness.
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Affiliation(s)
- Gareth Richards
- School of Psychology, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, Tyne and Wear, NE2 4DR, UK.
| | - Nancy L Segal
- Department of Psychology, California State University, Fullerton, CA, 92831, USA
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21
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Schernhammer E, Bogl L, Hublin C, Strohmaier S, Zebrowska M, Erber A, Haghayegh S, Papantoniou K, Ollikainen M, Kaprio J. The association between night shift work and breast cancer risk in the Finnish twins cohort. Eur J Epidemiol 2023; 38:533-543. [PMID: 36964875 PMCID: PMC10164004 DOI: 10.1007/s10654-023-00983-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 02/28/2023] [Indexed: 03/26/2023]
Abstract
Breast cancer is highly prevalent yet a more complete understanding of the interplay between genes and probable environmental risk factors, such as night work, remains lagging. Using a discordant twin pair design, we examined the association between night shift work and breast cancer risk, controlling for familial confounding. Shift work pattern was prospectively assessed by mailed questionnaires among 5,781 female twins from the Older Finnish Twin Cohort. Over the study period (1990-2018), 407 incident breast cancer cases were recorded using the Finnish Cancer Registry. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) adjusting for potential confounders. Within-pair co-twin analyses were employed in 57 pairs to account for potential familial confounding. Compared to women who worked days only, women with shift work that included night shifts had a 1.58-fold higher risk of breast cancer (HR = 1.58; 95%CI, 1.16-2.15, highest among the youngest women i.e. born 1950-1957, HR = 2.08; 95%CI, 1.32-3.28), whereas 2-shift workers not including night shifts, did not (HR = 0.84; 95%CI, 0.59-1.21). Women with longer sleep (average sleep duration > 8 h/night) appeared at greatest risk of breast cancer if they worked night shifts (HR = 2.91; 95%CI, 1.55-5.46; Pintx=0.32). Results did not vary by chronotype (Pintx=0.74). Co-twin analyses, though with limited power, suggested that night work may be associated with breast cancer risk independent of early environmental and genetic factors. These results confirm a previously described association between night shift work and breast cancer risk. Genetic influences only partially explain these associations.
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Affiliation(s)
- Eva Schernhammer
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, Vienna, 1090, Austria.
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA.
- Complexity Science Hub Vienna, Josefstädter Straße 39, Vienna, 1080, Austria.
| | - Leonie Bogl
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, Vienna, 1090, Austria
- Institute for Molecular Medicine (FIMM), University of, Helsinki, Tukholmankatu 8, P.O. Box 20, Helsinki, 00014, Finland
| | - Christer Hublin
- Finnish Institute of Occupational Health, Topeliuksenkatu 41 b, Helsinki, 00250, Finland
| | - Susanne Strohmaier
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, Vienna, 1090, Austria
| | - Magda Zebrowska
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, Vienna, 1090, Austria
| | - Astrid Erber
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, Vienna, 1090, Austria
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, New Richards Building, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LG, UK
| | - Shahab Haghayegh
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Kyriaki Papantoniou
- Department of Epidemiology, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, Vienna, 1090, Austria
| | - Miina Ollikainen
- Institute for Molecular Medicine (FIMM), University of, Helsinki, Tukholmankatu 8, P.O. Box 20, Helsinki, 00014, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum Helsinki 2U, Tukholmankatu 8, Helsinki, 00290, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine (FIMM), University of, Helsinki, Tukholmankatu 8, P.O. Box 20, Helsinki, 00014, Finland
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22
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Drouard G, Silventoinen K, Latvala A, Kaprio J. Genetic and Environmental Factors Underlying Parallel Changes in Body Mass Index and Alcohol Consumption: A 36-Year Longitudinal Study of Adult Twins. Obes Facts 2023; 16:224-236. [PMID: 36882010 PMCID: PMC10826601 DOI: 10.1159/000529835] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 02/17/2023] [Indexed: 03/09/2023] Open
Abstract
INTRODUCTION While the genetic and environmental underpinnings of body weight and alcohol use are fairly well-known, determinants of simultaneous changes in these traits are still poorly known. We sought to quantify the environmental and genetic components underlying parallel changes in weight and alcohol consumption and to investigate potential covariation between them. METHODS The analysis comprised 4,461 adult participants (58% women) from the Finnish Twin Cohort with four measures of alcohol consumption and body mass index (BMI) over a 36-year follow-up. Trajectories of each trait were described by growth factors, defined as intercepts (i.e., baseline) and slopes (i.e., change over follow-up), using latent growth curve modeling. Growth values were used for male (190 monozygotic pairs, 293 dizygotic pairs) and female (316 monozygotic pairs, 487 dizygotic pairs) same-sex complete twin pairs in multivariate twin modeling. The variances and covariances of growth factors were then decomposed into genetic and environmental components. RESULTS The baseline heritabilities were similar in men (BMI: h2 = 79% [95% confidence interval: 74, 83]; alcohol consumption: h2 = 49% [32, 67]) and women (h2 = 77% [73, 81]; h2 = 45% [29, 61]). Heritabilities of BMI change were similar in men (h2 = 52% [42, 61]) and women (h2 = 57% [50, 63]), but the heritability of change in alcohol consumption was significantly higher (p = 0.03) in men (h2 = 45% [34, 54]) than in women (h2 = 31% [22, 38]). Significant additive genetic correlations between BMI at baseline and change in alcohol consumption were observed in both men (rA = -0.17 [-0.29, -0.04]) and women (rA = -0.18 [-0.31, -0.06]). Non-shared environmental factors affecting changes in alcohol consumption and BMI were correlated in men (rE = 0.18 [0.06, 0.30]). Among women, non-shared environmental factors affecting baseline alcohol consumption and the change in BMI were inversely correlated (rE = -0.11 [-0.20, -0.01]). CONCLUSIONS Based on genetic correlations, genetic variation underlying BMI may affect changes in alcohol consumption. Independent of genetic effects, change in BMI correlates with change in alcohol consumption in men, suggesting direct effects between them.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Karri Silventoinen
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Antti Latvala
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Institute of Criminology and Legal Policy, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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23
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Herranen P, Palviainen T, Rantanen T, Tiainen K, Viljanen A, Kaprio J, Sillanpää E. A Polygenic Risk Score for Hand Grip Strength Predicts Muscle Strength and Proximal and Distal Functional Outcomes among Older Women. Med Sci Sports Exerc 2022; 54:1889-1896. [PMID: 35776845 DOI: 10.1249/mss.0000000000002981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
PURPOSE Hand grip strength (HGS) is a widely used indicator of overall muscle strength and general health. We computed a polygenic risk score (PRS) for HGS and examined whether it predicted muscle strength, functional capacity, and disability outcomes. METHODS Genomewide association study summary statistics for HGS from the Pan-UK Biobank was used. PRS were calculated in the Finnish Twin Study on Aging ( N = 429 women, 63-76 yr). Strength tests included HGS, isometric knee extension, and ankle plantarflexion strength. Functional capacity was examined with the Timed Up and Go, 6-min and 10-m walk tests, and dual-task tests. Disabilities in the basic activities of daily living (ADL) and instrumental ADL (IADL) were investigated with questionnaires. The proportion of variation in outcomes accounted for by PRS HGS was examined using linear mixed models and extended logistic regression. RESULTS The measured HGS increased linearly over increasing PRS ( β = 4.8, SE = 0.93, P < 0.001). PRS HGS independently accounted for 6.1% of the variation in the measured HGS ( β = 14.2, SE = 3.1, P < 0.001), 5.4% of the variation in knee extension strength ( β = 19.6, SE = 4.7, P < 0.001), 1.2% of the variation in ankle plantarflexion strength ( β = 9.4, SE = 4.2, P = 0.027), and 0.1%-1.5% of the variation in functional capacity tests ( P = 0.016-0.133). Further, participants with higher PRS HGS were less likely to have ADL/IADL disabilities (odds ratio = 0.74-0.76). CONCLUSIONS Older women with genetic risk for low muscle strength were significantly weaker than those with genetic susceptibility for high muscle strength. PRS HGS was also systematically associated with overall muscle strength and proximal and distal functional outcomes that require muscle strength.
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Affiliation(s)
- Päivi Herranen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | | | - Taina Rantanen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - Kristina Tiainen
- Gerontology Research Center, Faculty of Social Sciences, Health Sciences, Tampere University, Tampere, FINLAND
| | - Anne Viljanen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, Helsinki, FINLAND
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24
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Marttila S, Tamminen H, Rajić S, Mishra PP, Lehtimäki T, Raitakari O, Kähönen M, Kananen L, Jylhävä J, Hägg S, Delerue T, Peters A, Waldenberger M, Kleber ME, März W, Luoto R, Raitanen J, Sillanpää E, Laakkonen EK, Heikkinen A, Ollikainen M, Raitoharju E. Methylation status of VTRNA2-1/ nc886 is stable across populations, monozygotic twin pairs and in majority of tissues. Epigenomics 2022; 14:1105-1124. [PMID: 36200237 DOI: 10.2217/epi-2022-0228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Gerontology Research Center, Tampere University, Tampere, 33014, Finland
| | - Hely Tamminen
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sonja Rajić
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku & Turku University Hospital, Turku, 20014, Finland.,Research Centre of Applied & Preventive Cardiovascular Medicine, University of Turku, Turku, 20014, Finland.,Department of Clinical Physiology & Nuclear Medicine, Turku University Hospital, Turku, 20014, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
| | - Laura Kananen
- Faculty of Medicine & Health Technology, & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520,Finland.,Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sara Hägg
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,Competence Cluster for Nutrition & Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, 07743, Germany.,SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg, 86156, Germany.,Clinical Institute of Medical & Chemical Laboratory Diagnostics, Medical University of Graz, Graz, 8010, Austria
| | - Riitta Luoto
- The Social Insurance Institute of Finland (Kela), Helsinki, 00250, Finland.,The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland
| | - Jani Raitanen
- The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland.,Faculty of Social Sciences (Health Sciences), Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Elina Sillanpää
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland.,Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Eija K Laakkonen
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Emma Raitoharju
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
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25
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Lundgren S, Kuitunen S, Pietiläinen KH, Hurme M, Kähönen M, Männistö S, Perola M, Lehtimäki T, Raitakari O, Kaprio J, Ollikainen M. BMI is positively associated with accelerated epigenetic aging in twin pairs discordant for body mass index. J Intern Med 2022; 292:627-640. [PMID: 35699258 PMCID: PMC9540898 DOI: 10.1111/joim.13528] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND Obesity is a heritable complex phenotype that can increase the risk of age-related outcomes. Biological age can be estimated from DNA methylation (DNAm) using various "epigenetic clocks." Previous work suggests individuals with elevated weight also display accelerated aging, but results vary by epigenetic clock and population. Here, we utilize the new epigenetic clock GrimAge, which closely correlates with mortality. OBJECTIVES We aimed to assess the cross-sectional association of body mass index (BMI) with age acceleration in twins to limit confounding by genetics and shared environment. METHODS AND RESULTS Participants were from the Finnish Twin Cohort (FTC; n = 1424), including monozygotic (MZ) and dizygotic (DZ) twin pairs, and DNAm was measured using the Illumina 450K array. Multivariate linear mixed effects models including MZ and DZ twins showed an accelerated epigenetic age of 1.02 months (p-value = 6.1 × 10-12 ) per one-unit BMI increase. Additionally, heavier twins in a BMI-discordant MZ twin pair (ΔBMI >3 kg/m2 ) had an epigenetic age 5.2 months older than their lighter cotwin (p-value = 0.0074). We also found a positive association between log (homeostatic model assessment of insulin resistance) and age acceleration, confirmed by a meta-analysis of the FTC and two other Finnish cohorts (overall effect = 0.45 years, p-value = 4.1 × 10-25 ) from adjusted models. CONCLUSION We identified significant associations of BMI and insulin resistance with age acceleration based on GrimAge, which were not due to genetic effects on BMI and aging. Overall, these results support a role of BMI in aging, potentially in part due to the effects of insulin resistance.
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Affiliation(s)
- Sara Lundgren
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Sara Kuitunen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland.,Finnish Cardiovascular Research Center, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Satu Männistö
- Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- Finnish Institute for Health and Welfare, Helsinki, Finland.,Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.,Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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26
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Differences in DNA Methylation-Based Age Prediction Within Twin Pairs Discordant for Cancer. Twin Res Hum Genet 2022; 25:171-179. [PMID: 36073160 DOI: 10.1017/thg.2022.32] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
DNA methylation-based age acceleration (DNAmAA) is associated with cancer, with both cancer tissue and blood showing increased DNAmAA. We aimed to investigate whether DNAmAA is associated with cancer risk within twin pairs discordant for cancer, and whether DNAmAA has the potential to serve as a biomarker for such. The study included 47 monozygotic and 48 same-sex-dizygotic cancer-discordant twin pairs from the Finnish Twin Cohort study with blood samples available between 17 and 31 years after the cancer diagnosis. We studied all cancers (95 pairs), then separately breast cancer (24 pairs) and all sites other than breast cancer (71 pairs). DNAmAA was calculated for seven models: Horvath, Horvath intrinsic epigenetic age acceleration, Hannum, Hannum intrinsic epigenetic age acceleration, Hannum extrinsic epigenetic age acceleration, PhenoAge and GrimAge. Within-pair differences in DNAmAA were analyzed by paired t tests and linear regression. Twin pairs sampled before cancer diagnosis did not differ significantly in DNAmAA. However, the within-pair differences in DNAmAA before cancer diagnosis increased significantly the closer the cancer diagnosis was, and this acceleration extended for years after the diagnosis. Pairs sampled after the diagnosis differed for DNAmAA with the Horvath models capturing cancer diagnosis-associated DNAmAA across all three cancer groupings. The results suggest that DNAmAA in blood is associated with cancer diagnosis. This may be due to epigenetic alterations in relation to cancer, its treatment or associated lifestyle changes. Based on the current study, the biomarker potential of DNAmAA in blood appears to be limited.
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27
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Rose RJ, Latvala A, Silventoinen K, Kaprio J. Alcohol consumption at age 18-25 and number of children at a 33-year follow-up: Individual and within-pair analyses of Finnish twins. Alcohol Clin Exp Res 2022; 46:1552-1564. [PMID: 35719054 PMCID: PMC9545724 DOI: 10.1111/acer.14886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 05/14/2022] [Accepted: 06/13/2022] [Indexed: 01/31/2023]
Abstract
BACKGROUND Do drinking patterns in late adolescence/early adulthood predict lifetime childlessness and number of children? Research on this question has been only tangentially relevant and the results inconsistent. The designs used to date have been compromised by genetic and environmental confounds that are poorly controlled; covariate effects of smoking and education that are often ignored; males being understudied; population-based sampling rare, and long-term prospective studies with genetically informative designs yet to be reported. METHOD In a 33-year follow-up, we linked the drinking patterns of >3500 Finnish twin pairs, assessed at ages 18-25, to registry data on their eventual number of children. Analyses distinguished associations of early drinking patterns with lifetime childlessness from those predictive of family size. Within-twin pair analyses used fixed-effects regression models to account for shared familial confounds and genetic liabilities. Childlessness was analyzed with Cox proportional hazards models and family size with Poisson regression. Analyses within-pairs and of twins as individuals were run before and after adjustment for smoking and education, and for oral contraceptive (OC) use in individual-level analyses of female twins. RESULTS Baseline abstinence and heavier drinking both significantly predicted lifetime childlessness in individual-level analyses. Few abstinent women used OCs, but they were nonetheless more often eventually childless; adjusting for smoking and education did not affect this finding. Excluding childless twins, Poisson models of family size showed heavier drinking at 18-25 to be predictive of fewer children in both men and women. Those associations were replicated in within-pair analyses of dizygotic twins, each level of heavier drinking being associated with smaller families. Among monozygotic twins, associations of drinking with completed family size yielded effects of similar magnitude, reaching significance at the highest levels of consumption, ruling out familial confounds. CONCLUSIONS Compared to moderate levels of drinking, both abstinence and heavier drinking in late adolescence/early adulthood predicted a greater likelihood of lifetime childlessness and eventual number of children. Familial confounds do not fully explain these associations.
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Affiliation(s)
- Richard J. Rose
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
| | - Antti Latvala
- Institute of Criminology and Legal PolicyFaculty of Social Sciences, University of HelsinkiHelsinkiFinland
| | - Karri Silventoinen
- Population Research Unit, Faculty of Social SciencesUniversity of HelsinkiHelsinkiFinland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
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Azzolini F, Berentsen GD, Skaug HJ, Hjelmborg JVB, Kaprio JA. The heritability of BMI varies across the range of BMI-a heritability curve analysis in a twin cohort. Int J Obes (Lond) 2022; 46:1786-1791. [PMID: 35817850 DOI: 10.1038/s41366-022-01172-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 06/09/2022] [Accepted: 06/14/2022] [Indexed: 12/18/2022]
Abstract
BACKGROUND The heritability of traits such as body mass index (BMI), a measure of obesity, is generally estimated using family and twin studies, and increasingly by molecular genetic approaches. These studies generally assume that genetic effects are uniform across all trait values, yet there is emerging evidence that this may not always be the case. METHOD/SUBJECTS This paper analyzes twin data using a recently developed measure of heritability called the heritability curve. Under the assumption that trait values in twin pairs are governed by a flexible Gaussian mixture distribution, heritability curves may vary across trait values. The data consist of repeated measures of BMI on 1506 monozygotic (MZ) and 2843 like-sexed dizygotic (DZ) adult twin pairs, gathered from multiple surveys in older Finnish Twin Cohorts. RESULTS The heritability curve and BMI value-specific MZ and DZ pairwise correlations were estimated, and these varied across the range of BMI. MZ correlations were highest at BMI values from 21 to 24, with a stronger decrease for women than for men at higher values. Models with additive and dominance effects fit best at low and high BMI values, while models with additive genetic and common environmental effects fit best in the normal range of BMI. CONCLUSIONS We demonstrate that twin and molecular genetic studies need to consider how genetic effects vary across trait values. Such variation may reconcile findings of traits with high heritability and major differences in mean values between countries or over time.
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Affiliation(s)
| | - Geir D Berentsen
- Department of Business and Management Science, NHH Norwegian School of Economics, Bergen, Norway
| | - Hans J Skaug
- Department of Mathematics, University of Bergen, Bergen, Norway
| | - Jacob V B Hjelmborg
- Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jaakko A Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
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Kujala UM, Leskinen T, Rottensteiner M, Aaltonen S, Ala-Korpela M, Waller K, Kaprio J. Physical activity and health: Findings from Finnish monozygotic twin pairs discordant for physical activity. Scand J Med Sci Sports 2022; 32:1316-1323. [PMID: 35770444 PMCID: PMC9378553 DOI: 10.1111/sms.14205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 05/21/2022] [Accepted: 06/15/2022] [Indexed: 11/28/2022]
Abstract
Genetic and early environmental differences including early health habits associate with future health. To provide insight on the causal nature of these associations, monozygotic (MZ) twin pairs discordant for health habits provide an interesting natural experiment. Twin pairs discordant for leisure‐time physical activity (LTPA) in early adult life is thus a powerful study design to investigate the associations between long‐term LTPA and indicators of health and wellbeing. We have identified 17 LTPA discordant twin pairs from two Finnish twin cohorts and summarize key findings of these studies in this paper. The carefully characterized rare long‐term LTPA discordant MZ twin pairs have participated in multi‐dimensional clinical examinations. Key findings highlight that compared with less active twins in such MZ twin pairs, the twins with higher long‐term LTPA have higher physical fitness, reduced body fat, reduced visceral fat, reduced liver fat, increased lumen diameters of conduit arteries to the lower limbs, increased bone mineral density in loaded bone areas, and an increased number of large high‐density lipoprotein particles. The findings increase our understanding on the possible site‐specific and system‐level effects of long‐term LTPA.
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Affiliation(s)
- Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Tuija Leskinen
- Department of Public Health, University of Turku and Turku University Hospital, Turku, Finland
| | - Mirva Rottensteiner
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Sari Aaltonen
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
| | - Mika Ala-Korpela
- Systems Epidemiology, Faculty of Medicine, University of Oulu & Biocenter Oulu, Oulu, Finland.,Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine FIMM, University of Helsinki, Helsinki, Finland
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Drouard G, Ollikainen M, Mykkänen J, Raitakari O, Lehtimäki T, Kähönen M, Mishra PP, Wang X, Kaprio J. Multi-Omics Integration in a Twin Cohort and Predictive Modeling of Blood Pressure Values. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2022; 26:130-141. [PMID: 35259029 PMCID: PMC8978565 DOI: 10.1089/omi.2021.0201] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
Abnormal blood pressure is strongly associated with risk of high-prevalence diseases, making the study of blood pressure a major public health challenge. Although biological mechanisms underlying hypertension at the single omic level have been discovered, multi-omics integrative analyses using continuous variations in blood pressure values remain limited. We used a multi-omics regression-based method, called sparse multi-block partial least square, for integrative, explanatory, and predictive interests in study of systolic and diastolic blood pressure values. Various datasets were obtained from the Finnish Twin Cohort for up to 444 twins. Blocks of omics-including transcriptomic, methylation, metabolomic-data as well as polygenic risk scores and clinical data were integrated into the modeling and supported by cross-validation. The predictive contribution of each omics block when predicting blood pressure values was investigated using external participants from the Young Finns Study. In addition to revealing interesting inter-omics associations, we found that each block of omics heterogeneously improved the predictions of blood pressure values once the multi-omics data were integrated. The modeling revealed a plurality of clinical, transcriptomic, and metabolomic factors consistent with the literature and that play a leading role in explaining unit variations in blood pressure. These findings demonstrate (1) the robustness of our integrative method to harness results obtained by single omics discriminant analyses, and (2) the added value of predictive and exploratory gains of a multi-omics approach in studies of complex phenotypes such as blood pressure.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Address correspondence to: Gabin Drouard, MSc, Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, Helsinki 00014, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Juha Mykkänen
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Pashupati P. Mishra
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Xiaoling Wang
- Georgia Prevention Institute (GPI), Medical College of Georgia, Augusta University, Augusta, Georgia, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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Korhonen T, Hjelmborg J, Harris JR, Clemmensen S, Adami HO, Kaprio J. Cancer in twin pairs discordant for smoking: The Nordic Twin Study of Cancer. Int J Cancer 2022; 151:33-43. [PMID: 35143046 PMCID: PMC9304125 DOI: 10.1002/ijc.33963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 01/17/2022] [Indexed: 11/17/2022]
Abstract
The discordant twin pair study design is powerful to control for familial confounding. We employed this approach to investigate the associations of smoking with several cancers. The NorTwinCan study combines data from the Danish, Finnish, Norwegian and Swedish twin and cancer registries. Follow‐up started when smoking status was determined and ended at cancer diagnosis confirmed by information in the cancer registry, death or end of follow‐up. We classified the participants as never (n = 59 093), former (n = 21 168) or current (n = 47 314) smokers. We pooled data from twin pairs where one co‐twin was diagnosed with any of the following tobacco‐related cancers: esophagus, kidney, larynx, liver, oral cavity, pancreas, pharynx or urinary bladder, while their co‐twin had none of those. Lung cancer was included in further analysis. We used Cox regression allowing for pair‐specific baseline functions to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). For tobacco‐related cancer sites, we recorded 7379 cases during median 27 years of follow‐up. The analyses based on individual twins showed that former (HR 1.31, 95% CI: 1.17‐1.48) and current (HR 2.14 [1.95‐2.34]) smokers are at increased risk to develop one of cancers listed above, compared to never smokers. Among 109 monozygotic twin pairs discordant for cancer and smoking, the HR was 1.85 (95% CI: 1.15‐2.98) among current smokers and 1.69 (1.00‐2.87) among former smokers when compared to their never smoking co‐twin. Thus, associations of smoking with several cancers were replicated for discordant identical twin pairs. Analyses based on genetically informative data provide evidence consistent with smoking causing multiple cancers.
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Affiliation(s)
- Tellervo Korhonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Jacob Hjelmborg
- Department of Epidemiology, Biostatistics and Biodemography, University of Southern Denmark.,Denmark and the Danish Twin Registry, University of Southern Denmark, Odense, Denmark
| | - Jennifer R Harris
- Center for Fertility and Health, The Norwegian Institute of Public Health, Oslo, Norway
| | - Signe Clemmensen
- Department of Epidemiology, Biostatistics and Biodemography, University of Southern Denmark.,Denmark and the Danish Twin Registry, University of Southern Denmark, Odense, Denmark
| | - Hans-Olov Adami
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.,Clinical Effectiveness Group, Institute of Health, University of Oslo, Oslo, Norway
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
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Iso-Markku P, Kaprio J, Lindgrén N, Rinne JO, Vuoksimaa E. Education as a moderator of middle-age cardiovascular risk factor-old-age cognition relationships: testing cognitive reserve hypothesis in epidemiological study. Age Ageing 2022; 51:6520517. [PMID: 35134847 PMCID: PMC8824709 DOI: 10.1093/ageing/afab228] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 09/14/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND higher educational attainment and less midlife cardiovascular risk factors are related to better old-age cognition. Whether education moderates the association between cardiovascular risk factors and late-life cognition is not known. We studied if higher education provides resilience against the deteriorative effects of higher middle-age body mass index (BMI) and a combination of midlife cardiovascular risk factors on old-age cognition. METHODS the study population is the older Finnish Twin Cohort (n = 4,051, mean age [standard deviation, SD] = 45.5 years [6.5]). Cardiovascular risk factors and education were studied at baseline with questionnaires in 1975, 1981 and/or 1990 (participation rates of 89, 84 and 77%, respectively). Cognition was evaluated with telephone interviews (participation rate 67%, mean age [SD] =73.4 [2.9] years, mean follow-up [SD] = 27.8 [6.0] years) in 1999-2017. We studied the main and interactive effects of education and BMI/dementia risk score on late-life cognition with linear regression analysis. The study design was formulated before the pre-defined analyses. RESULTS years of education moderated the association between BMI with old-age cognition (among less educated persons, BMI-cognition association was stronger [B = -0.24 points per BMI unit, 95% CI -0.31, -0.18] than among more educated persons [B = -0.06 points per BMI unit, 95% CI -0.16, 0.03], Pinteraction < 0.01). There was a similar moderating effect of education on dementia risk score consisting of cardiovascular risk factors (P < 0.001). CONCLUSIONS our results support the cognitive reserve hypothesis. Those with higher education may tolerate the deteriorative effects of midlife cardiovascular risk factors on old-age cognition better than those with lower education.
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Affiliation(s)
- Paula Iso-Markku
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- HUS Diagnostic Center, Clinical Physiology and Nuclear Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland
| | | | - Juha O Rinne
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Helsinki, Finland
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Nustad HE, Steinsland I, Ollikainen M, Cazaly E, Kaprio J, Benjamini Y, Gervin K, Lyle R. Modeling dependency structures in 450k DNA methylation data. Bioinformatics 2022; 38:885-891. [PMID: 34788815 PMCID: PMC8796368 DOI: 10.1093/bioinformatics/btab774] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 11/01/2021] [Accepted: 11/09/2021] [Indexed: 02/04/2023] Open
Abstract
MOTIVATION DNA methylation has been shown to be spatially dependent across chromosomes. Previous studies have focused on the influence of genomic context on the dependency structure, while not considering differences in dependency structure between individuals. RESULTS We modeled spatial dependency with a flexible framework to quantify the dependency structure, focusing on inter-individual differences by exploring the association between dependency parameters and technical and biological variables. The model was applied to a subset of the Finnish Twin Cohort study (N = 1611 individuals). The estimates of the dependency parameters varied considerably across individuals, but were generally consistent across chromosomes within individuals. The variation in dependency parameters was associated with bisulfite conversion plate, zygosity, sex and age. The age differences presumably reflect accumulated environmental exposures and/or accumulated small methylation differences caused by stochastic mitotic events, establishing recognizable, individual patterns more strongly seen in older individuals. AVAILABILITY AND IMPLEMENTATION The twin dataset used in the current study are located in the Biobank of the National Institute for Health and Welfare, Finland. All the biobanked data are publicly available for use by qualified researchers following a standardized application procedure (https://thl.fi/en/web/thl-biobank/for-researchers). A R-script for fitting the dependency structure to publicly available DNA methylation data with the software used in this article is provided in supplementary data. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Haakon E Nustad
- Department of Medical Genetics and Norwegian Sequencing Centre, Oslo University Hospital, 0450 Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
- Department of Pharmacy, PharmaTox Strategic Research Initiative, University of Oslo, 0371 Oslo, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, 0213 Oslo, Norway
| | - Ingelin Steinsland
- Department of Mathematical Sciences, Norwegian University of Science and Technology, 7034 Trondheim, Norway
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute of Life Science, University of Helsinki, FI-00014 Helsinki, Finland
| | - Emma Cazaly
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute of Life Science, University of Helsinki, FI-00014 Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, Helsinki Institute of Life Science, University of Helsinki, FI-00014 Helsinki, Finland
| | - Yuval Benjamini
- Department of Statistics and Data Science, The Hebrew University, Mount Scopus, Jerusalem 9190501, Israel
| | - Kristina Gervin
- Department of Pharmacy, PharmaTox Strategic Research Initiative, University of Oslo, 0371 Oslo, Norway
- Division of Clinical Neuroscience, Department of Research and Innovation, Oslo University Hospital, 0450 Oslo, Norway
- Pharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, 0363 Oslo, Norway
| | - Robert Lyle
- Department of Medical Genetics and Norwegian Sequencing Centre, Oslo University Hospital, 0450 Oslo, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, 0213 Oslo, Norway
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Kankaanpää A, Tolvanen A, Saikkonen P, Heikkinen A, Laakkonen EK, Kaprio J, Ollikainen M, Sillanpää E. Do epigenetic clocks provide explanations for sex differences in lifespan? A cross-sectional twin study. J Gerontol A Biol Sci Med Sci 2021; 77:1898-1906. [PMID: 34752604 PMCID: PMC9434475 DOI: 10.1093/gerona/glab337] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Indexed: 11/22/2022] Open
Abstract
Background The sex gap in life expectancy has been narrowing in Finland over the past 4–5 decades; however, on average, women still live longer than men. Epigenetic clocks are markers for biological aging which predict life span. In this study, we examined the mediating role of lifestyle factors on the association between sex and biological aging in younger and older adults. Methods Our sample consists of younger and older twins (21‒42 years, n = 1 477; 50‒76 years, n = 763) including 151 complete younger opposite-sex twin pairs (21‒30 years). Blood-based DNA methylation was used to compute epigenetic age acceleration by 4 epigenetic clocks as a measure of biological aging. Path modeling was used to study whether the association between sex and biological aging is mediated through lifestyle-related factors, that is, education, body mass index, smoking, alcohol use, and physical activity. Results In comparison to women, men were biologically older and, in general, they had unhealthier life habits. The effect of sex on biological aging was partly mediated by body mass index and, in older twins, by smoking. Sex was directly associated with biological aging and the association was stronger in older twins. Conclusions Previously reported sex differences in life span are also evident in biological aging. Declining smoking prevalence among men is a plausible explanation for the narrowing of the difference in life expectancy between the sexes. Data generated by the epigenetic clocks may help in estimating the effects of lifestyle and environmental factors on aging and in predicting aging in future generations.
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Affiliation(s)
- Anna Kankaanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Asko Tolvanen
- Methodology Center for Human Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Pirkko Saikkonen
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Eija K Laakkonen
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Elina Sillanpää
- Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.,Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, Finland
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Lymphoma-Associated Biomarkers Are Increased in Current Smokers in Twin Pairs Discordant for Smoking. Cancers (Basel) 2021; 13:cancers13215395. [PMID: 34771561 PMCID: PMC8582438 DOI: 10.3390/cancers13215395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 10/19/2021] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Smoking is associated with a moderate increased risk of Hodgkin and follicular lymphoma. To help understand why, we examined lymphoma-related biomarker levels among 134 smoking and non-smoking twins (67 pairs) ascertained from the Finnish Twin Cohort. We validated self-reported smoking history by measuring serum cotinine, a metabolite of nicotine, from previously collected frozen serum samples. In total, 27 immune biomarkers were assayed using the Luminex Multiplex platform (R & D Systems). We found that four immune response biomarkers were higher and one was lower among smoking compared to non-smoking twins. The strongest association was observed for CCL17/TARC, a biomarker elevated in Hodgkin lymphoma patients. Immune biomarker levels were similar in former smokers and non-smokers. Current smoking may increase levels of immune proteins that could partially explain the association between smoking and risk of certain lymphomas. Abstract Smoking is associated with a moderate increased risk of Hodgkin and follicular lymphoma. To understand why, we examined lymphoma-related biomarker levels among 134 smoking and non-smoking twins (67 pairs) ascertained from the Finnish Twin Cohort. Previously collected frozen serum samples were tested for cotinine to validate self-reported smoking history. In total, 27 immune biomarkers were assayed using the Luminex Multiplex platform (R & D Systems). Current and non-current smokers were defined by a serum cotinine concentration of >3.08 ng/mL and ≤3.08 ng/mL, respectively. Associations between biomarkers and smoking were assessed using linear mixed models to estimate beta coefficients and standard errors, adjusting for age, sex and twin pair as a random effect. There were 55 never smokers, 43 current smokers and 36 former smokers. CCL17/TARC, sgp130, haptoglobin, B-cell activating factor (BAFF) and monocyte chemoattractant protein-1 (MCP1) were significantly (p < 0.05) associated with current smoking and correlated with increasing cotinine concentrations (Ptrend < 0.05). The strongest association was observed for CCL17/TARC (Ptrend = 0.0001). Immune biomarker levels were similar in former and never smokers. Current smoking is associated with increased levels of lymphoma-associated biomarkers, suggesting a possible mechanism for the link between smoking and risk of these two B-cell lymphomas.
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Lindgren N, Kaprio J, Karjalainen T, Ekblad L, Helin S, Karrasch M, Teuho J, Rinne JO, Vuoksimaa E. Episodic memory and cortical amyloid pathology: PET study in cognitively discordant twin pairs. Neurobiol Aging 2021; 108:122-132. [PMID: 34607247 DOI: 10.1016/j.neurobiolaging.2021.08.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 08/23/2021] [Accepted: 08/25/2021] [Indexed: 11/15/2022]
Abstract
We studied the association between episodic memory and cortical fibrillar β-amyloid pathology within twin pairs. Using telephone-administered cognitive screening of 1415 twin pairs in a population-based older Finnish Twin Cohort study, we identified 45 (mean [SD] age 72.9 [4.0] years, 40% women) cognitively discordant same-sex twin pairs (24 dizygotic and 21 monozygotic) without neurological or psychiatric disorders other than AD or mild cognitive impairment. In-person neuropsychological testing was conducted. Cortical amyloid was measured with carbon 11-labelled Pittsburgh compound B ([11C]PiB) positron emission tomography imaging and quantified as the average standardized uptake value ratio in cortical regions affected in AD. Larger within-twin pair differences in verbal immediate (r = -0.42) and delayed free recall (r = -0.41), and visual delayed free recall (r = -0.46) were associated with larger within-twin pair differences in [11C]PiB uptake (p's < 0.01). Correlations were not significantly different in dizygotic and monozygotic pairs suggesting that the episodic memory-cortical amyloid relationship is not confounded by genetic effects. However, larger samples are needed to draw more definitive conclusions.
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Affiliation(s)
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland
| | | | - Laura Ekblad
- Turku PET Centre, University of Turku, Finland; Alzheimer Center, Amsterdam UMC, Netherlands
| | - Semi Helin
- Turku PET Centre, University of Turku, Finland
| | - Mira Karrasch
- Department of Psychology, Åbo Akademi University, Turku, Finland
| | - Jarmo Teuho
- Turku PET Centre, University of Turku, Finland; Department of Medical Physics, Turku University Hospital, Turku, Finland; Turku PET Centre, Turku University Hospital, Turku, Finland
| | - Juha O Rinne
- Turku PET Centre, University of Turku, Finland; Division of Clinical Neurosciences, Turku University Hospital, Turku, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Finland.
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van Dongen J, Gordon SD, McRae AF, Odintsova VV, Mbarek H, Breeze CE, Sugden K, Lundgren S, Castillo-Fernandez JE, Hannon E, Moffitt TE, Hagenbeek FA, van Beijsterveldt CEM, Jan Hottenga J, Tsai PC, Min JL, Hemani G, Ehli EA, Paul F, Stern CD, Heijmans BT, Slagboom PE, Daxinger L, van der Maarel SM, de Geus EJC, Willemsen G, Montgomery GW, Reversade B, Ollikainen M, Kaprio J, Spector TD, Bell JT, Mill J, Caspi A, Martin NG, Boomsma DI. Identical twins carry a persistent epigenetic signature of early genome programming. Nat Commun 2021; 12:5618. [PMID: 34584077 PMCID: PMC8479069 DOI: 10.1038/s41467-021-25583-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 07/19/2021] [Indexed: 02/08/2023] Open
Abstract
Monozygotic (MZ) twins and higher-order multiples arise when a zygote splits during pre-implantation stages of development. The mechanisms underpinning this event have remained a mystery. Because MZ twinning rarely runs in families, the leading hypothesis is that it occurs at random. Here, we show that MZ twinning is strongly associated with a stable DNA methylation signature in adult somatic tissues. This signature spans regions near telomeres and centromeres, Polycomb-repressed regions and heterochromatin, genes involved in cell-adhesion, WNT signaling, cell fate, and putative human metastable epialleles. Our study also demonstrates a never-anticipated corollary: because identical twins keep a lifelong molecular signature, we can retrospectively diagnose if a person was conceived as monozygotic twin.
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Affiliation(s)
- Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands.
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands.
| | - Scott D Gordon
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Veronika V Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | | | - Karen Sugden
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Sara Lundgren
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | | | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Catharina E M van Beijsterveldt
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Josine L Min
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Erik A Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD, USA
| | - Franziska Paul
- Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore
| | - Claudio D Stern
- Department of Cell and Developmental Biology, University College London, London, UK
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Lucia Daxinger
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - Bruno Reversade
- Institute of Molecular and Cellular Biology, A*STAR, Singapore, Singapore
- Genome Institute of Singapore, A*STAR, Singapore, Singapore
- Medical Genetics Department, KOC University, School of Medicine, Istanbul, Turkey
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Avshalom Caspi
- Department of Psychology and Neuroscience and Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nicholas G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development (AR&D) Research Institute, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
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Föhr T, Törmäkangas T, Lankila H, Viljanen A, Rantanen T, Ollikainen M, Kaprio J, Sillanpää E. The association between epigenetic clocks and physical functioning in older women: a three-year follow-up. J Gerontol A Biol Sci Med Sci 2021; 77:1569-1576. [PMID: 34543398 PMCID: PMC9373966 DOI: 10.1093/gerona/glab270] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Indexed: 01/16/2023] Open
Abstract
Background Epigenetic clocks are composite markers developed to predict chronological age or mortality risk from DNA methylation (DNAm) data. The present study investigated the associations between 4 epigenetic clocks (Horvath’s and Hannum’s DNAmAge and DNAm GrimAge and PhenoAge) and physical functioning during a 3-year follow-up. Method We studied 63- to 76-year-old women (N = 413) from the Finnish Twin Study on Aging. DNAm was measured from blood samples at baseline. Age acceleration (AgeAccel), that is, discrepancy between chronological age and DNAm age, was determined as residuals from linear model. Physical functioning was assessed under standardized laboratory conditions at baseline and at follow-up. A cross-sectional analysis was performed with path models, and a longitudinal analysis was conducted with repeated measures linear models. A nonrandom missing data analysis was performed. Results In comparison to the other clocks, GrimAgeAccel was more strongly associated with physical functioning. At baseline, GrimAgeAccel was associated with lower performance in the Timed Up and Go (TUG) test and the 6-minute walk test. At follow-up, significant associations were observed between GrimAgeAccel and lowered performance in the TUG, 6-minute and 10-m walk tests, and knee extension and ankle plantar flexion strength tests. Conclusions The DNAm GrimAge, a novel estimate of biological aging, associated with decline in physical functioning over the 3-year follow-up in older women. However, associations between chronological age and physical function phenotypes followed similar pattern. Current epigenetic clocks do not provide strong benefits in predicting the decline of physical functioning at least during a rather short follow-up period and restricted age range.
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Affiliation(s)
- Tiina Föhr
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Timo Törmäkangas
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Hannamari Lankila
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Anne Viljanen
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Elina Sillanpää
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, Jyväskylä, Finland.,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
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Piirtola M, Kaprio J, Baker TB, Piasecki TM, Piper ME, Korhonen T. The associations of smoking dependence motives with depression among daily smokers. Addiction 2021; 116:2162-2174. [PMID: 33629475 PMCID: PMC8274496 DOI: 10.1111/add.15390] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 01/16/2020] [Accepted: 12/23/2020] [Indexed: 12/14/2022]
Abstract
AIMS To investigate how strongly smoking dependence and smoking dependence motives are associated with depressive symptoms among daily smokers and if these associations are independent of measured confounders and shared familial factors. DESIGN Cross-sectional individual-based and within-pair analyses. SETTING Fourth wave of the population-based Finnish Twin Cohort conducted in 2011. PARTICIPANTS 918 daily smokers born 1945-1957 (48% men), mean age 59.5 years including 38 twin pairs discordant for depression. MEASUREMENTS Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression scale with a cut off value ≥20 for depression. Smoking dependence was assessed using the Fagerström Test for Cigarette Dependence (FTCD) and smoking dependence motives with three subscales from the multi-dimensional Brief Wisconsin Inventory of Smoking Dependence Motives (WISDM): primary dependence motives (PDM), affective enhancement (AE), and Taste. Logistic regressions, using standardized scores of independent variables and adjusted for multiple confounders with correction for sampling as twin pairs, were used in the individual-based analyses. Conditional logistic regression was used to control for shared familial factors in discordant twin pairs. FINDINGS Prevalence of depression was 18% (n = 163: 61 [14%] in men, n = 102 [22%] in women). Higher smoking dependence measured by the FTCD (OR 1.45; 95% CI 1.20, 1.75), and dependence motives measured by the PDM (1.56; 1.30, 1.87) and the AE (1.54; 1.28, 1.85) were associated with higher odds of depression. The associations remained after adjusting for individual confounders, except for neuroticism, which attenuated all associations. FTCD, PDM, and AE showed associations with depression within depression-discordant monozygotic pairs, suggesting an association independent of familial factors. CONCLUSIONS Depression appears to be associated with smoking dependence and smoking dependence motives related to heavy, automatic use and use to regulate affective states. The associations appear to be confounded or mediated by neuroticism but are independent of shared familial influences.
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Affiliation(s)
- Maarit Piirtola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, PO. Box 20, 00014 University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, PO. Box 20, 00014 University of Helsinki, Helsinki, Finland; Department of Public Health, University of Helsinki, Po. Box 20, 20014 University of Helsinki, Helsinki, Finland
| | - Timothy B. Baker
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, 1930 Monroe Street, Madison, WI 53711 -2059, United States
| | - Thomas M. Piasecki
- Department of Psychological Sciences, University of Missouri, 210 McAlester Hall, Columbia, MO 65211, United States
| | - Megan E. Piper
- Department of Medicine, University of Wisconsin School of Medicine and Public Health, 1930 Monroe Street, Madison, WI 53711 -2059, United States
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, PO. Box 20, 00014 University of Helsinki, Helsinki, Finland
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40
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Föhr T, Waller K, Viljanen A, Sanchez R, Ollikainen M, Rantanen T, Kaprio J, Sillanpää E. Does the epigenetic clock GrimAge predict mortality independent of genetic influences: an 18 year follow-up study in older female twin pairs. Clin Epigenetics 2021; 13:128. [PMID: 34120642 PMCID: PMC8201844 DOI: 10.1186/s13148-021-01112-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 06/06/2021] [Indexed: 11/22/2022] Open
Abstract
Background Epigenetic clocks are based on DNA methylation (DNAm). It has been suggested that these clocks are useable markers of biological aging and premature mortality. Because genetic factors explain variations in both epigenetic aging and mortality, this association could also be explained by shared genetic factors. We investigated the influence of genetic and lifestyle factors (smoking, alcohol consumption, physical activity, chronic diseases, body mass index) and education on the association of accelerated epigenetic aging with mortality using a longitudinal twin design. Utilizing a publicly available online tool, we calculated the epigenetic age using two epigenetic clocks, Horvath DNAmAge and DNAm GrimAge, in 413 Finnish twin sisters, aged 63–76 years, at the beginning of the 18-year mortality follow-up. Epigenetic age acceleration was calculated as the residuals from a linear regression model of epigenetic age estimated on chronological age (AAHorvath, AAGrimAge, respectively). Cox proportional hazard models were conducted for individuals and twin pairs. Results The results of the individual-based analyses showed an increased mortality hazard ratio (HR) of 1.31 (CI95: 1.13–1.53) per one standard deviation (SD) increase in AAGrimAge. The results indicated no significant associations of AAHorvath with mortality. Pairwise mortality analyses showed an HR of 1.50 (CI95: 1.02–2.20) per 1 SD increase in AAGrimAge. However, after adjusting for smoking, the HR attenuated substantially and was statistically non-significant (1.29; CI95: 0.84–1.99). Similarly, in multivariable adjusted models the HR (1.42–1.49) was non-significant. In AAHorvath, the non-significant HRs were lower among monozygotic pairs in comparison to dizygotic pairs, while in AAGrimAge there were no systematic differences by zygosity. Further, the pairwise analysis in quartiles showed that the increased within pair difference in AAGrimAge was associated with a higher all-cause mortality risk. Conclusions In conclusion, the findings suggest that DNAm GrimAge is a strong predictor of mortality independent of genetic influences. Smoking, which is known to alter DNAm levels and is built into the DNAm GrimAge algorithm, attenuated the association between epigenetic aging and mortality risk. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01112-7.
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Affiliation(s)
- Tiina Föhr
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Anne Viljanen
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Riikka Sanchez
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Miina Ollikainen
- Department of Public Health, University of Helsinki, Helsinki, Finland.,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Taina Rantanen
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Elina Sillanpää
- Faculty of Sport and Health Sciences, Gerontology Research Center (GEREC), University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland. .,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
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Sillanpää E, Heikkinen A, Kankaanpää A, Paavilainen A, Kujala UM, Tammelin TH, Kovanen V, Sipilä S, Pietiläinen KH, Kaprio J, Ollikainen M, Laakkonen EK. Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning. Clin Epigenetics 2021; 13:110. [PMID: 34001218 PMCID: PMC8127311 DOI: 10.1186/s13148-021-01094-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 04/26/2021] [Indexed: 12/14/2022] Open
Abstract
The aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition. Two independent cohorts (N = 139 and N = 47) were included, whose age span covered adulthood (23–69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation was analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package ‘MEAT’. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry. DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r = 0.617–0.824) than in muscle (r = 0.523–0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath’s clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration. Based on our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain insight into muscle tissue-specific ageing and the underlying biological pathways.
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Affiliation(s)
- Elina Sillanpää
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland. .,Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Anna Kankaanpää
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Aini Paavilainen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
| | - Tuija H Tammelin
- LIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland
| | - Vuokko Kovanen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Sarianna Sipilä
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.,Obesity Center, Endocrinology, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Eija K Laakkonen
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland
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Molecular pathways behind acquired obesity: Adipose tissue and skeletal muscle multiomics in monozygotic twin pairs discordant for BMI. CELL REPORTS MEDICINE 2021; 2:100226. [PMID: 33948567 PMCID: PMC8080113 DOI: 10.1016/j.xcrm.2021.100226] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 12/31/2020] [Accepted: 03/04/2021] [Indexed: 12/12/2022]
Abstract
Tissue-specific mechanisms prompting obesity-related development complications in humans remain unclear. We apply multiomics analyses of subcutaneous adipose tissue and skeletal muscle to examine the effects of acquired obesity among 49 BMI-discordant monozygotic twin pairs. Overall, adipose tissue appears to be more affected by excess body weight than skeletal muscle. In heavier co-twins, we observe a transcriptional pattern of downregulated mitochondrial pathways in both tissues and upregulated inflammatory pathways in adipose tissue. In adipose tissue, heavier co-twins exhibit lower creatine levels; in skeletal muscle, glycolysis- and redox stress-related protein and metabolite levels remain higher. Furthermore, metabolomics analyses in both tissues reveal that several proinflammatory lipids are higher and six of the same lipid derivatives are lower in acquired obesity. Finally, in adipose tissue, but not in skeletal muscle, mitochondrial downregulation and upregulated inflammation are associated with a fatty liver, insulin resistance, and dyslipidemia, suggesting that adipose tissue dominates in acquired obesity. Multiomics analyses of adipose tissue and skeletal muscle in BMI-discordant twins Excess body weight downregulates mitochondrial pathways in both tissues Excess body weight upregulates proinflammatory pathways in both tissues Adipose tissue alterations are associated with metabolic health in acquired obesity
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Iso-Markku P, Kaprio J, Lindgren N, Rinne JO, Vuoksimaa E. Middle-age dementia risk scores and old-age cognition: a quasi-experimental population-based twin study with over 20-year follow-up. J Neurol Neurosurg Psychiatry 2021; 92:323-330. [PMID: 33154181 PMCID: PMC7892379 DOI: 10.1136/jnnp-2020-324009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 08/25/2020] [Accepted: 10/07/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND Middle-age risk scores predict cognitive impairment, but it is not known if these associations are evident when controlling for shared genetic and environmental factors. Using two risk scores, self-report educational-occupational score and Cardiovascular Risk Factors, Aging and Dementia (CAIDE), we investigated if twins with higher middle-age dementia risk have poorer old-age cognition compared with their co-twins with lower risk. METHODS We used a population-based older Finnish Twin Cohort study with middle-age questionnaire data (n=15 169, mean age=52.0 years, SD=11.8) and old-age cognition measured via telephone interview (mean age=74.1, SD=4.1, n=4302). Between-family and within-family linear regression analyses were performed. RESULTS In between-family analyses (N=2359), higher educational-occupational score was related to better cognition (B=0.76, 95% CI 0.69 to 0.83) and higher CAIDE score was associated with poorer cognition (B=-0.73, 95% CI -0.82 to -0.65). Within twin-pair differences in educational-occupational score were significantly related to within twin-pair differences in cognition in dizygotic (DZ) pairs (B=0.78, 95% CI 0.25 to 1.31; N=338) but not in monozygotic (MZ) pairs (B=0.12, 95% CI -0.44 to 0.68; N=221). Within twin-pair differences in CAIDE score were not related to within twin-pair differences in cognition: DZ B=-0.38 (95% CI -0.90 to 0.14, N=343) and MZ B=-0.05 (95% CI -0.59 to 0.49; N=226). CONCLUSION Middle-age dementia risk scores predicted old-age cognition, but within twin-pair analyses gave little support for associations independent of shared environmental and genetic factors. Understanding genetic underpinnings of risk score-cognition associations is important for early detection of dementia and designing intervention trials.
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Affiliation(s)
- Paula Iso-Markku
- Institute for Molecular Medicine Finland, FIMM, Helsinki Institute of Life Sciences, HiLIFE, University of Helsinki, Helsinki, Finland .,HUS Diagnostic Center, Clinical Physiology and Nuclear Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, FIMM, Helsinki Institute of Life Sciences, HiLIFE, University of Helsinki, Helsinki, Finland.,Clinicum, Department of Public Health, University of Helsinki Faculty of Medicine, Helsinki, Finland
| | | | - Juha O Rinne
- Turku PET Centre, University of Turku, Turku, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, FIMM, Helsinki Institute of Life Sciences, HiLIFE, University of Helsinki, Helsinki, Finland
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44
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KANKAANPÄÄ ANNA, TOLVANEN ASKO, BOLLEPALLI SAILALITHA, LESKINEN TUIJA, KUJALA URHOM, KAPRIO JAAKKO, OLLIKAINEN MIINA, SILLANPÄÄ ELINA. Leisure-Time and Occupational Physical Activity Associates Differently with Epigenetic Aging. Med Sci Sports Exerc 2021; 53:487-495. [PMID: 32868581 PMCID: PMC7886335 DOI: 10.1249/mss.0000000000002498] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE Greater leisure-time physical activity (LTPA) associates with healthier lives, but knowledge regarding occupational physical activity (OPA) is more inconsistent. DNA methylation (DNAm) patterns capture age-related changes in different tissues. We aimed to assess how LTPA and OPA are associated with three DNAm-based epigenetic age estimates, namely, DNAm age, PhenoAge, and GrimAge. METHODS The participants were young adult (21-25 yr, n = 285) and older (55-74 yr, n = 235) twin pairs, including 16 pairs with documented long-term LTPA discordance. Genome-wide DNAm from blood samples was used to compute DNAm age, PhenoAge, and GrimAge Age acceleration (Acc), which describes the difference between chronological and epigenetic ages. Physical activity was assessed with sport, leisure-time, and work indices based on the Baecke Questionnaire. Genetic and environmental variance components of epigenetic age Acc were estimated by quantitative genetic modeling. RESULTS Epigenetic age Acc was highly heritable in young adult and older twin pairs (~60%). Sport index was associated with slower and OPA with faster DNAm GrimAge Acc after adjusting the model for sex. Genetic factors and nonshared environmental factors in common with sport index explained 1.5%-2.7% and 1.9%-3.5%, respectively, of the variation in GrimAge Acc. The corresponding proportions considering OPA were 0.4%-1.8% and 0.7%-1.8%, respectively. However, these proportions were minor (<0.5%) after adjusting the model for smoking status. CONCLUSIONS LTPA associates with slower and OPA with faster epigenetic aging. However, adjusting the models for smoking status, which may reflect the accumulation of unhealthy lifestyle habits, attenuated the associations.
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Affiliation(s)
- ANNA KANKAANPÄÄ
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - ASKO TOLVANEN
- Methodology Center for Human Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - SAILALITHA BOLLEPALLI
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
| | - TUIJA LESKINEN
- Department of Public Health, University of Turku and Turku University Hospital, Turku, FINLAND
| | - URHO M. KUJALA
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | - JAAKKO KAPRIO
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
- Department of Public Health, University of Helsinki, Helsinki, FINLAND
| | - MIINA OLLIKAINEN
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
- Department of Public Health, University of Helsinki, Helsinki, FINLAND
| | - ELINA SILLANPÄÄ
- Gerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
- Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki, Helsinki, FINLAND
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Heiskanen MA, Honkala SM, Hentilä J, Ojala R, Lautamäki R, Koskensalo K, Lietzén MS, Saunavaara V, Saunavaara J, Helmiö M, Löyttyniemi E, Nummenmaa L, Collado MC, Malm T, Lahti L, Pietiläinen KH, Kaprio J, Rinne JO, Hannukainen JC. Systemic cross-talk between brain, gut, and peripheral tissues in glucose homeostasis: effects of exercise training (CROSSYS). Exercise training intervention in monozygotic twins discordant for body weight. BMC Sports Sci Med Rehabil 2021; 13:16. [PMID: 33627179 PMCID: PMC7905681 DOI: 10.1186/s13102-021-00241-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Accepted: 02/03/2021] [Indexed: 12/13/2022]
Abstract
BACKGROUND Obesity and physical inactivity are major global public health concerns, both of which increase the risk of insulin resistance and type 2 diabetes. Regulation of glucose homeostasis involves cross-talk between the central nervous system, peripheral tissues, and gut microbiota, and is affected by genetics. Systemic cross-talk between brain, gut, and peripheral tissues in glucose homeostasis: effects of exercise training (CROSSYS) aims to gain new systems-level understanding of the central metabolism in human body, and how exercise training affects this cross-talk. METHODS CROSSYS is an exercise training intervention, in which participants are monozygotic twins from pairs discordant for body mass index (BMI) and within a pair at least the other is overweight. Twins are recruited from three population-based longitudinal Finnish twin studies, including twins born in 1983-1987, 1975-1979, and 1945-1958. The participants undergo 6-month-long exercise intervention period, exercising four times a week (including endurance, strength, and high-intensity training). Before and after the exercise intervention, comprehensive measurements are performed in Turku PET Centre, Turku, Finland. The measurements include: two positron emission tomography studies (insulin-stimulated whole-body and tissue-specific glucose uptake and neuroinflammation), magnetic resonance imaging (brain morphology and function, quantification of body fat masses and organ volumes), magnetic resonance spectroscopy (quantification of fat within heart, pancreas, liver and tibialis anterior muscle), echocardiography, skeletal muscle and adipose tissue biopsies, a neuropsychological test battery as well as biosamples from blood, urine and stool. The participants also perform a maximal exercise capacity test and tests of muscular strength. DISCUSSION This study addresses the major public health problems related to modern lifestyle, obesity, and physical inactivity. An eminent strength of this project is the possibility to study monozygotic twin pairs that share the genome at the sequence level but are discordant for BMI that is a risk factor for metabolic impairments such as insulin resistance. Thus, this exercise training intervention elucidates the effects of obesity on metabolism and whether regular exercise training is able to reverse obesity-related impairments in metabolism in the absence of the confounding effects of genetic factors. TRIAL REGISTRATION ClinicalTrials.gov , NCT03730610 . Prospectively registered 5 November 2018.
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Affiliation(s)
- Marja A Heiskanen
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
| | - Sanna M Honkala
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
| | - Jaakko Hentilä
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
| | - Ronja Ojala
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
| | | | - Kalle Koskensalo
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Martin S Lietzén
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
| | - Virva Saunavaara
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Mika Helmiö
- Division of Digestive Surgery and Urology, Turku University Hospital, Turku, Finland
| | | | - Lauri Nummenmaa
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
- Department of Psychology, University of Turku, Turku, Finland
| | - Maria C Collado
- Institute of Agrochemistry and Food Technology-National Research Council (IATA-CSIC), Valencia, Spain
- Functional Food Forum, University of Turku, Turku, Finland
| | - Tarja Malm
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Leo Lahti
- Department of Future Technologies, University of Turku, Turku, Finland
| | - Kirsi H Pietiläinen
- Obesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Abdominal Center, Obesity Center, Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Juha O Rinne
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland
- Turku PET Centre, Turku University Hospital, Turku, Finland
| | - Jarna C Hannukainen
- Turku PET Centre, University of Turku, P.O. Box 52, FIN-20521, Turku, Finland.
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Kujala UM, Palviainen T, Pesonen P, Waller K, Sillanpää E, Niemelä M, Kangas M, Vähä-Ypyä H, Sievänen H, Korpelainen R, Jämsä T, Männikkö M, Kaprio J. Polygenic Risk Scores and Physical Activity. Med Sci Sports Exerc 2020; 52:1518-1524. [PMID: 32049886 PMCID: PMC7292502 DOI: 10.1249/mss.0000000000002290] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Supplemental digital content is available in the text. Purpose Polygenic risk scores (PRS) summarize genome-wide genotype data into a single variable that produces an individual-level risk score for genetic liability. PRS has been used for prediction of chronic diseases and some risk factors. As PRS has been studied less for physical activity (PA), we constructed PRS for PA and studied how much variation in PA can be explained by this PRS in independent population samples. Methods We calculated PRS for self-reported and objectively measured PA using UK Biobank genome-wide association study summary statistics, and analyzed how much of the variation in self-reported (MET-hours per day) and measured (steps and moderate-to-vigorous PA minutes per day) PA could be accounted for by the PRS in the Finnish Twin Cohorts (FTC; N = 759–11,528) and the Northern Finland Birth Cohort 1966 (NFBC1966; N = 3263–4061). Objective measurement of PA was done with wrist-worn accelerometer in UK Biobank and NFBC1966 studies, and with hip-worn accelerometer in the FTC. Results The PRS accounted from 0.07% to 1.44% of the variation (R2) in the self-reported and objectively measured PA volumes (P value range = 0.023 to <0.0001) in the FTC and NFBC1966. For both self-reported and objectively measured PA, individuals in the highest PRS deciles had significantly (11%–28%) higher PA volumes compared with the lowest PRS deciles (P value range = 0.017 to <0.0001). Conclusions PA is a multifactorial phenotype, and the PRS constructed based on UK Biobank results accounted for statistically significant but overall small proportion of the variation in PA in the Finnish cohorts. Using identical methods to assess PA and including less common and rare variants in the construction of PRS may increase the proportion of PA explained by the PRS.
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Affiliation(s)
- Urho M Kujala
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | | | - Paula Pesonen
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, FINLAND
| | - Katja Waller
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, FINLAND
| | | | - Maisa Niemelä
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, FINLAND
| | - Maarit Kangas
- Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, FINLAND
| | - Henri Vähä-Ypyä
- The UKK Institute for Health Promotion Research, Tampere, FINLAND
| | - Harri Sievänen
- The UKK Institute for Health Promotion Research, Tampere, FINLAND
| | | | | | - Minna Männikkö
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, FINLAND
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Abstract
Background and Purpose:
One of the largest twin studies to date suggested that subarachnoid hemorrhage (SAH) is mainly of nongenetic origin, but the causal effect of environmental factors on SAH is yet unknown. We hypothesized that if only one of the twins experience fatal SAH, they do not share the most important environmental risk factor for SAH, namely smoking. If true, such finding would suggest that smoking causes SAH.
Methods:
Through the nationwide cause-of-death register, we followed 16 282 same-sex twin pairs of Finnish origin from the older Finnish Twin Cohort between 1976 and 2018 and identified all participants who died from SAH. For the baseline, we collected risk factor information about smoking, hypertension, physical activity, body mass index, alcohol consumption, and education. We classified the pairs as monozygotic, dizygotic, or of unknown zygosity. We examined the within-pair risk factor differences in the pairs discordant for SAH, that is, where one twin died from SAH and the other did not. We computed both individual (whole cohort) and pairwise (discordant pair) hazard ratios and 95% CIs.
Results:
During the 869 469 person-years of follow-up, we identified 116 discordant and 2 concordant (both died from SAH) twin pairs for fatal SAH. Overall, 25 of the discordant twin pairs were monozygotic. For the whole cohort, smoking (occasional/current) was associated with increased risk of SAH death (hazard ratio, 3.33 [CI, 2.24–4.95]) as compared with nonsmokers (never/former). In the pairwise analyses for discordant twin pairs, we found that the twin who smoked had an increased risk of fatal SAH (hazard ratio, 6.33 [CI, 1.87–21.4]) as compared with the nonsmoking twin. The association remained consistent regardless of the twin pairs’ zygosity or sex.
Conclusions:
Our results provide strong evidence for a causal, rather than associative, role of smoking in SAH.
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Affiliation(s)
- Ilari Rautalin
- Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Finland (I.R., M.K.)
| | - Miikka Korja
- Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Finland (I.R., M.K.)
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Finland (J.K.)
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Hublin C, Haasio L, Kaprio J. Changes in self-reported sleep duration with age - a 36-year longitudinal study of Finnish adults. BMC Public Health 2020; 20:1373. [PMID: 32907578 PMCID: PMC7487757 DOI: 10.1186/s12889-020-09376-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 08/11/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Sleep deprivation is often claimed to be increasingly common, but most studies show small changes in sleep duration over the last decades. Our aim was to analyze long-term patterns in self-reported sleep duration in a population-based cohort. METHODS Members of the Older Finnish Twin Cohort have responded to questionnaires in 1975 (N = 30,915 individuals, response rate 89%, mean age 36 years), 1981 (24,535, 84%, 41 years), 1990 (12,450, 77%, 44 years), and 2011 (8334, 72%, 60 years). Weibull regression models were used to model the effects of follow-up time and age simultaneously. RESULTS Sleep duration has decreased in all adult age groups and in both genders. The mean duration was in men 7.57 h in 1975 and 7.39 in 2011, and in women 7.69 and 7.37, respectively. The decrease was about 0.5 min in men and 0.9 in women per year of follow-up. In the age-group 18-34 years, mean sleep length was 7.69 h in 1975 and 7.53 in 1990. Among 35-54-year-old it was 7.57 h in 1975 and 7.34 in 2011, and in the age group of 55+ year olds 7.52 and 7.38, correspondingly. The change was largest in middle-aged group: about 23 min or about 0.6 min per year of follow-up. CONCLUSIONS There has been a slight decrease in mean sleep duration during the 36-year follow-up. Although the sleep duration was longer in 1970s and 1980s, the probable main cause for the change in this study population is the effect of aging.
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Affiliation(s)
- Christer Hublin
- Finnish Institute of Occupational Health, University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Lassi Haasio
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, PO Box 20 (Tukholmankatu 8B), Helsinki, Finland
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Ranjit A, Latvala A, Kinnunen TH, Kaprio J, Korhonen T. Depressive symptoms predict smoking cessation in a 20-year longitudinal study of adult twins. Addict Behav 2020; 108:106427. [PMID: 32361366 DOI: 10.1016/j.addbeh.2020.106427] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 03/13/2020] [Accepted: 04/02/2020] [Indexed: 01/01/2023]
Abstract
Depression has been suggested to hinder smoking cessation, especially when co-occurring with nicotine dependence. The study aimed to examine the longitudinal association of depressive symptoms with smoking cessation among daily smokers. The study utilized adult Finnish twin cohort where 1438 daily smokers (mean age: 38.3, range: 33-45) in 1990 were re-examined for their smoking status in 2011. We assessed baseline depressive symptoms with the Beck Depression Inventory, and the self-reported smoking status at follow-up. The methods included multinomial logistic regression and time to event analyses, adjusted for multiple covariates (age, sex, marital status, social class, heavy drinking occasions, and health status) and smoking heaviness at baseline assessed by cigarettes per day (CPD). Additionally, within-twin-pair analyses were conducted. Results indicated that moderate/severe depressive symptoms at baseline were associated with a lower likelihood of smoking cessation two decades later. Adjusting for covariates, those with moderate/severe depressive symptoms (vs. no/minimal depressive symptoms) had 46% lower likelihood of quitting (relative risk ratio, RRR = 0.54, 95% CI: 0.30-0.96). After including CPD, the association of depressive symptoms with smoking cessation attenuated modestly (RRR = 0.62, 95% CI: 0.34-1.12). Further, time to event analysis for quitting year since baseline yielded similar findings. In the within-pair analysis, depressive symptoms were not associated with quitting smoking. The results suggest that reporting more depressive symptoms is associated with a lower likelihood of smoking cessation during a 20-year period. The baseline amount of smoking and familial factors partly explain the observed association. Smoking cessation programs should monitor depressive symptoms.
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Plasma cell-free DNA methylation marks for episodic memory impairment: a pilot twin study. Sci Rep 2020; 10:14192. [PMID: 32843700 PMCID: PMC7447764 DOI: 10.1038/s41598-020-71239-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 08/05/2020] [Indexed: 11/23/2022] Open
Abstract
Decline in episodic memory performance usually causes the first clinical symptoms of Alzheimer’s disease. At present, Alzheimer’s disease can only be diagnosed at a very late stage when neurodegeneration and cognitive impairment is already irreversible. New early disease markers are needed for earlier and more efficient Alzheimer’s disease intervention. To identify early disease markers, we implemented a genome-wide bisulphite sequencing method for the analysis of plasma cell-free DNA methylation profiles and compared differences associated with episodic memory performance in Finnish twin pairs. A noticeable amount of cell-free DNA was present in plasma, however, the amounts as well as the genomic coverage of these fragments varied substantially between individuals. We found no significant markers associated with episodic memory performance in the twins’ plasma cell-free DNA methylation profiles. Furthermore, our results indicate that due to the low genomic coverage of cell-free DNA fragments and the variety in these fragments between individuals, the implemented genome-wide bisulphite sequencing method is not optimal for comparing cell-free DNA methylation differences between large groups of individuals.
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