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Kerkelä M, Gissler M, Nordström T, Ukkola O, Veijola J. Association between participation in the Northern Finland Birth Cohorts and cardiometabolic disorders. Ann Med 2023; 55:1123-1133. [PMID: 36947119 PMCID: PMC10035958 DOI: 10.1080/07853890.2023.2186478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND We studied the association between participation in the longitudinal follow-up study and cardiometabolic disorders in two longitudinal studies which started prospectively in the antenatal period: the Northern Finland Cohort 1966 (NFBC1966) and the Northern Finland Birth Cohort 1986 (NFBC1986). Both birth cohorts have been followed up since birth with multiple follow-ups including questionnaires, and clinical examinations. METHODS The NFBC studies were compared to comparison cohorts of individuals who were born in the same area as the study cohorts, but in different years. The data for the comparison cohort were obtained from registers. The cumulative incidence rates of hospital-treated cardiometabolic disorders were calculated for study and comparison cohorts covering the age of 7-50 years in NFBC1966 and the age of 0-29 years in NFBC1986. Cardiometabolic-related causes of death were analysed in NFBC1966 and the comparison cohort from the age of 0-50 years. The analysed cardiometabolic disorders were diabetes mellitus, coronary artery disease, hyperlipidaemia, obesity, hypertension, and cerebrovascular disorders. The risk ratio (RR) with 95% confidence intervals (CI) was calculated by sex. RESULTS In NFBC1966, no differences in cumulative incidences of cardiometabolic disorders or cardiometabolic-related deaths compared to the comparison cohort were found. Male members of NFBC1986 had decreased risk of obesity (RR: 0.45, 95% CI: 0.27-0.75) and any cardiometabolic disorders (RR: 0.75, 95% CI: 0.59-0.95) compared to the comparison cohort. CONCLUSIONS The results suggest that participation in the NFBC1986 may have a weak positive health effect among men. Agreement to follow-up studies focusing on diet, substance use, and physical activity, may slightly decrease the incident risk of cardiometabolic disorders in the study population.KEY MESSAGESEven mild interventions, such as follow-up studies in the prospective follow-up studies, might affect participants' behaviour and consequently the incidence of cardiometabolic disordersThe fact that follow-up itself might affect the study population in terms of risk factors, has to be taken into account when estimating the representativeness of the followed population.
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Affiliation(s)
- Martta Kerkelä
- Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
| | - Mika Gissler
- Department of Knowledge Brokers, Finnish Institute for Health and Welfare, Helsinki, Finland
- Research Centre for Child Psychiatry, University of Turku, Turku, Finland
- Academic Primary Health Care Centre, Region Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institute, Stockholm, Sweden
| | - Tanja Nordström
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
- Research Unit of Population Health, University of Oulu, Oulu, Finland
- Medical Research Center, University Hospital and University of Oulu, Oulu, Finland
| | - Olavi Ukkola
- Medical Research Center, University Hospital and University of Oulu, Oulu, Finland
- Research Unit of Internal Medicine, University of Oulu, Oulu, Finland
| | - Juha Veijola
- Research Unit of Clinical Medicine, University of Oulu, Oulu, Finland
- Medical Research Center, University Hospital and University of Oulu, Oulu, Finland
- Department of Psychiatry, University Hospital of Oulu, Oulu, Finland
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2
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Association between participation in the Northern Finland Birth Cohort 1966 study and use of psychiatric care services. PLoS One 2023; 18:e0282714. [PMID: 36867634 PMCID: PMC9983849 DOI: 10.1371/journal.pone.0282714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 02/22/2023] [Indexed: 03/04/2023] Open
Abstract
AIMS In most population-based epidemiological follow-up studies the aim is not to intervene in the life of the participants. Although the idea is not to intervene, being a member of the longitudinal follow-up study and studies conducted during follow-up may affect the target population. A population-based study including mental health enquiries might reduce the unmet need for psychiatric treatment by motivating people to seek treatment for their psychiatric ill-health. We examined the use of psychiatric care services in the population born in the year 1966 in Northern Finland, of whom 96.3% are participants in the prospective Northern Finland Birth Cohort 1966 (NFBC1966). METHODS As a study cohort we used people born in 1966 in Northern Finland (n = 11 447). The comparison cohort included all the people born in the years 1965 and 1967 in the same geographical area (n = 23 339). The follow-up period was from age 10 to 50 years. The outcome measure was the use of psychiatric care services, which was analysed using Cox Proportional Hazard regression and Zero-Truncated Negative Binomial Regression. RESULTS People born in 1966 in Northern Finland did not differ from those born in 1965 and 1967 in terms of the outcome measure. CONCLUSIONS We found no association between participation in an epidemiological follow-up study and the use of psychiatric care services. The NFBC1966 may be regarded as a representative at the population level in terms of psychiatric outcomes despite the personal follow-up of the birth cohort. The associations of participation in epidemiological follow-up studies have previously been under-examined, and the results need to be replicated.
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Jain VG, Monangi N, Zhang G, Muglia LJ. Genetics, epigenetics, and transcriptomics of preterm birth. Am J Reprod Immunol 2022; 88:e13600. [PMID: 35818963 PMCID: PMC9509423 DOI: 10.1111/aji.13600] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 06/13/2022] [Accepted: 07/06/2022] [Indexed: 11/29/2022] Open
Abstract
Preterm birth contributes significantly to neonatal mortality and morbidity. Despite its global significance, there has only been limited progress in preventing preterm birth. Spontaneous preterm birth (sPTB) results from a wide variety of pathological processes. Although many non-genetic risk factors influence the timing of gestation and labor, compelling evidence supports the role of substantial genetic and epigenetic influences and their interactions with the environment contributing to sPTB. To investigate a common and complex disease such as sPTB, various approaches such as genome-wide association studies, whole-exome sequencing, transcriptomics, and integrative approaches combining these with other 'omics studies have been used. However, many of these studies were typically small or focused on a single ethnicity or geographic region with limited data, particularly in populations at high risk for sPTB, or lacked a robust replication. These studies found many genes involved in the inflammation and immunity-related pathways that may affect sPTB. Recent studies also suggest the role of epigenetic modifications of gene expression by the environmental signals as a potential contributor to the risk of sPTB. Future genetic studies of sPTB should continue to consider the contributions of both maternal and fetal genomes as well as their interaction with the environment.
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Affiliation(s)
- Viral G. Jain
- Division of Neonatology, Department of Pediatrics, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Nagendra Monangi
- Division of Neonatology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children’s Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Ge Zhang
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children’s Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
| | - Louis J. Muglia
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children’s Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America
- Burroughs Wellcome Fund, Research Triangle Park, North Carolina, USA
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Bianchi ME, Restrepo JM. Low Birthweight as a Risk Factor for Non-communicable Diseases in Adults. Front Med (Lausanne) 2022; 8:793990. [PMID: 35071274 PMCID: PMC8770864 DOI: 10.3389/fmed.2021.793990] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 12/08/2021] [Indexed: 11/18/2022] Open
Abstract
According to studies undertaken over the past 40 years, low birthweight (LBW) is not only a significant predictor of perinatal death and morbidity, but also increases the risk of chronic non-communicable diseases (NCDs) in adulthood. The purpose of this paper is to summarize the research on LBW as a risk factor for NCDs in adults. The Barker hypothesis was based on the finding that adults with an LBW or an unhealthy intrauterine environment, as well as a rapid catch-up, die due to NCDs. Over the last few decades, terminology such as thrifty genes, fetal programming, developmental origins of health and disease (DOHaD), and epigenetic factors have been coined. The most common NCDs include cardiovascular disease, diabetes mellitus type 2 (DMT2), hypertension (HT), dyslipidemia, proteinuria, and chronic kidney disease (CKD). Studies in mothers who experienced famine and those that solely reported birth weight as a risk factor for mortality support the concept. Although the etiology of NCD is unknown, Barry Brenner explained the notion of a low glomerular number (nGlom) in LBW children, followed by the progression to hyperfiltration as the physiopathologic etiology of HT and CKD in adults based on Guyton's renal physiology work. Autopsies of several ethnic groups have revealed anatomopathologic evidence in fetuses and adult kidneys. Because of the renal reserve, demonstrating renal function in proportion to renal volume in vivo is more difficult in adults. The greatest impact of these theories can be seen in pediatrics and obstetrics practice.
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Affiliation(s)
- Maria Eugenia Bianchi
- Laboratory Physiology, Department Basic Sciences, Institute School of Medicine, National Northeast University, Corrientes, Argentina
| | - Jaime M Restrepo
- Department of Pediatrics, Pediatric Nephrology Service, Icesi University, Valle del Lili, Cali, Colombia.,Fundación Valle del Lili, Cali, Colombia
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Nordström T, Miettunen J, Auvinen J, Ala-Mursula L, Keinänen-Kiukaanniemi S, Veijola J, Järvelin MR, Sebert S, Männikkö M. Cohort Profile: 46 years of follow-up of the Northern Finland Birth Cohort 1966 (NFBC1966). Int J Epidemiol 2022; 50:1786-1787j. [PMID: 34999878 PMCID: PMC8743124 DOI: 10.1093/ije/dyab109] [Citation(s) in RCA: 87] [Impact Index Per Article: 43.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/06/2021] [Indexed: 01/17/2023] Open
Grants
- GRANTS NO. 65354, 24000692 University of Oulu
- GRANTS NO. 2/97, 8/97, 24301140 Oulu University Hospital
- GRANTS NO. 23/251/97, 160/97, 190/97 National research funding via City of Oulu, Ministry of Health and Social Affairs
- GRANT NO. 54121 National Institute for Health and Welfare, Helsinki
- GRANTS NO. 50621, 54231 Regional Institute of Occupational Health
- GRANT NO. 539/2010 A31592 ERDF European Regional Development Fund
- PREcisE project and ZonMw The Netherlands no. P75416
- H2020-633595 DynaHealth, H2020-733206 LifeCycle, H2020-824989 EUCANCONNECT, H2020-873749 LongITools, H2020-848158 EarlyCause, the JPI HDHL
- National research funding via City of Oulu
- Ministry of Health and Social Affairs
- National Institute for Health and Welfare
- European Commission research and innovation program Horizon 2020 under the following projects: DynaHealth
- LifeCycle
- EUCANCONNECT
- LongITools
- EarlyCause
- Programming Initiative Healthy Diet Healthy Life (PREcisE project - ZonMw the Netherlands
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Affiliation(s)
- Tanja Nordström
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jouko Miettunen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Oulunkaari Health Center, Ii, Finland
| | - Leena Ala-Mursula
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Sirkka Keinänen-Kiukaanniemi
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Healthcare and Social Services of Selänne, Pyhäjärvi, Finland
- Healthcare and Social Services of City of Oulu, Oulu, Finland
| | - Juha Veijola
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
- Department of Psychiatry, Research Unit of Clinical Neuroscience, University of Oulu, Oulu, Finland
- Department of Psychiatry, University Hospital of Oulu, Oulu, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Sylvain Sebert
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Minna Männikkö
- Northern Finland Birth Cohorts, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
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Palaniswamy S, Abass K, Rysä J, Odland JØ, Grimalt JO, Rautio A, Järvelin MR. Non-occupational exposure to pesticides and health markers in general population in Northern Finland: Differences between sexes. ENVIRONMENT INTERNATIONAL 2021; 156:106766. [PMID: 34271428 DOI: 10.1016/j.envint.2021.106766] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/02/2021] [Accepted: 07/06/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Occupational exposure to pesticides has been reported among general population worldwide. However, little is known about the associations between non-occupational exposure to pesticides, and biological markers of health and their response by sex. OBJECTIVES We aimed to assess the associations between non-occupational overall pesticide exposure, length of exposure and specific pesticides reported with 35 biological markers of health representing cardiometabolic, haematological, lung function, sex hormones, liver and kidney function profiles, and vitamin D in Finnish cohort. METHODS 31-year cross-sectional examination of the Northern Finland Birth Cohort 1966 provided blood samples for biomarker measurements in 1997-1998. Number of subjects varied between 2361 and 5037 for given exposures and certain outcome associations. Multivariable regression analyses were performed to examine associations between overall pesticide exposure (OPE), length of pesticide exposure in months (PEM), in years (PEY), and specific pesticides use (PEU) or not with cardiometabolic [SBP, DBP, TC, LDL, HDL, triglycerides, fasting glucose, insulin, HOMA-IR, HOMA-B, HOMA-S, hs-CRP], hematological [WBC, RBC, Hb, HCT, MCV, MCH, MCHC, platelets], lung function (FVC, FEV1), sex hormones [luteinizing hormone (LH), testosterone (TT), sex-hormone binding globulin (SHBG)], liver and kidney function profiles [total protein, albumin, globulin, ALP, ALT, GGT, urea, creatinine], and vitamin D adjusting for sex, BMI, socioeconomic position (SEP) and season of pesticide use. RESULTS This cohort study on up to 5037 adults with non-occupational OPE, PEM, PEY and PEU differed by sex and SEP. In regression analyses, all the exposures were positively associated with total cholesterol and low-density lipoprotein cholesterol, and PEU was negatively associated with high-density lipoprotein cholesterol in females. OPE and PEM were positively associated with haematocrit in females and PEU with platelets in males. PEU was negatively associated with mean corpuscular haemoglobin. OPE and PEM were positively associated with LH in males. OPE was negatively associated with total protein and albumin in males. DISCUSSION In Finnish young adults, non-occupational overall pesticide exposure, length of exposure and specific pesticides were associated with multiple biological markers of health. The biological markers seem to be indicative of adverse effects of pesticides and warrant for further studies to replicate the findings and determine the underlying mechanisms.
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Affiliation(s)
- Saranya Palaniswamy
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.
| | - Khaled Abass
- Arctic Health, Faculty of Medicine, University of Oulu, Oulu, Finland; Department of Pesticides, Menoufia University, Menoufia, Egypt
| | - Jaana Rysä
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Jon Øyvind Odland
- NTNU The Norwegian University of Science and Technology, Trondheim, Norway; Department of General Hygiene, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
| | - Joan O Grimalt
- Institute of Environmental Assessment and Water Research (IDAEA), Spanish Council for Scientific Research (CSIC), Barcelona, Catalonia, Spain
| | - Arja Rautio
- Arctic Health, Faculty of Medicine, University of Oulu, Oulu, Finland; Thule Institute, University of Arctic, University of Oulu, Oulu, Finland.
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Unit of Primary Care, Oulu University Hospital, Oulu, Finland; MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, United Kingdom.
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7
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Espin-Garcia O, Craiu RV, Bull SB. Two-phase sample selection strategies for design and analysis in post-genome-wide association fine-mapping studies. Stat Med 2021; 40:6792-6817. [PMID: 34596256 PMCID: PMC9293221 DOI: 10.1002/sim.9211] [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: 04/01/2020] [Revised: 09/13/2021] [Accepted: 09/14/2021] [Indexed: 11/08/2022]
Abstract
Post-GWAS analysis, in many cases, focuses on fine-mapping targeted genetic regions discovered at GWAS-stage; that is, the aim is to pinpoint potential causal variants and susceptibility genes for complex traits and disease outcomes using next-generation sequencing (NGS) technologies. Large-scale GWAS cohorts are necessary to identify target regions given the typically modest genetic effect sizes. In this context, two-phase sampling design and analysis is a cost-reduction technique that utilizes data collected during phase 1 GWAS to select an informative subsample for phase 2 sequencing. The main goal is to make inference for genetic variants measured via NGS by efficiently combining data from phases 1 and 2. We propose two approaches for selecting a phase 2 design under a budget constraint. The first method identifies sampling fractions that select a phase 2 design yielding an asymptotic variance covariance matrix with certain optimal characteristics, for example, smallest trace, via Lagrange multipliers (LM). The second relies on a genetic algorithm (GA) with a defined fitness function to identify exactly a phase 2 subsample. We perform comprehensive simulation studies to evaluate the empirical properties of the proposed designs for a genetic association study of a quantitative trait. We compare our methods against two ranked designs: residual-dependent sampling and a recently identified optimal design. Our findings demonstrate that the proposed designs, GA in particular, can render competitive power in combined phase 1 and 2 analysis compared with alternative designs while preserving type 1 error control. These results are especially evident under the more practical scenario where design values need to be defined a priori and are subject to misspecification. We illustrate the proposed methods in a study of triglyceride levels in the North Finland Birth Cohort of 1966. R code to reproduce our results is available at github.com/egosv/TwoPhase_postGWAS.
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Affiliation(s)
- Osvaldo Espin-Garcia
- Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Radu V Craiu
- Department of Statistical Sciences, Faculty of Arts and Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Shelley B Bull
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
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8
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Monangi N, Xu H, Khanam R, Khan W, Deb S, Pervin J, Price JT, Kennedy SH, Al Mahmud A, Fan Y, Le TQ, Care A, Landero JA, Combs GF, Belling E, Chappell J, Kong F, Lacher C, Ahmed S, Chowdhury NH, Rahman S, Kabir F, Nisar I, Hotwani A, Mehmood U, Nizar A, Khalid J, Dhingra U, Dutta A, Ali S, Aftab F, Juma MH, Rahman M, Vwalika B, Musonda P, Ahmed T, Islam MM, Ashorn U, Maleta K, Hallman M, Goodfellow L, Gupta JK, Alfirevic A, Murphy S, Rand L, Ryckman KK, Murray JC, Bahl R, Litch JA, Baruch-Gravett C, Alfirevic Z, Ashorn P, Baqui A, Hirst J, Hoyo C, Jehan F, Jelliffe-Pawlowski LL, Rahman A, Roth DE, Sazawal S, Stringer J, Zhang G, Muglia L. Association of maternal prenatal selenium concentration and preterm birth: a multicountry meta-analysis. BMJ Glob Health 2021; 6:bmjgh-2021-005856. [PMID: 34518202 PMCID: PMC8438754 DOI: 10.1136/bmjgh-2021-005856] [Citation(s) in RCA: 6] [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: 03/29/2021] [Accepted: 08/04/2021] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Selenium (Se), an essential trace mineral, has been implicated in preterm birth (PTB). We aimed to determine the association of maternal Se concentrations during pregnancy with PTB risk and gestational duration in a large number of samples collected from diverse populations. METHODS Gestational duration data and maternal plasma or serum samples of 9946 singleton live births were obtained from 17 geographically diverse study cohorts. Maternal Se concentrations were determined by inductively coupled plasma mass spectrometry analysis. The associations between maternal Se with PTB and gestational duration were analysed using logistic and linear regressions. The results were then combined using fixed-effect and random-effect meta-analysis. FINDINGS In all study samples, the Se concentrations followed a normal distribution with a mean of 93.8 ng/mL (SD: 28.5 ng/mL) but varied substantially across different sites. The fixed-effect meta-analysis across the 17 cohorts showed that Se was significantly associated with PTB and gestational duration with effect size estimates of an OR=0.95 (95% CI: 0.9 to 1.00) for PTB and 0.66 days (95% CI: 0.38 to 0.94) longer gestation per 15 ng/mL increase in Se concentration. However, there was a substantial heterogeneity among study cohorts and the random-effect meta-analysis did not achieve statistical significance. The largest effect sizes were observed in UK (Liverpool) cohort, and most significant associations were observed in samples from Malawi. INTERPRETATION While our study observed statistically significant associations between maternal Se concentration and PTB at some sites, this did not generalise across the entire cohort. Whether population-specific factors explain the heterogeneity of our findings warrants further investigation. Further evidence is needed to understand the biologic pathways, clinical efficacy and safety, before changes to antenatal nutritional recommendations for Se supplementation are considered.
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Affiliation(s)
- Nagendra Monangi
- Division of Neonatology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Huan Xu
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Rasheda Khanam
- International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Waqasuddin Khan
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Saikat Deb
- Center for Public Health Kinetics, New Delhi, India
- Research Division, Public Health Laboratory, Center for Public Health Kinetics, Chake Chake, Tanzania
| | - Jesmin Pervin
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Dhaka District, Bangladesh
| | - Joan T Price
- Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | - Stephen H Kennedy
- INTERBIO-21st Study Consortium, Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK
| | - Abdullah Al Mahmud
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Dhaka District, Bangladesh
| | - Yuemei Fan
- Center for Child Health Research, Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
| | - Thanh Q Le
- Benh Vien Tu Du, Ho Chi Minh City, Viet Nam
| | - Angharad Care
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK
| | - Julio A Landero
- Department of Chemistry, University of Cincinnati, Cincinnati, Ohio, USA
| | - Gerald F Combs
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Medford, Massachusetts, USA
| | - Elizabeth Belling
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Joanne Chappell
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Fansheng Kong
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Criag Lacher
- Grand Forks Human Nutrition Research Center, USDA ARS, Grand Forks, North Dakota, USA
| | | | | | | | - Furqan Kabir
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Imran Nisar
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Aneeta Hotwani
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Usma Mehmood
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Ambreen Nizar
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Javairia Khalid
- Biorepository and Omics Research Group, Department of Pediatrics and Child Health, Faculty of Health Sciences, Medical College, The Aga Khan University, Karachi, Sindh, Pakistan
| | - Usha Dhingra
- Center for Public Health Kinetics, New Delhi, India
| | - Arup Dutta
- Center for Public Health Kinetics, New Delhi, India
| | - Said Ali
- Research Division, Public Health Laboratory, Center for Public Health Kinetics, Chake Chake, Tanzania
| | - Fahad Aftab
- Research Division, Public Health Laboratory, Center for Public Health Kinetics, Chake Chake, Tanzania
| | - Mohammed Hamad Juma
- Research Division, Public Health Laboratory, Center for Public Health Kinetics, Chake Chake, Tanzania
| | - Monjur Rahman
- Nutritional and Clinical Services Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Dhaka District, Bangladesh
| | | | - Patrick Musonda
- School of Public Health, University of Zambia, Lusaka, Zambia
| | | | - Md Munirul Islam
- Nutrition and Clinical Services Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Bangladesh
| | - Ulla Ashorn
- University of Tampere, Tampere, Pirkanmaa, Finland
| | - Kenneth Maleta
- School of Public Health, University of Malawi College of Medicine, Blantyre, Malawi
| | - Mikko Hallman
- Medical Research Centre Oulu, PEDEGO Research Unit, University of Oulu, Oulu, Pohjois-Pohjanmaa, Finland
| | - Laura Goodfellow
- Department of Women's and Children's Health, University of Liverpool, Liverpool, Merseyside, UK
| | - Juhi K Gupta
- Department of Women's and Children's Health, University of Liverpool, Liverpool, Merseyside, UK
| | - Ana Alfirevic
- Department of Women's and Children's Health, University of Liverpool, Liverpool, Merseyside, UK
| | - Susan Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina, USA
| | - Larry Rand
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of California San Francisco, San Francisco, California, USA
| | - Kelli K Ryckman
- Department of Epidemiology, University of Iowa, Iowa City, Iowa, USA
| | - Jeffrey C Murray
- Department of Pediatrics, University of Iowa, Iowa City, Iowa, USA
| | - Rajiv Bahl
- Department of Medicine, World Health Organization, Geneva, Switzerland
| | - James A Litch
- Global Alliance to Prevent Prematurity and Stillbirth, Lynnwood, Washington, USA
| | | | - Zarko Alfirevic
- Division of Perinatal Medicine, University of Liverpool, Liverpool, UK
| | - Per Ashorn
- Center for Child Health Research, Faculty of Medicine and Health Technology, University of Tampere, Tampere, Pirkanmaa, Finland
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland
| | - Abdullah Baqui
- International Center for Maternal and Newborn Health, Department of International Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jane Hirst
- Nuffield Department of Women's and Reproductive Health, University of Oxford, Oxford, UK
| | - Cathrine Hoyo
- Department of Biological Sciences and Center for Human Health and the Enivironment, North Carolina State University, Raleigh, North Carolina, USA
| | - Fyezah Jehan
- Department of Pediatrics and Child Health, Aga Khan University, Karachi, Pakistan
| | - Laura L Jelliffe-Pawlowski
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA
| | - Anisur Rahman
- Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research Bangladesh, Dhaka, Dhaka District, Bangladesh
| | - Daniel E Roth
- Department of Paediatrics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Sunil Sazawal
- Center for Public Health Kinetics, New Delhi, India
- Research Division, Public Health Laboratory, Center for Public Health Kinetics, Chake Chake, Tanzania
| | - Jeffrey Stringer
- Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ge Zhang
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Louis Muglia
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center and March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, Ohio, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Burroughs Wellcome Fund, Research Triangle Park, North Carolina, USA
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9
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Auvinen J, Tapio J, Karhunen V, Kettunen J, Serpi R, Dimova EY, Gill D, Soininen P, Tammelin T, Mykkänen J, Puukka K, Kähönen M, Raitoharju E, Lehtimäki T, Ala-Korpela M, Raitakari OT, Keinänen-Kiukaanniemi S, Järvelin MR, Koivunen P. Systematic evaluation of the association between hemoglobin levels and metabolic profile implicates beneficial effects of hypoxia. SCIENCE ADVANCES 2021; 7:eabi4822. [PMID: 34261659 PMCID: PMC8279517 DOI: 10.1126/sciadv.abi4822] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 06/01/2021] [Indexed: 05/22/2023]
Abstract
Activation of the hypoxia-inducible factor (HIF) pathway reprograms energy metabolism. Hemoglobin (Hb) is the main carrier of oxygen. Using its normal variation as a surrogate measure for hypoxia, we explored whether lower Hb levels could lead to healthier metabolic profiles in mice and humans (n = 7175) and used Mendelian randomization (MR) to evaluate potential causality (n = 173,480). The results showed evidence for lower Hb levels being associated with lower body mass index, better glucose tolerance and other metabolic profiles, lower inflammatory load, and blood pressure. Expression of the key HIF target genes SLC2A4 and Slc2a1 in skeletal muscle and adipose tissue, respectively, associated with systolic blood pressure in MR analyses and body weight, liver weight, and adiposity in mice. Last, manipulation of murine Hb levels mediated changes to key metabolic parameters. In conclusion, low-end normal Hb levels may be favorable for metabolic health involving mild chronic activation of the HIF response.
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Affiliation(s)
- Juha Auvinen
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, 90014 Oulu, Finland
- Medical Research Center, Oulu University Hospital and University of Oulu, 90220 Oulu, Finland
| | - Joona Tapio
- Biocenter Oulu, 90014 Oulu, Finland
- Faculty of Biochemistry and Molecular Medicine, Oulu Center for Cell-Matrix Research, University of Oulu, 90014 Oulu, Finland
| | - Ville Karhunen
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, 90014 Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, W2 1PG London, UK
- Research Unit of Mathematical Sciences, University of Oulu, 90014 Oulu, Finland
| | - Johannes Kettunen
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, 90014 Oulu, Finland
- Biocenter Oulu, 90014 Oulu, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, 90014 Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, 70210 Kuopio, Finland
| | - Raisa Serpi
- Biocenter Oulu, 90014 Oulu, Finland
- Faculty of Biochemistry and Molecular Medicine, Oulu Center for Cell-Matrix Research, University of Oulu, 90014 Oulu, Finland
| | - Elitsa Y Dimova
- Biocenter Oulu, 90014 Oulu, Finland
- Faculty of Biochemistry and Molecular Medicine, Oulu Center for Cell-Matrix Research, University of Oulu, 90014 Oulu, Finland
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, W2 1PG London, UK
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George's, University of London, London, UK
| | - Pasi Soininen
- Computational Medicine, Faculty of Medicine, University of Oulu, 90014 Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, 70210 Kuopio, Finland
| | - Tuija Tammelin
- LIKES Research Center for Physical Activity and Health, 40700 Jyväskylä, Finland
| | - Juha Mykkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520 Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Katri Puukka
- NordLab Oulu, Medical Research Center Oulu, Oulu University Hospital and Department of Clinical Chemistry, University of Oulu, 90014 Oulu, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, Tampere, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Faculty of Medicine and Health Technology, Finnish Cardiovascular Research Center - Tampere, Tampere University, Tampere, Finland
| | - Mika Ala-Korpela
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, 90014 Oulu, Finland
- Biocenter Oulu, 90014 Oulu, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, 90014 Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, 70210 Kuopio, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520 Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20520 Turku, Finland
| | - Sirkka Keinänen-Kiukaanniemi
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, 90014 Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, 90220 Oulu, Finland
| | - Marjo-Riitta Järvelin
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, 90014 Oulu, Finland.
- Biocenter Oulu, 90014 Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, 90220 Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, Middlesex UB8 3PH, UK
| | - Peppi Koivunen
- Biocenter Oulu, 90014 Oulu, Finland.
- Faculty of Biochemistry and Molecular Medicine, Oulu Center for Cell-Matrix Research, University of Oulu, 90014 Oulu, Finland
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10
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Zhang Y, Liang J, Liu Q, Fan X, Xu C, Gu A, Zhao W, Hang D. Birth Weight and Adult Obesity Index in Relation to the Risk of Hypertension: A Prospective Cohort Study in the UK Biobank. Front Cardiovasc Med 2021; 8:637437. [PMID: 34222359 PMCID: PMC8245673 DOI: 10.3389/fcvm.2021.637437] [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: 12/03/2020] [Accepted: 05/12/2021] [Indexed: 11/21/2022] Open
Abstract
Objectives: To investigate the association between birth weight and the risk of hypertension, and to examine the interaction between birth weight and the adult obesity index. Methods: We included 199,893 participants who had birth weight data and no history of hypertension at baseline (2006–2010) from the UK Biobank. A multivariate cubic regression spline was used to visually explore the dose-response relationship. Multivariate Cox proportional hazard regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: We observed a nonlinear inverse association between birth weight and hypertension. The risk for hypertension decreased as birth weight increased up to approximately 3.80 kg. Compared with the participants with the fourth quintile of birth weight (3.43–3.80 kg), those with the first quartile of birth weight (<2.88 kg) were associated with a 25% higher risk of hypertension [HR 1.25; 95% CI (1.18–1.32)]. In addition, the participants with birth weight <2.88 kg and body mass index ≥30 kg/m2 had the highest risk [HR 3.54; 95% CI (3.16–3.97); p for interaction <0.0001], as compared with those with birth weight between 3.43–3.80 kg and body mass index between 18.5–25.0 kg/m2. These associations were largely consistent in the stratified and sensitivity analyses. Conclusion: Our findings indicate that lower birth weight is nonlinearly correlated with higher risk of hypertension, and birth weight between 3.43–3.80 kg might represent an intervention threshold. Moreover, lower birth weight may interact with adult obesity to significantly increase hypertension risk.
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Affiliation(s)
- Yi Zhang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing, China
| | - Jingjia Liang
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing, China
| | - Qian Liu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing, China
| | - Xikang Fan
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Cheng Xu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing, China
| | - Aihua Gu
- State Key Laboratory of Reproductive Medicine, Institute of Toxicology, Nanjing Medical University, Nanjing, China
| | - Wei Zhao
- Jinling Hospital Department of Reproductive Medical Center affiliated School of Medicine, Nanjing University, Nanjing, China
| | - Dong Hang
- Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China
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11
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Demandt JAF, van Kuijk K, Theelen TL, Marsch E, Heffron SP, Fisher EA, Carmeliet P, Biessen EAL, Sluimer JC. Whole-Body Prolyl Hydroxylase Domain (PHD) 3 Deficiency Increased Plasma Lipids and Hematocrit Without Impacting Plaque Size in Low-Density Lipoprotein Receptor Knockout Mice. Front Cell Dev Biol 2021; 9:664258. [PMID: 34055796 PMCID: PMC8160238 DOI: 10.3389/fcell.2021.664258] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 04/23/2021] [Indexed: 12/19/2022] Open
Abstract
Background and aims: Atherosclerosis is an important cause of clinical cardiovascular events. Atherosclerotic plaques are hypoxic, and reoxygenation improves plaque phenotype. Central players in hypoxia are hypoxia inducible factors (HIF) and their regulators, HIF-prolyl hydroxylase (PHD) isoforms 1, 2, and 3. PHD inhibitors, targeting all three isoforms, are used to alleviate anemia in chronic kidney disease. Likewise, whole-body PHD1 and PHD2ko ameliorate hypercholesterolemia and atherogenesis. As the effect of whole-body PHD3 is unknown, we investigated the effects of germline whole-body PHD3ko on atherosclerosis. Approach and Results: To initiate hypercholesterolemia and atherosclerosis low-density lipoprotein receptor knockout (LDLrko) and PHD3/LDLr double knockout (PHD3dko), mice were fed a high-cholesterol diet. Atherosclerosis and hypoxia marker pimonidazole were analyzed in aortic roots and brachiocephalic arteries. In contrast to earlier reports on PHD1- and PHD2-deficient mice, a small elevation in the body weight and an increase in the plasma cholesterol and triglyceride levels were observed after 10 weeks of diet. Dyslipidemia might be explained by an increase in hepatic mRNA expression of Cyp7a1 and fatty acid synthase, while lipid efflux of PHD3dko macrophages was comparable to controls. Despite dyslipidemia, plaque size, hypoxia, and phenotype were not altered in the aortic root or in the brachiocephalic artery of PHD3dko mice. Additionally, PHD3dko mice showed enhanced blood hematocrit levels, but no changes in circulating, splenic or lymphoid immune cell subsets. Conclusion: Here, we report that whole-body PHD3dko instigated an unfavorable lipid profile and increased hematocrit, in contrast to other PHD isoforms, yet without altering atherosclerotic plaque development.
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Affiliation(s)
- Jasper A. F. Demandt
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center (MUMC), Maastricht, Netherlands
| | - Kim van Kuijk
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center (MUMC), Maastricht, Netherlands
- Institute of Experimental Medicine and Systems Biology, RWTH Aachen University, Aachen, Germany
| | - Thomas L. Theelen
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center (MUMC), Maastricht, Netherlands
| | - Elke Marsch
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center (MUMC), Maastricht, Netherlands
| | - Sean P. Heffron
- Center for the Prevention of Cardiovascular Disease, Department of Medicine, Grossman School of Medicine, New York University, New York, NY, United States
| | - Edward A. Fisher
- Center for the Prevention of Cardiovascular Disease, Department of Medicine, Grossman School of Medicine, New York University, New York, NY, United States
| | - Peter Carmeliet
- Laboratory of Angiogenesis and Vascular Metabolism, Department of Oncology, KU Leuven, Leuven, Belgium
- Laboratory of Angiogenesis and Vascular Metabolism, VIB Center for Cancer Biology, Leuven, Belgium
| | - Erik A. L. Biessen
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center (MUMC), Maastricht, Netherlands
- Institute for Molecular Cardiovascular Research, RWTH Aachen University, Aachen, Germany
| | - Judith C. Sluimer
- Department of Pathology, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University Medical Center (MUMC), Maastricht, Netherlands
- BHF Centre for Cardiovascular Sciences (CVS), University of Edinburgh, Edinburgh, United Kingdom
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12
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Pinot de Moira A, Haakma S, Strandberg-Larsen K, van Enckevort E, Kooijman M, Cadman T, Cardol M, Corpeleijn E, Crozier S, Duijts L, Elhakeem A, Eriksson JG, Felix JF, Fernández-Barrés S, Foong RE, Forhan A, Grote V, Guerlich K, Heude B, Huang RC, Järvelin MR, Jørgensen AC, Mikkola TM, Nader JLT, Pedersen M, Popovic M, Rautio N, Richiardi L, Ronkainen J, Roumeliotaki T, Salika T, Sebert S, Vinther JL, Voerman E, Vrijheid M, Wright J, Yang TC, Zariouh F, Charles MA, Inskip H, Jaddoe VWV, Swertz MA, Nybo Andersen AM. The EU Child Cohort Network's core data: establishing a set of findable, accessible, interoperable and re-usable (FAIR) variables. Eur J Epidemiol 2021; 36:565-580. [PMID: 33884544 PMCID: PMC8159791 DOI: 10.1007/s10654-021-00733-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 02/14/2021] [Indexed: 10/24/2022]
Abstract
The Horizon2020 LifeCycle Project is a cross-cohort collaboration which brings together data from multiple birth cohorts from across Europe and Australia to facilitate studies on the influence of early-life exposures on later health outcomes. A major product of this collaboration has been the establishment of a FAIR (findable, accessible, interoperable and reusable) data resource known as the EU Child Cohort Network. Here we focus on the EU Child Cohort Network's core variables. These are a set of basic variables, derivable by the majority of participating cohorts and frequently used as covariates or exposures in lifecourse research. First, we describe the process by which the list of core variables was established. Second, we explain the protocol according to which these variables were harmonised in order to make them interoperable. Third, we describe the catalogue developed to ensure that the network's data are findable and reusable. Finally, we describe the core data, including the proportion of variables harmonised by each cohort and the number of children for whom harmonised core data are available. EU Child Cohort Network data will be analysed using a federated analysis platform, removing the need to physically transfer data and thus making the data more accessible to researchers. The network will add value to participating cohorts by increasing statistical power and exposure heterogeneity, as well as facilitating cross-cohort comparisons, cross-validation and replication. Our aim is to motivate other cohorts to join the network and encourage the use of the EU Child Cohort Network by the wider research community.
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Affiliation(s)
- Angela Pinot de Moira
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
| | - Sido Haakma
- Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Katrine Strandberg-Larsen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Esther van Enckevort
- Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marjolein Kooijman
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Tim Cadman
- Population Health Science, Bristol Medical School, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2PS, UK
| | - Marloes Cardol
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Eva Corpeleijn
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sarah Crozier
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Applied Research Collaboration Wessex, Southampton Science Park, Innovation Centre, 2 Venture Road, Chilworth, Southampton, SO16 7NP, UK
| | - Liesbeth Duijts
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Ahmed Elhakeem
- Population Health Science, Bristol Medical School, Bristol, BS8 2BN, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, BS8 2PS, UK
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore
- Singapore Institute for Clinical Sciences (SICS), Agency for Science and Technology (A*STAR), Singapore, Singapore
| | - Janine F Felix
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Sílvia Fernández-Barrés
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Rachel E Foong
- Telethon Kids Institute, Perth, WA, Australia
- School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia
| | - Anne Forhan
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, LMU University Hospital Munich, Munich, Germany
| | - Kathrin Guerlich
- Division of Metabolic and Nutritional Medicine, Department of Pediatrics, Dr. von Hauner Children's Hospital, LMU University Hospital Munich, Munich, Germany
| | - Barbara Heude
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | | | - Marjo-Riitta Järvelin
- Faculty of Medicine, Center for Life-Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Anne Cathrine Jørgensen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Tuija M Mikkola
- Folkhälsan Research Center, Helsinki, Finland
- Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johanna L T Nader
- Department of Genetics and Bioinformatics, Division of Health Data and Digitalisation, Norwegian Institute of Public Health, Oslo, Norway
| | - Marie Pedersen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Maja Popovic
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Nina Rautio
- Faculty of Medicine, Center for Life-Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Justiina Ronkainen
- Faculty of Medicine, Center for Life-Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
| | - Theano Roumeliotaki
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Crete, Greece
| | - Theodosia Salika
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
| | - Sylvain Sebert
- Faculty of Medicine, Center for Life-Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
| | - Johan L Vinther
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Ellis Voerman
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Tiffany C Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Faryal Zariouh
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | - Marie-Aline Charles
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
- ELFE Joint Unit, French Institute for Demographic Studies (Ined), French Institute for Medical Research and Health (INSERM), French Blood Agency, Aubervilliers, France
| | - Hazel Inskip
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Vincent W V Jaddoe
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Morris A Swertz
- Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anne-Marie Nybo Andersen
- Section for Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
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13
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Islam MT, Siraj MS, Hassan MZ, Nayem M, Chandra Nag D, Islam MA, Islam R, Mazumder T, Choudhury SR, Siddiquee AT. Influence of height on blood pressure and hypertension among Bangladeshi adults. INTERNATIONAL JOURNAL CARDIOLOGY HYPERTENSION 2021; 5:100028. [PMID: 33447757 PMCID: PMC7803027 DOI: 10.1016/j.ijchy.2020.100028] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 03/16/2020] [Accepted: 04/07/2020] [Indexed: 12/30/2022]
Abstract
Background Recent studies have reported that height is inversely associated with blood pressure and hypertension. However, there is lack of comprehensive findings from Bangladesh in this regard. Objective The purpose of this study was to explore the association between height and blood pressure in a Bangladeshi population. Setting Rural and urban sites from seven divisions of Bangladesh. Participants Participants were 7932 males and females (aged ≥35 years) evaluated in the 2011 Bangladesh Demographic Health Survey. Participants (n = 7647) who had complete height, weight, systolic and diastolic blood pressure (SBP and DBP) measurements and non-missing medication history, were included in the analysis. Methods Hypertension was defined as an SBP over 140 mmHg or/and a DBP over 90 mmHg, or current use of antihypertensive medication. Difference between SBP and DBP was calculated to get pulse pressure (PP). Multivariate linear and logistic regression models were used. Results PP decreased linearly with increasing height among males (−0.11, P < 0.05) and females (−0.19, P < 0.05) after adjusting for age, BMI, living region, type of occupation, wealth index, and highest level of education. SBP decreased linearly with increasing height among only females (−0.14, P < 0.05), after adjusting for age, BMI, living region, type of occupation, wealth index, and highest level of education. No association was found between quartiles of height and prevalence of hypertension. Conclusions Height was found to be inversely associated with pulse pressure in both sexes. Studies with longitudinal design are needed to investigate the association between shortness with blood pressure and hypertension.
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Affiliation(s)
| | | | | | | | | | | | | | - Tapas Mazumder
- International Centre for Diarrheal Disease Research, Bangladesh
| | | | - Ali Tanweer Siddiquee
- International Centre for Diarrheal Disease Research, Bangladesh.,Shiga University of Medical Science, Otsu, Japan
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14
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Dior UP, Karavani G, Bursztyn M, Paltiel O, Calderon-Margalit R, Friedlander Y, Youssim I, Manor O, Hochner H. Birth Weight and Maternal Body Size as Determinants of Blood Pressure at Age 17: Results from the Jerusalem Perinatal Study Cohort. Matern Child Health J 2020; 25:162-171. [PMID: 33247825 DOI: 10.1007/s10995-020-03096-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2020] [Indexed: 11/27/2022]
Abstract
OBJECTIVES To investigate the effect of birth weight (BW) and maternal pre-pregnancy BMI (mBMI) on blood pressure (BP) in adolescence. METHODS A Population-based cohort of 11,729 births in Jerusalem during 1974-1976, with archival data on maternal and birth characteristics was performed. Measurements at age 17 were assessed and linear regression models were used to evaluate the associations of birth characteristics with BP outcomes. RESULTS BW was inversely associated with both systolic (SBP) and diastolic (DBP) BP at age 17 (SBP: B = - 0.829, p = 0.002; DBP: B = - 0.397, p = 0.033). The interaction term between BW and weight at age 17 was significant for DBP (p = 0.017) and pulse pressure (p = 0.005). mBMI yielded significant positive associations with BP, independent of BW. CONCLUSIONS FOR PRACTICE Our findings indicate that there are at least two distinct pathways linking early life characteristics with subsequent BP: Intrauterine growth, as reflected by BW and other genetic or environmental factors, reflected by mBMI and maternal education, contribute to offspring adolescent BP. These results warrant replication in other birth cohorts and underline the need to explore specific mechanisms that account for these associations.
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Affiliation(s)
- Uri P Dior
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel. .,Department of Obstetrics and Gynecology, Hadassah Medical Center and Hebrew University-Hadassah Medical School, P.O. Box 12000, 91120, Jerusalem, Israel.
| | - Gilad Karavani
- Department of Obstetrics and Gynecology, Hadassah Medical Center and Hebrew University-Hadassah Medical School, P.O. Box 12000, 91120, Jerusalem, Israel
| | - Michael Bursztyn
- Hypertension Unit, Department of Medicine, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Ora Paltiel
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Ronit Calderon-Margalit
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Yechiel Friedlander
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Iaroslav Youssim
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Orly Manor
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - Hagit Hochner
- Braun School of Public Health, The Hebrew University-Hadassah Medical Center, Jerusalem, Israel
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15
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Li Y, Wang F, Wu M, Ma S. Integrative functional linear model for genome-wide association studies with multiple traits. Biostatistics 2020; 23:574-590. [PMID: 33040145 DOI: 10.1093/biostatistics/kxaa043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 06/30/2020] [Accepted: 09/12/2020] [Indexed: 11/14/2022] Open
Abstract
In recent biomedical research, genome-wide association studies (GWAS) have demonstrated great success in investigating the genetic architecture of human diseases. For many complex diseases, multiple correlated traits have been collected. However, most of the existing GWAS are still limited because they analyze each trait separately without considering their correlations and suffer from a lack of sufficient information. Moreover, the high dimensionality of single nucleotide polymorphism (SNP) data still poses tremendous challenges to statistical methods, in both theoretical and practical aspects. In this article, we innovatively propose an integrative functional linear model for GWAS with multiple traits. This study is the first to approximate SNPs as functional objects in a joint model of multiple traits with penalization techniques. It effectively accommodates the high dimensionality of SNPs and correlations among multiple traits to facilitate information borrowing. Our extensive simulation studies demonstrate the satisfactory performance of the proposed method in the identification and estimation of disease-associated genetic variants, compared to four alternatives. The analysis of type 2 diabetes data leads to biologically meaningful findings with good prediction accuracy and selection stability.
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Affiliation(s)
- Yang Li
- Center For Applied Statistics, School Of Statistics, And Statistical Consulting Center, Renmin University Of China, Beijing 100872, China
| | - Fan Wang
- Center For Applied Statistics, School Of Statistics, And Statistical Consulting Center, Renmin University Of China, Beijing 100872, China
| | - Mengyun Wu
- School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China
| | - Shuangge Ma
- Department of Biostatistics, Yale School of Public Health, New Haven 06520, USA
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16
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Cardiovascular risk factors in those born preterm - systematic review and meta-analysis. J Dev Orig Health Dis 2020; 12:539-554. [PMID: 33028453 DOI: 10.1017/s2040174420000914] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Emerging evidence demonstrates a link between preterm birth (PTB) and later life cardiovascular disease (CVD). We conducted a systematic review and meta-analysis to compare conventional CVD risk factors between those born preterm and at term. PubMed, CINAHL, SCOPUS, and EMBASE databases were searched. The review protocol is registered in PROSPERO (CRD42018095005). CVD risk factors including systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index, lipid profile, blood glucose, and fasting insulin among those born preterm (<37 weeks' gestation) were compared with those born at term (≥37 weeks' gestation). Subgroup analyses based on gender, age, gestational at birth (<32 weeks' gestation and <28 weeks' gestation), and PTB associated with small for gestational age or average for gestational age were also performed. Fifty-six studies provided data on 308,987 individuals. Being born preterm was associated with 3.26 mmHg (95% confidence interval [CI] 2.08 to 4.44) higher mean SBP and 1.32 mmHg (95% CI: 0.61 to 2.04) higher mean DBP compared to being born at term. Subgroup analyses demonstrated that SBP was higher among (a) preterm compared to term groups from early adolescence until adulthood; (b) females born preterm but not among males born preterm compared to term controls; and (c) those born at <32 weeks or <28 weeks compared to term. Our meta-analyses demonstrate higher SBP and DBP among those born preterm compared to term. The difference in SBP is evident from early adolescence until adulthood.
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17
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Rauschert S, Melton PE, Heiskala A, Karhunen V, Burdge G, Craig JM, Godfrey KM, Lillycrop K, Mori TA, Beilin LJ, Oddy WH, Pennell C, Järvelin MR, Sebert S, Huang RC. Machine Learning-Based DNA Methylation Score for Fetal Exposure to Maternal Smoking: Development and Validation in Samples Collected from Adolescents and Adults. ENVIRONMENTAL HEALTH PERSPECTIVES 2020; 128:97003. [PMID: 32930613 PMCID: PMC7491641 DOI: 10.1289/ehp6076] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Revised: 08/20/2020] [Accepted: 08/28/2020] [Indexed: 05/19/2023]
Abstract
BACKGROUND Fetal exposure to maternal smoking during pregnancy is associated with the development of noncommunicable diseases in the offspring. Maternal smoking may induce such long-term effects through persistent changes in the DNA methylome, which therefore hold the potential to be used as a biomarker of this early life exposure. With declining costs for measuring DNA methylation, we aimed to develop a DNA methylation score that can be used on adolescent DNA methylation data and thereby generate a score for in utero cigarette smoke exposure. METHODS We used machine learning methods to create a score reflecting exposure to maternal smoking during pregnancy. This score is based on peripheral blood measurements of DNA methylation (Illumina's Infinium HumanMethylation450K BeadChip). The score was developed and tested in the Raine Study with data from 995 white 17-y-old participants using 10-fold cross-validation. The score was further tested and validated in independent data from the Northern Finland Birth Cohort 1986 (NFBC1986) (16-y-olds) and 1966 (NFBC1966) (31-y-olds). Further, three previously proposed DNA methylation scores were applied for comparison. The final score was developed with 204 CpGs using elastic net regression. RESULTS Sensitivity and specificity values for the best performing previously developed classifier ("Reese Score") were 88% and 72% for Raine, 87% and 61% for NFBC1986 and 72% and 70% for NFBC1966, respectively; corresponding figures using the elastic net regression approach were 91% and 76% (Raine), 87% and 75% (NFBC1986), and 72% and 78% for NFBC1966. CONCLUSION We have developed a DNA methylation score for exposure to maternal smoking during pregnancy, outperforming the three previously developed scores. One possible application of the current score could be for model adjustment purposes or to assess its association with distal health outcomes where part of the effect can be attributed to maternal smoking. Further, it may provide a biomarker for fetal exposure to maternal smoking. https://doi.org/10.1289/EHP6076.
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Affiliation(s)
- Sebastian Rauschert
- Telethon Kids Institute, University of Western Australia, Nedlands, Perth, Western Australia, Australia
| | - Phillip E. Melton
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Perth, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin University, Perth, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Graham Burdge
- Institute of Developmental Sciences, University of Southampton, Faculty of Medicine, Southampton, UK
| | - Jeffrey M. Craig
- Centre for Molecular and Medical Research, School of Medicine, Deakin University, Geelong, Victoria, Australia
- Molecular Epidemiology, Murdoch Children’s Research Institute, Parkville, Australia
| | - Keith M. Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Karen Lillycrop
- Biological Sciences, Faculty of Natural and Environmental Sciences, University of Southampton, Southampton, Hampshire, UK
| | - Trevor A. Mori
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Perth, Western Australia
| | - Lawrence J. Beilin
- Medical School, Royal Perth Hospital Unit, University of Western Australia, Perth, Western Australia
| | - Wendy H. Oddy
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, Australia
| | - Craig Pennell
- School of Medicine and Public Health, University of Newcastle, Newcastle, New South Wales, Australia
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Metabolism, Digestion and Reproduction, Genomic Medicine, Imperial College London, London, UK
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Nedlands, Perth, Western Australia, Australia
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18
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Jaddoe VWV, Felix JF, Andersen AMN, Charles MA, Chatzi L, Corpeleijn E, Donner N, Elhakeem A, Eriksson JG, Foong R, Grote V, Haakma S, Hanson M, Harris JR, Heude B, Huang RC, Inskip H, Järvelin MR, Koletzko B, Lawlor DA, Lindeboom M, McEachan RRC, Mikkola TM, Nader JLT, de Moira AP, Pizzi C, Richiardi L, Sebert S, Schwalber A, Sunyer J, Swertz MA, Vafeiadi M, Vrijheid M, Wright J, Duijts L. The LifeCycle Project-EU Child Cohort Network: a federated analysis infrastructure and harmonized data of more than 250,000 children and parents. Eur J Epidemiol 2020; 35:709-724. [PMID: 32705500 PMCID: PMC7387322 DOI: 10.1007/s10654-020-00662-z] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 07/04/2020] [Indexed: 12/15/2022]
Abstract
Early life is an important window of opportunity to improve health across the full lifecycle. An accumulating body of evidence suggests that exposure to adverse stressors during early life leads to developmental adaptations, which subsequently affect disease risk in later life. Also, geographical, socio-economic, and ethnic differences are related to health inequalities from early life onwards. To address these important public health challenges, many European pregnancy and childhood cohorts have been established over the last 30 years. The enormous wealth of data of these cohorts has led to important new biological insights and important impact for health from early life onwards. The impact of these cohorts and their data could be further increased by combining data from different cohorts. Combining data will lead to the possibility of identifying smaller effect estimates, and the opportunity to better identify risk groups and risk factors leading to disease across the lifecycle across countries. Also, it enables research on better causal understanding and modelling of life course health trajectories. The EU Child Cohort Network, established by the Horizon2020-funded LifeCycle Project, brings together nineteen pregnancy and childhood cohorts, together including more than 250,000 children and their parents. A large set of variables has been harmonised and standardized across these cohorts. The harmonized data are kept within each institution and can be accessed by external researchers through a shared federated data analysis platform using the R-based platform DataSHIELD, which takes relevant national and international data regulations into account. The EU Child Cohort Network has an open character. All protocols for data harmonization and setting up the data analysis platform are available online. The EU Child Cohort Network creates great opportunities for researchers to use data from different cohorts, during and beyond the LifeCycle Project duration. It also provides a novel model for collaborative research in large research infrastructures with individual-level data. The LifeCycle Project will translate results from research using the EU Child Cohort Network into recommendations for targeted prevention strategies to improve health trajectories for current and future generations by optimizing their earliest phases of life.
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Affiliation(s)
- Vincent W V Jaddoe
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, The Generation R Study Group, (Na 29-18), PO Box 2040, 3000 CA, Rotterdam, The Netherlands. .,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
| | - Janine F Felix
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, The Generation R Study Group, (Na 29-18), PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Anne-Marie Nybo Andersen
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Marie-Aline Charles
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France.,ELFE Joint Unit, French Institute for Demographic Studies (Ined), French Institute for Medical Research and Health (INSERM), French Blood Agency, Aubervilliers, France
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Eva Corpeleijn
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nina Donner
- Concentris Research Management GmbH, Fürstenfeldbruck, Germany
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland.,Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore.,Singapore Institute for Clinical Sciences (SICS), Agency for Science and Technology (A*STAR), Singapore, Singapore
| | - Rachel Foong
- Telethon Kids Institute, Perth, WA, Australia.,School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia
| | - Veit Grote
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU, Munich, Germany
| | - Sido Haakma
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, The Netherlands
| | - Mark Hanson
- Institute of Developmental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.,NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Jennifer R Harris
- Centre for Fertility and Health, The Norwegian Institute of Public Health, Oslo, Norway.,Division of Health Data and Digitalization, Norwegian Institute of Public Health, Oslo, Norway
| | - Barbara Heude
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, Paris, France
| | | | - Hazel Inskip
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK.,MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
| | - Marjo-Riitta Järvelin
- Center for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.,Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
| | - Berthold Koletzko
- Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU, Munich, Germany
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Maarten Lindeboom
- Department of Economics, VU University Amsterdam, Amsterdam, The Netherlands
| | - Rosemary R C McEachan
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | | | - Johanna L T Nader
- Department of Genetics and Bioinformatics, Division of Health Data and Digitalisation, Norwegian Institute of Public Health, Oslo, Norway
| | - Angela Pinot de Moira
- Section of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Costanza Pizzi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Sylvain Sebert
- Center for Life-Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Ameli Schwalber
- Concentris Research Management GmbH, Fürstenfeldbruck, Germany
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Morris A Swertz
- University of Groningen, University Medical Center Groningen, Genomics Coordination Center, Groningen, The Netherlands.,Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Marina Vafeiadi
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Crete, Greece
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Liesbeth Duijts
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, The Generation R Study Group, (Na 29-18), PO Box 2040, 3000 CA, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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19
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Korpela N, Kaikkonen K, Auvinen J, Tulppo MP, Junttila J, Perkiömäki J, Järvelin MR, Huikuri HV, Kiviniemi AM. Early Growth Patterns and Cardiac Structure and Function at Midlife: Northern Finland 1966 Birth Cohort Study. J Pediatr 2020; 221:151-158.e1. [PMID: 32446475 DOI: 10.1016/j.jpeds.2020.03.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 02/29/2020] [Accepted: 03/03/2020] [Indexed: 12/16/2022]
Abstract
OBJECTIVES To evaluate the influence of early growth patterns that have previously been associated with later cardiometabolic risk on cardiac left ventricular (LV) structure and function in midlife. STUDY DESIGN A subpopulation of the Northern Finland Birth Cohort 1966 took part in follow-up, including echocardiography (n = 1155) at the age of 46 years. Body mass index (BMI) growth curves were modeled based on frequent anthropometric measurements in childhood. Age and BMI at adiposity peak (n = 482, mean age 9.0 months) and at adiposity rebound (n = 586, mean age 5.8 years) were determined. Results are reported as unstandardized beta (β) or OR with 95% CIs for 1 SD increase in early growth variable. RESULTS Earlier adiposity rebound was associated with increased LV mass index (β = -4.10 g/m2 (-6.9, -1.3); P = .004) and LV end-diastolic volume index (β = -2.36 mL/m2 (-3.9, -0.84); P = .002) as well as with eccentric LV hypertrophy (OR 0.54 [0.38, 0.77]; P = .001) in adulthood in males. BMI at adiposity rebound was directly associated with LV mass index (β = 2.33 g/m2 [0.80, 3.9]; P = .003). Higher BMI at both adiposity peak and at adiposity rebound were associated with greater LV end-diastolic volume index (β = 1.47 mL/m2; [0.51, 2.4], β = 1.28 mL/m2 [0.41, 2.2], respectively) and also with eccentric LV hypertrophy (OR 1.41 [1.10, 1.82], OR 1.53 [1.23, 1.91], respectively) and LV concentric remodeling (OR 1.38 [1.02, 1.87], OR 1.40 [1.06, 1.83], respectively) in adulthood (P < .05 for all). These relationships were only partly mediated by adult BMI. CONCLUSIONS Early growth patterns in infancy and childhood contribute to cardiac structure at midlife.
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Affiliation(s)
- Nelli Korpela
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Kari Kaikkonen
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Unit of Primary Health Care, Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Mikko P Tulppo
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juhani Junttila
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juha Perkiömäki
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Unit of Primary Health Care, Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Department of Life Sciences, College of Health and Life Sciences, Brunel University London, United Kingdom
| | - Heikki V Huikuri
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Antti M Kiviniemi
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
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20
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Palaniswamy S, Gill D, De Silva NM, Lowry E, Jokelainen J, Karhu T, Mutt SJ, Dehghan A, Sliz E, Chasman DI, Timonen M, Viinamäki H, Keinänen-Kiukaanniemi S, Hyppönen E, Herzig KH, Sebert S, Järvelin MR. Could vitamin D reduce obesity-associated inflammation? Observational and Mendelian randomization study. Am J Clin Nutr 2020; 111:1036-1047. [PMID: 32232398 PMCID: PMC7198294 DOI: 10.1093/ajcn/nqaa056] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 03/02/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Obesity is associated with inflammation but the role of vitamin D in this process is not clear. OBJECTIVES We aimed to assess the associations between serum 25-hydroxyvitamin D [25(OH)D], BMI, and 16 inflammatory biomarkers, and to assess the role of vitamin D as a potential mediator in the association between higher BMI and inflammation. METHODS Northern Finland Birth Cohort 1966 (NFBC1966) 31-y data on 3586 individuals were analyzed to examine the observational associations between BMI, 25(OH)D, and 16 inflammatory biomarkers. Multivariable regression analyses and 2-sample regression-based Mendelian randomization (MR) mediation analysis were performed to assess any role of vitamin D in mediating a causal effect of BMI on inflammatory biomarkers [soluble intercellular adhesion molecule 1 (sICAM-1), high sensitivity C-reactive protein (hs-CRP), and α1-acid glycoprotein (AGP)] for which observational associations were detected. For MR, genome-wide association study summary results ranging from 5163 to 806,834 individuals were used for biomarkers, 25(OH)D, and BMI. Findings were triangulated with a literature review of vitamin D supplementation trials. RESULTS In NFBC1966, mean BMI (kg/m2) was 24.8 (95% CI: 24.7, 25.0) and mean 25(OH)D was 50.3 nmol/L (95% CI: 49.8, 50.7 nmol/L). Inflammatory biomarkers correlated as 4 independent clusters: interleukins, adhesion molecules, acute-phase proteins, and chemokines. BMI was positively associated with 9 inflammatory biomarkers and inversely with 25(OH)D (false discovery rate < 0.05). 25(OH)D was inversely associated with sICAM-1, hs-CRP, and AGP, which were positively associated with BMI. The MR analyses showed causal association of BMI on these 3 inflammatory biomarkers. There was no observational or MR evidence that circulating 25(OH)D concentrations mediated the association between BMI and these 3 inflammatory markers. Review of randomized controlled trials (RCTs) supported our findings showing no impact of vitamin D supplementation on inflammatory biomarkers. CONCLUSIONS The findings from our observational study and causal MR analyses, together with data from RCTs, do not support a beneficial role of vitamin D supplementation on obesity-related inflammation.
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Affiliation(s)
- Saranya Palaniswamy
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Biocenter Oulu, University of Oulu, Oulu, Finland,Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, United Kingdom,Address correspondence to SP (e-mail: )
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - N Maneka De Silva
- Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Estelle Lowry
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jari Jokelainen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Toni Karhu
- Biocenter Oulu, University of Oulu, Oulu, Finland,Institute of Biomedicine, Medical Research Center, University of Oulu, and Oulu University Hospital, Oulu, Finland
| | - Shivaprakash J Mutt
- Biocenter Oulu, University of Oulu, Oulu, Finland,Institute of Biomedicine, Medical Research Center, University of Oulu, and Oulu University Hospital, Oulu, Finland
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, United Kingdom
| | - Eeva Sliz
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Biocenter Oulu, University of Oulu, Oulu, Finland,Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Daniel I Chasman
- Preventive Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Markku Timonen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Heimo Viinamäki
- Institute of Clinical Medicine/Psychiatry, University of Eastern Finland, Kuopio, Finland; and Department of Psychiatry, Kuopio University Hospital, Kuopio, Finland
| | - Sirkka Keinänen-Kiukaanniemi
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Elina Hyppönen
- Australian Centre for Precision Health, South Australian Cancer Research Institute, University of South Australia, Adelaide, Australia,South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Karl-Heinz Herzig
- Institute of Biomedicine, Medical Research Center, University of Oulu, and Oulu University Hospital, Oulu, Finland,Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - Sylvain Sebert
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Biocenter Oulu, University of Oulu, Oulu, Finland,Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, London, United Kingdom
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland,Biocenter Oulu, University of Oulu, Oulu, Finland,Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, United Kingdom,Unit of Primary Care, Oulu University Hospital, Oulu, Finland,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, United Kingdom,Address correspondence to M-RJ (e-mail: )
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21
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Bjerregaard LG, Wasenius N, Nedelec R, Gjærde LK, Ängquist L, Herzig KH, Jensen GB, Mortensen EL, Osler M, Overvad K, Skaaby T, Tjønneland A, Sørensen TIA, Järvelin MR, Eriksson JG, Sebert S, Baker JL. Possible Modifiers of the Association Between Change in Weight Status From Child Through Adult Ages and Later Risk of Type 2 Diabetes. Diabetes Care 2020; 43:1000-1007. [PMID: 32139388 DOI: 10.2337/dc19-1726] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 02/04/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We investigated the association between changes in weight status from childhood through adulthood and subsequent type 2 diabetes risks and whether educational attainment, smoking, and leisure time physical activity (LTPA) modify this association. RESEARCH DESIGN AND METHODS Using data from 10 Danish and Finnish cohorts including 25,283 individuals, childhood BMI at 7 and 12 years was categorized as normal or high using age- and sex-specific cutoffs (<85th or ≥85th percentile). Adult BMI (20-71 years) was categorized as nonobese or obese (<30.0 or ≥30.0 kg/m2, respectively). Associations between BMI patterns and type 2 diabetes (989 women and 1,370 men) were analyzed using Cox proportional hazards regressions and meta-analysis techniques. RESULTS Compared with individuals with a normal BMI at 7 years and without adult obesity, those with a high BMI at 7 years and adult obesity had higher type 2 diabetes risks (hazard ratio [HR]girls 5.04 [95% CI 3.92-6.48]; HRboys 3.78 [95% CI 2.68-5.33]). Individuals with a high BMI at 7 years but without adult obesity did not have a higher risk (HRgirls 0.74 [95% CI 0.52-1.06]; HRboys 0.93 [95% CI 0.65-1.33]). Education, smoking, and LTPA were associated with diabetes risks but did not modify or confound the associations with BMI changes. Results for 12 years of age were similar. CONCLUSIONS A high BMI in childhood was associated with higher type 2 diabetes risks only if individuals also had obesity in adulthood. These associations were not influenced by educational and lifestyle factors, indicating that BMI is similarly related to the risk across all levels of these factors.
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Affiliation(s)
- Lise G Bjerregaard
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Niko Wasenius
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland
| | - Rozenn Nedelec
- Centre for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Line K Gjærde
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Lars Ängquist
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark.,Novo Nordisk Foundation Center for Basic Metabolic Research, Human Genomics and Metagenomics in Metabolism, University of Copenhagen, Copenhagen, Denmark
| | - Karl-Heinz Herzig
- Research Unit of Biomedicine, Department of Physiology and Biocenter Oulu, Medical Research Center, University of Oulu, Oulu University Hospital, Oulu, Finland.,Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - Gorm B Jensen
- The Copenhagen City Heart Study, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Erik L Mortensen
- Department of Public Health and Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
| | - Merete Osler
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark.,Section of Epidemiology, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Tea Skaaby
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark.,Section of Environmental Health, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Human Genomics and Metagenomics in Metabolism, University of Copenhagen, Copenhagen, Denmark.,Section of Epidemiology, Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marjo-Riitta Järvelin
- Centre for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, U.K.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, U.K
| | - Johan G Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland.,Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.,Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore
| | - Sylvain Sebert
- Centre for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, London, U.K
| | - Jennifer L Baker
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark.,Novo Nordisk Foundation Center for Basic Metabolic Research, Human Genomics and Metagenomics in Metabolism, University of Copenhagen, Copenhagen, Denmark
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22
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Leal LG, Hoggart C, Jarvelin MR, Herzig KH, Sternberg MJE, David A. A polygenic biomarker to identify patients with severe hypercholesterolemia of polygenic origin. Mol Genet Genomic Med 2020; 8:e1248. [PMID: 32307928 PMCID: PMC7284038 DOI: 10.1002/mgg3.1248] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 02/24/2020] [Accepted: 03/02/2020] [Indexed: 12/11/2022] Open
Abstract
Background Severe hypercholesterolemia (HC, LDL‐C > 4.9 mmol/L) affects over 30 million people worldwide. In this study, we validated a new polygenic risk score (PRS) for LDL‐C. Methods Summary statistics from the Global Lipid Genome Consortium and genotype data from two large populations were used. Results A 36‐SNP PRS was generated using data for 2,197 white Americans. In a replication cohort of 4,787 Finns, the PRS was strongly associated with the LDL‐C trait and explained 8% of its variability (p = 10–41). After risk categorization, the risk of having HC was higher in the high‐ versus low‐risk group (RR = 4.17, p < 1 × 10−7). Compared to a 12‐SNP LDL‐C raising score (currently used in the United Kingdom), the PRS explained more LDL‐C variability (8% vs. 6%). Among Finns with severe HC, 53% (66/124) versus 44% (55/124) were classified as high risk by the PRS and LDL‐C raising score, respectively. Moreover, 54% of individuals with severe HC defined as low risk by the LDL‐C raising score were reclassified to intermediate or high risk by the new PRS. Conclusion The new PRS has a better predictive role in identifying HC of polygenic origin compared to the currently available method and can better stratify patients into diagnostic and therapeutic algorithms.
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Affiliation(s)
- Luis G Leal
- Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom
| | - Clive Hoggart
- Department of Medicine, Imperial College London, London, United Kingdom
| | - Marjo-Riitta Jarvelin
- Faculty of Medicine, Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Middlesex, United Kingdom
| | - Karl-Heinz Herzig
- Biocenter Oulu, University of Oulu, Oulu, Finland.,Research Unit of Biomedicine, Oulu University, Oulu, Oulu University Hospital and Medical Research Center Oulu, Oulu, Finland.,Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - Michael J E Sternberg
- Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom
| | - Alessia David
- Department of Life Sciences, Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London, United Kingdom
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23
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Arima Y, Fukuoka H. Developmental origins of health and disease theory in cardiology. J Cardiol 2020; 76:14-17. [PMID: 32115330 DOI: 10.1016/j.jjcc.2020.02.003] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 01/29/2020] [Accepted: 02/09/2020] [Indexed: 01/17/2023]
Abstract
Numerous epidemiological and animal studies disclosed that birth weight is inversely associated with the incidence of the lifestyle-related disorders in adult life, such as cardiovascular disease, diabetes, and /or chronic kidney disease. Lower birth weight occurs in numerous undesired intrauterine environments including malnutrition, smoking, alcohol consumption, or stress. The Developmental Origin of Health and Disease (DOHaD) theory is based on the concept that the origins of lifestyle-related disease is formed at the time of fertilization, embryonic, fetal, and neonatal stages by the interrelation between genes and the environments (nutrition, stress, or environmental chemicals). Adult disease develops after delivery facing to abnormal environments such as over-nutrition, much stress, or lack of exercise. Disease develops through these two insults. This concept was first proposed as the "Barker Hypothesis." David Barker had discovered the relation between the lower birth weight and the higher prevalence of ischemic heart disease mortality. Previous epidemiologic studies have found the people exposed to famine during early life had higher risks of cardiovascular diseases in adulthood. Yet, the exact mechanisms that permanently change the structure, physiology, and endocrine status of an individual across their lifespan following altered growth during fetal life are not entirely clear. Epidemiological studies including prospective cohort and observational analysis of the people exposed to malnutrition during fetal or infancy have disclosed the strong relation between the lower birth weight and the higher cardiovascular risks in adults. Recent progress of epigenetic studies unveiled strong genetic association. Hormonal regulation and epigenetic modifications have an important role for proper organ development and physiological functions. The molecular mechanism of predisposition is supposed to be the epigenetics modifications. Their dysregulation is related to the acquisition of the disease-susceptible trait. In this review, we overview the concept of DOHaD and introduce related clinical and basic research.
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Affiliation(s)
- Yuichiro Arima
- Department of Cardiovascular Medicine, Kumamoto University, Kumamoto City, Japan; International Research Center for Medical Science, Kumamoto University, Kumamoto City, Japan.
| | - Hideoki Fukuoka
- Department of Progressive DOHaD Research, Fukushima Medical University, Fukushima, Japan
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24
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Kooiman J, Terstappen F, van Wagensveld L, Franx A, Wever KE, Roseboom TJ, Joles JA, Gremmels H, Lely AT. Conflicting Effects of Fetal Growth Restriction on Blood Pressure Between Human and Rat Offspring: A Meta-Analysis. Hypertension 2020; 75:806-818. [PMID: 31983304 DOI: 10.1161/hypertensionaha.119.14111] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Low birth weight is associated with hypertension. Low birth weight can result from fetal growth restriction (FGR) or prematurity. FGR is postulated to impact blood pressure (BP) by developmental programming. This systematic review and meta-analysis studies BP in human and animal offspring following FGR. Pubmed and Web of Science were searched for studies reporting on BP after placental insufficiency induced FGR compared with normal growth controls. Primary outcome was mean absolute BP difference (ΔBP mm Hg [95% CI]). Meta-analysis was performed using random-effects models. Subgroup analyses were executed on species, sex, age, pregnancy duration, and stress during BP readings. Due to large interspecies heterogeneity, analyses were performed separately for human (n=41) and animal (n=31) studies, the latter restricted to rats (n=27). Human studies showed a ΔBP between FGR and controls of -0.6 mm Hg ([95% CI, -1.7 to 0.6]; I2=91%). Mean ΔBP was -2.6 mm Hg (95% CI, -5.7 to 0.4) in women versus -0.5 mm Hg (95% CI, -3.7 to 2.7) in men. Subgroup analyses did not indicate age, gestational age, and stress during measurements as sources of heterogeneity. In rats, mean BP was 12.0 mm Hg ([95% CI, 8.8-15.2]; I2=81%) higher in FGR offspring. This difference was more pronounced in FGR males (13.6 mm Hg [95% CI, 10.3-17.0] versus 9.1 mm Hg [95% CI, 5.3-12.8]). Subgroup analyses on age showed no statistical interaction. BP readings under restrained conditions resulted in larger BP differences between FGR and control rats (15.3 mm Hg [95% CI, 11.6-18.9] versus 5.7 mm Hg [95% CI, 1.1-10.3]). Rat studies confirm the relation between FGR and offspring BP, while observational studies in humans do not show such differences. This may be due to the observational nature of human studies, methodological limitations, or an absence of this phenomenon in humans. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: CRD42018091819.
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Affiliation(s)
- Judith Kooiman
- From the Department of Obstetrics (J.K., F.T., L.v.W., A.F., A.T.L.), University Medical Center Utrecht, the Netherlands
| | - Fieke Terstappen
- From the Department of Obstetrics (J.K., F.T., L.v.W., A.F., A.T.L.), University Medical Center Utrecht, the Netherlands.,Department of Developmental Origin of Disease (F.T.), University Medical Center Utrecht, the Netherlands
| | - Lilian van Wagensveld
- From the Department of Obstetrics (J.K., F.T., L.v.W., A.F., A.T.L.), University Medical Center Utrecht, the Netherlands
| | - Arie Franx
- From the Department of Obstetrics (J.K., F.T., L.v.W., A.F., A.T.L.), University Medical Center Utrecht, the Netherlands
| | - Kimberley E Wever
- Systematic Review Center for Laboratory animal Experimentation (SYRCLE), Department for Health Evidence, Radboud University Medical Center, Nijmegen, the Netherlands (K.E.W.)
| | - Tessa J Roseboom
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Obstetrics and Gynecology, Amsterdam Public Health Research Institute, Amsterdam Reproduction and Development Research Institute, Amsterdam UMC, University of Amsterdam, the Netherlands (T.J.R.)
| | - Jaap A Joles
- Wilhelmina Children's Hospital and Department of Nephrology and Hypertension (J.A.J., H.G.), University Medical Center Utrecht, the Netherlands
| | - Hendrik Gremmels
- Wilhelmina Children's Hospital and Department of Nephrology and Hypertension (J.A.J., H.G.), University Medical Center Utrecht, the Netherlands
| | - A Titia Lely
- From the Department of Obstetrics (J.K., F.T., L.v.W., A.F., A.T.L.), University Medical Center Utrecht, the Netherlands
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25
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Ohukainen P, Kuusisto S, Kettunen J, Perola M, Järvelin MR, Mäkinen VP, Ala-Korpela M. Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease. Atherosclerosis 2019; 294:10-15. [PMID: 31931463 DOI: 10.1016/j.atherosclerosis.2019.12.009] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 12/02/2019] [Accepted: 12/12/2019] [Indexed: 01/14/2023]
Abstract
BACKGROUND AND AIMS Population subgrouping has been suggested as means to improve coronary heart disease (CHD) risk assessment. We explored here how unsupervised data-driven metabolic subgrouping, based on comprehensive lipoprotein subclass data, would work in large-scale population cohorts. METHODS We applied a self-organizing map (SOM) artificial intelligence methodology to define subgroups based on detailed lipoprotein profiles in a population-based cohort (n = 5789) and utilised the trained SOM in an independent cohort (n = 7607). We identified four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk and compared those to univariate subgrouping by apolipoprotein B quartiles. RESULTS The SOM-based subgroup with highest concentrations for non-HDL measures had the highest, and the subgroup with lowest concentrations, the lowest risk for CHD. However, apolipoprotein B quartiles produced better resolution of risk than the SOM-based subgroups and also striking dose-response behaviour. CONCLUSIONS These results suggest that the majority of lipoprotein-mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles. Therefore, even advanced multivariate subgrouping, with comprehensive data on lipoprotein metabolism, may not advance CHD risk assessment.
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Affiliation(s)
- Pauli Ohukainen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Sanna Kuusisto
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Johannes Kettunen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; National Institute for Health and Welfare, Helsinki, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland; Diabetes and Obesity Research Program, University of Helsinki, Helsinki, Finland; Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland; Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Department of Life Sciences, College of Health and Life Sciences, Brunel University London, UK
| | - Ville-Petteri Mäkinen
- Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Australia; Hopwood Centre for Neurobiology, Lifelong Health Theme, SAHMRI, Australia
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland; Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
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26
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Wang Q, Jokelainen J, Auvinen J, Puukka K, Keinänen-Kiukaanniemi S, Järvelin MR, Kettunen J, Mäkinen VP, Ala-Korpela M. Insulin resistance and systemic metabolic changes in oral glucose tolerance test in 5340 individuals: an interventional study. BMC Med 2019; 17:217. [PMID: 31779625 PMCID: PMC6883544 DOI: 10.1186/s12916-019-1440-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 10/02/2019] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Insulin resistance (IR) is predictive for type 2 diabetes and associated with various metabolic abnormalities in fasting conditions. However, limited data are available on how IR affects metabolic responses in a non-fasting setting, yet this is the state people are mostly exposed to during waking hours in the modern society. Here, we aim to comprehensively characterise the metabolic changes in response to an oral glucose test (OGTT) and assess the associations of these changes with IR. METHODS Blood samples were obtained at 0 (fasting baseline, right before glucose ingestion), 30, 60, and 120 min during the OGTT. Seventy-eight metabolic measures were analysed at each time point for a discovery cohort of 4745 middle-aged Finnish individuals and a replication cohort of 595 senior Finnish participants. We assessed the metabolic changes in response to glucose ingestion (percentage change in relative to fasting baseline) across the four time points and further compared the response profile between five groups with different levels of IR and glucose intolerance. Further, the differences were tested for covariate adjustment, including gender, body mass index, systolic blood pressure, fasting, and 2-h glucose levels. The groups were defined as insulin sensitive with normal glucose (IS-NGT), insulin resistant with normal glucose (IR-NGT), impaired fasting glucose (IFG), impaired glucose tolerance (IGT), and new diabetes (NDM). IS-NGT and IR-NGT were defined as the first and fourth quartile of fasting insulin in NGT individuals. RESULTS Glucose ingestion induced multiple metabolic responses, including increased glycolysis intermediates and decreased branched-chain amino acids, ketone bodies, glycerol, and triglycerides. The IR-NGT subgroup showed smaller responses for these measures (mean + 23%, interquartile 9-34% at 120 min) compared to IS-NGT (34%, 23-44%, P < 0.0006 for difference, corrected for multiple testing). Notably, the three groups with glucose abnormality (IFG, IGT, and NDM) showed similar metabolic dysregulations as those of IR-NGT. The difference between the IS-NGT and the other subgroups was largely explained by fasting insulin, but not fasting or 2 h glucose. The findings were consistent after covariate adjustment and between the discovery and replication cohort. CONCLUSIONS Insulin-resistant non-diabetic individuals are exposed to a similar adverse postprandial metabolic milieu, and analogous cardiometabolic risk, as those with type 2 diabetes. The wide range of metabolic abnormalities associated with IR highlights the necessity of diabetes diagnostics and clinical care beyond glucose management.
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Affiliation(s)
- Qin Wang
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland. .,Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. .,Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland. .,Biocenter Oulu, University of Oulu, Oulu, Finland.
| | - Jari Jokelainen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Unit of Primary Care and Medical Research Center, Oulu University Hospital, Oulu, Finland
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Oulunkaari Health Center, Ii, Finland
| | - Katri Puukka
- NordLab Oulu, Oulu University Hospital and Department of Clinical Chemistry, University of Oulu, Oulu, Finland
| | - Sirkka Keinänen-Kiukaanniemi
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Unit of Primary Care and Medical Research Center, Oulu University Hospital, Oulu, Finland.,Health and Wellfare Center, Oulu, Finland.,Healthcare and Social Services of Selänne, Pyhäjärvi, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Care and Medical Research Center, Oulu University Hospital, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, Middlesex, UK
| | - Johannes Kettunen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland.,Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,National Institute for Health and Welfare, Helsinki, Finland
| | - Ville-Petteri Mäkinen
- Computational and Systems Biology Program, Precision Medicine Theme, South Australian Health and Medical Research Institute, Adelaide, Australia.,Hopwood Centre for Neurobiology, Lifelong Health Theme, SAHMRI, Adelaide, Australia
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland. .,Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. .,Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland. .,Biocenter Oulu, University of Oulu, Oulu, Finland. .,MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK. .,Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK. .,NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland. .,Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, VIC, Australia.
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27
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Cardiovascular effects of prenatal stress-Are there implications for cerebrovascular, cognitive and mental health outcome? Neurosci Biobehav Rev 2019; 117:78-97. [PMID: 31708264 DOI: 10.1016/j.neubiorev.2018.05.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Revised: 05/21/2018] [Accepted: 05/22/2018] [Indexed: 01/17/2023]
Abstract
Prenatal stress programs offspring cognitive and mental health outcome. We reviewed whether prenatal stress also programs cardiovascular dysfunction which potentially modulates cerebrovascular, cognitive and mental health disorders. We focused on maternal stress and prenatal glucocorticoid (GC) exposure which have different programming effects. While maternal stress induced cortisol is mostly inactivated by the placenta, synthetic GCs freely cross the placenta and have different receptor-binding characteristics. Maternal stress, particularly anxiety, but not GC exposure, has adverse effects on maternal-fetal circulation throughout pregnancy, probably by co-activation of the maternal sympathetic nervous system, and by raising fetal catecholamines. Both effects may impair neurodevelopment. Experimental data also suggest that severe maternal stress and GC exposure during early and mid-gestation may increase the risk for cardiovascular disorders. Human data are scarce and especially lacking for older age. Programming mechanisms include aberrations in cardiac and kidney development, and functional changes in the renin-angiotensin-aldosterone-system, stress axis and peripheral and coronary vasculature. Adequate experimental or human studies examining the consequences for cerebrovascular, cognitive and mental disorders are unavailable.
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Couto Alves A, De Silva NMG, Karhunen V, Sovio U, Das S, Taal HR, Warrington NM, Lewin AM, Kaakinen M, Cousminer DL, Thiering E, Timpson NJ, Bond TA, Lowry E, Brown CD, Estivill X, Lindi V, Bradfield JP, Geller F, Speed D, Coin LJM, Loh M, Barton SJ, Beilin LJ, Bisgaard H, Bønnelykke K, Alili R, Hatoum IJ, Schramm K, Cartwright R, Charles MA, Salerno V, Clément K, Claringbould AAJ, van Duijn CM, Moltchanova E, Eriksson JG, Elks C, Feenstra B, Flexeder C, Franks S, Frayling TM, Freathy RM, Elliott P, Widén E, Hakonarson H, Hattersley AT, Rodriguez A, Banterle M, Heinrich J, Heude B, Holloway JW, Hofman A, Hyppönen E, Inskip H, Kaplan LM, Hedman AK, Läärä E, Prokisch H, Grallert H, Lakka TA, Lawlor DA, Melbye M, Ahluwalia TS, Marinelli M, Millwood IY, Palmer LJ, Pennell CE, Perry JR, Ring SM, Savolainen MJ, Rivadeneira F, Standl M, Sunyer J, Tiesler CMT, Uitterlinden AG, Schierding W, O’Sullivan JM, Prokopenko I, Herzig KH, Smith GD, O'Reilly P, Felix JF, Buxton JL, Blakemore AIF, Ong KK, Jaddoe VWV, Grant SFA, Sebert S, McCarthy MI, Järvelin MR. GWAS on longitudinal growth traits reveals different genetic factors influencing infant, child, and adult BMI. SCIENCE ADVANCES 2019; 5:eaaw3095. [PMID: 31840077 PMCID: PMC6904961 DOI: 10.1126/sciadv.aaw3095] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 08/06/2019] [Indexed: 05/29/2023]
Abstract
Early childhood growth patterns are associated with adult health, yet the genetic factors and the developmental stages involved are not fully understood. Here, we combine genome-wide association studies with modeling of longitudinal growth traits to study the genetics of infant and child growth, followed by functional, pathway, genetic correlation, risk score, and colocalization analyses to determine how developmental timings, molecular pathways, and genetic determinants of these traits overlap with those of adult health. We found a robust overlap between the genetics of child and adult body mass index (BMI), with variants associated with adult BMI acting as early as 4 to 6 years old. However, we demonstrated a completely distinct genetic makeup for peak BMI during infancy, influenced by variation at the LEPR/LEPROT locus. These findings suggest that different genetic factors control infant and child BMI. In light of the obesity epidemic, these findings are important to inform the timing and targets of prevention strategies.
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Affiliation(s)
- Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | - N. Maneka G. De Silva
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Ulla Sovio
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - Shikta Das
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - H. Rob Taal
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
| | - Nicole M. Warrington
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
| | - Alexandra M. Lewin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Marika Kaakinen
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Centre for Pharmacology and Therapeutics, Division of Experimental Medicine, Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
| | - Diana L. Cousminer
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Elisabeth Thiering
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom A. Bond
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Estelle Lowry
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Christopher D. Brown
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Xavier Estivill
- Genomics and Disease Group, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Virpi Lindi
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
| | - Jonathan P. Bradfield
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Doug Speed
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark
- UCL Genetics Institute, University College London, London, UK
| | - Lachlan J. M. Coin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Marie Loh
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) Singapore, Singapore
| | - Sheila J. Barton
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Lawrence J. Beilin
- Medical School, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
| | - Hans Bisgaard
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Klaus Bønnelykke
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rohia Alili
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
| | - Ida J. Hatoum
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Katharina Schramm
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
| | - Rufus Cartwright
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Marie-Aline Charles
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
| | - Vincenzo Salerno
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Karine Clément
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
| | - Annique A. J. Claringbould
- University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713 AV Groningen, Netherlands
| | - BIOS Consortium
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Centre for Pharmacology and Therapeutics, Division of Experimental Medicine, Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Genomics and Disease Group, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Sidra Medical and Research Center, Doha, Qatar
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark
- UCL Genetics Institute, University College London, London, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) Singapore, Singapore
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Medical School, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
- University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713 AV Groningen, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, UK
- Health Data Research UK London, Imperial College London, London, UK
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- School of Psychology, College of Social Science, University of Lincoln Brayford Pool Lincoln, Lincolnshire, UK
- Human Genetics and Medical Genomics, Faculty of Medicine, University of Southampton, Southampton, UK
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Great Ormond Street Hospital Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, North Terrace, Adelaide, South Australia, Australia
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University Medical School, Stanford, CA, USA
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Old Road Campus, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Oxford, UK
- School of Public Health and Robinson Research Institute, University of Adelaide, Adelaide, Australia
- Avon Longitudinal Study of Parents and Children, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Division of Internal Medicine, and Biocenter of Oulu, Faculty of Medicine, Oulu University, Oulu, Finland
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Liggins Institute, University of Auckland, Auckland, New Zealand
- A Better Start—National Science, Challenge, University of Auckland, Auckland, New Zealand
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Research Unit of Biomedicine, University Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, De Crespigny Park, London, UK
- School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Elena Moltchanova
- Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
| | - Cathy Elks
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Claudia Flexeder
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
| | - Stephen Franks
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
| | - Timothy M. Frayling
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Rachel M. Freathy
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, UK
- Health Data Research UK London, Imperial College London, London, UK
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Hakon Hakonarson
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Andrew T. Hattersley
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Alina Rodriguez
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Psychology, College of Social Science, University of Lincoln Brayford Pool Lincoln, Lincolnshire, UK
| | - Marco Banterle
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Joachim Heinrich
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
| | - Barbara Heude
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
| | - John W. Holloway
- Human Genetics and Medical Genomics, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Albert Hofman
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Elina Hyppönen
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Great Ormond Street Hospital Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, North Terrace, Adelaide, South Australia, Australia
| | - Hazel Inskip
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Lee M. Kaplan
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Asa K. Hedman
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
| | - Esa Läärä
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Timo A. Lakka
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Debbie A. Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University Medical School, Stanford, CA, USA
| | - Tarunveer S. Ahluwalia
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marcella Marinelli
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
| | - Iona Y. Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Old Road Campus, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Oxford, UK
| | - Lyle J. Palmer
- School of Public Health and Robinson Research Institute, University of Adelaide, Adelaide, Australia
| | - Craig E. Pennell
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - John R. Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Susan M. Ring
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Avon Longitudinal Study of Parents and Children, School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Markku J. Savolainen
- Division of Internal Medicine, and Biocenter of Oulu, Faculty of Medicine, Oulu University, Oulu, Finland
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marie Standl
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
| | - Jordi Sunyer
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
| | - Carla M. T. Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
| | - Andre G. Uitterlinden
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | | | - Justin M. O’Sullivan
- Liggins Institute, University of Auckland, Auckland, New Zealand
- A Better Start—National Science, Challenge, University of Auckland, Auckland, New Zealand
| | - Inga Prokopenko
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
| | - Karl-Heinz Herzig
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Research Unit of Biomedicine, University Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
| | - Paul O'Reilly
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, De Crespigny Park, London, UK
| | - Janine F. Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jessica L. Buxton
- School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, UK
| | - Alexandra I. F. Blakemore
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
| | - Ken K. Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
| | - Vincent W. V. Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Struan F. A. Grant
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sylvain Sebert
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Mark I. McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Early Growth Genetics (EGG) Consortium
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
- Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Paediatrics, Erasmus MC, Sophia Children’s Hospital, Rotterdam, Netherlands
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, Queensland, Australia
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK
- Centre for Pharmacology and Therapeutics, Division of Experimental Medicine, Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
- Department of Clinical and Experimental Medicine, School of Biosciences and Medicine, University of Surrey, Surrey, UK
- Division of Human Genetics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Institute of Biomedicine, Department of Physiology, University of Eastern Finland, Kuopio, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich Neuherberg, Germany
- Division of Metabolic Diseases and Nutritional Medicine, Dr von Hauner Children’s Hospital, Ludwig-Maximilians University Munich, Munich, Germany
- MRC Integrative Epidemiology Unit at the University of Bristol and NIHR Bristol Biomedical Research Center, Bristol, UK
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Genomics and Disease Group, Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Catalonia, Spain
- Pompeu Fabra University (UPF), Barcelona, Catalonia, Spain
- Hospital del Mar Medical Research Institute (IMIM), Barcelona, Catalonia, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Sidra Medical and Research Center, Doha, Qatar
- Center for Applied Genomics, Abramson Research Center, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark
- UCL Genetics Institute, University College London, London, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR) Singapore, Singapore
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Medical School, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
- COPSAC, The Copenhagen Prospective Studies on Asthma in Childhood, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
- CRNH Ile de France, Hôpital Pitié-Salpêtrière, Paris, France
- Obesity, Metabolism, and Nutrition Institute and Gastrointestinal Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, München, Germany
- Institute for Reproductive and Developmental Biology, Imperial College London, London, UK
- Inserm, UMR 1153 (CRESS), Paris Descartes University, Villejuif, Paris, France
- University Medical Centre Groningen, Department of Genetics, Antonius Deusinglaan 1, 9713 AV Groningen, Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand
- Department of General Practice and Primary Health Care, University of Helsinki, and Helsinki University Hospital, Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
- Folkhalsan Research Center, Helsinki, Finland
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Institute of Biomedical and Clinical Science, University of Exeter Medical School, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, UK
- Health Data Research UK London, Imperial College London, London, UK
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- School of Psychology, College of Social Science, University of Lincoln Brayford Pool Lincoln, Lincolnshire, UK
- Human Genetics and Medical Genomics, Faculty of Medicine, University of Southampton, Southampton, UK
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
- Great Ormond Street Hospital Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, North Terrace, Adelaide, South Australia, Australia
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Cardiovascular Medicine Unit, Department of Medicine, Karolinska Institute, Stockholm, Sweden
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Medicine, Stanford University Medical School, Stanford, CA, USA
- ISGlobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), University of Oxford, Old Road Campus, Oxford, UK
- Medical Research Council Population Health Research Unit (MRC PHRU) at the University of Oxford, Oxford, UK
- School of Public Health and Robinson Research Institute, University of Adelaide, Adelaide, Australia
- Avon Longitudinal Study of Parents and Children, School of Social and Community Medicine, University of Bristol, Bristol, UK
- Division of Internal Medicine, and Biocenter of Oulu, Faculty of Medicine, Oulu University, Oulu, Finland
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Liggins Institute, University of Auckland, Auckland, New Zealand
- A Better Start—National Science, Challenge, University of Auckland, Auckland, New Zealand
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Headington, Oxford, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Research Unit of Biomedicine, University Oulu, Oulu, Finland
- Medical Research Center and Oulu University Hospital, University of Oulu, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
- MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King’s College London, De Crespigny Park, London, UK
- School of Life Sciences, Pharmacy and Chemistry, Kingston University, Kingston upon Thames, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
- Section of Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
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30
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Sliz E, Kalaoja M, Ahola-Olli A, Raitakari O, Perola M, Salomaa V, Lehtimäki T, Karhu T, Viinamäki H, Salmi M, Santalahti K, Jalkanen S, Jokelainen J, Keinänen-Kiukaanniemi S, Männikkö M, Herzig KH, Järvelin MR, Sebert S, Kettunen J. Genome-wide association study identifies seven novel loci associating with circulating cytokines and cell adhesion molecules in Finns. J Med Genet 2019; 56:607-616. [PMID: 31217265 PMCID: PMC6817708 DOI: 10.1136/jmedgenet-2018-105965] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Revised: 04/10/2019] [Accepted: 04/20/2019] [Indexed: 12/11/2022]
Abstract
BACKGROUND Inflammatory processes contribute to the pathophysiology of multiple chronic conditions. Genetic factors play a crucial role in modulating the inflammatory load, but the exact mechanisms are incompletely understood. OBJECTIVE To assess genetic determinants of 16 circulating cytokines and cell adhesion molecules (inflammatory phenotypes) in Finns. METHODS Genome-wide associations of the inflammatory phenotypes were studied in Northern Finland Birth Cohort 1966 (N=5284). A subsequent meta-analysis was completed for 10 phenotypes available in a previous genome-wide association study, adding up to 13 577 individuals in the study. Complementary association tests were performed to study the effect of the ABO blood types on soluble adhesion molecule levels. RESULTS We identified seven novel and six previously reported genetic associations (p<3.1×10-9). Three loci were associated with soluble vascular cell adhesion molecule-1 (sVCAM-1) level, one of which was the ABO locus that has been previously associated with soluble E-selectin (sE-selectin) and intercellular adhesion molecule-1 (sICAM-1) levels. Our findings suggest that the blood type B associates primarily with sVCAM-1 level, while the A1 subtype shows a robust effect on sE-selectin and sICAM-1 levels. The genotypes in the ABO locus associating with higher soluble adhesion molecule levels tend to associate with lower circulating cholesterol levels and lower cardiovascular disease risk. CONCLUSION The present results extend the knowledge about genetic factors contributing to the inflammatory load. Our findings suggest that two distinct mechanisms contribute to the soluble adhesion molecule levels in the ABO locus and that elevated soluble adhesion molecule levels per se may not increase risk for cardiovascular disease.
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Affiliation(s)
- Eeva Sliz
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
| | - Marita Kalaoja
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
| | - Ari Ahola-Olli
- Department of Internal Medicine, Satakunta Central Hospital, Pori, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Olli Raitakari
- 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
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- University of Tartu, Estonian Genome Center, Tartu, Estonia
| | - Veikko Salomaa
- National Institute for Health and Welfare, 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
| | - Toni Karhu
- Biocenter Oulu, Oulu, Finland
- Institute of Biomedicine, University of Oulu, Oulu, Finland
| | - Heimo Viinamäki
- Department of Psychiatry, University of Eastern Finland, and Kuopio University Hospital, Kuopio, Finland
| | - Marko Salmi
- Medicity Research Laboratory and Institute of Biomedicine, University of Turku, Turku, Finland
| | - Kristiina Santalahti
- Medicity Research Laboratory and Institute of Biomedicine, University of Turku, Turku, Finland
| | - Sirpa Jalkanen
- Medicity Research Laboratory and Institute of Biomedicine, University of Turku, Turku, Finland
| | - Jari Jokelainen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Unit of General Practice, Oulu University Hospital, Oulu, Finland
| | - Sirkka Keinänen-Kiukaanniemi
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Unit of General Practice, Oulu University Hospital, Oulu, Finland
- Oulu Deaconess Institute/Diapolis Oy Research Unit, Oulu, Finland
| | - Minna Männikkö
- Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Karl-Heinz Herzig
- Biocenter Oulu, Oulu, Finland
- Institute of Biomedicine, University of Oulu, Oulu, Finland
- Medical Research Center (MRC), University of Oulu, and Oulu University Hospital, Oulu, Finland
- Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
- Department of Genomics and Complex Diseases, School of Public Health, Imperial College, London, UK
| | - Johannes Kettunen
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Biocenter Oulu, Oulu, Finland
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31
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Vitamin D status and correlates of low vitamin D in schizophrenia, other psychoses and non-psychotic depression - The Northern Finland Birth Cohort 1966 study. Psychiatry Res 2019; 279:186-194. [PMID: 30876732 DOI: 10.1016/j.psychres.2019.02.060] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 02/22/2019] [Accepted: 02/23/2019] [Indexed: 02/07/2023]
Abstract
There is limited knowledge available on the association of vitamin D with psychiatric disorders in young adults. We aimed to investigate vitamin D levels and associating factors in schizophrenia, other psychoses and non-psychotic depression. We studied 4,987 participants from the Northern Finland Birth Cohort 1966 (31 years) with available serum 25-hydroxyvitamin D [25(OH)D] measurements. The final sample was divided into four groups: schizophrenia (n = 40), other psychoses (n = 24), non-psychotic depression (n = 264) and control (n = 4659). To account for the influence of environmental and technical covariates, we generated a vitamin D score variable with correction for season, sex, batch effect and latitude. We further examined how vitamin D levels correlate with anthropometric, lifestyle, socioeconomic and psychiatric measures. Neither serum 25(OH)D concentration nor vitamin D score differed between schizophrenia, other psychoses, non-psychotic depression and control group. The prevalence of vitamin D deficiency was 3.2%, insufficiency 25.5%, and sufficiency 71.3%. Low vitamin D score correlated with regular smoking in the group with schizophrenia. No difference was observed in other psychiatric conditions. We did not find any difference in vitamin D status between schizophrenia, psychoses, non-psychotic depression and control groups, but future studies are warranted to elucidate the role of vitamin D in psychiatric conditions.
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32
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Markopoulou P, Papanikolaou E, Analytis A, Zoumakis E, Siahanidou T. Preterm Birth as a Risk Factor for Metabolic Syndrome and Cardiovascular Disease in Adult Life: A Systematic Review and Meta-Analysis. J Pediatr 2019; 210:69-80.e5. [PMID: 30992219 DOI: 10.1016/j.jpeds.2019.02.041] [Citation(s) in RCA: 179] [Impact Index Per Article: 35.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 01/30/2019] [Accepted: 02/27/2019] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To determine if preterm birth is associated with components of the metabolic syndrome in adult life. STUDY DESIGN A structured literature search was performed using PubMed. All comparative studies reported metabolic and cardiovascular outcomes in adults (≥18 years of age) born preterm (<37 weeks of gestation) compared with adults born at term (37-42 weeks of gestation) and published through March 2018 were included. The major outcomes assessed were body mass index, waist circumference, waist-to-hip ratio, fat mass, systolic blood pressure (SBP), diastolic blood pressure (DBP), 24-hour SBP, 24-hour DBP, endothelium-dependent brachial artery flow-mediated dilation, carotid intima-media thickness, pulse wave velocity, fasting glucose and insulin, Homeostasis Model Assessment-Estimated Insulin Resistance Index, and lipid profiles. Quality appraisal was performed using a modified version of the Newcastle-Ottawa scale. A meta-analysis was performed for comparable studies which reported sufficient data. RESULTS Forty-three studies were included, including a combined total of 18 295 preterm and 294 063 term-born adults. Prematurity was associated with significantly higher fat mass (P = .03), SBP (P < .0001), DBP (P < .0001), 24-hour SBP (P < .001), and 24-hour DBP (P < .001). Furthermore, preterm-born adults presented higher values of fasting glucose (P = .01), insulin (P = .002), Homeostasis Model Assessment-Estimated Insulin Resistance Index (P = .05), and total cholesterol levels (P = .05) in comparison with adults born at term, in random effect models. No statistically significant difference was found between preterm and term-born adults for the other outcomes studied. CONCLUSIONS Preterm birth is strongly associated with a number of components of the metabolic syndrome and cardiovascular disease in adult life.
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Affiliation(s)
- Panagiota Markopoulou
- First Department of Pediatrics, National and Kapodistrian University of Athens, Athens, Greece
| | - Eleni Papanikolaou
- Laboratory of Biology, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Antonis Analytis
- Department of Hygiene, Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Emmanouil Zoumakis
- First Department of Pediatrics, National and Kapodistrian University of Athens, Athens, Greece
| | - Tania Siahanidou
- First Department of Pediatrics, National and Kapodistrian University of Athens, Athens, Greece.
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33
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Enoksson Wallas A, Eriksson C, Edstedt Bonamy AK, Gruzieva O, Kull I, Ögren M, Pyko A, Sjöström M, Pershagen G. Traffic noise and other determinants of blood pressure in adolescence. Int J Hyg Environ Health 2019; 222:824-830. [PMID: 31036481 DOI: 10.1016/j.ijheh.2019.04.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Revised: 04/23/2019] [Accepted: 04/23/2019] [Indexed: 10/26/2022]
Abstract
BACKGROUND Exposure to traffic noise has been associated with hypertension in adults but the evidence in adolescents is limited. We investigated long-term road traffic noise exposure, maternal occupational noise during pregnancy and other factors in relation to blood pressure and prehypertension at 16 years of age. METHODS Systolic and diastolic blood pressure were measured in 2597 adolescents from the Swedish BAMSE birth cohort. Levels of road traffic noise were estimated at home addresses during lifetime and for the mother during pregnancy as well as maternal occupational noise exposure during pregnancy. Exposure to NOx from local sources was also assessed. Associations between noise or NOx exposure and blood pressure or prehypertension were analysed using linear and logistic regression. RESULTS The prevalence of prehypertension was higher among males and in those with overweight, low physical activity or overweight mothers. No strong or consistent associations were observed between pre- or postnatal exposure to road traffic noise and blood pressure at 16 years of age. However, inverse associations were suggested for systolic or diastolic blood pressure and prehypertension, which reached statistical significance among males (OR 0.80 per 10 dB Lden, 95% CI 0.65-0.99) and those with maternal occupational noise exposure ≥ 70 dB LAeq8h (OR 0.60, 95% CI 0.41-0.87). On the other hand, occupational noise exposure during pregnancy tended to increase systolic blood pressure and prehypertension risk in adolescence. No associations were seen for NOx exposure. CONCLUSION No conclusive associations were observed between pre- or postnatal noise exposure and blood pressure or prehypertension in adolescents.
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Affiliation(s)
| | - Charlotta Eriksson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Anna-Karin Edstedt Bonamy
- Clinical Epidemiology Division, Department of Medicine Solna, Sweden; Department of Women's and Children's Health, Karolinska Institutet, Sweden
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Inger Kull
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Sachs' Children and Youth Hospital, Stockholm, Sweden
| | - Mikael Ögren
- Department of Occupational and Environmental Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Andrei Pyko
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Mattias Sjöström
- Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
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34
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Warrington NM, Beaumont RN, Horikoshi M, Day FR, Helgeland Ø, Laurin C, Bacelis J, Peng S, Hao K, Feenstra B, Wood AR, Mahajan A, Tyrrell J, Robertson NR, Rayner NW, Qiao Z, Moen GH, Vaudel M, Marsit CJ, Chen J, Nodzenski M, Schnurr TM, Zafarmand MH, Bradfield JP, Grarup N, Kooijman MN, Li-Gao R, Geller F, Ahluwalia TS, Paternoster L, Rueedi R, Huikari V, Hottenga JJ, Lyytikäinen LP, Cavadino A, Metrustry S, Cousminer DL, Wu Y, Thiering E, Wang CA, Have CT, Vilor-Tejedor N, Joshi PK, Painter JN, Ntalla I, Myhre R, Pitkänen N, van Leeuwen EM, Joro R, Lagou V, Richmond RC, Espinosa A, Barton SJ, Inskip HM, Holloway JW, Santa-Marina L, Estivill X, Ang W, Marsh JA, Reichetzeder C, Marullo L, Hocher B, Lunetta KL, Murabito JM, Relton CL, Kogevinas M, Chatzi L, Allard C, Bouchard L, Hivert MF, Zhang G, Muglia LJ, Heikkinen J, Morgen CS, van Kampen AHC, van Schaik BDC, Mentch FD, Langenberg C, Luan J, Scott RA, Zhao JH, Hemani G, Ring SM, Bennett AJ, Gaulton KJ, Fernandez-Tajes J, van Zuydam NR, Medina-Gomez C, de Haan HG, Rosendaal FR, Kutalik Z, Marques-Vidal P, Das S, Willemsen G, Mbarek H, Müller-Nurasyid M, Standl M, Appel EVR, Fonvig CE, Trier C, van Beijsterveldt CEM, Murcia M, Bustamante M, Bonas-Guarch S, Hougaard DM, Mercader JM, Linneberg A, Schraut KE, Lind PA, Medland SE, Shields BM, Knight BA, Chai JF, Panoutsopoulou K, Bartels M, Sánchez F, Stokholm J, Torrents D, Vinding RK, Willems SM, Atalay M, Chawes BL, Kovacs P, Prokopenko I, Tuke MA, Yaghootkar H, Ruth KS, Jones SE, Loh PR, Murray A, Weedon MN, Tönjes A, Stumvoll M, Michaelsen KF, Eloranta AM, Lakka TA, van Duijn CM, Kiess W, Körner A, Niinikoski H, Pahkala K, Raitakari OT, Jacobsson B, Zeggini E, Dedoussis GV, Teo YY, Saw SM, Montgomery GW, Campbell H, Wilson JF, Vrijkotte TGM, Vrijheid M, de Geus EJCN, Hayes MG, Kadarmideen HN, Holm JC, Beilin LJ, Pennell CE, Heinrich J, Adair LS, Borja JB, Mohlke KL, Eriksson JG, Widén EE, Hattersley AT, Spector TD, Kähönen M, Viikari JS, Lehtimäki T, Boomsma DI, Sebert S, Vollenweider P, Sørensen TIA, Bisgaard H, Bønnelykke K, Murray JC, Melbye M, Nohr EA, Mook-Kanamori DO, Rivadeneira F, Hofman A, Felix JF, Jaddoe VWV, Hansen T, Pisinger C, Vaag AA, Pedersen O, Uitterlinden AG, Järvelin MR, Power C, Hyppönen E, Scholtens DM, Lowe WL, Davey Smith G, Timpson NJ, Morris AP, Wareham NJ, Hakonarson H, Grant SFA, Frayling TM, Lawlor DA, Njølstad PR, Johansson S, Ong KK, McCarthy MI, Perry JRB, Evans DM, Freathy RM. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet 2019; 51:804-814. [PMID: 31043758 PMCID: PMC6522365 DOI: 10.1038/s41588-019-0403-1] [Citation(s) in RCA: 317] [Impact Index Per Article: 63.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 03/26/2019] [Indexed: 12/21/2022]
Abstract
Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
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Affiliation(s)
- Nicole M Warrington
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Robin N Beaumont
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Momoko Horikoshi
- RIKEN Centre for Integrative Medical Sciences, Laboratory for Endocrinology, Metabolism and Kidney Diseases, Yokohama, Japan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Felix R Day
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Øyvind Helgeland
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
- Department of Genetics and Bioinformatics, Domain of Health Data and Digitalisation, Norwegian Institute of Public Health, Oslo, Norway
| | - Charles Laurin
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jonas Bacelis
- Department of Obstetrics and Gynecology, Sahlgrenska University Hospital Östra, Gothenburg, Sweden
| | - Shouneng Peng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bjarke Feenstra
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - Andrew R Wood
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Jessica Tyrrell
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
- European Centre for Environment and Human Health, University of Exeter, Truro, UK
| | - Neil R Robertson
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - N William Rayner
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Zhen Qiao
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia
| | - Gunn-Helen Moen
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Marc Vaudel
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Carmen J Marsit
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Nodzenski
- Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Theresia M Schnurr
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mohammad H Zafarmand
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Amsterdam UMC, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Jonathan P Bradfield
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research, San Diego, CA, USA
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marjolein N Kooijman
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frank Geller
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
| | - Tarunveer S Ahluwalia
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Lavinia Paternoster
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ville Huikari
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Alana Cavadino
- Section of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Sarah Metrustry
- Department of Twin Research, King's College London, St. Thomas' Hospital, London, UK
| | - Diana L Cousminer
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Elisabeth Thiering
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, University of Munich Medical Center, Munich, Germany
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Christian T Have
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Natalia Vilor-Tejedor
- Center for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
- Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | - Peter K Joshi
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Jodie N Painter
- QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Brisbane, Queensland, Australia
| | - Ioanna Ntalla
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Ronny Myhre
- Department of Genes and Environment, Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Elisabeth M van Leeuwen
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Raimo Joro
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Vasiliki Lagou
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Neuroscience, Katholieke Universiteit Leuven, Leuven, Belgium
- VIB Center for Brain and Disease Research, Leuven, Belgium
| | - Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ana Espinosa
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Epidemiología y Salud Pública, Madrid, Spain
- Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Sheila J Barton
- Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Hazel M Inskip
- Medical Research Council Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Loreto Santa-Marina
- CIBER de Epidemiología y Salud Pública, Madrid, Spain
- Subdirección de Salud Pública y Adicciones de Gipuzkoa, San Sebastián, Spain
- Instituto de Investigación Sanitaria Biodonostia, San Sebastián, Spain
| | - Xavier Estivill
- Sidra Medicine Research Department, Sidra Medicine, Doha, Qatar
- Genomics Unit, Dexeus Woman's Health, Barcelona, Spain
| | - Wei Ang
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | - Julie A Marsh
- Division of Obstetrics and Gynaecology, The University of Western Australia, Perth, Western Australia, Australia
| | | | - Letizia Marullo
- Department of Life Sciences and Biotechnology, Genetic Section, University of Ferrara, Ferrara, Italy
| | - Berthold Hocher
- Fifth Department of Medicine, University Medical Centre Mannheim, University of Heidelberg, Heidelberg, Germany
- Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, China
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Joanne M Murabito
- Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Manolis Kogevinas
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Epidemiología y Salud Pública, Madrid, Spain
- Hospital del Mar Medical Research Institute, Barcelona, Spain
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Catherine Allard
- Centre de recherche, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Luigi Bouchard
- Centre de recherche, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Quebec, Canada
- ECOGENE-21 and Lipid Clinic, Chicoutimi Hospital, Saguenay, Quebec, Canada
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, Quebec, Canada
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Diabetes Center, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Universite de Sherbrooke, Sherbooke, Quebec, Canada
| | - Ge Zhang
- Human Genetics Division, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH, USA
| | - Louis J Muglia
- Human Genetics Division, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Center for Prevention of Preterm Birth, Perinatal Institute, Cincinnati Children's Hospital Medical Center, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- March of Dimes Prematurity Research Center Ohio Collaborative, Cincinnati, OH, USA
| | - Jani Heikkinen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Camilla S Morgen
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Antoine H C van Kampen
- Bioinformatics Laboratory, Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
- Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands
| | - Barbera D C van Schaik
- Bioinformatics Laboratory, Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam Public Health Research Institute, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Frank D Mentch
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Susan M Ring
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amanda J Bennett
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Kyle J Gaulton
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | | | - Natalie R van Zuydam
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Carolina Medina-Gomez
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Hugoline G de Haan
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Institute of Social and Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Pedro Marques-Vidal
- Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Shikta Das
- Medical Research Council Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Sciences, University College London, London, UK
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
| | - Hamdi Mbarek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
- Amsterdam Reproduction and Development, Amsterdam, the Netherlands
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University Munich, Munich, Germany
- Division of Genetic Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Marie Standl
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Emil V R Appel
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Cilius E Fonvig
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
- Hans Christian Andersen Children's Hospital, Odense University Hospital, Odense, Denmark
| | - Caecilie Trier
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | | | - Mario Murcia
- CIBER de Epidemiología y Salud Pública, Madrid, Spain
- FISABIO-Universitat Jaume I-Universitat de València, Joint Research Unit of Epidemiology and Environmental Health, Valencia, Spain
| | - Mariona Bustamante
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Epidemiología y Salud Pública, Madrid, Spain
| | - Sílvia Bonas-Guarch
- Joint BSC-CGR-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain
| | - David M Hougaard
- Danish Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Josep M Mercader
- Joint BSC-CGR-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Allan Linneberg
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Frederiksberg, Denmark
| | - Katharina E Schraut
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Penelope A Lind
- QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Brisbane, Queensland, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Brisbane, Queensland, Australia
| | - Beverley M Shields
- NIHR Exeter Clinical Research Facility, University of Exeter College of Medicine and Health and Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Bridget A Knight
- NIHR Exeter Clinical Research Facility, University of Exeter College of Medicine and Health and Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore
| | | | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
| | - Friman Sánchez
- Joint BSC-CGR-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain
- Computer Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain
| | - Jakob Stokholm
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - David Torrents
- Joint BSC-CGR-IRB Research Program in Computational Biology, Barcelona Supercomputing Center, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
| | - Rebecca K Vinding
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Sara M Willems
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Mustafa Atalay
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Bo L Chawes
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Peter Kovacs
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Inga Prokopenko
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Section of Genomics of Common Disease, Department of Medicine, Imperial College London, London, UK
| | - Marcus A Tuke
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Hanieh Yaghootkar
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Katherine S Ruth
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Samuel E Jones
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Po-Ru Loh
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Anna Murray
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Michael N Weedon
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Anke Tönjes
- Medical Department, University of Leipzig, Leipzig, Germany
| | - Michael Stumvoll
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Medical Department, University of Leipzig, Leipzig, Germany
| | - Kim F Michaelsen
- Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Aino-Maija Eloranta
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
| | - Timo A Lakka
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Wieland Kiess
- Pediatric Research Center, Department of Women's andChild Health, University of Leipzig, Leipzig, Germany
| | - Antje Körner
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Pediatric Research Center, Department of Women's andChild Health, University of Leipzig, Leipzig, Germany
| | - Harri Niinikoski
- Department of Pediatrics, Turku University Hospital, Turku, Finland
- Department of Physiology, University of Turku, Turku, Finland
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Department of Physical Activity and Health, University of Turku, Turku, Finland
| | - Olli T Raitakari
- 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
| | - Bo Jacobsson
- Department of Genetics and Bioinformatics, Domain of Health Data and Digitalisation, Norwegian Institute of Public Health, Oslo, Norway
- Department of Obstetrics and Gynecology, Sahlgrenska University Hospital Östra, Gothenburg, Sweden
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Hinxton, UK
- Institute of Translational Genomics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - George V Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore
- Singapore Eye Research Institute, Singapore, Singapore
| | - Grant W Montgomery
- QIMR Berghofer Medical Research Institute, Royal Brisbane Hospital, Brisbane, Queensland, Australia
| | - Harry Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - James F Wilson
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Tanja G M Vrijkotte
- Department of Public Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Martine Vrijheid
- ISGlobal, Barcelona Institute for Global Health, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- CIBER de Epidemiología y Salud Pública, Madrid, Spain
| | - Eco J C N de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
| | - M Geoffrey Hayes
- Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Haja N Kadarmideen
- Quantitative and Systems Genomics Group, Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark
| | - Jens-Christian Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Children's Obesity Clinic, Department of Pediatrics, Copenhagen University Hospital Holbæk, Holbæk, Denmark
| | - Lawrence J Beilin
- School of Medicine, Royal Perth Hospital, University of Western Australia, Perth, Western Australia, Australia
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, New South Wales, Australia
| | - Joachim Heinrich
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute and Outpatient Clinic for Occupational Social and Environmental Medicine, Inner City Clinic, University Hospital Munich, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Linda S Adair
- Department of Nutrition, University of North Carolina, Chapel Hill, NC, USA
| | - Judith B Borja
- USC-Office of Population Studies Foundation, University of San Carlos, Cebu City, Philippines
- Department of Nutrition and Dietetics, University of San Carlos, Cebu City, Philippines
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Johan G Eriksson
- National Institute for Health and Welfare, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Elisabeth E Widén
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Andrew T Hattersley
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
- NIHR Exeter Clinical Research Facility, University of Exeter College of Medicine and Health and Royal Devon and Exeter NHS Foundation Trust, Exeter, UK
| | - Tim D Spector
- Department of Twin Research, King's College London, St. Thomas' Hospital, London, UK
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Department of Clinical Physiology, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jorma S Viikari
- Division of Medicine, Turku University Hospital, Turku, Finland
- Department of Medicine, University of Turku, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Netherlands Twin Register, Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Public Health, Amsterdam, the Netherlands
- Amsterdam Reproduction and Development, Amsterdam, the Netherlands
| | - Sylvain Sebert
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Department of Genomics of Complex Diseases, Imperial College London, London, UK
| | - Peter Vollenweider
- Department of Medicine, Internal Medicine, Lausanne University Hospital, Lausanne, Switzerland
| | - Thorkild I A Sørensen
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hans Bisgaard
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Klaus Bønnelykke
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Jeffrey C Murray
- Department of Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Mads Melbye
- Department of Epidemiology Research, Statens Serum Institute, Copenhagen, Denmark
- Department of Medicine, Stanford School of Medicine, Stanford, CA, USA
| | - Ellen A Nohr
- Research Unit for Gynaecology and Obstetrics, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, the Netherlands
- Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, the Netherlands
| | - Fernando Rivadeneira
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Charlotta Pisinger
- Research Center for Prevention and Health, Center for Sundhed, Rigshospitalet Glostrup, Copenhagen University, Glostrup, Denmark
| | - Allan A Vaag
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, Copenhagen University, Copenhagen, Denmark
- Cardiovascular, Renal and Metabolism, Translational Medicine Unit, Early Clinical Development, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - André G Uitterlinden
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Biocenter Oulu, University of Oulu, Oulu, Finland
- Unit of Primary Health Care, Oulu University Hospital, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Christine Power
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Elina Hyppönen
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, South Australia, Australia
- South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia
| | - Denise M Scholtens
- Department of Preventive Medicine, Division of Biostatistics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - William L Lowe
- Department of Medicine, Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Nicholas J Timpson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew P Morris
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Biostatistics, University of Liverpool, Liverpool, UK
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Struan F A Grant
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy M Frayling
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK
| | - Debbie A Lawlor
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Pål R Njølstad
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Stefan Johansson
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Ken K Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - John R B Perry
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - David M Evans
- University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Queensland, Australia.
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Rachel M Freathy
- Institute of Biomedical and Clinical Science, College of Medicine and Health, University of Exeter, Royal Devon and Exeter Hospital, Exeter, UK.
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
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Punakallio A, Lusa S, Ala-Mursula L, Ek E, Nevanperä N, Remes J, Auvinen J, Seitsamo J, Karppinen J, Laitinen J. Personal meaning of work and perceived work ability among middle-aged workers with physically strenuous work: a Northern Finland Birth Cohort 1966 Study. Int Arch Occup Environ Health 2019; 92:371-381. [PMID: 30767053 PMCID: PMC6420453 DOI: 10.1007/s00420-019-01412-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Accepted: 01/24/2019] [Indexed: 11/26/2022]
Abstract
PURPOSE To investigate the association between personal meaning of work and perceived work ability among middle-aged workers with physically strenuous or light work. We evaluated the course of perceived work ability from 31 to 46 years and examined the possible differences in the association between personal meaning of work and perceived work ability at the age of 46 depending on physical workload. METHODS The study population consisted of participants of the Northern Finland Birth Cohort 1966 (n = 4420). Data were collected through questionnaires at 31 and 46 years. The main outcome was perceived work ability (0-7 = poor, 8-10 = good) and the main explanatory measures were physically strenuous work and personal meaning of work. Multivariate logistic regression analyses were adjusted for unhealthy habits, number of diseases, job strain, social support at work, employment history and gender. They were also stratified for the strenuousness of work. RESULTS Perceived work ability decreased during the 15-year follow-up in both the strenuous and light work groups, and was lowest among workers with strenuous work. Perceived work ability remained poor or decreased in 22% of men and 21% of women in the strenuous work group vs. 14% and 13% in the light work group, respectively. After adjusting for confounders, the participants in both groups who reported low personal meaning of work were at approximately a twofold risk of having poor perceived work ability at 46 years compared to the participants who reported high personal meaning of work. CONCLUSIONS Perceived work ability was significantly lower and deteriorated more during the follow-up among participants with strenuous work. High personal meaning of work was important for good work ability, irrespective of the strenuousness of work.
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Affiliation(s)
- Anne Punakallio
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland.
| | - Sirpa Lusa
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland
| | - Leena Ala-Mursula
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Ellen Ek
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Nina Nevanperä
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland
| | - Jouko Remes
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland
| | - Juha Auvinen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jorma Seitsamo
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland
| | - Jaro Karppinen
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Jaana Laitinen
- Finnish Institute of Occupational Health, PO Box 40, 00032, Työterveyslaitos, Helsinki, Finland
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36
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Perkiömäki N, Auvinen J, Tulppo MP, Ollila MM, Junttila J, Perkiömäki J, Karhunen V, Puukka K, Järvelin MR, Huikuri HV, Kiviniemi AM. Childhood growth patterns and cardiovascular autonomic modulation in midlife: Northern Finland 1966 Birth Cohort Study. Int J Obes (Lond) 2019; 43:2264-2272. [PMID: 30718821 DOI: 10.1038/s41366-019-0333-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 01/15/2019] [Accepted: 01/20/2019] [Indexed: 12/31/2022]
Abstract
OBJECTIVES To test the hypothesis that age and body mass index (BMI) at BMI peak during infancy and at BMI rebound in childhood are related to cardiovascular autonomic modulation in adulthood. METHODS At the age of 46 years, a sample (n = 5861) of the participants of the Northern Finland Birth Cohort 1966 took part in follow-up examinations. Heart rate variability (HRV), baroreflex sensitivity (BRS) and low-frequency oscillations of systolic blood pressure (LFSBP) were measured during sympathetic stimulus by standing. BMI at various ages was calculated from frequent anthropometric measurements collected from child welfare clinical records. BRS and LFSBP were available for 1243 participants with BMI peak data and 1524 participants with BMI rebound data, and HRV for 2137 participants with BMI peak data and 2688 participants with BMI rebound data. RESULTS Age at BMI rebound had a significant inverse association with LFSBP (beta = -0.071, p = 0.006) after all adjustments (p < 0.001) and was also directly associated with BRS (beta = 0.082, p = 0.001) independently of birth and maternal factors (p = 0.023). BMI at BMI peak and at BMI rebound was inversely associated with high-frequency component of HRV (HF) (beta = -0.045, p = 0.036 for BMI at peak; beta = -0.043, p = 0.024 for BMI at rebound) and directly associated with the ratio of low- and high-frequency components of HRV (LF/HF ratio) (beta = 0.084, p = < 0.001 for BMI at peak; beta = 0.069, p < 0.001 for BMI at rebound). These associations remained significant after all adjustments (p < 0.05 for all). CONCLUSIONS This novel study shows that younger age at BMI rebound and higher BMI at BMI peak and at BMI rebound are associated with higher levels in markers suggestive of augmented sympathetic and reduced vagal cardiovascular modulation in midlife.
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Affiliation(s)
- Nelli Perkiömäki
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland.
| | - Juha Auvinen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Unit of Primary Health Care, Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland
| | - Mikko P Tulppo
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Meri-Maija Ollila
- PEDEGO Research Unit, Medical Research Center Oulu, Department of Obstetrics and Gynecology, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juhani Junttila
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Juha Perkiömäki
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Ville Karhunen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Katri Puukka
- NordLab Oulu, Medical Research Center Oulu, Oulu University Hospital and Department of Clinical Chemistry, University of Oulu, Oulu, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Unit of Primary Health Care, Medical Research Center Oulu, Oulu University Hospital, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, UK.,Department of Life Sciences, College of Health and Life Sciences, Brunel University London, Uxbridge, UK
| | - Heikki V Huikuri
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Antti M Kiviniemi
- Research Unit of Internal Medicine, Medical Research Center Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
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37
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Cai L, Ma B, Lin L, Chen Y, Yang W, Ma J, Jing J. The differences of lipid profiles between only children and children with siblings: A national survey in China. Sci Rep 2019; 9:1441. [PMID: 30723228 PMCID: PMC6363803 DOI: 10.1038/s41598-018-37695-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Accepted: 12/07/2018] [Indexed: 11/17/2022] Open
Abstract
With the increasing number of the one-child family, it is important to investigate whether the only-child status is associated with dyslipidemia. Among a national sample of 65,347 Chinese children aged 6–17 years, 16,100 lipid profiles were available. Children’s height, weight, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured. In comparison to children with siblings, only children (OC) were more likely to be boys and live in urban areas. OC had less physical activity, less fried food intake, but more meat and dairy intakes. OC had significantly higher levels of TC (3.97 ± 0.78 vs. 3.89 ± 0.77) and LDL-C (2.12 ± 0.65 vs. 2.06 ± 0.64) in the overall group, and also in the subgroups of rural boys and girls. The prevalence of hyper-TC (5.48% vs. 4.43%) and hyper-LDL-C (3.97% vs. 2.96%) were significantly higher in OC than their counterparts. Furthermore, we found higher odds of hyper-LDL-C [1.43 (1.12, 1.83)] in OC after adjustments. In the subgroup analysis, only-child status was associated with increased risk of hyper-TC [1.86 (1.06, 3.26)] and hyper-LDL-C [2.65 (1.14, 6.16)] among rural boys, and hyper-LDL-C among rural girls [2.20 (1.14, 4.22)]. In conclusion, higher levels of TC and LDL-C were found in OC especially for rural children. Being an only-child was associated with increased risk of hyper-LDL-C.
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Affiliation(s)
- Li Cai
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Bingjie Ma
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Lizi Lin
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China.,Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China
| | - Yajun Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Wenhan Yang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing, China.
| | - Jin Jing
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, Guangzhou, China.
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38
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Naidoo S, Kagura J, Fabian J, Norris SA. Early Life Factors and Longitudinal Blood Pressure Trajectories Are Associated With Elevated Blood Pressure in Early Adulthood. Hypertension 2019; 73:301-309. [DOI: 10.1161/hypertensionaha.118.11992] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Sanushka Naidoo
- From the MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics and Child Health (S.N., J.K., S.A.N.), University of the Witwatersrand, Johannesburg, South Africa
| | - Juliana Kagura
- From the MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics and Child Health (S.N., J.K., S.A.N.), University of the Witwatersrand, Johannesburg, South Africa
- School of Public Health (J.K.), University of the Witwatersrand, Johannesburg, South Africa
| | - June Fabian
- Wits Donald Gordon Medical Centre (J.F.), University of the Witwatersrand, Johannesburg, South Africa
- Division of Nephrology, Department of Internal Medicine, School of Clinical Medicine (J.F.), University of the Witwatersrand, Johannesburg, South Africa
| | - Shane A. Norris
- From the MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics and Child Health (S.N., J.K., S.A.N.), University of the Witwatersrand, Johannesburg, South Africa
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Abstract
Blood pressure (BP) tracks from childhood to adulthood, and early BP trajectories predict cardiovascular disease risk later in life. Excess postnatal weight gain is associated with vascular changes early in life. However, to what extent it is associated with children's BP is largely unknown. In 853 healthy 5-year-old children of the Wheezing-Illnesses-Study-Leidsche-Rijn (WHISTLER) birth cohort, systolic (SBP) and diastolic BP (DBP) were measured, and z scores of individual weight gain rates adjusted for length gain rates were calculated using at least two weight and length measurements from birth until 3 months of age. Linear regression analyses were conducted to investigate the association between weight gain rates adjusted for length gain rates and BP adjusted for sex and ethnicity. Each standard deviation increase in weight gain rates adjusted for length gain rates was associated with 0.9 mmHg (95% CI 0.3, 1.5) higher sitting SBP after adjustment for confounders. Particularly in children in the lowest birth size decile, high excess weight gain was associated with higher sitting SBP values compared to children with low weight gain rates adjusted for length gain rates. BMI and visceral adipose tissue partly explained the association between excess weight gain and sitting SBP (β 0.5 mmHg, 95% CI -0.3, 1.3). Weight gain rates adjusted for length gain rates were not associated with supine SBP or DBP. Children with excess weight gain, properly adjusted for length gain, in the first three months of life, particularly those with a small birth size, showed higher sitting systolic BP at the age of 5 years.
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40
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Brzyski D, Gossmann A, Su W, Bogdan M. Group SLOPE - adaptive selection of groups of predictors. J Am Stat Assoc 2018; 114:419-433. [PMID: 31217649 PMCID: PMC6583898 DOI: 10.1080/01621459.2017.1411269] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Revised: 11/01/2017] [Indexed: 10/18/2022]
Abstract
Sorted L-One Penalized Estimation (SLOPE, Bogdan et al., 2013, 2015) is a relatively new convex optimization procedure which allows for adaptive selection of regressors under sparse high dimensional designs. Here we extend the idea of SLOPE to deal with the situation when one aims at selecting whole groups of explanatory variables instead of single regressors. Such groups can be formed by clustering strongly correlated predictors or groups of dummy variables corresponding to different levels of the same qualitative predictor. We formulate the respective convex optimization problem, gSLOPE (group SLOPE), and propose an efficient algorithm for its solution. We also define a notion of the group false discovery rate (gFDR) and provide a choice of the sequence of tuning parameters for gSLOPE so that gFDR is provably controlled at a prespecified level if the groups of variables are orthogonal to each other. Moreover, we prove that the resulting procedure adapts to unknown sparsity and is asymptotically minimax with respect to the estimation of the proportions of variance of the response variable explained by regressors from different groups. We also provide a method for the choice of the regularizing sequence when variables in different groups are not orthogonal but statistically independent and illustrate its good properties with computer simulations. Finally, we illustrate the advantages of gSLOPE in the context of Genome Wide Association Studies. R package grpSLOPE with an implementation of our method is available on CRAN.
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Affiliation(s)
- Damian Brzyski
- Department of Epidemiology and Biostatistics, Indiana University, Bloomington, IN 47405, USA
- Institute of Mathematics, Jagiellonian University, 30-348 Cracow, Poland
| | - Alexej Gossmann
- Bioinnovation PhD Program, Tulane University, New Orleans, LA 70118, USA
| | - Weijie Su
- Department of Statistics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Małgorzata Bogdan
- Institute of Mathematics, University of Wroclaw, 50-384 Wroclaw, Poland
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41
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Effect of early postnatal nutrition on chronic kidney disease and arterial hypertension in adulthood: a narrative review. J Dev Orig Health Dis 2018; 9:598-614. [PMID: 30078383 DOI: 10.1017/s2040174418000454] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Intrauterine growth restriction (IUGR) has been identified as a risk factor for adult chronic kidney disease (CKD), including hypertension (HTN). Accelerated postnatal catch-up growth superimposed to IUGR has been shown to further increase the risk of CKD and HTN. Although the impact of excessive postnatal growth without previous IUGR is less clear, excessive postnatal overfeeding in experimental animals shows a strong impact on the risk of CKD and HTN in adulthood. On the other hand, food restriction in the postnatal period seems to have a protective effect on CKD programming. All these effects are mediated at least partially by the activation of the renin-angiotensin system, leptin and neuropeptide Y (NPY) signaling and profibrotic pathways. Early nutrition, especially in the postnatal period has a significant impact on the risk of CKD and HTN at adulthood and should receive specific attention in the prevention of CKD and HTN.
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42
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Nedelec R, Jokelainen J, Miettunen J, Ruokonen A, Herzig KH, Männikkö M, Järvelin MR, Sebert S. Early determinants of metabolically healthy obesity in young adults: study of the Northern Finland Birth Cohort 1966. Int J Obes (Lond) 2018; 42:1704-1714. [PMID: 29795454 DOI: 10.1038/s41366-018-0115-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 04/06/2018] [Accepted: 04/17/2018] [Indexed: 12/13/2022]
Abstract
BACKGROUND A body of literature suggests a metabolically healthy phenotype in individuals with obesity. Despite important clinical implications, the early origins of metabolically healthy obesity (MHO) have received little attention. OBJECTIVE To assess the prevalence of MHO among the Northern Finland Birth Cohort 1966 (NFBC1966) at 31 years of age, examine its determinants in early life taking into account the sex specificity. METHODS We studied 3205 term-born cohort participants with data available for cardio-metabolic health outcomes at 31 years, and longitudinal height and weight data. After stratifying the population by sex, adult BMI and a strict definition of metabolic health (i.e., no risk factors meaning metabolic health), we obtained six groups. Repeated childhood height and weight measures were used to model early growth and early adiposity phenotypes. We employed marginal means adjusted for mother and child covariates including socio-economic status, birth weight and gestational-age, to compare differences between the groups. RESULTS The prevalence of adult MHO was 6% in men and 13.5% in women. Differences in adult metabolic status were linked to alterations in BMI and age at adiposity peak in infancy (p < 0.0003 in men and p = 0.027 in women), and BMI and age at adiposity rebound (AR) (p < 0.0001 irrespective of sex). Compared to MHO, metabolically unhealthy obese (MUO) women were five and a half months younger at AR (p = 0.007) with a higher BMI while MUO men were four months older (p = 0.036) with no difference in BMI at AR. CONCLUSION At the time of AR, MHO women appeared to be older than their MUO counterparts while MHO men were younger. These original results support potential risk factors at the time of adiposity rebound linked to metabolic health in adulthood. These variations by sex warrant independent replication.
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Affiliation(s)
- Rozenn Nedelec
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jari Jokelainen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Unit of Primary Care, Oulu University Hospital, Oulu, Finland
| | - Jouko Miettunen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University, Oulu, Finland
| | - Aimo Ruokonen
- NordLab Oulu, Department of Clinical Chemistry, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Karl-Heinz Herzig
- Biocenter Oulu, University of Oulu, Oulu, Finland.,Unit of Primary Care, Oulu University Hospital, Oulu, Finland.,Medical Research Center Oulu, Oulu University Hospital and University, Oulu, Finland.,Research Unit of Biomedicine, Department of Physiology, University of Oulu, Oulu, Finland.,Department of Gastroenterology and Metabolism, Poznan University of Medical Sciences, Poznan, Poland
| | - Minna Männikkö
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland. .,Biocenter Oulu, University of Oulu, Oulu, Finland. .,Unit of Primary Care, Oulu University Hospital, Oulu, Finland. .,Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK. .,MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College, London, UK. .,Department of Life Sciences, College of Health and Life Sciences, Brunel University, London, UK.
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland.,Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Genomics of Complex Diseases, School of Public Health, Imperial College, London, UK
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43
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Metrustry SJ, Karhunen V, Edwards MH, Menni C, Geisendorfer T, Huber A, Reichel C, Dennison EM, Cooper C, Spector T, Jarvelin MR, Valdes AM. Metabolomic signatures of low birthweight: Pathways to insulin resistance and oxidative stress. PLoS One 2018; 13:e0194316. [PMID: 29566009 PMCID: PMC5863971 DOI: 10.1371/journal.pone.0194316] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2017] [Accepted: 02/27/2018] [Indexed: 12/20/2022] Open
Abstract
Several studies suggest that low birthweight resulting from restricted intrauterine growth can leave a metabolic footprint which may persist into adulthood. To investigate this, we performed metabolomic profiling on 5036 female twins, aged 18-80, with weight at birth information available from the TwinsUK cohort and performed independent replication in two additional cohorts. Out of 422 compounds tested, 25 metabolites associated with birthweight in these twins, replicated in 1951 men and women from the Hertfordshire Cohort Study (HCS, aged 66) and in 2391 men and women from the North Finland Birth 1986 cohort (NFBC, aged 16). We found distinct heterogeneity between sexes and, after adjusting for multiple tests and heterogeneity, two metabolites were reproducible overall (propionylcarnitine and 3-4-hydroxyphenyllactate). Testing women only, we found other metabolites associated with lower birthweight from the meta-analysis of the three cohorts (2-hydroxy-butyric acid and γ-glutamylleucine). Higher levels of all these metabolites can be linked to insulin resistance, oxidative stress or a dysfunction of energy metabolism, suggesting that low birthweight in both twins and singletons are having an impact on these pathways in adulthood.
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Affiliation(s)
- Sarah Jane Metrustry
- Department of Twin Research and Genetic Epidemiology, Kings College London, St Thomas' Hospital, London, United Kingdom
| | - Ville Karhunen
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Oulu University Hospital, Unit of Primary Care, Oulu, Finland
| | - Mark H Edwards
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, United Kingdom
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, Kings College London, St Thomas' Hospital, London, United Kingdom
| | | | - Anja Huber
- Seibersdorf Labor GmbH, Seibersdorf, Vienna, Austria
| | | | - Elaine M Dennison
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, United Kingdom.,Victoria University, Wellington, New Zealand
| | - Cyrus Cooper
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, United Kingdom.,NIHR Musculoskeletal Biomedical Research Unit, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom.,NIHR Nutrition Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton General Hospital, Southampton, United Kingdom
| | - Tim Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, St Thomas' Hospital, London, United Kingdom
| | - Marjo-Riitta Jarvelin
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.,Oulu University Hospital, Unit of Primary Care, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment & Health, School of Public Health, Imperial College London, London, United Kingdom.,Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Ana M Valdes
- Department of Twin Research and Genetic Epidemiology, Kings College London, St Thomas' Hospital, London, United Kingdom.,University of Nottingham, Nottingham, United Kingdom
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Abstract
Atherosclerotic cardiovascular disease is a leading cause of death and disability worldwide, and the atherosclerotic process begins in childhood. Prevention or containment of risk factors that accelerate atherosclerosis can delay the development of atherosclerotic cardiovascular disease. Although current recommendations are to periodically screen for commonly prevailing risk factors for atherosclerosis in children, a single test that could quantify the cumulative effect of all risk factors on the vasculature, thus assessing arterial health, would be helpful in further stratifying risk. Measurement of pulse wave velocity and assessment of augmentation index - measures of arterial stiffness - are easy-to-use, non-invasive methods of examining arterial health. Various studies have assessed pulse wave velocity and augmentation index in children with commonly occurring conditions including obesity, hypertension, insulin resistance, diabetes mellitus, dyslipidaemia, physical inactivity, chronic kidney disease, CHD and acquired heart diseases, and in children who were born premature or small for gestational age. This article summarises pulse wave velocity and augmentation index assessments and the effects of commonly prevailing chronic conditions on arterial health in children. In addition, currently available reference values for pulse wave velocity and augmentation index in healthy children are included. Further research to establish widely applicable normative values and the effect of lifestyle and pharmacological interventions on arterial health in children is needed.
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Würtz P, Wang Q, Niironen M, Tynkkynen T, Tiainen M, Drenos F, Kangas AJ, Soininen P, Skilton MR, Heikkilä K, Pouta A, Kähönen M, Lehtimäki T, Rose RJ, Kajantie E, Perola M, Kaprio J, Eriksson JG, Raitakari OT, Lawlor DA, Davey Smith G, Järvelin MR, Ala-Korpela M, Auro K. Metabolic signatures of birthweight in 18 288 adolescents and adults. Int J Epidemiol 2018; 45:1539-1550. [PMID: 27892411 PMCID: PMC5100627 DOI: 10.1093/ije/dyw255] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2016] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Lower birthweight is associated with increased susceptibility to cardiometabolic diseases in adulthood, but the underlying molecular pathways are incompletely understood. We examined associations of birthweight with a comprehensive metabolic profile measured in adolescents and adults. METHODS High-throughput nuclear magnetic resonance metabolomics and biochemical assays were used to quantify 87 circulating metabolic measures in seven cohorts from Finland and the UK, comprising altogether 18 288 individuals (mean age 26 years, range 15-75). Metabolic associations with birthweight were assessed by linear regression models adjusted for sex, gestational age and age at blood sampling. The metabolic associations with birthweight were compared with the corresponding associations with adult body mass index (BMI). RESULTS Lower birthweight adjusted for gestational age was adversely associated with cardiometabolic biomarkers, including lipoprotein subclasses, fatty acids, amino acids and markers of inflammation and impaired liver function (P < 0.0015 for 46 measures). Associations were consistent across cohorts with different ages at metabolic profiling, but the magnitudes were weak. The pattern of metabolic deviations associated with lower birthweight resembled the metabolic signature of higher adult BMI (R2 = 0.77) assessed at the same time as the metabolic profiling. The resemblance indicated that 1 kg lower birthweight is associated with similar metabolic aberrations as caused by 0.92 units higher BMI in adulthood. CONCLUSIONS Lower birthweight adjusted for gestational age is associated with adverse biomarker aberrations across multiple metabolic pathways. Coherent metabolic signatures between lower birthweight and higher adult adiposity suggest that shared molecular pathways may potentially underpin the metabolic deviations. However, the magnitudes of metabolic associations with birthweight are modest in comparison to the effects of adiposity, implying that birthweight is only a weak indicator of the metabolic risk profile in adulthood.
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Affiliation(s)
- Peter Würtz
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
| | - Qin Wang
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Marjo Niironen
- Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Tuulia Tynkkynen
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Mika Tiainen
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Fotios Drenos
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Antti J Kangas
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
| | - Pasi Soininen
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Michael R Skilton
- Boden Institute of Obesity, Nutrition, Exercise, and Eating Disorders, University of Sydney, Sydney, NSW, Australia
| | - Kauko Heikkilä
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Anneli Pouta
- Center for Life Course Health Research and Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland
| | - Richard J Rose
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Eero Kajantie
- Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.,Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Research Unit for Pediatrics, Dermatology, Clinical Genetics, Obstetrics and Gynecology, and Medical Research Unit Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland
| | - Markus Perola
- Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Jaakko Kaprio
- Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.,Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Johan G Eriksson
- Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.,Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland.,Unit of General Practice, Helsinki University Hospital, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland.,Vasa Central Hospital, Vasa, Finland
| | - Olli T Raitakari
- 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
| | - Debbie A Lawlor
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Marjo-Riitta Järvelin
- Center for Life Course Health Research and Biocenter Oulu, University of Oulu, Oulu, Finland.,Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Mika Ala-Korpela
- Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory School of Pharmacy, University of Eastern Finland, Kuopio, Finland.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Kirsi Auro
- Department of Genomics and Biomarkers, National Institute for Health and Welfare, Helsinki, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
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Arima Y, Nishiyama K, Izumiya Y, Kaikita K, Hokimoto S, Tsujita K. Fetal Origins of Hypertension. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2018; 1012:41-48. [PMID: 29956193 DOI: 10.1007/978-981-10-5526-3_5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Hypertension is a common noncommunicable disease. According to the World Health Organization, 1.13 billion people were suffering from hypertension in the year 2015. High blood pressure, hypertension, has a multifactorial etiology. Arterial atherosclerotic changes, systolic or diastolic dysfunction of the heart, and other noncardiac factors are involved. Epidemiological evidence has revealed that perinatal growth disturbance elevates the prevalence of hypertension. However, the specific effects of developmental disturbances on the pathological process of hypertension are poorly understood. Recently, it has become apparent that the perinatal period plays many essential roles in cardiovascular development. In this chapter, we focus on the perinatal development of the cardiovascular system, especially in murine models. Individual organs, blood, blood vessels, and the heart show unique growth characteristics during this period. We also introduce evidence from related clinical studies regarding the developmental origins of hypertension. Finally, evidence from several animal models is presented to reveal the effects of developmental disturbance or stress on arterial pathology. Improving our understanding of both developmental events and the results of clinical studies will give fresh insight into the fetal origins of hypertension.
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Affiliation(s)
- Yuichiro Arima
- Department of Cardiovascular Medicine, Kumamoto University, Kumamoto, Japan. .,International Research Center for Medical Science, Kumamoto University, Kumamoto, Japan.
| | - Koichi Nishiyama
- International Research Center for Medical Science, Kumamoto University, Kumamoto, Japan
| | - Yasuhiro Izumiya
- Department of Cardiovascular Medicine, Kumamoto University, Kumamoto, Japan
| | - Koichi Kaikita
- Department of Cardiovascular Medicine, Kumamoto University, Kumamoto, Japan
| | - Seiji Hokimoto
- Department of Cardiovascular Medicine, Kumamoto University, Kumamoto, Japan
| | - Kenichi Tsujita
- Department of Cardiovascular Medicine, Kumamoto University, Kumamoto, Japan
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Salo PP, Havulinna AS, Tukiainen T, Raitakari O, Lehtimäki T, Kähönen M, Kettunen J, Männikkö M, Eriksson JG, Jula A, Blankenberg S, Zeller T, Salomaa V, Kristiansson K, Perola M. Genome-Wide Association Study Implicates Atrial Natriuretic Peptide Rather Than B-Type Natriuretic Peptide in the Regulation of Blood Pressure in the General Population. CIRCULATION. CARDIOVASCULAR GENETICS 2017; 10:e001713. [PMID: 29237677 PMCID: PMC6072381 DOI: 10.1161/circgenetics.117.001713] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 10/03/2017] [Indexed: 12/25/2022]
Abstract
BACKGROUND Cardiomyocytes secrete atrial natriuretic peptide (ANP) and B-type natriuretic peptide (BNP) in response to mechanical stretching, making them useful clinical biomarkers of cardiac stress. Both human and animal studies indicate a role for ANP as a regulator of blood pressure with conflicting results for BNP. METHODS AND RESULTS We used genome-wide association analysis (n=6296) to study the effects of genetic variants on circulating natriuretic peptide concentrations and compared the impact of natriuretic peptide-associated genetic variants on blood pressure (n=27 059). Eight independent genetic variants in 2 known (NPPA-NPPB and POC1B-GALNT4) and 1 novel locus (PPP3CC) associated with midregional proANP (MR-proANP), BNP, aminoterminal proBNP (NT-proBNP), or BNP:NT-proBNP ratio. The NPPA-NPPB locus containing the adjacent genes encoding ANP and BNP harbored 4 independent cis variants with effects specific to either midregional proANP or BNP and a rare missense single nucleotide polymorphism in NT-proBNP seriously altering its measurement. Variants near the calcineurin catalytic subunit gamma gene PPP3CC and the polypeptide N-acetylgalactosaminyltransferase 4 gene GALNT4 associated with BNP:NT-proBNP ratio but not with BNP or midregional proANP, suggesting effects on the post-translational regulation of proBNP. Out of the 8 individual variants, only those correlated with midregional proANP had a statistically significant albeit weak impact on blood pressure. The combined effect of these 3 single nucleotide polymorphisms also associated with hypertension risk (P=8.2×10-4). CONCLUSIONS Common genetic differences affecting the circulating concentration of ANP associated with blood pressure, whereas those affecting BNP did not, highlighting the blood pressure-lowering effect of ANP in the general population.
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48
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Metabolomics applied to diabetes-lessons from human population studies. Int J Biochem Cell Biol 2017; 93:136-147. [PMID: 29074437 DOI: 10.1016/j.biocel.2017.10.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 09/30/2017] [Accepted: 10/20/2017] [Indexed: 02/08/2023]
Abstract
The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism.
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49
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Bustos P, Amigo H, Bangdiwala SI, Pizarro T, Rona RJ. Does the association between birth weight and blood pressure increase with age? A longitudinal study in young adults. J Hypertens 2017; 34:1062-7. [PMID: 27077730 DOI: 10.1097/hjh.0000000000000912] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To assess whether the association between birth weight and blood pressure (BP) increases with age using three different statistical methods. METHODS A representative sample of 1232 study participants born between 1974-1978 in Limache, Chile were assessed in 2000-2002, of whom 796 were reassessed in 2010-2012. An 'amplification effect' was assessed by the change in the β coefficient in the two periods, the association between birth weight and the difference of BP overtime, and the interaction between birth weight and BP in the two periods. RESULTS Birth weight was negatively associated with SBP in 2000-2002 (β = -2.46, 95% confidence interval (CI) -3.77 to -1.16) and in 2010-2012 (β = -3.64, 95% CI -5.20 to -2.08), and with DBP in 2000-2002 (β = -1.26, 95% CI -2.23 to -0.29) , and 2010-2012 (β = -1.64, 95% CI -2.84 to -0.45) after adjustment for sex, physical activity, and BMI. There was no association between birth weight and the difference in BP between the two periods or the interaction between birth weight, BP, and time interval. CONCLUSION Birth weight is a factor associated with BP in adults. This association increased with age, but amplification was shown only with one of the three methods.
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Affiliation(s)
- Patricia Bustos
- aDepartment of Nutrition, Faculty of Medicine, University of Chile, Santiago, Chile bDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, USA cMinistry of Health of Chile, Santiago, Chile dDepartment of Psychological Medicine, Weston Education Centre, King's College London, London, UK
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50
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Berry DJ, Dutton J, Fraser WD, Järvelin M, Hyppönen E. Harmonization Study Between LC-MS/MS and Diasorin RIA for Measurement of 25-Hydroxyvitamin D Concentrations in a Large Population Survey. J Clin Lab Anal 2017; 31:e22049. [PMID: 27595769 PMCID: PMC5484299 DOI: 10.1002/jcla.22049] [Citation(s) in RCA: 14] [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: 08/02/2015] [Accepted: 07/13/2016] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Population-based research on vitamin D has increased dramatically in recent years. Such studies are typically reliant on assay procedures to measure reliable and comparable levels of 25-hydroxyvitamin D [25(OH)D] concentrations. METHODS Concentrations of 25(OH)D3 and 25(OH)D2 were measured using LC-MS/MS in 5,915 participants (aged 31 years) of Northern Finland Birth Cohort 1966. Blood samples were assayed in batches over a course of 18 months. As anomalies were present in the measurements, 200 samples were reassayed using Diasorin RIA. Agreement between measurements was assessed by Passing-Bablok regression and limits of agreement (LoA). To harmonize LC-MS/MS with Diasorin RIA measurements, formulae were derived from the LoA. RESULTS Concentrations measured by LC-MS/MS were much higher than those measured by Diasorin RIA, with a mean difference of 12.9 ng/ml. Constant variation was evident between batch measurements after log transformation. Statistical formula was applied separately for each batch of LC-MS/MS measurements, enabling us to remove both the constant and proportional bias that was evident prior to the transformation. CONCLUSION Despite the introduction of schemes/programs to improve accuracy of assays to measure 25(OH)D, significant differences can still happen. In these instances, methods to harmonize measurements based on a relatively small number of replicates can be successfully applied to establish confidence and to enable between-study comparisons.
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Affiliation(s)
- Diane J. Berry
- Population, Policy and PracticeUCL Institute of Child HealthLondonUK
| | - John Dutton
- Department of Clinical BiochemistryRoyal Liverpool University HospitalLiverpoolUK
| | - William D. Fraser
- Norwich Medical SchoolUniversity of East AngliaNorwich Research ParkNorwichUK
| | - Marjo‐Riitta Järvelin
- Department of Epidemiology and BiostatisticsMRC Health Protection Agency (HPA) Centre for Environment and HealthSchool of Public HealthImperial College LondonLondonUK
- Unit of Primary CareOulu University HospitalOuluFinland
- Department of Children, Young People and FamiliesNational Institute for Health and WelfareOuluFinland
- Biocenter OuluInstitute of Health SciencesUniversity of OuluOuluFinland
| | - Elina Hyppönen
- Population, Policy and PracticeUCL Institute of Child HealthLondonUK
- Centre for Population Health ResearchSchool of Health Sciences and Sansom Institute of Health ResearchUniversity of South AustraliaAdelaideAustralia
- South Australian Health and Medical Research InstituteAdelaideAustralia
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