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Kaptoge S, Seshasai SRK, Sun L, Walker M, Bolton T, Spackman S, Ataklte F, Willeit P, Bell S, Burgess S, Pennells L, Altay S, Assmann G, Ben-Shlomo Y, Best LG, Björkelund C, Blazer DG, Brenner H, Brunner EJ, Dagenais GR, Cooper JA, Cooper C, Crespo CJ, Cushman M, D'Agostino RB, Daimon M, Daniels LB, Danker R, Davidson KW, de Jongh RT, Donfrancesco C, Ducimetiere P, Elders PJM, Engström G, Ford I, Gallacher I, Bakker SJL, Goldbourt U, de La Cámara G, Grimsgaard S, Gudnason V, Hansson PO, Imano H, Jukema JW, Kabrhel C, Kauhanen J, Kavousi M, Kiechl S, Knuiman MW, Kromhout D, Krumholz HM, Kuller LH, Laatikainen T, Lowler DA, Meyer HE, Mukamal K, Nietert PJ, Ninomiya T, Nitsch D, Nordestgaard BG, Palmieri L, Price JF, Ridker PM, Sun Q, Rosengren A, Roussel R, Sakurai M, Salomaa V, Schöttker B, Shaw JE, Strandberg TE, Sundström J, Tolonen H, Tverdal A, Verschuren WMM, Völzke H, Wagenknecht L, Wallace RB, Wannamethee SG, Wareham NJ, Wassertheil-Smoller S, Yamagishi K, Yeap BB, Harrison S, Inouye M, Griffin S, Butterworth AS, Wood AM, Thompson SG, Sattar N, Danesh J, Di Angelantonio E, Tipping RW, Russell S, Johansen M, Bancks MP, Mongraw-Chaffin M, Magliano D, Barr ELM, Zimmet PZ, Knuiman MW, Whincup PH, Willeit J, Willeit P, Leitner C, Lawlor DA, Ben-Shlomo Y, Elwood P, Sutherland SE, Hunt KJ, Cushman M, Selmer RM, Haheim LL, Ariansen I, Tybjaer-Hansen A, Frikkle-Schmidt R, Langsted A, Donfrancesco C, Lo Noce C, Balkau B, Bonnet F, Fumeron F, Pablos DL, Ferro CR, Morales TG, Mclachlan S, Guralnik J, Khaw KT, Brenner H, Holleczek B, Stocker H, Nissinen A, Palmieri L, Vartiainen E, Jousilahti P, Harald K, Massaro JM, Pencina M, Lyass A, Susa S, Oizumi T, Kayama T, Chetrit A, Roth J, Orenstein L, Welin L, Svärdsudd K, Lissner L, Hange D, Mehlig K, Salomaa V, Tilvis RS, Dennison E, Cooper C, Westbury L, Norman PE, Almeida OP, Hankey GJ, Hata J, Shibata M, Furuta Y, Bom MT, Rutters F, Muilwijk M, Kraft P, Lindstrom S, Turman C, Kiyama M, Kitamura A, Yamagishi K, Gerber Y, Laatikainen T, Salonen JT, van Schoor LN, van Zutphen EM, Verschuren WMM, Engström G, Melander O, Psaty BM, Blaha M, de Boer IH, Kronmal RA, Sattar N, Rosengren A, Nitsch D, Grandits G, Tverdal A, Shin HC, Albertorio JR, Gillum RF, Hu FB, Cooper JA, Humphries S, Hill- Briggs F, Vrany E, Butler M, Schwartz JE, Kiyama M, Kitamura A, Iso H, Amouyel P, Arveiler D, Ferrieres J, Gansevoort RT, de Boer R, Kieneker L, Crespo CJ, Assmann G, Trompet S, Kearney P, Cantin B, Després JP, Lamarche B, Laughlin G, McEvoy L, Aspelund T, Thorsson B, Sigurdsson G, Tilly M, Ikram MA, Dorr M, Schipf S, Völzke H, Fretts AM, Umans JG, Ali T, Shara N, Davey-Smith G, Can G, Yüksel H, Özkan U, Nakagawa H, Morikawa Y, Ishizaki M, Njølstad I, Wilsgaard T, Mathiesen E, Sundström J, Buring J, Cook N, Arndt V, Rothenbacher D, Manson J, Tinker L, Shipley M, Tabak AG, Kivimaki M, Packard C, Robertson M, Feskens E, Geleijnse M, Kromhout D. Life expectancy associated with different ages at diagnosis of type 2 diabetes in high-income countries: 23 million person-years of observation. Lancet Diabetes Endocrinol 2023; 11:731-742. [PMID: 37708900 PMCID: PMC7615299 DOI: 10.1016/s2213-8587(23)00223-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 07/14/2023] [Accepted: 07/14/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND The prevalence of type 2 diabetes is increasing rapidly, particularly among younger age groups. Estimates suggest that people with diabetes die, on average, 6 years earlier than people without diabetes. We aimed to provide reliable estimates of the associations between age at diagnosis of diabetes and all-cause mortality, cause-specific mortality, and reductions in life expectancy. METHODS For this observational study, we conducted a combined analysis of individual-participant data from 19 high-income countries using two large-scale data sources: the Emerging Risk Factors Collaboration (96 cohorts, median baseline years 1961-2007, median latest follow-up years 1980-2013) and the UK Biobank (median baseline year 2006, median latest follow-up year 2020). We calculated age-adjusted and sex-adjusted hazard ratios (HRs) for all-cause mortality according to age at diagnosis of diabetes using data from 1 515 718 participants, in whom deaths were recorded during 23·1 million person-years of follow-up. We estimated cumulative survival by applying age-specific HRs to age-specific death rates from 2015 for the USA and the EU. FINDINGS For participants with diabetes, we observed a linear dose-response association between earlier age at diagnosis and higher risk of all-cause mortality compared with participants without diabetes. HRs were 2·69 (95% CI 2·43-2·97) when diagnosed at 30-39 years, 2·26 (2·08-2·45) at 40-49 years, 1·84 (1·72-1·97) at 50-59 years, 1·57 (1·47-1·67) at 60-69 years, and 1·39 (1·29-1·51) at 70 years and older. HRs per decade of earlier diagnosis were similar for men and women. Using death rates from the USA, a 50-year-old individual with diabetes died on average 14 years earlier when diagnosed aged 30 years, 10 years earlier when diagnosed aged 40 years, or 6 years earlier when diagnosed aged 50 years than an individual without diabetes. Using EU death rates, the corresponding estimates were 13, 9, or 5 years earlier. INTERPRETATION Every decade of earlier diagnosis of diabetes was associated with about 3-4 years of lower life expectancy, highlighting the need to develop and implement interventions that prevent or delay the onset of diabetes and to intensify the treatment of risk factors among young adults diagnosed with diabetes. FUNDING British Heart Foundation, Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.
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Bosman A, Koek WNH, Campos-Obando N, van der Eerden BCJ, Ikram MA, Uitterlinden AG, van Leeuwen JPTM, Zillikens MC. Sexual dimorphisms in serum calcium and phosphate concentrations in the Rotterdam Study. Sci Rep 2023; 13:8310. [PMID: 37221192 DOI: 10.1038/s41598-023-34800-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 05/08/2023] [Indexed: 05/25/2023] Open
Abstract
Sex differences in serum phosphate and calcium have been reported but the exact nature and underlying regulatory mechanisms remain unclear. We aimed to compare calcium and phosphate concentrations between sexes, and explore potential covariates to elucidate underlying mechanisms of sex differences in a prospective, population-based cohort study. Pooled data of subjects > 45 years from three independent cohorts of the Rotterdam Study (RS) were used: RS-I-3 (n = 3623), RS-II-1 (n = 2394), RS-III-1 (n = 3241), with separate analyses from an additional time point of the first cohort RS-I-1 (n = 2688). Compared to men, women had significantly higher total serum calcium and phosphate concentrations which was not explained by BMI, kidney function nor smoking. Adjustment for serum estradiol diminished sex differences in serum calcium while adjustment for serum testosterone diminished sex differences in serum phosphate. Adjustment for vitamin D and alkaline phosphatase did not change the association between sex and calcium or phosphate in RS-I-1. In the sex-combined group, both serum calcium and phosphate decreased with age with a significant interaction for sex differences for serum calcium but not phosphate. In sex-stratified analyses, serum estradiol but not testosterone was inversely associated with serum calcium in both sexes. Serum estradiol was inversely associated with serum phosphate in both sexes to a similar degree, while serum testosterone was inversely associated with serum phosphate in both sexes with an apparent stronger effect in men than in women. Premenopausal women had lower serum phosphate compared to postmenopausal women. Serum testosterone was inversely associated with serum phosphate in postmenopausal women only. In conclusion, women > 45 years have higher serum calcium and phosphate concentrations compared to men of similar age, not explained by vitamin D or alkaline phosphatase concentrations. Serum estradiol but not testosterone was inversely associated with serum calcium while serum testosterone was inversely associated with serum phosphate in both sexes. Serum testosterone may in part explain sex differences in serum phosphate while estradiol could partly explain sex differences in serum calcium.
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Affiliation(s)
- Ariadne Bosman
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - W Nadia H Koek
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Natalia Campos-Obando
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - Bram C J van der Eerden
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Johannes P T M van Leeuwen
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands
| | - M C Zillikens
- Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, PO Box 2040, 3000 CA, Rotterdam, The Netherlands.
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Lu Z, Tilly M, Wolters F, De Groot NMS, Ikram MA, Kavousi M. Plasma amyloid-beta levels and risk of new-onset atrial fibrillation in the general population. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.2302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
Atrial fibrillation (AF) is a major health burden worldwide, with significant sex differences in epidemiology and risk factors. Amyloid-β40 (Aβ40) and Amyloid-β42 (Aβ42), the hallmark of cerebral amyloid angiopathy, have recently been linked to prevalence and prognosis of several cardiovascular outcomes including stroke and coronary heart disease. However, whether these biomarkers are associated with incident AF remains largely unknown.
Purpose
To investigate the associations between plasma concentrations of Aβ40 and Aβ42 with new-onset AF.
Methods
4,134 participants without a history of AF at baseline (from 2002 to 2005) with qualified plasma samples in the Rotterdam Study were included in this study. AF was diagnosed by electrocardiograms, general practitioners' and hospital records. Cox proportional hazards regression models with natural cubic splines were used to assess the linear/nonlinear association between biomarkers and risk of new-onset AF. All models were adjusted for traditional cardiovascular risk factors.
Results
Mean age was 71.3±7.2 years and 2,383 (57.6%) were women. Median follow-up time was 9.2 years. In the fully adjusted model, higher levels of Aβ40 [hazard ratio, 95% confidence interval: 1.16 (1.05–1.28)] and Aβ42 [1.19 (1.09–1.31)], as well as Amyloid-β42 to β40 ratio (Aβ42/40) [1.09 (1.02–1.17)] were significantly associated with incident AF. The observed association between Aβ40 and AF attenuated after mutual adjustment for Aβ42 [1.05 (0.92–1.19)]. In addition, a J-shaped association was found between Aβ40 and AF with the lowest AF risk at Aβ40 values of 212.5 pg/ml.
Conclusions
Both Aβ40 and Aβ42 were independently significantly associated with new-onset AF in the general population independent of cardiovascular risk factors. Findings also suggest a stronger association between AF onset and Aβ42 and AF onset, compared to Aβ40. A nonlinear association was found between Aβ40 and AF, reflecting a substantially increased AF risk among participants with severely increased Aβ40 values.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- Z Lu
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - M Tilly
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - F Wolters
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - N M S De Groot
- Erasmus University Medical Centre, Department of Cardiology , Rotterdam , The Netherlands
| | - M A Ikram
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - M Kavousi
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
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4
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Zhu F, Wolters FJ, Yaqub A, Boersma H, Ikram MA, Kavousi M. Plasma amyloid-beta in relation to cardiac function and risk of heart failure in the general population. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Amyloid-β is a major hallmark of Alzheimer's disease, and its pathology has been hypothesized as a multiple organ syndrome that may also affect cardiac function. There are limited data on association of plasma amyloid-β with cardiac dysfunction and risk of HF in the general population.
Objective
To determine the association of plasma amyloid-β40 (Aβ40) and amyloid-β42 (Aβ42) with echocardiographic measurements of cardiac dysfunction, and with incident heart failure (HF) in the general population.
Methods
We included 4156 participants of the population-based cohort (mean age 71.4 years, 57.1% women), who had plasma amyloid-β measured between 2002 and 2005, and were free of dementia and HF at baseline. Multivariable linear regression models were used to explore the associations of plasma Aβ40 and Aβ42 with echocardiographic measures. Participants were followed for the occurrence of HF until December 2016. Cause-specific hazard models were used to assess the association of plasma amyloid-β with incident HF and competing risk event. Models were adjusted for cardiovascular risk factors.
Results
Higher plasma Aβ40 concentrations were associated with lower left ventricular ejection fraction (β, −0.39; 95% CI, −0.68 to −0.10) and larger left ventricular mass (β, 0.70; 95% CI, 0.06 to 1.34). Aβ42 was not significantly associated with echocardiographic measures cross-sectionally. During follow-up (median 10.2 years), 472 incident HF cases were identified. Higher plasma Aβ40 was associated with an increased risk of incident HF (HR, 1.32; 95% CI, 1.15 to 1.51), more profound in men than in women (P value for interaction: 0.022). One SD increase in Aβ40 was associated with a 31% increase in the hazard of HF in men (HR, 1.32; 95% CI, 1.14 to 1.54) but the association was not significant in women (HR, 1.06; 95% CI, 0.93 to 1.20). Higher plasma Aβ42 concentrations were associated with increased risk of HF (HR, 1.12; 95% CI, 1.02 to 1.24), while further adjustment for concomitant Aβ40 attenuated this association (HR, 1.03; 95% CI, 0.92 to 1.16).
Conclusion
Higher levels of plasma Aβ40 were independently associated with worse cardiac function and higher risk of new-onset HF in the general population, in particular among men.
Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): The Netherlands Organization for Health Research and Development (ZonMw); the Dutch Heart Foundation;This study is further funded by the European Union's Horizon 2020 research and innovation programme as part of the Common mechanisms and pathways in Stroke and Alzheimer's disease (CoSTREAM) project.
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Affiliation(s)
- F Zhu
- Erasmus University Medical Centre , Rotterdam , The Netherlands
| | - F J Wolters
- Erasmus University Medical Centre , Rotterdam , The Netherlands
| | - A Yaqub
- Erasmus University Medical Centre , Rotterdam , The Netherlands
| | - H Boersma
- Erasmus University Medical Centre , Rotterdam , The Netherlands
| | - M A Ikram
- Erasmus University Medical Centre , Rotterdam , The Netherlands
| | - M Kavousi
- Erasmus University Medical Centre , Rotterdam , The Netherlands
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Melgarejo J, Vernooij MW, Ikram MA, Zhang ZY, Bos D. Intracranial carotid arteriosclerosis mediates the association between blood pressure and cerebral small vessel disease: the Rotterdam Study. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.2177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Cerebral arteriosclerosis could explain the physiopathological mechanisms linking high blood pressure (BP) and cerebral small vessel disease (CSVD).
Objectives
To test the hypothesis that ICAC mediates the association between BP and CSVD.
Methods
1458 stroke-free participants from the Rotterdam Study underwent nonenhanced computed tomography to quantify ICAC and brain magnetic resonance imaging scans to assess CSVD. ICAC subtypes included atherosclerotic (intimal) and non-atherosclerotic internal elastic lamina (IEL) calcifications. We analyzed systolic BP (SBP), diastolic BP (DBP), pulse pressure (PP), and mean arterial pressure (MAP). Mediation analysis included a two way decomposition to compute the natural direct effect (NDE), natural indirect effect (NIE) and percentage of mediation (%) of ICAC on the association between BP and CSVD.
Results
The study population had a mean age of 68.0 years old, and 52% (n=758) of the participants were women. In analyses including participants with predominantly IEL calcification, we observed that larger log-ICAC volume was positively related to a higher pulse pressure (β=0.020; P<0.001), and lower diastolic BP (β=0.024; P=0.001). None of the BP components were associated with log-ICAC volume among participants with predominantly intimal calcifications (β≤0.008; P≥0.060). Among all participants, log-ICAC volume mediated the association of DBP (NIE, 0.003; −14.5%) and PP (NIE,0.003; 16.5%) with log-white matter hyperintensities (log WMH). In participants with IEL calcification, log-ICAC volume mediated the association of DBP with log-WMH (NIE, 0.004, −19.5%); no mediations were observed for intimal ICAC. For Lacunes, in all participants, log-ICAC volume mediated the association of DBP (NIE, −0.015, −40%) and PP (NIE,0.015; 26.9%). In participants with IEL calcification; the NIE was 0.020 (45.8%) for DBP and 0.017 (18.2%) for PP. No interactions were detected.
Conclusions
ICAC mediated the association between BP and CSVD. Non-atherosclerotic IEL calcification, considered a proxy of arterial stiffness, was the main physiopathological mechanism explaining how BP links to CSVD due to cerebral arteriosclerosis.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- J Melgarejo
- University of Leuven, Cardiovascular Sciences , Leuven , Belgium
| | - M W Vernooij
- Erasmus University Medical Centre, Department of Radiology and Nuclear Medicine , Rotterdam , The Netherlands
| | - M A Ikram
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - Z Y Zhang
- University of Leuven, Cardiovascular Sciences , Leuven , Belgium
| | - D Bos
- Erasmus University Medical Centre, Department of Radiology and Nuclear Medicine , Rotterdam , The Netherlands
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Lu Z, Ntlapto N, Tilly M, Ikram MA, De Groot NMS, Kavousi M. Cardiometabolic multimorbidity and lifetime risk of atrial fibrillation among men and women. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.2241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Background
Atrial fibrillation (AF) is the most common cardiac arrythmia worldwide, with an increased risk of comorbidity, and significant sex differences in pathophysiology and prognosis. Cardiometabolic disorders, including obesity, hypertension, diabetes mellitus, coronary heart disease, stroke, and heart failure commonly coexist with AF. However, the sex-specific patterns and (combined) impact of cardiometabolic disorders on the risk of new-onset AF remains largely unknown.
Purpose
To examine the association between patterns of cardiometabolic multimorbidity and new-onset AF and lifetime risk of AF incidence among men and women.
Methods
4,113 men and 5,432 women free of prevalent AF at baseline (from 1996 to 2008) from the Rotterdam Study were included. AF incidents were assessed by electrocardiograms and general practitioners' and hospital records, and followed up to January 1st, 2014. Sex-specific Cox proportional hazards regression models were used to assess the association between the amount of cardiometabolic disorders and risks of new-onset AF. Models were adjusted for traditional cardiovascular risk factors. Remaining lifetime risk for AF was estimated across the cardiometabolic multimorbidity groups at index ages of 55, 65, and ≥75 years up to age 108.
Results
Mean age at baseline was 65.5±9.4 years. Median follow-up time was 10.8 years. In the fully-adjusted model, a significant association was found between the amount of cardiometabolic disorders and incident AF among women but not men. Compared to women without cardiometabolic disorders, women with 3 (hazard ratios, 95% conference intervals: 2.17 (1.24–3.79)) and ≥4 comorbidities (4.58 (2.22–9.48)) had higher AF risks. The lifetime risk for AF was significantly increased with the number of cardiometabolic disorders among both men and women. At index age of 55 years, the lifetime risks (95% confidence interval) for AF were 25.2% (17.1–33.4), 24.2% (20.0–28.9), 27.1% (23.2–31.0), 30.0% (24.3–35.7) and 34.1% (22.4–45.7), for 0, 1, 2, 3, and ≥4 comorbid cardiometabolic disorders among men, respectively. Corresponding risks were 16.3% (6.68–25.9), 20.3% (16.3–24.3), 27.6% (24.1–31.2), 23.6% (17.8–29.4) and 33.3% (16.0–50.2) among women.
Conclusions
We observed a significant combined impact of cardiometabolic disorders on AF risk, most evidently among women. Participants with cardiometabolic multimorbidity had a significantly increased lifetime risk of AF, especially at a young index age.
Funding Acknowledgement
Type of funding sources: None.
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Affiliation(s)
- Z Lu
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - N Ntlapto
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - M Tilly
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - M A Ikram
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
| | - N M S De Groot
- Erasmus University Medical Centre, Department of Cardiology , Rotterdam , The Netherlands
| | - M Kavousi
- Erasmus University Medical Centre, Department of Epidemiology , Rotterdam , The Netherlands
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Waziry R, Hofman A, Ghanbari M, Tiemeier H, Ikram MA, Viswanathan A, Klap J, Ikram MK, Goudsmit J. Biological aging for risk prediction of first-ever intracerebral hemorrhage and cerebral infarction in advanced age. J Stroke Cerebrovasc Dis 2022; 31:106568. [PMID: 35749936 DOI: 10.1016/j.jstrokecerebrovasdis.2022.106568] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 04/30/2022] [Accepted: 05/15/2022] [Indexed: 10/18/2022] Open
Abstract
BACKGROUND AND OBJECTIVES successful interventions to prevent cerebrovascular disease and stroke require early identification of persons at risk before clinical manifestation of disease. The literature remains to be sparse on accessible plasma-based biomarkers for monitoring brain health and cerebrovascular disease in advanced age. We assessed the predictive value of biological age (BA) as an early indicator for cerebrovascular disease and risk of first-ever intracerebral hemorrhage (ICH) and cerebral infarction (CI) in advanced age and compared these relationships with chronological age (CA) and commonly used biomarkers including tau and Aβ40 and Aβ42. METHODS The study included Individuals who consented for blood draw and follow-up. We computed biological age using structural equation modelling. The criteria for the biomarkers included their representability of the various body systems; their availability in the Rotterdam study and their pre-hypothesized reflection of aging in other populations. The algorithm integrates biomarkers that represent six body systems involved in overall cerebrovascular health including metabolic function, cardiac function, lung function, kidney function, liver function, immunity, and inflammation. Time to event analysis was conducted using Cox-regression models. Prediction analysis was conducted using Harrel's C and Area under the receiver operating characteristic curve. RESULTS The sample included a total of 1699 individuals at baseline followed up over a median of 11 years. During a period of 15, 780 and 16, 172 person-years, a total of 17 first-ever intracerebral hemorrhage and 83 cerebral infarction cases occurred. In time-to-event analysis, BA showed higher magnitude of associations with ICH compared to CA (HRBA-ICH: 2.30, 95% CI: 1.20, 4.30; HRCA-ICH: 1.40, 95% CI: 0.76, 2.53) and higher precision with CI (HRBA-CI: 1.30, 95% CI: 1.01,1.75; HRCA-CI:1.90, 95% CI: 1.48, 2.66). BA outperformed CA for prediction of ICH (AUC: 0.68 vs 0.53; Harrel's C: 0.72 vs 0.53) and for CI (AUC:0.63 vs 0.62; Harrel's C: 0.68 vs 0.67). CONCLUSIONS Biological aging (delta biological aging) based on integrated physiology biomarkers provides a novel tool for monitoring and identification of persons at highest risk of cerebrovascular disease in advanced age with varying degrees of precision and magnitude for stroke subtypes. These variations are likely related to differences in pathophysiology of intracerebral hemorrhage and cerebral infarction. Wider validation and applicability require extension of these findings in other comparable samples and in clinical settings.
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Affiliation(s)
- Reem Waziry
- Columbia University Irving Medical Center, New York, United States; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, United States; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
| | - Albert Hofman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, United States
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Henning Tiemeier
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, United States
| | - M A Ikram
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, United States; Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Anand Viswanathan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Harvard University, United States
| | - Jaco Klap
- Janssen Prevention Center, Leiden, the Netherlands
| | - M Kamran Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jaap Goudsmit
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, United States; World Without Disease Accelerator (WWDA), The Janssen Pharmaceutical Companies of Johnson & Johnson, Leiden, the Netherlands and Leyden Laboratories, Leiden, the Netherlands
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Siland JE, Geelhoed B, Roselli C, Wang B, Lin HJ, Weiss S, Trompet S, van den Berg ME, Soliman EZ, Chen LY, Ford I, Jukema JW, Macfarlane PW, Kornej J, Lin H, Lunetta KL, Kavousi M, Kors JA, Ikram MA, Guo X, Yao J, Dörr M, Felix SB, Völker U, Sotoodehnia N, Arking DE, Stricker BH, Heckbert SR, Lubitz SA, Benjamin EJ, Alonso A, Ellinor PT, van der Harst P, Rienstra M. Resting heart rate and incident atrial fibrillation: A stratified Mendelian randomization in the AFGen consortium. PLoS One 2022; 17:e0268768. [PMID: 35594314 PMCID: PMC9122202 DOI: 10.1371/journal.pone.0268768] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 05/06/2022] [Indexed: 12/02/2022] Open
Abstract
Background Both elevated and low resting heart rates are associated with atrial fibrillation (AF), suggesting a U-shaped relationship. However, evidence for a U-shaped causal association between genetically-determined resting heart rate and incident AF is limited. We investigated potential directional changes of the causal association between genetically-determined resting heart rate and incident AF. Method and results Seven cohorts of the AFGen consortium contributed data to this meta-analysis. All participants were of European ancestry with known AF status, genotype information, and a heart rate measurement from a baseline electrocardiogram (ECG). Three strata of instrumental variable-free resting heart rate were used to assess possible non-linear associations between genetically-determined resting heart rate and the logarithm of the incident AF hazard rate: <65; 65–75; and >75 beats per minute (bpm). Mendelian randomization analyses using a weighted resting heart rate polygenic risk score were performed for each stratum. We studied 38,981 individuals (mean age 59±10 years, 54% women) with a mean resting heart rate of 67±11 bpm. During a mean follow-up of 13±5 years, 4,779 (12%) individuals developed AF. A U-shaped association between the resting heart rate and the incident AF-hazard ratio was observed. Genetically-determined resting heart rate was inversely associated with incident AF for instrumental variable-free resting heart rates below 65 bpm (hazard ratio for genetically-determined resting heart rate, 0.96; 95% confidence interval, 0.94–0.99; p = 0.01). Genetically-determined resting heart rate was not associated with incident AF in the other two strata. Conclusions For resting heart rates below 65 bpm, our results support an inverse causal association between genetically-determined resting heart rate and incident AF.
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Affiliation(s)
- J. E. Siland
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - B. Geelhoed
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - C. Roselli
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
| | - B. Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
| | - H. J. Lin
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States of America
| | - S. Weiss
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics; University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
| | - S. Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - M. E. van den Berg
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - E. Z. Soliman
- Division of Public Health Sciences and Department of Medicine, Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, Section on Cardiology, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - L. Y. Chen
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, United States of America
| | - I. Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, United Kingdom
| | - J. W. Jukema
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
- Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - P. W. Macfarlane
- Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - J. Kornej
- National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA, United States of America
| | - H. Lin
- National Heart Lung and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA, United States of America
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, Unites States of America
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
- National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA, United States of America
| | - M. Kavousi
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J. A. Kors
- Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M. A. Ikram
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - X. Guo
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States of America
| | - J. Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - M. Dörr
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B-Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - S. B. Felix
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B-Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - U. Völker
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics; University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
| | - N. Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, Unites States of America
| | - D. E. Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University SOM, Baltimore, MD, Unites States of America
| | - B. H. Stricker
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - S. R. Heckbert
- Cardiovascular Health Research Unit and the Department of Epidemiology, University of Washington, Seattle, WA, Unites States of America
| | - S. A. Lubitz
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, Unites States of America
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, Unites States of America
| | - E. J. Benjamin
- Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
- Department of Medicine, Boston University School of Medicine, Boston, MA, Unites States of America
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, Unites States of America
| | - A. Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, Unites States of America
| | - P. T. Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, Unites States of America
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, Unites States of America
| | - P. van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
- University Medical Center Utrecht, Department of Heart and Lungs, University of Utrecht, Utrecht, The Netherlands
| | - M. Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- * E-mail:
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9
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Geurts S, Tilly MJ, Kors JA, Deckers JW, Stricker BHC, De Groot NMS, Ikram MA, Kavousi M. Electrocardiographic parameters and the risk of new-onset atrial fibrillation in the general population. Europace 2022. [DOI: 10.1093/europace/euac053.152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public Institution(s). Main funding source(s): The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This study is further supported by the Senior Scientist Grant from Dutch Heart Foundation (03-004-2021-T050).
Background
The (shape of the) association and sex-differences between electrocardiographic parameters and new-onset atrial fibrillation (AF) remain incompletely understood.
Purpose
To investigate the association between electrocardiographic parameters and new-onset atrial fibrillation among men and women in the general population.
Methods
12,212 participants free of AF from a large population-based cohort study were included. Up to five repeated measurements of electrocardiographic parameters including PR, QRS, QT, QT corrected for heart rate (QTc), JT, RR interval, and heart rate were assessed at baseline and follow-up examinations. Cox proportional hazards models and joint models, both adjusted for cardiovascular risk factors, were used to determine the (shape of) association between baseline and longitudinal electrocardiographic parameters with new-onset AF. Additionally, we evaluated potential sex-differences.
Results
During a median follow-up of 9.3 years, 1,282 incident AF cases occurred among 12,212 participants (mean age 64.9 years, 58.2% women). Penalized cubic splines revealed that associations between baseline electrocardiographic measures and risk of new-onset AF were generally U-shaped (Figure 1). Sex-differences in terms of the shape of the various associations were most apparent for baseline PR, QT, QTc, RR, and heart rate in relation to new-onset AF. Longitudinal measures of PR (hazard ratio (HR), 95% confidence interval (CI), 1.43, 1.02-2.04, p=0.0393), and QTc interval (HR, 95% CI, 5.23, 2.18-12.45, p=0.0002) were significantly associated with new-onset AF. Sex-stratified analyses showed that the longitudinal associations were more prominent among men.
Conclusions
Baseline electrocardiographic measures and risk of new-onset AF were generally U-shaped. Longitudinal electrocardiographic measures of PR, and QTc interval were significantly associated with new-onset AF, more pronounced in men. Our findings imply that different thresholds of electrocardiographic parameters might translate to a differential risk of AF among men and women, and that treatment options targeting specific electrocardiographic parameters might prevent AF in the general population, in particular in men.
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Affiliation(s)
- S Geurts
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - MJ Tilly
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - JA Kors
- Erasmus University Medical Centre, Medical Informatics, Rotterdam, Netherlands (The)
| | - JW Deckers
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - BHC Stricker
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - NMS De Groot
- Erasmus University Medical Centre, Cardiology, Rotterdam, Netherlands (The)
| | - MA Ikram
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
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10
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Geurts S, Tilly MJ, Arshi B, Stricker BHC, Kors JA, Deckers JW, De Groot NMS, Ikram MA, Kavousi M. Heart rate variability and atrial fibrillation in the general population: a longitudinal and mendelian randomization study. Eur J Prev Cardiol 2022. [DOI: 10.1093/eurjpc/zwac056.111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public Institution(s). Main funding source(s): The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. This study is further supported by the Gender and prevention grant (555003017) from ZonMw.
Background
Sex-differences and the causality of the association between heart rate variability (HRV) and atrial fibrillation (AF) remain unclear.
Purpose
To investigate the sex-differences and the causality of the association between heart rate variability and atrial fibrillation.
Methods
12,334 participants free of AF from a large population-based cohort study were included. Measures of HRV including the standard deviation of normal RR-intervals (SDNN), SDNN corrected for heart rate (SDNNc), RR-interval differences (RMSSD), RMSSD corrected for heart rate (RMSSDc), and heart rate were assessed at baseline and follow-up examinations. Joint models, adjusted for cardiovascular risk factors, were used to determine the association between longitudinal measures of HRV with new-onset AF. Additionally, we evaluated sex-differences. Genetic variants for HRV were used as instrumental variables in a Mendelian randomization (MR) analysis using GWAS summary-level data.
Results
During a median follow-up of 9.4 years, 1,302 incident AF cases occurred. In joint models, higher SDNN (hazard ratio (HR), 95% confidence interval (CI), 1.24, 1.04-1.47, p=0.0213), and higher RMSSD (HR, 95% CI, 1.33, 1.13-1.54, p=0.0010) were significantly associated with new-onset AF. Sex-stratified analyses showed that the associations were mostly prominent among women. In MR analyses, genetically determined decreases in SDNN (odds ratio (OR), 95% CI, 1.60, 1.27-2.02, p=8.36x10-05), and RMSSD (OR, 95% CI, 1.56, 1.31-1.86, p= 6.32x10-07) were significantly associated with increased AF risk.
Conclusions
Longitudinal measures of uncorrected HRV were significantly associated with new-onset AF, in particular among women. MR analyses supported the causal relationship between uncorrected measures of HRV with AF. Our findings indicate that measures to modulate HRV might prevent AF in the general population, especially among women.
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Affiliation(s)
- S Geurts
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - MJ Tilly
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - B Arshi
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - BHC Stricker
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - JA Kors
- Erasmus University Medical Centre, Medical Informatics, Rotterdam, Netherlands (The)
| | - JW Deckers
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - NMS De Groot
- Erasmus University Medical Centre, Cardiology, Rotterdam, Netherlands (The)
| | - MA Ikram
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
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11
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Tilly MJ, Geurts S, Pezzullo AM, Bramer WM, Ikram MA, De Groot NMS, Kavousi M, De Maat MPM. The association of coagulation and hemostasis with atrial fibrillation: a systematic review and meta-analysis. Eur J Prev Cardiol 2022. [DOI: 10.1093/eurjpc/zwac056.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Public hospital(s). Main funding source(s): - Erasmus MC MRace grant- The Netherlands Organization for the Health Research and Development (ZonMw)
Background
Atrial fibrillation (AF) is a highly prevalent cardiac tachyarrhythmia. Recent literature suggests that AF induces a prothrombotic state, ultimately leading to thrombotic events. It is also hypothesized that coagulation underlies AF development through coagulation.
Purpose
We aimed to assess the associations between selected coagulation factors with AF in both longitudinal and cross-sectional studies, to give further insight on the interaction of coagulation and AF.
Methods
Through a systematic search of large databases, including Embase, Medline ALL, and Web of Science Core Collection, all longitudinal cohort studies and cross-sectional studies published before 25th of May, 2021 were reviewed. For longitudinal studies, pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated through log-transformed HRs and 95% CIs using the generic inverse variance method. For cross-sectional studies the pooled standardized mean differences (SMD) were calculated through inverse variance weighting.
Results
16 longitudinal studies and 44 cross-sectional studies were included. In the longitudinal studies, using complex multivariable models, we found significant associations between fibrinogen (HR1.06, 95% CI 1.01-1.12), Plasminogen activator inhibitor 1 (PAI-1) (HR 1.06, 95% CI 1.00-1.12), and D-dimer (HR 1.10, 95% CI 1.02-1.19), with AF incidence. In cross-sectional studies, we found significant differences between AF patients and controls for fibrinogen (SMD 0.47), D-dimer (SMD 1.74), P-selectin (SMD 0.31), von Willebrand factor (SMD 0.96), PAI-1 (SMD 1.73), ß-thromboglobulin (SMD 0.82), and Platelet Factor 4 (SMD 0.42).
Conclusions
Atrial fibrillation is associated with higher levels of coagulation factors. These associations are most pronounced in cross-sectional analyses, but limited studies are available investigating a prothrombotic state underlying AF initiation. These results further support the hypothesis of "AF begets AF".
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Affiliation(s)
- MJ Tilly
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - S Geurts
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - AM Pezzullo
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - WM Bramer
- Erasmus University Medical Centre, Medical Library, Rotterdam, Netherlands (The)
| | - MA Ikram
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - NMS De Groot
- Erasmus University Medical Centre, Department of Cardiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - MPM De Maat
- Erasmus University Medical Centre, Department of Hematology, Rotterdam, Netherlands (The)
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12
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Huizinga W, Poot DHJ, Vinke EJ, Wenzel F, Bron EE, Toussaint N, Ledig C, Vrooman H, Ikram MA, Niessen WJ, Vernooij MW, Klein S. Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis. Front Big Data 2021; 4:577164. [PMID: 34723175 PMCID: PMC8552517 DOI: 10.3389/fdata.2021.577164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 05/21/2021] [Indexed: 12/03/2022] Open
Abstract
For the segmentation of magnetic resonance brain images into anatomical regions, numerous fully automated methods have been proposed and compared to reference segmentations obtained manually. However, systematic differences might exist between the resulting segmentations, depending on the segmentation method and underlying brain atlas. This potentially results in sensitivity differences to disease and can further complicate the comparison of individual patients to normative data. In this study, we aim to answer two research questions: 1) to what extent are methods interchangeable, as long as the same method is being used for computing normative volume distributions and patient-specific volumes? and 2) can different methods be used for computing normative volume distributions and assessing patient-specific volumes? To answer these questions, we compared volumes of six brain regions calculated by five state-of-the-art segmentation methods: Erasmus MC (EMC), FreeSurfer (FS), geodesic information flows (GIF), multi-atlas label propagation with expectation–maximization (MALP-EM), and model-based brain segmentation (MBS). We applied the methods on 988 non-demented (ND) subjects and computed the correlation (PCC-v) and absolute agreement (ICC-v) on the volumes. For most regions, the PCC-v was good (>0.75), indicating that volume differences between methods in ND subjects are mainly due to systematic differences. The ICC-v was generally lower, especially for the smaller regions, indicating that it is essential that the same method is used to generate normative and patient data. To evaluate the impact on single-subject analysis, we also applied the methods to 42 patients with Alzheimer’s disease (AD). In the case where the normative distributions and the patient-specific volumes were calculated by the same method, the patient’s distance to the normative distribution was assessed with the z-score. We determined the diagnostic value of this z-score, which showed to be consistent across methods. The absolute agreement on the AD patients’ z-scores was high for regions of thalamus and putamen. This is encouraging as it indicates that the studied methods are interchangeable for these regions. For regions such as the hippocampus, amygdala, caudate nucleus and accumbens, and globus pallidus, not all method combinations showed a high ICC-z. Whether two methods are indeed interchangeable should be confirmed for the specific application and dataset of interest.
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Affiliation(s)
- W Huizinga
- Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine and Medical Informatics, Erasmus MC, Rotterdam, Netherlands
| | - D H J Poot
- Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine and Medical Informatics, Erasmus MC, Rotterdam, Netherlands
| | - E J Vinke
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
| | - F Wenzel
- Philips Research Hamburg, Hamburg, Germany
| | - E E Bron
- Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine and Medical Informatics, Erasmus MC, Rotterdam, Netherlands
| | - N Toussaint
- School of Biomedical Engineering, King's College London, London, United Kingdom
| | - C Ledig
- Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom
| | - H Vrooman
- Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine and Medical Informatics, Erasmus MC, Rotterdam, Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
| | - W J Niessen
- Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine and Medical Informatics, Erasmus MC, Rotterdam, Netherlands.,Quantitative Imaging Group, Department of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, Netherlands
| | - M W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Epidemiology, Erasmus MC, Rotterdam, Netherlands
| | - S Klein
- Biomedical Imaging Group Rotterdam, Department of Radiology & Nuclear Medicine and Medical Informatics, Erasmus MC, Rotterdam, Netherlands
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13
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Dommershuijsen LJ, Van der Heide A, Van den Berg EM, Labrecque JA, Ikram MK, Ikram MA, Bloem BR, Helmich RC, Darweesh SKL. Mental health in people with Parkinson's disease during the COVID-19 pandemic: potential for targeted interventions? NPJ Parkinsons Dis 2021; 7:95. [PMID: 34711842 PMCID: PMC8553848 DOI: 10.1038/s41531-021-00238-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 09/15/2021] [Indexed: 12/14/2022] Open
Abstract
The COVID-19 pandemic has introduced a myriad of challenges to the social life and care of people with Parkinson’s disease (PD), which could potentially worsen mental health problems. We used baseline data of the PRIME-NL study (N = 844) to examine whether the association between COVID-19 stressors and mental health is disproportionately large in specific subgroups of people with PD and to explore effects of hypothetical reductions in COVID-19 stressors on mental health and quality of life. The mean (SD) age of the study population was 70.3 (7.8) years and 321 (38.0%) were women. The linear regression effect estimate of the association of COVID-19 stressors with mental health was most pronounced in women, highly educated people, people with advanced PD and people prone to distancing or seeking social support. Smaller effect estimates were found in people scoring high on confrontive coping or planful problem solving. The parametric G-formula method was used to calculate the effects of hypothetical interventions on COVID-19 stressors. An intervention reducing stressors with 50% in people with above median MDS-UPDRS-II decreased the Beck Depression Inventory in this group from 14.7 to 10.6, the State-Trait Anxiety Inventory from 81.6 to 73.1 and the Parkinson’s Disease Quality of Life Questionnaire from 35.0 to 24.3. Insights from this cross-sectional study help to inform tailored care interventions to subgroups of people with PD most vulnerable to the impact of COVID-19 on mental health and quality of life.
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Affiliation(s)
- L J Dommershuijsen
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Centre of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - A Van der Heide
- Centre of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - E M Van den Berg
- Centre of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - J A Labrecque
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M K Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - B R Bloem
- Centre of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - R C Helmich
- Centre of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - S K L Darweesh
- Centre of Expertise for Parkinson & Movement Disorders, Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.
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14
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Lu Z, Tilly MJ, Aribas E, Bos D, De Knegt R, Ikram MA, De Groot NMS, Voortman T, Kavousi M. Imaging-based body fat depots and new-onset atrial fibrillation in general population. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Background
Obesity is a well-established risk factor for incident atrial fibrillation (AF). Whether different body fat depots differentially associate with AF development remains largely unknown.
Purpose
We aimed to investigate the associations between various body fat depots and the risk of new-onset AF among middle-aged and elderly individuals from general population.
Methods
In the prospective population-based cohort study, body composition was assessed using dual-energy X-ray absorptiometry (DXA) and total body mass, lean mass, fat mass, android and gynoid fat were analyzed (N=3468). Liver fat and epicardial fat were assessed using computed tomography (CT) (N=2145). A body fat score was defined by adding tertiles of each fat depot. All participants were followed for the occurrence of AF until 1st Jan. 2014. Principle component analysis was conducted to identify body fat distribution patterns. Time-to-event analyses were performed using Cox proportional hazards regression analysis. Hazard ratios (HR) and 95% confidence-intervals (95% CI), adjusted for cardiovascular risk factors, were calculated.
Results
Mean (standard deviation) of age for participants in DXA study and CT study was 74.42 (6.85) and 68.66 (6.41) years, respectively. AF incidence rate was 13.1 per 1000 person-years during a median follow-up time of 9.62 years. In the adjusted model, fat mass (HR; 95% CI: 1.33; 1.05–1.68), lean mass (1.40; 1.15–1.72), gynoid fat mass (1.36; 1.12–1.65), and total body mass (1.51; 1.21–1.89) were significantly associated with new-onset AF. Of note, android-to-gynoid fat ratio was inversely associated with incident AF (HR; 95% CI: 0.81; 0.70–0.94). Larger body fat score was associated with increased risk of incident AF (P for trend <0.01). Two fat distribution patterns were identified. Adherence to the fat- and gynoid fat- pattern (P for trend = 0.035), but not muscle- and visceral fat- pattern (P for trend = 0.35), was significantly associated with larger risk of new-onset AF.
Conclusions
Various body fat depots were associated with new-onset AF. Larger values of total body mass carried the highest risk for incident AF. The inverse association between android to gynoid fat ratio with AF presents a novel finding. A significant dose-response relationship between body fat accumulation and risk of new-onset AF was observed, implying a collective impact of fat depots on AF development. Findings also suggest that various fat depots, characterized by different fat distribution patterns, may exert differential combined effect on the risk of incident AF.
Funding Acknowledgement
Type of funding sources: None. Fat depots and atrial fibrillation
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Affiliation(s)
- Z Lu
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M J Tilly
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - E Aribas
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - D Bos
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - R De Knegt
- Erasmus University Medical Centre, Department of Internal Medicine, Rotterdam, Netherlands (The)
| | - M A Ikram
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - N M S De Groot
- Erasmus University Medical Centre, Department of Cardiology, Rotterdam, Netherlands (The)
| | - T Voortman
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
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15
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Geurts S, Van Der Burgh AC, Ikram MA, Kors JA, Stricker BHC, Deckers JW, Hoorn EJ, Chaker L, Kavousi M. Disentangling the association between kidney function and atrial fibrillation: a bidirectional Mendelian randomization study. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
Observational studies suggest that kidney function and atrial fibrillation (AF) are bidirectionally associated. Whether this bidirectional association is causal remains unclear.
Purpose
To investigate the causality of the bidirectional association between kidney function and AF.
Methods
Genetic variants associated with different measures of kidney function including estimated glomerular filtration rate (eGFR) based on creatinine (eGFRcreat), blood urea nitrogen (BUN), chronic kidney disease (CKD, eGFR <60ml/min/1.73m2), eGFR based on cystatin (eGFRcys), urine albumin-to-creatinine ratio (UACR) and microalbuminuria (MA, UACR >30mg/g) were retrieved from multiple Genome-Wide Association Studies (GWAS). These GWAS were all part of the Chronic Kidney Disease Genetics (CKDGen) Consortium (n=24,063–1,040,070). Genetic variants associated with AF were retrieved from a GWAS on AF (n=1,030,836). We used two-sample MR analyses to assess the potential causality of the bidirectional association between kidney function and AF.
Results
MR analyses supported a causal effect of genetically predicted BUN, CKD and MA on AF risk (for BUN: n=18 SNPs, outlier corrected odds ratio (OR): 2.05, per 1 unit increase of BUN (mg/dL), 95% CI: 1.30–3.25, p-value = 2.13E-03. For CKD: n=9 SNPs, outlier corrected OR: 1.10, 95% CI: 1.04–1.17, p-value = 1.97E-03. For MA: n=5 SNPs, outlier corrected OR: 1.26, 95% CI: 1.10–1.46, p-value = 1.38E-03). MR analyses also supported a causal effect of genetically predicted AF on eGFRcreat (n=97 SNPs, outlier corrected OR: 0.998, per 1 unit increase of log transformed eGFRcreat (ml/min/1.73m2), 95% CI: 0.997–0.999, p-value = 6.78E-03), CKD risk (n=107 SNPs, outlier corrected OR: 1.06, 95% CI: 1.03–1.09, p-value = 2.97E-04) and MA risk (n=83 SNPs, outlier corrected OR: 1.07, 95% CI: 1.04–1.09, p-value = 2.49E-08). A suggestive causal effect of genetically predicted AF on eGFRcys was found (n=103 SNPs, outlier corrected OR: 0.993, per 1 unit increase of log transformed eGFRcys (ml/min/1.73m2), 95% CI: 0.986–0.999, p-value = 4.60E-02). MR analyses did not support a significant causal effect of the other kidney function measures on AF risk and vice versa. Moreover, sensitivity analyses, including weighted median estimator (WME), MR-Egger and the MR pleiotropy residual sum and outlier test (MR-PRESSO) indicated that these findings were robust. Furthermore, the associations did not change when genetic variants associated with coronary artery disease and heart failure were excluded.
Conclusions
MR analyses supported a bidirectional causal association between kidney function and AF. Our findings carry the potential for identification of important therapeutic targets for both conditions with implications for secondary prevention.
Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): Erasmus Medical Center and Erasmus University, Rotterdam Forest plot with the MR effect estimatesBidirectional MR: Kidney function and AF
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Affiliation(s)
- S Geurts
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - A C Van Der Burgh
- Erasmus University Medical Centre, Internal Medicine, Rotterdam, Netherlands (The)
| | - M A Ikram
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - J A Kors
- Erasmus University Medical Centre, Medical Informatics, Rotterdam, Netherlands (The)
| | - B H C Stricker
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - J W Deckers
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
| | - E J Hoorn
- Erasmus University Medical Centre, Internal Medicine, Rotterdam, Netherlands (The)
| | - L Chaker
- Erasmus University Medical Centre, Internal Medicine, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Epidemiology, Rotterdam, Netherlands (The)
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16
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Tilly MJ, Lu Z, Geurts S, Ikram MA, De Maat MPM, Ikram MK, De Groot NMS, Kavousi M. Distribution and risk profile of atrial fibrillation patterns among women and men from the general population. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
In a clinical setting, atrial fibrillation (AF) subgroups are defined, including paroxysmal, persistent, and permanent AF. These subgroups differ in terms of clinical characteristics, management strategy, and long-term outcomes. Application of clinical classifications in population-based settings is challenging as they are based on the duration of symptoms, recurrence, and treatment.
Purpose
We aim to develop an objective and standardized classification for AF patterns in the general population and examine the associated cardiovascular risk profiles and outcomes for the identified AF patterns.
Methods
Participants with only one reported AF episode were categorized as single-documented AF, if at least two separate AF episodes were reported as multiple-documented AF and as longstanding persistent AF if at least two consecutive ECG's at the research center showed AF, not followed by an ECG showing sinus rhythm. We fitted mixed effect models with age as time scale to characterize sex-specific cardiovascular risk factor trajectories preceding each AF pattern. We further used Cox proportional hazard modelling to describe the risk of coronary heart disease (CHD), heart failure (HF), stroke, and all-cause mortality following AF.
Results
We included 14,620 men and women aged ≥45 years. 1137 participants were categorized as single-documented AF, 208 as multiple-documented AF, and 57 as longstanding persistent AF. We identified significant differences in the preceding trajectories of weight, body mass index, systolic blood pressure, diastolic blood pressure, waist circumference, hip circumference, and waist-hip ratio with various AF patterns. In general, both men and women with persistent-elevated levels of these risk factors were prone to longstanding persistent AF.
AF was associated with a large risk for subsequent CHD, HF, stroke, and mortality in the general population. Among the different AF patterns, single-documented AF conferred the largest risk of CHD [hazard ratio, 95% confidence interval: 1.92 (1.19–3.03)] and mortality [1.70 (1.41–2.07)] as compared to multiple-documented AF, and as compared to longstanding persistent AF [1.45 (0.72–2.90) and 3.66 (2.25–5.95), respectively].
Conclusion
We developed a classification for AF patterns within a general population. We identified differences in risk factor trajectories preceding each AF pattern, which implies differences in pathophysiological mechanisms underlying AF. Participants with single-documented AF showed worse prognosis than those with multiple AF episodes. This might be due to the subgroup definition, since participants should live for a longer period of time to be categorized in the multiple-documented AF and longstanding persistent AF groups. This can also imply that participants suffering from multiple AF episodes are more frequently monitored, and treated for other risk factors. However, this could also suggest that singular AF episodes are not as innocent as commonly thought.
Funding Acknowledgement
Type of funding sources: Public hospital(s). Main funding source(s): - Erasmus MC Mrace grant. - Netherlands Organization for the Health Research and Development (ZonMw) Figure 1Figure 2. Progosis of various AF patterns
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Affiliation(s)
- M J Tilly
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - Z Lu
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - S Geurts
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M A Ikram
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M P M De Maat
- Erasmus University Medical Centre, Department of Hematology, Rotterdam, Netherlands (The)
| | - M K Ikram
- Erasmus University Medical Centre, Department of Neurology, Rotterdam, Netherlands (The)
| | - N M S De Groot
- Erasmus University Medical Centre, Department of Cardiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
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17
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Roa Diaz ZM, Asllanaj E, Amin HA, Rojas LZ, Nano J, Ikram MA, Drenos F, Franco OH, Pazoki R, Marques-Vidal P, Voortman T, Muka T. Causal and observational evidence on the role of early menopause in hypertension. Eur Heart J 2021. [DOI: 10.1093/eurheartj/ehab724.2339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Introduction
Blood pressure has been suggested as potential factor contributing to the increased risk of cardiovascular disease observed in women experiencing early menopause (<45 years). However, whether the association between early menopause and hypertension is causal remains unclear (1,2).
Purpose
To evaluate the observational and causal association between age at natural menopause (ANM) and blood pressure (BP) traits in Caucasian women.
Methods
Cross-sectional and one-sample Mendelian randomization (MR) study was conducted in 4451 postmenopausal women from two different cohort studies. Hypertension was defined as a systolic BP (SBP) ≥140 mmHg, and/or diastolic BP (DBP) ≥90 mmHg, and/or the use of antihypertensive medication. Multivariable linear and logistic regressions were implemented in the observational analysis. We calculated a weighted genetic risk score with 54 variants associated with ANM (GRS-ANM) (3). The genetic variants were previously identified in a genome wide association study (4), after that we implemented two-stage least squares in the one-sample MR. Estimates from all cohorts were pooled through meta-analysis
Results
The pooled analysis across cohorts showed early menopause, compared to menopause between 50–54 years, to be associated with lower DBP (β=−1.31 mmHg, 95% CI: −2.43; −0.18), while no association was found between other ANM categories and DBP. Similarly, the pooled analysis of both cohorts did not show an association of ANM with SBP, neither as a continuous variable nor by category. One year of later onset of menopause was associated with higher odds of developing hypertension (Odds ratio (OR): 1.02, 95% CI: 1:00; 1.04) while no association was found for the ANM categories and hypertension (Table 1). Results of the evaluation of MR assumption, supported their compliance, the GRS-ANM was associated with observed ANM and explained between 1.4% and 3.4% of the ANM variance in the included cohorts, F statistic values were among 11.15 and 40.63 (Figure 1). We found no association between GRS-ANM and SBP, DBP or hypertension (Table 1).
Conclusion
The present study does not support the hypothesis that early onset of menopause is associated with higher BP.
Funding Acknowledgement
Type of funding sources: Public Institution(s). Main funding source(s): The CoLaus study was and is supported by research grants from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (grants 33CSCO-122661, 33CS30-139468 and 33CS30-148401).Zayne M. Roa-Díaz has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 801076, through the SSPH+ Global PhD Fellowship Programme in Public Health Sciences (GlobalP3HS) of the Swiss School of Public Health.
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Affiliation(s)
- Z M Roa Diaz
- Institute of Social and Preventive Medicine. University of Bern, Bern, Switzerland
| | - E Asllanaj
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - H A Amin
- Brunel University, Department of Life Sciences, College of Health and Life Sciences, Uxbridge, United Kingdom
| | - L Z Rojas
- Cardiovascular Foundation of Colombia, Nursing Research and Knowledge Development Group GIDCEN, Bucaramanga, Colombia
| | - J Nano
- Helmholtz Center Munich, Institute of Epidemiology, Neuherberg, Germany
| | - M A Ikram
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - F Drenos
- Brunel University, Department of Life Sciences, College of Health and Life Sciences, Uxbridge, United Kingdom
| | - O H Franco
- Institute of Social and Preventive Medicine. University of Bern, Bern, Switzerland
| | - R Pazoki
- Brunel University, Department of Life Sciences, College of Health and Life Sciences, Uxbridge, United Kingdom
| | - P Marques-Vidal
- Lausanne University Hospital (CHUV) and University of Lausanne, Department of Medicine, Internal Medicine, Laussane, Switzerland
| | - T Voortman
- Erasmus University Medical Centre, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - T Muka
- Institute of Social and Preventive Medicine. University of Bern, Bern, Switzerland
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18
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Zhu F, Arshi B, Aribas E, Ikram MA, Ikram MK, Kavousi M. Cardiac biomarkers for cardiovascular risk prediction among women and men from the general population. Eur J Prev Cardiol 2021. [DOI: 10.1093/eurjpc/zwab061.240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: Foundation. Main funding source(s): the Erasmus Medical Center and Erasmus University Rotterdam; the Netherlands Organization for Health Research and Development (ZonMw);
Purpose
To evaluate the sex-specific predictive value of two cardiac biomarkers; N-terminal pro B-type natriuretic peptide (NT-proBNP) and high sensitivity cardiac troponin T (hs-cTnT), alongside traditional cardiovascular risk factors, for 10-year cardiovascular risk prediction in general population.
Methods
A total of 5430 participants (mean age 68.1 years; 59.9% women) free of cardiovascular disease (CVD), with blood sample measurements between 1997 and 2001 were included. We developed a ‘base’ model using cardiovascular risk factors used in the Pooled Cohort Equation (includes age, sex, systolic blood pressure, treatment of hypertension, total and high-density lipoprotein cholesterol levels, smoking, and diabetes) and then extended the ‘base’ model with NT-proBNP or hs-cTnT. These models were developed for coronary heart disease (CHD), stroke, and heart failure (HF) and also for composite CVD outcomes. To evaluate biomarkers’ added predictive value, c-statistic, and net reclassification improvement index (NRI) for events and non-events were calculated. NRI was calculated using cutoffs of 5%, 7.5% and 20% to categorize participants as low, borderline, intermediate, or high risk.
Results
Adding NT-proBNP to the ‘base’ model significantly improved c-statistic for all outcomes (increases ranged between 0.012-0.047), with the largest improvement in HF [0.026 (95% CI, 0.013, 0.040) for women and 0.047 (95% CI, 0.026, 0.069) for men]. Adding hs-TnT to ‘base’ model increased the c-statistic for CHD in women by 0.040 (95% CI, 0.013, 0.067) and for HF in men by 0.032 (95% CI, 0.005, 0.059). Improvments in reclassification by both biomarkers were mostly limited to modest improvemetns in reclassification of non-events [largest non-event NRI for global CVD in women (NT-proBNP: 11.8%; hs-cTnT: 10.5%) and for HF in men (NT-proBNP: 9.6%; hs-cTnT: 8.4%)].
Conclusion
NT-proBNP improved model performance for prediction of all cardiovascular outcomes, in particular for HF, beyond traditional risk factors for both women and men. Hs-cTnT showed modest added predictive value beyond traditional risk factors for CHD among women and for HF among men. Imropovements in reclassification by both biomarkers were modest and not clinically relevant.
Improvements of 10-year risk predictions Events Adding NT-proBNP Adding troponin T Delta c-statistic* Event NRI, % Non-event NRI, % Delta c-statistic* Event NRI, % Non-event NRI, % WomenASCVD Global CVD 0.012 (0.004, 0.020) 0.018 (0.010, 0.026) -1.7 (-5.0, 1.5)-0.8 (-3.8, 2.2) 5.4 (3.5, 7.2)11.8 (9.6, 14.1) 0.028 (0.009, 0.048)0.025 (0.009, 0.040) -0.4 (-7.1, 6.2)2.9 (-2.4, 8.3) 6.9 (3.9, 9.9)10.5 (7.3, 13.8) MenASCVD Global CVD 0.016 (0.005, 0.027)0.023 (0.012, 0.033) 0.7 (-2.3, 3.7)-0.3 (-3.0, 2.4) 5.2 (3.2, 7.2)7.2 (4.9, 9.4) 0.007 (-0.002, 0.016)0.011 (0.000, 0.021) -1.1 (-5.0, 2.7)-1.6 (-6.0, 2.8) 4.0 (1.2, 6.9)6.4 (3.1, 9.7) ASCVD comprises coronary heart disease and stroke; Global CVD comprises coronary heart disease, stroke and heart failure.
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Affiliation(s)
- F Zhu
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - B Arshi
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - E Aribas
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - MA Ikram
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - MK Ikram
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
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19
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Ahmadizar F, Wang K, Mattace Raso F, Ikram MA, Kavousi M. Associations of markers of arterial stiffness and remodeling with new-onset type 2 diabetes mellitus. Eur J Prev Cardiol 2021. [DOI: 10.1093/eurjpc/zwab061.394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Abstract
Funding Acknowledgements
Type of funding sources: None.
Background. Arterial stiffness/remodeling results in impaired blood flow and, eventually, decreased glucose disposal in peripheral tissues and increased blood glucose. Besides, increased arterial stiffness/remodeling may lead to hypertension, as a potential reciprocal risk factor for type 2 diabetes mellitus (T2D). We, therefore, hypothesized that increased arterial stiffness/remodeling is associated with an increased risk of T2D. Purpose. To study the associations between arterial stiffness/remodeling and incident T2D. Methods. We used the prospective population-based Rotterdam Study. Common carotid arterial properties were ultrasonically determined in plaque-free areas. Aortic stiffness was estimated by carotid-femoral pulse wave velocity (cf_PWV), carotid stiffness was estimated by the carotid distensibility coefficient (carDC). Arterial remodeling was estimated by carotid artery lumen diameter (carDi), carotid intima-media thickness (cIMT), mean circumferential wall stress (CWSmean), and pulsatile circumferential wall stress (CWSpuls). Cox proportional hazard regression analysis was used to estimate the associations between arterial stiffness/remodeling and the risk of incident T2D, adjusted for age, sex, cohort, mean arterial pressure (MAP), antihypertensive medications, heart rate, non- high-density lipoprotein (HDL)-cholesterol, lipid-lowering medications, and smoking. We included interaction terms in the fully adjusted models to study whether any significant associations were modified by sex, age, blood glucose, or MAP. Spearman correlation analyses were applied to examine the correlations between measurements of arterial stiffness/remodeling and glycemic traits. Results. We included 3,055 individuals free of T2D at baseline (mean (SD) age, 67.2 (7.9) years). During a median follow-up of 14.0 years, 395 (12.9%) T2D occurred. After adjustments, higher cf_PWV (hazard ratio (HR),1.18; 95%CI:1.04-1.35), carDi (1.17; 1.04-1.32), cIMT (1.15; 1.01-1.32), and CWSpuls (1.28; 1.12-1.47) were associated with increased risk of incident T2D. After further adjustment for the baseline glucose, the associations attenuated but remained statistically significant. Sex, age, blood glucose, or MAP did not modify the associations between measurements of arterial stiffness/remodeling, and incident T2D. Among the population with prediabetes at baseline (n = 513) compared to the general population, larger cIMT was associated with a greater increase in the risk of T2D. Most measurements of arterial stiffness/remodeling significantly but weakly correlated with baseline glycemic traits, particularly with blood glucose. Conclusions. Our study suggests that greater arterial stiffness/remodeling is independently associated with an increased risk of T2D development. Blood glucose and hypertension do not seem to play significant roles in these associations. Further studies should disentangle the underlying mechanism that links arterial stiffness/remodeling and T2D.
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Affiliation(s)
- F Ahmadizar
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - K Wang
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - F Mattace Raso
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - MA Ikram
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus University Medical Centre, Rotterdam, Netherlands (The)
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20
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Koek WNH, Campos-Obando N, van der Eerden BCJ, de Rijke YB, Ikram MA, Uitterlinden AG, van Leeuwen JPTM, Zillikens MC. Age-dependent sex differences in calcium and phosphate homeostasis. Endocr Connect 2021; 10:273-282. [PMID: 33543729 PMCID: PMC8052581 DOI: 10.1530/ec-20-0509] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 02/04/2021] [Indexed: 11/08/2022]
Abstract
BACKGROUND Sex differences in calcium and phosphate have been observed. We aimed to assess a relation with age. METHODS We used the laboratory values of serum calcium, phosphate and albumin from three different samples ( 2005, 2010 and 2014 years) using the hospital information system of Erasmus MC, Rotterdam. The samples were divided into three age groups: 1-17, 18-44 and ≥45 years. Sex differences in calcium and phosphate were analyzed using ANCOVA, adjusting for age and serum albumin. Furthermore, sex by age interactions were determined and we analyzed differences between age groups stratified by sex. RESULTS In all three samples there was a significant sex × age interaction for serum calcium and phosphate, whose levels were significantly higher in women compared to men above 45 years. No sex differences in the younger age groups were found. In men, serum calcium and phosphate levels were highest in the youngest age group compared to age groups of 18-44 and ≥45 years. In women, serum calcium levels were significantly higher in the age group 1-17 and the age group ≥45 years compared to the 18-44 years age group. In women, serum phosphate was different between the three different age groups with highest level in the group 1-17 years and lowest in the group 18-44 years. CONCLUSION There are age- dependent sex differences in serum calcium and phosphate. Furthermore, we found differences in serum calcium and phosphate between different age groups. Underlying mechanisms for these age- and sex- differences are not yet fully elucidated.
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Affiliation(s)
- W N H Koek
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - N Campos-Obando
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - B C J van der Eerden
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - Y B de Rijke
- Department of Clinical Chemistry, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - A G Uitterlinden
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands
| | - J P T M van Leeuwen
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - M C Zillikens
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Correspondence should be addressed to M C Zillikens:
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21
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Aribas E, Ahmadizar F, Mutlu U, Ikram MK, Bos D, Laven JSE, Klaver CCW, Ikram MA, Roeters van Lennep JL, Kavousi M. Sex steroids and markers of micro- and macrovascular damage among women and men from the general population. Eur J Prev Cardiol 2021; 29:1322-1330. [PMID: 33580786 DOI: 10.1093/eurjpc/zwaa031] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/11/2020] [Accepted: 07/27/2020] [Indexed: 12/18/2022]
Abstract
AIMS The contribution of sex hormones to micro- and macrovascular damage might differ among women and men. In particular, little is known about the association between sex hormones and small vessel disease. Therefore, we examined the association of total oestradiol, total testosterone, free-androgen index (FAI), dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), and androstenedione levels with micro- and macrovascular diseases. METHODS AND RESULTS This cross-sectional study included 2950 women and 2495 men from the population-based Rotterdam Study. As proxy of microvascular damage, we measured diameters of retinal arterioles and venules. Markers of macrovascular damage included carotid intima-media thickness and carotid plaque, coronary artery calcification (CAC), and peripheral artery disease. Linear and logistic regression models were used and adjusted for age, cardiovascular risk factors, and years since menopause. Associations with microvasculature: In women, total testosterone [mean difference per 1-unit increase in natural-log transformed total testosterone (95% confidence interval, CI): 2.59 (0.08-5.09)] and androstenedione [4.88 (1.82-7.95)] and in men DHEAS [2.80 (0.23-5.37)] and androstenedione [5.83 (2.19-9.46)] were associated with larger venular caliber. Associations with markers of large vessel disease: In women, higher total testosterone [-0.29 (-0.56 to -0.03)], FAI [-0.33 (-0.56 to -0.10)], and androstenedione levels [-0.33 (-0.64 to -0.02)] were associated with lower CAC burden and FAI [odds ratio (95% CI): 0.82 (0.71-0.94)] was associated with lower prevalence of plaque. CONCLUSION A more androgenic profile was associated with more microvascular damage in both women and men. Among women, however, higher androgen levels were also associated with less macrovascular damage. Our findings suggest that androgens might have distinct effects on the vasculature, depending on the vascular bed and stages of the atherosclerosis process.
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Affiliation(s)
- E Aribas
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - F Ahmadizar
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - U Mutlu
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M K Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - D Bos
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J S E Laven
- Division of Reproductive Medicine, Department of Obstetrics and Gynaecology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - C C W Klaver
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Ophthalmology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands.,Institute for Molecular and Clinical Ophthalmology, Basel, Switzerland
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J L Roeters van Lennep
- Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - M Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
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22
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Heshmatollah A, Mutlu U, Koudstaal PJ, Ikram MA, Ikram MK. Cognitive and physical impairment and the risk of stroke - A prospective cohort study. Sci Rep 2020; 10:6274. [PMID: 32286410 PMCID: PMC7156475 DOI: 10.1038/s41598-020-63295-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Accepted: 03/03/2020] [Indexed: 11/16/2022] Open
Abstract
The manifestation of cognitive and physical impairment in stroke patients before the acute event suggests accumulating subclinical vascular pathology in the brain. We investigated whether impairments in cognitive and physical functioning were associated with an increased stroke risk. Between 2002 and 2008, 8,519 stroke-free non-demented participants from the population-based Rotterdam Study underwent cognition and physical assessments including Mini-Mental State Examination, 15-word learning test, Stroop test, letter-digit substitution test, verbal fluency test, Purdue pegboard test and questionnaires on basic and instrumental activities of daily living (BADL; IADL). Principal component analysis was used to derive global cognition (G-factor). Incident stroke was assessed through continuous monitoring of medical records until 2016. Among 8,519 persons (mean age 66.0 years; 57.8% women), 489 suffered a stroke during mean follow-up of 8.7 years (SD: 2.9). Worse G-factor was associated with higher stroke risk (Hazard Ratio 1.21, 95% CI: 1.06–1.38), largely driven by unspecified stroke. Likewise, worse scores on 15-word learning test, Stroop test, Purdue pegboard test, IADL, and BADL were associated with higher risk of stroke. Thus both worse cognitive and physical functioning were associated with a higher stroke risk, in particular unspecified stroke and persons with worse memory, information processing, executive function, and motor function.
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Affiliation(s)
- A Heshmatollah
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - U Mutlu
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - P J Koudstaal
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M K Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands. .,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
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23
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Arkesteijn GAM, Poot DHJ, Ikram MA, Niessen WJ, Van Vliet LJ, Vernooij MW, Vos FM. Orientation Prior and Consistent Model Selection Increase Sensitivity of Tract-Based Spatial Statistics in Crossing-Fiber Regions. IEEE Trans Med Imaging 2020; 39:308-319. [PMID: 31217096 DOI: 10.1109/tmi.2019.2922615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The goal of this paper is to increase the statistical power of crossing-fiber statistics in voxelwise analyses of diffusion-weighted magnetic resonance imaging (DW-MRI) data. In the proposed framework, a fiber orientation atlas and a model complexity atlas were used to fit the ball-and-sticks model to diffusion-weighted images of subjects in a prospective population-based cohort study. Reproducibility and sensitivity of the partial volume fractions in the ball-and-sticks model were analyzed using TBSS (tract-based spatial statistics) and compared to a reference framework. The reproducibility was investigated on two scans of 30 subjects acquired with an interval of approximately three weeks by studying the intraclass correlation coefficient (ICC). The sensitivity to true biological effects was evaluated by studying the regression with age on 500 subjects from 65 to 90 years old. Compared to the reference framework, the ICC improved significantly when using the proposed framework. Higher t-statistics indicated that regression coefficients with age could be determined more precisely with the proposed framework and more voxels correlated significantly with age. The application of a fiber orientation atlas and a model complexity atlas can significantly improve the reproducibility and sensitivity of crossing-fiber statistics in TBSS.
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24
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de Las Fuentes L, Sung YJ, Sitlani CM, Avery CL, Bartz TM, Keyser CD, Evans DS, Li X, Musani SK, Ruiter R, Smith AV, Sun F, Trompet S, Xu H, Arnett DK, Bis JC, Broeckel U, Busch EL, Chen YDI, Correa A, Cummings SR, Floyd JS, Ford I, Guo X, Harris TB, Ikram MA, Lange L, Launer LJ, Reiner AP, Schwander K, Smith NL, Sotoodehnia N, Stewart JD, Stott DJ, Stürmer T, Taylor KD, Uitterlinden A, Vasan RS, Wiggins KL, Cupples LA, Gudnason V, Heckbert SR, Jukema JW, Liu Y, Psaty BM, Rao DC, Rotter JI, Stricker B, Wilson JG, Whitsel EA. Genome-wide meta-analysis of variant-by-diuretic interactions as modulators of lipid traits in persons of European and African ancestry. Pharmacogenomics J 2019; 20:482-493. [PMID: 31806883 PMCID: PMC7260079 DOI: 10.1038/s41397-019-0132-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Revised: 11/13/2019] [Accepted: 11/20/2019] [Indexed: 01/11/2023]
Abstract
Hypertension (HTN) is a significant risk factor for cardiovascular morbidity and mortality. Metabolic abnormalities, including adverse cholesterol and triglycerides (TG) profiles, are frequent comorbid findings with HTN and contribute to cardiovascular disease. Diuretics, which are used to treat HTN and heart failure, have been associated with worsening of fasting lipid concentrations. Genome-wide meta-analyses with 39,710 European-ancestry (EA) individuals and 9,925 African-ancestry (AA) individuals were performed to identify genetic variants that modify the effect of loop or thiazide diuretic use on blood lipid concentrations. Both longitudinal and cross-sectional data were used to compute cohort-specific interaction results, which were then combined through meta-analysis in each ancestry. These ancestry-specific results were further combined through trans-ancestry meta-analysis. Analysis of EA data identified two genome-wide significant (p < 5×10−8) loci with single nucleotide variant (SNV)-loop diuretic interaction on TG concentrations (including COL11A1). Analysis of AA data identified one genome-wide significant locus adjacent to BMP2 with SNV-loop diuretic interaction on TG concentrations. Trans-ancestry analysis strengthened evidence of association for SNV-loop diuretic interaction at two loci (KIAA1217 and BAALC). There were few significant SNV-thiazide diuretic interaction associations on TG concentrations and for either diuretic on cholesterol concentrations. Several promising loci were identified that may implicate biologic pathways that contribute to adverse metabolic side effects from diuretic therapy.
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Affiliation(s)
- L de Las Fuentes
- Cardiovascular Division, Department of Medicine, Washington University, St. Louis, MO, USA.
| | - Y J Sung
- Division of Biostatistics, Washington University, St. Louis, MO, USA
| | - C M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - C L Avery
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - T M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - C de Keyser
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - D S Evans
- Research Institute, California Pacific Medical Center, San Francisco, CA, USA
| | - X Li
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - S K Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - R Ruiter
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - A V Smith
- Icelandic Heart Association, Kopavogur, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - F Sun
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - S Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - H Xu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - D K Arnett
- Dean's Office, University of Kentucky College of Public Health, Lexington, KY, USA
| | - J C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - U Broeckel
- Section of Genomic Pediatrics, Department of Pediatrics, Medicine and Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - E L Busch
- Channing Division of Network Medicine, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Y-D I Chen
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - A Correa
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - S R Cummings
- Research Institute, California Pacific Medical Center, San Francisco, CA, USA
| | - J S Floyd
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, USA
| | - I Ford
- Robertson Center for biostatistics, University of Glasgow, Glasgow, UK
| | - X Guo
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - T B Harris
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - M A Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L Lange
- Department of Genetics, University of Colorado, Denver, Denver, CO, USA
| | - L J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - A P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.,School of Public Health, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - K Schwander
- Division of Biostatistics, Washington University, St. Louis, MO, USA
| | - N L Smith
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA.,Seattle Epidemiologic Research and Information Center (ERIC), VA Cooperative Studies Program, VA Puget Sound Health Care System, Seattle, WA, USA
| | - N Sotoodehnia
- Cardiovascular Health Research Unit, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, USA.,Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - J D Stewart
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA
| | - D J Stott
- Institute of cardiovascular and medical sciences, Faculty of Medicine, University of Glasgow, Glasgow, United Kingdom
| | - T Stürmer
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,Center for Pharmacoepidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - K D Taylor
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - A Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - R S Vasan
- The Framingham Heart Study, Framingham, MA, USA.,Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - K L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - L A Cupples
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.,The Framingham Heart Study, Framingham, MA, USA
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - S R Heckbert
- Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - J W Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands.,Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
| | - Y Liu
- Division of Public Health Sciences, Department of Epidemiology and Prevention, Wake Forest University, Winston-, Salem, NC, USA
| | - B M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine, and Health Services, University of Washington, Seattle, WA, USA.,Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - D C Rao
- Division of Biostatistics, Washington University, St. Louis, MO, USA
| | - J I Rotter
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - B Stricker
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - J G Wilson
- Biophysics and Physiology, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - E A Whitsel
- Gillings School of Global Public Health, Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,School of Medicine, Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
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25
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Arshi B, Van Den Berge JC, Van Dijk B, Deckers JW, Ikram MA, Kavousi M. P4152Implications of the ACC/AHA risk score for heart failure risk prediction and its comparison with existing heart failure risk prediction models: A prospective population-based cohort study. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz745.0724] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
In 2013, the American College of Cardiology (ACC) and the American Heart Association (AHA) developed a score for assessment of cardiovascular risk. Due to between study variability in ascertainment and adjudication of heart failure (HF), incident HF was not included as an endpoint in the ACC/AHA risk score.
Purpose
To assess the performance of the ACC/AHA risk score for HF risk prediction in a large population-based cohort and to compare its performance with the existing HF risk prediction models including the Atherosclerosis Risk in Communities (ARIC) model and the Health Aging and Body Composition (Health ABC) model.
Methods
The study included 2743 men and 3646 women from a prospective population-based cohort study. Cox proportional hazards models were fitted using risk factors applied by the ACC/AHA model for cardiovascular risk, the ARIC model and the Health ABC model. Independent relationship of each predictor with 10-year HF incidence was estimated in men and women. Next, N-terminal pro-b-type natriuretic peptide (NT-pro-BNP) was added to the ACC/AHA model.
The performance of all fitted models was evaluated and compared in terms of discrimination, calibration and the Akaike Information Criterion (AIC). In addition, area under the receiver operator characteristic curve (AUC), sensitivity and specificity of each model in predicting 10-year incident of HF was assessed. The incremental value of NT-pro-BNP to the ACC/AHA model, was assessed using the continuous net reclassification improvement index (NRI).
Results
During a median follow-up of 13 years (63127 person-years), 387 HF events in women and 259 in men were recorded. The Optimism-corrected c-statistic for ACC/AHA model was 0.76 (95% confidence interval (CI): 0.73–0.79) for men and 0.76 (95% CI: 0.74–0.79) for women. The ARIC model provided the largest c-statistic for both men [0.82 (95% CI: 0.80–0.84)] and women [95% CI: 0.81 (0.79–0.83)] among the three models. Calibration of the models was reasonable.
Addition of NT-pro-BNP to the ACC/AHA model considerably improved model fitness for men and for women. The AIC improved from 3104.62 to 2976.28 among men and from 5161.63 to 4921.51 among women. The c-statistic also improved to 0.81 (0.78–0.84) in men and 0.79 (0.77–0.81) in women. The continuous NRI for the addition of NT-pro-BNP to the base model was 5.3% (95% CI: −12.3–28.6%) for men and 15.9% (95% CI: 2.7–24.7%) for women.
Conclusions
Compared to HF-specific models, the ACC/AHA model, containing routine clinically available risk factors, had a reasonable performance in prediction of HF risk. Inclusion of NT-pro-BNP in the ACC/AHA model strongly increased the model performance. To achieve a better model performance for 10-year prediction of incident HF, updating the simple ACC/AHA risk score with the addition of NT-pro-BNP is recommended.
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Affiliation(s)
- B Arshi
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - J C Van Den Berge
- Erasmus Medical Center, Department of Cardiology, Rotterdam, Netherlands (The)
| | - B Van Dijk
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - J W Deckers
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M A Ikram
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
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Rueda-Ochoa OL, Rojas Sanchez LZ, Ikram MA, Deckers JW, Franco OH, Rizopoulos D, Kavousi M. P796Intensive blood pressure treatment significantly increases visit-to-visit systolic blood pressure variability. A randomized clinical trial. Eur Heart J 2019. [DOI: 10.1093/eurheartj/ehz747.0395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Abstract
Background
Intensive blood pressure lowering is increasingly gaining attention. Besides higher baseline blood pressure, visit-to-visit variability has showed association with target organ damage and major adverse cardiovascular outcomes in multiple medical reports.
Purpose
Our aim was to assess the effect of intensive treatment on systolic blood pressure (SBP) visit-to-visit variability in the SPRINT trial population during follow-up.
Methods
We included 9068 SPRINT participants with 128139 repeated SBP measurements. Participants were randomly assigned to intensive (SBP <120 mmHg) vs standard treatment (SBP between 135–139 mmHg). The primary outcome was a composite outcome of myocardial infarction, other acute coronary syndromes, acute decompensated heart failure, stroke, and cardiovascular mortality. We calculated the coefficient of variation (CV) and standard deviation (SD), taking into account all SBP measurements prior to the SPRINT primary outcome. Comparison of CV between intensive and standard treatment in the total SPRINT population and among different subgroups was made.
Results
CVs in intensive treatment groups were higher in total population and in all groups under study (See table). While second and third CV quartile showed a larger tendency to increase the risk for the primary SPRINT outcome in the intensive treatment compared to the standard treatment group, fourth CV quartiles were significantly associated with increase in primary SPRINT outcome in both intensive and standard treatment groups.
Coefficient of variation in SPRINT trial Group Intensive treatment Standard treatment Total population 9.80 (3.22)* 8.52 (2.96) Females 10.46 (3.29)* 9.18 (3.15) Black person 9.99 (3.38)* 8.82 (3.15) Prevalence CKD 10.14 (3.22)* 9.12 (3.06) Prevalence CVD 10.28 (3.32)* 8.93 (3.23) ≥75 year 10.40 (3.18)* 9.01 (3.07) SAEs 10.30 (3.39)* 9.08 (3.13) (CKD: chronic kidney disease; CVD: cardiovascular disease; SAEs: serious adverse events. *P<0.05).
Conclusions
Intensive blood pressure treatment significantly increases SBP visit-to-visit variability in total SPRINT population and in all subgroups under study. Additional longitudinal studies with long-term follow-up are warranted to evaluate the impact of increases in SBP visit-to-visit variability due to intensive treatment on risk of major cardiovascular events.
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Affiliation(s)
- O L Rueda-Ochoa
- Industrial University of Santander, Department of Basic Sciences, Bucaramanga, Colombia
| | - L Z Rojas Sanchez
- Industrial University of Santander, School of Nursing, Bucaramanga, Colombia
| | - M A Ikram
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - J W Deckers
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - O H Franco
- University of Bern, Institute of Social and Preventive Medicine (ISPM), Bern, Switzerland
| | - D Rizopoulos
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
| | - M Kavousi
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands (The)
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Aribas E, Elias-Smale SE, Duncker DJ, Piek JJ, Ikram MA, Appelman Y, Roeters van Lennep JE, Kavousi M. Questionnaire survey on cardiologists' view and management of coronary microvascular disease in clinical practice. Neth Heart J 2019; 27:252-262. [PMID: 30980346 PMCID: PMC6470226 DOI: 10.1007/s12471-019-1274-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Objective We aimed to assess the opinion of Dutch cardiologists on coronary microvascular disease (CMD) and its management in clinical practice, and to assess the need for a CMD guideline among Dutch cardiologists. Methods We developed an online questionnaire including different aspects of CMD which was reviewed by an expert panel. The questionnaire was distributed by e‑mail among all members of the Dutch Society of Cardiology. Results A total of 103 cardiologists (70% male) completed the questionnaire (response rate: 10%). Median age and years of experience as a cardiologist were 49 ± 15 and 12 ± 12 years, respectively. Overall, 93% of the cardiologists had considered the CMD diagnosis, 85% had ever made such a diagnosis, 90% had treated a patient with CMD, and 61% had referred patients to tertiary care. The median (interquartile range) self-rated knowledge level was 7.0 (2.0) (scale of 0–10). 84% rated their knowledge as sufficient (>5.5) and 58% viewed CMD as a disease entity. Overall, 61% and 17%, respectively, agreed that evidence-based diagnostic and treatment modalities for CMD do not exist, while 56% believed that CMD patients have a higher risk for cardiovascular disease and mortality. Finally, 82% of the responders stated that a CMD guideline is needed, and 91% wanted to receive the guideline once developed. Discussion Fifty-eight per cent of the responders recognise CMD as a separate disease entity. Our study underscores the need for a dedicated CMD guideline for Dutch cardiology practice. However, the response rate was low (10%), and it is likely that mainly cardiologists interested in CMD have participated in our study. Electronic supplementary material The online version of this article (10.1007/s12471-019-1274-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- E Aribas
- Department of Epidemiology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - S E Elias-Smale
- Department of Cardiology, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - D J Duncker
- Department of Cardiology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - J J Piek
- Department of Cardiology, Amsterdam University Medical Centres, location AMC, Amsterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Y Appelman
- Department of Cardiology, Amsterdam University Medical Centres, location VU University Medical Centre, Amsterdam, The Netherlands
| | - J E Roeters van Lennep
- Department of Internal Medicine, Erasmus MC, University Medical Centre, Rotterdam, The Netherlands
| | - M Kavousi
- Department of Epidemiology, Erasmus MC, University Medical Centre Rotterdam, Rotterdam, The Netherlands.
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28
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Fest J, Ruiter R, Mooijaart SP, Ikram MA, van Eijck CHJ, Stricker BH. Erythrocyte sedimentation rate as an independent prognostic marker for mortality: a prospective population-based cohort study. J Intern Med 2019; 285:341-348. [PMID: 30537394 DOI: 10.1111/joim.12853] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
BACKGROUND A very high erythrocyte sedimentation rate (ESR) is usually an indication of underlying pathology. Additionally, a moderately elevated ESR may also be attributable to biological ageing. Whether the ESR is a prognostic factor for mortality, regardless of age, has been scarcely investigated. Therefore, the objective was to analyse the association between elevated ESR levels and the risk of mortality in a prospective cohort of the general population. METHODS We studied data from the Rotterdam Study (1990-2014). ESR levels were measured at baseline and individuals were followed until death or end of study. Associations between moderately (20-50 mm h-1 ) and markedly (>50 mm h-1 ) elevated ESR levels and all-cause mortality were assessed using multivariate Cox proportional hazard models. RESULTS In total, 5226 participants were included, and the mean age was 70.3 years. During a median follow-up time of 14.9 years, 3749 participants died (71.7%). After adjustment, both a moderately elevated ESR and a markedly elevated ESR were associated with a significantly higher risk of overall mortality [hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.12-1.35 and HR 1.89, 95% CI 1.38-2.60, respectively]. Although the ESR becomes higher with age, in a group aged above 75 years, without any comorbidities, an ESR > 20 mm h-1 remained associated with a significantly increased risk of mortality (HR 1.29, 95%CI 1.01-1.64). CONCLUSION An elevated ESR is an independent prognostic factor for mortality. Despite the fact that ESR increases with age, it remains associated with an increased risk of mortality and warrants close follow-up.
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Affiliation(s)
- J Fest
- Department of Surgery, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - R Ruiter
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - S P Mooijaart
- Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands.,Institute for Evidence-based Medicine in Old Age, Leiden, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - C H J van Eijck
- Department of Surgery, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - B H Stricker
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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van Opbroek A, Achterberg HC, Vernooij MW, Ikram MA, de Bruijne M. Transfer learning by feature-space transformation: A method for Hippocampus segmentation across scanners. Neuroimage Clin 2018; 20:466-475. [PMID: 30128285 PMCID: PMC6098216 DOI: 10.1016/j.nicl.2018.08.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 07/26/2018] [Accepted: 08/05/2018] [Indexed: 11/09/2022]
Abstract
Many successful approaches in MR brain segmentation use supervised voxel classification, which requires manually labeled training images that are representative of the test images to segment. However, the performance of such methods often deteriorates if training and test images are acquired with different scanners or scanning parameters, since this leads to differences in feature representations between training and test data. In this paper we propose a feature-space transformation (FST) to overcome such differences in feature representations. The proposed FST is derived from unlabeled images of a subject that was scanned with both the source and the target scan protocol. After an affine registration, these images give a mapping between source and target voxels in the feature space. This mapping is then used to map all training samples to the feature representation of the test samples. We evaluated the benefit of the proposed FST on hippocampus segmentation. Experiments were performed on two datasets: one with relatively small differences between training and test images and one with large differences. In both cases, the FST significantly improved the performance compared to using only image normalization. Additionally, we showed that our FST can be used to improve the performance of a state-of-the-art patch-based-atlas-fusion technique in case of large differences between scanners. We present a feature-space transformation for image segmentation across scanners. This FST is trained on unlabeled images of subjects scanned with multiple scanners. These are used to transform training samples to values observed in target samples. The FST makes SVM hippocampus segmentation across scanners significantly better. Our FST can also increase performance of patch-based fusion methods.
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Affiliation(s)
- Annegreet van Opbroek
- Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC - University Medical Center Rotterdam, 3000, CA, Rotterdam, the Netherlands.
| | - Hakim C Achterberg
- Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC - University Medical Center Rotterdam, 3000, CA, Rotterdam, the Netherlands
| | - Meike W Vernooij
- Department of Radiology and Epidemiology, Erasmus MC - University Medical Center Rotterdam, Postbus 2040, 3000, CA, Rotterdam, the Netherlands
| | - M A Ikram
- Department of Radiology and Epidemiology, Erasmus MC - University Medical Center Rotterdam, Postbus 2040, 3000, CA, Rotterdam, the Netherlands
| | - Marleen de Bruijne
- Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC - University Medical Center Rotterdam, 3000, CA, Rotterdam, the Netherlands; Department of Computer Science, University of Copenhagen, DK-2100 Copenhagen, Denmark.
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30
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Mulder M, Kiefte-de Jong JC, Goessens WHF, de Visser H, Ikram MA, Verbon A, Stricker BH. Diet as a risk factor for antimicrobial resistance in community-acquired urinary tract infections in a middle-aged and elderly population: a case-control study. Clin Microbiol Infect 2018; 25:613-619. [PMID: 30099137 DOI: 10.1016/j.cmi.2018.07.029] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Revised: 07/13/2018] [Accepted: 07/29/2018] [Indexed: 01/22/2023]
Abstract
OBJECTIVES There is an ongoing debate as to what extent antimicrobial resistance (AMR) can be transmitted from animals to humans via the consumption of animal products. Because epidemiological data on the role of diet in AMR in humans are lacking, we investigated this association between diet and AMR for different antimicrobial drugs in Escherichia coli (E. coli) in urinary tract infections (UTIs). METHODS Susceptibility of E. coli in urinary cultures and information on diet (with food frequency questionnaires) were obtained from participants of the Rotterdam study, a population-based prospective cohort study. The association between intake of several food groups (meat, seafood, eggs, dairy products, crops) and resistance of E. coli to several antimicrobial drugs (amoxicillin, amoxicillin-clavulanic acid, trimethoprim, sulfamethoxazole-trimethoprim, first-generation cephalosporins, cefotaxime, nitrofurantoin, norfloxacin) was studied. RESULTS Urinary cultures with E. coli were obtained from 612 individuals, of whom 481 (78.6%) were women. Resistance rates varied from 246/611 (40.3%) for amoxicillin and 167/612 (27.3%) for trimethoprim to only 29/612 (4.7%) for nitrofurantoin and 16/462 (3.5%) for cefotaxime. A higher intake of chicken was associated with cefotaxime resistance (OR 2.18; 95% CI 1.05-4.51 per tertile increase); a higher intake of pork was associated with norfloxacin resistance (OR 1.42; 95% CI 1.04-1.95 per quartile increase). In contrast, a higher intake of cheese was associated with lower AMR to amoxicillin (OR 0.84; 95% CI 0.72-0.99 per quartile increase) and amoxicillin-clavulanic acid (OR 0.67; 95% CI 0.53-0.86 per quartile increase). CONCLUSIONS These findings support the hypothesis that diet may play a role in the AMR of E. coli in UTIs.
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Affiliation(s)
- M Mulder
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; Youth and Healthcare Inspectorate, Utrecht, The Netherlands
| | - J C Kiefte-de Jong
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; Leiden University College, The Hague, The Netherlands; Department of Public Health and Primary Care / LUMC Campus the Hague, Leiden, The Netherlands
| | - W H F Goessens
- Department of Medical Microbiology and Infectious Diseases, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H de Visser
- Star-Medisch Diagnostisch Centrum, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - A Verbon
- Department of Public Health and Primary Care / LUMC Campus the Hague, Leiden, The Netherlands; Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - B H Stricker
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; Youth and Healthcare Inspectorate, Utrecht, The Netherlands; Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
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31
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Darweesh SKL, Ikram MK, Faber MJ, de Vries NM, Haaxma CA, Hofman A, Koudstaal PJ, Bloem BR, Ikram MA. Professional occupation and the risk of Parkinson's disease. Eur J Neurol 2018; 25:1470-1476. [PMID: 30007105 PMCID: PMC6282552 DOI: 10.1111/ene.13752] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Accepted: 07/10/2018] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND PURPOSE Creativity in Parkinson's disease (PD) is strongly related to dopaminergic activity and medication. We hypothesized that patients with PD, including those who are in the pre-diagnostic phase of PD, are prone to choose highly structured 'conventional' professional occupations and avoid highly creative 'artistic' occupations. METHODS At baseline of the population-based Rotterdam Study, we asked 12 147 individuals aged ≥45 years about their latest occupation and categorized occupations according to the RIASEC model. Participants underwent baseline and follow-up (median 11 years) examinations for PD. We determined associations of artistic (versus any other occupation) and conventional (versus any other occupation) occupations with PD. Additionally, we pooled our results with a recently published case-control study (Radboud Study). RESULTS At baseline, conventional occupations were common [n = 4356 (36%)], whereas artistic occupations were rare [n = 137 (1%)]. There were 217 patients with PD, including 91 with prevalent PD and 126 with incident PD. The risk of PD varied substantially across occupational categories (chi-square, 14.61; P = 0.01). The penalized odds ratio (OR) of artistic occupations for PD was 0.19 [95% confidence interval (CI), 0.00-1.31; P = 0.11], whereas the OR of conventional occupations for PD was 1.23 (95% CI, 0.95-1.66; P = 0.10). The direction and magnitude of ORs were similar in cross-sectional and longitudinal subsamples. Pooled ORs across the Rotterdam and Radboud Studies were 0.20 (95% CI, 0.08-0.52; P < 0.001) for artistic and 1.23 (95% CI, 0.92-1.67; P = 0.08) for conventional occupations. CONCLUSIONS The risk of PD varies substantially by choice of professional occupation. Our findings suggest that dopaminergic degeneration affects choice of occupation, which may start in the pre-diagnostic phase of PD.
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Affiliation(s)
- S K L Darweesh
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Parkinson Center Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - M K Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M J Faber
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Parkinson Center Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - N M de Vries
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Parkinson Center Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - C A Haaxma
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Parkinson Center Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - P J Koudstaal
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - B R Bloem
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands.,Parkinson Center Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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32
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Aribas E, Ikram MK, Mutlu U, Bos D, Franco Duran OH, Ikram MA, Roeters Van Lennep JE, Kavousi M. P4449Sex steroids, sex hormone-binding globulin and markers of micro- and macrovascular damage. Eur Heart J 2018. [DOI: 10.1093/eurheartj/ehy563.p4449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- E Aribas
- Erasmus Medical Center, Rotterdam, Netherlands
| | - M K Ikram
- Erasmus Medical Center, Rotterdam, Netherlands
| | - U Mutlu
- Erasmus Medical Center, Rotterdam, Netherlands
| | - D Bos
- Erasmus Medical Center, Rotterdam, Netherlands
| | | | - M A Ikram
- Erasmus Medical Center, Rotterdam, Netherlands
| | | | - M Kavousi
- Erasmus Medical Center, Rotterdam, Netherlands
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33
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Rueda Ochoa OL, Milkas AN, Fournier S, Muller O, Cicarrelli G, Xaplanteris P, Van Rooij F, Ikram MA, Wyffels E, Vanderheyden M, Bartunek J, Franco OH, Barbato E, De Bruyne B, Kavousi M. P3649Evaluating the 10-year survival after an FFR-guided strategy in patients with proximal isolated stenosis in the left anterior descending coronary artery: impact of control selection. Eur Heart J 2018. [DOI: 10.1093/eurheartj/ehy563.p3649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- O L Rueda Ochoa
- Industrial University of Santander, Department of Basic Sciences, Bucaramanga, Colombia
| | - A N Milkas
- Naval Hospital of Athens, Cardiology, Athens, Greece
| | - S Fournier
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands
| | - O Muller
- University of Lausanne, Department of Cardiology, Lausanne, Switzerland
| | | | | | - F Van Rooij
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands
| | - M A Ikram
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands
| | - E Wyffels
- Federico II University of Naples, Department of Advanced Biomedical Sciences, Naples, Italy
| | - M Vanderheyden
- Federico II University of Naples, Department of Advanced Biomedical Sciences, Naples, Italy
| | - J Bartunek
- Federico II University of Naples, Department of Advanced Biomedical Sciences, Naples, Italy
| | - O H Franco
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands
| | - E Barbato
- Federico II University of Naples, Department of Advanced Biomedical Sciences, Naples, Italy
| | | | - M Kavousi
- Erasmus Medical Center, Department of Epidemiology, Rotterdam, Netherlands
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34
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Aribas E, Roeters Van Lennep JE, Franco Duran OH, Ikram MA, Kavousi M. P5087Sex hormone-binding globulin, aging, and cardiovascular risk. Eur Heart J 2018. [DOI: 10.1093/eurheartj/ehy566.p5087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- E Aribas
- Erasmus Medical Center, Rotterdam, Netherlands
| | | | | | - M A Ikram
- Erasmus Medical Center, Rotterdam, Netherlands
| | - M Kavousi
- Erasmus Medical Center, Rotterdam, Netherlands
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Abstract
Dementia is among the leading causes of death and disability. Due to the ageing population, its prevalence is expected to nearly triple worldwide by 2050, urging the development of preventive and curative interventions. Various modifiable risk factors have been identified in community-based cohort studies, but insight into the underlying pathophysiological mechanisms is lacking. Clinical trials have thus far failed in the development of disease-modifying therapy in patients with dementia, thereby triggering a shift of focus toward the presymptomatic phase of disease. The extensive preclinical disease course of Alzheimer's disease warrants reliable, easily obtainable biomarkers to aid in timely application of preventive strategies, selecting participants for neuroprotective trials, and disease monitoring in trials and clinical practice. Biomarker and drug discovery may yield the fruits from technology-driven developments in the field of genomics, epigenetics, metabolomics, and brain imaging. In that context, bridging the gap between translational and population research may well prove a giant leap toward development of successful preventive and curative interventions against dementia.
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Affiliation(s)
- Frank J Wolters
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - M A Ikram
- Departments of Epidemiology, Radiology, Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands.
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36
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Arkesteijn GAM, Poot DHJ, de Groot M, Ikram MA, Niessen WJ, van Vliet LJ, Vernooij MW, Vos FM. CSF contamination-invariant statistics in conventional diffusion-weighted MRI of the fornix. Biomed Phys Eng Express 2017. [DOI: 10.1088/2057-1976/aa890e] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Abstract
BACKGROUND Subjectively assessed health is related to mortality. Various subjective indicators of health have been studied, but it is unclear whether perceived physical functioning or mental health best accounts for the relation with mortality. METHOD We studied the relation of subjective measures of health with all-cause mortality in 5538 participants of age 55 to 96 years at baseline from the Rotterdam Study. Various instruments of subjectively assessed health were used, that included basic activities of daily living (BADL), instrumental activities of daily living (IADL), quality of life (QoL), positive affect, somatic symptoms and negative affect. All participants completed questionnaires for each subjective measure of health and were followed for mortality for a mean of 12.2 (s.e. = 0.09) years. Cox regression analysis was conducted in the total sample. RESULTS In this cohort, 2021 persons died during 48 534 person-years of follow-up. All measures of subjective health were related to mortality after adjusting for age, gender, education, cognition, prevalent chronic diseases and cardiovascular risk [BADL hazard ratio (HR, calculated per Z-score) = 1.35, 95% confidence interval (CI) 1.29-1.41; IADL HR = 1.27, 95% CI 1.22-1.32; QoL HR = 0.85, 95% CI 0.81-0.89; positive affect HR = 0.92, 95% CI 0.88-0.96; somatic symptoms HR = 1.11, 95% CI 1.06-1.16; and negative affect HR = 1.05, 95% CI 1.01-1.10]. In the mutually adjusted model, only BADL (HR = 1.24, 95% CI 1.16-1.32) and IADL (HR = 1.10, 95% CI 1.04-1.17) remained independently associated with mortality. CONCLUSIONS Measures of subjectively assessed health are important indicators of mortality. Our study shows that of the different measures of subjective health, perceived physical health predicts mortality over and above mental health. Conversely, the association between mental health and mortality may partly be explained by poor perceived physical health.
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Affiliation(s)
- A Sajjad
- Department of Epidemiology,Erasmus University Medical Center,Rotterdam,The Netherlands
| | - R L Freak-Poli
- Department of Epidemiology,Erasmus University Medical Center,Rotterdam,The Netherlands
| | - A Hofman
- Department of Epidemiology,Erasmus University Medical Center,Rotterdam,The Netherlands
| | - S J Roza
- Department of Psychiatry,Erasmus University Medical Center,Rotterdam,The Netherlands
| | - M A Ikram
- Department of Epidemiology,Erasmus University Medical Center,Rotterdam,The Netherlands
| | - H Tiemeier
- Department of Epidemiology,Erasmus University Medical Center,Rotterdam,The Netherlands
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van den Bouwhuijsen QJA, Vernooij MW, Verhaaren BFJ, Vrooman HA, Niessen WJ, Krestin GP, Ikram MA, Franco OH, van der Lugt A. Carotid Plaque Morphology and Ischemic Vascular Brain Disease on MRI. AJNR Am J Neuroradiol 2017; 38:1776-1782. [PMID: 28705824 DOI: 10.3174/ajnr.a5288] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 04/27/2017] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Vulnerable carotid plaque components are reported to increase the risk of cerebrovascular events. Yet, the relation between plaque composition and subclinical ischemic brain disease is not known. We studied, in the general population, the association between carotid atherosclerotic plaque characteristics and ischemic brain disease on MR imaging. MATERIALS AND METHODS From the population-based Rotterdam Study, 951 participants underwent both carotid MR imaging and brain MR imaging. The presence of intraplaque hemorrhage, lipid core, and calcification and measures of plaque size was assessed in both carotid arteries. The presence of plaque characteristics in relation to lacunar and cortical infarcts and white matter lesion volume was investigated and adjusted for cardiovascular risk factors. Stratified analyses were conducted to explore effect modification by sex. Additional analyses were conducted per carotid artery in relation to vascular brain disease in the ipsilateral hemisphere. RESULTS Carotid intraplaque hemorrhage was significantly associated with the presence of cortical infarcts (OR, 1.9; 95% confidence interval, 1.1-3.3). None of the plaque characteristics were related to the presence of lacunar infarcts. Calcification was the only characteristic that was associated with higher white matter lesion volume. There was no significant interaction by sex. CONCLUSIONS The presence of carotid intraplaque hemorrhage on MR imaging is independently associated with MR imaging-defined cortical infarcts, but not with lacunar infarcts. Plaque calcification, but not vulnerable plaque components, is related to white matter lesion volume.
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Affiliation(s)
- Q J A van den Bouwhuijsen
- From the Departments of Epidemiology (Q.J.A.v.d.B., M.W.V., B.F.J.V., M.A.I., O.H.F.).,Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.)
| | - M W Vernooij
- From the Departments of Epidemiology (Q.J.A.v.d.B., M.W.V., B.F.J.V., M.A.I., O.H.F.).,Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.)
| | - B F J Verhaaren
- From the Departments of Epidemiology (Q.J.A.v.d.B., M.W.V., B.F.J.V., M.A.I., O.H.F.)
| | - H A Vrooman
- Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.).,Medical Informatics (H.A.V., W.J.N.), Erasmus MC, Rotterdam, the Netherlands
| | - W J Niessen
- Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.).,Medical Informatics (H.A.V., W.J.N.), Erasmus MC, Rotterdam, the Netherlands
| | - G P Krestin
- Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.)
| | - M A Ikram
- From the Departments of Epidemiology (Q.J.A.v.d.B., M.W.V., B.F.J.V., M.A.I., O.H.F.).,Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.)
| | - O H Franco
- From the Departments of Epidemiology (Q.J.A.v.d.B., M.W.V., B.F.J.V., M.A.I., O.H.F.)
| | - A van der Lugt
- Radiology (Q.J.A.v.d.B., M.W.V., H.A.V., W.J.N., G.P.K., M.A.I., A.v.d.L.)
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39
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Schmaal L, Hibar DP, Sämann PG, Hall GB, Baune BT, Jahanshad N, Cheung JW, van Erp TGM, Bos D, Ikram MA, Vernooij MW, Niessen WJ, Tiemeier H, Hofman A, Wittfeld K, Grabe HJ, Janowitz D, Bülow R, Selonke M, Völzke H, Grotegerd D, Dannlowski U, Arolt V, Opel N, Heindel W, Kugel H, Hoehn D, Czisch M, Couvy-Duchesne B, Rentería ME, Strike LT, Wright MJ, Mills NT, de Zubicaray GI, McMahon KL, Medland SE, Martin NG, Gillespie NA, Goya-Maldonado R, Gruber O, Krämer B, Hatton SN, Lagopoulos J, Hickie IB, Frodl T, Carballedo A, Frey EM, van Velzen LS, Penninx BWJH, van Tol MJ, van der Wee NJ, Davey CG, Harrison BJ, Mwangi B, Cao B, Soares JC, Veer IM, Walter H, Schoepf D, Zurowski B, Konrad C, Schramm E, Normann C, Schnell K, Sacchet MD, Gotlib IH, MacQueen GM, Godlewska BR, Nickson T, McIntosh AM, Papmeyer M, Whalley HC, Hall J, Sussmann JE, Li M, Walter M, Aftanas L, Brack I, Bokhan NA, Thompson PM, Veltman DJ. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group. Mol Psychiatry 2017; 22:900-909. [PMID: 27137745 PMCID: PMC5444023 DOI: 10.1038/mp.2016.60] [Citation(s) in RCA: 687] [Impact Index Per Article: 98.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2016] [Revised: 02/25/2016] [Accepted: 03/17/2016] [Indexed: 12/20/2022]
Abstract
The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.
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Affiliation(s)
- L Schmaal
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - D P Hibar
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - P G Sämann
- Neuroimaging Core Unit, Max Planck Institute of Psychiatry, Munich, Germany
| | - G B Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - B T Baune
- Discipline of Psychiatry, University of Adelaide, Adelaide, SA, Australia
| | - N Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - J W Cheung
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - T G M van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - D Bos
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M W Vernooij
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - W J Niessen
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Center-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - K Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Germany
| | - H J Grabe
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - D Janowitz
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - R Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - M Selonke
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - H Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Center for Cardiovascular Research (DZHK), partner site Griefswald, Greifswald, Germany
- German Center for Diabetes Research (DZD), partner site Griefswald, Greifswald, Germany
| | - D Grotegerd
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - U Dannlowski
- Department of Psychiatry, University of Muenster, Muenster, Germany
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - V Arolt
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - N Opel
- Department of Psychiatry, University of Muenster, Muenster, Germany
| | - W Heindel
- Department of Clinical Radiology, University of Muenster, Muenster, Germany
| | - H Kugel
- Department of Clinical Radiology, University of Muenster, Muenster, Germany
| | - D Hoehn
- Neuroimaging Core Unit, Max Planck Institute of Psychiatry, Munich, Germany
| | - M Czisch
- Neuroimaging Core Unit, Max Planck Institute of Psychiatry, Munich, Germany
| | - B Couvy-Duchesne
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Center for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - M E Rentería
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - L T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Center for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - N T Mills
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - G I de Zubicaray
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - K L McMahon
- Center for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - S E Medland
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N G Martin
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA
| | - R Goya-Maldonado
- Centre for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Georg-August-University, Göttingen, Germany
| | - O Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - B Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - S N Hatton
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - J Lagopoulos
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - I B Hickie
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - T Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University, Magdeburg, Germany
- Department of Psychiatry and Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - A Carballedo
- Department of Psychiatry and Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - E M Frey
- Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany
| | - L S van Velzen
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - B W J H Penninx
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - M-J van Tol
- Neuroimaging Center, Section of Cognitive Neuropsychiatry, Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - N J van der Wee
- Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, The Netherlands
| | - C G Davey
- Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - B J Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Melbourne, VIC, Australia
| | - B Mwangi
- UT Center of Excellence on Mood Disoders, Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - B Cao
- UT Center of Excellence on Mood Disoders, Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - J C Soares
- UT Center of Excellence on Mood Disoders, Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - I M Veer
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - H Walter
- Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - D Schoepf
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - B Zurowski
- Center for Integrative Psychiatry, University of Lübeck, Lübeck, Germany
| | - C Konrad
- Department of Psychiatry, University of Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, Agaplesion Diakonieklinikum Rotenburg, Rotenburg, Germany
| | - E Schramm
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg, Germany
| | - C Normann
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg, Germany
| | - K Schnell
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - M D Sacchet
- Neurosciences Program and Department of Psychology, Stanford University, Stanford, CA, USA
| | - I H Gotlib
- Neurosciences Program and Department of Psychology, Stanford University, Stanford, CA, USA
| | - G M MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - B R Godlewska
- University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - T Nickson
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cogntive Ageing and Cogntive Epidemiology, University of Edinburgh, Edinburg, UK
| | - M Papmeyer
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Division of Systems Neuroscience of Psychopathology, Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - H C Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - J Hall
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
| | - J E Sussmann
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Department of Psychiatry, NHS Borders, Melrose, UK
| | - M Li
- Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - M Walter
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Psychiatry, University Tübingen, Tübingen, Germany
| | - L Aftanas
- Department of Experimental and Clinical Neuroscience, Scientific Research Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - I Brack
- Department of Experimental and Clinical Neuroscience, Scientific Research Institute of Physiology and Basic Medicine, Novosibirsk, Russia
| | - N A Bokhan
- Mental Health Research Institute, Tomsk, Russia
- Faculty of Psychology, National Research Tomsk State University, Tomsk, Russia
- Department of General Medicine, Siberian State Medical University, Tomsk, Russia
| | - P M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - D J Veltman
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
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Amin N, Jovanova O, Adams HHH, Dehghan A, Kavousi M, Vernooij MW, Peeters RP, de Vrij FMS, van der Lee SJ, van Rooij JGJ, van Leeuwen EM, Chaker L, Demirkan A, Hofman A, Brouwer RWW, Kraaij R, Willems van Dijk K, Hankemeier T, van Ijcken WFJ, Uitterlinden AG, Niessen WJ, Franco OH, Kushner SA, Ikram MA, Tiemeier H, van Duijn CM. Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms. Mol Psychiatry 2017; 22:537-543. [PMID: 27431295 DOI: 10.1038/mp.2016.101] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 04/19/2016] [Accepted: 04/20/2016] [Indexed: 11/09/2022]
Abstract
Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10-08, β=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10-03, β=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 10-02) and a higher risk of Alzheimer's disease (odds ratio=2.01; P-value=2.8 × 10-02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.
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Affiliation(s)
- N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - O Jovanova
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - H H H Adams
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - A Dehghan
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - M Kavousi
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - M W Vernooij
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - R P Peeters
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Rotterdam Thyroid Center, Erasmus MC, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - F M S de Vrij
- Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - S J van der Lee
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - J G J van Rooij
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - E M van Leeuwen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - L Chaker
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Rotterdam Thyroid Center, Erasmus MC, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - A Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Human Genetics, Leiden University Medical Center, RC Leiden, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - R W W Brouwer
- Center for Biomics, Department of Cell Biology, Erasmus MC, Rotterdam, The Netherlands
| | - R Kraaij
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - K Willems van Dijk
- Department of Human Genetics, Leiden University Medical Center, RC Leiden, The Netherlands.,Division of Endocrinology, Department of Medicine, Leiden University Medical Center, RC Leiden, The Netherlands
| | - T Hankemeier
- Leiden Academic Center for Drug Research, Division of Analytical Biosciences, Leiden University, Leiden, The Netherlands.,The Netherlands Metabolomics Centre, Leiden University, Leiden, The Netherlands
| | - W F J van Ijcken
- Center for Biomics, Department of Cell Biology, Erasmus MC, Rotterdam, The Netherlands
| | - A G Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - W J Niessen
- Departments of Radiology and Medical Informatics, Erasmus MC, Rotterdam, The Netherlands.,Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - O H Franco
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - S A Kushner
- Department of Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.,Department of Radiology, Erasmus MC, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - C M van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
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Bos D, van der Lugt A, Ikram MA, Vernooij MW. [Incidental findings on brain MRIPrevalence, clinical management and natural course]. Ned Tijdschr Geneeskd 2017; 161:D1051. [PMID: 28145215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
OBJECTIVE Diagnostic brain imaging has been performed increasingly since the 1990s. A direct result of this is the rise in the detection of incidental findings. The objective of this study is to provide insight into the prevalence, clinical relevance and natural course of incidental findings on brain magnetic resonance imaging (MRI) scans. DESIGN Prospective cohort study. METHOD Within the framework of the Rotterdam study, 5800 participants underwent a brain MRI scan during the period 2005-2014. Their average age was 64.9 years, and 55.1% were female. Trained reviewers and experienced neuroradiologists evaluated all scans for clinically relevant incidental findings. We calculated the prevalence of abnormalities discovered, and investigated which clinical management followed in those participants who were referred. On the basis of subsequent scans within the framework of the Rotterdam study we investigated the natural course of findings found in participants who were not referred. RESULTS There were incidental findings in 549 of 5800 (9.5%) participants. The most common abnormalities were meningiomas in 143 participants (2.5%) and aneurysms in 134 participants (2.3%). A total of 188 participants (3.2%) were referred to a medical specialist, who chose for a wait-and-see policy or discharge after the initial consultation in 144 participants (76.6%). The majority of meningiomas and aneurysms not referred or untreated, remained stable in size during the average follow-up period of 48-60 months. CONCLUSION Incidental findings on brain MRI are made relatively frequently in people of middle age or older. In 3% of these people these findings are reason for additional clinical evaluation, mostly without further clinical consequences.
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Affiliation(s)
- D Bos
- * Dit onderzoek werd eerder gepubliceerd in Radiology (2016;281:507-15) met als titel 'Prevalence, clinical management, and natural course of incidental findings on brain MR images: the population-based Rotterdam Scan Study'. Afgedrukt met toestemming
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Sonneveld MAH, Kavousi M, Ikram MA, Hofman A, Rueda Ochoa OL, Turecek PL, Franco OH, Leebeek FWG, de Maat MPM. Low ADAMTS-13 activity and the risk of coronary heart disease - a prospective cohort study: the Rotterdam Study. J Thromb Haemost 2016; 14:2114-2120. [PMID: 27559008 DOI: 10.1111/jth.13479] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2016] [Indexed: 12/28/2022]
Abstract
Essentials An association between ADAMTS-13 and coronary heart disease (CHD) has been suggested. 5688 participants ≥ 55 years from the Rotterdam Study without a history of CHD were included. Over a median follow-up time of 9.7 years, 456 individuals suffered from CHD. Low ADAMTS-13 activity was associated with an increased CHD risk. SUMMARY Background The metalloprotease ADAMTS-13 cleaves high-molecular-weight von Willebrand factor multimers into smaller, less procoagulant forms. Low ADAMTS-13 activity is associated with an increased risk of ischemic stroke but its pathogenic role in coronary heart disease (CHD) is unclear. Objectives We aimed to determine the association between ADAMTS-13 activity and the risk of CHD in a large prospective population-based cohort study. Methods A total of 5688 participants of the Rotterdam Study, a population-based cohort study involving individuals aged ≥ 55 years without a history of CHD, were included. ADAMTS-13 activity was measured by the FRETS-VWF73 assay and VWF:Ag levels by ELISA. We assessed the association between ADAMTS-13 activity, VWF:Ag levels and CHD using Cox proportional hazard regression analysis, adjusting for cardiovascular risk factors. Results Over a median follow-up time of 9.7 years, 456 individuals suffered from CHD. A low ADAMTS-13 activity (quartile 1) was associated with an increased CHD risk (HR 1.42, 95% CI 1.07-1.89) compared with the reference highest quartile. Conclusions Low ADAMTS-13 activity is associated with an increased risk of CHD in the elderly, independently of VWF and established cardiovascular risk factors.
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Affiliation(s)
- M A H Sonneveld
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Neurology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Radiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - O L Rueda Ochoa
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- School of Medicine, Faculty of Health, Universidad Industrial de Santander, Bucaramanga, Colombia
| | | | - O H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - F W G Leebeek
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M P M de Maat
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
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Roshchupkin GV, Adams HHH, Vernooij MW, Hofman A, Van Duijn CM, Ikram MA, Niessen WJ. HASE: Framework for efficient high-dimensional association analyses. Sci Rep 2016; 6:36076. [PMID: 27782180 PMCID: PMC5080584 DOI: 10.1038/srep36076] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2016] [Accepted: 10/10/2016] [Indexed: 12/21/2022] Open
Abstract
High-throughput technology can now provide rich information on a person’s biological makeup and environmental surroundings. Important discoveries have been made by relating these data to various health outcomes in fields such as genomics, proteomics, and medical imaging. However, cross-investigations between several high-throughput technologies remain impractical due to demanding computational requirements (hundreds of years of computing resources) and unsuitability for collaborative settings (terabytes of data to share). Here we introduce the HASE framework that overcomes both of these issues. Our approach dramatically reduces computational time from years to only hours and also requires several gigabytes to be exchanged between collaborators. We implemented a novel meta-analytical method that yields identical power as pooled analyses without the need of sharing individual participant data. The efficiency of the framework is illustrated by associating 9 million genetic variants with 1.5 million brain imaging voxels in three cohorts (total N = 4,034) followed by meta-analysis, on a standard computational infrastructure. These experiments indicate that HASE facilitates high-dimensional association studies enabling large multicenter association studies for future discoveries.
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Affiliation(s)
- G V Roshchupkin
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, Netherlands
| | - H H H Adams
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Epidemiology, Erasmus MC, Netherlands
| | - M W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Epidemiology, Erasmus MC, Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC, Netherlands
| | | | - M A Ikram
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Epidemiology, Erasmus MC, Netherlands.,Department of Neurology, Erasmus MC, Rotterdam, Netherlands
| | - W J Niessen
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, Netherlands.,Faculty of Applied Sciences, Delft University of Technology, Delft, Netherlands
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Wen K, Nguyen NT, Hofman A, Ikram MA, Franco OH. Migraine is associated with better cognition in the middle‐aged and elderly: the Rotterdam Study. Eur J Neurol 2016; 23:1510-6. [DOI: 10.1111/ene.13066] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2015] [Accepted: 05/13/2016] [Indexed: 11/26/2022]
Affiliation(s)
- K. Wen
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands
| | - N. T. Nguyen
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands
| | - A. Hofman
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands
| | - M. A. Ikram
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands
- Department of Radiology Erasmus MC University Medical Center Rotterdam The Netherlands
| | - O. H. Franco
- Department of Epidemiology Erasmus MC University Medical Center Rotterdam The Netherlands
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45
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Schmaal L, Veltman DJ, van Erp TGM, Sämann PG, Frodl T, Jahanshad N, Loehrer E, Tiemeier H, Hofman A, Niessen WJ, Vernooij MW, Ikram MA, Wittfeld K, Grabe HJ, Block A, Hegenscheid K, Völzke H, Hoehn D, Czisch M, Lagopoulos J, Hatton SN, Hickie IB, Goya-Maldonado R, Krämer B, Gruber O, Couvy-Duchesne B, Rentería ME, Strike LT, Mills NT, de Zubicaray GI, McMahon KL, Medland SE, Martin NG, Gillespie NA, Wright MJ, Hall GB, MacQueen GM, Frey EM, Carballedo A, van Velzen LS, van Tol MJ, van der Wee NJ, Veer IM, Walter H, Schnell K, Schramm E, Normann C, Schoepf D, Konrad C, Zurowski B, Nickson T, McIntosh AM, Papmeyer M, Whalley HC, Sussmann JE, Godlewska BR, Cowen PJ, Fischer FH, Rose M, Penninx BWJH, Thompson PM, Hibar DP. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group. Mol Psychiatry 2016; 21:806-12. [PMID: 26122586 PMCID: PMC4879183 DOI: 10.1038/mp.2015.69] [Citation(s) in RCA: 677] [Impact Index Per Article: 84.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2014] [Revised: 03/13/2015] [Accepted: 04/01/2015] [Indexed: 11/09/2022]
Abstract
The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen's d=-0.14, % difference=-1.24). This effect was driven by patients with recurrent MDD (Cohen's d=-0.17, % difference=-1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen's d=-0.20, % difference=-1.85) and a trend toward smaller amygdala (Cohen's d=-0.11, % difference=-1.23) and larger lateral ventricles (Cohen's d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.
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Affiliation(s)
- L Schmaal
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands,Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, P.O. Box 74077, Amsterdam 1070 BB, The Netherlands. E-mail:
| | - D J Veltman
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - T G M van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - P G Sämann
- Max Planck Institute of Psychiatry, Munich, Germany
| | - T Frodl
- Department of Psychiatry, University of Regensburg, Regensburg, Germany,Department of Psychiatry, University of Dublin, Trinity College, Dublin, Ireland
| | - N Jahanshad
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - E Loehrer
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Department of Psychiatry, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - A Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - W J Niessen
- Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Imaging Science and Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - M W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Departments of Radiology and Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - K Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - H J Grabe
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany,Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany,Helios Hospital Stralsund, Stralsund, Germany
| | - A Block
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - K Hegenscheid
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - H Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - D Hoehn
- Max Planck Institute of Psychiatry, Munich, Germany
| | - M Czisch
- Max Planck Institute of Psychiatry, Munich, Germany
| | - J Lagopoulos
- Clinical Research Unit, Brain and Mind Research Institute, University of Sydney, Camperdown, Australia
| | - S N Hatton
- Clinical Research Unit, Brain and Mind Research Institute, University of Sydney, Camperdown, Australia
| | - I B Hickie
- Clinical Research Unit, Brain and Mind Research Institute, University of Sydney, Camperdown, Australia
| | - R Goya-Maldonado
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - B Krämer
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - O Gruber
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, Goettingen, Germany
| | - B Couvy-Duchesne
- NeuroImaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,School of Psychology, University of Queensland, Brisbane, QLD, Australia,Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - M E Rentería
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - L T Strike
- NeuroImaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,School of Psychology, University of Queensland, Brisbane, QLD, Australia,Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - N T Mills
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia,Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - G I de Zubicaray
- School of Psychology, University of Queensland, Brisbane, QLD, Australia
| | - K L McMahon
- Center for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - S E Medland
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - N G Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - N A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - M J Wright
- NeuroImaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - G B Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - G M MacQueen
- Department of Psychiatry, Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - E M Frey
- Department of Psychiatry, University of Regensburg, Regensburg, Germany
| | - A Carballedo
- Department of Psychiatry and Institute of Neuroscience, University of Dublin, Trinity College Dublin, Dublin, Ireland
| | - L S van Velzen
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - M J van Tol
- University of Groningen, University Medical Center Groningen, NeuroImaging Center, Groningen, The Netherlands
| | - N J van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden University, Leiden, The Netherlands,Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - I M Veer
- Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - H Walter
- Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - K Schnell
- Department of General Psychiatry, University Hospital Heidelberg, Heidelberg, Germany
| | - E Schramm
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - C Normann
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg im Breisgau, Germany
| | - D Schoepf
- Department of Psychiatry, University of Bonn, Bonn, Germany
| | - C Konrad
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - B Zurowski
- Center for Integrative Psychiatry, University of Lübeck, Lübeck, Germany
| | - T Nickson
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK,Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - M Papmeyer
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - H C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - J E Sussmann
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - B R Godlewska
- University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - P J Cowen
- University Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - F H Fischer
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin, Berlin, Germany,Institute for Social Medicine, Epidemology and Health Economics, Charité Universitätsmedizin, Berlin, Germany
| | - M Rose
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin, Berlin, Germany,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - B W J H Penninx
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - P M Thompson
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - D P Hibar
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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46
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Schmaal L, Veltman DJ, van Erp TGM, Sämann PG, Frodl T, Jahanshad N, Loehrer E, Vernooij MW, Niessen WJ, Ikram MA, Wittfeld K, Grabe HJ, Block A, Hegenscheid K, Hoehn D, Czisch M, Lagopoulos J, Hatton SN, Hickie IB, Goya-Maldonado R, Krämer B, Gruber O, Couvy-Duchesne B, Rentería ME, Strike LT, Wright MJ, de Zubicaray GI, McMahon KL, Medland SE, Gillespie NA, Hall GB, van Velzen LS, van Tol MJ, van der Wee NJ, Veer IM, Walter H, Schramm E, Normann C, Schoepf D, Konrad C, Zurowski B, McIntosh AM, Whalley HC, Sussmann JE, Godlewska BR, Fischer FH, Penninx BWJH, Thompson PM, Hibar DP. Response to Dr Fried & Dr Kievit, and Dr Malhi et al. Mol Psychiatry 2016; 21:726-8. [PMID: 26903270 PMCID: PMC4876636 DOI: 10.1038/mp.2016.9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
- L Schmaal
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - D J Veltman
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - T G M van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - P G Sämann
- Max Planck Institute of Psychiatry, Neuroimaging Research Group, Munich, Germany
| | - T Frodl
- Department of Psychiatry and Psychotherapy, Otto von Guericke University of Magdeburg, Magdeburg, Germany
- Department of Psychiatry, Trinity College, University of Dublin, Dublin, Ireland
| | - N Jahanshad
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - E Loehrer
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MS, USA
| | - M W Vernooij
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - W J Niessen
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Medical Informatics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - K Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - H J Grabe
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Helios Hospital Stralsund, Stralsund, Germany
| | - A Block
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - K Hegenscheid
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - D Hoehn
- Max Planck Institute of Psychiatry, Neuroimaging Research Group, Munich, Germany
| | - M Czisch
- Max Planck Institute of Psychiatry, Neuroimaging Research Group, Munich, Germany
| | - J Lagopoulos
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - S N Hatton
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - I B Hickie
- Clinical Research Unit, Brain and Mind Centre, University of Sydney, Camperdown, NSW, Australia
| | - R Goya-Maldonado
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Gerog-August-University, Goettingen, Germany
| | - B Krämer
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center (UMG), Gerog-August-University, Goettingen, Germany
| | - O Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University Hospital, Heidelberg, Germany
| | - B Couvy-Duchesne
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Center for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
- Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - M E Rentería
- Department of Genetic Epidemiology, Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - L T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - M J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
- Center for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - G I de Zubicaray
- Faculty of Health, The Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, QLD, Australia
| | - K L McMahon
- Center for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - S E Medland
- Department of Quantitative Genetics, Queensland Institute of Medical Research Berghofer, Brisbane, QLD, Australia
| | - N A Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - G B Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
- Imaging Research Centre, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - L S van Velzen
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - M-J van Tol
- University of Groningen, University Medical Center Groningen, Department of Neuroscience, Neuroimaging Center, Groningen, The Netherlands
| | - N J van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - I M Veer
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - H Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - E Schramm
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg, Germany
- Psychiatric University Clinic, Basel, Switzerland
| | - C Normann
- Department of Psychiatry and Psychotherapy, University Medical Center Freiburg, Freiburg, Germany
| | - D Schoepf
- Department of Psychiatry, University of Bonn, Bonn, Germany
| | - C Konrad
- Department of Psychiatry and Psychotherapy, Agaplesion Diakoniklinikum, Rotenburg, Germany
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - B Zurowski
- Center for Integrative Psychiatry, University of Lübeck, Lübeck, Germany
| | - A M McIntosh
- Division of Psychiatry, University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, UK
| | - H C Whalley
- Division of Psychiatry, University of Edinburgh, UK
| | - J E Sussmann
- Division of Psychiatry, University of Edinburgh, UK
| | - B R Godlewska
- Department of Psychiatry, Warneford Hospital, Oxford, UK
| | - F H Fischer
- Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology, Charité Universitätsmedizin, Berlin, Germany
- Institute for Social Medicine, Epidemology and Health Economics, Charité Universitätsmedizin, Berlin, Germany
| | - B W J H Penninx
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - P M Thompson
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - D P Hibar
- Imaging Genetics Center, Department of Neurology, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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Ibrahim-Verbaas CA, Bressler J, Debette S, Schuur M, Smith AV, Bis JC, Davies G, Trompet S, Smith JA, Wolf C, Chibnik LB, Liu Y, Vitart V, Kirin M, Petrovic K, Polasek O, Zgaga L, Fawns-Ritchie C, Hoffmann P, Karjalainen J, Lahti J, Llewellyn DJ, Schmidt CO, Mather KA, Chouraki V, Sun Q, Resnick SM, Rose LM, Oldmeadow C, Stewart M, Smith BH, Gudnason V, Yang Q, Mirza SS, Jukema JW, deJager PL, Harris TB, Liewald DC, Amin N, Coker LH, Stegle O, Lopez OL, Schmidt R, Teumer A, Ford I, Karbalai N, Becker JT, Jonsdottir MK, Au R, Fehrmann RSN, Herms S, Nalls M, Zhao W, Turner ST, Yaffe K, Lohman K, van Swieten JC, Kardia SLR, Knopman DS, Meeks WM, Heiss G, Holliday EG, Schofield PW, Tanaka T, Stott DJ, Wang J, Ridker P, Gow AJ, Pattie A, Starr JM, Hocking LJ, Armstrong NJ, McLachlan S, Shulman JM, Pilling LC, Eiriksdottir G, Scott RJ, Kochan NA, Palotie A, Hsieh YC, Eriksson JG, Penman A, Gottesman RF, Oostra BA, Yu L, DeStefano AL, Beiser A, Garcia M, Rotter JI, Nöthen MM, Hofman A, Slagboom PE, Westendorp RGJ, Buckley BM, Wolf PA, Uitterlinden AG, Psaty BM, Grabe HJ, Bandinelli S, Chasman DI, Grodstein F, Räikkönen K, Lambert JC, Porteous DJ, Price JF, Sachdev PS, Ferrucci L, Attia JR, Rudan I, Hayward C, Wright AF, Wilson JF, Cichon S, Franke L, Schmidt H, Ding J, de Craen AJM, Fornage M, Bennett DA, Deary IJ, Ikram MA, Launer LJ, Fitzpatrick AL, Seshadri S, van Duijn CM, Mosley TH. GWAS for executive function and processing speed suggests involvement of the CADM2 gene. Mol Psychiatry 2016; 21:189-197. [PMID: 25869804 PMCID: PMC4722802 DOI: 10.1038/mp.2015.37] [Citation(s) in RCA: 103] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2013] [Revised: 01/21/2015] [Accepted: 02/11/2015] [Indexed: 01/20/2023]
Abstract
To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32,070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.
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Affiliation(s)
- CA Ibrahim-Verbaas
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - J Bressler
- Human Genetics Center, School of Public Health, University of
Texas Health Science Center at Houston, Houston, TX, USA,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Debette
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,Institut National de la Santé et de la Recherche
Médicale (INSERM), U897, Epidemiology and Biostatistics, University of Bordeaux,
Bordeaux, France,Department of Neurology, Bordeaux University Hospital, Bordeaux,
France,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - M Schuur
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - AV Smith
- Icelandic Heart Association, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik,
Iceland,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - JC Bis
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - G Davies
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - S Trompet
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands,Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - JA Smith
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - C Wolf
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - LB Chibnik
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Y Liu
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - V Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - M Kirin
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - K Petrovic
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - O Polasek
- Department of Public Health, University of Split, Split,
Croatia
| | - L Zgaga
- Department of Public Health and Primary Care, Trinity College
Dublin, Dublin, Ireland
| | - C Fawns-Ritchie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - P Hoffmann
- Institute of Neuroscience and Medicine (INM -1), Research
Center Juelich, Juelich, Germany,Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - J Karjalainen
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - J Lahti
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland,Folkhälsan Research Centre, Helsinki, Finland
| | - DJ Llewellyn
- Institute of Biomedical and Clinical Sciences, University of
Exeter Medical School, Exeter, UK
| | - CO Schmidt
- Institute for Community Medicine, University Medicine
Greifswald, Greifswald, Germany
| | - KA Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia
| | - V Chouraki
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - Q Sun
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - SM Resnick
- Laboratory of Behavioral Neuroscience, National Institute on
Aging, NIH, Baltimore, MD, USA
| | - LM Rose
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - C Oldmeadow
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - M Stewart
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - BH Smith
- Medical Research Institute, University of Dundee, Dundee,
UK
| | - V Gudnason
- Icelandic Heart Association, Kopavogur, Iceland,Faculty of Medicine, University of Iceland, Reykjavik,
Iceland
| | - Q Yang
- The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - SS Mirza
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - JW Jukema
- Department of Cardiology, Leiden University Medical Center,
Leiden, The Netherlands
| | - PL deJager
- Program in Translational Neuropsychiatric Genomics, Department
of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - TB Harris
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - DC Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - N Amin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - LH Coker
- Division of Public Health Sciences and Neurology, Wake Forest
School of Medicine, Winston-Salem, NC, USA
| | - O Stegle
- Max Planck Institute for Developmental Biology, Max Planck
Institute for Intelligent Systems, Tübingen, Germany
| | - OL Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA
| | - R Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - A Teumer
- Interfaculty Institute for Genetics and Functional Genomics,
University Medicine Greifswald, Greifswald, Germany
| | - I Ford
- Robertson Center for biostatistics, University of Glasgow,
Glasgow, UK
| | - N Karbalai
- RG Statistical Genetics, Max Planck Institute of Psychiatry,
Munich, Germany
| | - JT Becker
- Department of Neurology, University of Pittsburgh, Pittsburgh,
PA, USA,Department of Psychiatry, University of Pittsburgh, Pittsburgh,
PA, USA,Department of Psychology, University of Pittsburgh, Pittsburgh,
PA, USA
| | | | - R Au
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - RSN Fehrmann
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - S Herms
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - M Nalls
- Laboratory of Neurogenetics, National Institute on Aging,
Bethesda, MD, USA
| | - W Zhao
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - ST Turner
- Division of Nephrology and Hypertension, Department of Internal
Medicine, Mayo Clinic, Rochester, MN, USA
| | - K Yaffe
- Departments of Psychiatry, Neurology and Epidemiology,
University of California, San Francisco and San Francisco VA Medical Center, San Francisco,
CA, USA
| | - K Lohman
- Department of Epidemiology, Wake Forest School of Medicine,
Winston-Salem, NC, USA
| | - JC van Swieten
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - SLR Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor,
MI, USA
| | - DS Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - WM Meeks
- Department of Medicine, Division of Geriatrics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - G Heiss
- Department of Epidemiology, Gillings School of Global Public
Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - EG Holliday
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - PW Schofield
- School of Medicine and Public Health, Faculty of Health,
University of Newcastle, Newcastle, SW, Australia
| | - T Tanaka
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - DJ Stott
- Department of Cardiovascular and Medical Sciences, University
of Glasgow, Glasgow, UK
| | - J Wang
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - P Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - AJ Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - A Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK
| | - JM Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Alzheimer Scotland Research Centre, Edinburgh, UK
| | - LJ Hocking
- Division of Applied Medicine, University of Aberdeen, Aberdeen,
UK
| | - NJ Armstrong
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Cancer Research Program, Garvan Institute of Medical Research,
Sydney, NSW, Australia,School of Mathematics & Statistics and Prince of Wales
Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - S McLachlan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - JM Shulman
- Department of Neurology, Baylor College of Medicine, Houston,
TX, USA,Department of Molecular and Human Genetics, The Jan and Dan
Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, USA
| | - LC Pilling
- Epidemiology and Public Health Group, University of Exeter
Medical School, Exeter, UK
| | | | - RJ Scott
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - NA Kochan
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - A Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus,
Cambridge, UK,Institute for Molecular Medicine Finland (FIMM), University of
Helsinki, Helsinki, Finland,Department of Medical Genetics, University of Helsinki and
University Central Hospital, Helsinki, Finland
| | - Y-C Hsieh
- School of Public Health, Taipei Medical University, Taipei,
Taiwan
| | - JG Eriksson
- Folkhälsan Research Centre, Helsinki, Finland,Department of General Practice and Primary Health Care,
University of Helsinki, Helsinki, Finland,National Institute for Health and Welfare, Helsinki,
Finland,Helsinki University Central Hospital, Unit of General Practice,
Helsinki, Finland,Vasa Central Hospital, Vasa, Finland
| | - A Penman
- Center of Biostatistics and Bioinformatics, University of
Mississippi Medical Center, Jackson, MS, USA
| | - RF Gottesman
- Department of Neurology, Johns Hopkins University School of
Medicine, Baltimore, MD, USA
| | - BA Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands
| | - L Yu
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - AL DeStefano
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - A Beiser
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA,Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - M Garcia
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - JI Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los
Angeles, CA, USA,Institute for Translational Genomics and Population Sciences,
Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA,
USA,Division of Genetic Outcomes, Department of Pediatrics,
Harbor-UCLA Medical Center, Torrance, CA, USA
| | - MM Nöthen
- Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany,German Center for Neurodegenerative Diseases (DZNE), Bonn,
Germany
| | - A Hofman
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - PE Slagboom
- Department of Molecular Epidemiology, Leiden University Medical
Center, Leiden, The Netherlands
| | - RGJ Westendorp
- Leiden Academy of Vitality and Ageing, Leiden, The
Netherlands
| | - BM Buckley
- Department of Pharmacology and Therapeutics, University College
Cork, Cork, Ireland
| | - PA Wolf
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - AG Uitterlinden
- Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands,Department of Internal Medicine, Erasmus University Medical
Center, Rotterdam, The Netherlands
| | - BM Psaty
- Cardiovascular Health Research Unit, Department of Medicine,
University of Washington, Seattle, WA, USA,Department of Epidemiology, University of Washington, Seattle,
WA, USA,Department of Health Services, University of Washington,
Seattle, WA, USA,Group Health Research Institute, Group Health, Seattle, WA,
USA
| | - HJ Grabe
- Department of Psychiatry and Psychotherapy, University Medicine
Greifswald, HELIOS-Hospital Stralsund, Stralsund, Germany
| | - S Bandinelli
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence,
Italy
| | - DI Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital,
Boston, MA, USA
| | - F Grodstein
- Channing Division of Network Medicine, Department of Medicine,
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - K Räikkönen
- Institute of Behavioural Sciences, University of Helsinki,
Helsinki, Finland
| | - J-C Lambert
- Inserm, U1167, Institut Pasteur de Lille, Université
Lille-Nord de France, Lille, France
| | - DJ Porteous
- Centre for Genomic and Experimental Medicine, Institute of
Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - JF Price
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - PS Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW
Medicine, University of New South Wales, Sydney, Australia,Neuropsychiatric Institute, The Prince of Wales Hospital,
Sydney, NSW, Australia
| | - L Ferrucci
- Translational Gerontology Branch, National Institute on Aging,
Baltimore, MD, USA
| | - JR Attia
- Hunter Medical Research Institute and Faculty of Health,
University of Newcastle, Newcastle, NSW, Australia
| | - I Rudan
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - AF Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular
Medicine, University of Edinburgh, Edinburgh, UK
| | - JF Wilson
- Centre for Population Health Sciences, University of Edinburgh,
Edinburgh, UK
| | - S Cichon
- Division of Medical Genetics, Department of Biomedicine,
University of Basel, Basel, Switzerland,Department of Genomics, Life and Brain Research Center,
Institute of Human Genetics, University of Bonn, Bonn, Germany,Institute of Neuroscience and Medicine (INM-1), Research Center
Juelich, Juelich, Germany
| | - L Franke
- Department of Genetics, University Medical Centre Groningen,
University of Groningen, Groningen, The Netherlands
| | - H Schmidt
- Department of Neurology, Medical University and General
Hospital of Graz, Graz, Austria
| | - J Ding
- Department of Internal Medicine, Wake Forest University School
of Medicine, Winston-Salem, NC, USA
| | - AJM de Craen
- Department of Gerontology and Geriatrics, Leiden University
Medical Center, Leiden, The Netherlands
| | - M Fornage
- Institute for Molecular Medicine and Human Genetics Center,
University of Texas Health Science Center at Houston, Houston, TX, USA
| | - DA Bennett
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - IJ Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The
University of Edinburgh, Edinburgh, UK,Department of Psychology, University of Edinburgh, Edinburgh,
UK
| | - MA Ikram
- Department of Neurology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Department of Epidemiology, Erasmus University Medical Center,
Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands,Department of Radiology, Erasmus University Medical Center,
Rotterdam, The Netherlands
| | - LJ Launer
- Laboratory of Epidemiology and Population Sciences, National
Institute on Aging, Bethesda, MD, USA
| | - AL Fitzpatrick
- Department of Epidemiology, University of Washington, Seattle,
WA, USA
| | - S Seshadri
- Department of Neurology, Boston University School of Medicine,
Boston, MA, USA,The National Heart Lung and Blood Institute's Framingham Heart
Study, Framingham, MA, USA
| | - CM van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus
University Medical Center, Rotterdam, The Netherlands,Netherlands Consortium for Healthy Ageing, Leiden, The
Netherlands
| | - TH Mosley
- Department of Medicine and Neurology, University of Mississippi
Medical Center, Jackson, MS, USA
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48
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Abstract
Peripheral neuropathies are diseases of the peripheral nervous system that can be divided into mononeuropathies, multifocal neuropathies, and polyneuropathies. Symptoms usually include numbness and paresthesia. These symptoms are often accompanied by weakness and can be painful. Polyneuropathies can be divided into axonal and demyelinating forms, which is important for diagnostic reasons. Most peripheral neuropathies develop over months or years, but some are rapidly progressive. Some patients only suffer from mild, unilateral, slowly progressive tingling in the fingers due to median nerve compression in the wrist (carpal tunnel syndrome), while other patients can be tetraplegic, with respiratory insufficiency within 1-2 days due to Guillain-Barré syndrome. Carpal tunnel syndrome, with a prevalence of 5% and incidence of 1-2 per 1000 person-years, is the most common mononeuropathy. Population-based data for chronic polyneuropathy are relatively scarce. Prevalence is estimated at 1% and increases to 7% in persons over 65 years of age. Incidence is approximately 1 per 1000 person-years. Immune-mediated polyneuropathies like Guillain-Barré syndrome and chronic inflammatory demyelinating polyradiculoneuropathy are rare diseases, with an annual incidence of approximately 1-2 and 0.2-0.5 per 100 000 persons respectively. Most peripheral neuropathies are more prevalent in older adults and in men, except for carpal tunnel syndrome, which is more common in women. Diabetes is a common cause of peripheral neuropathy and is associated with both mono- and polyneuropathies. Among the group of chronic polyneuropathies, in about 20-25% no direct cause can be found. These are slowly progressive axonal polyneuropathies.
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Affiliation(s)
- R Hanewinckel
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
| | - P A Van Doorn
- Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands
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49
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Abstract
With 16.9 million people who suffered a first-ever stroke in 2010 worldwide, stroke is a very common vascular disease. Epidemiologic studies have played an essential role in assessing this burden and in detecting the risk factors for stroke. Primary prevention of these risk factors, primarily hypertension, smoking, diabetes, and atrial fibrillation, has reduced the incidence in high-income countries. However, stroke remains a major cause of death and disability, and therefore research should be continued. Subarachnoid hemorrhages are less prevalent than strokes but have an even higher risk of death. Similar to stroke, epidemiologic studies identified smoking and hypertension as its most important risk factors, together with excessive alcohol intake. Although rare, arterial dissections, CADASIL, arteriovenous malformations, venous sinus thrombosis, moyamoya disease, and vasculitis can lead to serious symptoms. The burden and risk factors of those rare diseases are more challenging to assess. Whenever possible, they should be recognized in a timely manner for their increased risk of stroke, but most often they are diagnosed only at the time of stroke. Some cerebrovascular abnormalities do not result in immediate symptoms. This subclinical cerebrovascular disease includes silent infarcts, white-matter lesions, and microbleeds, and is incidentally found by neuroimaging. These lesions are not innocent, as several epidemiologic studies have associated subclinical cerebrovascular disease with an increased risk of stroke, cognitive decline, dementia, and death.
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Affiliation(s)
- M L P Portegies
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
| | - P J Koudstaal
- Department of Neurology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - M A Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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50
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de Kruijf M, Bos D, Huygen FJPM, Niessen WJ, Tiemeier H, Hofman A, Uitterlinden AG, Vernooij MW, Ikram MA, van Meurs JBJ. Structural Brain Alterations in Community Dwelling Individuals with Chronic Joint Pain. AJNR Am J Neuroradiol 2015; 37:430-8. [PMID: 26542234 DOI: 10.3174/ajnr.a4556] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Accepted: 07/11/2015] [Indexed: 12/22/2022]
Abstract
BACKGROUND AND PURPOSE Central sensitization in chronic pain involves structural brain changes that influence vulnerability to pain. Identifying brain regions involved in pain processing and sensitization can provide more insight into chronic pain. This study examines structural brain changes in chronic pain and experimental pain in a large population-based study. MATERIALS AND METHODS For 3892 participants in the Rotterdam study, global and regional MR imaging brain volumes were automatically segmented and quantified. Chronic joint pain was defined as pain for more than half of all days during the past 6 weeks. Heat pain thresholds were measured in a subset of 1538 individuals. The association between the presence of chronic joint pain and global and lobar brain volumes was studied. Subsequently, literature was reviewed and the association of chronic pain and heat pain thresholds with 11 brain regions associated with musculoskeletal pain in previous publications was studied. RESULTS Total gray matter volume was smaller in women with chronic pain (β = -0.066, P = .016). This effect was primarily driven by lower gray matter volume in the temporal lobe (β = 0.086, P = .005), the frontal lobe (β = -0.060, P = .039), and the hippocampus (β = -0.099, P = .002). In addition, we observed that a lower heat pain threshold was associated with smaller volumes of the hippocampus (β = 0.017, P = .048), the thalamus (β = 0.018, P = .009), and the anterior cingulate cortex (β = -0.016, P = .037). In men, no significant associations were observed. CONCLUSIONS The primary identified brain areas, the temporal and frontal lobes and the hippocampus, indicated involvement of emotional processing. The volumetric differences found indicated a sex-specific neuroplasticity in chronic pain. These results emphasized sex-specific and multidisciplinary pain treatment.
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Affiliation(s)
- M de Kruijf
- From the Departments of Internal Medicine (M.d.K., A.G.U., J.B.J.v.M.) Anaesthesiology (M.d.K., F.J.P.M.H.)
| | - D Bos
- Radiology (D.B., W.J.N., M.W.V., M.A.I.) Epidemiology (D.B., H.T., A.H., A.G.U., M.W.V., M.A.I.)
| | | | - W J Niessen
- Radiology (D.B., W.J.N., M.W.V., M.A.I.) Medical Informatics (W.J.N.) Faculty of Applied Sciences (W.J.N.), Delft University of Technology, Delft, the Netherlands
| | - H Tiemeier
- Epidemiology (D.B., H.T., A.H., A.G.U., M.W.V., M.A.I.)
| | - A Hofman
- Epidemiology (D.B., H.T., A.H., A.G.U., M.W.V., M.A.I.)
| | - A G Uitterlinden
- From the Departments of Internal Medicine (M.d.K., A.G.U., J.B.J.v.M.) Epidemiology (D.B., H.T., A.H., A.G.U., M.W.V., M.A.I.)
| | - M W Vernooij
- Radiology (D.B., W.J.N., M.W.V., M.A.I.) Epidemiology (D.B., H.T., A.H., A.G.U., M.W.V., M.A.I.)
| | - M A Ikram
- Radiology (D.B., W.J.N., M.W.V., M.A.I.) Epidemiology (D.B., H.T., A.H., A.G.U., M.W.V., M.A.I.) Neurology (M.A.I.), Erasmus MC, University Medical Center, Rotterdam, the Netherlands
| | - J B J van Meurs
- From the Departments of Internal Medicine (M.d.K., A.G.U., J.B.J.v.M.)
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