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The AGES-Reykjavik study atlases: Non-linear multi-spectral template and atlases for studies of the ageing brain.

https://arctichealth.org/en/permalink/ahliterature292006
Source
Med Image Anal. 2017 Jul; 39:133-144
Publication Type
Journal Article
Date
Jul-2017
Author
Lars Forsberg
Sigurdur Sigurdsson
Jesper Fredriksson
Asdis Egilsdottir
Bryndis Oskarsdottir
Olafur Kjartansson
Mark A van Buchem
Lenore J Launer
Vilmundur Gudnason
Alex Zijdenbos
Author Affiliation
The Icelandic Heart Association, Kopavogur, Iceland; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden. Electronic address: larsef@me.com.
Source
Med Image Anal. 2017 Jul; 39:133-144
Date
Jul-2017
Language
English
Publication Type
Journal Article
Keywords
Aged
Aging
Algorithms
Anatomy, Artistic
Atlases as Topic
Brain - diagnostic imaging
Female
Humans
Image Processing, Computer-Assisted - methods
Magnetic Resonance Imaging - methods
Male
Abstract
Quantitative analyses of brain structures from Magnetic Resonance (MR) image data are often performed using automatic segmentation algorithms. Many of these algorithms rely on templates and atlases in a common coordinate space. Most freely available brain atlases are generated from relatively young individuals and not always derived from well-defined cohort studies. In this paper, we introduce a publicly available multi-spectral template with corresponding tissue probability atlases and regional atlases, optimised to use in studies of ageing cohorts (mean age 75 ± 5 years). Furthermore, we provide validation data from a regional segmentation pipeline to assure the integrity of the dataset.
Notes
Cites: Neuroimage. 2010 Feb 1;49(3):2352-65 PMID 19857578
Cites: Neuroimage. 2004;23 Suppl 1:S208-19 PMID 15501092
Cites: Stroke. 2008 Apr;39(4):1134-41 PMID 18323507
Cites: J Cereb Blood Flow Metab. 1990 Jul;10 (4):443-57 PMID 2347878
Cites: Neuron. 2002 Jan 31;33(3):341-55 PMID 11832223
Cites: Neuroimage. 2008 Feb 1;39(3):1064-80 PMID 18037310
Cites: Neuroimage. 1997 Oct;6(3):209-17 PMID 9344825
Cites: NMR Biomed. 2015 Apr;28(4):468-85 PMID 25802212
Cites: Neuroimage. 2006 Oct 15;33(1):115-26 PMID 16860573
Cites: Neuroimage. 2011 Jan 1;54(1):313-27 PMID 20656036
Cites: Neuroimage. 2009 Jul 1;46(3):726-38 PMID 19245840
Cites: Neuroimage. 2001 Jul;14(1 Pt 1):21-36 PMID 11525331
Cites: J Comput Assist Tomogr. 1994 Mar-Apr;18(2):192-205 PMID 8126267
Cites: IEEE Trans Med Imaging. 2007 Apr;26(4):479-86 PMID 17427735
Cites: Image Vis Comput. 2001 Jan 1;19(1-2):3-24 PMID 19890483
Cites: Neuroimage. 2005 Jul 15;26(4):1009-18 PMID 15908234
Cites: Comput Methods Programs Biomed. 2011 Dec;104(3):e158-77 PMID 21871688
Cites: IEEE Trans Med Imaging. 2002 Oct;21(10):1280-91 PMID 12585710
Cites: Ann N Y Acad Sci. 2002 Nov;977:141-8 PMID 12480744
Cites: Neuroimage. 1995 Jun;2(2):89-101 PMID 9343592
Cites: Neuroimage. 2007 Apr 1;35(2):686-97 PMID 17320415
Cites: Neuroimage. 2002 Jan;15(1):273-89 PMID 11771995
Cites: Hum Brain Mapp. 2002 Nov;17(3):143-55 PMID 12391568
Cites: IEEE Trans Med Imaging. 2009 Aug;28(8):1266-77 PMID 19228554
Cites: Inf Process Med Imaging. 2001;2082:488-501 PMID 21218175
Cites: Philos Trans R Soc Lond B Biol Sci. 2001 Aug 29;356(1412):1293-322 PMID 11545704
Cites: Clin Chem. 1974 Dec;20(12):1535-42 PMID 4430131
Cites: Biometrics. 1996 Dec;52(4):1195-203 PMID 8962450
Cites: Neuroimage. 2012 Feb 15;59(4):3862-3870 PMID 22119006
Cites: Hum Brain Mapp. 1994;1(3):173-84 PMID 24578038
Cites: Clin Neuroradiol. 2016 Dec;26(4):423-430 PMID 25791203
PubMed ID
28501699 View in PubMed
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The AGES-Reykjavik study atlases: Non-linear multi-spectral template and atlases for studies of the ageing brain.

https://arctichealth.org/en/permalink/ahliterature282555
Source
Med Image Anal. 2017 May 06;39:133-144
Publication Type
Article
Date
May-06-2017
Author
Lars Forsberg
Sigurdur Sigurdsson
Jesper Fredriksson
Asdis Egilsdottir
Bryndis Oskarsdottir
Olafur Kjartansson
Mark A van Buchem
Lenore J Launer
Vilmundur Gudnason
Alex Zijdenbos
Source
Med Image Anal. 2017 May 06;39:133-144
Date
May-06-2017
Language
English
Publication Type
Article
Abstract
Quantitative analyses of brain structures from Magnetic Resonance (MR) image data are often performed using automatic segmentation algorithms. Many of these algorithms rely on templates and atlases in a common coordinate space. Most freely available brain atlases are generated from relatively young individuals and not always derived from well-defined cohort studies. In this paper, we introduce a publicly available multi-spectral template with corresponding tissue probability atlases and regional atlases, optimised to use in studies of ageing cohorts (mean age 75 ± 5 years). Furthermore, we provide validation data from a regional segmentation pipeline to assure the integrity of the dataset.
PubMed ID
28501699 View in PubMed
Less detail

The AGES-Reykjavik Study suggests that change in kidney measures is associated with subclinical brain pathology in older community-dwelling persons.

https://arctichealth.org/en/permalink/ahliterature292670
Source
Kidney Int. 2018 Jun 27; :
Publication Type
Journal Article
Date
Jun-27-2018
Author
Sanaz Sedaghat
Jie Ding
Gudny Eiriksdottir
Mark A van Buchem
Sigurdur Sigurdsson
M Arfan Ikram
Osorio Meirelles
Vilmundur Gudnason
Andrew S Levey
Lenore J Launer
Author Affiliation
Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Source
Kidney Int. 2018 Jun 27; :
Date
Jun-27-2018
Language
English
Publication Type
Journal Article
Abstract
Decreased glomerular filtration rate (GFR) and albuminuria may be accompanied by brain pathology. Here we investigated whether changes in these kidney measures are linked to development of new MRI-detected infarcts and microbleeds, and progression of white matter hyperintensity volume. The study included 2671 participants from the population-based AGES-Reykjavik Study (mean age 75, 58.7% women). GFR was estimated from serum creatinine, and albuminuria was assessed by urinary albumin-to-creatinine ratio. Brain MRI was acquired at baseline (2002-2006) and 5 years later (2007-2011). New MRI-detected infarcts and microbleeds were counted on the follow-up scans. White matter hyperintensity progression was estimated as percent change in white matter hyperintensity volumes between the two exams. Participants with a large eGFR decline (over 3 ml/min per 1.73m2 per year) had more incident subcortical infarcts (odds ratio 1.53; 95% confidence interval 1.05, 2.22), and more marked progression of white matter hyperintensity volume (difference: 8%; 95% confidence interval: 4%, 12%), compared to participants without a large decline. Participants with incident albuminuria (over 30 mg/g) had 21% more white matter hyperintensity volume progression (95% confidence interval: 14%, 29%) and 1.86 higher odds of developing new deep microbleeds (95% confidence interval 1.16, 2.98), compared to participants without incident albuminuria. The findings were independent of cardiovascular risk factors. Changes in kidney measures were not associated with occurrence of cortical infarcts. Thus, larger changes in eGFR and albuminuria are associated with increased risk for developing manifestations of cerebral small vessel disease. Individuals with larger changes in these kidney measures should be considered as a high risk population for accelerated brain pathology.
PubMed ID
29960746 View in PubMed
Less detail

The AGES-Reykjavik Study suggests that change in kidney measures is associated with subclinical brain pathology in older community-dwelling persons.

https://arctichealth.org/en/permalink/ahliterature300494
Source
Kidney Int. 2018 09; 94(3):608-615
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Date
09-2018
Author
Sanaz Sedaghat
Jie Ding
Gudny Eiriksdottir
Mark A van Buchem
Sigurdur Sigurdsson
M Arfan Ikram
Osorio Meirelles
Vilmundur Gudnason
Andrew S Levey
Lenore J Launer
Author Affiliation
Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
Source
Kidney Int. 2018 09; 94(3):608-615
Date
09-2018
Language
English
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Keywords
Aged
Albuminuria - physiopathology - urine
Cerebral Small Vessel Diseases - diagnosis - epidemiology
Creatinine - urine
Disease Progression
Female
Follow-Up Studies
Glomerular Filtration Rate - physiology
Humans
Incidence
Independent living
Kidney - physiopathology
Magnetic Resonance Imaging
Male
Prospective Studies
Renal Insufficiency, Chronic - physiopathology - urine
Risk factors
Serum Albumin
White Matter - diagnostic imaging - pathology
Abstract
Decreased glomerular filtration rate (GFR) and albuminuria may be accompanied by brain pathology. Here we investigated whether changes in these kidney measures are linked to development of new MRI-detected infarcts and microbleeds, and progression of white matter hyperintensity volume. The study included 2671 participants from the population-based AGES-Reykjavik Study (mean age 75, 58.7% women). GFR was estimated from serum creatinine, and albuminuria was assessed by urinary albumin-to-creatinine ratio. Brain MRI was acquired at baseline (2002-2006) and 5 years later (2007-2011). New MRI-detected infarcts and microbleeds were counted on the follow-up scans. White matter hyperintensity progression was estimated as percent change in white matter hyperintensity volumes between the two exams. Participants with a large eGFR decline (over 3 ml/min/1.73m2 per year) had more incident subcortical infarcts (odds ratio 1.53; 95% confidence interval 1.05, 2.22), and more marked progression of white matter hyperintensity volume (difference: 8%; 95% confidence interval: 4%, 12%), compared to participants without a large decline. Participants with incident albuminuria (over 30 mg/g) had 21% more white matter hyperintensity volume progression (95% confidence interval: 14%, 29%) and 1.86 higher odds of developing new deep microbleeds (95% confidence interval 1.16, 2.98), compared to participants without incident albuminuria. The findings were independent of cardiovascular risk factors. Changes in kidney measures were not associated with occurrence of cortical infarcts. Thus, larger changes in eGFR and albuminuria are associated with increased risk for developing manifestations of cerebral small vessel disease. Individuals with larger changes in these kidney measures should be considered as a high risk population for accelerated brain pathology.
PubMed ID
29960746 View in PubMed
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The alcohol paradox: light-to-moderate alcohol consumption, cognitive function, and brain volume.

https://arctichealth.org/en/permalink/ahliterature259852
Source
J Gerontol A Biol Sci Med Sci. 2014 Dec;69(12):1528-35
Publication Type
Article
Date
Dec-2014
Author
Benjamin J K Davis
Jean-Sebastian Vidal
Melissa Garcia
Thor Aspelund
Mark A van Buchem
Maria K Jonsdottir
Sigurdur Sigurdsson
Tamara B Harris
Vilmundur Gudnason
Lenore J Launer
Source
J Gerontol A Biol Sci Med Sci. 2014 Dec;69(12):1528-35
Date
Dec-2014
Language
English
Publication Type
Article
Keywords
Aged
Aging
Alcohol Drinking - epidemiology - physiopathology - psychology
Brain - pathology
Cognition Disorders - diagnosis - epidemiology - psychology
Disease Progression
Female
Follow-Up Studies
Humans
Iceland - epidemiology
Incidence
Magnetic Resonance Imaging
Male
Neuropsychological Tests
Prevalence
Prognosis
Questionnaires
Retrospective Studies
Risk factors
Abstract
Studies of older persons show consumption of light-to-moderate amounts of alcohol is positively associated with cognitive function and, separately, is negatively associated with total brain volume (TBV). This is paradoxical as generally, cognitive function is positively associated with TBV. We examined the relationships of TBV, global cognitive function (GCF), and alcohol consumption in a population-based cohort of 3,363 men and women (b. 1907-1935) participating in the Age Gene/Environment Susceptibility-Reykjavik Study (2002-2006) and who were free of dementia or mild cognitive impairment
Drinking status (never, former, and current) and current amount of alcohol consumed were assessed by questionnaire. GCF is a composite score derived from a battery of cognitive tests. TBV, standardized to head size, is estimated quantitatively from brain magnetic resonance imaging.
Among women and not men, adjusting for demographic and cardiovascular risk factors, current drinkers had significantly higher GCF scores than abstainers and former drinkers (p
PubMed ID
24994845 View in PubMed
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Allometric scaling of brain regions to intra-cranial volume: An epidemiological MRI study.

https://arctichealth.org/en/permalink/ahliterature289829
Source
Hum Brain Mapp. 2017 01; 38(1):151-164
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Intramural
Date
01-2017
Author
Laura W de Jong
Jean-Sébastien Vidal
Lars E Forsberg
Alex P Zijdenbos
Thaddeus Haight
Sigurdur Sigurdsson
Vilmundur Gudnason
Mark A van Buchem
Lenore J Launer
Author Affiliation
Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Source
Hum Brain Mapp. 2017 01; 38(1):151-164
Date
01-2017
Language
English
Publication Type
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Intramural
Keywords
Aged
Aged, 80 and over
Aging
Algorithms
Alzheimer Disease - diagnostic imaging - epidemiology
Brain - diagnostic imaging - pathology
Brain Mapping
Community Health Planning
Coronary Artery Disease - diagnostic imaging - epidemiology - pathology
Female
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Male
Netherlands - epidemiology
Reproducibility of Results
Sex Factors
Abstract
There is growing evidence that sub-structures of the brain scale allometrically to total brain size, that is, in a non-proportional and non-linear way. Here, scaling of different volumes of interest (VOI) to intra-cranial volume (ICV) was examined. It was assessed whether scaling was allometric or isometric and whether scaling coefficients significantly differed from each other. We also tested to what extent allometric scaling of VOI was introduced by the automated segmentation technique. Furthermore, reproducibility of allometric scaling was studied different age groups and study populations. Study samples included samples of cognitively healthy adults from the community-based Age Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik Study) (N?=?3,883), the Coronary Artery Risk Development in Young Adults Study (CARDIA) (N =709), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N?=?180). Data encompassed participants with different age, ethnicity, risk factor profile, and ICV and VOI obtained with different automated MRI segmentation techniques. Our analysis showed that (1) allometric scaling is a trait of all parts of the brain, (2) scaling of neo-cortical white matter, neo-cortical gray matter, and deep gray matter structures including the cerebellum are significantly different from each other, and (3) allometric scaling of brain structures cannot solely be explained by age-associated atrophy, sex, ethnicity, or a systematic bias from study-specific segmentation algorithm, but appears to be a true feature of brain geometry. Hum Brain Mapp 38:151-164, 2017. © 2016 Wiley Periodicals, Inc.
Notes
Cites: Hum Brain Mapp. 2011 Apr;32(4):641-53 PMID 20572207
Cites: Am J Epidemiol. 2007 May 1;165(9):1076-87 PMID 17351290
Cites: Brain Behav Evol. 1985;27(1):28-40 PMID 3836731
Cites: Acad Radiol. 2008 Mar;15(3):300-13 PMID 18280928
Cites: Hum Brain Mapp. 2006 Apr;27(4):314-24 PMID 16124013
Cites: Neuroimage. 2010 Dec;53(4):1244-55 PMID 20600995
Cites: Med Image Comput Comput Assist Interv. 2008;11(Pt 1):620-7 PMID 18979798
Cites: Psychiatry Res. 2011 Aug 30;193(2):113-22 PMID 21684724
Cites: Neuroreport. 2002 Dec 3;13(17):2371-4 PMID 12488829
Cites: Neuroimage. 2008 Aug 15;42(2):535-47 PMID 18599317
Cites: J Comput Assist Tomogr. 1998 Sep-Oct;22(5):827-37 PMID 9754125
Cites: Cereb Cortex. 1994 Jul-Aug;4(4):331-43 PMID 7950307
Cites: J Theor Biol. 1982 Mar 7;95(1):37-41 PMID 7087496
Cites: IEEE Trans Med Imaging. 2003 Mar;22(3):414-23 PMID 12760558
Cites: Cereb Cortex. 2008 Sep;18(9):2181-91 PMID 18234686
Cites: Neurosci Lett. 2011 Apr 8;493(1-2):8-13 PMID 21296128
Cites: IEEE Trans Med Imaging. 2002 Oct;21(10):1280-91 PMID 12585710
Cites: Front Aging Neurosci. 2014 Oct 07;6:264 PMID 25339897
Cites: J Clin Epidemiol. 1988;41(11):1105-16 PMID 3204420
Cites: Neuroimage. 2002 Feb;15(2):422-34 PMID 11798276
Cites: Neuroimage. 2012 Feb 15;59(4):3862-70 PMID 22119006
Cites: Brain Behav Evol. 1988;32(1):17-26 PMID 3056571
Cites: Neuroimage. 2012 Nov 15;63(3):1257-72 PMID 22877579
Cites: Neuroimage. 1999 Feb;9(2):179-94 PMID 9931268
Cites: Nat Neurosci. 1999 Oct;2(10):859-61 PMID 10491602
Cites: Brain. 1997 Apr;120 ( Pt 4):701-22 PMID 9153131
Cites: Comput Med Imaging Graph. 1994 Jan-Feb;18(1):11-23 PMID 8156533
Cites: Front Neurosci. 2014 Nov 06;8:356 PMID 25414635
PubMed ID
27557999 View in PubMed
Less detail

Allometric scaling of brain regions to intra-cranial volume: An epidemiological MRI study.

https://arctichealth.org/en/permalink/ahliterature275481
Source
Hum Brain Mapp. 2016 Aug 25;
Publication Type
Article
Date
Aug-25-2016
Author
Laura W de Jong
Jean-Sébastien Vidal
Lars E Forsberg
Alex P Zijdenbos
Thaddeus Haight
Sigurdur Sigurdsson
Vilmundur Gudnason
Mark A van Buchem
Lenore J Launer
Source
Hum Brain Mapp. 2016 Aug 25;
Date
Aug-25-2016
Language
English
Publication Type
Article
Abstract
There is growing evidence that sub-structures of the brain scale allometrically to total brain size, that is, in a non-proportional and non-linear way. Here, scaling of different volumes of interest (VOI) to intra-cranial volume (ICV) was examined. It was assessed whether scaling was allometric or isometric and whether scaling coefficients significantly differed from each other. We also tested to what extent allometric scaling of VOI was introduced by the automated segmentation technique. Furthermore, reproducibility of allometric scaling was studied different age groups and study populations. Study samples included samples of cognitively healthy adults from the community-based Age Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik Study) (N?=?3,883), the Coronary Artery Risk Development in Young Adults Study (CARDIA) (N =709), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) (N?=?180). Data encompassed participants with different age, ethnicity, risk factor profile, and ICV and VOI obtained with different automated MRI segmentation techniques. Our analysis showed that (1) allometric scaling is a trait of all parts of the brain, (2) scaling of neo-cortical white matter, neo-cortical gray matter, and deep gray matter structures including the cerebellum are significantly different from each other, and (3) allometric scaling of brain structures cannot solely be explained by age-associated atrophy, sex, ethnicity, or a systematic bias from study-specific segmentation algorithm, but appears to be a true feature of brain geometry. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc.
PubMed ID
27557999 View in PubMed
Less detail

Arterial stiffness, pressure and flow pulsatility and brain structure and function: the Age, Gene/Environment Susceptibility--Reykjavik study.

https://arctichealth.org/en/permalink/ahliterature129735
Source
Brain. 2011 Nov;134(Pt 11):3398-407
Publication Type
Article
Date
Nov-2011
Author
Gary F Mitchell
Mark A van Buchem
Sigurdur Sigurdsson
John D Gotal
Maria K Jonsdottir
Ólafur Kjartansson
Melissa Garcia
Thor Aspelund
Tamara B Harris
Vilmundur Gudnason
Lenore J Launer
Author Affiliation
Cardiovascular Engineering, Inc., Norwood, MA 02062, USA. garyfmitchell@mindspring.com
Source
Brain. 2011 Nov;134(Pt 11):3398-407
Date
Nov-2011
Language
English
Publication Type
Article
Keywords
Age Factors
Aged
Aged, 80 and over
Aorta - physiopathology
Blood Flow Velocity - physiology
Blood Pressure - physiology
Brain - blood supply - pathology - physiopathology
Cardiovascular Diseases - pathology - physiopathology
Carotid Arteries - physiopathology
Female
Gene-Environment Interaction
Humans
Iceland
Male
Prospective Studies
Pulsatile Flow - physiology
Risk factors
Vascular Stiffness - physiology
Abstract
Aortic stiffness increases with age and vascular risk factor exposure and is associated with increased risk for structural and functional abnormalities in the brain. High ambient flow and low impedance are thought to sensitize the cerebral microcirculation to harmful effects of excessive pressure and flow pulsatility. However, haemodynamic mechanisms contributing to structural brain lesions and cognitive impairment in the presence of high aortic stiffness remain unclear. We hypothesized that disproportionate stiffening of the proximal aorta as compared with the carotid arteries reduces wave reflection at this important interface and thereby facilitates transmission of excessive pulsatile energy into the cerebral microcirculation, leading to microvascular damage and impaired function. To assess this hypothesis, we evaluated carotid pressure and flow, carotid-femoral pulse wave velocity, brain magnetic resonance images and cognitive scores in participants in the community-based Age, Gene/Environment Susceptibility--Reykjavik study who had no history of stroke, transient ischaemic attack or dementia (n = 668, 378 females, 69-93 years of age). Aortic characteristic impedance was assessed in a random subset (n = 422) and the reflection coefficient at the aorta-carotid interface was computed. Carotid flow pulsatility index was negatively related to the aorta-carotid reflection coefficient (R = -0.66, P
Notes
Cites: J Appl Physiol (1985). 2008 Nov;105(5):1652-6018772322
Cites: J Gerontol A Biol Sci Med Sci. 2008 Aug;63(8):848-5418772473
Cites: Hypertension. 2008 Dec;52(6):1120-618852384
Cites: Stroke. 2009 Mar;40(3):677-8219131654
Cites: Hypertension. 2009 Apr;53(4):668-7319237680
Cites: Stroke. 2009 Apr;40(4):1229-3619246701
Cites: JAMA. 2009 Jun 24;301(24):2563-7019549973
Cites: Radiology. 2009 Dec;253(3):681-819864506
Cites: Circulation. 2010 Feb 2;121(4):505-1120083680
Cites: Eur Radiol. 2010 May;20(5):1132-819915847
Cites: Stroke. 2010 May;41(5):891-720360538
Cites: Circulation. 2010 Oct 5;122(14):1379-8620855656
Cites: Ann Neurol. 2000 Feb;47(2):145-5110665484
Cites: Hypertension. 2001 May;37(5):1236-4111358934
Cites: Arterioscler Thromb Vasc Biol. 2001 Dec;21(12):2046-5011742883
Cites: Hypertension. 2002 Jan;39(1):10-511799071
Cites: Circulation. 2002 Jun 25;105(25):2955-6112081987
Cites: IEEE Trans Med Imaging. 2002 Oct;21(10):1280-9112585710
Cites: Stroke. 2003 May;34(5):1203-612677025
Cites: Hypertension. 2004 Jun;43(6):1239-4515123572
Cites: Hypertension. 2004 Aug;44(2):134-915249547
Cites: J Psychiatr Res. 1975 Nov;12(3):189-981202204
Cites: Circulation. 1980 Jul;62(1):105-167379273
Cites: Med Biol Eng Comput. 1981 Sep;19(5):565-87334864
Cites: J Am Coll Cardiol. 1992 Oct;20(4):952-631527307
Cites: Stroke. 1997 Mar;28(3):652-99056627
Cites: Psychol Aging. 1998 Mar;13(1):8-209533186
Cites: J Gerontol B Psychol Sci Soc Sci. 1999 May;54(3):P155-6010363036
Cites: Circulation. 2005 Jun 28;111(25):3384-9015967850
Cites: Hypertension. 2005 Sep;46(3):454-6216103272
Cites: Stroke. 2005 Oct;36(10):2193-716151027
Cites: Circulation. 2005 Dec 13;112(24):3722-816330686
Cites: Circulation. 2006 Feb 7;113(5):657-6316461838
Cites: Circulation. 2006 Feb 7;113(5):664-7016461839
Cites: Stroke. 2007 Mar;38(3):888-9217272780
Cites: J Hypertens. 2007 May;25(5):1035-4017414668
Cites: Am J Epidemiol. 2007 May 1;165(9):1076-8717351290
Cites: Circulation. 2007 May 22;115(20):2628-3617485578
Cites: Hypertension. 2008 Jan;51(1):99-10418025297
Cites: Hypertension. 2008 Apr;51(4):1123-818259005
Cites: Am J Hypertens. 2008 Dec;21(12):1304-918802428
PubMed ID
22075523 View in PubMed
Less detail

Associations between arterial stiffness, depressive symptoms and cerebral small vessel disease: cross-sectional findings from the AGES-Reykjavik Study.

https://arctichealth.org/en/permalink/ahliterature267325
Source
J Psychiatry Neurosci. 2015 Oct 20;41(1):140334
Publication Type
Article
Date
Oct-20-2015
Author
Thomas T van Sloten
Gary F Mitchell
Sigurdur Sigurdsson
Mark A van Buchem
Palmi V Jonsson
Melissa E Garcia
Tamara B Harris
Ronald M A Henry
Andrew S Levey
Coen D A Stehouwer
Vilmundur Gudnason
Lenore J Launer
Source
J Psychiatry Neurosci. 2015 Oct 20;41(1):140334
Date
Oct-20-2015
Language
English
Publication Type
Article
Abstract
Arterial stiffness may contribute to depression via cerebral microvascular damage, but evidence for this is scarce. We therefore investigated whether arterial stiffness is associated with depressive symptoms and whether cerebral small vessel disease contributes to this association.
This cross-sectional study included a subset of participants from the AGES-Reykjavik study second examination round, which was conducted from 2007 to 2011. Arterial stiffness (carotid-femoral pulse wave velocity [CFPWV]), depressive symptoms (15-item geriatric depression scale [GDS-15]) and cerebral small vessel disease (MRI) were determined. Manifestations of cerebral small vessel disease included higher white matter hyperintensity volume, subcortical infarcts, cerebral microbleeds, Virchow-Robin spaces and lower total brain parenchyma volume.
We included 2058 participants (mean age 79.6 yr; 59.0% women) in our analyses. Higher CFPWV was associated with a higher GDS-15 score, after adjustment for potential confounders (ß 0.096, 95% confidence interval [CI] 0.005-0.187). Additional adjustment for white matter hyperintensity volume or subcortical infarcts attenuated the association between CFPWV and the GDS-15 score, which became nonsignificant (p > 0.05). Formal mediation tests showed that the attenuating effects of white matter hyperintensity volume and subcortical infarcts were statistically significant. Virchow-Robin spaces, cerebral microbleeds and cerebral atrophy did not explain the association between CFPWV and depressive symptoms.
Our study was limited by its cross-sectional design, which precludes any conclusions about causal mediation. Depressive symptoms were assessed by a self-report questionnaire.
Greater arterial stiffness is associated with more depressive symptoms; this association is partly accounted for by white matter hyperintensity volume and subcortical infarcts. This study supports the hypothesis that arterial stiffness leads to depression in part via cerebral small vessel disease.
PubMed ID
26505140 View in PubMed
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Brain tissue volumes in the general population of the elderly: the AGES-Reykjavik study.

https://arctichealth.org/en/permalink/ahliterature129325
Source
Neuroimage. 2012 Feb 15;59(4):3862-70
Publication Type
Article
Date
Feb-15-2012
Author
Sigurdur Sigurdsson
Thor Aspelund
Lars Forsberg
Jesper Fredriksson
Olafur Kjartansson
Bryndis Oskarsdottir
Palmi V Jonsson
Gudny Eiriksdottir
Tamara B Harris
Alex Zijdenbos
Mark A van Buchem
Lenore J Launer
Vilmundur Gudnason
Author Affiliation
The Icelandic Heart Association, Kopavogur, Iceland. sigurdur@hjarta.is
Source
Neuroimage. 2012 Feb 15;59(4):3862-70
Date
Feb-15-2012
Language
English
Publication Type
Article
Keywords
Age Factors
Aged
Aged, 80 and over
Atrophy
Brain - pathology
Female
Humans
Magnetic Resonance Imaging
Male
Organ Size
Abstract
Imaging studies have reported conflicting findings on how brain structure differs with age and sex. This may be explained by discrepancies and limitations in study population and study design. We report a study on brain tissue volumes in one of the largest cohorts of individuals studied to date of subjects with high mean age (mean ± standard deviation (SD) 76 ± 6 years). These analyses are based on magnetic resonance imaging (MRI) scans acquired at baseline on 4303 non-demented elderly, and 367 who had a second MRI, on average 2.5 ± 0.2 years later. Tissue segmentation was performed with an automatic image analysis pipeline. Total brain parenchymal (TBP) volume decreased with increasing age while there was an increase in white matter hyperintensities (WMH) in both sexes. A reduction in both normal white matter (NWM)- and gray matter (GM) volume contributed to the brain shrinkage. After adjusting for intra-cranial volume, women had larger brain volumes compared to men (3.32%, p
PubMed ID
22119006 View in PubMed
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