Do cardiovascular risk factors explain the link between white matter hyperintensities and brain volumes in old age? A population‐based study

Wang, Rui; Fratiglioni, Laura; Laveskog, Anna; Kalpouzos, Grégoria; Ehrenkrona, Christina; Zhang, Y.; Bronge, Lena; Wahlund, Lars‐Olof; Bäckman, Lars; Qiu, Chengxuan

doi:10.1111/ene.12319

Cited by 30 publications

(32 citation statements)

References 33 publications

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“…12 We found a slight increase in the global score for PVS number with advancing age, which is in accordance with most other studies. 4,8,9,13,[28][29][30][31] Our study sample was relatively healthy, 20 which might partly explain a smaller increase with age than expected, because PVS are presumably correlated with the degree of cerebral small-vessel disease and amyloid deposition with increasing age. 17,18 We did not find a sex difference in the distribution of PVS, even though it has been reported in earlier studies 11,13,16 ; notably, one of these studies comprised a very large population-based sample (n ϭ ϳ1800), in which men were found to have more PVS in the basal ganglia than women, 13 while another large-scale study of patients with ischemic stroke (n ϭ 1090) found that men had more PVS in the white matter than women, but there was no sex difference in the distribution of PVS in the basal ganglia.…”

Section: Discussionmentioning

confidence: 72%

“…20 Briefly, the SNAC-K study included 4 younger cohorts with 6-year intervals (60, 66, 72, and 78 years of age) and 7 older cohorts with 3-year intervals (81, 84, 87, 90, 93, 96, and 99 and older years of age). Of all 4590 persons who were eligible to participate in SNAC-K, 3363 (73.3%) were eventually examined at baseline (March 2001 to June 2004).…”

Section: Study Participantsmentioning

confidence: 99%

“…From September 2001 to October 2003, five hundred fifty-five SNAC-K participants who were not institutionalized or disabled and who did not have dementia also underwent brain MR imaging examinations. 20 Of these, 2 persons did not complete the entire examination owing to claustrophobia, 4 had suboptimal MR imaging because of motion artifacts, 2 were excluded because of large meningiomas, and images for 17 persons were lost due to technical problems. Therefore, 530 subjects were included in this study.…”

Section: Study Participantsmentioning

confidence: 99%

“…20 Hypertension was defined as arterial blood pressure of Ն140/90 mm Hg or current use of antihypertensive agents. Obesity was defined as a body mass index of Ն30 kg/m 2 .…”

Section: Assessment Of Cardiovascular Healthmentioning

confidence: 99%

“…10 Here we present data from a population-based MR imaging study within the Swedish National study on Aging and Care in Kungsholmen (SNAC-K) in central Stockholm, Sweden. 20 Within this study, we have the unique opportunity to describe a new visual rating scale for PVS by considering the number, size, and location of PVS. Furthermore, we sought to investigate the age-and sex-specific distribution of PVS in older individuals and to explore whether global and regional PVS are associated with the load of global and regional WMH.…”

mentioning

confidence: 99%

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Perivascular Spaces in Old Age: Assessment, Distribution, and Correlation with White Matter Hyperintensities

Laveskog

Wang²,

Bronge

et al. 2017

AJNR Am J Neuroradiol

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Section: Discussionmentioning

confidence: 72%

Section: Study Participantsmentioning

confidence: 99%

Section: Study Participantsmentioning

confidence: 99%

“…20 Hypertension was defined as arterial blood pressure of Ն140/90 mm Hg or current use of antihypertensive agents. Obesity was defined as a body mass index of Ն30 kg/m 2 .…”

Section: Assessment Of Cardiovascular Healthmentioning

confidence: 99%

mentioning

confidence: 99%

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Perivascular Spaces in Old Age: Assessment, Distribution, and Correlation with White Matter Hyperintensities

Laveskog

Wang²,

Bronge

et al. 2017

AJNR Am J Neuroradiol

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Peripheral (deep) but not periventricular MRI white matter hyperintensities are increased in clinical vascular dementia compared to Alzheimer's disease

et al. 2016

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Background and purposeVascular dementia (VAD) is a complex diagnosis at times difficult to distinguish from Alzheimer's disease (AD). MRI scans often show white matter hyperintensities (WMH) in both conditions. WMH increase with age, and both VAD and AD are associated with aging, thus presenting an attribution conundrum. In this study, we sought to show whether the amount of WMH in deep white matter (dWMH), versus periventricular white matter (PVH), would aid in the distinction between VAD and AD, independent of age.MethodsBlinded semiquantitative ratings of WMH validated by objective quantitation of WMH volume from standardized MRI image acquisitions. PVH and dWMH were rated separately and independently by two different examiners using the Scheltens scale. Receiver operator characteristic (ROC) curves were generated using logistic regression to assess classification of VAD (13 patients) versus AD (129 patients). Clinical diagnoses were made in a specialty memory disorders clinic.ResultsUsing PVH rating alone, overall classification (area under the ROC curve, AUC) was 75%, due only to the difference in age between VAD and AD patients in our study and not PVH. In contrast, dWMH rating produced 86% classification accuracy with no independent contribution from age. A global Longstreth rating that combines dWMH and PVH gave an 88% AUC.ConclusionsIncreased dWMH indicate a higher likelihood of VAD versus AD. Assessment of dWMH on MRI scans using Scheltens and Longstreth scales may aid the clinician in distinguishing the two conditions.

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The interactive effect of demographic and clinical factors on hippocampal volume: A multicohort study on 1958 cognitively normal individuals

et al. 2017

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Alzheimer's disease is characterized by hippocampal atrophy. Other factors also influence the hippocampal volume, but their interactive effect has not been investigated before in cognitively healthy individuals. The aim of this study is to evaluate the interactive effect of key demographic and clinical factors on hippocampal volume, in contrast to previous studies frequently investigating these factors in a separate manner. Also, to investigate how comparable the control groups from ADNI, AIBL, and AddNeuroMed are with five population-based cohorts. In this study, 1958 participants were included (100 AddNeuroMed, 226 ADNI, 155 AIBL, 59 BRC, 295 GENIC, 279 BioFiNDER, 398 PIVUS, and 446 SNAC-K). ANOVA and random forest were used for testing between-cohort differences in demographic-clinical variables. Multiple regression was used to study the influence of demographic-clinical variables on hippocampal volume. ANCOVA was used to analyze whether between-cohort differences in demographic-clinical variables explained between-cohort differences in hippocampal volume. Age and global brain atrophy were the most important variables in explaining variability in hippocampal volume. These variables were not only important themselves but also in interaction with gender, education, MMSE, and total intracranial volume. AddNeuroMed, ADNI, and AIBL differed from the population-based cohorts in several demographic-clinical variables that had a significant effect on hippocampal volume. Variability in hippocampal volume in individuals with normal cognition is high. Differences that previously tended to be related to disease mechanisms could also be partly explained by demographic and clinical factors independent from the disease. Furthermore, cognitively normal individuals especially from ADNI and AIBL are not representative of the general population. These findings may have important implications for future research and clinical trials, translating imaging biomarkers to the general population, and validating current diagnostic criteria for Alzheimer's disease and predementia stages.

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Do cardiovascular risk factors explain the link between white matter hyperintensities and brain volumes in old age? A population‐based study

Cited by 30 publications

References 33 publications

Perivascular Spaces in Old Age: Assessment, Distribution, and Correlation with White Matter Hyperintensities

Perivascular Spaces in Old Age: Assessment, Distribution, and Correlation with White Matter Hyperintensities

Peripheral (deep) but not periventricular MRI white matter hyperintensities are increased in clinical vascular dementia compared to Alzheimer's disease

The interactive effect of demographic and clinical factors on hippocampal volume: A multicohort study on 1958 cognitively normal individuals

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