Metabolic syndrome is associated with incidence of deep cerebral microbleeds.
Shingo MitakiHiroyuki TakayoshiTomonori NakagawaAtsushi NagaiHiroaki OguroShuhei YamaguchiPublished in: PloS one (2018)
Metabolic syndrome (MetS) has been associated with silent brain lesions; however, there are no data on the relationship between MetS and the incidence of cerebral microbleeds (CMBs) in Asian populations. The aim of this study was to evaluate the longitudinal association between MetS and incidence of CMBs in the Japanese population. We performed a prospective cohort study involving 684 Japanese participants (mean age, 61.7 years) with a mean 6.5 ± 3.4 years follow-up. All participants underwent 1.5 T magnetic resonance imaging, and CMBs were classified by their locations. Logistic regression analyses were performed to examine the relationship of MetS and its components with the incidence of CMBs. MetS was observed in 7.5% of the study population. Forty-nine (7.2%) subjects (36 had new deep or infratentorial CMBs, 13 had new strictly lobar CMBs) developed new CMBs during the follow-up period. In multivariable analysis, MetS was significantly associated with the incidence of deep or infratentorial CMBs (odds ratio, 4.03; 95% confidence interval, 1.72-9.41), and the elevated blood pressure component was most robustly associated with the incidence of deep or infratentorial CMBs (odds ratio, 5.16; 95% confidence interval, 2.02-13.2). Increased body mass index was also associated with incidence of deep or infratentorial CMBs (odds ratio, 2.45; 95% confidence interval, 1.06-5.67). The present study showed that MetS predicts incidence of CMBs in the deep brain regions and high blood pressure is the most important among the MetS components.
Keyphrases
- risk factors
- metabolic syndrome
- blood pressure
- magnetic resonance imaging
- body mass index
- insulin resistance
- subarachnoid hemorrhage
- computed tomography
- cerebral ischemia
- skeletal muscle
- resting state
- electronic health record
- functional connectivity
- uric acid
- cross sectional
- blood brain barrier
- big data
- blood glucose
- weight loss
- cardiovascular risk factors
- artificial intelligence