title: Risk factors for lacune subtypes in the Atherosclerosis Risk in Communities (ARIC) Study.
abstract: OBJECTIVE
  Lacunar infarctions are mainly due to 2 microvascular pathologies: lipohyalinosis and microatheroma. Little is known about risk factor differences for these subtypes. We hypothesized that diabetes and glycated hemoglobin (HbA(1)c) would be related preferentially to the lipohyalinotic subtype.
  
  
  METHODS
  We performed a cross-section analysis of the brain MRI data from 1,827 participants in the Atherosclerosis Risk in Communities study. We divided subcortical lesions ≤ 20 mm in diameter into those ≤ 7 mm (of probable lipohyalinotic etiology) and 8-20 mm (probably due to microatheroma) and used Poisson regression to investigate associations with the number of each type of lesion. Unlike previous studies, we also fitted a model involving lesions <3 mm.
  
  
  RESULTS
  Age (prevalence ratio [PR] 1.11 per year; 95% confidence interval [CI] 1.08-1.14), black ethnicity (vs white, PR 1.66; 95% CI 1.27-2.16), hypertension (PR 2.12; 95% CI 1.61-2.79), diabetes (PR 1.42; 95% CI 1.08-1.87), and ever-smoking (PR 1.34; 95% CI 1.04-1.74) were significantly associated with lesions ≤ 7 mm. Findings were similar for lesions <3 mm. HbA(1)c, substituted for diabetes, was also associated with smaller lesions. Significantly associated with 8-20 mm lesions were age (PR 1.14; 95% CI 1.09-1.20), hypertension (PR 1.79; 95% CI 1.14-2.83), ever-smoking (PR 2.66; 95% CI 1.63-4.34), and low-density lipoprotein (LDL) cholesterol (PR 1.27 per SD; 95% CI 1.06-1.52). When we analyzed only participants with lesions, history of smoking (PR 1.99; 95% CI 1.23-3.20) and LDL (PR 1.33 per SD; 95% CI 1.08-1.65) were associated with lesions 8-20 mm.
  
  
  CONCLUSIONS
  Smaller lacunes (even those <3 mm) were associated with diabetes and HbA(1)c, and larger lacunes associated with LDL cholesterol, differences which support long-held theories relating to their underlying pathology. The findings may contribute to broader understanding of cerebral microvascular disease.
authors.affiliation: danielcbezerra@gmail.com
authors.forename: D C
authors.initials: DC
authors.lastname: Bezerra
authors.forename: A R
authors.initials: AR
authors.lastname: Sharrett
authors.forename: K
authors.initials: K
authors.lastname: Matsushita
authors.forename: R F
authors.initials: RF
authors.lastname: Gottesman
authors.forename: D
authors.initials: D
authors.lastname: Shibata
authors.forename: T H
authors.initials: TH
authors.lastname: Mosley
authors.forename: J
authors.initials: J
authors.lastname: Coresh
authors.forename: M
authors.initials: M
authors.lastname: Szklo
authors.forename: M S
authors.initials: MS
authors.lastname: Carvalho
authors.forename: E
authors.initials: E
authors.lastname: Selvin
mesh_terms: D050197:Atherosclerosis / Q000453:epidemiology*; D001921:Brain / Q000473:pathology*; D008076:Cholesterol, HDL / Q000097:blood; D003430:Cross-Sectional Studies; D003920:Diabetes Mellitus / Q000453:epidemiology; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D005500:Follow-Up Studies; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D012111:Residence Characteristics / Q000706:statistics & numerical data; D012307:Risk Factors; D059409:Stroke, Lacunar / Q000145:classification* / Q000453:epidemiology*
chemical_list: D008076:Cholesterol, HDL; D006442:Glycated Hemoglobin