1

Supplemental e-methods

Excluded subjects

Of all potentially eligible subjects (n=1740), 24 individuals refused to enroll, 1 could not undergo MRI because of severe

claustrophobia, 9 had a history of neurological disorder (stroke, n = 6; meningitis, n = 1; encephalitis, n = 1; spinocerebellar

degeneration, n = 1) and 3 had brain injury with abnormalities seen on MRI. No participants with dementia were included.

Among the remaining 1703 subjects, 8 subjects with MRI motion artifacts, 1 with numerous cavernous angiomas, and 119

with incomplete data were excluded.

Brain MRI acquisition and analysis

MRIs were performed with the following parameters: axial T1-weighted imaging, repetition time (TR), 550 ms; echo time

(TE), 15 ms; flip angle (FA), 80°; section thickness, 7 mm; gap width, 1.4 mm; matrix, 256×352 mm 2; filed of view 220×220

mm2; axial fast spin-echo T2-weighted imaging, TR, 4000 ms; TE, 108 ms; FA, 90°; section thickness, 7 mm; gap width, 1.4

mm; matrix, 352×400 mm2; filed of view 220×220 mm2, axial fluid-attenuated inversion recovery (FLAIR) imaging, TR,

10,000 ms; inversion time, 2500 ms; TE, 96 ms; FA, 90°; section thickness, 7 mm; gap width, 1.4 mm; matrix, 224×336

mm2; filed of view 220×220 mm2, and axial gradient-echo T2*-weighted imaging TR, 735 ms; TE, 20 ms; flip angle, 30°;

section thickness, 7 mm; gap width, 1.4 mm; matrix, 224×320 mm2; filed of view 220×220 mm2.

White matter changes on T2-weighted imaging and FLAIR imaging were assessed with both white matter hyperintensities

(WMH) and periventricular hyperintensities (PVH) of Fazekas scale,1 because there is some differences in pathogenesis

between the both (i.e. PVH is considered as non-vascular origin).2 Each grade was as follows; WMH: grade 1, punctuate;

2

grade 2, early confluence; and grade 3, confluent; and PVH: grade 1, caps or lining; grade 2, bands; and grade 3, irregular

extension into the deep white matter.1 Lacunes were defined as focal, sharply demarcated lesions >3 mm in diameter

showing high intensity on T2-weighted imaging and low intensity on T1-weighted imaging.3 They were distinguished from

perivascular spaces by their larger size, spheroid shape and surrounding hyperintensity on FLAIR.

Using a computer-assisted processing system (Image J version 1.46r; National Institutes of Health, Bethesda, MD),4, 5 we

calculated the percentage of brain area on one axial T2-weighted image in 2 slices above the pineal body as an index of

brain atrophy.

Supplemental e-discussion

A previous population-based study revealed associations between each both PVS locations and WMH or PVH.6 Meanwhile,

our study showed only an association between BG-PVS and WMH. These discrepancies might be explained by some

methodological or cohort differences, such as the different mean age of the samples cohorts or the rating scale used.

However, the lack of association between PVS and PVH might also be explained by the hypotheses that PVH is non-

vascular origin.2

The explanation for our observed association between smoking and centrum semiovale perivascular spaces severity is

unknown. In vitro, nicotinic receptor stimulation protects neurons from degeneration induced by amyloid-β. 7 However,

among population-based studies, such effects are controversial,8, 9, suggesting that a complex relationship between tobacco

3

use and Alzheimer’s disease pathology, which may include the established adverse effects of smoking on cerebrovascular

system and interactions between amyloid and microvascular pathology in Alzheimer’s disease.7

Supplemental References

1. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA. MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. AJR Am J Roentgenol 1987;149:351-356. 2. Schmidt R, Schmidt H, Haybaeck J, et al. Heterogeneity in age-related white matter changes. Acta Neuropathol 2011;122:171-185. 3. Wardlaw JM, Smith EE, Biessels GJ, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 2013;12:822-838. 4. Yakushiji Y, Noguchi T, Hara M, et al. Distributional impact of brain microbleeds on global cognitive function in adults without neurological disorder. Stroke 2012;43:1800-1805. 5. Koga H, Yuzuriha T, Yao H, et al. Quantitative MRI findings and cognitive impairment among community dwelling elderly subjects. J Neurol Neurosurg Psychiatry 2002;72:737-741. 6. Zhu YC, Tzourio C, Soumare A, Mazoyer B, Dufouil C, Chabriat H. Severity of dilated Virchow-Robin spaces is associated with age, blood pressure, and MRI markers of small vessel disease: a population-based study. Stroke 2010;41:2483-2490. 7. Court JA, Johnson M, Religa D, et al. Attenuation of Abeta deposition in the entorhinal cortex of normal elderly individuals associated with tobacco smoking. Neuropathol Appl Neurobiol 2005;31:522-535.

4

8. Ott A, Slooter AJ, Hofman A, et al. Smoking and risk of dementia and Alzheimer's disease in a population-based cohort study: the Rotterdam Study. Lancet 1998;351:1840-1843. 9. van Duijn CM, Havekes LM, Van Broeckhoven C, de Knijff P, Hofman A. Apolipoprotein E genotype and association between smoking and early onset Alzheimer's disease. BMJ 1995;310:627-631.

4 Supplemental Tables Table e-1. Sensitively Analysis (univariable analysis): Differences in clinical characteristics and MRI findings between the groups

dichotomized by the different BG-PVS classification.

BG-PVS Low degree (0-2) High degree (3-4)

p-value Variables n= 1535 n= 40

Age, mean (SD), years 56.8 (9.7) 66.1 (6.9) <0.001

Sex, male, n (%) 718 (47) 26 (65) 0.023

Current smoker, n (%) 258 (17) 9 (23) 0.344

Ischemic heart disease, n (%) 27 (2) 3 (8) 0.009

Hypertension, n (%) 519 (34) 28 (70) <0.001

Diabetes mellitus, n (%) 140 (9) 7 (18) 0.072

Dyslipidemia, n (%) 829 (54) 27 (68) 0.091

Lacunes, n (%), n (%) 59 (4) 14 (35) <0.001

Severe WMH, n (%) 191 (12) 28 (70) <0.001

Severe PVH, n (%) 36 (2) 12 (30) <0.001

Brain atrophy, mean (SD), % 84.3 (4.2) 81.5 (4.6) <0.001

CMBs distribution, n (%) <0.001*

D/I CMBs 66 (4)

14 (35)

Strictly Lobar CMBs 45 (3) 2 (5)

High degree of CSO-PVS, n (%) 333 (22) 24 (60) <0.001

Abbreviations: BG = basal ganglia; PVS= perivascular spaces; SD= standard deviation; WMH = white matter hyperintensities; PVH = perventricular hyperintensities; CMBs = cerebral microbleeds; D/I = deep or infratentorial; CSO = centrum semioval. Values of age and

brain atrophy are compared using t-test. CMBs count is compared using Mann–Whitney U test. The chi-square test is used for frequency comparisons. * p-value is calculated with 2 (low and high degree PVS) x 3 (subjects without CMBs, with D/I CMBs, and with strictly lobar CMBs) the chi-square test.

5 Table e-2. Sensitively Analysis (Multivariable analysis): Multivariable logistic

regression analysis of independent predictors of high degree BG-PVS

using different BG-PVS dichotomization: low degree (score 0-2) vs. high

degree (score 3,4)

High degree of BG-PVS (3,4)

OR (95%CI) p-value

Age (/10 years) 2.12 (1.20-3.75) 0.009

Sex, male 1.79 (0.82-3.91) 0.142

Ischemic heart disease 2.23 (0.51-9.80) 0.288

Hypertension 1.42 (0.65-3.13) 0.381

Diabetes mellitus 0611 (0.22-1.69) 0.340

Dyslipidemia 1.59 (0.74-3.42) 0.232

Lacunes 3.81 (1.56-9.31) 0.003

Severe WMH 4.74 (2.01- 11.22) <0.001

Severe PVH 2.42 (0.94-6.26) 0.068

Brain atrophy 1.01 (0.92-1.12) 0.776

D/I CMBs* 3.40 (1.41-8.19) 0.007

Strictly lobar CMBs* 0.88 (0.17-4.46) 0.877

Abbreviations: BG = basal ganglia; PVS= perivascular spaces; WMH = white matter hyperintensities; PVH = perventricular

hyperintensities; D/I = deep or infratentorial; CMBs = cerebral microbleeds.

*Regarding the different CMBs, we created dummy variables to compare the influence of distributional pattern of CMBs, including

subject without CMBs (reference), with D/I CMBs and with strictly lobar CMBs.

Sensitivity analyses using each actual blood pressures value instead of presence of hypertension reveal that high degree BG-PVS

(score 3-4) have association with only diastolic blood pressure (per SD increase, OR 1.67/SD 95%CI 1.16-2.47, P =0.006). There

was no association of high degree of BG-PVS (score 3-4) and pulse pressure or mean arterial pressure.

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Table e-3. Detail of prevalence of high degree PVS and CMBs by age group

≤39 40-49 60-69 ≥70 ≥50

PVS, n (%)

With high degree BG-PVS* 4 (6.1) 24 (8.9) 62 (11.3) 86 (15.0) 36 (31.0) 212 (13.5) 184 (14.8)

With high degree CSO-PVS 8 (12.1) 33 (12.3) 109 (19.8) 160 (27.9) 47 (40.5) 357 (22.7) 316 (25.5)

CMBs, n (%)

Without CMBs 64 (97.0) 259 (96.3) 517 (94.0) 511 (89.0) 97 (83.6) 1448 (91.9) 1125 (90.7)

D/I CMBs** 0 (0.0) 4 (1.5) 12 (2.2) 23 (4.0) 8 (6.9) 47 (3.0) 43 (3.5)***

Strictly lobar CMBs 2 (3.0) 6 (2.2) 21 (3.8) 40 (7.0) 11 (9.5) 80 (5.1) 72 (5.8)***

Abbreviations: BG = basal ganglia; PVS= perivascular spaces; CMBs = cerebral microbleeds; D/I = deep or infratentorial.

* Score 2-4

** Including mixed lobar and D/I CMBs

*** The proportions of subjects with D/I CMBs and with strictly lobar CMBs were 63% and 37%.

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Supplemental Figure Figure e-1

Representative axial MRI images of high degree perivascular sapaces (PVS) and cerebral microbleeds (CMBs). A, B) Images of 67 years old female having hypertension

treatment. T2-weighted MRI (A) shows dot-like

hyperintensities characteristic of PVS in the basal ganglia

(BG: score 4). T2*-weighted MRI (B) shows rounded areas

of signal loss characteristic of CMBs in BG and thalamus

(arrows). C, D) Images of 63 years old female without

hypertension.

T2-weighted MRI (C) reveals linear hyperintensities typical of

PVS in the centrum semiovale (score3). T2*-weighted MRI

(D) shows CMBs in parietal cortical areas (arrows) A right

frontal rounded signal loss was defined as vessel

(arrowhead).