OBJECTIVE

To assess the prevalence of cerebral small-vessel disease (SVD) in subjects with type 1 diabetes compared with healthy control subjects and to characterize the diabetes-related factors associated with SVD.

RESEARCH DESIGN AND METHODS

This substudy was cross-sectional in design and included 191 participants with type 1 diabetes and median age 40.0 years (interquartile range 33.0–45.1) and 30 healthy age- and sex-matched control subjects. All participants underwent clinical investigation and brain MRIs, assessed for cerebral SVD.

RESULTS

Cerebral SVD was more common in participants with type 1 diabetes than in healthy control subjects: any marker 35% vs. 10% (P = 0.005), cerebral microbleeds (CMBs) 24% vs. 3.3% (P = 0.008), white matter hyperintensities 17% vs. 6.7% (P = 0.182), and lacunes 2.1% vs. 0% (P = 1.000). Presence of CMBs was independently associated with systolic blood pressure (odds ratio 1.03 [95% CI 1.00–1.05], P = 0.035).

CONCLUSIONS

Cerebral SVD, CMBs in particular, is more common in young people with type 1 diabetes compared with healthy control subjects.

Type 1 diabetes is associated with a fivefold increased risk of stroke (1), with cerebral small-vessel disease (SVD) as the most common etiology (2). Cerebral SVD in type 1 diabetes, however, remains scarcely investigated and is challenging to study in vivo per se owing to the size of affected vasculature (3); instead, MRI signs of SVD are studied. In this study, we aimed to assess the prevalence of cerebral SVD in subjects with type 1 diabetes compared with healthy control subjects and to characterize diabetes-related variables associated with SVD in stroke-free people with type 1 diabetes.

All study participants are part of the Finnish Diabetic Nephropathy (FinnDiane) Study (4). Participants attending the Helsinki University Hospital (HUH) study center were consecutively recruited and underwent brain MRI as part of their study visit. In 2011–2017, we studied 191 participants with type 1 diabetes. Inclusion criteria were age 18–50 years and type 1 diabetes onset at age <40 years. Exclusion criteria were presence of end-stage renal disease, clinical signs of cerebrovascular disease, or contraindications for MRI. We studied 30 healthy age- and sex-matched control subjects with mean fasting glucose 4.4 ± 0.4 mmol/L.

The study protocol was approved by the ethics committee of the HUH, and the study was carried out in accordance with the Declaration of Helsinki. Each participant signed a written informed consent form.

All participants underwent a clinical study visit (4). Brain MRI was performed with a 3.0 Tesla scanner (Achieva; Philips, Best, the Netherlands) at the Helsinki Medical Imaging Center, HUH, and included T1, T2, fluid-attenuated inversion recovery, susceptibility-weighted imaging, T2*, diffusion-weighted imaging, T1 MPRAGE (Magnetization-Prepared RApid Gradient Echo), and magnetic resonance angiography time-of-flight. An experienced neuroradiologist (J.M.) assessed the images, and repeated the assessment three times per participant, for markers of SVD (5,6): presence of cerebral microbleeds (CMBs), cortical superficial siderosis, white matter hyperintensities (WMHs) (Fazekas scale used, with category ≥1 considered to be significant burden), or lacunes. The neuroradiologist was blinded to clinical data but not to whether the participant had diabetes.

We analyzed parametric variables with t tests with results presented as means ± SD and nonparametric variables with Mann-Whitney U tests with results presented as medians (interquartile range). We analyzed categorical variables with χ2 test or Fisher exact test when appropriate. We performed logistic regression to determine independent associations with cerebral SVD and present results as odds ratio (OR) with 95% CIs. Statistical significance was P < 0.05. All analyses were performed with IBM SPSS Statistics, version 22.0, software (IBM, Armonk, NY).

Clinical characteristics and MRI findings of the 191 participants with type 1 diabetes and the 30 age- and sex-matched control subjects appear in Table 1. Of the 67 participants with type 1 diabetes and SVD, 32 (48%) had only CMBs, 20 (30%) only WMHs, 11 (16%) both CMBs and WMHs, 2 (3%) both CMBs and lacunes, and 2 (3%) both WMHs and lacunes (Supplementary Fig. 1).

Table 1

Clinical characteristics and MRI findings in participants with type 1 diabetes and control subjects matched for age and sex

Subjects with type 1 diabetesControl subjectsP
N 191 30  
Clinical characteristics    
 Female sex 101 (53) 17 (57) 0.699 
 Age, years 40.0 (33.0–45.1) 38.4 (31.4–43.2) 0.443 
 Diabetes duration, years 21.7 (18.3–30.9) — — 
 BMI, kg/m2 26.7 ± 4.2 24.5 ± 3.2 0.002 
 Systolic blood pressure, mmHg 130 ± 14 121 ± 11 0.001 
 Diastolic blood pressure, mmHg 77 (71–82) 76 (74–85) 0.387 
 HbA1c, % (mmol/mol) 8.2 ± 1.1 (66 ± 12) 5.1 ± 0.2 (33 ± 2) <0.001 
 Creatinine, µmol/L 68 (61–79) 74 (68–81) 0.067 
 Total cholesterol, mmol/L 4.4 (4.0–4.9) 4.6 (4.2–5.4) 0.178 
 LDL cholesterol, mmol/L 2.4 (2.0–2.9) 2.6 (2.3–3.3) 0.017 
 HDL cholesterol, mmol/L 1.50 (1.25–1.80) 1.46 (1.26–1.68) 0.362 
 Triglycerides, mmol/L 0.90 (0.68–1.38) 0.84 (0.69–1.26) 0.398 
 Antihypertensive medication 68 (36) <0.001 
 Statin therapy 42 (22) 0.002 
 Aspirin therapy 15 (7.9) 0.232 
 Albuminuria 30 (16) 0.018 
 Retinal photocoagulation 42 (22) 0.002 
 Coronary heart disease 1 (0.5) 1.000 
 Current smoking 15 (7.9) 5 (17) 0.118 
 Other autoimmune disease 63 (33) 6 (20) 0.149 
MRI findings    
 Cerebral SVD 67 (35) 3 (10) 0.005 
 CMBs 45 (24) 1 (3.3) 0.008 
 Number of CMBs   1.000 
  1, N (% of those with CMBs) 27 (60) 1 (100)  
  2, N (% of those with CMBs) 6 (13)  
  ≥3, N (% of those with CMBs) 12 (27)  
 Topography of CMBs    
  Strictly lobar, N (% of those with CMBs) 38 (84) 1 (100) 1.000 
  Strictly deep or infratentorial, N (% of those with CMBs) 3 (6.7) 1.000 
  Mixed, N (% of those with CMBs) 4 (8.9) 1.000 
 Cortical superficial siderosis — 
 Any WMH 44 (23) 2 (6.7) 0.051 
 Fazekas category 1 33 (17) 2 (6.7) 0.182 
 Lacunes 4 (2.1) 1.000 
 Stenosis of carotid arteries 2 (1.0) 1.000 
 Incidental findings 20 (10) 4 (13) 0.751 
 Unremarkable MRI scan 107 (56) 24 (80) 0.013 
Subjects with type 1 diabetesControl subjectsP
N 191 30  
Clinical characteristics    
 Female sex 101 (53) 17 (57) 0.699 
 Age, years 40.0 (33.0–45.1) 38.4 (31.4–43.2) 0.443 
 Diabetes duration, years 21.7 (18.3–30.9) — — 
 BMI, kg/m2 26.7 ± 4.2 24.5 ± 3.2 0.002 
 Systolic blood pressure, mmHg 130 ± 14 121 ± 11 0.001 
 Diastolic blood pressure, mmHg 77 (71–82) 76 (74–85) 0.387 
 HbA1c, % (mmol/mol) 8.2 ± 1.1 (66 ± 12) 5.1 ± 0.2 (33 ± 2) <0.001 
 Creatinine, µmol/L 68 (61–79) 74 (68–81) 0.067 
 Total cholesterol, mmol/L 4.4 (4.0–4.9) 4.6 (4.2–5.4) 0.178 
 LDL cholesterol, mmol/L 2.4 (2.0–2.9) 2.6 (2.3–3.3) 0.017 
 HDL cholesterol, mmol/L 1.50 (1.25–1.80) 1.46 (1.26–1.68) 0.362 
 Triglycerides, mmol/L 0.90 (0.68–1.38) 0.84 (0.69–1.26) 0.398 
 Antihypertensive medication 68 (36) <0.001 
 Statin therapy 42 (22) 0.002 
 Aspirin therapy 15 (7.9) 0.232 
 Albuminuria 30 (16) 0.018 
 Retinal photocoagulation 42 (22) 0.002 
 Coronary heart disease 1 (0.5) 1.000 
 Current smoking 15 (7.9) 5 (17) 0.118 
 Other autoimmune disease 63 (33) 6 (20) 0.149 
MRI findings    
 Cerebral SVD 67 (35) 3 (10) 0.005 
 CMBs 45 (24) 1 (3.3) 0.008 
 Number of CMBs   1.000 
  1, N (% of those with CMBs) 27 (60) 1 (100)  
  2, N (% of those with CMBs) 6 (13)  
  ≥3, N (% of those with CMBs) 12 (27)  
 Topography of CMBs    
  Strictly lobar, N (% of those with CMBs) 38 (84) 1 (100) 1.000 
  Strictly deep or infratentorial, N (% of those with CMBs) 3 (6.7) 1.000 
  Mixed, N (% of those with CMBs) 4 (8.9) 1.000 
 Cortical superficial siderosis — 
 Any WMH 44 (23) 2 (6.7) 0.051 
 Fazekas category 1 33 (17) 2 (6.7) 0.182 
 Lacunes 4 (2.1) 1.000 
 Stenosis of carotid arteries 2 (1.0) 1.000 
 Incidental findings 20 (10) 4 (13) 0.751 
 Unremarkable MRI scan 107 (56) 24 (80) 0.013 

Data are n (%), median (interquartile range), or mean ± SD unless otherwise indicated.

Participants with type 1 diabetes and CMBs more often had presence of albuminuria (27% vs. 12%, P = 0.021), were on antihypertensive medication (49% vs. 32%, P = 0.033), and had higher systolic blood pressure (135 ± 17 vs. 129 ± 13 mmHg, P = 0.009) (Supplementary Table 1). Only systolic blood pressure was independently associated with CMBs: OR for 1-mmHg increment 1.03 (95% CI 1.00–1.05); P = 0.035. Eight participants had >10 CMBs (range 10–105). These eight participants were older than 38 years; 50% had albuminuria, 75% history of retinal photocoagulation, and 88% hypertension; 25% were on aspirin therapy; and none used anticoagulant therapy.

Participants with WMHs (Fazekas ≥1) were significantly older (median 44.9 years [interquartile range 40.8–47.6] vs. 38.6 years (32.5–44.2); P < 0.001) and had a higher systolic blood pressure (mean ± SD 137 ± 15 vs. 129 ± 14 mmHg, P = 0.005) (Supplementary Table 2). Only age was independently associated with WMHs (OR for age per 1-year increment 1.11 [95% CI 1.04–1.19]; P = 0.003).

Cerebral SVD is more common in participants with type 1 diabetes than in healthy control subjects. CMBs especially are more prevalent and are independently associated with hypertension. Our results indicate that cerebral SVD starts early in type 1 diabetes but is not explained solely by diabetes-related vascular risk factors or the generalized microvascular disease that takes place in diabetes (7).

There are only small-scale studies on cerebral SVD, especially CMBs, in type 1 diabetes. Compared with the current study, one study with similar diabetes characteristics (i.e., diabetes duration, glycemic control, and blood pressure levels) as in the current study, but lacking a control population, showed a higher prevalence of WMHs, with more than half of the participants affected, but similar prevalence of lacunes and lower prevalence of CMBs (8). In another study, including 67 participants with type 1 diabetes and 33 control subjects, there was no difference in WMH prevalence but a higher prevalence of CMBs in participants with type 1 diabetes and retinopathy compared with control subjects (9).

In the current study, CMBs were not associated with retinopathy but were, on the other hand, associated with albuminuria, a strong marker of generalized microvascular disease. In addition, CMBs were independently associated with higher systolic blood pressure. Hypertension has also been associated with CMBs in the general population (10), but other studies show conflicting results (11). In type 1 diabetes, albuminuria and systolic blood pressure independently increase the risk for both ischemic and hemorrhagic stroke (12).

Cerebral amyloid angiopathy and hypertensive vasculopathy are the two most common pathogenetic processes underlying cerebral SVD. Both diseases cause microaneurysms, vessel disruption, microthrombosis, and arteriolosclerosis, leading to permeable and disrupted microvasculature (3). In the current study, CMBs were mainly observed in the lobar brain regions, which has been associated with cerebral amyloid angiopathy, a condition generally affecting the elderly, whereas CMBs in the deeper parts associate with hypertensive vasculopathy (3). It is, however, unlikely that the lobar predominance of CMBs in our younger participants would indicate cerebral amyloid angiopathy. The majority of those with several CMBs had hypertension and presence of microvascular diabetes complications, indicating a more generalized vasculopathy, although CMBs were not associated with other vascular risk factors, such as diabetes duration, BMI, glycemic control, or smoking. Lobar CMBs mostly lie on the proximal course of medullary end arteries supplying the white matter of the brain. We hypothesize that CMBs represent pathology similar to that observed in diabetic retinopathy, e.g., rupture of a microaneurysm (13). Chronic inflammation or some factor associated solely with type 1 diabetes itself, e.g., autoimmunity, could also contribute to the increase in CMBs observed in our study.

We showed a trend toward more WMHs in type 1 diabetes. Previous studies in type 1 diabetes show conflicting results, with some reporting more WMHs in type 1 diabetes (14) and others not (9,15). Most WMHs in our study were classified as Fazekas category 1, and only four participants had lacunes—all of them with type 1 diabetes.

The strengths of our study include standardized enrollment of participants, age- and sex-matched healthy control subjects, and standardized imaging and assessment. Although our study is the largest on type 1 diabetes and SVD prevalence to date, we did not have sufficient power to detect minor differences between the groups. The cross-sectional study setting also limits the interpretation of causal relationships.

We conclude that cerebral SVD is more common in subjects with type 1 diabetes than in healthy control subjects. Future studies will focus on longitudinal development of SVD in type 1 diabetes and the associations with brain health and cognition.

Acknowledgments. The authors acknowledge the skilled technical assistance of Anna Sandelin, Jaana Tuomikangas, and Mira Korolainen (research nurses in the FinnDiane Study Group). They also gratefully thank Pentti Pölönen, Department of Radiology, HUH, for performing the MRI scans. They are indebted to Markku Kaste, Department of Neurology, HUH, for help in the initiation of the study.

Funding. The FinnDiane Study was supported by grants from the Folkhälsan Research Foundation, Academy of Finland, Wilhelm and Else Stockmann Foundation, Liv och Hälsa Society, Novo Nordisk Foundation, and Päivikki and Sakari Sohlberg Foundation and by HUH state research funding (EVO governmental grant). L.M.T. was supported by personal grants from the Medical Society of Finland and the Dorothea Olivia, Karl Walter and Jarl Walter Perklén Foundation. D.G. was supported by the Biomedicum Helsinki Foundation, the Finnish Medical Foundation, and the Swedish Cultural Foundation in Finland. P.S. was supported by Silmäsäätiö Foundation. J.P. was supported by Diabetes Wellness Finland and the Diabetes Research Foundation.

None of funding bodies had any role in the study design; collection, analysis, or interpretation of data; writing of the manuscript; or the decision to submit the manuscript for publication.

Duality of Interest. P.S. has received lecture honoraria from Bayer and Santen. T.T. is an advisory board member of Boehringer Ingelheim, Bayer, Pfizer, and Lumosa Therapeutics and has received speaker honoraria from the University of Donau (Austria) and the Finnish Neurological Association. P.-H.G. has received lecture honoraria from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Elo Water, Genzyme, Medscape, Merck Sharp & Dohme (MSD), Novartis, Novo Nordisk, and Sanofi and is an advisory board member of AbbVie, Boehringer Ingelheim, Eli Lilly, Janssen, Medscape, MSD, Novartis, Novo Nordisk, and Sanofi. No other potential conflicts of interest relevant to this article were reported.

Author Contributions. L.M.T., S.S., D.G., R.L., C.F., P.S., S.H.-H., T.T., O.S., J.P., J.M., and P.-H.G. contributed to the study design and acquisition of data, as well as the interpretation of data. L.M.T. and S.S. had the main responsibility for analyzing data and writing the first draft of the paper. D.G., R.L., C.F., P.S., S.H.-H., T.T., O.S., J.P., J.M., and P.-H.G. critically revised the manuscript. P.-H.G. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Supplementary data