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Original Paper

Free Access

Brain Microvasculature Involvement in ANCA Positive Vasculitis

González-Suárez I.a · Arpa J.a · Ríos-Blanco J.J.b

Author affiliations

aNeurology Department, Hospital of Clínico San Carlos, C/Professor Martin Lagos, and bInternal Medicine Department, Hospital Universitario La Paz, Madrid, Spain

Corresponding Author

Inés González-Suárez

Hospital Universitario San Carlos

C/Professor Martin Lagos

ES-28006 Madrid (Spain)

E-Mail igonsua@gmail.com

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Cerebrovasc Dis 2016;41:313-321

Abstract

Objective: Endothelial dysfunction is associated with arterial stiffness, a factor that is increasingly recognised as an important determinant of cardiovascular risk. High-flow organs such as the brain and kidneys are particularly sensitive to excessive pressure and flow pulsatility. High, local blood flow is associated with low microvascular impedance, which facilitates the penetration of excessive pulsatile energy into the microvascular bed leading to tissue damage. Systemic endothelial dysfunction and arterial stiffness have been demonstrated in peripheral vessels in associated vasculitis (AAV). Although, the brain involvement is not infrequent in AAV, it has not been evaluated previously. Our aim is to evaluate the involvement of the brain microvasculature in AAV. Methods: Twenty-three patients with inactive AAV were studied. Brain blood flow was assessed by transcranial Doppler (TCD) and single-photon positron emission tomography (SPECT), structural brain involvement by brain MRI and cognitive scores by Montreal Cognitive Assessment (MoCA) test. Results: Lower mean flow velocity (MFV) was associated to altered SPECT perfusion, higher white matter changes (WMC), lower MoCA scores and younger age (p < 0.05). Middle cerebral artery pulsatility index (MCA-PI) was related to hypertension, diabetes, lower scores on MoCA, increased vasculitis damage index (VDI) and perfusion impairment in SPECT (p < 0.05). These data were reproduced for all intracranial arteries. Up to 88.9% of patients had WMC on MRI. A higher lesion load was associated with age, decreased MoCA and fewer MFV with higher PI. The multivariable linear regression analysis showed that the greater the lesion loads, greater the bifrontal atrophy, MCA-PI and lower MoCA scores. Up to 60.9% of patients presented a decreased MoCA score (p = 0.012). It appeared to be related to VDI (p = 0.04), WMC (p = 0.004) and altered SPECT (p = 0.05). Conclusions: The alterations in brain perfusion SPECT, the presence of white matter lesions on MRI, as well as increased PI and RI with lower MFV of the cerebral vessels in TCD suggest the presence of microangiopathy in asymptomatic AAV that could lead to cognitive impairment.

© 2016 S. Karger AG, Basel


Introduction

Anti-neutrophil cytoplasmic antibodies (ANCA)-associated vasculitis (AAV) is a group of autoimmune disorders characterized by inflammation and necrosis of the small-sized vessels (capillaries, venules, arterioles and small arteries) [1]. The AAV includes granulomatosis with polyangiitis (GPA), eosinophilic GPA (EGPA) and microscopic polyangiitis (MPA) [1]. Although AAV may involve multiple organs, the central nervous system (CNS) is rarely affected [2,3,4]. Several mechanisms have been postulated as pathogenic in the CNS injury, the vasculitis involvement of intracranial vessels being the most accepted [3].

Endothelium is a highly specialized cell and is considered an important step in the progression of atherosclerosis. Impaired endothelium vasomotor response is a diffuse process resulting in abnormal regulation of blood vessels tone of several atheroprotective effects of the normal endothelium. Consequently, increased arterial stiffness causes a reduced damp of the arterial waveform and increased pulsatility of cerebral blood flow. Several studies have suggested a relationship between increased middle cerebral artery pulsatility index (MCA-PI) and white matter changes (WMC) or lacunar ischemia in patients with hypertension [5] and diabetes [6]. Microvascular ischemia is manifested as leukoaraiosis and brain infarcts and ultimately, as cognitive impairment.

We hypothesized that chronic inflammation in AAV leads to intracranial arterial stiffening, with secondary local hypoxia leading to microvascular damage and impaired function.

Patients and Methods

A sequential cohort of consecutive patients aged 18-85 with positive ANCA vasculitis was recruited from the internal medicine and nephrology department at the University Hospital La Paz. All patients fulfilled the American College of Rheumatology classification criteria [7,8] and/or the international consensus conference definitions for GPA, GEPA and PAM vasculitis [1]. Exclusion criteria were age under 18, failure to meet the diagnostic criteria, exclusively renal disease and active disease defined as BVAS ≥1. Complete remission was defined as the absence of attributed symptoms to vasculitis for a period of 6 months [9].

Demographic, disease information, cardiovascular risk factors (hypertension, diabetes mellitus (DM), atrial fibrillation, smoking status, dyslipidemia) and immunosuppressive and antiplatelet/anticoagulation therapy data were collected prospectively of each patient. The complete neurologic history (polyneuropathy/mononeuritis, stroke, cognitive impairment, seizures and/or cranial neuropathy) was recorded. A neurologic examination and the Montreal Cognitive Assessment (MoCA) as screening test for cognitive impairment completed the evaluation [10].

Transcranial Doppler (TCD) examination was performed by a single experienced sonographer using 2-MHz frequency ultrasound probe (Viarys Sonora). A standardized protocol [11] was used to evaluate each artery of the Willis Polygon (MCA, anterior cerebral artery (ACA) and posterior cerebral artery (PCA)) and the vertebro basilar territory (vertebral artery (VA) and basilar artery (BA)). Individual Doppler spectra were recorded for each segment with mean flow velocity (MFV), Gosling PI and resistance index (RI) calculated automatically by the software. For each vessel, 2 measures of the proximal portion were taken for analysis. MFV, PI and RI were compared to the reference values used in our laboratory [12].

The carotid ultrasonography (DTSA) was performed using a portable ultrasound Toshiba Inc. Model ‘SSA-660A' (Xario) with a 7.5 MHz linear transducer. The intima-media thickness (IMT) was defined as the distance between light carotid intima-media-adventitia and the distal wall interface determined approximately 1 cm proximal to the bulbus at 3 different positions. The Spanish societies of neurosonology (SONES) values were taken as reference [13]. The atherosclerotic plaques were defined as focal thickening of IMT ≥1.5 mm or greater than 50% of the adjacent IMT [13,14]. The PI of the internal carotid artery (ICA-PI) was automatically calculated by the software.

1.5 tesla MRI was assessed with a basic acquisition protocol (sagittal T1-weighted (T1-W), axial and coronal T2-weighted (T2-W), axial fluid attenuated inversion recovery (FLAIR), axial T2-W*, axial DW and T1-W post contrast). An expert neuroradiologist evaluated the images independently. Cerebral vascular pathology was studied following the recommendations stipulated by the consortium of the National Institute of Neurological Disorders and Stroke (NINDS) and the Canadian Stroke Network (CSN) [15].

Periventricular and deep white matter disease were graded according to the Fazekas scale [16]. White matter abnormalities (WMA) on MRI were considered ill-defined hyperintensities >5 mm on both T2 and FLAIR. The lesions were classified into 3 categories: grade 1 (mild): single lesions smaller than 10 mm and/or confluence of lesions with a diameter <20 mm; grade 2 (moderate): single lesions 10-20 mm and hyperintense areas linked by ‘jumpers' greater than 20 mm; grade 3 (severe): single lesions or confluent exceeding 20 mm diameter. Also, a semiquantitative analysis based on Age-Related White Matter Changes (ARWMC) scale was applied [17] (0, no lesions; 1, focal lesions; 2, beginning confluence; and 3, diffuse involvement rated in 5 different regions).

The single-photon positron emission tomography (SPECT) study was performed within 30 min after intravenous administration of tracer 99mTc-HMPAO (dose: 720 MBq). The images were analysed and classified by a qualitative visual scale into 3 categories: I, no injuries; II, focal hypoperfusion; III, diffuse hypoperfusion (patchy pattern).

For each participant, an informed consent was obtained. The local Ethics Committee gave approval for the study. The investigations were consistent with the principles outlined in the Declaration of Helsinki.

The statistical analysis was performed with the SPSS program (Statistical Package for Social Science, SPSS, Chicago, Ill., USA). Qualitative variables are expressed as frequency, quantitative by mean and SD. The comparison between 2 groups was performed using the χ2 test or Fisher's exact test for dichotomous variables expressing effects OR with 95% CIs. The Mann-Whitney U test or Kruskal-Wallis test was used to compare quantitative with qualitative variables. To test the sample mean against a theoretical value test Student t of a sample was used for unknown variances. Linear regression models were adjusted to account for factors associated with the outcome variables, MoCA, ARWMC and Doppler. Biologically relevant variables were included. The results are expressed with the parameter model (beta or slope) and 95%. In all contrasts, the null hypothesis p < 0.05 was rejected.

Results

Twenty-three patients were enrolled. Demographic data are listed in table 1. Nine patients were GPA (39.1%), 6 EGPA (26.1%) and 8 MPA (34.8%). Thirteen patients (56.5%) of the study cohort displayed involvement of the CNS and/or peripheral nervous system in the course of their VAA.

Table 1

Demographic data

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Twenty patients were evaluated with TCD. No data of intracranial stenosis were found. The MFV, PI and RI results of each artery are summarized in table 2. The MFV was found to be below normal values in all the vessels (p < 0.005); PI were increased statistically in ACA, VA and BA.

Table 2

TCD values of the anterior and posterior cerebral circulation and statically significance when compared to the reference value

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MRI was performed in 19 patients; 88.9% patients presented WMA. The distribution according to Fazekas score: absent: 2 patients (10.5%), mild: 10 patients (55.6%), moderate: 4 patients (21.1) and severe: 2 patients (10.5%). There were no differences between vasculitis (p = 0.53). The mean score in ARWMC was 4.74 (SD 4.32).

The presence of degrees Fazekas ≥2 was associated with older age (p = 0.02) lower scores on MoCA (p = 0.02), lower MFV-MCA (p = 0.02) and MFV-PCA (p = 0.04) and PCA-PI high values (p = 0.04) and BA-PI (p = 0.01), showing a trend in the rest of the arteries (table 3).

Table 3

Univariate analysis for Fazekas, MoCA and SPECT

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Twenty-two patients completed the MoCA test (one excluded by low education level); 14 patients (60.9%) scored below the cutoff (sample mean 23.91 (SD 3.56); p = 0.012). No differences between the AAV (p = 0.63) or ANCA (p = 0.97) were observed. The presence of an altered MoCA was associated with hypertension (p = 0.01, OR 0.21, 95% CI 0.03-1.25), higher vasculitis damage index (VDI, p = 0.04), Fazekas ≥2 (p = 0.02, OR 0.46, 95% CI 0.24-0.87) and perfusion defects on SPECT (p = 0.05, OR 0.42, 95% CI 0.17-1.06). Comparing the MoCA values with the TCD, a trend to decreased MFV in MCA, ACA and BA is observed, while increased PI values are observed in patients with perfusion defects. Eight patients had normal perfusion by means of SPECT (47.1%), 7 were focal hypoperfusion (41.2%) and 2 a diffuse hypoperfusion (11.8%). All the patients presented parietal deficits, bilaterally 5/7 and 2/7 in left hemisphere. Perfusion defects were found to be more frequent in association with hypertension (p = 0.03, OR 3.25, 95% CI 1.44-7.35), hypertriglyceridemia (p = 0.002), lower MFV-MCA (p = 0.04) and MFV-VA (p = 0.03), while a trend was observed in the rest of the vessels. An increased WMC was found in patients with abnormal perfusion; ARWMC score was 6.11 (SD 4.65) in patients with abnormal perfusion vs. 2.63 (SD 3.11) in patients with normal SPECT (p = 0.08).

Multivariate Analysis

Linear regression was performed with MoCA, ARMWC, MFV and PI of all vessels. The model influences 95.3% of the MoCA variability (table 4). This model predicts that every one-point increase in MoCA scale is associated with an increase of 0.160 years (p = 0.000), a decrease in of 0.464 points of VDI (p = 0.003), a decrease of 0.39 mg/dl in low-density lipoprotein (LDL, p = 0.000), a reduction of 0.905 units in ARWMC score (p = 0.000) and diminution of 2.883 units in ICA-PI (p = 0.030) and non-smoking (p = 0.000).

Table 4

Multivariate analysis for ARWMC and MoCA

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The ARWMC-model explains the 72.5% of the variability (table 4). For each incremental point in ARWMC, there is a decrease in the MoCA score of 0.539 points (p = 0.038), a decrease of 0.027 mg/dl of LDL (p = 0.077) and an increase of MCA-PI in 5.760 units (p = 0.069) and higher brain atrophy (p = 0.009).

MFV-MCA variability up to the extent of 99.9% is explained by the variables included in the model (table 5). Higher MFV-MCA values are related to hypertension (p = 0.033), diabetes (p = 0.020), non-smoking (p = 0.021), male sex (p = 0.021) and normal SPECT (p = 0.022). For each increase in MFV-MCA is observed a decrease of 0.142 mg/dl in triglycerides (TG, p = 0.035), an increase of 0.163 mg/dl of LDL (p = 0.023), an increase of 1.604 points in VDI (p = 0.023), a decrease of 2.444 points in MoCA (p = 0.041), a reduction of 1.478 in the ARWMC score (p = 0.032) and a diminution of 108.386 units in ICA-PI (p = 0.021).

Table 5

Multivariate analysis for MFV-MCA and MCA-PI

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The MCA-PI model explained the 96.8% of the variability (table 5). Increased MCA-PI are related to HTA (p = 0.003), DM (p = 0.015), female (p = 0.023), and abnormal SPECT (p = 0.003). For each increase in MCA-PI is observed a decrease of 0.040 years (p = 0.006), an increase of 0.001 months in disease duration (p = 0.013), an increase of 0.013 points in VDI (p = 0.088), a decrease of 0.059 points in MoCA; (p = 0.040), a decrease of 0.001 mg/dl of LDL (p = 0.058) and of 0.007 mg/dl of TG (p = 0.007) and an increment of 1.560 units of ICA-PI (p = 0.001).

The linear regression analysis was performed in all the intracranial vessels (table 6). In all the vessels, a greater MFV is associated with greater age, lower ARWMC, normal SPECT, lower ICA-PI and greater MoCA. Greater PI and RI are associated with greater.

Table 6

Summary of the TCD multivariate analysis

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Discussion

This study shows for the first time the presence of cerebral microvascular impairment in AAV and that these changes are related to cognitive impairment. Our data are consistent with previous studies, which demonstrated the presence of peripheral endothelial injury and vasoreactivity dysfunction in AAV [18,19,20,21]. However, we demonstrated that these alterations are not only present in peripheral circulation but also in the intracranial vasculature.

Endothelium is a highly specialized cell [22,23]; it is involved in numerous physiological processes, including regulation of inflammatory and immune responses, thrombosis, adhesion, permeability and angiogenesis [22]. Healthy vascular endothelium synthesizes vasoactive mediators, including nitric oxide (NO), prostacyclin and endothelium-derived hyperpolarizing factor (EDHF). In vitro and in vivo evidence suggest a role for NO in vascular homeostasis, vascular tone and cerebral blood flow [23,24,25,26]. Endothelial dysfunction entails an impaired vasomotor response with decreased vasodilation and increased endothelium-dependent contraction reflecting as arterial stiffness, and other processes that participate in vascular inflammation and increased adhesion and platelet aggregation [27,28]. There is growing evidence that endothelial dysfunction may influence the progression of atherosclerotic lesions [29,30]. Certain degrees of endothelial dysfunction may play an important role in the pathogenesis of various cerebrovascular diseases such as Alzheimer's disease, epilepsy and stroke [22,31,32,33].

Endothelial dysfunction is present in AAV [18,19,20,21] with impaired vascular reactivity in both large and small-size vessels even in chronic phases of the disease [18,19]. Several mechanisms are proposed for endothelial involvement in AAV: endothelial function suppressed by pro-inflammatory cytokines [34], the neutrophil/ANCA interaction close to the vessel wall as a triggering of endothelial injury [35] and the direct endothelial cell toxicity by LDL oxidation promoted by the proinflammatory microenvironment [36]. These alterations could lead to cerebral small vessel atherosclerosis and ischemia reflecting as WMA in MRI.

The TCD evaluation showed decreased MFV with increased PI in all intracranial arteries. Previous studies have demonstrated associations between decreased MFV and older age [37], mild cognitive impairment [38], Alzheimer or vascular dementia [39]. In our study, higher MFV is associated with normal SPECT perfusion, fewer WMA, higher MoCA scores and older age. PI is considered the minimal and maximal arterial input resistance and impedance, respectively, and is accepted as a simple, robust and non-invasive surrogate measure of arterial impedances; it increases with increased vascular tone and decreases with vasoconstriction and vasodilation [40]. An increase in resistance distal to the site of insonation results in increased blood pulsatility [11]. Previous studies have shown that greater PI is associated with age [41,42], hypertension [43], vascular [44] and Alzheimer dementia [44]. Furthermore, a recent study has demonstrated that the presence of low MFV and high PI is associated with diffuse intracranial disease independent of other stroke risk factors [45]. In our study, PI has been shown to be related to hypertension, DM, lower scores on MoCA, increased VDI and perfusion impairment in SPECT. These data could be reproduced for all intracranial arteries and the RI.

Furthermore, up to 88.9% of our patients have had white matter lesions on MRI. White matter alteration is the most common biomarker of small-vessel disease [46]. Alterations in white matter reflect arterial processes by affecting small penetrating vessels [47,48,49,50]. Histopathological examination of these lesions show a partial replacement of smooth muscle by fibrous tissue that increases the thickness of the arterial wall, decreasing light, and thus its elastic properties [51]. Previous studies have demonstrated that higher MCA-PI may be correlated with small vessel disease including periventricular hyperintensities, deep white matter hyperintensities, lacunar infarcts and pontine hyperintensity [46,47,52,53]. Moreover, higher MCA-PI was able to predict higher lesion load on MRI [46,47]. Our study is in agreement with those previously reported, demonstrating that in AAV patients, higher lesion load was associated with age, low MoCA-score and decreased MFV/high PI probably demonstrating the presence of an alteration in the mechanoelastic properties of intracranial vessel and reduced compliance of these arteries.

Several studies have demonstrated the relationship between WMA and mild cognitive impairment [54,55]. Up to 60.9% of our patients presented decreased MoCA score (p = 0.012). It appeared to be related to VDI (p = 0.04), ARWMC (p = 0.004), and altered SPECT (p = 0.05).

Our work also includes limitations due to the small size of the cohort due to the absence of controls. However, the data and the fitted model were very homogeneous despite the sample size, suggesting the presence of microangiopathy that may cause changes in brain perfusion and cognitive decline even in the absence of systemic disease activity.

Conclusions

The lower MFV and increased PI in AAV Doppler, the presence of white matter lesions on MRI and the altered perfusion by SPECT suggest the existence of an impairment of the intracranial small vessels circulation. Our hypothesis is that chronic inflammation causes endothelial injury and altered vascular reactivity with consequent increased peripheral resistance demonstrated by the increased PI and decreased MFV. These alterations involve cerebral hypoxia demonstrated by WMA in MRI and perfusion abnormalities on SPECT.

Acknowledgements

The statistical analysis was conducted by Cristina Fernandez MD, PhD. Hospital Clinico San Carlos.

Financial Support

No grants or financial support have been received.

Disclosure Statement

The authors confirm there are no conflicts of interest.


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  52. Pullicino P, Ostrow P, Miller L, Snyder W, Munschauer F: Pontine ischemic rarefaction. Ann Neurol 1995;37:460-466.
  53. Scarpelli M, Salvolini U, Diamanti L, Montironi R, Chiaromoni L, Maricotti M: MRI and pathological examination of post-mortem brains: the problem of white matter high signal areas. Neuroradiology 1994;36:393-398.
  54. Breteler MM, van Amerongen NM, van Swieten JC, Claus JJ, Grobbee DE, van Gijn J, et al: Cognitive correlates of ventricular enlargement and cerebral white matter lesions on magnetic resonance imaging. The Rotterdam study. Stroke 1994;25:1109-1115.
  55. van Swieten JC, Staal S, Kappelle LJ, Derix MM, van Gijn J: Are white matter lesions directly associated with cognitive impairment in patients with lacunar infarcts? J Neurol 1996;243:196-200.

Author Contacts

Inés González-Suárez

Hospital Universitario San Carlos

C/Professor Martin Lagos

ES-28006 Madrid (Spain)

E-Mail igonsua@gmail.com


Article / Publication Details

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Abstract of Original Paper

Received: October 20, 2015
Accepted: December 30, 2015
Published online: February 18, 2016
Issue release date: April 2016

Number of Print Pages: 9
Number of Figures: 0
Number of Tables: 6

ISSN: 1015-9770 (Print)
eISSN: 1421-9786 (Online)

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