Factors associated with increased white matter hyperintense lesion (WMHI) load in patients with systemic lupus erythematosus (SLE)

Abstract

Introduction

White matter hyperintense (WMHI) lesions are the most common finding in magnetic resonance imaging (MRI) of the brain in patients with systemic lupus erythematosus (SLE).

Objective

The objective of this article is to determine the clinical factors associated with an increase in WMHI lesion load among SLE patients.

Method

A total of 83 SLE patients with MRI of the brain from National University of Malaysia Medical Centre were included. The WMHI lesion load was determined using the Scheltens score and Fazekas scale, and their distribution was divided into the deep white matter (DWMHI) and periventricular (PVH) regions. The clinical correlates of WMHI lesions were initially determined using univariate analyses and subsequently multivariable regression analyses were performed to determine the independent factors of increased WMHI lesion load.

Results

MRI of the brain of 46 patients who had WMHI lesions were compared with 37 patients with normal MRI. We found significant association between the presence of WMHI lesions and age, presence of cerebral infarcts, positive antiphospholipid antibody (aPL), active disease, neuropsychiatric lupus (NPSLE) and disease damage. Age, SLEDAI scores, cerebral infarcts and disease damage were significantly associated with higher DWMHI and PVH Scheltens scores. Meanwhile, patients with active lupus nephritis (LN), lower serum albumin and more severe proteinuria were associated with larger Fazekas WMHI lesions. Multivariable regression analysis revealed that the independent factors associated with presence of WMHI lesions were positive aPL and SLEDAI scores (p < 0.05). Higher WMHI Scheltens scores in both DWMHI and PVH were associated with presence of cerebral infarct but higher PVH lesion load was significantly associated with active SLE disease.

Conclusion

Presence of WMHI lesions in SLE was significantly associated with cerebral infarcts, aPL and high general SLE activity, suggesting both inflammation and ischaemia as the underlying pathology of these lesions.

Keywords

Lupus anticoagulant neuropsychiatric lupus systemic lupus erythematosus

Introduction

Magnetic resonance imaging (MRI) remains the most important neuroimaging tool in diagnostic work-up for systemic lupus erythematosus (SLE) patients with neurological manifestations. White matter hyperintensity (WMHI) lesions are striking abnormalities that are often found on T2-weighted and fluid-attenuated inversion recovery (FLAIR) images in lupus patients. These lesions have been reported to be present in up to 70% of SLE patients.¹ Despite being the most prevalent MRI finding, they are often non-specific as these lesions may occur without underlying neuropsychiatric lupus (NPSLE).^2,3

WMHI lesions are divided into two classes depending on their location: deep and periventricular WMHI. Deep white matter lesions (DWMHI) are located at the end and border zones of arterial perfusion of the white matter. Meanwhile, periventricular white matter lesions (PVH) are located near the ventricular ependyma, particularly at the anterior and posterior horns of the lateral ventricles. Both of these lesions have different underlying aetiologies as DWMHI are believed to be primarily driven by arterial ischaemia and are strongly correlated with vascular risk factors. On the other hand, the association between PVH and vascular risk factors is weaker⁴ as they can be non-ischaemic in origin, which include periventricular venous collagenosis, and ependymal leakage due to endothelial dysfunction.^4,5

The exact pathology of these non-necrotic hyperintensity or non-specific WMHI lesions in SLE is largely unknown as the majority of histopathological studies involved mainly patients with NPSLE symptoms only. However, it is likely that the presence of WMHI lesions in SLE are multifactorial as the white matter lesions can be produced by small-vessel angiopathy related to endothelial dysfunction,⁶ vasculitis,⁷ microthromboemboli⁸ and demyelination.⁹ Histopathologically, these lesions represent areas of gliosis,¹⁰ demyelination¹¹ and loss of axons.⁵

In patients with SLE, the clinical significance of the presence of incidental non-necrotic WMHI lesions is still unclear but various studies have shown that these lesions are associated with fatigue,¹² headache, cognitive impairment, seizures, and Raynaud’s phenomenon.¹³ Positive antiphospholipid antibodies (aPL)^14–16 and hypertension¹³ were also reported to be significantly associated with WMH lesions.

There have been only a few studies which involved patients with isolated white matter lesions¹³ and several other studies included patients with various other cerebral pathologies¹⁷ or patients with NPSLE only.¹⁸ Therefore, this study was performed to determine the various associated factors of increase WMHI lesions among our multi-racial Asian lupus cohort.

Methodology

SLE patients

Consecutive SLE patients who had brain MRI at the National University of Malaysia Medical Centre (UKMMC) from June 2007 until June 2016 were reviewed. All patients fulfilled the revised American College Rheumatology (ACR) 1997 criteria for SLE.¹⁹ The MRI protocol included sagittal T1-weighted, axial T1-weighted, axial T2-weighted, coronal fluid-attenuated inversion recovery (FLAIR) sequences, followed by diffusion-weighted imaging (DWI). In these individuals, T2-weighted and FLAIR images were screened for the presence of WMHI lesions, which were defined as areas with increased signal intensity in the white matter on T2 and FLAIR sequences. These lesions were generally ill defined, small, had no cavitations and could not be related to any types of pathology such as mass effects, other than non-specific WMHI.^20,21 The WMHI lesions were differentiated from acute infarcts by the presence of diffusion restriction in the DWI in the latter condition.²² Apart from that, presence of old infarcts were distinguished from WMHI lesions by having more distinct, sharp margins, rounded shape, and high signal on T2 but reduced signal centrally on FLAIR, indicating a cerebrospinal fluid (CSF)-containing cavity.²³ This study was approved by the Research Ethics Committee, National University of Malaysia (FF-2016-436).

SLE patients with normal brain MRI were included into the study as controls. Subsequently the visual and semi-quantitative rating of the WMHI lesions were performed. All MRI scans were read by an experienced neuroradiologist who was blinded to the demographic or clinical data.

Visual and semi-quantitative rating of WMHI lesions

Assessments of the WMHI lesions’ severity were performed using the semi-quantitative visual rating of the Scheltens score²⁴ and Fazekas scale,²⁵ which are frequently used in research. Both scales have been validated histopathologically^5,26 and have good agreement with quantitative volumetric measurements.²⁷

The total numbers on the WMHI lesions were traced on T2 proton density (PD)-weighted images and they were evaluated using Scheltens score in four regions: (1) the periventricular region (PV), (2) the subcortical and deep white matter of the frontal, parietal, temporal and occipital areas (FPTOs), (3) the basal ganglia (BG) and (4) the infratentorial region (IT).²⁴ The total score for the PVH lesions ranged from 0 to 9, for the DWMHI lesions from 0 to 24, for basal ganglia WMHI lesions ranged from 0 to 30, and for infratentorial ranged from 0 to 24. The total WMHI lesions score for the Scheltens scale for each participant thus ranged from 0 to 84, with a higher score indicating a larger amount of total WMHI lesions.

With the brain MRI with FLAIR sequences, we applied the visual rating scales of Fazekas of the WMHI lesions in two regions: (1) the periventricular area and (2) white matter area. These lesions were graded from 0 to 3, depending on size and confluence of the lesions as below.²⁵

(1) PVH

0 = absent

1 = “caps” or pencil-thin lining

2 = smooth “halo”

3 = irregular periventricular signal extending into the deep white matter

(2) DWMHI

0 = absent

1 = punctate foci

2 = beginning confluence

3 = large confluent areas

All ratings were performed by an experienced neuroradiologist who was blinded to the patients’ clinical data.

SLE disease characteristics

The disease characteristics (disease duration and organ or system involvement) during the time of the brain MRI scans were obtained from the medical records. Active neuropsychiatric involvement at the time of MRI imaging was defined according to the ACR nomenclature and case definitions for NPSLE.²⁹

Presence of aPL was defined as either lupus anticoagulant positive and/or anticardiolipin antibody (aCL) titre of more than 20 GPL, and/or B2 glycoprotein-I positive. Presence of comorbidities, e.g. cardiovascular disease, diabetes mellitus, hypertension and hyperlipidaemia, were also recorded.

Disease activity and disease damage assessment

Disease activity during the MRI was measured using the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI).²⁹ The index has been validated and shown to be reliable and sensitive to changes in disease activity in SLE.^30–32 It includes 24 clinical features and laboratory variables from different organs or system involvement, e.g. renal, haematological, neuropsychiatric, mucocutaneous, musculoskeletal, serositis, vasculitis and fever. These variables are weighted by the type of manifestations and disease activity scores may range from 0 to 105.²⁹ Patients with SLEDAI score ≥4 were categorized into the active disease group.³³

Cumulative SLE-related damage at the time of MRI was determined by the Systemic Lupus International Collaborating Clinics/ACR (SLICC/ACR) Disease Damage index.³⁴ It was developed and validated to measure accumulated organ damage from either the disease process or its sequelae, in 12 organ systems.³⁴ Patients were categorized into presence of damage if the score was 1 or more (SDI ≥ 1), and absence of damage if the score was 0 (SDI = 0).

Statistical analysis

All normally distributed numerical data were expressed as mean ± SD and non-normally distributed data were expressed as median ± interquartile range (IQR). Comparisons were made between SLE patients with presence of WMHI lesions and without WMHI lesions. Subsequently, statistical analyses were performed to determine the associated factors of an increase in WMHI lesions assessed by Scheltens scores and Fazekas classification. Group differences among subject characteristics and associated factors were tested for statistical significance using the t-test or analysis of variance (ANOVA) (for normally distributed continuous data), Mann-Whitney U test (for non-normally distributed continuous data) and χ² test (categorical data). Bivariate Pearson (for normally distributed continuous data) and Spearman (for non-normally distributed data) were performed to determine the factors which correlated with the number of WMHI Scheltens scores. Significance was taken as p ≤ 0.05.

Multivariable binary logistic regression analysis was performed to determine the odds ratio of each independent predictor of presence of WMHI lesions in SLE patients. In the binary logistic regression analysis, all factors which were found to be associated with presence of WMHI in the univariate analyses with p < 0.01 were included.

Subsequently, multiple regression analyses (stepwise method) were used to determine the independent factors which were correlated with the Scheltens scores of DWMHI, PVH and total WMHI lesions. All variables in the univariate analyses were included in the multiple regression analyses.

Due to the small sample size in each category of the Fazekas scale, we did not proceed to any multivariate analysis. All statistical analyses were performed using the SPSS program version 18.0.

Results

A total of 88 patients were identified to have MRI brain performed from June 2007 until June 2016. However, two of them were excluded due to MRI finding of brain abscess and tuberculoma. Meanwhile three of the patients were excluded in view of the inability to retrieve the MRI images from the electronic medical records. Ultimately a total of 83 patients were includ into the study and 46 (55.4%) of them had WMHI lesions. The average age at the time when the MRI was performed was 35.9 ± 12.3 years and more than half of them were Malays (n = 53, 63.9%) followed by Chinese (n = 25, 30.1%) and Indians (n = 5, 6.1%). More than half of the cohort had haematological manifestations (n = 55, 66.3%), followed by musculoskeletal (n = 54, 65.9%), LN (n = 37, 45.1%), mucocutaneous (n = 36, 43.9%), NPSLE (n = 36, 43.9%) and serositis (n = 8, 9.8%).

The main reason for the MRI brain to be performed was investigation of headache (n = 32, 38.5%), followed by visual disturbances (n = 12, 14.6%), seizure or epilepsy (n = 11, 13.3%), psychosis (n = 5, 6.1%), cognitive dysfunction (n = 5, 6.1%), investigation for limb weakness (n = 5, 6.1%), cerebrovascular accidents (n = 3, 3.7%), mood disorders (n = 2, 2.4%), cranial neuropathy (n = 2, 2.4%), acute confusional state (n = 2,2.4%), abnormal movement/dyskinesia (n = 1, 1.2%), transient global amnesia (n = 1, 1.2%), facial numbness (n = 1, 1.2%) and transverse myelitis (n = 1, 1.2%). Twenty-six patients (31.7%) had hypertension, 23 (28%) had dyslipidaemia while only two of them (2.4%) had steroid-induced diabetes mellitus. Two patients were ex-smokers (2.4%) and no patients in this lupus cohort had underlying cardiovascular disease.

Presence of WMHI lesions was significantly associated with higher age, positive aPL, presence of disease damage, higher SLEDAI score, NPSLE, and presence of cerebral infarcts (all p < 0.05). Table 1 illustrates the demographic and disease characteristics between SLE patients with and without WMHI lesions.

Table 1

Clinical and disease characteristics of SLE patients with white matter hyperintensity (WMHI) lesions and without WMHI

Parameters	WMHI present (n = 46)	Normal MRI (n = 37)	p
Race,% (n)
Malay (n = 53)	63.0 (29)	64.9 (24)	0.19
Chinese (n = 25)	34.8 (16)	24.3 (9)
Indian (n = 5)	2.2 (1)	10.8 (4)
Gender,% (n)
Female (n = 76)	87.0 (40)	97.3 (36)	0.09
Male (n = 7)	13.0 (6)	2.7 (1)
Age, years (mean ± SD)	38.4 ± 13.8	33.0 ± 10.1	0.045
Disease duration, years (mean ± SD)	5.0 ± 5.1	4.1 ± 4.8	0.42
Hypertension,% (n)	34.8 (16)	27.0 (10)	0.30
Dyslipidaemia, % (n)	30.4 (14)	24.3 (9)	0.54
Positive aPL,% (n)	39.1 (18)	16.2 (6)	0.02
NPSLE, % (n)	56.5 (26)	29.7 (11)	0.01
Active NPSLE, % (n)	41.3 (19)	21.6 (8)	0.06
Lupus nephritis,% (n)	54.3 (25)	35.1 (13)	0.08
Active lupus nephritis, % (n)	39.1 (18)	24.3 (9)	0.15
Disease damage, % (n)	39.1 (18)	21.6 (8)	0.04
SLEDAI score (mean ± SD)	8 (IQR 10)	4 (IQR 8)	0.001
Active disease, % (n)	73.9 (34)	37.8 (14)	0.002
C3, mg/dl (mean ± SD)	77.6 ± 36.2	89.6 ± 40.6	0.15
C4, mg/dl (mean ± SD)	15.8 ± 8.6	18.5 ± 8.8	0.17
Urine PCI, g/mmol (median, IQR)	0.02 (IQR 0.16)	0.02 (IQR 0.06)	0.39
Serum albumin, g/l (mean ± SD)	38.2 ± 6.8	36.5 ± 8.0	0.28
Cerebral infarcts, % (n)	47.8 (22)	0 (0)	<0.001

SLE: systemic lupus erythematosus; aPL: antiphospholipid antibodies; IQR: interquartile range; NPSLE: neuropsychiatric lupus; SLEDAI: Systemic Lupus Erythematosus Disease Activity Index; SD: standard deviation; UPCI: urine protein-creatinine index. Bold values indicate significant p value at < 0.05

Pearson’s correlation analyses revealed that there were significant correlations between total DWMHI, PVH and WMHI Scheltens scores with age, SLEDAI scores, presence of cerebral infarcts, and disease damage (Table 2).

Table 2

Correlations and associations of demographic and disease characteristics of SLE patients with Scheltens scores of deep white matter hyperintense lesions (DWMHI), periventricular white matter hyperintense lesions (PVH) lesions and total white matter hyperintense lesions (total WMHI)

Parameters	Total DWMHI scores	Total PVH scores	TOTAL WMHI scores
Age, years	r_s = 0.31	r_s = 0.24	r_s = 0.29
p	0.004	0.03	0.007
Disease duration, years	r_s = 0.21	r_s = 0.14	r_s = 0.23
p	0.06	0.19	0.05
SLEDAI scores	r_s = 0.24	r_s = 0.27	r_s = 0.34
p	0.03	0.01	0.002
UPCI, g/mmol	r_s = 0.09	r_s = 0.05	r_s = 0.11
p	0.44	0.68	0.13
Serum albumin, mg/dl	r_s = −0.10	r_s = −0.13	r_s = −0.14
p	0.35	0.21	0.19
Gender
Female	2.04 ± 3.41	1.03 ± 1.25	3.16 ± 4.60
Male	2.57 ± 3.15	1.29 ± 1.60	4.43 ± 5.09
p	0.69	0.61	0.49
Race
Malay	1.89 ± 3.52	1.06 ± 1.28	3.17 ± 4.84
Chinese	2.64 ± 3.17	1.12 ± 1.31	3.72 ± 4.23
Indian	1.40 ± 3.13	0.60 ± 1.34	1.89 ± 3.52
p	0.59	0.71	0.72
aPL
Positive	2.83 ± 4.28	1.29 ± 1.33	4.33 ± 5.58
Negative	1.78 ± 2.97	0.95 ± 1.25	2.83 ± 4.15
p	0.27	0.27	0.18
Active NPSLE
Yes	2.41 ± 3.69	1.15 ± 1.29	3.70 ± 4.95
No	1.93 ± 3.24	1.00 ± 1.28	3.05 ± 4.49
p	0.19	0.98	0.55
Active lupus nephritis
Yes	3.00 ± 4.52	1.30 ± 1.38	4.63 ± 5.90
No	2.64 ± 2.59	0.93 ± 1.22	2.61 ± 3.69
p	0.09	0.24	0.06
Disease damage
Yes	3.18 ± 4.32	1.57 ± 1.37	5.07 ± 5.77
No	1.53 ± 2.66	0.78 ± 1.15	2.35 ± 3.65
p	0.02	0.01	0.01
Hypertension
Yes	3.08 ± 4.43	1.30 ± 1.38	4.65 ± 5.79
No	1.63 ± 2.69	0.93 ± 1.22	2.63 ± 3.89
p	0.07	0.22	0.06
Dyslipidaemia
Yes	2.57 ± 3.76	1.04 ± 1.33	3.66 ± 4.93
No	1.90 ± 3.24	1.05 ± 1.26	3.16 ± 4.53
p	0.47	0.98	0.60
Infarct
Yes	4.45 ± 4.18	1.82 ± 1.22	6.86 ± 5.3
No	1.23 ± 2.56	0.77 ± 1.19	1.96 ± 3.60
p	<0.001	<0.001	<0.001

SLE: systemic lupus erythematosus; aPL: antiphospholipid antibodies; SLEDAI: Systemic Lupus Erythematosus Disease Activity Index; NPSLE: neuropsychiatric lupus; UPCI: urine protein-creatinine index.

Further analysis of the size and shape of DWMHI and PVH lesions using the Fazekas scale revealed that presence of disease damage, active LN with more severe proteinuria (higher urine protein-creatinine index (PCI)), and higher SLEDAI scores were associated with higher Fazekas grades of DWMHI and PVH. Age was associated only with higher DWMHI Fazekas scale but not with PVH. Tables 3 and 4 compare the clinical characteristics of SLE patients with Fazekas scales of the DWMHI and PVH.

Table 3

Correlations and associations of demographic and disease characteristics of SLE patients and Fazekas scale of periventricular white matter hyperintense lesions (PVH)

Parameters	FAZEKAS PVH			p
Parameters	0 (n = 45)	1 (n = 32)	2 (n = 6)	p
Age (years)	33.8 ± 11.3	37.9 ± 13.2	42.0 ± 15.7	0.17
Disease duration (years)	3.9 ± 4.5	5.1 ± 5.3	7.5 ± 5.6	0.19
SLEDAI	4 (IQR 8)	8 (IQR 8)	13 (IQR 7)	0.01
Serum albumin (g/l)	38.0 ± 7.1	37.9 ± 6.2	28.2 ± 12.2	0.008
UPCI, g/mmol	0.02 (IQR 0.09)	0.02 (IQR 0.09)	0.25 (IQR 1.36)	0.01
Race
Malay, %	62.2 (28)	65.6 (21)	66.7 (4)	0.82
Chinese, %	28.9 (13)	31.3 (10)	33.3 (2)
Indian, %	8.9 (4)	3.1 (1)	0 (0)
Gender
Female, %	91.1 (41)	93.8 (30)	83.3 (5)	0.69
Male, %	8.9 (4)	6.3 (2)	6.7 (1)
Active NPSLE, %	28.9 (13)	34.4 (11)	50.0 (3)	0.56
Active lupus nephritis,%	26.7 (12)	31.3 (10)	83.3 (5)	0.02
Disease damage, %	22.2 (10)	40.6 (13)	83.3 (5)	0.007
aPL, %	24.4 (11)	37.5 (12)	16.7 (1)	0.36
Infarcts, %	11.1 (5)	46.9 (15)	33.3 (2)	0.002
Hypertension	31.1 (14)	31.3 (10)	33.3 (2)	0.99
Dyslipidaemia	28.9 (13)	25.0 (8)	33.3 (2)	0.89

UPCI: urine protein-creatinine index; aPL: antiphospholipid antibodies; NPSLE: neuropsychiatric lupus; SLEDAI: Systemic Lupus Erythematosus Disease Activity Index; IQR: interquartile range.

Table 4

Correlations and associations of demographic and disease characteristics of SLE patients and Fazekas scale of deep matter hyperintense lesions (DWMHI)

Parameters	FAZEKAS DWMHI			p
Parameters	0 (n = 42)	1 (n = 31)	2 (n = 10)	p
Age (years)	32.4 ± 10.0	38.5 ± 13.1	43.3 ± 15.6	0.02
Disease duration (years)	3.9 ± 4.6	4.9 ± 5.2	6.6 ± 5.6	0.35
SLEDAI	4 (IQR 9)	8 (IQR 8)	10 (IQR 8)	0.03
Serum albumin (g/l)	37.7 ± 7.3	38.3 ± 6.0	32.1 ± 10.9	0.07
UPCI, g/mmol	0.02 (IQR 0.09)	0.02 (IQR 0.09)	0.15 (IQR 0.34)	0.007
Race
Malay, %	66.7 (2)	61.3 (19)	60.0 (6)	0.54
Chinese, %	23.8 (10)	35.5 (11)	40.0 (4)
Indian, %	9.5 (4)	3.2 (1)	0 (0)
Gender
Female, %	95.2 (40)	87.1 (27)	90.0 (9)	0.46
Male, %	4.8 (2)	12.9 (4)	10.0 (1)
Active NPSLE	23.8 (10)	41.9 (13)	40.0 (4)	0.23
Active lupus nephritis,%	26.2 (11)	29.0 (9)	70.0 (7)	0.03
Disease damage, %	21.4 (9)	38.7 (12)	70.0 (7)	0.01
aPL, %	19.0 (8)	41.9 (13)	30.0 (3)	0.10
Infarcts, %	2.4 (1)	48.4 (15)	60.0 (6)	0.001
Hypertension	26.2 (11)	32.3 (10)	50.0 (5)	0.34
Dyslipidaemia	21.4 (9)	32.3 (10)	40.0 (4)	0.39

aPL: antiphospholipid antibodies; NPSLE: neuropsychiatric lupus; SLEDAI: Systemic Lupus Erythematosus Disease Activity Index; UPCI: urine protein-creatinine index; IQR: interquartile range.

Multivariable logistic regression analysis revealed that only positive aPL and SLEDAI scores were the significant independent associated factors with the WMHI in SLE (Table 5). Multiple regression analysis revealed that presence of cerebral infarct was significantly associated with higher WMHI Scheltens scores both in DWMHI (β = 0.42, 3.23 (1.70–4.75), p < 0.001) and PVH (β = 0.32, 0.93 (0.34–1.52), p = 0.002). Meanwhile, active disease was found to be significantly associated with a higher total PVH Scheltens scores (β = 0.22, 0.58 (0.05–1.10), p = 0.03) but not DWMHI Scheltens scores.

Table 5

Multivariate logistic regression analysis of the factors associated with the presence of white matter hyperintense (WMHI) lesions

Parameters	B coefficient	HR (95% CI)	p
Age	0.03	1.03 (0.97–1.10)	0.39
Male	−0.25	0.78 (0.003–216.72)	0.93
SLEDAI	0.18	1.20 (1.06–1.35)	0.003
aPL positive	1.99	7.34 (1.86–28.9)	0.004
Active disease	−0.44	0.64 (0.04–10.83)	0.76
Cerebral infarcts	−22.60	0.00 (0.00–0.00)	0.99
NPSLE	0.97	2.64 (0.45–15.55)	0.28
Active NPSLE	0.24	1.26 (0.25–6.44)	0.77
Lupus nephritis	1.19	3.28 (0.62–17.35)	0.16
Damage	1.40	4.07 (0.69–23.87)	0.12

aPL: antiphospholipid antibodies; NPSLE: neuropsychiatric lupus; SLEDAI: Systemic Lupus Erythematosus Disease Activity Index; HR: hazard ratio; CI: confidence interval.

Discussion

WMHI lesions on T2 and FLAIR brain MRI are very common and can be found in up to 60% in patients with SLE, especially in the fronto-parietel regions, followed by the periventricular regions.^13,35–37 The exact underlying pathophysiology and clinical correlations of WMHIs in SLE are largely unknown but these lesions may represent biochemical changes of brain tissue and may reflect underlying small-vessel diseases, focal ischaemia, vasculitis and demyelination.^12,38 Our study is the first study to analyse the factors associated with presence of WMHI and its correlation with the semi-quantitative scoring of Scheltens and Fazekas classifications of WMHI lesions in SLE patients.

Increasing age has been demonstrated to be associated with the presence of WMHI lesions in general populations^39–41 and SLE patients.^13,37 Our study demonstrated that age was no longer an independent factor associated with the presence of WMHI lesions in the multivariable logistic regression analysis and it was not significantly correlated with the WMHI lesion load in the DWMHI and PVH regions. This finding further supports the notion that WMHI lesions in SLE may have different pathogenesis as positive aPL and higher SLEDAI scores were the factors strongly associated with the presence of WMHI lesions among our SLE cohort.

Since the hallmark pathophysiology of SLE is secondary to autoantibody-mediated inflammation, generalized active lupus may lead to generalized vascular inflammation and endothelial dysfunction, which in turn can produce the white matter changes seen on MRI. There was also a postulation that a subclinical central nervous system (CNS) involvement may occur in SLE patients who have no overt neuropsychiatric symptoms.¹⁸ Despite a higher prevalence of NPSLE patients with WMHI lesions, the associations between them were weak as it was no longer found to be significant in multivariable regression analysis. Therefore, presence of WMHI is not specific for NPSLE as it has been demonstrated by other studies to also occur in non-NPSLE patients.^42,43 Nonetheless, our study demonstrated that presence of NPSLE was significantly associated with larger Fazekas scales of WMHI lesions both in DWMHI and PVH regions and this is in keeping with many other previous studies which reported a higher volume of WMHI lesions among NPSLE patients.^13,43,44

aPL have long been recognized to be one of the risk factors of vasculopathy in SLE.⁴⁵ Thus many other studies have demonstrated a significant association between positive aPL with WMHI^14–16 and it was postulated that these lesions are related to thromboembolism or small-vessel injury promoted by the presence of aPL. Since WMHI also represents microvascular disease, it is not surprising that the presence of these lesions were significantly associated with the presence of cerebral infarcts both in univariate and multivariate analyses.

The association between presence of cerebral infarcts and the WMHI lesion burden both in DWMHI and PVH regions was in agreement with the concept of a shared underlying pathogenesis of these two lesions, which involved small-vessel ischaemia.⁴⁶ Interestingly, our study also demonstrated that SLE patients with active disease had a higher WMHI lesion load at the PVH regions (total PVH Scheltens scores), rather than at the DWMHI regions. This phenomenon again raises the question of the existence of a distinct pathogenesis involved in the development of the hyperintense lesions in the DWMHI and PVH regions as described earlier. Indeed, an earlier post-mortem study found that the typical pathology of PVH lesions were oedema related to blood-barrier disruption,⁴⁷ which is the hallmark of SLE activity.

In this study, we also demonstrated that SLE patients with active LN who had a more severe degree of proteinuria or higher urine PCI and hypoalbuminaemia were also associated with higher grade of DWMHI and PVH lesions. Indeed, many other studies have demonstrated that proteinuria indicates a generalized endothelial dysfunction⁴⁸ which may lead to the leakage of fluid into the white matter, and among the general population, microalbuminuria was shown to be associated with WMHI lesions in hypertensive patients⁴⁹ and elderly individuals. Presence of disease damage was also found to be associated with higher grades of DWMHI and PVH lesions and this finding concurred with other previous studies which showed a similar observation.

This study has several limitations due to the retrospective design and the small number of participants. Apart from that, since the MRIs were performed for patients with neurological symptoms, selection bias was inevitable and therefore the findings may not be representative of other general SLE cohorts. Therefore, larger prospective studies are needed in the future. Nevertheless, to our knowledge, our study is the first to use semi-quantitative scoring of WMHI lesion load to determine the associated factors of such lesions in a multi-ethnic Asian SLE cohort.

In summary, our study demonstrated that WMHI lesions in SLE could be linked to ischaemic or occlusive vascular disease as they were significantly associated with presence of cerebral infarct and presence of aPL. Apart from that, WMHI lesions may represent active inflammation as they were significantly associated with high general SLE activity.

Footnotes

Acknowledgment

The authors acknowledge Prof Dr Zaleha Abdullah Mahdy, dean and director of the National University of Malaysia Medical Centre (UKMMC).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

References

Rovaris

Viti

Ciboddo

et al.

Brain involvement in systemic immune mediated diseases: Magnetic resonance and magnetisation transfer imaging study. J Neurol Neurosurg Psychiatry 2000; 68: 170–177.

Filley

Kozora

Brown

et al.

White matter microstructure and cognition in non-neuropsychiatric systemic lupus erythematosus. Cogn Behav Neurol 2009; 22: 38–44.

Jennekens

Kater

. The central nervous system in systemic lupus erythematosus. Part 2. Pathogenetic mechanisms of clinical syndromes: A literature investigation. Rheumatology (Oxford) 2002; 41: 619–630.

DeCarli

Fletcher

Ramey

Harvey

Jagust

. Anatomical mapping of white matter hyperintensities (WMH): Exploring the relationships between periventricular WMH, deep WMH, and total WMH burden. Stroke 2005; 36: 50–55.

Fazekas

Kleinert

Offenbacher

et al.

Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 1993; 43: 1683–1689.

Jickling

Salam

Mohammad

et al.

Circulating endothelial progenitor cells and age-related white matter changes. Stroke 2009; 40: 3191–3196.

Pomper

Miller

Stone

Tidmore

Hellmann

. CNS vasculitis in autoimmune disease: MR imaging findings and correlation with angiography. AJNR Am J Neuroradiol 1999; 20: 75–85.

Sibbitt

Jr Brooks

Kornfeld

Hart

Bankhurst

Roldan

. Magnetic resonance imaging and brain histopathology in neuropsychiatric systemic lupus erythematosus. Semin Arthritis Rheum 2010; 40: 32–52.

Kim

MacFall

Payne

. Classification of white matter lesions on magnetic resonance imaging in elderly persons. Biol Psychiatry 2008; 64: 273–280.

10.

Scarpelli

Salvolini

Diamanti

Montironi

Chiaromoni

Maricotti

. MRI and pathological examination of post-mortem brains: The problem of white matter high signal areas. Neuroradiology 1994; 36: 393–398.

11.

Fazekas

Kleinert

Offenbacher

et al.

The morphologic correlate of incidental punctate white matter hyperintensities on MR images. AJNR Am J Neuroradiol 1991; 12: 915–921.

12.

Harboe

Greve

Beyer

et al.

Fatigue is associated with cerebral white matter hyperintensities in patients with systemic lupus erythematosus. J Neurol Neurosurg Psychiatry 2008; 79: 199–201.

13.

Appenzeller

Vasconcelos Faria

Costallat

Cendes

. Quantitative magnetic resonance imaging analyses and clinical significance of hyperintense white matter lesions in systemic lupus erythematosus patients. Ann Neurol 2008; 64: 635–643.

14.

Csépány

Bereczki

Kollár

Sikula

Kiss

Csiba

. MRI findings in central nervous system systemic lupus erythematosus are associated with immunoserological parameters and hypertension. J Neurol 2003; 250: 1348–1354.

15.

Sanna

Piga

Terryberry

et al.

Central nervous system involvement in systemic lupus erythematosus: Cerebral imaging and serological profile in patients with and without overt neuropsychiatric manifestations. Lupus 2000; 9: 573–583.

16.

Popescu

Kao

. Neuropsychiatric systemic lupus erythematosus. Curr Neuropharmacol 2011; 9: 449–457.

17.

Kaichi

Kakeda

Moriya

et al.

Brain MR findings in patients with systemic lupus erythematosus with and without antiphospholipid antibody syndrome. AJNR Am J Neuroradiol 2014; 35: 100–105.

18.

Luyendijk

Steens

Ouwendijk

et al.

Neuropsychiatric systemic lupus erythematosus: Lessons learned from magnetic resonance imaging. Arthritis Rheum 2011; 63: 722–732.

19.

Hochberg

. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 1997; 40: 1725–1725.

20.

Spilt

Goekoop

Westendorp

Blauw

de Craen

van Buchem

. Not all age-related white matter hyperintensities are the same: A magnetization transfer imaging study. AJNR Am J Neuroradiol 2006; 27: 1964–1968.

21.

Wardlaw

Smith

Biessels

et al.

Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 2013; 12: 822–838.

22.

Schaefer

Grant

Gonzalez

. Diffusion-weighted MR imaging of the brain. Radiology 2000; 217: 331–345.

23.

Chowdhury

Wardlaw

Dennis

. Are multiple acute small subcortical infarctions caused by embolic mechanisms? J Neurol Neurosurg Psychiatry 2004; 75: 1416–1420.

24.

Scheltens

Barkhof

Leys

et al.

A semiquantative rating scale for the assessment of signal hyperintensities on magnetic resonance imaging. J Neurol Sci 1993; 114: 7–12.

25.

Fazekas

Chawluk

Alavi

Hurtig

Zimmerman

. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol 1987; 149: 351–356.

26.

Scheltens

Barkhof

Leys

Wolters

Ravid

Kamphorst

. Histopathologic correlates of white matter changes on MRI in Alzheimer’s disease and normal aging. Neurology 1995; 45: 883–888.

27.

Kapeller

Barber

Vermeulen

et al.

Visual rating of age-related white matter changes on magnetic resonance imaging: Scale comparison, interrater agreement, and correlations with quantitative measurements. Stroke 2003; 34: 441–445.

28.

The American College of Rheumatology nomenclature and case definitions for neuropsychiatric lupus syndromes. Arthritis Rheum 1999; 42: 599–608.

29.

Bombardier

Gladman

Urowitz

Caron

Chang

. Derivation of the SLEDAI. A disease activity index for lupus patients. The Committee on Prognosis Studies in SLE. Arthritis Rheum 1992; 35: 630–640.

30.

Hawker

Gabriel

Bombardier

Goldsmith

Caron

Gladman

. A reliability study of SLEDAI: A disease activity index for systemic lupus erythematosus. J Rheumatol 1993; 20: 657–660.

31.

Petri

Hellmann

Hochberg

. Validity and reliability of lupus activity measures in the routine clinic setting. J Rheumatol 1992; 19: 53–59.

32.

Ward

Marx

Barry

. Comparison of the validity and sensitivity to change of 5 activity indices in systemic lupus erythematosus. J Rheumatol 2000; 27: 664–670.

33.

Yee

Farewell

Isenberg

et al.

The use of Systemic Lupus Erythematosus Disease Activity Index-2000 to define active disease and minimal clinically meaningful change based on data from a large cohort of systemic lupus erythematosus patients. Rheumatology (Oxford) 2011; 50: 982–988.

34.

Gladman

Ginzler

Goldsmith

et al.

The development and initial validation of the Systemic Lupus International Collaborating Clinics/American College of Rheumatology damage index for systemic lupus erythematosus. Arthritis Rheum 1996; 39: 363–369.

35.

Baum

Hopf

Nehrig

Stöver

Schörner

. Systemic lupus erythematosus: Neuropsychiatric signs and symptoms related to cerebral MRI findings. Clin Neurol Neurosurg 1993; 95: 29–34.

36.

Friedman

Stidley

Brooks

Hart

Sibbitt

Jr . Brain injury and neurometabolic abnormalities in systemic lupus erythematosus. Radiology 1998; 209: 79–84.

37.

Hachulla

Michon-Pasturel

Leys

et al.

Cerebral magnetic resonance imaging in patients with or without antiphospholipid antibodies. Lupus 1998; 7: 124–131.

38.

Sibbitt

Jr Schmidt

Hart

Brooks

. Fluid attenuated inversion recovery (FLAIR) imaging in neuropsychiatric systemic lupus erythematosus. J Rheumatol 2003; 30: 1983–1989.

39.

Ylikoski

Erkinjuntti

Raininko

Sarna

Sulkava

Tilvis

. White matter hyperintensities on MRI in the neurologically nondiseased elderly. Analysis of cohorts of consecutive subjects aged 55 to 85 years living at home. Stroke 1995; 26: 1171–1177.

40.

Launer

Berger

Breteler

et al.

Regional variability in the prevalence of cerebral white matter lesions: An MRI study in 9 European countries (CASCADE). Neuroepidemiology 2006; 26: 23–29.

41.

Liao

Cooper

Cai

et al.

The prevalence and severity of white matter lesions, their relationship with age, ethnicity, gender, and cardiovascular disease risk factors: The ARIC Study. Neuroepidemiology 1997; 16: 149–162.

42.

Gonzalez-Crespo

Blanco

Ramos

et al.

Magnetic resonance imaging of the brain in systemic lupus erythematosus. Br J Rheumatol 1995; 34: 1055–1060.

43.

Castellino

Padovan

Bortoluzzi

et al.

Single photon emission computed tomography and magnetic resonance imaging evaluation in SLE patients with and without neuropsychiatric involvement. Rheumatology (Oxford) 2008; 47: 319–323.

44.

Sailer

Burchert

Ehrenheim

et al.

Positron emission tomography and magnetic resonance imaging for cerebral involvement in patients with systemic lupus erythematosus. J Neurol 1997; 244: 186–193.

45.

Piette

Frances

Papo

Karmochkine

. Vasculopathy and antiphospholipid antibodies in systemic lupus. J Clin Pathol 1993; 46: 781–782.

46.

Pantoni

Garcia

. Pathogenesis of leukoaraiosis. A review. Stroke 1997; 28: 652–659.

47.

Munoz

Hastak

Harper

Lee

Hachinski

. Pathologic correlates of increased signals of the centrum ovale on magnetic resonance imaging. Arch Neurol 1993; 50: 492–497.

48.

O’Rourke

Safar

. Relationship between aortic stiffening and microvascular disease in brain and kidney: Cause and logic of therapy. Hypertension 2005; 46: 200–204.

49.

Knopman

Mosley

Jr Bailey

Jack

Jr Schwartz

Turner

. Associations of microalbuminuria with brain atrophy and white matter hyperintensities in hypertensive sibships. J Neurol Sci 2008; 271: 53–60.