 |
|
||||
| Home | Login | |||||
| About | Editorial board | Articles
|
NSI Publications
|
Search | Instructions | Online Submission | Subscribe | Videos | Etcetera | Contact |
|
||||||||||||||||||||
|
|
|
Preliminary Study on the Effect of Impaired Glucose Tolerance on Blood-Brain Barrier Permeability in Non-Neurosyphilis Patients
Correspondence Address: Source of Support: None, Conflict of Interest: None DOI: 10.4103/0028-3886.344667
Keywords: Blood-brain barrier permeability, DCE MRI, impaired glucose tolerance, non-neurosyphilis
The blood-brain barrier (BBB) is a neurovascular unit consisting of endothelial cells and astrocytic foot processes, which limits the entry of neurotoxic plasma-derived proteins, circulating metals, pathogens, red blood cells, and leukocytes into the brain.[1],[2] There is emerging evidence that BBB is a target structure for microvascular complications of diabetes, such as endothelium degeneration, cerebral microvascular basement membrane thickening, and astrocytic endfeet swelling.[3],[4] The degradation of BBB tight junction proteins and an increase of BBB permeability have been observed in diabetes. Diabetes and its complications can induce transient or permanent cognitive abnormalities,[5],[6],[7],[8],[9],[10] which may result from BBB dysfunction.[11],[12] It has been reported that prediabetes is associated with memory declining.[13] However, it is currently unknown whether BBB is damaged in prediabetes. Prediabetes, typically defined as blood glucose concentration higher than normal, but lower than the diabetes threshold, is a high-risk state for diabetes development.[14] Impaired glucose tolerance (IGT), defined as a fasting plasma glucose (FPG) concentration of <7.0 mmol/L and a 2 h postload plasma glucose concentration of ≥7.8 and <11.1 mmol/L, measured during a 75 g oral glucose tolerance test (OGTT), is a prediabetic state of hyperglycemia that is associated with increased risk of neurological pathology.[13] IGT affects about 11% of people aged 20–74 years in the United States and 17% of people aged 40–65 years in Britain.[15],[16] Furthermore, the number of adults with IGT is expected to increase worldwide, reaching 472 million by 2030. It is reported that there is an association between neurosyphilis (NS) and diabetes mellitus (DM). The prevalence of DM is significantly higher in NS patients than in those without NS.[17] Non-neurosyphilis (non-NS) is defined as syphilis of any stage excluding NS. In other words, non-NS patients are those who are seropositive for Treponema pallidum particle agglutination (TPPA) and rapid plasma reagin (RPR), but negative for cerebrospinal fluid (CSF) venereal disease research laboratory (VDRL), CSF fluorescent treponemal antibody absorption (FTA-ABS), CSF TPPA, CSF pleocytosis, and CSF protein without any characteristic symptoms or signs of NS.[18] In clinical practice, we find that many patients with non-NS suffer from IGT and they are likely to develop NS and/or DM later. Therefore, we suppose that IGT combined with non-NS may accelerate BBB disruption. In this study, we used dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) technique and postprocessing analysis[1] with improved spatial and temporal resolutions to quantify BBB permeability in patients with non-NS and/or IGT.
Study design and participants This study was approved by the Institutional Ethics Committee of Zhongshan Hospital (Approval No. xmzsyyky 2019041, Approval date: March 1 2013), and all participants provided written informed consent. A total of 21 subjects (18–75 years old) were recruited at Zhongshan Hospital, Medical College of Xiamen University from July 2013 to July 2015 (excluding returning patients), including six patients with IGT only (group 1), nine patients with non-NS only (group 2), and six patients with both IGT and non-NS (group 3) [Table 1].
Exclusion criteria Subjects who had other psychiatric or neurological diseases history which might influence BBB permeability were excluded, such as substance abuse, dementia, immune system diseases, stroke, head injury, intracranial infection, and organ failure. Subjects with NS were also excluded. Procedures All patients were examined by DCE-MRI. Lumbar punctures were completed in all the patients. NS was defined as reactive CSF VDRL or a CSF white blood cell count ≥20 cells/μL.[19],[20],[21] All analyses were performed by an investigator blinded to the experimental conditions. DCE-MRI and regions of interest T1-weighted MRI sequence (8 slices, flip angle = 30°, echo time = 1.9 ms, repetition time = 3.9 ms, field of view = 230 × 230 mm2) with a slice thickness of 8 mm was performed on a 3T Siemens MR scanner. The preprocessing operations of MRI data were realized by FMRIB Software Library (FSL), such as brain extraction[22] and registration.[23] The regions of interest (ROIs) were manually defined by an experienced neuroradiologist. The time resolution of 1.25 s and 720-time points made a sampling duration of 15 min. The dose of contrast agent (Gd-DTPA) was 0.045 mmol/kg bodyweight. A series of saturation time delays from 120 ms to 12 s were used to generate initial relaxation time and equilibrium magnetization. Permeability estimation A two-compartment model was used to estimate the volume transfer constant Ktrans which represents the permeability of BBB. Detailed theories and formulas have been described in the literature.[24],[25],[26] The signal intensities in the DCE time series were converted to values of contrast agent concentration using initial relaxation time and equilibrium magnetization got above. The voxels near the internal carotid artery (ICA) with maximal signal change during the passage of the contrast agent were used to calculate the arterial input function (AIF). We used the median values of Ktrans obtained for every ROI to exclude the effects of possible outliers. The value of hematocrit (Hct) setting to 0.45 and brain tissue density to 1 g/mL in the process of calculation.[27] Laboratory tests The syphilitic serological tests were fulfilled by using TPPA (Fujirebio, Tokyo, Japan) and RPR (InTec, Xiamen, China) tests according to the manufacturer's instructions. CSF/plasma albumin quotient was calculated as Qalb = CSF albumin (mg/L)/plasma albumin (g/L). The colorimetric method and immune turbidimetric method were used to determine plasma and CSF albumin, respectively (Roche, Inc., Switzerland). Enzyme-linked immunosorbent assay (ELISA) Soluble intercellular cell adhesion molecule-1 (sICAM-1) and soluble vascular cell adhesion molecule-1 (sVCAM-1) concentrations in CSF and serum samples were measured by using sandwich enzyme-linked immunosorbent assay (ELISA) with sICAM-1 and sVCAM-1 ELISA kit (R&D Systems, Inc., USA) according to the manufacturer's protocol. Tumor necrosis factor (TNF)-α, interleukin (IL) 1-β, IL-6, and IL-10 concentrations in CSF and serum samples were measured using a solid-phase sandwich ELISA kits (OptEIA, Becton Dickinson, Belgium). Matrix metalloproteinase 9 (MMP-9) concentrations in CSF and serum samples were measured by using an ELISA kit (AnaSpec, Fremont, CA, USA). Statistical analysis Statistical analyses were performed with a statistical package for the social sciences (SPSS) v20.0 software. Univariate differences among groups were determined by one-way analysis of variance (ANOVA). Data in normal distribution were presented as mean ± SD and P value < 0.05 was considered significant. The data in abnormal distribution were described as the median and interquartile range (IQR) and analyzed by the Mann-Whitney U test.
Clinical features of the recruited patients There were no significant differences in CSF leukocyte, CSF protein, CSF glucose, CSF chloride, CSF lactate, CSF lactate dehydrogenase, and intracranial pressure among the three groups. Besides, no significant differences were observed in serum RPR titer and serum TPPA titer between group 2 and group 3 [Table 1]. All of the patients from group 1, group 2, and group 3 had mild to moderate headaches. BBB permeability in three groups of patients The ROIs and the BBB permeability maps of three patients from different groups were shown in [Figure 1]. [Table 2] showed that the BBB permeability of the cortex superior frontal gyrus was higher in group 3 than in group 1 and group 2 (P = 0.012, P = 0.010, respectively). The Ktrans values showed higher BBB permeability of the white matter (WM) in group 3 than in group 1 (P = 0.011) and group 2 (P = 0.001). The value of the region of the thalamus in group 3 was high, compared with group 1 (P = 0.029) and group 2 (P = 0.004). However, the three groups had similar BBB permeability levels in the hippocampus, cortex inferior temporal gyrus, caudate nucleus, and internal capsule (P > 0.05) [Figure 2].
CSF biomarkers in three groups of patients The level of Qalb in group 3 is found to be higher than those in group 1 (P = 0.006) and group 2 (P = 0.001). Similarly, CSF secretion is highest in group 3, including MMP9 (in group 1, P = 0.039; in group 2, P = 0.021), sICAM-1 (in group 1, P = 0.020; in group 2, P = 0.013), and sVCAM-1 (in group 1, P = 0.002; in group 2, P = 0.001) [Table 3]. However, no significant differences were found in TNF-α, IL1-β, IL-6, and IL-10 levels of CSF among all three groups [Figure 3].
Correlations between CSF biomarkers and permeability We found correlations of cortex superior frontal gyrus BBB permeability with sICAM-1 level (correlation coefficient [CC] = 0.694, P < 0.01), WM BBB permeability with sICAM-1 level (CC = 0.723, P < 0.01), thalamus BBB permeability with sICAM-1 level (CC = 0.586, P < 0.01), cortex superior frontal gyrus BBB permeability with sVCAM-1 level (CC = 0.713, P < 0.01), WM BBB permeability with sVCAM-1 level (CC = 0.606, P < 0.01), and thalamus BBB permeability with sVCAM-1 level (CC = 0.5, P = 0.021). Similarly, we found correlations between cortex superior frontal gyrus BBB permeability and Qalb level (CC = 0.509, P = 0.018), WM BBB permeability and Qalb level (CC = 0.685, P < 0.01), and thalamus BBB permeability and Qalb level (CC = 0.488, P = 0.025). MMP9 level was correlated with BBB permeability of cortex superior frontal gyrus (CC = 0.563, P = 0.008) and BBB permeability of WM (CC = 0.612, P = 0.003), but was not correlated with thalamus BBB permeability. The correlations can be seen in [Figure 4].
DCE MRI has been successfully used for the evaluation of BBB permeability in some diseases, such as acute intracerebral hemorrhage, multiple sclerosis, DM, and cognitive impairment.[1],[12],[28],[29] In this study, we used the DCE MRI to demonstrate BBB leakage in non-NS patients with IGT. Our results show an increase in CSF albumin and provide quantitative data to support the role of CSF albumin in indicating BBB disruption in non-NS patients with IGT. According to the DCE MRI results, the areas with increased permeability include cortex superior frontal gyrus, WM regions, and thalamus in IGT patients with non-NS. As we know, frontal lobe dysfunctions are commonly associated with numerous neuropsychological signs such as cognitive and memory decline, planning and emotional behavior abnormality, and logical reasoning deficiency.[30],[31],[32],[33] Recent studies have focused on the role of the thalamus in the regulation of emotions, motivation and reward, and the robust anatomical connection from the prefrontal cortex to the thalamus is a major source.[34],[35],[36] The IGT patients with non-NS are likely to have cognitive and memory decline, and behavior abnormality. Our results suggest that some cerebral areas of non-NS patients may be sensitive to a certain fluctuation of blood glucose, such as in the situation of IGT, so BBB integrity may be easy to break down. However, we observe no obvious change in BBB integrity in the hippocampus, cortex inferior temporal gyrus, caudate nucleus, and internal capsule. One potential explanation is that the fluctuation of blood glucose during IGT is not enough to disrupt BBB in these areas in non-NS patients. However, our previous study suggested that BBB integrity may be liable to be disrupted in non-NS patients with high HbA1c levels, and it is particularly important to control blood glucose in these patients.[37] An increased level of albumin in CSF is detected in patients with IGT and non-NS, suggesting that the albumin content in CSF can be used as a biomarker of BBB destruction for patients with both IGT and non-NS. A remarkable relationship is observed between Qalb and Ktrans in cortex superior frontal gyrus, WM regions, and thalamus. These results confirmed BBB damages in these areas. We observe that sICAM-1, sVCAM-1, and MMP9 levels increase in patients with IGT and non-NS. Hyperglycemia may lead to endothelial dysfunction.[38] Elevated plasma levels of ICAM-1 and VCAM-1 as the biomarkers of endothelial dysfunction are predictors of incident diabetes in nondiabetic women. The association of ICAM-1 with diabetes is independent of the confounding effects of usual risk factors for diabetes.[39] Besides, the circulating level of MMP-9 is higher in DM patients.[40] Endothelial dysfunction and elevated levels of ICAM-1 and VCAM-1 have been described in non-diabetic subjects with an increased risk of diabetes.[41] While in oral lesions of secondary syphilis, high ICAM-1 expression in endothelial cells and leukocytes favors the development of the inflammatory reaction. The expressions of ICAM-1 and VCAM-1 increase in dermal endothelial cells exposed to a 47 kDa antigen derived from T. pallidum.[42] Our results are partly consistent with these observations, and support the notion that endothelial dysfunction leads to BBB destruction in non-NS patients combined with IGT. Moreover, our results provide significant links between concentrations of sICAM-1 and sVCAM-1 in CSF and BBB permeability in the areas of cortex superior frontal gyrus, WM regions, and thalamus. This study has several limitations. This was a preliminary retrospective study, and the relatively small sample size might cause some bias.
In summary, increased BBB permeability in non-NS patients with IGT supports a relationship between BBB disruption and the development of hyperglycemia and exposure to T. pallidum. A limitation of this study is that we enrolled relatively small numbers of patients because few patients met the inclusion criteria. In future studies, we need to screen more cases to confirm our conclusion. Highlights
Acknowledgment This study was supported by the National Natural Science Foundation of China (Nos. 41201462 and 81400984) and the Natural Science Foundation of Fujian Province of China (Nos. 2014D009 and 2015J01264). We thank Prof. Shuhui Cai (Xiamen University) for providing language help and writing assistance. Declaration of patient consent The authors certify that they have obtained all appropriate patient consent forms. In the form, the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed. Financial support and sponsorship This study was supported by the National Natural Science Foundation of China (Nos. 41201462 and 81400984) and the Natural Science Foundation of Fujian Province of China (Nos. 2014D009 and 2015J01264). Conflicts of interest There are no conflicts of interest.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2]
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
|||||
