The expression and clinical significance of MATK in chronic hypoperfusion patients with white matter hyperintensity

doi:10.21203/rs.3.rs-2984592/v1

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The expression and clinical significance of MATK in chronic hypoperfusion patients with white matter hyperintensity

https://doi.org/10.21203/rs.3.rs-2984592/v1

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Background

Chronic cerebral hypoperfusion (CCH) is one of the important causes of vascular cognitive impairment, and such people can often be found with white matter hyperintensity (WMH) under magnetic resonance imaging (MRI). This study aimed to investigate the expression and clinical significance of MATK in CCH patients with WMH.

Methods

A total of 42 patients with CCH complicated with WMH were defined as the WMH group and 45 healthy volunteers as the control group. The peripheral blood mononuclear cell (PBMC) levels of MATK were separated and detected by quantitative real-time polymerase chain (qPCR). A correlation analysis of MATK level and Fazekas scales in patients with WMH was also conducted.

Results

The qPCR results showed that the relative MATK expression was downregulated in the WMH group compared to the control group; the expression of MATK in the control group was 1.84 ± 0.87, while the expression of MATK in the WMH group was 1.20 ± 0.99, which was a statistically significant difference (t = 3.24, P < 0.01). Correlation analysis showed that the MATK level in the WMH group was negatively correlated with the Fazekas scale of WMH (R² = 0.3405, P < 0.001). MOCA (OR, 0.766; 95% CI 0.594–0.986; P < 0.05) and MATK (OR, 0.498; 95% CI 0.268–0.927; P < 0.05) were independent high-risk factors to predict the clinical outcomes of WMH in patients with CCH.

Conclusions

The expression of MATK in the peripheral blood of CCH patients was negatively correlated with the severity of WMH, and it may help CCH patients identify the progression of WMH as early as possible.

Biological sciences/Neuroscience/Cognitive neuroscience

Health sciences/Biomarkers/Diagnostic markers

Health sciences/Biomarkers/Predictive markers

Chronic cerebral hypoperfusion

White matter hyperintensity

Magnetic resonance imaging

MATK

Vascular cognitive impairment (VCI) is one of the most important causes of cognitive disorders in the elderly. The morbidity accounts for more than 20–40% of all dementia diagnoses, second only to Alzheimer's disease (AD), seriously affecting the quality of life of patients^1,2. Cerebral hypoperfusion can contribute to VCI, especially chronic cerebral hypoperfusion (CCH) has a significant correlation with the severity of dementia, and also predicts which individuals with mild cognitive impairment (MCI) will develop into dementia^3,4.

This pathological change is due to cerebral deep vessels of white matter being more vulnerable to ischemia and hypoxia. Therefore, CCH can cause ischemic changes in the white matter, along with the destruction of the blood-brain barrier and inflammatory cell infiltration, it leads to demyelinating in the white matter of the brain. Usually, these lesions can be found by magnetic resonance imaging (MRI) of the cerebral with white matter hyperintensities (WMH) on the T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) sequence^5–8. Common causes of cerebral hypoperfusion include carotid stenosis, intracranial atherosclerosis, heart failure, and other diseases that cause abnormal cerebral blood-flow dynamics^9,10. However, there is still no clear evidence on whether patients with CCH will have WMH and cognitive dysfunction, and there is a lack of specific biomarkers to predict the prognosis of the disease.

Megakaryocyte-associated tyrosine kinase (MATK), also known as Csk homologous kinase (CHK), is a kind of tyrosine protein kinase of the Csk family, which is mainly expressed in blood cells and the brain. MATK can be found in both astrocytes and oligodendrocytes and is related to the differentiation of oligodendrocytes¹¹. Overexpression of MATK in neuroblastoma and astrocytoma cells can inhibit the growth and differentiation of tumor cells¹². Studies have shown that MATK can promote the differentiation of anti-inflammatory monocytes. Cytokines IL-4 and its family can increase the expression of MATK in peripheral blood monocytes, while IFN-γ will reduce its expression¹³. Meanwhile, the inflammatory monocytes are significantly correlated with the progression of cerebrovascular disease, which can lead to an increase in WMH volume¹⁴. However, the role of MATK in CCH patients with WMH has not been reported. The purpose of this study was to analyze the correlation between WMH severity and serum MATK expression in patients with CCH, to provide predictive indicators for the prevention of cognitive dysfunction and dementia in CCH patients.

Cerebral MRI examination

As shown in Figure 1, MRI monitoring revealed that patients in the WMH group showed various cerebral WMH, especially near the lateral ventricles. We graded patients on a scale of 0-3 according to the extent of fusion of WMH by the Fazekas scale. The white matter of patients with CCH appears hypointense on T1 weighted, but punctate, patchy, or fusion areas of hyperintensities on T2 weighted, in addition to hyperintensity changes in the lateral ventricles, the deep white matter was also found WMHs in patients with severe CCH (Fig. 1B-C). As white matter lesions worsen, CCH patients also developed varying degrees of brain atrophy (Fig. 1D). This result also verified that cerebral white matter damage caused by cerebral chronic hypoperfusion is a characteristic manifestation of developing cerebral degenerative pathology, which may cause cognitive impairment.

WMH Patients and Healthy Controls demographics, and cognitive function Characteristics.

MRI data from 42 WMH patients (63.84±5.78 years old; 18 females) and 45 healthy controls (67.74±4.85 years old; 22 females) were eventually included in the study and analyzed. The control group without WMH was randomly selected, the baseline data and Fazekas scales of the two groups were recorded, and the MoCA score was used for rapid cognitive function assessment. The WMH patient demographics are listed in Table 1. It can be seen that the WMH differed significantly from the control group among the elderly (67.74±4.85 years versus 63.84±5.78 years; P=0.010), there was no difference in the gender ratio (40% versus 52.38% females; P=0.668). Regarding comorbidities, patients with WMH more frequently had hypertension (60% versus 38.1%; P=0.010), although the proportion of diabetes mellitus (37.78% versus 35.31%; P=0.513) and hyperlipidemia (42.22% versus 33.33%; P=0.192) were higher, there was no statistical difference.

The average Fazekas scale of WMH patients was1.833±0.82, which had significant differences compared to healthy controls(P<0.010). After adjustment of education, patients with WMH had worse MoCA scores (24.36±2.31 versus 26.11±1.87; P<0.010), suggesting a more severe cognitive impairment.

The expression of MATK mRNAs in mononuclear cells of peripheral venous blood

Because mononuclear cells are critical in the pathogenesis of WMH, we next explored the correlation between MATK in mononuclear cells and WMH. We first examined the MATK mRNAs expression in mononuclear cells sorted by lymphocyte separation medium of peripheral venous blood from the WMH and control group. The qPCR results showed that the relative MATK expression was downregulated in the WMH group compared to the control group (Fig.2). The expression of MATK in the control group was 1.84±0.87, while the expression of MATK in the WMH group was 1.20±0.99, which was a statistically significant difference (t=3.24, P<0.01). The data suggest that MATK in the PBMCs may be a protective factor for WMH patients.

Correlation analysis between WMH and MOCA with MATK

To further verify whether MATK expression in peripheral blood could reflect WMH severity in vivo, we then assessed the correlation between the relative expression of MATK in peripheral blood and Fazekas scales using Pearson's correlation analysis and found that as the MATK decreased, the Fazekas scales gradually raised (R²=0.3405, P<0.001) (Fig.3A), indicating that changes in MATK expression exhibited a significant negative correlation with the degree of WMH. However, there was no significant correlation between MATK and MoCA score (R²=0.0044, P = 0.6759) (Fig.3B).

Risk factors for WMH and their diagnostic and predictive value.

As summarized in Table 2, We further performed multivariate risk factor assessment for WMH by binary logistic regression analysis model, which included the characteristics with significant difference (P < 0.05) in basic data and the expression of MATK. The binary logistic regression showed that only MOCA (OR, 0.766; 95% CI 0.594-0.986; P < 0.05), and MATK (OR, 0.498; 95% CI 0.268-0.927; P < 0.05) were independent high-risk factors to predict the clinical outcomes of WMH in patients with CCH.

We also generated ROC curves to explore the indicators with predictive and diagnostic values for WMH. Among them, the AUC of the final regression model (including both of the independent risk factors) was 0.803（p＜0.001） and had the highest predictive value. The AUCs for MATK and MOCA were 0.743（95% CI 0.6369-0.8493，P＜0.001）and 0.717（95% CI 0.6093- 0.8246，P＜0.001）. The potency and superiority of MATK as a predictor and diagnostic of WMH alone were demonstrated with a cutoff value of 0.454, a sensitivity:0.4762, and a specificity: 0.9778. (Fig.4).

Cerebral hypoperfusion is one of the causes that contribute to the occurrence and development of VCI and dementia. With the decrease in cerebral blood flow (CBF), the cognitive function of patients also deteriorates^16,17. This reduction in CBF is related to the severity of WMHs under T2 sequences of MRI^18,19. However, the pathological mechanisms of hypoperfusion-induced white matter damage remain incompletely elucidated, and there are still no effective diagnostic methods to predict the occurrence of WMH. In the present study, we investigated the expression of MATK in peripheral blood and verified whether MATK could be a biomarker for predicting and diagnosing WMH and VCI.

Studies have shown that CCH, like cerebral small-vessel disease (CSVD), was often ignored by patients due to less severe clinical symptoms or lower mortality than common stroke. With the development of neuroimaging equipment, MRI can allow us to detect the presence of CSVD at an early stage. Similarly, we can prevent the progression of CCH through effective treatment measures. MRI examination in elderly patients with cognitive dysfunction shows that WMH is one of the biomarkers for the diagnosis of CSVD^20–22. MRI scans of 560 older individuals, the subjects were followed up with annual neuropsychological examinations for 3 years and evaluation of instrumental activities of daily living for 7 years, found that WMH was an independent predictor of cognitive impairment in a multivariate linear mixed model ²³. However, just relying on WMH is not specific for the diagnosis of CSVD, because it is difficult to distinguish CSVD or CCH from other demyelinating diseases such as multiple sclerosis and optic neuromyelitis by WMHs²⁴. There was also some mismatch between WMH and cognitive function scores in patients with CSVD. Among 156 patients with CSVD, 37 (23.7%) showed mismatching. Conventional imaging features and penetrating artery injury may explain this heterogeneity²⁵. Therefore, the use of other biomarkers to further clarify the prognosis of CCH is particularly important. In patients with a clinical diagnosis of CSVD, changes in several biomarkers such as low molecular weight neurofilament(NF-L), matrix metalloproteinase-9(MMP-9), tissue inhibitor of metalloproteinase-1(TIMP-1), matrix metalloproteinase-2 (MMP-2) and albumin CSF/plasma ratio were found to be increased^26–28. In our study, we found that the relative mRNA expression of MATK in the peripheral blood of patients with CCH was significantly decreased, and it was significantly negatively correlated with Fazekas scales. Logistic regression analysis indicated that MATK and MoCA were two independent factors strongly associated with WMH. The area under the ROC curve of MATK was 0.743, which was not significantly different from the final regression model 0.803, suggesting that MATK can be used as a biomarker for diagnosis and prediction of WMH, indicating that MATK can provide help in the diagnosis and prognosis of CCH.

MATK is mainly expressed in blood cells and the brain [12]. It has been reported that IL-4 can induce MATK/CHK expression in human peripheral blood mononuclear cells, while IFN-γ can inhibit it¹³. Another study showed that mouse primary microglia cells were stimulated with IL-4 and IFN-γ respectively to obtain differential gene expression profiles of microglia cells in vitro. The expression of the MATK molecule was significantly up-regulated under IL-4 (M2 polarization) stimulation, but significantly down-regulated under IFN-γ (M1 polarization) stimulation²⁹. These studies suggest that MATK in myeloid cells has the potential to inhibit inflammation both in the peripheral circulation and the central nervous system, with its expression significantly increased in the anti-inflammatory environment.

Microglia cells are also one of the mechanisms that cause WMH in the brain of patients with CSVD. As resident macrophages of the central nervous system (CNS), microglia cells play the role of endogenous innate immunity. Although microglia cells are generally favorable initially in performing immune functions, prolonged or excessive activation can lead to cytotoxic effects^30,31. When chronic hypoperfusion and blood-brain barrier destruction occur in the brain, the infiltration of peripheral mononuclear macrophages and overactivation of microglia will aggravate the injury of white matter and cause the demyelination of axons. This is one of the important mechanisms of CCH brain injury.

In one early study, the degree of microglial activation increased with aging, becoming diffusely distributed within the white matter. The degree of activation correlates with the aggravation of cognitive impairment³². A large number of microglia were activated in the acute or progressive stages of multiple sclerosis in the white matter lesion area, presenting an IFN-γ activation phenotype, which changed to IL-4 activation in the disease remission phase. Macrophages in the peripheral blood also further increase this process after the breakdown of the blood-brain barrier. Simultaneous removal of microglia in vivo also alleviates blood-brain barrier disruption in EAE, and this mechanism could be modulated by altering microRNA-126 expression in microglia³³.

In our study, we found that MATK expression was significantly decreased in the peripheral blood of patients with severe degrees of cerebral WMHs, suggesting that reduced MATK can drive macrophages to the IFN-γ phenotype in the peripheral blood, which has an inflammatory damaging function. While within the brain, it may also promote microglia towards a pro-inflammatory phenotype to damage the white matter. But the role of MATK on the phenotypic conversion of microglia still needs further studies to be clarified.

WMH is very common in older adults and develops with age ³⁴. Black race, female sex, and the presence of the APOE-4 allele were all associated with greater WMH burden or progression^34,35. These factors are all non-modifiable factors as in hereditary CSVD, while the risk factors for WMH severity and progression are also associated with cerebrovascular, cardiometabolic, and nutritional³⁴. Of these, hypertension had the strongest association. In a cross-sectional study, increased BP was clearly associated with the presence or severity of WMH. Hypertension is commonly found to be associated with the subsequent appearance of WMH in studies of early hypertension, with elevated blood pressure being able to increase the risk of developing WMH after 5 and 20 years. Similarly, midlife and older age BP were both associated with an increased risk of WMH³⁶.In another study, increasing midlife BP was significantly associated with WMH volume in old age³⁷. A meta-analysis of the effects of antihypertensive drugs on CSVD showed that patients in the intensive BP-lowering group had significantly less WMH progression³⁸.

The limitations of this study are as follows. First of all, due to the limited number of cases collected, there may be some selective bias. It is necessary to expand the sample size in later studies to observe the overall change of MATK expression in CCH patients. Secondly, the WMH patients included those with or without MCA/ICA artery stenosis. Intracranial artery stenosis itself is also a risk factor for WMH. The role of MATK in the occurrence of WMH can be determined by observing whether intracranial artery stenosis will cause changes in MATK expression alone. Third, MATK in peripheral blood is derived from monocytes and cannot fully represent the expression of MATK in intracranial microglia. Further animal experiments are needed to clarify the changes of MATK in the peripheral and brain pathology of WMH. As there are currently limited drugs that can treat WMH caused by CCH, the decreased expression of MATK in peripheral blood found in our study is a biomarker in CCH patients, so MATK may become a potential target for treating WMH in patients with CCH. Finding drugs that act on the MATK signaling pathway may be an effective way to treat the progression of WMH.

CCH has a severe impact on neurological and cognitive function in elderly patients, the expression of MATK in peripheral blood mononuclear cells was significantly downregulated in CCH patients with WMH. Meanwhile, the expression of MATK showed a significant negative correlation with the severity of WMH, and detecting the level of MATK in peripheral blood could help CCH patients identify the appearance and progression of WMH as early as possible.

Study population

The WMH group consisted of 42 CCH patients with WMH from the PLA 983rd Hospital from February 2022 to February 2023, including 24 males and 18 females, with an average age of 67.74 ± 4.85 years. Inclusion criteria: (1) the perfusion in one or both cerebral hemispheres detected by computed tomography perfusion (CTP) was reduced; (2) with or without severe middle cerebral artery (MCA)/ internal carotid artery (ICA) stenosis; (3) white-matter hyperintensities on T2-FLAIR sequence of MRI. Exclusion criteria: (1) cognitive decline due to neurological diseases (eg, Alzheimer’s disease, vascular dementia, and Parkinson's disease dementia); (2) hereditary dementia; (3) depression or mental illness; (4) history of acute stroke, intracranial infection, or traumatic brain injury; (5) Blood diseases, tumors, and other systemic diseases. The control group included 45 healthy volunteers with normal MRI findings, including 23 males and 22 females, with an average age of 63.84 ± 5.78 years. Demographic characteristics and the MoCA scores of patients were collected. The study protocol was approved by the Ethics Committee of the Chinese People’s Liberation Army NO.983 Hospital and performed in compliance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). All participants provided a written informed consent before participation. the Ethics Committee of the Chinese People’s Liberation Army NO.983 Hospital.

Cognitive assessment

Cognition was evaluated by the Montreal Cognitive Assessment (MoCA) test, including naming, attention, language, abstraction, memory, and orientation, which is widely accepted for screening mild cognitive impairment. Data were normalized with age and education-matched norms, and the cognitive deficit was determined by a score of < 26.

Isolation of mononuclear cells and MATK expression by quantitative real-time PCR (qPCR).

Peripheral blood mononuclear cells (PBMCs) were isolated from human peripheral blood using a lymphocyte separation medium (GE Healthcare) as described previously¹⁵. Total RNA was extracted from PBMC using Trizol RNA isolation reagent (Invitrogen) according to the manufacturer's protocol. cDNA from each sample was synthesized using a Revert Aid First Strand cDNA Synthesis Kit (Thermo Scientific). qPCR was performed on a Light Cycler96 apparatus (Roche) using the SYBR Green Real-time PCR Master Mix (Toyobo). Expression of GAPDH in cDNA samples was used to control for differences in the extraction and reverse transcription of total RNA. Gene expression was normalized to a standard housekeeping gene using the ΔΔCT method. The following primers were used for real-time RT-PCR: MATK 5’-GGTGAGACCAAAGCGGAAACAC-3’ (sense); 5’-TCCGATCTGTGCTCCCAATGTC-3’ (antisense); GAPDH 5′-AAATGGTGAAGGTCGGTGTG-3′ (sense); and 5′-AGGTCAATGAAGGGGTCGTT-3′ (antisense).

Imaging Acquisition

All patients underwent MRI on a 3.0-T MRI system (GE Signa 3.0 T HDxt, GE Healthcare, WI, USA) using an eight-channel head coil. The protocol comprises T1-weighted (T1WI), T2-weighted (T2WI), and T2-FLAIR sequences. The parameters were as follows: (1) T2 FLAIR: TR/TE = 8000/97.0 ms, FOV = 220 × 220 mm², slice thickness = 5 mm, slice gaps = 1.5, flip angle = 150.0, ETL = 19, matrix = 320 × 420; (2)T2-weighted FSE: TR/TE = 2883/50 ms, FOV = 10×10 cm2, NEX = 3, matrix = 320×256, echo-train length (ETL) = 20, slice thickness = 2 mm, and sequence duration = 111 seconds, no-phase-wrap option (acquiring a larger FOV and cut the edges) was used to avoid wrapping artifacts. (3) T1WI: TR/TE = 567/16 ms, FOV = 10×10 cm², NEX = 2, matrix = 320×256, ETL = 6, slice thickness = 2 mm, and sequence duration = 48.4 seconds. WMHs were grouped according to the distribution of hyperintensities in the paraventricular and deep white matter on T2WI using the Fazekas scale (0, normal; 1, mild; 2, moderate; 3, severe). MRI data were evaluated by two radiologists who had no knowledge of the clinical information.

Statistical analysis

All statistical analyses were performed using SPSS24.0 and GraphPad Prism 8.0. First, the test of normal distribution was conducted on all metrics. Then, mean and SD were recorded for continuous variables, and the frequency and percentage were recorded for categorical variables. Student’s t tests were used for comparing continuous variables and chi-square tests were used for comparing categorical variables. The correlation between the expression of MATK in mononuclear cells and the white matter lesions, MATK and MoCA were analyzed by Pearson’s correlation. A binary logistic regression model was used to analyze the correlation between multiple biomarkers and WMH in patients with CCH. The diagnostic performance was described using receiver operating characteristic (ROC) curves and area under the curve (AUC) values. P value < 0.05 indicated a statistically significant difference.

Data availability

The datasets analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

This work was supported by the National Natural Science Foundation of China (82101412), and Naval Specialty Medical Center Foundation (23M2702).

Author contributions

MZ and JZ contributed to the study concept and design, analysis and interpretation of data, drafting/revising the manuscript for content, and statistical analysis. QY was involved in analysis and interpretation of data. YH contributed to the study concept and design and manuscript revision. ZS and HS performed analysis and interpretation of data. Material preparation, YP contributed to material preparation and data collection. All authors read and approved the final manuscript.

Competing interests

The authors declare no competing interests.

Additional Information

Correspondence and requests for materials should be addressed to M.Z.

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TABLE 1. Demographics Characteristics Between WMH Patient and Healty Control.
Clinical Characteristics	WMH Patients (N = 42)	Control (N = 45)	P value
Age	67.74±4.85	63.84±5.78	0.001
Gender
Female	18(40%)	22（52.38%）	0.668
Hypertension	27(60%)	16(38.10%)	0.010
Diabetes mellitus	17(37.78%)	15(35.71%)	0.513
Hyperlipidemia	19(42.22%)	14(33.33%)	0.192
Smoking	13(28.89)	10(23.81%)	0.467
Drinking	9(20%)	8(19.05%)	0.789
Fezakas	1.833±0.82	0	＜0.001
Education	9.36±3.18	10.02±3.26	0.466
MOCA	24.36±2.31	26.11±1.87	＜0.001
WMH=White Matter Hyperintensity; MOCA=Montreal Cognitive Assessment

TABLE 2. Logistic Regression of Risk Factors for WMH.
Clinical Characteristics	Odds ratio (95% CI)	P value
Age	1.109(0.995-1.236)	0.061
Hypertension	1.734(0.626-4.804)	0.290
MOCA	0.766(0.594-0.986)	0.039
MATK	0.498(0.268-0.927)	0.028
WMH=White Matter Hyperintensity; MOCA=Montreal Cognitive Assessment

No competing interests reported.

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The expression and clinical significance of MATK in chronic hypoperfusion patients with white matter hyperintensity

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Abstract

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Introduction

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Discussion

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Methods

Study population

Cognitive assessment

Imaging Acquisition

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