Association of Genetic Variation in a Wnt Signaling Pathway Gene ( β-Catenin ) with Susceptibility to Leukoaraiosis

Abstract

Aim:

Blood-brain barrier (BBB) disruption is the primary initiating cause of cerebral small-vessel diseases including leukoaraiosis (LA). β-Catenin is a key regulator of the BBB and plays an important role in cell-cell adhesion at adherens junctions by interacting with cadherin molecules. Thus, β-Catenin may be a good candidate gene for LA. We performed a genetic analyses to investigate the association between β-catenin alleles and LA.

Materials and Methods:

A total of 339 LA cases and 203 controls were enrolled from individuals who underwent brain magnetic resonance imaging with obtainable vascular risk factors. Genotyping of β-catenin single nucleotide polymorphisms (SNPs), including rs1880481 C > A, rs13072632 C > T, and rs4135385 A > G, was performed by real-time polymerase chain reaction using a LightCycler 2.0.

Results:

Two SNPs, rs1880481 and rs4135385, showed significant differences in their allelic frequencies between the control and LA groups and the combinatorial effects of the risk alleles for these two SNPs also significantly increased the risk of LA. The G-T-A, A-T-A, and A-T-G haplotypes for the three SNPs showed significant differences in both types of LA: LA-periventricular white matter and LA-deep white matter. However, the C-T-G haplotype was only significantly different for LA-PVWM, while the A-C-A was only significantly different for LA-DWM. The combination of diabetes mellitis, hypertension, and these risk alleles increased the likelihood of both types of LA.

Conclusion:

This study provides evidence that β-catenin polymorphisms and their associated haplotypes are associated with susceptibility to LA.

Introduction

Leukoaraiosis (LA) is regarded as a part of the normal aging process in brains of elderly and demented individuals, especially in those with vascular risk factors, and is found as bilateral, patchy, or diffuse areas of hypodensity on computed tomography scans or hyperintensities on T2-weighted magnetic resonance imaging (MRI) scans (de Leeuw et al., 2001; Ward, 2002; Pantoni, 2010). LA is classified into two major groups using the Fazekas scale, and each group is given a grade depending on the size and confluence of white matter lesions (Fazekas et al., 1987). LA is a prognostic indicator of lacunar infarction (Inzitari et al., 1987), and an independent risk factor for both ischemic and hemorrhagic stroke (George et al., 1986; Breteler et al., 1994), which is the second most common cause of death throughout the world and a major cause of long-term disability in adults (Lopez et al., 2006).

A study by Wardlaw (2010) concluded that derangement of the blood-brain barrier (BBB) is the primary initiating cause of cerebral small-vessel disease (SVD). The BBB is a specialized structure in the brain that maintains the neuronal microenvironment and plays a pivotal role in central nervous system homeostasis during physiological and pathological processes (Zheng et al., 2003). The major components of the BBB are brain microvascular endothelial cells (BMVECs), astrocytes, basement membrane, and pericytes and neurons that are in close physical proximity to the endothelia. The junctional complexes between BMVECs include tight junctions (TJs) comprising occludin, claudins, zonula occludens, cingulin, AF6, and 7H6; adherens junctions (AJs) comprising cadherins, catenins, vinculin, and actinin; and junctional adhesion molecules (Doolittle et al., 2005). The cadherin protein of the AJ joins the actin cytoskeleton to α-, β-, and γ-catenin scaffolding proteins to form adhesive contacts between cells. Thus, AJs hold the cells together, giving structural support to brain tissue. They are also involved in the formation of TJs, and any disruption in AJs also causes the breakdown of the BBB (Wolburg and Lippoldt, 2002).

β-Catenin, which is encoded by the Catenin β-1 gene, is a well-recognized transcriptional coactivator situated in the Wnt/β-catenin pathway (Willert and Nusse, 1998). The Wnt/β-catenin pathway is a well-understood, transcriptionally active signaling cascade that acts as a major regulator of brain development through β-catenin stabilization (Schuller and Rowitch, 2007; Chenn, 2008). At the AJ, β-catenin plays an important role in cell-cell adhesion by interacting with cadherin molecules. Thus, any alteration to AJs can alter other neighboring structures, including TJs. β-Catenin is mainly involved in the regulation of TJ proteins (e.g., protein kinase and G-proteins). During embryonic and postnatal development, Wnt/Catenin β-1 signaling regulates BBB induction and maintenance. β-Catenin also enhances BBB maturation by inducing the expression of mRNA and the claudin-3 protein, whereas its inactivation causes a significant downregulation in claudin-3 and upregulation of the plasmalemma vesicle-associated protein, which results in a compromised BBB (Liebner et al., 2008). The T cell factor 4/β-catenin complex can further regulate E-cadherin transcription by binding to its promoter region (Huber et al., 1996). Therefore, any ablation of β-catenin leads to deficient cell-cell contacts and increased paracellular permeability (Cattelino et al., 2003). These findings provide a direct link among E-cadherin, β-catenin, and Wnt signaling and demonstrate the role of the Wnt/β-catenin pathway as a key regulator of the BBB. Therefore, β-catenin is a good candidate gene for LA. Previous studies have reported that a mutation in β-catenin causes stabilization and cytoplasmic and nuclear accumulation of β-catenin (Morin et al., 1997; Rubinfeld et al., 1997; Palacios and Gamallo, 1998). Several studies on different carcinomas have demonstrated that a mutation in Catenin β-1 also leads to increased β-catenin accumulation and its impaired degradation (Chesire et al., 2000; Ebert et al., 2002; Bjorklund et al., 2008).

LA is correlated with motor and gait disturbances, depressive symptoms, urinary disturbances, and some cognitive deficits and considered as an unfavorable prognostic marker in acute stroke, hemorrhagic transformation of thrombolysis of the brain infarct, and dementia (Guttmann et al., 2000). The exact pathogenesis of LA is still unclear, although advanced age, hypertension, atherosclerosis, and ischemia of the subcortical white matter are suggested (George et al., 1986; Ostrow and Miller, 1993; Breteler et al., 1994). However, genetic factors are thought to be important in any type of cerebrovascular disease (Brass et al., 1992; Carmelli et al., 1998). To understand the genetic basis of LA, we hypothesized that defects in Wnt signaling pathway genes and proteins are responsible for alterations in the BBB structure and function that promote LA. However, to date, no study has been conducted to investigate any type of association between β-catenin genetic polymorphisms and LA. Therefore, this study was designed to investigate the associations between β-catenin genetic polymorphisms and LA.

Materials and Methods

Study population

The study subjects were only, in part, the same as included in our previous study (Yadav and Shin, 2018). After obtaining ethical approval from the Institutional Review Board of Jeonbuk National University Hospital, Jeonju, South Korea (Reference No: CUH 2014-01-028), LA patients and controls were enrolled from individuals visiting the neurology clinic who underwent a brain MRI with obtainable vascular risk factors. Written informed consent was obtained from each participant.

LA patients were rated using the Fazekas scale, which included two major groups, periventricular white matter (PVWM) and subcortical deep white matter (DWM), and each group was assigned a grade depending on the size and confluence of white matter lesions (Fazekas et al., 1987). Subjects with grades 0 and 1, who had no clinically significant neurological disease, were categorized as controls and those with grades 2 and 3 were categorized as disease cases. As per this classification protocol, a total of 339 LA patients (183 LA-PVWM and 156 LA-DWM) and 203 controls were enrolled.

Blood collection, biochemical analysis, and genotyping

Venous blood samples (10 mL) taken under fasting conditions from all study subjects were collected and divided into two-vials: 5 mL in an ethylenediaminetetraaceticacid (EDTA) vial for DNA extraction and also in a plain gel tube for serum separation for biochemical analysis.

Genomic DNA was extracted and purified from EDTA blood using the QuickGene DNA Whole Blood Kit S (Life Science, Tokyo, Japan), according to the manufacturer's instructions. The specific serum biochemical parameters were analyzed at the Department of Laboratory Medicine as daily routine work with a standardized protocol. Single nucleotide polymorphisms (SNPs) in the β-catenin gene were selected based on their functional significance as key components in the Wnt signaling pathway. These SNPs were identified by searching the dbSNP database, and SNPs with a minor allele frequency >0.15 were given higher priority. Furthermore, based on previous findings (Sims et al., 2008; Feng et al., 2011; Alanazi et al., 2013), we decided to include the rs1880481 C > A, rs13072632 C > T, and rs4135385 A > G SNPs in this study. Genotyping of these SNPs was performed by real-time polymerase chain reaction (PCR) with a LightCycler 2.0 real-time PCR instrument (Roche Applied Science, Mannheim, Germany) using the LightSNiP reagent (coupled with primers and probes; TIBMOLBIO, Berlin, Germany) and FastStart DNA Master HybProbe (Roche Diagnostics GmBH, Mannheim, Germany). Amplifications were performed as per the manufacturer's recommendation. The obtained data were analyzed using Gene Scanning software (Roche Diagnostics). Only PCR samples showing clear melting curves were included in the study. Double-distilled sterilized water (PCR grade) was used as a negative control to confirm the accuracy of the PCR process.

Statistical analysis

Differences in demographic characteristics, vascular risk factors, and biochemical parameters between cases and controls were initially compared using Fisher's exact test for categorical variables and the chi-square (χ²) test for continuous variables. Genotype and allele frequencies between cases and controls were compared by the χ² test Yates correction or Fisher's exact test using SPSS 16.0 (SPSS, Chicago, IL). Multiple logistic regression analysis was performed to evaluate the role of the β-catenin genotype and other confounding variables, including age, sex, and hypertension. Haplotype analysis was performed using case-controlled haplotype analysis-permutation tests. Allele frequencies were calculated by the gene counting method (Hardy-Weinberg equilibrium). The odds ratio (OR) was calculated with GraphPad Prism 4.0 (GraphPad Software, Inc., San Diego, CA) and MedCalc (version 7.4 for Windows; Frank Schoonjans, Belgium). One-way analysis of variance was used to compare the mean levels of different biochemical parameters among the different genotypes. In all cases, a p-value <0.05 was considered statistically significant based on three or more independent experiments. Post hoc significance values were adjusted using the Bonferroni correction.

Results

The demographic and clinical characteristics of the study subjects are presented in our previous study (Yadav and Shin, 2018). The results showed that advanced age, being female, and hypertension are aggravating factors for LA and can influence the risk estimation of genetic factors in LA patients.

The genotype distributions for rs1880481 and rs4135385 were found to be significantly different between both LA types (PVWM and DWM) and controls (p < 0.05). Subjects carrying the rs1880481 AA genotype and the rs4135385 AG genotype exhibited an increased risk for both LA-PVWM (OR = 3.19, p < 0.05, and OR = 1.81, p < 0.05, respectively) and LA-DWM (OR = 4.05, p < 0.001, and OR = 2.23, p < 0.05, respectively). However, there were no statistically significant differences in the rs13072632 genotype and allelic frequencies between the controls and both types of LA. We also investigated two different inheritance models, including a dominant model (homozygous wild type vs. variant-containing genotype) and a recessive model (wild type-containing genotype versus homozygous variant genotype). In the dominant model, a subject carrying the rs1880481 AC/AA genotype showed a 1.55- and 2.02-fold increased risk for development of LA-PVWM and LA-DWM, respectively. Similarly, individuals carrying the rs4135385 AG/GG genotype showed a 1.79- and 1.81-fold increased risk for development of LA-PVWM and LA-DWM, respectively. However, in the recessive model, the rs1880481 AA genotype only showed a 2.48- and 3.20-fold increased risk for LA-PVWM and LA-DWM, respectively. We further investigated the adjusted odds ratio acquired with logistic regression analysis with respect to age, sex, and hypertension as these characteristics were significantly different in the cases and controls and found that rs4135385 remained statistically significant for both types of LA, while rs1880481 only showed a significant association with LA-DWM (Table 1). We next investigated the combined effect of all these SNPs on LA. When rs1880481 and rs4135385 were combined, the risk for LA was dramatically increased up to 13-fold for LA-PVWM [OR = 4.0 for AC/AG, OR = 13.25 for AA/AG, and OR = 3.79 for (AC + AA)/(AG + GG)] and up to 19-fold for LA-DWM [OR = 5.54 for AC/AG, OR = 19 for AA/AG, and OR = 5.23 for (AC + AA)/(AG + GG)] (Table 2).

Table 1.

Comparison of Genetic Frequencies of β-Catenin Polymorphisms in the Control and Leukoaraiosis Patients

Genotypes	Control (n = 203, %)	LA-PVWM (n = 183, %)	OR (95% CI), p	AOR (95% CI), p
rs1880481
CC	125 (61.6)	93 (50.8)	1.0 (Reference)	1.0 (Reference)
AC	70 (34.5)	71 (38.8)	1.36 (0.89-2.086), 0.15	1.14 (0.69-1.89), 0.58
AA	8 (3.9)	19 (10.4)	3.19 (1.33-7.61), 0.006	2.37 (0.82-6.84), 0.108
Dominant (CC vs. AC + AA)	125/78	93/80	1.55 (1.03-2.32), 0.033	1.28 (0.79-2.07), 0.30
Recessive (CC + AC vs. AA)	175/8	167/19	2.48 (1.061-5.84), 0.0312	2.35 (0.84-6.53), 0.105
rs13071632
CC	11 (5.4)	10 (5.5)	1.0 (Reference)	1.0 (Reference)
CT	67 (33.0)	66 (36.1)	1.08 (0.43-2.72), 0.86	0.96 (0.32-2.90), 0.95
TT	125 (61.6)	107 (58.5)	0.94 (0.38-2.30), 0.89	1.13 (0.40-3.21), 0.80
Dominant (CC vs. CT + TT)	11/192	10/173	0.99 (0.41-1.39), 0.98	1.11 (0.40-3.06), 0.83
Recessive (CC + CT vs. TT)	78/125	76/107	0.87 (0.58-1.32), 0.53	1.05 (0.65-1.72), 0.81
rs4135385
AA	83 (40.9)	51 (27.9)	1.0 (Reference)	1.0 (Reference)
AG	87 (42.9)	97 (53.0)	1.81 (1.15-2.85), 0.0097	1.87 (1.81-3.23), 0.022
GG	33 (16.3)	35 (19.1)	1.76 (0.95-3.113), 0.068	1.62 (0.80-3.27), 0.17
Dominant (AA vs. AG + GG)	83/120	51/132	1.79 (1.16-2.74), 0.0073	1.79 (1.07-2.98), 0.0247
Recessive (AA + AG vs. GG)	170/33	148/35	1.21 (0.72-2.05), 0.45	1.12 (0.60-2.10), 0.70
Genotypes	Control (n = 230, %)	LA-DWM (n = 156, %)	OR (95% CI), p	AOR (95% CI), p
rs1880481
CC	146 (63.5)	72 (46.2)	1.0 (Reference)	1.0 (Reference)
AC	75 (32.6)	66 (42.3)	1.78 (1.15-2.75), 0.008	1.64 (1.02-2.63), 0.039
AA	9 (3.9)	18 (11.5)	4.05 (1.73-9.47), 0.0006	3.31 (1.32-8.32), 0.01
Dominant (CC vs. AC + AA)	146/84	72/84	2.02 (1.34-3.067), 0.0008	1.83 (1.17-2.88), 0.008
Recessive (CC + AC vs. AA)	221/9	138/18	3.20 (1.39-7.32), 0.0039	2.72 (1.10-6.71), 0.029
rs13071632
CC	11 (4.8)	10 (6.4)	1.0 (Reference)	1.0 (Reference)
CT	74 (32.2)	59 (37.8)	0.87 (0.34-2.20), 0.78	0.78 (0.27-2.19), 0.64
TT	145 (63.0)	87 (55.8)	0.66 (0.26-1.61), 0.36	0.68 (0.26-1.78), 0.43
Dominant (CC vs. CT + TT)	11/219	10/146	0.73 (0.30-1.77), 0.48	0.72 (0.28-1.88), 0.51
Recessive (CC + CT vs. TT)	85/145	69/87	0.73 (0.48-1.118), 0.15	0.80 (0.51-1.26), 0.34
rs4135385
AA	92 (40.0)	42 (26.9)	1.0 (Reference)	1.0 (Reference)
AG	91 (39.6)	93 (59.6)	2.23 (1.40-3.56), 0.0006	2.34 (1.38-3.95), 0.0014
GG	47 (20.4)	21 (13.5)	0.97 (0.52-1.83), 0.94	0.82 (0.41-1.65), 0.59
Dominant (AA vs. AG + GG)	92/138	42/114	1.81 (1.16-2.81), 0.008	1.79 (1.10-2.91), 0.018
Recessive (AA + AG vs. GG)	183/47	135/21	0.60 (0.34-1.06), 0.077	0.50 (0.27-0.93), 0.02

DWM, deep white matter; LA, leukoaraiosis; PVWM, periventricular white matter; OR, odds ratio; CI, confidence interval; AOR, adjusted odds ratio.

Table 2.

Combinatorial Effects in Leukoaraiosis Subjects According to β-Catenin Genetic Polymorphism

Genotype	Control	LA-PVWM	OR (95% CI)	p
rs1880481/rs4135385
CC/AA	53	16	1.0 (Reference)
AC/AG	35	43	4.0 (1.99-8.3)	<0.0001
AC/GG	9	6	2.2 (0.68-7.15)	0.17
AA/AG	1	4	13.25 (1.38-127.2)	0.0057
AA/GG	3	2	2.20 (0.33-14.4)	0.39
(AC + AA)/(AG + GG)	48	55	3.79 (1.92-7.49)	<0.0001
Genotype	Control	LA-DWM	OR (95% CI)	p
rs1880481/rs4135385
CC/AA	57	12	1.0 (Reference)
AC/AG	36	42	5.54 (2.57-11.91)	<0.0001
AC/GG	9	6	3.16 (0.99-10.58)	0.053
AA/AG	1	4	19.0 (1.94-185.5)	0.001
AA/GG	3	2	3.16 (0.47-21.06)	0.21
(AC + AA)/(AG + GG)	49	54	5.23 (2.51-10.90)	<0.0001

Notably, neither rs13072632 alone nor in combination with rs1880481 and rs4135385 showed any significant associations with LA development. We performed further haplotype analysis with each SNP and found that several haplotype frequencies were significantly different between the control and both types of LA (Table 3). The C-T-A, A-T-A, A-C-G, and A-T-G haplotypes (rs1880481/rs13072632/rs4135385) were significantly different in both types of LA. However, C-T-G and A-C-A haplotypes were significantly different in only one type of LA (LA-PVWM and LA-DWM, respectively).

Table 3.

Haplotype Frequency of β-Catenin in Controls and Leukoaraiosis-Periventricular White Matter Patients

Genotype	Control	LA-PVWM	OR (95%CI)	p-Value
rs1880481/rs13071632/rs4135385
C-C-A	0.0059	0.0048	1.11 (0.05-7.92)	0.91
A-C-A	0.1242	0.201	0.9 (0.63-1.27)	0.33
C-T-A	0.493	0.2914	0.42 (0.31-0.57)	<0.0001
A-T-A	0	0.0465	40.7 (2.43-679.9^*)	<0.0001
C-C-G	0.0065	0.0041	0.156 (0.019-1.276)	0.05
A-C-G	0.0826	0.0251	0.285 (0.134-0.60)	0.0005
C-T-G	0.2828	0.4019	0.108 (0.06-0.188)	<0.0001
A-T-G	0.005	0.0252	5.09 (1.09-23.73)	0.021
rs1880481/rs13071632/rs4135385
C-C-A	0.0058	0.0035	0.5 (0.05-4.73)	0.52
A-C-A	0.1296	0.2141	1.82 (1.24-2.67)	0.0019
C-T-A	0.4558	0.3004	0.51 (0.37-0.69)	<0.0001
A-T-A	0.0066	0.0494	7.69 (2.20-26.81)	0.0002
C-C-G	0.0073	0.0036	0.5 (0.05-4.73)	0.52
A-C-G	0.066	0.0321	0.47 (0.22-0.98)	0.04
C-T-G	0.3289	0.3657	1.17 (0.87-1.59)	0.28
A-T-G	0	0.314	31.97 (1.86-548.0)	0.0001

Furthermore, we sought to determine whether β-catenin polymorphisms were associated with environmental risk factors such as hypertension, diabetes, total homocysteine, and other biochemical parameters (Tables 4 and 5). This analysis demonstrated that both the rs1880481 and rs4135385 variant-containing genotypes displayed significantly higher numbers of individuals with hypertension, diabetes, and homocysteine among LA patients compared with controls, which dramatically increased the risk of LA.

Table 4.

Stratified Effects Between Genotypes and Environmental Factors for Leukoaraiosis-Periventricular White Matter Patients

Factors	Genotype	Control	LA-PVWM	OR (95% CI)	p
Hypertension
	rs1880481
No	CC	58	29	1.0 (Reference)
No	CA + AA	32	20	2.25 (0.61-2.55)	0.54
Yes	CC	67	64	1.91 (1.08-3.35)	0.023
Yes	CA + AA	45	70	3.11 (1.73-5.57)	<0.0001
	rs13071632				0.0075
No	CC	7	3	1.0 (Reference)
No	CT + TT	83	46	1.29 (0.31-5.24)	0.71
Yes	CC	3	7	5.44 (0.80-36.88)	0.01
Yes	CT + TT	108	127	2.74 (0.69-10.87)	0.13
	rs4135385
No	AA	39	15	1.0 (Reference)
No	AG + GG	51	34	1.73 (0.82-3.62)	0.14
Yes	AA	44	36	2.12 (1.01-4.46)	0.044
Yes	AG + GG	68	96	3.67 (1.887-7.18)	<0.0001
Diabetes
	rs1880481
No	CC	90	56	1.0 (Reference)
No	CA + AA	54	62	1.55 (0.96-2.52)	0.07
Yes	CC	35	37	1.69 (0.96-3.005)	0.06
Yes	CA + AA	23	28	1.95 (1.02-3.728)	0.039
	rs13071632
No	CC	10	6	1.0 (Reference)
No	CT + TT	134	112	1.39 (0.49-3.95)	0.53
Yes	CC	1	4	0.66 (0.59-74.55)	0.097
Yes	CT + TT	57	61	1.78 (0.60-5.22)	0.28
	rs4135385
No	AA	57	33	1.0 (Reference)
No	AG + GG	87	85	1.68 (1.00-2.84)	0.048
Yes	AA	26	18	1.86 (0.93-3.68)	0.07
Yes	AG + GG	47	32	1.17 (0.63-2.18)	0.608
HTN + DM
	rs1880481
No	CC	47	18	1.0 (Reference)
No	CA + AA	28	16	1.49 (0.65-3.38)	0.377
Yes	CC	24	26	2.89 (1.30-6.15)	0.007
Yes	CA + AA	19	24	3.29 (1.46-7.42)	0.0033
	rs13071632
No	CC	7	2	1.0 (Reference)
No	CT + TT	68	32	1.64 (0.32-8.38)	0.544
Yes	CC	1	3	10.50 (0.66-165.2)	0.07
Yes	CT + TT	42	47	3.91 (0.77-19.91)	0.80
	rs4135385
No	AA	28	10	1.0 (Reference)
No	AG + GG	47	24	1..43 (0.59-3.42)	0.42
Yes	AA	15	13	2.42 (0.86-6.83)	0.09
Yes	AG + GG	37	28	2.11 (0.88-5.07)	0.088
Homocysteine
	rs1880481
<12 μmol/L	CC	63	33	1.0 (Reference)
<12 μmol/L	CA + AA	37	33	1.70 (0.90-3.19)	0.09
≥12 μmol/L	CC	61	59	1.84 (1.06-3.21)	0.028
≥12 μmol/L	CA + AA	41	57	3.49 (1.97-6.61)	<0.0001
	rs13071632
<12 μmol/L	CC	2	4	1.0 (Reference)
<12 μmol/L	CT + TT	98	62	0.31 (0.05-1.78)	0.17
≥12 μmol/L	CC	9	6	0.33 (0.45-2.43)	0.26
≥12 μmol/L	CT + TT	93	110	0.59 (0.10-3.30)	0.54
	rs4135385
<12 μmol/L	AA	42	19	1.0 (Reference)
<12 μmol/L	AG + GG	58	47	1.79 (0.92-3.48)	0.08
≥12 μmol/L	AA	40	32	1.76 (0.86-3.61)	0.116
≥12 μmol/L	AG + GG	62	84	2.99 (1.58-5.640)	0.0005

Table 5.

Stratified Effects Between Genotypes and Environmental Factors for Leukoaraiosis-Deep White Matter Patients

LA-DWM	SNP1	Control	Case	OR (95% CI)	p
Hypertension
	rs1880481
No	CC	64	23	1.0 (Reference)
No	CA + AA	32	20	1.73 (0.83-3.62)	0.13
Yes	CC	82	49	1.66 (0.91-3.011)	0.09
Yes	CA + AA	51	64	3.49 (1.91-6.37)	<0.0001
	rs13071632
No	CC	7	3	1.0 (Reference)
No	CT + TT	89	40	1.04 (0.25-4.26)	0.94
Yes	CC	4	7	4.08 (0.65-25.39)	0.12
Yes	CT + TT	106	129	2.84 (0.71-11.25)	0.122
	rs4135385
No	AA	43	11	1.0 (Reference)
No	AG + GG	53	32	2.36 (1.06-5.224)	0.0317
Yes	AA	49	31	2.47 (1.11-5.50)	0.0245
Yes	AG + GG	84	82	3.81 (1.84-7.91)	0.0002
Diabetes
	rs1880481
No	CC	100	46	1.0 (Reference)
No	CA + AA	58	58	2.17 (1.31-3.60)	0.0024
Yes	CC	46	26	1.22 (0.67-2.22)	0.49
Yes	CA + AA	25	26	2.26 (1.17-4.33)	0.0129
	rs13071632
No	CC	8	8	1.0 (Reference)
No	CT + TT	150	96	0.64 (0.23-1.76)	0.38
Yes	CC	2	2	1.0090.11-8.95)	1.00
Yes	CT + TT	68	50	0.73 (0.25-2.09)	0.56
	rs4135385
No	AA	61	29	1.0 (Reference)
No	AG + GG	97	75	1.62 (0.95-2.77)	0.07
Yes	AA	31	13	0.88 (0.40-1.933)	0.75
Yes	AG + GG	40	39	2.05 (1.09-3.83)	0.023
HTN + DM
	rs1880481
No	CC	48	17	1.0 (Reference)
No	CA + AA	28	16	1.61 (0.70-3.688)	0.255
Yes	CC	30	20	1.88 (0.85-4.15)	0.115
Yes	CA + AA	21	22	2.95 (1.31-6.68)	0.0081
	rs13071632
No	CC	7	2	1.0 (Reference)
No	CT + TT	69	31	1.57 (0.30-8.01)	0.58
Yes	CC	3	1	1.16 (0.07-18.36)	0.91
Yes	CT + TT	48	41	2.99 (0.58-15.20)	0.16
	rs4135385
No	AA	30	8	1.0 (Reference)
No	AG + GG	46	25	2.03 (0.81-5.11)	0.12
Yes	AA	18	10	2.08 (0.69-6.24)	0.18
Yes	AG + GG	33	32	3.63 (1.45-9.11)	0.0046
Homocysteine
	rs1880481
<12 μmol/L	CC	70	26	1.0 (Reference)
<12 μmol/L	CA + AA	41	29	1.90 (0.98-3.66)	0.05
≥12 μmol/L	CC	75	45	1.61 (0.93-2.89)	0.105
≥12 μmol/L	CA + AA	43	55	3.44 (1.88-6.28)	<0.0001
	rs13071632
<12 μmol/L	CC	3	3	1.0 (Reference)
<12 μmol/L	CT + TT	108	52	0.48 (0.09-2.46)	0.37
≥12 μmol/L	CC	7	8	1.14 (0.17-7.60)	0.89
≥12 μmol/L	CT + TT	110	93	0.84 (0.166-4.29)	0.83
	rs4135385
<12 μmol/L	AA	47	14	1.0 (Reference)
<12 μmol/L	AG + GG	64	41	2.15 (1.05-4.39)	0.0336
≥12 μmol/L	AA	44	28	2.13 (0.99-4.57)	0.048
≥12 μmol/L	AG + GG	74	72	3.26 (1.65-6.44)	0.0004

SNP, single nucleotide polymorphism.

Finally, we also examined the genetic association of β-catenin with different biochemical analytes in LA subjects and controls. None of the β-catenin SNP genotypes showed any significant difference between the control and LA subjects on biochemical analysis (data not shown).

Discussion

Cerebral SVD occurs in lacunar stroke, LA, and subcortical ischemic dementia. The BBB becomes more permeable with aging, and permeability progressively increases in patients with vascular cognitive damage, including LA patients (Farrall and Wardlaw, 2009). BBB derangement is the principal initiating cause of cerebral SVD such as LA (Wardlaw, 2010).

β-Catenin is a well-recognized transcriptional coactivator situated in the Wnt/β-catenin pathway. The Wnt/β-catenin pathway is a transcriptionally active signaling cascade that acts as a major regulator of brain development through β-catenin stabilization. During embryonic and postnatal development, Wnt/β-catenin signaling regulates the formation and maintenance of the BBB and enhances its maturation (Schuller and Rowitch, 2007; Chenn, 2008; Liebner et al., 2008). Therefore, Wnt/β-catenin signaling is a key regulator of the BBB and it appears to be a good candidate gene for LA susceptibility. We hypothesized that changes in the β-catenin gene may alter the structure and function of BBB due to its accumulation at junctional complexes in the BBB, which may initiate the development of LA. Several previous studies have shown a significant association between genetic polymorphisms of β-catenin genes and different diseases (Voeller et al., 1998; Machin et al., 2002; Wang et al., 2012; Alanazi et al., 2013; Hu et al., 2014; Liu et al., 2014; Yu et al., 2016; Wang et al., 2020), unfortunately most of them are in cancer patients. Our study provides the first evidence of association between β-catenin genetic polymorphisms and LA susceptibility in LA patients.

Among the three SNPs in the β-catenin gene analyzed in this study, only rs1880481 C > A and rs4135385 A > G were found to have significant associations with LA susceptibility. Individuals carrying the A- (rs1880481) and G-alleles (rs4135385) demonstrated a higher risk for LA. The rs1880481 and rs4135385 variant genotypes conferred increased risk for both types of LA. Furthermore, the AA/AG combination of rs1880481 and rs4135385 was associated with a higher risk for LA than other combinations. Moreover, combination analyses indicated that polymorphic loci in the β-catenin gene interact with one another, thus showing synergistic effects on LA susceptibility. It is well documented that the haplotype analysis is superior to SNP analysis for identifying the risk of specific genotypes for specific diseases (Humar et al., 2002; Yamada et al., 2007). We also found that the A-T-A and A-T-G haplotypes (rs1880481/rs13072632/rs4135385) increased the susceptibility to develop both types of LA, whereas the C-T-A, C-C-G, and A-C-G haplotypes (rs1880481/rs13072632/rs4135385) showed protective effects against LA. Thus, our study of β-catenin genetic polymorphisms and their further haplotype analyses demonstrated evidence for an increased susceptibility to LA. β-Catenin with its partner proteins (cadherin, plakoglobin, and vinculin) also plays a vital role in the structural stabilization of AJ complexes in the BBB (Doolittle et al., 2005). Any damage to AJs causes BBB disruption (Wolburg and Lippoldt, 2002), which may play a major role in any type of white matter disease, including LA (Young et al., 2008; Wardlaw, 2010). LA is a complicated, multifactorial pathogenic disease whose exact mechanism is not clear yet, but it is speculated that the function of β-catenin is altered due to these genetic changes, which affect RNA splicing that leads to aberrant β-catenin expression (Modrek et al., 2001). However, there are no published reports showing altered protein functions or cellular phenotypes associated with these SNPs. Therefore, in this preliminary study, we aimed to study one important gene (β-catenin) involved in Wnt signaling and identify significant associations with LA. Previous studies have documented that both genetic and vascular risk factors, that is, diabetes, hypertension, and hyperhomocysteinemia, are major contributing factors to LA susceptibility and its progression (Lindgren et al., 1994; Roybal et al., 2004; Hill and Bisognano, 2005). Several studies have reported that diabetes is an aggravating factor for cerebral vascular disease (Giorda et al., 2007; Sunaga et al., 2008), and our study also showed that subjects with the rs1880481 and rs413538 variant genotypes with diabetes had a higher risk for LA susceptibility. We also encountered an individual with hypertension and mutated rs1880481 and rs4135385 genotypes who had an even higher risk of developing LA. More importantly, individuals with the mutated rs1880481 and rs4135385 genotypes who presented with both hypertension and diabetes had a higher risk of developing LA than if they had diabetes or hypertension alone. Hyperhomocysteinemia is one of the leading causes of endothelial dysfunction that promotes platelet activation and thrombus formation, which can develop into cerebrovascular disease (Ross, 1990). Several studies have found an association between hyperhomocysteinemia and cerebral white matter lesions (Vermeer et al., 2002; Dufouil et al., 2003; Wright et al., 2005). In accordance with this finding, our study also demonstrated a higher susceptibility to LA in individuals with high total homocysteine (tHcy) (≥12 μmol/L) and the mutated rs1880481 and rs4135385 genotypes. Based on our results, we suggest a relationship among β-catenin genetic polymorphisms, hypertension, diabetes, tHcy, and LA susceptibility.

The limitations of our study are as follows. Although we attempted to perform this study with a design to minimize limitations, the possibility of some selection bias still exists. Next, our study has a hospital-based case-control design with a small number of subjects in a local area of Korea; thus, these findings cannot be generalized to represent the entire Korean population. The results should be interpreted cautiously since the sample size of the subgroup was too small to make definitive conclusions. Moreover, the absence of a replication study in an independent cohort, which is normally a requirement of a candidate gene association study, is one of the major limitations in the present study. Additional studies using large population-based cohorts are required to validate our result. Furthermore, our result cannot be extrapolated to other races because interethnic variability produces different results across races, so these findings will need to be validated in other ethnic groups. In addition, control subjects were not recruited from a completely healthy population. These individuals were seeking medical attention, but none had clinically significant neurologic disease or a Fazekas scale grade of 1, they were categorized as controls. Finally, the LA severity score was acquired using only a single MRI, and future functional studies will need to be based on genetic polymorphisms.

In summary, our study provides the first evidence of a genetic association between β-catenin and susceptibility to LA, demonstrating that β-catenin is a contributing factor and may be one of the key elements of the underlying mechanisms of LA. Future functional studies are warranted to identify the role of β-catenin in LA susceptibility, after which it can be listed as a genetic marker to predict the risk of LA and other BBB-related diseases.

Footnotes

Acknowledgments

The biospecimens and data used in this study were provided by the Biobank of Jeonbuk National University Hospital, a member of the Korea Biobank Network, which is supported by the Ministry of Health, Welfare, and Family Affairs. All samples derived from the Korea Biobank Network were obtained with informed consent under institutional review board-approved protocols.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was supported by funds from the Biomedical Research Institute, Jeonbuk National University Hospital, South Korea.

References

Alanazi

, Parine

, Shaik

, et al. (2013) Association of single nucleotide polymorphisms in Wnt signaling pathway genes with breast cancer in Saudi patients. PLoS One, 8:e59555.

Bjorklund

, Lindberg

, Akerstrom

, Westin

(2008) Stabilizing mutation of CTNNB1/beta-catenin and protein accumulation analyzed in a large series of parathyroid tumors of Swedish patients. Mol Cancer, 7:53.

Brass

, Isaacsohn

, Merikangas

, Robinette

(1992) A study of twins and stroke. Stroke, 23:221-223.

Breteler

, van Swieten

, Bots

, et al. (1994) Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam study. Neurology, 44:1246-1252.

Carmelli

, DeCarli

, Swan

, et al. (1998) Evidence for genetic variance in white matter hyperintensity volume in normal elderly male twins. Stroke, 29:1177-1181.

Cattelino

, Liebner

, Gallini

, et al. (2003) The conditional inactivation of the beta-catenin gene in endothelial cells causes a defective vascular pattern and increased vascular fragility. J Cell Biol, 162:1111-1122.

Chenn

(2008) Wnt/beta-catenin signaling in cerebral cortical development. Organogenesis, 4:76-80.

Chesire

, Ewing

, Sauvageot

, et al. (2000) Detection and analysis of beta-catenin mutations in prostate cancer. Prostate, 45:323-334.

de Leeuw

, de Groot

, Achten

, et al. (2001) Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam scan study. J Neurol Neurosurg Psychiatry, 70:9-14.

10.

Doolittle

, Abrey

, Bleyer

, et al. (2005) New frontiers in translational research in neuro-oncology and the blood-brain barrier: report of the tenth annual Blood-Brain Barrier Disruption Consortium Meeting. Clin Cancer Res, 11:421-428.

11.

Dufouil

, Alperovitch

, Ducros

, Tzourio

(2003) Homocysteine, white matter hyperintensities, and cognition in healthy elderly people. Ann Neurol, 53:214-221.

12.

Ebert

, Fei

, Kahmann

, et al. (2002) Increased beta-catenin mRNA levels and mutational alterations of the APC and beta-catenin gene are present in intestinal-type gastric cancer. Carcinogenesis, 23:87-91.

13.

Farrall

, Wardlaw

(2009) Blood-brain barrier: ageing and microvascular disease—systematic review and meta-analysis. Neurobiol Aging, 30:337-352.

14.

Fazekas

, Chawluk

, Alavi

, et al. (1987) MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. AJR Am J Roentgenol, 149:351-356.

15.

Feng

, Mokrousov

, Wang

, et al. (2011) Tag SNP polymorphism of CCL2 and its role in clinical tuberculosis in Han Chinese pediatric population. PLoS One, 6:e14652.

16.

George

, de Leon

, Gentes

, et al. (1986) Leukoencephalopathy in normal and pathologic aging: 1. CT of brain lucencies. AJNR Am J Neuroradiol, 7:561-566.

17.

Giorda

, Avogaro

, Maggini

, et al. (2007) Incidence and risk factors for stroke in type 2 diabetic patients: the DAI study. Stroke, 38:1154-1160.

18.

Guttmann

, Benson

, Warfield

, et al. (2000) White matter abnormalities in mobility-impaired older persons. Neurology, 54:1277-1283.

19.

Hill MD, Bisognano JD (2005) Leukoaraiosis: the brain under pressure: target for treatment? Neurology 64:1832-1833.

20.

, Shang

, Zhou

, et al. (2014) Association of genetic variants in Wnt signaling pathway with tuberculosis in Chinese Han population. PLoS One, 9:e93841.

21.

Huber

, Korn

, McLaughlin

, et al. (1996) Nuclear localization of beta-catenin by interaction with transcription factor LEF-1. Mech Dev, 59:3-10.

22.

Humar

, Graziano

, Cascinu

, et al. (2002) Association of CDH1 haplotypes with susceptibility to sporadic diffuse gastric cancer. Oncogene, 21:8192-8195.

23.

Inzitari

, Diaz

, Fox

, et al. (1987) Vascular risk factors and leuko-araiosis. Arch Neurol, 44:42-47.

24.

Liebner

, Corada

, Bangsow

, et al. (2008) Wnt/beta-catenin signaling controls development of the blood-brain barrier. J Cell Biol, 183:409-417.

25.

Lindgren

, Roijer

, Rudling

, et al. (1994) Cerebral lesions on magnetic resonance imaging, heart disease, and vascular risk factors in subjects without stroke. A population-based study. Stroke, 25:929-934.

26.

Liu

, Patel

, Mills

, et al. (2014) Clinical significance of CTNNB1 mutation and Wnt pathway activation in endometrioid endometrial carcinoma. J Natl Cancer Inst, 106:dju245.

27.

Lopez

, Mathers

, Ezzati

, et al. (2006) Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. Lancet, 367:1747-1757.

28.

Machin

, Catasus

, Pons

, et al. (2002) CTNNB1 mutations and beta-catenin expression in endometrial carcinomas. Hum Pathol, 33:206-212.

29.

Modrek

, Resch

, Grasso

, et al. (2001) Genome-wide detection of alternative splicing in expressed sequences of human genes. Nucleic Acids Res, 29:2850-2859.

30.

Morin

, Sparks

, Korinek

, et al. (1997) Activation of beta-catenin-Tcf signaling in colon cancer by mutations in beta-catenin or APC. Science, 275:1787-1790.

31.

Ostrow

, Miller

(1993) Pathology of small artery disease. Adv Neurol, 62:93-123.

32.

Palacios

, Gamallo

(1998) Mutations in the beta-catenin gene (CTNNB1) in endometrioid ovarian carcinomas. Cancer Res, 58:1344-1347.

33.

Pantoni

(2010) Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol, 9:689-701.

34.

Ross

(1990) Mechanisms of atherosclerosis—a review. Adv Nephrol Necker Hosp, 19:79-86.

35.

Roybal

, Yang

, Sun

, et al. (2004) Homocysteine increases the expression of vascular endothelial growth factor by a mechanism involving endoplasmic reticulum stress and transcription factor ATF4. J Biol Chem, 279:14844-14852.

36.

Rubinfeld

, Robbins

, El-Gamil

, et al. (1997) Stabilization of beta-catenin by genetic defects in melanoma cell lines. Science, 275:1790-1792.

37.

Schuller

, Rowitch

(2007) Beta-catenin function is required for cerebellar morphogenesis. Brain Res, 1140:161-169.

38.

Sims

, Shephard

, Carter

, et al. (2008) Genetic analyses in a sample of individuals with high or low BMD shows association with multiple Wnt pathway genes. J Bone Miner Res, 23:499-506.

39.

Sunaga

, Miura

, Naruse

, et al. (2008) Glycated hemoglobin and risk of stroke, ischemic and hemorrhagic, in Japanese men and women. Cerebrovasc Dis, 26:310-316.

40.

Vermeer

, van Dijk

, Koudstaal

, et al. (2002) Homocysteine, silent brain infarcts, and white matter lesions: the Rotterdam scan study. Ann Neurol, 51:285-289.

41.

Voeller

, Truica

, Gelmann

(1998) Beta-catenin mutations in human prostate cancer. Cancer Res, 58:2520-2523.

42.

Wang

, Wang

, Li

, et al. (2020) Variations in the Wnt/beta-catenin pathway key genes as predictors of cervical cancer susceptibility. Pharmacogenomics Pers Med, 13:157-165.

43.

Wang

, Tian

, Wu

, et al. (2012) Genetic variation of CTNNB1 gene is associated with susceptibility and prognosis of gastric cancer in a Chinese population. Mutagenesis, 27:623-630.

44.

Ward NS

(2002) Leukoaraiosis. In: Donnan

, Norrving

, Bamford

, Bogousslavsky J (eds) Subcortical Stroke. Oxford. University Press, New York, pp 47-66.

45.

Wardlaw

(2010) Blood-brain barrier and cerebral small vessel disease. J Neurol Sci, 299:66-71.

46.

Willert

, Nusse

(1998) Beta-catenin: a key mediator of Wnt signaling. Curr Opin Genet Dev, 8:95-102.

47.

Wolburg

, Lippoldt

(2002) Tight junctions of the blood-brain barrier: development, composition and regulation. Vascul Pharmacol, 38:323-337.

48.

Wright

, Paik

, Brown

, et al. (2005) Total homocysteine is associated with white matter hyperintensity volume: the northern Manhattan study. Stroke, 36:1207-1211.

49.

Yadav

, Shin

(2018) Single-nucleotide polymorphisms of the adherent junction component cadherin gene are associated with leukoaraiosis. Gene, 676:65-72.

50.

Yamada

, Shinmura

, Ikeda

, et al. (2007) Association between CDH1 haplotypes and gastric cancer risk in a Japanese population. Scand J Gastroenterol, 42:1479-1485.

51.

Young

, Halliday

, Kril

(2008) Neuropathologic correlates of white matter hyperintensities. Neurology, 71:804-811.

52.

, Huang

, Liu

, et al. (2016) Genetic polymorphisms of Wnt/beta-catenin pathway genes are associated with the efficacy and toxicities of radiotherapy in patients with nasopharyngeal carcinoma. Oncotarget, 7:82528-82537.

53.

Zheng

, Aschner

, Ghersi-Egea

(2003) Brain barrier systems: a new frontier in metal neurotoxicological research. Toxicol Appl Pharmacol, 192:1-11.