Obesity is a major chronic disease associated with the risk of serious cardiovascular or endocrinal diseases, such as hypertension, diabetes, atherosclerosis and stroke. Considerable interest has been directed towards the potential effects of epigenetic variations in obesity. In this study, we evaluated DNA methylation level at the promoter region of the gene encoding TSPO-associated protein 1 antisense RNA 1 (TSPOAP1-AS1) in 80 overweight/obese subjects (body mass index (BMI) > 25) and 104 non-obese subjects who participated in the SOPI-Stroke study in Korea. DNA methylation was measured using bisulfite amplicon sequencing (BSAS). A general linear model or relative correlation was used to determine the effects of DNA methylation on obesity and obese phenotypes. Notably, the mean level of DNA methylation was significantly higher in the overweight/obese group than in the non-obese group (18.62% vs. 17.18%). Further analyses revealed significant positive correlations of the BMI, the serum total cholesterol and low-density lipoprotein cholesterol levels with the DNA methylation level (p = 0.0493, p = 0.003, and p = 0.0094, respectively). The study findings suggest an association between DNA methylation at the TSPOAP1-AS1 promoter and overweight/obesity. Accordingly, methylation in this promoter region might be a potential predictor of obesity.

Background: Patients with stroke have various syndromes and symptoms. Through pattern identification (PI), traditional Korean medicine (TKM) classifies the several syndromes and symptoms of stroke patients into five categories: Fire-heat (FH), Dampness-phlegm (DP), Yin-deficiency (YD), Qi-deficiency (QD) and Blood-stasis (BS). DP has been associated with obesity and hyperlipidemia. Uncoupling protein-1 (UCP-1), which plays a major role in thermogenesis and energy expenditure can increase the risk of obesity and can be related metabolic disorders. In this study, we elucidated the association of three polymorphisms located in the UCP-1 promoter and coding region with DP among Korean stroke patients. Methods: 1,593 patients with cerebral infarction (583/DP, 1,010/non-DP) and 587 normal subjects were enrolled. The genotypes A-3826G, G-1766A and Ala64Thr (G+1068A) for each subject were determined by polymerase chain reaction with TaqMan probes and five percent of subjects were re-genotyped by sequencing method to confirm the accuracy of genotyping. The results were analyzed using a multiple logistic regression model to evaluate the genetic associations: the UCP-1polymorphisms of normal versus those of DP subjects and those of normal versus those of non-DP subjects. Results: A significantly higher percentage of subjects in the DP group possessed the A-3826G G allele than the A allele (OR=1.508, p=0.006). Furthermore, the number of subjects with the GG type of A-1766G was significantly lower in the non-DP group than the normal group in the recessive model (OR=0.606, p=0.042). In addition, an analysis of the relationship among 2 SNPs of UCP-1 and lipid serum concentration showed that the serum level of HDL cholesterol was significantly higher in subjects with the A-3826G G allele in the normal group (p=0.032). Serum triglyceride and HDL cholesterol were also associated with the A-1766G variant in the recessive model (p=0.002, p=0.046). Conclusions: These results suggest that that the A-3826G and A-1766G UCP-1 polymorphisms, which are related to obesity, might be candidate genetic markers for the DP pattern in the TKM diagnosis system.

To investigate if single nucleotide polymorphisms on chromosome 12p13 and within 11 kb of the gene NINJ2 would be associated with earlier-onset (vs. late-onset) first-ever ischemic stroke and increase silent cerebrovascular lesions prior to the manifestation of the stroke.

Traditional Korean Medicine classifies stroke into four subtype patterns according to symptomatic pattern identification: Qi deficiency (QD), Yin deficiency (YD), Dampness-phlegm (DP), and Fire and Heat (FH). This study investigated the difference in metabolic profiles of plasma comparing subjects displaying non-DP and DP patterns. A total of 141 patients with cerebral infarction enrolled in this study were distributed as non-DP (N=68) and DP (N=73). Anthropometric parameters and symptom/sign index were measured. Metabolic profiling was performed using ultrahigh-performance liquid chromatography-mass spectrometry. The Ratio of subjects with slippery pulse was higher in DP pattern, but fine pulse was lower than that in non-DP pattern. As a result of metabolomics analysis, twenty-one metabolites displayed different levels between non-DP and DP patterns. Two were identified as lysophosphatidylcholines (LPCs), LPC(18:2), and LPC(20:3) having an unsaturated acyl chain and showed lower levels in DP pattern than in non-DP pattern (P=0.015, 0.034, resp.). However, the saturated LPCs, LPC(18:0) and LPC(16:0), exhibited slight but statistically insignificant elevation in DP pattern. Our results demonstrated that plasma LPCs with polyunsaturated fatty acid groups were associated with DP pattern and suggest that variation of plasma lipid profiles may serve as potential biomarker for diagnosis of DP pattern.

Blood stasis (BS) is characterized as a disorder of blood circulation. In traditional Korean medicine (TKM), it is viewed as a cause factor of diseases such as multiple sclerosis and stroke. This study investigated differences in the plasma metabolites profiles of subjects displaying BS or non-BS patterns. Thirty-one patients with cerebral infarction diagnosed with BS and an equal number of sex- and age-matched non-BS patients were enrolled. Metabolic profiling was performed using UPLC-MS. The ratio of subjects with a rough pulse and purple coloration of the tongue was higher in patients presenting with BS pattern. Through metabolomics analysis, 82 metabolites that differed significantly between the BS and non-BS pattern were identified, and the two groups were significantly separated using an orthogonal partial least square-discriminant analysis model(P<0.001). Of these 82 metabolites, acetyl carnitine, leucine, kynurenine, phosphocholine, hexanoyl carnitine, and decanoyl carnitine were present in significantly higher levels in patients with a BS pattern than those with a non-BS pattern. Our results also demonstrated that seven plasma metabolites, including acyl-carnitines and kynurenine, were associated with a BS pattern, suggesting that variant plasma metabolic profiles may serve as a biomarker for diagnosis of BS in patients with cerebral infarction.