Dataset Information

Relative risk values of age, acrolein, IL-6 and CRP as markers of periventricular hyperintensities: a cross-sectional study.

ABSTRACT:

Objective

Brain white matter hyperintensities can be divided into periventricular hyperintensity (PVH) and deep-and-subcortical white matter hyperintensity (DSWMH); the former contributes more to cognitive dysfunction and infarction risk. We conducted the present investigation to define the relationship between PVH and DSWMH.

Design

Cross-sectional study.

Setting

University hospital.

Participants

We prospectively enrolled 228 healthy Japanese volunteers with relative risk values (RRVs) >0.5.

Primary outcome measures

We investigated whether it is possible to use the RRV to predict PVH and DSWMH.

Results

Among 228 volunteers, 103 (45.1%) and 157 (68.8%) exhibited PVH and DSWMH, respectively. Age, body mass index and PVH were significant independent determinants of RRV. A significant OR for PVH was noted in the highest RRV tertile compared with the lowest, after adjusting for potential confounding factors. A significant OR for high predicted PVH risk was found for RRV levels as well.

Conclusions

Elevated RRV levels were significantly associated with increased predicted PVH, suggesting that measuring the plasma protein-conjugated acrolein, interleukin 6 and C reactive protein levels may be useful for identifying Japanese at high risk for PVH.

SUBMITTER: Abe A

PROVIDER: S-EPMC4139621 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Relative risk values of age, acrolein, IL-6 and CRP as markers of periventricular hyperintensities: a cross-sectional study.

Abe Arata A Nishiyama Yasuhiro Y Harada-Abe Mina M Okubo Seiji S Ueda Masayuki M Mishina Masahiro M Katayama Yasuo Y

BMJ open 20140101 8

<h4>Objective</h4>Brain white matter hyperintensities can be divided into periventricular hyperintensity (PVH) and deep-and-subcortical white matter hyperintensity (DSWMH); the former contributes more to cognitive dysfunction and infarction risk. We conducted the present investigation to define the relationship between PVH and DSWMH.<h4>Design</h4>Cross-sectional study.<h4>Setting</h4>University hospital.<h4>Participants</h4>We prospectively enrolled 228 healthy Japanese volunteers with relative ...[more]

PMID: 25232562

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Project description:Background and purposePeriventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings.MethodsParticipants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC.ResultsIn the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype.ConclusionsOur study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

Project description:The aim of the study was the evaluation whether in primary colorectal cancer (CRC) patients (n = 55): age, sex, TNM classification results, WHO grade, tumor location (proximal colon, distal colon, rectum), tumor size, platelet count (PLT), mean platelet volume (MPV), mean platelet component (MCP), levels of carcinoembryonic antigen (CEA), cancer antigen (CA 19-9), as well as soluble lectin adhesion molecules (L-, E-, and P-selectins) may influence circulating inflammatory biomarkers: IL-6, CRP, and sCD40L. We found that CRP concentration evaluation in routine clinical practice may have an advantage as a prognostic biomarker in CRC patients, as this protein the most comprehensively reflects clinicopathological features of the tumor. Univariate linear regression analysis revealed that in CRC patients: (1) with an increase in PLT by 10 × 103/μL, the mean concentration of CRP increases by 3.4%; (2) with an increase in CA 19-9 of 1 U/mL, the mean concentration of CRP increases by 0.7%; (3) with the WHO 2 grade, the mean CRP concentration increases 3.631 times relative to the WHO 1 grade group; (4) with the WHO 3 grade, the mean CRP concentration increases by 4.916 times relative to the WHO 1 grade group; (5) with metastases (T1-4N+M+) the mean CRP concentration increases 4.183 times compared to non-metastatic patients (T1-4N0M0); (6) with a tumor located in the proximal colon, the mean concentration of CRP increases 2.175 times compared to a tumor located in the distal colon; (7) in patients with tumor size > 3 cm, the CRP concentration is about 2 times higher than in patients with tumor size ≤ 3 cm. In the multivariate linear regression model, the variables that influence the mean CRP value in CRC patients included: WHO grade and tumor localization. R2 for the created model equals 0.50, which indicates that this model explains 50% of the variance in the dependent variable. In CRC subjects: (1) with the WHO 2 grade, the mean CRP concentration rises 3.924 times relative to the WHO 1 grade; (2) with the WHO 3 grade, the mean CRP concentration increases 4.721 times in relation to the WHO 1 grade; (3) with a tumor located in the rectum, the mean CRP concentration rises 2.139 times compared to a tumor located in the distal colon; (4) with a tumor located in the proximal colon, the mean concentration of CRP increases 1.998 times compared to the tumor located in the distal colon; if other model parameters are fixed.

Dataset Information

Relative risk values of age, acrolein, IL-6 and CRP as markers of periventricular hyperintensities: a cross-sectional study.

Objective

Design

Setting

Participants

Primary outcome measures

Results

Conclusions

Publications

Relative risk values of age, acrolein, IL-6 and CRP as markers of periventricular hyperintensities: a cross-sectional study.

Similar Datasets

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