| Literature DB >> 35893255 |
Drahomira Holmannova1, Pavel Borsky1, Ctirad Andrys2, Kvetoslava Hamakova3, Eva Cermakova4, Gabriela Poctova1, Zdenek Fiala1, Jindra Smejkalova1, Vladimir Blaha5, Lenka Borska1.
Abstract
Psoriasis and metabolic syndrome (MetS), a common comorbidity of psoriasis, are associated with mild chronic systemic inflammation that increases oxidative stress and causes cell and tissue damage. At the cellular level, chromosomal and DNA damage has been documented, thus confirming their genotoxic effect. The main objective of our study was to show the genotoxic potential of chronic inflammation and determine whether the presence of both pathologies increases chromosomal damage compared to psoriasis alone and to evaluate whether there are correlations between selected parameters and chromosomal aberrations in patients with psoriasis and MetS psoriasis. Clinical examination (PASI score and MetS diagnostics according to National Cholesterol Education Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults; NCE/ATPIII criteria), biochemical analysis of blood samples (fasting glucose, total cholesterol, low density and high density lipoproteins; LDL, HDL, non-HDL, and triglycerides;TAG), DNA/RNA oxidative damage, and chromosomal aberration test were performed in 41 participants (20 patients with psoriasis without MetS and 21 with MetS and psoriasis). Our results showed that patients with psoriasis without metabolic syndrome (nonMetS) and psoriasis and MetS had a higher rate of chromosomal aberrations than the healthy population for which the limit of spontaneous, natural aberration was <2%. No significant differences in the aberration rate were found between the groups. However, a higher aberration rate (higher than 10%) and four numerical aberrations were documented only in the MetS group. We found no correlations between the number of chromosomal aberrations and the parameters tested except for the correlation between aberrations and HDL levels in nonMetS patients (rho 0.44; p < 0.02). Interestingly, in the MetS group, a higher number of chromosomal aberrations was documented in non-smokers compared to smokers. Data from our current study revealed an increased number of chromosomal aberrations in patients with psoriasis and MetS compared to the healthy population, especially in psoriasis with MetS, which could increase the genotoxic effect of inflammation and the risk of genomic instability, thus increasing the risk of carcinogenesis.Entities:
Keywords: chromosomal aberration; metabolic syndrome; psoriasis
Year: 2022 PMID: 35893255 PMCID: PMC9331653 DOI: 10.3390/metabo12080688
Source DB: PubMed Journal: Metabolites ISSN: 2218-1989
Biochemical parameters and parameters associated with MetS and psoriasis.
| Measured Parameters | Mets; n = 21; nonMetS; n = 20 | Median | Q1–Q3 | |
|---|---|---|---|---|
| Glu mmol/L | MetS | 5.1 | 4.53–6.91 | <0.02 |
| nonMetS | 4.48 | 3.7–4.97 | ||
| Chol mmol/L | MetS | 4.7 | 4.23–5.49 | NS; |
| nonMetS | 4.77 | 4.2–5.45 | ||
| HDL mmol/L | MetS | 0.91 | 0.83–1.05 | <0.001 |
| nonMetS | 1.27 | 1.09–1.46 | ||
| TAG (mmol/L) | MetS | 1.92 | 1.75–2.66 | <0.001 |
| nonMetS | 1.01 | 0.9–1.46 | ||
| LDL (mmol/L) | MetS (n = 20) | 2.64 | 2.24–3.47 | NS; |
| nonMetS | 2.92 | 2.17–3.5 | ||
| BMI | MetS | 30.5 | 28.1–32.2 | <0.001 |
| nonMetS | 24.75 | 24.3–28.45 | ||
| Waist (cm) | MetS | 103 | 98–111 | <0.001 |
| nonMetS | 88.5 | 84–98 | ||
| sBP (mmHg) | MetS | 140 | 130–150 | <0.01 |
| nonMetS | 130 | 121–140 | ||
| dBP (mmHg) | MetS | 90 | 88–100 | NS; |
| nonMetS | 90 | 81–95 | ||
| PASI | MetS | 15.6 | 13.2–30.5 | NS; |
| nonMetS | 14.7 | 12.15–20.15 | ||
| DoI (years) | MetS | 8 | 4.5–22 | NS; |
| nonMetS | 10 | 6.25–19.5 |
Legend: Glu, fasting glucose; Chol, total cholesterol; nonHDL, non-high-density lipoprotein; LDL, low-density lipoprotein, BMI, body mass index; sBP, systolic blood pressure; dSB, diastolic blood pressure; DoI, duration of illness; NS: statistically nonsignificant.
Group analysis; the total number of aberrated cells in all samples.
| Numbers of Analyzed Cells | ABB | SAB | NAB |
|---|---|---|---|
| MetS (2100 cells) | 120 (5.7%) | 116 (5.5%) | 4 (0.2%) |
| nonMetS (2000 cells) | 105 (5.3%) | 105 (5.3%) | 0 |
Legend: ABB, the total number of aberrated cells; SAB, structural aberrations; NAB, numerical aberrations.
Figure 1Levels of DNA/RNA damage in MetS and nonMetS patients. Legend: The horizontal line in the boxes indicates the position of the median, the ends of the boxes define the 25th and 75th percentiles, and error bars mark the 10th and 90th percentiles. Y is an outlier.
Numbers of chromosomal aberrations in MetS and nonMetS patients.
| Numbers of Patients | ABB | SAB | NAB | |||||
|---|---|---|---|---|---|---|---|---|
| n = 41 | Median | Q1–Q3 | Min, Max | Median | Q1–Q3 | Min, Max | Total Number | |
| MetS (n = 21) | 6 | 4–7 | 2, 11 | 5 | 4–7 | 2, 11 | 4 | NS, |
| nonMetS (n = 20) | 5 | 4–6 | 0, 9 | 5 | 4–6 | 0, 9 | 0 | |
Legend: ABB, the total number of aberrated cells; SAB, structural aberrations; NAB, numerical aberrations.
Figure 2Numbers of chromosomal aberrations in MetS and nonMetS patients. Legend: The horizontal line in the boxes indicates the position of the median, the ends of the boxes define the 25th and 75th percentiles, and error bars mark the 10th and 90th percentiles. Y is an outlier.
Individual analysis, number of persons with aberration.
| Percentage of Total Aberration | nonMetS n = 20 | MetS n = 21 |
|---|---|---|
| ≥5% ABB | 8 (40%) | 11 (52.4%) |
| ≥10% ABB | 0 (0%) | 2 (9.5%) |
| NAB | 0 (0%) | 3 (19%) (1 person had 2 aberration) |
Figure 3Number of aberrations in smokers and non-smokers with MetS. Legend: The horizontal line in the boxes indicates the position of the median, the ends of the boxes define the 25th and 75th percentiles, and error bars mark the 10th and 90th percentiles. Y is an outlier.
Figure 4Correlation between the number of ABB and HDL levels in non-MetS patients. Legend: The scatter plot shows the relationship between the number of ABB and HDL levels. Spots represent the plotted values of the measured variables obtained for each patient, and the line represents the best fit for the correlation.