Next Article in Journal
Prevention of UVB Induced Metabolic Changes in Epidermal Cells by Lipid Extract from Microalgae Nannochloropsis oceanica
Next Article in Special Issue
Effect of Allergen-Specific Immunotherapy on Transcriptomic Changes in Canine Atopic Dermatitis
Previous Article in Journal
An RNAi-Mediated Reduction in Transcription Factor Nrf-2 Blocks the Positive Effects of Dimethyl Fumarate on Metabolic Stress in Alzheimer’s Disease
Previous Article in Special Issue
Gender Influences Gut Microbiota among Patients with Irritable Bowel Syndrome
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Single-Nucleotide Polymorphisms in Base-Excision Repair-Related Genes Involved in the Risk of an Occurrence of Non-Alcoholic Fatty Liver Disease

by
Sylwia Ziółkowska
1,†,
Marcin Kosmalski
2,†,
Łukasz Kołodziej
3,
Aleksandra Jabłkowska
4,
Janusz Zbigniew Szemraj
1,
Tadeusz Pietras
2,
Maciej Jabłkowski
4 and
Piotr Lech Czarny
1,*
1
Department of Medical Biochemistry, Medical University of Lodz, 92-215 Lodz, Poland
2
Department of Clinical Pharmacology, Medical University of Lodz, 90-153 Lodz, Poland
3
Laboratory of Medical Genetics, Faculty of Biology and Environmental Protection, University of Lodz, 90-236 Lodz, Poland
4
Department of Infectious and Liver Diseases, Medical University of Lodz, 91-347 Lodz, Poland
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Int. J. Mol. Sci. 2023, 24(14), 11307; https://doi.org/10.3390/ijms241411307
Submission received: 9 June 2023 / Revised: 3 July 2023 / Accepted: 6 July 2023 / Published: 11 July 2023
(This article belongs to the Special Issue State-of-the-Art Molecular Genetics and Genomics in Poland 2.0)

Abstract

:
Oxidative stress is one of the pillars crucial in the development of a non-alcoholic fatty liver disease (NAFLD) and may cause DNA damage. Since the main pathway responsible for the repair of oxidative DNA damage is the base-excision repair (BER) pathway, we examined the relationship between the presence of different genetic variants of BER-associated genes and the risk of NAFLD. The study evaluates seven single nucleotide polymorphisms (SNPs) within five genes, hOGG1, APEX1, NEIL1, LIG3, LIG1, in 150 NAFLD patients and 340 healthy controls. The genotyping was performed using TaqMan probes and the results were presented as odds ratio with its corresponding 95% confidence interval. The following SNPs were assessed in the study: hOGG1 (rs1052133), APEX1 (rs176094 and rs1130409), NEIL1 (rs4462560), LIG3 (rs1052536), LIG3 (rs4796030), and LIG1 (rs20579). Four of the investigated SNPs, i.e., rs176094, rs1130409, rs4462560 and rs4796030, were found to be associated with NAFLD risk. Furthermore, the occurrence of insulin resistance in patients with steatosis depended on various LIG3 genetic variants. The findings imply the impact of genes involved in BER on NAFLD and fatty liver-related insulin sensitivity.

1. Introduction

Non-alcoholic fatty liver disease (NAFLD; fatty liver; steatosis) affects almost a quarter of the world population, and it is considered to be the most common liver disorder. Admittedly, the disease often affects adults, but there is a growing number of reports confirming a notable increased frequency of NAFLD onset in the childhood [1,2]. Based on the recent conclusions of international experts, the nomenclature should undergo an update. Currently, it is proposed to rename NAFLD to metabolic fatty liver disease (MAFLD), due to its highly prominent link with metabolic syndrome, as well as to diagnose steatosis independently from alcohol consumption [3].
Due to the fact that NAFLD is observed mostly in individuals on a diet rich in fatty acids and/or fructose [4,5,6], it could be assumed that the disorder is directly associated with dietary habits. However, steatosis is frequently observed even in lean individuals, suggesting that the mechanisms responsible for fatty livers are not solely related to the caloric values of diet. Thus, the exact mechanism underlying the development of fatty livers must be revealed. It is particularly important to recognize the moment of deterioration, i.e., an appearance of insulin resistance (IR), diabetes mellitus, non-alcoholic steatohepatitis (NASH), and eventually cirrhosis, which often leads to hepatocellular carcinoma (HCC) [7].
One of the crucial factors of hepatic steatosis is the excessive accumulation of fat in hepatocytes. This may arise from both increased fatty acid intake as well as increased glucose and fructose intake, leading to de novo production of free fatty acids (FFA) and lipogenesis, respectively [8]. Therefore, it could not only result in triglycerides (TG) accumulation, but also in an inhibition of fatty acid oxidation, which may later mediate an increase in very-low-density lipoprotein (VLDL) particle numbers and a reduction in insulin sensitivity [7]. Observed IR disrupts normal lipid metabolism, leading to an increased release of FFA from adipose tissue. An elevated level of FFA can induce oxidative stress by impairing the antioxidant defense system and promoting the generation of reactive oxygen species (ROS). Furthermore, IR is often accompanied by a reduction in effectiveness of the antioxidant defense mechanisms. This can result in decreased levels of antioxidant enzymes and molecules, such as glutathione, which play a vital role in neutralizing ROS. Insufficient antioxidant defenses lead to the accumulation of ROS and oxidative stress [9].
Increased activity of beta oxidation can contribute to the elevated production of ROS, and, thus, increased oxidative stress. ROS are oxygen metabolites that have a high oxidizing capacity. In a system in which the balance between pro- and antioxidants is maintained, ROS are responsible for cellular signaling, regulation of intra-cellular processes, proliferation, differentiation, and migration of cells. However, due to their highly reactive nature, they can also act destructively [10]. ROS not only oxidize proteins and lipids, but also damage the DNA structure. DNA damage caused by free radicals includes base modifications, abasic sites, and strand breaks. The main oxidized base lesion caused by ROS is 8-oxo-2′-deoxyguanosine (8-OHdG, 8-oxo-dG), which is also a biomarker for the measurement of endogenous oxidative DNA damage. It can cause G to T transversion or lead to genome instability. As a result, the DNA damage response (DDR) may trigger apoptotic and necrotic cell death pathways [10].
The impairment of the DDR system may lead to the accumulation of DNA damage caused by ROS, among others [11]. The main mechanism responsible for the repair of oxidative damage is base-excision repair (BER), although it is also responsible for repairing damage caused by alkylation, deamination, and depurination/depyrimidination [12]. The pathway is initiated by DNA glycosylases, which recognize and remove the damaged or modified base. There are several glycosylases, the choice of which depends on the type of damage that should be recognized [13]. The resultant gap after excision of the base is an abasic site, which is recognized and cleaved by an AP endonuclease. The resulting single-strand break is processed by a DNA polymerase. BER can be distinguished to two subpathways. The first one is short-patch BER, in which DNA polymerase β incorporates a single nucleotide, while the second is long-patch, where DNA polymerase δ/ε incorporates 2–10 nucleotides [14]. Eventually, the gap is sealed by a DNA ligase, completing the repair process [15]. This paper focuses on the study of two glycosylases, hOGG1 and NEIL1, the AP endonuclease APEX1, and two ligases, LIG and LIG3. The chosen genetic variations’ functional significance in other disorders has been confirmed. Additionally, the protein products of these genes represent a cross-section of molecules acting at different stages of the BER pathway.
Recent studies in the field of NAFLD confirm that oxidative mitochondrial damage has an impact on the development of a fatty liver. Mitophagy (autophagy in which mitochondria are eliminated) of the dysfunctional mitochondria modulates liver metabolism and protects against NAFLD progression. On the other hand, increased mitophagy leads to hepatic mitochondrial depletion and dysfunction [16,17,18,19]. Nevertheless, multiple DNA strand breaks in mitochondrial DNA (mtDNA) have been observed in patients with advanced fibrosis [10]. These lesions are associated with disease development and inflammation. In addition, an increase in 8-OHdG can be observed in patients with advanced hepatitis [20]. When it comes to overall DNA damage, increased p-53-binding protein (p53BP1 or TP53BP1) expression can be observed in NAFLD [21]. This protein is responsible for the detection and localization of DNA double-strand breaks. Its overexpression may suggest that DNA damage is present in patients with steatosis.
Due to the fact that the accumulation of DNA damage is associated with NAFLD, we suspect that an insufficient DNA repair may contribute to the development of NAFLD. Thus, alterations in the genetic material encoding repair pathways-related proteins can also be related to the occurrence of the disease. To evaluate the hypothesis, we performed SNP genotyping to assess the link between the presence of polymorphisms in BER-related genes and the occurrence of a fatty liver.

2. Results

2.1. Single Nucleotide Polymorphisms in BER Associated Genes Modulate the Risk of NAFLD Occurrence

The distribution of all genotypes was in an agreement with the Hardy–Weinberg equation. The results present the distribution of the gene variants in both NAFLD patients and healthy individuals. Four of the studied SNPs, i.e., APEX1 rs1760944, APEX1 rs1130409, NEIL1 rs4462560, and LIG3 rs4796030, modulate the risk of NAFLD occurrence, shown as OR values with corresponding p-values. The exact data is presented in Table 1.

2.2. Single Nucleotide Polymorphism in LIG3 Modulate the Risk of IR Occurrence in NAFLD Patients

In accordance with the link between IR, oxidative stress, DNA repair, and NAFLD, we established the differences in the frequency of occurrence of gene variants in groups of people with and without IR. Among the studied polymorphisms, only in LIG3 c.*83A>C (rs4796030) was there a significant difference. It can be observed that the presence of the AC genotype and the A allele is much more frequent in the IR group than the CC genotype and the C allele. The results are presented in Table 2.

2.3. Haplotypes of Single Nucleotide Polymorphisms in APEX1 as Well as in LIG3 Modulate the Risk of IR Occurrence in NAFLD Patients

We investigated the association between NAFLD risk and haplotypes of rs1760944 and rs1130409 of APEX1, as well as haplotypes of rs1052536 and rs4796030 of LIG3. The distribution of such haplotypes is shown in Table 3. In the case of APEX1, the TT haplotype significantly increases the risk of fatty liver occurrence, while the GG haplotype decreases it. When it comes to LIG3, the CC haplotype elevates the risk of steatosis, but the CA haplotype reduces it.

3. Discussion

In the following study, the relationship between the occurrence of NAFLD and the presence of SNPs in genes associated with the BER repair pathway was examined. Some of the studied genetic variants were significantly more common in people with fatty livers. In accordance with our knowledge, this study is the first to show a relation between SNPs in BER-associated genes and NAFLD risk. To date, the most frequently observed polymorphisms associated with fatty livers were found in the PNPLA3, TM6SF2, GCKR, MBOAT7, and HSD17B13 genes [22]. These genes encode proteins responsible for the metabolism of lipids and sugars in the liver, pancreas, or adipocytes. Less frequently observed polymorphisms occur in genes which are also related to energy metabolism [23]. In our previous study investigating liver disease, we focused on evaluating the ability of HCV-infected lymphocytes to repair DNA via the BER pathway. We were able to confirm that DNA repair was impaired after infection with hepatitis virus [24]. The current study, the first in the area of steatosis, also detected the relationship between genes encoding proteins responsible for BER and the liver disorder. The results demonstrate the impact of BER on the occurrence of liver disease, suggesting a link between DNA repair and NAFLD. In another of our studies, we demonstrated that the presence of different gene variants may be related to the occurrence of HCC. A tumor may appear as a consequence of an untreated fatty liver. We were able to confirm both the relationship between the occurrence of SNPs in genes related to BER, and the increase in expression for some variants of these genes [12]. This study on SNPs agrees with previous results showing the association of BER with liver disorders.
The polymorphisms that we have studied either occur in the coding sequence, where they can effect amino acid substitution, or in UTR-3 and UTR-5, which may result in changes in translational regulatory sequences or signaling sequences. Both cases may result in BER pathway impairment, either by modulating the proteins’ activity or their expression. In consequence, this may lead to the accumulation of oxidative DNA damage, which is an effect of the overproduction of ROS. Since increased free radical levels is one hit among the multi-hit hypothesis suggesting the explanation of the mechanism of NAFLD development, insufficient oxidative DNA damage repair may lead to the accumulation of such damage. The liver is particularly exposed to the elevated levels of ROS due to the large number of mitochondria in hepatocytes, which may lead to subsequent oxidative DNA lesions, creating a vicious cycle [7].
Selected SNPs have confirmed functional significance and have been tested in other diseases, including liver disorders, in the context of BER activity. Moreover, the gene products studied in the experiment show a cross-section of proteins at three different steps of the repair pathway. The first step is recognition of a lesion, where glycosylases play a vital role; the next step is the cleavage of abasic site and is performed by endonucleases; and in the last step, i.e., ligation of DNA strands, ligases are involved.
Apurinic/apyrimidinic endonuclease-1 (APEX1) participates in both short- and long-patch BER by incising AP sites. Among the polymorphisms of APEX1 examined in our research, i.e., c.-468T>G (rs1760944) and c.444T>G (rs1130409), the latter had the greatest association with the risk of NAFLD. The TG genotype increased the risk of steatosis, while the GG genotype significantly reduced the risk of NAFLD. We found that the TT haplotype of both the studied SNPs raises the risk of a fatty liver, and the GG haplotype reduces it. The frequency of rs1130409, which is localized in exon 5 of APEX1 and causes asparagine to glutamic acid in codon 148, is increased in HCC [24]. APEX1 rs1760944 polymorphism is localized near 5′ end, and was found to be related to abnormal liver function caused by N, N-dimethylformamide in the Chinese population [25]. Moreover, other articles demonstrated that rs1760944 increases the risk of lung and breast cancer, as well as neural tube defects, and decreases the risk of prostate cancer [26,27,28,29]. On the other hand, rs1130409 elevates the risk of HIV-1 infection, prostate cancer, and HCC and reduces cervical cancer [28,30,31,32]. Increased expression of APEX1 has been observed in HCC patients when compared to healthy individuals [33]. Moreover, overexpression of APEX1 is associated with increased expression of pro-inflammatory and pro-apoptotic factors [34]. When it comes to the haplotypes, the TG and GG haplotypes were related to a decreased risk of ovarian cancer [35].
Endonuclease VIII-like DNA glycosylase (NEIL1; c.*589G>C; rs4462560) removes mutagenic DNA bases induced by ROS in the first step of BER. The examined SNP is localized in the gene promoter of NEIL1 near untranscribed region at the 3′ end (UTR-3) region. In our study, the CG genotype in the c.*589G>C NEIL1 SNP increased the risk of NAFLD. The other publications showed that the GC and CC genotypes decrease the risk of grade ≥ 2 radiation pneumonitis in patients with esophageal squamous cell carcinoma [36]. Furthermore, it was previously suggested that the SNP in NEIL1 modulates the risk of recurrent depressive disorder [37]. In HCV-infected cells, NEIL1 is downregulated in comparison to healthy cells [38]. Moreover, knockout of this gene results in an increased incidence of HCC and tumor size [39].
Another two studied SNPs, c.*83A>C (rs4796030) and c.*50C>T (rs1052536), were localized in UTR-3 of DNA ligase 3 (LIG3). It encodes a protein responsible for ligation of single-strand breaks during short-patch BER. In our study, haplotypes of rs1052536 and rs4796030 modulate the risk of the occurrence of the disease. The CC haplotype increases the risk, while the CA haplotype decreases it. In the literature, rs4796030 raised the risk of ovarian cancer (especially in patients with high BMI) [40], while the haplotypes of rs1052536 and rs4796030 modulate the risk of recurrent depressive disorder [14]. Our previous experiments on c.*83A>C did not show any significant differences between patients with HCC and healthy individuals [12]. However, high glucose treatment on hepatocytes cell line HepG2 triggered higher expression levels of LIG3 [41]. When it comes to our study, among the two SNPs of LIG3, only c.*83A>C had a strong association with NAFLD risk.
The other of the studied polymorphisms, c.977C>G (rs1052133) in the coding region of human oxoguanine glycosylase 1 (hOGG1) gene, is known as Ser326Cys, since it causes alteration from serine to cysteine. The product of the gene is involved in BER through recognizing and removing 8-OHdG [42]. Although we did not find any differences, the SNP is associated with glucose metabolism, particularly as it triggers decreased insulin sensitivity in subjects with normal glucose tolerance [43]. Recent studies confirm that high glucose intake decreased expression of hOGG1, while hOGG1-null mice had reduced insulin secretion [44,45,46,47]. Furthermore, the SNP increases the risk of bladder and gallbladder cancer [48,49].
The polymorphism of DNA ligase 1 (LIG1; rs20579, c.-7C>T) is localized in untranscribed region at 5′ end (UTR-5). LIG1 engages in long-patch BER and joining of Okazaki fragments. In our results, there was no relationship with fatty livers. Although the studied SNP has not been related to fatty livers so far, there are papers in which this polymorphism is important in diseases closely associated with fatty liver, such as diabetes [50,51,52] and HCC [12,30,53,54]. However, in our research, we did not find any correlation with NAFLD.
We observed an association between the LIG3 gene variant (c.*83A>C; rs4796030) and the IR phenomenon in patients. Due to the fact that IR is a crucial factor in NAFLD development and progression [55], we may assume that individuals with the tested variant of LIG3 may develop the disease later than people with a different genotype. Nevertheless, the study group of patients without IR is small, and therefore the results should be treated with caution. However, we acknowledge that this may be the right direction for the research.
The main limitation of our study is the modest number of patients of Polish origin. For this reason, it is difficult to relate our research to the global population. There are also very few published studies on BER in NAFLD. Apparently, this is still a poorly researched topic, and it should be thoroughly explored.

4. Materials and Methods

4.1. Ethics

All subjects gave their written consent to participate in this study. An approval of the study was obtained from the Bioethics Committee of the Medical University of Lodz, Poland (no. RNN/160/20/KE).

4.2. Patients

The groups of participants in the study were composed of 150 patients with NAFLD and 340 people without fatty livers as controls. Subjects were recruited from two Polish medical centers: the Bieganski Provincial Specialist Hospital in Lodz, Poland and the Norbert Barlicki Memorial Teaching Hospital in Lodz, Poland. NAFLD was diagnosed using ultrasonography (USG). Patients were included in the control group based on medical history as well as ALT, AST, and TG blood results. Furthermore, among the selected individuals, minors as well as people with a history of tumors and other liver diseases were excluded from the study. Moreover, patients were considered as individuals without IR according to their medical history as well as a HbA1c below 6.5% and, in some cases, a HOMA-IR (homeostatic model assessment of insulin resistance) of less than 2.5. The characteristics of the groups are presented in Table 4 and Table 5. Clinical and biochemical features of NAFLD patients were measured from blood samples in standard hospital examinations and are demonstrated in Table 6.

4.3. Samples Collection

Approximately 5 mL of venous blood was taken from each participant to tubes containing EDTA and aliquoted of 200 μL. The blood was frozen and stored at −20 °C until the isolation of DNA.

4.4. DNA Isolation

Genomic DNA was isolated using the Invisorb® Spin Blood Mini Kit (Invitek Molecular GmbH, Berlin, Germany). DNA concentrations and purity of samples were determined by measurement of an absorbance at 260 nm and 280 nm (Picodrop, Syngen Biotech, Wroclaw, Poland).

4.5. SNPs Selection

We selected seven potentially functional SNPs of five genes related to the BER pathway using the public domain of the National Center for Biotechnology Information, the database for single nucleotide polymorphisms, available at http://www.ncbi.nlm.nih.gov/snp, assessed on 10 March 2021 (Bethesda, MD, USA). SNPs were selected according to the following criteria: (i) a minor allele frequency greater than 0.05 in a European population; (ii) localization in coding region causing non-synonymous substitution or in regulatory regions. The studied polymorphisms are presented in Table 7.

4.6. SNP Genotyping

2X Master Mix Takyon for Probe Assay—No ROX (Eurogentec, Liège, Belgium) and TaqMan™ Universal PCR Master Mix (Applied Biosystems™, Waltham, MA, USA) were used to genotype selected polymorphisms in accordance with the manufacturer’s protocol. The TaqMan Assay IDs are presented in Table 7. Reactions were performed in a Bio-Rad CFX96 thermal cycler with Real-Time PCR Detection System (Bio-Rad Laboratories Inc., Hercules, CA, USA). Results were analyzed in CFX Manager Software, Bio-Rad CFX Maestro 1.1 (Bio-Rad Laboratories Inc.).

4.7. Statistical Analysis

The collected data was analyzed in SigmaPlot 11.0 (Systat Software Inc., San Jose, CA, USA). Multiple logistic regression analysis was used to obtain the odds ratio (OR) and its corresponding 95% confidence interval (95% CI) with p-values below 0.05 for the risk of NAFLD onset. Chi-square (χ2) analysis was used to assess the significance of the differences between distributions of alleles and genotypes in NAFLD patients and controls. Haplotypes were assessed on the basis of the studied genotypes of four SNPs (rs1760944, rs1130409, rs1052536, and rs4796030), and the SHEsisPlus software (http://shesisplus.bio-x.cn/SHEsis.html, accessed on 10 February 2023) [56] was used. Haplotypes with frequencies of <0.03 were excluded from the analysis.

5. Conclusions

Our study is the first to demonstrate an association between SNPs in BER-associated genes and the risk of NAFLD. One of the polymorphisms could be also related to the appearance of IR in people with fatty livers. The results of the study suggest that the impairment of DNA repair may be an important mechanism in the development of NAFLD. It revealed the interplay between oxidative stress, DNA repair, and liver steatosis.
Future research should focus on expanding the examined genes panel involved in DNA repair. It is highly crucial to evaluate the DNA repair capacity of NAFLD patients, as well as to investigate the level of gene-related BER expression.

Author Contributions

Conceptualization, S.Z. and P.L.C.; methodology, S.Z. and P.L.C.; formal analysis, S.Z., M.K.; investigation, S.Z., M.K., Ł.K. and A.J.; data curation, S.Z.; writing—original draft preparation, S.Z.; writing—review and editing, P.L.C. and M.K.; visualization, S.Z.; supervision, J.Z.S., T.P. and M.J.; project administration, J.Z.S., T.P. and M.J.; funding acquisition, J.Z.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Science Centre (2019/35/O/NZ5/02502).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Bioethics Committee of the Medical University of Lodz (no. RNN/160/20/KE).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Additional data can be requested via e-mail from the corresponding authors.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Shaunak, M.; Byrne, C.D.; Davis, N.; Afolabi, P.; Faust, S.N.; Davies, J.H. Non-Alcoholic Fatty Liver Disease and Childhood Obesity. Arch. Dis. Child. 2021, 106, 3–8. [Google Scholar] [CrossRef] [PubMed]
  2. Yu, E.L.; Golshan, S.; Harlow, K.E.; Angeles, J.E.; Durelle, J.; Goyal, N.P.; Newton, K.P.; Sawh, M.C.; Hooker, J.; Sy, E.Z.; et al. Prevalence of Nonalcoholic Fatty Liver Disease in Children with Obesity. J. Pediatr. 2019, 207, 64–70. [Google Scholar] [CrossRef] [PubMed]
  3. Pipitone, R.M.; Ciccioli, C.; Infantino, G.; La Mantia, C.; Parisi, S.; Tulone, A.; Pennisi, G.; Grimaudo, S.; Petta, S. MAFLD: A Multisystem Disease. Ther. Adv. Endocrinol. Metab. 2023, 14, 20420188221145548. [Google Scholar] [CrossRef] [PubMed]
  4. Hliwa, A.; Ramos-Molina, B.; Laski, D.; Mika, A.; Sledzinski, T. The Role of Fatty Acids in Non-Alcoholic Fatty Liver Disease Progression: An Update. Int. J. Mol. Sci. 2021, 22, 6900. [Google Scholar] [CrossRef]
  5. Yu, S.; Li, C.; Ji, G.; Zhang, L. The Contribution of Dietary Fructose to Non-Alcoholic Fatty Liver Disease. Front. Pharmacol. 2021, 12, 783393. [Google Scholar] [CrossRef]
  6. Coronati, M.; Baratta, F.; Pastori, D.; Ferro, D.; Angelico, F.; Del Ben, M. Added Fructose in Non-Alcoholic Fatty Liver Disease and in Metabolic Syndrome: A Narrative Review. Nutrients 2022, 14, 1127. [Google Scholar] [CrossRef]
  7. Ziolkowska, S.; Binienda, A.; Jabłkowski, M.; Szemraj, J.; Czarny, P. The Interplay between Insulin Resistance, Inflammation, Oxidative Stress, Base Excision Repair and Metabolic Syndrome in Nonalcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2021, 22, 11128. [Google Scholar] [CrossRef]
  8. Stanhope, K.L.; Havel, P.J. Fructose Consumption: Potential Mechanisms for Its Effects to Increase Visceral Adiposity and Induce Dyslipidemia and Insulin Resistance. Curr. Opin. Lipidol. 2008, 19, 16. [Google Scholar] [CrossRef] [Green Version]
  9. Kosmalski, M.; Frankowski, R.; Ziółkowska, S.; Różycka-Kosmalska, M.; Pietras, T. What’s New in the Treatment of Non-Alcoholic Fatty Liver Disease (NAFLD). J. Clin. Med. 2023, 12, 1852. [Google Scholar] [CrossRef]
  10. Masarone, M.; Rosato, V.; Dallio, M.; Gravina, A.G.; Aglitti, A.; Loguercio, C.; Federico, A.; Persico, M. Role of Oxidative Stress in Pathophysiology of Nonalcoholic Fatty Liver Disease. Oxid. Med. Cell. Longev. 2018, 2018, 9547613. [Google Scholar] [CrossRef]
  11. Karkucinska-Wieckowska, A.; Simoes, I.C.M.; Kalinowski, P.; Lebiedzinska-Arciszewska, M.; Zieniewicz, K.; Milkiewicz, P.; Górska-Ponikowska, M.; Pinton, P.; Malik, A.N.; Krawczyk, M.; et al. Mitochondria, Oxidative Stress and Nonalcoholic Fatty Liver Disease: A Complex Relationship. Eur. J. Clin. Investig. 2022, 52, e13622. [Google Scholar] [CrossRef]
  12. Krupa, R.; Czarny, P.; Wigner, P.; Wozny, J.; Jablkowski, M.; Kordek, R.; Szemraj, J.; Sliwinski, T. The Relationship Between Single-Nucleotide Polymorphisms, the Expression of DNA Damage Response Genes, and Hepatocellular Carcinoma in a Polish Population. DNA Cell Biol. 2017, 36, 693–708. [Google Scholar] [CrossRef] [PubMed]
  13. Ide, H.; Kotera, M. Human DNA Glycosylases Involved in the Repair of Oxidatively Damaged DNA. Biol. Pharm. Bull. 2004, 27, 480–485. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Czarny, P.; Kwiatkowski, D.B.; Toma, M.; Gałecki, P.B.; Orzechowska, A.B.; Bobińska, K.C.; Bielecka-Kowalska, A.; Szemraj, J.C.; Berk, M.C.; Anderson, G.; et al. Single-Nucleotide Polymorphisms of Genes Involved in Repair of Oxidative DNA Damage and the Risk of Recurrent Depressive Disorder. Experiment 2016, 22, 4455–4474. [Google Scholar] [CrossRef] [Green Version]
  15. Czarny, P.; Wigner, P.; Galecki, P.; Sliwinski, T. The Interplay between Inflammation, Oxidative Stress, DNA Damage, DNA Repair and Mitochondrial Dysfunction in Depression. Prog. Neuropsychopharmacol. Biol. Psychiatry 2018, 80, 309–321. [Google Scholar] [CrossRef]
  16. Paoli, A.; Cerullo, G. Investigating the Link between Ketogenic Diet, NAFLD, Mitochondria, and Oxidative Stress: A Narrative Review. Antioxidants 2023, 12, 1065. [Google Scholar] [CrossRef]
  17. Dabravolski, S.A.; Bezsonov, E.E.; Orekhov, A.N. The Role of Mitochondria Dysfunction and Hepatic Senescence in NAFLD Development and Progression. Biomed. Pharmacother. 2021, 142, 112041. [Google Scholar] [CrossRef] [PubMed]
  18. Dornas, W.; Schuppan, D. Mitochondrial Oxidative Injury: A Key Player in Nonalcoholic Fatty Liver Disease. Am. J. Physiol. Gastrointest. Liver Physiol. 2020, 319, G400–G411. [Google Scholar] [CrossRef] [PubMed]
  19. Ajith, T.A. Role of Mitochondria and Mitochondria-Targeted Agents in Non-Alcoholic Fatty Liver Disease. Clin. Exp. Pharmacol. Physiol. 2018, 45, 413–421. [Google Scholar] [CrossRef] [Green Version]
  20. Seki, S.; Kitada, T.; Sakaguchi, H. Clinicopathological Significance of Oxidative Cellular Damage in Non-Alcoholic Fatty Liver Diseases. Hepatol. Res. 2005, 33, 132–134. [Google Scholar] [CrossRef]
  21. Akazawa, Y.; Nakashima, R.; Matsuda, K.; Okamaoto, K.; Hirano, R.; Kawasaki, H.; Miuma, S.; Miyaaki, H.; Malhi, H.; Abiru, S.; et al. Detection of DNA Damage Response in Nonalcoholic Fatty Liver Disease via P53-Binding Protein 1 Nuclear Expression. Mod. Pathol. 2019, 32, 997–1007. [Google Scholar] [CrossRef] [PubMed]
  22. Paternostro, R.; Staufer, K.; Traussnigg, S.; Stättermayer, A.F.; Halilbasic, E.; Keritam, O.; Meyer, E.L.; Stift, J.; Wrba, F.; Sipos, B.; et al. Combined Effects of PNPLA3, TM6SF2 and HSD17B13 Variants on Severity of Biopsy-Proven Non-Alcoholic Fatty Liver Disease. Hepatol. Int. 2021, 15, 922. [Google Scholar] [CrossRef] [PubMed]
  23. Sulaiman, S.A.; Dorairaj, V.; Adrus, M.N.H. Genetic Polymorphisms and Diversity in Nonalcoholic Fatty Liver Disease (NAFLD): A Mini Review. Biomedicines 2023, 11, 106. [Google Scholar] [CrossRef] [PubMed]
  24. Czarny, P.; Merecz-Sadowska, A.; Majchrzak, K.; Jabłkowski, M.; Szemraj, J.; Śliwiński, T.; Karwowski, B. The Influence of Hepatitis C Virus Therapy on the DNA Base Excision Repair System of Peripheral Blood Mononuclear Cells. DNA Cell. Biol. 2017, 36, 535–540. [Google Scholar] [CrossRef]
  25. Tong, Z.; Shen, H.; Yang, D.; Zhang, F.; Bai, Y.; Li, Q.; Shi, J.; Zhang, H.; Zhu, B. Genetic Variations in the Promoter of the APE1 Gene Are Associated with DMF-Induced Abnormal Liver Function: A Case-Control Study in a Chinese Population. Int. J. Environ. Res. Public Health 2016, 13, 752. [Google Scholar] [CrossRef] [Green Version]
  26. Liao, Z.; Yi, M.; Li, J.; Zhang, Y. DNA Repair in Lung Cancer: A Large-Scale Quantitative Analysis for Polymorphisms in DNA Repairing Pathway Genes and Lung Cancer Susceptibility. Expert Rev. Respir. Med. 2022, 16, 997–1010. [Google Scholar] [CrossRef]
  27. Wang, X.; Yue, H.; Li, S.; Guo, J.; Guan, Z.; Zhu, Z.; Niu, B.; Zhang, T.; Wang, J. Genetic Polymorphisms in DNA Repair Gene APE1/Ref-1 and the Risk of Neural Tube Defects in a High-Risk Area of China. Reprod. Sci. 2021, 28, 2592–2601. [Google Scholar] [CrossRef]
  28. Liu, J.; Zheng, J.; Guo, Y.; Sheng, X.; Yin, Y.; Qian, S.; Xu, B.; Xiong, W.; Yin, X. Association between APE1 Rs1760944 and Rs1130409 Polymorphism with Prostate Cancer Risk: A Systematic Review and Meta-Analysis. Medicine 2021, 100, E27630. [Google Scholar] [CrossRef]
  29. Qiao, L.; Feng, X.; Wang, G.; Zhou, B.; Yang, Y.; Li, M. Polymorphisms in BER Genes and Risk of Breast Cancer: Evidences from 69 Studies with 33760 Cases and 33252 Controls. Oncotarget 2018, 9, 16220–16233. [Google Scholar] [CrossRef]
  30. Saad, A.M.; Abdel-Megied, A.E.S.; Elbaz, R.A.; Hassab El-Nabi, S.E.; Elshazli, R.M. Genetic Variants of APEX1 p.Asp148Glu and XRCC1 p.Gln399Arg with the Susceptibility of Hepatocellular Carcinoma. J. Med. Virol. 2021, 93, 6278–6291. [Google Scholar] [CrossRef]
  31. Datkhile, K.D.; Durgawale, P.P.; Patil, M.N.; Gudur, R.A.; Gudur, A.K.; Patil, S.R. Impact of Polymorphism in Base Excision Repair and Nucleotide Excision Repair Genes and Risk of Cervical Cancer: A Case-Control Study. Asian Pac. J. Cancer Prev. 2022, 23, 1291–1300. [Google Scholar] [CrossRef] [PubMed]
  32. Liu, B.; Wang, K.; Wu, J.; Hu, Y.; Yang, X.; Xu, L.; Sun, W.; Jia, X.; Wu, J.; Fu, S.; et al. Association of APEX1 and XRCC1 Gene Polymorphisms With HIV-1 Infection Susceptibility and AIDS Progression in a Northern Chinese MSM Population. Front. Genet. 2022, 13, 861355. [Google Scholar] [CrossRef] [PubMed]
  33. Cao, L.; Cheng, H.; Jiang, Q.; Li, H.; Wu, Z. APEX1 Is a Novel Diagnostic and Prognostic Biomarker for Hepatocellular Carcinoma. Aging 2020, 12, 4573–4591. [Google Scholar] [CrossRef] [PubMed]
  34. Sawakami, T.; Sun, Z.; Inagaki, Y.; Hasegawa, K.; Tang, W.; Xu, G.; Zhang, N. The Impact of Apurinic-Apyrimidinic Endonuclease I on Hepatocyte Immuno-Inflammatory Factors and Cell Apoptosis. Biosci. Trends 2019, 13, 539–545. [Google Scholar] [CrossRef]
  35. Zhang, X.; Xin, X.; Zhang, J.; Li, J.; Chen, B.; Zou, W. Apurinic/Apyrimidinic Endonuclease 1 Polymorphisms Are Associated with Ovarian Cancer Susceptibility in a Chinese Population. Int. J. Gynecol. Cancer 2013, 23, 1393–1399. [Google Scholar] [CrossRef]
  36. Chen, Y.; Zhu, M.; Zhang, Z.; Jiang, G.; Fu, X.; Fan, M.; Sun, M.; Wei, Q.; Zhao, K. A NEIL1 Single Nucleotide Polymorphism (Rs4462560) Predicts the Risk of Radiation-Induced Toxicities in Esophageal Cancer Patients Treated with Definitive Radiotherapy. Cancer 2013, 119, 4205–4211. [Google Scholar] [CrossRef]
  37. Czarny, P.; Kwiatkowski, D.; Galecki, P.; Talarowska, M.; Orzechowska, A.; Bobinska, K.; Bielecka-Kowalska, A.; Szemraj, J.; Maes, M.; Su, K.P.; et al. Association between Single Nucleotide Polymorphisms of MUTYH, HOGG1 and NEIL1 Genes, and Depression. J. Affect. Disord. 2015, 184, 90–96. [Google Scholar] [CrossRef]
  38. Pal, S.; Polyak, S.J.; Bano, N.; Qiu, W.C.; Carithers, R.L.; Shuhart, M.; Gretch, D.R.; Das, A. Hepatitis C Virus Induces Oxidative Stress, DNA Damage and Modulates the DNA Repair Enzyme NEIL1. J. Gastroenterol. Hepatol. 2010, 25, 627–634. [Google Scholar] [CrossRef] [Green Version]
  39. Vartanian, V.; Minko, I.G.; Chawanthayatham, S.; Egner, P.A.; Lin, Y.C.; Earley, L.F.; Makar, R.; Eng, J.R.; Camp, M.T.; Li, L.; et al. NEIL1 Protects against Aflatoxin-Induced Hepatocellular Carcinoma in Mice. Proc. Natl. Acad. Sci. USA 2017, 114, 4207–4212. [Google Scholar] [CrossRef]
  40. Zhang, M.; Zhao, Z.; Chen, S.; Liang, Z.; Zhu, J.; Zhao, M.; Xu, C.; He, J.; Duan, P.; Zhang, A. The Association of Polymorphisms in Base Excision Repair Genes with Ovarian Cancer Susceptibility in Chinese Women: A Two-Center Case-Control Study. J. Cancer 2021, 12, 264–269. [Google Scholar] [CrossRef]
  41. Pang, J.; Xi, C.; Dai, Y.; Gong, H.; Zhang, T.M. Altered Expression of Base Excision Repair Genes in Response to High Glucose-Induced Oxidative Stress in HepG2 Hepatocytes. Med. Sci. Monit. 2012, 18, BR281-5. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Torres-Gonzalez, M.; Gawlowski, T.; Kocalis, H.; Scott, B.T.; Dillmann, W.H. Mitochondrial 8-Oxoguanine Glycosylase Decreases Mitochondrial Fragmentation and Improves Mitochondrial Function in H9C2 Cells under Oxidative Stress Conditions. Am. J. Physiol. Cell Physiol. 2014, 306, C221. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Wang, C.L.; Hsieh, M.C.; Hsin, S.C.; Lin, H.Y.; Lin, K.D.; Lo, C.S.; Chen, Z.H.; Shin, S.J. The HOGG1 Ser326Cys Gene Polymorphism Is Associated with Decreased Insulin Sensitivity in Subjects with Normal Glucose Tolerance. J. Hum. Genet. 2006, 51, 124–128. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Xie, X.; Chen, Y.; Liu, J.; Zhang, W.; Zhang, X.; Zha, L.; Liu, W.; Ling, Y.; Li, S.; Tang, S. High Glucose Induced Endothelial Cell Reactive Oxygen Species via OGG1/PKC/NADPH Oxidase Pathway. Life Sci. 2020, 256, 117886. [Google Scholar] [CrossRef]
  45. Zhao, X.; Ma, Y.; Shi, M.; Huang, M.; Xin, J.; Ci, S.; Chen, M.; Jiang, T.; Hu, Z.; He, L.; et al. Excessive Iron Inhibits Insulin Secretion via Perturbing Transcriptional Regulation of SYT7 by OGG1. Cell. Mol. Life Sci. 2023, 80, 159. [Google Scholar] [CrossRef]
  46. Sampath, H.; Lloyd, R.S. Roles of OGG1 in Transcriptional Regulation and Maintenance of Metabolic Homeostasis. DNA Repair 2019, 81, 102667. [Google Scholar] [CrossRef]
  47. Komakula, S.S.B.; Blaze, B.; Ye, H.; Dobrzyn, A.; Sampath, H. A Novel Role for the DNA Repair Enzyme 8-Oxoguanine DNA Glycosylase in Adipogenesis. Int. J. Mol. Sci. 2021, 22, 1152. [Google Scholar] [CrossRef]
  48. Srivastava, A.; Srivastava, K.; Pandey, S.N.; Choudhuri, G.; Mittal, B. Single-Nucleotide Polymorphisms of DNA Repair Genes OGG1 and XRCC1: Association with Gallbladder Cancer in North Indian Population. Ann. Surg. Oncol. 2009, 16, 1695–1703. [Google Scholar] [CrossRef]
  49. Arizono, K.; Osada, Y.; Kuroda, Y. DNA Repair Gene HOGG1 Codon 326 and XRCC1 Codon 399 Polymorphisms and Bladder Cancer Risk in a Japanese Population. Jpn. J. Clin. Oncol. 2008, 38, 186–191. [Google Scholar] [CrossRef]
  50. Thameem, F.; Puppala, S.; Lehman, D.M.; Stern, M.P.; Blangero, J.; Abboud, H.E.; Duggirala, R.; Habib, S.L. The Ser(326)Cys Polymorphism of 8-Oxoguanine Glycosylase 1 (OGG1) Is Associated with Type 2 Diabetes in Mexican Americans. Hum. Hered. 2010, 70, 97–101. [Google Scholar] [CrossRef] [Green Version]
  51. Pcal, L.; Varvašovsk, J.; Ruav, Z.; Lacigov, S.; Tětina, R.; Racek, J.; Pomahačov, R.; Tanhuserov, V.; Kaňkov, K. Parameters of Oxidative Stress, DNA Damage and DNA Repair in Type 1 and Type 2 Diabetes Mellitus. Arch. Physiol. Biochem. 2011, 117, 222–230. [Google Scholar] [CrossRef] [PubMed]
  52. Das, S.; Purkayastha, S.; Roy, H.; Sinha, A.; Choudhury, Y. Polymorphisms in DNA Repair Genes Increase the Risk for Type 2 Diabetes Mellitus and Hypertension. Biomol. Concepts 2018, 9, 80–93. [Google Scholar] [CrossRef] [PubMed]
  53. Jung, S.W.; Park, N.H.; Shin, J.W.; Park, B.R.; Kim, C.J.; Lee, J.E.; Shin, E.S.; Kim, J.A.; Chung, Y.H. Polymorphisms of DNA Repair Genes in Korean Hepatocellular Carcinoma Patients with Chronic Hepatitis B: Possible Implications on Survival. J. Hepatol. 2012, 57, 621–627. [Google Scholar] [CrossRef] [PubMed]
  54. Mahmoud, A.A.; Hassan, M.H.; Ghweil, A.A.; Abdelrahman, A.; Mohammad, A.N.; Ameen, H.H. Urinary 8-Hydroxydeoxyguanosine in Relation to XRCC1 Rs25487 G/A (Arg399Gln) and OGG1 Rs1052133 C/G (Ser326Cys) DNA Repair Genes Polymorphisms in Patients with Chronic Hepatitis C and Related Hepatocellular Carcinoma. Cancer Manag. Res. 2019, 11, 5343–5351. [Google Scholar] [CrossRef] [Green Version]
  55. Parameswaran, M.; Hasan, H.A.; Sadeque, J.; Jhaveri, S.; Avanthika, C.; Arisoyin, A.E.; Dhanani, M.B.; Rath, S.M. Factors That Predict the Progression of Non-Alcoholic Fatty Liver Disease (NAFLD). Cureus 2021, 13, e20776. [Google Scholar] [CrossRef]
  56. Qin, Z.S.; Niu, T.; Liu, J.S. Partition-Ligation–Expectation-Maximization Algorithm for Haplotype Inference with Single-Nucleotide Polymorphisms. Am. J. Hum. Genet. 2002, 71, 1242. [Google Scholar] [CrossRef] [Green Version]
Table 1. Association between the studied single-nucleotide polymorphism and NAFLD. The table presents a distribution of genotypes and alleles of hOGG1 rs1052133, APEX1 rs1760944 and rs1130409, NEIL1 rs4462560, LIG3 rs1052536 and rs4796030, and LIG1 rs20579, as well as OR with 95% CI in groups of patients with NAFLD and controls without hepatic disorders.
Table 1. Association between the studied single-nucleotide polymorphism and NAFLD. The table presents a distribution of genotypes and alleles of hOGG1 rs1052133, APEX1 rs1760944 and rs1130409, NEIL1 rs4462560, LIG3 rs1052536 and rs4796030, and LIG1 rs20579, as well as OR with 95% CI in groups of patients with NAFLD and controls without hepatic disorders.
Genotype/AlleleNAFLD (n = 150)Control (n = 340)Crude OR
(95% CI)
p-Value
NumberFrequencyNumberFrequency
hOGG1 rs1052133
CC880.5871870.5501.161
(0.787–1.713)
0.955
CG560.3731400.4120.851
0.573–1.263)
0.424
GG60.040130.0381.048
(0.391–2.812)
0.926
χ2 = 0.642; p = 0.725
C2320.773580.7561.114
(0.793–1.563)
0.534
G680.227380.2440.898
(0.640–1.260)
0.534
APEX1 rs1760944
TT290.193650.1911.014
(0.623–1.650)
0.955
TG910.6071540.4531.863
(1.260–2.754)
0.002
GG300.2001210.3560.452
(0.286–0.715)
≤0.001
χ2 = 13.129; p = 0.001
T1490.4972840.4181.385
(1.049–1.827)
0.021
G1510.5033960.5820.722
(0.547–0.953)
0.021
APEX1 rs1130409
TT360.240710.2091.196
(0.758–1.889)
0.442
TG1120.7472020.5942.014
(1.314–3.086)
0.001
GG20.013670.1970.055
(0.013–0.228)
≤0.001
χ2 = 29.192; p  ≤ 0.001
T1840.6133440.5061.870
(1.335–2.618)
≤0.001
G1160.3873360.4940.535
(0.382–0.749)
≤0.001
NEIL1 rs4462560
CC850.5672230.6550.702
(0.472–1.045)
0.081
CG650.4331090.3211.580
(1.060–2.355)
0.025
GG00.00080.024<0.001
(0.000 ± inf)
0.990
χ2 = 8.573; p = 0.014
C2350.7835550.8160.802
(0.555–1.159)
0.240
G650.2171250.1841.247
(0.863–1.803)
0.240
LIG3 rs1052536
CC250.167620.1820.897
(0.538–1.493)
0.675
CT810.5401840.5410.995
(0.677–1.463)
0.981
TT440.293940.2771.086
(0.711–1.660)
0.702
χ2 = 0.250; p = 0.883
C1310.4373080.4530.930
(0.698–1.240)
0.620
T1690.5633720.5471.075
(0.807–1.434)
0.620
LIG3 rs4796030
AA150.100330.0971.041
(0.547–1.981)
0.902
AC490.3271670.4910.492
(0.329–0.737)
≤0.001
CC860.5731400.4121.950
(1.320–2.881)
≤0.001
χ2 = 12.290; p = 0.002
A790.2632330.3430.675
(0.496–0.918)
0.012
C2210.7374470.6571.482
(1.089–2.015)
0.012
LIG1 rs20579
AA10.00730.0090.764
(0.079–7.407)
0.816
AG430.287840.2471.208
(0.782–1.864)
0.394
GG1060.7062530.7440.840
(0.546–1.291)
0.426
χ2 = 0.889; p = 0.641
A450.150900.1321.160
(0.771–1.748)
0.476
G2550.8505900.8680.862
(0.572–1.298)
0.476
χ2—chi-square; CI—confidence interval; OR—odds ratio.
Table 2. Association between the studied single-nucleotide polymorphism and IR in NAFLD. The table presents a distribution of genotypes and alleles of LIG3 rs4796030 and OR with 95% CI in groups of patients with NAFLD and accompanying IR or without IR.
Table 2. Association between the studied single-nucleotide polymorphism and IR in NAFLD. The table presents a distribution of genotypes and alleles of LIG3 rs4796030 and OR with 95% CI in groups of patients with NAFLD and accompanying IR or without IR.
Genotype/Allelewithout IR (n = 130)IR (n = 20)Crude OR
(95% CI)
p-Value
NumberFrequencyNumberFrequency
LIG3 rs4796030
AA140.10810.0502.293
(0.285–18.464)
0.436
AC480.36910.05011.122
(1.443–85.722)
0.021
CC680.523180.9000.122
(0.027–0.547)
0.006
χ2 = 10.279; p = 0.006
A760.29230.0754.420
(1.351–14.466)
0.014
C1840.708370.9250.226
(0.069–0.740)
0.014
χ2—chi-square; CI—confidence interval; OR—odds ratio.
Table 3. Distribution of haplotypes of rs1760944 and rs1130409 of APEX1, as well as haplotypes of rs1052536 and rs4796030 of LIG3, and odds ratio (OR) with 95% confidence interval (95% CI) in patients with NAFLD and controls.
Table 3. Distribution of haplotypes of rs1760944 and rs1130409 of APEX1, as well as haplotypes of rs1052536 and rs4796030 of LIG3, and odds ratio (OR) with 95% confidence interval (95% CI) in patients with NAFLD and controls.
HaplotypeNAFLD (n = 150)Control (n = 340)Crude OR
(95% CI)
p-Value
NumberFrequencyNumberFrequency
APEX1 rs1760944 and rs1130409
TT1260.4202050.3011.677
(1.265–2.223)
≤0.001
GG930.3102570.3770.739
(0.553–0.987)
0.040
TG230.076790.1160.631
(0.388–1.026)
0.061
GT580.1931390.2040.932
(0.662–1.312)
0.690
LIG3 rs1052536 and rs4796030
CC560.186920.1351.466
(1.019–2.111)
0.042
TC1650.5503550.5221.118
(0.851–1.469)
0.445
CA750.2502160.3170.716
(0.526–0.973)
0.032
CI—confidence interval; OR—odds ratio.
Table 4. The characteristic of patients who qualified for the study.
Table 4. The characteristic of patients who qualified for the study.
Number of Patients (Male/Female)77/73
Mean age of patients ± SD60.56 ± 11.04
Mean BMI of patients ± SD33.99 ± 5.38
BMI—body mass index; SD—standard deviation.
Table 5. The number of patients and controls included in the study.
Table 5. The number of patients and controls included in the study.
Patients with NAFLDControls
With IRWithout IR
13020340
IR—insulin resistance; NAFLD—non-alcoholic fatty liver disease.
Table 6. Clinical and biochemical features of patients with non-alcoholic fatty liver disease.
Table 6. Clinical and biochemical features of patients with non-alcoholic fatty liver disease.
ParametersMeanSD
Age, years60.5611.04
BMI, kg m−233.995.38
Fasting glucose, mg dL−1132.0532.52
HbA1c, %7.051.45
ALT, U L−149.0538.34
AST, U L−137.8627.11
Total cholesterol, mg dL−1186.8646.29
HDL cholesterol, mg dL−152.1015.35
LDL cholesterol, mg dL−1102.9739.26
TG, mg dL−1175.1992.17
ALT—alanine transaminase; AST—aspartate aminotransferase; BMI—body mass index; HDL—high-density lipoprotein; LDL—low-density lipoprotein; SD—standard deviation; TG—triglycerides.
Table 7. Single nucleotide polymorphisms selected to the study.
Table 7. Single nucleotide polymorphisms selected to the study.
GeneNCBI
db SNP ID
SNP
Localization
MAF *
hOGG1rs1052133c.977C>G 0.22140
APEX1rs1760944c.-468T>G0.60318
APEX1rs1130409c.444T>G0.46836
NEIL1rs4462560c.*589G>C0.74094
LIG3rs1052536c.*50C>T0.46071
LIG3rs4796030c.*83A>C0.55784
LIG1rs20579c.-7C>T0.12513
*—minor allele frequency (MAF) in European population.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Ziółkowska, S.; Kosmalski, M.; Kołodziej, Ł.; Jabłkowska, A.; Szemraj, J.Z.; Pietras, T.; Jabłkowski, M.; Czarny, P.L. Single-Nucleotide Polymorphisms in Base-Excision Repair-Related Genes Involved in the Risk of an Occurrence of Non-Alcoholic Fatty Liver Disease. Int. J. Mol. Sci. 2023, 24, 11307. https://doi.org/10.3390/ijms241411307

AMA Style

Ziółkowska S, Kosmalski M, Kołodziej Ł, Jabłkowska A, Szemraj JZ, Pietras T, Jabłkowski M, Czarny PL. Single-Nucleotide Polymorphisms in Base-Excision Repair-Related Genes Involved in the Risk of an Occurrence of Non-Alcoholic Fatty Liver Disease. International Journal of Molecular Sciences. 2023; 24(14):11307. https://doi.org/10.3390/ijms241411307

Chicago/Turabian Style

Ziółkowska, Sylwia, Marcin Kosmalski, Łukasz Kołodziej, Aleksandra Jabłkowska, Janusz Zbigniew Szemraj, Tadeusz Pietras, Maciej Jabłkowski, and Piotr Lech Czarny. 2023. "Single-Nucleotide Polymorphisms in Base-Excision Repair-Related Genes Involved in the Risk of an Occurrence of Non-Alcoholic Fatty Liver Disease" International Journal of Molecular Sciences 24, no. 14: 11307. https://doi.org/10.3390/ijms241411307

APA Style

Ziółkowska, S., Kosmalski, M., Kołodziej, Ł., Jabłkowska, A., Szemraj, J. Z., Pietras, T., Jabłkowski, M., & Czarny, P. L. (2023). Single-Nucleotide Polymorphisms in Base-Excision Repair-Related Genes Involved in the Risk of an Occurrence of Non-Alcoholic Fatty Liver Disease. International Journal of Molecular Sciences, 24(14), 11307. https://doi.org/10.3390/ijms241411307

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop