Association of Genomic Instability with HbA1c levels and Medication in Diabetic Patients

Annemarie Grindel, Helmut Brath, Armen Nersesyan, Siegfried Knasmueller, Karl-Heinz Wagner, Annemarie Grindel, Helmut Brath, Armen Nersesyan, Siegfried Knasmueller, Karl-Heinz Wagner

Abstract

Diabetes Mellitus type 2 (DM2) is associated with increased cancer risk. Instability of the genetic material plays a key role in the aetiology of human cancer. This study aimed to analyse genomic instability with the micronucleus cytome assay in exfoliated buccal cells depending on glycated haemoglobin (HbA1c) levels and medication in 146 female DM2 patients. The occurrence of micronuclei was significantly increased in DM2 patients compared to healthy controls. Furthermore, it was doubled in DM2 patients with HbA1c > 7.5% compared to subjects with HbA1c ≤ 7.5%. Positive correlations were found between micronuclei frequencies and HbA1c as well as fasting plasma glucose. Patients under insulin treatment showed a two-fold increase in micronuclei frequencies compared to subjects under first-line medication (no drugs or monotherapy with non-insulin medication). However, after separation of HbA1c (cut-off 7.5%) only patients with severe DM2 characterised by high HbA1c and insulin treatment showed higher micronuclei frequencies but not patients with insulin treatment and low HbA1c. We demonstrated that the severity of DM2 accompanied by elevated micronuclei frequencies predict a possible enhanced cancer risk among female DM2 patients. Therapy, therefore, should focus on a strict HbA1c control and personalised medical treatments.

Conflict of interest statement

The authors declare no competing financial interests.

Figures

Figure 1. Differences of MN between HbA1c…
Figure 1. Differences of MN between HbA1c ≤ 7.5%, HbA1c > 7.5% and healthy controls.
Control group comprised 15 female healthy controls which were described previously. General characteristics of controls can be found in Supplementary Table 1. Bars show means and standard errors. White numbers in bars indicate the number of patients. Differences between the groups were analysed with Kruskal-Wallis test with pairwise comparisons. All groups were significantly different to each other with p 

Figure 2

Spearman correlation analyses were performed…

Figure 2

Spearman correlation analyses were performed for total MN and HbA1c ( a )…

Figure 2
Spearman correlation analyses were performed for total MN and HbA1c (a) and for total MN and FPG (b) for all DM2 subjects plus healthy controls (n = 161). Correlation analyses for controls (n = 15) and patients with either HbA1c ≤ 7.5% (n = 74) or HbA1c > 7.5% (n = 72) are presented for HbA1c with total MN (c). Control group comprised 15 female healthy controls which were described previously. r, spearman correlation coefficient; * indicates significance with p < 0.05 and *** for p < 0.001.

Figure 3. MN frequencies depending on Med…

Figure 3. MN frequencies depending on Med groups.

Total MN frequencies were assessed in controls…

Figure 3. MN frequencies depending on Med groups.
Total MN frequencies were assessed in controls (n = 15) and patients of three medication groups: Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication).Control group comprised 15 female healthy controls which were described previously. Bars show means and standard errors. White numbers in bars indicate the number of patients. Differences between the groups were analysed with Kruskal-Wallis test with pairwise comparisons. Significance was assumed with p 

Figure 4. Distribution of MN frequencies depending…

Figure 4. Distribution of MN frequencies depending on Med groups and HbA1c (cut-off 7.5%).

Med…

Figure 4. Distribution of MN frequencies depending on Med groups and HbA1c (cut-off 7.5%).
Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication). Each dot represents MN frequency of one patient. Med A within HbA1c > 7.5% was excluded from statistics due to only two cases. Differences between the groups were analysed with ANCOVA, diabetes duration and BMI as covariates. *represents significant difference to Med C of HbA1c > 7.5% with p < 0.01. #represents significant difference to Med B of HbA1c > 7.5% with p < 0.05. †indicates trend of difference to Med B of HbA1c > 7.5% with p < 0.1.

Figure 5. COVAIN results of PCA and…

Figure 5. COVAIN results of PCA and bi-clustering of the 5 groups, divided by HbA1c…

Figure 5. COVAIN results of PCA and bi-clustering of the 5 groups, divided by HbA1c and medication (Med A, B, C for HbA1c ≤ 7.5% and Med B, C for HbA1c > 7.5%).
Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication). Med A for HbA1c > 7.5% was excluded from statistics because of only 2 cases. (a) PCA plot shows two overlapping clusters representing the high HbA1c Med groups (red circle 1) and the low HbA1c Med groups (green circle 2). (b) Heat map shows bi-clustering of the 5 groups with contributing variables. A distinct grouping of Med B&C for either HbA1c ≤ 7.5% or HbA1c > 7.5% and a separate standing of Med A resulted. For detailed information about the differences between the 5 groups see Supplementary Table 2.
Similar articles
Cited by
References
    1. Inzucchi S. E. et al.. Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 55, 1577–1596, doi: 10.1007/s00125-012-2534-0 (2012). - DOI - PubMed
    1. Inzucchi S. E. et al.. Management of hyperglycaemia in type 2 diabetes, 2015: a patient-centred approach. Update to a Position Statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetologia 58, 429–442, doi: 10.1007/s00125-014-3460-0 (2015). - DOI - PubMed
    1. Inzucchi S. E. & Majumdar S. K. Current Therapies for the Medical Management of Diabetes. Obstet. Gynecol. 127, 780–794, doi: 10.1097/aog.0000000000001332 (2016). - DOI - PubMed
    1. American Diabetes Association. Glycemic targets. Diabetes Care 38 Suppl, S33–40, doi: 10.2337/dc15-S009 (2015). - DOI - PubMed
    1. Zoungas S. et al.. Association of HbA(1c) levels with vascular complications and death in patients with type 2 diabetes: evidence of glycaemic thresholds. Diabetologia 55, 636–643, doi: 10.1007/s00125-011-2404-1 (2012). - DOI - PubMed
Show all 39 references
Publication types
MeSH terms
Related information
[x]
Cite
Copy Download .nbib
Format: AMA APA MLA NLM
Figure 2
Figure 2
Spearman correlation analyses were performed for total MN and HbA1c (a) and for total MN and FPG (b) for all DM2 subjects plus healthy controls (n = 161). Correlation analyses for controls (n = 15) and patients with either HbA1c ≤ 7.5% (n = 74) or HbA1c > 7.5% (n = 72) are presented for HbA1c with total MN (c). Control group comprised 15 female healthy controls which were described previously. r, spearman correlation coefficient; * indicates significance with p < 0.05 and *** for p < 0.001.
Figure 3. MN frequencies depending on Med…
Figure 3. MN frequencies depending on Med groups.
Total MN frequencies were assessed in controls (n = 15) and patients of three medication groups: Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication).Control group comprised 15 female healthy controls which were described previously. Bars show means and standard errors. White numbers in bars indicate the number of patients. Differences between the groups were analysed with Kruskal-Wallis test with pairwise comparisons. Significance was assumed with p 

Figure 4. Distribution of MN frequencies depending…

Figure 4. Distribution of MN frequencies depending on Med groups and HbA1c (cut-off 7.5%).

Med…

Figure 4. Distribution of MN frequencies depending on Med groups and HbA1c (cut-off 7.5%).
Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication). Each dot represents MN frequency of one patient. Med A within HbA1c > 7.5% was excluded from statistics due to only two cases. Differences between the groups were analysed with ANCOVA, diabetes duration and BMI as covariates. *represents significant difference to Med C of HbA1c > 7.5% with p < 0.01. #represents significant difference to Med B of HbA1c > 7.5% with p < 0.05. †indicates trend of difference to Med B of HbA1c > 7.5% with p < 0.1.

Figure 5. COVAIN results of PCA and…

Figure 5. COVAIN results of PCA and bi-clustering of the 5 groups, divided by HbA1c…

Figure 5. COVAIN results of PCA and bi-clustering of the 5 groups, divided by HbA1c and medication (Med A, B, C for HbA1c ≤ 7.5% and Med B, C for HbA1c > 7.5%).
Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication). Med A for HbA1c > 7.5% was excluded from statistics because of only 2 cases. (a) PCA plot shows two overlapping clusters representing the high HbA1c Med groups (red circle 1) and the low HbA1c Med groups (green circle 2). (b) Heat map shows bi-clustering of the 5 groups with contributing variables. A distinct grouping of Med B&C for either HbA1c ≤ 7.5% or HbA1c > 7.5% and a separate standing of Med A resulted. For detailed information about the differences between the 5 groups see Supplementary Table 2.
Figure 4. Distribution of MN frequencies depending…
Figure 4. Distribution of MN frequencies depending on Med groups and HbA1c (cut-off 7.5%).
Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication). Each dot represents MN frequency of one patient. Med A within HbA1c > 7.5% was excluded from statistics due to only two cases. Differences between the groups were analysed with ANCOVA, diabetes duration and BMI as covariates. *represents significant difference to Med C of HbA1c > 7.5% with p < 0.01. #represents significant difference to Med B of HbA1c > 7.5% with p < 0.05. †indicates trend of difference to Med B of HbA1c > 7.5% with p < 0.1.
Figure 5. COVAIN results of PCA and…
Figure 5. COVAIN results of PCA and bi-clustering of the 5 groups, divided by HbA1c and medication (Med A, B, C for HbA1c ≤ 7.5% and Med B, C for HbA1c > 7.5%).
Med A: no medication or non-insulin monotherapy; Med B: non-insulin combination therapy; Med C: insulin medication (with or without other non-insulin medication). Med A for HbA1c > 7.5% was excluded from statistics because of only 2 cases. (a) PCA plot shows two overlapping clusters representing the high HbA1c Med groups (red circle 1) and the low HbA1c Med groups (green circle 2). (b) Heat map shows bi-clustering of the 5 groups with contributing variables. A distinct grouping of Med B&C for either HbA1c ≤ 7.5% or HbA1c > 7.5% and a separate standing of Med A resulted. For detailed information about the differences between the 5 groups see Supplementary Table 2.

References

    1. Inzucchi S. E. et al.. Management of hyperglycaemia in type 2 diabetes: a patient-centered approach. Position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD). Diabetologia 55, 1577–1596, doi: 10.1007/s00125-012-2534-0 (2012).
    1. Inzucchi S. E. et al.. Management of hyperglycaemia in type 2 diabetes, 2015: a patient-centred approach. Update to a Position Statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetologia 58, 429–442, doi: 10.1007/s00125-014-3460-0 (2015).
    1. Inzucchi S. E. & Majumdar S. K. Current Therapies for the Medical Management of Diabetes. Obstet. Gynecol. 127, 780–794, doi: 10.1097/aog.0000000000001332 (2016).
    1. American Diabetes Association. Glycemic targets. Diabetes Care 38 Suppl, S33–40, doi: 10.2337/dc15-S009 (2015).
    1. Zoungas S. et al.. Association of HbA(1c) levels with vascular complications and death in patients with type 2 diabetes: evidence of glycaemic thresholds. Diabetologia 55, 636–643, doi: 10.1007/s00125-011-2404-1 (2012).
    1. de Beer J. C. & Liebenberg L. Does cancer risk increase with HbA(1c), independent of diabetes? Br. J. Cancer 110, 2361–2368, doi: 10.1038/bjc.2014.150 (2014).
    1. Goto A. et al.. High hemoglobin A1c levels within the non-diabetic range are associated with the risk of all cancers. Int. J. Cancer 138, 1741–1753, doi: 10.1002/ijc.29917 (2016).
    1. Hua F., Yu J. J. & Hu Z. W. Diabetes and cancer, common threads and missing links. Cancer Lett. 374, 54–61, doi: 10.1016/j.canlet.2016.02.006 (2016).
    1. Ferguson L. R. et al.. Genomic instability in human cancer: Molecular insights and opportunities for therapeutic attack and prevention through diet and nutrition. Semin. Cancer Biol. 35, S5–S24, doi: 10.1016/j.semcancer.2015.03.005 (2015).
    1. Shen Z. Y. Genomic instability and cancer: an introduction. J. Mol. Cell Biol. 3, 1–3, doi: 10.1093/jmcb/mjq057 (2011).
    1. Thomas P. et al.. Buccal micronucleus cytome assay. Nat. Protoc. 4, 825–837, doi: 10.1038/nprot.2009.53 (2009).
    1. Bolognesi C., Knasmueller S., Nersesyan A., Thomas P. & Fenech M. The HUMNxl scoring criteria for different cell types and nuclear anomalies in the buccal micronucleus cytome assay - An update and expanded photogallery. Mutat. Res.-Rev. Mutat. Res. 753, 100–113, doi: 10.1016/j.mrrev.2013.07.002 (2013).
    1. Mullner E. et al.. Nuclear anomalies in exfoliated buccal cells in healthy and diabetic individuals and the impact of a dietary intervention. Mutagenesis 29, 1–6, doi: 10.1093/mutage/get056 (2014).
    1. Sun X. L. & Weckwerth W. COVAIN: a toolbox for uni- and multivariate statistics, time-series and correlation network analysis and inverse estimation of the differential Jacobian from metabolomics covariance data. Metabolomics 8, S81–S93, doi: 10.1007/s11306-012-0399-3 (2012).
    1. Gomez-Meda B. C. et al.. Nuclear abnormalities in buccal mucosa cells of patients with type I and II diabetes treated with folic acid. Mutat. Res. Genet. Toxicol. Environ. Mutagen. 797, 1–8, doi: 10.1016/j.mrgentox.2015.12.003 (2016).
    1. Castillo J. J., Mull N., Reagan J. L., Nemr S. & Mitri J. Increased incidence of non-Hodgkin lymphoma, leukemia, and myeloma in patients with diabetes mellitus type 2: a meta-analysis of observational studies. Blood 119, 4845–4850, doi: 10.1182/blood-2011-06-362830 (2012).
    1. El-Serag H. B., Hampel H. & Javadi F. The association between diabetes and hepatocellular carcinoma: A systematic review of epidemiologic evidence. Clin. Gastroenterol. Hepatol. 4, 369–380, doi: 10.1016/j.cgh.2005.12.007 (2006).
    1. Song S. S. et al.. Long-Term Diabetes Mellitus Is Associated with an Increased Risk of Pancreatic Cancer: A Meta-Analysis. PLoS One 10, 27, doi: e0134321 10.1371/journal.pone.0134321 (2015).
    1. Lee J. Y., Jeon I., Lee J. M., Yoon J. M. & Park S. M. Diabetes mellitus as an independent risk factor for lung cancer: A meta-analysis of observational studies. Eur. J. Cancer 49, 2411–2423, doi: 10.1016/j.ejca.2013.02.025 (2013).
    1. Fang H. et al.. Diabetes Mellitus Increases the Risk of Bladder Cancer: An Updated Meta-Analysis of Observational Studies. Diabetes Technol. Ther. 15, 914–922, doi: 10.1089/dia.2013.0131 (2013).
    1. Guraya S. Y. Association of type 2 diabetes mellitus and the risk of colorectal cancer: A meta-analysis and systematic review. World J. Gastroenterol. 21, 6026–6031, doi: 10.3748/wjg.v21.i19.6026 (2015).
    1. Hardefeldt P. J., Edirimanne S. & Eslick G. D. Diabetes increases the risk of breast cancer: a meta-analysis. Endocrine-related cancer 19, 793–803, doi: 10.1530/erc-12-0242 (2012).
    1. Gong Y. H., Wei B. J., Yu L. & Pan W. J. Type 2 diabetes mellitus and risk of oral cancer and precancerous lesions: A meta-analysis of observational studies. Oral Oncol. 51, 332–340, doi: 10.1016/j.oraloncology.2015.01.003 (2015).
    1. Nathan D. M., Turgeon H. & Regan S. Relationship between glycated haemoglobin levels and mean glucose levels over time. Diabetologia 50, 2239–2244, doi: 10.1007/s00125-007-0803-0 (2007).
    1. Wu L., Zhu J. J., Prokop L. J. & Murad M. H. Pharmacologic Therapy of Diabetes and Overall Cancer Risk and Mortality: A Meta-Analysis of 265 Studies. Sci Rep 5, 10, doi: 10.1038/srep10147 (2015).
    1. Holden S. E., Jenkins-Jones S., Morgan C. L., Schernthaner G. & Currie C. J. Glucose-lowering with exogenous insulin monotherapy in type 2 diabetes: dose association with all-cause mortality, cardiovascular events and cancer. Diabetes Obes. Metab. 17, 350–362, doi: 10.1111/dom.12412 (2015).
    1. Biddinger S. B. & Ludwig D. S. The insulin-like growth factor axis: a potential link between glycemic index and cancer. Am. J. Clin. Nutr. 82, 277–278 (2005).
    1. Noto H., Goto A., Tsujimoto T., Osame K. & Noda M. Latest insights into the risk of cancer in diabetes. J. Diabetes Investig. 4, 225–232, doi: 10.1111/jdi.12068 (2013).
    1. Kowall B. & Rathmann W. & Kostev, K. Are Sulfonylurea and Insulin Therapies Associated With a Larger Risk of Cancer Than Metformin Therapy? A Retrospective Database Analysis. Diabetes Care 38, 59–65, doi: 10.2337/dc14-0977 (2015).
    1. Bolognesi C. et al.. Clinical application of micronucleus test in exfoliated buccal cells: A systematic review and metanalysis. Mutat. Res.-Rev. Mutat. Res. 766, 20–31, doi: 10.1016/j.mrrev.2015.07.002 (2015).
    1. Bonassi S. et al.. The HUman MicroNucleus project on eXfoLiated buccal cells (HUMNXL): The role of life-style, host factors, occupational exposures, health status, and assay protocol. Mutat. Res.-Rev. Mutat. Res. 728, 88–97, doi: 10.1016/j.mrrev.2011.06.005 (2011).
    1. Bonassi S. et al.. An increased micronucleus frequency in peripheral blood lymphocytes predicts the risk of cancer in humans. Carcinogenesis 28, 625–631, doi: 10.1093/carcin/bgl177 (2007).
    1. Ceppi M., Biasotti B., Fenech M. & Bonassi S. Human population studies with the exfoliated buccal micronucleus assay: Statistical and epidemiological issues. Mutat. Res.-Rev. Mutat. Res. 705, 11–19, doi: 10.1016/j.mrrev.2009.11.001 (2010).
    1. Cairns J. Mutation selection and natural-history of cancer. Nature 255, 197–200, doi: 10.1038/255197a0 (1975).
    1. Grindel A. et al.. Oxidative Stress, DNA Damage and DNA Repair in Female Patients with Diabetes Mellitus Type 2. PLoS One 11, e0162082, doi: 10. 1371/journal.pone.016082 (2016).
    1. Mullner E. et al.. Vegetables and PUFA-rich plant oil reduce DNA strand breaks in individuals with type 2 diabetes. Mol. Nutr. Food Res. 57, 328–338, doi: 10.1002/mnfr.201200343 (2013).
    1. Mullner E. et al.. Impact of polyunsaturated vegetable oils on adiponectin levels, glycaemia and blood lipids in individuals with type 2 diabetes: a randomised, double-blind intervention study. J. Hum. Nutr. Diet. 27, 468–478, doi: 10.1111/jhn.12168 (2014).
    1. D’Agostino R. B. et al.. General cardiovascular risk profile for use in primary care: The Framingham heart study. Circulation 118, E86–E86, doi: 10.1161/circulationaha.108.190154 (2008).
    1. Tolbert P. E., Shy C. M. & Allen J. W. Micronuclei and other nuclear anomalies in buccal smears - methods development. Mutation Research 271, 69–77, doi: 10.1016/0165-1161(92)90033-i (1992).

Source: PubMed

3
Subscribe