Pharmacogenomics of Drug Response in Type 2 Diabetes: Toward the Definition of Tailored Therapies?

Evaluation of important human CYP450 isoforms and P-glycoprotein phenotype changes and genotype in type 2 diabetic patients, before and after intensifying treatment regimen using Geneva cocktail

The present study evaluates the influence of type 2 diabetes (T2D) on important CYP450 (CYP) isoforms and P-glycoprotein (Pgp) transporter activities before and 3 months after an intensifying treatment regimen involving 40 patients. Results have been compared with 21 non-T2D healthy participants (the control group). CYPs and Pgp activities were assessed after administering the Geneva cocktail. The mean metabolic ratios (MR) for CYP2B6 (1.81 ± 0.93 versus 2.68 ± 0.87), CYP2C19 (0.420 ± 0.360 versus 0.687 ± 0.558) and CYP3A4/5 (0.487 ± 0.226 versus 0.633 ± 0.254) significantly decreased in T2D patients compared to the control group (p < 0.05). CYP2C9 (0.089 ± 0.037 versus 0.069 ± 0.017) activities slightly increased in diabetic patients, and no difference was observed regarding CYP1A2 (0.154 ± 0.085 versus 0.136 ± 0.065), CYP2D6 (1.17 ± 0.56 versus 1.24 ± 0.83), and Pgp activities in comparison to the control group. Three months after the intensifying treatment regimen, MRs of CYP2C9 (0.080 ± 0.030) and CYP3A4/5 (0.592 ± 0.268) improved significantly and were not statistically different compared to the control group (P > 0.05). Several covariables, such as inflammatory markers (IL-1β and IL-6), genotypes, diabetes and demographic-related factors, were considered in the analyses. The results indicate that chronic inflammatory status associated with T2D modulates CYP450 activities in an isoform-specific manner.

CYP2C8 and CYP2E1 genetic variants increase risk of tuberculosis in northwest Chinese Han population

OBJECTIVE

Tuberculosis (TB) is a chronic infectious disease which remains a main cause of death worldwide, and arises more and more concerns in recent years. CytochromeP450 (CYP450) is involved in the metabolism of many exogenous and endogenous compounds, and its polymorphism is associated with many diseases. The objective of our study was to explore the relationship between CYP450 polymorphisms and TB susceptibility in Northwest Chinese Han population.

METHODS

506 TB patients and 506 controls were recruited for our study, and their DNA were extracted. Six single nucleotide polymorphisms (SNPs) were selected for genotype. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated to evaluate the correlation between SNPs and TB risk.

RESULTS

The genotype "TA" of CYP2C8 rs2275620 was related to an increased risk of TB in the co-dominant model (OR = 1.33, 95%CI =1.00-1.76, p = 0.049). In females, CYP2E1 rs2070672 was related to an increased TB susceptibility (co-dominant: OR = 1.62, 95%CI = 1.04-2.52, p = 0.032; dominant: OR = 1.66, 95%CI = 1.08-2.56, p = 0.020; additive: OR = 1.60, 95%CI = 1.08-2.36, p = 0.018), and CYP2E1 rs2515641 was also associated with an increased risk of TB (co-dominant: OR = 1.90, 95%CI = 1.19-3.04, p = 0.007; dominant: OR = 1.94, 95%CI = 1.23-3.05, p = 0.004; additive: OR = 1.80, 95%CI = 1.20-2.71, p = 0.005) in women. But there was no statistical significance between haplotypes and TB risk (p > 0.05).

CONCLUSIONS

Our research showed CYP2C8 and CYP2E1 polymorphisms are associated with an increased risk of TB in Northwest Chinese Han population, which may provide a crucial help on defining new therapeutic strategies for chemoprevention.

Genetic and Epigenomic Modifiers of Diabetic Neuropathy

Diabetic neuropathy (DN), the most common chronic and progressive complication of diabetes mellitus (DM), strongly affects patients’ quality of life. DN could be present as peripheral, autonomous or, clinically also relevant, uremic neuropathy. The etiopathogenesis of DN is multifactorial, and genetic components play a role both in its occurrence and clinical course. A number of gene polymorphisms in candidate genes have been assessed as susceptibility factors for DN, and most of them are linked to mechanisms such as reactive oxygen species production, neurovascular impairments and modified protein glycosylation, as well as immunomodulation and inflammation. Different epigenomic mechanisms such as DNA methylation, histone modifications and non-coding RNA action have been studied in DN, which also underline the importance of “metabolic memory” in DN appearance and progression. In this review, we summarize most of the relevant data in the field of genetics and epigenomics of DN, hoping they will become significant for diagnosis, therapy and prevention of DN.

PPARγ and Diabetes: Beyond the Genome and Towards Personalized Medicine

PURPOSE OF REVIEW

Full and partial synthetic agonists targeting the transcription factor PPARγ are contained in FDA-approved insulin-sensitizing drugs and used for the treatment of metabolic syndrome-related dysfunctions. Here, we discuss the association between PPARG genetic variants and drug efficacy, as well as the role of alternative splicing and post-translational modifications as contributors to the complexity of PPARγ signaling and to the effects of synthetic PPARγ ligands.

RECENT FINDINGS

PPARγ regulates the transcription of several target genes governing adipocyte differentiation and glucose and lipid metabolism, as well as insulin sensitivity and inflammatory pathways. These pleiotropic functions confer great relevance to PPARγ in physiological regulation of whole-body metabolism, as well as in the etiology of metabolic disorders. Accordingly, PPARG gene mutations, nucleotide variations, and post-translational modifications have been associated with adipose tissue disorders and the related risk of insulin resistance and type 2 diabetes (T2D). Moreover, PPARγ alternative splicing isoforms-generating dominant-negative isoforms mainly expressed in human adipose tissue-have been related to impaired PPARγ activity and adipose tissue dysfunctions. Thus, multiple regulatory levels that contribute to PPARγ signaling complexity may account for the beneficial as well as adverse effects of PPARγ agonists. Further targeted analyses, taking into account all these aspects, are needed for better deciphering the role of PPARγ in human pathophysiology, especially in insulin resistance and T2D. The therapeutic potential of full and partial PPARγ synthetic agonists underlines the clinical significance of this nuclear receptor. PPARG mutations, polymorphisms, alternative splicing isoforms, and post-translational modifications may contribute to the pathogenesis of metabolic disorders, also influencing the responsiveness of pharmacological therapy. Therefore, in the context of the current evidence-based trend to personalized diabetes management, we highlight the need to decipher the intricate regulation of PPARγ signaling to pave the way to tailored therapies in patients with insulin resistance and T2D.

Single Nucleotide Polymorphisms Associated with Metformin and Sulphonylureas' Glycaemic Response among South African Adults with Type 2 Diabetes Mellitus

Aims: To examine the association of polymorphisms belonging to SLC22A1, SP1, PRPF31, NBEA, SCNN1B, CPA6 and CAPN10 genes with glycaemic response to metformin and sulphonylureas (SU) combination therapy among South African adults with diabetes mellitus type 2 (T2DM). Methods: A total of 128 individuals of Swati (n = 22) and Zulu (n = 106) origin attending chronic care for T2DM were recruited. Nine SNPs previously associated with metformin and SUs were selected and genotyped using MassArray. Uncontrolled T2DM was defined as HbA1c > 7%. The association between genotypes, alleles and glycaemic response to treatment was determined using multivariate logistic regression model analysis. Results: About 85.93% (n = 110) of the study participants were female and 77.34% (n = 99) had uncontrolled T2DM (HbA1c > 7%). In the multivariate (adjusted) logistic regression model analysis, the CC genotype of rs2162145 (CPA6), GG and GA genotypes of rs889299 (SCNN1B) were significantly associated with uncontrolled T2DM. On the other hand, the C allele of rs254271 (PRPF31) and the GA genotype of rs3792269 (CAPN10) were associated with controlled T2DM. A significant interaction between rs2162145 and rs889299 in response to metformin and SU combination therapy was observed. Conclusions: In this study, we reported the association of rs2162145 (CC) and rs889299 (GG and GA) with uncontrolled T2DM. We also reported the association of rs254271 (C) and rs3792269 (GA) with controlled T2DM in response to metformin and SU combination therapy. Furthermore, an interaction between rs2162145 and rs889299 was established, where the genotype combination GA (rs889299) and TT (rs2162145) was associated with uncontrolled T2DM.

Analysis of the Potential Association of Drug-Metabolizing Enzymes CYP2C9*3 and CYP2C19*3 Gene Variations With Type 2 Diabetes: A Case-Control Study

BACKGROUND

Cytochrome P450s (CYPs) are drug-metabolizing enzymes catalyzing the metabolism of about 75% of drug in clinical use. CYP2C9 represents 20% CYP proteins in liver cells and is a crucial member of CYPs superfamily. CYP2C19 metabolizes very important drugs such as antiulcer drug omeprazole, the antiplatelet drug clopidogrel and anticonvulsant mephenytoin. Single nucleotide polymorphisms (SNPs) of CYP genes have been associated with unexpected drug reactions and diseases in different populations.

OBJECTIVE

We examined the associations of CYP2C9*3 (rs1057910) and CYP2C19*3 (rs4986893) with T2D in Saudi population.

METHODS

We used the allele-specific PCR (AS-PCR) and DNA sequencing in 111 cases and 104 controls for rs1057910, and in 119 cases and 110 controls for rs4986893.

RESULTS

It is indicated that the genotype distribution of rs1057910 in cases and controls were not significantly different (P=0.0001). The genotypes of rs1057910 were not associated with type 2 diabetes (T2D) (P>0.05). Whereas the genotype distribution of rs4986893 in cases and controls was significantly different (P=0.049). The AA genotype of rs4986893 may be associated in increased risk to T2D with OR=17.25 (2.06-143.8), RR=6.14(0.96-39.20), P=0.008.

CONCLUSION

The CYP2C9*3 (rs1057910) may not be associated with T2D, while CYP2C19*3 (rs4986893) is probably associated with T2D. These findings need to be validated in follow-up studies with larger sample sizes and different populations.

Genetic predisposition in type 2 diabetes: A promising approach toward a personalized management of diabetes

Diabetes mellitus, also known simply as diabetes, has been described as a chronic and complex endocrine metabolic disorder that is a leading cause of death across the globe. It is considered a key public health problem worldwide and one of four important non-communicable diseases prioritized for intervention through world health campaigns by various international foundations. Among its four categories, Type 2 diabetes (T2D) is the commonest form of diabetes accounting for over 90% of worldwide cases. Unlike monogenic inherited disorders that are passed on in a simple pattern, T2D is a multifactorial disease with a complex etiology, where a mixture of genetic and environmental factors are strong candidates for the development of the clinical condition and pathology. The genetic factors are believed to be key predisposing determinants in individual susceptibility to T2D. Therefore, identifying the predisposing genetic variants could be a crucial step in T2D management as it may ameliorate the clinical condition and preclude complications. Through an understanding the unique genetic and environmental factors that influence the development of this chronic disease individuals can benefit from personalized approaches to treatment. We searched the literature published in three electronic databases: PubMed, Scopus and ISI Web of Science for the current status of T2D and its associated genetic risk variants and discus promising approaches toward a personalized management of this chronic, non-communicable disorder.

The Play of Genes and Non-genetic Factors on Type 2 Diabetes

Diabetes has been a disease of public health concern for a number of decades. It was in the 1930s when scientists made an interesting discovery that the disease is actually divided into two types as some patients were insensitive to insulin treatment then. Type 2 Diabetes which happens to be the non-insulin dependent one is the most common form of the disease and is caused by the interaction between genetic and non-genetic factors. Despite conflicting results, numerous studies have identified genetic and non-genetic factors associated with this common type of diabetes. This review has summarized literature on some genes and non-genetic factors which have been identified to be associated with Type 2 diabetes. It has sourced literature from PubMed, Web of Science and Medline without any limitation to regions, publication types, or languages. The paper has started with the introduction, the play of non-genetic factors, the impact of genes in general, and ended with the interaction between some genes and environmental factors.

Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes

Type 2 diabetes (T2D) mellitus is a common complex disease that currently affects more than 400 million people worldwide and has become a global health problem. High-throughput sequencing technologies such as whole-genome and whole-exome sequencing approaches have provided numerous new insights into the molecular bases of T2D. Recent advances in the application of sequencing technologies to T2D research include, but are not limited to: (1) Fine mapping of causal rare and common genetic variants; (2) Identification of confident gene-level associations; (3) Identification of novel candidate genes by specific scoring approaches; (4) Interrogation of disease-relevant genes and pathways by transcriptional profiling and epigenome mapping techniques; and (5) Investigation of microbial community alterations in patients with T2D. In this work we review these advances in application of next-generation sequencing methods for elucidation of T2D pathogenesis, as well as progress and challenges in implementation of this new knowledge about T2D genetics in diagnosis, prevention, and treatment of the disease.

Cytochrome P450: Polymorphisms and Roles in Cancer, Diabetes and Atherosclerosis

Cytochromes P450s (CYPs) constitute a superfamily of enzymes that catalyze the metabolism of drugs and other substances. Endogenous substrates of CYPs include eicosanoids, estradiol, arachidonic acids, cholesterol, vitamin D and neurotransmitters. Exogenous substrates of CYPs include the polycyclic aromatic hydrocarbons and about 80% of currently used drugs. Some isoforms can activate procarcinogens to ultimate carcinogens. Genetic polymorphisms of CYPs may affect the enzyme catalytic activity and have been reported among different populations to be associated with various diseases and adverse drug reactions. With regard of drug metabolism, phenotypes for CYP polymorphism range from ultrarapid to poor metabolizers. In this review, we discuss some of the most clinically important CYPs isoforms (CYP2D6, CYP2A6, CYP2C19, CYP2C9, CYP1B1 and CYP1A2) with respect to gene polymorphisms and drug metabolism. Moreover, we review the role of CYPs in renal, lung, breast and prostate cancers and also discuss their significance for atherosclerosis and type 2 diabetes mellitus.

Pharmacogenetic landscape of Metabolic Syndrome components drug response in Tunisia and comparison with worldwide populations

Genetic variation is an important determinant affecting either drug response or susceptibility to adverse drug reactions. Several studies have highlighted the importance of ethnicity in influencing drug response variability that should be considered during drug development. Our objective is to characterize the genetic variability of some pharmacogenes involved in the response to drugs used for the treatment of Metabolic Syndrome (MetS) in Tunisia and to compare our results to the worldwide populations. A set of 135 Tunisians was genotyped using the Affymetrix Chip 6.0 genotyping array. Variants located in 24 Very Important Pharmacogenes (VIP) involved in MetS drug response were extracted from the genotyping data. Analysis of variant distribution in Tunisian population compared to 20 worldwide populations publicly available was performed using R software packages. Common variants between Tunisians and the 20 investigated populations were extracted from genotyping data. Multidimensional screening showed that Tunisian population is clustered with North African and European populations. The greatest divergence was observed with the African and Asian population. In addition, we performed Inter-ethnic comparison based on the genotype frequencies of five VIP biomarkers. The genotype frequencies of the biomarkers rs3846662, rs1045642, rs7294 and rs12255372 located respectively in HMGCR, ABCB1, VKORC1 and TCF7L2 are similar between Tunisian, Tuscan (TSI) and European (CEU). The genotype frequency of the variant rs776746 located in CYP3A5 gene is similar between Tunisian and African populations and different from CEU and TSI. The present study shows that the genetic make up of the Tunisian population is relatively complex in regard to pharmacogenes and reflects previous historical events. It is important to consider this ethnic difference in drug prescription in order to optimize drug response to avoid serious adverse drug reactions. Taking into account similarities with other neighboring populations, our study has an impact not only on the Tunisian population but also on North African population which are underrepresented in pharmacogenomic studies.

The Application of Genomics in Diabetes: Barriers to Discovery and Implementation

The emerging availability of genomic and electronic health data in large populations is a powerful tool for research that has drawn interest in bringing precision medicine to diabetes. In this article, we discuss the potential application of genomics to the prediction, prevention, and treatment of diabetes, and we use examples from other areas of medicine to illustrate some of the challenges involved in conducting genomics research in human populations and implementing findings in practice. At this time, a major barrier to the application of genomics in diabetes care is the lack of actionable genomic findings. Whether genomic information should be used in clinical practice requires a framework for evaluating the validity and clinical utility of this approach, an improved integration of genomic data into electronic health records, and the clinical decision support and educational resources for clinicians to use these data. Efforts to identify optimal approaches in all of these domains are in progress and may help to bring diabetes into the era of genomic medicine.

Challenges of implementing personalized (precision) medicine: a focus on diabetes

The concept of personalized (precision) medicine (PM) emphasizes the scientific and technological innovations that enable the physician to tailor disease prediction, diagnosis and treatment to the individual patient, based on a personalized data-driven approach. The major challenge for the medical systems is to translate the molecular and genomic advances into clinical available means. Patients and healthcare providers, the pharmaceutical and diagnostic industries manifest a growing interest in PM. Multiple stakeholders need adaptation and re-engineering for successful clinical implementation of PM. Drawing primarily from the field of ‘diabetes’, this article will summarize the main challenges to implementation of PM into current medical practice and some of the approaches currently being implemented to overcome these challenges.

Computational Analysis of Single Nucleotide Polymorphisms Associated with Altered Drug Responsiveness in Type 2 Diabetes

Type 2 diabetes (T2D) is one of the most frequent mortality causes in western countries, with rapidly increasing prevalence. Anti-diabetic drugs are the first therapeutic approach, although many patients develop drug resistance. Most drug responsiveness variability can be explained by genetic causes. Inter-individual variability is principally due to single nucleotide polymorphisms, and differential drug responsiveness has been correlated to alteration in genes involved in drug metabolism (CYP2C9) or insulin signaling (IRS1, ABCC8, KCNJ11 and PPARG). However, most genome-wide association studies did not provide clues about the contribution of DNA variations to impaired drug responsiveness. Thus, characterizing T2D drug responsiveness variants is needed to guide clinicians toward tailored therapeutic approaches. Here, we extensively investigated polymorphisms associated with altered drug response in T2D, predicting their effects in silico. Combining different computational approaches, we focused on the expression pattern of genes correlated to drug resistance and inferred evolutionary conservation of polymorphic residues, computationally predicting the biochemical properties of polymorphic proteins. Using RNA-Sequencing followed by targeted validation, we identified and experimentally confirmed that two nucleotide variations in the CAPN10 gene—currently annotated as intronic—fall within two new transcripts in this locus. Additionally, we found that a Single Nucleotide Polymorphism (SNP), currently reported as intergenic, maps to the intron of a new transcript, harboring CAPN10 and GPR35 genes, which undergoes non-sense mediated decay. Finally, we analyzed variants that fall into non-coding regulatory regions of yet underestimated functional significance, predicting that some of them can potentially affect gene expression and/or post-transcriptional regulation of mRNAs affecting the splicing.