Mitochondrial-targeted curcumin inhibits T-cell activation via Nrf2 and inhibits graft-versus-host-disease in a mouse model.

Anti-inflammatory and immune suppressive agents are required to moderate hyper-activation of lymphocytes under disease conditions or organ transplantation. However, selective disruption of mitochondrial redox has not been evaluated as a therapeutic strategy for suppression of T-cell-mediated pathologies. Using mitochondrial targeted curcumin (MitoC), we studied the effect of mitochondrial redox modulation on T-cell responses by flow cytometry, transmission electron microscopy, transcriptomics, and proteomics, and the role of Nrf2 was studied using Nrf2- /- mice. MitoC decreased mitochondrial TrxR activity, enhanced mitochondrial ROS (mROS) production, depleted mitochondrial glutathione, and suppressed activation-induced increase in mitochondrial biomass. This led to suppression of T-cell responses and metabolic reprogramming towards Treg differentiation. MitoC induced nuclear translocation and DNA binding of Nrf2, leading to upregulation of Nrf2-dependent genes and proteins. MitoC-mediated changes in mitochondrial redox and modulation of T-cell responses are abolished in Nrf2- /- mice. Restoration of mitochondrial thiols abrogated inhibition of T-cell responses. MitoC suppressed alloantigen-induced lymphoblast formation, inflammatory cytokines, morbidity, and mortality in acute graft-versus-host disease mice. Disruption of mitochondrial thiols but not mROS increase inculcates an Nrf2-dependent immune-suppressive disposition in T cells for the propitious treatment of graft-versus-host disease.

Association of Catechol-O-Methyltransferase Gene Polymorphisms and Haplotypes in the Levodopa-Induced Adverse Events in Subjects with Parkinson's Disease.

The presence of dyskinesia is the most common side effect of chronic administration of levodopa in Parkinson's disease (PD) subjects. Genetic polymorphisms in levodopa metabolizing gene, catechol-O-methyl transferase (COMT), is shown to influence the inter-individual variability in drug response and adverse events. In the present study, the association of COMT rs6269, rs4633, rs4818, and rs4680 polymorphisms and haplotypes on pharmacokinetics and adverse events with levodopa was investigated in 150 PD patients. The age of onset of PD was 58.00 ± 10 yrs. The most common side effect faced by 78% of the subjects was dyskinesia. The AUC of levodopa was found to be significantly higher in subjects with dyskinesia (1695 ± 113 ng/ml/hr, p < 0.0001) than those without dyskinesia (1550 ± 122 ng/ml/hr). We found that the frequency of subjects presenting dyskinesia was significantly higher in subjects carrying variant genotype of COMT rs6269, rs4633, and rs4680 than that with wild genotype and these subjects presented higher AUC of levodopa. In addition, in subjects with dyskinesia, the AUC of levodopa was found to be significantly higher with low COMT (ACCG) haplotype. The association of COMT rs6269, COMT rs4633, COMT rs4818, and COMT rs4680 variant genotypes with the risk of dyskinesia due to levodopa therapy showed an ROC AUC of 0.67 indicating the moderate prediction of dyskinesia (p = 0.0021) with these COMT variants. In conclusion, PD subjects carrying the variant genotypes of COMT strongly influence high levodopa-induced dyskinesia. Hence the genotyping of COMT before the levodopa therapy will be useful to reduce the adverse events associated with the chronic levodopa treatment.

Development of pharmacogenomic algorithm to optimize nateglinide dose for the treatment of type 2 diabetes mellitus.

BACKGROUND: Nateglinide is a meglitinide used for the treatment of type 2 diabetes mellitus. Individual studies demonstrated the association of CYP2C9, SLCO1B1, and MTNR1B variants with the safety and efficacy of nateglinide. The current study aimed to develop a pharmacogenomic algorithm to optimize nateglinide therapy. METHODS: Multiple linear regression (MLR) and classification and regression tree (CART) were used to develop a pharmacogenomic algorithm for nateglinide dosing based on the published nateglinide pharmacokinetic data on the area under the curve data (AUC) and Cmax (n = 143). CYP2C9 metabolizer phenotype, SLCO1B1, MTNR1B genotypes, and CYP2C9 inhibitor usage were used as the input variables. The results and associations were further confirmed by meta-analysis and in silico studies. RESULTS: The MLR models of AUC and Cmax explain 87.4% and 59% variability in nateglinide pharmacokinetics. The Bland and Altman analysis of the nateglinide dose predicted by these two MLR models showed a bias of ± 26.28 mg/meal. The CART algorithm was proposed based on these findings. This model is further justified by the meta-analysis showing increased AUCs in CYP2C9 intermediate metabolizers and SLCOB1 TC and CC genotypes compared to the wild genotypes. The increased AUC in SLCO1B1 mutants is due to decreased binding affinity of nateglinide to the mutant affecting the influx of nateglinide into hepatocytes. MTNR1B rs10830963 G-allele-mediated poor response to nateglinide is attributed to increased transcriptional factor binding causing decreased insulin secretion. CONCLUSION: CYP2C9, SLCO1B1, and MTNR1B genotyping help in optimizing nateglinide therapy based on this algorithm and ensuring safety and efficacy.

Association of Promoter Methylation and Expression of Inflammatory Genes IL-6 and TNF-α with the Risk of Coronary Artery Disease in Diabetic and Obese Subjects among Asian Indians.

The inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α) are considered as the most important contributors to the endothelial dysfunction in subjects with type 2 diabetes mellitus (T2DM) and obesity. The hypomethylation of CpG sites in the promoter region of the IL-6 and TNF-α have shown to be associated with the increased expression of IL-6 and TNF-α. However, there are no studies on the methylation and expression of IL-6 and TNF-α with the risk of coronary artery disease (CAD) in subjects with T2DM and obesity in Asian Indians. Hence, the present study was aimed to investigate whether the IL-6, TNF-α promoter methylation and expression in blood leukocyte DNA is associated with the risk of CAD in diabetic and obese subjects in Asian Indians. For this study, we recruited 574 subjects which includes, 207 angiographically confirmed CAD patients, 100 T2DM patients, 82 obese subjects and 185 healthy controls. The methylation status of IL-6 and TNF-α gene loci was determined by methylation specific PCR (MPCR) and gene expression was determined by qPCR. We found significant hypomethylation of IL-6 in CAD and T2DM subjects (OR 1.98 95% CI: 1.32-2.97, p = 0.001, OR: 2.23 95% CI:1.34-3.76, p = 0.001, respectively). Further, a significant increase in the expression of IL-6 in CAD and T2DM subjects (fold change: 26.39 & 14.7, p = 0.0001) compared to the control subjects was observed. A significant increase in the hypomethylation of TNF-α in CAD, T2DM and obese subjects was observed as compared to the control (OR: 2.04 95% CI: 1.36-3.05, p = 0.0005, OR: 1.81 95% CI 1.10-2.96, p = 0.01, and OR: 2.1 95% CI 1.24-3.57, p = 0.007, respectively).We also found an increased expression of TNF-α in CAD, T2DM and obese subjects as compared to controls. In addition, presence of low folate, and hyperhomocysteinemia was observed in the present study, may be the contributing factors for the hypomethylation of IL-6 and TNF-α and oxidative stress. In conclusion, increased expression of IL-6 and TNF-α due to hypomethylation in T2DM and obese individuals may contribute to CAD risk in these subjects. The presence of hyperhomocysteinemia and increased oxidative risk may enhance the CAD risk further.

Pharmacogenetic determinants of warfarin in the Indian population.

BACKGROUND: Several studies optimized the warfarin dose based on CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, CYP4F2 V433M. But, the information on the rare variants is lacking. In this study, we have explored the prevalence of common and rare pharmacogenetic determinants of warfarin and determined their damaging nature. METHODS: We have analyzed 2000 healthy adults using the Infinium global screening array (GSA) for 15 pharmacogenetic determinants of warfarin. In addition, we have elucidated the impact of these variants on protein function, stability, dynamics, evolutionary preservation, and ligand binding propensity. RESULTS: The GSA Analysis has revealed that CYP4F2 V433M (MAF: 39.425%), VKORC1 -1639 G > A (MAF: 20.5%), CYP2C9*3 (MAF:9.925%), and CYP2C9*2 (MAF:4.575%) are common, while CYP2C9*14 (MAF: 1.475%), CYP2C9*4 (0.175%), CYP2C9*5 (0.125%), and CYP2C9*11 (0.125%) are rare. Position-specific evolutionary preservation (PSEP) analysis has revealed that CYP2C9*4 is possibly damaging, while CYP2C9*5, CYP2C9*11, and CYP2C9*14 are probably damaging. CYP2C9*4 has high thermolability (-10.14 kcal/mol). Among the rare CYP2C9 variants, CYP2C9*4 and CYP2C9*11 exert destabilizing effects and may have increased molecular flexibility, while CYP2C9*5 and CYP2C9*14 exert stabilizing effects and may have decreased molecular flexibility. DNase I footprint analysis has revealed the loss of the E-box consensus sequence due to VKORC1 -1639 G > A polymorphism. CONCLUSION: CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A and CYP4F2 V433M are common; CYP2C9*4, CYP2C9*5, CYP2C9*11, and CYP2C9*14 variants are rare in Indian subjects. All the CYP2C9 variants are found to be damaging. DNase I footprint analysis provided the mechanistic rationale for the association of VKORC1 -1639 G > A with warfarin sensitivity.

Association of DNA repair gene XPC Ala499Val (rs2228000 C>T) and Lys939Gln (rs2228001 A>C) polymorphisms with the risk of chronic myeloid leukemia: A case-control study in a South Indian population.

BACKGROUND: Xeroderma pigmentosum complementation group C (XPC), a DNA repair protein, plays an important role in the maintenance of genomic integrity and is essential for the nucleotide excision repair pathway. Polymorphisms in the XPC gene may alter DNA repair leading to genetic instability and oncogenesis. The present study aimed to assess the relationship between the XPC Ala499Val (rs2228000 C>T) and Lys939Gln (rs2228001 A>C) non-synonymous polymorphisms and susceptibility to chronic myeloid leukemia (CML) pathogenesis, disease progression and the response to targeted therapeutic regimen, imatinib mesylate. METHODS: This case-control study included 212 cases and 212 controls, and the genotypes were determined by polymerase chain reaction-restriction fragment length polymorphism assays. RESULTS: Our results showed significant association of variant CT (odds ratio = 1.92, 95% confidence interval = 1.21-3.06, p = 0.003) and TT (odds ratio = 2.84, 95% confidence interval = 1.22-6.71, p = 0.007) genotypes in patients with the XPC Ala499Val polymorphism and CML risk. In addition, these genotypes were associated with CML progression to advanced phases (p = 0.006), splenomegaly (p = 0.017) and abnormal lactate dehydrogenase levels (p = 0.03). XPC Lys939Gln was found to correlate with a poor response to therapy, showing borderline significant association with minor cytogenetic response (p = 0.08) and a poor molecular response (p = 0.06). Significant association of the Ala499Val and Lys939Gln polymorphisms with prognosis was observed (Hasford high risk, p = 0.031 and p = 0.019, respectively). Haplotype analysis showed a strong correlation of variant TC haplotype with poor therapy responses (minor cytogenetic response, p = 0.019; poor molecular response, p < 0.0001). CONCLUSIONS: In conclusion, our results suggest that XPC Ala499Val is a high-penetrance CML susceptibility polymorphism. Both polymorphisms studied are considered as genetic markers with respect to assessing disease progression, therapy response and prognosis in CML patients.

Alpha synuclein (SNCA) rs7684318 variant contributes to Parkinson's disease risk by altering transcription factor binding related with Notch and Wnt signaling.

In view of inconsistencies in the association studies of alpha synuclein (SNCA) rs7684318 (chr4: 90655003 T > C) with Parkinson's disease (PD), we conducted a meta-analysis to establish the association of this variant with PD and examined changes in transcription factor binding. SNCA rs7684318 C-allele was identified as genetic risk factor for PD in fixed (OR: 1.53, 95 % CI: 1.40-1.68, p < 0.0001) and random effect (OR: 1.65, 95 % CI: 1.30-2.09, p = 0.0003) models. Heterogeneity was observed in association (Tau2: 0.0576, H: 2.32, I2: 0.815, Q: 21.64, p = 0.0002). Egger's test showed no evidence of publication bias (p = 0.37). Subgroup analysis showed that rs7684318 is contributing to PD risk in Japanese (OR: 1.46, 95 % CI: 1.30-1.64) and Indian (OR: 2.63, 95 % CI: 1.79-3.86) populations while showing no significant association in Chinese population (OR: 1.68, 95 % CI: 0.93-3.02). Sensitivity analysis showed that exclusion of any one of the studies has no significant impact on the association, which justifies the robustness of the analysis. Tissue-specific DNase foot print analysis revealed that this variant contributes to increased transcription factor binding in midbrain, putamen and caudate nucleus. The substitution of T > C increased binding of RBPJ and GATA-family transcription factors; and decreased binding of NKX2 family, SNAI2, SNAI3, DMRT1, HOXA13, HOXB13, HOXC13, HOXD13, WT1, POU4F1, POU4F2, POU4F3 transcriptional factors. TRANSFAC and DNA curvature analyses substantiate the association of this variant with increased binding of GATA1 that contribute to intensity of DNA curvature peaks and splitting pattern. These studies along with the meta-analysis strongly suggest that the rs7684318 variant contributes to the pathophysiology of PD by modulating binding of transcription factors related to Notch and Wnt signalling pathways that are likely to impair dopmanergic transmission.

Mechanistic insights into the CYP2C19 genetic variants prevalent in the Indian population.

PURPOSE: CYP2C19 metabolizes the antiplatelet and antiepileptic drugs. Any alteration in CYP2C19 activity might influence the therapeutic efficacy. The objective of this study was to identify CYP2C19 variants prevalent in Indians and perform their in silico characterization. METHODS: Infinium global screening array (GSA) was used for CYP2C19 genotyping in 2000 healthy Indians. In addition, we performed in silico characterization of the identified variants. RESULTS: Out of the 11 variants covered (*2, *3, *4,*5,*6, *7,*8, *9,*10,*11, and *17), five were identified in Indians (*2, *3, *6,*8 and *17). The *2 and *17 were the most prevalent alleles (minor allele frequencies, MAF: 32.0% and 13.95%). The *3, *6 and *8 were rare (MAFs: 0.425%, 0.025% and 0.05%). The *2 variant is shown to affect the splicing at the fifth exon-intron boundary. The *3 variant is a non-sense variant that is predicted to be deleterious. On the otherhand, the *17 variant showed more binding affinity for GATA binding protein 1 (GATA1), myocyte enhancer factor 2 (MEF2) and ectotropic viral integration site 1 (EVI1). The *6 and *8 variants predicted to be deleterious. The *2, *3 and *7 variants showed lesser probability of exon skipping, while *17 showed more probability. The genotype distribution of Indian subjects is comparable with that of South Asians (SAS) (1000 genome project, phase 3). CONCLUSION: The *2, *3 and *17 variants are the key pharmacogenetic determinants in Indians. The *2 and *3 are loss-of-function variants. The *17 is a gain-of-function variant with increased binding of transcriptional factors.

Synergetic Interaction of HLA-DRB1*07 Allele and TNF-Alpha - 863 C/A Single Nucleotide Polymorphism in the Susceptibility to Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease which is characterized by dysregulation of various cytokines propagating the inflammatory processes that is responsible for tissue damage. Tumor necrosis factor alpha (TNF-α) is one of the most important immunoregulatory cytokines that has been implicated in the different autoimmune diseases including SLE. Two hundred and two patients with SLE and 318 controls were included in the study. The TNF-α gene promoter region (from - 250 to - 1000 base pairs) was analyzed by direct Sanger's DNA sequencing method to find promoter variants associated with South Indian SLE patients. We have analyzed six TNF-α genetic polymorphisms including, - 863C/A (rs1800630), - 857C/T (rs1799724), - 806C/T (rs4248158), - 646G/A (rs4248160), - 572A/C (rs4248161) and - 308G/A (rs1800629) in both SLE patients and controls. We did not find association of TNF-α gene promoter SNPs with SLE patients. However, the - 863A (rs1800630) allele showed association with lupus nephritis phenotype in patients with SLE (OR: 1.62, 95%CI 1.04-2.53, P = 0.034). We found serum TNF-α level was significantly elevated in SLE cases as compared to control and found no association with any of the polymorphisms. The haplotype analysis revealed a significant protective association between the wild TNF-α alleles at positions - 863C, - 857C, - 806C, - 646G, - 572A and - 308G (CCCGAG) haplotype with lupus nephritis phenotype (OR 0.53, 95% CI 0.35-0.82, P = 0.004). Additionally, the TNF-α - 863 C/A (rs1800630) polymorphism and HLA-DRB1*07 haplotype showed significant differences between SLE patients and controls (OR 4.79, 95% CI 1.73-13.29, P = 0.0009). In conclusion, TNF-α - 863A allele (rs1800630) polymorphism is associated with increased risk of nephritis in South Indian SLE patients. We also found an interaction between HLA-DRB1*07 allele with TNF-α - 863 C/A promoter polymorphism giving supportive evidence for the tight linkage disequilibrium between TNF-α promoter SNPs and MHC class II DRB1 alleles.

Impact of Pharmacogenetic Determinants of Tacrolimus and Mycophenolate on Adverse Events in Renal Transplant Patients.

BACKGROUND: Graft acceptance against immunity is one of the major challenges in solid organ transplant. Immunosuppressive medications have effectively improved the post-transplantation outcome however, it has its own limitations. Genetic polymorphisms in drug-metabolizing enzymes have been identified as the potential targets in developing a pharmacogenetic strategy, to individualize drug dose and also in preventing the adverse events. OBJECTIVE: The rationale of the study was to explore polymorphisms in tacrolimus and mycophenolate metabolic pathways that influence the adverse clinical outcomes in renal transplant recipients. METHODS: A total of 255 renal transplant recipients were analyzed for the pharmacogenetic determinants of tacrolimus (CYP3A5*3 ABCB1 1236 T>C ABCB1 2677 G>A/T ABCB1 3435 T>C) and mycophenolate (UGT1A8*3 UGT1A9 IMPDH I IMPDH II c.787C>T ABCC2 -24 C>T and c.3972C>T) using Sanger sequencing. RESULTS: Acute rejection (AR) was observed in 5.88% of the transplant recipients whereas acute tubular necrosis (ATNs) was observed in 7.45% of the patients within early stage of the maintenance phase. Infections such as urinary tract infection (UTI) and cytomegalovirus (CMV) infection were observed in 11.37% and 12.16% of the patients. The AUC of mycophenolate was significantly higher in patients with increased risk for infections. ABCC2 -24 C>T c.3972C>T polymorphisms and ABCB1 3435 C-allele were associated with reduced risk for infections. ABCC2 rs3740066 was associated with 2.06-fold all-cause mortality risk. CYP3A5 AG- and UGT1A9-440 CC-genotypes showed increased risk and ABCC 3972C>T CC-genotype showed protection against adverse events. CONCLUSION: Genetic variants in tacrolimus and mycophenolate metabolic pathways were found to influence the morbidity and mortality in renal transplant recipients.

Pharmacogenetic determinants of thiopurines in an Indian cohort.

BACKGROUND: Several genetic variants of thiopurine metabolic pathway are associated with 6-thiopurine-mediated leucopenia. A population-based evaluation of these variants lays the foundation for Pharmacogenetic-guided thiopurine therapy. METHODS: A total of 2000 subjects were screened for the pharmacogenetic determinants using the infinium global screening array (GSA). The functional relevance of these variants was deduced using SNAP2, SIFT, Provean, Mutalyzer, Mutation Taster, Phyre2, SwissDock, AGGRESCAN, and CUPSAT. RESULTS: The minor allele frequencies of NUDT15*3, NUDT15*5, TPMT*3C, TPMT*3B variant alleles were 6.78%, 0.11%, 1.98% and 0.69%, respectively. TPMT*3A genotype was observed in 0.35% subjects. No gender-based differences were observed in the incidence of these variants. Data from studies of the Indian population showed that 92.86% subjects heterozygous for NUDT15*3 and 60% subjects heterozygous for TPMT*3C exhibit thiopurine-mediated hematological toxicity. NUDT15 variants have no impact on the binding of 'dGTP' to the NUDT protein. NUDT15*3 variant increases aggregation 'hot spot' region and induces unfavourable torsion in the protein. NUDT15*5 destabilizes the protein and impairs Mg/Mn binding. TPMT*3A, TPMT*3B and TPMT*3C variants lower binding affinity to 6-mercaptopurine compared to the wild protein. TPMT*3C variant destabilizes the TPMT protein in the thermal experiment. Compared to the data of European and African/African American populations, NUDT15*3 frequency is higher and TPMT*3C frequency is lower in our population. CONCLUSIONS: TPMT variants were less frequent in Indian population, while NUDT15*3 is more frequent compared to European and African/African American populations. NUDT15*3 increases aggregation 'hot spot' and induces unfavourable torsion in the protein. NUDT15*5 and TPMT*3C destabilize the respective proteins. TPMT*3A, TPMT*3B and TPMT*3C are associated with a lower binding affinity towards 6-mercaptopurine.

Pharmacogenetic profiling of dihydropyrimidine dehydrogenase (DPYD) variants in the Indian population.

BACKGROUND: The present study aimed to delineate the pharmacologically relevant dihydropyrimidine dehydrogenase (DPYD) variants in the Indian population. METHODS: We screened 2000 Indian subjects for DPYD variants using the Infinium Global Screening Array (GSA) (Illumina Inc., San Diego, CA, USA). RESULTS: The GSA analysis identified seven coding, two intronic and three synonymous DPYD variants. Level 1A alleles (rs75017182, rs3918290, P633Qfs*5 and D949V) were found to be rare (minor allele frequency: 1.889%), whereas Level 3 alleles were observed to be predominant (C29R: 24.91%, I543V: 9.047%, M166V: 8.993% and V732I: 8.44%). In silico predictions revealed that all Level 1A alleles were deleterious, whereas three (M166V, S534N and V732I) of seven Level 3 alleles were damaging. CUPSAT analysis revealed that two Level 1A (P633Qfs*, D949V) and three Level 3 (I543V, V732I and S534N) variants were thermolabile. The pooled Indian data showed that V732I, S534N and rs3918290 variants were associated with 5-FU/capecitabine toxicity, whereas C29R, I543V and M166V variants exhibited the null association. A comparison of our data with other population data from the 'Allele Frequency Aggregator' (https://www.ncbi.nlm.nih.gov/snp/docs/gsr/alfa/) database showed similarities with the South Asian data. CONCLUSIONS: We have identified four Level 1A (non-functional/dysfunctional) and seven Level 3 variants in the DPYD gene. The pooled Indian data revealed the association of V732I, S534N and rs3918290 variants with 5-FU/capecitabine toxicity. Clustering analysis revealed the similarities in the DPYD profiles of the Indian and South Asian populations.

Probing the epigenetic signatures in subjects with coronary artery disease.

Depletion of S-adenosyl methionine and 5-methyltetrahydrofolate; and elevation of total plasma homocysteine were documented in CAD patients, which might modulate the gene-specific methylation status and alter their expression. In this study, we have aimed to delineate CAD-specific epigenetic signatures by investigating the methylation and expression of 11 candidate genes i.e. ABCG1, LIPC, PLTP, IL-6, TNF-α, CDKN2A, CDKN2B, F2RL3, FGF2, P66 and TGFBR3. The methylation-specific PCR and qRT-PCR were used to assess the methylation status and the expression of candidate genes, respectively. CAD patients showed the upregulation of IL-6, TNF-α, CDKN2A, CDKN2B, F2RL3, FGF2, P66, and TGFBR3. Hypomethylation of CDKN2A loci was shown to increase risk for CAD by 1.79-folds (95% CI 1.22-2.63). Classification and regression tree (CART) model of gene expression showed increased risk for CAD with F2RL3 > 3.4-fold, while demonstrating risk reduction with F2RL3 < 3.4-fold and IL-6 < 7.7-folds. This CAD prediction model showed the excellent sensitivity (0.98, 95% CI 0.88-1.00), specificity (0.91, 95% CI 0.86-0.92), positive predictive value (0.82, 95% CI 0.75-0.84), and negative predictive value (0.99, 95% CI 0.94-1.00) with an overall accuracy of 92.8% (95% CI 87.0-94.1%). Folate and B12 deficiencies were observed in CAD cases, which were shown to contribute to hypomethylation and upregulation of the prime candidate genes i.e. CDKN2A and F2RL3. Early onset diabetes was associated with IL-6 and TNF-α hypomethylation and upregulation of CDKN2A. The expression of F2RL3 and IL-6 (or) hypomethylation status at CDKN2A locus are potential biomarkers in CAD risk prediction. Early epigenetic imprints of CAD were observed in early onset diabetes. Folate and B12 deficiencies are the contributing factors to these changes in CAD-specific epigenetic signatures.

Artificial neural network and bioavailability of the immunosuppression drug.

PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial intelligence tools, such as artificial neural networks (ANNs) or classification and regression trees (CART) can handle multiple independent variables and predict the dependent variables by deducing the complex nonlinear relationships between variables. RECENT FINDINGS: In the last two decades, several researchers employed these tools to identify donor-recipient matching pairs, to optimize immunosuppressant doses, to predict allograft survival and to minimize adverse drug reactions. These models showed better performance characteristics than the empirical dosing strategies in terms of sensitivity, specificity, overall accuracy, or area under the curve of receiver-operating characteristic curves. The performance of the models was dependent directly on the input variables. Recent studies identified protein biomarkers and pharmacogenetic determinants of immunosuppressants as additional variables that increase the precision in prediction. Accessibility of medical records, proper follow-up of transplant cases, deep understanding of pharmacokinetic and pharmacodynamic pathways of immunosuppressant drugs coupled with genomic and proteomic markers are essential in developing an effective artificial intelligence platform for transplantation. SUMMARY: Artificial intelligence has a greater clinical utility both in pretransplantation and posttransplantation periods to get favourable clinical outcomes, thus ensuring successful graft survival.

In silico analysis of the structural and functional implications of SLC19A1 R27H polymorphism.

In view of the documented association of solute carrier family 19 member 1 (SLC19A1) G80A (R27H) polymorphism with the risk for different types of cancers and systemic lupus erythematosus (SLE), we have reanalysed the case-control study on breast cancer to ascertain the conditions in which this polymorphic variant exerts the risk of breast cancer. Association statistics have revealed that this polymorphism exerts the risk for breast cancer under the conditions of low folate intake, and in the absence of well-documented protective polymorphism in cytosolic serine hydroxymethyltransferase. To substantiate this observation, we have developed a homology model of SLC19A1 using glycerol-3-phosphate transporter (d1pw4a) as a template where 73% of the residues were modelled at 90% confidence while 162 residues were modelled ab initio. The wild and mutant proteins shared same topology in S3, S5, S6, S7, S11 and S12 transmembrane domains. The topology varied at S1 (28-43 residue vs 28-44 residue), S2 (66-87 residue vs 69-87 residue), S4 (117-140 residue vs 117-139 residue), S8 (305-325 residue vs 305-324 residue), S9 (336-356 residue vs 336-355residue), and S10 (361-386 residue vs 361-385 residue) transmembrane domains between wild versus mutant proteins. S2 domain is shortened by three amino acid residues in the mutant while in other domains the difference corresponds to one amino acid residue. The 3DLigandSite analysis revealed that the metallic-ligand-binding sites at 273Trp, 277Asn, 379Leu, 439Phe and 442Leu are although unaffected, there is a loss of active sites corresponding to nonmetallic ligand binding. Tetrahydrofolate and methotrexate have lesser affinity towards the mutant protein than the wild protein. To conclude, the R27H polymorphism affects the secondary and tertiary structures of SLC19A1 with the significant loss in ligand-binding sites.

Dual Effect of IL-6 -174 G/C Polymorphism and Promoter Methylation in the Risk of Coronary Artery Disease Among South Indians.

Inflammation plays an important role in the pathogenesis of atherosclerosis and coronary syndromes; moreover, various lines of evidence suggest that genetic factors do contribute to the risk of coronary artery disease (CAD). The proinflammatory cytokine IL-6 is a central mediator of inflammation associated with CAD. The present study is aimed to investigate the association of single nucleotide polymorphism in the promoter region of the IL-6 gene (-174 G > C) and methylation with the susceptibility of CAD. Genotyping of IL-6 -174 G/C polymorphism was performed by PCR-RFLP. Methylation-specific PCR method was used to study the IL-6 gene promoter methylation. Analysis of 470 subjects (265 CAD patients and 205 controls) showed association of the -174 G/C variant with the CAD risk in dominant model (OR 1.58, 95% CI, 1.024-2.23, P = 0.04). Further, the analysis of the distribution of genotypes and alleles of -174 G > C polymorphism according to clinical features of CAD, revealed significant association of genotype and allele (OR 1.86, 95% CI 1.18-2.84 P = 0.01, and OR 1.71, 95% CI 1.09-2.23 P = 0.02 respectively) with diabetes, and we found no association with hypertension (OR 0.95, 95% CI 0.57-1.59, P = 0.8). We also analyzed the methylation status of IL-6 promoter region between cases and controls showed significant hypo methylation in CAD subjects (OR 2.36, 95% CI 1.51-4.259, P = 0.006). Additionally, GC, CC genotypes and C allele carriers show hypomethylation in CAD cases compared to controls (54.58 vs. 76.85%, 29.83 vs. 40% respectively). In conclusion, the promoter polymorphism -174 G/C is associated with CAD risk and further carriers of 'C' allele at -174 locus showed significant hypo methylation which could contribute to increased risk of CAD. The present study highlights the association of allele and genotypes with differential DNA methylation of CpG islands in the IL-6 promoter region which may affect IL-6 gene regulation.

Recipient ABCB1, donor and recipient CYP3A5 genotypes influence tacrolimus pharmacokinetics in liver transplant cases.

BACKGROUND: Effective immunosuppression through optimization of trough levels tacrolimus reduces post-transplant mortality rate in liver transplant cases. METHODS: Meta-analysis was carried out to evaluate how donor/recipient CYP3A5 (n = 678) and recipient ABCB1 (n = 318) genotypes influence tacrolimus pharmacokinetics till one-month of transplantation. RESULTS: The donor CYP3A5*3/*3 genotype exhibited higher concentration/dose (C/D) ratio of tacrolimus in week 1 (mean difference: 65.04, 95% CI: 15.30-114.79 ng/ml/mg/kg), week 2 (mean difference: 21.7, 95% CI: 12.6-30.9 ng/ml/mg/kg) and week 4 (mean difference: 43.28, 95% CI: 17.09 - 69.49 ng/ml/mg/kg) compared to *1/*1 and *1/*3 genotypes. The recipient CYP3A5 *3/*3 genotype did not showed significant difference in tacrolimus C/D ratio in week 1 compared to other two genotypes. However, week 2 (mean difference: 44.16, 95% CI: 3.68-84.65 ng/ml/mg/kg) and week 4 (mean difference: 43.74, 95% CI: 12.50-75.00 ng/ml/mg/kg) availability was higher in *3/*3 mutant recipients. However, the recipient ABCB1 3435 C > T polymorphism has no significant influence on tacrolimus pharmacokinetics till one month of transplant. CONCLUSIONS: The donor and recipient CYP3A5*3 polymorphism influences tacrolimus pharmacokinetics in the first month post-transplantation, whereas the association with recipient ABCB1 3435 C > T is inconclusive.

Classification and regression tree-based prediction of 6-mercaptopurine-induced leucopenia grades in children with acute lymphoblastic leukemia.

PURPOSE: The rationale of the current study was to develop 6-mercaptopurine (6-MP)-mediated hematological toxicity prediction model for acute lymphoblastic leukemia (ALL) therapeutic management. METHODS: A total of 96 children with ALL undergoing therapy with MCP-841 protocol were screened for all the ten exons of TPMT, exon 2, exon 3 and intron 2 of ITPA using bidirectional sequencing. This dataset was used to construct prediction models of leucopenia grade by constructing classification and regression trees (CART) followed by smart pruning. RESULTS: The developed CART model indicated TPMT*12 and TPMT*3C as the key determinants of toxicity. TPMT int3, int4 and int7 polymorphisms exert toxicity when co-segregated with one mutated allele of TPMT*12 or TPMT*3C or ITPA exon 3. The developed CART model exhibited 93.6% accuracy in predicting the toxicity. The area under the receiver operating characteristic curve was 0.9649. CONCLUSIONS: TPMT *3C and TPMT*12 are the key determinants of 6-MP-mediated hematological toxicity while other variants of TPMT (int3, int4 and int7) and ITPA ex2 interact synergistically with TPMT*3C or TPMT*12 variant alleles to enhance the toxicity. TPMT and ITPA variants cumulatively are excellent predictors of 6-MP-mediated toxicity.

Machine learning algorithm-based risk prediction model of coronary artery disease.

In view of high mortality associated with coronary artery disease (CAD), development of an early predicting tool will be beneficial in reducing the burden of the disease. The database comprising demographic, conventional, folate/xenobiotic genetic risk factors of 648 subjects (364 cases of CAD and 284 healthy controls) was used as the basis to develop CAD risk and percentage stenosis prediction models using ensemble machine learning algorithms (EMLA), multifactor dimensionality reduction (MDR) and recursive partitioning (RP). The EMLA model showed better performance than other models in disease (89.3%) and stenosis prediction (82.5%). This model depicted hypertension and alcohol intake as the key predictors of CAD risk followed by cSHMT C1420T, GCPII C1561T, diabetes, GSTT1, CYP1A1 m2, TYMs 5'-UTR 28 bp tandem repeat and MTRR A66G. MDR and RP models are in agreement in projecting increasing age, hypertension and cSHMTC1420T as the key determinants interacting in modulating CAD risk. Receiver operating characteristic curves exhibited clinical utility of the developed models in the following order: EMLA (C = 0.96) > RP (C = 0.83) > MDR (C = 0.80). The stenosis prediction model showed that xenobiotic pathway genetic variants i.e. CYP1A1 m2 and GSTT1 are the key determinants of percentage of stenosis. Diabetes, diet, alcohol intake, hypertension and MTRR A66G are the other determinants of stenosis. These eleven variables contribute towards 82.5% stenosis. To conclude, the EMLA model exhibited higher predictability both in terms of disease prediction and stenosis prediction. This can be attributed to higher number of iterations in EMLA model that can increase the prediction accuracy.