Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

BACKGROUND: The hepatitis C virus (HCV) infects nearly 3% of the World's population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B single nucleotide polymorphisms (SNPs), rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of HCV infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (more than 1%) haplotypes for IL28B, one tagged by the rs8099917 minor allele, four tagged by rs12979860. METHODS: We used massively parallel sequencing of the IL28B and IL28A gene regions generated by polymerase chain reaction (PCR) from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. RESULTS: Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previously been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. CONCLUSIONS: Massively parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV. SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs

IL28B, HLA-C, and KIR Variants Additively Predict Response to Therapy in Chronic Hepatitis C Virus Infection in a European Cohort: A Cross-Sectional Study

Vijayaprakash Suppiah and colleagues show that genotyping hepatitis C patients for the IL28B, HLA-C, and KIR genes improves the ability to predict whether or not patients will respond to antiviral treatment

High Rates of Hepatitis C Virus Reinfection and Spontaneous Clearance of Reinfection in People Who Inject Drugs: A Prospective Cohort Study

Hepatitis C virus reinfection and spontaneous clearance of reinfection were examined in a highly characterisedcohort of 188 people who inject drugs over a five-year period. Nine confirmed reinfections and 17 possiblereinfections were identified (confirmed reinfections were those genetically distinct from the previous infection andpossible reinfections were used to define instances where genetic differences between infections could not beassessed due to lack of availability of hepatitis C virus sequence data). The incidence of confirmed reinfection was28.8 per 100 person-years (PY), 95%CI: 15.0-55.4; the combined incidence of confirmed and possible reinfectionwas 24.6 per 100 PY (95%CI: 16.8-36.1). The hazard of hepatitis C reinfection was approximately double that ofprimary hepatitis C infection; it did not reach statistical significance in confirmed reinfections alone (hazard ratio [HR]:2.45, 95%CI: 0.87-6.86, p=0.089), but did in confirmed and possible hepatitis C reinfections combined (HR: 1.93,95%CI: 1.01-3.69, p=0.047) and after adjustment for the number of recent injecting partners and duration of injecting.In multivariable analysis, shorter duration of injection (HR: 0.91; 95%CI: 0.83-0.98; p=0.019) and multiple recentinjecting partners (HR: 3.12; 95%CI: 1.08-9.00, p=0.035) were independent predictors of possible and confirmedreinfection. Time to spontaneous clearance was shorter in confirmed reinfection (HR: 5.34, 95%CI: 1.67-17.03,p=0.005) and confirmed and possible reinfection (HR: 3.10, 95%CI: 1.10-8.76, p-value=0.033) than primary infection.Nonetheless, 50% of confirmed reinfections and 41% of confirmed or possible reinfections did not spontaneouslyclear.Conclusions: Hepatitis C reinfection and spontaneous clearance of hepatitis C reinfection were observed at highrates, suggesting partial acquired natural immunity to hepatitis C virus. Public health campaigns about the risks ofhepatitis C reinfection are required

Genetics of autoimmune diseases : a study of immuno-regulatory genes : CTLA4, IL-4, IL-4RA, SOCS3, IFNG and IL-26 in multiple sclerosis, rheumatoid arthritis and juvenile idiopathic arthritis

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Pharmacogenomics of interferon beta and glatiramer acetate response : a review of the literature

Multiple sclerosis (MS) is one of the most common inflammatory and degenerative autoimmune diseases of the central nervous system with considerable heterogeneity in all aspects, including response to therapy. A number of disease modifying drugs, including traditional first line agents such as, interferon-beta (IFN-β) and glatiramer acetate (GA) are available for disease management. However, a considerable number of patients fail to achieve adequate response at therapeutic doses of IFN-β or GA. This variability in response to treatment has prompted the search for prognostic markers in order to personalize and optimize therapy so as to treat MS more efficiently. This review will summarize the existing literature examining the pharmacogenomics of IFN-β and GA response in MS patients.

Pharmacogenomics of Cancer Pain Treatment Outcomes in Asian Populations: A Review

In advanced cancer, pain is a poor prognostic factor, significantly impacting patients’ quality of life. It has been shown that up to 30% of cancer patients in Southeast Asian countries may receive inadequate analgesia from opioid therapy. This significant under-management of cancer pain is largely due to the inter-individual variability in opioid dosage and relative efficacy of available opioids, leading to unpredictable clinical responses to opioid treatment. Single nucleotide polymorphisms (SNPs) cause the variability in opioid treatment outcomes, yet their association in Asian populations remains unclear. Therefore, this review aimed to evaluate the association of SNPs with variability in opioid treatment responses in Asian populations. A literature search was conducted in Medline and Embase databases and included primary studies investigating the association of SNPs in opioid treatment outcomes, namely pharmacokinetics, opioid dose requirements, and pain control among Asian cancer patients. The results show that CYP2D6*10 has the most clinical relevance in tramadol treatment. Other SNPs such as rs7439366 (UGT2B7), rs1641025 (ABAT) and rs1718125 (P2RX7) though significant have limited pharmacogenetic implications due to insufficient evidence. OPRM1 rs1799971, COMT rs4680 and ABCB1 (rs1045642, rs1128503, and rs2032582) need to be further explored in future for relevance in Asian populations

Overview of GWA studies investigated in this analysis.

<p>Overview of GWA studies investigated in this analysis.</p

Identification of Shared Genes and Pathways: A Comparative Study of Multiple Sclerosis Susceptibility, Severity and Response to Interferon Beta Treatment

<div><p>Recent genome-wide association studies (GWAS) have successfully identified several gene loci associated with multiple sclerosis (MS) susceptibility, severity or interferon-beta (IFN-ß) response. However, due to the nature of these studies, the functional relevance of these loci is not yet fully understood. We have utilized a systems biology based approach to explore the genetic interactomes of these MS related traits. We hypothesised that genes and pathways associated with the 3 MS related phenotypes might interact collectively to influence the heterogeneity and unpredictable clinical outcomes observed. Individual genetic interactomes for each trait were constructed and compared, followed by prioritization of common interactors based on their frequencies. Pathway enrichment analyses were performed to highlight shared functional pathways. Biologically relevant genes <i>ABL1, GRB2, INPP5D, KIF1B, PIK3R1, PLCG1, PRKCD, SRC, TUBA1A</i> and <i>TUBA4A</i> were identified as common to all 3 MS phenotypes. We observed that the highest number of first degree interactors were shared between MS susceptibility and MS severity (p = 1.34×10⁻⁷⁹) with <i>UBC</i> as the most prominent first degree interactor for this phenotype pair from the prioritisation analysis. As expected, pairwise comparisons showed that MS susceptibility and severity interactomes shared the highest number of pathways. Pathways from <i>signalling molecules and interaction</i>, and <i>signal transduction</i> categories were found to be highest shared pathways between 3 phenotypes. Finally, <i>FYN</i> was the most common first degree interactor in the MS drugs-gene network. By applying the systems biology based approach, additional significant information can be extracted from GWAS. Results of our interactome analyses are complementary to what is already known in the literature and also highlight some novel interactions which await further experimental validation. Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.</p> </div