HCV research: Recent findings and future challenges

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Information about HCV research: Recent findings and future challenges
Health & Medicine

Published on December 10, 2013

Author: MaxMoldovan

Source: slideshare.net

HCV research: Recent findings and future challenges Max Moldovan Bioinformatics Division, WEHI moldovan@wehi.edu.au Bioinformatics Seminar September 28, 2009

Presentation plan  Introduce Hepatitis C Virus and give information about treatment and related problems  Summarize the recent findings reported in the literature  Indicate the remaining questions to answer

Hepatitis C Virus (HCV)  Known from 1970s, but officially discovered in 1989  Around 200mln people affected worldwide  Affects liver  Often asymptomatic or with mild symptoms e.g. fatigue, poor appetite, joint pains etc.  Chronic infection can lead to fibrosis, cirrhosis and liver cancer  The standard, only approved and currently most effective treatment is pegylated interferon-α plus ribavirin

HCV infection transmission by source (USA) Source: Center for Disease Control and Prevention

Source: www.hepatitisctreatmentcenter.com

HCV infection by genotype

HCV infection by genotype Genotype 1: 77%

HCV genotype 1 progression HCV infection Clearance (~20%) Source: Based on NIH information Chronic HCV (~80%) No treatment response (~50%) Treatment response (~50%)

Approved treatment  Pegylated interferon-α plus ribavirin (PEGIFN-α/RBV) for 24 to 48 weeks  It is assumed that interferon mobilizes body’s natural defense against viral infection  The mechanism of action of ribavirin is not completely understood  Treatment leads to a number of side effects

Common side effects of PEGIFN-α/RBV treatment  fatigue  muscle aches  headaches  nausea and vomiting  skin irritation at the injection site  low-grade fever  weight loss  irritability  depression  mild bone marrow suppression  hair loss (reversible)

Uncommon side effects of PEGIFN-α/RBV treatment (~2%)  autoimmune disease (especially thyroid disease)  severe bacterial infections  marked thrombocytopenia  marked neutropenia  seizures  depression and suicidal ideation or attempts  retinopathy (microhemorrhages)  hearing loss and tinnitus

The problem summary  The viral infection (HCV) potentially leading to life-threatening liver damage  There is only one approved treatment (PEGIFN-α/RBV) with a number of side effects  Only about 50% of infected people respond to treatment  It is not known who is gong to respond

Genome-wide association study (GWAS)  Among chronic HCV genotype 1 affected individuals, treatment non-responders are taken as cases and responders as controls  Individuals are genotyped using a high throughput technology i.e. SNP Chips  Genotypes are assessed with respect to association with the case-control status

Expected GWAS outcomes  Identification of a genetic marker or a set of genetic markers truly associated with the phenotype  This can point to markers specific to cases (controls) and further assist with the casecontrol status prediction  The location of detected markers can point to specific genes and potentially reveal underlying biological mechanisms

Recent findings reported in the literature within a single month Nature: online 16th of August, 2009

Nature Genetics online 13th of September, 2009

Comparison of the three GWA studies Study Ancestry (sample size) Ge et al. Genotyping platform Case/Control Associated SNPs Cauc/Afric/Hisp Illumina 610(N=1615) Quad R/NR rs12979860 (OR=3.10) Suppiah et al. Cauc (N=293) Illumina CNV370Quad R/NR rs8099917 (OR=1.98) Tanaka et al. Jap (N=154) Affymetrix 6.0 NVR/VR rs8099917 (OR=12.10) R/NR – sustained virological response/no sustained virological response NVR – null virological responders VR – viralogical responders: subject who respond to treatment, but do not necessary clear the virus)

Ge et al. and Suppiah et al. case-control split Case Control NO-SVR SVR SVR – Sustained Virological Response: Absence of HCV RNA in blood 6 months after treatment

Tanaka et al. case-control split Case Control NO-SVR SVR TVR – Transient Virological Response: Substantial reduction but not absence of HCV RNA in blood

Tanaka et al. case-control split Case NVR Control TVR+SVR NVR – Null Virological Response: No reduction of HCV RNA in blood

The main common finding: rs8099917 rs12980275 Source: Tanaka et al. Nature Genet

LD structure of IL28B genomic region Source: Suppiah et al. Nature Genet

LD structure of IL28B genomic region rs12979860 Source: Suppiah et al. Nature Genet

Ge et al. specific findings  Rates of treatment response vary across populations together with frequency of specific genotypes

Suppiah et al. specific findings  Expression levels of IL28A and IL28B in healthy individuals vary with genotype frequencies at rs8099917

Tanaka et al. specific findings  Alternative study design: NULL virological responders (cases) vs. virological responders (controls)  This more distinct phenotypical discordance leads to much higher odds ratios

IL28B  Location: Chromosome 19, q13.13 (44426112 to 44427451: 1339 bp)  Protein: interferon-λ3 (interleukin 28B)  One of three genes (the other two are IL28A and IL29) known as type III of λ interferons  Type III interferons are shown to be unregulated by viral infection and other interferons  IFN-λ has effects similar to IFN-α, but more selective (i.e. it can produce less side effects)

The gap between genetic information and medical innovation Size of GenBank database The number of new SNPs The number of new drug applications submitted to FDA The number of new drugs approved by FDA Source: Nature

Remaining challenges  Precise identification of antiviral mechanism (mostly biological challenge)  Accurate prediction of PEG-IFN-α/RBV treatment response

Pharmacogenomics  Composite discipline covering the range of applied biomedical research areas, from bioinformatics to molecular chemistry  Opens entirely new opportunities such as treatment personalisation and genomic information assisted clinical trials  Attractive from the clinical research point of view, as well as from the financial viability point of view (e.g. given $10bln size of HCV treatment market)

Identification of antiviral mechanism  This is achieved mainly through a series of biological experiments  Likely to lead to new treatments  Even if the discovery process is successful, the way to clinical practice acceptance can take years

Prediction of PEG-IFN-α/RBV treatment response Types of relevant predictors:  Genomic information (SNPs, CNVs etc.)  Clinical baseline factors (age, BMI, viral load etc.)  Unknown/unmeasurable environmental factors e.g. stress-level

Approaches to building a clinically functional prediction model  More sensitive statistical significance testing procedures, e.g. efficiency robust tests (to identify additional association signals missed otherwise)  Identification of non-genetic predictive variables e.g. age, BMI etc. (account for confounding!)  Finite sample model selection procedure e.g. penalised regressions and cross-validation  Biologically motivated variable selection  Out-of-sample validation

Work in progress

Acknowledgments Bioinformatics, WEHI Melanie Bahlo Millenium Institute & Westmead Children’s Hospital, Sydney AGRF Vijay Suppiah Rust Turakulov David Booth Jacob George Math and Stats, UniMelb Hugh Miller Funding MBS, UniMelb Chris Lloyd ARC Linkage Grant

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