Determining and utilizing the quasispecies of the hepatitis B virus in clinical applications

Chronic hepatitis B caused by infection with the hepatitis B virus (HBV) affects about 240 million people worldwide and is one of the major causes of severe liver cirrhosis and liver cancer. Hepatitis B treatment options have improved dramatically in the last decade. Effective direct-acting antiviral drugs, so-called nucleos(t)ide analogs, and one effective immunomodulatory drug (pegylated interferon alpha-2a) are available presently. Current challenges for treating HBV involve the careful selection of patients who require therapy and the thoughtful choice of the treatment option tailored to each patient individually. Personalized medicine aims to optimize treatment decisions based on the analysis of host factors and virus characteristics. The population of viruses within a host is called the viral quasispecies. This thesis provides statistical methods to infer relevant information about the viral quasispecies of HBV to support treatment decisions. We introduce a new genotyping methodology to identify dual infections, which can help to quantify the risk of interferon therapy failure. We present a method to infer short-range linkage information from Sanger sequencing chromatograms, a method to support treatment adjustment after the development of resistance to nucleos(t)ide analogs. Additionally, we provide the first full-genome analysis of the G-to-A hypermutation patterns of the HBV genome. Hypermutated viral genomes form a subpopulation of the quasispecies caused by proteins of the human innate immune system editing the genome of exogenous viral agents. We show that hypermutation is associated with the natural progression of hepatitis B, but does not correlate with treatment response to interferon.Die Hepatitis-B-Erkrankung wird durch eine Infektion mit dem Hepatitis-B-Virus (HBV) verursacht. Weltweit sind schätzungsweise 240 Millionen Menschen chronisch infiziert. Dabei stellt Hepatitis-B eine der häufigsten Ursachen für die Entwicklung von Leberzirrhose und Leberkrebs dar. Die Behandlungsmöglichkeiten wurden in den letzten zehn Jahren signifikant verbessert. Mittlerweile stehen effektive direkt antivirale Medikamente – sogenannte Nukleos(t)id-Analoga – und ein effektives immunmodulierendes Medikament (pegyliertes Interferon alpha-2a) für die Behandlung zur Verfügung. Zentrale Fragen bei der Behandlung von Hepatitis-B beinhalten die zielgerichtete Auswahl der Patienten, welche therapiert werden müssen, sowie die passgenaue Auswahl der Behandlungsoption. Die personalisierte Medizin verfolgt das Ziel, die Behandlung basierend auf der Analyse von Patientencharakteristika und Eigenschaften des Virus zu optimieren. Die Gesamtheit der Viren innerhalb eines Wirtes wird als virale Quasispezies bezeichnet. Diese Arbeit stellt statistische Methoden zur Verfügung, um relevante Informationen über die Quasispezies von HBV zur Unterstützung von Therapieentscheidungen zu ermitteln. Wir entwickeln eine neue Methode zur Genotypisierung, welche Zweifachinfektionen mit HBV identifiziert und somit hilfreich sein kann, das Risiko eines Therapieversagens einer Interferonbehandlung korrekt einzuschätzen. Des Weiteren stellen wir eine Methode vor, welche Linkage-Informationen der viralen Quasispezies, basierend auf den Chromatogrammen der DNA-Sequenzierung nach Sanger, extrahieren kann. Diese Methode kann bei der Umstellung einer Therapie mit Nukleos(t)id-Analoga nach Resistenzentwicklung verwendet werden. Schließlich präsentieren wir die erste Vollgenomanalyse der G-zu-A Hypermutationsmuster von HBV. Hypermutierte virale Genome stellen eine Teilmenge der Quasispezies dar, welche durch von Proteinen der angeborenen Immunabwehr bewirkte Mutationen im viralen Genom entsteht. Wir zeigen, dass diese Subpopulation mit dem natürlichen Verlauf einer Hepatitis-B-Erkrankung, jedoch nicht mit dem Therapieansprechen auf Interferon, statistisch signifikant assoziiert werden kann

Bestimmung und Verwendung der Quasispecies des Hepatitis-B-Virus in klinischen Anwendungen

Chronic hepatitis B caused by infection with the hepatitis B virus (HBV) affects about 240 million people worldwide and is one of the major causes of severe liver cirrhosis and liver cancer. Hepatitis B treatment options have improved dramatically in the last decade. Effective direct-acting antiviral drugs, so-called nucleos(t)ide analogs, and one effective immunomodulatory drug (pegylated interferon alpha-2a) are available presently. Current challenges for treating HBV involve the careful selection of patients who require therapy and the thoughtful choice of the treatment option tailored to each patient individually. Personalized medicine aims to optimize treatment decisions based on the analysis of host factors and virus characteristics. The population of viruses within a host is called the viral quasispecies. This thesis provides statistical methods to infer relevant information about the viral quasispecies of HBV to support treatment decisions. We introduce a new genotyping methodology to identify dual infections, which can help to quantify the risk of interferon therapy failure. We present a method to infer short-range linkage information from Sanger sequencing chromatograms, a method to support treatment adjustment after the development of resistance to nucleos(t)ide analogs. Additionally, we provide the first full-genome analysis of the G-to-A hypermutation patterns of the HBV genome. Hypermutated viral genomes form a subpopulation of the quasispecies caused by proteins of the human innate immune system editing the genome of exogenous viral agents. We show that hypermutation is associated with the natural progression of hepatitis B, but does not correlate with treatment response to interferon.Die Hepatitis-B-Erkrankung wird durch eine Infektion mit dem Hepatitis-B-Virus (HBV) verursacht. Weltweit sind schätzungsweise 240 Millionen Menschen chronisch infiziert. Dabei stellt Hepatitis-B eine der häufigsten Ursachen für die Entwicklung von Leberzirrhose und Leberkrebs dar. Die Behandlungsmöglichkeiten wurden in den letzten zehn Jahren signifikant verbessert. Mittlerweile stehen effektive direkt antivirale Medikamente – sogenannte Nukleos(t)id-Analoga – und ein effektives immunmodulierendes Medikament (pegyliertes Interferon alpha-2a) für die Behandlung zur Verfügung. Zentrale Fragen bei der Behandlung von Hepatitis-B beinhalten die zielgerichtete Auswahl der Patienten, welche therapiert werden müssen, sowie die passgenaue Auswahl der Behandlungsoption. Die personalisierte Medizin verfolgt das Ziel, die Behandlung basierend auf der Analyse von Patientencharakteristika und Eigenschaften des Virus zu optimieren. Die Gesamtheit der Viren innerhalb eines Wirtes wird als virale Quasispezies bezeichnet. Diese Arbeit stellt statistische Methoden zur Verfügung, um relevante Informationen über die Quasispezies von HBV zur Unterstützung von Therapieentscheidungen zu ermitteln. Wir entwickeln eine neue Methode zur Genotypisierung, welche Zweifachinfektionen mit HBV identifiziert und somit hilfreich sein kann, das Risiko eines Therapieversagens einer Interferonbehandlung korrekt einzuschätzen. Des Weiteren stellen wir eine Methode vor, welche Linkage-Informationen der viralen Quasispezies, basierend auf den Chromatogrammen der DNA-Sequenzierung nach Sanger, extrahieren kann. Diese Methode kann bei der Umstellung einer Therapie mit Nukleos(t)id-Analoga nach Resistenzentwicklung verwendet werden. Schließlich präsentieren wir die erste Vollgenomanalyse der G-zu-A Hypermutationsmuster von HBV. Hypermutierte virale Genome stellen eine Teilmenge der Quasispezies dar, welche durch von Proteinen der angeborenen Immunabwehr bewirkte Mutationen im viralen Genom entsteht. Wir zeigen, dass diese Subpopulation mit dem natürlichen Verlauf einer Hepatitis-B-Erkrankung, jedoch nicht mit dem Therapieansprechen auf Interferon, statistisch signifikant assoziiert werden kann

Inferring Short-Range Linkage Information from Sequencing Chromatograms

Direct Sanger sequencing of viral genome populations yields multiple ambiguous sequence positions. It is not straightforward to derive linkage information from sequencing chromatograms, which in turn hampers the correct interpretation of the sequence data. We present a method for determining the variants existing in a viral quasispecies in the case of two nearby ambiguous sequence positions by exploiting the effect of sequence context-dependent incorporation of dideoxynucleotides. The computational model was trained on data from sequencing chromatograms of clonal variants and was evaluated on two test sets of in vitro mixtures. The approach achieved high accuracies in identifying the mixture components of 97.4% on a test set in which the positions to be analyzed are only one base apart from each other, and of 84.5% on a test set in which the ambiguous positions are separated by three bases. In silk experiments suggest two major limitations of our approach in terms of accuracy. First, due to a basic limitation of Sanger sequencing, it is not possible to reliably detect minor variants with a relative frequency of no more than 10%. Second, the model cannot distinguish between mixtures of two or four clonal variants, if one of two sets of linear constraints is fulfilled. Furthermore, the approach requires repetitive sequencing of all variants that might be present in the mixture to be analyzed. Nevertheless, the effectiveness of our method on the two in vitro test sets shows that short-range linkage information of two ambiguous sequence positions can be inferred from Sanger sequencing chromatograms without any further assumptions on the mixture composition. Additionally, our model provides new insights into the established and widely used Sanger sequencing technology. The source code of our method is made available at http://bioinf.mpi-inf.mpg.de/publications/beggel/linkageinformation.zip

Sequencing chromatogram.

<p>The sequencing chromatogram shows two nearby ambiguous sequence positions 610 and 612. At position 610 adenine and guanine are present. At position 612 adenine and thymine are present. Positions are numbered with respect to the <i>Reverse Transcriptase</i> of the hepatitis B virus genome. This chromatogram raises the question which of the bases at positions 610 and 612 are present on the same clonal variant.</p

Fraction estimates for dilution series.

<p>All subplots show nominal mixture fractions versus estimated mixture fractions for three dilution series. A–C use all peak heights and provide proportions estimates with low error and low variance. D–E ignore the peak heights at the ambiguous positions and try to estimate the mixture proportions based on the unambiguous positions only. The resulting fraction estimates show higher error and higher variance.</p

Peak heights of dilution series.

<p>The figure shows the median normalized peak heights of the chromatograms of a dilution series sorted by nominal mixture proportion. The normalized peak heights before the ambiguous sequence position are almost identical for all nominal mixture proportions. At the ambiguous sequence position and at up to five bases downstream of the ambiguous sequence position a smooth and apparently linear transition between the peak heights of the samples with nominal mixture proportions 10∶0 and 0∶10 can be observed.</p

Prediction accuracy on <i>in vitro</i> test sets.

<p>The figure shows the prediction accuracy on test sets TS1 (subplots A and B) and TS2 (subplots C and D). Prediction accuracy was evaluated both at the clone and at the model level. Each test sample is either predicted correctly, predicted incorrectly or unassigned. The latter happens when the marginal likelihood of the best model divided by the marginal likelihoods of all other models falls below the uncertainty cutoff displayed on the x-axis.</p

<i>In silico</i> prediction results.

<p>1771 <i>in silico</i> test chromatograms were created by computing the mixture profiles on a grid of values with precision 0.05. Test chromatograms were classified by the mixture model with . The subplots show all falsely classified samples separately for each falsely predicted label. Six major cases of misclassification can be observed. Subplots A–D show test samples that consist of four haplotypes with at least one haplotype having low frequency. Subplots E and F show test samples that were predicted as mixtures of haplotypes 1 and 4 or of haplotypes 2 and 3, respectively. The data points of subplot E satisfy the linear constraints , and . The data points of subplot F satisfy , and .</p

Hepatitis B virus reverse transcriptase sequence variant database for sequence analysis and mutation discovery

Drug resistance resulting from reverse transcriptase (RI) mutations is one of the main obstacles to successful hepatitis B virus (HBV) therapy. Indeed, HBV treatment guidelines recommend HBV genotypic resistance testing for patients receiving nucleos(t)ide RT inhibitors (N(t)RTIs) who develop virological failure. N(t)RTI-resistance mutations at 10 RT positions have been well characterized in phenotypic studies, however, data are lacking on the relative frequency of these mutations in N(t)RTI-treated and untreated individuals. There are also few published data on the extent of amino acid variation at most of the 344 positions of HBV RI and the extent to which this variation is influenced by N(t)RTI treatment. We retrieved 23,871 HBV RI sequences from GenBank and reviewed the published reports of these sequences to ascertain the number of individuals from whom the sequences were obtained, the N(t)RTI treatments of these individuals, and the year and region of virus sampling. We then used these data to populate a relational database we named HBVrtDB. As of July 2010, HBVrtDB contained 6811 sequences from 3869 individuals reported in 281 references. Among these 3869 individuals, 73% were N(t)RTI-naive and 27% received one or more N(t)RTIs. Among the 10 well-characterized N(t)RTI-resistance mutations, L80I/V, V173L, L180M, A181T, T184S, S202G and M204I/V were significantly assocated with treatment with lamivudine, an L-nucleoside analog, and A181S/T/V and N236T were significantly associated with treatment with adefovir, an acyclic nucleoside phosphonate. A similar analysis of ten additional less well-characterized resistance mutations demonstrated a significant association with N(t)RTI treatment for four of the mutations: L82M, S85A, A200V, and Q215S. We also created an interactive program, HBVseq, to enable users to identify mutations in submitted sequences and retrieve the prevalence of these mutations in HBVrtDB according to genotype and N(t)RTI treatment. HBVrtDB and HBVseq are available at http://hivdb.stanford.edu/HBV/releaseNotes/. (C) 2010 Elsevier B.V. All rights reserved