Explore the vast range of titles available.

A greater understanding of the causes of human disease can come from identifying characteristics that are specific to disease genes. However, a full understanding of the contribution of essential genes to human disease is lacking, due to the premise that these genes tend to cause developmental abnormalities rather than adult disease. We tested the hypothesis that human orthologs of mouse essential genes are associated with a variety of human diseases, rather than only those related to miscarriage and birth defects. We segregated human disease genes according to whether the knockout phenotype of their mouse ortholog was lethal or viable, defining those with orthologs producing lethal knockouts as essential disease genes. We show that the human orthologs of mouse essential genes are associated with a wide spectrum of diseases affecting diverse physiological systems. Notably, human disease genes with essential mouse orthologs are over-represented among disease genes associated with cancer, suggesting links between adult cellular abnormalities and developmental functions. The proteins encoded by essential genes are highly connected in protein-protein interaction networks, which we find correlates with an over-representation of nuclear proteins amongst essential disease genes. Disease genes associated with essential orthologs also are more likely than those with non-essential orthologs to contribute to disease through an autosomal dominant inheritance pattern, suggesting that these diseases may actually result from semi-dominant mutant alleles. Overall, we have described attributes found in disease genes according to the essentiality status of their mouse orthologs. These findings demonstrate that disease genes do occupy highly connected positions in protein-protein interaction networks, and that due to the complexity of disease-associated alleles, essential genes cannot be ignored as candidates for causing diverse human diseases.

ObjectivesCurrent technologies for delivering gene testing are labour-intensive and expensive. Over the last 3 years, new high-throughput DNA sequencing techniques (next generation sequencing; NGS), with the capability to analyse multiple genes or entire genomes, have been rapidly adopted into research. This study examines the possibility of incorporating NGS into a clinical UK service context.MethodsThe study applied NGS of 105 genes to 50 patients known to be affected by inherited forms of blindness in the setting of a UK National Health Service-accredited diagnostic molecular genetics laboratory. The study assessed the ability of an NGS protocol to identify likely disease-causing genetic variants when compared with current methodologies available through UK diagnostic laboratories.ResultsConventional testing is only applicable to the minority of patients with inherited retinal disease and identifies mutations in fewer than one in four of those patients tested. By contrast, the NGS assay is directed at all patients with such disorders and identifies disease-causing mutations in 50–55%, which is a dramatic increase. This includes patients with apparently ‘sporadic’ disease, and those for whom clinical management and prognosis are altered as a consequence of defining their disease at a molecular level.ConclusionsThe new NGS approach delivers a step change in the diagnosis of inherited eye disease, provides precise diagnostic information and extends the possibility of targeted treatments including gene therapy. The approach represents an exemplar that illustrates the opportunity that NGS provides for broadening the availability of genetic testing. The technology will be applied to many conditions that are associated with high levels of genetic heterogeneity.

Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection.

There are three established HIV-1 lineages, M, N and O, which arose after cross-species transmission of simian immunodeficiency virus circulating in chimpanzees. An unusual variant of HIV-1 has now been identified that seems to be the prototype of a new lineage derived from gorillas. We have identified a new human immunodeficiency virus in a Cameroonian woman. It is closely related to gorilla simian immunodeficiency virus (SIVgor) and shows no evidence of recombination with other HIV-1 lineages. This new virus seems to be the prototype of a new HIV-1 lineage that is distinct from HIV-1 groups M, N and O. We propose to designate it HIV-1 group P.

Over 3,000 human diseases are known to be linked to heritable genetic variation, mapping to over 1,700 unique genes. Dating of the evolutionary age of these disease-associated genes has suggested that they have a tendency to be ancient, specifically coming into existence with early metazoa. The approach taken by past studies, however, assumes that the age of a disease is the same as the age of its common ancestor, ignoring the fundamental contribution of duplication events in the evolution of new genes and function. Here, we date both the common ancestor and the duplication history of known human disease-associated genes. We find that the majority of disease genes (80%) are genes that have been duplicated in their evolutionary history. Periods for which there are more disease-associated genes, for example, at the origins of bony vertebrates, are explained by the emergence of more genes at that time, and the majority of these are duplicates inferred to have arisen by whole-genome duplication. These relationships are similar for different disease types and the disease-associated gene's cellular function. This indicates that the emergence of duplication-associated diseases has been ongoing and approximately constant (relative to the retention of duplicate genes) throughout the evolution of life. This continued until approximately 390 Ma from which time relatively fewer novel genes came into existence on the human lineage, let alone disease genes. For single-copy genes associated with disease, we find that the numbers of disease genes decreases with recency. For the majority of duplicates, the disease-associated mutation is associated with just one of the duplicate copies. A universal explanation for heritable disease is, thus, that it is merely a by-product of the evolutionary process; the evolution of new genes (de novo or by duplication) results in the potential for new diseases to emerge.

Background In order to replicate, HIV, like all viruses, needs to invade a host cell and hijack it for its own use, a process that involves multiple protein interactions between virus and host. The HIV-1, Human Protein Interaction Database available at NCBI's website captures this information from the primary literature, containing over 2,500 unique interactions. We investigate the general properties and biological context of these interactions and, thus, explore the molecular specificity of the HIV-host perturbation. In particular, we investigate (i) whether HIV preferentially interacts with highly connected and 'central' proteins, (ii) known phenotypic properties of host proteins inferred from essentiality and disease-association data, and (iii) biological context (molecular function, processes and location) of the host proteins to identify attributes most strongly associated with specific HIV interactions. Results After correcting for ascertainment bias in the literature, we demonstrate a significantly greater propensity for HIV to interact with highly connected and central host proteins. Unexpectedly, we find there are no associations between HIV interaction and inferred essentiality. Similarly, we find a tendency for HIV not to interact with proteins encoded by genes associated with disease. Crucially, we find that functional categories over-represented in HIV-host interactions are innately enriched for highly connected and central proteins in the host system. Conclusions Our results imply that HIV's propensity to interact with highly connected and central proteins is a consequence of interactions with particular cellular functions, rather than being a direct effect of network topological properties. The lack of a propensity for interactions with phenotypically essential proteins suggests a selective pressure to minimise virulence in retroviral evolution. Thus, the specificity of HIV-host interactions is complex, and only superficially explained by network properties.

Deafness, onychodystrophy, osteodystrophy, mental retardation, and seizures (DOORS) syndrome is a rare autosomal recessive disorder of unknown cause. We aimed to identify the genetic basis of this syndrome by sequencing most coding exons in affected individuals. Through a search of available case studies and communication with collaborators, we identified families that included at least one individual with at least three of the five main features of the DOORS syndrome: deafness, onychodystrophy, osteodystrophy, intellectual disability, and seizures. Participants were recruited from 26 centres in 17 countries. Families described in this study were enrolled between Dec 1, 2010, and March 1, 2013. Collaborating physicians enrolling participants obtained clinical information and DNA samples from the affected child and both parents if possible. We did whole-exome sequencing in affected individuals as they were enrolled, until we identified a candidate gene, and Sanger sequencing to confirm mutations. We did expression studies in human fibroblasts from one individual by real-time PCR and western blot analysis, and in mouse tissues by immunohistochemistry and real-time PCR. 26 families were included in the study. We did exome sequencing in the first 17 enrolled families; we screened for TBC1D24 by Sanger sequencing in subsequent families. We identified TBC1D24 mutations in 11 individuals from nine families (by exome sequencing in seven families, and Sanger sequencing in two families). 18 families had individuals with all five main features of DOORS syndrome, and TBC1D24 mutations were identified in half of these families. The seizure types in individuals with TBC1D24 mutations included generalised tonic-clonic, complex partial, focal clonic, and infantile spasms. Of the 18 individuals with DOORS syndrome from 17 families without TBC1D24 mutations, eight did not have seizures and three did not have deafness. In expression studies, some mutations abrogated TBC1D24 mRNA stability. We also detected Tbc1d24 expression in mouse phalangeal chondrocytes and calvaria, which suggests a role of TBC1D24 in skeletogenesis. Our findings suggest that mutations in TBC1D24 seem to be an important cause of DOORS syndrome and can cause diverse phenotypes. Thus, individuals with DOORS syndrome without deafness and seizures but with the other features should still be screened for TBC1D24 mutations. More information is needed to understand the cellular roles of TBC1D24 and identify the genes responsible for DOORS phenotypes in individuals who do not have a mutation in TBC1D24. US National Institutes of Health, the CIHR (Canada), the NIHR (UK), the Wellcome Trust, the Henry Smith Charity, and Action Medical Research.

Human immunodeficiency virus type 1 (HIV-1) exploits a diverse array of host cell functions in order to replicate. This is mediated through a network of virus-host interactions. A variety of recent studies have catalogued this information. In particular the HIV-1, Human Protein Interaction Database (HHPID) has provided a unique depth of protein interaction detail. However, as a map of HIV-1 infection, the HHPID is problematic, as it contains curation error and redundancy; in addition, it is based on a heterogeneous set of experimental methods. Based on identifying shared patterns of HIV-host interaction, we have developed a novel methodology to delimit the core set of host-cellular functions and their associated perturbation from the HHPID. Initially, using biclustering, we identify 279 significant sets of host proteins that undergo the same types of interaction. The functional cohesiveness of these protein sets was validated using a human protein-protein interaction network, gene ontology annotation and sequence similarity. Next, using a distance measure, we group host protein sets and identify 37 distinct higher-level subsystems. We further demonstrate the biological significance of these subsystems by cross-referencing with global siRNA screens that have been used to detect host factors necessary for HIV-1 replication, and investigate the seemingly small intersect between these data sets. Our results highlight significant host-cell subsystems that are perturbed during the course of HIV-1 infection. Moreover, we characterise the patterns of interaction that contribute to these perturbations. Thus, our work disentangles the complex set of HIV-1-host protein interactions in the HHPID, reconciles these with siRNA screens and provides an accessible and interpretable map of infection.

Research into human disease has classically been 'bottom-up', focussing on individual genes. However, the emergence of Systems Biology has prompted a more holistic 'top-down' approach to decoding life. Less than a decade since the complete draft of the human genome was published, we are increasingly in a position to model the interacting constituents of a cell and thus understand molecular perturbations. Given biological systems are rarely attributable to individual molecules and linear pathways, we must understand the complex dynamic interplay as cellular components interact, combine, overlap and conflict. The integrative approach afforded by Network Biology provides us with a powerful toolset to understand the vast volumes of omics data. In this thesis, I investigate both infectious disease, specifically HIV infection and heritable disease. HIV, the causative agent of AIDS, represents an extensive perturbation of the host system and results in hijacking of cellular proteins to replicate. I first introduce the HIV-interaction data and then characterise HIV's hijack, revealing the ways Network Biology can greatly enhance our understanding of host-pathogen systems and ultimately the systems itself. I find a significantly greater propensity for HIV to interact with ''key'' host proteins that are highly connected and represent critical cellular functions. Unexpectedly, however, I find there are no associations between HIV interaction and inferred essentiality and genetic disease-association. I hypothesise that these observations could be the result of ancestral selection pressure on retroviruses to minimise interactions with phenotypically crucial proteins. Investigating inherited disease, I apply a similar integrative approach to determine the relationships between inherited disease, evolution and function. I find that 'disease' genes are not a homogenous group, and that their emergence has been ongoing throughout the evolution of life; contradicting previous studies. Finally, I consider the consequence of bias in literature-curated interaction datasets. I develop a novel method to identify and correct for ascertainment bias and demonstrate that failure to do this weakens conclusions. correct for ascertainment bias and demonstrate that failure to do this weakens conclusions. The aim of this thesis has been to explore the ways Network Biology can provide an integrative biological approach to studying infectious and inherited disease. Given billions of people around the world are susceptible to disease, it is ultimately hoped that a Systems Biology approach to understanding disease will herald new pharmaceutical interventions.

Most patients with Alzheimer's disease present with amnestic problems; however, a substantial proportion, over-represented in young-onset cases, have atypical phenotypes including predominant visual, language, executive, behavioural, or motor dysfunction. In the past, these individuals often received a late diagnosis; however, availability of CSF and PET biomarkers of Alzheimer's disease pathologies and incorporation of atypical forms of Alzheimer's disease into new diagnostic criteria increasingly allows them to be more confidently diagnosed early in their illness. This early diagnosis in turn allows patients to be offered tailored information, appropriate care and support, and individualised treatment plans. These advances will provide improved access to clinical trials, which often exclude atypical phenotypes. Research into atypical Alzheimer's disease has revealed previously unrecognised neuropathological heterogeneity across the Alzheimer's disease spectrum. Neuroimaging, genetic, biomarker, and basic science studies are providing key insights into the factors that might drive selective vulnerability of differing brain networks, with potential mechanistic implications for understanding typical late-onset Alzheimer's disease.