School of Mathematics and Statistics - Research Publications
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ItemGenetic Variants in ERAP1 and ERAP2 Associated With Immune-Mediated Diseases Influence Protein Expression and the Isoform Profile(WILEY, 2018-02-01)OBJECTIVE: Endoplasmic reticulum aminopeptidase 1 (ERAP-1) and ERAP-2, encoded on chromosome 5q15, trim endogenous peptides for HLA-mediated presentation to the immune system. Polymorphisms in ERAP1 and/or ERAP2 are strongly associated with several immune-mediated diseases with specific HLA backgrounds, implicating altered peptide handling and presentation as prerequisites for autoreactivity against an arthritogenic peptide. Given the thorough characterization of disease risk-associated polymorphisms that alter ERAP activity, this study aimed instead to interrogate the expression effect of chromosome 5q15 polymorphisms to determine their effect on ERAP isoform and protein expression. METHODS: RNA sequencing and genotyping across chromosome 5q15 were performed to detect genetic variants in ERAP1 and ERAP2 associated with altered total gene and isoform-specific expression. The functional implication of a putative messenger RNA splice-altering variant on ERAP-1 protein levels was validated using mass spectrometry. RESULTS: Polymorphisms associated with ankylosing spondylitis (AS) significantly influenced the transcript and protein expression of ERAP-1 and ERAP-2. Disease risk-associated polymorphisms in and around both genes were also associated with increased gene expression. Furthermore, key risk-associated ERAP1 variants were associated with altered transcript splicing, leading to allele-dependent alternate expression of 2 distinct isoforms and significant differences in the type of ERAP-1 protein produced. CONCLUSION: In accordance with studies demonstrating that polymorphisms that increase aminopeptidase activity predispose to immune disease, the increased risk also attributed to increased expression of ERAP1 and ERAP2 supports the notion of using aminopeptidase inhibition to treat AS and other ERAP-associated conditions.
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ItemHuman Hepatocellular Carcinomas With a Periportal Phenotype Have the Lowest Potential for Early Recurrence After Curative Resection(WILEY, 2017-11-01)UNLABELLED: Hepatocellular carcinomas (HCCs) exhibit a diversity of molecular phenotypes, raising major challenges in clinical management. HCCs detected by surveillance programs at an early stage are candidates for potentially curative therapies (local ablation, resection, or transplantation). In the long term, transplantation provides the lowest recurrence rates. Treatment allocation is based on tumor number, size, vascular invasion, performance status, functional liver reserve, and the prediction of early (<2 years) recurrence, which reflects the intrinsic aggressiveness of the tumor. Well-differentiated, potentially low-aggressiveness tumors form the heterogeneous molecular class of nonproliferative HCCs, characterized by an approximate 50% β-catenin mutation rate. To define the clinical, pathological, and molecular features and the outcome of nonproliferative HCCs, we constructed a 1,133-HCC transcriptomic metadata set and validated findings in a publically available 210-HCC RNA sequencing set. We show that nonproliferative HCCs preserve the zonation program that distributes metabolic functions along the portocentral axis in normal liver. More precisely, we identified two well-differentiated, nonproliferation subclasses, namely periportal-type (wild-type β-catenin) and perivenous-type (mutant β-catenin), which expressed negatively correlated gene networks. The new periportal-type subclass represented 29% of all HCCs; expressed a hepatocyte nuclear factor 4A-driven gene network, which was down-regulated in mouse hepatocyte nuclear factor 4A knockout mice; were early-stage tumors by Barcelona Clinic Liver Cancer, Cancer of the Liver Italian Program, and tumor-node-metastasis staging systems; had no macrovascular invasion; and showed the lowest metastasis-specific gene expression levels and TP53 mutation rates. Also, we identified an eight-gene periportal-type HCC signature, which was independently associated with the highest 2-year recurrence-free survival by multivariate analyses in two independent cohorts of 247 and 210 patients. CONCLUSION: Well-differentiated HCCs display mutually exclusive periportal or perivenous zonation programs. Among all HCCs, periportal-type tumors have the lowest intrinsic potential for early recurrence after curative resection. (Hepatology 2017;66:1502-1518).
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ItemMultiparameter analysis of naevi and primary melanomas identifies a subset of naevi with elevated markers of transformation.(Wiley, 2016-07)Here we have carried out a multiparameter analysis using a panel of 28 immunohistochemical markers to identify markers of transformation from benign and dysplastic naevus to primary melanoma in three separate cohorts totalling 279 lesions. We have identified a set of eight markers that distinguish naevi from melanoma. None of markers or parameters assessed differentiated benign from dysplastic naevi. Indeed, the naevi clustered tightly in terms of their immunostaining patterns whereas primary melanomas showed more diverse staining patterns. A small subset of histopathologically benign lesions had elevated levels of multiple markers associated with melanoma, suggesting that these represent naevi with an increased potential for transformation to melanoma.
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ItemHLA Alleles Associated With Risk of Ankylosing Spondylitis and Rheumatoid Arthritis Influence the Gut Microbiome(WILEY, 2019-08-12)OBJECTIVE: HLA alleles affect susceptibility to more than 100 diseases, but the mechanisms that account for these genotype-disease associations are largely unknown. HLA alleles strongly influence predisposition to ankylosing spondylitis (AS) and rheumatoid arthritis (RA). Both AS and RA patients have discrete intestinal and fecal microbiome signatures. Whether these changes are the cause or consequence of the diseases themselves is unclear. To distinguish these possibilities, we examined the effect of HLA-B27 and HLA-DRB1 RA risk alleles on the composition of the intestinal microbiome in healthy individuals. METHODS: Five hundred sixty-eight stool and biopsy samples from 6 intestinal sites were collected from 107 healthy unrelated subjects, and stool samples were collected from 696 twin pairs from the TwinsUK cohort. Microbiome profiling was performed using sequencing of the 16S ribosomal RNA bacterial marker gene. All subjects were genotyped using the Illumina CoreExome SNP microarray, and HLA genotypes were imputed from these data. RESULTS: Associations were observed between the overall microbial composition and both the HLA-B27 genotype and the HLA-DRB1 RA risk allele (P = 0.0002 and P = 0.00001, respectively). These associations were replicated using the stool samples from the TwinsUK cohort (P = 0.023 and P = 0.033, respectively). CONCLUSION: This study shows that the changes in intestinal microbiome composition seen in AS and RA are at least partially due to effects of HLA-B27 and HLA-DRB1 on the gut microbiome. These findings support the hypothesis that HLA alleles operate to cause or increase the risk of these diseases through interaction with the intestinal microbiome and suggest that therapies targeting the microbiome may be effective in preventing or treating these diseases.
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ItemAn improved clinical model to predict stimulated C-peptide in children with recent-onset type 1 diabetes.(Wiley, 2019-03)BACKGROUND: Stimulated C-peptide measurement after a mixed meal tolerance test (MMTT) is the accepted gold standard for assessing residual beta-cell function in type 1 diabetes (T1D); however, this approach is impractical outside of clinical trials. OBJECTIVE: To develop an improved estimate of residual beta-cell function in children with T1D using commonly measured clinical variables. SUBJECTS/METHODS: A clinical model to predict 90-minute MMTT stimulated C-peptide in children with recent-onset T1D was developed from the combined AbATE, START, and TIDAL placebo subjects (n = 46) 6 months post-recruitment using multiple linear regression. This model was then validated in a clinical cohort (Hvidoere study group, n = 262). RESULTS: A model of estimated C-peptide at 6 months post-diagnosis, which included age, gender, body mass index (BMI), hemoglobin A1c (HbA1c), and insulin dose predicted 90-minute stimulated C-peptide measurements (adjusted R2 = 0.63, P < 0.0001). The predictive value of insulin dose and HbA1c alone (IDAA1c) for 90-minute stimulated C-peptide was significantly lower (R2 = 0.37, P < 0.0001). The slopes of linear regression lines of the estimated and stimulated 90-minute C-peptide levels obtained at 6 and 12 months post diagnosis in the Hvidoere clinical cohort were R2 = 0.36, P < 0.0001 at 6 months and R2 = 0.37, P < 0.0001 at 12 months. CONCLUSIONS: A clinical model including age, gender, BMI, HbA1c, and insulin dose predicts stimulated C-peptide levels in children with recent-onset T1D. Estimated C-peptide is an improved surrogate to monitor residual beta-cell function outside clinical trial settings.
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ItemImplementation and evaluation of amyloidosis subtyping by laser-capture microdissection and tandem mass spectrometry.(Springer Science and Business Media LLC, 2016)BACKGROUND: Correct identification of the amyloidosis-causing protein is crucial for clinical management. Recently the Mayo Clinic reported laser-capture microdissection (LCM) with liquid chromatography-coupled tandem mass spectrometry (MS/MS) as a new diagnostic tool for amyloid diagnosis. Here, we report an independent implementation of this proteomic diagnostics method at the Princess Alexandra Hospital Amyloidosis Centre in Brisbane, Australia. RESULTS: From 2010 to 2014, 138 biopsies received from 35 different organ sites were analysed by LCM-MS/MS using Congo Red staining to visualise amyloid deposits. There was insufficient tissue in the block for LCM for 7 cases. An amyloid forming protein was ultimately identified in 121 out of 131 attempted cases (94 %). Of the 121 successful cases, the Mayo Clinic amyloid proteomic signature (at least two of Serum Amyloid P, ApoE and ApoA4) was detected in 92 (76 %). Low levels of additional amyloid forming proteins were frequently identified with the main amyloid forming protein, which may reflect co-deposition of fibrils. Furthermore, vitronectin and clusterin were frequently identified in our samples. Adding vitronectin to the amyloid signature increases the number of positive cases, suggesting a potential 4th protein for the signature. In terms of clinical impact, amyloid typing by immunohistochemistry was attempted in 88 cases, reported as diagnostic in 39, however, 5 were subsequently revealed by proteomic analysis to be incorrect. Overall, the referring clinician's diagnosis of amyloid subtype was altered by proteomic analysis in 24 % of cases. While LCM-MS/MS was highly robust in protein identification, clinical information was still required for subtyping, particularly for systemic versus localized amyloidosis. CONCLUSIONS: This study reports the independent implementation and evaluation of a proteomics-based diagnostic for amyloidosis subtyping. Our results support LCM-MS/MS as a powerful new diagnostic technique for amyloidosis, but also identified some challenges and further development opportunities.
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ItemDynOmics to identify delays and co-expression patterns across time course experiments(NATURE PUBLISHING GROUP, 2017-01-09)Dynamic changes in biological systems can be captured by measuring molecular expression from different levels (e.g., genes and proteins) across time. Integration of such data aims to identify molecules that show similar expression changes over time; such molecules may be co-regulated and thus involved in similar biological processes. Combining data sources presents a systematic approach to study molecular behaviour. It can compensate for missing data in one source, and can reduce false positives when multiple sources highlight the same pathways. However, integrative approaches must accommodate the challenges inherent in 'omics' data, including high-dimensionality, noise, and timing differences in expression. As current methods for identification of co-expression cannot cope with this level of complexity, we developed a novel algorithm called DynOmics. DynOmics is based on the fast Fourier transform, from which the difference in expression initiation between trajectories can be estimated. This delay can then be used to realign the trajectories and identify those which show a high degree of correlation. Through extensive simulations, we demonstrate that DynOmics is efficient and accurate compared to existing approaches. We consider two case studies highlighting its application, identifying regulatory relationships across 'omics' data within an organism and for comparative gene expression analysis across organisms.
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ItemIntegrating Multi-omics Data to Dissect Mechanisms of DNA repair Dysregulation in Breast Cancer.(Springer Science and Business Media LLC, 2016-09-26)DNA repair genes and pathways that are transcriptionally dysregulated in cancer provide the first line of evidence for the altered DNA repair status in tumours, and hence have been explored intensively as a source for biomarker discovery. The molecular mechanisms underlying DNA repair dysregulation, however, have not been systematically investigated in any cancer type. In this study, we performed a statistical analysis to dissect the roles of DNA copy number alteration (CNA), DNA methylation (DM) at gene promoter regions and the expression changes of transcription factors (TFs) in the differential expression of individual DNA repair genes in normal versus tumour breast samples. These gene-level results were summarised at pathway level to assess whether different DNA repair pathways are affected in distinct manners. Our results suggest that CNA and expression changes of TFs are major causes of DNA repair dysregulation in breast cancer, and that a subset of the identified TFs may exert global impacts on the dysregulation of multiple repair pathways. Our work hence provides novel insights into DNA repair dysregulation in breast cancer. These insights improve our understanding of the molecular basis of the DNA repair biomarkers identified thus far, and have potential to inform future biomarker discovery.