Type-2 diabetes (T2D), a multi-factorial disease characterised by chronic hyperglycaemia, is caused by a complex interaction between genetic and environmental factors. Genetic and phenotypic characterisations of diabetic patients suggest that a combination of β-cell failure, culminating in defective insulin secretion, as well as impairment of glucagon secretion in α-cells is central to the aetiology of the disease. Mouse models represent a valuable tool in such investigations. With the advent of large-scale genetic tools, a myriad of novel susceptibility loci associated with T2D have been identified. For many of these genes, it is unclear how genetic variation is linked to increased disease susceptibility. Our first study elucidates the implication of a transcription factor, SOX4, which is believed to underlie a T2D susceptibility locus (CDKAL1) in human. Using an N-ethyl-N-nitrosourea (ENU) mouse model, we explored β-cell function in mice carrying a point mutation in Sox4 (Sox4mt mice). This mouse strain displayed a significant reduction in glucose-stimulated insulin secretion (GSIS) that was associated with a 2-fold increase in wild-type Sox4 expression. The exocytotic events in mutant β-cells, as measured by single-vesicle (on-cell) capacitance measurements, suggested the presence of a persistent fusion pore. Subsequent failure of fusion pore expansion beyond the initial 1–2 nm results in an incomplete insulin release due to steric hindrance (insulin diameter: 3–4 nm). The proportion of full fusion events diminished in favour of kiss-and-run events in mutant β-cells. Stxbp6, which encodes amisyn, was shown to be the target gene of Sox4. Increased expression of amisyn, a protein previously shown to be involved in the stabilisation of the fusion pore in chromaffin cells, was observed in islets isolated from Sox4mt mice. The possible involvement of amisyn is further suggested by the finding that overexpression of amisyn mimicked the effect of the Sox4 mutation and resulted in reduced insulin secretion. Knockdown of amisyn expression restored the secretory defect in Sox4mt-overexpressing cells. Importantly, the effect of the Sox4 mutation was recapitulated by the overexpression of Sox4. Similar effects were obtained in the human β-cell line EndoC-βH2. We also observed a negative correlation between SOX4 expression and GSIS in a large collection of human islet preparations. There was also a positive correlation between SOX4 expression and STXBP6 (amisyn) expression and a tendency towards increased SOX4 expression in islets from organ donors with T2D. The second part of the thesis focuses on the role of the Krebs cycle enzyme fumarate hydratase (FH) in insulin release. Ablation of the Fh1 gene (which is initially implicated as a tumour suppressor in hereditary leiomyomatosis and renal cell cancer) in pancreatic β-cells led to a complete loss of GSIS, as determined by ex vivo pancreatic perfusion studies, although this was not associated with any detectable abnormalities in [Ca²⁺]_i homeostasis, ATP production or glucose oxidation. The phenotype was rescued by the introduction of the human orthologue FH into the cytosol alone or in both the cytoplasm and mitochondria of Fh1 knockout (Fh1KO) mice, confirming the role of Fh1 in insulin secretion. Moreover, the addition of exogenous glutamate, previously implicated as a 2^nd messenger between glucose metabolism and insulin secretion, corrected the insulin secretory defect in Fh1^-/- β-cells. We hypothesise that the loss of GSIS in Fh1KO mice results from enhanced anaplerosis, which is necessary to replenish Krebs cycle reactants. Consequently, this is followed by the depletion of the intracellular amino acid pool (including glutamate). Thus, our study demonstrates that the pancreatic Fh1KO mouse is a novel model of severe hyperglycaemia that harbours dysregulated metabolic features at the interface between both cancer and diabetes. The final study investigates the effect of ageing, a risk factor for T2D, on glucose-stimulated insulin and glucagon release. However, GSIS increased rather than decreased with ageing in both human and mouse islets (6 and 20 mmol/l glucose). Notably, ageing was not associated with reduced insulin content. Normal calcium homeostasis was observed in old (24-month-old) mice, demonstrating that the glucose sensing machinery was intact. In human islets, the inhibitory effect of glucose on glucagon secretion deteriorated with age. In the oldest group (>60 years of age), the inhibitory effect was completely abolished with 20 mmol/l glucose, while 6 mmol/l glucose only achieved less than 20% inhibition (which was not statistically significant). Our study reports the exciting possibility that hypersecretion of glucagon represents a link between senescence and increased diabetes risk.

Genome-wide association studies (GWAS) have made substantial progress in implicating genomic regions in type 2 diabetes (T2D) susceptibility. Whilst attributing causal mechanisms to loci has proved non trivial, these studies have provided insights into the genetic architecture underlying the disease. GWAS findings indicate a causal role for gene regulatory processes, and suggest that pancreatic beta-cells play a pivotal role in mediating common T2D association. Work presented in this thesis therefore sought to generate novel regulatory annotations from human islets, and to assess whether T2D-associated loci can be accurately fine-mapped using statistical approaches, with the aim of improving understanding of causal mechanisms underlying these associations through integration of the two approaches. Using small RNA sequencing in human islets and enriched beta-cell populations (both n=3) and mRNA sequencing in a large number of human islets (n=130), I increased the number of available human islet annotations. These studies identified high or islet-specific expression in many micro RNAs (miRNAs) without previously known roles in human islets. It also provided the largest study of quantitative trait loci (eQTLs) and allele-specific expression (ASE) in human islets to date, identifying significant eQTLs for 1,636 genes and significant ASE at 8,754 genes. There was enrichment of active islet chromatin, compared to other tissues, at the best eQTL variant for each gene, but also substantial sharing of significant eQTLs between islets and other tissues. Simulations were used to assess the utility of fine-mapping approaches for refining common disease-associated loci to smaller intervals or sets of variants likely to include the causal variant. The results demonstrated that fine-mapping can indeed refine these loci to sets or intervals of a size more amenable to functional follow-up or focussed intersection with high quality annotations. Furthermore, using an approximated Bayesian approach, I was able to refine twenty-one of the known common T2D-associated loci. Finally, using the newly generated annotations, I demonstrated enrichment of T2D association signal for regulatory RNA annotations (islet lncRNAs and miRNA target gene sets). I also identified examples in which these types of annotation overlap common and rare variation suggestive of a role in T2D pathogenesis. Using further islet annotations, I also uncovered potential causal mechanisms at four of the twentyone fine-mapped common T2D loci. These data therefore provide many novel islet regulatory annotations that can be intersected with T2D genetics, and provide a first example of how such an approach can lead to novel potential causal mechanisms underlying association loci.

Background: Pancreatic islet transplantation for type-1 diabetes has resulted in considerable success over the past decade. However, the worldwide shortage of pancreatic donors remains a major challenge. In an attempt to expand the donor pool, pancreases from obese organs donors (>30 kg/m²) are now routinely offered to islet transplantation in the UK. In addition, it has been suggested that pancreases from donors with early type-2 diabetes mellitus may also be suitable. However, for both these donor groups, although high islet yields (IEQ) may be obtained, it is unclear whether these islets function optimally. An additional approach to the donor shortage is to minimise the number of donors required per islet recipient. One strategy to achieve this is to use different pharmacological agents to enhance post-transplant islet function. Aims: The aims of this thesis were fourfold; 1) To determine whether islets isolated from high BMI donors function normally in vitro and in vivo; 2) To establish why islet yields are higher from obese donors; 3) To determine whether islets from donors with type-2 diabetes are suitable for islet transplantation; 4) To investigate whether glucagon-like peptide 1 receptor agonist therapy improves post-transplant islet graft function. Results: Stimulated insulin and glucagon secretion, and markers of mitochondrial function (intra-islet ATP content and mitochondrial copy number) were compared in islets isolated from obese (BMI>30kg/m²; n= 27) and non-obese (BMI<28kg/m²; n=25) donors. No differences in secretory function or intra-islet ATP were observed between the two groups. Pancreatic lipid and intra-islet triglyceride concentrations were higher in the obese group. In vivo clinical outcomes of patients transplanted in Oxford and a larger cohort (n=35) in Edmonton, Canada with islets from obese or non-obese donors showed no differences in post-transplant outcomes. Improved islet yields were shown to be a result of improved islet recovery of larger islets, in obese donors. Abnormal insulin and glucagon secretory responses were observed in islets from type-2 diabetic subjects (n=6) and islet amyloid content was significantly higher in diabetes. The glucagon-like peptide 1 receptor agonist, exenatide, administered for 20 weeks, significantly improved graft function in patients whom islet function was impaired. Conclusion: The high lipid environment of islets isolated from donors with high BMI appears not to be deleterious to their function either in vitro or when transplanted, supporting the use of islets from high BMI donors for clinical islet transplantation. However, islet dysfunction and pathological changes indicate that islets from type-2 diabetic donors are unsuitable. Therapeutic options such as exenatide, improve transplanted islet viability and function, and could have a significant role in the future of beta-cell replacement therapy for type-1 diabetes.

No description available.

Maturity-onset diabetes of the young (MODY), due to hepatocyte nuclear factor 1 alpha mutations (HNF1A-MODY), is the most common form of monogenic diabetes presenting in young adults. An accurate genetic diagnosis of HNF1A-MODY has therapeutic implications for the patients and their family members. However, the majority of people with HNF1A-MODY are not referred for genetic testing and remain misdiagnosed as type 1 or type 2 diabetes. As part of measures to address this misdiagnosis, over the last few years there have been efforts to define clinical features and biomarkers that can be used to identify those at high risk of HNF1A-MODY. Secreted hepatic proteins regulated by HNF1A are attractive candidates for diagnostic biomarkers that would be specific for this form of diabetes. Apolipoprotein M (apoM), C-reactive protein (CRP) and plasma glycan profile have all been investigated as biomarkers to improve selection of suspected MODY cases for genetic testing. In my thesis, I have addressed questions about the variation in apoM between different forms of diabetes and assessed the performance of hsCRP and plasma glycan profile to identify HNF1A-MODY in previously uninvestigated individuals with young-onset diabetes and in a non-European population. Additionally because CRP and plasma glycans are both important components of an acute inflammatory response, I examined the effect of haploinsufficiency of HNF1A in a standardised model of inflammation. When investigating apoM, I showed that serum apoM levels are lower in HNF1A-MODY than controls, and have demonstrated for the first time that serum apoM provides good discrimination between HNF1A-MODY and type 1 diabetes. CRP and plasma glycan profile both performed well in identifying HNF1A-MODY cases in unselected young adults with diabetes. The results also suggested that both biomarkers have value for assessing the functional impact of novel HNF1A variants. I went on to examine the use of a low CRP for selecting those at risk of HNF1A-MODY in South Asian subjects with young-onset diabetes. This study suggests that the overall population prevalence of HNF1A-MODY is similar in South Asians to Europeans, but that MODY represents a lower proportion of those with diabetes (due to the higher prevalence of type 2 diabetes in South Asians). The specific selection strategy employed in this study was not successful in identifying subjects at high risk of HNF1A-MODY (only 3% of those sequenced had mutations), suggesting that additional clinical and biochemical features will be required in addition to CRP to distinguish South Asians at high risk of HNF1A-MODY. Lastly, using endotoxaemia as a standardised model of acute inflammation for the first time in HNF1A-MODY, I have shown that despite low baseline levels, subjects with HNF1A-MODY had peak stimulated CRP levels comparable to non-diabetic controls. An attenuated cytokine response was observed in HNF1A-MODY, which requires further investigation. This is also the first report of inflammation-associated changes in plasma and white cell membrane glycan profile in diabetes. This research work adds substantially to current understanding of performance of HNF1A-MODY biomarkers, a critical step before their clinical translation. The work presented also provides novel insights into the regulation of the acute inflammatory response in HNF1A-MODY.

Type 2 diabetes (T2D) has a genetic component which is only partially understood. The majority of genetic variance in disease susceptibility is unaccounted for, whilst the precise transcripts and molecular mechanisms through which most risk variants exert their effect is unclear. A complete understanding of T2D susceptibility mechanisms could have benefits in risk prediction, and in drug discovery through the identification of novel therapeutic targets. Work presented in this thesis aims to define relevant transcripts and disease mechanisms at known susceptibility loci, and to identify disease association with classes of genetic variation other than common single nucleotide polymorphisms (SNPs). KCNQ1 contains intronic variants associated with T2D susceptibility and β-cell dysfunction, but only maternally-inherited alleles confer increased disease risk. It maps within an imprinted domain with an established role in congenital and islet-specific growth phenotypes. Using human adult islet and foetal pancreas samples, I refined the transcripts and developmental stage at which T2D susceptibility must be conferred by demonstrating developmentally plastic monoallelic and biallelic expression. I identified a potential risk mechanism through the effect of T2D risk alleles upon DNA methylation. The disease-associated regions identified through genome-wide association (GWA) studies often contain multiple transcripts. I performed mRNA expression profiling of genes within loci associated with raised proinsulin/insulin ratios in human islets and metabolically relevant tissues. Some genes (notably CT62) were not expressed and therefore excluded from consideration for a risk effect, whilst others (for example C2CD4A) were highlighted as good regional candidates due to specific expression in relevant tissues. GWA studies for T2D risk have focused predominantly upon common single nucleotide polymorphisms. As part of a consortium conducing GWA analysis for copy number variation (CNV) and T2D risk, I optimised and compared alternative methods of CNV genotyping, before using this information to validate two signals of disease association. I genotyped three rare single nucleotide variants emerging from an association study with T2D risk based on imputed data, providing an indication of imputation accuracy and more powerful disease association analysis. These data underscore the challenge of translating association signals to causal mechanisms, and of identifying alternative forms of genomic variation which contribute to T2D risk. My work highlights candidates for functional analysis around proinsulin-associated loci, and makes significant progress towards uncovering risk mechanisms at the KCNQ1 locus.

The rising prevalence of type 2 diabetes (T2D) is a global problem, and suggests that we need better therapeutic strategies against this disease. The glycolytic enzyme glucokinase (GCK) catalyses the phosphorylation of glucose, and is a well-established T2D drug target. Rare GCK mutations cause monogenic beta-cell dysfunction, whilst common genetic variants within GCK are associated with fasting plasma glucose (FPG) levels and T2D risk. Since GCK is expressed in both the pancreas and liver, pharmacological GCK activation provides the promise of a two-pronged attack on hyperglycaemia. In vivo, GCK activity is modulated by the hepatic inhibitor glucokinase regulatory protein (GKRP, gene GCKR). GKRP negatively regulates GCK activity competitively with respect to glucose, and is controlled by fructose 6- and fructose 1-phosphate (F6P and F1P), which compete with each other for binding and enhance or diminish GCK inhibition respectively. GKRP also sequesters GCK in the nucleus and paradoxically stabilises the enzyme. As GCK and its regulatory protein are fundamental to glucose homeostasis, we aimed to investigate the role of genetic variation in both GCK and GCKR to further our understanding of these important T2D drug targets in a system that would be relevant to man. I demonstrated that two novel GCK mutations (T103S and V389L) identified in patients with hyperinsulinaemic hypoglycaemia were kinetically activating and through structural modelling identified a novel regulatory site for GCK activation by small molecular activators. Genome-wide association studies (GWAS) identified GCKR as a regulator of FPG and triglyceride levels, and showed a role for GKRP in T2D risk. Unlike most GWAS hits, this signal included a non-synonymous variant within GCKR (P446L), thus facilitating functional studies. P446L-GKRP was characterised kinetically and at the cellular sequestration-level. This variant showed diminished F6P-mediated modulation, which was proposed to reduce hepatic GCK inhibition, increase glycolytic flux (decreasing FPG), and feed metabolites into liver pathways (elevating triglycerides). As GCKR was not expressed at functional levels within human islets, this phenotype was thought to be driven by the liver. Preliminary analysis at the cellular level was inconclusive, with optimisation required to study human P446L-GKRP in this cellular system. Finally, I showed that mutations within GCKR are not a common cause of “GCK-Like” phenotypes in man, despite the regulatory protein directly modulating GCK activity. These data provide further insight as to the pathogenic consequences of perturbing GCK activity. This must be considered if this enzyme is to be the subject of therapeutic intervention in T2D.

The analysis of non steady state physiological and pathological processes concerns the abstraction, extraction, formalisation and analysis of information from physiological systems that is obscured, hidden or unable to be assessed using traditional methods. Time Series Analysis (TSA) techniques were developed and built into a software program, Easy TSA, with the aim of examining the oscillations of hormonal concentrations in respect to their temporal aspects – periodicity, phase, pulsatility. The Easy TSA program was validated using constructed data sets and used in a clinical study to examine the relationship between insulin and obesity in people without diabetes. In this study fifty-six non-diabetic subjects (28M, 28F) were examined using data from a number of protocols. Fourier Transform and Autocorrelation techniques determined that there was a critical effect of the level of BMI on the frequency, amplitude and regularity of insulin oscillations. Second, information systems formed the background to the development of an algorithm to examine glycaemic variability and a new methodology termed the Glycaemic Risk in Diabetes Equation (GRADE) was developed. The aim was to report an integrated glycaemic risk score from glucose profiles that would complement summary measures of glycaemia, such as the HbA1c. GRADE was applied retrospectively to blood glucose data sets to determine if it was clinically relevant. Subjects with type 1 and type 2 diabetes had higher GRADE scores than the non-diabetic population and the contribution of hypo- and hyperglycaemic episodes to risk was demonstrated. A prospective study was then designed with the aim to apply GRADE in a clinical context and to measure the statistical reproducibility of using GRADE. Fifty-three (Male 26, Female 27) subjects measured their blood glucose 4 times daily for twenty-one days. The results were that lower HbA1c’s correlated with an increased risk of hypoglycaemia and higher HbA1c’s correlated with an increased risk of hyperglycaemia. Some subjects had HbA1c of 7.0 but had median GRADE values ranging from 2.2 to 10.5. The GRADE score summarized diverse glycaemic profiles into a single assessment of risk. Well-controlled glucose profiles yielded GRADE scores <= 5 and higher GRADE scores represented increased clinical risk from hypo or hyperglycaemia. Third, an information system was developed to analyse data-rich multi-variable retinal images using the concept of assessment of change rather than specific lesion recognition. A fully Automated Retinal Image Differencing (ARID) computer system was developed to highlight change between retinal images over time. ARID was validated using a study and then a retrospective study sought to determine if the use of the ARID software was an aid to the retinal screener. One hundred and sixty images (80 image pairs) were obtained from Gloucestershire Diabetic Eye Screening Programme. Images pairs were graded manually and categorised according to how each type of lesion had progressed, regressed, or not changed between image A and image B. After a 30 day washout period image pairs were graded using ARID and the results compared. The comparison of manual grading to grading using ARID (Table 4.3) demonstrated an increased sensitivity and specificity. The mean sensitivity of ARID (87.9%) was increased significantly in comparison to manually grading sensitivity (84.1%) (p<0.05). The specificity of the automated analysis (87.5%) increased significantly from the specificity (56.3%) achieved by manually grading (p<0.05). The conclusion was that automatic display of an ARID differenced image where sequential photographs are available would allow rapid assessment and appropriate triage. Forth, non-linear dynamic systems analysis methods were utilised to build a system to assess the extent of chaos characteristics within the insulin-glucose feedback domain. Biological systems exist that are deterministic yet are neither predictable nor repeatable. Instead they exhibit chaos, where a small change in the initial conditions produces a wholly different outcome. The glucose regulatory system is a dynamic system that maintains glucose homeostasis through the feedback mechanism of glucose, insulin, and contributory hormones and was ideally suited to chaos analysis. To investigate this system a new algorithm was created to assess the Normalised Area of Attraction (NAA). The NAA was calculated by defining an oval using the 95% CI of glucose & Insulin (the limit cycle) on a phasic plot. Thirty non-diabetic subjects and four subjects with type 2 diabetes were analysed. The NAA indicated a smaller range for glucose and insulin excursions with the non-diabetics subjects (p<0.05). The conclusion was that the evaluation of glucose metabolism in terms of homeostatic integrity and not in term of cut-off values may enable a more realistic approach to the effective treatment and prevention of diabetes and its complications.

No description available.