We are an inter-disciplinary team of basic and clinical scientists with shared interests in using molecular genetics as a tool to uncover novel biology. We use a variety of different approaches to address important challenges in the field, which range from studies that work genome wide to those which are focused on specific genes and even precise nucleotide changes to understand their impact on pancreatic islet biology.
We have developed a series of pipelines that use primary human islets and authentic beta-cell models which allow us to generate and then integrate complex genomic, transcriptomic and cellular datasets. We use state-of-the art genome engineering approaches combined with induced pluripotent stem-cells to study the impact of T2D-associated genetic variants on islet cell development and function. We are also funded to investigate the impact of T2D risk variants on pancreatic beta-cell function in vivo.
We are a highly collaborative team and work with multiple national and international consortia involved in efforts to understand the genetic basis of type 2 diabetes (eg DIAGRAM, NIDDK Funded Accelerated Medicines Partnership) and related glycaemic traits (MAGIC). We are also part of several Innovative Medicines Initiatives (IMIs) efforts including STEMBANCC and RHAPSODY and Horizon 2020 initiatives (eg T2DSYSTEMS), which are working to develop tools and frameworks to capitalize on genetic and genomic data.
We are also part of the NIDDK funded Human Islet Research Network (HIRN) where we play a role in two of their initiatives. The Human Pancreas Atlas Program- T2 (HPAP-T2D) and the Integrated Islet Phenotype Program (IIPP). Our role is to support the genetic and genomic characterization of islets which are distributed for research and to support the genomic characterization of the pancreas’ phenotyped within the HPAP-T2D program.
Our work extends to playing a role in the interpretation of genetic variants identified in genes with known roles in monogenic forms of diabetes. We are part of the Clin Gen Expert Review Panel for Monogenic Diabetes where are expertise contributes to interpretation of coding alleles in glucokinase (GCK) and Hepatocyte Nuclear Factor 1 alpha (HNF1A). We are a number of on-going projects which are supporting efforts to better understand how to use exome-sequencing data in a diagnostic setting.
Insights into pancreatic islet cell dysfunction from type 2 diabetes mellitus genetics. Nature reviews. Endocrinology Krentz, N. A., Gloyn, A. L.2020 More
Type 2 diabetes mellitus (T2DM) is an increasingly prevalent multifactorial disease that has both genetic and environmental risk factors, resulting in impaired glucose homeostasis. Genome-wide association studies (GWAS) have identified over 400 genetic signals that are associated with altered risk of T2DM. Human physiology and epigenomic data support a central role for the pancreatic islet in the pathogenesis of T2DM. This Review focuses on the promises and challenges of moving from genetic associations to molecular mechanisms and highlights efforts to identify the causal variant and effector transcripts at T2DM GWAS susceptibility loci. In addition, we examine current human models that are used to study both beta-cell development and function, including EndoC-beta cell lines and human induced pluripotent stem cell-derived beta-like cells. We use examples of four T2DM susceptibility loci (CDKAL1, MTNR1B, SLC30A8 and PAM) to emphasize how a holistic approach involving genetics, physiology, and cellular and developmental biology can disentangle disease mechanisms at T2DM GWAS signals.
View details for DOI 10.1038/s41574-020-0325-0
View details for PubMedID 32099086
Deep learning models predict regulatory variants in pancreatic islets and refine type 2 diabetes association signals. eLife Wesolowska-Andersen, A., Zhuo Yu, G., Nylander, V., Abaitua, F., Thurner, M., Torres, J. M., Mahajan, A., Gloyn, A. L., McCarthy, M. I.2020; 9 More
Genome-wide association analyses have uncovered multiple genomic regions associated with T2D, but identification of the causal variants at these remains a challenge. There is growing interest in the potential of deep learning models - which predict epigenome features from DNA sequence - to support inference concerning the regulatory effects of disease-associated variants. Here, we evaluate the advantages of training convolutional neural network (CNN) models on a broad set of epigenomic features collected in a single disease-relevant tissue - pancreatic islets in the case of type 2 diabetes (T2D) - as opposed to models trained on multiple human tissues. We report convergence of CNN-based metrics of regulatory function with conventional approaches to variant prioritization - genetic fine-mapping and regulatory annotation enrichment. We demonstrate that CNN-based analyses can refine association signals at T2D-associated loci and provide experimental validation for one such signal. We anticipate that these approaches will become routine in downstream analyses of GWAS.
View details for DOI 10.7554/eLife.51503
View details for PubMedID 31985400
Homozygous Hypomorphic HNF1A Alleles Are a Novel Cause of Young-Onset Diabetes and Result in Sulphonylurea-Sensitive Diabetes. Diabetes care Misra, S., Hassanali, N., Bennett, A. J., Juszczak, A., Caswell, R., Colclough, K., Valabhji, J., Ellard, S., Oliver, N. S., Gloyn, A. L.2020 More
Heterozygous loss-of-function mutations in HNF1A cause maturity-onset diabetes of the young (MODY). Affected individuals can be treated with low-dose sulphonylureas. Individuals with homozygous HNF1A mutations causing MODY have not been reported.We phenotyped a kindred with young-onset diabetes and performed molecular genetic testing, a mixed meal tolerance test, a sulphonylurea challenge, and in vitro assays to assess variant protein function.A homozygous HNF1A variant (p.A251T) was identified in three insulin-treated family members diagnosed with diabetes before 20 years of age. Those with the homozygous variant had low hs-CRP levels (0.2-0.8 mg/L), and those tested demonstrated sensitivity to sulphonylurea given at a low dose, completely transitioning off insulin. In silico modeling predicted a variant of unknown significance; however, in vitro studies supported a modest reduction in transactivation potential (79% of that for the wild type; P < 0.05) in the absence of endogenous HNF1A.Homozygous hypomorphic HNF1A variants are a cause of HNF1A-MODY. We thus expand the allelic spectrum of variants in dominant genes causing diabetes.
View details for DOI 10.2337/dc19-1843
View details for PubMedID 32001615