Soren K. Thomsen

Systematic Functional Characterization of Candidate Causal Genes for Type 2 Diabetes Risk Variants.

Most genetic association signals for type 2 diabetes risk are located in noncoding regions of the genome, hindering translation into molecular mechanisms. Physiological studies have shown a majority of disease-associated variants to exert their effects through pancreatic islet dysfunction. Systematically characterizing the role of regional transcripts in β-cell function could identify the underlying disease-causing genes, but large-scale studies in human cellular models have previously been impractical. We developed a robust and scalable strategy based on arrayed gene silencing in the human β-cell line EndoC-βH1. In a screen of 300 positional candidates selected from 75 type 2 diabetes regions, each gene was assayed for effects on multiple disease–relevant phenotypes, including insulin secretion and cellular proliferation. We identified a total of 45 genes involved in β-cell function, pointing to possible causal mechanisms at 37 disease-associated loci. The results showed a strong enrichment for genes implicated in monogenic diabetes. Selected effects were validated in a follow-up study, including several genes (ARL15, ZMIZ1, and THADA) with previously unknown or poorly described roles in β-cell biology. We have demonstrated the feasibility of systematic functional screening in a human β-cell model and successfully prioritized plausible disease-causing genes at more than half of the regions investigated.

Loss-of-Function Mutations in the Cell-Cycle Control Gene CDKN2A Impact on Glucose Homeostasis in Humans

At the CDKN2A/B locus, three independent signals for type 2 diabetes risk are located in a noncoding region near CDKN2A. The disease-associated alleles have been implicated in reduced β-cell function, but the underlying mechanism remains elusive. In mice, β-cell–specific loss of Cdkn2a causes hyperplasia, while overexpression leads to diabetes, highlighting CDKN2A as a candidate effector transcript. Rare CDKN2A loss-of-function mutations are a cause of familial melanoma and offer the opportunity to determine the impact of CDKN2A haploinsufficiency on glucose homeostasis in humans. To test the hypothesis that such individuals have improved β-cell function, we performed oral and intravenous glucose tolerance tests on mutation carriers and matched control subjects. Compared with control subjects, carriers displayed increased insulin secretion, impaired insulin sensitivity, and reduced hepatic insulin clearance. These results are consistent with a model whereby CDKN2A loss affects a range of different tissues, including pancreatic β-cells and liver. To test for direct effects of CDKN2A-loss on β-cell function, we performed knockdown in a human β-cell line, EndoC-bH1. This revealed increased insulin secretion independent of proliferation. Overall, we demonstrated that CDKN2A is an important regulator of glucose homeostasis in humans, thus supporting its candidacy as an effector transcript for type 2 diabetes–associated alleles in the region.

The pancreatic β cell: recent insights from human genetics

Highlights • Genes involved in pancreatic development are implicated in Mendelian diabetes.• Studying the genetic basis of diabetes has delivered insights into β cell biology.• Most genetic associations influence diabetes risk through defects in β cell function.• Sequencing-based methods and improved genomic annotations have facilitated advances.

Phenotypic severity of homozygous GCK mutations causing neonatal or childhood-onset diabetes is primarily mediated through effects on protein stability

Mutations in glucokinase (GCK) cause a spectrum of glycemic disorders. Heterozygous loss-of-function mutations cause mild fasting hyperglycemia irrespective of mutation severity due to compensation from the unaffected allele. Conversely, homozygous loss-of-function mutations cause permanent neonatal diabetes requiring lifelong insulin treatment. This study aimed to determine the relationship between in vitro mutation severity and clinical phenotype in a large international case series of patients with homozygous GCK mutations. Clinical characteristics for 30 patients with diabetes due to homozygous GCK mutations (19 unique mutations, including 16 missense) were compiled and assigned a clinical severity grade (CSG) based on birth weight and age at diagnosis. The majority (28 of 30) of subjects were diagnosed before 9 months, with the remaining two at 9 and 15 years. These are the first two cases of a homozygous GCK mutation diagnosed outside infancy. Recombinant mutant GCK proteins were analyzed for kinetic and thermostability characteristics and assigned a relative activity index (RAI) or relative stability index (RSI) value. Six of 16 missense mutations exhibited severe kinetic defects (RAI ≤ 0.01). There was no correlation between CSG and RAI (r2 = 0.05, P = 0.39), indicating that kinetics alone did not explain the phenotype. Eighty percent of the remaining mutations showed reduced thermostability, the exceptions being the two later-onset mutations which exhibited increased thermostability. Comparison of CSG with RSI detected a highly significant correlation (r2 = 0.74, P = 0.002). We report the largest case series of homozygous GCK mutations to date and demonstrate that they can cause childhood-onset diabetes, with protein instability being the major determinant of mutation severity.

Human genetics as a model for target validation: finding new therapies for diabetes

Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are ‘experiments of nature’ that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck.

Prioritising Causal Genes at Type 2 Diabetes Risk Loci

Purpose of ReviewGenome-wide association studies (GWAS) for type 2 diabetes (T2D) risk have identified a large number of genetic loci associated with disease susceptibility. However, progress moving from association signals through causal genes to functional understanding has so far been slow, hindering clinical translation. This review discusses the benefits and limitations of emerging, unbiased approaches for prioritising causal genes at T2D risk loci.Recent FindingsCandidate causal genes can be identified by a number of different strategies that rely on genetic data, genomic annotations, and functional screening of selected genes. To overcome the limitations of each particular method, integration of multiple data sets is proving essential for establishing confidence in the prioritised genes. Previous studies have also highlighted the need to support these efforts through identification of causal variants and disease-relevant tissues.SummaryPrioritisation of causal genes at T2D risk loci by integrating complementary lines of evidence promises to accelerate our understanding of disease pathology and promote translation into new therapeutics.

The Importance of Context: Uncovering Species- and Tissue-Specific Effects of Genetic Risk Variants for Type 2 Diabetes.

Genome-wide association studies (GWAS) have been highly successful in identifying genetic variation associated with type 2 diabetes (T2D) risk and related quantitative traits (1–3). The vast majority of association signals are located in non-coding regions of the genome, influencing nearby genes through regulation of transcriptional, translational, or splicing activity (4). Due to the highly context-dependent nature of gene expression, the effects of many risk variants are restricted to specific cell types and produce more subtle effects than those observed in organism-wide (or “global”) knockouts. In addition, identification of the underlying causal genes and target tissues is often a major challenge, hindering translation into disease mechanisms. Recent studies have shown that the intersection of genetic data and genomic annotations can be used to produce a cellular atlas with which to understand the phenotypes of GWAS signals. Through the generation of directed hypotheses, this integrated framework has the potential to bridge the gap between association signals and disease biology.

Keys to the kingdom.

A full list of authors and affiliations appears at the end of the paper. a an academic bioentrepreneur, you will face many challenges. At the very least, you must identify a novel and valuable life science opportunity, create a viable business model, build a team with technical and business acumen, manage resources and orchestrate partnerships, communicate your team’s legitimacy to customers and stakeholders, as well as effectively ‘pivot’ as circumstances evolve (or, in other words, have the vision and courage to dramatically change your research or business strategy before your company runs into the ground)1,2. In addition, you will most likely have to negotiate with your university’s technology transfer office (TTO) to license the intellectual property (IP) related to your research. Keep in mind that technology transfer regimes and policies regarding ownership of IP rights vary substantially across academic institutions for a variety of reasons. And that university TTOs in the United States and the United Kingdom govern themselves by different strategic and operational models3. This administrative complexity and opacity in university technology transfer presents an extra obstacle to academic entrepreneurs who already face a multitude of technical and commercial hurdles before their discovery can reach the marketplace. The best way to overcome these issues is to be fully informed before initiating negotiations with your TTO. We hope the information in this article will better prepare you to meet these challenges.

Loss of ZnT8 function protects against diabetes by enhanced insulin secretion

A rare loss-of-function variant p.Arg138* in SLC30A8 encoding the zinc transporter 8 (ZnT8) enriched in Western Finland protects against type 2 diabetes (T2D). We recruited relatives of the identified carriers and showed that protection was associated with better insulin secretion due to enhanced glucose responsiveness and proinsulin conversion, especially compared with individuals matched for the genotype of a common T2D risk variant in SLC30A8, p.Arg325. In genome-edited human IPS-derived β-like cells, we establish that the p.Arg138* variant results in reduced SLC30A8 expression due to haploinsufficiency. In human β-cells loss of SLC30A8 leads to increased glucose responsiveness and reduced KATP channel function, which was also seen in isolated islets from carriers of the T2D-protective allele p.Trp325. These data position ZnT8 as an appealing target for treatment aiming at maintaining insulin secretion capacity in T2D.

Type 2 diabetes risk alleles in PAM impact insulin release from human pancreatic β-cells

The molecular mechanisms underpinning susceptibility loci for type 2 diabetes (T2D) remain poorly understood. Coding variants in peptidylglycine α-amidating monooxygenase (PAM) are associated with both T2D risk and insulinogenic index. Here, we demonstrate that the T2D risk alleles impact negatively on overall PAM activity via defects in expression and catalytic function. PAM deficiency results in reduced insulin content and altered dynamics of insulin secretion in a human β-cell model and primary islets from cadaveric donors. Thus, our results demonstrate a role for PAM in β-cell function, and establish molecular mechanisms for T2D risk alleles at this locus.Coding variants in peptidylglycine α-amidating monooxygenase (PAM) associated with type 2 diabetes risk negatively impact overall PAM activity via defects in expression and catalytic function, resulting in reduced insulin content and altered dynamics of insulin secretion.