Targeting metabolism to overcome obesity and related disorders

Globally, increasing rates of obesity and type 2 diabetes signify an urgent need for new treatment options. This thesis sought to explore novel strategies to overcome obesity and diabetes by demonstrating the therapeutic value of targeting mitochondrial uncoupling and investigating the glucose transporter GLUT6 in pancreatic islets. Mitochondrial uncoupling works by decreasing the efficiency by which nutrients are converted to ATP, resulting in a need for greater nutrient oxidation to produce normal amounts of ATP, which may stimulate weight loss. Herein, the mitochondrial uncoupler BAM15 was tested in the db/db mouse model of metabolic disease and compared to current therapies. BAM15 decreased body weight, improved blood glucose homeostasis, and decreased liver steatosis to a similar or greater extent compared to current therapies, including calorie restriction, semaglutide, and rosiglitazone. In particular, BAM15 stands out for its superior effects on blood glucose control compared to calorie restriction, and BAM15 decreases liver steatosis better than semaglutide and rosiglitazone. Following an extensive medicinal chemistry campaign, an isomer of BAM15 that was 2-fold more potent in vitro was identified and named SHC517. In this thesis, SHC517 was demonstrated to be also 2 times more potent than BAM15 in vivo in diet-induced obese mice, in which it safely and effectively reversed obesity and glucose intolerance. The improved potency of this molecule is important because it suggests that SHC517 can be used at a lower dose, which is predicted to result in decreased chances of drug-drug interactions. Herein, we also investigated the glucose transporter GLUT6 as a potential drug target, because GLUT6 expression is upregulated in pancreatic islets of obese mice. Whole-body knockout of GLUT6 in ob/ob mice increased ex vivo glucose-stimulated insulin secretion (GSIS) from isolated islets without affecting body weight, body composition, or glucose tolerance. These data suggested that GLUT6 may have an inhibitory role on islet insulin secretion under high glucose conditions and could be a potential drug target to modulate high glucose-induced insulin secretion. Overall, these findings have identified a potential clinical opportunity for BAM15-related molecules, such as SHC517, as a therapeutic option that targets multiple aspects of metabolic disease, in addition to recognising a potential role for GLUT6 as a drug target in the pancreatic islet

Investigating the Expression and Function of the Glucose Transporter GLUT6 in Obesity

Obesity-related insulin resistance is a highly prevalent and growing health concern, which places stress on the pancreatic islets of Langerhans by increasing insulin secretion to lower blood glucose levels. The glucose transporters GLUT1 and GLUT3 play a key role in glucose-stimulated insulin secretion in human islets, while GLUT2 is the key isoform in rodent islets. However, it is unclear whether other glucose transporters also contribute to insulin secretion by pancreatic islets. Herein, we show that SLC2A6 (GLUT6) is markedly upregulated in pancreatic islets from genetically obese leptin-mutant (ob/ob) and leptin receptor-mutant (db/db) mice, compared to lean controls. Furthermore, we observe that islet SLC2A6 expression positively correlates with body mass index in human patients with type 2 diabetes. To investigate whether GLUT6 plays a functional role in islets, we crossed GLUT6 knockout mice with C57BL/6 ob/ob mice. Pancreatic islets isolated from ob/ob mice lacking GLUT6 secreted more insulin in response to high-dose glucose, compared to ob/ob mice that were wild type for GLUT6. The loss of GLUT6 in ob/ob mice had no adverse impact on body mass, body composition, or glucose tolerance at a whole-body level. This study demonstrates that GLUT6 plays a role in pancreatic islet insulin secretion in vitro but is not a dominant glucose transporter that alters whole-body metabolic physiology in ob/ob mice

Risk measures for direct real estate investments with non-normal or unknown return distributions

The volatility of returns is probably the most widely used risk measure for real estate. This is rather surprising since a number of studies have cast doubts on the view that volatility can capture the manifold risks attached to properties and corresponds to the risk attitude of investors. A central issue in this discussion is the statistical properties of real estate returns—in contrast to neoclassical capital market theory they are mostly non-normal and often unknown, which render many statistical measures useless. Based on a literature review and an analysis of data from Germany we provide evidence that volatility alone is inappropriate for measuring the risk of direct real estate. We use a unique data sample by IPD, which includes the total returns of 939 properties across different usage types (56% office, 20% retail, 8% others and 16% residential properties) from 1996 to 2009, the German IPD Index, and the German Property Index. The analysis of the distributional characteristics shows that German real estate returns in this period were not normally distributed and that a logistic distribution would have been a better fit. This is in line with most of the current literature on this subject and leads to the question which indicators are more appropriate to measure real estate risks. We suggest that a combination of quantitative and qualitative risk measures more adequately captures real estate risks and conforms better with investor attitudes to risk. Furthermore, we present criteria for the purpose of risk classification

Head-to-head comparison of BAM15, semaglutide, rosiglitazone, NEN, and calorie restriction on metabolic physiology in female <i>db/db</i> mice

Metabolic disorders such as type 2 diabetes, fatty liver disease, hyperlipidemia, and obesity commonly co-occur but clinical treatment options do not effectively target all disorders. Calorie restriction, semaglutide, rosiglitazone, and mitochondrial uncouplers have all demonstrated efficacy against one or more obesity-related metabolic disorders, but it currently remains unclear which therapeutic strategy best targets the combination of hyperglycaemia, liver fat, hypertriglyceridemia, and adiposity. Herein we performed a head-to-head comparison of 5 treatment interventions in the female db/db mouse model of severe metabolic disease. Treatments included ∼60 % calorie restriction (CR), semaglutide, rosiglitazone, BAM15, and niclosamide ethanolamine (NEN). Results showed that BAM15 and CR improved body weight and liver steatosis to levels superior to semaglutide, NEN, and rosiglitazone, while BAM15, semaglutide, and rosiglitazone improved glucose tolerance better than CR and NEN. BAM15, CR, semaglutide, and rosiglitazone all had efficacy against hypertriglyceridaemia. These data provide a comprehensive head-to-head comparison of several key treatment strategies for metabolic disease and highlight the efficacy of mitochondrial uncoupling to correct multiple facets of the metabolic disease milieu in female db/db mice.</p

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Publisher Copyright: © 2022, The Author(s).Background: Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results: To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions: Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk.Peer reviewe

Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

Abstract Background Genetic variants within nearly 1000 loci are known to contribute to modulation of blood lipid levels. However, the biological pathways underlying these associations are frequently unknown, limiting understanding of these findings and hindering downstream translational efforts such as drug target discovery. Results To expand our understanding of the underlying biological pathways and mechanisms controlling blood lipid levels, we leverage a large multi-ancestry meta-analysis (N = 1,654,960) of blood lipids to prioritize putative causal genes for 2286 lipid associations using six gene prediction approaches. Using phenome-wide association (PheWAS) scans, we identify relationships of genetically predicted lipid levels to other diseases and conditions. We confirm known pleiotropic associations with cardiovascular phenotypes and determine novel associations, notably with cholelithiasis risk. We perform sex-stratified GWAS meta-analysis of lipid levels and show that 3–5% of autosomal lipid-associated loci demonstrate sex-biased effects. Finally, we report 21 novel lipid loci identified on the X chromosome. Many of the sex-biased autosomal and X chromosome lipid loci show pleiotropic associations with sex hormones, emphasizing the role of hormone regulation in lipid metabolism. Conclusions Taken together, our findings provide insights into the biological mechanisms through which associated variants lead to altered lipid levels and potentially cardiovascular disease risk