Gene-Network Analysis Identifies Susceptibility Genes Related to Glycobiology in Autism

The recent identification of copy-number variation in the human genome has opened up new avenues for the discovery of positional candidate genes underlying complex genetic disorders, especially in the field of psychiatric disease. One major challenge that remains is pinpointing the susceptibility genes in the multitude of disease-associated loci. This challenge may be tackled by reconstruction of functional gene-networks from the genes residing in these loci. We applied this approach to autism spectrum disorder (ASD), and identified the copy-number changes in the DNA of 105 ASD patients and 267 healthy individuals with Illumina Humanhap300 Beadchips. Subsequently, we used a human reconstructed gene-network, Prioritizer, to rank candidate genes in the segmental gains and losses in our autism cohort. This analysis highlighted several candidate genes already known to be mutated in cognitive and neuropsychiatric disorders, including RAI1, BRD1, and LARGE. In addition, the LARGE gene was part of a sub-network of seven genes functioning in glycobiology, present in seven copy-number changes specifically identified in autism patients with limited co-morbidity. Three of these seven copy-number changes were de novo in the patients. In autism patients with a complex phenotype and healthy controls no such sub-network was identified. An independent systematic analysis of 13 published autism susceptibility loci supports the involvement of genes related to glycobiology as we also identified the same or similar genes from those loci. Our findings suggest that the occurrence of genomic gains and losses of genes associated with glycobiology are important contributors to the development of ASD

Reversal of Obesity and Insulin Resistance by a Non-Peptidic Glucagon-Like Peptide-1 Receptor Agonist in Diet-Induced Obese Mice

BACKGROUND: Glucagon-like peptide-1 (GLP-1) is recognized as an important regulator of glucose homeostasis. Efforts to utilize GLP-1 mimetics in the treatment of diabetes have yielded clinical benefits. A major hurdle for an effective oral therapy has been the difficulty of finding a non-peptidic GLP-1 receptor (GLP-1R) agonist. While its oral bioavailability still poses significant challenges, Boc5, one of the first such compounds, has demonstrated the attainment of GLP-1R agonism in diabetic mice. The present work was to investigate whether subchronic Boc5 treatment can restore glycemic control and induce sustainable weight loss in diet-induced obese (DIO) mice, an animal model of human obesity and insulin resistance. METHODOLOGY/PRINCIPAL FINDINGS: DIO mice were treated three times a week with Boc5 (0.3, 1 and 3 mg) for 12 weeks. Body weight, body mass index (BMI), food intake, fasting glucose, intraperitoneal glucose tolerance and insulin induced glucose clearance were monitored regularly throughout the treatment. Glucose-stimulated insulin secretion, β-cell mass, islet size, body composition, serum metabolic profiles, lipogenesis, lipolysis, adipose hypertrophy and lipid deposition in the liver and muscle were also measured after 12 weeks of dosing. Boc5 dose-dependently reduced body weight, BMI and food intake in DIO mice. These changes were associated with significant decreases in fat mass, adipocyte hypertrophy and peripheral tissue lipid accumulation. Boc5 treatment also restored glycemic control through marked improvement of insulin sensitivity and normalization of β-cell mass. Administration of Boc5 (3 mg) reduced basal but enhanced insulin-mediated glucose incorporation and noradrenaline-stimulated lipolysis in isolated adipocytes from obese mice. Furthermore, circulating leptin, adiponectin, triglyceride, total cholesterol, nonesterified fatty acid and high-density lipoprotein/low-density lipoprotein ratio were normalized to various extents by Boc5 treatment. CONCLUSIONS/SIGNIFICANCE: Boc5 may produce metabolic benefits via multiple synergistic mechanisms and may represent an attractive tool for therapeutic intervention of obesity and diabetes, by means of non-peptidic GLP-1R agonism

The Danish Myelodysplastic Syndromes Database: Patient Characteristics and Validity of Data Records

Tine Bichel Lauritsen,1 Jan Maxwell Nørgaard,1 Kirsten Grønbæk,2– 4 Anders Pommer Vallentin,5 Syed Azhar Ahmad,6 Louise Hur Hannig,7 Marianne Tang Severinsen,8,9 Kasper Adelborg,10,11 Lene Sofie Granfeldt Østgård11,12 1Department of Hematology, Aarhus University Hospital, Aarhus, Denmark; 2Department of Hematology, Rigshospitalet, Copenhagen, Denmark; 3Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark; 4Novo Nordisk Foundation Center for Stem Cell Biology (DanStem), Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark; 5Zealand University Hospital, Roskilde, Denmark; 6Department of Hematology, Herlev Hospital, Herlev, Denmark; 7Department of Hematology, Vejle Hospital, Vejle, Denmark; 8Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Aalborg, Denmark; 9Department of Clinical Medicine, Aalborg University, Aalborg, Denmark; 10Department of Clinical Biochemistry, Aarhus University Hospital, Aarhus, Denmark; 11Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 12Department of Hematology, Odense University Hospital, Odense, DenmarkCorrespondence: Tine Bichel LauritsenDepartment of Hematology, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, Aarhus N, 8200 Email [email protected]: The Danish Myelodysplastic Syndromes Database (DMDSD) comprises nearly all patients diagnosed with myelodysplastic syndromes (MDS) in Denmark since 2010. The DMDSD has not yet been used for epidemiological research and the quality of registered variables remains to be investigated.Objective: To describe characteristics of the patients registered in the DMDSD and to calculate predictive values and the proportion of missing values of registered data records.Methods: We performed a nationwide cross-sectional validation study of recorded disease and treatment data on MDS patients during 2010– 2019. Patient characteristics and the proportion of missing values were tabulated. A random sample of 12% was drawn to calculate predictive values with 95% confidence intervals (CIs) of 48 variables using information from medical records as a reference standard.Results: Overall, 2284 patients were identified (median age: 76 years, men 62%). Of these, 10% had therapy-related MDS, and 6% had an antecedent hematological disease. Hemoglobin level was less than 6.2 mmol/L for 59% of patients. Within the first two years of treatment, 59% received transfusions, 35% received erythropoiesis-stimulating agents, and 15% were treated with a hypomethylating agent. For the majority of variables (around 80%), there were no missing data. A total of 260 medical records were available for validation. The positive predictive value of the MDS diagnosis was 92% (95% CI: 88– 95). Predictive values ranged from 64% to 100% and exceeded 90% for 36 out of 48 variables. Stratification by year of diagnosis suggested that the positive predictive value of the MDS diagnosis improved from 88% before 2015 to 95% after.Conclusion: In this study, there was a high accuracy of recorded data and a low proportion of missing data. Thus, the DMDSD serves as a valuable data source for future epidemiological studies on MDS.Keywords: myelodysplastic syndromes, cohort, validation, accuracy, databas