Role of liraglutide in Alzheimer's disease pathology

Background The described relationship between Alzheimer's disease (AD) and type 2 diabetes (T2D) and the fact that AD has no succesful treatment has led to the study of antidiabetic drugs that may limit or slow down AD pathology. Main body Although T2D treatment has evident limitations, options are increasing including glucagon-like peptide 1 analogs. Among these, liraglutide (LRGT) is commonly used by T2D patients to improve beta cell function and suppress glucagon to restore normoglycaemia. Interestingly, LRGT also counterbalances altered brain metabolism and has anti-inflammatory properties. Previous studies have reported its capacity to reduce AD pathology, including amyloid production and deposition, tau hyperphosphorylation, or neuronal and synaptic loss in animal models of AD, accompanied by cognitive improvement. Given the beneficial effects of LRGT at central level, studies in patients have been carried out, showing modest beneficial effects. At present, the ELAD trial (Evaluating Liraglutide in Alzheimer's Disease NCT01843075) is an ongoing phase IIb study in patients with mild AD. In this minireview, we resume the outcomes of LRGT treatment in preclinical models of AD as well as the available results in patients up to date. Conclusion The effects of LRGT on animal models show significant benefits in AD pathology and cognitive impairment. While studies in patients are limited, ongoing clinical trials will probably provide more definitive conclusions on the role of LRGT in AD patients

Discovering context-specific relationships from biological literature by using multi-level context terms

<p>Abstract</p> <p>Background</p> <p>The Swanson's ABC model is powerful to infer hidden relationships buried in biological literature. However, the model is inadequate to infer relations with context information. In addition, the model generates a very large amount of candidates from biological text, and it is a semi-automatic, labor-intensive technique requiring human expert's manual input. To tackle these problems, we incorporate context terms to infer relations between AB interactions and BC interactions.</p> <p>Methods</p> <p>We propose 3 steps to discover meaningful hidden relationships between drugs and diseases: 1) multi-level (gene, drug, disease, symptom) entity recognition, 2) interaction extraction (drug-gene, gene-disease) from literature, 3) context vector based similarity score calculation. Subsequently, we evaluate our hypothesis with the datasets of the "Alzheimer's disease" related 77,711 PubMed abstracts. As golden standards, PharmGKB and CTD databases are used. Evaluation is conducted in 2 ways: first, comparing precision of the proposed method and the previous method and second, analysing top 10 ranked results to examine whether highly ranked interactions are truly meaningful or not.</p> <p>Results</p> <p>The results indicate that context-based relation inference achieved better precision than the previous ABC model approach. The literature analysis also shows that interactions inferred by the context-based approach are more meaningful than interactions by the previous ABC model.</p> <p>Conclusions</p> <p>We propose a novel interaction inference technique that incorporates context term vectors into the ABC model to discover meaningful hidden relationships. By utilizing multi-level context terms, our model shows better performance than the previous ABC model.</p

Hunter disease eClinic: interactive, computer-assisted, problem-based approach to independent learning about a rare genetic disease

<p>Abstract</p> <p>Background</p> <p>Computer-based teaching (CBT) is a well-known educational device, but it has never been applied systematically to the teaching of a complex, rare, genetic disease, such as Hunter disease (MPS II).</p> <p>Aim</p> <p>To develop interactive teaching software functioning as a virtual clinic for the management of MPS II.</p> <p>Implementation and Results</p> <p>The <it>Hunter disease eClinic</it>, a self-training, user-friendly educational software program, available at the Lysosomal Storage Research Group (<url>http://www.lysosomalstorageresearch.ca</url>), was developed using the Adobe Flash multimedia platform. It was designed to function both to provide a realistic, interactive virtual clinic and instantaneous access to supporting literature on Hunter disease. The <it>Hunter disease eClinic </it>consists of an <it>eBook </it>and an <it>eClinic</it>. The <it>eClinic </it>is the interactive virtual clinic component of the software. Within an environment resembling a real clinic, the trainee is instructed to perform a medical history, to examine the patient, and to order appropriate investigation. The program provides clinical data derived from the management of actual patients with Hunter disease. The <it>eBook </it>provides instantaneous, electronic access to a vast collection of reference information to provide detailed background clinical and basic science, including relevant biochemistry, physiology, and genetics. In the <it>eClinic</it>, the trainee is presented with quizzes designed to provide immediate feedback on both trainee effectiveness and efficiency. User feedback on the merits of the program was collected at several seminars and formal clinical rounds at several medical centres, primarily in Canada. In addition, online usage statistics were documented for a 2-year period. Feedback was consistently positive and confirmed the practical benefit of the program. The online English-language version is accessed daily by users from all over the world; a Japanese translation of the program is also available.</p> <p>Conclusions</p> <p>The Hunter disease <it>eClinic </it>employs a CBT model providing the trainee with realistic clinical problems, coupled with comprehensive basic and clinical reference information by instantaneous access to an electronic textbook, the <it>eBook</it>. The program was rated highly by attendees at national and international presentations. It provides a potential model for use as an educational approach to other rare genetic diseases.</p

Vaccination against GIP for the Treatment of Obesity

BACKGROUND: According to the WHO, more than 1 billion people worldwide are overweight and at risk of developing chronic illnesses, including cardiovascular disease, type 2 diabetes, hypertension and stroke. Current therapies show limited efficacy and are often associated with unpleasant side-effect profiles, hence there is a medical need for new therapeutic interventions in the field of obesity. Gastric inhibitory peptide (GIP, also known as glucose-dependent insulinotropic polypeptide) has recently been postulated to link over-nutrition with obesity. In fact GIP receptor-deficient mice (GIPR(-/-)) were shown to be completely protected from diet-induced obesity. Thus, disrupting GIP signaling represents a promising novel therapeutic strategy for the treatment of obesity. METHODOLOGY/PRINCIPAL FINDINGS: In order to block GIP signaling we chose an active vaccination approach using GIP peptides covalently attached to virus-like particles (VLP-GIP). Vaccination of mice with VLP-GIP induced high titers of specific antibodies and efficiently reduced body weight gain in animals fed a high fat diet. The reduction in body weight gain could be attributed to reduced accumulation of fat. Moreover, increased weight loss was observed in obese mice vaccinated with VLP-GIP. Importantly, despite the incretin action of GIP, VLP-GIP-treated mice did not show signs of glucose intolerance. CONCLUSIONS/SIGNIFICANCE: This study shows that vaccination against GIP was safe and effective. Thus active vaccination may represent a novel, long-lasting treatment for obesity. However further preclinical safety/toxicology studies will be required before the therapeutic concept can be addressed in humans

Proteomic profiling of Burkholderia cenocepacia clonal isolates with different virulence potential retrieved from a cystic fibrosis patient during chronic lung infection

Respiratory infections with Burkholderia cepacia complex (Bcc) bacteria in cystic fibrosis (CF) are associated with a worse prognosis and increased risk of death. In this work, we assessed the virulence potential of three B. cenocepacia clonal isolates obtained from a CF patient between the onset of infection (isolate IST439) and before death with cepacia syndrome 3.5 years later (isolate IST4113 followed by IST4134), based on their ability to invade epithelial cells and compromise epithelial monolayer integrity. The two clonal isolates retrieved during late-stage disease were significantly more virulent than IST439. Proteomic profiling by 2-D DIGE of the last isolate recovered before the patient's death, IST4134, and clonal isolate IST439, was performed and compared with a prior analysis of IST4113 vs. IST439. The cytoplasmic and membrane-associated enriched fractions were examined and 52 proteins were found to be similarly altered in the two last isolates compared with IST439. These proteins are involved in metabolic functions, nucleotide synthesis, translation and protein folding, cell envelope biogenesis and iron homeostasis. Results are suggestive of the important role played by metabolic reprogramming in the virulence potential and persistence of B. cenocepacia, in particular regarding bacterial adaptation to microaerophilic conditions. Also, the content of the virulence determinant AidA was higher in the last 2 isolates. Significant levels of siderophores were found to be secreted by the three clonal isolates in an iron-depleted environment, but the two late isolates were more tolerant to low iron concentrations than IST439, consistent with the relative abundance of proteins involved in iron uptake.This work was supported by FEDER and FCT – Fundação para a Ciência e a Tecnologia (contract PEst-OE/EQB/LA0023/2011_ research line: Systems and Synthetic Biology; PhD grant to A.M. – SFRH/BD/37012/2007, and PD grants to S.S. – SFRH/BPD/75483/2010 and C.C. – SFRH/BPD/ 81220/2011. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Mechanisms Underlying Insulin Deficiency-Induced Acceleration of β-Amyloidosis in a Mouse Model of Alzheimer's Disease

Although evidence is accumulating that diabetes mellitus is an important risk factor for sporadic Alzheimer's disease (AD), the mechanisms by which defects in insulin signaling may lead to the acceleration of AD progression remain unclear. In this study, we applied streptozotocin (STZ) to induce experimental diabetes in AD transgenic mice (5XFAD model) and investigated how insulin deficiency affects the β-amyloidogenic processing of amyloid precursor protein (APP). Two and half months after 5XFAD mice were treated with STZ (90 mg/kg, i.p., once daily for two consecutive days), they showed significant reductions in brain insulin levels without changes in insulin receptor expression. Concentrations of cerebral amyloid-β peptides (Aβ40 and Aβ42) were significantly increased in STZ-treated 5XFAD mice as compared with vehicle-treated 5XFAD controls. Importantly, STZ-induced insulin deficiency upregulated levels of both β-site APP cleaving enzyme 1 (BACE1) and full-length APP in 5XFAD mouse brains, which was accompanied by dramatic elevations in the β-cleaved C-terminal fragment (C99). Interestingly, BACE1 mRNA levels were not affected, whereas phosphorylation of the translation initiation factor eIF2α, a mechanism proposed to mediate the post-transcriptional upregulation of BACE1, was significantly elevated in STZ-treated 5XFAD mice. Meanwhile, levels of GGA3, an adapter protein responsible for sorting BACE1 to lysosomal degradation, are indistinguishable between STZ- and vehicle-treated 5XFAD mice. Moreover, STZ treatments did not affect levels of Aβ-degrading enzymes such as neprilysin and insulin-degrading enzyme (IDE) in 5XFAD brains. Taken together, our findings provide a mechanistic foundation for a link between diabetes and AD by demonstrating that insulin deficiency may change APP processing to favor β-amyloidogenesis via the translational upregulation of BACE1 in combination with elevations in its substrate, APP

Gastric inhibitory polypeptide receptor: association analyses for obesity of several polymorphisms in large study groups

<p>Abstract</p> <p>Background</p> <p>Gastric inhibitory polypeptide (GIP) is postulated to be involved in type 2 diabetes mellitus and obesity. It exerts its function through its receptor, GIPR. We genotyped three <it>GIPR </it>SNPs (rs8111428, rs2302382 and rs1800437) in German families with at least one obese index patient, two case-control studies and two cross-sectional population-based studies.</p> <p>Methods</p> <p>Genotyping was performed by MALDI-TOF, ARMS-PCR and RFLP. The family-study: 761 German families with at least one extremely obese child or adolescent (n = 1,041) and both parents (n = 1,522). Case-control study: (a) German obese children (n = 333) and (b) obese adults (n = 987) in comparison to 588 adult lean controls. The two cross-sectional population-based studies: KORA (n = 8,269) and SHIP (n = 4,310).</p> <p>Results</p> <p>We detected over-transmission of the A-allele of rs2302382 in the German families (p_TDT-Test= 0.0089). In the combined case-control sample, we estimated an odd ratio of 1.54 (95%CI 1.09;2.19, p_CA-Test= 0.014) for homozygotes of the rs2302382 A-allele compared to individuals with no A-allele. A similar trend was found in KORA where the rs2302382 A-allele led to an increase of 0.12 BMI units (p = 0.136). In SHIP, however, the A-allele of rs2302382 was estimated to contribute an average decrease of 0.27 BMI units (p-value = 0.031).</p> <p>Conclusion</p> <p>Our data suggest a potential relevance of <it>GIPR </it>variants for obesity. However, additional studies are warranted in light of the conflicting results obtained in one of the two population-based studies.</p

Reduced phosphorylation of brain insulin receptor substrate and Akt proteins in apolipoprotein-E4 targeted replacement mice

10.1038/srep03754Scientific Reports4

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned