Budget impact analysis of continuous glucose monitoring in individuals with type 2 diabetes on insulin treatment in England.

INTRODUCTION: In 2022, updated guidance from NICE expanded the options for self-monitoring of blood glucose for patients with type 2 diabetes (T2DM), to include continuous glucose monitoring (CGM). In this budget impact analysis, the cost impact of CGM was compared with traditional self-monitoring of blood glucose (SMBG) in adults with T2DM over 1 year from the commissioner perspective in England. RESEARCH DESIGN AND METHODS: The NICE-eligible T2DM cohort was split into 4 subgroups to enable nuanced costing by insulin administration frequency: basal human insulin, premixed insulin, basal-bolus insulin and bolus insulin. The model's cost components comprised mild and severe hypoglycaemia (SH), diabetic ketoacidosis (DKA), consumables and healthcare resource utilisation in primary and secondary care. RESULTS: The introduction of CGM is estimated to be cost additive by approximately £4.6 million in the basecase, driven by increased spending on the CGM device. Overall, healthcare activity was reduced by approximately 20,000 attendances, due to fewer SH and DKA episodes in the CGM arm. General Practitioner (GP) practice-based activity is expected to drop after the first year as patients requiring CGM training is reduced. The budget impact could be neutralised if the CGM sensor was discounted by 13.2% (£29.76 to £25.83). CONCLUSIONS: CGM may result in increased spending in the NICE-eligible T2DM cohort but is expected to reduce demand on secondary care services and GP time. These findings may be of interest to local decision-makers who wish to resolve the COVID-19 backlog with transformational investment in primary care to reduce secondary care activity.

Provision of Bilingual Dispensing Labels to Non-Native English Speakers: An Exploratory Study.

Patients with limited English proficiency living in the U.K. receive prescribed medication labels in English. These patients are at risk of worse health outcomes compared with the general population. This article describes a service evaluation of the use of bilingual dispensing labels to facilitate patient understanding of medicine administration instructions. Recruited patients answered two questionnaires to assess engagement with and understanding of their medicine labels. The first was completed at the point of dispensing, and the second within six weeks. Questionnaires were either self-completed or via facilitation over the telephone. A total of 151 participants completed the first questionnaire, and 130 completed the follow-up. Key findings highlighted the lack of engagement by participants with English-language labels and their reliance on asking for help from pharmacy staff, friends, or family to understand the information. However, when provided with information in their preferred language, they reported high levels of understanding and sought help less frequently from a third party. This study has shown that this service has improved understanding of labelling information in this target group.

Multiplex immunoassay analysis of plasma shows differences in biomarkers related to manic or mixed mood states in bipolar disorder patients.

BACKGROUND: The molecular understanding of bipolar disorder (BD) aetiology has advanced over the last years through the identification of peripheral disease biomarkers. Here, we have attempted to identify plasma biomarkers associated with distinct BD mood states. METHODS: Plasma from BD patients with either a current manic (n=29) or mixed (n=17) mood state and healthy controls (n=53) were analysed using a multiplex immunoassay platform. A total of 145 hormones, growth factors, transport proteins and inflammatory factors were measured. RESULTS: Plasma levels of the hormones C-peptide, progesterone and insulin, and the inflammatory protein cancer antigen 125 were altered in both mood states. The hormone peptide YY and the growth factor trafficking protein sortilin were changed only in mania patients. Finally, the inflammatory factors haptoglobin, chemokine CC4 and matrix metalloproteinase 7 were altered specifically in mixed mood patients. LIMITATIONS: This study was limited by a small sample size, potential confounding effects of multiple drug treatments in the patient groups, and lack of dietary restrictions at sampling. CONCLUSIONS: Plasma from mania and mixed mood BD patients revealed similar changes in proteins related to insulin signalling, suggesting that these could be trait biomarkers. However, mania patients showed specific changes in hormonal and growth factor functions and mixed mood patients had a higher number of changes in inflammation-related molecules. Further studies of these and other biomarker candidates will increase our understanding of the systemic biological pathways affected in different BD mood states. This could lead to the identification of differential surrogate readouts and potential new drug targets for improved treatment outcomes.

Distinct proteomic profiles in post-mortem pituitary glands from bipolar disorder and major depressive disorder patients.

Disturbances of the hypothalamic-pituitary-adrenal axis have been implicated in the pathophysiology of bipolar disorder (BD) and major depressive disorder (MDD). To examine this further, we carried out proteomic profiling of post-mortem pituitaries from 13 BD and 14 MDD patients, in comparison to 15 controls. Liquid chromatography-mass spectrometry (LC-MS(E)) analysis showed that BD patients had significantly increased levels of the major pituitary hormones pro-opiomelanocortin (POMC) and galanin. BD patients also showed changes in proteins associated with gene transcription, stress response, lipid metabolism and growth signalling. In contrast, LC-MS(E) profiling revealed that MDD patients had significantly decreased levels of the prohormone-converting enzyme carboxypeptidease E and follow-up enzymatic analysis showed decreased activity of prolyl-oligopeptidase convertase. This suggested that altered prohormone processing may occur in pituitaries of MDD patients. In addition, MDD patients had significant changes in proteins involved in intracellular transport and cytoskeletal signalling. Finally, we carried out selective reaction monitoring (SRM) mass spectrometry profiling for validation of protein changes in key biological pathways. This confirmed increased POMC levels in BD patients with no change in the levels of this prohormone in MDD. This study demonstrates that proteomic profiling analysis of the pituitary can lead to new insights into the pathophysiology of BD and MDD. Also, given that the pituitary directly releases a variety of bioactive molecules into the bloodstream, many of the proteins identified here could serve as focal points in the search for peripheral biomarkers in clinical or drug treatment studies of BD and MDD patients.

Multiplex immunoassay analysis of plasma shows prominent upregulation of growth factor activity pathways linked to GSK3ß signaling in bipolar patients.

BACKGROUND: Our understanding of bipolar disorder (BD) aetiology has advanced in recent years but our ability to translate this to improve patient care in the clinic is still limited. METHODS: In this study, we have measured the concentrations of 190 different molecules using sensitive multiplex immunoassays in plasma of 17 BD patients compared to 46 matched control subjects. RESULTS: The analyses led to the identification of 26 dysregulated proteins in BD patients compared to controls. These molecules were comprised mostly of growth factors, hormones, lipid transport and inflammatory proteins. Decreased apolipoprotein A1 has previously been associated with BD patients and this was confirmed in our study. LIMITATIONS: The present pilot study was limited by its small sample size, use of multiple drug treatments and the lack of dietary restrictions at the time of sampling. CONCLUSIONS: Future studies may increase our understanding of BD which will help to pave the way for much-needed patient stratification for better treatment outcomes.

Application of meta-analysis methods for identifying proteomic expression level differences.

We present new statistical approaches for identification of proteins with expression levels that are significantly changed when applying meta-analysis to two or more independent experiments. We showed that the Euclidean distance measure has reduced risk of false positives compared to the rank product method. Our Ψ-ranking method has advantages over the traditional fold-change approach by incorporating both the fold-change direction as well as the p-value. In addition, the second novel method, Π-ranking, considers the ratio of the fold-change and thus integrates all three parameters. We further improved the latter by introducing our third technique, Σ-ranking, which combines all three parameters in a balanced nonparametric approach.

Proteomic profiling in schizophrenia: enabling stratification for more effective treatment.

Schizophrenia is a heterogeneous psychiatric disorder characterized by an array of clinical manifestations. Although the best known manifestations include serious effects on mood and behavior, patients can also display co-morbidities, including immune system or metabolic abnormalities. Thorough characterization of these conditions using proteomic profiling methods has increased our knowledge of these molecular differences and has helped to unravel the complexity and heterogeneity of this debilitating condition. This could lead to patient stratification through characterization of biochemically different subtypes of the disease. In addition, proteomic methods have recently been used for molecular characterization of the mechanism of action of antipsychotic medications in both preclinical models and patients. This has resulted in identification of molecular panels that show some promise for prediction of response or for monitoring treatment outcome. This review describes how proteomic profiling methods can impact the future of schizophrenia diagnosis and therapeutics, and facilitate personalized medicine approaches for more effective treatment management of schizophrenia patients.

Challenges in drug target discovery in bipolar disorder.

INTRODUCTION: Misdiagnosis and subsequent inappropriate treatment of patients with bipolar disorder (BD) can worsen their clinical condition and outcome. AREAS COVERED: This review focuses on the therapeutic targets which have been implicated in BD, including the glycogen synthase kinase 3 (GSK-3) and phosphoinositide signaling pathways. In addition, evidence is presented for potential new molecular strategies which involve targeting neuropeptide-converting endopeptidases, glutamatergic excitotoxicity, insulin signaling and dysfunctions in mitochondrial metabolism. Current limitations in study design, molecular platforms, preclinical and cellular models in the context of BD drug target discovery, suggest that there are many areas for improvement. EXPERT OPINION: For the future outlook, this review outlines the importance of developments such as the use of BD patient-derived cellular models for providing better understanding of the BD etiology and robust translational drug screening tools in combination with developments in the fields of bioinformatics and systems biology.

Analysis of serum and plasma identifies differences in molecular coverage, measurement variability, and candidate biomarker selection.

PURPOSE: To compare the use of serum and plasma in multiplex immunoassay analyses of 190 proteins and small molecules, and associated molecular pathways. We also tested whether differences between these biofluids can influence the identification of potential biomarkers in a preliminary study comparing bipolar disorder patients with controls. EXPERIMENTAL DESIGN: Using multiplexed immunoassay analyses, we compared the measurement levels and interindividual variation of 190 proteins and small molecules between serum and plasma collected from 21 healthy individuals. We exemplify how this can impact on the outcome of biomarker discovery studies using a case study of 24 patients with bipolar disorder. RESULTS: Detection of analytes was similar for serum and plasma, although there were marked differences in measurement variability for 29 proteins and cortisol. When considering the disease cohort we identified six proteins that changed significantly in serum and ten in plasma with an overlap of two proteins. CONCLUSIONS AND CLINICAL RELEVANCE: In spite of the similarities of coverage on a multiplexed platform for serum and plasma, there were important differences in interindividual variability, which can have significant impact on identifications made in biomarker studies.

The application of selective reaction monitoring confirms dysregulation of glycolysis in a preclinical model of schizophrenia.

BACKGROUND: Establishing preclinical models is essential for novel drug discovery in schizophrenia. Most existing models are characterized by abnormalities in behavioral readouts, which are informative, but do not necessarily translate to the symptoms of the human disease. Therefore, there is a necessity of characterizing the preclinical models from a molecular point of view. Selective reaction monitoring (SRM) has already shown promise in preclinical and clinical studies for multiplex measurement of diagnostic, prognostic and treatment-related biomarkers. METHODS: We have established an SRM assay for multiplex analysis of 7 enzymes of the glycolysis pathway which is already known to be affected in human schizophrenia and in the widely-used acute PCP rat model of schizophrenia. The selected enzymes were hexokinase 1 (Hk1), aldolase C (Aldoc), triosephosphate isomerase (Tpi1), glyceraldehyde-3-phosphate dehydrogenase (Gapdh), phosphoglycerate mutase 1 (Pgam1), phosphoglycerate kinase 1 (Pgk1) and enolase 2 (Eno2). The levels of these enzymes were analyzed using SRM in frontal cortex from brain tissue of PCP treated rats. RESULTS: Univariate analyses showed statistically significant altered levels of Tpi1 and alteration of Hk1, Aldoc, Pgam1 and Gapdh with borderline significance in PCP rats compared to controls. Most interestingly, multivariate analysis which considered the levels of all 7 enzymes simultaneously resulted in generation of a bi-dimensional chart that can distinguish the PCP rats from the controls. CONCLUSIONS: This study not only supports PCP treated rats as a useful preclinical model of schizophrenia, but it also establishes that SRM mass spectrometry could be used in the development of multiplex classification tools for complex psychiatric disorders such as schizophrenia.

Differential expression of HINT1 in schizophrenia brain tissue.

Recent findings in the literature suggest a relation between histidine triad nucleotide-binding protein-1 (HINT1) and psychiatric disorders such as major depression, anxiety, and schizophrenia, although its physiological roles are not completely comprehended. Using Western blot, we compared HINT1 protein expression in the postmortem dorsolateral prefrontal cortex and thalamus of schizophrenia patients and healthy controls for contributing to elucidate the role of HINT1 in schizophrenia pathophysiology. HINT1 was found to be downregulated in the dorsolateral prefrontal cortex and upregulated in the thalamus. Our results combined to previous studies in human samples and preclinical models support the notion that HINT1 must be more explored as a potential target for psychiatric disorders.

Behavioral and molecular biomarkers in translational animal models for neuropsychiatric disorders.

Modeling neuropsychiatric disorders in animals poses a significant challenge due to the subjective nature of diverse often overlapping symptoms, lack of objective biomarkers and diagnostics, and the rudimentary understanding of the pathophysiology. Successful translational research requires animal models that can inform about disease mechanisms and therapeutic targets. Here, we review behavioral and neurobiological findings from selected animal models, based on presumed etiology and risk factors, for schizophrenia, bipolar disorder, and major depressive disorder. We focus on the use of appropriate statistical tools and newly developed Research Domain Criteria (RDoC) to link biomarkers from animal models with the human disease. We argue that this approach will lead to development of only the most robust animal models for specific psychiatric disorders and may ultimately lead to better understanding of the pathophysiology and identification of novel biomarkers and therapeutic targets.

Translating potential biomarker candidates for schizophrenia and depression to animal models of psychiatric disorders.

Schizophrenia and major depressive disorder are severe mental illnesses, which are diagnosed based on patient interviews. Despite many years of extensive research, scientists have not yet fully deciphered how genetic and environmental factors interact to cause these illnesses. Biomarker tests that can confirm diagnoses of schizophrenia or depression are only now beginning to emerge, and could result in a paradigm shift in this field. These tests will help to evaluate the validity of animal models of psychiatric disorders, which are currently characterized based on behavioral measures. In this article, we explore the utility of translating both behavioral and molecular phenotypes of such models to the corresponding human disorders. This approach may help to provide construct validity to animal models and could lead to the identification of models corresponding to defined subtypes of neuropsychiatric disorders based on molecular profiles. Here, we review the molecular and biological pathway alterations that have been found in animal models of schizophrenia and depression and focus on those that are mirrored by similar abnormalities in human patients. Such parallels may provide insight into the validity of specific animal models and therefore help to provide more valuable and accurate tools for the discovery and development of improved psychiatric medications.