Aims/hypothesis Metabolomics approaches in humans have identified around 40 plasma metabolites associated with insulin resistance (IR) and type 2 diabetes, which often coincide with those for obesity. We aimed to separate diabetesassociated from obesity-associated metabolite alterations in plasma and study the impact of metabolically important tissues on plasma metabolite concentrations. Methods Two obese mouse models were studied; one exclusively with obesity (ob/ob) and another with type 2 diabetes (db/db). Both models have impaired leptin signalling as a cause for obesity, but the different genetic backgrounds determine the susceptibility to diabetes. In these mice, we profiled plasma, liver, skeletal muscle and adipose tissue via semiquantitative GC-MS and quantitative liquid chromatography (LC)-MS/MS for a wide range of metabolites. Results Metabolite profiling identified 24 metabolites specifically associated with diabetes but not with obesity. Among these are known markers such as 1,5-anhydro-D-sorbitol, 3-hydroxybutyrate and the recently reported marker glyoxylate. New metabolites in the diabetic model were lysine, Ophosphotyrosine and branched-chain fatty acids. We also identified 33 metabolites that were similarly altered in both models, represented by branched-chain amino acids (BCAA) as well as glycine, serine, trans-4-hydroxyproline, and various lipid species and derivatives. Correlation analyses showed stronger associations for plasma amino acids with adipose tissue metabolites in db/db mice compared with ob/ob mice, suggesting a prominent contribution of adipose tissue to changes in plasma in a diabetic state. Conclusions/interpretation By studying mice with metabolite signatures that resemble obesity and diabetes in humans, we have found new metabolite entities for validation in appropriate human cohorts and revealed their possible tissue of origin.
ObjectiveThe objective of the current study was to find a metabolic signature associated with the early manifestations of type-2 diabetes mellitus.Research Design and MethodModern metabolic profiling technology (MxP™ Broad Profiling) was applied to find early alterations in the plasma metabolome of type-2 diabetic patients. The results were validated in an independent study. Eicosanoid and single inon monitoring analysis (MxP™ Eicosanoid and MxP™ SIM analysis) were performed in subsets of samples.ResultsA metabolic signature including significantly increased levels of glyoxylate as a potential novel marker for early detection of type-2 diabetes mellitus was identified in an initial study (Study1). The signature was significantly altered in fasted diabetic and pre-diabetic subjects and in non-fasted subjects up to three years prior to the diagnosis of type-2 diabetes; most alterations were also consistently found in an independent patient group (Study 2). In Study 2 diabetic and most control subjects suffered from heart failure. In Study 1 a subgroup of diabetic subjects, with a history of use of anti-hypertensive medication further showed a more pronounced increase of glyoxylate levels, compared to a non-diabetic control group when tested in a hyperglycemic state. In the context of a prior history of anti-hypertensive medication, alterations in hexosamine and eicosanoid levels were also found.ConclusionA metabolic signature including glyoxylate was associated with type-2 diabetes mellitus, independent of the fasting status and of occurrence of another major disease. The same signature was also found to be associated with pre-diabetic subjects. Glyoxylate levels further showed a specifically strong increase in a subgroup of diabetic subjects. It could represent a new marker for the detection of medical subgroups of diabetic subjects.
Introduction: Detailed data on the long-term consequences and treatment of stroke are scarce. We aimed to assess the needs and disease burden of community-dwelling stroke patients and their carers and to compare their treatment to evidence-based guidelines by a stroke neurologist. Methods: We invited long-term stroke patients from two previous acute clinical studies (n ¼ 516) in Berlin, Germany to participate in an observational, cross-sectional study. Participants underwent a comprehensive interview and examination using the Post-Stroke Checklist and validated standard measures of: self-reported needs, quality of life, overall outcome, spasticity, pain, aphasia, cognition, depression, secondary prevention, social needs and caregiver burden. Results: Fifty-seven participants (median initial National Institutes of Health Stroke Scale score 10 interquartile range 4-12.75) consented to assessment (median 41 months (interquartile range 36-50) after stroke. Modified Rankin Scale was 2 (median; interquartile range 1-3), EuroQoL index value was 0.81 (median; interquartile range 0.70-1.00). The frequencies for disabilities in the major domains were: spasticity 35%; cognition 61%; depression 20%; medication noncompliance 14%. Spasticity (p ¼ 0.008) and social needs (p < 0.001) had the strongest impact on quality of life. The corresponding items in the Post-Stroke Checklist were predictive for low mood (p < 0.001), impaired cognition (p ¼ 0.015), social needs (p ¼ 0.005) and caregiver burden (p ¼ 0.031). In the comprehensive interview, we identified the following needs: medical review (30%), optimization of pharmacotherapy (18%), outpatient therapy (47%) and social work input (33%). Conclusion: These results suggest significant unmet needs and gaps in health and social care in long-term stroke patients. Further research to develop a comprehensive model for managing stroke aftercare is warranted. Clinical Trial Registration: clinicaltrials.gov NCT02320994.
BackgroundPrevious studies examining social work interventions in stroke often lack information on content, methods and timing over different phases of care including acute hospital, rehabilitation and out-patient care. This limits our ability to evaluate the impact of social work in multidisciplinary stroke care.We aimed to quantify social-work-related support in stroke patients and their carers in terms of timing and content, depending on the different phases of stroke care.MethodsWe prospectively collected and evaluated data derived from a specialized “Stroke-Service-Point” (SSP); a “drop in” center and non-medical stroke assistance service, staffed by social workers and available to all stroke patients, their carers and members of the public in the metropolitan region of Berlin, Germany.ResultsEnquiries from 257 consenting participants consulting the SSP between March 2010 and April 2012 related to out-patient and in-patient services, therapeutic services, medical questions, medical rehabilitation, self-help groups and questions around obtaining benefits. Frequency of enquiries for different topics depended on whether patients were located in an in-patient or out-patient setting. The majority of contacts involved information provision. While the proportion of male and female patients with stroke was similar, about two thirds of the carers contacting the SSP were female.ConclusionThe social-work-related services provided by a specialized center in a German metropolitan area were diverse in terms of topic and timing depending on the phase of stroke care. Targeting the timing of interventions might be important to increase the impact of social work on patient’s outcome.Electronic supplementary materialThe online version of this article (doi:10.1186/s12883-016-0626-z) contains supplementary material, which is available to authorized users.
The SH2-containing inositol 5'-phosphatase, SHIP1, negatively regulates signal transduction from the B cell antigen receptor (BCR). The mode of coupling between SHIP1 and the BCR has not been elucidated so far. In comparison to wild-type cells, B cells expressing a mutant IgD- or IgM-BCR containing a C-terminally truncated Ig-α respond to pervanadate stimulation with markedly reduced tyrosine phosphorylation of SHIP1 and augmented activation of protein kinase B. This indicates that SHIP1 is capable of interacting with the C-terminus of Ig-α. Employing a system of fluorescence resonance energy transfer in S2 cells, we can clearly demonstrate interaction between the SH2-domain of SHIP1 and Ig-α. Furthermore, a fluorescently labeled SH2-domain of SHIP1 translocates to the plasma membrane in an Ig-α-dependent manner. Interestingly, whereas the SHIP1 SH2-domain can be pulled-down with phospho-peptides corresponding to the immunoreceptor tyrosine-based activation motif (ITAM) of Ig-α from detergent lysates, no interaction between full-length SHIP1 and the phosphorylated Ig-α ITAM can be observed. Further studies show that the SH2-domain of SHIP1 can bind to the C-terminus of the SHIP1 molecule, most probably by inter- as well as intra-molecular means, and that this interaction regulates the association between different forms of SHIP1 and Ig-α.
Background Accurate, early diagnosis of type 2 diabetes (T2D) would enable more effective clinical management and a reduction in T2D complications. Therefore, we sought to identify plasma metabolite and protein biomarkers that, in combination with glucose, can better predict future T2D compared with glucose alone. Methods In this case-control study, we used plasma samples from the Bavarian Red Cross Blood Transfusion Center study (61 T2D cases and 78 non-diabetic controls) for discovering T2D-associated metabolites, and plasma samples from the Personalized Medicine Research Project in Wisconsin (56 T2D cases and 445 non-diabetic controls) for validation. All samples were obtained before or at T2D diagnosis. We tested whether the T2D-associated metabolites could distinguish incident T2D cases from controls, as measured by the area under the receiver operating characteristic curve (AUC). Additionally, we tested six metabolic/pro-inflammatory proteins for their potential to augment the ability of the metabolites to distinguish cases from controls. Results A panel of 10 metabolites discriminated better between T2D cases and controls than glucose alone (AUCs: 0.90 vs 0.87; p = 2.08 × 10−5) in Bavarian samples, and associations between these metabolites and T2D were confirmed in Wisconsin samples. With use of either a Bayesian network classifier or ridge logistic regression, the metabolites, with or without the proteins, discriminated incident T2D cases from controls marginally better than glucose in the Wisconsin samples, although the difference in AUCs was not statistically significant. However, when the metabolites and proteins were added to two previously reported T2D prediction models, the AUCs were higher than those of each prediction model alone (AUCs: 0.92 vs 0.87; p = 3.96 × 10−2 and AUCs: 0.91 vs 0.71; p = 1.03 × 10−5, for each model, respectively). Conclusions Compared with glucose alone or with previously described T2D prediction models, a panel of plasma biomarkers showed promise for improved discrimination of incident T2D, but more investigation is needed to develop an early diagnostic marker.
Background Stroke patients are often affected by long-term disabilities with needs concerning social issues. There is relatively little consideration of social recovery of patients and the support required to return to work, receive social benefits, participate in daily life activities, maintain contact with family and friends and to organize financial affairs. In our study we aimed to investigate if existing tools record social needs adequately. We analyzed the current provision of social support provided in long-term care after stroke and whether unmet social needs were associated with quality of life, caregiver burden, overall function and degree of disability. Methods Our analysis is part of the Managing Aftercare of Stroke study (MAS-I), a cross-sectional exploratory study of patient needs 2–3 years after initial stroke. Assessment tools included the Nikolaus-score (social situation), the EuroQoL (quality of life), the German Burden Scale for Family Caregivers (caregiver burden), the modified Rankin Scale (disability / dependence), Stroke Impact Scale (function and degree of disability) and the Stroke Survivor Needs Questionnaire (unmet needs). Results Overall 57 patients were included in MAS-I, with ten patients classified in urgent need of socio-economic support according to the Nikolaus-score. Patients with lower than normal Nikolaus-score had a higher degree of disability. Thirty percent of all patients had never received professional social support. Social worker contact happened mostly during the stay in acute hospital or rehabilitation institution. Only four patients (11%) reported long-term support after discharge. Apart from social worker contact during acute care, 43% of patients had unmet needs in the long-term aftercare. Forty percent of all patients included in MAS-I were recommended for social work intervention after an in-depth analysis of their situation. Finally, we saw that unmet social needs were associated with lower quality of life and higher caregiver burden. Conclusions Our data suggest significant unmet needs in social care in long-term stroke patients. Screening tools for unmet social needs such as the Nikolaus-score do not holistically report patients’ needs. Trial registration Clinicaltrials.Gov NCT02320994 . Registered 19 December 2014 (retrospectively registered). Electronic supplementary material The online version of this article (10.1186/s12883-019-1451-y) contains supplementary material, which is available to authorized users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.