Specific alterations in plasma proteins during depressed,manic, and euthymic states of bipolar disorder

Bipolar disorder (BD) is a common psychiatric mood disorder affecting more than 1-2% of the general population of different European countries. Unfortunately, there is no objective laboratory-based test to aid BD diagnosis or monitor its progression, and little is known about the molecular basis of BD. Here, we performed a comparative proteomic study to identify differentially expressed plasma proteins in various BD mood states (depressed BD, manic BD, and euthymic BD) relative to healthy controls. A total of 10 euthymic BD, 20 depressed BD, 15 manic BD, and 20 demographically matched healthy control subjects were recruited. Seven high-abundance proteins were immunodepleted in plasma samples from the 4 experimental groups, which were then subjected to proteome-wide expression profiling by two-dimensional electrophoresis and matrix-assisted laser desorption/ionization-time-of-flight/time-of-flight tandem mass spectrometry. Proteomic results were validated by immunoblotting and bioinformatically analyzed using MetaCore. From a total of 32 proteins identified with 1.5-fold changes in expression compared with healthy controls, 16 proteins were perturbed in BD independent of mood state, while 16 proteins were specifically associated with particular BD mood states. Two mood-independent differential proteins, apolipoprotein (Apo) A1 and Apo L1, suggest that BD pathophysiology may be associated with early perturbations in lipid metabolism. Moreover, down-regulation of one mood-dependent protein, carbonic anhydrase 1 (CA-1), suggests it may be involved in the pathophysiology of depressive episodes in BD. Thus, BD pathophysiology may be associated with early perturbations in lipid metabolism that are independent of mood state, while CA-1 may be involved in the pathophysiology of depressive episodes.     

Distribution of temperature changes and neurovascular coupling in rat brain following 3,4‐methylenedioxymethamphetamine (MDMA, “ecstasy”) exposure

(+/?)3,4‐methylenedioxymethamphetamine (MDMA, “ecstasy”) is an abused psychostimulant that produces strong monoaminergic stimulation and whole‐body hyperthermia. MDMA‐induced thermogenesis involves activation of uncoupling proteins (UCPs), primarily a type specific to skeletal muscle (UCP‐3) and absent from the brain, although other UCP types are expressed in the brain (e.g. thalamus) and might contribute to thermogenesis. Since neuroimaging of brain temperature could provide insights into MDMA action, we measured spatial distributions of systemically administered MDMA‐induced temperature changes and dynamics in rat cortex and subcortex using a novel magnetic resonance method, Biosensor Imaging of Redundant Deviation in Shifts (BIRDS), with an exogenous temperature‐sensitive probe (thulium ion and macrocyclic chelate 1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetramethyl‐1,4,7,10‐tetraacetate (DOTMA^4?)). The MDMA‐induced temperature rise was greater in the cortex than in the subcortex (1.6 ± 0.4 °C versus 1.3 ± 0.4 °C) and occurred more rapidly (2.0 ± 0.2 °C/h versus 1.5 ± 0.2 °C/h). MDMA‐induced temperature changes and dynamics in the cortex and body were correlated, although the body temperature exceeded the cortex temperature before and after MDMA. Temperature, neuronal activity, and blood flow (CBF) were measured simultaneously in the cortex and subcortex (i.e. thalamus) to investigate possible differences of MDMA‐induced warming across brain regions. MDMA‐induced warming correlated with increases in neuronal activity and blood flow in the cortex, suggesting that the normal neurovascular response to increased neural activity was maintained. In contrast to the cortex, a biphasic relationship was seen in the subcortex (i.e. thalamus), with a decline in CBF as temperature and neural activity rose, transitioning to a rise in CBF for temperature above 37 °C, suggesting that MDMA affected CBF and neurovascular coupling differently in subcortical regions. Considering that MDMA effects on CBF and heat dissipation (as well as potential heat generation) may vary regionally, neuroprotection may require different cooling strategies. Copyright © 2015 John Wiley & Sons, Ltd.     

Association of Early Kidney Allograft Failure with Preformed IgA Antibodies to β2-Glycoprotein I

In the current immunosuppressive therapy era, vessel thrombosis is the most common cause of early graft loss after renal transplantation. The prevalence of IgA anti–β₂-glycoprotein I antibodies (IgA-aB2GPI-ab) in patients on dialysis is elevated (>30%), and these antibodies correlate with mortality and cardiovascular morbidity. To evaluate the effect of IgA-aB2GPI-ab in patients with transplants, we followed all patients transplanted from 2000 to 2002 in the Hospital 12 de Octubre prospectively for 10 years. Presence of IgA-aB2GPI-ab in pretransplant serum was examined retrospectively. Of 269 patients, 89 patients were positive for IgA-aB2GPI-ab (33%; group 1), and the remaining patients were negative (67%; group 2). Graft loss at 6 months post-transplant was significantly higher in group 1 (10 of 89 versus 3 of 180 patients in group 2; P=0.002). The most frequent cause of graft loss was thrombosis of the vessels, which was observed only in group 1 (8 of 10 versus 0 of 3 patients in group 2; P=0.04). Multivariate analysis showed that the presence of IgA-aB2GPI-ab was an independent risk factor for early graft loss (P=0.04) and delayed graft function (P=0.04). There were no significant differences regarding patient survival between the two groups. Graft survival was similar in both groups after 6 months. In conclusion, patients with pretransplant IgA-aB2GPI-ab have a high risk of early graft loss caused by thrombosis and a high risk of delayed graft function. Therefore, pretransplant IgA-aB2GPI-ab may have a detrimental effect on early clinical outcomes after renal transplantation.     

Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).