The haplotype block, NFKBIL1-ATP6V1G2-BAT1-MICB-MICA, within the class III-class I boundary region of the human major histocompatibility complex may control susceptibility to hepatitis C virus-associated dilated cardiomyopathy

Cardiomyopathy is a heart muscle disease with impaired stretch response that can result in severe heart failure and sudden death. A small proportion of hepatitis C virus (HCV)-infected patients may be predisposed to develop dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM). The molecular mechanisms involved in the predisposition remain unknown due in part to the lack of information on their genetic background. Because the human leukocyte antigen (HLA) region has a pivotal role in controlling the susceptibility to HCV-induced liver disease, we hypothesized that particular HLA alleles and/or non-HLA gene alleles within the human major histocompatibility complex (MHC) genomic region might control the predisposition to HCV-associated DCM (HCV-DCM) and/or HCV-associated HCM (HCV-HCM). Here, we present mapping results of the MHC-related susceptibility gene locus for HCV-associated cardiomyopathy by analyzing microsatellite and single nucleotide polymorphism markers. To delineate the susceptibility locus, we genotyped 44 polymorphic markers scattered across the entire MHC region in a total of 59 patients (21 HCV-DCM and 38 HCV-HCM) and 120 controls. We mapped HCV-DCM susceptibility to a non-HLA gene locus spanning from NFKBIL1 to MICA gene loci within the MHC class III-class I boundary region. Our results showed that HCV-DCM was more strongly associated with alleles of the non-HLA genes rather than the HLA genes themselves. In addition, no significant association was found between the MHC markers and HCV-HCM. This marked difference in the MHC-related disease susceptibility for HCV- associated cardiomyopathy strongly suggests that the development of HCV- DCM and HCV-HCM is under the control of different pathogenic mechanisms.     

The feasibility and validity of care mapping in the clinical neurosciences

Dementia Care Mapping (DCM) is an observational tool and process that is widely used in dementia care in measuring and improving person-centred care (PCC). DCM was previously piloted on a neurorehabilitation ward, where it was found to be feasible and acceptable in this setting. Following this, a new modified tool and accompanying manual were developed: Care Mapping – Neurorehabilitation (DCM-NR). The current study aimed to assess the feasibility and validity of DCM-NR by piloting its use in a range of clinical neuroscience settings. A mixed-methods design was used employing both quantitative and qualitative techniques. The new DCM-NR was found to be feasible for use both in terms of the suitability of its coding system and the implementation process. DCM-NR was shown to have a moderate level of concurrent validity with participants' self-report of PCC. Participants' subjective reports on their experiences of care provided validation for the areas of psychological need observed in DCM-NR. The results of this study indicate that DCM-NR is feasible and valid for use in a range of clinical neuroscience settings. Further longitudinal research is required to evaluate the impact of DCM-NR on PCC practices over time.     

The natural history of a genetic subtype of arrhythmogenic right ventricular cardiomyopathy caused by a p.S358L mutation in TMEM43

To determine the phenotype and natural history of a founder genetic subtype of autosomal dominant arrhythmogenic right ventricular cardiomyopathy (ARVC) caused by a p.S358L mutation in TMEM43. The age of onset of cardiac symptoms, clinical events and test abnormalities were studied in 412 subjects (258 affected and 154 unaffected), all of which occurred in affected males significantly earlier and more often than unaffected males. Affected males were hospitalized four times more often than affected females (p ≤ 0.0001) and died younger (p ≤ 0.001). The temporal sequence from symptoms onset to death was prolonged in affected females by 1–2 decades. The most prevalent electrocardiogram (ECG) manifestation was poor R wave progression (PRWP), with affected males twice as likely to develop PRWP as affected females (p ≤ 0.05). Left ventricular enlargement (LVE) occurred in 43% of affected subjects, with 11% fulfilling criteria for dilated cardiomyopathy. Ventricular ectopy on Holter monitor was common and occurred early: the most diagnostically useful clinical test. No symptom or test could rule out diagnosis. This ARVC subtype is a sex‐influenced lethal arrhythmogenic cardiomyopathy, with a unique ECG finding, LV dilatation, heart failure and early death, where molecular pre‐symptomatic diagnosis has the greatest clinical utility.     

New population-based exome data are questioning the pathogenicity of previously cardiomyopathy-associated genetic variants

Cardiomyopathies are a heterogeneous group of diseases with various etiologies. We focused on three genetically determined cardiomyopathies: hypertrophic (HCM), dilated (DCM), and arrhythmogenic right ventricular cardiomyopathy (ARVC). Eighty-four genes have so far been associated with these cardiomyopathies, but the disease-causing effect of reported variants is often dubious. In order to identify possible false-positive variants, we investigated the prevalence of previously reported cardiomyopathy-associated variants in recently published exome data. We searched for reported missense and nonsense variants in the NHLBI-Go Exome Sequencing Project (ESP) containing exome data from 6500 individuals. In ESP, we identified 94 variants out of 687 (14%) variants previously associated with HCM, 58 out of 337 (17%) variants associated with DCM, and 38 variants out of 209 (18%) associated with ARVC. These findings correspond to a genotype prevalence of 1:4 for HCM, 1:6 for DCM, and 1:5 for ARVC. PolyPhen-2 predictions were conducted on all previously published cardiomyopathy-associated missense variants. We found significant overrepresentation of variants predicted as being benign among those present in ESP compared with the ones not present. In order to validate our findings, seven variants associated with cardiomyopathy were genotyped in a control population and this revealed frequencies comparable with the ones found in ESP. In conclusion, we identified genotype prevalences up to more than one thousand times higher than expected from the phenotype prevalences in the general population (HCM 1:500, DCM 1:2500, and ARVC 1:5000) and our data suggest that a high number of these variants are not monogenic causes of cardiomyopathy.     

Penta-block copolymer microspheres: Impact of polymer characteristics and process parameters on protein release

Here, we aimed to develop protein loaded microspheres (MSs) using penta-block PLGA-based copolymers to obtain sustained and complete protein release. We varied MS morphology and studied the control of protein release. Lysozyme was used as a model protein and MSs were prepared using the solid-in-oil-in-water emulsion solvent extraction method. We synthesized and studied various penta-block PLGA-based copolymers. Copolymer characteristics (LA/GA ratio and molecular weight of PLGA blocks) influenced MS morphology. MS porosity was influenced by process parameters (such as solvent type, polymer concentration, emulsifying speed), whereas the aqueous volume for extraction and stabilizer did not have a significant effect. MSs of the same size, but different morphologies, exhibited different protein release behavior, with porous structures being essential for the continuous and complete release of encapsulated protein. These findings suggest strategies to engineer the morphology of MSs produced from PLGA-based multi-block copolymers to achieve appropriate release rates for a protein delivery system.     

Cognitive impairment and cardiovascular disease: So near,so far

In the spectrum of cognitive impairment, ranging from “pure” vascular dementia to Alzheimer's disease (AD), clinical interest has recently expanded from the brain to also include the vessels, shifting the pathophysiological focus from the leaves of synaptic dysfunction to the sap of cerebral microcirculation and the roots of cardiovascular function. From a diagnostic viewpoint, a thorough clinical evaluation of individuals presenting cognitive impairment might systematically include the assessment of the major cardiovascular rings of the chain linking regional perfusion to brain function: 1) lung (with assessment of asthma, chronic obstructive pulmonary disease, obstructive sleep apnea syndrome); 2) heart function (with clinical examination and echocardiography) and cardiovascular risk factors; 3) orthostatic hypotension (with medical history and measurement of heart rate and blood pressure in supine and upright positions); 4) aorta and large artery stiffness (with assessment of pulse wave velocity); 5) large cerebro-vascular vessel status (with neuroimaging techniques); 6) assessment of microcirculation (with cerebrovascular reactivity testing with transcranial Doppler sonography or MRI perfusion imaging); and 7) assessment of venous cerebral circulation. The apparent difference in approaches to “brain” and “vascular” environmental enrichment with physical, cognitive and sensorial training is conceptually identical to that of a constant gardener caring for an unhealthy tree, watering the leaves (“train the brain”) or simply the roots (“mind the vessel”). The therapeutic difference probably consists in the amount and quality of water added to the tree, rather than by where one pours it, with either a top-down (leaves to roots) or bottom-up (roots to leaves) approach.     

Stochastic dynamic causal modeling of working memory connections in cocaine dependence

Although reduced working memory brain activation has been reported in several brain regions of cocaine‐dependent subjects compared with controls, very little is known about whether there is altered connectivity of working memory pathways in cocaine dependence. This study addresses this issue by using functional magnetic resonance imaging‐based stochastic dynamic causal modeling (DCM) analysis to study the effective connectivity of 19 cocaine‐dependent subjects and 14 healthy controls while performing a working memory task. Stochastic DCM is an advanced method that has recently been implemented in SPM8 that can obtain improved estimates, relative to deterministic DCM, of hidden neuronal causes before convolution with the hemodynamic response. Thus, stochastic DCM may be less influenced by the confounding effects of variations in blood oxygen level‐dependent response caused by disease or drugs. Based on the significant regional activation common to both groups and consistent with previous working memory activation studies, seven regions of interest were chosen as nodes for DCM analyses. Bayesian family level inference, Bayesian model selection analyses, and Bayesian model averaging (BMA) were conducted. BMA showed that the cocaine‐dependent subjects had large differences compared with the control subjects in the strengths of prefrontal–striatal modulatory (B matrix) DCM parameters. These findings are consistent with altered cortical–striatal networks that may be related to reduced dopamine function in cocaine dependence. As far as we are aware, this is the first between‐group DCM study using stochastic methodology. Hum Brain Mapp 35:760–778, 2014. © 2012 Wiley Periodicals, Inc.