Brenner, David A.

Background: Causative Classification of Stroke (CCS) system is a novel, web-based, and fully-computerized algorithm that integrates clinical, diagnostic, and etiologic stroke characteristics in an evidence-based manner (available at http://ccs.mgh.harvard.edu ) and provides in a given patient both phenotypic subtypes where abnormal evaluation findings are simply organized in major etiologic categories and causative subtypes where abnormal evaluation findings are filtered through a decision making process to identify the most likely cause of stroke. In this study, we sought to identify the concordance between phenotypic and causative CCS subtypes in the NINDS Stroke Genetics Network (SiGN). Methods: A total of 24 adjudicators from 15 US and European sites certified in CCS retrospectively determined CCS subtypes through chart review in 7134 patients. The CCS software provided causative subtypes in 3 confidence levels as “evident”, “probable” or “possible” based on the weight of causal evidence. We estimated how often CCS classified a given major abnormal evaluation finding as the causative stroke mechanism. Results: CCS assigned 55% of patients with the phenotype of moderate-to-severe atherosclerotic stenosis into the causative category of “evident large artery atherosclerosis”. Likewise, 50% of patients with a major cardiac source (such as atrial fibrillation) were classified into “evident cardio-aortic embolism”, and 74% of those with imaging evidence of a typical lacunar infarct into “evident small artery occlusion”. In 20% to 30% of patients, phenotypic and causative categories were the same but the causative subtype was assigned with a lower level of confidence. Six to 20% of patients with a given phenotypic feature were classified into a different causative category. Failure to investigate for other subtypes in the presence of a positive test finding and the presence of multiple competing etiologies were key contributors to the observed disconcordance between phenotypic and causative subtypes. Conclusions: Our findings show that the presence of a major abnormality in stroke evaluation does not necessarily mean that it is always the cause. The ability of CCS system to discriminate between phenotypic and causative characteristics of stroke etiology provides the opportunity to refine stroke phenotypes for use in research studies.

Objectives: Identification of gene variants of stroke subtypes is important for the development of tailored ischemic stroke therapies among various ethnic groups. Valid and reliable determination of ischemic stroke subtype is essential for achieving this goal and to standardize a classification scheme across multi-center studies and different populations. Causative Classification System for Ischemic Stroke (CCS) is a novel computerized subclassification tool developed to improve reliability and accuracy of classifying stroke types. The CCS algorithm relies on both phenotypic and causative stroke variables. A Hispanic subset of the SiGN, an important and distinct target population with greater risk of certain stroke subtypes, was evaluated with Trial of Org 10172 in Acute Stroke Treatment (TOAST) and CCS and the agreement between the two classification systems was analyzed. Methods: Over 6000 subjects at 15 sites across US and Europe were enrolled, with TOAST and CCS locally adjudicated. Blood collection and central data quality control (10% central readjudication) were performed on all participants. A subset of Hispanics was analyzed for the purpose of this study and the agreement between the TOAST and CCS were assessed by kappa statistic. Findings: Hispanics (n=595, 10.9%) compared to non-Hispanics (n=5457) were more likely to be younger (63.7 vs. 64.0), male (55% vs. 46%) and have fewer of the traditional stroke risk factors HTN (54% vs. 64%), Afib (11% vs. 14%), DM(23% vs. 25%), CAD(16% vs. 20%) and smoking(19% vs. 22%). While the TOAST showed no differences between stroke subtypes for Hispanic vs. non-Hispanics, in CCS, Hispanics were classified with more of large vessel (22% vs. 20%), cardioembolic (37% vs. 30%) and small vessel strokes (13% vs. 9%) and fewer with undetermined etiology (28% vs. 40%) as compared to non-Hispanics. TOAST and CCS offered moderate correlation across all stroke types in Hispanics: kappa of 0.66 for large artery atherosclerosis, 0.58 for cardioembolic, and 0.58 for small artery occlusion. Conclusion: CCS offers a more sensitive and accurate system for subphenotyping of strokes in Hispanics who tended to have relatively fewer risk factors and unclassified strokes. Further studies correlating the two classification systems and their relation to genotyping data are warranted.

The scaffold protein synectin plays a critical role in the trafficking and regulation of membrane receptor pathways. As platelet-derived growth factor receptor (PDGFR) is essential for hepatic stellate cell (HSC) activation and liver fibrosis, we sought to determine the role of synectin on the PDGFR pathway and development of liver fibrosis. Mice with deletion of synectin from HSC were found to be protected from liver fibrosis. mRNA sequencing revealed that knockdown of synectin in HSC demonstrated reductions in the fibrosis pathway of genes, including PDGFR-β. Chromatin IP assay of the PDGFR-β promoter upon synectin knockdown revealed a pattern of histone marks associated with decreased transcription, dependent on p300 histone acetyltransferase. Synectin knockdown was found to downregulate PDGFR-α protein levels, as well, but through an alternative mechanism: protection from autophagic degradation. Site-directed mutagenesis revealed that ubiquitination of specific PDGFR-α lysine residues was responsible for its autophagic degradation. Furthermore, functional studies showed decreased PDGF-dependent migration and proliferation of HSC after synectin knockdown. Finally, human cirrhotic livers demonstrated increased synectin protein levels. This work provides insight into differential transcriptional and posttranslational mechanisms of synectin regulation of PDGFRs, which are critical to fibrogenesis.

Ezetimibe inhibits intestinal cholesterol absorption and lowers low‐density lipoprotein cholesterol. Uncontrolled studies have suggested that it reduces liver fat as estimated by ultrasound in nonalcoholic steatohepatitis (NASH). Therefore, we aimed to examine the efficacy of ezetimibe versus placebo in reducing liver fat by the magnetic resonance imaging‐derived proton density‐fat fraction (MRI‐PDFF) and liver histology in patients with biopsy‐proven NASH. In this randomized, double‐blind, placebo‐controlled trial, 50 patients with biopsy‐proven NASH were randomized to either ezetimibe 10 mg orally daily or placebo for 24 weeks. The primary outcome was a change in liver fat as measured by MRI‐PDFF in colocalized regions of interest within each of the nine liver segments. Novel assessment by two‐dimensional and three‐dimensional magnetic resonance elastography was also performed. Ezetimibe was not significantly better than placebo at reducing liver fat as measured by MRI‐PDFF (mean difference between the ezetimibe and placebo arms ‐1.3%, P = 0.4). Compared to baseline, however, end‐of‐treatment MRI‐PDFF was significantly lower in the ezetimibe arm (15%‐11.6%, P < 0.016) but not in the placebo arm (18.5%‐16.4%, P = 0.15). There were no significant differences in histologic response rates, serum alanine aminotransferase and aspartate aminotransferase levels, or longitudinal changes in two‐dimensional and three‐dimensional magnetic resonance elastography‐derived liver stiffness between the ezetimibe and placebo arms. Compared to histologic nonresponders (25/35), histologic responders (10/35) had a significantly greater reduction in MRI‐PDFF (‐4.35 ± 4.9% versus ‐0.30 ± 4.1%, P < 0.019). Conclusions : Ezetimibe did not significantly reduce liver fat in NASH. This trial demonstrates the application of colocalization of MRI‐PDFF‐derived fat maps and magnetic resonance elastography‐derived stiffness maps of the liver before and after treatment to noninvasively assess treatment response in NASH. (H epatology 2015;61:1239–1250)

Background and Purpose— Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke. Methods— The National Institute of Neurological Disorders and Stroke SiGN includes ischemic stroke cases from 24 genetic research centers: 13 from the United States and 11 from Europe. Investigators harmonize ischemic stroke phenotyping using the Web-based causative classification of stroke system, with data entered by trained and certified adjudicators at participating genetic research centers. Through the Center for Inherited Diseases Research, the Network plans to genotype 10 296 carefully phenotyped stroke cases using genome-wide single nucleotide polymorphism arrays and adds to these another 4253 previously genotyped cases, for a total of 14 549 cases. To maximize power for subtype analyses, the study allocates genotyping resources almost exclusively to cases. Publicly available studies provide most of the control genotypes. Center for Inherited Diseases Research–generated genotypes and corresponding phenotypes will be shared with the scientific community through the US National Center for Biotechnology Information database of Genotypes and Phenotypes, and brain MRI studies will be centrally archived. Conclusions— The Stroke Genetics Network, with its emphasis on careful and standardized phenotyping of ischemic stroke and stroke subtypes, provides an unprecedented opportunity to uncover genetic determinants of ischemic stroke.