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Background Right ventricular (RV) maladaptation to elevated pulmonary afterload is the primary determinant of outcomes in pulmonary artery (PA) hypertension; however, the pathobiological mechanisms underlying RV decompensation remain poorly understood. Methods We performed global untargeted metabolomics on plasma from 55 patients who underwent gold‐standard RV‐PA coupling measurements using multibeat pressure volume loop assessment in a single‐center cohort and from 1027 patients with coupling surrogate measurements in a larger multicenter cohort, the PVDOMICS (Pulmonary Vascular Disease Phenomics) study. Age and sex‐adjusted linear regression was performed to identify associations between metabolites and coupling metrics. Additionally, we performed a metabolic flux analysis using gene expression data from RV tissue in an independent cohort of 32 patients. Partial least squares–discriminant analysis was used to identify metabolites and reactions characteristic of the decompensated RV. Results RV‐PA coupling was negatively associated with tricarboxylic acid (TCA) cycle intermediate levels. Specifically, plasma α‐ketoglutarate and fumarate were significantly associated with all coupling metrics in both cohorts. Metabolic flux analysis indicated that decompensated RVs exhibited aberrant TCA cycle activity, including reduced acetyl coenzyme A entry and increased lactate elimination, suggesting a shift from the TCA cycle toward glycolysis at the RV tissue level. Conclusions We identify an association between circulating TCA cycle intermediate levels and RV‐PA uncoupling in 2 independent cohorts, and dysregulated TCA cycle metabolism in decompensated PA hypertension RVs, suggesting that aberrant TCA cycle metabolism could represent a hallmark of RV maladaptation in PA hypertension. Further study of this pathway is warranted to develop novel biomarkers of RV function or RV‐targeted therapies.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Background. Elderly patients with chronic diseases (CDs) have a higher predilection for falls, with more severe consequences once they fall. Therefore, it is necessary to explore an effective way to prevent falls in elderly patients with CDs. Objective. To clarify the clinical effects of outpatient health education on fall prevention and self-health management in elderly patients with CDs. Methods. This retrospective study enrolled 102 elderly patients with CDs who received treatment in the School of Medicine, Sir Run Run Shaw Hospital of Zhejiang University, between January 2019 and December 2020. Patients intervened by routine nursing were assigned to the regular group (n = 48), and those additionally treated with outpatient health education were included in the research group (n = 54). Assessment of patients’ negative emotions (NEs) adopted the Self-Rating Anxiety/Depression Scale (SAS/SDS), determination of their sense of self-efficacy employed the Falls Efficacy Scale International (FES-I), and their self-care capacity evaluation used the Exercise of Self-Care Agency (ESCA). Patients’ falls, hospitalization time, fall prevention knowledge, fall prevention-related health behavior, and nursing satisfaction were recorded. Results. After the nursing intervention, lower SAS, SDS, and FES-I scores were determined in the research group versus the regular group; the total ESCA score assessed from various dimensions was higher in the research group; the research group also exhibited a markedly lower incidence of falls, and shorter hospitalization time than the regular group, with better mastery of fall prevention knowledge, fall prevention-related health behavior and nursing satisfaction. Conclusions. Outpatient health education intervention can prevent senile patients with CDs from falling, promote their rehabilitation, and enhance their mastery of fall prevention knowledge; moreover, it can improve patients’ healthy behaviors to prevent falls, mitigate their NEs, and improve their sense of self-efficacy and self-care ability, which has high clinical application value.

Background: Progress in genome technology allows analysis of previously completed trials to identify subgroups potentially benefiting from therapy. Enzastaurin is a potent inhibitor of protein kinase C beta (PKC-β) and suppresses the phosphoinositide 3-kinase (PI3K)/AKT pathway. The safety and efficacy of Enzastaurin has been tested in more than 60 clinical trials including 2 major studies in DLBCL: (1) PRELUDE (A phase III maintenance trial of Enzastaurin vs Placebo, N=758) (Crump, 2016), and (2) S028 (A randomized phase II study of Enzastaurin/R-CHOP vs R-CHOP in frontline intermediate/high-risk DLBCL, N=101) (Hainsworth, 2016). DNA samples extracted from blood of patients from PRELUDE were retrospectively genotyped using whole genome SNP arrays. From the genome wide screening a novel genetic biomarker, DGM1, was identified showing high correlation with response to Enzastaurin treatment (Luo, ASH 2018). Importantly, these findings were replicated in the phase II S028 study. In the S028 study the hazard ratio (HR) for OS in high-risk (IPI ≥ 3) DGM1 positive (+) patients who received Enzastaurin/R-CHOP was 0.28 (0.1-0.81) when compared to subjects who received R-CHOP, a benefit favoring Enzastaurin (p=0.018). These data suggest that addition of Enzastaurin to R-CHOP may significantly improve outcome in frontline high-risk DGM1 (+) DLBCL. The ENGINE study was initiated to validate this finding in a prospective study. Study Design and Methods: Adult patients must have untreated CD20+ DLBCL, IPI ≥ 3. Patients are randomized 1:1 to Enzastaurin/R-CHOP or Placebo/R-CHOP for 6 cycles during combination phase. Each subject's treatment assignment will be unblinded after response assessment at the end of the combination phase. Subjects randomized to the investigational arm who have a complete or partial response will have the option to continue in the single agent phase to receive Enzastaurin for up to 2 additional years. The study intends to enroll approximately 235 patients with primary endpoint of OS in DGM1 (+) patients. The study is ongoing with 57 sites open in the US and China. As of 20 July 2019, 128 patients have been randomized. Clinical trial information: NCT03263026. Disclosures Nowakowski: Genentech, Inc.: Research Funding; Curis: Research Funding; Bayer: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; F. Hoffmann-La Roche Ltd: Research Funding; Selvita: Membership on an entity's Board of Directors or advisory committees; NanoString: Research Funding; MorphoSys: Consultancy, Research Funding. Brody:Acerta Pharma: Research Funding; Merck: Research Funding; Celldex Therapeutics: Research Funding; Genentech: Research Funding; Oncovir, Inc.: Research Funding; BMS: Research Funding; Kite Pharma: Research Funding. Lue:Kymera Therapeutics: Honoraria; Astex Pharmaceuticals: Honoraria. Luo:Denovo Biopharma LLC: Employment, Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties. Zhang:Denovo Biopharma LLC: Employment. Han:Denovo Biopharma LLC: Employment. Jivani:TRACON Pharmaceuticals, Inc.: Other: Stock; Denovo Biopharma LLC: Employment. Liu:Denovo Biopharma LLC: Employment. Li:Denovo Biopharma LLC: Employment. Sun:Novartis: Other: Stock; Denovo Biopharma LLC: Employment.