👤 Wendy R Uhlmann

Left ventricular non-compaction has been increasingly diagnosed in recent years. However, it is still debated whether non-compaction is a pathological condition or a physiological trait. In this meta-analysis and systematic review, we compare studies, which investigated these two different perspectives. Furthermore, we provide a comprehensive overview on the clinical outcome as well as genetic background of left ventricular non-compaction cardiomyopathy in adult patients. We retrieved PubMed/Medline literatures in English language from 2000 to 19/09/2018 on clinical outcome and genotype of patients with non-compaction. We summarized and extensively reviewed all studies that passed selection criteria and performed a meta-analysis on key phenotypic parameters. Altogether, 35 studies with 2271 non-compaction patients were included in our meta-analysis. The mean age at diagnosis was the mid of their fifth decade. Two-thirds of patients were male. Congenital heart diseases including atrial or ventricular septum defect or Ebstein anomaly were reported in 7% of patients. Twenty-four percent presented with family history of cardiomyopathy. The mean frequency of neuromuscular diseases was 5%. Heart rhythm abnormalities were reported frequently: conduction disease in 26%, supraventricular tachycardia in 17%, and sustained or non-sustained ventricular tachycardia in 18% of patients. Three important outcome measures were reported including systemic thromboembolic events with a mean frequency of 9%, heart transplantation with 4%, and adequate ICD therapy with 15%. Nine studies investigated the genetics of non-compaction cardiomyopathy. The most frequently mutated gene was TTN with a pooled frequency of 11%. The average frequency of MYH7 mutations was 9%, for MYBPC3 mutations 5%, and for CASQ2 and LDB3 3% each. TPM1, MIB1, ACTC1, and LMNA mutations had an average frequency of 2% each. Mutations in PLN, HCN4, TAZ, DTNA, TNNT2, and RBM20 were reported with a frequency of 1% each. We also summarized the results of eight studies investigating the non-compaction in altogether 5327 athletes, pregnant women, patients with sickle cell disease, as well as individuals from population-based cohorts, in which the presence of left ventricular hypertrabeculation ranged from 1.3 to 37%. The summarized data indicate that non-compaction may lead to unfavorable outcome in different cardiomyopathy entities. The presence of key features in a multimodal diagnostic approach could distinguish between benign morphological trait and manifest cardiomyopathy. Show less

The clinical presentation, course and treatment of methamphetamine (METH)-associated psychosis (MAP) are similar to that observed in schizophrenia (SCZ) and subsequently MAP has been hypothesized as a pharmacological and environmental model of SCZ. However, several challenges currently exist in diagnosing MAP accurately at the molecular and neurocognitive level before the MAP model can contribute to the discovery of SCZ biomarkers. We directly assessed subcortical brain structural volumes and clinical parameters of MAP within the framework of an integrative genome-wide RNA-Seq blood transcriptome analysis of subjects diagnosed with MAP (N=10), METH dependency without psychosis (MA; N=10) and healthy controls (N=10). First, we identified discrete groups of co-expressed genes (that is, modules) and tested them for functional annotation and phenotypic relationships to brain structure volumes, life events and psychometric measurements. We discovered one MAP-associated module involved in ubiquitin-mediated proteolysis downregulation, enriched with 61 genes previously found implicated in psychosis and SCZ across independent blood and post-mortem brain studies using convergent functional genomic (CFG) evidence. This module demonstrated significant relationships with brain structure volumes including the anterior corpus callosum (CC) and the nucleus accumbens. Furthermore, a second MAP and psychoticism-associated module involved in circadian clock upregulation was also enriched with 39 CFG genes, further associated with the CC. Subsequently, a machine-learning analysis of differentially expressed genes identified single blood-based biomarkers able to differentiate controls from methamphetamine dependents with 87% accuracy and MAP from MA subjects with 95% accuracy. CFG evidence validated a significant proportion of these putative MAP biomarkers in independent studies including CLN3, FBP1, TBC1D2 and ZNF821 (RNA degradation), ELK3 and SINA3 (circadian clock) and PIGF and UHMK1 (ubiquitin-mediated proteolysis). Finally, focusing analysis on brain structure volumes revealed significantly lower bilateral hippocampal volumes in MAP subjects. Overall, these results suggest similar molecular and neurocognitive mechanisms underlying the pathophysiology of psychosis and SCZ regardless of substance abuse and provide preliminary evidence supporting the MAP paradigm as an exemplar for SCZ biomarker discovery. Show less