Identification of a serum biomarker panel for the differential diagnosis of cholangiocarcinoma and primary sclerosing cholagnitis

The non-invasive differentiation of malignant and benign biliary disease is a clinical challenge. Carbohydrate antigen 19-9 (CA19-9), leucine-rich α2-glycoprotein (LRG1), interleukin 6 (IL6), pyruvate kinase M2 (PKM2), cytokeratin 19 fragment (CYFRA21.1) and mucin 5AC (MUC5AC) have reported utility for differentiating cholangiocarcinoma (CCA) from benign biliary disease. Herein, serum levels of these markers were tested in 66 cases of CCA and 62 cases of primary sclerosing cholangitis (PSC) and compared with markers of liver function and inflammation. Markers panels were assessed for their ability to discriminate malignant and benign disease. Several of the markers were also assessed in pre-diagnosis biliary tract cancer (BTC) samples with performances evaluated at different times prior to diagnosis. We show that LRG1 and IL6 were unable to accurately distinguish CCA from PSC, whereas CA19-9, PKM2, CYFRA21.1 and MUC5AC were significantly elevated in malignancy. Area under the receiver operating characteristic curves for these individual markers ranged from 0.73–0.84, with the best single marker (PKM2) providing 61% sensitivity at 90% specificity. A panel combining PKM2, CYFRA21.1 and MUC5AC gave 76% sensitivity at 90% specificity, which increased to 82% sensitivity by adding gamma-glutamyltransferase (GGT). In the pre-diagnosis setting, LRG1, IL6 and PKM2 were poor predictors of BTC, whilst CA19-9 and C-reactive protein were elevated up to 2 years before diagnosis. In conclusion, LRG1, IL6 and PKM2 were not useful for early detection of BTC, whilst a model combining PKM2, CYFRA21.1, MUC5AC and GGT was beneficial in differentiating malignant from benign biliary disease, warranting validation in a prospective trial

Defects in cell spreading and ERK1/2 activation in fibroblasts with lamin A/C mutations

AbstractIn-frame mutations in nuclear lamin A/C lead to a multitude of tissue-specific degenerative diseases known as the ‘laminopathies’. Previous studies have demonstrated that lamin A/C-null mouse fibroblasts have defects in cell polarisation, suggesting a role for lamin A/C in nucleo-cytoskeletal-cell surface cross-talk. However, this has not been examined in patient fibroblasts expressing modified forms of lamin A/C. Here, we analysed skin fibroblasts from 3 patients with Emery–Dreifuss muscular dystrophy and from 1 with dilated cardiomyopathy. The emerin–lamin A/C interaction was impaired in each mutant cell line. Mutant cells exhibited enhanced cell proliferation, collagen-dependent adhesion, larger numbers of filopodia and smaller cell spread size, compared with control cells. Furthermore, cell migration, speed and polarization were elevated. Mutant cells also showed an enhanced ability to contract collagen gels at early time points, compared with control cells. Phosphotyrosine measurements during cell spreading indicated an initial temporal lag in ERK1/2 activation in our mutant cells, followed by hyper-activation of ERK1/2 at 2 h post cell attachment. Deregulated ERK1/2 activation is linked with cardiomyopathy, cell spreading and proliferation defects. We conclude that a functional emerin–lamin A/C complex is required for cell spreading and proliferation, possibly acting through ERK1/2 signalling

Cyclospora cayetanensis among expatriate and indigenous populations of West Java, Indonesia.

From January 1995 through July 1998, we investigated the occurrence of Cyclospora cayetanensis infection associated with gastrointestinal illness or diarrhea in foreign residents and natives of West Java, Indonesia. We found that C. cayetanensis was the main protozoal cause of gastrointestinal illness and diarrhea in adult foreign residents during the wet season. The parasite rarely caused illness in the indigenous population or in children

Muscular Dystrophy-Associated SUN1 and SUN2 Variants Disrupt Nuclear-Cytoskeletal Connections and Myonuclear Organization

Proteins of the nuclear envelope (NE) are associated with a range of inherited disorders, most commonly involving muscular dystrophy and cardiomyopathy, as exemplified by Emery-Dreifuss muscular dystrophy (EDMD). EDMD is both genetically and phenotypically variable, and some evidence of modifier genes has been reported. Six genes have so far been linked to EDMD, four encoding proteins associated with the LINC complex that connects the nucleus to the cytoskeleton. However, 50% of patients have no identifiable mutations in these genes. Using a candidate approach, we have identified putative disease-causing variants in the SUN1 and SUN2 genes, also encoding LINC complex components, in patients with EDMD and related myopathies. Our data also suggest that SUN1 and SUN2 can act as disease modifier genes in individuals with co-segregating mutations in other EDMD genes. Five SUN1/SUN2 variants examined impaired rearward nuclear repositioning in fibroblasts, confirming defective LINC complex function in nuclear-cytoskeletal coupling. Furthermore, myotubes from a patient carrying compound heterozygous SUN1 mutations displayed gross defects in myonuclear organization. This was accompanied by loss of recruitment of centrosomal marker, pericentrin, to the NE and impaired microtubule nucleation at the NE, events that are required for correct myonuclear arrangement. These defects were recapitulated in C2C12 myotubes expressing exogenous SUN1 variants, demonstrating a direct link between SUN1 mutation and impairment of nuclear-microtubule coupling and myonuclear positioning. Our findings strongly support an important role for SUN1 and SUN2 in muscle disease pathogenesis and support the hypothesis that defects in the LINC complex contribute to disease pathology through disruption of nuclear-microtubule association, resulting in defective myonuclear positioning

Estimation of the genetic contribution of presenilin-1 and -2 mutations in a population-based study of presenile Alzheimer disease

Two closely related genes, the presenilins ( PS ), located at chromosomes 14q24.3 and 1q42.1, have been identified for autosomal dominant Alzheimer disease (AD) with onset age below 65 years (presenile AD). We performed a systematic mutation analysis of all coding and 5'-non-coding exons of PS -1 and PS -2 in a population-based epidemiological series of 101 unrelated familial and sporadic presenile AD cases. The familial cases included 10 patients of autosomal dominant AD families sampled for linkage analysis studies. In all pat

Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis:a case-control development and validation study

Background: Many individuals who will experience a first episode of psychosis (FEP) are not detected before occurrence, limiting the effect of preventive interventions. The combination of machine-learning methods and electronic health records (EHRs) could help address this gap. Methods: This case-control development and validation study is based on EHR data from IBM Explorys. The IBM Explorys Platform holds standardised, longitudinal, de-identified, patient-level EHR data pooled from different health-care systems with distinct EHRs. The present EHR-based studies were retrospective, matched (1:1), case-control studies compliant with RECORD, STROBE, and TRIPOD statements. The study included individuals in the IBM Explorys database who at some point between 1990 and 2018 had a diagnosis of FEP followed by schizophrenia, and psychosis-free matched control individuals from a random subsample of the full cohort. For every individual in the FEP cohort, the individual in the control cohort was matched to have a similar date for inclusion in the database and a similar total observation time. Individuals in the FEP cohort had their index date defined as the first diagnosis of psychosis or the first prescription of antipsychotic medication. Individuals in the control cohort had their index date defined to occur the same number of days after inclusion in the database as their matching FEP individual. The FEP and control cohorts were both randomly split into development and validation datasets in a ratio of 7:3. The subset of individuals in the validation dataset who had all their health-care encounters at providers that were not seen in the development dataset made up the external validation subset. A novel recurrent neural network model was developed to predict the risk of FEP 1 year before the index date by employing demographics and medical events (in the categories diagnoses, prescriptions, procedures, encounters and admissions, observations, and laboratory test results) dynamically collected in the EHR as part of clinical routine. We named the recurrent neural network Dynamic ElecTronic hEalth reCord deTection (DETECT). The main outcomes were accuracy and area under receiver operating characteristic curve (AUROC). Decision-curve analyses and dynamic patient journey plots were used to evaluate clinical usefulness. Findings: The FEP and control cohorts each comprised 72 860 individuals. 102 030 individuals (51 015 matching pairs) were randomly allocated to the development dataset and the remaining 43 690 to the validation dataset. In the validation dataset, 4770 individuals had all their encounters outside of the 118 790 health-care providers that were encountered in the development dataset. The data from these individuals made up the external validation subset. The median follow-up (observation time before index date) was 6·0 years (IQR 3·0–10·4). In the development dataset, DETECT's prognostic accuracy was 0·787 and AUROC was 0·868. In the validation dataset, DETECT's prognostic accuracy was 0·774 and AUROC was 0·856. In the external test subset, DETECT's balanced prognostic accuracy was 0·724 and AUROC was 0·799. Prevalence-adjusted decision-curve analyses suggested that DETECT was associated with a positive net benefit in two different scenarios for FEP detection. Interpretation: DETECT showed adequate prognostic accuracy to detect individuals at risk of developing a FEP in primary and secondary care. Replication and refinement in a population-based setting are needed to consolidate these findings. Funding: Lundbeck