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- Genetic ablation of ataxin-2 increases several global translation factors in their transcript abundance but decreases translation rate (2015)
- Spinocerebellar ataxia type 2 (SCA2) and amyotrophic lateral sclerosis (ALS) are neurodegenerative disorders, caused or modified by an unstable CAG-repeat expansion in the SCA2 gene, which encodes a polyglutamine (polyQ) domain expansion in ataxin-2 (ATXN2). ATXN2 is an RNA-binding protein and interacts with the poly(A)-binding protein PABPC1, localizing to ribosomes at the rough endoplasmic reticulum. Under cell stress, ATXN2, PABPC1 and small ribosomal subunits are relocated to stress granules, where mRNAs are protected from translation and from degradation. It is unknown whether ATXN2 associates preferentially with specific mRNAs or how it modulates RNA processing. Here, we investigated the RNA profile of the liver and cerebellum from Atxn2 knockout (Atxn2−/−) mice at two adult ages, employing oligonucleotide microarrays. Prominent increases were observed for Lsm12/Paip1 (>2-fold), translation modulators known as protein interactor/competitor of ATXN2 and for Plin3/Mttp (>1.3-fold), known as apolipoprotein modulators in agreement with the hepatosteatosis phenotype of the Atxn2−/− mice. Consistent modest upregulations were also observed for many factors in the ribosome and the translation/secretion apparatus. Quantitative reverse transcriptase PCR in liver tissue validated >1.2-fold upregulations for the ribosomal biogenesis modulator Nop10, the ribosomal components Rps10, Rps18, Rpl14, Rpl18, Gnb2l1, the translation initiation factors Eif2s2, Eif3s6, Eif4b, Pabpc1 and the rER translocase factors Srp14, Ssr1, Sec61b. Quantitative immunoblots substantiated the increased abundance of NOP10, RPS3, RPS6, RPS10, RPS18, GNB2L1 in SDS protein fractions, and of PABPC1. In mouse embryonal fibroblasts, ATXN2 absence also enhanced phosphorylation of the ribosomal protein S6 during growth stimulation, while impairing the rate of overall protein synthesis rates, suggesting a block between the enhanced translation drive and the impaired execution. Thus, the physiological role of ATXN2 subtly modifies the abundance of cellular translation factors as well as global translation.
- Exome sequencing of osteosarcoma reveals mutation signatures reminiscent of BRCA deficiency (2015)
- Osteosarcomas are aggressive bone tumours with a high degree of genetic heterogeneity, which has historically complicated driver gene discovery. Here we sequence exomes of 31 tumours and decipher their evolutionary landscape by inferring clonality of the individual mutation events. Exome findings are interpreted in the context of mutation and SNP array data from a replication set of 92 tumours. We identify 14 genes as the main drivers, of which some were formerly unknown in the context of osteosarcoma. None of the drivers is clearly responsible for the majority of tumours and even TP53 mutations are frequently mapped into subclones. However, >80% of osteosarcomas exhibit a specific combination of single-base substitutions, LOH, or large-scale genome instability signatures characteristic of BRCA1/2-deficient tumours. Our findings imply that multiple oncogenic pathways drive chromosomal instability during osteosarcoma evolution and result in the acquisition of BRCA-like traits, which could be therapeutically exploited.
- Regret among primary care physicians: a survey of diagnostic decisions (2020)
- Background: Experienced and anticipated regret influence physicians’ decision-making. In medicine, diagnostic decisions and diagnostic errors can have a severe impact on both patients and physicians. Little empirical research exists on regret experienced by physicians when they make diagnostic decisions in primary care that later prove inappropriate or incorrect. The aim of this study was to explore the experience of regret following diagnostic decisions in primary care. Methods: In this qualitative study, we used an online questionnaire on a sample of German primary care physicians. We asked participants to report on cases in which the final diagnosis differed from their original opinion, and in which treatment was at the very least delayed, possibly resulting in harm to the patient. We asked about original and final diagnoses, illness trajectories, and the reactions of other physicians, patients and relatives. We used thematic analysis to assess the data, supported by MAXQDA 11 and Microsoft Excel 2016. Results: 29 GPs described one case each (14 female/15 male patients, aged 1.5–80 years, response rate < 1%). In 26 of 29 cases, the final diagnosis was more serious than the original diagnosis. In two cases, the diagnoses were equally serious, and in one case less serious. Clinical trajectories and the reactions of patients and relatives differed widely. Although only one third of cases involved preventable harm to patients, the vast majority (27 of 29) of physicians expressed deep feelings of regret. Conclusion: Even if harm to patients is unavoidable, regret following diagnostic decisions can be devastating for clinicians, making them ‘second victims’. Procedures and tools are needed to analyse cases involving undesirable diagnostic events, so that ‘true’ diagnostic errors, in which harm could have been prevented, can be distinguished from others. Further studies should also explore how physicians can be supported in dealing with such events in order to prevent them from practicing defensive medicine.
- Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice (2020)
- Background Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices. Methods Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses. Results Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke’s R² 0.507) were depressive symptoms (−2.73 (95% CI: −3.56 to −1.91)), MAI (−0.39 (95% CI: −0.7 to −0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables. Conclusions Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.
