The role of clinical phenotypes in decisions to limit life-sustaining treatment for very old patients in the ICU.

BACKGROUND: Limiting life-sustaining treatment (LST) in the intensive care unit (ICU) by withholding or withdrawing interventional therapies is considered appropriate if there is no expectation of beneficial outcome. Prognostication for very old patients is challenging due to the substantial biological and functional heterogeneity in that group. We have previously identified seven phenotypes in that cohort with distinct patterns of acute and geriatric characteristics. This study investigates the relationship between these phenotypes and decisions to limit LST in the ICU. METHODS: This study is a post hoc analysis of the prospective observational VIP2 study in patients aged 80 years or older admitted to ICUs in 22 countries. The VIP2 study documented demographic, acute and geriatric characteristics as well as organ support and decisions to limit LST in the ICU. Phenotypes were identified by clustering analysis of admission characteristics. Patients who were assigned to one of seven phenotypes (n = 1268) were analysed with regard to limitations of LST. RESULTS: The incidence of decisions to withhold or withdraw LST was 26.5% and 8.1%, respectively. The two phenotypes describing patients with prominent geriatric features and a phenotype representing the oldest old patients with low severity of the critical condition had the largest odds for withholding decisions. The discriminatory performance of logistic regression models in predicting limitations of LST after admission to the ICU was the best after combining phenotype, ventilatory support and country as independent variables. CONCLUSIONS: Clinical phenotypes on ICU admission predict limitations of LST in the context of cultural norms (country). These findings can guide further research into biases and preferences involved in the decision-making about LST. Trial registration Clinical Trials NCT03370692 registered on 12 December 2017.

Multi-Knock-a multi-targeted genome-scale CRISPR toolbox to overcome functional redundancy in plants.

Plant genomes are characterized by large and complex gene families that often result in similar and partially overlapping functions. This genetic redundancy severely hampers current efforts to uncover novel phenotypes, delaying basic genetic research and breeding programmes. Here we describe the development and validation of Multi-Knock, a genome-scale clustered regularly interspaced short palindromic repeat toolbox that overcomes functional redundancy in Arabidopsis by simultaneously targeting multiple gene-family members, thus identifying genetically hidden components. We computationally designed 59,129 optimal single-guide RNAs that each target two to ten genes within a family at once. Furthermore, partitioning the library into ten sublibraries directed towards a different functional group allows flexible and targeted genetic screens. From the 5,635 single-guide RNAs targeting the plant transportome, we generated over 3,500 independent Arabidopsis lines that allowed us to identify and characterize the first known cytokinin tonoplast-localized transporters in plants. With the ability to overcome functional redundancy in plants at the genome-scale level, the developed strategy can be readily deployed by scientists and breeders for basic research and to expedite breeding efforts.

Clustering analysis of geriatric and acute characteristics in a cohort of very old patients on admission to ICU.

PURPOSE: The biological and functional heterogeneity in very old patients constitutes a major challenge to prognostication and patient management in intensive care units (ICUs). In addition to the characteristics of acute diseases, geriatric conditions such as frailty, multimorbidity, cognitive impairment and functional disabilities were shown to influence outcome in that population. The goal of this study was to identify new and robust phenotypes based on the combination of these features to facilitate early outcome prediction. METHODS: Patients aged 80 years old or older with and without limitations of life-sustaining treatment and with complete data were recruited from the VIP2 study for phenotyping and from the COVIP study for external validation. The sequential organ failure assessment (SOFA) score and its sub-scores taken on admission to ICU as well as demographic and geriatric patient characteristics were subjected to clustering analysis. Phenotypes were identified after repeated bootstrapping and clustering runs. RESULTS: In patients from the VIP2 study without limitations of life-sustaining treatment (n = 1977), ICU mortality was 12% and 30-day mortality 19%. Seven phenotypes with distinct profiles of acute and geriatric characteristics were identified in that cohort. Phenotype-specific mortality within 30 days ranged from 3 to 57%. Among the patients assigned to a phenotype with pronounced geriatric features and high SOFA scores, 50% died in ICU and 57% within 30 days. Mortality differences between phenotypes were confirmed in the COVIP study cohort (n = 280). CONCLUSIONS: Phenotyping of very old patients on admission to ICU revealed new phenotypes with different mortality and potential need for anticipatory intervention.

CRISPys: Optimal sgRNA Design for Editing Multiple Members of a Gene Family Using the CRISPR System.

The development of the CRISPR-Cas9 system in recent years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simple and effective task. The system is directed to a genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with it, subsequently leading to site-specific modifications. However, many gene families in eukaryotic genomes exhibit partially overlapping functions, and thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR-Cas9 system, which may lead to the modification of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. We introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the efficiency to edit the induced targets is maximized. We suggest several approaches for designing the optimal individual sgRNA and an approach to compute the optimal set of sgRNAs for cases when the experimental platform allows for more than one. The latter may optionally account for the homologous relationships among gene-family members. We further show that CRISPys outperforms simpler alignment-based techniques by in silico examination over all gene families in the Solanum lycopersicum genome.