Revising the MELD Score to Address Sex-Bias in Liver Transplant Prioritization for a German Cohort.

(1) Background: Prioritization of patients for liver transplantation in Germany relies on the MELD (model for end-stage liver disease) scoring system that does not consider the patient's sex. Many studies have shown that women are disadvantaged by the MELD score. Using a large patient cohort from a German liver transplant centre, we investigated options to reduce gender inequality in the patient prioritization for liver transplantation. (2) Methods: We calculated female-as-male MELD scores in our cohort by substituting the serum creatinine of a female patient with that of their male equivalent to test for the fairness of the scores. We investigated the effects of the female-as-male scores compared to the original MELD score of 1759 patients listed for liver transplantation. (3) Results: Serum creatinine sex correction (female-as-male) for MELD scores added up to 5.4 points in females, while the median changed by +1.6 points for females. We identified 72 females with an original MELD score < 20, for whom the adjusted female-as-male MELD score would be >20, thus giving them a better chance to receive a liver transplant. (4) Conclusions: Mathematical conversion of female to male creatinine concentrations identified disadvantages in liver transplantation prioritization for females and ascertained MELD 3.0 as having high potential to compensate for these inequalities.

Evolutionary Conservation of RNA Secondary Structure.

Noncoding RNAs, ncRNAs, naturally fold into structures, which allow them to perform their functions in the cell. Evolutionarily close species share structures and functions. This occurs because of shared selective pressures, resulting in conserved groups. Previous efforts in finding functional RNAs have been made in detecting conserved structures in genomes or alignments. It may occur that, within a conserved group, species-specific structures arise after species split due to positive selection. Detecting positive selection in ncRNAs is a hard problem in biology as well as bioinformatics. To detect positive selection, one should find species-specific structures within a conserved set. This chapter provides protocols to detect and analyze positive selection in ncRNA structures with the SSS-test and other free software.

The Clinical Decision Support System AMPEL for Laboratory Diagnostics: Implementation and Technical Evaluation.

BACKGROUND: Laboratory results are of central importance for clinical decision making. The time span between availability and review of results by clinicians is crucial to patient care. Clinical decision support systems (CDSS) are computational tools that can identify critical values automatically and help decrease treatment delay. OBJECTIVE: With this work, we aimed to implement and evaluate a CDSS that supports health care professionals and improves patient safety. In addition to our experiences, we also describe its main components in a general manner to make it applicable to a wide range of medical institutions and to empower colleagues to implement a similar system in their facilities. METHODS: Technical requirements must be taken into account before implementing a CDSS that performs laboratory diagnostics (labCDSS). These can be planned within the functional components of a reactive software agent, a computational framework for such a CDSS. RESULTS: We present AMPEL (Analysis and Reporting System for the Improvement of Patient Safety through Real-Time Integration of Laboratory Findings), a labCDSS that notifies health care professionals if a life-threatening medical condition is detected. We developed and implemented AMPEL at a university hospital and regional hospitals in Germany (University of Leipzig Medical Center and the Muldental Clinics in Grimma and Wurzen). It currently runs 5 different algorithms in parallel: hypokalemia, hypercalcemia, hyponatremia, hyperlactatemia, and acute kidney injury. CONCLUSIONS: AMPEL enables continuous surveillance of patients. The system is constantly being evaluated and extended and has the capacity for many more algorithms. We hope to encourage colleagues from other institutions to design and implement similar CDSS using the theory, specifications, and experiences described in this work.

Selection Pressures on RNA Sequences and Structures.

With the discovery of increasingly more functional noncoding RNAs (ncRNAs), it becomes eminent to more strongly consider them as important players during species evolution. Although tests for negative selection of ncRNAs already exist since the beginning of this century, the SSS-test is the first one for also investigating positive selection. When analyzing selection in ncRNAs, it should be taken into account that selection pressures can independently act on sequence and structure. We applied the SSS-test to explore the evolution of ncRNAs in primates and identified more than 100 long noncoding RNAs (lncRNAs) that might evolve under positive selection in humans. With this test, it is now possible to more thoroughly include ncRNAs into evolutionary studies.

SSS-test: a novel test for detecting positive selection on RNA secondary structure.

BACKGROUND: Long non-coding RNAs (lncRNAs) play an important role in regulating gene expression and are thus important for determining phenotypes. Most attempts to measure selection in lncRNAs have focused on the primary sequence. The majority of small RNAs and at least some parts of lncRNAs must fold into specific structures to perform their biological function. Comprehensive assessments of selection acting on RNAs therefore must also encompass structure. Selection pressures acting on the structure of non-coding genes can be detected within multiple sequence alignments. Approaches of this type, however, have so far focused on negative selection. Thus, a computational method for identifying ncRNAs under positive selection is needed. RESULTS: We introduce the SSS-test (test for Selection on Secondary Structure) to identify positive selection and thus adaptive evolution. Benchmarks with biological as well as synthetic controls yield coherent signals for both negative and positive selection, demonstrating the functionality of the test. A survey of a lncRNA collection comprising 15,443 families resulted in 110 candidates that appear to be under positive selection in human. In 26 lncRNAs that have been associated with psychiatric disorders we identified local structures that have signs of positive selection in the human lineage. CONCLUSIONS: It is feasible to assay positive selection acting on RNA secondary structures on a genome-wide scale. The detection of human-specific positive selection in lncRNAs associated with cognitive disorder provides a set of candidate genes for further experimental testing and may provide insights into the evolution of cognitive abilities in humans. AVAILABILITY: The SSS-test and related software is available at: https://github.com/waltercostamb/SSS-test . The databases used in this work are available at: http://www.bioinf.uni-leipzig.de/Software/SSS-test/ .

Divergent evolution in the genomes of closely related lacertids, Lacerta viridis and L. bilineata, and implications for speciation.

BACKGROUND: Lacerta viridis and Lacerta bilineata are sister species of European green lizards (eastern and western clades, respectively) that, until recently, were grouped together as the L. viridis complex. Genetic incompatibilities were observed between lacertid populations through crossing experiments, which led to the delineation of two separate species within the L. viridis complex. The population history of these sister species and processes driving divergence are unknown. We constructed the first high-quality de novo genome assemblies for both L. viridis and L. bilineata through Illumina and PacBio sequencing, with annotation support provided from transcriptome sequencing of several tissues. To estimate gene flow between the two species and identify factors involved in reproductive isolation, we studied their evolutionary history, identified genomic rearrangements, detected signatures of selection on non-coding RNA, and on protein-coding genes. FINDINGS: Here we show that gene flow was primarily unidirectional from L. bilineata to L. viridis after their split at least 1.15 million years ago. We detected positive selection of the non-coding repertoire; mutations in transcription factors; accumulation of divergence through inversions; selection on genes involved in neural development, reproduction, and behavior, as well as in ultraviolet-response, possibly driven by sexual selection, whose contribution to reproductive isolation between these lacertid species needs to be further evaluated. CONCLUSION: The combination of short and long sequence reads resulted in one of the most complete lizard genome assemblies. The characterization of a diverse array of genomic features provided valuable insights into the demographic history of divergence among European green lizards, as well as key species differences, some of which are candidates that could have played a role in speciation. In addition, our study generated valuable genomic resources that can be used to address conservation-related issues in lacertids.

Temporal ordering of substitutions in RNA evolution: Uncovering the structural evolution of the Human Accelerated Region 1.

The Human Accelerated Region 1 (HAR1) is the most rapidly evolving region in the human genome. It is part of two overlapping long non-coding RNAs, has a length of only 118 nucleotides and features 18 human specific changes compared to an ancestral sequence that is extremely well conserved across non-human primates. The human HAR1 forms a stable secondary structure that is strikingly different from the one in chimpanzee as well as other closely related species, again emphasizing its human-specific evolutionary history. This suggests that positive selection has acted to stabilize human-specific features in the ensemble of HAR1 secondary structures. To investigate the evolutionary history of the human HAR1 structure, we developed a computational model that evaluates the relative likelihood of evolutionary trajectories as a probabilistic version of a Hamiltonian path problem. The model predicts that the most likely last step in turning the ancestral primate HAR1 into the human HAR1 was exactly the substitution that distinguishes the modern human HAR1 sequence from that of Denisovan, an archaic human, providing independent support for our model. The MutationOrder software is available for download and can be applied to other instances of RNA structure evolution.