Refinement of evolutionary medicine predictions based on clinical evidence for the manifestations of Mendelian diseases

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11120%2F19%3A43919410" target="_blank" >RIV/00216208:11120/19:43919410 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1038/s41598-019-54976-4" target="_blank" >https://doi.org/10.1038/s41598-019-54976-4</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-019-54976-4" target="_blank" >10.1038/s41598-019-54976-4</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Refinement of evolutionary medicine predictions based on clinical evidence for the manifestations of Mendelian diseases

Popis výsledku v původním jazyce

Prediction methods have become an integral part of biomedical and biotechnological research. However, their clinical interpretations are largely based on biochemical or molecular data, but not clinical data. Here, we focus on improving the reliability and clinical applicability of prediction algorithms. We assembled and curated two large non-overlapping large databases of clinical phenotypes. These phenotypes were caused by missense variations in 44 and 63 genes associated with Mendelian diseases. We used these databases to establish and validate the model, allowing us to improve the predictions obtained from EVmutation, SNAP2 and PoPMuSiC 2.1. The predictions of clinical effects suffered from a lack of specificity, which appears to be the common constraint of all recently used prediction methods, although predictions mediated by these methods are associated with nearly absolute sensitivity. We introduced evidence-based tailoring of the default settings of the prediction methods; this tailoring substantially improved the prediction outcomes. Additionally, the comparisons of the clinically observed and theoretical variations led to the identification of large previously unreported pools of variations that were under negative selection during molecular evolution. The evolutionary variation analysis approach described here is the first to enable the highly specific identification of likely disease-causing missense variations that have not yet been associated with any clinical phenotype.

Název v anglickém jazyce

Refinement of evolutionary medicine predictions based on clinical evidence for the manifestations of Mendelian diseases

Popis výsledku anglicky

Prediction methods have become an integral part of biomedical and biotechnological research. However, their clinical interpretations are largely based on biochemical or molecular data, but not clinical data. Here, we focus on improving the reliability and clinical applicability of prediction algorithms. We assembled and curated two large non-overlapping large databases of clinical phenotypes. These phenotypes were caused by missense variations in 44 and 63 genes associated with Mendelian diseases. We used these databases to establish and validate the model, allowing us to improve the predictions obtained from EVmutation, SNAP2 and PoPMuSiC 2.1. The predictions of clinical effects suffered from a lack of specificity, which appears to be the common constraint of all recently used prediction methods, although predictions mediated by these methods are associated with nearly absolute sensitivity. We introduced evidence-based tailoring of the default settings of the prediction methods; this tailoring substantially improved the prediction outcomes. Additionally, the comparisons of the clinically observed and theoretical variations led to the identification of large previously unreported pools of variations that were under negative selection during molecular evolution. The evolutionary variation analysis approach described here is the first to enable the highly specific identification of likely disease-causing missense variations that have not yet been associated with any clinical phenotype.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30202 - Endocrinology and metabolism (including diabetes, hormones)

Projekt

<a href="/cs/project/GJ15-03834Y" target="_blank" >GJ15-03834Y: Mechanismy vzniku, progrese a terapie monogenních typů diabetu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Scientific Reports

ISSN

2045-2322

e-ISSN

—

Svazek periodika

9

Číslo periodika v rámci svazku

December

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

17

Strana od-do

"Article 18577"

Kód UT WoS článku

000501751300001

EID výsledku v databázi Scopus

2-s2.0-85076356246