Article (Scientific journals)
SyMetrics: an integrated machine learning model for evaluating the pathogenicity of synonymous variants in the human genome
Bundalian, Linnaeus; Strnadová, Martina Schmidt; Garten, Felix et al.
2026In NAR Genomics and Bioinformatics, 8 (1)
Peer Reviewed verified by ORBi
 

Files


Full Text
lqaf211.pdf
Publisher postprint (2.72 MB) Creative Commons License - Public Domain Dedication
Download

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Synonymous variants; Machine Learning; Genetics; Genomics
Abstract :
[en] Synonymous single nucleotide variants (sSNVs), traditionally seen as neutral, are now recognized for their biological impact. To assess their relevance, we developed SyMetrics, a framework that integrates predictors of splicing, RNA stability, evolutionary conservation, codon usage, synonymous variation effects, sequence properties, and allele frequency. We analyzed all possible sSNVs across the human genome, and our machine-learning model achieved 97% accuracy in distinguishing deleterious from benign variants, with a ROC–AUC of 0.89, outperforming individual predictors. Our estimates indicate that about 1.98 ± 0.17% of sSNVs absent from population databases are damaging (roughly 900 000 sSNVs), with an odds ratio of 3.87 for deleteriousness compared to common sSNVs (P < 0.05). To validate predictions, we performed functional assays on selected sSNVs in the AVPR2 gene and additionally used available large scale mutagenesis screens of RAD51C and BAP1 variants. In a clinical cohort, we identified 15 predicted deleterious sSNVs in genes linked to patient phenotypes; 9 were classified as (likely) pathogenic while 6 were variants of uncertain significance (VUS) per American College of Medical Genetics guidelines. For three VUS, segregation data supported their suspected inheritance patterns (de novo, X-linked). Our findings underscore the functional importance of sSNVs. To support further research and clinical applications, we provide a Python package and web application (https://symetrics.org/) for evaluating these variants comprehensively.
Research center :
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Genetics & genetic processes
Author, co-author :
Bundalian, Linnaeus ;  Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Saxony 04103 , ; Institute for Clinical Genetics, Technische Universität Dresden, and National Cancer Center (NCT) Dresden , Dresden, Saxony 01307 ,
Strnadová, Martina Schmidt;  Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, University of Leipzig , Leipzig, Saxony 04103 ,
Garten, Felix;  Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Saxony 04103 ,
Horn, Susanne ;  Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, University of Leipzig , Leipzig, Saxony 04103 ,
Stenzel, Udo;  Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, University of Leipzig , Leipzig, Saxony 04103 ,
Popp, Denny;  Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Saxony 04103 ,
Lemke, Johannes R;  Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Saxony 04103 ,
Biskup, Saskia;  CeGaT GmbH , Tübingen, Baden-Württemberg 72076 ,
Schulte, Björn;  CeGaT GmbH , Tübingen, Baden-Württemberg 72076 ,
MAY, Patrick  ;  University of Luxembourg
Bösebeck, Frank;  Agaplesion Diakonie Clinic Rottenburg , Rottenburg, Lower Saxony 27356 ,
Garten, Antje;  Hospital for Children and Adolescents and Center for Pediatric Research (CPL), University of Leipzig , Leipzig, Saxony 04103 ,
Thor, Doreen;  Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, University of Leipzig , Leipzig, Saxony 04103 ,
Schulz, Angela;  Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, University of Leipzig , Leipzig, Saxony 04103 ,
Hentschel, Julia;  Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Saxony 04103 ,
Kelso, Janet ;  Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology , Leipzig, Saxony 04103 ,
Schöneberg, Torsten;  Rudolf Schönheimer Institute of Biochemistry, Medical Faculty, University of Leipzig , Leipzig, Saxony 04103 , ; School of Medicine, University of Global Health Equity , Kigali 6955 ,
Le Duc, Diana ;  Institute of Human Genetics, University of Leipzig Medical Center , Leipzig, Saxony 04103 , ; Institute for Clinical Genetics, Technische Universität Dresden, and National Cancer Center (NCT) Dresden , Dresden, Saxony 01307 , ; Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology , Leipzig, Saxony 04103 , ; Center for Diagnostics GmbH, Department of Genetics, Chemnitz Clinics , Chemnitz, Saxony 09116 ,
More authors (8 more) Less
External co-authors :
yes
Language :
English
Title :
SyMetrics: an integrated machine learning model for evaluating the pathogenicity of synonymous variants in the human genome
Publication date :
06 January 2026
Journal title :
NAR Genomics and Bioinformatics
eISSN :
2631-9268
Publisher :
Oxford University Press (OUP)
Volume :
8
Issue :
1
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Systems Biomedicine
Development Goals :
3. Good health and well-being
Funders :
Else Kroner-Fresenius-Stiftung
German Research Foundation
Deutsche Forschungsgemeinschaft
Deutsche Forschungsgemeinschaft
Funding text :
This study is funded by the Else Kroner-Fresenius-Stiftung 2020_EKEA.42 to D.L.D., the German Research Foundation SFB 1052 project B10 to D.L.D. and A.G, and Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through CRC 1423/2 (project number 421152132) to T.S. and D.T..
Available on ORBilu :
since 16 January 2026

Statistics


Number of views
15 (0 by Unilu)
Number of downloads
1 (0 by Unilu)

Scopus citations®
 
0
Scopus citations®
without self-citations
0
OpenCitations
 
0
OpenAlex citations
 
0

Bibliography


Similar publications



Contact ORBilu