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medRxivGenetic & Genomic MedicinePreprint

Integration of proteomics with genomics and transcriptomics increases the diagnostic rate of Mendelian disorders

Robert KopajtichiD, Dmitrii SmirnoviD, Sarah L. StentoniD, Stefan LoipfingeriD, Chen MengiD, Ines F. SchelleriD, Peter FreisingeriD, Robert Baski, Riccardo BeruttiiD, Jürgen Behr, Martina Bucher, Felix DistelmaieriD, Elisabeth GrafiD, Mirjana GušićiD, Maja HempeliD, Lea Kulterer, Johannes Adalbert MayriD, Thomas MeitingeriD, Christian MertesiD, Metodi Dimitrov MetodieviD, Agnieszka NadeliD, Alessia NascaiD, Akira OhtakeiD, Yasushi OkazakiiD, Rikke Katrine Jentoft OlseniD, , Holger ProkischiD

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Abstract

By lack of functional evidence, genome-based diagnostic rates cap at approximately 50% across diverse Mendelian diseases. Here, we demonstrate the effectiveness of combining genomics, transcriptomics, and, for the first time, proteomics and phenotypic descriptors, in a systematic diagnostic approach to discover the genetic cause of mitochondrial diseases. On fibroblast cell lines from 145 individuals, tandem mass tag labelled proteomics detected approximately 8,000 proteins per sample and covered over 50% of all Mendelian disease-associated genes. Aberrant protein expression analysis allowed the validation of candidate protein-destabilising variants, in addition to providing independent complementary functional evidence to variants leading to aberrant RNA expression. Overall, our integrative computational workflow led to genetic resolution for 22% of 121 genetically unsolved whole exome or whole genome negative cases and to the discovery of two novel disease genes. With increasing democratization of high-throughput omics assays, our approach and code provide a blueprint for implementing multi-omics based Mendelian disease diagnostics in routine clinical practice.

Abstract summary

Claude Opus 5.5 · xhigh effort · 18 Oct 2026 · from the abstract · CC BY-NC-ND 4.0

Adding tandem mass tag proteomics to genome and transcriptome data resolved 22% of 121 unsolved suspected mitochondrial disease cases and surfaced two new disease genes.

Genome-based diagnosis caps at about half of Mendelian cases, which the authors attribute to a lack of functional evidence. This work adds proteomics, alongside genomics, transcriptomics and phenotypic descriptors, as a second functional read-out for candidate variants.

Key results

  1. ShownThe integrated workflow produced a genetic diagnosis in 22% of cases that exome or genome sequencing had left unexplained, and identified two previously unreported disease genes.

    Genetic resolution for 22% of 121 genetically unsolved cases that were negative on whole exome or whole genome sequencing, plus two novel disease genes. · Abstract

  2. ShownProteomics covers enough of the clinically relevant gene space to be usable as a diagnostic layer in patient fibroblasts.

    Tandem mass tag labelled proteomics quantified approximately 8,000 proteins per sample in fibroblast lines from 145 individuals, spanning over 50% of genes already associated with Mendelian disease; genome-based diagnosis alone is cited as capping near 50%. · Abstract

  3. ClaimedOutlier protein levels supply functional evidence of two kinds: confirming variants predicted to destabilise a protein, and independently backing variants that show aberrant RNA expression.

    Described qualitatively as aberrant protein expression analysis; the abstract reports no counts of validated variants, no false-positive rate and no concordance figure between the protein and RNA signals. · Abstract

Methods, data and reproducibility

Patient-derived fibroblast lines were profiled with tandem mass tag labelled quantitative proteomics and combined with genome, transcriptome and phenotype information in one computational workflow that flags aberrant protein and RNA expression to prioritise and validate candidate causal variants.

  • Fibroblast cell lines profiled by tandem mass tag proteomics · human · n = 145 individuals
  • Genetically unsolved cases negative on whole exome or whole genome sequencing · human · n = 121 cases
Methods & tools
tandem mass tag labelled proteomics, whole exome sequencing, whole genome sequencing
Reproducibility gaps
The authors offer their approach and code as a blueprint for clinical use, but the abstract gives no repository URL and no accession for the proteomics, RNA or sequencing data.
Limitations (2)
  • Profiling is done in fibroblasts, so disease genes not expressed in that cell type cannot produce an aberrant protein or RNA signal. · noted in this summary
  • The cohort is centred on suspected mitochondrial disease, so the 22% additional yield need not carry over to other Mendelian presentations. · noted in this summary

Read this if you run or design diagnostic pipelines for rare disease and want to know what quantitative proteomics adds on top of exome, genome and RNA sequencing.

Citations
47

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