The usage of different synonymous codons reflects the genome organization and has been connected to parameters such as mRNA abundance and protein folding. It is also been established that mutations targeting specific synonymous codons can trigger disease. We performed a systematic meta-analysis of transcriptome results from 75 datasets representing 40 pathologies. We found that a subset of codons was preferentially employed in abundant transcripts, while other codons were preferentially found in low-abundance transcripts. By comparing control and pathological transcriptomes, we observed a shift in the employment of synonymous codons for every analyzed disease. For example, cancerous tissue employed preferentially A- or U-ending codons, shifting from G- or C-ending codons, which were preferred by control tissues. This analysis was able to discriminate patients and controls with high specificity and sensitivity. Here we show that the employment of specific synonymous codons, quantified at the whole transcriptome level, changes profoundly in many diseases. We propose that the changes in codon employment offer a novel perspective for disease studies, and could be used to design new diagnostic tools.
