Bariatric surgery can result in remission of type 2 diabetes mellitus (T2DM). However, as not all patients will respond in the same way, a method to predict which patients are most likely to undergo remission of T2DM after bariatric surgery would be useful. Now, a team from Denmark has combined information on clinical traits and genetic variants to create a machine-learning model that could be used to predict which patients are likely to experience remission of T2DM after bariatric surgery. Insulin treatment, baseline serum levels of HbA1c and insulin and use of insulin-sensitizing agents were the most important clinical factors. Adding information on eight single nucleotide polymorphisms in ABCA1, ARHGEF12, CTNNBL1, GLI3, PROK2, RYBP, SMUG1 and STXBP5 improved the accuracy of the model.
References
Pedersen, H. K. et al. Ranking factors involved in diabetes remission after bariatric surgery using machine-learning integrating clinical and genomic biomarkers. npj Genomic Medicine http://dx.doi.org/10.1038/npjgenmed.2016.35 (2016)
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Greenhill, C. Which patients will respond to bariatric surgery?. Nat Rev Endocrinol 13, 5 (2017). https://doi.org/10.1038/nrendo.2016.188
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DOI: https://doi.org/10.1038/nrendo.2016.188
