Transcriptome Changes and Metabolic Outcomes After Bariatric Surgery in Adults With Obesity and Type 2 Diabetes

Author:

Rashid Mamoon1ORCID,Al Qarni Ali2ORCID,Al Mahri Saeed3ORCID,Mohammad Sameer3ORCID,Khan Altaf4,Abdullah Mashan L3ORCID,Lehe Cynthia3ORCID,Al Amoudi Reem2,Aldibasi Omar4ORCID,Bouchama Abderrezak3ORCID

Affiliation:

1. Department of AI and Bioinformatics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs , Riyadh 11426 , Saudi Arabia

2. Endocrinology and Metabolism, Department of Medicine, King Abdulaziz Hospital, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs , Al Ahsa 31982 , Saudi Arabia

3. Experimental Medicine Department, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs , Riyadh 11426 , Saudi Arabia

4. Department of Biostatistics, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs , Riyadh , Saudi Arabia

Abstract

Abstract Context Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery. Objective We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome. Methods We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction. Results Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (SKT4, SIRT1, and TNF superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery. Conclusion The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.

Funder

King Abdulaziz City Science and Technology

King Abdullah International Medical Research Center

Publisher

The Endocrine Society

Subject

Endocrinology, Diabetes and Metabolism

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