Genetic Correlates as a Predictor of Bariatric Surgery Outcomes after 1 Year

Author:

Thanos Panayotis K.1,Hanna Colin1,Mihalkovic Abrianna12,Hoffman Aaron3ORCID,Posner Alan4,Butsch John4,Blum Kenneth567891011ORCID,Georger Lesley12,Mastrandrea Lucy D.13,Quattrin Teresa13

Affiliation:

1. Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Department of Pharmacology and Toxicology, Clinical Research Institute on Addictions, Jacobs School of Medicine and Biosciences, University at Buffalo, Buffalo, NY 14203, USA

2. Department of Psychology, University at Buffalo, Buffalo, NY 14203, USA

3. Department of Surgery, Methodist Hospital Medical Center, Dallas, TX 75208, USA

4. Department of Surgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY 14203, USA

5. Division of Nutrigenomics, SpliceGen, Therapeutics, Inc., Austin, TX 78701, USA

6. Department of Psychiatry, Wright State University Boonshoft School of Medicine and Dayton VA Medical Center, Dayton, OH 45435, USA

7. Division of Addiction Research & Education, Center for Exercise Sports & Global Mental Health, Western University Health Sciences, Pomona, CA 91766, USA

8. The Kenneth Blum Behavioral & Neurogenetic Institute, LLC., Austin, TX 78701, USA

9. Institute of Psychology, ELTE Eötvös Loránd University, 1075 Budapest, Hungary

10. Centre for Genomics and Applied Gene Technology, Institute of Integrative Omics and Applied Biotechnology (IIOAB), Nonakuri, Purba Medinipur 721172, West Bengal, India

11. Department of Molecular Biology, Adelson School of Medicine, Ariel University, Ariel 40700, Israel

12. Department of Natural Sciences and Mathematics, D’Youville University, Buffalo, NY 14201, USA

13. UBMD Pediatrics, JR Oishei Children’s Hospital, University at Buffalo, Buffalo, NY 14203, USA

Abstract

This study analyzed genetic risk assessments in patients undergoing bariatric surgery to serve as a predictive factor for weight loss parameters 1 year after the operation. Thirty (30) patients were assessed for Genetic Addiction Risk Severity (GARS), which analyzes neurogenetic polymorphisms involved in addiction and reward deficiency. Genetic and psychosocial data collected before the operation were correlated with weight loss data, including changes in weight, body mass index (BMI), and percent of expected weight loss (%EWL). Results examined correlations between individual gene risk alleles, 1-year body weight data, and psychosocial trait scores. Spearman’s correlations revealed that the OPRM1 (rs1799971) gene polymorphism had significant negative correlation with 1-year weight (rs = −0.4477, p < 0.01) and BMI (rs = −0.4477, p < 0.05). In addition, the DRD2 risk allele (rs1800497) was correlated negatively with BMI at 1 year (rs = −0.4927, p < 0.05), indicating that one risk allele copy was associated with lower BMI. However, this allele was positively correlated with both ∆Weight (rs = 0.4077, p < 0.05) and %EWL (rs = 0.5521, p < 0.05) at 1 year post-surgery. Moreover, the overall GARS score was correlated with %EWL (rs = 0.4236, p < 0.05), ∆Weight (rs = 0.3971, p < 0.05) and ∆BMI (rs = 0.3778, p < 0.05). Lastly, Food Cravings Questionnaire (FCQ) scores were negatively correlated with %EWL (rs = −0.4320, p < 0.05) and ∆Weight at 1 year post-surgery (rs = −0.4294, p < 0.05). This suggests that individuals with a higher genetic addiction risk are more responsive to weight loss treatment, especially in the case of the DRD2 polymorphism. These results should translate clinically to improve positivity and attitude related to weight management by those individuals born with the risk alleles (rs1800497; rs1799971).

Funder

University at Buffalo VPR Buffalo Blue Sky

Publisher

MDPI AG

Subject

General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)

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