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. 2023 Jul 20;13(7):1164.
doi: 10.3390/jpm13071164.

The First Exploratory Personalized Medicine Approach to Improve Bariatric Surgery Outcomes Utilizing Psychosocial and Genetic Risk Assessments: Encouraging Clinical Research

Panayotis K Thanos  1   2 , Colin Hanna  1 , Abrianna Mihalkovic  1   2 , Aaron B Hoffman  3 , Alan R Posner  4 , John Busch  4 , Caroline Smith  5 , Rajendra D Badgaiyan  6 , Kenneth Blum  7   8   9   10   11   12   13 , David Baron  8 , Lucy D Mastrandrea  3 , Teresa Quattrin  3
Affiliations

The First Exploratory Personalized Medicine Approach to Improve Bariatric Surgery Outcomes Utilizing Psychosocial and Genetic Risk Assessments: Encouraging Clinical Research

Panayotis K Thanos et al. J Pers Med. .

Abstract

It is predicted that by 2030, globally, an estimated 2.16 billion adults will be overweight, and 1.12 billion will be obese. This study examined genetic data regarding Reward Deficiency Syndrome (RDS) to evaluate their usefulness in counselling patients undergoing bariatric surgery and gathered preliminary data on the potential use in predicting short term (6-month) weight loss outcomes. Methods: Patients undergoing bariatric surgery (n = 34) were examined for Genetic Addiction Risk Severity (GARS) [measures the presence of risk alleles associated with RDS]; as well as their psychosocial traits (questionnaires). BMI changes and sociodemographic data were abstracted from Electronic Health Records. Results: Subjects showed ∆BMI (M = 10.0 ± 1.05 kg/m2) and a mean % excess weight loss (56 ± 13.8%). In addition, 76% of subjects had GARS scores above seven. The homozygote risk alleles for MAO (rs768062321) and DRD1 (rs4532) showed a 38% and 47% prevalence among the subjects. Of the 11 risk alleles identified by GARS, the DRD4 risk allele (rs1800955), was significantly correlated with change in weight and BMI six months post-surgery. We identified correlations with individual risk alleles and psychosocial trait scores. The COMT risk allele (rs4680) showed a negative correlation with EEI scores (r = -0.4983, p < 0.05) and PSQI scores (r = -0.5482, p < 0.05). The GABRB3 risk allele (rs764926719) correlated positively with EEI (r = 0.6161, p < 0.01) and FCQ scores (r = 0.6373, p < 0.01). The OPRM1 risk allele showed a positive correlation with the DERS score (r = 0.5228, p < 0.05). We also identified correlations between DERS and BMI change (r = 0.61; p < 0.01). Conclusions: These data support the potential benefit of a personalized medicinal approach inclusive of genetic testing and psychosocial trait questionnaires when counselling patients with obesity considering bariatric surgery. Future research will explore epigenetic factors that contribute to outcomes of bariatric surgery.

Keywords: Reward Deficiency Syndrome; addiction; bariatric surgery; genetic risk assessment; obesity; psychosocial risk factors.

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Conflict of interest statement

Blum is the inventor of the Genetic Addiction Risk Severity (GARS) test and KB220 pro-dopamine variants and through his companies Synaptamine, Inc. and SpliceGen Holdings own all relevant worldwide patents.

Figures

Figure 1
Figure 1
GARS results represented as the percent frequency of gene type for each risk allele analyzed within the patient population (n = 34). The homozygote category represents having two copies of the risk allele, heterozygous represents one copy of the risk allele, and the low-risk category represents no copies of the risk allele per gene.
Figure 2
Figure 2
Frequency of patients with a GARS score qualifying them for high risk or low risk of alcohol addiction. Risk category is based on total number of GARS risk alleles.
Figure 3
Figure 3
(a–j). BMI and specific psychosocial inventory outcomes are correlated with GARS: (a) DRD4 risk allele positively correlated with preop weight (r = 0.4331, R2 = 0.1876, p = 0.0345); (b) DRD4 risk allele positively correlated with change in weight (r = 0.4726, R2 = 0.2234, p = 0.0197); (c) DRD4 risk allele positively correlated with change in BMI (r = 0.4577, R2 = 0.2095, p = 0.0245) (d) COMT risk allele negatively correlated with EEI scores (r = −0.4983, R2 = 0.2483, p = 0.0418); (e) COMT risk allele negatively correlated with PSQI scores (r = −0.5482, R2 = 0.3005, p = 0.0279); (f) GABRB3 risk allele positively correlated with EEI scores (r = 0.6161, R2 = 0.3796, p = 0.0084); (g) GABRB3 risk allele positively correlated with FCQ scores (r = 0.6373, R2 = 0.4062, p = 0.0044); (h) OPRM1 risk allele positively correlated with DERS scores (r = 0.5228, R2 = 0.2733, p = 0.0260). (i) DERS scores negatively correlated with preop BMI (r = −0.5142, R2 = 0.2644, p = 0.0290); (j) DERS scores negatively correlated with BMI 6 months post-surgery (r = −0.6137, R2 = 0.3766, p = 0.0068).
Figure 4
Figure 4
(a–c). Heterosis in DRD4 gene: (a) significant difference (t = 2.400, p = 0.03) of mean change in weight at 6 months between patients with 0 and 1 copies of the DRD4 risk allele; (b) significant difference (t = 2.234, p = 0.04) of mean change in BMI at 6 months between patients with 0 and 1 copies of the DRD4 risk allele; (c) significant difference (t = 2.418, p = 0.03) of %EWL at 6 months between patients with 0 and 1 copies of the DRD4 risk allele. Data are M ± SEM Student’s t test.
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