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

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.

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

“…Understanding these results should clinically translate to the patient providing additional positivity and as such augmented attitude based on genetic and psychosocial information. This report is the second part of a longitudinal study observing the genetic and psychosocial effects on bariatric surgery outcomes [62]. A summary of the present findings along with previous data can be seen in Table 2.…”

“…The Yale Food Addiction Scale (mYFAS) results were lower than anticipated [67,68]. The summarized psychosocial scores (previously reported) [62] can be seen in Table 3. GARS results were categorized as homozygote (two copies of the risk allele), heterozygote (one copy of the risk allele), or low risk (no copies of the risk allele).…”

“…These reports included: nutrition (Eating Attitudes Test-26 (EAT-26) [53]; Food Cravings Questionnaire-Trait Reduced (FCQ-TR) [54]; Eating Expectancies Inventory (EEI) [55]; food addiction (modified Yale Food Addiction Scale 2.0 (mYFAS 2.0) [56]; binge-eating disorder symptoms (Weight-Influenced Self-Esteem Questionnaire (WISE-Q) [57]; depression and anxiety (Difficulties in Emotion Regulation Scale) (DERS) [58]; Center for Epidemiologic Studies Depression Scale (CESDS) [59], and chronic stress and life quality (Chronic Stress Index (CSI) [60]; sleep (Pittsburgh Sleep Quality Index (PSQI) [61]. This methodology was utilized as previously described [62].…”

Genes linked to obesity-related infertility: bridging the knowledge gap

“…This knowledge can be translated into personalized nutrition plans tailored to an individual's genetic predisposition to manage obesity and improve fertility outcomes [57] . Additionally, understanding genetic factors can help identify individuals who may benefit from specific interventions, such as bariatric surgery, based on their genetic risk assessments [58] . Furthermore, the impact of obesity on female fertility and fertility treatment outcomes has been a subject of research, highlighting the importance of personalized approaches in managing obesity-related infertility Furthermore, the impact of obesity on female fertility and fertility treatment outcomes has been a subject of research, highlighting the importance of personalized approaches in managing obesity-related infertility [59] .…”

A Pharmacogenomics-Based In Silico Investigation of Opioid Prescribing in Post-operative Spine Pain Management and Personalized Therapy

“…The statistical analyses found the OR, 95% CI for OR, and a post-risk for 8% estimation of the population's alcoholism prevalence showed a significant detection. The OR results indicated significance for COMT, OPRM1, DRD2, DRD3, DRD4, DAT1, and 5HTT at 5% (Blum et al 2018 , 2020 , 2021 ; Blum et al 2022a , b ; Blum et al 2022a , b ; Fried et al 2020 ; Moran et al 2021 ; Bajaj et al 2022 ; Dennen et al 2022 ; Gondré-Lewis et al 2022 ; Gupta et al 2022 ; Vereczkei et al 2022 ; Thanos et al 2023a , b ; Thanos et al 2023a , b ). Consequently, this study aimed to explore the most effective pharmacogenomic approach to managing spinal pain in postoperative patients by analyzing potential actionable genetic variants associated with FDA-approved drugs targeting specific receptors, that is, the genes themselves (Table 2 ).…”