Predictors of weight loss in participants with obesity following bariatric surgery – A prospective longitudinal fMRI study

Bach, Patrick; Grosshans, Martin; Koopmann, Anne; Pfeifer, Anna-Maria; Vollstädt‐Klein, Sabine; Otto, Mirko; Kienle, Peter; Bumb, Jan Malte; Kiefer, Falk

doi:10.1016/j.appet.2021.105237

Cited by 11 publications

(13 citation statements)

References 53 publications

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“…Our findings are in agreement with studies that report increased activation in behavioral control regions after bariatric surgery (Bruce et al, 2012;Goldman et al, 2013;Holsen et al, 2018;Zoon et al, 2018;Baboumian et al, 2019;Bach et al, 2021;Koenis et al, 2021), although some studies report a post-surgical decrease in the dorsolateral PFC (Ochner et al, 2012b), or decreased activity of the angular gyrus after weight loss intervention (Murdaugh et al, 2012). Activation of the visual cortex is also associated with food picture viewing (van der Laan et al, 2011;Tang et al, 2012;van Meer et al, 2015;Bach et al, 2021), and activity in these regions decreases after weight loss interventions (Bruce et al, 2014;Baboumian et al, 2019). Lower activation in visual processing areas during sham-deflation and after surgery could be related to decreased salience to (appetitive) food when the stomach is restricted (Tang et al, 2012).…”

Section: Discussionsupporting

confidence: 93%

“… Ness et al (2014) reported that LAGB participants with higher pre-operative activity in brain regions associated with cognitive control (prefrontal cortex, posterior cingulate) showed more weight loss 3–6 months post-surgery. The brain’s response to food pictures is also changed after Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) ( Pursey et al, 2014 ; Faulconbridge et al, 2016 ; Zoon et al, 2018 ; Baboumian et al, 2019 ; Bach et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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Food cue reactivity in successful laparoscopic gastric banding: A sham-deflation-controlled pilot study

Koenis

Anderson

et al. 2022

Front. Hum. Neurosci.

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Laparoscopic adjustable gastric banding (LAGB) offers a unique opportunity to examine the underlying neuronal mechanisms of surgically assisted weight loss due to its instant, non-invasive, adjustable nature. Six participants with stable excess weight loss (%EWL ≥ 45) completed 2 days of fMRI scanning 1.5–5 years after LAGB surgery. In a within-subject randomized sham-controlled design, participants underwent (sham) removal of ∼ 50% of the band’s fluid. Compared to sham-deflation (i.e., normal band constriction) of the band, in the deflation condition (i.e., decreasing restriction) participants showed significantly lower activation in the anterior (para)cingulate, angular gyrus, lateral occipital cortex, and frontal cortex in response to food images (p < 0.05, whole brain TFCE-based FWE corrected). Higher activation in the deflation condition was seen in the fusiform gyrus, inferior temporal gyrus, lingual gyrus, lateral occipital cortex. The findings of this within-subject randomized controlled pilot study suggest that constriction of the stomach through LAGB may indirectly alter brain activation in response to food cues. These neuronal changes may underlie changes in food craving and food preference that support sustained post-surgical weight-loss. Despite the small sample size, this is in agreement with and adds to the growing literature of post-bariatric surgery changes in behavior and control regions.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Food cue reactivity in successful laparoscopic gastric banding: A sham-deflation-controlled pilot study

Koenis

Anderson

et al. 2022

Front. Hum. Neurosci.

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“…Some studies did not support a link between incentive salience or goal-directed control and treatment outcome. The fMRI studies of Bach et al and Ten Kulve et al did not show such a link [ 85 , 86 ]. In addition, associations between cortical thickness of the superior frontal gyrus and weight loss reported by Liu et al did not reach a multiple comparison corrected significance level [ 148 ].…”

Section: Discussionmentioning

confidence: 99%

“…However, some studies did not support a link between incentive salience and treatment outcome. Specifically, neither the BS fMRI study of Bach et al nor the PI fMRI study of Ten Kulve et al found significant associations between brain activity evoked by food-cue presentation before the treatment and treatment-induced weight loss [ 85 , 86 ].…”

Section: Central Nervous Mechanisms Affecting Body Weightmentioning

confidence: 99%

“…For the interpretation of parameters reported in columns “Modelling: Outcome”, “Predictor”, and “Significant prediction results”, please see Table 1 Study Modelling: Outcome #Participants (per group) Experimental design Predictor Pred. meth Significant prediction results Task-fMRI Bach et al [ 85 ] Prognostic: Bodyweight 11 OB: 10 RYGB, 1 SG T0 (2 weeks before surgery) T6.5 (24 weeks after surgery) Voxel CR activity OLS CR_fMRI_T0 → OUT_T0_6.5: No association between WL and evaluated neuroimaging predictors was found Smith et al [ 176 ] Prognostic: Bodyweight 39 OB: 19 RYGB, 20 SG T0 (pre surgery), T6 (after 6 months) Voxel CR activity OLS CR_fMRI_T0 → OUT_T0_6: Negative association between WL and CR activity of ventral tegmental area after RYGB (but not SG) Holsen et al [ 196 ] Prognostic: Bodyweight 18 OB: SG T0 (pre surgery), T12 (12 months after surgery) Voxel CrvR activity OLS CrvR_fMRI_T0 → OUT_T0_12: Negative association between WL and upregulated CR activity in ncl. accumbens and hypothalamus Ness et al [ 178 ] Prognostic: Bodyweight 19 OB: LAGB T0 (pre surgery), T3 (3 months after surgery), T6 (6 months after surgery) Voxel CR activity OLS CR_fMRI_T0 → OUT_T0_3: Positive association between WL and CR activity in left superior frontal and transverse temporal gyrus; Negative association between WL and CR activity in right and left post.…”

Section: Study Overviewmentioning

confidence: 99%

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Computational approaches to predicting treatment response to obesity using neuroimaging

Kozarzewski

Maurer

Mähler

et al. 2021

Rev Endocr Metab Disord

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Obesity is a worldwide disease associated with multiple severe adverse consequences and comorbid conditions. While an increased body weight is the defining feature in obesity, etiologies, clinical phenotypes and treatment responses vary between patients. These variations can be observed within individual treatment options which comprise lifestyle interventions, pharmacological treatment, and bariatric surgery. Bariatric surgery can be regarded as the most effective treatment method. However, long-term weight regain is comparably frequent even for this treatment and its application is not without risk. A prognostic tool that would help predict the effectivity of the individual treatment methods in the long term would be essential in a personalized medicine approach. In line with this objective, an increasing number of studies have combined neuroimaging and computational modeling to predict treatment outcome in obesity. In our review, we begin by outlining the central nervous mechanisms measured with neuroimaging in these studies. The mechanisms are primarily related to reward-processing and include “incentive salience” and psychobehavioral control. We then present the diverse neuroimaging methods and computational prediction techniques applied. The studies included in this review provide consistent support for the importance of incentive salience and psychobehavioral control for treatment outcome in obesity. Nevertheless, further studies comprising larger sample sizes and rigorous validation processes are necessary to answer the question of whether or not the approach is sufficiently accurate for clinical real-world application.

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Towards precision medicine in bariatric surgery prescription

Pereira

Guimarães

Monteiro

2023

Rev Endocr Metab Disord

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Obesity is a complex, multifactorial and chronic disease. Bariatric surgery is a safe and effective treatment intervention for obesity and obesity-related diseases. However, weight loss after surgery can be highly heterogeneous and is not entirely predictable, particularly in the long-term after intervention. In this review, we present and discuss the available data on patient-related and procedure-related factors that were previously appointed as putative predictors of bariatric surgery outcomes. In addition, we present a critical appraisal of the available evidence on which factors could be taken into account when recommending and deciding which bariatric procedure to perform. Several patient-related features were identified as having a potential impact on weight loss after bariatric surgery, including age, gender, anthropometrics, obesity co-morbidities, eating behavior, genetic background, circulating biomarkers (microRNAs, metabolites and hormones), psychological and socioeconomic factors. However, none of these factors are sufficiently robust to be used as predictive factors. Overall, there is no doubt that before we long for precision medicine, there is the unmet need for a better understanding of the socio-biological drivers of weight gain, weight loss failure and weight-regain after bariatric interventions. Machine learning models targeting preoperative factors and effectiveness measurements of specific bariatric surgery interventions, would enable a more precise identification of the causal links between determinants of weight gain and weight loss. Artificial intelligence algorithms to be used in clinical practice to predict the response to bariatric surgery interventions could then be created, which would ultimately allow to move forward into precision medicine in bariatric surgery prescription.

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Predictors of weight loss in participants with obesity following bariatric surgery – A prospective longitudinal fMRI study

Cited by 11 publications

References 53 publications

Food cue reactivity in successful laparoscopic gastric banding: A sham-deflation-controlled pilot study

Food cue reactivity in successful laparoscopic gastric banding: A sham-deflation-controlled pilot study

Computational approaches to predicting treatment response to obesity using neuroimaging

Towards precision medicine in bariatric surgery prescription

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