Myths Associated with Obesity and Bariatric Surgery—Myth 5: “Patient behavior is the primary determinant of outcomes after bariatric surgery.”

| August 20, 2012

Exclusive Series: The Metabolic Applied Research Strategy initiative

Part 6: Myths Associated with Obesity and Bariatric Surgery
Myth 5: “Patient behavior is the primary determinant of outcomes after bariatric surgery.”

by Lee M. Kaplan, MD, PhD; Randy J. Seeley, PhD; and Jason L. Harris, PhD

Bariatric Times. 2012;9(8):8–10

The Metabolic Applied Research Strategy is a multi-year, multi-generational collaborative research program between the Massachusetts General Hospital, the University of Cincinnati, and Ethicon Endo-Surgery. Its focus is to interrogate and understand the physiologic and metabolic changes that occur after bariatric surgery (i.e., how bariatric surgery works to resolve conditions such as type 2 diabetes) with the goal of inventing new, less invasive, and less expensive treatments for patients suffering from obesity and its related health issues. In this article, which is the sixth in a series of articles published in Bariatric Times dedicated to the Metabolic Applied Research Strategy initiative, the authors discuss past and present understanding on why bariatric surgery works, its mechanism of action, and how these findings might help researchers, surgeons, and industry harness the remarkable effectiveness of bariatric surgery.

Lee M. Kaplan, MD, PhD
Lee M. Kaplan, MD, PhD, is Director of the Obesity, Metabolism & Nutrition Institute at Massachusetts General Hospital (MGH) and Associate Professor of Medicine at Harvard Medical School. He is the Director of the subspecialty Fellowship Program in Obesity Medicine and Nutrition at MGH; Associate Director of the NIH-sponsored Boston-area Obesity and Nutrition Research Center; a member of the NIH Clinical Obesity Research Panel; and past chairman of the Board of the Campaign to End Obesity. Dr. Kaplan’s clinical expertise is in the areas of obesity medicine, gastroenterology, and liver disease. His research program is focused on understanding the mechanisms by which the gastrointestinal tract regulates metabolic function and using physiological and genetic approaches to identify therapeutically relevant subtypes of obesity and its complications.

Randy J. Seeley, PhD
Dr. Randy J. Seeley is Professor of Medicine and holds the Donald C. Harrison Endowed Chair at the University of Cincinnati College of Medicine. In 2009, Dr. Seeley was appointed as the Director of the Cincinnati Diabetes and Obesity Center (CDOC). His scientific work has focused on the actions of various peripheral hormones in the central nervous system that serve to regulate food intake, body weight, and the regulation of circulating fuels. In particular, he focuses upon the numerous hypothalamic and gastrointestinal peptides and their associated receptors that influence both energy intake as well as peripheral metabolic processes with the aim of developing new treatment strategies for both obesity and diabetes.

Jason L. Harris, PhD
Dr. Jason L. Harris is a Principal Engineer leading Metabolic Applied Research Strategy co-invention and product development efforts at Ethicon Endo-Surgery, a Johnson and Johnson company. Since 2006, he has been exploring novel treatment approaches for patients suffering from the effects of metabolic disease. His primary focus is applying insights from basic and applied research efforts to develop improved therapies and predictive tools for the treatment of this disease.


The therapeutic effects of bariatric surgery are clear. Compared with other treatments for obesity, these operations routinely induce substantially more sustained weight loss than lifestyle changes and medication (Figure 1). Moreover, as a result of both the weight loss itself and weight-independent physiological effects of the gastrointestinal (GI) manipulation, bariatric procedures lead to long-term improvements in diabetes, other metabolic disorders, cardiovascular risk factors, cancer outcomes, quality of life, and overall mortality.[1–7] Despite these impressive results, however, many studies have demonstrated that outcomes after each of these operations vary widely from patient to patient. For Roux-en-Y gastric bypass (RYGB), which is reliably associated with an average 65 to 70-percent excess weight loss (EWL), several studies[8] have demonstrated a broad distribution around that average, with a standard deviation of approximately 20-percent EWL (Figure 2). When the distribution of weight loss outcomes is examined for other procedures, a similarly broad variation is observed.[8] In addition, this high degree of variability extends to other outcomes from surgery, including the magnitude of weight regain, improvements in diabetes, lipid levels, hypertension, and the occurrence of adverse metabolic and nutritional effects.

Variations in Surgical Outcomes
Several hypotheses have been put forward to explain these broad variations in outcome. They include 1) major and subtle differences in technique among surgeons, 2) differing patient behavior and adherence with postoperative care plans, and 3) intrinsic, biological differences among patients. Often, the focus is on surgical “failures,” defined arbitrarily as a percent EWL below a particular cutoff, leading to a search for a specific cause of the clinical failure. However, this approach overlooks the continuous nature of the variability with results in individual patients distributed across a broad spectrum of weight loss, improvement in glucose regulation, or other outcome measures.

Using Research to Improve Outcomes
Understanding the basis for this variability could improve the overall utility of surgery in two ways.

Enhancing patient and procedure selection. First, the ability to predict beneficial and adverse outcomes in individual patients would allow for more effective patient selection, leading to an overall improvement in the risk-benefit (and cost-benefit) profile of the operation. Although we do not know to what degree patients who fare less well with one operation might do better with another, clinical experience suggests that many patients who have lost less weight with more limited procedures, such as adjustable gastric banding (AGB), respond very well to conversion to RYGB, sleeve gastrectomy, or biliopancreatic diversion (BPD). Given the varied physiological mechanisms of action of these different procedures, it would not be surprising if individual patients exhibited divergent responses to each of them. This is the typical situation with medications, where the ability to change therapies allows more direct comparison of responses across populations. Certainly, some operations are more effective, on average, than others. Nonetheless, given the broad variation in outcomes, the response of an individual patient may not parallel the average. For example, some patients may be particularly responsive to gastric banding or sleeve gastrectomy, making one of these operations more effective for that patient than RYGB or even BPD. If an individual patient is likely to be particularly responsive to a specific procedure or less likely to experience adverse nutritional or metabolic outcomes, there would be a rational basis for choosing that procedure for that patient over the available alternatives.

Predicting individual results and targeting interventions. A second important reason to seek better understanding of the cause of patient-to-patient variation in outcome is to use that understanding to improve results in those patients predicted to fare less well. Thus, an improved ability to predict outcomes, by enhancing patient and procedure selection and by facilitating targeted complementary interventions (e.g., more intensive follow up, specific dietary programs, or weight loss medications) to improve outcomes in individual patients, would enhance the overall benefit of each procedure, further improving their risk- and cost-benefit profiles. Because such complementary interventions could be selectively targeted to the patients who most need them, their overall cost would be minimized.

Other factors in weight loss surgery success
So what accounts for the variable response to bariatric and metabolic surgery? Patients’ post-operative behavior has long been postulated as a determinant factor. While lifestyle and behavioral patterns certainly play a role in post-operative outcomes—as they do for medical and surgical interventions for many diseases—there are other important factors that correlate strongly with outcomes of specific bariatric procedures.

Clinical contributors. Several studies have identified clinical contributors to surgical outcomes. Hatoum et al,[9] for example, demonstrated several clinical measures that are associated with significantly better weight loss after RYGB, including lower preoperative body mass index (BMI), absence of type 2 diabetes mellitus (T2DM), higher capacity for physical activity, higher education level, and greater participation in postoperative care. Together, these variables account for a substantial portion of the variation in weight loss, but do not provide sufficient discriminatory power to drive clinical decision-making. For example, although the presence of T2DM is associated with significantly diminished weight loss after RYGB, diabetes itself—particularly inadequately controlled T2DM—can be a strong indication for surgery.[6,7] Active participation in post-operative care clearly enhances the efficacy of RYGB, but with a strong clinical indication for surgery, does the inability to participate actively substantially negate the benefits of surgery? Should anticipated failure of participation be a strong contraindication to this operation? Opinions vary, but evidence to support using the known clinical predictors to determine whether to operate and which procedure to use are sparse. Similarly, currently known predictors have limited utility in choosing patients for surgical treatment of T2DM. The response of T2DM to surgery is more robust in patients who have been diagnosed more recently (typically less than 5 years earlier),[6] with full remission inversely associated with the duration of disease.10 Nonetheless, for patients with T2DM inadequately controlled with lifestyle modification and medications, the benefits of surgery can be profound, even in patients with longstanding disease. Given all of this, the need for more clinically useful predictors is clear.

As described in parts 2 and 5 in this series,[11,12] the preponderance of evidence indicates that most bariatric procedures alter the physiology of energy balance and metabolic regulation, and that biological mechanisms largely account for the efficacy of these operations. In this context, the variable response to surgery most likely reflects variation in patient susceptibility to the physiological effects of surgery. In other words, variation in the pathophysiology underlying obesity (and diabetes) in different patients likely contributes to the patient-to-patient variability in clinical response. If so, we should be able to identify objective markers of this biological variation, such as blood levels of key signaling molecules, results of physiological testing, or DNA variations.

Genetic variation. Indeed, several recent publications suggest that genetic variation plays a significant role in determining weight loss after RYGB. Based on analysis of approximately 1,000 patients undergoing RYGB at a single center, Hatoum et al[13] observed that patients who were genetically related exhibited similar weight loss. In this study, patients were separated into three groups: 1) those who were completely unrelated to each other, 2) those who were first-degree genetic relatives (parent-child or sibling relationships), and 3) those who were environmentally related (i.e., genetically unrelated but sharing the same household). Random pairing of the unrelated patients showed that, on average, EWL in the two patients in each pair differed by more than 20 percent (Figure 3).[13] Similar results were seen when comparing EWL in the pairs of cohabitating (but genetically unrelated) patients. However, EWL in members of the pairs of genetically related patients differed on average by only nine percent, demonstrating a strong genetic contribution to weight loss after this operation. The dramatic contribution of genetic background to outcomes of RYGB is further reinforced by two case series that describe RYGB in four pairs of identical twins (the two members of each pair sharing 100% of their genes).[14] Within each twin pair, postoperative weight loss was highly similar, with EWL differing by an average of only 1.5 percent (Figure 3). Thus, knowing the outcome of RYGB in one twin would provide an accurate estimate of the outcome in the other, neutralizing the high outcome variability observed in the general, genetically diverse population.

So, if genes are important for surgical outcomes, which genes are responsible? A few recent studies that have examined whether any of the genes known to contribute to obesity, diabetes, or other metabolic disorders also help determine outcomes after RYGB. To date, none of these genes clearly regulates RYGB outcomes, although Still et al[15] have observed that a “cocktail” of different genes can account for some of the observed variation in postoperative weight loss. One particular gene that has been the subject of more intensive study is the gene encoding the melanocortin-4 receptor (MC4R). Mutations in this gene are the most common form of human genetic obesity with up to five percent of patients with severe obesity harboring one of these mutations.[16] In mouse models, complete deletion of the MC4R gene reduces the ability of RYGB to cause weight loss.[16] However, the situation in human patients is less clear, since we have found no one with severe mutations in both copies of the MC4R gene who has undergone uncomplicated gastric bypass. Whether more subtle variations in the MC4R gene account for some of the variable response to RYGB is also unclear. Two recently published studies[16,17] have had conflicting results, and more work needs to be done to reconcile the data.

Since the obvious “candidate” genes do not appear to account for the strong genetic contribution to weight loss after RYGB, a broader search needs to be undertaken to find the responsible genes. The first such search is currently underway, with results expected later this year. These are the first steps in exploring the new field of “surgicogenomics,” the surgical analogue of pharmacogenomics—the use of genetics to predict outcomes and guide the use of medical therapies. The recognition of complex biological (physiological and genetic) determinants of surgical outcomes for individual patients that complement and may even outweigh variations in patient compliance or surgical technique provides new opportunities for more effective use of bariatric and metabolic surgery.

Final Thoughts
The ability to predict outcomes by whatever means (clinical traits, genetics, biomarkers, or some combination thereof) could allow for improved selection of surgical patients and more sophisticated and effective procedure selection for individual patients. In addition, by providing enhanced guidance to surgeons, patients, and referring physicians, providing rational predictive strategies could help demystify surgery, reducing the associated stigma and conceptual barriers that often prevent patients from benefiting from these powerful therapies.

1.     Sjöström L, Peltonen M, Jacobson, P, et al; Bariatric Surgery and Long-term Cardiovascular Events. N Engl J Med. 2012;307(1):56–65
2.    Sjöström L, Lindroos AK, Peltonen M, et al; Swedish Obese Subjects Study Scientific Group. Lifestyle, diabetes, and cardiovascular risk factors 10 years after bariatric surgery. N Engl J Med. 2004;351(26):2683–2693.
3.    Karlsson J, Taft C, Rydén A, et al. Ten-year trends in health-related quality of life after surgical and conventional treatment for severe obesity: the SOS intervention study. Int J Obes (Lond). 2007;31(8):1248–1261.
4.    Sjöström L, Narbro K, Sjöström CD, et al; Swedish Obese Subjects Study. Effects of bariatric surgery on mortality in Swedish obese subjects. N Engl J Med. 2007;357(8):741–752.
5.    Sjöström L, Gummesson A, Sjöström CD, et al; Swedish Obese Subjects Study. Effects of bariatric surgery on cancer incidence in obese patients in Sweden (Swedish Obese Subjects Study): a prospective, controlled intervention trial. Lancet Oncol. 2009;10 (7):653–662.
6.    Schauer PR, Kashyap SR, Wolski K, et al. Bariatric surgery versus intensive medical therapy in obese patients with diabetes. N Engl J Med. 2012;366(17):1567–1576.
7.    Mingrone G, Panunzi S, De Gaetano A, et al. Bariatric surgery versus conventional medical therapy for type 2 diabetes. N Engl J Med. 2012;366(17):1577–1585.
8.    Bessler M, Daud A, DiGiorgi MF, et al. Frequency distribution of weight loss percentage after gastric bypass and adjustable gastric banding. Surg Obes Relat Dis. 2008;4(4):486–491.
9.    Hatoum IJ, Stein HK, Merrifield BF, Kaplan LM. Capacity for physical activity predicts weight loss after Roux-en-Y gastric bypass. Obesity. 2009;17(1):92–99.
10.    Schauer PR, Burguera B, Ikramuddin S, Effect of laparoscopic Roux-en Y gastric bypass on type 2 diabetes mellitus. Ann Surg. 2003;238(4):467–484; discussion 84–85.
11.    Kaplan LM, Seeley RJ, Harris J. Myths Associated with Obesity and Bariatric Surgery. Myth 1: “Weight can be reliably controlled by voluntarily adjusting energy balance through diet and exercise.” Bariatric Times. 2012;9(4):12–13.
12.    Kaplan LM, Seeley RJ, Harris J. Myths Associated with Obesity and Bariatric Surgery. Myth 4: “Diabetes improvement after bariatric surgery is dependent on weight loss.” Bariatric Times. 2012;9(7):12–14.
13.    Hatoum IJ, Greenawalt DM, Cotsapas C, et al. Heritability of the weight loss response to gastric bypass surgery. J Clin Endocrinol Metab. 2011;96(10):E1630–E1633.
14.    Hagedorn JC, Morton JM.Nature versus nurture: identical twins and bariatric surgery. Obes Surg. 2007;17(6):728–731.
15.    Still CD, Wood GC, Chu X, et al. High allelic burden of four obesity SNPs is associated with poorer weight loss outcomes following gastric bypass surgery. Obesity (Silver Spring). 2011;19(8):1676–1683.
16.    Hatoum IJ, Stylopoulos N, Vanhoose AM, et al. Melanocortin-4 receptor signaling is required for weight loss after gastric bypass surgery. J Clin Endocrinol Metab. 2012;97(6):E1023–E1031.
17.    Mirshahi UL, Still CD, Masker KK, et al. The MC4R(I251L) allele is associated with better metabolic status and more weight loss after gastric bypass surgery. J Clin Endocrinol Metab. 2011;96(12):E2088–E2096. Epub 2011 Oct 5.

FUNDING: No funding was provided.

DISCLOSURES: Dr. Kaplan has received research support from the National Institute of Diabetes and Digestive and Kidney Diseases (NIH), Ethicon Endo-Surgery, Merck Research Laboratories, and GI Dynamics. He has done consulting for C.R. Bard, Gelesis, Rhythm Pharmaceuticals, Medtronic, Sanofi-Aventis, Amylin Pharmaceuticals, Allergan, Merck, GI Dynamics, and Johnson & Johnson. Dr. Seeley has received research support, has done speaking or consulting for the following companies: Amylin Pharmaceuticals, Eli Lilly, Ethicon Endo-Surgery, Novo Nordisk, Zafgen Inc., Merck, Roche, Alkermes, and Pfizer. Dr. Harris is an employee of Ethicon Endo-Surgery.

Category: MARS Initiative Series, Past Articles

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