<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03239782</url>
  </required_header>
  <id_info>
    <org_study_id>MONW</org_study_id>
    <nct_id>NCT03239782</nct_id>
  </id_info>
  <brief_title>The &quot;Metabolically-obese Normal-weight&quot; Phenotype and Its Reversal by Calorie Restriction</brief_title>
  <official_title>The &quot;Metabolically-obese Normal-weight&quot; Phenotype in Two Asian Ethnic Groups and Its Reversal by Calorie Restriction</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Clinical Nutrition Research Centre, Singapore</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Clinical Nutrition Research Centre, Singapore</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The prevalence of overweight and obesity in Singapore is approximately half of that in the&#xD;
      United States, yet the incidence of type 2 diabetes is similar, and is expected to double in&#xD;
      the near future. This indicates that metabolic dysfunction, particularly insulin resistance,&#xD;
      is widely prevalent even among individuals who are considered normal-weight or lean by&#xD;
      conventional measures, i.e. body mass index (BMI) and percent body fat. These individuals are&#xD;
      often referred to as &quot;metabolically-obese normal-weight&quot; (MONW), and have increased risk for&#xD;
      cardiometabolic disease despite their normal BMI and total body fat values. The prevalence of&#xD;
      the MONW phenotype varies across populations and differs markedly among different&#xD;
      ethnicities. However, our understanding of the complex interactions between ethnicity, body&#xD;
      composition, and metabolic dysfunction and its reversal remains rudimentary. Previous&#xD;
      attempts to characterize the MONW phenotype are confounded by the small but significant&#xD;
      differences in BMI or percent body fat between groups (even if all subjects were lean, within&#xD;
      the &quot;normal&quot; range), with MONW subjects being always &quot;fatter&quot; than the corresponding control&#xD;
      subjects. There are no published studies that prospectively recruited groups of metabolically&#xD;
      healthy and unhealthy lean individuals matched on BMI and percent body fat. Furthermore,&#xD;
      although weight loss improves body composition and many of the cardiometabolic abnormalities&#xD;
      in most obese patients, little is known about the possible therapeutic effects of calorie&#xD;
      restriction in MONW subjects.&#xD;
&#xD;
      Accordingly, a better understanding of the MONW phenotype and the evaluation of therapeutic&#xD;
      approaches for its reversal will have important implications for public health. By&#xD;
      facilitating earlier identification of these subjects, who are more likely to go undiagnosed&#xD;
      and thus less likely to be treated before clinically overt cardiometabolic disease develops,&#xD;
      results from this study will allow for earlier and effective intervention.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      By the year 2050, it is estimated that more than half of the Singapore population will be&#xD;
      overweight or obese, defined as having a body mass index (BMI, calculated as the weight in&#xD;
      kilograms divided by the square of height in meters) equal to or greater than 25 kg/m2 (Phan&#xD;
      et al. 2014). This is likely responsible, at least in part, for the concomitant increase in&#xD;
      obesity-related co-morbid conditions, particularly type 2 diabetes (Phan et al. 2014; Ni&#xD;
      Mhurchu et al. 2006). The relationship between BMI and the risk for type 2 diabetes in&#xD;
      populations from the Asia-Pacific region is linear within a wide range of BMI values (from&#xD;
      ~21 kg/m2 to ~34 kg/m2), so that for every 2 kg/m2 increase in BMI (which corresponds to ~6&#xD;
      kg for a normal-weight person of average stature), the risk for developing type 2 diabetes&#xD;
      rises by ~27 % (Ni Mhurchu et al. 2006). In Singapore, the prevalence of type 2 diabetes is&#xD;
      expected to double from 7.3 % in 1990 to ~15 % in 2050, predominantly as a result of the&#xD;
      fattening of the population, with the burden being greater for those of Indian descent than&#xD;
      those of Chinese descent (Phan et al. 2014). This is expected to reduce productivity, inflate&#xD;
      healthcare costs, and increase mortality among Singaporeans (Phan et al. 2014; Ma et al.&#xD;
      2003).&#xD;
&#xD;
      The prevalence of type 2 diabetes in Singapore is similar to that in the United States, even&#xD;
      though the prevalence of overweight and obesity (BMI ≥25 kg/m2) in Singapore is approximately&#xD;
      half that in the US (Yoon et al. 2006). This observation corroborates findings from many&#xD;
      studies showing that markers of metabolic dysfunction (e.g. hyperglycemia, hyperinsulinemia,&#xD;
      insulin resistance, dyslipidemia, and hypertension) are highly prevalent among Singaporean&#xD;
      adults even at normal BMI values, i.e. even among people who are considered &quot;normal-weight&quot;&#xD;
      or &quot;lean&quot; by conventional measures (Deurenberg-Yap et al. 1999; Deurenberg-Yap, Chew, et al.&#xD;
      2001). The existence of people who have normal body weight but also have metabolic&#xD;
      dysfunction, and therefore greater risk for developing cardiometabolic disease, was&#xD;
      recognized several decades ago (Ruderman et al. 1998; Ruderman, Schneider, and Berchtold&#xD;
      1981). At the extreme of this paradigm, even among members of the Calorie Restriction Society&#xD;
      who undergo self-imposed calorie restriction for years based on the belief that this will&#xD;
      help them ensure a long and healthy life, there are many individuals (~40 %) with impaired&#xD;
      glucose tolerance, despite very low BMI and total body fat (Fontana, Klein, and Holloszy&#xD;
      2010). These individuals are often referred to as &quot;metabolically-obese normal-weight&quot; (MONW)&#xD;
      or &quot;metabolically-abnormal lean&quot; or &quot;metabolically-unhealthy lean&quot; subjects. The prevalence&#xD;
      of this phenotype ranges from 5 % to 45 % depending on the BMI and the metabolic criteria&#xD;
      used for its definition, as well as the characteristics of the population (i.e. age, sex, and&#xD;
      ethnicity) (Conus, Rabasa-Lhoret, and Peronnet 2007; Teixeira et al. 2015). Similar&#xD;
      variability has been observed across Asia (Lee et al. 2011; Luo et al. 2015; Yoo et al. 2014;&#xD;
      Jung et al. 2015; Indulekha et al. 2015). For example, among the Chinese, ~8 % of the&#xD;
      population as a whole, or ~13 % of those who are considered lean by virtue of body fat&#xD;
      percent (i.e. ≤25 % for men and ≤35 % for women), are metabolically unhealthy, defined as&#xD;
      having three or more metabolic abnormalities characteristic of the metabolic syndrome (Luo et&#xD;
      al. 2015). Among Indians, on the other hand, 15-25 % of the population (or 20-40 % of those&#xD;
      who are considered lean by virtue of BMI, i.e. &lt;25 kg/m2) satisfies the criteria for&#xD;
      metabolic syndrome (Indulekha et al. 2015; Geetha et al. 2011). The MONW phenotype in Asians&#xD;
      is associated with 3-fold greater risk for carotid atherosclerosis (i.e. cardiovascular&#xD;
      disease) (Yoo et al. 2014) and 4.5-8.5-fold greater risk for developing type 2 diabetes (Luo&#xD;
      et al. 2015). In fact, MONW subjects have increased risk for cardiometabolic disease (Luo et&#xD;
      al. 2015; Yoo et al. 2014) and greater all-cause mortality (Choi et al. 2013) not only&#xD;
      compared to metabolically-healthy lean subjects, but also compared to metabolically-healthy&#xD;
      obese subjects. This underscores the importance of metabolic dysfunction independent of&#xD;
      excess body weight and total adiposity.&#xD;
&#xD;
      The mechanisms responsible for the development of metabolic abnormalities in lean people are&#xD;
      not entirely clear. The MONW phenotype can manifest early in life, e.g. during childhood&#xD;
      (Guerrero-Romero et al. 2013), which corroborates the existence of genetic predisposition for&#xD;
      metabolic dysfunction in the face of low BMI values (Yaghootkar et al. 2014). Previous&#xD;
      studies have identified a number of factors associated with the MONW phenotype, including&#xD;
      increased intra-abdominal (visceral) adipose tissue, increased liver and muscle fat content,&#xD;
      increased fat cell size, adipose tissue inflammation, altered inflammatory and adipokine&#xD;
      profiles, reduced skeletal muscle mass, lack of physical activity, and low cardio-respiratory&#xD;
      fitness (Badoud et al. 2015; Dvorak et al. 1999; Ruderman et al. 1998; Conus, Rabasa-Lhoret,&#xD;
      and Peronnet 2007; De Lorenzo et al. 2007; Karelis et al. 2004; Kim et al. 2013; Lee 2009;&#xD;
      Oliveros et al. 2014; Teixeira et al. 2015; Di Renzo et al. 2006; Conus et al. 2004;&#xD;
      Indulekha et al. 2015; Luo et al. 2015; Fontana, Klein, and Holloszy 2010). All of these&#xD;
      factors have been directly or indirectly associated with insulin resistance (defined by a&#xD;
      variety of methods), which is by far the commonest metabolic correlate of the MONW phenotype&#xD;
      across all ethnicities, age groups, and sexes (Conus, Rabasa-Lhoret, and Peronnet 2007;&#xD;
      Oliveros et al. 2014; Karelis et al. 2004; Ruderman et al. 1998). In fact, the greater&#xD;
      prevalence of the MONW phenotype in Indians (Indulekha et al. 2015; Geetha et al. 2011) than&#xD;
      in the Chinese (Luo et al. 2015) mirrors results obtained recently by our team, showing that&#xD;
      among lean Singaporean men (BMI &lt;25 kg/m2 or body fat ≤20 %), those of Indian descent have&#xD;
      significantly lower insulin sensitivity, evaluated as the insulin-mediated glucose disposal&#xD;
      rate during a hyperinsulinemic-euglycemic clamp procedure, compared to those of Chinese&#xD;
      descent (Khoo et al. 2014). Similar results have been reported by other investigators in&#xD;
      smaller groups of subjects (Liew et al. 2003) or when using simpler indices of insulin&#xD;
      sensitivity (Khoo et al. 2011; Tai et al. 2000). Therefore, an insulin resistant glucose&#xD;
      metabolism, broadly defined by subnormal responses to physiological insulin concentrations&#xD;
      (Kahn 1978), is the hallmark of the MONW phenotype.&#xD;
&#xD;
      Owing to the lack of a consistent definition, there is some variability among studies in the&#xD;
      phenotypic characterization of MONW subjects (Teixeira et al. 2015). This is further&#xD;
      complicated by the small but significant differences in BMI and, more commonly, percent body&#xD;
      fat between groups of metabolically healthy and unhealthy lean subjects, with MONW subjects&#xD;
      being always somewhat &quot;fatter&quot; (even though within the &quot;lean&quot; range) (Ruderman et al. 1998;&#xD;
      Di Renzo et al. 2006; Badoud et al. 2015; Luo et al. 2015; Indulekha et al. 2015; Dvorak et&#xD;
      al. 1999; Conus et al. 2004; De Lorenzo et al. 2007). Likewise, BMI and body fat are&#xD;
      typically greater in relatively insulin-resistant (e.g. Indian) than in relatively&#xD;
      insulin-sensitive (e.g. Chinese) individuals in studies reporting on ethnic differences in&#xD;
      insulin action among lean people (Khoo et al. 2014; Khoo et al. 2011). This in itself could&#xD;
      be responsible for the differences observed in metabolic function. There is considerable&#xD;
      (~2-fold range) variability between individuals in the percent body fat (Gallagher et al.&#xD;
      2000; Gallagher et al. 1996) and the insulin-mediated glucose disposal rate (a direct measure&#xD;
      of whole-body insulin sensitivity) (Bradley, Magkos, and Klein 2012) for the same BMI value&#xD;
      within the normal-weight range (i.e. BMI &lt;25 kg/m2), so that people with the same BMI can&#xD;
      have very different body fat and insulin sensitivity without this necessarily being&#xD;
      associated with the presence or absence of generalized metabolic dysfunction. Even among lean&#xD;
      and metabolically-healthy Asians, total body fat is a major correlate of insulin-mediated&#xD;
      glucose disposal (Rattarasarn et al. 2003). It is thus possible that some of the reported&#xD;
      differences between metabolically healthy and unhealthy lean subjects arise from normal&#xD;
      variability and the differences in body fat between groups, rather than being an inherent&#xD;
      characteristic of the MONW phenotype. In support of this possibility, when metabolically&#xD;
      healthy and unhealthy lean subjects (defined as those having normal and impaired glucose&#xD;
      tolerance, respectively) were retrospectively matched on total body fat, there were no&#xD;
      differences between phenotypes in circulating concentrations of metabolic and inflammatory&#xD;
      markers (i.e. high-density lipoprotein (HDL)-cholesterol, triglycerides, free fatty acids,&#xD;
      C-reactive protein, adiponectin, and leptin) (Fontana, Klein, and Holloszy 2010). There are&#xD;
      no studies that prospectively recruited groups of metabolically healthy and unhealthy lean&#xD;
      individuals matched on BMI and percent body fat. A deeper understanding of the MONW&#xD;
      phenotype, as proposed here, is important to dissect the metabolic abnormalities that are&#xD;
      inherent to the phenotype from those merely associated with differences in total body fat.&#xD;
      This will allow for proper identification and more efficient therapeutic targeting of MONW&#xD;
      individuals, who are at greater risk for cardiometabolic disease.&#xD;
&#xD;
      Little is known about possible interventions for improving metabolic function in MONW&#xD;
      subjects. It is well established that diet-induced weight loss can improve body composition&#xD;
      and many of the cardiometabolic abnormalities in most obese patients (e.g. decreases total&#xD;
      body fat, intra-abdominal adipose tissue, and ectopic fat deposition in liver and muscle;&#xD;
      increases insulin sensitivity; improves blood lipid profile; and reduces blood pressure)&#xD;
      (Dattilo and Kris-Etherton 1992; de Leiva 1998; Goldstein 1992; Kirk et al. 2009; Muscelli et&#xD;
      al. 1997; Pi-Sunyer 1993; Pasanisi et al. 2001; Escalante-Pulido et al. 2003; Mazzali et al.&#xD;
      2006; Klein, Wadden, and Sugerman 2002), so that a moderate 10 % weight loss has become the&#xD;
      cornerstone of obesity treatment (Jensen et al. 2014). However, MONW individuals are by&#xD;
      definition lean, so recommending even moderate amounts of weight loss may not be a feasible&#xD;
      therapeutic target (Miller and Parsonage 1975). It is therefore important to better&#xD;
      understand the metabolic effects of smaller amounts of weight loss. Recently, the principal&#xD;
      investigator conducted a randomized controlled trial to evaluate the effects of mild weight&#xD;
      loss (5 % of initial body weight) on cardiometabolic function in non-Asian subjects with&#xD;
      obesity and insulin resistance and found that even this small amount of weight loss decreases&#xD;
      fat deposition in the liver and the intra-abdominal area, and increases insulin action in&#xD;
      skeletal muscle, liver, and adipose tissue (Magkos et al. 2016). These results demonstrate&#xD;
      that mild weight loss can improve many cardiometabolic abnormalities in&#xD;
      metabolically-unhealthy obese subjects, but whether the same holds true for&#xD;
      metabolically-unhealthy lean subjects is not known. A small, non-randomized, single-arm study&#xD;
      in 7 lean, insulin-resistant offspring of parents with type 2 diabetes reported that modest&#xD;
      ~6 % diet-induced weight loss reduced intra-myocellular lipid (i.e. fat within skeletal&#xD;
      muscle fibers) content and increased insulin-mediated glucose disposal rate (both by ~30 %&#xD;
      compared with baseline values), but did not significantly affect intra-abdominal adipose&#xD;
      tissue volume or liver fat content (Petersen et al. 2012). It is thus not known whether mild&#xD;
      diet-induced weight loss produces similar changes in body composition, fat distribution, and&#xD;
      metabolic function in lean versus obese metabolically unhealthy subjects.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">March 29, 2016</start_date>
  <completion_date type="Actual">October 7, 2017</completion_date>
  <primary_completion_date type="Actual">October 7, 2017</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Basic Science</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Whole-body insulin sensitivity</measure>
    <time_frame>3 hours</time_frame>
    <description>Our primary endpoint is whole-body insulin sensitivity (i.e. the major metabolic correlate of the MONW phenotype), determined by using the hyperinsulinemic-euglycemic clamp.</description>
  </primary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">77</enrollment>
  <condition>Glucose Metabolism Disorders</condition>
  <condition>Obesity, Visceral</condition>
  <condition>Obesity; Endocrine</condition>
  <condition>Insulin Sensitivity/Resistance</condition>
  <arm_group>
    <arm_group_label>Metabolically unhealthy</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Subjects classified as metabolically unhealthy (MONW) go on to participate in a calorie restriction intervention.&#xD;
MONW subjects will participate in a supervised weight loss program to help ensure they are under a similar weekly energy deficit and achieve a 5 % weight loss at approximately the same time. Participants will be prescribed a reduced-calorie diet (~500 kcal/d below their needs for weight maintenance), and will be instructed not to change their physical activity habits, in order to achieve a weekly weight loss of ~0.5 kg.&#xD;
The macronutrient composition of the diet will be the same for all groups (55-60 % of energy from carbohydrate, 15-20 % from protein, and 20-30 % from fat); no vitamins or other nutritional supplements will be given.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Calorie restriction</intervention_name>
    <description>Calorie restriction with behavioral modification and provision of one catered, reduced calorie meal a day</description>
    <arm_group_label>Metabolically unhealthy</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Healthy male or female&#xD;
&#xD;
          -  Chinese or Indian descent&#xD;
&#xD;
          -  Between 21-65 years old (inclusive)&#xD;
&#xD;
          -  BMI from &gt;=19 to &lt;25 kg/m2&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  BMI ≥25 kg/m2&#xD;
&#xD;
          -  BMI &lt;19 kg/m2 (to avoid the risk of subjects becoming seriously underweight (i.e. BMI&#xD;
             ≤18 kg/m2) after 5 % weight loss)&#xD;
&#xD;
          -  Age &lt;21 and &gt;65 yrs&#xD;
&#xD;
          -  Use of medications that can affect metabolic function (including oral contraceptives&#xD;
             and hormone replacement therapy)&#xD;
&#xD;
          -  Regular use of tobacco products&#xD;
&#xD;
          -  Regular consumption of alcohol&#xD;
&#xD;
          -  Pregnant or breastfeeding women&#xD;
&#xD;
          -  Evidence of significant organ system dysfunction or disease&#xD;
&#xD;
          -  Recent weight loss (≥5 % over the past 6 months)&#xD;
&#xD;
          -  Severe asthma and respiratory problems that prevent subjects from exercising&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>21 Years</minimum_age>
    <maximum_age>65 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Faidon Magkos, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research</affiliation>
  </overall_official>
  <reference>
    <citation>Phan TP, Alkema L, Tai ES, Tan KH, Yang Q, Lim WY, Teo YY, Cheng CY, Wang X, Wong TY, Chia KS, Cook AR. Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore. BMJ Open Diabetes Res Care. 2014 Jun 11;2(1):e000012. doi: 10.1136/bmjdrc-2013-000012. eCollection 2014.</citation>
    <PMID>25452860</PMID>
  </reference>
  <reference>
    <citation>Asia Pacific Cohort Studies Collaboration; Ni Mhurchu C, Parag V, Nakamura M, Patel A, Rodgers A, Lam TH. Body mass index and risk of diabetes mellitus in the Asia-Pacific region. Asia Pac J Clin Nutr. 2006;15(2):127-33.</citation>
    <PMID>16672195</PMID>
  </reference>
  <reference>
    <citation>Ma S, Cutter J, Tan CE, Chew SK, Tai ES. Associations of diabetes mellitus and ethnicity with mortality in a multiethnic Asian population: data from the 1992 Singapore National Health Survey. Am J Epidemiol. 2003 Sep 15;158(6):543-52. doi: 10.1093/aje/kwg199.</citation>
    <PMID>12965880</PMID>
  </reference>
  <reference>
    <citation>Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, Zimmet P, Son HY. Epidemic obesity and type 2 diabetes in Asia. Lancet. 2006 Nov 11;368(9548):1681-8. doi: 10.1016/S0140-6736(06)69703-1.</citation>
    <PMID>17098087</PMID>
  </reference>
  <reference>
    <citation>Deurenberg-Yap M, Yian TB, Kai CS, Deurenberg P, VAN Staveren WA. Manifestation of cardiovascular risk factors at low levels of body mass index and waist-to-hip ratio in Singaporean Chinese. Asia Pac J Clin Nutr. 1999 Sep;8(3):177-83. doi: 10.1046/j.1440-6047.1999.00091.x.</citation>
    <PMID>24394159</PMID>
  </reference>
  <reference>
    <citation>Deurenberg-Yap M, Chew SK, Lin VF, Tan BY, van Staveren WA, Deurenberg P. Relationships between indices of obesity and its co-morbidities in multi-ethnic Singapore. Int J Obes Relat Metab Disord. 2001 Oct;25(10):1554-62. doi: 10.1038/sj.ijo.0801739.</citation>
    <PMID>11673781</PMID>
  </reference>
  <reference>
    <citation>Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes. 1998 May;47(5):699-713. doi: 10.2337/diabetes.47.5.699.</citation>
    <PMID>9588440</PMID>
  </reference>
  <reference>
    <citation>Ruderman NB, Schneider SH, Berchtold P. The &quot;metabolically-obese,&quot; normal-weight individual. Am J Clin Nutr. 1981 Aug;34(8):1617-21. doi: 10.1093/ajcn/34.8.1617.</citation>
    <PMID>7270486</PMID>
  </reference>
  <reference>
    <citation>Conus F, Rabasa-Lhoret R, Peronnet F. Characteristics of metabolically obese normal-weight (MONW) subjects. Appl Physiol Nutr Metab. 2007 Feb;32(1):4-12. doi: 10.1139/h06-092.</citation>
    <PMID>17332780</PMID>
  </reference>
  <reference>
    <citation>Teixeira TF, Alves RD, Moreira AP, Peluzio Mdo C. Main characteristics of metabolically obese normal weight and metabolically healthy obese phenotypes. Nutr Rev. 2015 Mar;73(3):175-90. doi: 10.1093/nutrit/nuu007. Epub 2015 Feb 13.</citation>
    <PMID>26024540</PMID>
  </reference>
  <reference>
    <citation>Lee SH, Ha HS, Park YJ, Lee JH, Yim HW, Yoon KH, Kang MI, Lee WC, Son HY, Park YM, Kwon HS. Identifying metabolically obese but normal-weight (MONW) individuals in a nondiabetic Korean population: the Chungju Metabolic disease Cohort (CMC) study. Clin Endocrinol (Oxf). 2011 Oct;75(4):475-81. doi: 10.1111/j.1365-2265.2011.04085.x.</citation>
    <PMID>21521351</PMID>
  </reference>
  <reference>
    <citation>Luo D, Liu F, Li X, Yin D, Lin Z, Liu H, Hou X, Wang C, Jia W. Comparison of the effect of 'metabolically healthy but obese' and 'metabolically abnormal but not obese' phenotypes on development of diabetes and cardiovascular disease in Chinese. Endocrine. 2015 May;49(1):130-8. doi: 10.1007/s12020-014-0444-2. Epub 2014 Oct 14.</citation>
    <PMID>25312689</PMID>
  </reference>
  <reference>
    <citation>Yoo HJ, Hwang SY, Hong HC, Choi HY, Seo JA, Kim SG, Kim NH, Choi DS, Baik SH, Choi KM. Association of metabolically abnormal but normal weight (MANW) and metabolically healthy but obese (MHO) individuals with arterial stiffness and carotid atherosclerosis. Atherosclerosis. 2014 May;234(1):218-23. doi: 10.1016/j.atherosclerosis.2014.02.033. Epub 2014 Mar 16.</citation>
    <PMID>24681911</PMID>
  </reference>
  <reference>
    <citation>Jung CH, Lee MJ, Kang YM, Jang JE, Leem J, Hwang JY, Kim EH, Park JY, Kim HK, Lee WJ. The risk of incident type 2 diabetes in a Korean metabolically healthy obese population: the role of systemic inflammation. J Clin Endocrinol Metab. 2015 Mar;100(3):934-41. doi: 10.1210/jc.2014-3885. Epub 2014 Dec 9. Erratum In: J Clin Endocrinol Metab. 2015 Apr;100(4):1709.</citation>
    <PMID>25490279</PMID>
  </reference>
  <reference>
    <citation>Badoud F, Perreault M, Zulyniak MA, Mutch DM. Molecular insights into the role of white adipose tissue in metabolically unhealthy normal weight and metabolically healthy obese individuals. FASEB J. 2015 Mar;29(3):748-58. doi: 10.1096/fj.14-263913. Epub 2014 Nov 19.</citation>
    <PMID>25411437</PMID>
  </reference>
  <reference>
    <citation>Bradley D, Magkos F, Klein S. Effects of bariatric surgery on glucose homeostasis and type 2 diabetes. Gastroenterology. 2012 Oct;143(4):897-912. doi: 10.1053/j.gastro.2012.07.114. Epub 2012 Aug 8.</citation>
    <PMID>22885332</PMID>
  </reference>
  <reference>
    <citation>Choi KM, Cho HJ, Choi HY, Yang SJ, Yoo HJ, Seo JA, Kim SG, Baik SH, Choi DS, Kim NH. Higher mortality in metabolically obese normal-weight people than in metabolically healthy obese subjects in elderly Koreans. Clin Endocrinol (Oxf). 2013 Sep;79(3):364-70. doi: 10.1111/cen.12154. Epub 2013 May 11.</citation>
    <PMID>23330616</PMID>
  </reference>
  <reference>
    <citation>Conus F, Allison DB, Rabasa-Lhoret R, St-Onge M, St-Pierre DH, Tremblay-Lebeau A, Poehlman ET. Metabolic and behavioral characteristics of metabolically obese but normal-weight women. J Clin Endocrinol Metab. 2004 Oct;89(10):5013-20. doi: 10.1210/jc.2004-0265.</citation>
    <PMID>15472199</PMID>
  </reference>
  <reference>
    <citation>Dattilo AM, Kris-Etherton PM. Effects of weight reduction on blood lipids and lipoproteins: a meta-analysis. Am J Clin Nutr. 1992 Aug;56(2):320-8. doi: 10.1093/ajcn/56.2.320.</citation>
    <PMID>1386186</PMID>
  </reference>
  <reference>
    <citation>de Leiva A. What are the benefits of moderate weight loss? Exp Clin Endocrinol Diabetes. 1998;106 Suppl 2:10-3. doi: 10.1055/s-0029-1212030.</citation>
    <PMID>9792475</PMID>
  </reference>
  <reference>
    <citation>De Lorenzo A, Del Gobbo V, Premrov MG, Bigioni M, Galvano F, Di Renzo L. Normal-weight obese syndrome: early inflammation? Am J Clin Nutr. 2007 Jan;85(1):40-5. doi: 10.1093/ajcn/85.1.40.</citation>
    <PMID>17209175</PMID>
  </reference>
  <reference>
    <citation>Di Renzo L, Del Gobbo V, Bigioni M, Premrov MG, Cianci R, De Lorenzo A. Body composition analyses in normal weight obese women. Eur Rev Med Pharmacol Sci. 2006 Jul-Aug;10(4):191-6.</citation>
    <PMID>16910350</PMID>
  </reference>
  <reference>
    <citation>Dvorak RV, DeNino WF, Ades PA, Poehlman ET. Phenotypic characteristics associated with insulin resistance in metabolically obese but normal-weight young women. Diabetes. 1999 Nov;48(11):2210-4. doi: 10.2337/diabetes.48.11.2210.</citation>
    <PMID>10535456</PMID>
  </reference>
  <reference>
    <citation>Escalante-Pulido M, Escalante-Herrera A, Milke-Najar ME, Alpizar-Salazar M. Effects of weight loss on insulin secretion and in vivo insulin sensitivity in obese diabetic and non-diabetic subjects. Diabetes Nutr Metab. 2003 Oct-Dec;16(5-6):277-83.</citation>
    <PMID>15000438</PMID>
  </reference>
  <reference>
    <citation>Fontana L, Klein S, Holloszy JO. Effects of long-term calorie restriction and endurance exercise on glucose tolerance, insulin action, and adipokine production. Age (Dordr). 2010 Mar;32(1):97-108. doi: 10.1007/s11357-009-9118-z. Epub 2009 Nov 11.</citation>
    <PMID>19904628</PMID>
  </reference>
  <reference>
    <citation>Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000 Sep;72(3):694-701. doi: 10.1093/ajcn/72.3.694.</citation>
    <PMID>10966886</PMID>
  </reference>
  <reference>
    <citation>Gallagher D, Visser M, Sepulveda D, Pierson RN, Harris T, Heymsfield SB. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? Am J Epidemiol. 1996 Feb 1;143(3):228-39. doi: 10.1093/oxfordjournals.aje.a008733.</citation>
    <PMID>8561156</PMID>
  </reference>
  <reference>
    <citation>Geetha L, Deepa M, Anjana RM, Mohan V. Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians. J Diabetes Sci Technol. 2011 Mar 1;5(2):439-46. doi: 10.1177/193229681100500235.</citation>
    <PMID>21527117</PMID>
  </reference>
  <reference>
    <citation>Goldstein DJ. Beneficial health effects of modest weight loss. Int J Obes Relat Metab Disord. 1992 Jun;16(6):397-415.</citation>
    <PMID>1322866</PMID>
  </reference>
  <reference>
    <citation>Guerrero-Romero F, Aradillas-Garcia C, Simental-Mendia LE, Torres-Rodriguez ML, Mendoza Ede L, Rosales-Cervantes J, Rodriguez-Ramirez G, Rodriguez-Moran M. Biochemical characteristics and risk factors for insulin resistance at different levels of obesity. Pediatrics. 2013 Apr;131(4):e1211-7. doi: 10.1542/peds.2012-1421. Epub 2013 Mar 11.</citation>
    <PMID>23478864</PMID>
  </reference>
  <reference>
    <citation>Indulekha K, Surendar J, Anjana RM, Geetha L, Gokulakrishnan K, Pradeepa R, Mohan V. Metabolic obesity, adipocytokines, and inflammatory markers in Asian Indians--CURES-124. Diabetes Technol Ther. 2015 Feb;17(2):134-41. doi: 10.1089/dia.2014.0202. Epub 2014 Dec 5.</citation>
    <PMID>25478993</PMID>
  </reference>
  <reference>
    <citation>Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, Loria CM, Millen BE, Nonas CA, Pi-Sunyer FX, Stevens J, Stevens VJ, Wadden TA, Wolfe BM, Yanovski SZ; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):2985-3023. doi: 10.1016/j.jacc.2013.11.004. Epub 2013 Nov 12. No abstract available. Erratum In: J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):3029-3030.</citation>
    <PMID>24239920</PMID>
  </reference>
  <reference>
    <citation>Kahn CR. Insulin resistance, insulin insensitivity, and insulin unresponsiveness: a necessary distinction. Metabolism. 1978 Dec;27(12 Suppl 2):1893-902. doi: 10.1016/s0026-0495(78)80007-9.</citation>
    <PMID>723640</PMID>
  </reference>
  <reference>
    <citation>Karelis AD, St-Pierre DH, Conus F, Rabasa-Lhoret R, Poehlman ET. Metabolic and body composition factors in subgroups of obesity: what do we know? J Clin Endocrinol Metab. 2004 Jun;89(6):2569-75. doi: 10.1210/jc.2004-0165.</citation>
    <PMID>15181025</PMID>
  </reference>
  <reference>
    <citation>Khoo CM, Leow MK, Sadananthan SA, Lim R, Venkataraman K, Khoo EY, Velan SS, Ong YT, Kambadur R, McFarlane C, Gluckman PD, Lee YS, Chong YS, Tai ES. Body fat partitioning does not explain the interethnic variation in insulin sensitivity among Asian ethnicity: the Singapore adults metabolism study. Diabetes. 2014 Mar;63(3):1093-102. doi: 10.2337/db13-1483. Epub 2013 Dec 18. Erratum In: Diabetes. 2014 Jun;63(6):2183. Lee, Yun Seng [corrected to Lee, Yung Seng].</citation>
    <PMID>24353181</PMID>
  </reference>
  <reference>
    <citation>Khoo CM, Sairazi S, Taslim S, Gardner D, Wu Y, Lee J, van Dam RM, Shyong Tai E. Ethnicity modifies the relationships of insulin resistance, inflammation, and adiponectin with obesity in a multiethnic Asian population. Diabetes Care. 2011 May;34(5):1120-6. doi: 10.2337/dc10-2097. Epub 2011 Apr 4.</citation>
    <PMID>21464462</PMID>
  </reference>
  <reference>
    <citation>Kim TN, Park MS, Yang SJ, Yoo HJ, Kang HJ, Song W, Seo JA, Kim SG, Kim NH, Baik SH, Choi DS, Choi KM. Body size phenotypes and low muscle mass: the Korean sarcopenic obesity study (KSOS). J Clin Endocrinol Metab. 2013 Feb;98(2):811-7. doi: 10.1210/jc.2012-3292. Epub 2013 Jan 4.</citation>
    <PMID>23293328</PMID>
  </reference>
  <reference>
    <citation>Kirk E, Reeds DN, Finck BN, Mayurranjan SM, Patterson BW, Klein S. Dietary fat and carbohydrates differentially alter insulin sensitivity during caloric restriction. Gastroenterology. 2009 May;136(5):1552-60. doi: 10.1053/j.gastro.2009.01.048. Epub 2009 Jan 25. Erratum In: Gastroenterology. 2009 Jul;137(1):393. Mayurranjan, Mitra S [corrected to Mayurranjan S Mitra].</citation>
    <PMID>19208352</PMID>
  </reference>
  <reference>
    <citation>Klein S, Wadden T, Sugerman HJ. AGA technical review on obesity. Gastroenterology. 2002 Sep;123(3):882-932. doi: 10.1053/gast.2002.35514. No abstract available. Erratum In: Gastroenterology 2002 Nov;123(5):1752.</citation>
    <PMID>12198715</PMID>
  </reference>
  <reference>
    <citation>Lee K. Metabolically obese but normal weight (MONW) and metabolically healthy but obese (MHO) phenotypes in Koreans: characteristics and health behaviors. Asia Pac J Clin Nutr. 2009;18(2):280-4.</citation>
    <PMID>19713189</PMID>
  </reference>
  <reference>
    <citation>Liew CF, Seah ES, Yeo KP, Lee KO, Wise SD. Lean, nondiabetic Asian Indians have decreased insulin sensitivity and insulin clearance, and raised leptin compared to Caucasians and Chinese subjects. Int J Obes Relat Metab Disord. 2003 Jul;27(7):784-9. doi: 10.1038/sj.ijo.0802307.</citation>
    <PMID>12821962</PMID>
  </reference>
  <reference>
    <citation>Magkos F, Fraterrigo G, Yoshino J, Luecking C, Kirbach K, Kelly SC, de Las Fuentes L, He S, Okunade AL, Patterson BW, Klein S. Effects of Moderate and Subsequent Progressive Weight Loss on Metabolic Function and Adipose Tissue Biology in Humans with Obesity. Cell Metab. 2016 Apr 12;23(4):591-601. doi: 10.1016/j.cmet.2016.02.005. Epub 2016 Feb 22.</citation>
    <PMID>26916363</PMID>
  </reference>
  <reference>
    <citation>Mazzali G, Di Francesco V, Zoico E, Fantin F, Zamboni G, Benati C, Bambara V, Negri M, Bosello O, Zamboni M. Interrelations between fat distribution, muscle lipid content, adipocytokines, and insulin resistance: effect of moderate weight loss in older women. Am J Clin Nutr. 2006 Nov;84(5):1193-9. doi: 10.1093/ajcn/84.5.1193.</citation>
    <PMID>17093174</PMID>
  </reference>
  <reference>
    <citation>Miller DS, Parsonage S. Resistance to slimming: adaptation or illusion? Lancet. 1975 Apr 5;1(7910):773-5. doi: 10.1016/s0140-6736(75)92437-x.</citation>
    <PMID>48002</PMID>
  </reference>
  <reference>
    <citation>Muscelli E, Camastra S, Catalano C, Galvan AQ, Ciociaro D, Baldi S, Ferrannini E. Metabolic and cardiovascular assessment in moderate obesity: effect of weight loss. J Clin Endocrinol Metab. 1997 Sep;82(9):2937-43. doi: 10.1210/jcem.82.9.4228.</citation>
    <PMID>9284723</PMID>
  </reference>
  <reference>
    <citation>Oliveros E, Somers VK, Sochor O, Goel K, Lopez-Jimenez F. The concept of normal weight obesity. Prog Cardiovasc Dis. 2014 Jan-Feb;56(4):426-33. doi: 10.1016/j.pcad.2013.10.003. Epub 2013 Oct 5.</citation>
    <PMID>24438734</PMID>
  </reference>
  <reference>
    <citation>Pasanisi F, Contaldo F, de Simone G, Mancini M. Benefits of sustained moderate weight loss in obesity. Nutr Metab Cardiovasc Dis. 2001 Dec;11(6):401-6.</citation>
    <PMID>12055705</PMID>
  </reference>
  <reference>
    <citation>Petersen KF, Dufour S, Morino K, Yoo PS, Cline GW, Shulman GI. Reversal of muscle insulin resistance by weight reduction in young, lean, insulin-resistant offspring of parents with type 2 diabetes. Proc Natl Acad Sci U S A. 2012 May 22;109(21):8236-40. doi: 10.1073/pnas.1205675109. Epub 2012 Apr 30.</citation>
    <PMID>22547801</PMID>
  </reference>
  <reference>
    <citation>Pi-Sunyer FX. Short-term medical benefits and adverse effects of weight loss. Ann Intern Med. 1993 Oct 1;119(7 Pt 2):722-6. doi: 10.7326/0003-4819-119-7_part_2-199310011-00019.</citation>
    <PMID>8363205</PMID>
  </reference>
  <reference>
    <citation>Rattarasarn C, Leelawattana R, Soonthornpun S, Setasuban W, Thamprasit A, Lim A, Chayanunnukul W, Thamkumpee N. Relationships of body fat distribution, insulin sensitivity and cardiovascular risk factors in lean, healthy non-diabetic Thai men and women. Diabetes Res Clin Pract. 2003 May;60(2):87-94. doi: 10.1016/s0168-8227(03)00017-2.</citation>
    <PMID>12706316</PMID>
  </reference>
  <reference>
    <citation>Tai ES, Lim SC, Chew SK, Tan BY, Tan CE. Homeostasis model assessment in a population with mixed ethnicity: the 1992 Singapore National Health Survey. Diabetes Res Clin Pract. 2000 Aug;49(2-3):159-68. doi: 10.1016/s0168-8227(00)00152-2.</citation>
    <PMID>10963828</PMID>
  </reference>
  <reference>
    <citation>Yaghootkar H, Scott RA, White CC, Zhang W, Speliotes E, Munroe PB, Ehret GB, Bis JC, Fox CS, Walker M, Borecki IB, Knowles JW, Yerges-Armstrong L, Ohlsson C, Perry JR, Chambers JC, Kooner JS, Franceschini N, Langenberg C, Hivert MF, Dastani Z, Richards JB, Semple RK, Frayling TM. Genetic evidence for a normal-weight &quot;metabolically obese&quot; phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes. Diabetes. 2014 Dec;63(12):4369-77. doi: 10.2337/db14-0318. Epub 2014 Jul 21.</citation>
    <PMID>25048195</PMID>
  </reference>
  <verification_date>March 2018</verification_date>
  <study_first_submitted>August 3, 2017</study_first_submitted>
  <study_first_submitted_qc>August 3, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">August 4, 2017</study_first_posted>
  <last_update_submitted>March 10, 2018</last_update_submitted>
  <last_update_submitted_qc>March 10, 2018</last_update_submitted_qc>
  <last_update_posted type="Actual">March 13, 2018</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Clinical Nutrition Research Centre, Singapore</investigator_affiliation>
    <investigator_full_name>Faidon Magkos</investigator_full_name>
    <investigator_title>Principal Investigator</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Obesity</mesh_term>
    <mesh_term>Insulin Resistance</mesh_term>
    <mesh_term>Metabolic Diseases</mesh_term>
    <mesh_term>Glucose Metabolism Disorders</mesh_term>
    <mesh_term>Obesity, Abdominal</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>March 22, 2016</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/82/NCT03239782/Prot_SAP_000.pdf</document_url>
    </provided_document>
    <provided_document>
      <document_type>Informed Consent Form</document_type>
      <document_has_protocol>No</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>No</document_has_sap>
      <document_date>March 22, 2016</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/82/NCT03239782/ICF_001.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03239782
org study id: MONW
nct id: NCT03239782
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The prevalence of overweight and obesity in Singapore is approximately half of that in the
      United States, yet the incidence of type 2 diabetes is similar, and is expected to double in
      the near future. This indicates that metabolic dysfunction, particularly insulin resistance,
      is widely prevalent even among individuals who are considered normal-weight or lean by
      conventional measures, i.e. body mass index (BMI) and percent body fat. These individuals are
      often referred to as "metabolically-obese normal-weight" (MONW), and have increased risk for
      cardiometabolic disease despite their normal BMI and total body fat values. The prevalence of
      the MONW phenotype varies across populations and differs markedly among different
      ethnicities. However, our understanding of the complex interactions between ethnicity, body
      composition, and metabolic dysfunction and its reversal remains rudimentary. Previous
      attempts to characterize the MONW phenotype are confounded by the small but significant
      differences in BMI or percent body fat between groups (even if all subjects were lean, within
      the "normal" range), with MONW subjects being always "fatter" than the corresponding control
      subjects. There are no published studies that prospectively recruited groups of metabolically
      healthy and unhealthy lean individuals matched on BMI and percent body fat. Furthermore,
      although weight loss improves body composition and many of the cardiometabolic abnormalities
      in most obese patients, little is known about the possible therapeutic effects of calorie
      restriction in MONW subjects.

      Accordingly, a better understanding of the MONW phenotype and the evaluation of therapeutic
      approaches for its reversal will have important implications for public health. By
      facilitating earlier identification of these subjects, who are more likely to go undiagnosed
      and thus less likely to be treated before clinically overt cardiometabolic disease develops,
      results from this study will allow for earlier and effective intervention.
By the year 2050, it is estimated that more than half of the Singapore population will be
      overweight or obese, defined as having a body mass index (BMI, calculated as the weight in
      kilograms divided by the square of height in meters) equal to or greater than 25 kg/m2 (Phan
      et al. 2014). This is likely responsible, at least in part, for the concomitant increase in
      obesity-related co-morbid conditions, particularly type 2 diabetes (Phan et al. 2014; Ni
      Mhurchu et al. 2006). The relationship between BMI and the risk for type 2 diabetes in
      populations from the Asia-Pacific region is linear within a wide range of BMI values (from
      ~21 kg/m2 to ~34 kg/m2), so that for every 2 kg/m2 increase in BMI (which corresponds to ~6
      kg for a normal-weight person of average stature), the risk for developing type 2 diabetes
      rises by ~27 % (Ni Mhurchu et al. 2006). In Singapore, the prevalence of type 2 diabetes is
      expected to double from 7.3 % in 1990 to ~15 % in 2050, predominantly as a result of the
      fattening of the population, with the burden being greater for those of Indian descent than
      those of Chinese descent (Phan et al. 2014). This is expected to reduce productivity, inflate
      healthcare costs, and increase mortality among Singaporeans (Phan et al. 2014; Ma et al.
      2003).

      The prevalence of type 2 diabetes in Singapore is similar to that in the United States, even
      though the prevalence of overweight and obesity (BMI ≥25 kg/m2) in Singapore is approximately
      half that in the US (Yoon et al. 2006). This observation corroborates findings from many
      studies showing that markers of metabolic dysfunction (e.g. hyperglycemia, hyperinsulinemia,
      insulin resistance, dyslipidemia, and hypertension) are highly prevalent among Singaporean
      adults even at normal BMI values, i.e. even among people who are considered "normal-weight"
      or "lean" by conventional measures (Deurenberg-Yap et al. 1999; Deurenberg-Yap, Chew, et al.
      2001). The existence of people who have normal body weight but also have metabolic
      dysfunction, and therefore greater risk for developing cardiometabolic disease, was
      recognized several decades ago (Ruderman et al. 1998; Ruderman, Schneider, and Berchtold
      1981). At the extreme of this paradigm, even among members of the Calorie Restriction Society
      who undergo self-imposed calorie restriction for years based on the belief that this will
      help them ensure a long and healthy life, there are many individuals (~40 %) with impaired
      glucose tolerance, despite very low BMI and total body fat (Fontana, Klein, and Holloszy
      2010). These individuals are often referred to as "metabolically-obese normal-weight" (MONW)
      or "metabolically-abnormal lean" or "metabolically-unhealthy lean" subjects. The prevalence
      of this phenotype ranges from 5 % to 45 % depending on the BMI and the metabolic criteria
      used for its definition, as well as the characteristics of the population (i.e. age, sex, and
      ethnicity) (Conus, Rabasa-Lhoret, and Peronnet 2007; Teixeira et al. 2015). Similar
      variability has been observed across Asia (Lee et al. 2011; Luo et al. 2015; Yoo et al. 2014;
      Jung et al. 2015; Indulekha et al. 2015). For example, among the Chinese, ~8 % of the
      population as a whole, or ~13 % of those who are considered lean by virtue of body fat
      percent (i.e. ≤25 % for men and ≤35 % for women), are metabolically unhealthy, defined as
      having three or more metabolic abnormalities characteristic of the metabolic syndrome (Luo et
      al. 2015). Among Indians, on the other hand, 15-25 % of the population (or 20-40 % of those
      who are considered lean by virtue of BMI, i.e. <25 kg/m2) satisfies the criteria for
      metabolic syndrome (Indulekha et al. 2015; Geetha et al. 2011). The MONW phenotype in Asians
      is associated with 3-fold greater risk for carotid atherosclerosis (i.e. cardiovascular
      disease) (Yoo et al. 2014) and 4.5-8.5-fold greater risk for developing type 2 diabetes (Luo
      et al. 2015). In fact, MONW subjects have increased risk for cardiometabolic disease (Luo et
      al. 2015; Yoo et al. 2014) and greater all-cause mortality (Choi et al. 2013) not only
      compared to metabolically-healthy lean subjects, but also compared to metabolically-healthy
      obese subjects. This underscores the importance of metabolic dysfunction independent of
      excess body weight and total adiposity.

      The mechanisms responsible for the development of metabolic abnormalities in lean people are
      not entirely clear. The MONW phenotype can manifest early in life, e.g. during childhood
      (Guerrero-Romero et al. 2013), which corroborates the existence of genetic predisposition for
      metabolic dysfunction in the face of low BMI values (Yaghootkar et al. 2014). Previous
      studies have identified a number of factors associated with the MONW phenotype, including
      increased intra-abdominal (visceral) adipose tissue, increased liver and muscle fat content,
      increased fat cell size, adipose tissue inflammation, altered inflammatory and adipokine
      profiles, reduced skeletal muscle mass, lack of physical activity, and low cardio-respiratory
      fitness (Badoud et al. 2015; Dvorak et al. 1999; Ruderman et al. 1998; Conus, Rabasa-Lhoret,
      and Peronnet 2007; De Lorenzo et al. 2007; Karelis et al. 2004; Kim et al. 2013; Lee 2009;
      Oliveros et al. 2014; Teixeira et al. 2015; Di Renzo et al. 2006; Conus et al. 2004;
      Indulekha et al. 2015; Luo et al. 2015; Fontana, Klein, and Holloszy 2010). All of these
      factors have been directly or indirectly associated with insulin resistance (defined by a
      variety of methods), which is by far the commonest metabolic correlate of the MONW phenotype
      across all ethnicities, age groups, and sexes (Conus, Rabasa-Lhoret, and Peronnet 2007;
      Oliveros et al. 2014; Karelis et al. 2004; Ruderman et al. 1998). In fact, the greater
      prevalence of the MONW phenotype in Indians (Indulekha et al. 2015; Geetha et al. 2011) than
      in the Chinese (Luo et al. 2015) mirrors results obtained recently by our team, showing that
      among lean Singaporean men (BMI <25 kg/m2 or body fat ≤20 %), those of Indian descent have
      significantly lower insulin sensitivity, evaluated as the insulin-mediated glucose disposal
      rate during a hyperinsulinemic-euglycemic clamp procedure, compared to those of Chinese
      descent (Khoo et al. 2014). Similar results have been reported by other investigators in
      smaller groups of subjects (Liew et al. 2003) or when using simpler indices of insulin
      sensitivity (Khoo et al. 2011; Tai et al. 2000). Therefore, an insulin resistant glucose
      metabolism, broadly defined by subnormal responses to physiological insulin concentrations
      (Kahn 1978), is the hallmark of the MONW phenotype.

      Owing to the lack of a consistent definition, there is some variability among studies in the
      phenotypic characterization of MONW subjects (Teixeira et al. 2015). This is further
      complicated by the small but significant differences in BMI and, more commonly, percent body
      fat between groups of metabolically healthy and unhealthy lean subjects, with MONW subjects
      being always somewhat "fatter" (even though within the "lean" range) (Ruderman et al. 1998;
      Di Renzo et al. 2006; Badoud et al. 2015; Luo et al. 2015; Indulekha et al. 2015; Dvorak et
      al. 1999; Conus et al. 2004; De Lorenzo et al. 2007). Likewise, BMI and body fat are
      typically greater in relatively insulin-resistant (e.g. Indian) than in relatively
      insulin-sensitive (e.g. Chinese) individuals in studies reporting on ethnic differences in
      insulin action among lean people (Khoo et al. 2014; Khoo et al. 2011). This in itself could
      be responsible for the differences observed in metabolic function. There is considerable
      (~2-fold range) variability between individuals in the percent body fat (Gallagher et al.
      2000; Gallagher et al. 1996) and the insulin-mediated glucose disposal rate (a direct measure
      of whole-body insulin sensitivity) (Bradley, Magkos, and Klein 2012) for the same BMI value
      within the normal-weight range (i.e. BMI <25 kg/m2), so that people with the same BMI can
      have very different body fat and insulin sensitivity without this necessarily being
      associated with the presence or absence of generalized metabolic dysfunction. Even among lean
      and metabolically-healthy Asians, total body fat is a major correlate of insulin-mediated
      glucose disposal (Rattarasarn et al. 2003). It is thus possible that some of the reported
      differences between metabolically healthy and unhealthy lean subjects arise from normal
      variability and the differences in body fat between groups, rather than being an inherent
      characteristic of the MONW phenotype. In support of this possibility, when metabolically
      healthy and unhealthy lean subjects (defined as those having normal and impaired glucose
      tolerance, respectively) were retrospectively matched on total body fat, there were no
      differences between phenotypes in circulating concentrations of metabolic and inflammatory
      markers (i.e. high-density lipoprotein (HDL)-cholesterol, triglycerides, free fatty acids,
      C-reactive protein, adiponectin, and leptin) (Fontana, Klein, and Holloszy 2010). There are
      no studies that prospectively recruited groups of metabolically healthy and unhealthy lean
      individuals matched on BMI and percent body fat. A deeper understanding of the MONW
      phenotype, as proposed here, is important to dissect the metabolic abnormalities that are
      inherent to the phenotype from those merely associated with differences in total body fat.
      This will allow for proper identification and more efficient therapeutic targeting of MONW
      individuals, who are at greater risk for cardiometabolic disease.

      Little is known about possible interventions for improving metabolic function in MONW
      subjects. It is well established that diet-induced weight loss can improve body composition
      and many of the cardiometabolic abnormalities in most obese patients (e.g. decreases total
      body fat, intra-abdominal adipose tissue, and ectopic fat deposition in liver and muscle;
      increases insulin sensitivity; improves blood lipid profile; and reduces blood pressure)
      (Dattilo and Kris-Etherton 1992; de Leiva 1998; Goldstein 1992; Kirk et al. 2009; Muscelli et
      al. 1997; Pi-Sunyer 1993; Pasanisi et al. 2001; Escalante-Pulido et al. 2003; Mazzali et al.
      2006; Klein, Wadden, and Sugerman 2002), so that a moderate 10 % weight loss has become the
      cornerstone of obesity treatment (Jensen et al. 2014). However, MONW individuals are by
      definition lean, so recommending even moderate amounts of weight loss may not be a feasible
      therapeutic target (Miller and Parsonage 1975). It is therefore important to better
      understand the metabolic effects of smaller amounts of weight loss. Recently, the principal
      investigator conducted a randomized controlled trial to evaluate the effects of mild weight
      loss (5 % of initial body weight) on cardiometabolic function in non-Asian subjects with
      obesity and insulin resistance and found that even this small amount of weight loss decreases
      fat deposition in the liver and the intra-abdominal area, and increases insulin action in
      skeletal muscle, liver, and adipose tissue (Magkos et al. 2016). These results demonstrate
      that mild weight loss can improve many cardiometabolic abnormalities in
      metabolically-unhealthy obese subjects, but whether the same holds true for
      metabolically-unhealthy lean subjects is not known. A small, non-randomized, single-arm study
      in 7 lean, insulin-resistant offspring of parents with type 2 diabetes reported that modest
      ~6 % diet-induced weight loss reduced intra-myocellular lipid (i.e. fat within skeletal
      muscle fibers) content and increased insulin-mediated glucose disposal rate (both by ~30 %
      compared with baseline values), but did not significantly affect intra-abdominal adipose
      tissue volume or liver fat content (Petersen et al. 2012). It is thus not known whether mild
      diet-induced weight loss produces similar changes in body composition, fat distribution, and
      metabolic function in lean versus obese metabolically unhealthy subjects.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Basic Science
masking: None (Open Label)
measure: Whole-body insulin sensitivity
time frame: 3 hours
description: Our primary endpoint is whole-body insulin sensitivity (i.e. the major metabolic correlate of the MONW phenotype), determined by using the hyperinsulinemic-euglycemic clamp.
arm group label: Metabolically unhealthy
arm group type: Experimental
description: Subjects classified as metabolically unhealthy (MONW) go on to participate in a calorie restriction intervention.
MONW subjects will participate in a supervised weight loss program to help ensure they are under a similar weekly energy deficit and achieve a 5 % weight loss at approximately the same time. Participants will be prescribed a reduced-calorie diet (~500 kcal/d below their needs for weight maintenance), and will be instructed not to change their physical activity habits, in order to achieve a weekly weight loss of ~0.5 kg.
The macronutrient composition of the diet will be the same for all groups (55-60 % of energy from carbohydrate, 15-20 % from protein, and 20-30 % from fat); no vitamins or other nutritional supplements will be given.
intervention type: Behavioral
intervention name: Calorie restriction
description: Calorie restriction with behavioral modification and provision of one catered, reduced calorie meal a day
arm group label: Metabolically unhealthy
criteria: 
gender: All
minimum age: 21 Years
maximum age: 65 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Faidon Magkos, PhD
role: Principal Investigator
affiliation: Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research
citation: Phan TP, Alkema L, Tai ES, Tan KH, Yang Q, Lim WY, Teo YY, Cheng CY, Wang X, Wong TY, Chia KS, Cook AR. Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore. BMJ Open Diabetes Res Care. 2014 Jun 11;2(1):e000012. doi: 10.1136/bmjdrc-2013-000012. eCollection 2014.
PMID: 25452860
citation: Asia Pacific Cohort Studies Collaboration; Ni Mhurchu C, Parag V, Nakamura M, Patel A, Rodgers A, Lam TH. Body mass index and risk of diabetes mellitus in the Asia-Pacific region. Asia Pac J Clin Nutr. 2006;15(2):127-33.
PMID: 16672195
citation: Ma S, Cutter J, Tan CE, Chew SK, Tai ES. Associations of diabetes mellitus and ethnicity with mortality in a multiethnic Asian population: data from the 1992 Singapore National Health Survey. Am J Epidemiol. 2003 Sep 15;158(6):543-52. doi: 10.1093/aje/kwg199.
PMID: 12965880
citation: Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, Zimmet P, Son HY. Epidemic obesity and type 2 diabetes in Asia. Lancet. 2006 Nov 11;368(9548):1681-8. doi: 10.1016/S0140-6736(06)69703-1.
PMID: 17098087
citation: Deurenberg-Yap M, Yian TB, Kai CS, Deurenberg P, VAN Staveren WA. Manifestation of cardiovascular risk factors at low levels of body mass index and waist-to-hip ratio in Singaporean Chinese. Asia Pac J Clin Nutr. 1999 Sep;8(3):177-83. doi: 10.1046/j.1440-6047.1999.00091.x.
PMID: 24394159
citation: Deurenberg-Yap M, Chew SK, Lin VF, Tan BY, van Staveren WA, Deurenberg P. Relationships between indices of obesity and its co-morbidities in multi-ethnic Singapore. Int J Obes Relat Metab Disord. 2001 Oct;25(10):1554-62. doi: 10.1038/sj.ijo.0801739.
PMID: 11673781
citation: Ruderman N, Chisholm D, Pi-Sunyer X, Schneider S. The metabolically obese, normal-weight individual revisited. Diabetes. 1998 May;47(5):699-713. doi: 10.2337/diabetes.47.5.699.
PMID: 9588440
citation: Ruderman NB, Schneider SH, Berchtold P. The "metabolically-obese," normal-weight individual. Am J Clin Nutr. 1981 Aug;34(8):1617-21. doi: 10.1093/ajcn/34.8.1617.
PMID: 7270486
citation: Conus F, Rabasa-Lhoret R, Peronnet F. Characteristics of metabolically obese normal-weight (MONW) subjects. Appl Physiol Nutr Metab. 2007 Feb;32(1):4-12. doi: 10.1139/h06-092.
PMID: 17332780
citation: Teixeira TF, Alves RD, Moreira AP, Peluzio Mdo C. Main characteristics of metabolically obese normal weight and metabolically healthy obese phenotypes. Nutr Rev. 2015 Mar;73(3):175-90. doi: 10.1093/nutrit/nuu007. Epub 2015 Feb 13.
PMID: 26024540
citation: Lee SH, Ha HS, Park YJ, Lee JH, Yim HW, Yoon KH, Kang MI, Lee WC, Son HY, Park YM, Kwon HS. Identifying metabolically obese but normal-weight (MONW) individuals in a nondiabetic Korean population: the Chungju Metabolic disease Cohort (CMC) study. Clin Endocrinol (Oxf). 2011 Oct;75(4):475-81. doi: 10.1111/j.1365-2265.2011.04085.x.
PMID: 21521351
citation: Luo D, Liu F, Li X, Yin D, Lin Z, Liu H, Hou X, Wang C, Jia W. Comparison of the effect of 'metabolically healthy but obese' and 'metabolically abnormal but not obese' phenotypes on development of diabetes and cardiovascular disease in Chinese. Endocrine. 2015 May;49(1):130-8. doi: 10.1007/s12020-014-0444-2. Epub 2014 Oct 14.
PMID: 25312689
citation: Yoo HJ, Hwang SY, Hong HC, Choi HY, Seo JA, Kim SG, Kim NH, Choi DS, Baik SH, Choi KM. Association of metabolically abnormal but normal weight (MANW) and metabolically healthy but obese (MHO) individuals with arterial stiffness and carotid atherosclerosis. Atherosclerosis. 2014 May;234(1):218-23. doi: 10.1016/j.atherosclerosis.2014.02.033. Epub 2014 Mar 16.
PMID: 24681911
citation: Jung CH, Lee MJ, Kang YM, Jang JE, Leem J, Hwang JY, Kim EH, Park JY, Kim HK, Lee WJ. The risk of incident type 2 diabetes in a Korean metabolically healthy obese population: the role of systemic inflammation. J Clin Endocrinol Metab. 2015 Mar;100(3):934-41. doi: 10.1210/jc.2014-3885. Epub 2014 Dec 9. Erratum In: J Clin Endocrinol Metab. 2015 Apr;100(4):1709.
PMID: 25490279
citation: Badoud F, Perreault M, Zulyniak MA, Mutch DM. Molecular insights into the role of white adipose tissue in metabolically unhealthy normal weight and metabolically healthy obese individuals. FASEB J. 2015 Mar;29(3):748-58. doi: 10.1096/fj.14-263913. Epub 2014 Nov 19.
PMID: 25411437
citation: Bradley D, Magkos F, Klein S. Effects of bariatric surgery on glucose homeostasis and type 2 diabetes. Gastroenterology. 2012 Oct;143(4):897-912. doi: 10.1053/j.gastro.2012.07.114. Epub 2012 Aug 8.
PMID: 22885332
citation: Choi KM, Cho HJ, Choi HY, Yang SJ, Yoo HJ, Seo JA, Kim SG, Baik SH, Choi DS, Kim NH. Higher mortality in metabolically obese normal-weight people than in metabolically healthy obese subjects in elderly Koreans. Clin Endocrinol (Oxf). 2013 Sep;79(3):364-70. doi: 10.1111/cen.12154. Epub 2013 May 11.
PMID: 23330616
citation: Conus F, Allison DB, Rabasa-Lhoret R, St-Onge M, St-Pierre DH, Tremblay-Lebeau A, Poehlman ET. Metabolic and behavioral characteristics of metabolically obese but normal-weight women. J Clin Endocrinol Metab. 2004 Oct;89(10):5013-20. doi: 10.1210/jc.2004-0265.
PMID: 15472199
citation: Dattilo AM, Kris-Etherton PM. Effects of weight reduction on blood lipids and lipoproteins: a meta-analysis. Am J Clin Nutr. 1992 Aug;56(2):320-8. doi: 10.1093/ajcn/56.2.320.
PMID: 1386186
citation: de Leiva A. What are the benefits of moderate weight loss? Exp Clin Endocrinol Diabetes. 1998;106 Suppl 2:10-3. doi: 10.1055/s-0029-1212030.
PMID: 9792475
citation: De Lorenzo A, Del Gobbo V, Premrov MG, Bigioni M, Galvano F, Di Renzo L. Normal-weight obese syndrome: early inflammation? Am J Clin Nutr. 2007 Jan;85(1):40-5. doi: 10.1093/ajcn/85.1.40.
PMID: 17209175
citation: Di Renzo L, Del Gobbo V, Bigioni M, Premrov MG, Cianci R, De Lorenzo A. Body composition analyses in normal weight obese women. Eur Rev Med Pharmacol Sci. 2006 Jul-Aug;10(4):191-6.
PMID: 16910350
citation: Dvorak RV, DeNino WF, Ades PA, Poehlman ET. Phenotypic characteristics associated with insulin resistance in metabolically obese but normal-weight young women. Diabetes. 1999 Nov;48(11):2210-4. doi: 10.2337/diabetes.48.11.2210.
PMID: 10535456
citation: Escalante-Pulido M, Escalante-Herrera A, Milke-Najar ME, Alpizar-Salazar M. Effects of weight loss on insulin secretion and in vivo insulin sensitivity in obese diabetic and non-diabetic subjects. Diabetes Nutr Metab. 2003 Oct-Dec;16(5-6):277-83.
PMID: 15000438
citation: Fontana L, Klein S, Holloszy JO. Effects of long-term calorie restriction and endurance exercise on glucose tolerance, insulin action, and adipokine production. Age (Dordr). 2010 Mar;32(1):97-108. doi: 10.1007/s11357-009-9118-z. Epub 2009 Nov 11.
PMID: 19904628
citation: Gallagher D, Heymsfield SB, Heo M, Jebb SA, Murgatroyd PR, Sakamoto Y. Healthy percentage body fat ranges: an approach for developing guidelines based on body mass index. Am J Clin Nutr. 2000 Sep;72(3):694-701. doi: 10.1093/ajcn/72.3.694.
PMID: 10966886
citation: Gallagher D, Visser M, Sepulveda D, Pierson RN, Harris T, Heymsfield SB. How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? Am J Epidemiol. 1996 Feb 1;143(3):228-39. doi: 10.1093/oxfordjournals.aje.a008733.
PMID: 8561156
citation: Geetha L, Deepa M, Anjana RM, Mohan V. Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians. J Diabetes Sci Technol. 2011 Mar 1;5(2):439-46. doi: 10.1177/193229681100500235.
PMID: 21527117
citation: Goldstein DJ. Beneficial health effects of modest weight loss. Int J Obes Relat Metab Disord. 1992 Jun;16(6):397-415.
PMID: 1322866
citation: Guerrero-Romero F, Aradillas-Garcia C, Simental-Mendia LE, Torres-Rodriguez ML, Mendoza Ede L, Rosales-Cervantes J, Rodriguez-Ramirez G, Rodriguez-Moran M. Biochemical characteristics and risk factors for insulin resistance at different levels of obesity. Pediatrics. 2013 Apr;131(4):e1211-7. doi: 10.1542/peds.2012-1421. Epub 2013 Mar 11.
PMID: 23478864
citation: Indulekha K, Surendar J, Anjana RM, Geetha L, Gokulakrishnan K, Pradeepa R, Mohan V. Metabolic obesity, adipocytokines, and inflammatory markers in Asian Indians--CURES-124. Diabetes Technol Ther. 2015 Feb;17(2):134-41. doi: 10.1089/dia.2014.0202. Epub 2014 Dec 5.
PMID: 25478993
citation: Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, Loria CM, Millen BE, Nonas CA, Pi-Sunyer FX, Stevens J, Stevens VJ, Wadden TA, Wolfe BM, Yanovski SZ; American College of Cardiology/American Heart Association Task Force on Practice Guidelines; Obesity Society. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):2985-3023. doi: 10.1016/j.jacc.2013.11.004. Epub 2013 Nov 12. No abstract available. Erratum In: J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):3029-3030.
PMID: 24239920
citation: Kahn CR. Insulin resistance, insulin insensitivity, and insulin unresponsiveness: a necessary distinction. Metabolism. 1978 Dec;27(12 Suppl 2):1893-902. doi: 10.1016/s0026-0495(78)80007-9.
PMID: 723640
citation: Karelis AD, St-Pierre DH, Conus F, Rabasa-Lhoret R, Poehlman ET. Metabolic and body composition factors in subgroups of obesity: what do we know? J Clin Endocrinol Metab. 2004 Jun;89(6):2569-75. doi: 10.1210/jc.2004-0165.
PMID: 15181025
citation: Khoo CM, Leow MK, Sadananthan SA, Lim R, Venkataraman K, Khoo EY, Velan SS, Ong YT, Kambadur R, McFarlane C, Gluckman PD, Lee YS, Chong YS, Tai ES. Body fat partitioning does not explain the interethnic variation in insulin sensitivity among Asian ethnicity: the Singapore adults metabolism study. Diabetes. 2014 Mar;63(3):1093-102. doi: 10.2337/db13-1483. Epub 2013 Dec 18. Erratum In: Diabetes. 2014 Jun;63(6):2183. Lee, Yun Seng [corrected to Lee, Yung Seng].
PMID: 24353181
citation: Khoo CM, Sairazi S, Taslim S, Gardner D, Wu Y, Lee J, van Dam RM, Shyong Tai E. Ethnicity modifies the relationships of insulin resistance, inflammation, and adiponectin with obesity in a multiethnic Asian population. Diabetes Care. 2011 May;34(5):1120-6. doi: 10.2337/dc10-2097. Epub 2011 Apr 4.
PMID: 21464462
citation: Kim TN, Park MS, Yang SJ, Yoo HJ, Kang HJ, Song W, Seo JA, Kim SG, Kim NH, Baik SH, Choi DS, Choi KM. Body size phenotypes and low muscle mass: the Korean sarcopenic obesity study (KSOS). J Clin Endocrinol Metab. 2013 Feb;98(2):811-7. doi: 10.1210/jc.2012-3292. Epub 2013 Jan 4.
PMID: 23293328
citation: Kirk E, Reeds DN, Finck BN, Mayurranjan SM, Patterson BW, Klein S. Dietary fat and carbohydrates differentially alter insulin sensitivity during caloric restriction. Gastroenterology. 2009 May;136(5):1552-60. doi: 10.1053/j.gastro.2009.01.048. Epub 2009 Jan 25. Erratum In: Gastroenterology. 2009 Jul;137(1):393. Mayurranjan, Mitra S [corrected to Mayurranjan S Mitra].
PMID: 19208352
citation: Klein S, Wadden T, Sugerman HJ. AGA technical review on obesity. Gastroenterology. 2002 Sep;123(3):882-932. doi: 10.1053/gast.2002.35514. No abstract available. Erratum In: Gastroenterology 2002 Nov;123(5):1752.
PMID: 12198715
citation: Lee K. Metabolically obese but normal weight (MONW) and metabolically healthy but obese (MHO) phenotypes in Koreans: characteristics and health behaviors. Asia Pac J Clin Nutr. 2009;18(2):280-4.
PMID: 19713189
citation: Liew CF, Seah ES, Yeo KP, Lee KO, Wise SD. Lean, nondiabetic Asian Indians have decreased insulin sensitivity and insulin clearance, and raised leptin compared to Caucasians and Chinese subjects. Int J Obes Relat Metab Disord. 2003 Jul;27(7):784-9. doi: 10.1038/sj.ijo.0802307.
PMID: 12821962
citation: Magkos F, Fraterrigo G, Yoshino J, Luecking C, Kirbach K, Kelly SC, de Las Fuentes L, He S, Okunade AL, Patterson BW, Klein S. Effects of Moderate and Subsequent Progressive Weight Loss on Metabolic Function and Adipose Tissue Biology in Humans with Obesity. Cell Metab. 2016 Apr 12;23(4):591-601. doi: 10.1016/j.cmet.2016.02.005. Epub 2016 Feb 22.
PMID: 26916363
citation: Mazzali G, Di Francesco V, Zoico E, Fantin F, Zamboni G, Benati C, Bambara V, Negri M, Bosello O, Zamboni M. Interrelations between fat distribution, muscle lipid content, adipocytokines, and insulin resistance: effect of moderate weight loss in older women. Am J Clin Nutr. 2006 Nov;84(5):1193-9. doi: 10.1093/ajcn/84.5.1193.
PMID: 17093174
citation: Miller DS, Parsonage S. Resistance to slimming: adaptation or illusion? Lancet. 1975 Apr 5;1(7910):773-5. doi: 10.1016/s0140-6736(75)92437-x.
PMID: 48002
citation: Muscelli E, Camastra S, Catalano C, Galvan AQ, Ciociaro D, Baldi S, Ferrannini E. Metabolic and cardiovascular assessment in moderate obesity: effect of weight loss. J Clin Endocrinol Metab. 1997 Sep;82(9):2937-43. doi: 10.1210/jcem.82.9.4228.
PMID: 9284723
citation: Oliveros E, Somers VK, Sochor O, Goel K, Lopez-Jimenez F. The concept of normal weight obesity. Prog Cardiovasc Dis. 2014 Jan-Feb;56(4):426-33. doi: 10.1016/j.pcad.2013.10.003. Epub 2013 Oct 5.
PMID: 24438734
citation: Pasanisi F, Contaldo F, de Simone G, Mancini M. Benefits of sustained moderate weight loss in obesity. Nutr Metab Cardiovasc Dis. 2001 Dec;11(6):401-6.
PMID: 12055705
citation: Petersen KF, Dufour S, Morino K, Yoo PS, Cline GW, Shulman GI. Reversal of muscle insulin resistance by weight reduction in young, lean, insulin-resistant offspring of parents with type 2 diabetes. Proc Natl Acad Sci U S A. 2012 May 22;109(21):8236-40. doi: 10.1073/pnas.1205675109. Epub 2012 Apr 30.
PMID: 22547801
citation: Pi-Sunyer FX. Short-term medical benefits and adverse effects of weight loss. Ann Intern Med. 1993 Oct 1;119(7 Pt 2):722-6. doi: 10.7326/0003-4819-119-7_part_2-199310011-00019.
PMID: 8363205
citation: Rattarasarn C, Leelawattana R, Soonthornpun S, Setasuban W, Thamprasit A, Lim A, Chayanunnukul W, Thamkumpee N. Relationships of body fat distribution, insulin sensitivity and cardiovascular risk factors in lean, healthy non-diabetic Thai men and women. Diabetes Res Clin Pract. 2003 May;60(2):87-94. doi: 10.1016/s0168-8227(03)00017-2.
PMID: 12706316
citation: Tai ES, Lim SC, Chew SK, Tan BY, Tan CE. Homeostasis model assessment in a population with mixed ethnicity: the 1992 Singapore National Health Survey. Diabetes Res Clin Pract. 2000 Aug;49(2-3):159-68. doi: 10.1016/s0168-8227(00)00152-2.
PMID: 10963828
citation: Yaghootkar H, Scott RA, White CC, Zhang W, Speliotes E, Munroe PB, Ehret GB, Bis JC, Fox CS, Walker M, Borecki IB, Knowles JW, Yerges-Armstrong L, Ohlsson C, Perry JR, Chambers JC, Kooner JS, Franceschini N, Langenberg C, Hivert MF, Dastani Z, Richards JB, Semple RK, Frayling TM. Genetic evidence for a normal-weight "metabolically obese" phenotype linking insulin resistance, hypertension, coronary artery disease, and type 2 diabetes. Diabetes. 2014 Dec;63(12):4369-77. doi: 10.2337/db14-0318. Epub 2014 Jul 21.
PMID: 25048195
responsible party type: Principal Investigator
investigator affiliation: Clinical Nutrition Research Centre, Singapore
investigator full name: Faidon Magkos
investigator title: Principal Investigator
mesh term: Obesity
mesh term: Insulin Resistance
mesh term: Metabolic Diseases
mesh term: Glucose Metabolism Disorders
mesh term: Obesity, Abdominal
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