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Sugar is a highly addictive carbohydrate linked to obesity, diabetes, metabolic disorders, and mood disorders. Individuals ready to phase out sugar will improve overall health, regardless of age and health status, but the transition can be challenging. A sugar-free or low-sugar diet can help individuals with blood sugar or systemic inflammation, including pre-diabetes, diabetes, heart disease, PCOS, hormonal imbalances, and autoimmune diseases. Phase Out Sugar Low-Sugar Diet A low-sugar nutrition plan focuses on maintaining a low overall sugar intake that limits sugar to avoid blood sugar instability and general inflammation. - This means choosing food with natural sugars like fruit, certain dairy products, vegetables, and natural sugars.
- Reducing and replacing packaged or prepared foods with added sugars, like store-bought tomato sauce, cured meats, or frozen meals.
- Reducing and replacing processed foods like snack items and fast food.
- Reducing restaurant food that can add sugar for flavor and appetite stimulation.
Recommended Ways Consult a healthcare provider, dietician, or nutritionist before altering diet, physical activity, or supplement routine. Eat More Healthy Fat - Healthy fat is more satisfying, making the body feel fuller for longer.
- Eating more healthy fat decreases sugar cravings and reduces sugar withdrawal symptoms.
Healthy fats include: - Avocados
- Nuts
- Seeds
- Coconut oil
- Extra virgin olive oil
- Salmon, mackerel, and sardines
More Sleep to Balance Hunger Hormones - Studies have shown that shorter sleep periods are associated with an elevated body mass index.
- Not getting enough sleep negatively impacts the appetite-regulating hormones leptin and ghrelin, causing cravings for instant energy that typically comes from sugar snack products.
- Individuals are recommended to get at least 7-9 hours per night. Enough sleep will balance the appetite hormones and decrease sugar cravings.
Manage Stress to Control Emotional Eating Emotional eating is common when stressed out. Finding something to take the mind off sugar cravings is necessary when having a stressful day. This includes: If sugar cravings are more serious, then professional help is recommended. Drink More Water When school, work, and life is happening, individuals can think they’re hungry; however, it is not hunger but the body needing hydration. - Drink one to two glasses of water when cravings kick in to satisfy the craving.
- Drinking water throughout the day helps keep cravings down and helps with sugar withdrawal symptoms.
- Individuals who have difficulty drinking water should add slices of fruit, cucumber, or mint to make it more pleasing.
- Try sparkling mineral water or naturally flavored carbonated waters.
- Try healthy juices, like celery, beet, or carrot juice, instead of water.
Sugar-Free Substitutes Sugar substitutes are available, but not all are considered healthy. - Individuals should be cautious about using sugar-free alternatives to phase out sugar.
- A study found that zero-calorie sweeteners such as aspartame and sucralose were actually found to increase, not decrease, weight.
- Stevia and monk fruit extract has been shown to be safe and has no negative side effects.
- Consult a dietician or nutritionist to determine the healthiest for you.
General Disclaimer * The information herein is not intended to replace a one-on-one relationship with a qualified healthcare professional or licensed physician and is not medical advice. We encourage you to make your own healthcare decisions based on your research and partnership with a qualified healthcare professional. Our information scope is limited to chiropractic, musculoskeletal, physical medicines, wellness, sensitive health issues, functional medicine articles, topics, and discussions. We provide and present clinical collaboration with specialists from a wide array of disciplines. Each specialist is governed by their professional scope of practice and their jurisdiction of licensure. We use functional health & wellness protocols to treat and support care for the injuries or disorders of the musculoskeletal system. Our videos, posts, topics, subjects, and insights cover clinical matters, issues, and topics that relate to and directly or indirectly support our clinical scope of practice.* Our office has reasonably attempted to provide supportive citations and identified the relevant research study or studies supporting our posts. We provide copies of supporting research studies available to regulatory boards and the public upon request. We understand that we cover matters that require an additional explanation of how it may assist in a particular care plan or treatment protocol; therefore, to further discuss the subject matter above, please feel free to ask Dr. Alex Jimenez or contact us at 915-850-0900. Dr. Alex Jimenez DC, MSACP, CCST, IFMCP*, CIFM*, ATN* email: coach@elpasofunctionalmedicine.com Licensed in: Texas & New Mexico* References Azad, Meghan B et al. “Nonnutritive sweeteners and cardiometabolic health: a systematic review and meta-analysis of randomized controlled trials and prospective cohort studies.” CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne vol. 189,28 (2017): E929-E939. doi:10.1503/cmaj.161390 Bayon, Virginie et al. “Sleep debt and obesity.” Annals of medicine vol. 46,5 (2014): 264-72. doi:10.3109/07853890.2014.931103 DiNicolantonio, James J et al. “Sugar addiction: is it real? A narrative review.” British journal of sports medicine vol. 52,14 (2018): 910-913. doi:10.1136/bjsports-2017-097971 Franklin, Jane L et al. “Extended exposure to sugar and/or caffeine produces distinct behavioral and neurochemical profiles in the orbitofrontal cortex of rats: Implications for neural function.” Proteomics vol. 16,22 (2016): 2894-2910. doi:10.1002/pmic.201600032 Freeman, Clara R et al. “Impact of sugar on the body, brain, and behavior.” Frontiers in bioscience (Landmark edition) vol. 23,12 2255-2266. 1 Jun. 2018, doi:10.2741/4704 https://www.health.harvard.edu/heart-health/the-sweet-danger-of-sugar
With the world population being obese or even overweight, especially in the United States. One of the most common disorders that mostly everyone has from being obese, and it is called metabolic syndrome. Metabolic syndrome is a cluster of conditions that happens to many individuals that can create many complications to the body, and most individuals who have metabolic syndrome would have an apple or pear-shaped bodies. With many supplements and natural foods helping the body, there is a supplement that can help the body combat metabolic syndrome and can be combined with a specific diet to make anyone who is obese or overweight lose the extra pounds. One of the supplements that have been known to help combat metabolic syndrome is Coleus forskohlii. Coleus forskohlii is a plant supplement that is found in parts of India, Thailand, and Nepal. While being part of the mint family, Coleus forskohlii has been used in traditional folk medicine that has been known to treat asthma and various ailments that the body may encounter. Studies have found that Coleus forskohlii extract may be able to aid in weight management; however, there have been limited studies on this extract. The Coleus forskohlii has been known to extract the critical markers for obesity and metabolic parameter for overweight and obese individuals who might benefit from this supplement.
Metabolic Syndrome: Key indexing terms: - Metabolic syndrome X
- Insulin resistance
- Hyperglycemia
- Inflammation
- Weight loss
Abstract
Objective: This article presents an overview of metabolic syndrome (MetS), which is a collection of risk factors that can lead to diabetes, stroke, and heart disease. The purposes of this article are to describe the current literature on the etiology and pathophysiology of insulin resistance as it relates to MetS and to suggest strategies for dietary and supplemental management in chiropractic practice. Methods: The literature was searched in PubMed, Google Scholar, and the Web site of the American Heart Association, from the earliest date possible to May 2014. Review articles were identified that outlined pathophysiology of MetS and type 2 diabetes mellitus (T2DM) and relationships among diet, supplements, and glycemic regulation, MetS, T2DM, and musculoskeletal pain. Results: Metabolic syndrome has been linked to increased risk of developing T2DM and cardiovascular disease and increased risk of stroke and myocardial infarction. Insulin resistance is linked to musculoskeletal complaints both through chronic inflammation and the effects of advanced glycosylation end products. Although diabetes and cardiovascular disease are the most well-known diseases that can result from MetS, an emerging body of evidence demonstrates that common musculoskeletal pain syndromes can be caused by MetS. Conclusions: This article provides an overview of lifestyle management of MetS that can be undertaken by doctors of chiropractic by means of dietary modification and nutritional support to promote blood sugar regulation. Introduction: Metabolic SyndromeMetabolic syndrome (MetS) has been described as a cluster of physical examination and laboratory findings that directly increases the risk of degenerative metabolic disease expression. Excess visceral adipose tissue, insulin resistance, dyslipidemia, and hypertension are conditions that significantly contribute to the syndrome. These conditions are united by a pathophysiological basis in low-grade chronic inflammation and increase an individual's risk of cardiovascular disease, type 2 diabetes mellitus (T2DM), and all-cause mortality.1 The National Health and Nutrition Examination Survey (NHANES) 2003-2006 estimated that approximately 34% of United States adults aged 20 years and more had MetS.2 The same NHANES data found that 53% had abdominal adiposity, a condition that is closely linked to visceral adipose stores. Excess visceral adiposity generates increased systemic levels of pro-inflammatory mediator molecules. Chronic, low- grade inflammation has been well documented as an associated and potentially inciting factor for the development of insulin resistance and T2DM.1 NHANES 2003-2006 data showed that 39% of subjects met criteria for insulin resistance. Insulin resistance is a component of MetS that significantly contributes to the expression of chronic, low-grade inflammation and predicts T2DM expression. T2DM costs the United States in excess of $174 billion in 2007. 3 It is estimated that 1 in 4 adults will have T2DM by the year 2050.3 Currently, more than one third of US adults (34.9%) are obese, 4 and, in 2008, the annual medical cost of obesity was $147 billion.4,5 This clearly represents a health care concern. The pervasiveness of MetS dictates that doctors of chiropractic will see a growing proportion of patients who fit the syndrome criteria.6 Chiropractic is most commonly used for musculoskeletal complaints believed to be mechanical in nature;6 however, an emerging body of evidence identifies MetS as a biochemical promoter of musculoskeletal complaints such as neck pain, shoulder pain, patella tendinopathy, and widespread musculoskeletal pain. 7–13 As an example, the cross-linking of collagen fibers can be caused by increased advanced glycation end-product (AGE) formation as seen in insulin resistance.14 Increased collagen cross-linking is observed in both osteoarthritis and degenerative disc disease, 15 and reduced mobility in elderly patients with T2DM has also been attributed to AGE-induced collagen cross-linking. 16,17 A diagnosis of MetS is made from a patient having 3 of the 5 findings presented in Table 1. Fasting hyperglycemia is termed impaired fasting glucose and indicates insulin resistance. 18,19 An elevated hemoglobin A1c (HbA1c) level measures long-term blood glucose regulation and is diagnostic for T2DM when elevated in the presence of impaired fasting glucose. 3,18 The emerging evidence demonstrates that we cannot view musculoskeletal pain as only coming from conditions that are purely mechanical in nature. Doctors of chiropractic must demonstrate prowess in identification and management of MetS and an understanding of insulin resistance as its main pathophysiological feature. The purposes of this article are to describe the current literature on the etiology and pathophysiology of insulin resistance as it relates to MetS and to suggest strategies for dietary and supplemental management in chiropractic practice. MethodsPubMed was searched from the earliest possible date to May 2014 to identify review articles that outlined the pathophysiology of MetS and T2DM. This led to further search refinements to identify inflammatory mechanisms that occur in the pancreas, adipose tissue, skeletal muscle, and hypothalamus. Searches were also refined to identify relationships among diet, supplements, and glycemic regulation. Both animal and human studies were reviewed. The selection of specific supplements was based on those that were most commonly used in the clinical setting, namely, gymnema sylvestre, vanadium, chromium and α-lipoic acid. DiscussionInsulin Resistance OverviewUnder normal conditions, skeletal muscle, hepatic, and adipose tissues require the action of insulin for cellular glucose entry. Insulin resistance represents an inability of insulin to signal glucose passage into insulin-dependent cells. Although a genetic predisposition can exist, the etiology of insulin resistance has been linked to chronic low-grade inflammation.1 Combined with insulin resistance-induced hyperglycemia, chronic low-grade inflammation also sustains MetS pathophysiology.1 Two thirds of postprandial blood glucose metabolism occurs within skeletal muscle via an insulin-dependent mechanism.18,19 Insulin binding to its receptor triggers glucose entry and subsequently inhibits lipolysis within the target tissue.21,22 Glucose enters skeletal muscles cells by way of a glucose transporter designated Glut4. 18 Owing to genetic variability, insulin-mediated glucose uptake can vary more than 6-fold among non-diabetic individuals. 23 Prolonged insulin resistance leads to structural changes within skeletal muscle such as decreased Glut4 transporter number, intramyocellular fat accu- mulation, and a reduction in mitochondrial con- tent.19,24 These events are thought to impact energy generation and functioning of affected skeletal mus- cle.24 Insulin-resistant skeletal muscle is less able to suppress lipolysis in response to insulin binding.25 Subsequently, saturated free fatty acids accumulate and generate oxidative stress. 22 The same phenomenon within adipose tissue generates a rapid adipose cell expansion and tissue hypoxia.26 Both these processes increase inflammatory pathway activation and the generation of proinflammatory cytokines (PICs).27 Multiple inflammatory mediators are associated with the promotion of skeletal muscle insulin resistance. The PICs tumor necrosis factor α (TNF-α), interleukin 1 (IL- 1), and IL-6 have received much attention because of their direct inhibition of insulin signaling.28–30 Since cytokine testing is not performed clinically, elevated levels of high- sensitivity C-reactive protein (hsCRP) best represent the low-grade systemic inflammation that characterizes insulin resistance.31,32 Insulin resistance–induced hyperglycemia can lead to irreversible changes in protein structure, termed glycation, and the formation of AGEs. Cells such as those of the vascular endothelium are most vulnerable to hyperglycemia due to utilization of an insulin-independent Glut1 transporter. 33 This makes AGE generation responsible for most diabetic complications, 15,33,34 including collagen cross-linking.15 If unchanged, prolonged insulin resistance can lead to T2DM expression. The relationship between chronic low-grade inflammation and T2DM has been well characterized. 35 Research has demonstrated that patients with T2DM also have chronic inflammation within the pancreas, termed insulitis, and it worsens hyperglycemia due to the progressive loss of insulin- producing β cells.36–39 Visceral Adiposity And Insulin ResistanceCaloric excess and a sedentary lifestyle contribute to the accumulation of subcutaneous and visceral adipose tissue. Adipose tissue was once thought of as a metabolically inert passive energy depot. A large body of evidence now demonstrates that excess visceral adipose tissue acts as a driver of chronic low-grade inflammation and insulin resistance.27,34 It has been documented that immune cells infiltrate rapidly expanding visceral adipose tissue. 26,40 Infil- trated macrophages become activated and release PICs that ultimately cause a phenotypic shift in resident macrophage phenotype to a classic inflammatory M1 profile.27 This vicious cycle creates a chronic inflam- matory response within adipose tissue and decreases the production of adipose-derived anti-inflammatory cytokines.43 As an example, adiponectin is an adipose- derived anti-inflammatory cytokine. Macrophage- invaded adipose tissue produces less adiponectin, and this has been correlated with increasing insulin resistance. 26 Hypothalamic Inflammation And Insulin ResistanceEating behavior in the obese and overweight has been popularly attributed to a lack of will power or genetics. However, recent research has demonstrated a link between hypothalamic inflammation and increased body weight.41,41 Centers that govern energy balance and glucose homeostasis are located within the hypothalamus. Recent studies demonstrate that inflammation in the hypothalamus coincides with metabolic inflammation and an increase in appetite.43 These hypothalamic centers simultaneously become resistant to anorexigenic stimuli, leading to altered energy intake. It has been suggested that this provides a neuropathological basis for MetS and drives a progressive increase in body weight. 41 Central metabolic inflammation pathologically activates hypothalamic immune cells and disrupts central insulin and leptin signaling.41 Peripherally, this has been associated with dysregulated glucose homeostasis that also impairs pancreatic β cell functioning.41,44 Hypothalamic inflammation contributes to hypertension through similar mechanisms, and it is thought that central inflammation parallels chronic low-grade systemic inflammation and insulin resistance.41–44 Clinical Correlates Diet-Induced Inflammation & Insulin ResistanceFeeding generally leads to a short-term increase in both oxidative stress and inflammation. 41 Total calories consumed, glycemic index, and fatty acid profile of a meal all influence the degree of postprandial inflammation. It is estimated that the average American consumes approximately 20% of calories from refined sugar, 20% from refined grains and flour, 15% to 20% from excessively fatty meat products, and 20% from refined seed/legume oils.45 This pattern of eating contains a macronutrient composition and glycemic index that promote hyperglycemia, hyperlipemia, and an acute postprandial inflammatory response. 46 Collectively referred to as postprandial dysmetabolism, this pro-inflammatory response can sustain levels of chronic low-grade inflammation that leads to excess body fat, coronary heart disease (CHD), insulin resistance, and T2DM.28,29,47 Recent evidence suggests that several MetS criteria may not sufficiently identify all individuals with postprandial dysmetabolism. 48,49 A 2-hour oral glucose tolerance test (2-h OGTT) result greater than 200 mg/dL can be used clinically to diagnose T2DM. Although MetS includes a fasting blood glucose level less than 100 mg/dL, population studies have shown that a fasting glucose as low as 90 mg/dL can be associated with an 2-h OGTT level greater than 200 mg/dL.49 Further, a recent large cohort study indicated that an increased 2-h OGTT was independently predictive of cardiovascular and all-cause mortality in a nondiabetic population. 48 Mounting evidence indicates that post- prandial glucose levels are better correlated with MetS and predicting future cardiovascular events than fasting blood glucose alone.41,48 Fasting triglyceride levels generally correlate with postprandial levels, and a fasting triglyceride level greater than 150 mg/dL reflects MetS and insulin resistance. Contrastingly, epidemiologic data indicate that a fasting triglyceride level greater than 100 mg/dL influences CHD risk via postprandial dysmetabolism. 48 The acute postprandial inflammatory response that contributes to CHD risk includes an increase in PICs, free radicals, and hsCRP.48,49 These levels are not measured clinically but, monitoring fasting glucose, 2-hour postprandial glucose and fasting triglycerides can be used as correlates of postprandial dysmetabolic and low-grade systemic inflammation. MetS And Disease ExpressionDiagnosis of MetS has been linked to an increased risk of developing T2DM and cardiovascular disease over the following 5 to 10 years. 1 It further increases a patient's risk of stroke, myocardial infarction, and death from any of the aforementioned conditions.1 Facchini et al47 followed 208 apparently healthy, non-obese subjects for 4 to 11 years while monitoring the incidence of clinical events such as hypertension, stroke, CHD, cancer, and T2DM. Approximately one fifth of participants experienced clinical events, and all of these subjects were either classified as intermediately or severely insulin resistant. It is important to note that all of these clinical events have a pathological basis in chronic low-grade inflammation,50 and no events were experienced in the insulin-sensitive groupings. 47 Insulin resistance is linked to musculoskeletal com- plaints both through chronic inflammation and the effects of AGEs. Advanced glycation end-products have been shown to extensively accumulate in osteoarthritic cartilage and treatment of human chondrocytes with AGEs increased their catabolic activity. 51 Advanced glycation end-products increase collagen stiffness via cross-linking and likely contribute to reduced joint mobility seen in elderly patients with T2DM.52 Com- pared to non-diabetics, type II diabetic patients are known to have altered proteoglycan metabolism in their intervertebral discs. This altered metabolism may pro- mote weakening of the annular fibers and subsequently, disc herniation.53 The presence of T2DM increases a person's risk of expressing disc herniation in both the cervical and lumbar spines.17,54 Patients with T2DM are also more likely to develop lumbar stenosis compared with non-diabetics, and this has been documented as a plausible relationship between MetS risk factors and physician-diagnosed lumbar disc herniation. 55–57 There are no specific symptoms that denote early skeletal muscle structural changes. Fatty infiltration and decreased muscle mitochondria content are observed within age-related sarcopenia 58 ; however, it is still being argued whether fatty infiltration is a risk factor for low back pain. 59,60 Clinical management of MetS should be geared toward improving insulin sensitivity and reducing chronic low-grade inflammation. 1 Regular exercise without weight loss is associated with reduced insulin resistance, and at least 30 minutes of aerobic activity and resistance training is recommended daily. 61,62 Although frequently considered preventative, exercise, dietary, and weight loss interventions should be considered alongside pharmacological management in those with MetS. 1 Data regarding the exact amount of weight loss needed to improve chronic inflammation are inconclusive. In overweight individuals without diagnosed MetS, a very-low-carbohydrate diet (b 10% calories from carbohydrate) has significantly reduced plasma inflammatory markers (TNF-α, hsCRP, and IL-6) with as little as 6% reduction in body weight.63,64 Individuals who meet MetS criteria may require 10% to 20% body weight loss to reduce inflammatory markers. 65 Interestingly, the Mediterranean Diet has been shown to reduce markers of systemic inflammation independent of weight loss65 and was recommended in the American College of Cardiology and American Heart Association Adult Treatment Panel 4 guidelines.66 A growing body of research has examined the effects of the Spanish ketogenic Mediterranean diet, including olive oil, green vegetables and salads, fish as the primary protein, and moderate red wine consumption. In a sample of 22 patients, adoption of the Spanish ketogenic Mediterranean diet with 9 g of supplemental salmon oil on days when fish was not consumed has led to complete resolution of MetS.67 Significant reductions in markers of chronic systemic inflammation were seen in 31 patients following this diet for 12 weeks.68 A Paleolithic diet based on lean meat, fish, fruits, vegetables, root vegetables, eggs, and nuts has been described as more satiating per calorie than a diabetes diet in patients with T2DM.69 In a randomized crossover study, a Paleolithic diet resulted in lower mean HbA1c values, triglycerides, diastolic blood pressure, waist circumference, improved glucose tolerance, and higher high-density lipoprotein (HDL) values compared to a diabetes diet.70 Within the context of these changes, a referral for medication management may be advisable. Irrespective of name, a low-glycemic diet that focuses on vegetables, fruits, lean meats, omega-3 fish, nuts, and tubers can be considered anti-inflammatory and has been shown to ameliorate insulin resistance. 49,71–73 Inflammatory markers and insulin resistance further improve when weight loss coincides with adherence to an anti-inflammatory diet.70 A growing body of evidence suggests that specific supplemental nutrients also reduce insulin resistance and improve chronic low-grade inflammation. Key Nutrients That Promote Insulin SensitivityResearch has identified nutrients that play key roles in promoting proper insulin sensitivity, including vitamin D, magnesium, omega-3 (n-3) fatty acids, curcumin, gymnema, vanadium, chromium, and α-lipoic acid. It is possible to get adequate vitamin D from sun exposure and adequate amounts of magnesium and omega-3 fatty acids from food. Contrastingly, the therapeutic levels of chromium and α-lipoic acid that affect insulin sensitivity and reduce insulin resistance cannot be obtained in food and must be supplemented. Vitamin D, Magnesium, Omega-3 Fatty Acids, & CurcuminVitamin D, magnesium, and n-3 fatty acids have multiple functions, and generalized inflammation reduction is a common mechanism of action.74–80 Their supplemental use should be considered in the context of low-grade inflammation reduction and health promotion, rather than as a specific treatment for MetS or T2DM. Evidence pertaining to the precise role of vitamin D in MetS and insulin resistance is inconclusive. Increas- ing dietary and supplemental vitamin D intake in young men and women may lower the risk of MetS and T2DM development,81 and a low serum vitamin D level has been associated with insulin resistance and T2DM expression. 82 Supplementation to improve low serum vitamin D (reference range, 32-100 ng/mL) is effective, but its impact on improving central glycemia and insulin sensitivity is conflicting. 83 Treating insulin resistance and MetS with vitamin D as a monotherapy appears to be unsuccessful. 82,83 Achieving normal vitamin D blood levels through adequate sun exposure and/or supplementation is advised for general health. 84–86 The average American diet commonly contains a low magnesium intake.80 Recent studies suggest that supple- mental magnesium can improve insulin sensitivity. 81,82 Taking 365 mg/d may be effective in reducing fasting glucose and raising HDL cholesterol in T2DM,83 as well as normomagnesemic, overweight, nondiabetics. 84 Diets high in the omega-6 fat linoleic acid have been associated with insulin resistance85 and higher levels of serum pro-inflammatory mediator markers including IL-6, IL-1β, TNF-α, and hsCRP.87 Supplementation to increase dietary omega-3 fatty acids at the expense of omega-6 fatty acids has been shown to improve insulin sensitivity. 88–90 Six months of omega-3 supplementation at 3 g/d with meals has been shown to reduce MetS markers including fasting triglycerides, HDL cholesterol, and an increase in anti-inflammatory adiponectin. 91 Curcumin is responsible for the yellow pigmentation of the spice turmeric. Its biological effects can be characterized as antidiabetic and antiobesity via down- regulating TNF-α, suppressing nuclear factor κB activation, adipocytokine expression, and leptin level modulation,. 92–95 Curcumin has been reported to activate peroxisome proliferator-activated receptor-γ, the nuclear target of the thiazolidinedione class of antidiabetic drugs,93 and it also protects hepatic and pancreatic cells. 92,93 Numerous studies have reported weight loss, hsCRP reduction, and improved insulin sensitivity after curcumin supplementation.92–95 There is no established upper limit for curcumin, and doses of up to 12 g/d are safe and tolerable in humans. 96 A randomized, double-blinded, placebo- controlled trial (N = 240) showed a reduced progression of prediabetes to T2DM after 9 months of 1500 mg/d curcumin supplementation.97 Curcumin, 98 vitamin D, 84 magnesium, 91 and omega-3 fatty acids80 are advocated as daily supplements to promote general health. A growing body of evidence supports the views of Gymnema sylvestre, vanadium, chromium, and α-lipoic acid should as therapeutic supplements to assist in glucose homeostasis. G SylvestreGymnemic acids are the active component of the G sylvestre plant leaves. Gymnemic acids are the active component of the G sylvestre plant leaves. Studies evaluating G sylvestre's effects on diabetes in humans have generally been of poor methodological quality. Experimental animal studies have found that gymnemic acids may decrease glucose uptake in the small intestine, inhibit gluconeogenesis, and reduce hepatic and skeletal muscle insulin resistance.99 Other animal studies suggest that gymnemic acids may have comparable efficacy in reducing blood sugar levels to the first-generation sulfonylurea, tolbutamide.100 Evidence from open-label trials suggests its use as a supplement to oral antidiabetic hypoglycemic agents. 96 One quarter of patients were able to discontinue their drug and maintain normal glucose levels on an ethanolic gymnema extract alone. Although the evidence to date suggests its use in humans and animals is safe and well tolerated, higher quality human studies are warranted. Vanadyl SulfateVanadyl sulfate has been reported to prolong the events of insulin signaling and may actually improve insulin sensitivity.101 Limited data suggest that it inhibits gluconeogenesis, possibly ameliorating hepatic insulin resistance. 100,101 Uncontrolled clinical trials have reported improvements in insulin sensitivity using 50 to 300 mg daily for periods ranging from 3 to 6 weeks. 101–103 Contrastingly, a recent randomized, double-blind, placebo-controlled trial found that 50 mg of vanadyl sulfate twice daily for 4 weeks had no effect in individuals with impaired glucose tolerance. 104 Limited clinical and experimental data exist supporting the use of vanadyl sulfate to improve insulin resistance, and further research is warranted regarding its safety and efficacy. ChromiumDiets high in refined sugar and flour are deficient in chromium (Cr) and lead to an increased urinary excretion of chromium. 105,106 The progression of MetS is not likely caused by a chromium deficiency, 107 and dosages that benefit glycemic regulation are not achievable through food. 106,108,109 A recent randomize, double-blind trial demonstrated that 1000 μg Cr per day for 8 months improved insulin sensitivity by 10% in subjects with T2DM.110 Cefalu et al110 further suggested that these improvements might be more applicable to patients with a greater degree of insulin resistance, impaired fasting plasma glucose, and higher HbA1c values. Chromium's mechanism of action for improving insulin sensitivity is through increased Glut4 translocation via prolonging insulin receptor signaling.109 Chromium has been well tolerated at 1000 μg/d,105 and animal models using significantly more than 1000 μ Cr per day were not associated with toxicological consequences.109 α-Lipoic AcidHumans derive α-lipoic acid through dietary means and from endogenous synthesis. 111 The foods richest in α-lipoic acid are animal tissues with extensive metabolic activity such as animal heart, liver, and kidney, which are not consumed in large amounts in the typical American diet. 111 Supplemental amounts of α-lipoic acid used in the treatment of T2DM (300-600 mg) are likely to be as much as 1000 times greater than the amounts that could be obtained from the diet.112 Lipoic acid synthase (LASY) appears to be the key enzyme involved in the generation of endogenous lipoic acid, and obese mice with diabetes have reduced LASY expression when compared with age-and sex- matched controls.111 In vitro studies to identify potential inhibitors of lipoic acid synthesis suggest a role for diet-induced hyperglycemia and the PIC TNF- α in the down-regulation of LASY.113 The inflammatory basis of insulin resistance may therefore drive lowered levels of endogenous lipoic acid via reducing the activity of LASY. α-Lipoic acid has been found to act as insulin mimetic via stimulating Glut4-mediated glucose trans- port in muscle cells. 110,114α-Lipoic acid is a lipophilic free radical scavenger and may affect glucose homeostasis through protecting the insulin receptor from damage114 and indirectly via decreasing nuclear factor κB–mediated TNF-α and IL-1 production. 110 In postmenopausal women with MetS (presence of at least 3 ATPIII clinical criteria) 4 g/d of a combined inositol and α-lipoic acid supplement for 6 months significantly improved OGTT scores by 20% in two thirds of the subjects. 114 A recent randomized double-blinded placebo-controlled study showed that 300 mg/d α- lipoic acid for 90 days significantly decreased HbA1c values in subjects with T2DM.115 Side effects to α-lipoic acid supplementation as high as 1800 mg/d have largely been limited to nausea. 116 It may be best to take supplemental α-lipoic acid on an empty stomach (1 hour before or 2 hours after eating) because food intake reportedly reduces its bioavailability.117 Clinicians should be aware that α-lipoic acid supplementation might increase the risk of hypoglycemia in diabetic patients using insulin or oral antidiabetic agents.117 LimitationsThis is a narrative overview of the topic of MetS. A systematic review was not performed; therefore, there may be relevant information missing from this review. The contents of this overview focuses on the opinions of the authors, and therefore, others may disagree with our opinions or approaches to management. This overview is limited by the studies that have been published. To date, no studies have been published that identify the effectiveness of a combination of a dietary intervention, such as the Spanish ketogenic diet, and nutritional supplementation on the expression of the MetS. Similarly, this approach has not been studied in patients with musculoskeletal pain who also have the MetS. Consequently, the information presented in this article is speculative. Longitudinal studies are needed before any specific recommendations can be made for patients with musculoskeletal that may be influenced by the MetS. Conclusion: Metabolic SyndromeThis overview suggests that MetS and type 2 diabetes are complex conditions, and their prevalence is expected to increase substantially in the coming years. Thus, it is important to identify if the MetS may be present in patients who are nonresponsive to manual care and to help predict who may not respond adequately. We suggest that diet and exercise are essential to managing these conditions, which can be supported with key nutrients, such as vitamin D, magnesium, and omega-3 fatty acids. We also suggest that curcumin, G sylvestre, vanadyl sulfate chromium, and α-lipoic acid could be viewed as specific nutrients that may be taken during the process of restoring appropriate insulin sensitivity and signaling. David R. Seaman DC, MS,⁎, Adam D. Palombo DC Professor, Department of Clinical Sciences, National University of Health Sciences, Pinellas Park, FL Private Chiropractic Practice, Newburyport, MA Funding Sources and Conflicts of InterestNo funding sources were reported for this study. David Seaman is a paid consultant for Anabolic Laboratories, a manufacturer of nutritional products for health care professionals. Adam Palombo was sponsored and remunerated by Anabolic laboratories to speak at chiropractic conventions/meetings. References: 1. Kaur J. A comprehensive review on metabolic syndrome.<br />
Cardiol Res Pract 2014:943162, http://dx.doi.org/10.1155/<br />
2014/943162.<br />
2. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic<br />
syndrome among US adults. Findings from the Third National<br />
Health and Nutrition Examination Survey. J Am Med Assoc<br />
2006;287:356–9.<br />
3. Boyle JP, Thompson TJ, Gregg EW, Barker LE, Williamson<br />
DF. Projection of the year 2050 burden of diabetes in the US<br />
adult population: dynamic modeling of incidence, mortality,<br />
and prediabetes prevalence. Popul Health Metr 2010;8:29,<br />
http://dx.doi.org/10.1186/1478-7954-8-29.<br />
4. [Internet]Centers for Disease Control and Prevention.<br />
Adult Obesity Facts. Atlanta: CDC; 2014. [Available from<br />http://www.cdc.gov/obesity/data/adult.html].<br />
5. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of<br />
childhood and adult obesity in the United States, 2011–2012.<br />
JAMA 2014;311(8):806–14.<br />
6. Riksman JS, Williamson OD, Walker BF. Delineating<br />
inflammatory and mechanical sub-types of low back pain: a<br />
pilot survey of fifty low back pain patients in a chiropractic<br />
setting. Chiropr Man Therap 2011;19(1):5, http://dx.doi.org/<br />
10.1186/2045-709X-19-5.<br />
7. Dobretsov M, Ghaleb AH, Romanovsky D, Pablo CS, Stimers<br />
JR. Impaired insulin signaling as a potential trigger of<br />
pain in diabetes and prediabetes. Int Anesthesiol Clin<br />
2007;45(2):95–105.<br />
8. Mantyselka P, Miettola J, Niskanen L, Kumpusalo E. Glucose<br />
regulation and chronic pain at multiple sites. Rheumatology<br />
2008;47(8):1235–8.<br />
9. Mäntyselkä P, Miettola J, Niskanen L, Kumpusalo E.<br />
Persistent pain at multiple sites—connection to glucose<br />
derangement. Diabetes Res Clin Pract 2009;84(2):e30–2.<br />
10. Mantyselka P, Kautianen H, Vanhala M. Prevalence of neck<br />
pain in subjects with metabolic syndrome—a cross-sectional<br />
population-based study. BMC Musculoskelet Disord 2010;11:<br />
171, http://dx.doi.org/10.1186/1471-2474-11-171.<br />
11. Rechardt M, Shiri R, Karppinen J, Jula A, Heliövaara M,<br />
Viikari-Juntura E. Lifestyle and metabolic factors in relation<br />
to shoulder pain and rotator cuff tendinitis: a population-based<br />
study. BMC Musculoskelet Disord 2010;11:165.<br />
12. Gaida JE, Alfredson L, Kiss ZS, Wilson AM, Alfredson H,<br />
Cook JL. Dyslipidemia in Achilles tendinopathy is<br />
characteristic of insulin resistance. Med Sci Sports Exerc<br />
2009;41:1194–7.<br />
13. Malliaras P, Cook JL, Kent PM. Anthropometric risk factors<br />
for patellar tendon injury among volleyball players. Br J<br />
Sports Med 2007;41:259–63.<br />
14. Skrzynski S. DSC study of collagen in disc disease. J Biophys<br />
2009;2009:819635, http://dx.doi.org/10.1155/2009/819635.<br />
15. Luevano-Contreras C, Chapman-Novakofski K. Dietary<br />
advanced glycation end products and aging. Nutrients<br />
2010;2(12):1247–65 [2009;2009:819635].<br />
16. Abate M, Schiavone C, Pelotti P, Salini V. Limited joint<br />
mobility (LJM) in elderly subjects with type II diabetes<br />
mellitus. Arch Gerontol Geriatrics 2011;53:135–40.<br />
17. Sakellaridis N. The influence of diabetes mellitus on lumbar<br />
intervertebral disk herniation. Surg Neurol 2006;66:152–4.<br />
18. Shepherd PR, Kahn BB. Glucose transporters and insulin<br />
action: implications for insulin resistance and diabetes<br />
mellitus. New Eng J Med 1999;341(4):248–57.<br />
19. Abdul-Ghani MA, DeFronzo RA. Pathogenesis of insulin<br />
resistance in skeletal muscle. J Biomed Biotechnol 2010:19,<br />
http://dx.doi.org/10.1155/2010/476279 [Article ID 476279].<br />
20. [Internet]American Heart Association. About metabolic<br />
syndrome. Dallas: The Association; 2014. [Available from<br />http://www.heart.org/HEARTORG/Conditions/More/<br />MetabolicSyndrome/About-Metabolic-Syndrome_UCM_<br />301920_Article.jsp].<br />
21. Hotamisligil GS. Inflammation and metabolic disorders.<br />
Nature 2006;444:860–7.<br />
22. Glass CK, Olefsky JM. Inflammation and lipid signaling in the<br />
etiology of insulin resistance. Cell Metab 2012;15(5):635–45.<br />
23. Reaven GM. All obese individuals are not created equal:<br />
insulin resistance is the major determinant of cardiovascular<br />
disease in overweight/obese individuals. Diabetes Vasc Dis<br />
Res 2005;2:105–12.<br />
24. Ritov VB, Menshikova EV, He J, Ferrell RE, Goodpaster<br />
BH, Kelley DE. Deficiency of subsarcolemmal mitochondria<br />
in obesity and type 2 diabetes. Diabetes 2005;54:8–14.<br />
25. Corcoran MP, Lamon-Fava S, Fielding RA. Trans fats and<br />
insulin resistance: skeletal muscle lipid deposition and insulin<br />
resistance: effect of dietary fatty acids and exercise. Am J Clin<br />
Nutr 2007;85:662–77.<br />
26. Schipper HS, Prakken B, Kalkhoven E, Boes M. Adipose<br />
tissue-resident immune cells: key players in immunometabolism.<br />
Trends Endocrinol Metab 2012;23:407–15.<br />
27. Antuna-Puente B, Feve B, Fellahi S, Bastard JP. Adipokines:<br />
the missing link between insulin resistance and obesity.<br />
Diabetes Metab 2008;34:2–11.<br />
28. Grimble RF. Inflammatory status and insulin resistance. Curr<br />
Opin Clin Nutr Metab Care 2003;5:551–9.<br />
29. Tilg H, Moschen AR. Inflammatory mechanisms in<br />
the regulation of insulin resistance. Mol Med 2008;3–4:222–31.<br />
30. Johnson DR, O'Conner JC, Satpathy A, Freund GG.<br />
Cytokines in type 2 diabetes. Vitam Horm 2006;74:405–41.<br />
31. Ridker PM, Wilson PW, Grundy SM. Should C-reactive<br />
protein be added to the metabolic syndrome and to<br />
assessment of global cardiovascular risk? Circulation 2004;<br />
109:2818–25.<br />
32. Gelaye B, Revilla L, Lopez T, et al. Association between<br />
insulin resistance and c-reactive protein among Peruvian<br />
adults. Diabetol Metab Syn 2010;2:30.<br />
33. Singh VP, Bali A, Singh N, et al. Advanced glycation end<br />
products and diabetic complications. Korean J Physiol<br />
Pharmacol 2014;18(1):1–14.<br />
34. Baker RG, Hayden MS. NF-kB, inflammation and metabolic<br />
disease. Cell Metab 2011;13(1):11–22.<br />
35. Purkayastha S, Cair D. Neuroinflammatory basis of metabolic<br />
syndrome. Mol Metab Nov 2013;2(4):356–63.<br />
36. Ehse JA, Boni-Schnetzler M, Faulenbach M, Donath MY.<br />
Macrophages, cytokines and beta-cell death in type 2 diabetes.<br />
Biochem Soc Trans 2008;36(3):340–2.<br />
37. Boni-Schnetzler M, Ehses JA, Faulenbach M, Donath MY.<br />
Insulitis in type 2 diabetes. Diabetes Obes Metab 2008;10<br />
(Suppl 4):201–4.<br />
38. Donath MY, Schumann DM, Faulenbach M, Ellingsgaard H,<br />
Perren A, Ehses JA. Islet inflammation in type 2<br />
diabetes: from metabolic stress to therapy. Diabetes Care<br />
2008;31(Suppl 2):S161–4.<br />
39. Donath MY, Boni-Schnetzler M, Ellingsgaard H, Ehses JA.<br />
Islet inflammation impairs the pancreatic beta-cell in type 2<br />
diabetes. Physiology 2009;24:325–31.<br />
40. Harford KA, Reynolds CM, McGillicuddy FC, Roche HM.<br />
Fats, inflammation and insulin resistance: insights to the role<br />
of macrophage and T-cell accumulation in adipose tissue.<br />
Proc Nutr Soc 2011;70:408–17.<br />
41. Munoz A, Costa M. Nutritionally mediated oxidative stress and<br />
inflammation. Oxid Med Cell Longev 2013;2013:610950, http://<br />
dx.doi.org/10.1155/2013/610950.<br />
42. Wisse BE, Schwartz MW. Does hypothalamic inflammation<br />
cause obesity? Cell Metab 2009;10(4):241–2.<br />
43. Purkayastha S, Cair D. Neuroinflammatory basis of metabolic<br />
syndrome. Mol Metab Nov 2013;2(4):356–63.<br />
44. Calegari VC, Torsoni AS, Vanzela EC, Araújo EP, Morari<br />
J, Zoppi CC, et al. Inflammation of the hypothalamus leads<br />
to defective pancreatic islet function. J Biol Chem 2011;<br />
286(15):12870–80.<br />
45. Cordain L, Eaton SB, Sebastian A, et al. Origins and evolution<br />
of the Western diet: health implications for the 21st century.<br />
Am J Clin Nutr 2005;81:341–54.<br />
46. Barclay AW, Petocz P, McMillan-Price J, et al. Glycemic<br />
index, glycemic load, and chronic disease risk—a metaanalysis<br />
of observational studies. Am J Clin Nutr<br />
2008;87:627–37.<br />
47. Facchini FS, Hua N, Abbasi F, Reaven GM. Insulin resistance<br />
as a predictor of age-related disease. J Clin Endocrinol Metab<br />
2001;86:3574–8.<br />
48. Lin H, Lee B, Ho Y, et al. Postprandial glucose improves the<br />
risk prediction of cardiovascular death beyond the metabolic<br />
syndrome in the nondiabetic population. Diabetes Care Sep<br />
2009;32(9):1721–6.<br />
49. O'Keefe JH, Bell DS. Postprandial hyperglycemia/<br />
hyperlipidemia (postprandial dysmetabolism) is a cardiovascular<br />
risk factor. Am J Cardiol 2007;100:899–904.<br />
50. Cao H. Adipocytokines in obesity and metabolic disease.<br />
J Endocrinol 2014;220(2):T47–59.<br />
51. Nah SS, Choi IY, Lee CK, et al. Effects of advanced glycation<br />
end products on the expression of COX2, PGE2 and NO in human osteoarthritic chondrocytes. Rheumatology (Oxford)<br />
2008;47(4):425–31.<br />
52. Abate M, Schiavone C, Pelotti P, Salini V. Limited joint<br />
mobility (LJM) in elderly subjects with type II diabetes<br />
mellitus. Arch Gerontol Geriatr 2011;53:135–40.<br />
53. Robinson D, Mirovsky Y, Halperin N, Evron Z, Nevo Z.<br />
Changes in proteoglycans of intervertebral disc in diabetic<br />
patients: a possible cause of increased back pain. Spine<br />
1998;23:849–56.<br />
54. Sakellaridis N, Androulis A. Influence of diabetes mellitus on<br />
cervical intervertebral disc herniation. Clin Neurol Neurosurg<br />
2008;110:810–2.<br />
55. Jhawar BS, Fuchs CS, Colditz GA, Stampfer MJ. Cardiovascular<br />
risk factors for physician-diagnosed lumbar disc<br />
herniation. Spine J 2006;6:684–91.<br />
56. Lotan R, Oron A, Anekstein Y, Shalmon E, Mirovsky Y.<br />
Lumbar stenosis and systemic diseases: is there any relevance.<br />
J Spinal Disord Tech 2008;21:247–51.<br />
57. Anekstein Y, Smorgick Y, Lotan R, et al. Diabetes mellitus as<br />
a risk factor for the development of lumbar spinal stenosis. Isr<br />
Med Assoc J 2010;12:16–20.<br />
58. Choi KM. Sarcopenia and sarcopenic obesity. Endocrinol<br />
Metab (Seoul) 2013;28(2):86–9.<br />
59. D'hooge R, Cagnie B, Crombez G, et al. Increased<br />
intramuscular fatty infiltration without differences in lumbar<br />
muscle cross-sectional area during remission of unilateral<br />
recurrent low back pain. Man Ther 2012 Dec;17(6):5584–8.<br />
60. Chen YY, Pao JL, Liaw CK, et al. Image changes of paraspinal<br />
muscles and clinical correlations in patients with unilateral<br />
lumbar spinal stenosis. Eur Spine J 2014;23(5):999–1006.<br />
61. Kim Y, Park H. Does regular exercise without weight loss<br />
reduce insulin resistance in children and adolescents? In J<br />
Endocrinol 2013:402592, http://dx.doi.org/10.1155/2013/<br />
402592 [Epub 2013 Dec 12].<br />
62. Strasser B, Siebert U, Schobersberger W. Resistance training<br />
in the treatment of the metabolic syndrome: a systematic<br />
review and meta-analysis of the effect of resistance training on<br />
metabolic clustering in patients with abnormal glucose<br />
metabolism. Sports Med 2010;40:397–415.<br />
63. Sharman MJ, Volek JS. Weight loss leads to reductions in<br />
inflammatory biomarkers after a very-low-carbohydrate diet<br />
and a low-fat diet in overweight men. Clin Sci (Lond)<br />
2004;13:365–9.<br />
64. Teng KT, Chang CY, Chang LF, et al. Modulation of obesityinduced<br />
inflammation by dietary fats: mechanisms and<br />
clinical evidence. Nutr J 2014;13:12, http://dx.doi.org/<br />
10.1186/1475-2891-13-12.<br />
65. Tzotzas T, Evangelou P, Kiortsis DN. Obesity, weight loss<br />
and conditional cardiovascular risk factors. Obes Rev 2011;12<br />
(5):e282–9.<br />
66. Stone N, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA<br />
Guideline on the Treatment of Blood Cholesterol to Reduce<br />
Atherosclerotic Cardiovascular Risk in Adults: A report of<br />
the American College of Cardiology/American Heart<br />
Association Task Force on practice guidelines. Circulation<br />
2014;129(25 Suppl 2):S1–S45.<br />
67. Pérez-Guisado J, Muñoz-Serrano A. A pilot study of the<br />
Spanish ketogenic Mediterranean diet: an effective therapy for<br />
the metabolic syndrome. J Med Food 2011;14(7–8):681–7.<br />
68. Pérez-Guisado J, Muñoz-Serrano A, Alonso-Moraga A.<br />
Spanish ketogenic Mediterranean diet: a healthy cardiovascular<br />
diet for weight loss. Nutr J 2008;7:30, http://dx.doi.org/<br />
10.1186/1475-2891-7-30.<br />
69. Jonsson T, Granfeldt Y, Lindeberg S, et al. Subjective satiety<br />
and other experiences of a Paleolithic diet compared to a<br />
diabetes diet in patients with T2DM. Nutr J 2013;12:105,<br />
http://dx.doi.org/10.1186/1475-2891-12-105.<br />
70. Jonsson T, Granfeldt Y, Ahren B, et al. Beneficial effects of a<br />
Paleolithic diet on cardiovascular risk factors in T2DM: a<br />
randomized cross-over pilot study. Cardiovasc Diabetol<br />
2009;8:35, http://dx.doi.org/10.1186/1475-2840-8-35.<br />
71. Nicklas BJ, You T, Pahor M. Behavioural treatments<br />
for chronic system inflammation: effects of dietary<br />
weight loss and exercise training. Can Med Assoc J<br />
2005;172(9):1199–209.<br />
72. O'Keefe JH, Gheewala NM, O'Keefe JO. Dietary<br />
strategies for improving post-prandial glucose, lipids, inflammation,<br />
and cardiovascular health. J Am Coll Cardiol<br />
2008;51:249–55.<br />
73. O'Keefe Jr JH, Cordain L. Cardiovascular disease resulting<br />
from a diet and lifestyle at odds with our Paleolithic genome:<br />
how to become a 21st-century hunter–gatherer. Mayo Clin<br />
Proc 2004;79(1):101–8.<br />
74. Ames BN. Low micronutrient intake may accelerate the<br />
degenerative diseases of aging through allocation of scarce<br />
micronutrients by triage. Proc Natl Acad Sci U S A 2006;103<br />
(47):17589–94.<br />
75. Holick MF, Chen TC. Vitamin D deficiency: a worldwide<br />
problem with health consequences. Am J Clin Nutr<br />
2008;87:1080S–6S [Suppl.].<br />
76. Toubi E, Shoenfeld Y. The role of vitamin D in regulating<br />
immune responses. Isr Med Assoc J 2010;12(3):174–5.<br />
77. King DE, Mainous AG, Geesey ME, Egan BM, Rehman S.<br />
Magnesium supplement intake and C-reactive protein levels<br />
in adults. Nutr Res 2006;26:193–6.<br />
78. Rosanoff A, Weaver CM, Rude RK. Suboptimal magnesium<br />
status in the United States: are the health consequences<br />
underestimated? Nutr Rev 2012;70(3):153–64.<br />
79. Simopoulos AP. Omega-3 fatty acids in inflammation and<br />
autoimmune diseases. J Am Coll Nutr 2002;21(6):495–505.<br />
80. Simopoulos AP. The importance of the omega-6/omega-3<br />
fatty acid ratio in cardiovascular disease and other chronic<br />
diseases. Exp Biol Med 2008;233:674–88.<br />
81. Fung GJ, Steffen LM, Zhou X, et al. Vitamin D intake is<br />
inversely related to risk of developing metabolic syndrome<br />
in African American and white men and women over 20 y:<br />
the Coronary Artery Risk Development in Young Adults<br />
study. Am J Clin Nutr 2012;96(1):24–9 [Published online<br />2012 May 30].<br />
82. Palomer X, Gonzalez-Clemente JM, Blanco-Vaca F, Mauricio<br />
D. Role of vitamin D in the pathogenesis of type 2 diabetes<br />
mellitus. Diabetes Obes Metab 2008;10:185–97.<br />
83. Guadarrama-Lopez AL, Valdes-Ramos R, Martinex-Carrillo<br />
BE. T2DM, PUFAs, and vitamin D: their relation to<br />
inflammation. J Immunol Res 2014;2014:860703, http://dx.<br />
doi.org/10.1155/2014/860703.<br />
84. Cannell JJ, Hollis BW. Use of vitamin D in clinical practice.<br />
Altern Med Rev 2008;13(1):6–20.<br />
85. Davidson MB, Duran P, Lee ML, Friedman TC. High-dose<br />
vitamin D supplementation in people with prediabetes and<br />
hypovitaminosis D. Diabetes Care 2013;36(2):260–6, http://<br />
dx.doi.org/10.2337/dc12-1204.<br />
86. Schwalfenberg G. Vitamin D, and diabetes: improvement of<br />
glycemic control with vitamin D3 repletion. Can Fam<br />
Physician 2008;54:864–6.<br />
87. Kim DJ, Xun P, Liu K, et al. Magnesium intake in relation to<br />
systemic inflammation, insulin resistance, and the incidence<br />
of diabetes. Diabetes Care 2010;33(12):2604–10, http://dx.<br />
doi.org/10.2337/dc10-0994.<br />
88. Guerrero-Romero F, Tamez-Perez HE, González-González G,<br />
et al. Oral magnesium supplementation improves insulin<br />
sensitivity in non-diabetic subjects with insulin resistance. A<br />
double-blind placebo-controlled randomized trial. Diabetes<br />
Metab 2004;30(3):253–8.<br />
89. Rodríguez-Morán M, Guerrero-Romero F. Oral magnesium<br />
supplementation improves insulin sensitivity and metabolic<br />
control in type 2 diabetic subjects: a randomized double-blind<br />
controlled trial. Diabetes Care 2003;26(4):1147–52.<br />
90. Song Y, He K, Levitan EB, Manson JE, Liu S. Effects of oral<br />
magnesium supplementation on glycaemic control in type 2<br />
diabetes: a meta-analysis of randomized double-blind controlled<br />
trials. Diabet Med 2006;23(10):1050–6.<br />
91. Mooren FC, Krüger K, Völker K, Golf SW,Wadepuhl M, Kraus<br />
A. Oral magnesium supplementation reduces insulin resistance<br />
in non-diabetic subjects—a double-blind, placebo-controlled,<br />
randomized trial. Diabetes Obes Metab 2011;13(3):281–4.<br />
92. Aggarwal BB. Targeting inflammation induced obesity and<br />
metabolic diseases by curcumin and other nutraceuticals.<br />
Annu Rev Nutr 2010;30:173–9.<br />
93. Alappat L, Awad AB. Curcumin and obesity: evidence and<br />
mechanisms. Nutr Rev 2010;68(12):729–38.<br />
94. Gonzales AM, Orlando RA. Curcumin and resveratrol inhibit<br />
nuclear factor-kappaB-mediated cytokine expression in adipocytes.<br />
Nutr Metab 2008;5:17, http://dx.doi.org/10.1186/<br />
1743-7075-5-17.<br />
95. Sahebkar A. Why it is necessary to translate curcumin into<br />
clinical practice for the prevention and treatment of metabolic<br />
syndrome? Biofactors 2012, http://dx.doi.org/10.1002/<br />
biof.1062 [Epub ahead of print].<br />
96. Hsu CH, Cheng AL. Clinical studies with curcumin. Adv Exp<br />
Med Biol 2007;595:471–80.<br />
97. Chuengsamarn S, Rattanamongkolgul S, Luechapudiporn R,<br />
Phisalaphong C, Jirawatnotai S. Curcumin extract for prevention<br />
of type 2 diabetes. Diabetes Care 2012;35(11):2121–7.<br />
98. Jurenka JS. Anti-inflammatory properties of curcumin, a<br />
major constituent of curcuma longa: a review of preclinical<br />
and clinical research. Altern Med Rev 2009;14(2):141–53.<br />
99. Leach M. Gymnema sylvestre for diabetes mellitus: a systematic<br />
review. J Altern Complement Med 2007;13(9):977–83.<br />
100. Chattopadhyay R. A comparative evaluation of some blood<br />
sugar lowering agents of plant origin. J Ethnopharmacol<br />
1999;67:367–72.<br />
101. Nahas R, Moher M. Complementary and alternative medicine<br />
for the treatment of type 2 diabetes. Can Fam Physician<br />
2009;55:591–6.<br />
102. Vanadium/Vanadyl sulfate: monograph. Altern Med Rev<br />
2009;14:17–80.<br />
103. Boden G, Chen X, Ruiz J, et al. Effects of vanadyl sulfate<br />
on carbohydrate and lipid metabolism in patients with noninsulin-dependent<br />
diabetes mellitus. Metabolism 1996;45:<br />
1130–5.<br />
104. Jacques-Camarena O, González-Ortiz M, Martínez-Abundis E,<br />
et al. Effect of vanadium on insulin sensitivity in patients with<br />
impaired glucose tolerance. Ann Nutr Metab 2008;53:195–8.<br />
105. Vincent JB. The biochemisty of chromium. J Nutr<br />
2000;130:715–8.<br />
106. Anderson RA. Chromium and insulin resistance. Nutr Res<br />
Rev 2003;16:267–75.<br />
107. Vincent JB. Chromium: celebrating 50 years as an essential<br />
element? Dalton Trans 2010;39:3787–94.<br />
108. Office of Dietary Supplements. [Internet]. Dietary supplement<br />
fact sheet: Chromium. Washington, DC: United States<br />
Department of Health and Human Services. http://ods.od.nih.<br />
gov/factsheets/chromium/. Reviewed November 4, 2013.<br />
109. Anderson RA. Chromium, glucose intolerance and diabetes.<br />
J Am Coll Nutr 1998;17(6):548–55.<br />
110. Cefalu WT, Rood J, Patricia Pinsonat P, et al. Characterization<br />
of the metabolic and physiologic response to chromium<br />
supplementation in subjects with type 2 diabetes mellitus.<br />
Metab Clin Exp 2010;59:755–62.<br />
111. Heimbach JT, Anderson RA. Chromium: recent studies regarding<br />
nutritional roles and safety. Nutr Today 2005;40(4):180–95.<br />
112. Shay KP, Moreau RF, Smith EJ, Smith AR, Hagen TM.<br />
Alpha-lipoic acid as a dietary supplement: molecular<br />
mechanisms and therapeutic potential. Biochim Biophys<br />
Acta 2009;1790:1149–60.<br />
113. Morikawa T, Yasuno R, Wada H. Do mammalian cells<br />
synthesize lipoic acid? Identification of a mouse cDNA<br />
encoding a lipoic acid synthase located in mitochondria.<br />
FEBS Lett 2001;498:16–21.<br />
114. Singh U, Jialal I. Alpha-lipoic acid supplementation and<br />
diabetes. Nutr Rev 2008;66(11):646–57.<br />
115. Padmalayam I, Hasham S, Saxena U, Pillarisetti S. Lipoic acid<br />
synthase (LASY): a novel role in inflammation, mitochondrial<br />
function, and insulin resistance. Diabetes 2009;58:600–8.<br />
116. Capasso I, Esposito E, Maurea N, et al. Combination of<br />
inositol and alpha lipoic acid in metabolic syndrome-affected<br />
women: a randomized placebo-controlled trial. Trial<br />
2013;14:273, http://dx.doi.org/10.1186/1745-6215-14-273.<br />
117. Udupa A, Nahar P, Shah S, et al. A comparative study of<br />
effects of omega-3 fatty acids, alpha lipoic acid and vitamin E<br />
in T2DM. Ann Med Health Sci Res 2013;3(3):442–6.
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Dr. Alex Jimenez, health coach Kenna Vaughn, Astrid Ornelas, Truide Torres, and biochemist Alexander Isaiah Jimenez discuss what is metabolic syndrome and the steps to fix it. Metabolic Syndrome
For many individuals reclaiming their health, the incidence of metabolic syndrome, and type 2 diabetes along with many other conditions that can be related to insulin resistance. Many local healthcare practitioners need all the tools to inform their patients as a powerful supplement that has been receiving recognition for its efficacy in improving the multiple parameters for metabolic health and improving glycemic control. This supplement is known as berberine, and the studies have shown that berberine is as effective as metformin and can help patients who have type 2 diabetes. Berberine is an alkaloid compound that is found in several plants like goldenseal, barberry, and tree turmeric. When berberine is crushed, it has a yellow color hue that is similar to curcumin and has been part of Chinese and Ayurvedic traditional medicine that has been used for thousands of years. Surprisingly berberine has worked in multiple ways and has been able to make some changes within the body’s cells and metabolic system. There has been research showing that berberine can transport in the bloodstream once it has been ingested and can activate the AMPK (AMP-activated protein kinase) enzyme. Once this happens, the enzyme is referred to as a “metabolic master switch” and can help regulate the significant organs and regulating the body’s metabolism.
The increased prevalence of obesity and related comorbidities is a major public health problem. While genetic factors undoubtedly play a role in determining individual susceptibility to weight gain and obesity, the identified genetic variants only explain part of the variation. This has led to growing interest in understanding the potential role of epigenetics as a mediator of gene-environment interactions underlying the development of obesity and its associated comorbidities. Initial evidence in support of a role of epigenetics in obesity and type 2 diabetes mellitus (T2DM) was mainly provided by animal studies, which reported epigenetic changes in key metabolically important tissues following high-fat feeding and epigenetic differences between lean and obese animals and by human studies which showed epigenetic changes in obesity and T2DM candidate genes in obese/diabetic individuals. More recently, advances in epigenetic methodologies and the reduced cost of epigenome-wide association studies (EWAS) have led to a rapid expansion of studies in human populations. These studies have also reported epigenetic differences between obese/T2DM adults and healthy controls and epigenetic changes in association with nutritional, weight loss, and exercise interventions. There is also increasing evidence from both human and animal studies that the relationship between perinatal nutritional exposures and later risk of obesity and T2DM may be mediated by epigenetic changes in the offspring. The aim of this review is to summarize the most recent developments in this rapidly moving field, with a particular focus on human EWAS and studies investigating the impact of nutritional and lifestyle factors (both pre- and postnatal) on the epigenome and their relationship to metabolic health outcomes. The difficulties in distinguishing consequence from causality in these studies and the critical role of animal models for testing causal relationships and providing insight into underlying mechanisms are also addressed. In summary, the area of epigenetics and metabolic health has seen rapid developments in a short space of time. While the outcomes to date are promising, studies are ongoing, and the next decade promises to be a time of productive research into the complex interactions between the genome, epigenome, and environment as they relate to metabolic disease. Keywords: Epigenetics, DNA methylation, Obesity, Type 2 diabetes, Developmental programming IntroductionObesity is a complex, multifactorial disease, and better understanding of the mechanisms underlying the interactions between lifestyle, environment, and genetics is critical for developing effective strategies for prevention and treatment [1]. In a society where energy-dense food is plentiful and the need for physical activity is low, there is a wide variation in individuals’ susceptibility to develop obesity and metabolic health problems. Estimates of the role of heredity in this variation are in the range of 40–70 %, and while large genome-wide association studies (GWAS) have identified a number of genetic loci associated with obesity risk, the ~100 most common genetic variants only account for a few percent of variance in obesity [2, 3]. Genome-wide estimates are higher, accounting for ~20 % of the variation [3]; however, a large portion of the heritability remains unexplained. Recently, attention has turned to investigating the role of epigenetic changes in the etiology of obesity. It has been argued that the epigenome may represent the mechanistic link between genetic variants and environmental factors in determining obesity risk and could help explain the “missing heritability.” The first human epigenetic studies were small and only investigated a limited number of loci. While this generally resulted in poor reproducibility, some of these early findings, for instance the relationship between PGC1A methylation and type 2 diabetes mellitus (T2DM) [4] and others as discussed in van Dijk et al. [5], have been replicated in later studies. Recent advances and increased affordability of high- throughput technologies now allow for large-scale epigenome wide association studies (EWAS) and integration of different layers of genomic information to explore the complex interactions between the genotype, epigenome, transcriptome, and the environment [6–9]. These studies are still in their infancy, but the results thus far have shown promise in helping to explain the variation in obesity susceptibility. There is increasing evidence that obesity has develop mental origins, as exposure to a suboptimal nutrient supply before birth or in early infancy is associated with an increased risk of obesity and metabolic disease in later life [10–13]. Initially, animal studies demonstrated that a range of early life nutritional exposures, especially those experienced early in gestation, could induce epigenetic changes in key metabolic tissues of the offspring that persisted after birth and result in permanent alterations in gene function [13–17]. Evidence is emerging to support the existence of the same mechanism in humans. This has led to a search for epigenetic marks present early in life that predict later risk of metabolic disease, and studies to determine whether epigenetic programming of metabolic disease could be prevented or reversed in later life. This review provides an update of our previous systematic review of studies on epigenetics and obesity in humans [5]. Our previous review showcased the promising outcomes of initial studies, including the first potential epigenetic marks for obesity that could be detected at birth (e.g., RXRA) [18]. However, it also highlighted the limited reproducibility of the findings and the lack of larger scale longitudinal investigations. The current review focuses on recent developments in this rapidly moving field and, in particular, on human EWAS and studies investigating the impact of (pre- and postnatal) nutritional and lifestyle factors on the epigenome and the emerging role of epigenetics in the pathology of obesity. We also address the difficulties in identifying causality in these studies and the importance of animal models in providing insight into mechanisms. ReviewEpigenetic Changes In Animal Models Of ObesityAnimal models provide unique opportunities for highly controlled studies that provide mechanistic insight into the role of specific epigenetic marks, both as indicators of current metabolic status and as predictors of the future risk of obesity and metabolic disease. A particularly important aspect of animal studies is that they allow for the assessment of epigenetic changes within target tissues, including the liver and hypothalamus, which is much more difficult in humans. Moreover, the ability to harvest large quantities of fresh tissue makes it possible to assess multiple chromatin marks as well as DNA methylation. Some of these epigenetic modifications either alone or in combination may be responsive to environmental programming. In animal models, it is also possible to study multiple generations of offspring and thus enable differentiation between trans-generational and intergenerational transmission of obesity risk mediated by epigenetic memory of parental nutritional status, which cannot be easily distinguished in human studies. We use the former term for meiotic transmission of risk in the absence of continued exposure while the latter primarily entails direct transmission of risk through metabolic reprogramming of the fetus or gametes. Animal studies have played a critical role in our current understanding of the role of epigenetics in the developmental origins of obesity and T2DM. Both increased and decreased maternal nutrition during pregnancy have been associated with increased fat deposition in offspring of most mammalian species studied to date (reviewed in [11, 13–15, 19]). Maternal nutrition during pregnancy not only has potential for direct effects on the fetus, it also may directly impact the developing oocytes of female fetuses and primordial germ cells of male fetuses and therefore could impact both the off- spring and grand-offspring. Hence, multigenerational data are usually required to differentiate between maternal intergenerational and trans-generational transmission mechanisms. Table 1 summarizes a variety of animal models that have been used to provide evidence of metabolic and epigenetic changes in offspring associated with the parental plane of nutrition. It also contains information pertaining to studies identifying altered epigenetic marks in adult individuals who undergo direct nutritional challenges. The table is structured by suggested risk transmission type. (i) Epigenetic Changes In Offspring Associated With Maternal Nutrition During GestationMaternal nutritional supplementation, undernutrition, and over nutrition during pregnancy can alter fat deposition and energy homeostasis in offspring [11, 13–15, 19]. Associated with these effects in the offspring are changes in DNA methylation, histone post-translational modifications, and gene expression for several target genes, especially genes regulating fatty acid metabolism and insulin signaling [16, 17, 20–30]. The diversity of animal models used in these studies and the common metabolic pathways impacted suggest an evolutionarily conserved adaptive response mediated by epigenetic modification. However, few of the specific identified genes and epigenetic changes have been cross-validated in related studies, and large-scale genome-wide investigations have typically not been applied. A major hindrance to comparison of these studies is the different develop mental windows subjected to nutritional challenge, which may cause considerably different outcomes. Proof that the epigenetic changes are causal rather than being associated with offspring phenotypic changes is also required. This will necessitate the identification of a parental nutritionally induced epigenetic “memory” response that precedes development of the altered phenotype in offspring. (ii)Effects Of Paternal Nutrition On Offspring Epigenetic MarksEmerging studies have demonstrated that paternal plane of nutrition can impact offspring fat deposition and epigenetic marks [31–34]. One recent investigation using mice has demonstrated that paternal pre-diabetes leads to increased susceptibility to diabetes in F1 offspring with associated changes in pancreatic gene expression and DNA methylation linked to insulin signaling [35]. Importantly, there was an overlap of these epigenetic changes in pancreatic islets and sperm suggesting germ line inheritance. However, most of these studies, although intriguing in their implications, are limited in the genomic scale of investigation and frequently show weak and somewhat transient epigenetic alterations associated with mild metabolic phenotypes in offspring. (iii)Potential Trans-generational Epigenetic Changes Promoting Fat Deposition In OffspringStable transmission of epigenetic information across multiple generations is well described in plant systems and C. elegans, but its significance in mammals is still much debated [36, 37]. An epigenetic basis for grand- parental transmission of phenotypes in response to dietary exposures has been well established, including in livestock species [31]. The most influential studies demonstrating effects of epigenetic transmission impacting offspring phenotype have used the example of the viable yellow agouti (Avy) mouse [38]. In this mouse, an insertion of a retrotransposon upstream of the agouti gene causes its constitutive expression and consequent yellow coat color and adult onset obesity. Maternal transmission through the germ line results in DNA methylation mediated silencing of agouti expression resulting in wild-type coat color and lean phenotype of the offspring [39, 40]. Importantly, subsequent studies in these mice demonstrated that maternal exposure to methyl donors causes a shift in coat color [41]. One study has reported transmission of a phenotype to the F3 generation and alterations in expression of large number of genes in response to protein restriction in F0 [42]; however, alterations in expression were highly variable and a direct link to epigenetic changes was not identified in this system. (iv) Direct Exposure Of Individuals To Excess Nutrition In Postnatal LifeWhile many studies have identified diet-associated epigenetic changes in animal models using candidate site-specific regions, there have been few genome-wide analyses undertaken. A recent study focussed on determining the direct epigenetic impact of high-fat diets/ diet-induced obesity in adult mice using genome-wide gene expression and DNA methylation analyses [43]. This study identified 232 differentially methylated regions (DMRs) in adipocytes from control and high-fat fed mice. Importantly, the corresponding human regions for the murine DMRs were also differentially methylated in adipose tissue from a population of obese and lean humans, thereby highlighting the remarkable evolutionary conservation of these regions. This result emphasizes the likely importance of the identified DMRs in regulating energy homeostasis in mammals. Human Studies Drawing on the evidence from animal studies and with the increasing availability of affordable tools for genome- wide analysis, there has been a rapid expansion of epigenome studies in humans. These studies have mostly focused on the identification of site-specific differences in DNA methylation that are associated with metabolic phenotypes. A key question is the extent to which epigenetic modifications contribute to the development of the metabolic phenotype, rather than simply being a con- sequence of it (Fig. 1). Epigenetic programming could contribute to obesity development, as well as playing a role in consequent risk of cardiovascular and metabolic problems. In human studies, it is difficult to prove causality [44], but inferences can be made from a number of lines of evidence: (i) Genetic association studies. Genetic polymorphisms that are associated with an increased risk of developing particular conditions are a priori linked to the causative genes. The presence of differential methylation in such regions infers functional relevance of these epigenetic changes in controlling expression of the proximal gene(s). There are strong cis-acting genetic effects underpinning much epigenetic variation [7, 45], and in population-based studies, methods that use genetic surrogates to infer a causal or mediating role of epigenome differences have been applied [7, 46–48]. The use of familial genetic information can also lead to the identification of potentially causative candidate regions showing phenotype-related differential methylation [49]. (ii)Timing of epigenetic changes. The presence of an epigenetic mark prior to development of a phenotype is an essential feature associated with causality. Conversely, the presence of a mark in association with obesity, but not before its development, can be used to exclude causality but would not exclude a possible role in subsequent obesity-related pathology. (iii)Plausible inference of mechanism. This refers to epigenetic changes that are associated with altered expression of genes with an established role in regulating the phenotype of interest. One such example is the association of methylation at two CpG sites at the CPT1A gene with circulating triglyceride levels [50]. CPT1A encodes carnitine palmitoyltransferase 1A, an enzyme with a central role in fatty acid metabolism, and this is strongly indicative that differential methylation of this gene may be causally related to the alterations in plasma triglyceride concentrations. Epigenome-Wide Association Studies: Identifying Epigenetic Biomarkers Of Metabolic HealthA number of recent investigations have focused on exploring associations between obesity/metabolic diseases and DNA methylation across the genome (Table 2). The largest published EWAS so far, including a total of 5465 individuals, identified 37 methylation sites in blood that were associated with body mass index (BMI), including sites in CPT1A, ABCG1, and SREBF1 [51]. Another large-scale study showed consistent associations between BMI and methylation in HIF3A in whole blood and adipose tissue [52], a finding which was also partially replicated in other studies [9, 51]. Other recently reported associations between obesity-related measures and DNA methylation include (i) DNA methylation differences between lean and obese individuals in LY86 in blood leukocytes [53]; (ii) associations between PGC1A promoter methylation in whole blood of children and adiposity 5 years later [54]; (iii) associations between waist-hip ratio and ADRB3 methylation in blood [55]; and (iv) associations between BMI, body fat distribution measures, and multiple DNA methylation sites in adipose tissue [9, 56]. EWAS have also shown associations between DNA methylation sites and blood lipids [55, 57–59], serum metabolites [60], insulin resistance [9, 61], and T2DM [48, 62, 63] (Table 2). From these studies, altered methylation of PGC1A, HIF3A, ABCG1, and CPT1A and the previously described RXRA [18] have emerged as biomarkers associated with, or perhaps predictive of, metabolic health that are also plausible candidates for a role in development of metabolic disease. Interaction Between Genotype And The EpigenomeEpigenetic variation is highly influenced by the underlying genetic variation, with genotype estimated to explain ~20–40 % of the variation [6, 8]. Recently, a number of studies have begun to integrate methylome and genotype data to identify methylation quantitative trait loci (meQTL) associated with disease phenotypes. For instance, in adipose tissue, an meQTL overlapping with a BMI genetic risk locus has been identified in an enhancer element upstream of ADCY3 [8]. Other studies have also identified overlaps between known obesity and T2DM risk loci and DMRs associated with obesity and T2DM [43, 48, 62]. Methylation of a number of such DMRs was also modulated by high-fat feeding in mice [43] and weight loss in humans [64]. These results identify an intriguing link between genetic variations linked with disease susceptibility and their association with regions of the genome that undergo epigenetic modifications in response to nutritional challenges, implying a causal relationship. The close connection between genetic and epigenetic variation may signify their essential roles in generating individual variation [65, 66]. However, while these findings suggest that DNA methylation may be a mediator of genetic effects, it is also important to consider that both genetic and epigenetic processes could act independently on the same genes. Twin studies [8, 63, 67] can provide important insights and indicate that inter-individual differences in levels of DNA methylation arise predominantly from non-shared environment and stochastic influences, minimally from shared environmental effects, but also with a significant impact of genetic variation. The Impact Of The Prenatal And Postnatal Environment On The EpigenomePrenatal environment: Two recently published studies made use of human populations that experienced “natural” variations in nutrient supply to study the impact of maternal nutrition before or during pregnancy on DNA methylation in the offspring [68, 69]. The first study used a Gambian mother-child cohort to show that both seasonal variations in maternal methyl donor intake during pregnancy and maternal pre-pregnancy BMI were associated with altered methylation in the infants [69]. The second study utilized adult offspring from the Dutch Hunger Winter cohort to investigate the effect of prenatal exposure to an acute period of severe maternal undernutrition on DNA methylation of genes involved in growth and metabolism in adulthood [68]. The results highlighted the importance of the timing of the exposure in its impact on the epigenome, since significant epigenetic effects were only identified in individuals exposed to famine during early gestation. Importantly, the epigenetic changes occurred in conjunction with increased BMI; however, it was not possible to establish in this study whether these changes were present earlier in life or a consequence of the higher BMI. Other recent studies have provided evidence that prenatal over-nutrition and an obese or diabetic maternal environment are also associated with DNA methylation changes in genes related to embryonic development, growth, and metabolic disease in the offspring [70–73]. While human data are scarce, there are indications that paternal obesity can lead to altered methylation of imprinted genes in the newborn [74], an effect thought to be mediated via epigenetic changes acquired during spermatogenesis. Postnatal environment: The epigenome is established de novo during embryonic development, and therefore, the prenatal environment most likely has the most significant impact on the epigenome. However, it is now clear that changes do occur in the “mature” epigenome under the influence of a range of conditions, including aging, exposure to toxins, and dietary alterations. For example, changes in DNA methylation in numerous genes in skeletal muscle and PGC1A in adipose tissue have been demonstrated in response to a high-fat diet [75, 76]. Interventions to lose body fat mass have also been associated with changes in DNA methylation. Studies have reported that the DNA methylation profiles of adipose tissue [43, 64], peripheral blood mononuclear cells [77], and muscle tissue [78] in formerly obese patients become more similar to the profiles of lean subjects following weight loss. Weight loss surgery also partially reversed non-alcoholic fatty liver disease-associated methylation changes in liver [79] and in another study led to hypomethylation of multiple obesity candidate genes, with more pronounced effects in subcutaneous compared to omental (visceral) fat [64]. Accumulating evidence suggests that exercise interventions can also influence DNA methylation. Most of these studies have been conducted in lean individuals [80–82], but one exercise study in obese T2DM subjects also demonstrated changes in DNA methylation, including in genes involved in fatty acid and glucose transport [83]. Epigenetic changes also occur with aging, and recent data suggest a role of obesity in augmenting them [9, 84, 85]. Obesity accelerated the epigenetic age of liver tissue, but in contrast to the findings described above, this effect was not reversible after weight loss [84]. Collectively, the evidence in support of the capacity to modulate the epigenome in adults suggests that there may be the potential to intervene in postnatal life to modulate or reverse adverse epigenetic programming. Effect Sizes And Differences Between Tissue TypesDNA methylation changes associated with obesity or induced by diet or lifestyle interventions and weight loss are generally modest (<15 %), although this varies depending on the phenotype and tissue studied. For instance, changes greater than 20 % have been reported in adipose tissue after weight loss [64] and associations between HIF3A methylation and BMI in adipose tissue were more pronounced than in blood [52]. The biological relevance of relatively small methylation changes has been questioned. However, in tissues consisting of a mixture of cell types, a small change in DNA methylation may actually reflect a significant change in a specific cell fraction. Integration of epigenome data with transcriptome and other epigenetic data, such as histone modifications, is important, since small DNA methylation changes might reflect larger changes in chromatin structure and could be associated with broader changes in gene expression. The genomic context should also be considered; small changes within a regulatory element such as a promotor, enhancer, or insulator may have functional significance. In this regard, DMRs for obesity, as well as regions affected by prenatal famine exposure and meQTL for metabolic trait loci have been observed to overlap enhancer elements [8, 43, 68]. There is evidence that DNA methylation in famine-associated regions could indeed affect enhancer activity [68], supporting a role of nutrition-induced methylation changes in gene regulation. A major limitation in many human studies is that epigenetic marks are often assessed in peripheral blood, rather than in metabolically relevant tissues (Fig. 2). The heterogeneity of blood is an issue, since different cell populations have distinct epigenetic signatures, but algorithms have been developed to estimate the cellular composition to overcome this problem [86]. Perhaps more importantly, epigenetic marks in blood cells may not necessarily report the status of the tissues of primary interest. Despite this, recent studies have provided clear evidence of a relationship between epigenetic marks in blood cells and BMI. In the case of HIF3A for which the level of methylation (beta-value) in the study population ranged from 0.14–0.52, a 10 % increase in methylation was associated with a BMI increase of 7.8 % [52]. Likewise, a 10 % difference in PGC1A methylation may predict up to 12 % difference in fat mass [54]. ConclusionsThe study of the role of epigenetics in obesity and metabolic disease has expanded rapidly in recent years, and evidence is accumulating of a link between epigenetic modifications and metabolic health outcomes in humans. Potential epigenetic biomarkers associated with obesity and metabolic health have also emerged from recent studies. The validation of epigenetic marks in multiple cohorts, the fact that several marks are found in genes with a plausible function in obesity and T2DM development, as well as the overlap of epigenetic marks with known obesity and T2DM genetic loci strengthens the evidence that these associations are real. Causality has so far been difficult to establish; however, regardless of whether the associations are causal, the identified epigenetic marks may still be relevant as biomarkers for obesity and metabolic disease risk. Effect sizes in easily accessible tissues such as blood are small but do seem reproducible despite variation in ethnicity, tissue type, and analysis methods [51]. Also, even small DNA methylation changes may have biological significance. An integrative “omics” approach will be crucial in further unraveling the complex interactions between the epigenome, transcriptome, genome, and metabolic health. Longitudinal studies, ideally spanning multiple generations, are essential to establishing causal relationships. We can expect more such studies in the future, but this will take time. While animal studies continue to demonstrate an effect of early life nutritional exposure on the epigenome and metabolic health of the offspring, human data are still limited. However, recent studies have provided clear evidence that exposure to suboptimal nutrition during specific periods of prenatal development is associated with methylation changes in the offspring and therefore have the potential to influence adult phenotype. Animal studies will be important to verify human findings in a more controlled setting, help determine whether the identified methylation changes have any impact on metabolic health, and unravel the mechanisms underlying this intergenerational/transgenerational epigenetic regulation. The identification of causal mechanisms underlying metabolic memory responses, the mode of transmission of the phenotypic effects into successive generations, the degree of impact and stability of the transmitted trait, and the identification of an overarching and unifying evolutionary context also remain important questions to be addressed. The latter is often encapsulated by the predictive adaptive response hypothesis, i.e., a response to a future anticipated environment that increases fitness of the population. However, this hypothesis has increasingly been questioned as there is limited evidence for increased fitness later in life [87]. In summary, outcomes are promising, as the epigenetic changes are linked with adult metabolic health and they act as a mediator between altered prenatal nutrition and subsequent increased risk of poor metabolic health outcomes. New epigenetic marks have been identified that are associated with measures of metabolic health. Integration of different layers of genomic information has added further support to causal relationships, and there have been further studies showing effects of pre- and postnatal environment on the epigenome and health. While many important questions remain, recent methodological advances have enabled the types of large-scale population-based studies that will be required to address the knowledge gaps. The next decade promises to be a period of major activity in this important research area. Susan J. van Dijk1, Ross L. Tellam2, Janna L. Morrison3, Beverly S. Muhlhausler4,5† and Peter L. Molloy1*† Competing interests The authors declare that they have no competing interests. Authors’ contributions
All authors contributed to the drafting and critical revision of the manuscript, and all authors read and approved the final manuscript. Authors’ information
Beverly S. Muhlhausler and Peter L. Molloy are joint last authors. Acknowledgements This work has been supported by a grant from the Science and Industry Endowment Fund (Grant RP03-064). JLM and BSM are supported by the National Health and Medical Research Council Career Development Fellowships (JLM, APP1066916; BSM, APP1004211). We thank Lance Macaulay and Sue Mitchell for critical reading and comments on the manuscript. Author details 1CSIRO Food and Nutrition Flagship, PO Box 52, North Ryde, NSW 1670, Australia. 2CSIRO Agriculture Flagship, 306 Carmody Road, St Lucia, QLD 4067, Australia. 3Early Origins of Adult Health Research Group, School of Pharmacy and Medical Sciences, Sansom Institute for Health Research, University of South Australia, GPO Box 2471, Adelaide, SA 5001, Australia 4FOODplus Research Centre, Waite Campus, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia. 5Women’s and Children’s Health Research Institute, 72 King William Road, North Adelaide, SA 5006, Australia. References: 1. WHO. WHO | Overweight and obesity. http://www.who.int/gho/ncd/<br />
risk_factors/overweight/en/index.html. Accessed 29 January 2015.<br />
2. Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery.<br />
Am J Hum Genet. 2012;90:7–24.<br />
3. Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic<br />
studies of body mass index yield new insights for obesity biology. Nature.<br />
2015;518:197–206.<br />
4. Ling C, Del Guerra S, Lupi R, Rönn T, Granhall C, Luthman H, et al.<br />
Epigenetic regulation of PPARGC1A in human type 2 diabetic islets and<br />
effect on insulin secretion. Diabetologia. 2008;51:615–22.<br />
5. Van Dijk SJ, Molloy PL, Varinli H, Morrison JL, Muhlhausler BS. Epigenetics<br />
and human obesity. Int J Obes (Lond). 2015;39:85–97.<br />
6. Teh AL, Pan H, Chen L, Ong M-L, Dogra S, Wong J, et al. The effect of<br />
genotype and in utero environment on interindividual variation in neonate<br />
DNA methylomes. Genome Res. 2014;24:1064–74.<br />
7. Olsson AH, Volkov P, Bacos K, Dayeh T, Hall E, Nilsson EA, et al. Genomewide<br />
associations between genetic and epigenetic variation influence<br />
mRNA expression and insulin secretion in human pancreatic islets. PLoS<br />
Genet. 2014;10:e1004735.<br />
8. Grundberg E, Meduri E, Sandling JK, Hedman AK, Keildson S, Buil A, et al.<br />
Global analysis of DNA methylation variation in adipose tissue from twins<br />
reveals links to disease-associated variants in distal regulatory elements.<br />
Am J Hum Genet. 2013;93:876–90.<br />
9. Ronn T, Volkov P, Gillberg L, Kokosar M, Perfilyev A, Jacobsen AL, et al.<br />
Impact of age, BMI and HbA1c levels on the genome-wide DNA<br />
methylation and mRNA expression patterns in human adipose tissue<br />
and identification of epigenetic biomarkers in blood. Hum Mol Genet.<br />
2015;24:3792–813.<br />
10. Waterland RA, Michels KB. Epigenetic epidemiology of the developmental<br />
origins hypothesis. Annu Rev Nutr. 2007;27:363–88.<br />
11. McMillen IC, Rattanatray L, Duffield JA, Morrison JL, MacLaughlin SM, Gentili<br />
S, et al. The early origins of later obesity: pathways and mechanisms. Adv<br />
Exp Med Biol. 2009;646:71–81.<br />
12. Ravelli A, van der Meulen J, Michels R, Osmond C, Barker D, Hales C, et al.<br />
Glucose tolerance in adults after prenatal exposure to famine. Lancet.<br />
1998;351:173–7.<br />
13. McMillen IC, MacLaughlin SM, Muhlhausler BS, Gentili S, Duffield JL,<br />
Morrison JL. Developmental origins of adult health and disease: the role of<br />
periconceptional and foetal nutrition. Basic Clin Pharmacol Toxicol.<br />
2008;102:82–9.<br />
14. Zhang S, Rattanatray L, McMillen IC, Suter CM, Morrison JL. Periconceptional<br />
nutrition and the early programming of a life of obesity or adversity. Prog<br />
Biophys Mol Biol. 2011;106:307–14.<br />
15. Bouret S, Levin BE, Ozanne SE. Gene-environment interactions controlling<br />
energy and glucose homeostasis and the developmental origins of obesity.<br />
Physiol Rev. 2015;95:47–82.<br />
16. Borengasser SJ, Zhong Y, Kang P, Lindsey F, Ronis MJ, Badger TM, et al.<br />
Maternal obesity enhances white adipose tissue differentiation and alters<br />
genome-scale DNA methylation in male rat offspring. Endocrinology.<br />
2013;154:4113–25.<br />
17. Gluckman PD, Lillycrop KA, Vickers MH, Pleasants AB, Phillips ES, Beedle AS,<br />
et al. Metabolic plasticity during mammalian development is directionally<br />
dependent on early nutritional status. Proc Natl Acad Sci U S A.<br />
2007;104:12796–800.<br />
18. Godfrey KM, Sheppard A, Gluckman PD, Lillycrop KA, Burdge GC, McLean C,<br />
et al. Epigenetic gene promoter methylation at birth is associated with<br />
child’s later adiposity. Diabetes. 2011;60:1528–34.<br />
19. McMillen IC, Adam CL, Muhlhausler BS. Early origins of obesity:<br />
programming the appetite regulatory system. J Physiol. 2005;565(Pt 1):9–17.<br />
20. Begum G, Stevens A, Smith EB, Connor K, Challis JR, Bloomfield F, et al.<br />
Epigenetic changes in fetal hypothalamic energy regulating pathways are<br />
associated with maternal undernutrition and twinning. FASEB J.<br />
2012;26:1694–703.<br />
21. Ge ZJ, Liang QX, Hou Y, Han ZM, Schatten H, Sun QY, et al. Maternal obesity<br />
and diabetes may cause DNA methylation alteration in the spermatozoa of<br />
offspring in mice. Reprod Biol Endocrinol. 2014;12:29.<br />
22. Jousse C, Parry L, Lambert-Langlais S, Maurin AC, Averous J, Bruhat A, et al.<br />
Perinatal undernutrition affects the methylation and expression of the leptin<br />
gene in adults: implication for the understanding of metabolic syndrome.<br />
FASEB J. 2011;25:3271–8.<br />
23. Lan X, Cretney EC, Kropp J, Khateeb K, Berg MA, Penagaricano F, et al.<br />
Maternal diet during pregnancy induces gene expression and DNA<br />
methylation changes in fetal tissues in sheep. Front Genet. 2013;4:49.<br />
24. Li CC, Young PE, Maloney CA, Eaton SA, Cowley MJ, Buckland ME, et al.<br />
Maternal obesity and diabetes induces latent metabolic defects and<br />
widespread epigenetic changes in isogenic mice. Epigenetics. 2013;8:602–11.<br />
25. Lillycrop KA, Phillips ES, Jackson AA, Hanson MA, Burdge GC. Dietary protein<br />
restriction of pregnant rats induces and folic acid supplementation prevents<br />
epigenetic modification of hepatic gene expression in the offspring. J Nutr.<br />
2005;135:1382–6.<br />
26. Radford EJ, Ito M, Shi H, Corish JA, Yamazawa K, Isganaitis E, et al. In utero<br />
effects. In utero undernourishment perturbs the adult sperm methylome<br />
and intergenerational metabolism. Science. 2014;345(80):1255903.<br />
27. Suter M, Bocock P, Showalter L, Hu M, Shope C, McKnight R, et al.<br />
Epigenomics: maternal high-fat diet exposure in utero disrupts<br />
peripheral circadian gene expression in nonhuman primates. FASEB J.<br />
2011;25:714–26.<br />
28. Suter MA, Ma J, Vuguin PM, Hartil K, Fiallo A, Harris RA, et al. In utero<br />
exposure to a maternal high-fat diet alters the epigenetic histone code in a<br />
murine model. Am J Obs Gynecol. 2014;210:463 e1–463 e11.<br />
29. Tosh DN, Fu Q, Callaway CW, McKnight RA, McMillen IC, Ross MG, et al.<br />
Epigenetics of programmed obesity: alteration in IUGR rat hepatic IGF1<br />
mRNA expression and histone structure in rapid vs. delayed postnatal<br />
catch-up growth. Am J Physiol Gastrointest Liver Physiol.<br />
2010;299:G1023–9.<br />
30. Sandovici I, Smith NH, Nitert MD, Ackers-Johnson M, Uribe-Lewis S, Ito Y,<br />
et al. Maternal diet and aging alter the epigenetic control of a promoterenhancer<br />
interaction at the Hnf4a gene in rat pancreatic islets. Proc Natl<br />
Acad Sci U S A. 2011;108:5449–54.<br />
31. Braunschweig M, Jagannathan V, Gutzwiller A, Bee G. Investigations on<br />
transgenerational epigenetic response down the male line in F2 pigs. PLoS<br />
One. 2012;7, e30583.<br />
32. Carone BR, Fauquier L, Habib N, Shea JM, Hart CE, Li R, et al. Paternally<br />
induced transgenerational environmental reprogramming of metabolic<br />
gene expression in mammals. Cell. 2010;143:1084–96.<br />
33. Ost A, Lempradl A, Casas E, Weigert M, Tiko T, Deniz M, et al. Paternal diet<br />
defines offspring chromatin state and intergenerational obesity. Cell.<br />
2014;159:1352–64.<br />
34. Martínez D, Pentinat T, Ribó S, Daviaud C, Bloks VW, Cebrià J, et al. In utero<br />
undernutrition in male mice programs liver lipid metabolism in the secondgeneration<br />
offspring involving altered Lxra DNA methylation. Cell Metab.<br />
2014;19:941–51.<br />
35. Wei Y, Yang C-R, Wei Y-P, Zhao Z-A, Hou Y, Schatten H, et al. Paternally<br />
induced transgenerational inheritance of susceptibility to diabetes in<br />
mammals. Proc Natl Acad Sci U S A. 2014;111:1873–8.<br />
36. Grossniklaus U, Kelly WG, Kelly B, Ferguson-Smith AC, Pembrey M, Lindquist<br />
S. Transgenerational epigenetic inheritance: how important is it? Nat Rev<br />
Genet. 2013;14:228–35.<br />
37. Pembrey M, Saffery R, Bygren LO. Human transgenerational responses to<br />
early-life experience: potential impact on development, health and<br />
biomedical research. J Med Genet. 2014;51:563–72.<br />
38. Wolff GL, Kodell RL, Moore SR, Cooney CA. Maternal epigenetics and methyl<br />
supplements affect agouti gene expression in Avy/a mice. FASEB J.<br />
1998;12:949–57.<br />
39. Jirtle RL, Skinner MK. Environmental epigenomics and disease susceptibility.<br />
Nat Rev Genet. 2007;8:253–62.<br />
40. Morgan HD, Sutherland HG, Martin DI, Whitelaw E. Epigenetic inheritance at<br />
the agouti locus in the mouse. Nat Genet. 1999;23:314–8.<br />
41. Cropley JE, Suter CM, Beckman KB, Martin DI. Germ-line epigenetic<br />
modification of the murine A vy allele by nutritional supplementation. Proc<br />
Natl Acad Sci U S A. 2006;103:17308–12.<br />
42. Hoile SP, Lillycrop KA, Thomas NA, Hanson MA, Burdge GC. Dietary protein<br />
restriction during F0 pregnancy in rats induces transgenerational changes in<br />
the hepatic transcriptome in female offspring. PLoS One. 2011;6, e21668.<br />
43. Multhaup ML, Seldin MM, Jaffe AE, Lei X, Kirchner H, Mondal P, et al. Mousehuman<br />
experimental epigenetic analysis unmasks dietary targets and<br />
genetic liability for diabetic phenotypes. Cell Metab. 2015;21:138–49.<br />
44. Michels KB, Binder AM, Dedeurwaerder S, Epstein CB, Greally JM, Gut I, et al.<br />
Recommendations for the design and analysis of epigenome-wide<br />
association studies. Nat Methods. 2013;10:949–55.<br />
45. Dayeh TA, Olsson AH, Volkov P, Almgren P, Rönn T, Ling C. Identification of<br />
CpG-SNPs associated with type 2 diabetes and differential DNA methylation<br />
in human pancreatic islets. Diabetologia. 2013;56:1036–46.<br />
46. Relton CL, Davey Smith G. Two-step epigenetic Mendelian randomization: a<br />
strategy for establishing the causal role of epigenetic processes in pathways<br />
to disease. Int J Epidemiol. 2012;41:161–76.<br />
47. Liu Y, Aryee MJ, Padyukov L, Fallin MD, Hesselberg E, Runarsson A, et al.<br />
Epigenome-wide association data implicate DNA methylation as an<br />
intermediary of genetic risk in rheumatoid arthritis. Nat Biotechnol.<br />
2013;31:142–7.<br />
48. Yuan W, Xia Y, Bell CG, Yet I, Ferreira T, Ward KJ, et al. An integrated<br />
epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic<br />
twins. Nat Commun. 2014;5:5719.<br />
49. Nitert MD, Dayeh T, Volkov P, Elgzyri T, Hall E, Nilsson E, et al. Impact of an<br />
exercise intervention on DNA methylation in skeletal muscle from firstdegree<br />
relatives of patients with type 2 diabetes. Diabetes. 2012;61:3322–32.<br />
50. Gagnon F, Aïssi D, Carrié A, Morange P-E, Trégouët D-A. Robust validation of<br />
methylation levels association at CPT1A locus with lipid plasma levels.<br />
J Lipid Res. 2014;55:1189–91.<br />
51. Demerath EW, Guan W, Grove ML, Aslibekyan S, Mendelson M, Zhou Y-H,<br />
et al. Epigenome-wide association atudy (EWAS) of BMI, BMI change, and<br />
waist circumference in African American adults identifies multiple replicated<br />
loci. Hum Mol Genet. 2015:ddv161–.<br />
52. Dick KJ, Nelson CP, Tsaprouni L, Sandling JK, Aïssi D, Wahl S, et al. DNA<br />
methylation and body-mass index: a genome-wide analysis. Lancet.<br />
2014;6736:1–9.<br />
53. Su S, Zhu H, Xu X, Wang X, Dong Y, Kapuku G, et al. DNA methylation of<br />
the LY86 gene is associated with obesity, insulin resistance, and<br />
inflammation. Twin Res Hum Genet. 2014;17:183–91.<br />
54. Clarke-Harris R, Wilkin TJ, Hosking J, Pinkney J, Jeffery AN, Metcalf BS, et al.<br />
PGC1α promoter methylation in blood at 5–7 years predicts adiposity from<br />
9 to 14 years (EarlyBird 50). Diabetes. 2014;63:2528–37.<br />
55. Guay S-P, Brisson D, Lamarche B, Biron S, Lescelleur O, Biertho L, et al.<br />
ADRB3 gene promoter DNA methylation in blood and visceral adipose<br />
tissue is associated with metabolic disturbances in men. Epigenomics.<br />
2014;6:33–43.<br />
56. Agha G, Houseman EA, Kelsey KT, Eaton CB, Buka SL, Loucks EB. Adiposity is<br />
associated with DNA methylation profile in adipose tissue. Int J Epidemiol.<br />
2014:1–11.<br />
57. Irvin MR, Zhi D, Joehanes R, Mendelson M, Aslibekyan S, Claas SA, et al.<br />
Epigenome-wide association study of fasting blood lipids in the genetics of<br />
lipid-lowering drugs and diet network study. Circulation. 2014;130:565–72.<br />
58. Frazier-Wood AC, Aslibekyan S, Absher DM, Hopkins PN, Sha J, Tsai MY, et al.<br />
Methylation at CPT1A locus is associated with lipoprotein subfraction<br />
profiles. J Lipid Res. 2014;55:1324–30.<br />
59. Pfeifferm L, Wahl S, Pilling LC, Reischl E, Sandling JK, Kunze S, et al. DNA<br />
methylation of lipid-related genes affects blood lipid levels. Circ Cardiovasc<br />
Genet. 2015.<br />
60. Petersen A-K, Zeilinger S, Kastenmüller G, Römisch-Margl W, Brugger M, Peters<br />
A, et al. Epigenetics meets metabolomics: an epigenome-wide association<br />
study with blood serum metabolic traits. Hum Mol Genet. 2014;23:534–45.<br />
61. Hidalgo B, Irvin MR, Sha J, Zhi D, Aslibekyan S, Absher D, et al. Epigenomewide<br />
association study of fasting measures of glucose, insulin, and HOMA-IR<br />
in the genetics of lipid lowering drugs and diet network study. Diabetes.<br />
2014;63:801–7.<br />
62. Dayeh T, Volkov P, Salö S, Hall E, Nilsson E, Olsson AH, et al. Genome-wide<br />
DNA methylation analysis of human pancreatic islets from type 2 diabetic<br />
and non-diabetic donors identifies candidate genes that influence insulin<br />
secretion. PLoS Genet. 2014;10, e1004160.<br />
63. Nilsson E, Jansson PA, Perfilyev A, Volkov P, Pedersen M, Svensson MK, et al.<br />
Altered DNA methylation and differential expression of genes influencing<br />
metabolism and inflammation in adipose tissue from subjects with type 2<br />
diabetes. Diabetes. 2014;63:2962–76.<br />
64. Benton MC, Johnstone A, Eccles D, Harmon B, Hayes MT, Lea RA, et al. An analysis of DNA methylation in human adipose tissue reveals differential modification of obesity genes before and after gastric bypass and weight<br />
loss. Gene. 2015;16:1–21.<br />
65. Bateson P, Gluckman P. Plasticity and robustness in development and<br />
evolution. Int J Epidemiol. 2012;41:219–23.<br />
66. Feinberg AP, Irizarry RA, Feinberg AP, Irizarry RA. Evolution in health and<br />
medicine Sackler colloquium: stochastic epigenetic variation as a driving<br />
force of development, evolutionary adaptation, and disease. Proc Natl Acad<br />
Sci U S A. 2010;107(Suppl):1757–64.<br />
67. Martino D, Loke YJ, Gordon L, Ollikainen M, Cruickshank MN, Saffery R, et al.<br />
Longitudinal, genome-scale analysis of DNA methylation in twins from birth<br />
to 18 months of age reveals rapid epigenetic change in early life and pairspecific<br />
effects of discordance. Genome Biol. 2013;14:R42.<br />
68. Tobi EW, Goeman JJ, Monajemi R, Gu H, Putter H, Zhang Y, et al. DNA<br />
methylation signatures link prenatal famine exposure to growth and<br />
metabolism. Nat Commun. 2014;5:5592.<br />
69. Dominguez-Salas P, Moore SE, Baker MS, Bergen AW, Cox SE, Dyer RA, et al.<br />
Maternal nutrition at conception modulates DNA methylation of human<br />
metastable epialleles. Nat Commun. 2014;5:3746.<br />
70. Quilter CR, Cooper WN, Cliffe KM, Skinner BM, Prentice PM, Nelson L, et al.<br />
Impact on offspring methylation patterns of maternal gestational diabetes<br />
mellitus and intrauterine growth restraint suggest common genes and<br />
pathways linked to subsequent type 2 diabetes risk. FASEB J. 2014:1–12.<br />
71. Morales E, Groom A, Lawlor DA, Relton CL. DNA methylation signatures in<br />
cord blood associated with maternal gestational weight gain: results from<br />
the ALSPAC cohort. BMC Res Notes. 2014;7:278.<br />
72. Ruchat SM, Houde AA, Voisin G, St-Pierre J, Perron P, Baillargeon JP, et al.<br />
Gestational diabetes mellitus epigenetically affects genes predominantly<br />
involved in metabolic diseases. Epigenetics. 2013;8:935–43.<br />
73. Liu X, Chen Q, Tsai H-J, Wang G, Hong X, Zhou Y, et al. Maternal<br />
preconception body mass index and offspring cord blood DNA<br />
methylation: exploration of early life origins of disease. Environ Mol<br />
Mutagen. 2014;55:223–30.<br />
74. Soubry A, Murphy SK, Wang F, Huang Z, Vidal AC, Fuemmeler BF, et al.<br />
Newborns of obese parents have altered DNA methylation patterns at<br />
imprinted genes. Int J Obes (Lond). 2015;39:650–7.<br />
75. Jacobsen SC, Brøns C, Bork-Jensen J, Ribel-Madsen R, Yang B, Lara E, et al.<br />
Effects of short-term high-fat overfeeding on genome-wide DNA<br />
methylation in the skeletal muscle of healthy young men. Diabetologia.<br />
2012;55:3341–9.<br />
76. Gillberg L, Jacobsen SC, Rönn T, Brøns C, Vaag A. PPARGC1A DNA<br />
methylation in subcutaneous adipose tissue in low birth weight subjects–<br />
impact of 5 days of high-fat overfeeding. Metabolism. 2014;63:263–71.<br />
77. Huang Y-T, Maccani JZJ, Hawley NL, Wing RR, Kelsey KT, McCaffery JM.<br />
Epigenetic patterns in successful weight loss maintainers: a pilot study. Int J<br />
Obes (Lond). 2015;39:865–8.<br />
78. Barres R, Kirchner H, Rasmussen M, Yan J, Kantor FR, Krook A, Näslund E,<br />
Zierath JR. Weight loss after gastric bypass surgery in human obesity<br />
remodels promoter methylation. Cell Rep. 2013:1–8.<br />
79. Ahrens M, Ammerpohl O, von Schönfels W, Kolarova J, Bens S, Itzel T, et al.<br />
DNA methylation analysis in nonalcoholic fatty liver disease suggests<br />
distinct disease-specific and remodeling signatures after bariatric surgery.<br />
Cell Metab. 2013;18:296–302.<br />
80. Voisin S, Eynon N, Yan X, Bishop DJ. Exercise training and DNA methylation<br />
in humans. Acta Physiol (Oxf). 2014;213:39–59.<br />
81. Lindholm ME, Marabita F, Gomez-Cabrero D, Rundqvist H, Ekström TJ,<br />
Tegnér J, et al. An integrative analysis reveals coordinated reprogramming<br />
of the epigenome and the transcriptome in human skeletal muscle after<br />
training. Epigenetics. 2014;9:1557–69.<br />
82. Denham J, O’Brien BJ, Marques FZ, Charchar FJ. Changes in the leukocyte<br />
methylome and its effect on cardiovascular related genes after exercise.<br />
J Appl Physiol. 2014:jap.00878.2014.<br />
83. Rowlands DS, Page RA, Sukala WR, Giri M, Ghimbovschi SD, Hayat I, et al.<br />
Multi-omic integrated networks connect DNA methylation and miRNA with<br />
skeletal muscle plasticity to chronic exercise in type 2 diabetic obesity.<br />
Physiol Genomics. 2014;46:747–65.<br />
84. Horvath S, Erhart W, Brosch M, Ammerpohl O, von Schonfels W, Ahrens M,<br />
et al. Obesity accelerates epigenetic aging of human liver. Proc Natl Acad<br />
Sci. 2014;111:15538–43.<br />
85. Almén MS, Nilsson EK, Jacobsson JA, Kalnina I, Klovins J, Fredriksson R, et al.<br />
Genome-wide analysis reveals DNA methylation markers that vary with<br />
both age and obesity. Gene. 2014.;548:61–7<br />
86. Houseman EA, Molitor J, Marsit CJ. Reference-free cell mixture adjustments<br />
in analysis of DNA methylation data. Bioinformatics. 2014;30:1431–9.<br />
87. Wells JC. A critical appraisal of the predictive adaptive response hypothesis.<br />
Int J Epidemiol. 2012;41:229–35.<br />
88. Williams-Wyss O, Zhang S, MacLaughlin SM, Kleemann D, Walker SK, Suter<br />
CM, et al. Embryo number and periconceptional undernutrition in the<br />
sheep have differential effects on adrenal epigenotype, growth, and<br />
development. Am J Physiol Endocrinol Metab. 2014;307:E141–50.<br />
89. Zhang S, Rattanatray L, Morrison JL, Nicholas LM, Lie S, McMillen IC.<br />
Maternal obesity and the early origins of childhood obesity: weighing up<br />
the benefits and costs of maternal weight loss in the periconceptional<br />
period for the offspring. Exp Diabetes Res. 2011;2011:585749.<br />
90. Zhang S, Williams-Wyss O, MacLaughlin SM, Walker SK, Kleemann DO, Suter<br />
CM, et al. Maternal undernutrition during the first week after conception<br />
results in decreased expression of glucocorticoid receptor mRNA in the<br />
absence of GR exon 17 hypermethylation in the fetal pituitary in late<br />
gestation. J Dev Orig Heal Dis. 2013;4:391–401.<br />
91. Lie S, Morrison JL, Williams-Wyss O, Suter CM, Humphreys DT, Ozanne SE,<br />
et al. Periconceptional undernutrition programs changes in insulin-signaling<br />
molecules and microRNAs in skeletal muscle in singleton and twin fetal<br />
sheep. Biol Reprod. 2014;90:5.<br />
92. Van Straten EM, van Meer H, Huijkman NC, van Dijk TH, Baller JF, Verkade<br />
HJ, et al. Fetal liver X receptor activation acutely induces lipogenesis but<br />
does not affect plasma lipid response to a high-fat diet in adult mice. Am J<br />
Physiol Endocrinol Metab. 2009;297:E1171–8.<br />
93. Fernandez-Twinn DS, Alfaradhi MZ, Martin-Gronert MS, Duque-Guimaraes<br />
DE, Piekarz A, Ferland-McCollough D, et al. Downregulation of IRS-1 in<br />
adipose tissue of offspring of obese mice is programmed cellautonomously<br />
through post-transcriptional mechanisms. Mol Metab.<br />
2014;3:325–33.<br />
94. Waterland RA, Travisano M, Tahiliani KG. Diet-induced hypermethylation at<br />
agouti viable yellow is not inherited transgenerationally through the female.<br />
FASEB J. 2007;21:3380–5.<br />
95. Ge ZJ, Luo SM, Lin F, Liang QX, Huang L, Wei YC, et al. DNA methylation in<br />
oocytes and liver of female mice and their offspring: effects of high-fat-dietinduced<br />
obesity. Env Heal Perspect. 2014;122:159–64.<br />
96. Ollikainen M, Ismail K, Gervin K, Kyllönen A, Hakkarainen A, Lundbom J, et al.<br />
Genome-wide blood DNA methylation alterations at regulatory elements<br />
and heterochromatic regions in monozygotic twins discordant for obesity<br />
and liver fat. Clin Epigenetics. 2015;7:1–13.
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Individuals ready to phase out sugar will improve overall health, regardless of age and health status. Injury Medical Chiropractic and Functional Medicine Clinic can help. For answers to any questions, you may have, please call Dr. Alexander Jimenez at 915-850-0900 or 915-412-6677