1 Obesity is the problem (?) Obesity is the problem (?) Obesity is - - PDF document

1 Fructose and metabolic syndrome: Fructose and metabolic syndrome: Is there a link? Is there a link?

Baptist Health South Florida, Feb. 6, 2014

Robert H. Lustig, M.D., M.S.L. Robert H. Lustig, M.D., M.S.L. Division of Endocrinology, Department of Pediatrics Division of Endocrinology, Department of Pediatrics Institute for Health Policy Studies Institute for Health Policy Studies University of California, San Francisco University of California, San Francisco Adjunct Faculty Adjunct Faculty UC Hastings College of the Law UC Hastings College of the Law

• No disclosures

Past Past

2001

Currently there are 30% more obese than undernourished people worldwide

(World Health Organization)

371 million diabetics in 2012 (5% of the world‘s population)

(International Diabetes Federation)

Present Present Experts predict:

165 million Americans will be obese by 2030

(4 part obesity series in Lancet, 8/26/11)

42% of Americans will be obese by 2030

(Finkelstein et al. Am J Prev Med epub 5/7/12)

100 million Americans will have diabetes by 2050

(CDC Division of Diabetes Translation, 2011)

Medicare Medicare will will be be broke broke by by 2026 2026

Future Future

Obesity is the problem Obesity is the problem (?)

2 Obesity is the problem (?) Obesity is the problem (?) Obesity is the problem (?) Obesity is the problem (?)

Basu et al. PLoS One 8:e58783, 2013

Obesity is the problem (?) Obesity is the problem (?)

• Obesity is increasing worldwide by 1% per year
• Diabetes is increasing worldwide by 4% per year

“Exclusive Exclusive” view of obesity and view of obesity and metabolic dysfunction metabolic dysfunction

Obese (30%) Normal weight (70%) 240 million adults in U.S. 72 million 168 million Obese (30%) Obese and sick (80% of 30%) Normal weight (70%) 240 million adults in U.S. 72 million 168 million Total: 57 million sick

“Exclusive Exclusive” view of obesity and view of obesity and metabolic dysfunction metabolic dysfunction

Obese (30%) Normal weight (70%) 240 million adults in U.S. 72 million 168 million

“Inclusive Inclusive” view of obesity and view of obesity and metabolic dysfunction metabolic dysfunction

3

Obese (30%) Normal weight (70%) 240 million adults in U.S. Normal weight, Metabolic dysfunction (40% of 70%) Obese and sick (80% of 30%) 57 million 67 million Total: 124 million sick 72 million 168 million

“Inclusive Inclusive” view of obesity and view of obesity and metabolic dysfunction metabolic dysfunction

Relation between Relation between visceral and subcutaneous obesity: visceral and subcutaneous obesity: (thin on the outside, fat on the inside) (thin on the outside, fat on the inside)

Thomas et al. Obesity doi: 10.1038/oby.2011.142, 2011

Obesity is not the problem Obesity is not the problem Obesity is not the problem Obesity is not the problem

Metabolic Syndrome: where all the money goes Metabolic Syndrome: where all the money goes (75% of all healthcare dollars) (75% of all healthcare dollars)

Obesity is not the problem Obesity is not the problem

Metabolic Syndrome: where all the money goes Metabolic Syndrome: where all the money goes (75% of all healthcare dollars) (75% of all healthcare dollars) Diabetes Diabetes Hypertension Hypertension Lipid abnormalities Lipid abnormalities Cardiovascular disease Cardiovascular disease Non Non-alcoholic fatty liver disease alcoholic fatty liver disease Polycystic ovarian disease Polycystic ovarian disease Cancer Cancer Dementia Dementia Metabolic syndrome is difficult to define in adults Metabolic syndrome is difficult to define in adults

• WHO 1998
• AACE 2003
• EGIR 1998
• IDF 2005
• NCEP/ATPIII 2001
• AHA 2005

4

Metabolic syndrome is difficult to define in adults Metabolic syndrome is difficult to define in adults And even more difficult to define in children And even more difficult to define in children

• WHO 1998
• AACE 2003
• EGIR 1998
• IDF 2005
• NCEP/ATPIII 2001
• AHA 2005

Circulation 119:628, 2009

Because each of these definitions sought to define the Because each of these definitions sought to define the metabolic syndrome phenomenologically, with cutoffs metabolic syndrome phenomenologically, with cutoffs Because each of these definitions sought to define the Because each of these definitions sought to define the metabolic syndrome phenomenologically, with cutoffs metabolic syndrome phenomenologically, with cutoffs It is easier to define the metabolic syndrome mechanistically It is easier to define the metabolic syndrome mechanistically Where Where’s the insulin resistance? s the insulin resistance?

Cytokines

The standard model of insulin resistance The standard model of insulin resistance Familial Partial Lipodystrophy: Dunningan or Type 2 Familial Partial Lipodystrophy: Dunningan or Type 2

• X-linked or autosomal dominant
• Absence of limb fat

Easily visible veins Defined musculature

• Normal or excess facial fat
• Cushingoid facies (moon facies)
• Dorsocervical fat pad
• Acanthosis nigricans
• Metabolic Syndrome

Peters et al. Nature Genet 18:292, 1998

• Fat mass
• Leptin
• Adiponectin
• Inflam. Cytokines
• Metabolic Syndrome

Comparison between lipodystrophy and obesity Comparison between lipodystrophy and obesity

Asterholm et al. Drug Disc Today Dis Models 4:17, 2007

LD

• besity

± ++

5

• Fat mass
• Leptin
• Adiponectin
• Inflam. Cytokines
• Metabolic Syndrome

Comparison between lipodystrophy and obesity Comparison between lipodystrophy and obesity

Asterholm et al. Drug Disc Today Dis Models 4:17, 2007

LD

• besity

± ++

So the metabolic syndrome can arise from too much, or too little fat So the metabolic syndrome can arise from too much, or too little fat i.e. it i.e. it’s not the fat that counts s not the fat that counts

Obesity Lipodystrophy Insulin Resistance

Chehab, Endocrinol 149:925, 2008

Obesity and lipodystrophy share insulin resistance Obesity and lipodystrophy share insulin resistance

Relation between obesity, T2DM, and Metabolic Syndrome Relation between obesity, T2DM, and Metabolic Syndrome

Steinberger et al. Circulation 119:628, 2009

REFRAMING THE DEBATE REFRAMING THE DEBATE REFRAMING THE DEBATE REFRAMING THE DEBATE Obesity doesn Obesity doesn’t CAUSE metabolic syndrome t CAUSE metabolic syndrome Obesity is a MARKER for metabolic syndrome Obesity is a MARKER for metabolic syndrome REFRAMING THE DEBATE REFRAMING THE DEBATE Obesity doesn Obesity doesn’t CAUSE metabolic syndrome t CAUSE metabolic syndrome Obesity is a MARKER for metabolic syndrome Obesity is a MARKER for metabolic syndrome

OBESITY IS A OBESITY IS A “RED HERRING RED HERRING” RYONE IS AT RISK OF METABOLIC SYNDR RYONE IS AT RISK OF METABOLIC SYNDR

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Obesity isn Obesity isn’t enough! t enough! Insulin resistance isn Insulin resistance isn’t enough! t enough! What kind of obesity? What kind of obesity? What kind of insulin resistance? What kind of insulin resistance? In which tissue? In which tissue? Are all insulin pathways affected? Are all insulin pathways affected?

Intrahepatic fat explains metabolic perturbation Intrahepatic fat explains metabolic perturbation better than visceral fat better than visceral fat

Fabbrini et al. Proc Natl Acad Sci 106:15430, 2009

Hepatic Insulin Sensitivity Index Insulin Stimulated Glucose Disposal Rate Insulin Stimulated Palmitate Suppression Rate VLDL Secretion Rate Contribution Of Free Fatty Acids To VLDL

Insulin Receptor Knockouts (IRKO) Insulin Receptor Knockouts (IRKO) Kahn Lab, Kahn Lab, Joslin Joslin 1998 1998-present present

Obesity, Metabolic Syndrome Liver (LIRKO) Brain (NIRKO) Protected from Obesity Muscle (MIRKO) White Adipose Tissue (FIRKO) Brown Adipose Tissue (BATIRKO) β-cell (βIRKO) Vascular Smooth Muscle (VSMCIRKO) Glomerular Podocyte (PODIRKO)

Biddinger and Kahn, Ann Rev Physiol 68:123, 2006 Brown and Goldstein, Cell Metab 7:95, 2008

Insulin has two effects on the liver Insulin has two effects on the liver

Result: Obesity Hyperglycemia, hyperinsulinemia, DM Low TG, VLDL Normal BP NOT Metabolic Syndrome Result: Obesity Hyperglycemia, hyperinsulinemia, DM High TG, VLDL Low BP Metabolic Syndrome

7

In order to explain Metabolic Syndrome:

• We are looking for a ubiquitous factor that

– promotes obesity (preferably visceral) – promotes hypertension – induces selective hepatic insulin resistance

• blocks Foxo1 to promote gluconeogenesis

(hyperglycemia, hyperinsulinemia, and diabetes)

• stimulates de novo lipogenesis

(dyslipidemia, atherosclerosis)

U.N. General Assembly U.N. General Assembly Sept 20, 2011 Sept 20, 2011

• Non-communicable disease is now a bigger problem

than acute infectious diseases worldwide

• Plan to target, tobacco, alcohol, and diet

U.N. General Assembly U.N. General Assembly Sept 20, 2011 Sept 20, 2011

• Non-communicable disease is now a bigger problem

than acute infectious diseases worldwide

• Plan to target, tobacco, alcohol, and diet
• But exactly what about diet?

Total calories? Fat? Red meat? Dairy? Carbohydrate?

The Fiction The Fiction

“Beating obesity will take action by all of us, based on one simple common sense fact: All calories count, no matter where they come from, including Coca-Cola and everything else with calories…”

• The Coca Cola Company, “Coming Together”, 2013

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• Some Calories Cause Disease More than Others
• Different Calories are Metabolized Differently
• A Calorie is Not A Calorie

The Science The Science

High Fructose Corn Syrup is 42 High Fructose Corn Syrup is 42-55% Fructose; 55% Fructose; Sucrose is 50% Fructose Sucrose is 50% Fructose

Glucose Glucose Fructose Fructose Sucrose Sucrose

Ventura et al. Obesity 19:868, 2011

Actual fructose content in soft drinks Actual fructose content in soft drinks

55%

150 150 125 100 75 50 25

Grams per day

U.S. Commerce Service 1822-1910, combined with Economic Research Service, USDA 1910-2010

150 150 125 100 75 50 25

Grams per day

U.S. Commerce Service 1822-1910, combined with Economic Research Service, USDA 1910-2010

Growth of Sugar Industry Stabilization HFCS + Sugar for Fat

WWII

150 150 125 100 75 50 25

Grams per day

U.S. Commerce Service 1822-1910, combined with Economic Research Service, USDA 1910-2010

Growth of Sugar Industry Stabilization HFCS + Sugar for Fat

WWII Theoretical threshold based on EtOH AHA threshold for CVD

9

150 150 125 100 75 50 25

Grams per day

U.S. Commerce Service 1822-1910, combined with Economic Research Service, USDA 1910-2010

Growth of Sugar Industry Stabilization

WWII Emergence of CVD as health issue 1931

HFCS + Sugar for Fat

Theoretical threshold based on EtOH AHA threshold for CVD

150 150 125 100 75 50 25

Grams per day

U.S. Commerce Service 1822-1910, combined with Economic Research Service, USDA 1910-2010

Growth of Sugar Industry Stabilization

WWII Emergence of CVD as health issue 1931

HFCS + Sugar for Fat

Emergence of Adolescent T2DM as health issue 1988 AHA threshold for CVD Theoretical threshold based on EtOH

Global consumption of sugar/sugarcrops Global consumption of sugar/sugarcrops Calories per day, 2007 Calories per day, 2007

Data from Food and Agriculture Organization, World Health Organization, 2007 Mozaffarian et al. N Engl J Med 364:2392, 2011

Foods that cause weight gain Foods that cause weight gain

Mozaffarian et al. N Engl J Med 364:2392, 2011

Foods that cause weight gain Foods that cause weight gain

Mozaffarian et al. N Engl J Med 364:2392, 2011

Foods that cause weight gain Foods that cause weight gain

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Lowering sugar Raising sugar Effects of sugar on obesity (meta Effects of sugar on obesity (meta-

• analysis)

analysis)

Te Morenga et al. BMJ 345:e7492, 2013

Obesity is not the problem Obesity is not the problem Metabolic syndrome is the problem Metabolic syndrome is the problem Fructose is not glucose Fructose is not glucose

• Fructose is 7 times more likely than glucose

to form Advanced Glycation End-Products (AGE’s)

• Fructose does not suppress ghrelin
• Acute fructose does not stimulate insulin (or leptin)
• Hepatic fructose metabolism is different
• Chronic fructose exposure promotes the metabolic syndrome

Elliot et al. Am J Clin Nutr, 2002 Elliot et al. Am J Clin Nutr, 2002 Bray et al. Am J Clin Nutr, 2004 Bray et al. Am J Clin Nutr, 2004 Teff et al. J Clin Endocrinol Metab, 2004 Teff et al. J Clin Endocrinol Metab, 2004 Gaby, Alt Med Rev, 2005 Gaby, Alt Med Rev, 2005 Le and Tappy, Curr Opin Clin Nutr Metab Care, 2006 Le and Tappy, Curr Opin Clin Nutr Metab Care, 2006 Wei et al. J Nutr Biochem, 2006 Wei et al. J Nutr Biochem, 2006 Johnson et al. Am J Clin Nutr 2007 Johnson et al. Am J Clin Nutr 2007 Rutledge and Adeli, Nutr Rev, 2007 Rutledge and Adeli, Nutr Rev, 2007 Brown et al. Int. J. Obes, 2008 Brown et al. Int. J. Obes, 2008

A different model of insulin resistance A different model of insulin resistance

Cytokines

Fructose Fatty liver

Sensitivity Hepatic insulin resistance

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A different model of insulin resistance A different model of insulin resistance

Cytokines

Fructose Fatty liver

Sensitivity Hepatic insulin resistance

The second problem The second problem The browning reaction or Maillard reaction The browning reaction or Maillard reaction

• r non
• r non-enzymatic glycation

enzymatic glycation Instead of roasting 1 hour at 375 degrees Instead of roasting 1 hour at 375 degrees we slow cook at 98.6 degrees for 75 years we slow cook at 98.6 degrees for 75 years

Aging and costal cartilage Aging and costal cartilage

Courtesy Dr Baynes Figueroa-Romero et al. Rev Endo Metab Dis 9:301, 2008

Generation of reactive oxygen species by carbohydrate Generation of reactive oxygen species by carbohydrate

12

The furan ring of fructose is more unstable, so at equilibrium, fructose exists in the linear form

Lim et al. Nat Rev Gastro Hepatol 7:251, 2010

Glucose Fructose Days of in vitro glycation Fluorescence 600 400 200

Ahmed and Furth, Clin Chem 38:1301, 1992

Fructose and glycation in vitro

0 8 16 24

Rates of reactivity

Rate Carbonyl (/mM/hr) % Glucose 0.6 0.002 Galactose 2.8 0.02 Fructose 4.5 0.7

Bunn and Higgins, Science 213:222, 1981

Non Non-enzymatic glycation: fructose >> glucose enzymatic glycation: fructose >> glucose

Hepatocyte death Hepatocyte death in vitro in vitro upon fructose exposure upon fructose exposure (after generation of H (after generation of H2

2O

O2

2) Treatment ED50 Fructose 1.5 ± 0.13 M Glucose >1.5 M Glycoaldehyde 20 ± 2 mM Glyoxal 5 ± 0.5 mM

Lee et al. Chemico-biological Interactions 178:332, 2009

Hepatocyte death Hepatocyte death in vitro in vitro upon fructose exposure upon fructose exposure (after generation of H (after generation of H2

2O2 2) Treatment ED50 ED50 (with H2O2) Fructose 1.5 ± 0.13 M 12 ± 2 mM Glucose >1.5 M 1.5 M Glycoaldehyde 20 ± 2 mM 0.5 ± 0.1 mM Glyoxal 5 ± 0.5 mM 0.02 ± 0.002 mM

Lee et al. Chemico-biological Interactions 178:332, 2009

Prevented by addition of: antioxidant vitamins (VitB1, VitB6, VitC) P450 inhibitors hydroxyl radical and carbonyl scavengers heavy metal chelators

The Methionine The Methionine-Choline Deficient Diet Choline Deficient Diet

Pickens et al. J Lipid Res 50:2072, 2009

Fastest animal model of NASH

• sucrose necessary to provide the substrate for steatosis
• methionine deficiency reduces glutathione,

the hepatic hydroxyl radical scavenger

• choline deficiency reduces phosphatidyl choline,

another mechanism of hepatic lipid export

Sucrose is necessary for NAFLD in the Sucrose is necessary for NAFLD in the Methionine Methionine-Choline deficient diet Choline deficient diet

Pickens et al. J Lipid Res 50:2072, 2009

13

TUNEL staining in the TUNEL staining in the Methionine Methionine-Choline deficient diet Choline deficient diet

Pickens et al. J Lipid Res 50:2072, 2009

Association of fructose consumption with Association of fructose consumption with severity of steatosis and fibrosis severity of steatosis and fibrosis

Grade of Steatosis

p =0.06 p < 0.005

Stage of Fibrosis

p < 0.0007

Non Non Occasional Occasional Daily Daily

Error bar = 95%CI

Abdelmalek et al. Hepatology 51:1961, 2010

• > 30% obese
• > 30% obese

< 63% active

• > 30% obese

< 63% active

• > 30% obese

< 63% active

14

• > 30% obese

< 63% active

• > 30% obese

< 63% active

• Figure 1. Adjusted Hazard Ratio of the Usual Percent of Calories from Added Sugar for CVD Mortality

Among US Adults Aged >20 Years – NHANES Linked Mortality Files, 1988-2006 Histogram is the distribution of usual percent of calories from added sugar in population. Lines show the adjusted HRs from Cox models. Mid-value of quintile 1 (7.5%) was the reference standard. Model was adjusted for age, sex, race/ethnicity, educational attainment, smoking status, alcohol consumption, physical activity level, family history of CVD, antihypertensive medication use, health eating index score, body mass index, systolic blood pressure, total serum cholesterol and total calories. Solid line indicates point estimates; dashed lines indicate 95% CIs. CVD indicates cardiovascular disease; HR, hazard ratio; NHANES, National Health and Nutrition Examination Survey.

Yang et al. JAMA Int. Med epub Nov 15, 2013

Hazard ratio for CV mortality based on percent calories as sugar for US adult population, 1988-2006 Prevalence of diabetes, 2010

Romaguera-Bosch et al. Diabetologia 56:1520, 2013

SSB SSB’s and BMI s and BMI-adjusted risk of diabetes in adjusted risk of diabetes in EPIC EPIC-Interact (Europe) Interact (Europe) An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Food and Agriculture Organization (FAO); FAOSTAT Food Supply data in kcal/capita/day calculation: Food Supply= ∑Supply Elements - ∑Utilization Elements = (Production + Import Quantity + Stock Variation – Export Quantity)

• (Feed + Seed + Processing + Waste).

Only industrial waste factored in. Extracted Food Supply data for 2000 and 2007: Total Calories Roots & Tubers, Pulses, Nuts, Vegetables Fruits-Excluding Wine Meat Oils Cereals Sugar, Sugarcrops & Sweeteners International Diabetes Federation (IDF) 2000 (1st ed) and 2007 (3rd ed) The World Bank World Development Indicators Database GDP expressed in purchasing power parity in 2005 US dollars for comparability among countries

Basu et al. PLoS One, Feb 27, 2013

15

Total 204 countries; complete data for 154 countries (50 not different)

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Basu et al. PLoS One, Feb 27, 2013

Total 204 countries; complete data for 154 countries (50 not different) Data monitoring and quality Generalized estimating equations Conservative fixed effects approach (Hausman test) Hazard model to control for selection bias (Heckman selection model) Longitudinal data to determine what preceded diabetes (Granger causality) Period effects controlled for secular trends that may have occurred as a result of changes diabetes detection capacity or importation policies.

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Basu et al. PLoS One, Feb 27, 2013

Total 204 countries; complete data for 154 countries (50 not different) Data monitoring and quality Generalized estimating equations Conservative fixed effects approach (Hausman test) Hazard model to control for selection bias (Heckman selection model) Longitudinal data to determine what preceded diabetes (Granger causality) Period effects controlled for secular trends that may have occurred as a result of changes diabetes detection capacity or importation policies. Controlled for: GDP per capita % population living in urban areas Obesity % of population over age 65 physical inactivity

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Basu et al. PLoS One, Feb 27, 2013

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Diabetes prevalence rose from 5.5% to 7.0% for 204 countries 2000-2007

Basu et al. PLoS One, Feb 27, 2013

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Diabetes prevalence rose from 5.5% to 7.0% for 204 countries 2000-2007

Sugar Sugar+controls Sugar+controls+period Overall

Model # countries Effect (95% CI)

Basu et al. PLoS One, Feb 27, 2013

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Basu et al. PLoS One, Feb 27, 2013

16

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Context Only changes in sugar availability correlated with changes in diabetes prevalence Every extra 150 calories increased diabetes prevalence by 0.1% But if those 150 calories were a can of soda, diabetes prevalence increased 11-fold, by 1.1%; p <0.001) These data meet the criteria for Causal Medical Inference (Bradford Hill): — dose — directionality — duration — precedence Controlled for many confounders; obesity exacerbated, but did not confound the effect These data estimate that 25% of diabetes worldwide is explained by sugar

Basu et al. PLoS One, Feb 27, 2013

Limitations Ecologic, not raw data analysis Ecologic fallacy: inferences about individuals are based on aggregates Could the sugar consumers and the diabetes be different people? Food supply, not food consumption data (wastage, esp. in the U.S.?) but wastage does not appear to be different based on different foods And leaving the U.S. out of the analysis did not change the findings Only one decade (but longitudinal time-series data, not 2 cross-sectional points in time) Not a complete dietary analysis Different techniques used to screen for diabetes in different countries Different diagnostic criteria for diabetes in different countries Some countries used self-reported data; many diabetics are undiagnosed Data includes both Type 1 and Type 2 diabetes

An international longitudinal panel analysis of An international longitudinal panel analysis of diet and diabetes diet and diabetes

Basu et al. PLoS One, Feb 27, 2013

Foodstuffs and metabolic syndrome Foodstuffs and metabolic syndrome

• Transfats

Transfats

• Branched chain amino acids

Branched chain amino acids

• Ethanol

Ethanol

• Fructose

Fructose

• Liver is the only site for energy metabolism

Liver is the only site for energy metabolism

• Not insulin regulated

Not insulin regulated

• No glycogen popoff, mitochondria are overwhelmed

No glycogen popoff, mitochondria are overwhelmed

ROS

FRUCTOSE

ROS ROS

Mitochondria Peroxisome

ROS

UPR Cell death FRUCTOSE

Acetyl-CoA ROS ATP ROS

Cellular/ metabolic dysfunction

NH2

Endoplasmic Reticulum

Acyl-CoA Lipid droplet pSer-IRS-1 PKCε ε ε ε JNK1

Insulin resistance Fat deposition Insulin Receptor

Toward a unifying hypothesis of metabolic syndrome Toward a unifying hypothesis of metabolic syndrome

Bremer et al., Pediatrics 129:557. 2012

No drug target No drug target

• Mitochondrial overload promotes lipogenesis, leading to

Mitochondrial overload promotes lipogenesis, leading to hepatic insulin resistance, and metabolic syndrome hepatic insulin resistance, and metabolic syndrome

• Mitochondrial overload releases ROS

Mitochondrial overload releases ROS’ ’s, which lead to cell s, which lead to cell dysfunction, aging, and death dysfunction, aging, and death

• Only options are:

Only options are:

• reduce substrate availability (diet)

reduce substrate availability (diet)

• reduce hepatic flux (fiber)

reduce hepatic flux (fiber)

• increase clearance (exercise)

increase clearance (exercise)

Bremer et al., Pediatrics 129:557, 2012

Recognition at the Recognition at the American Heart Association American Heart Association

Johnson et al. Circulation 120:1011, 2009

Recommends reduction in added sugar intake from 22 tsp/day to 9 tsp/day (males) and 6 tsp/day (females)

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Philpott, Mother Jones 2012 (from Bureau of Labor Statistics)

How our food dollars have been reallocated How our food dollars have been reallocated Question 1: Question 1: Can our Can our “ “toxic food environment toxic food environment” ” be changed be changed without government/societal intervention? without government/societal intervention? Especially when there are potentially addictive Especially when there are potentially addictive substances involved? substances involved? Question 2: Question 2: Can we afford to wait to enact public health measures Can we afford to wait to enact public health measures when health care will be bankrupt due to when health care will be bankrupt due to chronic metabolic disease? chronic metabolic disease?

Nat Rev Gastroenterol Hepatol 7:251, 2010 J Am Diet Assoc 110:1305, 2010

Further reading Further reading

Arterioscler Throm Vasc Biol 25:2451, 2005 Is fast food addictive?

Andrea K. Garber, Robert H. Lustig

Curr Drug Abuse Rev 4:146, 2011 Pediatric Annals 41:23, 2012

Further reading Further reading

Arterioscler Throm Vasc Biol 25:2451, 2005 Andrew A. Bremer, M.D., Ph.D.a, Michele Mietus-Snyder, M.D.b, Robert H. Lustig, M.D.c* Pediatrics 129:557, 2012 Nature 487:27, 2012 Advances in Nutrition 4:1, 2013 Annals NY Academy of Sciences, 1, 2013

Further reading Further reading

18

PLoS One 8:e57873, 2013

Further reading Further reading

Current Opinion Gastroenterology, 29:170, 2013

We have started a non We have started a non-

• profit to provide

profit to provide medical, nutritional and legal analysis and consultation medical, nutritional and legal analysis and consultation to promote personal and public health vs. Big Food to promote personal and public health vs. Big Food

• Please let me know if you would like more information!

Please let me know if you would like more information! rlustigmd@earthlink.net rlustigmd@earthlink.net

UCSF Weight Assessment for Teen and Child Health (WATCH) Andrea Garber, Ph.D., R.D. Kristine Madsen, M.D., M.P.H. Patrika Tsai, M.D., M.P.H. Stephanie Nguyen, M.D. M.A.S. Emily Perito, M.D. Jung Sub Lim, M.D., Ph.D. UCSF Dept. of Epidemiology and Biostatistics Nancy Hills, M.S. Touro University Dept. of Biochemistry Jean-Marc Schwarz, Ph.D. San Francisco General Hospital Depts. of Medicine and Radiology Sanjay Basu, M.D., Ph.D. Susan Noworolski, Ph.D. Kathleen Mulligan, Ph.D. UC Berkeley Dept. of Nutritional Sciences and Integrative Biology Pat Crawford, R.D., Ph.D. Paula Yoffe, B.S. Vanderbilt University Dept. of Pediatrics Andrew Bremer, M.D., Ph.D. Children’s National Medical Center Michele Mietus-Snyder, M.D.

Collaborators Collaborators