two major us trends - kaeberlein lab

Life Expectancy in the US

Two Major US Trends

Obesity Trends* Among U.S. Adults

BRFSS, 1985

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1986

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1987

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1988

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1989

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1990

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1991

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1992

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1993

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1994

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1995

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1996

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1997

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1998

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 1999

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2000

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2001

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2002

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2003

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2004

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2005

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%


BRFSS, 2006

No Data <10% 10%–14% 15%–19% 20%-24% 25%-29% ?30%

What is Obesity?

Metabolic disordercharacterized by chronicexcess of energy intakeover expenditure, leadingto the accumulation offat.

N Engl J Med 355:763, August 24, 2006

Underweight = <18.5Normal weight = 18.5-24.9Overweight = 25-29.9Obese > 30

BMI correlates with mortality

Methods

• Genetic Approaches– Genome-wide Linkage Studies– Candidate Gene Association Studies

• Objective: to determine whether anassociation exists between a gene’sallelic variation and obesity-relatedtraits

Methods

• Genome-wide Linkage Studies– A systematic examination of all chromosomes in obese

families using polymorphic markers in order to detectincreased allele sharing in obese sibpairs

– Regions located on nearly all the chromosomes(except Y) have been linked to different obesity-related phenotypes

• BMI, distribution of adipose tissue, occurrence of ametabolic syndrome, resting energy expenditure, energyand macronutrient intake, weight variation, the levels ofcirculating leptin and insulin

– Limitations• Lack of replication and inconsistency between studies• Population heterogeneity limits power to detect true

linkage signals

Methods

• Candidate Gene Association Studies– Hypothesis driven approach used to detect

genetic variants that influence susceptibility tocommon disease

– Limitations• High proportion of false positive results published• False negative results may arise in small studies if

genetic effects are modest• True association in one population might not be true

in another due to heterogeneity in genetic orenvironmental background

Variables InfluencingHuman Obesity

• Monogenic Disorders– Leptin/Melanocortin Pathway

• Polygenic Susceptibility Factors– Gene-Gene Interaction– Gene-Environment Interaction

• Diet• Physical Activity

Table 1.Rare monogenic forms of human obesity.

Mutch, D.M. and K. Clement. Best Practice & Research ClinicalEndocrinology & Metabolism 2006, 20(4): 647-664

Leptin Melanocortin Pathway

Oswald and Yeo, Obesity Reviews 8:293-306

FOOD INTAKE

ENERGY METABOLISM

Obesity Gene Candidates

ADIPOSE TISSUE METABOLISM

LIPID AND GLUCOSE METABOLISM

Obesity Gene Candidates

Gene-Gene Interaction• PPARG2 – ADRB3

– Pro12Ala of PPARG2 gene - Trp64Arg of ADRB3 gene• Significantly higher BMI, insulin, and leptin levels

• ADRs– Gly/Gly genotypes of ADRB1 plus at least one β3- Arg allele

• Increases in BMI

– ADRB1/ADRB3 gene with UCP-1 gene and/or LPL

• LEP-LEPR– LEP-G2548A and LEPR Q223R

• May promote immune dysfunction associated with obesity

• Chromosome region interaction between obesity susceptibility loci– Chromosome regions 2p25-p24 and 13q13-21– 20q and chromosome 10 centromere– TBC1 domain family member 1 gene (TBC1D1) and 4q34-q35 region

Gene-Environment Interaction• Gene and Diet interaction

– Genes regulating energy homeostasis and thermoregulation• Neuropeptide Y (NPY), agouti-related protein (AGRP), melanocortin

pathway factors (MC4R), uncoupling proteins (UCPs), fatty acid bindingfactors (FABP)

– Diet intake control may be affected by genes encoding tastereceptors and peripheral signaling peptides

• Insulin (INS), leptin (LEP), ghrelin (GHRL), cholecystokinin (CCK)

– Protein levels may be altered during starvation or overfeeding• UCP-2 and UCP-3 genes, LEPR genes

– Genes involved in digestion of starch may be linked tocarbohydrate and protein intakes

• α-amylase genes (AMY1A, AMY2A, and AMY2B) insulin-like growth factor 1gene (IGF1)

– Genes controlling eating behavior• MC4R gene and neuromedin beta gene (NMB)

– Variable responses to diet in lipoprotein metabolism pathway• APOE, APOB, APOA4, APOC3, LDLR, FABP, LPL, MTP, CETP, HPL

Gene-Environment Interaction• Gene and Physical Activity Interaction

– Genes influence physical performance and physicalactivity

• Improved duration of exercise• II and ID genotype of ACE but not in DD genotype

• Maximal oxygen consumption after aerobic exercise training• HIF1 and TTN

• Maximal oxygen uptake in the sedentary state in response totraining

• CKMM, SGCB, SNTB1, SGCG, DAG1, LMNA, PYGL, GCH1,SUR

• Other genes that have been reported: GNB3, ADRB2, MC4R,CART, UCP-2, UCP-3

FTO Papers

• Genome-wide linkages study– Strong association between SNPs in FTO,

diabetes and obesity incidence– ~20,000 adults, ~10,000 children

• Gene-Environment Interaction– DNA demethylase

• DNA repair or transcriptional regulator?• Found in hypothalamus – energy control center of

brain• mRNA levels sensitive to food intake

two major us trends - kaeberlein lab

Documents