Does making too much insulin cause type 2 diabetes?

Does Making too much Insulin Cause Type 2 Diabetes?

Thomas A. Buchanan, MD

For the

USC Gestational Diabetes Study Group

Teach you something about the biology, prediction and prevention of type 2 diabetes

Show you what an interdisciplinary team working in humans can accomplish

Goals

The USC Gestational Diabetes Study Group

Research Staff

Enrique TrigoKarla GarciaLilit BaronikianMiwa Kawakubo

Aura MarroquinCesar OchoaJose GoicoSylvia Tan

Investigators

Tom Buchanan

Siri Kjos

Richard Watanabe

Stan Azen

Anny Xiang

Ruth Peters

Hooman Allayee

Jean Lawrence

Katie Page Penina Segall-GutierrezJorge Caro George AureaIsabel Enriquez

Participants: GDM Cohort Study, TRIPOD and PIPOD Studies, BetaGene Study

With Strong Support from:

Funding: NIDDK, NCRR/GCRC/CTSI, ADA, Parke-Davis, Takeda

Collaborators: Bergman group, Howard Hodis, Wendy Mack, Goran group

Gestational Diabetes

Population Screening for Mild Hyperglycemia

Definition

Glucose intolerance with onset or first recognition during pregnancy

Gestational Diabetes Mellitus

Detection

Screen pregnant women not known to have diabetes:for at-risk clinical characteristicsfor diagnostic oral glucose tolerance

“Population” screening for elevated glucose levels in young womenGlucose levels that might cause fetal morbidity

Circulating Glucose

Fre

quen

cy

No GDM GDM

Gestational Diabetes

Population Perspective

0

10

20

30

40

50

60

70

80

5 10 15 20 25 30

Navajoo

o

oo

o

o

o Zuni

Mixed/OtherHispanic (USC)

x x

x

xx

x x

x

x

x Boston Cohort

Years after Delivery

Cu

mu

lati

ve I

nci

den

ce o

f D

iab

etes

(%

)Diabetes After GDM

Kim et al: Diabetes Care, 2002

Multifaceted Approach to Diabetes after GDM

USC Gestational Diabetes Study Group

Clinical Cohort

Women followed in standard clinical care with annual testing for diabetes after index pregnancy

Main Outcomes: diabetes incidence and clinical risk factors

Physiological Cohort

Women followed with detailed physiological testing during pregnancy and at 15-month intervals thereafter

Main Outcomes: physiological mechanisms for development of diabetes

Interventional Cohort

Women enrolled in clinical trials of diabetes prevention and early treatment

Main Outcomes: feasibility and mechanisms for diabetes prevention

Genetic Cohort

GDM and control probands and their families studied with detailed physiological and morphological phenotyping and genetic analysis

Main Outcomes: genetic associations with diabetes quantitative traits

Defining Diabetes Incidence and Clinical Risk Factors

Subjects: Hispanic women with GDM who delivered at Womens Hospital (n=700-1000)

Setting: Outpatient clinic where women returned for diabetes testing postpartum and annually

Design: Observational

Main Outcomes: diabetes incidence rate and clinical risk factors for diabetes

Investigators: Siri Kjos, Anny Xiang, Ruth Peters, Tom Buchanan

Support: faculty blood, sweat and tears!

Clinical Cohort

Kjos et al: Diabetes 44:586-591, 1994

Diabetes after GDMCumulative Incidence in Clinical Cohort

Years Postpartum

Cum

ulat

ive

Inci

denc

e (%

)

0

20

40

80

60

0 1 2 3 4 5 6

n=671

Diabetes after GDM

Risk Factors in Clinical Cohort

At Baseline (pregnancy and immediate postpartum)

Early gestational age at diagnosis1

High glucose levels1

During Follow-up

Weight gain2

Additional pregnancy2

Progestin-only contraception3,4

1Kjos et al: Diabetes 44:586-591, 1995, 2Peters et al: Lancet 347:227-230, 1996 3Kjos et al: JAMA 280:533-538, 1998, 4Xiang et al: Diabetes Care 29:613-617, 2006

Insulin Resistance}Hypothesis: Insulin resistance is causing β-cell failure

Identifying Physiological Determinants of Diabetes

Subjects: Prospectively recruited cohort of Hispanic women with GDM who delivered at Womens Hospital (n=150)

Setting: GCRC-based study

Design: Observational - detailed physiological measurements of glucose regulation during pregnancy and at 15-month intervals thereafter

Main Outcomes: physiological changes that predict or attend the development of diabetes

Investigators: Tom Buchanan, Anny Xiang, Ruth Peters, Siri Kjos

Support: NIH R01 DK46374 (1993-2007)

Physiological Cohort

USC GDM Cohort Study

Overview of Study Design

Hispanic American womenGDM by 3rd GDM Workshop

criteriaIslet cell antibody negative

Detailed Metabolic Measurements Glucose levels Insulin resistance β-cell function Body composition

15 30 45 60 75 900

Months After Delivery

3rd TM

Non-Pregnant

105 120 132 144

n=150 GDMn=30 Control

Gestational Diabetes MellitusMultiple Metabolic Defects during the Third Trimester

Xiang et al: Diabetes 48:848-854, 1999

Beta Cell Compensation

1500

1000

500

0GDMControl

Dis

po

sit

ion

In

de

x

p<0.0001

IVGTT

Skeletal Muscle

Control (30)

GDM (150)

Adipose Tissue

Control

GDM

Liver

Control

GDM

Type 2 Diabetes after GDMCumulative Incidence in Physiological Cohort


n=72 with multiple visits

Resistant Sensitive

Regulation of Blood Glucose

Normal

Diabetic

Impaired

Insulin Sensitivity

Insu

lin S

ecre

tion

Insulin Sensitivity and Secretion

Bergman et al: J Clin Invest, 1981

NormalAbnormalSensitivity x Output = Constant

“Disposition Index”

Disposition Index

2000

1000

200

0 1 2 30

200

400

600

800

Insulin Sensitivity (SI)

Acu

te I

nsu

lin

Res

po

nse

Yes (n=24) No (n=47)Diabetes:


Longitudinal Changes: First Five Years

β-cell Function after GDM

3.9 years

3.7 years

Declining β-cell Function after GDMRelation to Glucose Levels

Prior GDMs (n=71): OGTTs and IVGTTs at 15, 30, 45, 60, 75 months postpartum

Yes (n=24)No (n=47)Diabetes:

Diabetes

0 200 400 600 800 10000

100

200

Disposition Index

mg

/dl

Fasting Glucose

0 200 400 600 800 10000

100

200

300

Disposition Index

mg

/dl

Diabetes


OGTT 2hr Glucose

Xiang et al: Diabetes 55:1074-1079, 2006 5-11-05

What predicts diabetes?

Evolution of Hyperglycemia after GDM

What predicts diabetes?

5-11-05

0 200 400 600 800 10000

100

200

300

Disposition Index

mg

/dl

Diabetes


OGTT 2hr Glucose

Answer: characteristics of people who almost have diabetes(PLUS: falling β-cell function, weight gain, pregnancy, progestins)

What predicts falling β-cell compensation?

Subjects: n=60 with at least two visits by 75 months

Baseline Variables: body mass and fat, glucose levels, insulin levels, insulin resistance, β-cell compensation, lipid levels (FFA and clinical lipids), adipocytokines

During Follow-up: pregnancy; hormonal contraception; weight and fat gain; change in insulin sensitivity, lipids, adipocytokines

Analysis: Random coefficients mixed modeling to identify factors predictive of (for baseline variables) or associated with (for follow-up variables) change β-cell compensation

Predicting Falling β-cell FunctionDesign

Only Independent Correlate: Weight Gain (p=0.003)

Results

Predicting Falling β-cell Function

Xiang et al: Diabetes Care 33:396-401, 2010

How does it work?

Progressive β-cell Failure

Type 2 Diabetes

How might obesity affect β-cell function?

Insulin Resistance

Obesity

Fatty Acids Adipokines

Glucose Toxicity

Strongest Correlate: Weight Gain (p=0.003)

“Explained” by three independent changes:

Adjust for:Impact on regression Residual p-value

Falling SI -40% <0.04

Falling Adiponectin -19% <0.02

Rising CRP -19% <0.02

All three -70% <0.29

Adipoiknes may directly influence the propensity for β-cells to fail.

Results

Predicting Changing β-cell Function

Xiang et al: Diabetes Care 33:396-401, 2010

Progressive β-cell Failure

Type 2 Diabetes

How might obesity affect β-cell function?

Insulin Resistance

Obesity

Fatty Acids Adipokines

Glucose ToxicityΧ

Can we do anything to stop progression to diabetes?

Feasibility and Mechanisms for Diabetes Prevention

Subjects: Prospective cohort of women Hispanic with prior GDM (n=266)

Setting: GCRC-based study

Design: Interventional clinical trial with detailed physiological measurements

Main Outcomes: diabetes rates and mechanisms for diabetes prevention and beta cell preservation; pre-clinical atherosclerosis

Investigators: Tom Buchanan, Anny Xiang, Ruth Peters, Stan Azen, Howard Hodis, Wendy Mack

Support: Investigator-initiated pharmaceutical grants (Parke-Davis and Takeda), NIH and ADA supplemental funding

Prevention Cohort

Preventing Type 2 DiabetesThree Levels of Opportunity

Adipose Tissue

Liver & Muscle

Adipokines

Fatty Acids

Insulin Resistance

2

InsulinResistance

1

Obesity

Energy BalanceNegative Positive

Weight Loss and Wasting

Fat Accumulation

3

β-cellFailure

Weak B-cells

Hyperglycemia

Robust B-cells

Hyperinsulinemia

TZDs

Overview of Design: Diabetes Prevention

TRoglitazone In Prevention Of Diabetes: TRIPOD Study

Buchanan et al: Diabetes 51:2796-2803, 2002

Hispanic women with prior GDM

2000 - 20011995Off

drug

Blinded Troglitazone

Blinded Placebo

TRIPOD Trial

Age: 34 yrsBMI: 30 kg/m2

Fasting glucose: 98 mg/dl2-hr Glucose: 154 mg/dlHbA1C: 5.7%

OGTTs: Diabetes

IVGTTs:Insulin Resistanceβ-cell Function

TRIPOD Study: Diabetes Rates

Months on Study

Peo

ple

with

Dia

bete

s

60%

40%

20%

0%0 10 20 30 40 50 60

Placebo

Troglitazone

55% Relative Risk Reduction


On TrialOff

Trial

Months after Randomization

Fra

ctio

n w

ith D

iabe

tes

60%

40%

20%

0%

0 20 40 60

Placebo

12.1% per year

Troglitazone

5.4% per year

21% per yearn=40

3% per yearn=44

ivGTT

Masking?

TRIPOD Study: Post-Trial Washout


p=0.01 between groups

Baseline 8 Months Post-trial

Placebo (n=40)

0 2 4 6

MINMOD SI

Acu

te In

sulin

Res

po

nse

(uU

/ml x

min

)

200

400

600

800

00 2 4 6

MINMOD SI

Troglitazone (n=44)

39% fall

Women without Diabetes during Trial

Stable

TRIPOD: Preservation of β-cell Function

Diabetes Prevention


Overview of Integrated Design

Off drug

Open Label Pioglitazone

PIPOD Trial

2004

TRIPOD and PIPOD

2000 - 20011995Off

drug


Blinded Placebo

TRIPOD Trial

Diabetes

Diabetes

Open Label Troglitazone

Open Label Troglitazone OGTTs

IVGTTs


0 2 4 6 80

400

800

1200

1600

Dis

po

siti

on

In

dex

(SI x

AIR

g)

Years

Effect of Pioglitazone after Placeboβ-cell Function in TRIPOD+PIPOD

n=32

Pioglitazone

PIPOD

p=0.14

OffPlacebo

TRIPOD

p=0.003

Off


0 2 4 6 80

400

800

1200

1600

Dis

po

siti

on

In

dex

(SI x

AIR

g)

Years

Effect of Pioglitazone after Troglitazoneβ-cell Function in TRIPOD+PIPOD

n=27

Troglitazone

TRIPOD

p=0.24

Off Pioglitazone

PIPOD

p=0.12

Off


Type 2 Diabetes PreventionResults of Recent Randomized Trials

Study Subjects Intervention Rel. Risk

*Similar β-cell protection with pioglitazone

Finnish DPS I.G.T. Lifestyle 58%

U.S. DPP I.G.T. Lifestyle 58%

XENDOS I.G.T. Orlistat 45%

Weight Loss

Stop-NIDDM I.G.T. Acarbose 25%

Metformin 31%U.S. DPP I.G.T.Glucose Absorption, Production

TRIPOD Prior GDM Troglitazone 55%*DREAM I.G.T. Rosiglitazone 62%

Fat-induced

Ins. Resist.ACT NOW I.G.T. Pioglitazone 72%

Reducing body fat or mitigating its biological consequences provides the best evidence for disease modification (β-cell protection) in “pre-diabetes”.

Diabetes Prevention Trials

Important Lesson

What is the mechanism for diabetes prevention with TZDs?

Overview of Design: Diabetes Prevention

TRoglitazone In Prevention Of Diabetes: TRIPOD Study

Hispanic women with prior GDM

2000 - 20011995Off

drug


Blinded Placebo

TRIPOD Trial

Age: 34 yrsBMI: 30 kg/m2

Fasting glucose: 98 mg/dl2-hr Glucose: 154 mg/dlHbA1C: 5.7%

OGTTs: Diabetes

IVGTTs:Insulin Resistanceβ-cell Function


Resistant SensitiveInsulin Sensitivity

Insu

lin O

utpu

tTRIPOD: β-cell “Rest” and Protection from Diabetes

Baseline 3 Months

β-cell “Rest” = Protection From Diabetes

10%/yrDiabetes

n=35 6%/yrDiabetes

n=31

0%/yrDiabetes

n=42

(IVG

TT In

sulin

Are

a)

(MINMOD SI)

Troglitazone12%/yr

Diabetes

Placebo


Resistant SensitiveInsulin Sensitivity

Insu

lin O

utpu

tβ-cell Protection in TRIPOD

Baseline3 Months

Diabetes 6% / yr

Diabetes 0% / yr

(IVG

TT In

sulin

Are

a)

(MINMOD SI)Buchanan et al: Diabetes, 2002

Fasting Glucose-7%

-3%

p=0.01Fasting FFA

-2%

-8%

p=0.17Triglycerides

-17%

-19%

p=0.60

Is it really “unloading” that counts?

-40 -20 0 20 40 600

5

10

15

Piogiltazone

Initial Reduction in Insulin Output* (% of Basal)

Dia

bet

es I

nci

den

ce (

%/y

r)

TRIPOD and PIPOD

β-cell “Rest” and Diabetes Rates

Troglitazone

*change in IVGTT insulin area, in tertilesXiang et al: Diabetes 55:517-522, 2006

Some Attractive Mechanisms

“Toxic” Effects of β-cell Loading

Unfolded protein response

insulin

Amylin (IAPP)

Oxidative stress

Direct amylin toxicity

All may increase apoptosis and impair insulin secretion

β-cell MassNeogenesis

Replication

Hypertrophy}Gain

Necrosis

ApoptosisLoss

Recruitment

Synthesis Stimulus Secretion Coupling

Insulin Secretion

Circulating Insulin Levels

Hepatic Extraction

Expansion Signals

Genetics

Drugs?

Insulin Resistance

Obesity

Genetics?

“Loading”

Adipokines

Χ+

Main Targets for Disease Modification in β-cells

Genetic Determinants of GDM and Type 2 Diabetes

Subjects: Mexican American GDM and control probands and family members recruited from a variety of sources across Los Angeles (n=~2200)

Setting: GCRC-base study

Design: Cross-sectional with longitudinal sub-study

Main Outcomes: associations between putative diabetes genes and intermediate phenotypes for glucose regulation

Investigators: Tom Buchanan, Richard Watanabe, Anny Xiang, Hooman Allayee, Jean Lawrence

Support: NIH R01s and ADA clinical research grants

Genetic Cohort

Where do we go from here?

New Research Directions

Gestational Diabetes Study Group

Impact of GDM on obesity and glucose regulation in offspring: Katie Page (CTSI K12 Scholar)

Enhancing compliance with follow-up for detection and prevention of diabetes: Penina Segall-Gutierrez (CDC research grant)

Bariatric surgery and β-cell preservation: Tom Buchanan, Anny Xiang, Namir Katkhouda, Elizabeth Beale (planning)

Ethnic differences in glucose regulation after GDM: Anny Xiang, Tom Buchanan (planning)

Prevention and Early Treatment of Type 2 Diabetes

One Clinical Strategy

Measure Glucose

Diabetes

Diet+Exercise and Medication

DiabeticHigher Risk

Diet and Exercise

Impaired

Continue Diet and Exercise

Stable Glycemia

Medication

DevelopsDiabetes

Lower RiskNormal

Diet and Exercise

Annual Follow-up

Prevention

Treatment

High Risk Individual

β-cells fail when they are exposed to obesity and insulin resistance.

“Overload” appears to be an important mechanism contributing to β-cell failure.

Unloading can preserve β-cell function and prevent diabetes. Weight loss and TZDs are the best approaches we have right now – but not perfect.

We have to do something big about obesity if we are to have any profound impact this problem.

Clinical and translational research is a great way to do science with your friends and have a real impact on human health.

Summary

Thank You!

Science

Does making too much insulin cause type 2 diabetes?