does making too much insulin cause type 2 diabetes?
DESCRIPTION
Presented at the Keck School of Medicine of USC Research Seminar in October 2011. Learn more about Tom's latest work: http://profiles.sc-ctsi.org/thomas.buchananTRANSCRIPT
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
Xiang et al: Diabetes 59:2652-2630, 2010
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:
Xiang et al: Diabetes 55:1074-1079, 2006
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
Yes (n=24)No (n=47)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
Yes (n=24)No (n=47)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
Buchanan et al: Diabetes 51:2796-2803, 2002
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
Buchanan et al: Diabetes 51:2796-2803, 2002
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
Buchanan et al: Diabetes 51:2796-2803, 2002
Overview of Integrated Design
Off drug
Open Label Pioglitazone
PIPOD Trial
2004
TRIPOD and PIPOD
2000 - 20011995Off
drug
Blinded Troglitazone
Blinded Placebo
TRIPOD Trial
Diabetes
Diabetes
Open Label Troglitazone
Open Label Troglitazone OGTTs
IVGTTs
Xiang et al: Diabetes 55:517-522, 2006
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
Xiang et al: Diabetes 55:517-522, 2006
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
Xiang et al: Diabetes 55:517-522, 2006
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 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
Buchanan et al: Diabetes 51:2796-2803, 2002
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
Buchanan et al: Diabetes 51:2796-2803, 2002
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!