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Oral Glucose Tolerance Test (OGTT)
Metabolomics: identification of type 2
diabetes effects on primary metabolism
Dmitry Grapov, et al.
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What is type 2 diabetes mellitus (T2DM)?
Clinically T2DM is:
Can we do a better job by defining the metabolic
signature of T2DM?
type 2
diabetic
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No Data 9.0%
19942000
2009
National trends for T2DM
FY2011 Obama administration proposes around $159.3 billion for the
Iraq and Afghanistan wars (wikipedia)
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Study Design
CohortOverweight women (12-15, obese sedentary, 100 < glucose < 128 mg/dL )
14 week diet* and exercise intervention
Weight management and exercise (4 days/week, 30-40 min)*same diet for all subjects = same background metabolites due to diet!
Sean Adams
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Study Design (cont.)
14 week diet and exercise intervention
OGTT / exercise
intervention
MeasurementsPre- and post-intervention
During Exercise
During oral glucose tolerance test (OGTT)Primary metabolites (n > 300) by GC/TOF
Clinical panel: insulin, glucose, lipids
0, 30, 60, 90, 120 minutes
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Study Goals: identify metabolites that are responsive toexercise, OGTT, and changes in insulin sensitivity
Study factors (X) :1. Dietary intervention leading to weight loss and increased fitness
2. Exercise
3. OGTT4. Insulin sensitivity
Questions:1. how does X affect metabolite baselines and excursion profiles
2. what are the independent metabolic markers for X
3. what is the biological consequence of metabolic changes associated with X
* Analyses I will talk about
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Dimensionality (n x m, 150 x 321)
Data Properties:
2 endpoints
(10) 5 time-points
15 samples x 3210
(48, 150) 321 metabolites x 10
(3210)
Structure
2 endpoints
5 time-points
15 samples 321 metabolitesn
m
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Metabolic Properties of Interest:
Excursions
Baseline and Area Under the Curve (AUC)
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Univariate Statistics:
Intervention associated effects: mixed effects models for changesin baseline and AUC
OGTT or exercise associated effects: one-sample t-Test (AUC 0)or ~2-way ANOVA with repeated measures
Some considerations Normality
Independence
False Discovery Rate
risk =
1-(1-p.value)tests
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Getting those significant differences is a
function of:significance level () and power (1- )
effect size (standardized difference in means)
sample size (n)
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Multivariate Analyses
Examples
1. Principal Components Analysis (PCA)
Unsupervised projection of X based on maximum
variance (exploratory)
2. Partial Least Squares Projection to Latent Structures(PLS)
Supervised projection of X based on maximum
correlation to Y (test of hypothesis)
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Interpreting PCA Results
Variance explained (eigenvalues)
Row (sample) scores and column (variable) loadings
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PCA example (OGTT time course data)
*no scaling or centering
glucose
219021
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How are scores and
loadings related?
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Data scaling is very important!
*autoscaling (unit variance and centered)
glucose
(GC/TOF)
glucose (clinical)
219021
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Intervention adjusted PLS model: Scores
Loadings on thefirst latent
variable (x-axis)
can be used to
interpret the
multivariate
changes in
metabolites
which are
correlated withtime during the
OGTT
time = 0 120 min.
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goodness of the model is all about the
perspective
Determine in-sample (Q2) and out-
of-sample error (RMSEP) andcompare to a random model
permutation tests
training/testing
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Model Training/Testing
Data set selection/splitting is not trivial
Where should
these guys go?
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Use networks to interpret statistical and
multivariate results within a biochemical and
mathematical context
Make aBasic network ingredients
adjacency matrix (what is connected)product/precursor (KEGG rpairs)
chemical similarity (Tanimoto distances)
Dependency (partial correlation)
Vertex and edge attributes(legend)
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Example: OGTT metabolomic networkVertex
Size =importance,
|PLS coefficient|
Color =
direction of
change, sign ofcoeff.
Border = p-
value < 0.05
(ANCOVA)
Edges
Tanimoto
similarity > 70
with time:
pink ()
cyan ()
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pink ()
cyan ()
?
?
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Gaussian Markov Network (intervention)
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Gaussian Markov Network (cont.)
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Future Goals
ExCytR: Excel + Cytoscape + R = Awesome
GUI for generating mapped networks
Devium -
Dynamic Multivariate Data Analysis and Visualization Platform
GUI for multivariate analysis of Omics data
Successor to imDEV
Fork me on GitHub: https://github.com/dgrapov/devium
The stack: