chapter 1 - fig. 1 The -omics subdisciplines. chapter 1 - fig. 2 Mechanism of transcriptional control by ppar agonists. 201 figures chapter 1
chapter 2 - fig. 1 Schematic overview of the different steps involved in dna-microarray based gene expression profiling studies. chapter 2 - fig. 2 Schematic overview of the different steps involved in nmr-based metabolomics studies. 202 evaluation of molecular profiling platforms in clinical pharmacology
chapter 2 - fig. 3 Overview of bioanalytical methods used for metabolomics studies. chapter 3 - fig. 1 Study design. This figure gives an overview of the study populations, different treatment periods (placebo run-in and active treatment period) and double blind placebo controlled randomized design of the study. Blood samples for biomarker assessments were collected on Visits 2 through 5. An oral glucose tolerance test (oggt) was performed at Visit 2 (baseline) and Visit 5 (end of the active treatment period). 203 f igu r e s chap t er 2 & chap t er 3
chapter 3 - fig. 2 Time profile of mean rsg plasma concentrations. This figure shows the mean rsg concentrations (ng/ml) at 3.5h and 10h (after first dose) and the mean trough levels at subsequent Visits. t2dm group: closed circles (+ sd); hvs group: open squares (+ sd). The virtually identical trough levels indicate equal rsg exposure in both study groups. 204 evaluation of molecular profiling platforms in clinical pharmacology
chapter 3 - fig. 3 Timing of treatment effects relative to placebo for selected markers (t2dm group only). The left figure shows the percentage change in time of plasma insulin and fasting plasma glucose (fpg) concentrations for rosiglitazone (rsg) vs. placebo treatment in the t2dm group. The right figure shows the plasma il-6 concentrations and wbc for rsg vs. placebo treatment in the t2dm group. Closed circle: fasting plasma glucose (fpg); open square: insulin; closed triangle: il-6; closed square: wbc. The bars indicate 95% confidence intervals. p 0.05; p 0.01. chapter 4 - fig. 1 Study design. Overview of the study populations, different treatment periods (placebo run-in and active treatment period) and double blind placebo controlled randomized design of the study. 205 f igu r e s chap t er 3 & chap t er 4
chapter 4 - fig. 2 Ex vivo mcp-1 and tnfα release at baseline. (a) Baseline mcp-1 release (pg/ml/x10e9/l wbc) in unstimulated, lps (5 ng/ml) and crp (10 µg/ml) stimulated whole-blood samples from type 2 Diabetes Mellitus (t2dm) patients and healthy volunteers (hvs). (b) Baseline tnfα release (pg/ml/x10e9/l wbc) in unstimulated, lps and crp stimulated whole-blood samples from t2dm patients and hvs. The bars represent the standard deviation. #: p<0.05 vs. unstimulated concentration within the same group (anova; log transformed data). a b 206 evaluation of molecular profiling platforms in clinical pharmacology
chapter 4 - fig. 3 Treatment effects on whole blood mcp-1 release. (a) mcp-1 release (pg/ml/x10e9/l wbc) at baseline and after 3 weeks of treatment with ciprofibrate or placebo in the t2dm group. (b) mcp-1 release (pg/ml/x10e9/l wbc) at baseline and after 3 weeks of treatment with ciprofibrate or placebo in the healthy volunteers group. The bars represent the standard deviation. *: p<0.05 vs. placebo and corrected for baseline differences (ancova mixed model; log-transformed data). **: p<0.01 vs. placebo and corrected for baseline differences (ancova mixed model; log-transformed data). a b 207 figures chapter 4
chapter 5 - fig. 1 Flow-chart of sample processing and analysis. 208 evaluation of molecular profiling platforms in clinical pharmacology
chapter 5 - fig. 2 Example of agarose gel electrophoresis of rna extracted from one blood sample. The intensity of 28S ribosomal rna band is approximately twice that of the 18S rna band, indicating integrity of the rna. chapter 5 - fig. 3 Dynamic range. Dynamic range of gene expression intensities in leukocytes and tissue samples, including three samples (in red) identified as putative outliers. 209 figures chapter 5
chapter 5 - fig. 4 Scatter plots and concordance correlations scheme of gene expression intensities among white blood cell samples. Samples 8941 and 8942 (in red) are identified as putative outliers. chapter 5 - fig. 5 Scatter plots and concordance correlations scheme of gene expression intensities among adipose tissue samples. Sample 9803 (in red) is identified as putative outlier. 210 evaluation of molecular profiling platforms in clinical pharmacology
chapter 5 - fig. 6 Clustering on 36 samples reveals 4 spurious samples. Gene number (at least 2 fold change in one sample and geo-mean): 4303. Two fat samples and two blood samples are clustered with muscle samples chapter 5 - fig. 7 Clustering on the remaining 32 samples after excluding 4 spurious samples. Gene umber (at least 2-fold change in one sample and geo-mean): 3709. 211 figures chapter 5
chapter 6 - fig. 1 Study design. Overview of the study populations, treatment periods (placebo run-in and active treatment period) and double blind placebo controlled randomized design of the study. Skeletal muscle and adipose tissue samples for global gene expression analyses were collected at baseline, and on Visit 3 and Visit 5. Blood samples for pbls gene expression analyses were collected on Visits 1 through 5. Additional blood samples (3.5 and 10 hr post-dose) to assess direct treatment effects on global pbls gene expression profiles were collected on Visit 2. 212 evaluation of molecular profiling platforms in clinical pharmacology
chapter 6 - fig. 2 Variance attributable to different factors in anova. Panels a and b exhibit variances in variance stabilizing transformation (vst) intensities explained by various factors in adipose and muscle tissues at baseline. Panels c and d illustrate variances in delta of intensities explained by various factors in adipose and muscle tissues post 2 week treatment. In each panel, x axis is the average of vst intensity, y axis is the mean square to measure the variance in vst intensity (a and b) or in delta of intensity (c and d). Every curve in each panel depicts a relationship between a variance explained by a particular factor or interaction of several factors and the average of vst intensity. Each curve was generated using smooth spline function in S-Plus (Insightful Corp. 03). T: treatment; D: disease; S: sex; X:Y : interaction of X and Y. 213 figures chapter 6
chapter 6 - fig. 3a Exploratory gene network analysis of differentially expressed genes for disease state in adipose tissue. Ingenuity Pathway Analysis (ipa) identified 2 gene networks, entirely composed of Focus Genes, with the top score of 59 for disease state within the adipose tissue dataset (Fisher s exact test). A central component of gene network 1 (a) is the gene encoding the pro-inflammatory cytokine tnfα, which has been recognized as an important negative regulator of molecular insulin action. Gene network 2 (b) includes the gene encoding the transcription factor pparγ, which activation is associated with improvements in insulin sensitivity. The yellow boxes indicate (a selection of) canonical pathways identified within each gene network. Symbols used in gene networks are explained the general ipa legend. Adipose tissue Network 1 214 evaluation of molecular profiling platforms in clinical pharmacology
chapter 6 - fig. 3b Adipose tissue Network 2 215 figures chapter 6
chapter 6 - fig. 4 Exploratory gene network analysis of differentially expressed genes for disease state in skeletal muscle tissue. Ingenuity Pathway Analysis (ipa) identified 1 gene network with the top score of 26 for disease state within the skeletal muscle dataset (Fisher s exact test). Symbols used in gene networks are explained in the general ipa legend. Muscle Network 1 216 evaluation of molecular profiling platforms in clinical pharmacology
chapter 6 - fig 5 Top 10 canonical pathways identified in adipose and skeletal muscle tissue. This figure shows the top 10 canonical pathways identified within all networks constructed from the top 200 and top 100 of focus genes for disease state in the adipose tissue (a), and skeletal muscle dataset (b), respectively. The number of focus genes differentially expressed between t2dm and hvs was insufficient for a meaningful pathway analysis of pbls using Ingenuity Pathway Analysis. a b chapter 6 - fig. 6 General legend Ingenuity Pathway Analysis. This legend provides a key of the main features of Network Explorer and Canonical Pathways, including node shapes and colours as well as edge labels and types. Bold: Focus Genes. Gene identifiers that made the userdefined cut-off and map to the Global Molecular Network are displayed with bold text. *: Duplicate. User input gene that had duplicate identifiers in the dataset file mapping to a single gene in the Ingenuity Pathway Knowledge Base. +: Indicates there are other networks from the analysis that contain this gene. Node colour intensity: All Focus Gene nodes are red by default; and higher colour intensity represents a lower (and thus more significant) p-value. 217 figures chapter 6
chapter 7 - fig. 1 Study design. Overview of the study populations, different treatment periods (placebo run-in and active treatment period) and double blind placebo controlled randomized design of the study. Skeletal muscle and adipose tissue samples for global gene expression analyses were collected at baseline, and at Visit 5. Blood samples for pbls gene expression analyses were collected on Visits 1 through 5. Additional blood samples (1, 3, 6 and 10 hrs post-dose) to assess immediate ( acute ) treatment effects on global pbls gene expression profiles were collected at Visit 2. chapter 7 - fig. 2a Exploratory gene network analysis of differentially expressed genes for disease state in adipose tissue. Adipose tissue Network 1 218 evaluation of molecular profiling platforms in clinical pharmacology
chapter 7 - fig. 2b Exploratory gene network analysis of differentially expressed genes for disease state in adipose tissue. Ingenuity Pathway Analysis (ipa) identified 2 gene networks, entirely composed of focus genes, with a top score of 59 for disease state within the adipose tissue dataset (Fisher s exact test). A central component of gene network 1 (a) is the gene encoding the chemokine il1β (interleukin 1-beta), which is a component of the ppar signalling pathway and believed to be an important negative modulator of insulin signalling. Gene network 2 (b) includes the gene encoding the transcription factor pparγ, which activation is associated with improvements in insulin sensitivity. The yellow boxes indicate a selection of canonical pathways identified within each gene network. Symbols used in gene networks are explained in the general ipa legend (figure 5). Adipose tissue Network 2 219 figures chapter 7
chapter 7 - fig. 3 Exploratory gene network analysis of differentially expressed genes for disease state in skeletal muscle tissue. Ingenuity Pathway Analysis (ipa) identified 1 gene network, entirely composed of focus genes, with a top score of 59 for disease state within the skeletal muscle dataset (Fisher s exact test). Muscle Network 1 220 evaluation of molecular profiling platforms in clinical pharmacology
chapter 7 - fig. 4 Differentially expressed canonical pathways in skeletal muscle and adipose tissue. Results of global pathway analysis which shows the top 15 putative disease related canonical pathways in the adipose tissue (a) and skeletal muscle (b) data sets. The number of focus genes differentially expressed between t2dm and hvs in pbls at baseline was insufficient for a meaningful pathway analysis. a b chapter 7 - fig. 5 General legend Ingenuity Pathway Analysis. This legend provides a key of the main features of Network Explorer and Canonical Pathways, including node shapes and colours as well as edge labels and types. Bold: Focus genes. Gene identifiers that made the userdefined cut-off and map to the Global Molecular Network are displayed with bold text. *: Duplicate. User input gene that had duplicate identifiers in the dataset file mapping to a single gene in the Ingenuity Pathway Knowledge Base. +: Indicates there are other networks from the analysis that contain this gene. Node colour intensity: All Focus Gene nodes are red by default; and higher colour intensity represents a lower (and thus more significant) p-value. 221 figures chapter 7
chapter 8 - fig. 1 Study design. Overview of the study populations, placebo run-in and active treatment period, and double blind placebo controlled randomized design of the study. Urine and blood plasma samples for ¹h nmr spectroscopic analysis were collected on Visits 1, 2, 3 and 5. chapter 8 - fig. 2 nmr spectra. Typical 600 MHz ¹h nmr Spectra (δ0.0-4.5) of urine (left) and blood plasma (right) from a (randomly chosen) healthy male subject (a), and diabetic male subject (b) both at Visit 1 of the study. The spectra illustrated, are scaled to the same signal to noise ratio in order to highlight the differences in typical glucose and lipid resonance intensities. 222 evaluation of molecular profiling platforms in clinical pharmacology
chapter 8 - fig. 3 Results of Supervised Principal Component Discriminant Analysis (pc-da) on plasma samples from run-in Visits (Visits 1 and 2). A good distinction between diabetic patients and healthy volunteers as well as separation by gender is accomplished when the glucose resonances are included in the analysis (a). The separation of the different groups is less pronounced but still clearly visible when the glucose resonances are excluded from the analysis (b). a b 223 figures chapter 8
224 evaluation of molecular profiling platforms in clinical pharmacology chapter 8 - fig.4 Results of Supervised Principal Component Discriminant Analysis (pc-da) on urine samples from Visits 1 and 2 (excluding glucose resonances). A clear separation between diabetic patients and healthy volunteers can be made in the first discriminant axis (D-1), and although not illustrated here, the third discriminant axis shows a clear separation between the female and male diabetic samples resulting in four well separated clusters in the data. chapter 8 - fig. 5 Results of Supervised Principal Component Discriminant Analysis (pc-da) from urine collected from t2dm patients (pooled for male and female samples) classified according to treatment regime, excluding glucose resonances. The first discriminant axis (d-1) appears to show the effect on treatment-related markers, whilst the second discriminant axis (d-2) appears to show a treatment-independent effect on metabolic markers.
chapter 8 - fig. 6 Factor spectrum corresponding to the first discriminant axis (d-1) in Figure 5. In this plot the variables contributing to the first discriminant are expressed as correlation coefficients. A high positive peak (correlation) belongs to a corresponding peak in the nmr spectrum of a metabolite that has a relative high concentration in the t2dm placebo-treated group, and a relative low concentration in the t2dm rsg-treated group. Similarly, a high negative peak belongs to a corresponding peak in the nmr spectrum of a metabolite that has a relative high concentration in the t2dm rsg-treated group and a relative low concentration in the t2dm placebo-treated group. As such the figure shows the urinary metabolites that appear to alter with the rsg-treatment regime relative to placebo. Subsequent interpretation of the peaks with distinctive ¹h nmr signatures showed that rsg-treatment appears to induce a decrease in hippurate and a further increase in aromatic amino acids. 225 figures chapter 8
chapter 9 - fig. 1 Typical 600 MHz urine spectrum of urine from a healthy male volunteer at the first office Visit. The bottom spectrum shows all the peaks to scale and the top spectrum is an eight-fold vertical expansion of the bottom spectrum. Abbreviations: ac: acetate; cr: creatinine; dma: dimethylamine; h: hippurate; sw: suppressed water; t: trimethylamine-n-oxide; tsp 3-trimethylsilylpropionic-(2,2,3,3-d ₄ )-acid. chapter 9 - fig. 2 Scores plot of urinary samples from Visits 1-6. 226 evaluation of molecular profiling platforms in clinical pharmacology
chapter 9 - fig. 3 pls-da three-dimensional score plot of urinary samples from male volunteers. The symbols represent the different classes: plus sign: healthy/ciprofibrate-treated; wedge: healthy/placebo-treated; cube: diabetic/ciprofibrate-treated and sphere: diabetic/ placebo-treated. chapter 9 - fig. 4 pls-da three-dimensional score plot of urinary samples from female volunteers. The symbols represent the different classes: plus sign: healthy/ciprofibrate-treated; wedge: healthy/placebo-treated; cube: diabetic/ciprofibrate-treated and sphere: diabetic/ placebo-treated. 227 figures chapter 9
228 evaluation of molecular profiling platforms in clinical pharmacology chapter 9 - fig. 5 Contribution plot showing the buckets that differentiate urinary samples of placebo-treated, healthy males (top) with those from ciprofibrate-treated, healthy males. Some bucket identifications are: glycine (3.58) and trimethylamine (2.86). chapter 9 - fig. 6 Contribution plot showing the buckets that differentiate urinary samples of placebo-treated, healthy females (top) with those from ciprofibrate-treated, healthy females. Bucket 1.94 is acetate.
chapter 9 - fig. 7 Contribution plot showing the buckets that differentiate urinary samples from placebotreated, diabetic males (top) with those from ciprofibrate-treated, diabetic males. Bucket 2.34 is acetoacetate. chapter 9 - fig. 8 Contribution plot showing the buckets that differentiate urinary samples from placebotreated, diabetic females (top) with those from ciprofibrate-treated, diabetic females. Bucket 2.86 is trimethylamine. 229 figures chapter 9
230 evaluation of molecular profiling platforms in clinical pharmacology chapter 9 - fig. 9 Contribution plot showing the buckets that differentiate urinary samples from placebotreated, healthy males (top) with those from placebo-treated, diabetic males. Some bucket identifications are: N-methylnicotinate (8.86, 8.82, 4.46) and citrate (2.7, 2.66, 2.54). chapter 9 - fig. 10 Contribution plot showing the buckets that differentiate urinary samples from placebotreated, healthy females (top) with those from placebo-treated, diabetic females. Bucket 4.06 is creatinine.