PRECLINOMICS: ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES

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1 4 PRECLINOMICS: ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES Wu-Kuang Yeh and Richard G. Peterson PreClinOmics, Inc., Indianapolis, Indiana I. INTRODUCTION The continuous improvement of human health and quality of life can be linked directly to discovery, development, manufacture, and applications of pharmaceutical agents. Though many drugs for some human diseases are available, there are still numerous unmet medical needs, providing plenty of career opportunities to researchers in the pharmaceutical and biotech industry. Drug discovery is a high-risk and potentially high-reward endeavor, costing approximately one billion US dollars in recent years for a new drug to reach the market place [1 3]. For a drug to reach patients, from a business perspective, it involves successive progression from discovery to development to commercialization. As a scientific endeavor, preclinical drug discovery programs focus on the identification of new chemical entities as drug candidates to enter clinical trials. Preclinical enzyme technologies are broadly defined in this chapter as those in vitro, in vivo, and ex vivo assays conducted prior to clinical trials. These enzyme technologies are applied in a variety of interdisciplinary fields including efficacy, pharmacokinetics and pharmacodynamics, toxicology, biomarkers, and computer-assisted structure activity-based designs. For all of these preclinical enzyme technologies, many enzyme assays and Enzyme Technologies: Pluripotent Players in Discovering Therapeutic Agents, First Edition. Edited by Hsiu-Chiung Yang, Wu-Kuang Yeh, and James R. McCarthy. 214 John Wiley & Sons, Inc. Published 214 by John Wiley & Sons, Inc. 131

2 132 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES animal models, especially small animals such as mice and rats, play critical roles in drug discovery and development. After the introduction, the next section describes different types of enzyme assays to evaluate drug targets as well as to measure efficacy end points and biomarkers. Not as an extensive literature review, this section focuses on evolving enzyme assays from direct experience by the authors, particularly on applying enzyme assays to metabolic diseases. Section III involves development of a rat model for drug discovery related to diabetes, metabolic syndrome, and obesity. For this volume on Enzyme Technologies, as an extension of enzyme assays, the authors consider a rat or mouse model as a complex and integrative enzyme system commonly used for preclinical drug discovery and development. Such consideration is based on the biochemical understanding that enzymes are involved in metabolism, both biosynthesis and degradation, of all essential components in human and animals, including DNA, RNA, proteins, peptides/hormones, lipids, and carbohydrates. Section IV briefly describes testing of current antidiabetic and anti-obesity drugs. Using common enzyme assays and commercially available mouse and rat models, the fifth section provides one case study using control compounds in antidiabetic and anti-obesity drug discovery. Another case study in the sixth section describes similar enzyme and rodent model applications for a diabetic efficacy of a nutritional supplement in combination with an existing antidiabetic drug. The sixth section also describes a serendipitous case of testing the same supplement with a terminal cancer patient. This chapter should be informative to the readers in understanding the critical roles of the enzyme assays and rodent models used in drug discovery for metabolic diseases. Readers will recognize that many of the preclinical enzyme assays are also applicable for clinical trials and in fact for monitoring human health. II. EVOLVING ENZYME ASSAYS Enzyme assays have been evolving from academic to industrial applications, though overlapping in time and use. They play a significant role in advancing metabolic disciplines from metabolic evolution [4,5] to metabolic engineering [6] and combinatorial biosynthesis [7] and to metabolic diseases [8]. Enzymes are typically proteins that catalyze biological reactions. In addition to typical enzymes, there are also RNA biocatalysts and catalytic antibodies. In this chapter, the authors focus on protein biocatalysts for biotech and pharmaceutical applications. Enzyme assays have been evolving based on their experimental applications. One type of early enzyme assay involves measuring an enzymatic product by the optical density at wavelength corresponding to maximal absorbance. As a common example, the activity of lactic dehydrogenase was measured by the optical density at 34 nm which corresponds to the disappearance of NADH to NAD. This assay was developed over 6 years ago using a Beckman spectrophotometer [9]. Similarly, the activity of catechol 1,2-oxygenase was determined by the accumulation of its reaction product, cis,cis-muconate, quantitated by the optical density at 26 nm using a Gilford spectrophotometer over 4 years ago [1]. For measuring enzymatic product directly and for improving the sample throughput, several new formats of enzyme assay have been developed in the last several decades for drug discovery and

3 EVOLVING ENZYME ASSAYS 133 development including HPLC, LC/MS, and fluorescence and luminescence coupled with micro-plate technology. Two HPLC-based enzyme assays are summarized in the following text to illustrate important metabolic engineering applications. As one early antibiotic development application, the activity of macrocin O-methyltransferase was measured by formation of its reaction product, tylosin, by HPLC [11]. The HPLC assay was used to purify the enzyme and characterize its kinetic mechanism [12]. The insertion of one extra copy of the gene for this enzyme to the chromosome of the industrial strain of Streptomyces fradiae by reverse engineering resulted in a significant improvement in the yield of tylosin [13]. Similarly, in another early antibiotic development application, the activity of deacetoxycephalosporin synthase (expandase) was measured also by the formation of its reaction product, deacetoxycephalosporin C, by HPLC. Using the HPLC assay, the expandase was purified and characterized [14]. One copy of the gene for the enzyme was inserted back to the chromosome of Cephalosporium acremonium, and such extra gene copy insertion led to a significant yield improvement of cephalosporin C [15]. Different types of enzyme assays are described in the following section for preclinical drug discovery in metabolic diseases [8], broadly defined as those related to abnormal and pathological metabolism. A. Enzymes as Drug Targets Numerous enzymes are potentially direct targets for drug discovery. Two such enzymes and their assays are summarized in the following text. b-secretase One of the leading hypotheses for the pathogenesis of Alzheimer s disease is the accumulation and aggregation of β-amyloid peptides in the brain, especially in the hippocampal and cortical regions. Two proteases, β-secretase (also known as BACE1, memapsin 2) and γ-secretase [16], catalyze the sequential cleavages of β-amyloid precursor protein to generate β-amyloid peptide. These two proteases have been targeted in the last two decades for the treatment of Alzheimer s disease, a metabolic disorder. For β-secretase, at least one inhibitor has been tested in clinical trials [16]. To measure β-secretase activity, one common micro-plate assay monitors the cleaved peptide product by fluorescence resonance energy transfer (FRET, [17]). Application of FRET assay confirmed the same major cleavage site for mouse and human substrates by both mouse and human β-secretases, thus suggesting the usefulness of APP transgenic mouse models in the development of BACE inhibitors for the treatment of Alzheimer s disease [17]. 11b-Hydroxysteroid Dehydrogenase Type 1 In the last decade, 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), catalyzing interconversion of cortisone to cortisol, has become an important drug target for inhibitor discovery in diabetes, metabolic syndrome, obesity, and related complications such as retinopathy, nephropathy, and cognition impairment [18]. Cortisol, glucocorticoid dihydrocorticosterone, is one major stress hormone for human. Thus, lowering its level through inhibition of 11β-HSD1 has the potential to prevent metabolic diseases and their associated symptoms. Cortisol plays a regulatory role by increasing pyruvate enol phosphate carboxykinase and glucose

4 134 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES 6-phosphatase, thus leading to more glucose production [19]. Multiple assay types, including radioactive and nonradioactive formats, have been used in basic research and drug discovery for this enzyme. To minimize the use of radioactive material and maintain high throughput, biotech and pharmaceutical researchers have used HPLC, LC/MS, and fluorescence [2 22] coupled with micro-plate technology for 11β-HSD1 assay applications. Several inhibitors for 11β-HSD1 have been advanced to clinical testing for several therapeutic indications [22,23]. B. Enzymes as Biocatalysts For drug discovery and development in metabolic diseases, enzymes can be used as biocatalysts in the assays. Table 1 lists selective enzyme assays, with enzymes as biocatalysts for gluconeogenesis, lipid metabolism, liver toxicity, and urine metabolic biomarkers. Enzyme and Immunological-Colorimetric Assays for Gluconeogenesis As the major disease biomarker for diabetes, glucose is measured by enzyme-catalyzed NADH formation (Scheme 1), typically using a clinical analyzer or a glucometer. Glucose is determined from blood, plasma, or urine. Hemoglobin A1C (HbA1c) is another common disease biomarker for diabetes. HbA1c has a longer half-life than glucose. The serum level of HbA1c is determined by the amount of HbA1c TABLE 1 Selective Enzyme Assays: Enzymes as Biocatalysts Enzyme assay Enzymes a as biocatalysts Assay kit sources Gluconeogenesis Glucose Hexokinase and G-6-P DH Beckman Lipid metabolism TG GK, GPO, and catalase (Step 1) Wako LPL, GK, GPO, and peroxidase Beckman and Wako (Step 2) Total CHOL CE, CO, and peroxidase Beckman and Wako HDL CHOL CE and peroxidase Beckman LDL CHOL CE, CO, and peroxidase Beckman Free fatty acids ACS, ACOD, and peroxidase Wako Glycerol GK, GPO, and peroxidase Zen-Bio Ketone bodies 3-HBDH and diaphorase Cayman Liver toxicity AST AST and MDH Beckman ALT ALT and LDH Beckman Urine metabolic biomarkers BUN Urease and GLDH Beckman Uric acid Uricase and peroxidase Beckman HDL, high-density lipoprotein; LDL, low-density lipoprotein; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BUN, blood urea nitrogen. a See SCHEMES 1, 2 and 3 for the enzyme abbreviations. GLDH, glutamate dehydrogenase; 3-HBDH, 3-hydroxybutyrate dehydrogenase.

5 EVOLVING ENZYME ASSAYS 135 using an immunoassay divided by the amount of total hemoglobin using a colorimetric method with a clinical analyzer, for example, from Beckman Coulter. Glucose + ATP Hexokinase G-6-P + ADP G-6-P + NAD + G-6-PDH 6-PG + NADH + H + G-6-P, Glucose-6-Phosphate G-6-PDH, Glucose-6-Phosphate Dehydrogenase 6-PG, 6-Phosphogluconate SCHEME 1 Enzymatic assay for glucose. Enzyme Assays for Lipid Metabolism Fat overload is one major hypothesis for insulin resistance and diabetes [24]. A few common lipids are used as indicators for rodent studies in drug discovery for diabetes, metabolic syndrome, and obesity. Triglycerides (TG), total cholesterol (CHOL), and free fatty acids are among the most frequently used lipid end points in rodent studies. Using enzyme- catalyzed reactions, TG (Scheme 2a, Step 2 for producing the red dye only) and total CHOL (Scheme 2b) from plasma are commonly analyzed by a clinical analyzer. Total CHOL from the liver and muscle can be determined using their homogenates with a clinical analyzer or a micro-plate reader, whereas TG can be determined from the homogenates using a micro-plate reader (Scheme 2a, Step 1 and Step 2 for producing the blue pigment) [25]. Similarly, free fatty acids from plasma, following three-step enzyme reactions (Scheme 2c), are measured with a micro-plate reader. (a) Triglycerides Step 1: Color A Reagent for Decomposing Free Glycerol in Sample Free Glycerol + ATP GK Glycerol-3-Phosphate + ADP Glycerol-3-Phosphate + O 2 GPO Dihydroacetone phosphate + H 2 O 2 2H 2 O 2 Catalase O 2 +H 2 O GK, Glycerol Kinase GPO, Glycerol-3-Phosphate Oxidase Step 2: Color B Reagent for Converting Triglyceride to Blue Pigment Triglyceride + 3H 2 O LPL Glycerol + 3Fatty Acids Glycerol + ATP GK Glycerol-3-Phosphate + ADP Glycerol-3-Phosphate + O 2 GPO Dihydroacetone phosphate + H 2 O 2 2H 2 O Aminoantipyrine + HMMPS Peroxidase Blue Pigment Or, H 2 O Aminoantipyrine + DHBS Peroxidase Red Dye LPL, Lipoprotein Lipase HMMPS, N-(3-sulfopropyl)-3-methoxy-5-methylaniline DHBS, 3,5-dichloro-2-hydroxybenzenesulfonic acid SCHEME 2 Enzymatic assays for (a) triglycerides, (b) total cholesterol, and (c) nonesterified free fatty acids.

6 136 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (b) Total Cholesterol Cholesterol Ester CE Cholesterol + Fatty Acid Cholesterol + O 2 CO Cholesterol-3-one + H 2 O 2 2H 2 O AAP + Phenol Peroxidase Quinoneimine + H 2 O CE, Cholesterol Esterase CO, Cholesterol Oxidase 4-AAP, 4-Aminoantipyrine (c) Free Fatty Acids Fatty Acid + CoA ACS Acyl-CoA Acyl-CoA + O 2 ACOD Oxidized Acyl-CoA + H 2 O 2 H 2 O AAP + MEFA Peroxidase Purple Adduct CoA, Coenzyme A ACS, Acyl-CoA Synthetase ACOD, Acyl-CoA Oxidase 4-AAP, 4-Aminoantipyrine MEFA, 3-Methyl-N-Ethyl-N(β-Hydroxyethyl)-Aniline SCHEME 2 (Continued ). Enzyme Assays for Liver Toxicity Biomarkers Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are enzymes that serve as common indicators of liver toxicity in rodent studies. Scheme 3 shows the two-step enzymatic reaction schemes of ALT and AST, the second step of each is converting NADH to NAD, resulting in a change in the optical density at 34 nm that is measured by a clinical analyzer. (a) AST L-Aspartate + α-ketoglutarate AST Oxaloacetate + L-Glutamate Oxaloacetate + NADH + H + MDH Malate + NAD + AST, Aspartate Aminotransferase MDH, Malate Dehydrogenase (b) ALT L-Alanine + α-ketoglutarate ALT Pyruvate + L-Glutamate Pyruvate + NADH + H + LDH Malate + NAD + ALT, Alanine Aminotransferase LDH, Lactate Dehydrogenase SCHEME 3 Enzymatic assays for (a) AST and (b) ALT.

7 EVOLVING ENZYME ASSAYS 137 C. Enzymes as Reporters The principle of a regular micro-plate ELISA involves binding of a peptide analyte to a polystyrene plate-coated specific antibody and reporting of the bound analyte by detecting antibody conjugated with an enzyme, typically horseradish peroxidase (HRP) or alkaline phosphatase (AP). In competitive micro-plate immunoassays, the small molecule or peptide/protein analyte competes with the tracer which is the same molecular entity conjugated with fluorescent dye or radioactive nuclei (as in EIA or RIA) for binding to a specific antibody pre-coated on the polystyrene micro-plate or beads. Table 2 lists selective analytes by both modes of micro-plate immunoassays for antidiabetic and anti-obesity drug discovery. Enzyme Assays for Metabolic Biomarkers Insulin and glucose have been the most frequently used indicators for diabetic drug discovery in vivo and in vitro. Insulin is measured by micro-plate ELISA, using a specific antibody against insulin coated on a micro-plate and a reporting antibody conjugated with HRP that catalyzes the conversion of a substrate TMB to a yellow product measured by the optical density at 45 nm (Scheme 4). Since obesity contributes significantly to the development of diabetes [24], leptin, linked to obesity, is also a frequently used biomarker for diabetic and obesity drug discovery and can be similarly analyzed by micro-plate ELISA. Mouse Monoclonal Anti-Insulin Coated Plate Insulin (Human, Rat or Mouse) from Plasma Sample Peroxidase-Conjugated Mouse Anti-Insulin Substrate TMB Yellow Color (45 nm) TMB, Trimethylbenzene SCHEME 4 Insulin assay, enzyme (peroxidase) as reporter. Enzyme Assays for Inflammation Biomarkers As an alternative hypothesis to fat overload, inflammation has also gained significance for insulin resistance and diabetes [24]. Many inflammation biomarkers have been used in early drug discovery for metabolic diseases; a few specific biomarkers such as IL-1β, IL-6, MCP- 1, and TNFα are among the most frequently used indicators for rodent studies in diabetes, obesity, and cardiovascular diseases and can be analyzed by micro-plate immunoassays. Multiplexing Enzyme Assays (Luminex) Micro-plate enzyme assay technology, typically 96-, 384-, or 1536-well plates, has significantly improved assay throughput for drug discovery. To further increase the assay throughput, in addition to micro-plate ELISA, Luminex is another micro-plate assay technology using coded beads allowing multiple assays for up to approximately 1 analytes to be run simultaneously from the same sample [26]. Luminex has become a popular choice for multiplexing assays

8 138 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES TABLE 2 Selective Enzyme Assays: Enzyme (Peroxidase) as Reporter Using Microplate/ELISA (Regular or Competitive Mode) ELISA Mode Assay kit sources Insulin Regular ALPCO Leptin Regular ALPCO GLP-1 Regular ALPCO GIP Regular Millipore Adiponectin Regular ALPCO PYY Regular ALPCO and Millipore Ghrelin Regular ALPCO and Millipore Micro-albumin Competitive ALPCO and Exocell Epinephrine Competitive ALPCO Norepinephrine Competitive ALPCO Corticosterone Competitive Cayman Angiotensin I and II Regular Phoenix IL-1β Regular ALPCO IL-6 Regular ALPCO MCP-1 Regular ALPCO C peptide Regular ALPCO and Millipore GLP-1, glucagon-like protein 1; GIP, gastric inhibitory polypeptide; PYY, peptide YY; MCP-1, monocyte chemotactic protein-1. Regular, signal is proportional to concentration of analyte in sample; competitive, signal is inversely proportional to concentration of analyte in sample. TABLE 3 Selective Enzyme Assays: Enzyme (Peroxidase) as Reporter Using Luminex Multiplexing 2-Plex 5-Plex 7-Plex (A) 7-Plex (B) Insulin Insulin Insulin Insulin GLP-1 Leptin Leptin Amylin GIP IL-6 IL-1β Leptin GLP-1 TNFα IL-6 Ghrelin MCP-1 Resistin MCP-1 GIP TNFa PAI-1 PYY TNFα PP Luminex (Austin, Texas). Commercial kits from Millipore (St. Louis, Missouri). See Tables 2 and 4 for the analyte abbreviations. in the last decade. Table 3 lists commonly used metabolic and inflammatory biomarkers analyzed by Luminex multiplexing. Nonenzymatic Immunoassays To improve assay dynamic range and sensitivity, the nonenzymatic immunoassays from MSD have gained significant bio-analytical popularity in the last several years. MSD is based on the signal from electrochemiluminescence [27]. Its major advantage over Luminex is better sensitivity, wider

9 DEVELOPING NEW RAT MODEL FOR METABOLIC DISEASES 139 dynamic range, and higher reproducibility most noticeably for GLP-1 (total and active) or insulin. However, the flexibility of multiplexing is not as great as compared to Luminex technology. III. DEVELOPING NEW RAT MODEL FOR METABOLIC DISEASES Metabolic diseases are broadly defined as pathological conditions caused by dysregulation of metabolic processes. They are commonly recognized as diabetes, metabolic syndrome, obesity, cardiovascular diseases, and diabetic complications. Together, they negatively affect the quality of life for about half of adult human population from the developed countries. It is imperative, for drug discovery, that developing and applying rodent models mimicking human conditions are required. We summarize here our development of the ZDSD rat, a new rat model for diabetes, metabolic syndrome, and obesity, without leptin and leptin receptor mutations. Currently, the ZDF rat, with a leptin receptor mutation, has been extensively used as a common preclinical animal model for antidiabetic drug discovery [28]. A. Breeding, Spontaneous Diabetic Development, and Characterization The ZDSD rat was developed by crossing a homozygous lean ZDF rat, expressing β-cell failure with the fa/fa genotype, with a diet-induced obese (DIO) Sprague Dawley (SD) rat, exhibiting insulin resistance and polygenic obesity [29]. Rat selection from breeding was based on major characteristics for diabetes and obesity. Spontaneous hyperglycemia of male ZDSD rats occurs with an age range of weeks (Fig. 1a). Insulin increases continuously until these rats become overtly diabetic and then drops gradually to the prediabetic level (Fig. 1b). The ZDSD rats, heavier than the ZDF rats, also have high TG and CHOL (Fig. 2). Food intake of the ZDSD rats is reduced in response to leptin, indicating a functional leptin pathway (Fig. 3). Such diabetic and obese characteristics as well as absence of a leptin or leptin receptor mutation render the ZDSD rats highly appropriate for preclinical rodent studies in diabetes, metabolic syndrome, and obesity. Evaluation of the ZDSD rats with current antidiabetic and anti-obesity drugs are described in Section IV. B. Diet-Induced Diabetes and Obesity The male ZDSD rats that have not become diabetic spontaneously within weeks old can be induced to diabetic level by providing a high-fat diet for 2 weeks (Fig. 4, [29]). Such hyperglycemic synchronization allows the ZDSD rats to be used in more predictable and practical durations in antidiabetic drug discovery. C. Determining Insulin Sensitivity Development of diabetes may be preceded by insulin resistance, glucose intolerance, hyperlipidemia, and hypertension. Testing insulin sensitivity is an important aspect of preclinical antidiabetic drug discovery. In comparison to the Zucker fatty

10 14 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) 6 PCO ZDSD rats: Glucose 5 Glucose (mg/dl) Weeks 19 Weeks Weeks (b) Insulin (ng/ml) PCO ZDSD rats: Insulin Age (Week) Weeks 15 Weeks 17 Weeks Age (Week) FIGURE 1 ZDSD rats: spontaneous diabetic development. Glucose (a) and insulin (b) were monitored for ZDSD male rats that became diabetic, using three different age ranges. (See insert for color representation of the figure.) (ZF) rats, the rat standard for testing insulin sensitivity, the ZDSD rats show a similar insulin resistance. With treatment by rosiglitazone, there is a significant improvement in insulin sensitivity for the ZDSD rats though less than that for the ZF rats (Fig. 5, [29]). When compared to the SD rats, the male ZDSD rats demonstrated age-dependent impaired glucose tolerance (Fig. 6, [3]). Thus, the ZDSD rats, with less fat content than the ZF rats (data not shown), appear to be an excellent

11 DEVELOPING NEW RAT MODEL FOR METABOLIC DISEASES PCO ZDSD rats: Analytes (Age 3~33 weeks old) Analytes (mg/dl) ZDF fa/fa CRL-SD (CD) ZDF +/fa ZDSD, Diabetic 7 11 Weeks ZDSD, Diabetic Weeks Glucose TG CHOL FIGURE 2 ZDSD rats: spontaneous diabetic development. Glucose, TG, and total CHOL were determined for five different 3 33-week-old rat models: ZDF fa/fa, CRL-SD (CD), ZDF + /fa, ZDSD diabetic from 7 11 weeks, and ZDSD diabetic from weeks. For statistical analysis of this and following studies, as specified, t-test from GraphPad Prism 5 was used. ZDF and ZDSD diabetic from 7 11 weeks and from weeks were analyzed with CRL-SD (CD) and ZDF + /fa; P <.1 for glucose. Similarly for TG, P values are <.1 with ZDF, =.14 and =.73 with ZDSD diabetic 7 11 weeks, and =.9 and =.75 with ZDSD diabetic weeks. For total CHOL, P values are <.1 with ZDF, <.1 and =.3 with ZDSD diabetic 7 11 weeks, and =.12 and =.32 with ZDSD diabetic weeks. (See insert for color representation of the figure.) alternative rat model in testing compounds for improving insulin sensitivity and glucose tolerance. D. Identifying Biomarkers of Metabolic Diseases Using Luminex multiplexing assays, collaboration between PreClinOmics (PCO) (Indianapolis, Indiana) and Rules-Based Medicine (Austin, Texas), the ZDSD rat has been shown as a highly useful model for multiple biomarkers in metabolic, renal, coagulation, and vascular diseases as well as for inflammation. Examples of these plasma biomarkers from an initial identification are shown in Table 4 [29].

12 142 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES 1 Leptin physiology Food Intake (g/4-h) SD-Sal SD-Lep ZDSD-Sal ZDSD-Lep Test article; IP FIGURE 3 ZDSD rats: leptin physiology. Assessment of leptin pathway function was determined by feeding response to leptin injection. ZDSD rats of 15 weeks old and SD rats of 17 weeks old, n = 9, were dosed with leptin, 1 mg/kg intraperitoneally (IP), just before starting the dark cycle, and food intake was measured for the first 4 dark hours. Sal: saline; Lep: leptin. The food intake of this study was analyzed by t-test; in comparison to the saline group, P =.196 for SD-Lep and P =.46 for ZDSD-Lep. (See insert for color representation of the figure.) 6 Synchronization of diabetic onset Glucose (mg/dl) Age (Week) ZDSD male rats ZDSD female rats SD male rats FIGURE 4 ZDSD rats: diet-induced diabetic synchronization. The ZDSD male rats, n = 12, can be placed on either D12468 (Research Diets) or 5SCA (LabDiet) at 17 weeks of age to synchronize the onset of diabetes. Two-way ANOVA from GraphPad Prism 5 was used in statistical analysis of this and following studies, as specified. Each P value is from interaction of column (effect) factor and row (time) factor, unless specified (i.e., from column factor only); in comparison to SD male rats, for analysis of glucose, P <.1 for ZDSD male rats. (See insert for color representation of the figure.) Also using the MSD platform, the ZDSD rat has been shown as a suitable model for evaluating several urine biomarkers of kidney injury related to nephropathy (Table 5, [3]). Neutrophil gelatinase-associated lipocalin (NGAL), the common plasma and kidney biomarker, has been shown recently as a biomarker of acute

13 ZDSD RAT: EVALUATING CURRENT DRUGS 143 Glucose infusion rate (mg/kg/min) Insulin sensitivity Rosiglitazone 3 mg/kg PO SD (age) SD (wt) ZDSD ZF Rat strain (SD rats are age or weight matched) FIGURE 5 ZDSD rats: insulin resistance and improved sensitivity with rosiglitazone. The insulin sensitivity (or Clamp ) study was initiated with 8-week-old ZDSD, ZF, and SD rats, n = 6 8. Using t-test for insulin sensitivity (glucose infusion rate), for ZDSD rats, P <.1, =.2 and =.3 when analyzed with SD (age) and SD (weight) control rats and with ZDSD rats treated with rosiglitazone 3 mg/kg, respectively, and for ZF rats, P <.1 when analyzed with SD (age) and SD (weight) control rats and with ZF rats treated with rosiglitazone 3 mg/kg. kidney injury and nephrotoxicity [31]. Selective use of these biomarkers, particularly upon further confirmation, should facilitate preclinical drug discovery in metabolic diseases. IV. ZDSD RAT: EVALUATING CURRENT DRUGS Since the ZDSD rat does not have a leptin or leptin receptor mutation and with apparent polygenic diseases that mimic type II diabetes in human population, this rat model appears more appropriate than other rodent models for use in antidiabetic drug discovery. One important question is whether current antidiabetic drugs are effective for the ZDSD rat. Tested in a prevention mode, metformin, rosiglitazone, and exenatide could significantly delay the development of diabetes in the ZDSD rats (Fig. 7). Though the modes of action for the antidiabetic drugs have not been completely elucidated, they appear to affect different molecular targets and metabolic pathways. Metformin acts through AMP-activated protein kinase (AMPK) pathway [32 35]. Rosiglitazone is peroxisome proliferator-activated receptor-γ (PPARγ) agonist [36] and inhibits obesity-linked phosphorylation of PPARγ by cyclin-dependent kinase 5 [37]. Exenatide is a GLP-1 mimetic for treatment of type 2 diabetes [38,39]. Showing preventive glucose-lowering effects by these antidiabetic drugs correlates with polygenic diseases of the ZDSD rats and validates its usefulness in drug discovery for metabolic diseases. Rimonabant is a commonly used positive control for testing anti-obesity compounds in rodent models; it decreases insulin resistance via both adiponectin-dependent and

14 (a) Glucose (mg/dl) OGTT: SD rats SD 12-weeks old SD 16-weeks old SD 2-weeks old SD 24-weeks old SD 28-weeks old Time (min) (b) Glucose (mg/dl) OGTT: ZDSD rats ZDSD 12-weeks old ZDSD 16-weeks old ZDSD 2-weeks old ZDSD 24-weeks old ZDSD 28-weeks old Time (min) FIGURE 6 ZDSD rats: age-dependent impaired glucose tolerance. SD rats (a), n = 1, and ZDSD rats (b), n = 1, were used in an oral glucose tolerance test (OGTT) starting 12 weeks old. From 12 to 28 weeks old, for every 2 weeks, the rats were dosed with 2 g/kg glucose orally, and the OGTT data are shown for every 4 weeks only. Two-way ANOVA was used in analyzing glucose of this study; in comparison to SD rats, P <.1 for ZDSD rats from four age groups (12 to 24 weeks old) and P =.83 from 28 weeks old. (See insert for color representation of the figure.) TABLE 4 ZDSD Rats: Serum Biomarkers a for Metabolic Disorders Metabolic disease Renal disease Coagulation and vascular disease Inflammation Insulin NGAL VEGF MCP-3 Leptin β-2-microglobulin Von Willebrand factor Lymphotactin GLP-1 Kim-1 Thrombopoietin IL-11 Resistin GST-α Factor VII MIP-1α Adiponectin Clusterin PAI-1 MPO Eotoxin CD4 ligand NGAL, neutrophil gelatinase-associated lipocalin; Kim-1, kidney-injury molecule-1; GST-α, glutathione S-transferase alpha; VEGF, vascular endothelial growth factor; PAI-1, plasminogen activator inhibitor-1; MCP-3, monocyte chemotactic protein-3; IL-11, interleukin-11; MIP-1α, macrophage inflammatory protein-1α; MPO, myeloperoxidase. a Statistically significant elevation of the listed analytes of ZDSD versus SD rats at 14, 18, and/or 2 weeks old, analyzed by Rules-Based Medicine. Rats were on Purina 5SCA from 17 to 19 weeks of age.

15 ZDSD RAT: EVALUATING CURRENT DRUGS 145 TABLE 5 ZDSD Rats: Urinary Excretion of Kidney Biomarkers for Renal Disease Biomarker ZDSD-8/SD (Fold) ZDSD-16/SD (Fold) Albumin 243 a 842 a Clusterin a GSTYb a NGAL a Osteopontin a RPA a 4.5 a Tim a 9.5 a The urinary biomarkers were compared from 33-week-old ZDSD rats to SD(CD) rats. ZDSD-8/SD is for the biomarker ratio that the ZDSD rats had been 8 weeks diabetic, and ZDSD-16/SD is for the biomarker ratio that the ZDSD rats had been 16 weeks diabetic. GSTYb-1, glutathione S-transferase Yb1; RPA-1, renal papillary antigen 1; Tim-1, T cell immunoglobulin-mucin; analyzed by MSD. a Statistically significant elevation of the analyte for the ZDSD rats. PCO ZDSD rats: Anti-diabetic drugs 6 5 BID (N=4/6) Metformin 15 mg/kg BID (N=7) Rosiglitazone 3 mg/kg BID (N=7) Exenatide 1 μg/rat BID (N=6) Glucose (mg/dl) Age (week) FIGURE 7 ZDSD rats: antidiabetic drug treatment with metformin, rosiglitazone, and exenatide. Using two-way ANOVA for glucose of the study, in comparison to the vehicle group, P <.1 for metformin, P =.24 for rosiglitazone, and P =.2 for exenatide. (See insert for color representation of the figure.)

16 146 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) Body weight (g) ZDSD rats: Body weight Rimonabant 3 mg/kg PO Rimonabant 1 mg/kg PO (b) % Body fat ZDSD rats: Body fat Age (week) 1 Rimonab 3* Rimonab 1* Test article (c) 8 Glucose (mg/dl) ZDSD rats: Glucose Rimonabant 3 mg/kg PO Rimonabant 1 mg/kg PO Age (week) (d) ZDSD rats: Triglycerides 15 Rimonabant 3* Triglycerides (mg/dl) Rimonabant 1* Age (week) FIGURE 8 ZDSD rats: anti-obesity drug treatment with rimonabant. The drug treatment started with 12-week-old rats, n = 8, that were on a standard diet for 3 weeks, followed by a high-fat diet for 2 weeks (15 17 weeks of age) and returned to the standard diet for 2 weeks. Body weight (a), fed plasma glucose (c), and TG (d) were monitored weekly; 3* is 3 mg/kg PO and 1* is 1 mg/kg PO. Body fat (b) was determined at 27-week-old rats by Quantitative Nuclear Magnetic Resonance (QNMR); Rimonab 3* is rimonabant 3 mg/kg and Rimonab 1* is rimonabant 1 mg/kg. Using two-way ANOVA, in comparison to the vehicle group, P <.1 for glucose at rimonabant 3 and 1 mg/kg and P =.18 and P <.1 for TG at rimonabant 3 and 1 mg/kg, respectively. For week-old rats on the standard diet, P =.2517 and P =.87 for body weight at rimonabant 3 and 1 mg/kg, respectively. Using t-test, in comparison to the vehicle group, P =.5419 and P <.22 for body fat at rimonabant 3 and 1 mg/kg, respectively. (See insert for color representation of the figure.) adiponectin-independent pathways [4]. Rimonabant lowered body weight increase of 12- to 15-week-old ZDSD rats on the standard diet (Fig. 8a). When tested with rimonabant at 1 mg/kg, the ZDSD rat showed a significant decrease in body fat (Fig. 8b). Interestingly, decreased body fat of the ZDSD rat also prevented spontaneous development of diabetes (Fig. 8c) and lowered TG (Fig. 8d). Thus, the ZDSD rat appears useful for both anti-obesity and antidiabetic drug discovery.

17 EXISTING RODENT MODELS: ESTABLISHING POSITIVE CONTROLS 147 V. EXISTING RODENT MODELS: ESTABLISHING POSITIVE CONTROLS Two types of existing rodent models are typically used in drug discovery for diabetes, metabolic syndrome, and obesity: genetic and diet induced. Two genetic models, db/db mice and ZDF rats, both with a leptin receptor mutation, as well as the DIO mice are probably the most used rodent models for antidiabetic drug discovery. Rosiglitazone is frequently used as a positive control in rodent efficacy studies for testing antidiabetic compounds. Rosiglitazone shows a significant efficacy in lowering plasma glucose in db/db mice and ZDF rats at low dose levels (Fig. 9a and b); similar glucose-lowering effects can be observed from dosing the (a) (b) 5 4 Fed plasma glucose (mg/dl) Fed plasma glucose (mg/dl) db/db Mice Rosiglitazone 1 mg/kg IP Duration (Day) ZDF Rats Rosiglitazone 6 mg/kg IP Duration (Day) FIGURE 9 Rosiglitazone as a positive control for lowering plasma glucose in db/db mice (A) and in ZDF rats (B). The db/db mice, n = 6, were dosed with rosiglitazone IP at 1 mg/kg starting 5 weeks old for 4 weeks, and the ZDF rats, n = 6, were dosed with rosiglitazone IP at 6 mg/kg starting 6 weeks old for 4 weeks. Using two-way ANOVA for glucose of the study, P <.1 for both the db/db mice and the ZDF rats.

18 148 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) Fed plasma insulin (pg/ml) (b) Fed plasma insulin (pg/ml) 25, 2, 15, 1, 5 15, 1, 5 db/db Mice Rosiglitazone 1 mg/kg Test article ZDF Rats Rosiglitazone 6 mg/kg Test article FIGURE 1 Rosiglitazone as a positive control for increasing plasma insulin in db/db mice (a) and in ZDF rats (b). The db/db mice and the ZDF rats were dosed with rosiglitazone as described in Figure 9. Plasma insulin was determined after the 4-week dosing with rosiglitazone. Using t-test for insulin of the study, P =.524 for the db/db mice and P =.1 for the ZDF rats. drug by oral, subcutaneous, or intraperitoneal route of administration. Other positive controls for lowering glucose in antidiabetic drug discovery include metformin, exenatide, and GLP-1. In addition to lowering glucose, rosiglitazone serves as a positive control for increasing plasma insulin (Fig. 1a and b), though with marginal statistical significance for db/db mice, and for lowering plasma TG (Fig. 11a and b) in db/db mice and ZDF rats. Rosiglitazone appears to raise the ratio of high-density lipoprotein (HDL) to total CHOL slightly (Fig. 12); however, not statistically significant, the ratio was not a good positive control for this study. Rosiglitazone also increased insulin extracted from pancreas (Fig. 13), particularly for the 6- to 9-week-old mice, and increased TG extracted from liver (Fig. 14) in db/db mice; thus, rosiglitazone is likely the most used positive control for both antidiabetic and anti-obesity drug discovery. For reminder, as a therapeutic agent from several years of concern, rosiglitazone (trade name Avandia) increases the risk of heart failure [41]. Both the United States and Europe have greatly restricted the use of the

19 EXISTING RODENT MODELS AND ONE CANCER PATIENT 149 (a) Fed plasma triglycerides (mg/dl) db/db Mice Rosiglitazone 1 mg/kg IP Duration (day) (b) Fed plasma triglycerides (mg/dl) ZDF Rats Rosiglitazone 6 mg/kg IP Duration (day) FIGURE 11 Rosiglitazone as a positive control for lowering plasma TG in db/db mice (a) and in ZDF rats (b). The db/db mice and the ZDF rats were dosed with rosiglitazone as described in Figure 9. Using two-way ANOVA for TG of the study, P =.74 for the db/db mice and P <.1 for the ZDF rats. diabetes drug. For anti-obesity drug discovery, rimonabant is frequently used as a positive control in rodent efficacy studies for testing anti-obesity compounds. Using diet-induced obesity for Long Evans rats at a low dose level, rimonabant shows a significant efficacy in lowering body weight (Fig. 15a) and body fat (Fig. 15b). Another genetic model, ob/ob mice with a leptin mutation, is also used for antidiabetic and anti-obesity studies. In addition to use in the treatment mode as described earlier, both rosiglitazone and rimonabant can be used in a preventive mode in rodent efficacy studies for metabolic syndrome, which is defined as abdominal obesity, high glucose and TG, low HDL, and high blood pressure [42]. Thus, rosiglitazone and rimonabant, among others, have been established as effective positive controls for these and other rodent models in drug discovery for diabetes, metabolic syndrome, and obesity.

20 15 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) Plasma HDL/CHOL ratio db/db Mice 6 9 weeks: HDL/CHOL ratio Rosiglitazone 1 mg/kg IP Duration (day) (b) Plasma HDL/CHOL ratio db/db Mice 9 12 weeks:hdl/chol ratio Rosiglitazone 1 mg/kg IP Duration (day) FIGURE 12 Rosiglitazone as a positive control for raising HDL/CHOL ratio in db/db mice. Starting 5 weeks (a) or 8 weeks (b) old, the db/db mice were dosed with 1 mg/kg rosiglitazone IP for 4 weeks. Using two-way ANOVA for HDL/CHOL ratio of the study, P =.435 for the db/db mice 6 9 weeks and P =.35 for the db/db mice 9 12 weeks. VI. EXISTING RODENT MODELS AND ONE CANCER PATIENT: TESTING NUTRITIONAL SUPPLEMENT (ALKA VITA) As this chapter goes to print, health-care reform will likely be a reality for the first time in the US history. Though there is a continuous debate about the economic impact of such health-care reform, unanimous scientific consensus is that obesity, diabetes, and metabolic diseases have a very significant role in human health and economic expenditure in the United States and worldwide. About 72 million Americans or onethird of adults were obese in 26, according to the US Centers for Disease Control and Prevention. Approximately 3 deaths per year in the United States are associated with obesity in 28 [43]. Obesity-related medical costs reached $147 billion in 28, or about 1% of US medical spending [43]. Since fat overload is considered as the major factor for diabetic development [24], many of the obese individuals are also diabetic; both the United States and China have an alarming and equal diabetic rate of 11% in 21. To improve or maintain good health, common knowledge and

21 EXISTING RODENT MODELS AND ONE CANCER PATIENT 151 (a) Pancreas insulin (ng/g-pancreas) (b) db/db/mice 9-week: Pancreas insulin Rosiglitazone 1 mg/kg Test article db/db Mice 12-week: Pancreas insulin Pancreas insulin (ng/g-pancreas) Test article Rosiglitazone 1 mg/kg FIGURE 13 Rosiglitazone as a positive control for raising pancreas insulin in db/db mice. Starting 5 weeks (a) or 8 weeks (b) old, the db/db mice were dosed with 1 mg/kg rosiglitazone IP for 4 weeks. The mice were fasted for 12 h and an OGTT was conducted on day 29. Following the OGTT, the pancreas was removed, and insulin was extracted from the pancreas and analyzed by an MSD assay. Using t-test for pancreas insulin of the study, P =.31 for the db/db mice 6 9 weeks and P =.94 for the db/db mice 9 12 weeks. experience recommend a balanced diet, with abundant fruits and vegetables and moderate meat consumption. Regular exercise, such as walking and running, is as important as balanced food for good health. Exercise is known to improve good hormone production and normal physiological function, the latter, for example, in raising AMPK-linked autophagy [44]. In addition, a recent Blockbuster Study finds that vigorous long-term exercise, as that from a distance runner, may contribute to the prevention of telomere shortening [45], thus reducing the risk of many diseases. The enzymes responsible for maintenance of telomeres, found on the ends of DNA structures, are called telomerases, the studies of which produced the 29 Nobel Prize in Physiology or Medicine [46]. Since there is deficiency for vitamins and minerals in

22 152 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) Liver triglycerides (mg/g-liver) db/db/mice 9-week: Liver triglycerides Rosiglitazone 1 mg/kg Test article (b) db/db/mice 12-week: Liver triglycerides Liver triglycerides (mg/g-liver) Rosiglitazone 1 mg/kg Test article FIGURE 14 Rosiglitazone as a positive control for increasing liver TG in db/db mice. The db/db mice were dosed with rosiglitazone, and an OGTT was conducted as described in Figure 13. Following the OGTT, the liver was removed and TG were determined from 1% Tween-8 homogenates (25) using a kit from Wako Diagnostics. Using t-test for liver TG of the study, P <.1 for both db/db mice 6 9 weeks and 9 12 weeks. western food, much of which is from mass commercial production, taking nutritional supplements (nutraceuticals) is often needed for maintaining healthy human physiology. For prevention of metabolic and other diseases, one needs balanced diet, moderate physical activity, and suitable nutritional supplements. To maintain good human health, there are two predominant yet not proven basic biochemical hypotheses. One is originated from German scientists, suggesting that adequate oxygenation is the basis of normal physiological processes [47]. The other was hypothesized from Japan researchers, implicating that alkalinity plays an important role in human health [47,48]. Acid waste accumulation in the body, which can be reduced by alkaline water and fruit/vegetable diet, may cause oxygen deficiency and related symptoms for a variety of adult diseases [47]. A recent report describes phosphoric acid acting

23 EXISTING RODENT MODELS AND ONE CANCER PATIENT 153 as a ph biosensor that links membrane biogenesis to metabolism [49]. To test the second ph-related hypothesis, an alkaline nutritional supplement has been extensively evaluated in preclinical antibacterial and antidiabetic applications. Alka Vita (renamed as Neutrevive and LipH, of Orizon International and Cisne Enterprises, Odessa, Texas) is a uniquely modified liquid silicon containing a mixture of trimeric sodium silicate and sodium silicate pentahydrate. At a low concentration, it can raise ph and is suitable for human consumption [48,5]. It shows a strong inhibition of common pathogenic bacteria, including Staphylococcus aureus [51], a major infectious agent at hospitals. The effect of Alka Vita is attributed to both alkalinity and liquid silicon. When tested in the db/db mice alone, Alka Vita moderately lowered glucose as well as AST and ALT (not shown), the liver toxicity biomarkers. When evaluated in (a) 65 Long Evans rats: Body weight Body weight (g) (b) Rimonabant 1 mg / kg PO Duration (day) Long Evans rats: Body fat 24 % Body Fat Test article Rimonabant FIGURE 15 Rimonabant as a positive control for reducing body weight (a) and fat (b) in Long Evans rats. DIO Long Evans rats, n = 6, at 14 weeks old were dosed orally with 1 mg/kg rimonabant (PO); body weight was measured daily for 21 days and % fat was determined by QNMR on day 21. Using two-way ANOVA by column (effect) factor only, in comparison to the vehicle group, P <.1 for body weight. Using t-test, in comparison to the vehicle group, P =.272 for body fat.

24 154 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) 1 ZDF rats: ALT 8 ALT (IU/L) 6 4 1% Alka Vita 2 Metformin (5 mg / kg PO) Duration (week) (b) AST (IU/L) ZDF rats: AST 1% Alka Vita 1 Metformin (5 mg / kg PO) Duration (week) FIGURE 16 Effects of Alka Vita and metformin on ALT (a) and AST (b) of ZDF rats. ZDF obese male rats, n = 15, were dosed orally with 1% Alka Vita daily from 11 weeks old and dosed orally with 5 mg/kg metformin daily from 6 weeks of the study for 6 weeks; and ALT and AST determined as indicated in Scheme 3. Using two-way ANOVA for the study, P =.192 for ALT and P =.59 for AST. the ZDF rats with metformin, it decreased ALT significantly and AST moderately (Fig. 16a and b). It also lowered glucose significantly when coadministered with metformin in the ZDF rats. The glucose-lowering effect appears to be additive (Fig. 17a). It decreased HbA1c and increased fasting insulin significantly (not shown). Alka Vita with metformin also significantly reduced cataract (Fig. 17b); the latter is a diabetic complication. From available scientific literature, including online publications, Alka Vita may serve as an effective and preventive nutritional supplement for bacterial and viral infections, diabetic development, and other pathological progression such as that of some cancer types [52]. The statement for Neutrevive to

25 EXISTING RODENT MODELS AND ONE CANCER PATIENT 155 (a) 35 ZDF rats: Glucose Fasted plasma glucose (mg / dl) % Alka Vita Metformin (5 mg / kg PO) Duration (week) (b) 1 ZDF rats: Cataract % Rats showing cateract % Alka Vita** FIGURE 17 Effects of Alka Vita and metformin on glucose (a) and cataract (b) of ZDE rats. ZDF obese male rats were dosed with 1% Alka Vita daily from 11 weeks old and with 5 mg/ kg metformin daily from 6 weeks of the study for 6 weeks as described in Figure 16; glucose determined from 16-h fasted rats; and cataract measured at a scale of (none) to 5 (all) from both eyes of each rat at 17 weeks of the study (i.e., 5 weeks after termination of metformin treatment at 12 weeks). 1% Alka Vita**: with 5 mg/kg metformin for 6 weeks. Using two-way ANOVA for the study, P =.1 for glucose. Cataract was observed in both eyes from six of eight rats for the control group and from two of eight rats for the Alka Vita group. revive the immune system has not been confirmed by the Food and Drug Administration [48]. More recently, Alka Vita was shown to have cancer chemotherapeutic properties in vitro, including an antioxidant response to glutathione, catalase, and superoxide dismutase [5]. In vivo tests are imperative to determine its true effectiveness, and an extreme in vivo case is described briefly here. After being informed by her physician that she had one and a half year to live and with the conventional chemotherapies, the 49-year-old female patient having terminal colon cancer survived for almost 2 years

26 156 ENZYME ASSAYS AND RODENT MODELS FOR METABOLIC DISEASES (a) 7 Cancer patient: CEA-1 2 CEA (ng/ml) Time (Day) % Alka Vita (ml/day) (b) 6 Cancer patient: CEA-2 6 CEA (ng/ml) Time (Day) FIGURE 18 Effect of Alka Vita on CEA of the colon cancer patient. A 49-year-old female was diagnosed for a terminal colon cancer in March of 28, and after surgeries she was informed by the physician that, with conventional chemotherapy, she would likely live for another 18 months. With the biweekly chemotherapies, the patient lived for 23 months, and in February of 21, she continued the biweekly chemotherapies and additionally started taking 2% Alka Vita (LipH as the new name). From day 1 to day 584, except for two extended times (36 days in Fig. 18a and 54 days in Fig. 18b) without taking Alka Vita due to its unavailability, she took two ounces of 2% Alka Vita once a day initially and increased 2% Alka Vita stepwise as shown in the following text: to two ounces twice a day, to two ounces three times a day, to three ounces three times a day, to three ounces four times a day, and to three ounces six times a day (dashed line). CEA (solid line) was determined from the serum of the non-fasting patient by a clinical laboratory, and normal values of CEA are ng/ml % Alka Vita (ml/day) before she started taking Alka Vita. With the additional use of Alka Vita, though interrupted twice due to unavailability of Alka Vita, the patient remains alive today for more than 24 months. Incrementally elevating the use of Alka Vita either lowered the level or slowed the increase of carcinoma embryonic antigen (CEA; Fig. 18a and b), a proposed biomarker for colon cancer [53]. Also, Alka Vita appears to function by maintaining lower levels of AST (Fig. 19a) and glucose (Fig. 19b). It is important to share with the readers that, after being informed by another physician that she had only 3 6 months of life by the regular chemotherapy, the patient has been surviving

27 CONCLUDING REMARKS 157 (a) 1 Cancer patient: AST 3 AST (IU/L) % Alka Vita (ml/day) Time (Day) (b) 2 Cancer patient: Glucose 3 Glucose (mg/dl) % Alka Vita (ml/day) Time (Day) FIGURE 19 Effects of Alka Vita on AST and glucose of the colon cancer patient. See the colon cancer history with conventional chemotherapy of the patient and additional use of Alka Vita in Figure 18. AST (solid line) and glucose (solid line) were determined as indicated in Figure 18. more than 16 months and is still looking forward to more quality life with continuous use of Alka Vita. Probably by modulating CEA, AST, glucose, and other biomarkers such as ALT and AP (not shown), Alka Vita boosts the immune system, as suggested for the product but not yet approved by FDA, and importantly it extends the life span and its quality for the patient. VII. CONCLUDING REMARKS The central theme for this chapter involves using preclinical enzyme assays and rodent models for drug discovery in metabolic diseases, especially diabetes, metabolic syndrome, and obesity. The chapter content derives from the research experience by the authors over three decades. Selective application of the enzyme assays as well as the rodent models (new and established) included in the chapter and others can significantly facilitate discovery of therapeutic agents for unmet medical needs.