WO2006031963A2 - Metabolite markers for weight management - Google Patents
Metabolite markers for weight management Download PDFInfo
- Publication number
- WO2006031963A2 WO2006031963A2 PCT/US2005/032920 US2005032920W WO2006031963A2 WO 2006031963 A2 WO2006031963 A2 WO 2006031963A2 US 2005032920 W US2005032920 W US 2005032920W WO 2006031963 A2 WO2006031963 A2 WO 2006031963A2
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- metabolite marker
- level
- metabolite
- pcdml8
- weight
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/92—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving lipids, e.g. cholesterol, lipoproteins, or their receptors
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/02—Nutritional disorders
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/04—Endocrine or metabolic disorders
- G01N2800/044—Hyperlipemia or hypolipemia, e.g. dyslipidaemia, obesity
Definitions
- This invention relates generally to the field of metabolic targets and markers, especially markers indicative of weight loss or gain and conditions associated therewith.
- Weight control has become increasingly relevant and important in modern daily life. Millions of people go on various types of diet each year, e.g., Weight- watcher, Jenny-Craig, NutriSystem, SlimFast, Atkins diet, The New Beverly Hill
- the present invention is based, in part, on the discovery that certain metabolites or metabolic pathways can be used as diagnostic or therapeutic markers for projecting weight development patterns and conditions associated therewith. Accordingly the present invention provides methods for predicting weight development patterns and compositions and kits useful for detecting metabolites associated with various weight conditions.
- the present invention provides a method for predicting weight loss or weight gain of a subject.
- the method comprises measuring the level of a first metabolite marker in a sample of a subject under a condition, wherein the first metabolite marker is selected from the group consisting of CE16:ln7, LY20:3n6, PC20:3n6, PE20:3n6, CE14:0, PC20:3n9, CELC, PCtl6:ln7, TGSAT, TG14:0, TGn7, CE20:3n6, TG16:ln7, FA18:0, FASAT, FA14:0, FA16:0, PC14:0, TG18:0, CE18:3n6, PC20:2n6, PC20:4n3, PE18:2n6, TG20:3n6, CE20:4n3, PC18:2n6, PELC, PC18:3n6, PC20:5n3, PC18:3n3, PE20:5n3, PCLC, CE18:2n
- the present invention provides a kit.
- the kit comprises an instruction for predicting weight condition of a subject and an agent capable of detecting the level of a metabolite marker in a sample of the subject, wherein the metabolite marker is selected from the group consisting of CE16:ln7, LY20:3n6, PC20:3n6, PE20:3n6, CE14:0, PC20:3n9, CELC, PCtl6:ln7, TGSAT, TG14:0, TGn7, CE20:3n6, TG16:ln7, FA18:0, FASAT, FA14:0, FA16:0, PC14:0, TGl 8:0, CE18:3n6, PC20:2n6, PC20:4n3, PE18:2n6, TG20:3n6, CE20:4n3,
- TGMUFA mono unsaturated fatty acid in triacylglycerol
- TGPUFA polyunsaturated fatty acid in triacylglycerol
- the present invention is based, in part, on the discovery that certain metabolites or metabolic pathways can be used as diagnostic or therapeutic markers for projecting weight development patterns and conditions associated therewith. Accordingly, the present invention provides methods of using metabolite markers for predicting weight development patterns and conditions associated therewith, e.g., weight related conditions. In addition, the present invention also provides compositions and kits useful for detecting metabolites associated with weight loss or weight gain or weight related conditions.
- levels of certain metabolites can be used as markers for projecting weight or weight related conditions of a subject, e.g., human, animals or animal models for various disease conditions over a period of time.
- levels of one or more metabolite markers can be compared to standard values of the metabolites corresponding to certain weight development patterns such as weight gain, weight loss, or weight neutral and the results of such comparison can be used to project weight development or weight related conditions of a subject over a period of time.
- a subject e.g., human or animal having levels of certain metabolite markers similar to or within the standard values of these metabolites that are assigned to or associated with a weight loss pattern or weight loss related condition is likely to lose weight or develop the weight loss related condition over a period of time.
- a subject e.g., human or animal having levels of certain metabolite markers similar to or within the standard values of these metabolites that are assigned to or associated with a weight gain or weight neutral pattern or their related conditions is likely to gain weight, experience no weight change, or develop weight gain related conditions over a period of time.
- Standard values of metabolite markers assigned to different weight development conditions can be readily established for people with certain characteristics and/or undergoing certain conditions.
- standard values of metabolites of interest can be established for people in certain age, gender, baseline body weight, and/or ethnic group, with certain physiological or pathological condition, and/or undergoing certain conditions, e.g., diet or therapeutic regimen.
- one way of obtaining standard values of metabolite markers is by recording the levels of the metabolites from human or animals of interest and conducting standard statistical analyses, e.g., determining the average or mean value of the levels of such metabolites associated with a weight development pattern.
- Standard values of metabolite markers can also be similarly obtained for formulations containing one or more metabolites as variables.
- metabolite markers associated with the development of a weight or weight related condition include any, mono- or poly-, saturated or unsaturated free fatty acids or fatty acids linked to other molecules, e.g., via their carboxylic acid group.
- metabolite markers of the present invention include fatty acids with long hydrocarbon tails, e.g., Cl 4 to C24.
- metabolite markers of the present invention include fatty acids of 14:0, 14:ln5, 16:0, 16:ln7, 18:0, 18:2n6, 18:ln7, 18:ln9, 18:3n3, 18:3n6, 20:2n6, 20:3n6, 20:3n9, 20:4n3, 20:4n6, 20:5n3, 22:5n3, 22:6n3, 24:ln9, n6, n7, n9, or lipid class.
- metabolite markers of the present invention include mono unsaturated fatty acids, polyunsaturated fatty acids, and saturated fatty acids.
- metabolite markers of the present invention include fatty acids stored in cholesterol or as energy reserve, e.g., in triglycerides.
- levels of metabolite markers of the present invention can be levels of metabolite markers at a specific time point or over a period of time.
- levels of metabolite markers of the present invention can be a baseline measurement of the metabolite markers. Such baseline measurement can be a measurement of the metabolite markers at the beginning of a condition or before any condition is imposed on a subject, e.g., diet or therapeutic regiment. In one embodiment, such baseline measurement is a measurement of metabolite markers at about day zero, day one, day two, or day three of a diet or therapeutic regiment.
- levels of metabolite markers of the present invention can be levels of metabolite markers over a period of time, e.g., a change of the level of a metabolite marker over a period of time.
- the level of a metabolite marker of the present invention can be a change of such metabolite marker between a first time point and a second time point under a condition.
- the level of a metabolite marker of the present invention is a change of such metabolite at the initial stage of a condition imposed to a subject, e.g., between about day one and day two, three, four, or day six of a diet or therapeutic regiment.
- Levels of metabolite markers of the present invention can be expressed or characterized by various suitable means.
- the level of a metabolite marker of the present invention can be either an absolute level or normalized level of the metabolite marker.
- the level of a metabolite marker of the present invention is represented as 1) an absolute amount of the metabolite, e.g., concentration such as nanomoles per gram, etc., 2) the amount of the metabolite in a metabolite class, e.g.
- the level of a metabolite marker of the present invention is normalized against another metabolite marker.
- the level of a metabolite marker of the present invention can be a ratio between two or more metabolite markers of the present invention or can be normalized against an index metabolite marker associated with a pathway, enzymatic activity, class of metabolites, and/or status of certain metabolic activities.
- the level of a metabolite marker of the present invention can be normalized against a housekeeping metabolite marker, e.g., the amount of which is relatively stable under one or more conditions imposed to a subject of interest.
- Levels of metabolite markers of the present invention can be measured via any suitable means known or later developed in the art. For example, levels of metabolite markers of the present invention can be measured directly or indirectly by immunoassay, enzymatic assay, mass spectroscopy, fluorimetry, radioisotope detection, etc. Levels of metabolite markers of the present invention can also be measured via chromatography, e.g., gas chromatography, high performance chromatography nuclear magnetic resonance, thin-layer chromatography, etc. For example, levels of metabolite markers of the present invention can be measured according to the method described in Watkins et al., Journal of Lipid Research Vol. 43, p ⁇ l-9, 2002 or methods described in PCT/US02/21426, both of which incorporated herein by reference.
- metabolite markers of the present invention can be measured using any suitable biological sample of a subject, e.g., human.
- a biological sample is a blood sample, e.g., plasma.
- a tissue sample e.g., adipose tissue, muscle, etc.
- levels of metabolite markers of the present invention can be either positively or negatively associated with weight gain (or weight loss) or its related conditions over a period of time under a condition, e.g., diet or therapeutic regiment.
- positive association of a metabolite marker with weight gain or its related conditions means that a higher than a standard metabolite value assigned to weight gain or its related conditions is predictive of a level of weight gain higher than the level of weight gain corresponding to the standard metabolite value or development of weight gain related conditions.
- an increase in the level of a metabolite marker is associated or correlates with an increase in weight gain or development of weight gain related conditions in a subject.
- a negative association of a metabolite marker with weight gain or its related conditions means that a higher than a standard metabolite value assigned to weight gain or its related conditions is predictive of a level of weight gain lower than the level of weight gain corresponding to the standard metabolite value, e.g., an increase in the level of a metabolite marker is associated or correlates with a decrease in weight gain or development of weight gain related conditions in a subject.
- a metabolite marker positively associated with weight gain or its related conditions normally can be negatively associated with weight loss or its related conditions, e.g., an increase in the level of a metabolite marker is associated or correlates with an increase in weight gain or development of weight gain related conditions and/or a decrease in weight loss in a subject.
- PC20:3n6, PE20:3n6, CE14:0, PC20:3n9, CELC, PCtl6:ln7, TGSAT, TG14:0, TGn7, CE20:3n6, TG16:ln7, FA18:0, FASAT, FA14:0, FA16:0, PC14:0, TG18:0, CE18:3n6, PC20:2n6, PC20:4n3, PE18:2n6, TG20:3n6, CE20:4n3, PC18:2n6, PELC, PC18:3n6, PC20:5n3, PC18:3n3, PE20:5n3, PCLC, CE18:2n6, PC18:0, LY18:0, TGLC, PC16:ln7, PE16:ln7, FA14:ln5, TGtI 6: In7, CE18:3n3, PEdml8:0, LYLC, or TG18:3n3, or a combination thereof over a period of time
- metabolite markers of the present invention can be used alone, in combination with each other, or in combination with other metabolites or factors in projecting weight development patterns of a subject.
- metabolite markers of the present invention especially metabolite markers that change concurrently or co-vary with each other under a condition, e.g., diet or therapeutic regiment can be used in connection with each other in projecting weight development or its related conditions of a subject.
- at least one, two, three, four, five, or six metabolite markers of the present invention are used as a lipid panel in assessing weight development patterns or their related conditions of a subject, e.g., human or animal.
- metabolite markers like 16:ln7 e.g., in phosphatidylcholine, trans-phosphatidylcholine, triacylglycerol, trans-triacylglycerol, phosphatidylethanolamine, free fatty acid, or cholesterol ester
- 18:ln9 e.g., in triacylglycerol, free fatty acid, cholesterol ester, or phosphatidylcholine dimethoxy acetal are used together for projecting weight development or its related conditions of a subject.
- metabolite markers like polyunsaturated fatty acid, e.g., in triacylglycerol and 18:0, e.g., in triacylglycerol, free fatty acid, phophatidylcholine, lysophophatidylcholine, phosphatidylethanolamine dimethoxy acetal, or sphingomyelin are used together for projecting weight development or its related conditions of a subject.
- metabolite markers like 18:ln9 e.g., in triacylglycerol, free fatty acid, cholesterol ester, or phosphatidylcholine dimethoxy acetal and 18:0, e.g., in triacylglycerol, free fatty acid, phophatidylcholine, lysophophatidylcholine, phosphatidylethanolamine dimethoxy acetal, or sphingomyelin are used together for projecting weight development or its related markers of a subject.
- 16:ln7 e.g., in phosphatidylcholine, trans-phosphatidylcholine, triacylglycerol, trans-triacylglycerol, phosphatidylethanolamine, free fatty acid, or cholesterol ester
- 18:2n6 e.g., in phosphatidylethanolamine, phosphatidylcholine, or cholesterol ester are used together for proj ecting weight development or its related markers of a subj ect.
- metabolite markers like mono unsaturated fatty acid, e.g., in triacylglycerol or free fatty acid, 18:ln9, e.g. in triacylglycerol, free fatty acid, cholesterol ester, or phosphatidylcholine dimethoxy acetal and 18:0, e.g., in triacylglycerol, free fatty acid, phophatidylcholine, lysophophatidylcholine, phosphatidylethanolamine dimethoxy acetal, or sphingomyelin are used together to predict weight development or its related conditions of a subject.
- mono unsaturated fatty acid e.g., in triacylglycerol or free fatty acid, 18:ln9, e.g. in triacylglycerol, free fatty acid, cholesterol ester, or phosphatidylcholine dimethoxy acetal and 18:0, e.g.,
- Metabolite markers of the present invention can also be used along with other characteristics of a subject in weight development or its related condition assessment, e.g., body weight, age, height, baseline body fat amount, etc.
- metabolite markers of the present invention can be used in combination with body weight of a subject in projecting weight or its related conditions of the subject.
- the body weight can be baseline body weight or the body weight of a subject at a time point, e.g. after the initial stage of a diet or therapeutic regiment.
- metabolite markers like 18:0 e.g., in triacylglycerol, free fatty acid, phophatidylcholine, lysophophatidylcholine, phosphatidylethanolamine dimethoxy acetal, or sphingomyelin, or saturated fatty acid, e.g., in triacylglycerol are used in combination with the baseline body weight of a subject to predict weight development or its related conditions of the subject.
- levels of metabolite markers like 18:0 in triacylglycerol, free fatty acid, phophatidylcholine, lysophophatidylcholine, phosphatidylethanolamine dimethoxy acetal, or sphingomyelin or saturated fatty acid in triacylglycerol are positively associated with weight loss or its related conditions of a subject when they are used in combination with the baseline body weight of the subject.
- a formula containing the levels of one or more metabolite markers of the present invention as variables includes any mathematic formula, model, equation, or expression established based on mathematic or statistical principles or methods using the values of one or more metabolite markers of the present invention as variables.
- any suitable mathematic analyses can be used to analyze the net effect of two or more metabolite markers of the present invention with respect to projecting the weight condition of a subject, e.g., human.
- methods such as multivariate analysis of variance, multivariate regression, multiple regression can be used to determine relationships between dependent variables, e.g., weight loss or weight gain and independent variables, e.g., baseline body weight and levels of metabolite markers of the present invention.
- Clustering including both hierarchical and nonhierarchical methods, as well as nonmetric Dimensional Scaling can be used to determine associations among variables and among changes in those variables.
- principal component analysis is a common way of reducing the dimension of studies, and can be used to interpret the variance-covariance structure of a data set.
- Principal components may be used in such applications as multiple regression and cluster analysis.
- Factor analysis is used to describe the covariance by constructing "hidden" variables from the observed variables.
- Factor analysis may be considered an extension of principal component analysis, where principal component analysis is used as parameter estimation along with the maximum likelihood method.
- simple hypothesis such as equality of two vectors of means can be tested using Hotelling' s T squared statistic.
- a formula containing one or more metabolite markers of the present invention as variables is established by using regression analyses, e.g., multiple linear regression.
- regression analyses e.g., multiple linear regression.
- formulas developed based on multiple linear regression include, without any limitation, the following.
- Formula II k + ki(TGMUFA) + k 2 (FAl 8: In9) + k 3 (FAl 8:0)
- Formula III k + ki(FAl 8: In9) + k 2 (FAl 8:0)
- Formula IV k + ki(CE16:0) + k 2 (TG18:ln9)
- Formula V k - ki(TGPUFA) + k 2 (FA18:ln9) + k 3 (FA18:0) - Iq(TGl 8:0)
- Formula VI k + kiCTG18:2n6) + k 2 (TG18:ln9) + k 3 (FA18:ln9) + k 4 (FA18:0) + k s (CE16:ln7)
- BW baseline body weight
- the constants of these formulas can be established by using a set of data obtained from known weight conditions.
- the levels of metabolite markers used in these formulas can be either the levels at a time point or changes of levels over a period of time.
- the levels of metabolite markers used in these formulas are baseline measurements of these metabolite markers whereas in Formulas VII, VIII, IX, X, XI, and XII the levels of metabolite markers used in these formulas are changes of levels of these metabolite markers during the initial stage of a condition.
- mathematic formulas established using metabolite markers of the present invention can be used to either qualitatively or quantitatively assess the weight condition of a subject over a period of time.
- a formula having one or more metabolite markers as variables can be used to directly calculate the weight condition of a subject.
- the net value of a formula containing one or more metabolite markers of the present invention can be compared to the standard value of such formula corresponding to a weight development pattern, e.g., weight loss, weight gain, or weight neutral and the results of such comparison can be used to project weight development.
- a subject e.g., human having a net value of a formula similar to or within the range of the standard value of such formula that is assigned to or associated with a weight loss pattern or its related conditions is likely to lose weight or develop weight loss related conditions over a period of time.
- a subject e.g., human having a net value of a formula similar to or within the range of the standard values of such formula that is assigned to or associated with a weight gain or weight gain related conditions or weight neutral pattern is likely to gain weight, develop weight gain related conditions, or experience no weight change over a period of time.
- weight related conditions e.g., weight gain related conditions or weight loss related conditions include any physiological or pathological conditions associated with weight development or secondary to a weight condition.
- weight gain can be associated with cardiovascular conditions, diabetic conditions, high blood pressure, stroke, sleep apnea, breast cancer, gall bladder, poor pregnancy outcome, kidney stones, arthritis, steatosis, steatohepatitis, colon cancer, endometrial cancer, etc whereas weight loss can be associated with depression, parasites, bulimia, anorexia, OTC drug side effects, AIDS/HIV, infection, TB, thyroid disease, chronic infections, GI diseases such as chronic IBS, periodontal disease, etc, wasting or neoplastic growth, e.g., cancer or tumor.
- compositions and kits useful for projecting weight conditions of a subject contains an agent capable of detecting the levels of metabolite markers of the present invention and an instruction for using the level of metabolite markers of the present invention to predict weight loss.
- the instruction can provide standard values corresponding to each weight development condition, e.g., formulas containing one or more metabolite markers of the present invention as variables or standard values for metabolites or formulas of the present invention.
- the agent used in the kit of the present invention can be any agent useful for measuring the levels of metabolite markers of the present invention.
- the agent contained in the kit of the present invention is an antibody, e.g., monoclonal antibody capable of detecting metabolite markers of the present invention.
- the agent is a label modified to specifically identify metabolite markers of the present invention, e.g., a phosphorescent label, a fluorescent label, a biotin or avidin label, or a radioactive label.
- the agent is a peptide or ligand containing a detectable moiety and capable of specifically binding to metabolite markers of the present invention.
- the agent is capable of reacting with the double bonds of unsaturated fatty acids to form various derivatives of double bonds, e.g., mercuric acetate derivatives, dimethyl disulfide addition, hydrogenation, deuteration, etc., which facilitate the measurements of the fatty acids.
- the methods and kits provided by the present invention can be used to assess weight conditions or development patterns under any condition for a subject, e.g., mammals such as humans or domesticated animals.
- a subject e.g., mammals such as humans or domesticated animals.
- the methods and kits provided by the present invention can be used to predict weight conditions for people on a diet, e.g., to assess or predict the effectiveness of a dietary change or nutritional treatment.
- the methods and kits provided by the present invention can also be used to project weight development conditions for people undergoing or to undergo a therapeutic regiment, e.g., drug or hormonal treatments associated with weight conditions or the side effect of drugs or hormones on weight conditions.
- metabolite markers of the present invention can be used to project susceptibility of weight related conditions, e.g., diabetic or cardiovascular conditions associated with weight gain or complications associated with weight loss or wasting.
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Molecular Biology (AREA)
- Chemical & Material Sciences (AREA)
- Biomedical Technology (AREA)
- Urology & Nephrology (AREA)
- Hematology (AREA)
- Immunology (AREA)
- Cell Biology (AREA)
- Analytical Chemistry (AREA)
- Biotechnology (AREA)
- Pathology (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Physics & Mathematics (AREA)
- Microbiology (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Biophysics (AREA)
- Endocrinology (AREA)
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
- Acyclic And Carbocyclic Compounds In Medicinal Compositions (AREA)
Abstract
Description
Claims
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CA002579809A CA2579809A1 (en) | 2004-09-13 | 2005-09-13 | Metabolite markers for weight management |
AU2005284830A AU2005284830A1 (en) | 2004-09-13 | 2005-09-13 | Metabolite markers for weight management |
EP05797616A EP1789806A2 (en) | 2004-09-13 | 2005-09-13 | Metabolite markers for weight management |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US60970304P | 2004-09-13 | 2004-09-13 | |
US60/609,703 | 2004-09-13 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2006031963A2 true WO2006031963A2 (en) | 2006-03-23 |
WO2006031963A3 WO2006031963A3 (en) | 2006-05-26 |
Family
ID=35457367
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US2005/032920 WO2006031963A2 (en) | 2004-09-13 | 2005-09-13 | Metabolite markers for weight management |
Country Status (5)
Country | Link |
---|---|
US (2) | US20060088860A1 (en) |
EP (1) | EP1789806A2 (en) |
AU (1) | AU2005284830A1 (en) |
CA (1) | CA2579809A1 (en) |
WO (1) | WO2006031963A2 (en) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2008021192A2 (en) | 2006-08-08 | 2008-02-21 | Lipomics Technologies, Inc. | Markers of non-alcoholic fatty liver disease (nafld) and non-alcoholic steatohepatitis (nash) and methods of use thereof |
WO2014188202A1 (en) * | 2013-05-24 | 2014-11-27 | King's College London | Biomarkers |
CN106680473A (en) * | 2017-01-23 | 2017-05-17 | 首都医科大学附属北京朝阳医院 | Application of biological marker to screening of drugs for treating or relieving metabolic syndrome |
US10299501B2 (en) | 2011-10-05 | 2019-05-28 | DuPont Nutrition USA, Inc. | Stabilizer composition of microcrystalline cellulose and carboxymethylcellulose, method for making, and uses |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2477909A1 (en) * | 2002-03-11 | 2003-09-25 | Lipomics Technologies, Inc. | Novel metabolic targets and markers |
US20060151845A1 (en) * | 2005-01-07 | 2006-07-13 | Shrinivas Govindarajan | Method to control interfacial properties for capacitors using a metal flash layer |
WO2007050318A2 (en) * | 2005-10-24 | 2007-05-03 | Duke University | Lipidomics approaches for central nervous system disorders |
US8137977B2 (en) * | 2006-04-24 | 2012-03-20 | Children's Hospital & Research Center At Oakland | Lipidomic approaches to determining drug response phenotypes in cardiovascular disease |
CA2678670A1 (en) * | 2007-02-22 | 2009-09-04 | Tethys Bioscience, Inc. | Metabolic markers of diabetic conditions and methods of use thereof |
FI20085101L (en) * | 2008-02-05 | 2009-08-06 | Valio Oy | Procedure for Diagnosing Irritable Bowel Syndrome IBS |
CN105424841B (en) * | 2015-12-25 | 2017-11-03 | 齐炼文 | Metabolic markers for diagnosing coronary atherosclerosis |
CN105445408B (en) * | 2016-01-25 | 2018-06-12 | 齐炼文 | The metabolic markers of coronary atherosclerosis and stable angina cordis are distinguished in diagnosis |
CN105486778B (en) * | 2016-01-25 | 2017-11-03 | 齐炼文 | The metabolic markers of stable angina cordis and acute coronary syndrome are distinguished in diagnosis |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2003028271A2 (en) * | 2001-09-24 | 2003-04-03 | Lipomics Technologies, Inc. | Methods of using quantitative lipid metabolome data |
Family Cites Families (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5790761A (en) * | 1992-12-11 | 1998-08-04 | Heseltine; Gary L. | Method and apparatus for the diagnosis of colorectal cancer |
US5578613A (en) * | 1993-12-21 | 1996-11-26 | Eli Lilly And Company | Methods for inhibiting weight gain or inducing weight loss |
US5628328A (en) * | 1995-04-25 | 1997-05-13 | Iowa State University Research Foundation | Method for measuring muscle mass |
US5983211A (en) * | 1996-01-24 | 1999-11-09 | Heseltine; Gary L. | Method and apparatus for the diagnosis of colorectal cancer |
US6678669B2 (en) * | 1996-02-09 | 2004-01-13 | Adeza Biomedical Corporation | Method for selecting medical and biochemical diagnostic tests using neural network-related applications |
US6235286B1 (en) * | 1996-05-09 | 2001-05-22 | Douglas D. Lazarus | Adult-onset diabetes treatment method |
US5981575A (en) * | 1996-11-15 | 1999-11-09 | Johns Hopkins University, The | Inhibition of fatty acid synthase as a means to reduce adipocyte mass |
PT1003501E (en) * | 1997-04-02 | 2005-07-29 | Brigham & Womens Hospital | USING AN AGENT TO REDUCE THE RISK OF CARDIOVASCULAR DISEASES |
CA2293718A1 (en) * | 1997-06-10 | 1998-12-17 | Medlyte Diagnostics, Inc. | Methods for early detection of heart disease |
US6013622A (en) * | 1998-04-15 | 2000-01-11 | Nutriceutical Technology Corporation | Method of regulating appetite and metabolism |
US6475530B1 (en) * | 2000-05-31 | 2002-11-05 | Eric H. Kuhrts | Methods and compositions for producing weight loss |
US6631330B1 (en) * | 2000-08-21 | 2003-10-07 | Assistance Publique-Hopitaux De Paris (Ap-Hp) | Diagnosis method of inflammatory, fibrotic or cancerous disease using biochemical markers |
US6573083B1 (en) * | 2000-08-24 | 2003-06-03 | Stanley Raider | Method of weight reduction in human beings |
EP1417629B1 (en) * | 2001-07-06 | 2008-02-20 | Lipomics Technologies, Inc. | Generating, viewing, interpreting, and utilizing a quantitative database of metabolites |
US6762035B1 (en) * | 2002-02-04 | 2004-07-13 | Surendra K. Gupta | Method and test strips for the measurement of fat loss during weight loss programs |
CA2477909A1 (en) * | 2002-03-11 | 2003-09-25 | Lipomics Technologies, Inc. | Novel metabolic targets and markers |
-
2005
- 2005-09-13 US US11/226,616 patent/US20060088860A1/en not_active Abandoned
- 2005-09-13 CA CA002579809A patent/CA2579809A1/en not_active Abandoned
- 2005-09-13 EP EP05797616A patent/EP1789806A2/en not_active Withdrawn
- 2005-09-13 AU AU2005284830A patent/AU2005284830A1/en not_active Abandoned
- 2005-09-13 WO PCT/US2005/032920 patent/WO2006031963A2/en active Application Filing
-
2008
- 2008-11-26 US US12/324,017 patent/US20090221081A1/en not_active Abandoned
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2003028271A2 (en) * | 2001-09-24 | 2003-04-03 | Lipomics Technologies, Inc. | Methods of using quantitative lipid metabolome data |
Non-Patent Citations (2)
Title |
---|
C.-E. VÖLCKER UND W. HAUDE: "Fatty acid composition of liver and adipose tissue lipids in Wistar rats with fat diet-induced obesitiy" DIE NAHRUNG, vol. 29, 1985, pages 577-583, XP009059093 * |
WATKINS STEVEN M: "Lipomic profiling in drug discovery, development and clinical trial evaluation." CURRENT OPINION IN DRUG DISCOVERY & DEVELOPMENT. JAN 2004, vol. 7, no. 1, January 2004 (2004-01), pages 112-117, XP009059092 ISSN: 1367-6733 * |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2008021192A2 (en) | 2006-08-08 | 2008-02-21 | Lipomics Technologies, Inc. | Markers of non-alcoholic fatty liver disease (nafld) and non-alcoholic steatohepatitis (nash) and methods of use thereof |
EP2057473A2 (en) * | 2006-08-08 | 2009-05-13 | Lipomics Technologies, Inc. | Markers of non-alcoholic fatty liver disease (nafld) and non-alcoholic steatohepatitis (nash) and methods of use thereof |
EP2057473A4 (en) * | 2006-08-08 | 2009-09-02 | Lipomics Technologies Inc | Markers of non-alcoholic fatty liver disease (nafld) and non-alcoholic steatohepatitis (nash) and methods of use thereof |
EP2607902A1 (en) * | 2006-08-08 | 2013-06-26 | Lipomics Technologies, Inc. | Markers of non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) and methods of use thereof |
EP3285072A1 (en) * | 2006-08-08 | 2018-02-21 | Metabolon, Inc. | Markers of non-alcoholic fatty liver disease (nafld) and non-alcoholic steatohepatitis (nash) and methods of use thereof |
US10299501B2 (en) | 2011-10-05 | 2019-05-28 | DuPont Nutrition USA, Inc. | Stabilizer composition of microcrystalline cellulose and carboxymethylcellulose, method for making, and uses |
WO2014188202A1 (en) * | 2013-05-24 | 2014-11-27 | King's College London | Biomarkers |
CN106680473A (en) * | 2017-01-23 | 2017-05-17 | 首都医科大学附属北京朝阳医院 | Application of biological marker to screening of drugs for treating or relieving metabolic syndrome |
CN106680473B (en) * | 2017-01-23 | 2019-04-09 | 首都医科大学附属北京朝阳医院 | Purposes of the biomarker in screening treatment or the drug for alleviating metabolic syndrome |
Also Published As
Publication number | Publication date |
---|---|
EP1789806A2 (en) | 2007-05-30 |
US20090221081A1 (en) | 2009-09-03 |
WO2006031963A3 (en) | 2006-05-26 |
US20060088860A1 (en) | 2006-04-27 |
AU2005284830A1 (en) | 2006-03-23 |
CA2579809A1 (en) | 2006-03-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20060088860A1 (en) | Metabolite markers for weight management | |
Zhou et al. | Identification of lysophosphatidylcholines and sphingolipids as potential biomarkers for acute aortic dissection via serum metabolomics | |
US10001468B2 (en) | Biomarkers for differentiating between non-alcoholic steatohepatitis (NASH) and non-alcoholic fatty liver disease (NAFLD) | |
Lv et al. | Identification of possible biomarkers for breast cancer from free fatty acid profiles determined by GC–MS and multivariate statistical analysis | |
EP3285072B1 (en) | Markers of non-alcoholic fatty liver disease (nafld) and non-alcoholic steatohepatitis (nash) and methods of use thereof | |
US20150011424A1 (en) | Method for determining liver fat amount and method for diagnosing nafld | |
Domínguez et al. | Lipidomic profiling of endometrial fluid in women with ovarian endometriosis | |
Furse et al. | A high-throughput platform for detailed lipidomic analysis of a range of mouse and human tissues | |
EP2126589A2 (en) | Metabolic markers of diabetic conditions and methods of use thereof | |
CN108872579A (en) | Tool and method for the diagnosis of pancreatic cancer in subject | |
CN108445241A (en) | Iipidomic mark for identifying high risk patients with coronary artery disease | |
Moritz et al. | Reference intervals for serum sphingosine-1-phosphate in the population-based Study of Health in Pomerania | |
Jiang et al. | Plasma lipidomics profiling reveals biomarkers for papillary thyroid cancer diagnosis | |
Horta et al. | Analysis of the association between fatigue and the plasma lipidomic profile of inflammatory bowel disease patients | |
Kou et al. | Discovery of potential biomarkers for postmenopausal osteoporosis based on untargeted GC/LC-MS | |
CN107454940A (en) | The serum biomarkers of hepatocellular carcinoma (HCC) | |
Le Gouellec et al. | What clinical metabolomics will bring to the medicine of tomorrow | |
KR101598597B1 (en) | An Apparatus diagnosing high-LDL-cholesterol disease using plasma metabolites and a method for diagnosing high-LDL-cholesterol disease thereby | |
Zoabi et al. | Adipose tissue composition determines its computed tomography radiodensity | |
Jung et al. | Age-related increase in LDL-cholesterol is associated with enhanced oxidative stress and disturbed sphingolipid metabolism | |
Kaya et al. | Serum sphingolipidomic analysis in acne vulgaris patients | |
WO2011089146A1 (en) | Method for assaying diseases characterised by dyslipidemia | |
Jung et al. | Associations between metabolomic‐identified changes of biomarkers and arterial stiffness in subjects progressing to impaired fasting glucose | |
KR20160087035A (en) | Kit and Method for Diagnosing Diabetes mellitus using PBMC Metabolites | |
Sharma et al. | MR spectroscopy in breast cancer metabolomics |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A2 Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BW BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE EG ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KM KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NA NG NI NO NZ OM PG PH PL PT RO RU SC SD SE SG SK SL SM SY TJ TM TN TR TT TZ UA UG US UZ VC VN YU ZA ZM ZW |
|
AL | Designated countries for regional patents |
Kind code of ref document: A2 Designated state(s): BW GH GM KE LS MW MZ NA SD SL SZ TZ UG ZM ZW AM AZ BY KG KZ MD RU TJ TM AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LT LU LV MC NL PL PT RO SE SI SK TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG |
|
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
WWE | Wipo information: entry into national phase |
Ref document number: 2579809 Country of ref document: CA |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2005797616 Country of ref document: EP |
|
WWE | Wipo information: entry into national phase |
Ref document number: 2005284830 Country of ref document: AU |
|
ENP | Entry into the national phase |
Ref document number: 2005284830 Country of ref document: AU Date of ref document: 20050913 Kind code of ref document: A |
|
WWP | Wipo information: published in national office |
Ref document number: 2005284830 Country of ref document: AU |
|
WWP | Wipo information: published in national office |
Ref document number: 2005797616 Country of ref document: EP |