WO2009012595A1 - Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders - Google Patents
Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders Download PDFInfo
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- WO2009012595A1 WO2009012595A1 PCT/CA2008/001366 CA2008001366W WO2009012595A1 WO 2009012595 A1 WO2009012595 A1 WO 2009012595A1 CA 2008001366 W CA2008001366 W CA 2008001366W WO 2009012595 A1 WO2009012595 A1 WO 2009012595A1
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- G—PHYSICS
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- 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
- G01N33/6803—General methods of protein analysis not limited to specific proteins or families of proteins
- G01N33/6848—Methods of protein analysis involving mass spectrometry
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- 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
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- 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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2405/00—Assays, e.g. immunoassays or enzyme assays, involving lipids
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2405/00—Assays, e.g. immunoassays or enzyme assays, involving lipids
- G01N2405/04—Phospholipids, i.e. phosphoglycerides
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- G—PHYSICS
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/30—Psychoses; Psychiatry
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/38—Pediatrics
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y10T—TECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
- Y10T436/00—Chemistry: analytical and immunological testing
- Y10T436/24—Nuclear magnetic resonance, electron spin resonance or other spin effects or mass spectrometry
Definitions
- the present invention relates to the diagnosis, risk assessment, and monitoring of Autism Spectrum Disorder (ASD). More specifically the present invention relates to the measurement of small molecules or metabolites that are found to have different abundances between persons with a clinical manifestation of ASD and subjects not expressing symptoms of ASD. Further, this invention relates to the monitoring of putative therapeutic strategies designed to ameliorate the biochemical abnormalities associated with ASD.
- ASSD Autism Spectrum Disorder
- Autism is a lifelong disorder of unknown origin.
- the disorder is characterized by behavioural, developmental, neuropathological, and sensory abnormalities (American Psychiatric Association 1994) and is usually diagnosed between the ages of 3 and 10 with peak prevalence rates observed in children aged 5-8 (Yeargin- Allsopp, Rice et al. 2003).
- decreased cerebellar Purkinje cell density (Courchesne 1997; Palmen, van Engeland et al. 2004)
- increased oxidative stress Yorbik, Sayal et al. 2002; Sogut, Zoroglu et al. 2003; Chauhan, Chauhan et al. 2004; James, Cutler et al. 2004; Zoroglu, Armutcu et al. 2004; Chauhan and Chauhan 2006)
- abnormal methionine/homocysteine metabolism (James, Cutler et al. 2004) are the only robust biological characteristics of autism.
- autism Although there is debate as to whether autism has a pre- (Courchesne, Redcay et al. 2004) or post-natal origin (Kern and Jones 2006), it is generally accepted that the symptoms and pathology persist throughout the life of the subject (Bauman and Kemper 2005). These findings suggest that there is an underlying and ongoing biochemical abnormality in autism, regardless of its origin. However, no such underlying biochemical abnormalities have been reported that correlate with the etiology or symptomology of ASD. As such, there is no biochemical test for autism.
- VLCFA very long chain fatty acid
- an experimental ASD therapeutic can modify the above biochemical ASD phenotype such that some ASD biochemical markers return to non-ASD levels and that some ASD biochemical markers remain unchanged. It has further been determined that ASD subjects taking acetyl-carnitine exhibit biochemical changes that differentiate them from both ASD subjects not taking carnitine as well as non-ASD subjects not taking acetyl-carnitine. As such, methods for the monitoring of experimental ASD therapeutics in general and for the specific monitoring of acetyl-carnitine therapy are provided.
- a method for the differential biochemical characterization of subjects presenting with ASD is provided.
- This differential biochemical characterizing has ramifications on the treatment and management of subjects presenting ASD symptoms.
- ASD subjects with similar clinical phenotypes have dramatically different biochemical phenotypes.
- These findings indicate that different therapeutic strategies may need to be developed for different ASD subjects depending on the subject's biochemical phenotype.
- the present findings indicate that the monitoring of the dose and therapeutic effectiveness of an ASD therapeutic in a subject diagnosed with ASD is preferably personalized to that particular subject's biochemical profile.
- the monitoring of saturated VLCFA levels may represent the most sensitive determiner of effective therapy or dosage, but such measurements may be of little or no value to an ASD subject exhibiting high polyunsaturated VLCFA levels and normal saturated VLCFA levels.
- the present invention provides for a method for diagnosing a human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or identifying a human subject's risk of ASD, the method comprising the steps of: a) analyzing a sample obtained from a patient to obtain quantifying data for one or more accurate masses; b) comparing the quantifying data for said one or more accurate masses to corresponding data obtained from one or more reference samples; and c) using said comparison to diagnose the human subject's health state or change in health state for ASD based on the differences between the quantifying data and the corresponding data of the one or more accurate masses; wherein the one or more accurate masses is listed in any one of Tables 2 to 10.
- ASD Autism Spectrum Disorder
- the present invention provides for a method for diagnosing a human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or identifying a human subject's risk of ASD, the method comprising the steps of:
- ASD Autism Spectrum Disorder
- VLCFA saturated or monounsaturated very long chain fatty acid
- DHA docosahexaenoic acid
- DHA precursors 24:5, 24:6
- polyunsaturated VLCFA containing phospholipids and combinations thereof
- the present invention provides for a method for diagnosing a human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or identifying a human subject's risk of ASD, the method comprising the steps of:
- ASD Autism Spectrum Disorder
- the present invention provides for a method for diagnosing a human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or identifying a human subject's risk of ASD, the method comprising: comparing quantifying data comprising one or more accurate masses listed in any one of Tables 2 to 10 of a sample from the human subject to corresponding data obtained from one or more reference samples; wherein the human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or risk of ASD is based on a difference in intensity of the one or more accurate masses between the sample from the human subject and one or more reference samples.
- ASSD Autism Spectrum Disorder
- the present invention provides for a method for diagnosing a human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or identifying a human subject's risk of ASD, the method comprising: comparing quantifying data comprising one or more metabolites listed in any one of Tables 3 to 10 of a sample from the human subject to corresponding data obtained from one or more reference samples; wherein the human subject's health state or change in health state for Autism Spectrum Disorder (ASD) or risk of ASD is based on a difference in intensity of the one or more metabolites between the sample from the human subject and one or more reference samples.
- ASSD Autism Spectrum Disorder
- Figure 1 is a summary of PtdEtn (phosphatidlyethanolamine) changes in plasma of autistic subjects
- Figure 6 is a graph illustrating a within family comparison of key DHA containing PlsEtn and PtdEtn and AA containing PlsEtn in longitudinal samples collected over the course of one year from autistic subjects and their asymptomatic siblings. Values are control-normalized and expressed as mean +/- SEM of the ratio to PtdEtn 16:0/18:0, * , p ⁇ 0.05 vs. control.
- a subject's health state or change in health state with respect to ASD may be determined.
- Methods for diagnosing a subject's health state for example for diagnosing the presence or absence of ASD are provided, and methods for diagnosing a change in health state, for example for monitoring an ASD therapy, are provided.
- Illustrative methods for diagnosing a subject's health state or change in health state with regard to ASD of the present invention comprise the steps of: a) analyzing a sample(s) obtained from a human subject to obtain quantifying data for one or more than one metabolite marker or accurate mass;
- the illustrative methods may further include the preliminary step of obtaining one or more than one sample from the human subject for analysis.
- metabolic it is meant specific small molecules, the levels or intensities of which are measured in a sample, and that may be used as markers to diagnose a disease state. These small molecules may also be referred to herein as “metabolite marker”, “metabolite component”, “biomarker”, or “biochemical marker”.
- a method for diagnosing the biochemical ASD phenotype of a subject comprising the steps of: introducing one or more than one sample from one or more than one patient with probable ASD into a high resolution mass spectrometer (for example, and without wishing to be limiting, a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (FTMS)); obtaining quantifying data for one or more than one metabolite marker; optionally creating a database of said quantifying data; comparing the quantifying data from the sample with corresponding reference data collected from non-ASD subjects; and using said comparison to determine the biochemical ASD phenotype of the subject.
- the biochemical ASD phenotype of the subject may be determined based on the differences identified when comparing the quantifying data from the sample with the corresponding reference data. The differences between ASD and non-ASD subjects are described in any one of Tables 2, 11-18.
- a method for identifying subjects at risk of ASD comprising the steps of: introducing one or more than one sample from one or more than one subject of unknown ASD status into a high resolution mass spectrometer (for example, and without wishing to be limiting, a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (FTMS)); obtaining quantifying data for one or more than one of the parent masses listed in any one of tables 2-10; optionally creating a database of said quantifying data; comparing the quantifying data from the sample with corresponding reference data collected from non-ASD subjects; and using said comparison to determine whether the subject has elevated risk of ASD.
- FTMS Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
- a method for monitoring an ASD therapy comprising the steps of: introducing a plurality of samples from one or more than one ASD subject into a high resolution mass spectrometer (for example, and without wishing to be limiting, a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (FTMS)); obtaining quantifying data for one or more than one of the parent masses listed in any one of tables 2-10; optionally creating a database of said quantifying data; comparing the quantifying data from the plurality of samples with each other and with corresponding reference data collected from non-ASD subjects and/or with previous collected quantifying data from a pre-therapy stage or an earlier-therapy stage of the subject(s) and using said comparison to determine whether the therapeutic strategy had a positive, negative, or no effect on the subject's underlying biochemical phenotype.
- FTMS Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
- a method for diagnosing the biochemical ASD phenotype of a subject comprising the steps of: introducing one or more than one sample from one or more than one patient with clinically diagnosed ASD into a multi-stage mass spectrometer (for example, and without wishing to be limiting, a triple quadrupole mass spectrometer (TQ)); obtaining quantifying data for one or more than one of the metabolites listed in any one of Tables 3-10; optionally creating a database of said quantifying data; comparing the quantifying data from the sample with corresponding reference data collected from non-ASD subjects; and using said comparison to determine whether the subject has ASD.
- a multi-stage mass spectrometer for example, and without wishing to be limiting, a triple quadrupole mass spectrometer (TQ)
- TQ triple quadrupole mass spectrometer
- a method for identifying subjects at risk of ASD comprising the steps of: introducing one or more than one sample from one or more than one subject of unknown ASD status into a multi-stage mass spectrometer (for example, and without wishing to be limiting, a triple quadrupole mass spectrometer (TQ)); obtaining quantifying data for one or more than one of the metabolites listed in any one of Tables 3-10; optionally creating a database of said quantifying data; comparing the quantifying data from the sample with corresponding reference data collected from non-ASD subjects; and using said comparison to determine whether the subject has elevated risk of ASD.
- a multi-stage mass spectrometer for example, and without wishing to be limiting, a triple quadrupole mass spectrometer (TQ)
- TQ triple quadrupole mass spectrometer
- a method for monitoring an ASD therapy comprising the steps of: introducing a plurality of samples from one or more than one ASD subject into a multi-stage mass spectrometer (for example, and without wishing to be limiting, a triple quadrupole mass spectrometer (TQ)); obtaining quantifying data for one or more than one of the metabolites listed in any one of Tables 3-10; optionally creating a database of said quantifying data; comparing the quantifying data from the plurality of samples with each other and/or with corresponding reference data collected from non-ASD subjects and/or with previously collected quantifying data from a pre-therapy stage or an earlier-therapy stage of the subject(s) and using said comparison to determine whether the therapeutic strategy had a positive, negative, or no effect on the subject's underlying biochemical phenotype.
- a multi-stage mass spectrometer for example, and without wishing to be limiting, a triple quadrupole mass spectrometer (TQ)
- TQ triple quadrupole mass
- a method for diagnosing the biochemical ASD phenotype of a subject comprising the steps of: obtaining quantifying data for one or more than one of the metabolites listed in any one of Tables 2-10 from one or more than one ASD subject; optionally creating a database of said quantifying data; comparing the quantifying data from the sample with corresponding reference data collected from non-ASD subjects; and using said comparison to determine whether the subject has ASD.
- a method for identifying subjects at risk of ASD comprising the steps of: obtaining quantifying data for one or more than one of the metabolites listed in any one of Tables 2-10 from one or more than one subject of unknown ASD status; optionally creating a database of said quantifying data; comparing the quantifying data from the sample with corresponding reference data collected from non-ASD subjects; and using said comparison to determine whether the subject has elevated risk of ASD.
- a method for monitoring an ASD therapy comprising the steps of: obtaining quantifying data for one or more than one of the metabolites listed in any one of Tables 2-10 from a plurality of samples collected from one or more than one ASD subject; optionally creating a database of said quantifying data; comparing the quantifying data from the plurality of samples with each other and/or with corresponding reference data collected from non-ASD subjects and/or with previously collected quantifying data from a pre-therapy stage or an earlier-therapy stage of the subject(s); and using said comparison to determine whether the therapeutic strategy had a positive, negative, or no effect on the subject's underlying biochemical phenotype.
- metabolites listed in Tables 2-10 may be used to quantify the metabolites listed in Tables 2-10 including colorimethc chemical assays (UV, or other wavelength), antibody- based enzyme-linked immunosorbant assays (ELISAs), chip-based and polymerase- chain reaction for nucleic acid detection assays, bead-based nucleic-acid detection methods, dipstick chemical assays or other chemical reaction, image analysis such as magnetic resonance imaging (MRI), positron emission tomography (PET) scan, computerized tomography (CT) scan, nuclear magnetic resonance (NMR), and various mass spectra metry-based systems.
- MRI magnetic resonance imaging
- PET positron emission tomography
- CT computerized tomography
- NMR nuclear magnetic resonance
- illustrative methods for diagnosing a subject's health state or change in health state with regard to ASD of the present invention comprise the steps of:
- the illustrative methods may further include the preliminary step of obtaining one or more than one sample from the human subject for analysis.
- the step of analyzing the sample may comprise analyzing the sample using a mass spectrometer (MS).
- MS mass spectrometer
- such mass spectrometer may be of the FTMS, orbitrap, time of flight (TOF), magnetic sector, linear ion trap (LIT) or quadrupole types.
- the mass spectrometer may be equipped with an additional pre-detector mass filter.
- MSn refers to the situation where the parent ion is fragmented by collision induced dissociation (CID) or other fragmentation procedures to create fragment ions, and then one or more than one of said fragments are detected by the mass spectrometer. Such fragments may then be further fragmented to create further fragments.
- the sample may be introduced into the mass spectrometer using a liquid or gas chromatographic system or by direct injection.
- differential diagnosis or “differentially diagnosing” it is meant that various aspects of a disease state may be distinguished from one another.
- the methods disclosed herein allow for differential diagnosis of various biochemical phenotypes of ASD; for example and without wishing to be limiting, the methods disclosed herein may provide the diagnosis of subjects with or at risk of ASD with the biochemical phenotype of:
- VLCFA very long chain fatty acid
- any type of biological sample that originates from anywhere within the body, for example but not limited to, blood (serum/plasma), CSF, urine, stool, breath, saliva, or biopsy of any solid tissue including tumor, adjacent normal, smooth and skeletal muscle, adipose tissue, liver, skin, hair, brain, kidney, pancreas, lung, colon, stomach, or other may be used.
- samples that are plasma.
- plasma While the term "plasma” is used herein, those skilled in the art will recognize that serum or whole blood or a sub- fraction of whole blood may also be used.
- CSF may be obtained by a lumbar puncture requiring a local anesthetic.
- a blood sample when drawn from a patient there are several ways in which the sample may be processed.
- the range of processing can be as little as none (i.e. frozen whole blood) or as complex as the isolation of a particular cell type.
- the most common and routine procedures involve the preparation of either serum or plasma from whole blood. All blood sample processing methods, including spotting of blood samples onto solid-phase supports, such as filter paper or other immobile materials, are within the scope of the methods described herein.
- the processed blood or plasma sample described above may then be further processed to make it compatible with the methodical analysis technique to be employed in the detection and measurement of the metabolites contained within the processed blood sample.
- the types of processing can range from as little as no further processing to as complex as differential extraction and chemical derivatization.
- Extraction methods may include sonication, soxhlet extraction, microwave assisted extraction (MAE), supercritical fluid extraction (SFE), accelerated solvent extraction (ASE), pressurized liquid extraction (PLE), pressurized hot water extraction (PHWE) and/or surfactant assisted extraction (PHWE) in common solvents such as methanol, ethanol, mixtures of alcohols and water, or organic solvents such as ethyl acetate or hexane.
- a method of particular interest for extracting metabolites for FTMS non-targeted analysis and for flow injection LC-MS/MS analysis is to perform a liquid/liquid extraction whereby non- polar metabolites dissolve in an organic solvent and polar metabolites dissolve in an aqueous solvent.
- the extracted samples may be analyzed using any suitable method including those known in the art.
- extracts of biological samples are amenable to analysis on essentially any mass spectrometry platform, either by direct injection or following chromatographic separation.
- Typical mass spectrometers are comprised of a source that ionizes molecules within the sample, and a detector for detecting the ionized molecules or fragments of molecules.
- Non-limiting examples of common sources include electron impact, electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI), atmospheric pressure photo ionization (APPI), matrix assisted laser desorption ionization (MALDI), surface enhanced laser desorption ionization (SELDI), and derivations thereof.
- Common mass separation and detection systems can include quadrupole, quadrupole ion trap, linear ion trap, time-of-flight (TOF), magnetic sector, ion cyclotron (FTMS), Orbitrap, and derivations and combinations thereof.
- TOF time-of-flight
- FTMS ion cyclotron
- Orbitrap derivations and combinations thereof.
- the advantage of FTMS over other MS-based platforms is its high resolving capability that allows for the separation of metabolites differing by only hundredths of a Dalton, many of which would be missed by lower resolution instruments.
- the metabolites are generally characterized by their accurate mass, as measured by mass spectrometry technique.
- the accurate mass may also be referred to as "accurate neutral mass” or “neutral mass”.
- the accurate mass of a metabolite is given herein in Daltons (Da), or a mass substantially equivalent thereto. By “substantially equivalent thereto”, it is meant that a +/- 5 ppm difference in the accurate mass would indicate the same metabolite.
- the accurate mass is given as the mass of the neutral metabolite.
- the metabolite will cause either a loss or gain of one or more hydrogen atoms and a loss or gain of an electron. This changes the accurate mass to the "ionized mass", which differs from the accurate mass by the mass of hydrogen atoms and electrons lost or gained during ionization.
- the accurate neutral mass will be referred to herein.
- the molecular formula of the neutral metabolite will be given.
- the molecular formula of the ionized metabolite will differ from the neutral molecular formula by the number of hydrogen atoms lost or gained during ionization or due to the addition of a non- hydrogen adduct ion.
- the "reference sample” is any suitable reference sample for the particular disease state.
- the reference sample may be a sample from a control individual, i.e., a person not suffering from ASD with or without a family history of ASD (also referred to herein as a " 'normal' counterpart"); the reference sample may also be a sample obtained from a patient clinically diagnosed with ASD.
- the one or more than one reference sample may be a first reference sample obtained from a non-ASD control individual.
- the one or more than one reference sample may further include a second reference sample obtained from a patient with clinically diagnosed ASD of the peroxisomal type, a third reference sample obtained from a patient with clinically diagnosed ASD of the mitochondrial type, a fourth reference sample obtained from a patient suffering from clinically diagnosed ASD of an unknown type, or any combination thereof.
- the reference sample may include a sample obtained an earlier time period either pre-therapy or during therapy to compare the change in disease state as a result of therapy.
- Plasma samples were stored at -8O 0 C until thawed for analysis. All extractions were performed on ice. Metabolites were extracted using 1 % ammonium hydroxide and ethyl acetate (EtOAc) in the ratio of 1 :1 :5, respectively, three times followed by two more extractions with 0.33 % formic acid and EtOAc in the ratio of 1 :1 :5. Samples were centrifuged between extractions at 4°C for 10 min at 3500 rpm, and the organic layers combined. The organic and aqueous extracts were then stored at -80 0 C until analysis.
- EtOAc ethyl acetate
- Plasma extracts were analyzed by direct injection into a FTMS and ionization by either ESI or atmospheric pressure chemical ionization (APCI) in both positive and negative modes.
- Sample extracts were diluted either three or six-fold in methanol:0.1%(v/v) ammonium hydroxide (50:50, v/v) for negative ionization modes, or in methanols.1 % (v/v) formic acid (50:50, v/v) for positive ionization modes.
- sample extracts were directly injected without diluting.
- instrument conditions were tuned to optimize ion intensity and broad-band accumulation over the mass range of 100-1000 amu according to the instrument manufacturer's recommendations.
- a mixture of the above mentioned standards was used to internally calibrate each sample spectrum for mass accuracy over the acquisition range of 100-1000 amu.
- Mass Spectrometry Data Processing Using a linear least-squares regression line, mass axis values were calibrated such that each internal standard mass peak had a mass error of ⁇ 1 p. p.m. compared with its theoretical mass. Using XMASS software from Bruker Daltonics Inc., data file sizes of 1 megaword were acquired and zero- filled to 2 megawords. A sinm data transformation was performed prior to Fourier transform and magnitude calculations. The mass spectra from each analysis were integrated, creating a peak list that contained the accurate mass and absolute intensity of each peak. Compounds in the range of 100-2000 m/z were analyzed.
- Example 2 The Diagnosis and Individual Characterization of ASD subjects using LC-MS/MS and the Evaluation of a ASD Therapeutic
- Plasma levels of 26:0 containing PtdEtn were not observed to be increased relative to 22:0 containing PtdEtn. These results are contrary to those observed from subjects suffering from peroxisomal disorders, where 26:0 is elevated to a much greater extent than 22:0 (Moser and Moser 1996). Therefore the methods described in this application provide a means to differentiate ASD from peroxisomal disorders.
- Example 5 Identifying subjects with elevated risk of ASD
- Table 1 Clinical information summary.
- Table 2 Accurate mass features differing between autistic subjects versus controls.
- Table 7 Molecular formula, accurate mass, and LC-MS/MS parameters for phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing four unsaturations.
- Table 8 Molecular formula, accurate mass, and LC-MS/MS parameters for phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing five unsaturations.
- Table 10 Molecular formula, accurate mass, and LC-MS/MS parameters for ethanolamine plasmalogens (PlsEtn) metabolites with selected sn-2 position fatty acids.
- Table 11 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with saturated fatty acids at the sn-2 position in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- Table 12 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing one unsaturation in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- PtdEtn 18 0/30 1 912 7 / 283 2 0 002 0 000 0 003 0 000 0 002 0 000 1 32 2 8E-02 1 26 1 8E-01 0 95 7 6E-01
- Table 13 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing two unsaturations in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- Table 14 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing three unsaturations in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- Table 15 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing four unsaturations in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- Table 16 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing five unsaturations in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- Table 17 Plasma levels of phosphatidylethanolamine (PtdEtn) metabolites with sn-2 position fatty acids containing six unsaturations in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
- PtdEtn phosphatidylethanolamine
- Table 18 Plasma levels of ethanolamine plasmalogens (PlsEtn) metabolites with selected sn-2 position fatty acids in non-autistic children, autistic children not taking carnitine supplements, and autistic children taking carnitine supplements (All values are expressed as the ratio to PtdEtn 16:0/18:0).
Abstract
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Priority Applications (8)
Application Number | Priority Date | Filing Date | Title |
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JP2010517243A JP5306345B2 (en) | 2007-07-26 | 2008-07-25 | Methods for diagnosing, assessing risk and monitoring autism spectrum disorders |
CN200880107178A CN101802607A (en) | 2007-07-26 | 2008-07-25 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
CA2693177A CA2693177A1 (en) | 2007-07-26 | 2008-07-25 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
AU2008280806A AU2008280806B2 (en) | 2007-07-26 | 2008-07-25 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
EP08783279A EP2183589A4 (en) | 2007-07-26 | 2008-07-25 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
US12/670,426 US8273575B2 (en) | 2007-07-26 | 2008-07-25 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
US13/594,455 US20120322088A1 (en) | 2007-07-26 | 2012-08-24 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
AU2015200060A AU2015200060B2 (en) | 2007-07-26 | 2015-01-07 | Methods for the diagnosis, risk assessment, and monitoring of autism spectrum disorders |
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2012064880A2 (en) * | 2010-11-09 | 2012-05-18 | University Of Washington Through Its Center For Commercialization | Urinary porphyrins as biomarkers of autistic spectrum disorder risk |
CN102597781A (en) * | 2009-10-14 | 2012-07-18 | 国立大学法人浜松医科大学 | Method and marker for determination of degree of risk of onset of high-functioning autism |
JP2013525801A (en) * | 2010-04-29 | 2013-06-20 | ウィスコンシン・アルムニ・リサーチ・ファウンデーション | Metabolic biomarkers of autism |
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CN113009122A (en) * | 2014-04-11 | 2021-06-22 | 美国控股实验室公司 | Methods and systems for determining risk of autism spectrum disorders |
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Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2012037365A1 (en) | 2010-09-16 | 2012-03-22 | Quest Diagnostics Investments Incorporated | Mass spectrometric determination of eicosapentaenoic acid and docosahexaenoic acid |
US10060932B2 (en) | 2013-07-09 | 2018-08-28 | Stemina Biomarker Discovery, Inc. | Biomarkers of autism spectrum disorder |
US20150294081A1 (en) | 2014-04-11 | 2015-10-15 | Synapdx Corporation | Methods and systems for determining autism spectrum disorder risk |
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US20220003753A1 (en) * | 2018-11-06 | 2022-01-06 | Stalicla Sa | Metabolic profiling for the diagnosis of a subset of idiopathic autism spectrum disorder patients, ads phenotype 1 |
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Family Cites Families (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2298181C (en) | 2000-02-02 | 2006-09-19 | Dayan Burke Goodnough | Non-targeted complex sample analysis |
DE60203388T2 (en) * | 2001-05-31 | 2006-04-13 | Daiichi Suntory Pharma Co., Ltd. | PROCESS FOR DETERMINING PLATES ACTIVATING FACTOR |
JP2003028849A (en) * | 2001-07-10 | 2003-01-29 | Hiromasa Tojo | Simultaneous autoanalyzer for lipid compound |
DE60337003D1 (en) * | 2002-03-22 | 2011-06-16 | Phenomenome Discoveries Inc | METHOD OF VISUALIZING UNSATURED METABOLOMIC DATA PRODUCED BY ION CYCLOTRON RESONANCE FOURIER TRANSFORMATION MASS SPECTROMETERS |
SE0300586L (en) * | 2003-03-04 | 2004-09-05 | Forskarpatent I Syd Ab | Diagnosis of autism |
JP2006226730A (en) * | 2005-02-15 | 2006-08-31 | Univ Of Tokyo | Identifying method of phospholipid produced by combining specific and exhaustive methods |
JP2008542742A (en) * | 2005-06-03 | 2008-11-27 | ケンブリッジ エンタープライズ リミティッド | Biomarker |
KR100967573B1 (en) * | 2005-06-30 | 2010-07-05 | 바이오크레이츠 라이프 사이언시스 아게 | Device for quantitative analysis of a metabolite profile |
KR20080027384A (en) * | 2005-07-08 | 2008-03-26 | 마텍 바이오싸이언스스 코포레이션 | Polyunsaturated fatty acids for treatment of dementia and pre-dementia-related conditions |
JP4176749B2 (en) * | 2005-07-29 | 2008-11-05 | 学校法人帝京大学 | Disease testing method |
CA2621126C (en) | 2005-09-15 | 2011-04-12 | Phenomenome Discoveries Inc. | Method and apparatus for fourier transform ion cyclotron resonance mass spectrometry |
US20080020472A1 (en) * | 2005-11-22 | 2008-01-24 | Frantz Biomarkers, Llc | Method for detecting an inflammatory disease or cancer |
KR20080104350A (en) * | 2006-02-28 | 2008-12-02 | 페노미넘 디스커버리스 인코포레이티드 | Methods for the diagnosis of dementia and other neurological disorders |
-
2008
- 2008-07-25 EP EP08783279A patent/EP2183589A4/en not_active Withdrawn
- 2008-07-25 AU AU2008280806A patent/AU2008280806B2/en not_active Ceased
- 2008-07-25 CN CN200880107178A patent/CN101802607A/en active Pending
- 2008-07-25 WO PCT/CA2008/001366 patent/WO2009012595A1/en active Application Filing
- 2008-07-25 US US12/670,426 patent/US8273575B2/en not_active Expired - Fee Related
- 2008-07-25 CA CA2693177A patent/CA2693177A1/en not_active Abandoned
- 2008-07-25 JP JP2010517243A patent/JP5306345B2/en not_active Expired - Fee Related
- 2008-07-25 SG SG2012048138A patent/SG182971A1/en unknown
-
2012
- 2012-08-24 US US13/594,455 patent/US20120322088A1/en not_active Abandoned
Non-Patent Citations (6)
Title |
---|
BELL ET AL.: "Essential fatty acids and phospholipase A2 in autistic spectrum disorders", PROSTAGLANDINS, LEUKOTRIENS AND ESSENTIAL FATTY ACIDS, vol. 71, 2004, pages 201 - 204, XP008129914 * |
BELL ET AL.: "Red blood cell fatty acid compositions in a patient with autistic spectrum disorder: a characteristics abnormality in neurodevelopmental disorders", PROSTAGLANDINS, LEUKOTRIENS AND ESSENTIAL FATTY ACIDS, vol. 63, no. 1/2, 2000, pages 21 - 25, XP008129948 * |
BU B. ET AL.: "Fatty acid compositions of red blood cell phospholipids in children with autism", PROSTAGLANDINS, LEUKOTRIENS AND ESSENTIAL FATTY ACIDS, vol. 74, 2006, pages 215 - 221, XP005361048 * |
RICHARDSON A.J. ET AL.: "Fatty acid metabolism in neurodevelopmental disorder: a new perspective on associations between attention-deficit/hyperactivity disorder dyslexia, dyspraxia and the autism spectrum", PROSTAGLANDINS, LEUKOTRIENS AND ESSENTIAL FATTY ACIDS, vol. 63, no. 1/2, 2000, pages 1 - 9, XP001028107 * |
See also references of EP2183589A4 * |
SLIWINSKI ET AL.: "Polyunsaturated fatty acids: Do they have a role in the pathophysiology of autism?", NEUROENDOCRINOLOGY LETTERS, vol. 27, no. 4, 2006, pages 465 - 471, XP008129915 * |
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EP2490028A4 (en) * | 2009-10-14 | 2013-07-10 | Nat University Corp Hamamatsu University School Of Medicine | Method and marker for determination of degree of risk of onset of high-functioning autism |
JP2013525801A (en) * | 2010-04-29 | 2013-06-20 | ウィスコンシン・アルムニ・リサーチ・ファウンデーション | Metabolic biomarkers of autism |
WO2012064880A2 (en) * | 2010-11-09 | 2012-05-18 | University Of Washington Through Its Center For Commercialization | Urinary porphyrins as biomarkers of autistic spectrum disorder risk |
WO2012064880A3 (en) * | 2010-11-09 | 2012-09-27 | University Of Washington Through Its Center For Commercialization | Urinary porphyrins as biomarkers of autistic spectrum disorder risk |
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Also Published As
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US20110053287A1 (en) | 2011-03-03 |
JP2010534826A (en) | 2010-11-11 |
US20120322088A1 (en) | 2012-12-20 |
AU2008280806A1 (en) | 2009-01-29 |
EP2183589A1 (en) | 2010-05-12 |
EP2183589A4 (en) | 2011-03-16 |
US8273575B2 (en) | 2012-09-25 |
CN101802607A (en) | 2010-08-11 |
AU2008280806B2 (en) | 2014-12-11 |
SG182971A1 (en) | 2012-08-30 |
CA2693177A1 (en) | 2009-01-29 |
JP5306345B2 (en) | 2013-10-02 |
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