WO2018081202A1 - Markers of chronic fatigue syndrome - Google Patents

Abstract

Methods of detecting, monitoring, assessing and treating chronic fatigue syndrome (CFS) and associated diseases or conditions in a subject comprising measuring the amount of extracellular vesicles (EVs) in the bodily sample, or the expression level or activity of at least one biomarker associated with CFS expressed or detected in the EVs. The increased amount of EVs in the bodily sample and/or the increased expression or detection level of the biomarker of interest correlate with the degree or severity of CFS.

Description

MARKERS OF CHRONIC FATIGUE SYNDROME CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the priority benefit of U.S. Provisional Patent

Application No. 62/412,368, filed October 25, 2016. The entire contents of which is incorporated by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0002] This invention was made with Government support under Grant Nos.

DK076852 and DK082451 awarded by the National Institutes of Health. The Government has certain rights in the invention. FIELD OF THE INVENTION

[0003] The present disclosure relates to chronic fatigue syndrome and related diseases.

BACKGROUND OF THE INVENTION

[0004] Chronic fatigue syndrome (CFS) is a serious and debilitating disorder with a wide spectrum of symptoms including pain, depression, and neurocognitive deterioration. The diagnosis of CFS has previously been made based on clinical symptoms that include a broad spectrum of disease from mild to debilitating. Therefore, in 2015, Institution of Medicine (IOM, USA) proposed a renamed CFS/myalgic encephalomyelitis (ME) to systemic exertion intolerance disease (SEID) with new diagnostic clinical criteria. However, there is currently no specific laboratory-based biomarker that allows for diagnosis and stratification of patients with CFS based on pathogenic mechanisms of disease.

[0005] Extracellular vesicles (EVs), mainly consist of exosomes and microparticles/microvesicles (MPs), are released from activated or dying cells and circulate in the bloodstream. Indeed, EVs are recognized as biomarkers in several other diseases including infectious diseases and cancer. Furthermore, EVs may contribute to disease progression as cell-to-cell communicators through the carrying of EV contents, such as miRNAs, proteins, or lipids, into target cells resulting in the activation of target cells.

[0006] It is believed that CFS is caused by the dysregulation of the neuronal- immunological system, but there is no candidate for specific CFS biomarkers in this system. It is reported that certain cytokines in the blood may be CFS biomarker candidates, but none have been fully validated. Overall, there are no reliable specific CFS biomarkers. Currently there are also no methods to determine disease severity, monitor disease progression, or the efficacy of therapy in patients with this condition other than doctor's diagnosis based on patient description.

SUMMARY OF THE INVENTION

[0007] The present invention provides that circulating extracellular vesicle (EV) number in CFS patients is higher than in that of healthy individuals. The circulating EV number is correlated with inflammation, such as serum C-reactive protein (CRP) and patient inflammatory history. Furthermore, circulating EV number is strongly correlated with brain inflammation in CFS.

[0008] In embodiments, the invention provides for the detection of biomarkers, including for example, the encapsulated microRNAs miR-21 and -146a. The invention provides that EV encapsulated miR-21 and -146a, have a positive correlation with brain inflammation, which is indicated with PK11195 (an isoquinoline carboxamide which binds selectively to the peripheral benzodiazepine receptor), in various brain regions, and CRP. Furthermore, these miRNAs have a negative correlation with DASB (a compound that binds to the serotonin transporter and has a reciprocal interaction with PK11195). Therefore, the invention provides for the encapsulated microRNAs in EVs ranked in Table I and the proteins in Table II as biomarkers for diagnosis of CFS. Furthermore, inhibition, binding, hindrance and antagonists of mRNA, lipids and proteins in the EVs are provided for therapeutic approaches for the treatment of CFS and related diseases and conditions. [0009] The invention provides methods for detection, diagnosis and treatment of

CFS comprising a biomarker panel consisting of a set of biomarkers selected from 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 30, 40, 50, 100 miRNAs in Table I and/or proteins in Table II.

[0010] BRIEF DESCRIPTION OF THE DRAWINGS [0011] Fig. 1A shows that the number of circulating EVs is significantly increased in CFS1, as well as CFS2, compared to healthy individuals. Fig. IB shows circulating EVs via dynamic light scatter. Fig. 1C shows circulating EVs via electron microscopy. Circulating EVs were characterized via dynamic light scatter in Fig. IB or electron microsopy in Fig. 1C into two populations: exosomes (<100 nm) and MPs (100-1000 nm). [0012] Fig. 2A shows that the circulating EV number was positively correlated with C-reactive protein (CRP) (r=0.448, p=0.001). Fig. 2B shows that the circulating EV number was negatively correlated with biological antioxidant potential (BAP) (r=-0.314, p=0.007).

[0013] Fig. 3 shows the specificity and sensitivity of circulating EV number with other indexes.

DETAILED DESCRIPTION

[0014] The invention provides the discovery of novel signaling factors in extracellular vesicles (EVs) that are formed and released from activated cells, such as inflammatory cells and neuronal cells, and damaged cells in CFS patients. CFS EVs found in patient blood can be detected and quantified using identified proteins, lipids, or microRNAs on or in the EVs by immunoassays (FACS, ELISA) or microRNA array.

[0015] Moreover, the invention provides specific miRNAs in the circulating EVs of CFS patients that allow quantification of CFS biomarkers in blood using microRNA- based assays. The invention provides specific proteins in circulating CFS EVs that allow quantification of CFS biomarkers in blood using immuno-based assays. The invention provides compositions and methods of therapeutic treatment of CFS comprising neutralizing EVs with specific an effective amount of anti-miRNAs, or antibodies, and inhibiting neuronal inflammation, thus improving the CFS and returning the patient to a healthy state.

[0016] The present invention may be understood more readily by reference to the following detailed description of the preferred embodiments of the invention and the Examples included herein. However, before the present methods and compositions are disclosed and described, it is to be understood that this invention is not limited to specific methods, specific conditions, specific sequences, specific host cells, etc., as such may, of course, vary, and the numerous modifications and variations therein will be apparent to those skilled in the art. It is also to be understood that the terminology used herein is for the purpose of describing specific embodiments only and is not intended to be limiting. It is also to be understood that as used in the specification and in the claims, "a" or "an" can mean one or more, depending upon the context in which it is used. Thus, for example, reference to "a vesicle" can mean that at least one vesicle can be utilized.

[0017] The invention provides a non-invasive or minimally invasive diagnostic method of detecting, monitoring, or assessing the degree, severity, or progression in a subject with chronic fatigue syndrome (CFS). In contrast to prior art diagnostic methods, the diagnostic method of the invention is able to readily diagnose CFS using a bodily sample that is obtained from the subject by non-invasive or minimally invasive methods. The bodily sample can include, for example, bodily fluids, such as blood, serum, or plasma that are obtained by minimally invasive methods. The invention can also be used as a diagnostic test to distinguish types of CFS, and detect early stages of CFS. The invention also provides a method for monitoring the response of a subject to treatment of CFS.

[0018] Unless specifically addressed herein, all terms used have the same meaning as would be understood by those of skilled in the art of the present invention. The following definitions will provide clarity with respect to the terms used in the specification and claims to describe the present invention.

[0019] The term "monitoring" as used herein refers to the use of results generated from datasets to provide useful information about an individual or an individual's health or disease status. "Monitoring" can include, for example, determination of prognosis, risk- stratification, selection of drug therapy, assessment of ongoing drug therapy, determination of effectiveness of treatment, prediction of outcomes, determination of response to therapy, diagnosis of a disease or disease complication, following of progression of a disease or providing any information relating to a patient's health status over time, selecting patients most likely to benefit from experimental therapies with known molecular mechanisms of action, selecting patients most likely to benefit from approved drugs with known molecular mechanisms where that mechanism may be important in a small subset of a disease for which the medication may not have a label, screening a patient population to help decide on a more invasive/expensive test, for example, a cascade of tests from a non-invasive blood test to a more invasive option such as biopsy, or testing to assess side effects of drugs used to treat another indication.

[0020] The term "quantitative data" as used herein refers to data associated with any dataset components (e.g., markers, clinical indicia, metabolic measures, or genetic assays) that can be assigned a numerical value. Quantitative data can be a measure of the level of a marker and expressed in units of measurement, such as molar concentration, concentration by weight, etc. For example, if the marker is the circulating extracellular vesicles (EVs) or biomarkers expressed thereon, quantitative data for that marker can be the EVs or the biomarkers measured using methods known to those skilled in the art and expressed in mM or mg/dL concentration units. [0021] The term "subject" as used herein relates to an animal, such as a mammal including a small mammal (e.g., mouse, rat, rabbit, or cat) or a larger mammal (e.g., dog, pig, or human). In particular aspects, the subject is a large mammal, such as a human, that is suspected of having or at risk of CFS, or related diseases.

[0022] The term "diagnosing CFS" as used herein refers to a process aimed at one or more of: determining if a subject is afflicted with CFS; determining the severity or stage of CFS, or disease related pathologies in a subject; determining the risk that a subject is afflicted with CFS; and determining the prognosis of a subject afflicted with CFS or other related diseases.

[0023] The terms "biological sample" or "bodily sample" are used herein in its broadest sense. A biological or bodily sample may be obtained from a subject (e.g., a human) or from components (e.g., tissues) of a subject. The sample can be obtained either invasively or non-invasively from the subject but is preferably obtained non-invasively. The sample includes any biological sample that is suspected of containing EVs and/or any biomarkers of interest. The sample obtained from the subject can potentially include body fluids, such as blood, plasma, serum, urine, blood, fecal matter, saliva, mucous, and cell extract as well as solid tissue, such as cells, a tissue sample, or a tissue or fine needle biopsy samples; and archival samples with known diagnosis, treatment and/or outcome history. Frequently, the sample will be a "clinical sample", i.e., a sample derived from a patient. The sample also encompasses any material derived by processing the biological sample. Processing of the sample may involve one or more of, filtration, distillation, extraction, concentration, inactivation of interfering components, addition of reagents, and the like. It will be appreciated by one skilled in the art that other biological or bodily samples not listed can also be used in accordance with the present invention.

[0024] The terms "normal" and "healthy" are used herein interchangeably. They refer to an individual or group of control individuals who have not shown any symptoms of CFS, such as inflammation, and have not been diagnosed with CFS. The normal individual (or group of individuals) is not on medication affecting CFS. In certain embodiments, normal individuals have similar sex, age, body mass index as compared with the individual from which the sample to be tested was obtained. The term "normal" is also used herein to qualify a sample isolated from a healthy individual.

[0025] The subject may be an "apparently healthy" subject. "Apparently healthy", as used herein, means individuals who have not been previously diagnosed with liver damage, liver disease and/or who have not been previously diagnosed as having any signs or symptoms indicating CFS. Additionally, apparently healthy subjects may include those individuals having low or no risk for developing CFS. In addition to apparently healthy subjects, subjects may include individuals having CFS and/or may be at an elevated risk of developing CFS.

[0026] The terms "control" or "control sample" or "control dataset" as used herein refer to one or more biological samples isolated from an individual or group of individuals that are normal (i.e., healthy). The term "control", "control value" or "control sample" can also refer to the compilation of data derived from samples of one or more individuals classified as normal, or one or more individuals not diagnosed with CFS.

[0027] The term "indicative of CFS" as used herein, when applied to an amount of circulating extracellular vesicles (EVs) or at least one biomarker expressed in the EVs in a sample, refers to a level or an amount, which is diagnostic of CFS, such that the level is found significantly more often in subjects with the disease than in patients without the disease or another stage of CFS (as determined using routine statistical methods setting confidence levels at a minimum of 95%). In certain embodiments, a level, which is indicative of CFS, is found in at least about 60%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95% or more in patients who have the disease of patients and is found in less than about 10%, less than about 8%, less than about 5%, less than about 2.5%, or less than about 1% of subjects who do not have the disease.

[0028] The term "biomarker" as used herein refers to an indicator and/or prognostic factor of biologic or pathologic processes or pharmacologic responses to a therapeutic intervention. As used herein, the term "prognostic factor" refers to any molecules and/or substances contributing to a predicted and/or expected course of CFS in a subject including various developments, changes and outcomes of the disease. As used herein, the term "detecting reagents" refer to any substances, chemicals, solutions used in chemical reactions and processes that are capable of detecting, measuring, and examining biomarker of interest, and isoforms thereof. In certain preferred embodiments, the biomarker refers to the circulating extracellular vesicles (EVs) detected and/or associated with CFS. In other embodiments, the biomarker refers to the gene or protein molecules expressed or detected in the EVs. The biomarkers expressed and/or detected in the EVs include, but are not limited to, those described herein as microRNAs, miR-21 and -146a. In other preferred embodiments, the biomarker detecting reagents used herein comprise chemicals, substances, and solutions that are suitable for determining either mRNA or protein, or both expression levels of the biomarker of interest, or isoforms or associated molecules thereof. The biomarkers used in the present invention can also be found in Table I. [0029] As used herein, the term isoforms or homologs of a biomarker of interest refer to a protein, or its encoded nucleic acid, having at least 60%, 75%, 85%, 90%, 95%, 96%, 97%, 98%, 99% or more identical, to a wild type of the protein biomarker core amino acid domain, or the nucleic acid domain encoding the said core amino acid domain. Identity can be determined using the BLAST program on default settings. As used herein, the core domain comprises one or more biologically active portions of the proteins or the nucleic acid portions encoding said proteins. As used herein, the "biologically active portions" include one or more fragments of the protein, or the nucleic acid fragment encoding said protein, comprising amino acid or nucleic acid sequences sufficiently homologous to, or derived from, the amino acid or nucleic acid sequence of the proteins, or their nucleic acids, which include fewer amino acids, or nucleic acids than the full length protein or its nucleic acid, and exhibit at least one activity of the full-length protein. Typically a biologically active portion comprises a domain or motif with at least one activity of the protein. A biologically active portion of a protein can be a polypeptide which is, for example, 10, 25, 50, 100, 200 or more amino acids in length. In one embodiment, a biologically active portion of these proteins can be used as a target for developing agents which modulate activities of these proteins.

[0030] Moreover, the protein biomarkers used herein include the proteins and/or enzymes encoded by polynucleotides that hybridize to the polynucleotide encoding these proteins under stringent conditions. As used herein, "hybridization" includes a reaction in which one or more polynucleotides react to form a complex that is stabilized via hydrogen bonding between the bases of the nucleotide residues. The hydrogen bonding may occur by Watson-Crick base pairing, Hoogstein binding, or in any other sequence-specific manner. The complex may comprise two strands forming a duplex structure, three or more strands forming a multi- stranded complex, a single self-hybridizing strand, or any combination of these. A hybridization reaction may constitute a step in a more extensive process, such as the initiation of a PCR reaction, or the enzymatic cleavage of a polynucleotide by a ribozyme.

[0031] Hybridization reactions can be performed under different stringent conditions. The invention includes polynucleotides capable of hybridizing under reduced stringency conditions, certain stringent conditions, or highly stringent conditions, to polynucleotides encoding the protein biomarker of interest described herein. As used herein, the term "stringent conditions" refers to hybridization overnight at 60°C in 10X Denhart's solution, 6X SSC, and 0.5% SDS. Blots are washed sequentially at 62°C for 30 minutes each time in 3X SSC/0.1% SDS, followed by IX SSC/0.1% SDS, and finally 0.1X SSC/0.1% SDS. As also used herein, in certain embodiments, the phrase "stringent conditions" refers to hybridization in a 6X SSC solution at 65°C. In another embodiment, "highly stringent conditions" refers to hybridization overnight at 65 °C in 10X Denhart's solution, 6X SSC, and 0.5% SDS. Blots are washed sequentially at 65°C for 30 minutes each time in 3X SSC/0.1% SDS, followed by IX SSC/0.1% SDS, and finally 0.1X SSC/0.1% SDS. Methods for nucleic acid hybridizations are described in Meinkoth and Wahl, 1984, Anal. Biochem. 138:267-284; Current Protocols in Molecular Biology, Chapter 2, Ausubel et al., eds., Greene Publishing and Wiley-Interscience, New York, 1995; and Tijssen, 1993, Laboratory Techniques in Biochemistry and Molecular Biology: Hybridization with Nucleic Acid Probes, Part I, Chapter 2, Elsevier, New York, 1993. [0032] As used herein, the term "expression level" refers to an amount of a gene and/or protein that is expressed in a cell or EV. As used herein, a "gene" includes a polynucleotide containing at least one open reading frame that is capable of encoding a particular polypeptide or protein after being transcribed and translated. Any of the polynucleotide sequences described herein may also be used to identify larger fragments or full-length coding sequences of the gene with which they are associated. Methods of isolating larger fragment sequences are known to those of skill in the art.

[0033] As used herein, the term "protein" or "polypeptide" is interchangeable, and includes a compound of two or more subunit amino acids, amino acid analogs, or peptidomimetics. The subunits may be linked by peptide bonds. In another embodiment, the subunit may be linked by other bonds, e.g., ester, ether, etc. As used herein, the term "amino acid" includes either natural and/or unnatural or synthetic amino acids, including both the D or L optical isomers, and amino acid analogs and peptidomimetics. A peptide of three or more amino acids is commonly referred to as an oligopeptide. Peptide chains of greater than three or more amino acids are referred to as a polypeptide or a protein. [0034] As used herein, the terms "polynucleotide," "nucleic acid/nucleotide" and

"oligonucleotide" are used interchangeably, and include polymeric forms of nucleotides of any length, either deoxyribonucleotides or ribonucleotides, or analogs thereof. Polynucleotides may have any three-dimensional structure, and may perform any function, known or unknown. The following are non-limiting examples of polynucleotides: a gene or gene fragment, exons, introns, messenger RNA (mRNA), transfer RNA, ribosomal RNA, ribozymes, DNA, cDNA, genomic DNA, recombinant polynucleotides, branched polynucleotides, plasmids, vectors, isolated DNA of any sequence, isolated RNA of any sequence, nucleic acid probes, and primers. Polynucleotides may be naturally-occurring, synthetic, recombinant or any combination thereof.

[0035] As used herein, a "naturally-occurring" polynucleotide molecule includes, for example, an RNA (mRNA) or DNA molecule having a nucleotide sequence that occurs in nature (e.g., encodes a natural protein). As used herein, "recombinant" refers to a polynucleotide synthesized or otherwise manipulated in vitro (e.g., "recombinant polynucleotide"), to methods of using recombinant polynucleotides to produce gene products in cells or other biological systems, or to a polypeptide ("recombinant protein") encoded by a recombinant polynucleotide. "Recombinant" also encompasses the ligation of nucleic acids having various coding regions or domains or promoter sequences from different sources into an expression cassette or vector for expression of, e.g., inducible or constitutive expression of a fusion protein comprising a translocation domain of the invention and a nucleic acid sequence amplified using a primer of the invention.

[0036] A polynucleotide may comprise modified nucleotides, such as methylated nucleotides and nucleotide analogs. If present, modifications to the nucleotide structure may be imparted before or after assembly of the polymer. The sequence of nucleotides may be interrupted by non-nucleotide components. A polynucleotide may be further modified after polymerization, such as by conjugation with a labeling component. The term also includes both double- and single-stranded molecules. Unless otherwise specified or required, any embodiment of this invention that is a polynucleotide encompasses both the double- stranded form and each of two complementary single- stranded forms known or predicted to make up the double- stranded form. The "polynucleotide sequence" is the alphabetical representation of a polynucleotide molecule. A polynucleotide is composed of a specific sequence of four nucleotide bases: adenine (A); cytosine (C); guanine (G); thymine (T); and uracil (U) in place of guanine when the polynucleotide is RNA. This alphabetical representation can be inputted into databases in a computer and used for bioinformatics applications such as, for example, functional genomics and homology searching.

[0037] As used herein, the term "primer" refers to a segment of DNA or RNA that is complementary to a given DNA or RNA sequences (e.g. sequences of a particular biomarker of interest or its isoform) and that is needed to initiate replication by DNA polymerase, and a term "probe" refers to a substance, such as DNA, that is radioactively labeled or otherwise marked and used to detect or identify another substance in a sample. As used herein, the term "primer" and "probe" are used interchangeably, and typically comprise a substantially isolated oligonucleotide typically comprising a region of nucleotide sequence that hybridizes under stringent conditions to at least about 12, preferably about 25, more preferably about 40, 50, or 75 consecutive nucleotides of a sense and/or an antisense strands of a nucleotide sequence of a biomarker of interest and its isoforms thereof; or naturally occurring mutants thereof. As used herein, primers based on the nucleotide sequence of a biomarker of interest, and isoforms thereof, can be used in PCR reactions to clone homologs of the biomarker and its isoforms. Probes based on the nucleotide sequences of the biomarker of interest, and isoforms thereof, can be used to detect transcripts or genomic sequences encoding the same or substantially identical polypeptides or proteins. In preferred embodiments, the probe further comprises a label group attached thereto, e.g. the label group can be a radioisotope, a fluorescent compound, an enzyme, or an enzyme co-factor. Such probes can be used as a part of a genomic marker test kit for identifying cells which express or over-express the biomarker of interest, or isoforms thereof, such as by measuring a level of encoding nucleic acid, in a sample of cells, e.g., detecting mRNA levels or determining whether a genomic gene has been mutated or deleted.

[0038] As used herein, the term "therapeutic agent" refers to any molecules naturally occurred or synthesized, including but not limited to, small molecule, biologies, peptide, proteins, or antibodies. The term "antibody" as used herein encompasses monoclonal antibodies (including full length monoclonal antibodies), polyclonal antibodies, multi- specific antibodies (e.g., bi-specific antibodies), and antibody fragments so long as they exhibit the desired biological activity of binding to a target protein biomarker and its isoforms of interest. The term "antibody fragments" comprise a portion of a full length antibody, generally the antigen binding or variable region thereof. Examples of antibody fragments include Fab, Fab', F(ab')², and Fv fragments. The term "antibody" as used herein encompasses any antibodies derived from any species and resources, including but not limited to, human antibody, rat antibody, mouse antibody, rabbit antibody, and so on, and can be synthetically made or naturally-occurring.

[0039] The term "monoclonal antibody" as used herein refers to an antibody obtained from a population of substantially homogeneous antibodies, i.e., the individual antibodies comprising the population are identical except for possible naturally occurring mutations that may be present in minor amounts. Monoclonal antibodies are highly specific, being directed against a single antigenic site. Furthermore, in contrast to conventional (polyclonal) antibody preparations which typically include different antibodies directed against different determinants (epitopes), each monoclonal antibody is directed against a single determinant on the antigen. The "monoclonal antibodies" may also be isolated from phage antibody libraries using the techniques known in the art.

[0040] The monoclonal antibodies herein include "chimeric" antibodies

(immunoglobulins) in which a portion of the heavy and/or light chain is identical with or homologous to corresponding sequences in antibodies derived from a particular species or belonging to a particular antibody class or subclass, while the remainder of the chain(s) is identical with or homologous to corresponding sequences in antibodies derived from another species or belonging to another antibody class or subclass, as well as fragments of such antibodies, so long as they exhibit the desired biological activity. As used herein, a "chimeric protein" or "fusion protein" comprises a first polypeptide operatively linked to a second polypeptide. Chimeric proteins may optionally comprise a third, fourth or fifth or other polypeptide operatively linked to a first or second polypeptide. Chimeric proteins may comprise two or more different polypeptides. Chimeric proteins may comprise multiple copies of the same polypeptide. Chimeric proteins may also comprise one or more mutations in one or more of the polypeptides. Methods for making chimeric proteins are well known in the art. [0041] The term "single-chain Fv" or "sFv" antibody fragments comprise the VH and VL domains of antibody, wherein these domains are present in a single polypeptide chain. Generally, the Fv polypeptide further comprises a polypeptide linker between the VH and VL domains which enables the sFv to form the desired structure for antigen binding.

[0042] An "isolated" antibody is one that has been identified and separated and/or recovered from a component of its natural environment. Contaminant components of its natural environment are materials that would interfere with diagnostic or therapeutic uses for the antibody, and may include enzymes, hormones, and other proteinaceous or nonproteinaceous solutes. In preferred embodiments, the antibody will be purified (1) to greater than 95% by weight of antibody as determined by the Lowry method, and most preferably more than 99% by weight, (2) to a degree sufficient to obtain at least 15 residues of N-terminal or internal amino acid sequence by use of a spinning cup sequenator, or (3) to homogeneity by SDS-polyacrylamide gel electrophoresis under reducing or non-reducing conditions using Coomassie blue or, preferably, silver stain. Isolated antibody includes the antibody in situ within recombinant cells since at least one component of the antibody's natural environment will not be present. Ordinarily, however, isolated antibody will be prepared by at least one purification step.

[0043] In order to avoid potential immunogenicity of the monoclonal antibodies in humans, the monoclonal antibodies that have the desired function are preferably human or humanized. "Humanized" forms of non-human (e.g., murine) antibodies are chimeric antibodies that contain minimal sequence derived from non-human immunoglobulin. For the most part, humanized antibodies are human immunoglobulins (recipient antibody) in which hyper variable region residues of the recipient are replaced by hyper variable region residues from a non-human species (donor antibody) such as mouse, rat, rabbit or nonhuman primate having the desired specificity, affinity, and capacity. In some instances, Fv framework region (FR) residues of the human immunoglobulin are replaced by corresponding non-human residues. Furthermore, humanized antibodies may comprise residues that are not found in the recipient antibody or in the donor antibody. These modifications are made to further refine antibody performance. In general, the humanized antibody will comprise substantially all of at least one, and typically two, variable domains, in which all or substantially all of the hyper variable loops correspond to those of a non-human immunoglobulin and all or substantially all of the FR regions are those of a human immunoglobulin sequence. The humanized antibody optionally also will comprise at least a portion of an immunoglobulin constant region (Fc), typically that of a human immunoglobulin. Antibodies capable of immunoreacting to particular protein biomarker of interest and their isoforms are made using conventional methods known in the art.

[0044] The therapeutic agent may also refer to any oligonucleotides (antisense oligonucleotide agents), polynucleotides (e.g. therapeutic DNA), ribozymes, dsRNAs, siRNA, RNAi, and/or gene therapy vectors. The term "antisense oligonucleotide agent" refers to short synthetic segments of DNA or RNA, usually referred to as oligonucleotides, which are designed to be complementary to a sequence of a specific mRNA to inhibit the translation of the targeted mRNA by binding to a unique sequence segment on the mRNA. Antisense oligonucleotides are often developed and used in the antisense technology. The term "antisense technology" refers to a drug-discovery and development technique that involves design and use of synthetic oligonucleotides complementary to a target mRNA to inhibit production of specific disease-causing proteins. Antisense technology permits design of drugs, called antisense oligonucleotides, which intervene at the genetic level and inhibit the production of disease-associated proteins. Antisense oligonucleotide agents are developed based on genetic information. [0045] As an alternative to antisense oligonucleotide agents, ribozymes or double stranded RNA (dsRNA), RNA interference (RNAi), and/or small interfering RNA (siRNA), can also be used as therapeutic agents for regulation of gene expression in cells. As used herein, the term "ribozyme" refers to a catalytic RNA-based enzyme with ribonuclease activity that is capable of cleaving a single-stranded nucleic acid, such as an mRNA, to which it has a complementary region. Ribozymes can be used to catalytically cleave target mRNA transcripts to thereby inhibit translation of target mRNA. The term "dsRNA," as used herein, refers to RNA hybrids comprising two strands of RNA. The dsRNAs can be linear or circular in structure. The dsRNA may comprise ribonucleotides, ribonucleotide analogs, such as 2'-0-methyl ribosyl residues, or combinations thereof. The term "RNAi" refers to RNA interference or post-transcriptional gene silencing (PTGS). The term "siRNA" refers to small dsRNA molecules (e.g., 21-23 nucleotides) that are the mediators of the RNAi effects. RNAi is induced by the introduction of long dsRNA (up to 1-2 kb) produced by in vitro transcription, and has been successfully used to reduce gene expression in variety of organisms. In mammalian cells, RNAi uses siRNA (e.g. 22 nucleotides long) to bind to the RNA-induced silencing complex (RISC), which then binds to any matching mRNA sequence to degrade target mRNA, thus, silences the gene.

[0046] As used herein, the therapeutic agents may also include any vectors/virus used for gene therapy. The term "gene therapy" refers to a technique for correcting defective genes or inhibiting or enhancing genes responsible for disease development. Such techniques may include inserting a normal gene into a nonspecific location within the genome to replace a nonfunctional gene; swapping an abnormal gene for a normal gene through homologous recombinants, repairing an abnormal gene to resume its normal function through selective reverse mutation; and altering or regulating gene expression and/or functions of a particular gene. [0047] As used herein, the term "biologically effective amount" or "therapeutically effective amount" of therapeutic agent is intended to mean a nontoxic but sufficient amount of such therapeutic agents to provide the desired therapeutic effect. The amount that is effective will vary from subject to subject, depending on the age and general condition of the individual, the particular active agent or agents, and the like. Thus, it is not always possible to specify an exact effective amount. However, an appropriate effective amount in any individual case may be determined by one of ordinary skill in the art using routine experimentation.

[0048] As used herein, the term "pharmaceutical composition" contemplates compositions comprising one or more therapeutic agents as described above, and one or more pharmaceutically acceptable excipients, carriers, or vehicles. As used herein, the term "pharmaceutically acceptable excipients, carriers, or vehicles" comprises any acceptable materials, and/or any one or more additives known in the art. As used herein, the term "excipients," "carriers" or "vehicle" refer to materials suitable for drug administration through various conventional administration routes known in the art. Excipients, carriers, and vehicles useful herein include any such materials known in the art, which are nontoxic and do not interact with other components of the composition in a deleterious manner.

[0049] One aspect of the invention therefore relates to a method of predicting, detecting, monitoring, or assessing the degree or severity of CFS in a subject. In certain embodiments, the method includes obtaining a bodily sample from the subject, and determining an amount of circulating EVs in the sample. An increased level of the circulating EVs in the subject compared to a control is indicative of an increase in degree or severity of CFS in the subject. In certain embodiments, the majority of the circulating EVs are microparticles (MPs), typically between 100-1000 nm, and exosomes, typically less than 100 nm. In these embodiments, an increased level of the circulating EVs, MPs and exosomes, in the subject compared to a control is indicative of an increase in degree or severity of CFS in the subject.

[0050] In other embodiments, the invention method comprises detecting and determining an expression level of at least one biomarker expressed or detected in the circulating EVs in a bodily sample. These biomarkers are involved in molecule function and cellular localization. In certain embodiments, the biomarkers expressed or detected in the circulating EVs are involved in CFS or inflammation. Exemplary biomarkers expressed in the circulating EVs are microRNAs selected from the group miR-21, -122, - 146a, -155, and -125b. Further biomarkers specific to CFS subjects can be found in Tables I and II below.

[0051] In certain embodiments, the bodily sample can comprise a blood sample obtained non-invasively from the subject. In some aspects, the amount of blood taken from a subject is about 0.1 ml or more. In an exemplary embodiment, the bodily sample is blood plasma isolated from a whole blood sample obtained from a subject. Blood plasma may be isolated from whole blood using well known methods, such as centrifugation. The bodily samples can be obtained from the subject using sampling devices, such as syringes, swabs or other sampling devices used to obtain liquid and/or solid bodily samples either invasively (i.e., directly from the subject) or non-invasively. These samples can then be stored in storage containers. The storage containers used to contain the collected sample can comprise a non-surface reactive material, such as polypropylene. The storage containers should generally not be made from untreated glass or other sample reactive material to prevent the sample from becoming absorbed or adsorbed by surfaces of the glass container.

[0052] Collected samples stored in the container may be stored under refrigeration temperature. For longer storage times, the collected sample can be frozen to retard decomposition and facilitate storage. For example, samples obtained from the subject can be stored in a falcon tube and cooled to a temperature of about -80°C. The collected bodily sample can be stored in the presence of a chelating agent, such as ethylenediaminetetraacetic acid (EDTA). The collected bodily sample can also be stored in the presence of an antioxidant, such as butylated hydroxytoluene (BHT) or diethylenetriamine pentaacetic acid, and/or kept in an inert atmosphere (e.g., overlaid with argon) to inhibit oxidation of the sample.

[0053] Bodily samples obtained from the subject can then be contacted with a solvent, such as an organic solvent. The solvent can include any chemical useful for the removal (i.e., extraction) of the EVs of interest from a bodily sample. For example, where the bodily sample comprises plasma, the solvent can include a water/methanol mixture. It will be appreciated by one skilled in the art that the solvent is not strictly limited to this context, as the solvent may be used for the removal of lipids from a liquid mixture, with which the liquid is immiscible in the solvent. Those skilled in the art will further understand and appreciate other appropriate solvents that can be employed to extract lipids from the bodily sample. The solvent can include solvent mixtures comprising miscible, partially miscible, and/or immiscible solvents. The solvent can also be combined with other solvents which can act as carriers facilitating mixing of the solvent with the bodily sample or transfer of the extracted EVs from the bodily sample.

[0054] The bodily sample may be pre-treated as necessary by dilution in an appropriate buffer solution, heparinized, concentrated if desired, or fractionated by any number of methods including, but not limited to, ultracentrifugation, fractionation by fast performance liquid chromatography, or other known methods. Any of a number of standard aqueous buffer solutions, employing one of a variety of buffers, such as phosphate, Tris, or the like at a physiological pH can be used. [0055] After obtaining the bodily sample (e.g., blood, serum, plasma), the amount of EVs in the bodily sample, or an expression level of one or more biomarkers expressed in the EVs, is detected, measured, and/or quantifying to determine the level of EVs, or the biomarkers of interest in the subject. An increase in the amount of EVs, or the expression level of the biomarker of interest is associated with CFS and related diseases.

[0056] In certain embodiments, the circulating EVs in the bodily sample, as well as protein biomarkers expressed therein, can be detected and/or quantified using an immunoassay, such as an enzyme-linked immunoabsorbent assay (ELISA), or other assays, now known or later developed, that can be used to detect and/or quantify EVs, and biomarkers of interest in the bodily sample. These assays include, but are not limited to, flow cytometry (FACS) analysis, radioimmunoassays, both solid and liquid phase, fluorescence-linked assays, competitive immunoassays, mass spectrometry (MS)-based methods (e.g., liquid chromatography MS), and HPLC.

[0057] Once the level or amount of the EVs or the expression level of the biomarker of interest in a sample are determined, the level/amount can be compared to a predetermined value or control value to provide information for diagnosing, monitoring, or assessing CFS in a subject. For example, the level/amount of EVs, or the expression level of the biomarker expressed therein in a sample can be compared to a predetermined value or control value to determine if a subject is afflicted with CFS or related diseases. [0058] The level/amount of EVs, or the expression level of the biomarkers expressed therein, in the subject's bodily sample may also be compared to the level/amount of the EVs, or the expression level of the biomarkers of interest obtained from a bodily sample previously obtained from the subject, such as prior to administration of therapeutic. Accordingly, the method described herein can be used to measure the efficacy of a therapeutic regimen for the treatment of CFS, or related diseases in a subject by comparing the level/amount of EVs, or the expression level of the biomarkers of interest in bodily samples obtained before and after a therapeutic regimen. Additionally, the method described herein can be used to measure the progression of CFS, or related diseases in a subject by comparing the level/amount of EVs, or the expression level of the biomarker of interest in a bodily sample obtained over a given time period, such as days, weeks, months, or years. [0059] The level/amount of EVs, or the expression level of the biomarker of interest in a sample may also be compared to a predetermined value or control value to provide information for determining the severity of the disease in the subject or the tissue of the subject. Thus, in some aspect, a level/amount of EVs, or the expression level of the biomarker of interest may be compared to control values obtained from subjects with well- known clinical categorizations, or stages, of histopathologies related to CFS. In one particular embodiment, a level/amount of EVs, or the expression level of the biomarker of interest in a sample can provide information for determining a particular stage of the disease in the subject. [0060] A predetermined value or control value can be based upon the level/amount of EVs, or the expression level of the biomarker of interest in comparable samples obtained from a healthy or normal subject or the general population or from a select population of control subjects. In some aspects, the select population of control subjects can include individuals diagnosed with CFS. For example, a subject having a greater level/amount of EVs, or the expression level of the biomarker of interest compared to a control value may be indicative of the subject having a more advanced stage of a histopathology related to CFS.

[0061] The select population of control subjects may also include subjects afflicted with CFS in order to distinguish subjects by comparing the level/amount of EVs, or the expression level of the biomarker of interest in the samples. The predetermined value can be related to the value used to characterize the level/amount of EVs, or the expression level of the biomarker of interest in the bodily sample obtained from the test subject. Thus, if the level/amount of EVs, or the expression level of the biomarker of interest is an absolute value, the predetermined value can also be based upon the absolute value in subjects in the general population or a select population of human subjects. Similarly, if the level/amount of EVs, or the expression level of the biomarker of interest is a representative value such as an arbitrary unit, the predetermined value can also be based on the representative value.

[0062] The predetermined value can take a variety of forms. The predetermined value can be a single cut-off value, such as a median or mean. The predetermined value can be established based upon comparative groups such as where the level/amount of EVs, or the expression level of the biomarker of interest in one defined group is double the level/amount of EVs, or the expression level of the biomarker of interest in another defined group. The predetermined value can be a range, for example, where the general subject population is divided equally (or unequally) into groups, or into quadrants, the lowest quadrant being subjects with the lowest level/amount of EVs, or the expression level of the biomarker of interest, the highest quadrant being individuals with the highest level/amount of EVs, or the expression level of the biomarker of interest. In an exemplary embodiment, two cutoff values are selected to minimize the rate of false positive and negative results. [0063] Predetermined values of the EVs, or the expression level of the biomarkers expressed therein, such as for example, mean levels, median levels, or "cut-off" levels, are established by assaying a large sample of subjects in the general population or the select population and using a statistical model such as the predictive value method for selecting a positively criterion or receiver operator characteristic curve that defines optimum specificity (highest true negative rate) and sensitivity (highest true positive rate) as described in Knapp, R. G., and Miller, M. C. (1992). Clinical Epidemiology and Biostatistics. William and Wilkins, Harual Publishing Co. Malvern, Pa., which is specifically incorporated herein by reference. A "cutoff value can be determined for EVs, MPs, or the expression level of each biomarker that is assayed. [0064] In other embodiments, the invention relates to a method for generating a result useful in diagnosing and monitoring CFS or other related diseases or conditions by obtaining a dataset associated with a sample, where the dataset includes quantitative data about the amounts of EVs, or the expression level of the biomarkers expressed therein which have been found to be predictive of severity of CFS with a statistical significance less than 0.2 (e.g., p value less than about 0.05), and inputting the dataset into an analytical process that uses the dataset to generate a result useful in diagnosing and monitoring CFS. In certain embodiments, the dataset also includes quantitative data about other clinical indicia or other marker associated with CFS.

[0065] Datasets containing quantitative data, typically the level/amount of EVs, or the expression levels of the biomarker of interest used herein, and quantitative data for other dataset components can be inputted into an analytical process and used to generate a result. The analytical process may be any type of learning algorithm with defined parameters, or in other words, a predictive model. Predictive models can be developed for a variety of CFS classifications by applying learning algorithms to the appropriate type of reference or control data. Multivariable modeling can be applied to generate a risk score for diagnosing CFS. A risk score can be derived from the amount of total EVs or the expression level of the biomarker of interest as determined by the methods described herein. The risk score can be compared to a control value, to provide information for diagnosing CFS in a subject. The result of the analytical process/predictive model can be used by an appropriate individual to take the appropriate course of action. [0066] In certain embodiments, a scoring system or risk score can be generated by the analytical process to diagnose and monitor CFS. In some aspects, the analytical process can use a dataset that includes the level/amount of total derived EVs, or the expression level of the biomarker of interest in a subject's sample as determined by the methods described herein. The risk score can then be compared to a control value, to provide information for diagnosing or monitoring or assessing CFS in a subject.

[0067] In other aspects, the analytical process can use a reference dataset that includes the determined level/amount of EVs, or the expression level of the biomarker of interest and quantitative data from one or more clinical indicia to generate a risk score. The risk score can be derived using an algorithm that weights the level/amount of EVs, or the expression level of the biomarker of interest in the sample and one more clinical indicia (or anthropometric features or measures) including but not limited to, age, gender, race, BMI, weight.

[0068] The analytical process used to generate a risk score may be any type of process capable of providing a result useful for classifying a sample, for example, comparison of the obtained dataset with a reference dataset, a linear algorithm, a quadratic algorithm, a decision tree algorithm, or a voting algorithm. Prior to input into the analytical process, the data in each dataset can be collected by measuring the values for EVs, or the biomarkers expressed therein usually in triplicate or in multiple triplicates. The data may be manipulated, for example, raw data may be transformed using standard curves, and the average of triplicate measurements used to calculate the average and standard deviation for each patient. These values may be transformed before being used in the models, e.g. log-transformed or Box-Cox transformed. This data can then be input into the analytical process with defined parameters. The analytical process may set a threshold for determining the probability that a sample belongs to a given class. The probability preferably is at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or higher. [0069] In certain embodiments, the analytical process determines whether a comparison between an obtained dataset and a reference dataset yields a statistically significant difference. If so, then the sample from which the dataset was obtained is classified as not belonging to the reference dataset class. Conversely, if such a comparison is not statistically significantly different from the reference dataset, then the sample from which the dataset was obtained is classified as belonging to the reference dataset class.

[0070] In general, the analytical process will be in the form of a model generated by a statistical analytical method. In some embodiments, the analytical process is based on a regression model, preferably a logistic regression model. Such a regression model includes a coefficient for EVs, or each of the biomarkers in a selected set of biomarkers disclosed herein. In such embodiments, the coefficients for the regression model are computed using, for example, a maximum likelihood approach. In particular embodiments, molecular marker data from the two groups (e.g., healthy and diseased) is used and the dependent variable is the status of the patient for which marker characteristic data are from.

[0071] By way of example, the analytical process can include a logistic regression model that generates a risk score based on the following algorithm: risk score = [- 10.051+0.0463*Age(years)+0.147*BMI(kg/m²)+0.0293*AST(IU/L)+2.658*Total EVs (EV number/microliter)]* 10) is determined. The risk score can be converted to a probability distribution with a value of 0 to 100 by the following algorithm; evCFS=100*exp(z)/[l+exp(z)], wherein evCFS is the probability distribution and z is the risk score calculated using the above noted algorithm.

[0072] It will be appreciated, that other analytical processes can be used to generate a risk score. These analytical processes can include for example a Linear Discriminant Analysis model, a support vector machine classification algorithm, a recursive feature elimination model, a prediction analysis of microarray model, a classification and regression tree (CART) algorithm, a FlexTree algorithm, a random forest algorithm, a multiple additive regression tree (MART) algorithm, or Machine Learning algorithms. [0073] A risk score or result generated by the analytical process can be any type of information useful for making a CFS classification, e.g., a classification, a continuous variable, or a vector. For example, the value of a continuous variable or vector may be used to determine the likelihood that a sample is associated with a particular classification.

[0074] CFS classification refer to any type of information or the generation of any type of information associated with CFS, for example, diagnosis, staging, assessing extent of CFS progression, prognosis, monitoring, therapeutic response to treatments, screening to identify compounds that act via similar mechanisms as known CFS treatments.

[0075] In some aspects, the result is used for diagnosis or detection of the occurrence of CFS. In this embodiment, a reference or training set containing "healthy" and "CFS" samples is used to develop a predictive model. A dataset, preferably containing level/amount of EVs, or the expression level of the biomarker expressed therein, indicative of CFS, is then inputted into the predictive model in order to generate a result. The result may classify the sample as either "healthy" or "CFS" or staging of "CFS". In other embodiments, the result is a continuous variable providing information useful for classifying the sample, e.g., where a high value indicates a high probability of being a "CFS" sample and a low value indicates a low probability of being a "healthy" sample.

[0076] In other embodiments, the result is used for CFS staging. In these embodiments, a reference or training dataset containing samples from individuals with disease at different stages is used to develop a predictive model. The model may be a simple comparison of an individual dataset against one or more datasets obtained from disease samples of known stage or a more complex multivariate classification model. In certain embodiments, inputting a dataset into the model will generate a result classifying the sample from which the dataset is generated as being at a specified CFS disease stage. Similar methods may be used to provide CFS prognosis, except that the reference or training set will include data obtained from individuals who develop disease and those who fail to develop disease at a later time.

[0077] In other embodiments, the result is used determine response to CFS treatments. In this embodiment, the reference or training dataset and the predictive model is the same as that used to diagnose CFS (samples of from individuals with disease and those without). However, instead of inputting a dataset composed of samples from individuals with an unknown diagnosis, the dataset is composed of individuals with known disease which have been administered a particular treatment and it is determined whether the samples trend toward or lie within a normal, healthy classification versus an CFS classification.

[0078] In other embodiments, the result is used for drug screening, i.e., identifying new agents that target EVs, or the biomarkers expressed therein to either internalize the circulating EVs in to the endothelial cells, or reduce the expression level of the biomarkers expressed therein so as to inhibit CFS. Any drug screening methods now known or later developed in the art will be encompassed by the invention. In certain embodiments, the invention provides a drug screening for an agent that is capable of internalizing circulating EVs into the endothelial cells. In other embodiments, the invention provides a drug screening for an agent that is capable of interacting with at least one biomarker listed above, which are expressed in the circulating EVs. [0079] In other embodiments, the result is used for drug screening, i.e., identifying compounds that act via similar mechanisms as known CFS drug treatments. In this embodiment, a reference or training set containing individuals treated with a known CFS drug treatment and those not treated with the particular treatment can be used develop a predictive model. A dataset from individuals treated with a compound with an unknown mechanism is input into the model. If the result indicates that the sample can be classified as coming from a subject dosed with a known CFS drug treatment, then the new compound is likely to act via the same mechanism.

[0080] One of skill will also recognize that the results generated using these methods can be used in conjunction with any number of the various other methods known to those of skill in the art for diagnosing and monitoring CFS, or other related diseases. [0081] Using methods described herein, skilled physicians may select and prescribe treatments adapted to each individual subject based on the diagnosis of CFS provided to the subject through determination of the level/amount of EVs, or the expression level of the biomarkers expressed therein in a subject's sample. In particular, the present invention provides physicians with a non-subjective means to diagnose CFS, which will allow for early treatment, when intervention is likely to have its greatest effect. Selection of an appropriate therapeutic regimen for a given patient may be made based solely on the diagnosis provided by the inventive methods. Alternatively, the physician may also consider other clinical or pathological parameters used in existing methods to diagnose CFS and assess its advancement.

[0082] The invention further provides a method of treating CFS using any drugs, compounds, small molecules, proteins, antibodies, nucleotides, and pharmaceutical compositions thereof, that are capable of reducing circular EVs by internalizing the EVs into endothelial cells so as to reduce factors associated with the degree and/or progression of CFS or related diseases. In certain embodiments, the invention provides a method of treating CFS, using any drugs, compounds, small molecules, proteins, antibodies, nucleotides, and pharmaceutical compositions thereof, that are capable of interacting one or more protein biomarkers expressed and/or detected on the EVs so as to reducing their expression and/or activity level. [0083] The invention contemplates any conventional methods for formulation of pharmaceutical compositions as described above. Various additives, known to those skilled in the art, may be included in the formulations. For example, solvents, including relatively small amounts of alcohol, may be used to solubilize certain drug substances. Other optional additives include opacifiers, antioxidants, fragrance, colorant, gelling agents, thickening agents, stabilizers, surfactants and the like. Other agents may also be added, such as antimicrobial agents, to prevent spoilage upon storage, i.e., to inhibit growth of microbes such as yeasts and molds. Suitable antimicrobial agents are typically selected from the group consisting of the methyl and propyl esters of p-hydroxybenzoic acid (i.e., methyl and propyl paraben), sodium benzoate, sorbic acid, imidurea, and combinations thereof. [0084] Effective dosages and administration regimens can be readily determined by good medical practice and the clinical condition of the individual subject. The frequency of administration will depend on the pharmacokinetic parameters of the active ingredient(s) and the route of administration. The optimal pharmaceutical formulation can be determined depending upon the route of administration and desired dosage. Such formulations may influence the physical state, stability, rate of in vivo release, and rate of in vivo clearance of the administered compounds.

[0085] Depending on the route of administration, a suitable dose may be calculated according to body weight, body surface area, or organ size. Optimization of the appropriate dosage can readily be made by those skilled in the art in light of pharmacokinetic data observed in human clinical trials. The final dosage regimen will be determined by the attending physician, considering various factors which modify the action of drugs, e.g., the drug's specific activity, the severity of the damage and the responsiveness of the patient, the age, condition, body weight, sex and diet of the patient, the severity of any present infection, time of administration and other clinical factors.

[0086] The invention is further illustrated by the following examples, which are not to be construed in any way as imposing limitations upon the scope thereof. On the contrary, it is to be clearly understood that resort may be had to various other embodiments, modifications, and equivalents thereof, which, after reading the description herein, may suggest themselves to those skilled in the art without departing from the spirit of the present invention and/or the scope of the appended claims.

[0087] It is to be noted that throughout this application various publications and patents are cited. The disclosures of these publications are hereby incorporated by reference in their entireties into this application in order to describe fully the state of the art to which this invention pertains.

EXAMPLE 1

[0088] This example provides that number of circulating EVs was significantly increased in CFS patients compared to healthy individuals. The circulating EV number was significantly related to CRP level and BAP (anti-oxidative marker, negative correlation). The area of ROC curve (AUC) with circulating EV was 0.80 and it was significantly higher than AUC of CRP level (0.620) and was higher than AUC of d-Roms (oxidative marker, positive correlation) (0.550), or BAP (0.695). When applying a cut off value of CFS1 to CFS2, diagnosis was for 90-94% as CFS patient. Encapsulated miRNAs miR-21 and -146a in EVs are up-regulated in EVs coming from CFS. Flow cytometry analysis of circulating EVs

[0089] 2 μΐ of plasma was incubated in the dark for 30 minutes at room temperature with or without final 4 ug/ml of Calcein-AM (Life Technologies, Carlsbad, CA). EVs acquisition was performed by means of the BD LSRII Flow Cytometer System (BD Biosciences, San Jose, CA) and the data was analyzed using FlowJo software (TreeStar Inc., Ashland, OR). Gating parameters were defined using 2.5-μιη Alignflow alignment beads (Life Technologies) and negative control. Exosomes or MPs were identified using a forward-scatter analysis. The EV number was counted using 2.5-μιη Alignflow alignment beads (Life Technologies) as the size standards.

EV size determination [0090] Circulating EVs were ultracentrifuged at 100,000 g for 60 min at 10°C and suspend in PBS. For dynamic light scattering analysis, entire size was measured by Zetasizer nano ZS90 (Malvern) and took average from 3 healthy individual or 5 CFS patients. For Transmission electron microscope, EVs were adhered to 100 mesh Formvar and carbon coated grids for 5 minutes at room temperature. Grids were washed once with water, stained with 1% uranyl acetate (Ladd Research Industries, Williston VT) for 1 minute, dried and viewed using a JEOL 1200 EXII transmission electron microscope. Images were captured using a Gatan Orius 600 digital camera (Gatan, Pleasanton CA).

Quantification of EV contents, encapsulated miRNAs levels and proteins, in circulating EVs

[0091] For encapsulated miRNAs, circulating EVs were purified using qEV columns (Izon Science) according to the manufacturer's instruction and extracted encapsulated total RNAs using miRNeasy (Qiagen) according to the manufacturer's instruction. Entire encapsulated miRNAs were detected via 3D-Gene microRNA chip at TORAY (Tokyo). Furthermore, circulating MPs were ultracentrifuged at 20,000 g for 30 min at 10°C and extracted encapsulated total RNAs using miRNeasy (Qiagen) according to the manufacturer's instruction. From making template to quantification of miRNAs were performed as previously described. Mitchell et al., Proc. Natl. Acad. Sci. US, 2008, 105(30: 10513-8). Briefly, the templates were made using microRNA reverse transcription kit (Life Technologies) with specific primers, which are provided with TaqMan microRNA probes (Life Technologies). Real-time PCR quantification for miRNA expression was performed using a TaqMan microRNA expression assay from Life Technologies. Cq value was converted to relative number using power formulation and indicated as fold change.

[0092] For proteins, circulating EVs were purified using qEV columns (Izon Science) according to the manufacturer's instruction and proteins were detected via shotgun proteomics using DiNa system (TYA TECH corp.) and TripleTOF 5600 (AB Sciex) at Oncomics Co Ltd (Nagoya). Protein list was generated using ProteinPilot software 4.5 (AB Sciex) at Oncomics Co Ltd.

Target prediction [0093] The target genes of the miRNAs were identified from DIANA-microT-

CDS, a target prediction algorithm/database with the highest sensitivity among popular methods. For the prediction score threshold, 0.9 was chosen to prioritize the most likely target genes in each microRNA. Then the union set of three individual sets of target genes were created to perform enrichment analysis against KEGG pathway and Gene Ontology using DAVID Tool and an interaction graph was drawn for a visualization using Cytoscape after converting to a simple interaction file (sif) format.

Statistics

[0094] All data are expressed as mean + S.D. unless otherwise indicated.

Differences between groups were compared by analysis of Mann-Whitney test. The correlation of EV number with CRP was made by the Spearman rank-sum test. The statistical analyses were performed using SPSS version 22.0J software for Windows (SPSS Japan, Inc., Tokyo). The statistical analyses for ROC curve were performed using Graph Pad (Graph Pad Software Inc., CA, USA). [0095] The data from this example provides the plasma from CFS patients (N=39,

CFS1) and healthy individuals (N=36) from both similar populations, such as age and sex. To verify the result, 30 CFS patients were recruited eliminating smokers and obesity, as a second group (CFS2). The data reveals that the number of circulating EVs was significantly increased in CFS1, as well as CFS2, compared to healthy individuals [Fig. 1A]. Circulating EVs were characterized via dynamic light scatter [Fig IB] or electron microscopy [Fig. 1C] into two populations: exosomes (<100 nm) and MPs (100-1000 nm).

[0096] The example provided significant correlations: 1) circulating EV number was positively correlated with C-reactive protein (CRP) (r=0.448, p=0.001) [Fig. 2A], and 2) circulating EV number was negatively correlated with biological antioxidant potential (BAP) (r=-0.314, p=0.007) [Fig. 2B]. Furthermore, significant correlation (p=0.023) was found between EV number and low CRP value in 0-0.1 range. These results demonstrated that circulating EVs are a new indicator for CFS diagnosis and correlate to current diagnosis methods, CRP and BAP. [0097] To compare the specificity and sensitivity of circulating EV number with other indexes, the area of ROC curve (AUC) was created using HC and CFS1. The AUC with circulating EV was 0.802 and it was significantly higher than AUC with CRP level (0.620) and was higher than AUC with d-Roms (0.550), or BAP (0.695) [Fig. 3A]. These results showed that circulating EV is a secure indicator of CFS diagnosis. When applying cut off value of CFS1 to CFS2, diagnosis is accurate for 90-94% CFS patients.

[0098] The data showed that circulating EV number is a novel biomarker for CFS diagnosis. Notably, the strong correlation between circulating EV number and CRP, which is indicator of inflammation. To investigate the encapsulated miRNAs in EV, the expression levels of several microRNAs, which are associated with inflammation, were checked. The microRNA profile is also be useful for a more specific CFS diagnosis.

[0099] The data provided that at least encapsulated miR-21 and -146a levels were higher in circulating EVs from CFS patients than that from healthy individuals. These results suggest that encapsulated miR-21 and -146a in circulating EVs may be used for additional CFS diagnosis. [00100] In conclusion, the example provides for using circulating EVs and their miRNA composition, such as miR-21 and 146a as novel biomarkers for CFS diagnosis. Since EVs are composed of lipids, proteins, and mRNA, these compositions are novel biomarker and therapeutic target candidates. Example 2

[00101] Analysis of EV samples from three CFS patients with low BAP, compared to a CFS patient with high BAP, provided a ranked listing of up-regulated and down- regulated miRNAs shown in Table I. Since BAP levels can be used for CFS diagnosis, miRNAs relating to BAP levels are also useful to diagnose CFS.

TABLE I

sa-m - - p .

Example 3

[00102] Analysis of EV samples from CFS patients and healthy patients demonstrated 178 proteins detectable in both CFS and healthy subjects (HC), whereas 427 proteins, including proteins related to skeletal muscle cells, were uniquely expressed in CFS subjects and 30 proteins were uniquely expressed in HC subjects. See Table II providing those proteins expressed uniquely in CFS patients.

TABLE II

REFERENCES:

1. Nakatomi, Y, Mizuno, K, Ishii A, et al. Neuroinflammation in patients with chronic fatigue syndrome/myalgic encephalomyelitis: an 11C-(R)-PK11195 PET study. J Nucl Med. 2014;55(6):945-950.

2. Afari N, Buchwald D. Chronic fatigue syndrome: a review. Am J Psychiatry.

2003;160:221-236.

3. Kuratsune H, Yamaguti K, Lindh G, et al. Brainregionsinvolvedinfatiguesensation: reduced acetylcarnitine uptake into the brain. Neuroimage. 2002;17:1256-1265. 4. Yamamoto S, Ouchi Y, Onoe H, et al. Reduction of serotonin transporters of patients with chronic fatigue syndrome. Neuroreport. 2004;15:2571-2574.

5. Okada T, Tanaka M, Kuratsune H, Watanabe Y, Sadato N. Mechanisms underlying fatigue: a voxel-based morphometric study of chronic fatigue syndrome. BMC Neurol. 2004;4:14. 6. Chaudhuri A, Behan PO. Fatigue in neurological disorders. Lancet. 2004;363:978- 988.

7. Pavese N, Metta V, Bose SK, Chaudhuri KR, Brooks DJ. Fatigue in Parkinson's disease is linked to striatal and limbic serotonergic dysfunction. Brain. 2010;133:3434-3443. 8. Natelson BH, Haghighi MH, Ponzio NM. Evidence for the presence of immune dysfunctioninchronicfatiguesyndrome. ClinDiagnLab Immunol. 2002;9:747-752.

9. Natelson BH, Weaver SA, Tseng CL, Ottenweller JE. Spinal fluid abnormalities in patients with chronic fatigue syndrome. Clin Diagn Lab Immunol. 2005;12:52-55.

10. Morris G, Maes M. A neuro-immune model of myalgic encephalomyelitis/chronic fatigue syndrome. Metab Brain Dis. 2013;28:523-540. 2012;32:1-5. 11. Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic fatigue syndrome: a comprehensive approach to its definition and study. International Chronic Fatigue Syndrome Study Group. Ann Intern Med. 1994; 121:953-959. 12. Lee KA, Hicks G, Nino-Murcia G. Validity and reliability of a scale to assess fatigue. Psychiatry Res. 1991;36:291-298.

13. Chalder T, Berelowitz G, Pawlikowska T, et al. Development of a fatigue scale. J Psychosom Res. 1993;37:147-153.

14. Radloff L. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385-401.

15. Vas A, Shchukin Y, Karrenbauer VD, et al. Functional neuroimaging in multiple sclerosis with radiolabelled glia markers: preliminary comparative PET studies withl lC-vinpocetine and 11C-PK11195 in patients. J Neurol Sci. 2008;264:9-17.

16. de Lange FP, Kalkman JS, Bleijenberg G, et al. Neural correlates of the chronic fatigue syndrome: an fMRI study. Brain. 2004;127:1948-1957.

17. Lipton P. Ischemic cell death in brain neurons. Physiol Rev.l999;79:1431-1568.

18. Pall ML. Elevated, sustained peroxynitrite levels as the cause of chronic fatigue syndrome. Med Hypotheses. 2000;54:115-125.

19. Morriss RK, Robson MJ, Deakin JF. Neuropsychological performance and nor- adrenaline function in chronic fatigue syndrome under conditions of high arousal.

Psychopharmacology (Berl). 2002;163:166-173.

20. Gupta A. Unconscious amygdalar fear conditioning in a subset of chronic fatigue syndrome patients. Med Hypotheses. 2002;59:727-735.

21. Van Houdenhove B, Kempke S, Luyten P. Psychiatric aspects of chronic fatigue syndrome and fibromyalgia. Curr Psychiatry Rep. 2010;12:208-214. Lyall M, Peakman M, Wessely S. A systematic review and critical evaluation of the immunology of chronic fatigue syndrome. J Psychosom Res. 2003;55:79-90. Fukuda S, Nojima J, Motoki Y, Yamaguti K, Nakatomi Y, Okawa N, Fujiwara K, Watanabe Y, Kuratsune H., A potential biomarker for fatigue: Oxidative stress and anti-oxidative activity, Biol Psychol. 2016 Jul;118:88-93. doi:

10.1016/j.biopsycho.2016.05.005. Epub 2016 May 17. PMID: 27224647.

Claims

What is claimed is:

1. A method of detecting chronic fatigue syndrome (CFS) in a subject, comprising: a) obtaining a biological sample of the subject, b) measuring circulating extracellular vesicles (EVs) in the sample, and c) deriving a risk score for CFS by calculating an amount of circulating EVs in the sample relative to circulating EVs in a control dataset from a population of individuals without CFS, wherein an increase in circulating EVs in the subject compared to the control database indicates CFS detection.

2. The method of claim 1, wherein the EVs are microparticles (MPs).

3. The method of claim 1, wherein at least one biomarker correlating with brain inflammation is measured in circulating EVs.

4. The method of claim 1, wherein said biomarkers are microRNAs miR-21 and - 146a.

5. The method of claim 3, wherien said biomarkers are microRNAs miR-146a, -130a, -199a, -199b, -21, -223, -142, -221, -22, and -107.

6. The method of claim 4, where at least one biomarker correlates with an isoquinoline carboxamide which binds selectively to the peripheral benzodiazepine receptor PK11195.

7. A method of treating chronic fatigue syndrome (CFS) in a subject in need, comprising: administering to said subject an effective amount of a composition comprising an agent that inhibits at least one biomarker correlating to brain inflammation expressed in circulating extracellular vesicles (EVs), thereby treating CFS in the subject.

8. The method of claim 7, wherein said circulating EVs are microparticles (MPs).

9. The method of claim 7, wherein at least one biomarker correlating with brain inflammation is measured in circulating EVs.

10. The method of claim 7, wherein said biomarkers are microRNAs miR-21 and - 146a.

11. The method of claim 7, wherien said biomarkers are microRNAs miR-146a, -130a, -199a, -199b, -21, -223, -142, -221, -22, and -107.

12. A pharmaceutical composition for use in the method of claims 7-11.

13. A method of detecting microRNAs miR-21 and -146a in a subject, comprising: a) obtaining a biological sample of the subject, b) measuring a biomarker pattern in the sample, wherein the biomarker pattern consists of a biomarker panel of microRNAs miR-21 and -146a.

14. A method of treating CFS in a subject, comprising: a) obtaining a biological sample of the subject, b) detecting a biomarker panel in the biological sample, wherein the biomarker panel comprises biomarkers microRNAs miR-146a, -130a, - 199a, -199b, -21, -223, -142, -221, -22, and -107, and c) administering to the subject an effective amount of a composition to down- regulate at least one of said biomarkers.