WO2015152724A2 - Biomarkers for the detection of frontotemporal dementia - Google Patents

Abstract

The present invention relates to methods and kits for classifying an individual as being afflicted with frontotemporal dementia (FTD). The invention further relates to the discrimination between different subtypes of FTD.

Description

Title: Biomarkers for the detection of Fronto temp oral dementia FIELD OF THE INVENTION

The present invention relates to methods and kits for classifying an individual as being afflicted with frontotemporal dementia (FTD). The invention further relates to the discrimination between different subtypes of FTD. BACKGROUND OF THE INVENTION

Frontotemporal dementia (FTD) is a neurodegenerative disorder that clinically presents with either behaviour and personality changes or language disturbance. It is the second most prevalent dementia of patients below age 65. The disease is often misdiagnosed in the early stage, either as a psychiatric disorder, or as a different type of dementia such as Alzheimer's disease (AD).

The underlying pathological spectrum of FTD, frontotemporal lobar degeneration (FTLD), can be divided in 2 main subtypes characterized by either tau or TDP-43 accumulations. These subtypes being referred to as FTLD-TDP-43 and FTLD-Tau. Correct diagnosis and subtyping is very relevant to determine patient management plans and to boost therapy development, especially to develop treatments targeting either Tau or TDP-43 pathological mechanisms.

Thus far, no reliable (set of) biomarker(s) with both high sensitivity and high specificity is available for FTD, let alone its pathological subtypes. The cerebrospinal fluid (CSF) biomarkers for AD, i.e. (p)Tau and amyloid beta-42, appear to be of limited value for the diagnosis of clinical FTD. While structural MM scans can be used to detect frontal lobe or temporal lobe atrophy, the early stages of FTD are normally not detectable. Therefore, novel biomarkers for diagnosis and prognosis and stratification of FTD subtypes are needed. SUMMARY OF THE INVENTION

One aspect of the disclosure provides a method of classifying the FTD (fr onto temp oral dementia ) status of an individual,comprising determining the concentration of at least one biomarker selected from Tables 2a, 2b, 2c, 2d, or 2e from a biological sample from said individual, and determining said FTD status based on the concentration of at least one of the biomarkers selected. Preferably, at least one biomarker selected from Table 2d and at least one biomarker selected from table 2e are determined. Preferably, the individual's FTD status is classified as

a) FTD negative

b) FTD positive

c) FTD-tau positive, or

d) FTD-TDP-43 positive.

Preferably, the method comprises determining the concentration of at least one biomarker selected from table 2a, wherein the alteration in the concentration of a biomarker from table 2a as compared to a FTD negative reference value classifies the individual as FTD-tau positive. Preferably, the method comprises determining the concentration of at least one biomarker selected from tables 2b or 2c, wherein the alteration in the concentration of a biomarker from table 2b or 2c as compared to a FTD negative reference value classifies the individual as FTD positive.

Preferably, the method comprises determining the concentration of at least one biomarker selected from table 2d, preferably wherein the alteration in the

concentration of a biomarker from table 2d as compared to a FTD negative reference value classifies the individual as FTD positive. Preferably, the method further comprises determining the concentration of at least one biomarker selected from table 2e. Preferably, the method comprises determining the concentration of at least one biomarker selected from table 2e, wherein the alteration in the concentration of a biomarker from table 2e as compared to a FTD-tau positive reference value classifies the individual as FTD-TDP-43 positive. Preferably, the sample is a bodily fluid preferably selected from blood or cerebrospinal fluid.

Preferably, the level of said biomarkers is determined by an immunoassay.

Preferably, the level of said biomarkers is determined by mass spectrometry.

One aspect of the disclosure provides for a kit for determining the concentration of at least two biomarkers in a bodily fluid, said kit comprising two binding agents, preferably wherein the binding agents are antibodies, each binding agent directed to a different biomarker selected from Tables 2a, 2b, 2c, 2d, and 2e.

Preferably the kit comprises at least one binding agent directed to a biomarker selected from Table 2d and at least one binding agent directed to a biomarker selected from Table 2e.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 FABP4 levels in CSF of the validation cohort as measured by ELISA.

**p<0.01.

Figure 2 Complement factor D levels in CSF of the validation cohort as measured by ELISA.

Figure 3 YKL-40 (i.e., CHI3L1) levels in CSF of the validation cohort as measured by ELISA. Levels were significantly higher in the FTD-tau group compared to controls, TDP-43, AD, DLB and VaD. ** pO.01.

Figure 4 MFGE-8 levels in CSF of the validation cohort as measured by ELISA. Levels were significantly decreased in FTD-TDP-43 subtype compared to control and AD. Moreover, levels were decreased in VaD patients compare to controls, AD and DBL (**p<0.01).

Figure 5 FABP4 levels in serum of the validation cohort as measured by ELISA. Levels were lower in the FTD-TDP-43 group compared to control (p=0.05).

Figure 6 YKL-40 (i.e., CHI3L1) levels in serum of the validation cohort as measured by ELISA.

Figure 7 Decision trees for diagnosis of FTD and its subtypes. DETAILED DESCRIPTION OF THE DISCLOSED EMBODIMENTS

The disclosure provides methods for classifying the FTD status of individual. The methods described herein can be used to determine whether an individual is afflicted with FTD, as well as to distinguish between FTD subtypes FTD-tau and FTD-TDP-43. As used herein, an individual's FTD status can be classified as

1) FTD negative

2) FTD positive

3) FTD-tau positive, or

4) FTD-TDP-43 positive.

Using unbiased in-depth mass-spectrometry based proteomics, candidate biomarkers were identified that are differentially expressed in FTD compared to controls, or between FTD-TDP-43 and FTD-tau subtypes. As can be seen from Tables 2a-2e, biomarkers are identified which can diagnosis FTD generally (both forms of FTD) in individuals, while other biomarkers can distinguish between the two subtypes.

The use of the term FTD refers to a disorder caused by the degeneration of the brain's frontal lobes. Diagnostic criteria according to the Lund-Manchester criteria include insidious onset and gradual progression, early decline in social interpersonal conduct, early impairment in regulation of personal conduct, early emotional blunting, and early loss of insight. Symptoms of FTD generally appear between the ages of 45 and 65 years of age. In the methods disclosed herein, the concentration of at least one biomarker selected from tables 2a-2e is determined in a biological sample from an individual. The level of biomarker in the individual can be compared to a reference value. Preferably, the concentration of at least one biomarker selected from Tables 2a, 2b, 2c, and 2d is compared to a FTD negative reference value. As used herein, an FTD negative reference value is the concentration of a biomarker in a control (FTD negative) individual or the average concentration in a population of control individuals.

Preferably, the concentration of at least one biomarker selected from table 2e is compared to a FTD-tau positive reference value or an FTD-TDP-43 positive reference value. As used herein, a FTD-tau positive reference value is the concentration of a biomarker in a FTD-tau positive individual or the average concentration in a population of FTD-tau positive individuals. As used herein, a FTD-TDP-43 positive reference value is the concentration of a biomarker in a FTD-TDP-43 positive individual or the average concentration in a population of FTD-TDP-43 positive individuals. A skilled person recognizes that the change of expression level which indicates a significant difference between the individual and the reference value will depend on the particular assay used. Preferably, a (positive or negative) fold change of at least 1.2 is significant.

The disclosure further provides a method for determining the concentration of at least two biomarkers selected from Tables 2a, 2b, 2c, 2d, and 2e from a biological sample from an individual, said method comprising contacting the sample with a first binding agent which recognizes a biomarker selected from Tables 2a, 2b, 2c, 2d, and 2e and a second binding agent which recognizes a different biomarker selected from Tables 2a, 2b, 2c, 2d, and 2e and determining the concentration of the at least two biomarkers from the amount of bound first and second binding agent.

As used herein, the terms individual, subject, or patient are used interchangeably and include mammals, such as primates and domesticated animals. Preferably said individual is a human. The methods disclosed herein may be used with healthy individuals, individuals suspected of suffering from FTD, or with individuals in which FTD has been diagnosed based on pathological or clinical symptoms. The disclosed methods are useful for not only for diagnosing or confirming a diagnosis of FTD but also distinguishing between pathological FTD subtypes.

In preferred embodiments, the level of biomarker is determined in vitro from a sample from an individual, preferably a biological fluid. Preferably, said sample is blood, urine, saliva, or cerebral spinal fluid (CSF), more preferably said sample is CSF.

Preferably, the methods disclosed herein determine the alteration in the

concentration of at least one biomarker from table 2a. Preferably an alteration in the concentration of at least one biomarker from table 2a as compared to a FTD negative reference value classifies said individual as FTD-tau positive. Preferably an alteration in the concentration of at least one biomarker from table 2a as compared to an FTD- TDP43 positive reference value classifies said individual as FTD-tau positive. In preferred embodiments, the concentration of at least two biomarkers from table 2a are determined. The use of multiple biomarkers increases the confidence of classifying the FTD status. Therefore, when multiple markers are used, not all of the biomarkers need to exhibit a significant differential expression in order for a risk to be

determined. It is clear to a skilled person that the alteration in the concentration of one of the two tested biomarkers also classifies said individual as FTD-tau positive. In an exemplary embodiment, the increase in FABP4, IGFALS, NDRG4 or APOL1 as compared to FTD negative reference value indicates that the individual is FTD-tau positive, whereas a decrease in MYOC, SHBG, FCGBP indicates that the individual is FTD-tau positive. Preferably, the at least one biomarker from table 2a is selected from NDRG4 and APOLl.

Preferably, the methods disclosed herein determine the alteration in the

concentration of at least one biomarker from table 2b. Preferably an alteration in the concentration of at least one biomarker from table 2b as compared to a FTD negative reference value classifies said individual as FTD positive, more preferably as FTD-tau positive. In preferred embodiments, the concentration of at least two biomarkers from table 2b are determined, wherein an alteration in one classifies the individual. In an exemplary embodiment, the decrease in IL1RAP,0LFML1, ISLR2, CNTNAP3, TENM2, GALNS, F5, QDPR, PCMT1, CTSH, OLFML3, or NOV or an increase in MAT2A, CA1, CAT, S100A7, LCAT, FSTL5, CDH15, C ASP 14, ACAN, FAH, VCL, or LRP8 indicates that the individual is FTD positive, preferably as FTD-tau positive. Preferably, at least one biomarker from Table 2b is selected from IL1RAP, OLFML1, MAT2A, CA1, CAT, and S100A7.

Preferably, the methods disclosed herein determine the alteration in the

concentration of at least one biomarker from table 2c. Preferably an alteration in the concentration of at least one biomarker from table 2c as compared to a FTD negative reference value classifies said individual as FTD positive, more preferably as FTD- TDP-43 positive. In preferred embodiments, the concentration of at least two biomarkers from table 2c are determined, wherein an alteration in one classifies the individual. In an exemplary embodiment, the decrease in GLA, LAMTOR2, MPZ, TMEM132B, IMPA1, DLD, GDA, or CPVL or the increase in CTSL1 or ST6GAL2 indicates that the individual is FTD positive. Preferably, the at least one biomarker from Table 2c is selected from GLA and LAMTOR2.

Preferably, the methods disclosed herein determine the alteration in the

concentration of at least one biomarker from table 2d. Preferably an alteration in the concentration of at least one biomarker from table 2d as compared to a FTD negative reference value classifies said individual as FTD positive. In preferred embodiments, the concentration of at least two biomarkers from table 2d are determined. It is clear to a skilled person that the alteration in the concentration of one of the two tested biomarkers also classifies said individual as FTD positive. In preferred embodiments, the concentration of at least two biomarkers from table 2d, preferably selected from SPTBN5, MFGE8, and CHI3L1, are determined and an alteration in the

concentration of the at least two biomarkers classifies said individual as FTD positive. A decrease in SPTBN5, RAD 23 B, AP2B1, CFD, MFGE8, or CHI3L1 indicates that the individual is FTD positive. Preferably, the biomarker from Table 2d is SPTBN5. Preferably the at least two biomarkers are SPTBN5 and MFGE8.

Preferably the at least two biomarkers are SPTBN5 and CHI3L1. Preferably the at least two biomarkers are MFGE8and CHI3L1.

Preferably, the methods disclosed herein determine the alteration in the

concentration of at least one biomarker from table 2e. Preferably an alteration in the concentration of at least one biomarker from table 2e as compared to a FTD-TDP-43 positive reference classifies said individual as FTD tau positive. Preferably an alteration in the concentration of at least one biomarker from table 2d as compared to a FTD-tau positive reference classifies said individual as FTD TDP-43 positive. In preferred embodiments, the concentration of at least two biomarkers from table 2e are determined. It is clear to a skilled person that the alteration in the concentration of one of the two tested biomarkers also classifies said individual. A decrease in KLK7, F13A1, HSPA8, FSCN1, CLIC4, or ABI3BP as compared to a FTD-TDP-43 positive reference indicates that the individual is FTD-tau positive. An increase in MOG, HEXA, CHIDl, UBL3 as compared to a FTD-TDP-43 positive reference indicates that the individual is FTD-tau positive. Preferably, a decrease in KLK7, F13A1, HSPA8, FSCN1, CLIC4, or ABI3BP as compared to a FTD-tau positive reference indicates that the individual is FTD-TDP-43 positive. An increase in MOG, HEXA, CHIDl, UBL3 as compared to a FTD- tau positive reference indicates that the individual is FTD-TDP-43 positive. Preferably, the at least one biomarker from Table 2e is selected from KLK7, F13A1, HSPA8, and UBL3.

In preferred embodiments, the determination of biomarkers from tables 2a-2e described above are combined.

Preferably, methods comprise 1) determining the concentration of at least one biomarker selected from table 2a as described above and 2) determining the concentration of at least one biomarker selected from table 2c as described above. Preferably, methods comprise 1) determining the concentration of at least one biomarker selected from table 2b as described above and 2) determining the concentration of at least one biomarker selected from table 2c as described above. Preferably, methods comprise 1) determining the concentration of at least one biomarker selected from table 2d as described above and 2) determining the concentration of at least one biomarker selected from table 2e or table 2a as described above.

Preferably, the methods comprise determining the concentration of SPTBN5 and KLK7, F13A1, HSPA8, or UBL3.

Preferably, the methods comprise determining the concentration of MFGE8 and KLK7, F13A1, HSPA8, or UBL3.

Preferably, the methods comprise determining the concentration of CHI3L1 and KLK7, F13A1, HSPA8, or UBL3.

Preferably, the methods comprise determining the concentration of APOL1 and GLA or LAMTOR.

Preferably, the methods comprise determining the concentration of NDRG4 and GLA or LAMTOR.

Preferably, the methods comprise determining the concentration of FABP4 and GLA or LAMTOR. Preferably, the methods comprise determining the concentration of GLA and

IL1RAP, OLFML1, MAT2A, CA1, CAT, or S100A7.

Preferably, the methods comprise determining the concentration of LAMTOR and IL1RAP, OLFML1, MAT2A, CA1, CAT, or S100A7.

The methods disclosed herein comprise determining the concentration of biomarkers. Any number of suitable assays known to one of skill in the art may be used to determine the level of the biomarkers disclosed herein. In preferred embodiments, a binding agent is used to bind and detect a biomarker disclosed herein. Preferably, the step of determining the concentration of a biomarker can also be expressed as determining the amount of binding of a binding agent to said biological sample from an individual, wherein said binding agent is specific for a biomarker selected from tables 2a-2e.

Binding agents include antibodies as well as non-immunoglobulin binding agents, such as phage display-derived peptide binders, and antibody mimics, e.g., affibodies, tetranectins (CTLDs), adnectins (monobodies), anticalins, DARPins (ankyrins), avimers, iMabs, microbodies, peptide aptamers, Kunitz domains, aptamers and affilins. As used herein, the term "antibodies" include, e.g., monoclonal antibodies; polyclonal antibodies, chimeric, human, humanized antibodies; antigen-binding fragments including, but not limited to, Fab, F(ab'), F(ab')2, complementarity determining region (CDR) fragments, single-chain antibodies (scFv), bivalent single-chain antibodies, diabodies, triabodies, tetrabodies, artificial antibodies, phage display-derived antibodies, and other antigen recognizing immunoglobulin fragments. Preferably, said binding agent is an antibody.

Techniques for producing binding agents are well known in the art. For example, monoclonal antibodies can be made by the conventional method of immunization of a mammal, followed by isolation of plasma B cells producing the monoclonal antibodies of interest and fusion with a myeloma cell. Antibodies produced by other techniques such as recombinant antibodies are also encompassed in the disclosure ("Recombinant Proteins, monoclonal antibodies and therapeutic genes", 1999, eds Mountain, A., Ney, U. and Schomburg, D., Wiley-VCH) as are polyclonal antibodies. Specific procedures for immunizing, additional immunogenic substances for boosting the immune system of the animals to be immunized and time scales for immunization are known in the art. Animals to be used for immunization include rabbits, goats, rats and chicks. The blood samples taken after sacrifice of the animals are processed according to standard procedures. Antibodies that specifically recognise the biomarkers can then be purified from the serum by known procedures, such as stepwise affinity purification. In addition, many commercially available antibodies exist, e.g., anti- FABP4 is available from, e.g., ProteinTech (15872- 1-AP) ; anti-CHI3Ll/CHI3Ll is available LifeSpan Biosciences( LS-C125352); anti-MFGE-8 is available from, e.g., Sigma (HPA002807)

Non-antibody molecules can be isolated or screened from compound libraries by conventional means. An automated system for generating and screening a compound library is described in U.S. Patents Nos. 5,901,069 and 5,463,564.

Suitable assays which utilize binding agents, generally referred to as binding or affinity assays, include, e.g., western blots, radio-immunoassay, ELISA (enzyme- linked immunosorbant assay), "sandwich" immunoassay, immunoradiometric assay, gel diffusion precipitation reaction, immunodiffusion assay, precipitation reaction, agglutination assay (e.g., gel agglutination assay, hemagglutination assay, etc.), complement fixation assay, immunofluorescence assay, protein A assay, and immunoelectrophoresis assay.

A typical ELISA assay performed in the art is described as follows. Briefly, the antigen is adsorbed to the wells of a microtiter plate. The wells are typically washed with a blocking buffer to block non-specific antibody binding and to minimize false positive results. Commonly used blocking agents are either protein solutions, such as BSA (typically used at concentrations between 1% and 5% (w/v) in PBS, pH=7.0), nonfat dry milk, or casein (the main protein component of non-fat dry milk).

After the blocking step, the wells of the microtiter plate are typically washed. The adsorbed antigen then undergoes the primary antibody incubation, after which it is typically washed again. Antibody/antigen complexes may then detected using a secondary antibody labeled with chromogenic (e.g., horseradish peroxidase and TMB), fluorescent or chemiluminescent (e.g., alkaline phosphatase) means. The amount of color or fluorescence may be measured using a luminometer, a spectrophotometer, or other similar instruments. There are many common variations on the standard ELISA protocol, including e.g., competitive ELISA and sandwich ELISA which are all known to a skilled person.

Binding agents can also be immobilized on a solid support such as a chip or microarray. A biological sample is passed over the solid support. Bound proteins are then detected using any suitable method, such as surface plasmon resonance (SPR) (See e.g., WO 90/05305, herein incorporated by reference). High throughput protein arrays are known in the art and are also described in U.S. Publication No.

20080146459. As used herein, "solid support" means a generally or substantially planar substrate onto which an array of antigens is disposed. A solid support can be composed of any material suitable for carrying the array. Materials used to construct these solid supports need to meet several requirements, such as (1) the presence of surface groups that can be easily derivatized, (2) inertness to reagents used in the assay, (3) stability over time, and (4) compatibility with biological samples. For example, suitable materials include glass, silicon, silicon dioxide (i.e., silica), plastics, polymers, hydrophilic inorganic supports, and ceramic materials. Illustrative plastics and polymers include poly(tetrafluoroethylene), poly(vinylidenedifluoride), polystyrene, polycarbonate, polymethacrylate, and combinations thereof.

The disclosed biomarkers are polypeptide based, meaning that they are characterized by mass-to-charge ratio as determined by mass spectrometry, by the shape of their spectral peak in time-of-flight mass spectrometry and by their binding characteristics to adsorbent surfaces.. Preferably, a form of mass spectrometry is used in the disclosed methods. Examples of mass spectrometers are time-of-flight, magnetic sector, quadrupole filter, ion trap, ion cyclotron resonance, electrostatic sector analyzer and hybrids of these. In a further preferred method, the mass spectrometer is a laser desorption/ionization mass spectrometer. Mass spectrometry methods are known to one in the art and are described in the examples herein, U.S. Patent Publication 20130122516, U.S. Pat. No. 5,719,060 (describing Surface Enhanced Laser Desorption and Ionization or SELDI) as well as Regnier et al. Clin Chem 2009 56: 165-171, which discusses approval of such diagnostics with the U.S. Food and Drug Administration.

In one embodiment, the biomarkers can be first captured on a chromatographic resin having chromatographic properties that bind the biomarkers. For example, one could capture the biomarkers on a cation exchange resin, wash the resin, elute the biomarkers and detect by MALDI (Matrix-assisted laser desorption/ionization. In another method, one could capture the biomarkers on a probe surface that comprises binding agents that bind the biomarkers, wash the surface to remove unbound material, elute the biomarkers from the surface and detect the eluted biomarkers by MALDI. For some probes, elution from the surface is not necessary and the biomarkers can be detected using mass spectrometry directly from the probe. In some embodiments, the sample is contacted with an affinity capture probe such as a ProteinChip array from Ciphergen Biosystems, Inc. The probe is washed with a buffer that will retain the biomarker while washing away unbound molecules. The biomarkers are detected by laser desorption/ionization mass spectrometry. These are just a few non-limiting examples of mass spectrometry technology known to a skilled person. Additional methods for detecting biomarkers using mass spectrometry are disclosed in U.S. Publication No. 20110129920.

The biomarkers may be detected in a gas phase ion spectrometer such as a time-of- flight mass spectrometer. The biomarkers are ionized by an ionization source such as a laser, the generated ions are collected by an ion optic assembly, and then a mass analyzer disperses and analyzes the passing ions. The detector then translates information of the detected ions into mass-to-charge ratios. Detection of a biomarker typically will involve detection of signal intensity. Thus, both the quantity and mass of the biomarker can be determined. Data generated by desorption and detection of biomarkers can be analyzed with the use of a programmable digital computer. The computer program analyzes the data to indicate the number of biomarkers detected, and optionally the strength of the signal and the determined molecular mass for each biomarker detected.

It is clear to a skilled person that the concentration of biomarker as disclosed herein does not need to be necessarily determined in absolute amounts. The concentration of biomarker in relation to positive or negative reference values is also encompassed within the disclosure.

The disclosure also provides kits for determining the concentration of the biomarkers disclosed herein. Preferably, said kits comprise at least two, at least three, or at least four binding agents, wherein each agent binds to a different biomarker selected from tables 2a-2e. More preferably, said kits comprise at least one binding agent that binds a biomarker from table 2a and at least one binding agent that binds a biomarker from table 2c. More preferably, said kits comprise at least one binding agent that binds a biomarker from table 2d and at least one binding agent that binds a biomarker from table 2e. Preferably, the biomarkers are the preferred biomarkers described in the methods herein.

Preferably said kits comprise a solid support, such as a chip, a microtiter plate or a bead or resin comprising said binding agents. In some embodiments, the kits comprise mass spectrometry probes, such as ProteinChip™.

The kits may also provide washing solutions and/or detection reagents specific for either unbound binding agent or for said biomarkers (sandwich type assay).

A further aspect of the disclosure provides a method of treating an individual with FTD comprising a) classifying the FTD status of the individual as FTD positive, FTD- tau positive, or FTD TDP-43 positive by a method disclosed herein and b) treating said individual with a therapeutic which treats either the pathology or symptoms of FTD. Exemplary therapeutics include antidepressants for the treatment of FTD related symptoms. Being able to distinguish the underlying pathology in FTD, is crucial for targeted therapeutics. For example, an international Phase III trial is currently being performed in FTD with LMTX, an inhibitor of tau- aggregation (TauRx Therapeutics).

Definitions

As used herein, "to comprise" and its conjugations is used in its non-limiting sense to mean that items following the word are included, but items not specifically mentioned are not excluded. In addition the verb "to consist" may be replaced by "to consist essentially of meaning that a compound or adjunct compound as defined herein may comprise additional component(s) than the ones specifically identified, said additional component(s) not altering the unique characteristic of the invention.

The articles "a" and "an" are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, "an element" means one element or more than one element.

The word "approximately" or "about" when used in association with a numerical value (approximately 10, about 10) preferably means that the value may be the given value of 10 more or less 1% of the value.

The term "treating" includes prophylactic and/or therapeutic treatments. The term "prophylactic or therapeutic" treatment is art-recognized and includes administration to the host of one or more of the subject compositions. If it is administered prior to clinical manifestation of the unwanted condition (e.g., disease or other unwanted state of the host animal) then the treatment is prophylactic (i.e., it protects the host against developing the unwanted condition), whereas if it is administered after manifestation of the unwanted condition, the treatment is therapeutic, (i.e., it is intended to diminish, ameliorate, or stabilize the existing unwanted condition or side effects thereof).

All patent and literature references cited in the present specification are hereby incorporated by reference in their entirety.

The invention is further explained in the following examples. These examples do not limit the scope of the invention, but merely serve to clarify the invention. EXAMPLES

Methods:

Patient selection: Patients with established FTLD subtypes and controls were included from the biobanks of the Amsterdam Dementia Cohort and from the

Erasmus MC. FTD pathology was reviewed according to international criteria

{Cairns, 2007}. Pathological examination was performed according protocolized procedures by the Dutch brain bank, including specific immunostaining for

intranuclear / intracytoplasmatic TDP-43- pathology and tau pathology. Genetic testing was performed for mutations in the tau and progranulin genes and for the hexanucleotide repeat at C9orf72.

All subjects underwent extensive dementia screening at baseline, including physical and neurological examination, MMSE, neuropsychological investigation, EEC, MM and laboratory tests, including lumbar puncture. Dementia diagnoses were made by consensus in a multidisciplinary meeting according to standard criteria {Roman, 1993;McKeith, 2005 }. Probable AD was diagnosed according to the criteria of the National Institute of Neurological and Communicative Disorders and Stroke- Alzheimer's Disease and Related Disorders association (NINCDS-ADRDA) {McKhann, 1984}, and all patients met the core clinical NIA-AA criteria {McKhann, 2011}.

Definite FTD was diagnosed according to the criteria of Rascovsky et al Control groups of subjects with subjective memory complaints consisted of individuals who presented with cognitive complaints, but cognitive and laboratory investigations were normal and criteria for MCI, dementia or any other neurological or psychiatric disorders known to cause cognitive complaints were not met. Groups were matched for age and gender. Patient characteristics of the discovery and validation cohorts are presented in Table 1.

The study was performed according to the ethical principles of the Declaration of Helsinki and was approved by the local ethics committee. We obtained written informed consent from all subjects participating in the study.

CSF A642, total tau and p-tau were measured with commercially available ELISAs (Innotest 6-amyloid(l-42), Innotest hTAU-Ag and Innotest Phosphotau(181P);

Innogenetics, Ghent, Belgium) on a routine basis as described before {Mulder, 2010 }. Table 1 Characteristics of included patient populations

CSF sample preparation and gel electrophoresis

For proteomics, CSF samples were recoded and analysed in a blinded fashion. To minimize inter-run bias, each gel contained 2 patients from each clinical group. All the samples were processed within the same batch of spin columns to avoid batch-to- batch variability. The depletion of top- 14 high abundant proteins was achieved as previously reported {Fratantoni, 2010}. Briefly, 1 mL aliquots of CSF from each patient were applied directly to the spin filters (Agilent Human 14 or Genway), following instructions from the manufacturer. Depleted CSF was further concentrated using 3kDa filters prior (Millipore) to loading the whole depleted CSF fraction on gradient gels from Invitrogen (NuPAGE 4-12% Bis-Tris gel, 1.5mmxl0 wells). The gels were then stained with Coomassie brilliant blue G-250 (Pierce, Rockford, IL). In-Gel Digestion

Before MS analysis, separated proteins were in-gel digested as previously described (Piersma et al., 2012). Briefly, gels were washed and dehydrated once in 50 mM ammonium bicarbonate (ABC) and twice in 50 mM ABC/50% acetonitrile (ACN). Cysteine bonds were reduced by incubation with 10 mM DTT/50 mM ABC at 56°C for 1 h and alkylated with 50 mM iodoacetamide/50 mM ABC at room temperature (RT) in the dark for 45 minutes. After washing sequentially with ABC and ABC/50% ACN, the whole gel was sliced in 5 bands for each lane. Gel parts were sliced up into approximately 1-mm cubes and collected in tubes, washed in ABC/ACN and dried in a vacuum centrifuge. Gel cubes were incubated overnight at 23°C with 6.25 ng/mL trypsin and covered with ABC to allow digestion. Peptides were extracted once in 1% formic acid and twice in 5% formic acid/50% ACN. The volume was reduced to 50 μΕ in a vacuum centrifuge prior to LC-MS analysis. NanoLC-MS/MS Analysis.

Extracted peptides were separated on a 75 μηι x 42 cm custom packed Reprosil C18 aqua column (1.9 μηι, 120 A) in a 90 min. gradient (2-32% Acetonitrile + 0.5% Acetic acid at 300 nl/min) using a U3000 RSLC high pressure nanoLC (Dionex). Eluting peptides were measured on-line by a Q Exactive mass spectrometer (ThermoFisher Scientific) operating in data- dependent acquisition mode. Peptides were ionized using a stainless-steel emitter at a potential of +2 kV (ThermoScientific). Intact peptide ions were detected at a resolution of 35,000 (at m/z 200) and fragment ions at a resolution of 17,500 (at m/z 200); the MS mass range was 350- 1,500 Da. AGC Target settings for MS were 3E6 charges and for MS/MS 2E5 charges. Peptides were selected for Higher- energy C-trap dissociation fragmentation at an underfill ratio of 1% and a quadrupole isolation window of 1.5 Da, peptides were fragmented at a normalized collision energy of 30. Raw files from MS analysis were processed using the MaxQuant computational proteomics platform version 1.3.0.5 (Cox and Mann, 2008).

Database Searching and Statistics

MS/MS spectra were searched against the Uniprot human database (release 2013_1 January 9th, 2013 , excluding fragment, 43,688 sequences) with initial precursor and fragment mass tolerance set to 7 and 20 p. p.m., respectively. Peptides with minimum of seven amino-acid length were considered with both the peptide and protein false discovery rate (FDR) set to 1%. Enzyme specificity was set to trypsin and up to two missed cleavage sites were allowed. Cysteine carbamidomethylation (Cys, +57.021464 Da) was searched as a fixed modification, whereas N-acetylation of proteins (N- terminal, +42.010565 Da), oxidized methionine (Met,+15.994915 Da), and serine, threonine, and tyrosine phosphorylations (Ser/Thr/Tyr, +79.966331 Da) were searched as variable modifications.

For each identified protein, the number of spectra was exported to a spreadsheet and normalized according to previously published procedures {Pham, 2010}. The beta- binomial test was performed to identify differentially expressed proteins among the different groups {Pham, 2010}.

Candidate biomarkers for validation were selected based on the following criteria: 1) fold change >1.2 and p-value <0.05; 2) mean spectral count of one of the clinical groups >2; 3) number of identified peptide sequences (>2?) . Next, we searched for availability of ELISA and antibodies, and selected those ELISAs with a detailed validation report (i.e. recovery, linearity results and coefficients of variation presented of individual samples) and those antibodies of which western blot reactivity against the full protein and human brain tissue was shown by the provider.

Protein expression clustering and biological functions

Functional annotation analysis has been carried out using different tools. As an initial step, all the identified proteins were searched using PANTHER classification system to retrieve a general gene ontology (GO) description of the proteomes. Then, putative biomarkers were analysed using DAVID knowledgebase {Huang, 200} to find specific enrichment of GO annotations either with respect to whole genome and the whole dataset. In particular, to reduce the redundancy of GO categories, the functional annotation clustering tool embedded in DAVID website was used. Results were reported using the most significant GO categories for each of the cluster found with the software.

Expression data were clustered using an unsupervised approach, a K-means method implemented in-house with a MATLAB script. Protein abundances were normalized to zero, mean and unit variance per protein. The number of clusters was arbitrarily set to 16. Proteins in the expression profiles were then analysed with DAVID bioinformatics tools in order to: i) gather as much information as possible on the biological functions of the proteins ii) see if the different expression profiles could match specific sets of biological functions, defining the possible involvement of those proteins in FTD pathological process. Assay validation

Human Adipocyte fatty acid protein (AFABP/FABP4) ELISA kit (Cat. No

RD191036200R) obtained from BioVendor (Karasek, Czech Republic) was used to measure the concentration of fatty acid binding protein 4 (FABP4). The recombinant AFABP protein was used as standard. CHI3Llwas detected by use of the MicroVue CHI3L1 enzyme immunoassay kit (Cat. No. 8020, QUIDEL Corporation, San Diego, USA). Purified CHI3L1 from osteosarcoma MG-63 cells was used as standard.

Complement Factor D Quantikinine ELISA (Cat. No. DFD00) was from R&D Systems, Abingdon , UK.

We tested the analytical performance of these assays for analysis of CSF. This was done with two different pools of CSF, prepared from left overs from routine diagnostics. The concentration and optimal dilution of the candidate biomarker was determined. Initial validation of linearity was performed by evaluating three serial dilutions of the CSF pools, the recovery of which had to be between 80 ad 120%, and we determined the paralellism between the standard curve and internal control samples, which also had to be between 80 and 120%. Intra-assay coefficient of variation had to be below 10%. For Western blot analysis, we analyzed whether a band was present in CSF at the expected molecular weight, if this signal was reproducible on two different days, and if the coefficient of variation between duplicate samples was acceptable.

Since the analysis of CSF from AD, LBD and VD was performed on a different day with a different batch of ELISA assays, we performed bridging by reanalysing n... samples from the validation study of FTD CSF samples.

Statistics in validation studies:

Statistics were performed in SPSS (version 20). Differences in mean values between clinical groups obtained in ELISA and Western blot experiments were analysed with with Mann-Whitney U test (2-groups), and Wilcoxon signed rank tests, applying a Bonferoni correction for multiple testing. Spearman correlation analyses were performed to study correlations between validated biomarkers and clinical and biochemical parameters. Forward logistic regression analysis was performed, with control or FTD (both pathological subtypes) and including all validated biomarkers. A p-value smaller than 0.05 was considered significant.

Results:

Identification of discriminatory CSF biomarkers and functions

To facilitate in-depth coverage of the CSF proteome, CSF samples were subjected to high-abundant protein depletion followed by SDS-PAGE fractionation, in-gel tryptic digestion and nanoLC-MS/MS analysis. In total 898 proteins were identified in CSF. The beta binomial test for comparison of the protein spectral counts in the three patient groups yielded 57 differentially regulated proteins (Table 2).

FTD-tau vs both SMC and TDP-43: In total six proteins were differentially regulated between FTD-Tau patients compared to SMC and FTD-TDP-43 patients (Table 2a). The proteins MYOC, APOL1 and NDRG4 had the highest fold change (>3.5 higher spectral counts in FTD-Tau compared to both SMC and TDP-43).

FTD-tau vs SMC: In total 25 proteins were differentially regulated between FTD-Tau patients compared to SMC only (Table 2b). The proteins IL1RAP, OLFML1 (both increased), MAT2A, CA1, CAT, S100A7 and MYOC (all five decreased) had the highest fold change (<-2.0 times decreased in FTD-Tau compared to SMC and >2.5 fold increased in FTD-Tau compared to SMC).

FTD-TDP-43 vs SMC: In total 10 CSF proteins were differentially regulated (p<0.05) between controls and FTD-TDP-43 patients (Table 2c). Of these, GLA and LAMTOR had the largest negative fold change (<-2.5 fold decrease in FTD-TDP-43 compared to SMC).

Both FTD-Tau and FTD-TDP-43 vs SMC: In total 5 proteins were differentially regulated between controls and FTD-Tau patients, of which 16 were upregulated and 15 down regulated (Table 2d). Among these, SPTBN5 had the largest negative fold change (<-2.5 fold decrease in both FTD subtypes compared to SMC).

FTD-Tau vs FTD-TDP-43: Ten proteins were differentially regulated between FTD- TDP-43 and FTD-Tau patients. The largest negative fold change was observed for KLK7, F13A1 and HSPA8 (<-2.0 fold), and the largest positive fold change was observed for UBL3 (>2.1 fold increase in FTD-Tau compared to FTD-TDP-43). As illustration, we defined two main scenario's or decision trees for diagnosing each of the FTD pathological subtypes, including only the candidate biomarkers with the a minimal/highest fold change of 2, indicated in bold in Table 2. Scenario 1 in Figure 7 starts with discrimination of FTD-Tau from control and TDP-43 using one of the biomarkers from Table 2a or Table 2b. Next, biomarkers from Table 2c are used to discriminate FTD-TDP-43 from controls.

In scenario 2, FTD diagnosis is defined first, based on combinations of biomarkers from Table 2d. Next, FTD-TDP-43 and FTD-Tau are discriminated based on biomarkers from Table 2e.

Biological pathway analyses:

To explore whether the different expression profiles were associated with specific networks and molecular and cellulite functions, the proteins in each profile were searched with the pathway tools of IPA. Distinct networks and functions were identified for each comparison. Cellular movement was the highest listed biological function for FTD-TDP-43 vs control, cellular morphology for FTD-Tau vs control, cellular death, celllar assembly and organisation and cellular function and

maintenance were shared networks. For the comparison between FTD-Tau with FTD- TDP-43, lipid metabolism was the highest list biological function, and metabolic functions were well represented.

Validation:

Three out of six tested ELISA assays and 1 out of two Western Blot assays met our validation criteria for reliable detection in CSF. These were FABP4, CHI3L1 and complement factor D, which are all related to inflammatory function. We next continued validation of these markers in a partly independent and larger cohort (n=51) of pathologically or genetically confirmed FTD pathology patients and SMC. The results in Figure 1 show that the levels of FABP4 were increased in the group of Tau-FTD patients compared to SMC (p = 0.02) and TDP-43-FTD (p =0.04) (results corrected for age ), which extended the proteomics discovery results which showed an increase in Tau-FTD compared to controls only. The FABP4 levels were also increased 2 fold in the Tau-FTD patients compared to AD-patients (p = 0.002) and LBD-patients (p=0.001)(data corrected for age and gender). The levels of FABP4 in AD and LBD were similar to SMC, while an increase was present in VaD compared to LBD

(p<0.01).

The Complement factor D levels were increased in the FTD-Tau patient group compared to the two other groups, but this difference was not significant (Figure 2). The levels of the CHI3L1 were 2-fold increased in both FTD pathological subtypes compared to controls (Figure 3), which confirmed the increase in FTD-TDP-43 and FTD-Tau compared to SMC of the discovery results. Further validation in other dementia subgroups showed that the levels of this protein even higher in FTD-Tau compared to AD (P<0.002) DLB (p<0.000) and VD (p=0.006), which remained significant after correction for age and gender.

We also analysed FABP4 and CHI3L1 in paired serum of the FTD patients available in the Amsterdam cohort (n=12 FTD-TDP-43, 4 FTD-Tau, 18 SMC), but no significant differences between the groups were observed. Serum and CSF levels of FABP4 levels correlated positively (r=0.461, p=0.009), in contrast to a lack of correlation between serum and CSF for CHI3L1.

As an additional validation, the abundance of several of the markers was determined by measuring the corresponding enzyme activity. Enzyme activity was determined as follows.

Total Be a -hexosaminidase activity was measured using 3 niM 4-methylumbelliferyl- 2-acetoamido-2-deoxy-8-D-glucopyranoside (4MUGlcNAc) as substrate in 0.1 M citric acid/0.2 M disodium phosphate buffer pH 4.5. 10 μΐ of CSF were incubated with 40 μΐ of the substrate solution for 10 min at 37°C. One unit (U) of enzyme activity was defined as the amount of enzyme that hy drolyses 1 nmol of substrate/min at 37°C. Substrate specificity: 100%.

8-hexosaminidase-A was measuerd using 3 mM 4-Methylumbelliferyl 6-Sulfo-2- acetamido-2-deoxy-8-I)-glucopy.ranoside (MUGlcNA.c-6-S04) in 0.1 M citric acid/0.2 M disodium phosphate buffer pH 4.5 . 10 μΐ of CSF were incubated with 40 μΐ of the substrate solution for 60 min at 37°C. One unit (U) of enzyme activity was defined as the amount of enzyme that hydrolyses 1 rmiol of substrate/min at 37°C. Substrate specificity: 100%,

Alpha-galactosidase A was measured using 4.5 mM 4-methylumbelliferyl- a-D- galactoside in 0.2M Na/ Acetate buffer, pH 4.5. 20 μ! of CSF were incubated with 40 μ.ί of substrate solution and 10 μΐ inhibitor alpha-galactosidase B (0.6M N-acetyl-D- galactosamine in water solution), for 120 mm at 37°C. One unit (U) of enzyme activity was defined as the amount of enzyme that hydrolyses 1 nmol of substrate/min at 37°C. Substrate specificity: 100%.

Catalase activity was analysed by a commercially available kit of Sigma, according to the manufacturer's instructions. allikrein concentrations were analysed as described by Diamandis et al, Clin Biochemistry (37:3, 2004). Specifically, CSF samples were diluted as necessary in a 60 g/1 bovine serum albumin solution and then analyzed for the following ka Slikrems, using immunofluorometric assays developed in-house: hK7, hK8 and hK10. All assays were calibrated with recombinant proteins produced in-house in yeast and

mammalian expression systems. The detection limits of these assays (in u /1) were as follows: h 7 (0.1), hK8 (0.2), and hK10 (0.05;. The within-ru and day-to-day precision of all assays was less than 10%.

Combination analysis:

We performed binary logistic regression to demonstrate the improved classification of pathological subtypes when two markers from the tables are used. Classification is expressed as sensitivity and specificity: sensitivity stands for percentage of patients that are correctly classified as patients using the test (measure for "false negatives"); specificity is the percentage of controls that are correctly classified as controls using the test (measure for "false positives").

Combination of markers from Table 2c and Table 2d:

The use of GLA (Table 2c) as a single marker discriminated FTD positive samples (samples from patients that were clinically defined as FTD) from FTD negative controls with 80% sensitivity and 80% specificity. In regards to discriminating between FTD subtypes, thus TDP-43-FTD from Tau- FTD, the percentages for sensitivity and specificity were as follows:

73% of clinically defined FTD-TDP-43 positive samples were correctly identified as TDP-43 positive (i.e, not Tau),and 50% of Tau positive samples were correctly identified as tau positive (i.e., not TDP-43) (Overall 67%)

For improving the ability to discriminate between FTD subtypes, thus TDP-43-FTD from Tau-FTD, addition of CHI311 (Table 2d) to GLA demonstrated added value. Including both GLA (Table 2c) and CHI3L1 (Table 2d) as biomarkers resulted in the following percentages for sensitivity and specificity:

82% of clinically defined FTD-TDP-43 positive samples were correctly identified as TDP-43 positive and 75% of Tau positive samples were correctly identified as Tau positive. Thus, overall 80% correctly classified both FTD-TDP-43 and FTD-Tau. Thus, the combination of markers from tables 2c and 2d improved the classification between the FTD subtypes and between these subtypes and controls.

Combination of markers from Table 2d and Table 2e

The use of MFGE8 (Table 2d) as a single marker discriminated FTD positive samples (samples from patients that were clinically defined as FTD) from FTD negative controls with 81% sensitivity and 71% specificity.

In regards to discriminating between FTD subtypes, thus TDP-43-FTD from Tau- FTD, the percentages for sensitivity and specificity were as follows:

To specifically discriminate FTD-TDP-43 from controls, use of MFGE8, 64% of clinically defined FTD-TDP-43 positive samples were correctly identified as TDP-43 positive (i.e. not control), and 77% of FTD -negative control samples were correctly identified as controls. Thus, overall 71% correctly classified both FTD-TDP-43 and controls.

For improving the ability to specifically identify TDP-43-FTD from control addition of HexA (Table 2e) to MFGE-8 demonstrated added value. Including both HexA (Table 2e) and MFGE-8 (Table 2d) as biomarkers resulted in the following percentages for sensitivity and specificity:

82% of clinically defined FTD-TDP-43 positive samples were correctly identified as TDP-43 positive and 73% of control samples were correctly identified as controls. Thus, overall 77% correctly classified both FTD-TDP-43 and controls.

Thus, the combination of markers from tables 2d and 2e improved the classification between the FTD subtypes and between these subtypes and controls. Combination of two markers from Table 2d

The use of CHI3L1 (Table 2d) as a single marker discriminated FTD positive samples (samples from patients that were clinically defined as FTD) from FTD negative controls with 69% sensitivity and 65% specificity. Including both CHI3L1 (Table 2d) and MFGE-8 (Table 2d) as biomarkers resulted in the following percentages for sensitivity and specificity:

75% of clinically defined FTD (either FTD-TDP-43 or FTD-tau) positive samples were correctly identified as FTD positive and 88% of FTD -negative control samples were correctly identified as controls. Thus, overall 82% correctly classified both FTD and controls.

Table 2a FTD-tau discriminated from control and TDP-43

Control

control Tau vs

Gene Name vs. TDP- vs tau TDP-43

43

Fold Fold Fold

p-value p-value p-value change change change

MYOC -1,817 0,011 2,054 0,016

SHBG -1,420 0,026 1,527 0,008

FCGBP -1,335 0,002 1,427 0,049

IGFALS 1,267 0,005 -1,299 0,011

NDRG4 3,459 0,000 -2,729 0,000 APOL1 5,127 0,001 -2,595 0,009

FABP4* 1.710 0,047 -1,500 0,039

* validated from immunoassay; increase in FTD-tau over control and FTD-TDP-43 Table 2b FTD-tau discriminated from control.

Control

Gene control vs vs. TDP- Tau vs TDP- Name tau 43 43

Fold Fold Fold

change p-value change p-value change p-value

IL1RAP -2,533 0,034

OLFML1 -2,013 0,023

MAT2A 2,471 0,022

CA1 3,283 0,036

CAT^# 4,473 0,031

S100A7 4,591 0,007

ISL 2 -1,969 0,014

CNTNAP3 -1,850 0,039

TENM2 -1,655 0,012

GALNS -1,462 0,041

F5 -1,424 0,037

Q.DPR -1,368 0,028

PCMT1 -1,307 0,049

CTSH -1,307 0,018

OLFML3 -1,277 0,027

NOV -1,266 0,011

LCAT 1,347 0,032 FSTL5 1,406 0,045

CDH15 1,519 0,019

CAS P 14 1,660 0,043

ACAN 1,671 0,026

FAH 1,731 0,018

VCL 1,856 0,036

L P8 1,901 0,013

^# validated in enzyme assay

Table 2c FTD-TDP-43 discriminated from control

^# validated in enzyme assay Table 2d FTD discriminated from control

validated from immunoassay; increase in FTD-tau over control and FTD-TDP-43 Table 2e TDP-43 discriminated from Tau.

Control

Gene control vs Tau vs

vs. TDP- Name tau TDP-43

43

Fold Fold Fold

p-value p-value p-value change change change

KLK7 -2,064 0,029

F13A1 -2,003 0,026

HSPA8 -1,634 0,036

UBL3 2,168 0,045

FSCN1 -1,491 0,032

CLIC4 -1,481 0,030

ABI3BP -1,268 0,044

MOG 1,295 0,042 H EXA^# 1,309 0,009

CH ID1 1,553 0,035

^# validated in enzyme assay

Table 3 provides the protein identities, gene and protein names and the sequences of the peptides identified in the examples. It is clear to a skilled person that determining the concentration of the biomarkers listed in the tables 2a- 2e includes determining the concentration of fragments of said biomarkers, such as described in the examples. Preferred fragments of the biomarkers are disclosed in Table 3.

Table 3

Prote Gene Protein name Identified Sequence Seq ID

D3YT ABI3B Target of Nesh-SH3 DAIWTERPFNSDSYSECK 1

FKGPHVR 2

FVGVQLCNSLR 3

FYNIGDQR 4

GHGEDHCQFVDSFLDGR 5

IYLSDSLTGK 6

KFVGVQLCNSLR 7

NPLGEGPVSNTVAFSTESADPR 8

RPPLPPRPTHPR 9

TGQQLTSDQLPIK 10

TGQQLTSDQLPIKEGYFR 1 1

VSEPVSAGR 12

YIQKPDNSPCSITDSVK 13

E7EX ACAN AISTRYTLDFDR 14

ARPNCGGNLLGVR 15

CYAGWLADGSLR 16

DRYEINSLVR 17

EGCYGDKDEFPGVR 18

EKEVVLLVATEGR 19

EQQSHLSSIVTPEEQEFVNNNAQDY 20

EVVLLVATEGR 21

FTFQEAANECR 22

GEWNDVPCNYHLPFTCK 23

GIVFHYR 24

GTVACGEPPVVEHAR 25

WWTQAQAH D L V I K 53

P0091 CA1 Carbonic anhydrase 1 ADGLAVIGVLMK 54

ASPDWGYDDK 55

ASPDWGYDDKNGPEQWSK 56

EIINVGHSFHVNFEDNDNR 57

ESISVSSEQLAQFR 58

GGPFSDSYR 59

HDTSLKPISVSYNPATAK 60

LFQFHFHWGSTNEHGSEHTVDGVK 61

LQKVLDALQAIK 62

LYPIANGNNQSPVDIK 63

MASPDWGYDDK 64

SLLSNVEGDNAVPMQHNNRPTQPLK 65

TSETKHDTSLKPISVSYNPATAK 66

VGEANPKLQK 67

VLDALQAIK 68

YSAELHVAHWNSAK 69

YSSLAEAASK 70

P319 CASP Caspase-14;Caspase-14 subunit DPTAEQFQEELEK 71

EDPVSCAFVVLMAHGR 72

EGSEEDLDALEHMFR 73

FQQAIDSR 74

KTNPEIQSTLR 75

KTNPEIQSTLRK 76

LENLFEALNNK 77

MAEAELVQEGK 78

RDPTAEQFQEELEK 79

RMAEAELVQEGK 80

TNPEIQSTLR 81

VYIIQACR 82

P040 CAT Catalase ADSRDPASDQMQHWK 83

ADVLTTGAGNPVGDK 84

ADVLTTGAGNPVGDKLNVITVGPR 85

AFYVNVLNEEQR 86

DAQIFIQK 87

DLFNAIATGK 88

DPILFPSFIHSQK 89

FNTANDDNVTQVR 90

FSTVAGESGSADTVR 91

FSTVAGESGSADTVRDPR 92

GAGAFGYFEVTHDITK 93

GPLLVQDVVFTDEMAHFDR 94

HMNGYGSHTFK 95

LCENIAGHLK 96

LCENIAGHLKDAQIFIQK 97

LFAYPDTHR 98

LGPNYLHIPVNCPYR 99

LSQEDPDYGIR 100

LVNANGEAVYCK 101

NAIHTFVQSGSHLAAR 102

NFTEVHPDYGSHIQALLDK 103

NFTEVHPDYGSHIQALLDKYNAEKPK 104

NLSVEDAAR 105

RFNTANDDNVTQVR 106

VWPHKDYPLIPVGK 107

P552 CDH1 Cadherin-15 AEATDADDPETDNAALR 108

AIVLAQDDASQPR 109

ALDYESCEHYELK 1 10

AWVIPPISVSENHK 1 1 1

AWVIPPISVSENHKR 1 12

DLPGSPNWVAR 1 13

DPDTEQLQR 1 14

DYDPEDWLQVDAATGR 1 15

FTILEGDPDGQFTIR 1 16

GVFSIDK 1 17

GVFSIDKFTGK 1 18

HQVPEGLHR 1 19

IQTQHVLSPASPFLK 120

LEVEDRDLPGSPNWVAR 121

LPYPLVQIK 122

SDKQQLGSVIYSIQGPGVDEEPR 123

TNEGVLSIVK 124

TSLAEGAPPGTLVATFSAR 125

VFLNAMLDR 126

VHVQDTNEPPVFQENPLR 127

VLEGAVPGTYVTR 128

VSVQNEAPLQAAALR 129

K7ER CFD Complement factor D ATLGPAVR 130

ATLGPAVRPLPWQR 131

AVPHPDSQPDTIDHDLLLLQLSEK 132

DSCKGDSGGPLVCGGVLEGVVTSGS 133

DVAPGTLCDVAGWGIVNHAGR 134

GDSGGPLVCGGVLEGVVTSGSR 135

KKPGIYTR 136

LMCAESNRR 137

RDSCKGDSGGPLVCGGVLEGVVTS 138

RLYDVLR 139

RPDSLQHVLLPVLDR 140

RTHHDGAITER 141

VASYAAW I DSVLA 142

VDRDVAPGTLCDVAGWGIVNHAGR 143

VQVLLGAHSLSQPEPSK 144

VQVLLGAHSLSQPEPSKR 145

P362 CHI3L C itinase-3-like protein 1 AEFIKEAQPGK 146

AEFIKEAQPGKK 147

DKQHFTTLIK 148

DKQHFTTLIKEMK 149

EAGTLAYYEICDFLR 150

EGDGSCFPDALDR 151

EMKAEFIK 152

FPLTNAIK 153

FPLTNAIKDALAAT 154

FSKIASNTQSR 155

FSNTDYAVGYMLR 156

FTKEAGTLAYYEICDFLR 157

GNQWVGYDDQESVK 158

GNQWVGYDDQESVKSK 159

GQEDASPDRFSNTDYAVGYMLR 160

GQEDASPDRFSNTDYAVGYMLRLGA 161

GTTGHHSPLFR 162

ILGQQVPYATK 163

ILGQQVPYATKGNQWVGYDDQESVK 164

ISQHLDFISIMTYDFHGAWR 165

KQLLLSAALSAGK 166

LGAPASKLVMG I PTFG R 167

LVCYYTSWSQYR 168

LVMGIPTFGR 169

LVMGIPTFGRSFTLASSETGVGAPIS 170

NRNPNLKTLLSVGGWNFGSQR 171

QHFTTLIK 172

QLAGAMVWALDLDDFQGSFCGQDL 173

QLLLSAALSAGK 174

RTFIKSVPPFLR 175

SFTLASSETGVGAPISGPGIPGR 176

SFTLASSETGVGAPISGPGIPGRFTK 177

SKVQYLK 178

SKVQYLKDR 179

SVPPFLR 180

TFIKSVPPFLR 181

THGFDGLDLAWLYPGR 182

THGFDGLDLAWLYPGRR 183

TLLSVGGWNFGSQR 184

TLLSVGGWNFGSQRFSKIASNTQSR 185

VQYLKDR 186

VTIDSSYDIAK 187

J3KN CHID Chitinase domain-containing protein 1 DAREPVVGAR 188

DRHFAGDVLGYVTPWNSHGYDVTK 189

EMFEVTGLHDVDQGWMR 190

FTQISPVWLQLK 191

GLVVTDLK 192

GLVVTDLKAESVVLEHR 193

HVVFYPTLK 194

LLFEDWTYDDFR 195

MVWDSQASEHFFEYK 196

NVLDSEDEIEELSK 197

SQFSDKPVQDR 198

Q9Y6 CLIC4 Chloride intracellular channel protein 4 AGSDGESIGNCPFSQR 199

DEFTNTCPSDKEVEIAYSDVAK 200

EMTGIWR 201

GVVFSVTTVDLK 202

GVVFSVTTVDLKR 203

HPESNTAGMDIFAK 204

KFLDGNEMTLADCNLLPK 205

KPADLQNLAPGTHPPFITFNSEVK 206

NSRPEANEALER 207

YLTNAYSR 208

Q9BZ CNTN Contactin-associated protein-like 3 LSLFQPGQSPR 209

SAVNLAER 210

Q9H3 CPVL Probable serine carboxypeptidase CPVL AFDMINR 21 1

CTEPEDQLYYVK 212

EDTVQSVKPWLTEIMNNYK 213

ELSLVGPFPGLNMK 214

FLSLPEVR 215

GDSGQPLFLTPYIEAGK 216

GGGHILPYDQPLR 217

GRELSLVGPFPGLNMK 218

GWDPYVG 219

IFKSDSEVAGYIR 220

KQNWFEAFEILDK 221

NNDFYVTGESYAGK 222

QAGDFHQVIIR 223

QCHECIEHIR 224

QCHECIEHIRK 225

QNWFEAFEILDK 226

SDSEVAGYIR 227

SLMGMDWK 228

SVSMPPKGDSGQPLFLTPYIEAGK 229

YLREDTVQSVKPWLTEIMNNYK 230

YVPAIAHLIHSLNPVR 231

P096 CTSH Pro-cathepsin H;Cathepsin H mini G I MG E DTYPYQG K 232

G I MG E DTYPYQG KDGYCK 233

GKNMCGLAACASYPIPLV 234

GNFVSPVK 235

GTGPYPPSVDWR 236

KGNFVSPVK 237

KKGNFVSPVK 238

KTYSTEEYHHR 239

LQTFASNWR 240

MALNQFSDMSFAEIK 241

MLSLAEQQLVDCAQDFNNHGCQGG 242

NGIPYWIVK 243

NMCGLAACASYPIPLV 244

NSWGPQWGMNGYFLIER 245

TGIYSSTSCHK 246

TPDKVNHAVLAVGYGEK 247

TYSTEEYHHR 248

VNHAVLAVGYGEK 249

P077 CTSL Cathepsin L1 ;Cathepsin L1 heavy AVATVGPISVAIDAGHESFLFYK 250

GKVFQEPLFYEAPR 251

HSFTMAMNAFGDMTSEEFR 252

LYGMNEEGWR 253

LYGMNEEGWRR 254

MIELHNQEYR 255

NHCGIASAASYPTV 256

NQGQCGSCWAFSATGALEGQMFR 257

NSWGEEWGMGGYVK 258

QVMNGFQNR 259

RNHCGIASAASYPTV 260

VFQEPLFYEAPR 261

P096 DLD Dihydrolipoyl dehydrogenase, ADGGTQVIDTK 262

ALLNNSHYYHMAHGK 263

ALTGGIAHLFK 264

EANLAASFGK 265

GIEMSEVR 266

GRIPVNTR 267

IPNIYAIGDVVAGPMLAHK 268

NETLGGTCLNVGCIPSK 269

NLGLEELGIELDPR 270

SEEQLKEEGIEYK 271

VCHAHPTLSEAFR 272

VGKFPFAANSR 273

P004 F13A Coagulation factor XIII A chain EIRPNSTVQWEEVCRPWVSGHR 274

ETFDVTLEPLSFK 275

GVNLQEFLNVTSVHLFK 276

KDGTHVVENVDATHIGK 277

KPLNTEGVMK 278

LALETALMYGAK 279

MYVAVWTPYGVLR 280

STVLTIPEIIIK 281

VEYVIGR 282

WDTNKVDHHTDKYENNK 283

P122 F5 Coagulation factor V;Coagulation factor V ADKPLSIHPQGIR 284

AGMQTPFLIMDR 285

AGMQTPFLIMDRDCR 286

APSHQQATTAGSPLR 287

ASEFLGYWEPR 288

ASKPGWWLLNTEVGENQR 289

AVQPGETYTYK 290

AWAYYSAVNPEKDIHSGLIGPLLICQK 291

AWGESTPLANKPGK 292

DGTDYIEIIPK 293

DIHSGLIGPLLICQK 294

DPDNIAAWYLR 295

DPPSDLLLLK 296

DSNMPMDMR 297

EDGILGPIIR 298

EEVQSSEDDYAEIDYVPYDDPYK 299

EFNPLVIVGLSK 300

EFVLLFMTFDEK 301

EFVLLFMTFDEKK 302

EKHTHHAPLSPR 303

EKPQSTISGLLGPTLYAEVGDIIK 304

ENQFDPPIVAR 305

ETDIEDSDDIPEDTTYK 306

ETDIEDSDDIPEDTTYKK 307

EYEPYFK 308

EYEPYFKK 309

FCENPDEVK 310

FCENPDEVKR 31 1

FCENPDEVKRDDPK 312

FTVNNLAEPQK 313

GEYEEHLGILGPIIR 314

HEDTLTLFPMR 315

HLQAGMQAYIDIK 316

HLSQDTGSPSGMRPWEDLPSQDTG 317

HSLVLHK 318

HTHHAPLSPR 319

HTVNPNMKEDGILGPIIR 320

IFEGNTNTK 321

ITAIITQGCK 322

IVYREYEPYFKK 323

KITAIITQGCK 324

KMHDRLEPEDEESDADYDYQNR 325

KSHEFHAINGMIYSLPGLK 326

KSWWGDYWEPFR 327

KSWYYEK 328

KVMYTQYEDESFTK 329

LAAALGIR 330

LAAEFASK 331

LAAEFASKPWIQVDMQK 332

LELFGCDIY 333

LELQGCEVNGCSTPLGMENGK 334

LELQGCEVNGCSTPLGMENGKIENK 335

LHLLNIGGSQDIHVVHFHGQTLLENG 336

LKHSLVLHK 337

LLSLGAGEFK 338

LNNGGSYNAWSVEK 339

LSEGASYLDHTFPAEK 340

LSEGASYLDHTFPAEKMDDAVAPGR 341

MDDAVAPGR 342

MPMGLSTGIISDSQIK 343

MRPWKDPPSDLLLLK 344

NKADKPLSIHPQGIR 345

NVMYFNGNSDASTIK 346

NVMYFNGNSDASTIKENQFDPPIVAR 347

NYYIAAEEISWDYSEFVQFt 348

PGWWLLNTEVGENQR 349

PWIQVDMQK 350

PYYSDVDIMR 351

QHQLGVWPLLPGSFK 352

QWLEIDLLK 353

RHEDTLTLFPMR 354

SEAYNTFSER 355

SHEFHAINGMIYSLPGLK 356

SQHLDNFSNQIGK 357

SSMVDKIFEGNTNTK 358

SSSPELSEMLEYDR 359

SWWGDYWEPFR 360

SWYLEDNINK 361

SWYLEDNINKFCENPDEVKR 362

SYTIHYSEQGVEWKPYR 363

VMYTQYEDESFTK 364

WHLASEK 365

WIISSLTPK 366

WNILEFDEPTENDAQCLTR 367

WNILEFDEPTENDAQCLTRPYYSDVD 368

YLDSTFTKR 369

P150 FABP Fatty acid-binding protein, adipocyte CDAFVGTWK 370

EDDKLVVECVMK 371

EVGVGFATR 372

LVSSENFDDYIVIKEVGVGFATR 373

NTEISFILGQEFDEVTADDRK 374

P169 FAH Fumarylacetoacetase HLFTGPVLSK 375

Q9Y6 FCGB IgGFc-binding protein AGCVAESTAVCR 376

AGVQVWLGANGK 377

AIGYATAADCGR 378

AISGLTIDGHAVGAK 379

ALAS YVAACQAAG V V 1 E DW R 380

APGWDPLCWDECR 381

AQDFSPCYG 382

ASQHGSDVVIETDFGLR 383

AVGGKPAGWQVGGAQGCGECVSK 384

AYSHSVSLTR 385

CECGPGGHVTCQEGAACGPHEECR 386

CECGPGGHVTCQEGAACGPHEECR 387

CFEGCECDDR 388

CFEGCECDDRFLLSQGVCIPVQDCG 389

CLANGGIHYITLDGR 390

CLLPGQSGPLCDALATYAAACQAAG 391

CPGLQNTIPWYR 392

CREGGEVSCEPSSCGPHETCR 393

CSCSSSSGLTCQAAGCPPGR 394

CSVQNGLLGCYPDR 395

CTCNGATHQVTCR 396

DPCHGVTCRPQETCK 397

EEFCGLLSSPTGPLSSCHK 398

EGCVCDAGFVLSGDTCVPVGQCGCL 399

EGGEVSCEPSSCGPHETCR 400

FAVLQENVAWGNGR 401

FDFMGTCTYLLVGSCGQNAALPAFR 402

FDFMGTCVYVLAQTCGTRPGLHR 403

FDFQGTCNYVLATTGCPGVSTQGLT 404

FLLSQGVCIPVQDCGCTHNGR 405

FYPAGDVLR 406

GATTSPGVYELSSR 407

GCGEGCGPQGCPVCLAEETAPYES 408

GCVLDVCMGGGDR 409

GCVLDVCMGGGDRDILCK 410

GDKAFLCR 41 1

GEVGFVLVDNQR 412

GGGQAANALAFGNSWQEETRPGCG 413

GLQAGDVVEFEVR 414

GMVCQEHSCKPGQVCQPSGGILSCV 415

GNPAVSYVR 416

GSCPTCPEDRLEQYEGPGFCGPLAP 417

GVWVNGLR 418

GVWVNGLRVDLPAEK 419

HTTCNHVVEQLLPTSAWGTHYVVPT 420

KFDFQGTCNYVLATTGCPGVSTQGL 421

KYQKEEFCGLLSSPTGPLSSCHK 422

LASVSVSR 423

LCGACGNFDGDQTNDWHDSQEKPA 424

LCGMLTK 425

LDDGDYLCEDGCQNNCPACTPGQA 426

LDDGDYLCEDGCQNNCPACTPGQA 427

LDGPFAVCHDTLDPR 428

LDGPFAVCHDTLDPRPFLEQCVYDL 429

LDPQGAVR 430

LDPQGAVRDCVYDR 431

LDSLVAQQLQSK 432

LEDGVQACHATGCGR 433

LEQYEGPGFCGPLAPGTGGPFTTCH 434

LLFDGDAHLLMSIPSPFR 435

LLISSLSESPASVSILSQADNTSK 436

LLISSLSESPASVSILSQADNTSKK 437

LPVSLSEGR 438

LPVVLANGQIR 439

LRVPAAYAASLCGLCGNYNQDPADD 440

LRVPAAYAGSLCGLCGNYNQDPADD 441

LTYNHGGITGSR 442

LVDPQGPLK 443

NECGILADPK 444

NMVLQTTK 445

NPQGPFATCQAVLSPSEYFR 446

NTGREEFLTAFLQNYQLAYSK 447

PAGWQVGGAQGCGECVSK 448

PFLEQCVYDLCVVGGER 449

PGDEDFSIVLEK 450

QCVYDLCAQK 451

QCVYDLCAQKGDK 452

RCECGPGGHVTCQEGAACGPHEEC 453

RCECGPGGHVTCQEGAACGPHEEC 454

RCTCNGATHQVTCR 455

RFDFMGTCTYLLVGSCGQNAALPAF 456

RFDFMGTCVYVLAQTCGTRPGLHR 457

RPDFCPFQCPAHSHYELCGDSCPGS 458

RPDFCPLQCPAHSHYELCGDSCPVS 459

RVSYVGLVTVR 460

SLAAYTAACQAAGVAVKPWR 461

SPANCPLSCPANSR 462

SRLPVSLSEGR 463

SVPGCEGVALVVAQTK 464

SVPGCEGVALVVAQTKAISGLTIDGH 465

TCQGSCAALSGLTGCTTR 466

TDSFCPLHCPAHSHYSICTR 467

TEAVGQVHIFFQDGMVTLTPNK 468

TPDGSLLVR 469

TVLSPVEPSCEGMQCAAGQR 470

VAVIVSNDHAGK 471

VAYDLVYYVR 472

VDLPAEK 473

VDVTLPSSYHGAVCGLCGNMDR 474

VLVENEHR 475

VNGVLTALPVSVADGR 476

VPAAYAASLCGLCGNYNQDPADDLK 477

VPAAYAGSLCGLCGNYNQDPADDLK 478

VPSSYAEALCGLCGNFNGDPADDLA 479

VSYVGLVTVR 480

VTASSPVAVLSGHSCAQK 481

VTLQPYNVAQLQSSVDLSGSK 482

VTVNGVDMK 483

VTVNGVDMKLPVVLANGQIR 484

VTVPGNYYQLMCGLCGNYNGDPK 485

VTVPGNYYQQMCGLCGNYNGDPK 486

VVAEVQICHGK 487

VVTVAALGTNISIHK 489

VVTVAALGTNISIHKDEIGK 490

VVVCQEHSCKPGQVCQPSGGILSCV 491

VVVCQEHSCKPGQVCQPSGGILSCV 492

VYDLHGSCSYVLAQVCHPKPGDEDF 493

VYQSGPR 494

YDLAFVVASQATK 495

YQKEEFCGLLSSPTGPLSSCHK 496

YYPLGEVFYPGPECER 497

YYPLGEVFYPGPECERR 498

YYPLGQTFYPGPGCDSLCR 499

Q166 FSCN Fascin KVTGTLDANR 500

LINRPIIVFR 501

LSCFAQTVSPAEK 502

LVARPEPATGYTLEFR 503

PADEIAVDR 504

SSYDVFQLEFNDGAYNIK 505

VGKDELFALEQSCAQVVLQAANER 506

VTGTLDANR 507

WSLQSEAHR 508

YLAADKDGNVTCER 509

YLAPSGPSGTLK 510

YLKGDHAGVLK 51 1

YLTAEAFGFK 512

YSVQTADHR 513

Q8N4 FSTL Follistatin-related protein 5 AFQVIQLSLPEDQK 514

CVWASAVNVK 515

DKFIYVAQPTLDR 516

DSLFILDGR 517

EPGVTASLR 518

ETGQAECACMDLCK 519

FGFILHKDEAALQK 520

GNTVIWVGDA 521

HLALEEFYR 522

HYKPVCGSDGEFYENHCEVHR 523

IDLETMSYIK 524

ITIVHNEDCFFKGDK 525

LLGFQDEVCPK 526

LLVDQMFK 527

LNCEITEVEK 528

NEAGVDEDISSLFVEDSAR 529

NGIDITPK 530

NMLLDLQNQK 531

NNIILNNLDLEDINDFGDDGSLYITK 532

QIQDSGLFGQYLMTPSK 533

SHDQVWVLSWGTLEK 534

SYQPLMR 535

TSPTLQVITLASGNVPHHTIHTQPVGK 536

VDDFFIPTTTLIITHMR 537

VIQPIECEFQR 538

VLIVDVQSQK 539

VQYITIR 540

VVQAVSTDPVPVK 541

YFDADSNGLVDINELTQVIK 542

P340 GALN N-acetylgalactosamine-6-sulfatase AHFWTWTNSWENFR 543

AIDGLNLLPTLLQGR 544

ARPNIPVYR 545

CLTPPESIPK 546

DWEMVGR 547

FPLSFASAEYQEALSR 548

GDTLMAATLGQHK 549

LMDRPIFYYR 550

LPLIFHLGR 551

NGFYTTNAHAR 552

PFLGTSQR 553

YYEEFPINLK 554

Q9Y2 GDA Guanine deaminase AVMVSNILLINK 555

AVMVSNILLINKVNEK 556

DHLLGVSDSGK 557

DLHIQSHISENR 558

DLHIQSHISENRDEVEAVK 559

EFDAILINPK 560

ETTEESIKETER 561

EWCFKPCEIR 562

FLYLGDDR 563

FLYLGDDRNIEEVYVGGK 564

FQNIDFAEEVYTR 565

FSLSCSETLMGELGNIAK 566

FVSEMLQK 567

GASIAHCPNSNLSLSSGFLNVLEVLK 568

GTFVHSTWTCPMEVLR 569

IGLGTDVAGGYSYSMLDAIR 570

IVFLEEASQQEK 571

LATLGGSQALGLDGEIGNFEVGK 572

LATLGGSQALGLDGEIGNFEVGKEFD 573

NIEEVYVGGK 574

NLYPSYK 575

NYTSVYDK 576

RAVMVSNILLINK 577

TVMAHGCYLSAEELNVFHER 578

VCMDLNDTFPEYK 579

VCMDLNDTFPEYKETTEESIKETER 580

VKPIVTPR 581

YTFPAEHR 582

P062 GLA Alpha-galactosidase A ALLQDKDVIAINQDPLGK 583

KLGFYEWTSR 584

NFADIDDSWK 585

QLANYVHSK 586

QYCNHWR 587

SILDWTSFNQER 588

SYTIAVASLGK 589

TPTMGWLHWER 590

P068 HEXA Beta-hexosaminidase subunit alpha ALLSAPWYLNR 591

ALVIGGEACMWGEYVDNTNLVPR 592

DLLFGSGSWPR 593

DLLFGSGSWPRPYLTGK 594

EDIPVNYMK 595

ELELVTK 596

EVIEYAR 597

GFGEDFK 598

GLETFSQLVWK 599

GLLLDTSR 600

GSYNPVTHIYTAQDVK 601

GVQAQPLNVGFCEQEFEQT 602

GYVVWQEVFDNK 603

GYVVWQEVFDNKVK 604

HYLPLSSILDTLDVMAYNK 605

IQPDTIIQVWR 606

IQPDTIIQVWREDIPVNYMK 607

ISYGPDWK 608

KGSYNPVTHIYTAQDVK 609

LNVFHWHLVDDPSFPYESFTFPELM 610

LTSDLTFAYER 61 1

LWFSLLLAAAFAGR 612

SNPEIQDFMR 613

TEIEDFPR 614

LEYLLLSR 644

LFQGLGK 645

LFQGLGKLEYLLLSR 646

LHSLHLEGSCLGR 647

LSHNAIASLRPR 648

LWLEGNPWDCGCPLK 649

NLIAAVAPGAFLGLK 650

NLPEQVFR 651

SFEGLGQLEVLTLDHNQLQEVK 652

SLALGTFAHTPALASLGLSNNR 653

TFKDLHFLEELQLGHNR 654

TFTPQPPGLER 656

VAGLLEDTFPGLLGLR 657

WLDLSHNR 658

Q9N IL1 RA lnterleukin-1 receptor accessory protein CDDWGLDTMR 659

DLEEPINFR 660

DSCFNSPMK 661

IKCPLFEHFLK 662

NAVPPVIHSPNDHVVYEK 663

NEVWWTIDGK 664

QIQVFEDEPAR 665

TQILSIK 666

P292 IMPA Inositol monophosphatase 1 EIQVIPLQR 667

EIQVIPLQRDDED 668

EKYPSHSFIGEESVAAGEK 669

LFCIPVHGIR 670

LQVSQQEDITK 671

MLISSIK 672

MVLSNMEK 673

SILTDNPTWIIDPIDGTTNFVHR 674

SLLVTELGSSR 675

SSPVDLVTATDQK 676

Q6U ISLR2 Immunoglobulin superfamily containing AGLAFVLHCIADGHPTPR 677

DALGALPDLR 678

GAFADVTQVTSLWLAHNEVR 679

HAPGAGGEPDGQAPTSER 680

LPALPCAPPSVHLSAEPPLEAPGTPL 681

NLDLSHNFISSFPWSDLR 682

TVEPGALAVLSQLK 683

VAVAATGPPK 684

VSLPEPDSIACASPPALQGVPVYR 685

YAHQFADCAYK 686

P498 KLK7 Kallikrein-7 HPGYSTQTHVNDLMLVK 687

LISPQDCTK 688

MNEYTVHLGSDTLGDRR 689

NACNGDSGGPLVCR 690

WINDTMK 691

WVLTAAHCK 692

Q9Y2 LAMT Ragulator complex protein LAMTOR2 ETVGFGMLK 693

FILMDCMEGR 694

NGNQAFNEDNLK 695

VANLLLCMYAK 696

P041 LCAT Phosphatidylcholine-sterol acyltransferase FIDGFISLGAPWGGSIK 697

ITTTSPWMFPSR 698

LAGYLHTLVQNLVNNGYVR 699

LAGYLHTLVQNLVNNGYVRDETVR 700

LDKPDVVNWMCYR 701

LEPGQQEEYYR 702

LEPGQQEEYYRK 703

PMLVLASGDNQGIPIMSSIK 704

PVILVPGCLGNQLEAK 705

SSGLVSNAPGVQIR 706

STELCGLWQGR 707

TYIYDHGFPYTDPVGVLYEDGDDTVA 708

TYSVEYLDSSK 709

Q141 LRP8 Low-density lipoprotein receptor-related AIAVDPLR 710

CGGDGGGACIPER 71 1

DCEKDQFQCR 712

GDEFQCGDGTCVLAIK 713

IGFECTCPAGFQLLDQK 714

IYWCDLSYR 715

LHQLSSIDFSGGNRK 716

SGECVHLGWR 717

SPSLIFTNR 718

TISVATVDGGR 719

TLISSTDFLSHPFGIAVFEDK 720

VFWTDLENEAIFSANR 721

WKCDGEEECPDGSDESEATCTK 722

P31 1 MAT2 S-adenosylmethionine synthase isoform FVIGGPQGDAGLTGR 723

GAVLPIR 724

NFDLRPGVIVR 725

YLDEDTIYHLQPSGR 726

Q084 MFGE Lactadherin;Lactadherin short form;Medin EFVGNWNK 727

EVTGIITQGAR 728

HKEFVGNWNK 729

ILPVAWHNR 730

LYPTSCHTACTLR 731

MWVTGVVTQGASR 732

NAVHVNLFETPVEAQYVR 733

NFGSVQFVASYK 734

NLFETPILAR 735

TWGLHLFSWNPSYAR 736

VAYSLNGHEFDFIHDVNK 737

VAYSLNGHEFDFIHDVNKK 738

VTFLGLQHWVPELAR 739

BOUZ MOG Myelin-oligodendrocyte glycoprotein ALVGDEVELPCR 740

DHSYQEEAAMELK 741

DQDGDQAPEYR 742

FSDEGGFTCFFR 743

GRTELLK 744

GRTELLKDAIGEGK 745

NGKDQDGDQAPEYR 746

TELLKDAIGEGK 747

P251 MPZ Myelin protein PO DAISIFHYAK 748

GQPYIDEVGTFK 749

NPPDIVGK 750

TSQVTLYVFEK 751

YQPEGGRDAISIFHYAK 752

Q999 MYO Myocilin DPKPTYPYTQETTWR 753

ELETAYSNLLR 754

ESPSGYLR 755

LRQENENLAR 756

LSSLESLLHQLTLDQAARPQETQEGL 757

RLESSSQEVAR 758

TLTIPFK 759

YELNTETVK 760

YSSMIDYNPLEK 761

Q9UL NDR Protein NDRG4 DLDINRPGTVPNAK 762

FPEEKPLLR 763

GNRPAILTYHDVGLNHK 764

GWIDWAATK 765

LDPTTTTFLK 766

MADSGGLPQVTQPGK 767

MAGLQELR 768

YFLQGMGYMPSASMTRLAR 769

P487 NOV Protein NOV homolog AVLDGCSCCLVCAR 770

CPATPPTCAPGVR 771

CQLDVLLPEPNCPAPR 772

DGQIGCVPR 773

FCGVCSDGR 774

FQCTCRDGQIGCVPR 775

GESCSDLEPCDESSGLYCDR 776

KPVMVIGTCTCHTNCPK 777

KVEVPGECCEK 778

LCMVRPCEQEPEQPTDK 779

LCMVRPCEQEPEQPTDKK 780

NNEAFLQELELK 781

QRGESCSDLEPCDESSGLYCDR 782

SADPSNQTGICTAVEGDNCVFDGVIY 783

TIQAEFQCSPGQIVK 784

VEVPGECCEK 785

Q6U OLFM Olfactomedin-like protein 1 AFMEDNTKPAPR 786

EIDYIQYLR 787

GFLFFHNQATSNEIIK 788

IEPGTLGVEHSWDTPCR 789

SAVGNLALR 790

SHSMIHYNPR 791

VLEQGLEK 792

VYLLIGSR 793

Q9N OLFM Olfactomedin-like protein 3 AALPYFPR 794

DFTLAMAAR 795

EALRTEADTISGR 796

EDDRHLCLAK 797

EVDYLETQNPALPCVEFDEK 798

FGGPAGLWTK 799

HAAELRDFK 800

IQCSFDASGTLTPER 801

LAALEER 802

LDPQTLDTEQQWDTPCPR 803

LRDFTLAMAAR 804

MGPSTPLLILFLLSWSGPLQGQQHHL 805

MGPSTPLLILFLLSWSGPLQGQQHHL 806

MLPLLEVAEK 807

MLPLLEVAEKER 808

NEKYDMVTDCGYTISQVR 809

QLYAWDDGYQIVYK 810

R FGGPAGLWTK 81 1

RLAALEER 812

RPPGRPGGGGEMENTLQLIK 813

YDMVTDCGYTISQVR 814

YGAHASLR 815

H7BY PCMT Protein-L-isoaspartate 0- ALDVGSGSGILTACFAR 816

DDPTLLSSGR 817

ELVDDSVNNVR 818

KDDPTLLSSGR 819

LILPVGPAGGNQMLEQYDK 820

LILPVGPAGGNQMLEQYDKLQDGSIK 821

IVIGYAEEAPYDAIHVGAAAPVVPQALI 822

MKPLMGVIYVPLTDK 823

MKPLMGVIYVPLTDKEK 824

SGGASHSELIHNLR 825

SGGASHSELIHNLRK 826

TDKVFEVMLATDR 827

VFEVMLATDR 828

VIGIDHIK 829

VIGIDHIKELVDDSVNNVR 830

VQLVVGDGR 831

P094 QDPR Dihydropteridine reductase AAAAAAGEAR 832

AALDGTPGMIGYGMAK 833

EGGLLTLAGAK 834

GAVHQLCQSLAGK 835

HLKEGGLLTLAGAK 836

MTDSFTEQADQVTAEVGK 837

NCDLMWK 838

NRPSSGSLIQVVTTEGR 839

NSGMPPGAAAIAVLPVTLDTPMNR 840

NSGMPPGAAAIAVLPVTLDTPMNRK 841

QSIWTSTISSHLATK 842

RVLVYGGR 843

TELTPAYF 844

VDAILCVAGGWAGGNAK 845

VLVYGGR 846

P547 RAD2 UV excision repair protein RAD23 homolog GKDAFPVAGQK 847

IDIDPEETVK 848

ILNDDTALK 849

ILNDDTALKEYK 850

NFVVVMVTKPK 851

P31 1 S100 Protein S100-A7 GTNYLADVFEK 852

GTNYLADVFEKK 853

KGTNYLADVFEK 854

P070 SERP Glia-derived nexin AKIEVSEDGTK 855

ASAATTAILIAR 856

FTAVAQTDLK 857

FTAVAQTDLKEPLK 858

HNPTGAVLFMGQINKP 859

LVLVNAVYFK 860

NKDIVTVANAVFVK 861

NKDVFQCEVR 862

SENLHVSHILQK 863

SYQVPMLAQLSVFR 864

TIDSWMSIMVPK 865

VLGITDMFDSSK 866

VQVILPK 867

P042 SHBG Sex hormone-binding globulin DDWFMLGLR 868

DGRPEIQLHNHWAQLTVGAGPR 869

DIPQPHAEPWAFSLDLGLK 870

DS W L D KQ A E I S AS A PTS L R 871

IALGGLLFPASNLR 872

LDVDQALNR 873

LPLVPALDGCLR 874

QAAGSGHLLALGTPENPSWLSLHLQ 875

QAEISASAPTSLR 876

SCDVESNPGIFLPPGTQAEFNLR 877

TSSSFEVR 878

TWDPEGVIFYGDTNPK 879

WHQVEVK 880

Q9N SPTB Spectrin beta chain, brain 4 AALRESFLK 881

EPVPPGDLR 882

KAALRESFLK 883

LLSTLGPR 884

SIMTYVSLYYHYCSR 885

Q96J ST6G Beta-galactoside alpha-2,6- AHPAGSFHAGPGDLQK 886

EFFSSQVGR 887

EGAFPAAQVQR 888

EVHVYEYIPSVR 889

IINSQILTNPSHHFIDSSLYK 890

LLPVQGK 891

LNMGTQGDLHR 892

LVPAVPLSQLHPR 893

NPNQPFYILHPK 894

RLLPVQGK 895

WAQSQDGFEHK 896

WAQSQDGFEHKEFFSSQVGR 897

Q9NT TENM Teneurin-2 AGHWFATTTPIIGK 898

ALGTAWAK 899

ASGWSVQYR 900

DLAGNSEVVAGTGEQCLPFDEAR 901

FDYTYHDNSFR 902

FSEEGMVNAR 903

GIMFAIK 904

GSDIFEYNSK 905

HSMSTHTSIGYIR 906

IASIKPVISETPLPVDLYR 907

IDDDGYLCQR 908

IGSADGDLVTLGTTIGR 909

IKEVQYEMFR 910

ITENHQVSIIAGR 91 1

KVASVLNNAYYLDK 912

LLAVTMPSVAR 913

MVNLQSGGFSCTIR 914

NVGKEPAPFNLYMFK 915

QYIFEYDSSDR 916

SDETGWTTFYDYDHEGR 917

SFQASPNLAYTFIWDK 918

SMVLLLQSQR 919

SNNPLSSELDLK 920

TNLGHHLQYFYSDLHNPTR 921

VASVLNNAYYLDK 922

VTTGVSSIASEDSR 923

VTTGVSSIASEDSRK 924

VWSYSYLDK 925

YGLTPDTLDEEK 926

YGYTITR 927

YSYDLNGNLHLLNPGNSVR 928

YTYDYDGDGQLQSVAVNDRPTWR 929

Q14D TME Transmembrane protein 132B EPGITTVQVLSPLSDSILAEK 930

FSSLPAYLPTNLHISNAEESFFLK 931

GCSLQYQHATVR 932

IGSVVVYPTQDDLK 933

MFAFPEAR 934

SHILDSSIYSNRPK 935

TVIVLDDR 936

VEPFFIYR 937

WPIVVAEGEGQGPLIK 938

0951 UBL3 Ubiquitin-like protein 3 EFLFSPNDSASDIAK 939

ETLPEPNSQGQR 940

FLHGNVTLGALK 941

LILVSGK 942

SSNVPADMINLR 943

TTVMHLVAR 944

P182 VCL Vinculin AGEVINQPMMMAAR 945

ALASQLQDSLK 946

ALASQLQDSLKDLK 947

AQQVSQGLDVLTAK 948

AVAGNISDPGLQK 949

CDRVDQLTAQLADLAAR 950

DPSASPGDAGEQAIR 951

DYLIDGSR 952

ELLPVLISAMK 953

ELTPQVVSAAR 954

ETVQTTEDQILKR 955

EVENSEDPKFR 956

GNDIIAAAK 957

GQGSSPVAMQK 958

GWLRDPSASPGDAGEQAIR 959

IPTISTQLK 960

LANVMMGPYR 961

LLAVAATAPPDAPNREEVFDER 962

LVQAAQMLQSDPYSVPAR 963

MALLMAEMSR 964

MLGQMTDQVADLR 965

MSAEINEIIR 966

MTGLVDEAIDTK 967

NPGNQAAYEHFETMK 968

NQGIEEALK 969

NQWIDNVEK 970

QILDEAGK 971

QVATALQNLQTK 972

SFLDSGYR 973

SLGEISALTSK 974

SLLDASEEAIKK 975

STVEGIQASVK 976

TDAGFTLR 977

TNLLQVCER 978

VLQLTSWDEDAWASK 979

VMLVNSMNTVK 980

WIDNPTVDDR 981

References

[1] Alcolea D, Martinez-Lage P, Izagirre A, Clerigue M, Carmona- Iragui M, Alvarez RM, et al. Feasibility of Lumbar Puncture in the Study of

Cerebrospinal Fluid Biomarkers for Alzheimer's Disease: A Multicenter Study in Spain. J Alzheimers Dis 2013.

[2] Arnold SE, Han LY, Clark CM, Grossman M, Trojanowski JQ.

Quantitative neurohistological features of frontotemporal degeneration. Neurobiol Aging 2000;21: 913-9.

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Claims

Claims

1. A method of classifying the FTD (frontotemporal dementia ) status of an individual, comprising determining the concentration of at least one biomarker selected from Table 2d and at least one biomarker selected from table 2e from a biological sample from said individual and determining said FTD status based on the concentration of said biomarkers.

2. A method of classifying the FTD (frontotemporal dementia ) status of an individual, comprising determining the concentration of at least one biomarker selected from Tables 2a, 2b, 2c, 2d, or 2e from a biological sample from said individual, and determining said FTD status based on the concentration of at least one of the biomarkers selected.

3. The method of claim 1 or 2, wherein the individual's FTD status is classified as a) FTD negative

b) FTD positive

c) FTD-tau positive, or

d) FTD-TDP-43 positive.

4. The method of any one of the preceding claims comprising determining the concentration of at least one biomarker selected from table 2a, wherein the alteration in the concentration of a biomarker from table 2a as compared to a FTD negative reference value classifies the individual as FTD-tau positive.

5. The method of any one of the preceding claims, comprising determining the concentration of at least one biomarker selected from tables 2b or 2c, wherein the alteration in the concentration of a biomarker from table 2b or 2c as compared to a FTD negative reference value classifies the individual as FTD positive.

6. The method of any one of the preceding claims, comprising determining the concentration of at least one biomarker selected from table 2d, preferably wherein the alteration in the concentration of a biomarker from table 2d as compared to a FTD negative reference value classifies the individual as FTD positive.

7. The method of any one of claims 3-6 further comprising determining the

concentration of at least one biomarker selected from table 2e.

8. The method of claim 2, comprising determining the concentration of at least one biomarker selected from table 2e, wherein the alteration in the concentration of a biomarker from table 2e as compared to a FTD-tau positive reference value classifies the individual as FTD-TDP-43 positive.

9. The method of any of the proceeding claims wherein the sample is a bodily fluid preferably selected from blood or cerebrospinal fluid.

10. The method of any one of the proceeding claims wherein the level of said biomarkers is determined by an immunoassay.

11. The method of any one of claims 1-9, wherein the level of said biomarkers is determined by mass spectrometry.

12. A kit for determining the concentration of at least two biomarkers in a bodily fluid, said kit comprising two binding agents, preferably wherein the binding agents are antibodies, each binding agent directed to a different biomarker selected from Tables 2a, 2b, 2c, 2d, and 2e.

13. The kit of claim 12 comprising at least one binding agent directed to a biomarker selected from Table 2d and at least one binding agent directed to a biomarker selected from Table 2e.

14. The kit of claim 12 or 13, wherein said binding agents are immobilized on a substrate surface.