Novel method

Abstract

The invention relates to methods of determining whether a subject has, or is at risk of developing, a neurodegenerative disorder using ultra-sensitive techniques, in particular a single-molecular array detection method.

Description

[0001]DRI-C-P3835PCT NOVEL METHOD FIELD OF THE INVENTION The present invention relates to methods of analysing protein complexes, particularly for usein methods of detecting protein complex biomarkers for use in the detection or diagnosis ofneurodegenerative disorders. BACKGROUND OF THE INVENTION Parkinson’s disease and Alzheimer’s disease (PD and AD) are the most prevalent neurodegenerative disorders, affecting 55 million people worldwide (Hampel, H. et al. (2021); Aarsland, D. et al. (2021)). Although diagnosis of well-established disease can be accurate, based on clinical features and supportive diagnostic imaging, there is a pressing need for quantitative biological tools that work at the early stage disease, allowing diagnostics andrecruitment for early phase clinical trials (Porsteinsson, A. P. et al. (2021)). There are disease-specific protein aggregates of α-synuclein (α-syn) in PD and amyloid-β (Aβ) and tau in AD, and both diseases are also characterised by chronic inflammation, which precedes and predicts clinical progression. The development of sensitive biomarkers of inflammation has potential to improve early diagnosis particularly if used in conjunction with protein aggregation markers, and also to support stratification and monitoring in immunotherapeutic clinical trials (Angiulli, F. et al. (2021); Zimmermann, M. & Brockmann, K. (2022)). Inflammatory cytokines show low grade elevation in the blood in mild cognitive impairment (MCI), AD and PD and may predict faster disease progression, but cannot distinguish reliably between the disease state and controls (Zimmermann, M. & Brockmann, K. (2022); King, E. et al.; Chatterjee, P. et al. (2021); Williams-Gray, C. H. et al. (2016)). However specific inflammatory molecules may be of more utility, such as the complement system component regulator, clusterin, which is elevated in prodromal AD ahead of conversion to clinically manifest disease (Hakobyan, S. etal. (2016)). Biomarker identification remains challenging due to a combination of extremelylow concentration (e.g. plasma tumour necrosis factor (TNF)-α ~7 pg / mL, plasma Aβ42~20 pg / mL (Julian, A. et al. (2015); Janelidze, S. et al. (2016)) and heterogeneity in both sizeand structure of candidate protein biomarkers; many of which form aggregates in disease rather than monomers. New methods are required which are sensitive and specific enough to identify the pathological species from the population of aggregates present in samples. ELISA and single-molecule array assays have been developed and utilised for detecting picomolar concentrations ofmonomeric proteins in the blood and cerebrospinal fluid (CSF) (Chong, J. R. et al. (2021)). DRI-C-P3835PCT However, these techniques do not distinguish aggregates over monomers or aggregates with different sizes and shapes. There is a need in the art to provide improved methods and biomarkers for the detection of neurodegenerative diseases. SUMMARY OF THE INVENTIONAccording to a first aspect of the invention, there is provided a method for determining whethera subject has, or is at risk of developing, a neurodegenerative disorder, the method comprising analysing two or more types of protein complexes in a body fluid sample obtained from the subject by performing a single-molecular array detection method to quantify the level of the protein complexes present in the sample, wherein the single-molecular array detection method comprises: (i) contacting the sample with a plurality of beads comprising a capturebinding agent which specifically binds to the protein complex, (ii) applying a detection binding agent to detect the presence of the proteincomplex bound by the capture binding agent, (iii) individually isolating the beads into separate isolations,(iv) detecting the presence of the detection binding agent in the separateisolations to determine the number of separate isolations containing a protein complex bound by the capture binding agent and quantify the level of protein complexes present in the sample, wherein the single-molecular array detection method is performed for each type of protein complex. BRIEF DESCRIPTION OF THE FIGURES Figure 1: Diffraction limited images of coupled silica nanoparticles showing nosignificant aggregation. (A) α-syn calibrators at 10 nM detected using SC211-SiMPull. (B)Aβ42 calibrators at 1nM detected using 6E10-SiMPull. (C) tau calibrators at 1 nM detected using HT7-SiMPull. Scale bar = 10 µm.Figure 2: Single-Molecule Array for the detection of protein aggregates. (A)Standard curve of α-syn calibrator using the 4B12-4B12 antibody pair. (B) Standard curve ofAβ calibrator using the 6E10-6E10 antibody pair. (C) Standard curve of tau lysate calibratorusing the HT7-HT7 antibody pair. (D) Standard curve of tau lysate calibrator using the AT8-AT8 antibody pair. Panels show the mean of n = 4 technical replicates. DRI-C-P3835PCTFigure 3: Validation of SIMOA assays for the detection of protein aggregates. (A)SIMOA assays were tested for cross-reactivity against other protein aggregates to ensurespecificity for the respective protein aggregate type. (B) Denaturation of the protein aggregateswith increasing concentrations of guanidinium chloride (0-6 M) to test the specificity of theSIMOA assays for protein aggregates as opposed to monomers. (C) Accuracy of theaggregate assays across the working range for α-synuclein aggregates (4B12 antibody pair),Aβ aggregates (6E10 antibody pair), tau aggregates (HT7 antibody pair), p-tau aggregates(AT8 antibody pair). Panel A shows the mean of n = 3 technical replicates. Statistical analysis was conducted using one-way ANOVA and Tukey’s multiple comparisons test. Panel A shows the mean ± S.D. of n = 3 technical replicates, B shows the mean of n = 2 technical replicates, C shows the mean ± S.D. of n = 4 technical replicates. ns: p > 0.05, ****: p < 0.0001.Figure 4: Aggregate levels in brain homogenate from AD and control patients. (A)Schematic of post-mortem brain tissue samples used in the study. (B-G) Aggregate levels detected in brain homogenate from AD (frontal cortex, Braak Stage VI,) and control patients(frontal cortex, Braak Stage 0) using aggregate SIMOA assays for (B) α-synuclein aggregates(SC211 antibody pair), (C) α-synuclein aggregates (4B12 antibody pair), (D) Aβ aggregates(6E10 antibody pair), (E) tau aggregates (HT7 antibody pair), (F) p-tau aggregates (AT8antibody pair). (G) The ratio of p-tau to total tau aggregates was determined showing improved separation between AD and control patients. Each data point in the plot represents the mean of 2 technical replicates. Panel A-G show the mean of n = 5 AD and n = 5 control patients from n = 2 technical replicates. Statistical analysis was conducted using Welch’s t-test. ns: p > 0.05, *: p < 0.05, ****: p < 0.0001.Figure 5: Quantification of protein aggregates in human serum. Aggregate levelsdetected in the serum of early AD and control patients using aggregate SIMOA assays for (A)α-synuclein aggregates (SC211 antibody pair, 15 data points not shown on graph due tovalues being zero), (B) α-synuclein aggregates (4B12 antibody pair), (C) Aβ aggregates (6E10antibody pair), (D) tau aggregates (HT7 antibody pair), (E) p-tau aggregates (AT8 antibody pair). (F) Ratio of p-tau to total tau aggregates. Each data point in the plot represents the meanof 2 technical replicates. Panels show the mean ± S.D. of n = 20 AD and n = 20 control patients.Statistical analysis was conducted using a t-test. ns: p > 0.05, **: p < 0.01.Figure 6: Comparison of two assays using 8B9 (A-C) and 5H3 (D-F) antibodies for detectingbrain-derived tau aggregates in human plasma and serum. DRI-C-P3835PCTFigure 7: Detecting (A) brain-derived and (B) total tau aggregates in Alzheimer’s disease (AD)patients compared to non-AD patients. (C) Normalisation of brain-derived tau aggregate levels to total tau aggregate levels for each patient enhanced the assay’s diagnostic performance, (D) achieving an area under the curve (AUC) of 0.8194.Figure 8: Measuring inflammasome activation in THP-1 cells treated with Nigericin in threedifferent assay set ups.Figure 9: Comparison of plasma and serum samples from AD and non-AD patients using theASC assays.Figure 10: Comparison of plasma and serum samples from PD and healthy control (CRL)patients. DETAILED DESCRIPTION OF THE INVENTION The misfolding and aggregation of proteins and peptides plays an important role in the pathogenesis of neurodegenerative diseases. For example, in Alzheimer’s disease (AD), beta- amyloid (Aβ) aggregates form extra-cellular plaques and hyperphosphorylated tau aggregates form intra-cellular tangles. In Parkinson’s disease (PD), alpha-synuclein (α-syn) aggregates form intra-cellular inclusions called Lewy Bodies. While these larger structures have been studied in AD and PD, a body of work suggests that the smaller, sub-micron aggregates formed during the aggregation process are the cytotoxic species, initiating and promoting the pathology through variety of mechanisms. It is therefore important to develop methods todetect these small aggregates in accessible biofluids for diagnosis of disease. However, thisis challenging due to the low concentration of these aggregates in biofluids and the fact that significant post-translational modification can also occur during the aggregation process such a truncation and phosphorylation, which may hinder immunolabelling.The present invention provides an optimised method for detecting neurodegenerativediseases, particularly at early stages. The inventors have used ultra-sensitive assay methods for single-aggregate detection, such as protein aggregates that form during the development of neurodegenerative disease and inflammasome ASC specks in human biofluids. DRI-C-P3835PCT METHODS OF DIAGNOSISUses and methods of detecting, monitoring and of diagnosis and prognosis according to theinvention described herein are useful to confirm the existence of a disease, to monitor development of the disease by assessing onset and progression, or to assess amelioration or regression of the disease. Uses and methods of detecting, monitoring and of diagnosis are also useful in methods for assessment of clinical screening, prognosis, choice of therapy, evaluation of therapeutic benefit, i.e. for drug screening and drug development.According to one aspect of the invention, there is provided a method for determining whethera subject has, or is at risk of developing, a neurodegenerative disorder, the method comprising analysing two or more types of protein complexes in a body fluid sample obtained from thesubject by performing a single-molecular array detection method to quantify the level of theprotein complexes present in the sample, wherein the single-molecular array detection method comprises: (i) contacting the sample with a plurality of beads comprising a capturebinding agent which specifically binds to the protein complex, (ii) applying a detection binding agent to detect the presence of the proteincomplex bound by the capture binding agent, (iii) individually isolating the beads into separate isolations,(iv) detecting the presence of the detection binding agent in the separateisolations to determine the number of separate isolations containing a protein complex bound by the capture binding agent and quantify the level of protein complexes present in the sample, wherein the single-molecular array detection method is performed for each type of protein complex. Single-molecular detection methods are ultra-sensitive assays that enable the detection of single molecules in a sample. In one embodiment, the single-molecular detection method is a single-molecule immunoassay. In one embodiment, the single-molecular detection method comprises a solution-capture step. In this embodiment, the protein complex is captured in solution and a detection agent is added to said solution without requiring isolation. This is in contrast to methods which use a surface- capture step (i.e. wherein the analyte is captured on a surface and isolated from solution). Solution-capture techniques have the advantage that all the protein complexes present can DRI-C-P3835PCT potentially be captured, while with surface-capture only the protein complexes that reach the surface can be captured. Surface-capture methods typically use a single, large (static) surface, such as a plate, whereas solution capture methods typically use small, diffusing beads.Single-molecular array technology offers sensitivity which is much greater than traditionalimmunoassays. In brief, the technology involves performing a paramagnetic microbead-based sandwich ELISA, followed by isolation of individual capture beads in arrays of femtoliter-sizedreaction wells. Singulation of capture beads within microwells permits buildup of fluorescentproduct from an enzyme label, so that signal from a single immunocomplex can be detectedwith a charge-coupled device (CCD) camera in 30 seconds. At very low analyteconcentrations, Poisson statistics dictate that bead-containing microwells in the array will contain either a single labelled analyte molecule or no analyte molecules, resulting in a digital signal of either “active” or “inactive” wells. Data collection involves counting active wells corresponding to single enzyme labels. At higher analyte concentrations, digital measurements transition to analog measurements of total fluorescence intensity. Data isusually reported as Average Enzymes per Bead (AEB).The method described herein provides that the detection binding agent is applied before individually isolating the bound complexes into separate isolations. However, it will be understood that the detection binding agent could also be applied after the isolation. Therefore, in some embodiments, the method comprises applying a detection binding agentto detect the presence of the protein complex bound by the capture binding agent andindividually isolating the beads into separate isolations, which may occur in any order. This technology has been shown in the Examples presented herein to be particularly well suited for the detection of protein complexes for the diagnosis of early neurodegenerativedisease. Disease pathology, particularly at the early stage, involves small changes in multipleaggregates / protein assemblies and the inventors have found that detecting several smallchanges together can form a combined biomarker which shows clear changes with diseaseand hence has high diagnostic accuracy. This method is for use in body fluids, in particularserum or plasma, as will be described herein.The terms “detecting”, “determining” or “diagnosing” as used herein encompassesidentification, confirmation, and / or characterisation of a disease state. Methods of determining,monitoring and of diagnosis and prognosis according to the invention are useful to confirm theexistence of a disease, to monitor development of the disease by assessing onset and DRI-C-P3835PCT progression, or to assess amelioration or regression of the disease. Methods of determining, monitoring and of diagnosis are also useful in methods for assessment of clinical screening, prognosis, choice of therapy, evaluation of therapeutic benefit, i.e. for drug screening and drugdevelopment. Methods of the invention find particular use in the detection of disease at anearly stage (e.g. before symptoms develop) and therefore find use in prognosis, i.e. identifying patients at risk of developing disease. According to a further aspect of the invention, there is provided a method of diagnosing a neurodegenerative disorder in a subject, comprising: (a) measuring the combined biomarker described herein in a sample obtained fromthe subject; and (b) using the measurement detected for the combined biomarker to determine ifthe subject has, or is at risk of developing, a neurodegenerative disorder. In one aspect, the combined biomarker is measured using the method of analysing protein complexes as described herein. Detecting and / or quantifying may be performed directly on the purified or enriched sample, or indirectly on an extract therefrom, or on a dilution thereof. Quantifying the amount of the biomarker present in a sample may include determining the concentration of the biomarker present in the sample. In one embodiment, the sample is a body fluid (which is used interchangeably with the term “biological fluid” herein). Any body fluid sample type may be used for the invention including without limitation blood, plasma, serum, cerebrospinal fluid (CSF), nasal discharge, faeces, urine, saliva, mucous, semen and breath, e.g. as condensed breath, or an extract or purification therefrom, or dilution thereof. Biological samples also include specimens from a live subject or taken post-mortem. The samples can be prepared, for example where appropriate diluted or concentrated, and stored in the usual manner. In one embodiment, the body fluid sample is selected from: blood, serum, plasma,cerebrospinal fluid and saliva. In a preferred embodiment, the body fluid sample is selectedfrom: blood, serum or plasma. It will be clear to those skilled in the art that the detection of chromatin fragments in a body fluid has the advantage of being a minimally invasive method that does not require biopsy. DRI-C-P3835PCT Detecting and / or quantifying may be compared to a cut-off level. Cut-off values can be predetermined by analysing results from multiple patients and controls, and determining a suitable value for classifying a subject as with or without the disease. For example, for diseases where the level of biomarker is higher in patients suffering from the disease, then if the level detected is higher than the cut-off, the patient is indicated to suffer from the disease. Alternatively, for diseases where the level of biomarker is lower in patients suffering from the disease, then if the level detected is lower than the cut-off, the patient is indicated to suffer from the disease. The advantages of using simple cut-off values include the ease with which clinicians are able to understand the test and the elimination of any need for software or other aids in the interpretation of the test results. Cut-off levels can be determined using methods in the art.Detecting and / or quantifying may also be compared to a control. Therefore, in oneembodiment, the method comprises comparing the measurement / information obtained for the protein complexes to one or more controls. It will be clear to those skilled in the art that the control subjects may be selected on a variety of basis which may include, for example, subjects known to be free of the disease or may be subjects with a different disease (for example, for the investigation of differential diagnosis). Comparison with a control is well known in the field of diagnostics. The “control” may comprise a healthy subject, a non-diseased subject and / or a subject without neurodegeneration. In a further embodiment, the control is a healthy subject, optionally a healthy aged subject. In one embodiment, the level of protein complex increases compared tothe control. In an alternative embodiment, the level of protein complex decreases comparedto the control. In the case of differential diagnosis, the “control” may comprise a subject with a different neurodegenerative disorder. Therefore, according to one aspect of the invention, there is provided a differential diagnosis method for determining whether a subject has, or is at risk of developing, a neurodegenerative disorder, the method comprising performing the method as defined herein to analyse one or more protein complexes in a body fluid sample obtained from the subject and comparing the results to one or more controls with a differentneurodegenerative disorder. In one embodiment, the method is used to distinguish betweendifferent forms of dementia. In one embodiment, the method is used to distinguish betweendifferent tauopathies. In a further embodiment, the method provides a differential diagnosis of a subject with AD from a subject with FTD. DRI-C-P3835PCTIn one embodiment, the level or score of the biomarker is elevated compared to the control.It will be understood that it is not necessary to measure controls levels for comparative purposes on every occasion. For example, for healthy / non-diseased controls, once the ‘normal range’ is established it can be used as a benchmark for all subsequent tests. A normal range can be established by obtaining samples from multiple control subjects withoutneurodegeneration and testing for the level of biomarker. Results (i.e. biomarker levels) forsubjects suspected to have neurodegeneration can then be examined to see if they fall within,or outside of, the respective normal range. Use of a ‘normal range’ is standard practice for the detection of disease. In one embodiment, the method described herein is repeated on multiple occasions. This embodiment provides the advantage of allowing the detection results to be monitored over a time period. Such an arrangement will provide the benefit of monitoring or assessing the efficacy of treatment of a disease state. Such monitoring methods of the invention can be used to monitor onset, progression, stabilisation, amelioration, relapse and / or remission. In monitoring methods, test samples may be taken on two or more occasions. The method may further comprise comparing the level of the biomarker(s) present in the test sample with one or more control(s) and / or with one or more previous test sample(s) taken earlier from the same test subject, e.g. prior to commencement of therapy, and / or from the same test subject at an earlier stage of therapy. The method may comprise detecting a change in the nature or amount of the biomarker(s) in test samples taken on different occasions. A change in the level of the biomarker in the test sample relative to the level in a previous test sample taken earlier from the same test subject may be indicative of a beneficial effect, e.g. stabilisation or improvement, of said therapy on the disorder or suspected disorder. Furthermore, once treatment has been completed, the method of the invention may be periodically repeated in order to monitor for the recurrence of a disease. Methods for monitoring efficacy of a therapy can be used to monitor the therapeutic effectiveness of existing therapies and new therapies in human subjects and in non-humananimals (e.g. in animal models). Current treatments are largely aimed at reducing the level oftarget aggregates or inflammation, therefore biomarkers and methods of the present invention DRI-C-P3835PCTcan be used to monitor the efficacy of a treatment. Monitoring methods can be used to optimisethe dose, increasing or lowering it depending on how the patient responds. According to a further aspect of the invention, there is provided monitoring the efficacy of atherapy in a subject having, suspected of having, or being predisposed to a neurodegenerativedisorder in a subject, comprising:(a) measuring the combined biomarker as defined herein in a sample obtainedfrom the subject; and (b) using the measurement detected for the combined biomarker to determine ifthe subject has, or is at risk of developing, a neurodegenerative disorder. According to a further aspect of the invention, there is provided monitoring the efficacy of atherapy in a subject having, suspected of having, or being predisposed to a neurodegenerativedisorder in a subject, comprising:(a) performing a method as defined herein to analyse one or more proteincomplexes in a body fluid sample obtained from the subject; and (b) using the analysis of the one or more protein complexes to determine if thesubject has, or is at risk of developing, a neurodegenerative disorder. These monitoring methods can also be incorporated into screens for new drug substances and combinations of substances. The identification of biomarkers for a disease state permits integration of diagnosticprocedures and therapeutic regimes. The biomarker of the invention provides the means toindicate therapeutic response, failure to respond, unfavourable side-effect profile, degree of medication compliance and achievement of adequate serum drug levels. The biomarkers may be used to provide warning of adverse drug response. Biomarkers are useful in development of personalized therapies, as assessment of response can be used to fine-tune dosage, minimise the number of prescribed medications, reduce the delay in attaining effective therapy and avoid adverse drug reactions. Thus by monitoring a biomarker of the invention, subject care can be tailored precisely to match the needs determined by the disorder and the pharmacogenomic profile of the subject, the biomarker can thus be used to titrate the optimal dose, predict a positive therapeutic response and identify those subjects at high risk of severe side effects. DRI-C-P3835PCT Methods and biomarkers described herein may be used to identify if a patient is in need of further tests to confirm diagnosis of a neurodegenerative disorder. Therefore, according to a further aspect of the invention there is provided a method of identifying a patient in need offurther diagnostic tests comprising obtaining a body fluid sample from said patient, detectingthe combined biomarker described herein in the body fluid sample, and using the resultsobtained to identify whether the patient is in need of further diagnostic tests. Such tests mayinclude brain imaging (such as magnetic resonance imaging, computed tomography (CT), apositron emission tomography (PET) scan, a dopamine transporter scan (DaTscan), a singlephoton emission computed tomography (SPECT) scan), referral to a neurologist, a neurological scan and / or a biopsy. References to “subject”, “individual” or “patient” are used interchangeably herein. The subjectmay be a human or an animal subject. Preferably, the subject is preferably a human. Thesubject may be at least 20, at least 25, at least 30, at least 35, at least 40, at least 45, at least50, at least 55, at least 60, at least 65, or at least 70 years of age. Preferably, the subject is atleast 60, or at least 65 years of age. Most preferably, the subject is at least 60 years of age.Alternatively, the subject may be up to 30, up to 35, up to 40, up to 45, up to 50, up to 55, upto 60, up to 65, or up to 70 years of age.In one embodiment, the subject has not been diagnosed with a neurodegenerative disorder.In addition, the subject may display no clinical symptoms associated with a neurodegenerativedisorder (e.g. PD or AD).Methods of the invention may be used to confirm a diagnosis of a neurodegenerative disorder.Therefore, in one embodiment, the subject is suspected of suffering from a neurodegenerativedisorder. In addition, the subject may display one or more clinical symptoms associated witha neurodegenerative disorder (e.g. PD or AD).Clinical symptoms of Parkinson's disease include motor and non-motor symptoms and arewell known to the skilled practitioner. Primary motor symptoms include bradykinesia (slownessof movement), rigidity, resting tremor (for example in the hand, foot, jaw or face), or postural instability. Secondary motor symptoms include stooped posture, dystonia, fatigue, impaired fine motor dexterity and motor coordination, impaired gross motor coordination, poverty of movement, akathisia, speech problems, loss of facial expression, micrographia, difficulty swallowing, sexual dysfunction and drooling. Non-motor symptoms of Parkinson's disease include pain, sleep disturbances, hyposmia, constipation, skin problems, depression, fear or DRI-C-P3835PCT anxiety, memory difficulties and slowed thinking, urinary problems, fatigue and aching, loss of energy, compulsive behaviour and cramping. Clinical symptoms of Alzheimer's disease are also well-known in the art and include forgetfulness, confusion, depression, social withdrawal, mood swings, distrust in others, irritability and aggressiveness, changes in sleeping habits, wandering, loss of inhibitions, and delusions.In addition, or alternatively, the subject may have a family history of a neurodegenerativedisorder, such as a first degree relative with a neurodegenerative disorder. Where theneurodegenerative disorder is Parkinson's disease, the subject may have been determined tohave a mutations or polymorphism in the SNCA gene, which encodes alpha-synuclein.The uses and methods described herein may be performed in vitro, in vivo or ex vivo. Themethods described herein are preferably performed in vitro. References to acts carried out on a body fluid sample “obtained” from a subject are intended to encompass acts carried only a body fluid sample already obtained of “obtainable” from a subject and vice versa. METHODS OF ANALYSING PROTEIN COMPLEXES In one embodiment, the single-molecular detection method is a single-molecular array (SIMOA) assay. The SIMOA assay, developed and commercialised by Quanterix Inc, makes use of antibody-coated paramagnetic beads for capture of the target protein in the sample, which in turn are then incubated with a biotinylated detector antibody in a diluent, and then streptavidin beta-galactosidase (SBG) to form an immunocomplex. These beads are then drawn into a flow cell consisting of a large array of microwells each of which has sufficient space for one bead only, where they are loaded magnetically into the array. Resorufin β-D- galactopyranoside (RGP) is added, and the array is sealed with oil to prevent contamination between microwells. Any wells containing an immuno-complexed bead will ultimately show as fluorescent (“ON”) when the flow cell is imaged. Other wells containing an empty bead (or no bead) will remain dark (“OFF”). The paramagnetic beads themselves are also fluorescent at a different wavelength , such that during readout the instrument can determine which microwells contain a bead and which do not. This information together with the number of “ON” beads isused to obtain the fraction of beads which have detected a protein of interest – which canthrough use of a calibration curve, be used to obtain estimate the analyte concentration in the DRI-C-P3835PCT sample. The SIMOA assay is very sensitive for low concentrations where it works in a digital fashion, where each capture bead only has 1 or 0 immunocomplex formed on it.Also described herein is a method of analysing one or more protein complexes in a body fluidsample comprising: (a) performing an assay to quantify the level of the one or more protein complexespresent in the sample, wherein the assay comprises a capture binding agent and a detectionbinding agent which specifically bind to the protein complex, wherein the same binding agentis used as the capture binding agent and the detection binding agent; and (b) performing a method for assessing one or more morphological features of theprotein complexes present in the sample, wherein the combination of information obtained from performing steps (a) and (b) is used to analyse the protein complex. It will be understood that references herein to “protein complex” refer to a protein assemblyformed by binding of two or more monomeric proteins. This includes whether the monomericproteins are the same (i.e. a protein aggregate) or different. As such, a protein complex can contain a protein aggregate. Methods of the invention are particularly suited to detectingprotein aggregates if the same binding agent is used as the capture and detection bindingagent. This means a pair of the same binding agents is used as first the capture binding agent,and then the detection binding agent. Therefore, the capture and detection binding agents bind to the same epitope in the protein complex. This ensures to minimise the signal from any monomers.Some protein complexes contain several components so they can be captured and detectedby using two different binding agents directed to different components of the same complex.Therefore, the capture and detection binding agents may comprise different binding agents which specifically bind to different components (e.g. different epitopes or different proteins) of the protein complex. The disadvantage of using conventional ELISA for aggregate quantification is that the assayscan only measure in terms of total mass-weight, not number of entities. Thus, they cannotdistinguish between a large number of small aggregates or a small number of largeaggregates. To overcome the limitation of conventional ELISA, single-moleculeimmunoassays, including surface-based Fluorescence Intensity Distribution Analysis (sFIDA) and Single Molecule Array (SIMOA) assay, may be used. The analytes are captured and form DRI-C-P3835PCT immunocomplexes on a surface, before single-molecule microscopy is used to report on the number of targets.Methods of single molecule localization microscopy (SMLM) involve imaging small randomsubsets of fluorophores in many consecutive diffraction-limited images, which arecomputationally detected and localized with high precision. It uses the photochemicalproperties of certain fluorophores to switch them between a dark and an emissive state. The combined fluorophore localizations are used to generate a dense super-resolution image (ordense image) defined for example as a 2D histogram of independent localizations. STORM,PALM and PAINT are all SMLM techniques; they differ only in how they achieve the random activation of a subset of molecules during the acquisition. In one embodiment, protein complex quantification is performed by measuring brightnessdistribution of the protein complexes present in the sample. This embodiment is based on theprinciple that larger protein complexes will bind more antibodies and hence be brighter and produce a larger fluorescence signal. It is therefore possible to use the brightness of thecapture complexes as a proxy for size and measure the fraction of complexes brighter than acertain threshold. Methods of the invention are highly sensitive. In one embodiment, the method has a limit of detection which is less than about 10, 5 or 1 pg / ml, such as less than about 0.5 pg / ml. In particular, the limit of detection is about 0.4 pg / ml. As used herein, the term "limit of detection" or "LOD" is the point at which the measured value is larger than the uncertainty associated with it.In one embodiment, the protein complex comprises more than one type of protein. In oneembodiment, two or more types of protein complexes are quantified. In this embodiment, a second detection binding agent may be used to detect another protein present in the proteincomplex. For example, a different second detector antibody with a different coloured dye label(to the capture antibody-matched detection antibody) can be used to study co-aggregatequantity and size by intensity with diffraction-limited co-localisation imaging. In oneembodiment, the single-molecular detection method is used to measure two or more types of protein complexes as a combined biomarker. DRI-C-P3835PCT BINDING AGENTS Binding agents as used herein may comprise a ligand or binder specific for the desired biomarker, e.g. target protein complexes and / or aggregates. It will be clear to those skilled in the art that the terms “antibody”, “binder” or “ligand” as used herein are intended to include any binder capable of binding to particular molecules or entities and that any suitable binder can be used in the method of the invention. In one embodiment, the binding agent, such as the antibody, specifically binds to the target biomarker. The specificity of an antibody is the ability of the antibody to recognize a particular antigen as a unique molecular entity and distinguish it from another. An antibody that “specifically binds” to an antigen or an epitope is a term well understood in the art. A molecule is said to exhibit “specific binding” if it reacts more frequently, more rapidly, with greater duration and / or with greater affinity with a particular target antigen or epitope, than it does with alternative targets. An antibody “specifically binds” to a target antigen or epitope if it binds with greater affinity, avidity, more readily, and / or with greater duration than it binds to other substances. Ligands or binders, for example, naturally occurring or chemically synthesised compounds, are capable of specific binding to the desired target. A ligand or binder may comprise a peptide, an antibody or a fragment thereof, or a synthetic ligand such as a plastic antibody, or an aptamer or oligonucleotide, capable of specific binding to the desired target. Non-limitingexemplary binding agents include aptamers, antibodies, adnectins, ankyrins, other antibodymimetics and other protein scaffolds, autoantibodies, chimeras, small molecules, nucleic acids, lectins, ligand-binding receptors, imprinted polymers, avimers, peptidomimetics, hormone receptors, cytokine receptors, synthetic receptors, and modifications and fragmentsthereof. In some embodiments, a binding agent is selected from an aptamer and an antibody.The antibody can be a monoclonal antibody or a fragment thereof. It will be understood that if an antibody fragment is used then it retains the ability to bind the biomarker so that the biomarker may be detected (in accordance with the present invention).In a preferred embodiment, the capture binding agent and detection binding agent areantibodies. In a further preferred embodiment, the capture binding agent and detection bindingagent are monoclonal antibodies. References herein to “detection binding agent” refers to an binding agent that is capable of being detected. For example, the detection binding agents used herein are labelled to enabledetection. Therefore, the detection binding agent may be labelled with a detectable marker,such as a luminescent, fluorescent, enzyme or radioactive marker. In one embodiment, the DRI-C-P3835PCTdetection binding agent is labelled with a fluorescent marker. In a further embodiment, thefluorescent marker is a fluorescent dye, in particular a fluorescent dye with photophysical properties. In another embodiment, the detection binding agent comprises a nucleic acid reporter. In thisembodiment, a nucleic acid sequence acts as a label (a “nucleic acid reporter”) to indicate thatthe detection binding agent is present in the sample. The nucleic acid reporter may then be detected by qPCR, digital PCR, or next generating sequencing (NGS). In a further embodiment, the nucleic acid reporter comprises a target ID or barcode sequence which may be used to identify the presence of the reporter.Alternatively, or additionally, a binding agent may be labelled with an affinity tag, e.g. a biotin,avidin, streptavidin or His (e.g. hexa-His) tag. In one embodiment, the capture binding agent is indirectly attached to the solid phase such as through biotin and streptavidin, neutravidin or avidin interactions. In one embodiment, the binding agent is selected from the monoclonal antibody clones: 4B12, SC211, 6E10, HT7, AT8, 8B9, 5H3, Syn202, Syn-O2, MJFR-14 and LB509. In a further embodiment, the binding agent is selected from the monoclonal antibody clones: 4B12,SC211, 6E10, HT7, AT8, 8B9 and 5H3. In a yet further embodiment, the binding agent isselected from the monoclonal antibody clones: 4B12, SC211, 6E10, HT7 and AT8. In oneembodiment, the binding agent is selected from the antibody clones: AL177 and TMS1, inparticular AL177. CALIBRATION STANDARDSIn one embodiment, the level (i.e. number) of protein complexes in the sample is quantified,at least in part, by comparison to a calibration standard. The development of calibration standards (also referred to as “calibrators”) as described herein has enabled ultra-sensitive assay methods to provide an output in the number ofentities detected in a sample. This is distinct from current methods which provide theconcentration of an analyte (e.g. in weight / volume) compared to a protein standard. Concentration is not always suitable for the detection of protein complexes where weight can be highly variable depending on the size of the complex, and therefore the quantity / number of DRI-C-P3835PCT complexes provides valuable information, especially when detecting small changes in complex levels during disease development. The skilled person will be aware on how to use a calibration standard. For example, a sample comprising an unknown number of binding sites and the calibration standard comprising a known number of binding sites, are treated with a detection binding agent (such as a fluorescent antibody or peptide), and the number of binding sites in the sample is inferred from the result of the calibration standard. Quantification may be carried out by performing parallel assays using the sample to be tested and the calibration standard with known concentration or titer. The results can be plotted as the calibration standard to provide a calibration curve. In some embodiments, quantifying the number of protein complexes present in the sample may be determined, at least in part, using a calibration curve developed using calibration standards containing a known number or molar concentration of the protein complex. In one embodiment, the calibration standard comprises one or more protein complex epitopes. References herein to “protein complex epitope” refers to the epitope present in the protein complex to which a detection binding agent (i.e. the same detection binding agent used in the assay) specifically binds. In one embodiment, the calibration standard comprises more than one protein complex epitope, such as two or more, three or more, four or more, five or more, protein complexepitopes. The epitopes may be the same (i.e. multiple of the same epitope are used) ordifferent (i.e. the multiple epitopes may be derived from different parts of the same protein, or derived from different proteins). In one embodiment, the calibration standard comprises more than one type of protein complex epitope. This also allows calibration standards for protein complexes, consisting of two or more different epitopes and / or monomers, to be produced. When more than one type of protein complex epitope is used, preferably the aggregation-prone sequence is avoided or excluded to minimise the risk of the calibration standard clumping. PROTEIN COMPLEXES Methods and biomarkers of the invention detect protein complexes, in particular protein aggregates. As used herein, the term “protein aggregate” refers to a collection of proteins that DRI-C-P3835PCTgrouped together. Therefore, protein aggregates comprise two or more protein monomers(e.g. wherein the monomers are the same protein, i.e. a homo-multimeric protein complex). The terms “protein complex”, “protein aggregate” or “protein assembly” are usedinterchangeably herein. It will be understood that protein aggregates or complexes are notnecessarily all one protein but will contain the protein targeted by the binding agent.Methods of the invention use the same binding agent for capture and detection, therebyensuring that only species larger than dimers are specifically measured, rather than inactivemonomers which may be present in the sample. Methods of the invention may be run multiple times, optionally in parallel, to detect more thanone type of protein complex. In one embodiment, two or more types of protein complexes areanalysed. Examples of proteins complexes, such as protein complexes associated withinflammation or protein aggregates that form during the development of neurodegenerativedisease, are described herein.As described herein, the protein complex may comprise more than one type of protein. Forexample, a co-aggregate that forms during the development of neurodegenerative disease.In one embodiment, the protein complexes analysed are protein aggregates that form duringthe development of neurodegenerative disease (e.g. an amyloidogenic protein aggregate)and / or a protein complex associated with inflammation.In one embodiment, the assay is performed to quantify a total level of the protein complex anda level of the protein complex which has been post-translationally modified or truncated, toproduce a combined biomarker. References herein to the “level” of a protein complex mayrefer to the molar concentration or the number of protein complexes present in a sample.In a further embodiment, the combined biomarker is the ratio of the total level of the proteincomplex to the level of protein complex which has been post-translationally modified or truncated.PROTEIN COMPLEXES ASSOCIATED WITH INFLAMMATIONProtein complexes detected by methods of the invention may be associated with inflammation. DRI-C-P3835PCT Inflammasomes are part of the innate immune system and activate inflammatory responses. An inflammasome is a multiprotein oligomer of caspase 1, PYCARD / ASC, and a member of the NOD-like receptor (NLR) family. NLRP1, NLRP3 and NLRC4 are subsets of the NLR family and thus have two common features: the first is a nucleotide-binding domain (NBD) which is bound to by ribonucleotide-phosphates (rNTP) and is important for self-oligomerization. The second is a C-terminus leucine-rich repeat (LRR), which serves as a ligand-recognition domain for other receptors (e.g. TLR) or microbial ligands. In some embodiments, the proteincomplex is a protein aggregate present in an inflammasome, such as an NLRP3inflammasome.One such protein complex is the adapter protein apoptosis associated speck-like proteincontaining a CARD (ASC) speck which is present in inflammasomes. Therefore, in oneembodiment, the protein complex analysed is an ASC speck.The term “ASC” refers to the human adapter protein apoptosis associated speck-like proteincontaining a CARD (UniProt Acc. No. Q9ULZ3) encoded by the PYCARD gene or an allelicvariant or ortholog thereof. It may also be referred to as “CARD5” or “TMS1”.Using the same ASC antibody for capture and detection, only species larger than dimers are detected which enables inflammasome-active aggregated ASC complexes / specks, rather than inactive monomers present in the cell-free supernatant (the amount of ASC specks released by the cells), to be specifically measured. Combining ASC speck detection with analysis of Aβ, p-tau and α-syn aggregates using the optimised method has revealed the improved diagnostic accuracy of their different combinations (e.g.: ASC / Aβ, ASC / p-tau, (p-tau + ASC) / Aβ, α-syn + ASC, (α-syn + ASC) / Aβ, etc.). The results establish the utility of ASC as a sensitive and specific biomarker at identifying disease stage when combined with other biomarkers of protein aggregates. PROTEIN COMPLEXES ASSOCIATED WITH NEURODEGENERATION Protein complexes detected by methods of the invention may be protein aggregates that form during the development of neurodegenerative disease.Protein complexes detected by methods of the invention may be amyloidogenic proteinaggregates. Amyloidogenic proteins are typically soluble monomeric precursors, whichundergo conformation changes associated with the polymerization into 8- to 10-nm wide fibrils,which culminate in the formation of amyloid aggregates. Some amyloidogenic aggregates are DRI-C-P3835PCT extracellular, such as senile plaques of Alzheimer's disease, which are composed of amyloid beta (Aβ) peptides. Intracytoplasmic amyloid aggregates, such as neurofibrillary tangles in Alzheimer's disease and Lewy bodies in Parkinson's disease, are composed of the proteins tau and alpha-synuclein, respectively. In one embodiment, the protein aggregates that form during the development of neurodegenerative disease are brain-derived. Aggregates that form during neurodegenerative diseases may not be specific to the brain and therefore aggregates of the same protein deriving from peripheral, non-brain sources may also be detected in body fluids. Methods of the invention may use binding agents that selectively bind brain-derived aggregates (e.g. brain-derived tau) and avoid isoforms which are associated with peripheral sources.In one embodiment, the protein complexes analysed are selected from: Amyloid-β (Aβ)aggregates, tau aggregates, α-synuclein (α-syn) aggregates, TAR DNA-binding protein 43(TDP-43) aggregates or co-aggregates thereof. In particular, the protein complexes analysedare protein aggregates comprising Aβ, p-tau, α-syn or TDP-43. Amyloid-beta (A-beta; Αβ) refers to 39 to 43 amino acid peptides which are derived by proteolytic cleavage from the amyloid precursor protein (APP). Amyloid-beta is a majorcomponent of proteinaceous plaques found in the brain tissue of Alzheimer's disease patients.Initially it was thought that amyloid-beta becomes cytotoxic when it forms large insoluble fibrillar aggregates but more recent studies have shown that small oligomers of amyloid-beta may be the major cytotoxic species. It has been hypothesized that these small oligomers bind to the neuronal membrane, leading to cell death, possibly by membrane permeabilization. Tau is a microtubule binding protein which can aggregate to form paired helical filaments(PHFs), which are amyloid in nature (based on cross β-sheet structure). The accumulation ofhyperphosphorylated tau (p-tau) in neurons is associated with neurofibrillary degeneration.Recent work shows that oligomeric tau aggregation intermediates are the most toxic compounds formed during the process of tau fibril formation. These oligomers effectively decrease cell viability and increase phospholipid vesicle leakage. Tau oligomers have also been identified as an acutely toxic tau species in vivo, and induce neurodegeneration by affecting mitochondrial and synaptic function, both of which are early hallmarks in AD and other tauopathies. DRI-C-P3835PCT Alpha-synuclein (α-synuclein; α-syn) is a small protein expressed at high levels in neuronalcells. The central role of α-synuclein in the pathogenesis of Parkinson's disease is wellestablished by genetic and pathological data. Point mutations and multiplications of the SNCA gene are sufficient to cause an autosomal dominant form of Parkinson's disease, suggesting that dysfunction of the alpha-synuclein protein is a primary step in disease pathogenesis.TAR DNA-binding protein 43 (TDP-43) is a highly conserved RNA / DNA-binding proteininvolved in the regulation of RNA processing. TDP-43 is an intranuclear protein encoded bythe TARDBP gene that is involved in RNA splicing, trafficking, stabilization, and thereforeaffects the regulation of gene expression. TDP-43 species have been shown to colocalize withsenile plaques and neurofibrillary tangles. Furthermore, TDP-43 has been associated with theseverity of AD pathology. Phosphorylated and truncated forms of TDP-43 have beenassociated with amyotrophic lateral sclerosis (ALS) and a subset of frontotemporal lobardegeneration (FTLD). Protein complexes that have been modified, in particular post-translationally modified, are of particular interest in the present invention because modified proteins are commonlyassociated with disease pathology. Therefore, in one embodiment, the protein complexcomprises a post-translationally modified protein or a truncated protein. It will be understoodthat references to “protein” include references to “peptides”.In one embodiment, the assay is performed to produce a combined biomarker. In a furtherembodiment, the combined biomarker is the ratio of the total level of the protein complex tothe level of protein complex which has been post-translationally modified or truncated. As used herein, the term “post-translational modification” or “PTM” refers to a reaction whereina chemical moiety is covalently added to or non-covalently binds to a protein, after the initialsynthesis (i.e. translation) of the polypeptide chain. The post translational modification mayinclude phosphorylation, ubiquitination, acetylation, methylation, which may be mono-, di-ortri-methylation, ribosylation, citrullination, hydroxylation, glycosylation, nitrosylation,glutamination, pyroglutamination and / or isomerisation. In a preferred embodiment, the post-translational modification is phosphorylation or ubiquitination. For example, tau can be phosphorylated at one or more amino acid residues including tyrosine at amino acid positions 18, 29, 97, 310, and 394 serine at amino acid positions 184, 185, 198, 199, 202, 208, 214, 235, 237, 238, 262, 293, 324, 356, 396, 400, 404, 409, 412, 413, and 422; DRI-C-P3835PCT and threonine at amino acids positions 175, 181, 205, 212, 217, 231, and 403. In one embodiment, p-tau is p-tau205, p-tau202, p-tau181, p-tau217 or p-tau231. In one embodiment, p-tau is p-tau202 and / or p-tau205. In one embodiment, the protein complex comprises a protein with an N-terminal or a C- terminal truncation. In one embodiment, the protein complex comprises phosphorylated α-syn, truncated α-syn,ubiquitinated α-syn, ubiquitinated tau, phosphorylated tau, pyroglutamate-modified Amyloid-β, truncated tau or truncated Amyloid-β.COMBINED BIOMARKER Aggregates of α-syn, Aβ and tau are sensed by the immune system via pattern recognitionreceptors (PRRs) (Kouli, A. et al. (2018); Tahara, K. et al. (2006); Meng, J. X. et al. (2022)).These aggregates trigger a pro-inflammatory cascade through Toll-like receptors and NLRP3 inflammasome formation in immune cells such as microglia, astrocytes and blood monocytes which, if not resolved, may lead to neuronal damage and ultimately neurodegeneration (Latz, E. et al. (2013); Gordon, R. et al. (2018); Halle, A. et al. (2008)). Inflammasome complexes contain an NLR (nucleotide-binding domain, leucine-rich repeat containing) protein, the adapter protein apoptosis associated speck-like protein containing a CARD (ASC) and an effector protein (caspase 1). Activation of inflammasomes results in cleavage of pro-IL-1β and pro-IL-18 (to form active inflammatory cytokines) and gasdermin D to trigger lytic cell death. During inflammasome activation ASC rapidly assembles into a large protein complex, up to1 µm in size, termed the ‘speck' which can, ultimately, be lost from the cell when it ruptures(Venegas, C. et al. (2017)). Inflammasome activation contributes to AD and PD pathology indisease models (Gordon, R. et al. (2018); Dempsey, C. et al. (2017)). There is increasedexpression of NLRP3 inflammasome in human AD and PD brain and blood (Holbrook, J. A. etal. (2021); Jewell, S. et al. (2022)).In one embodiment, the method (e.g. the single-molecular array detection method) is used tomeasure two or more types of protein complexes to produce a combined biomarker. In oneembodiment, the method (e.g. the single-molecular array detection method) is used tomeasure a total level of a protein complex and a level of the protein complex which has been post-translationally modified or truncated, to produce a combined biomarker. DRI-C-P3835PCTThe present inventors have developed assays for both total aggregates and post-translationalmodified aggregates which enables a ratio to be determined (i.e. as a combined biomarker).Aggregate concentration during assay runs due to the aggregates sticking to the walls ofcontainers and sample handling which is a big problem in the field. The present inventors havefound that measuring the changes in the proportion of aggregates, rather than concentration(i.e. total monomer concentration / weight, as currently measured), reduces the effect ofadsorption and sample handling to provide a more accurate diagnostic test on a sample. Thismay be done by taking ratios of the concentration of one type of aggregate to another.In one embodiment, the combined biomarker is determined as a ratio. In particular, thecombined biomarker may be the ratio of two or more protein aggregates that form during the development of neurodegenerative disease. In one embodiment, the combined biomarker comprises the sum of the level of two or more protein aggregates that form during the development of neurodegenerative disease. In one embodiment, the combined biomarker comprises: (i) the sum of the ratio of the level of α-synuclein aggregates to the level ofAmyloid-β aggregates, and the level of tau aggregates to the level of p-tau aggregates (i.e. (α-syn / Aβ) + (tau / p-tau)); (ii) the ratio of the level of p-tau aggregates to the level of tau aggregates(i.e. p-tau / tau);(iii) the ratio of the level of Amyloid-β aggregates to the sum of the level of Amyloid-β, α-synuclein and tau aggregates (i.e. Aβ aggregates / (Aβ + α-synuclein + tau aggregates)); (iv) the ratio of the sum of the level of Amyloid-β and p-tau aggregates to the levelof α-synuclein aggregates (i.e. (Aβ + p-tau aggregates) / α-syn aggregates); or(v) the ratio of the sum of the level of Amyloid-β and p-tau aggregates to the sumof the level of α-synuclein aggregates and the ratio of the level of p-tau aggregates to the levelof tau aggregates (i.e. (Aβ + p-tau aggregates) / (α-syn aggregates + (p-tau aggregates / tau aggregates))). In one embodiment, the combined biomarker is the ratio of the level of p-tau aggregates to thelevel of tau aggregates (i.e. p-tau / tau). The present inventors have surprisingly found that theproportion of phosphorylated tau aggregates increases in AD. DRI-C-P3835PCTThere are a number of small changes that occur in the aggregates described herein with thedevelopment of disease. The present inventors have found that combining several of thesesmall changes together in a combined biomarker indicates a bigger change with disease andprovides much higher diagnostic accuracy.According to one aspect of the invention, there is provided a combined biomarker for use inthe detection or prognosis of a neurodegenerative disorder, wherein the combined biomarkercomprises the sum of the proportion of two or more protein aggregates that form during thedevelopment of neurodegenerative disease.In one embodiment, the combined biomarker comprises the sum of the ratio of the level of α-synuclein aggregates to the level of Amyloid-β aggregates, and the level of tau aggregates to the level of p-tau aggregates (i.e. (α-syn / Aβ) + (tau / p-tau)).References herein to a "combined biomarker" or "composite biomarker" refer to a biomarkercomprising two or more discrete biomarkers. The combined biomarker may comprise a post-translationally modified protein or a truncated protein. Therefore, the combined biomarker maycomprise the same protein in two or more discrete formats, e.g. the protein in its natural state and post-translationally modified and / or truncated, or the protein with different post- translational modifications. The results presented herein show that the detection of ASC specks in patient samples is a useful marker of neuroinflammation that could help monitor disease progression, especiallywhen combined with measurement of protein aggregates associated with neurodegeneration,such as α-syn, Aβ and tau aggregates.According to a further aspect of the invention, there is provided a combined biomarker for usein the detection or prognosis of a neurodegenerative disorder, wherein the combinedbiomarker comprises two types of protein complexes present in a sample, wherein one of theprotein complexes is ASC speck.In one embodiment, the combined biomarker comprises two biomarkers, i.e. a level or scorerelated to ASC speck (e.g. number or morphology) and a second level or score related toanother type of protein complex (e.g. Aβ, tau or α-syn aggregates). DRI-C-P3835PCTReferences herein to "biomarker level" or "level" refer to a measurement that is made usingany analytical method for detecting the biomarker in a biological sample and that indicates thepresence, absence, absolute amount or concentration, relative amount (i.e. number) orconcentration, titer, a level, an expression level, a ratio of measured levels, or the like, of, for, or corresponding to the biomarker in the biological sample. The exact nature of the "level" depends on the specific design and components of the particular analytical method employed to detect the biomarker. The components of the combined biomarker can be elevated (i.e. they can be "higher") or they can be reduced (i.e. they can be "lower") with respect to a reference level. The term "reference level" as used herein refers to the level of one or more biomarkers disclosed herein, or a scorederived from the measurement of one or more biomarkers disclosed herein, obtained from areference / control group (e.g. healthy individuals, individuals associated with a particulargroup, such as a prognostic group, for example recurrence of the disease or non-response ofthe disease to a particular therapeutic agent or combination thereof).In one embodiment, the other type of protein complex is a protein aggregate that forms duringthe development of neurodegenerative disease, such as protein complexes selected fromAmyloid-β aggregates, tau aggregates, α-synuclein aggregates and TDP-43 aggregates.In one embodiment, the combined biomarker comprises the level of ASC speck and / or the level of one or more protein aggregates that form during the development of neurodegenerative disease.In one embodiment, the combined biomarker comprises the sum of the level of two or moreprotein aggregates that form during the development of neurodegenerative disease.In one embodiment, the combined biomarker is the sum of the level of ASC speck and thelevel of one or more protein aggregates that form during the development ofneurodegenerative disease.In one embodiment, the combined biomarker comprises a score for one or more morphologicalfeatures for the ASC speck and / or a score for one or more morphological features for theprotein aggregates that form during the development of neurodegenerative disease. DRI-C-P3835PCTIn a further embodiment, the one or more morphological features is selected from: the size ofthe ASC speck or the protein aggregate; or shape of the ASC speck or the protein aggregate. The shape and size of the aggregates can be detected as described hereinbefore.In one embodiment, the combined biomarker is determined as a ratio. In some embodiments,the combined biomarker is determined as the ratio of two or more biomarkers, e.g. where theratio is the level of ASC speck to the level of one or more protein aggregates that form duringthe development of neurodegenerative disease. This may be compared with a biomarkercontrol ratio reference value or control ratio reference value range, and biomarker ratio values greater than the value of the control ratio reference value are indicative of the condition (e.g. a neurodegenerative disorder).In one embodiment, the combined biomarker comprises:(i) the ratio of the level of ASC speck to the level of Amyloid-β aggregates;(ii) the ratio of the level of ASC speck to the level of p-tau aggregates;(iii) the ratio of the sum of the level of ASC speck and the level of p-tau aggregatesto the level of Amyloid-β aggregates; (iv) the ratio of the sum of the level of ASC speck and the level of α-synucleinaggregates to the level of Amyloid-β aggregates; (v) the ratio of the sum of the level of ASC speck and the score for one or moremorphological features for the ASC speck to the level of Amyloid-β aggregates. In one embodiment, the combined biomarker comprises the ratio of the sum of the level ofASC speck and the level of α-synuclein aggregates to the level of Amyloid-β aggregates foruse in the detection of Parkinson’s disease. In another embodiment, the combined biomarker comprises the ratio of the sum of the level of ASC speck and the score for one or moremorphological features for the ASC speck to the level of Amyloid-β aggregates for use in thedetection of Parkinson’s disease. In one embodiment, the combined biomarker comprises the ratio of the sum of the level ofASC speck and the level of p-tau aggregates to the level of Amyloid-β aggregates for use inthe detection of Alzheimer’s disease. In one embodiment, the combined biomarker comprises the ratio of the level of ASC speck to the level of p-tau aggregates for use in the differential diagnosis between Alzheimer’s disease dementia and frontotemporal dementia. DRI-C-P3835PCT According to a further aspect of the invention, there is provided the use of the combinedbiomarker defined herein as a biomarker for the manufacture of a diagnostic kit for diagnosingor detecting a neurodegenerative disorder. According to a further aspect of the invention, there is provided the use of the combinedbiomarker defined herein as a biomarker for the manufacture of a diagnostic kit for determiningthe prognosis of a subject with a neurodegenerative disorder. According to a further aspect of the invention, there is provided the use of the combinedbiomarker defined herein as a biomarker for the manufacture of a diagnostic kit for monitoringthe efficacy of a therapy in a subject having, suspected of having, or being predisposed to a neurodegenerative disorder. NEURODEGENERATIVE DISORDERS The neurodegenerative disorder is preferably characterised by protein aggregation. Protein aggregation is known to underlie a number of neurodegenerative diseases, includingParkinson's disease, Alzheimer's disease, Huntington's disease, dementia with Lewy bodies(DLB), pure autonomic failure (PAF), multiple system atrophy (MSA), progressivesupranuclear palsy (PSP), corticobasal syndrome (CBS), Hallervorden-Spatz disease,dementia such as frontotemporal dementia, frontal temporal dementia with Parkinsonismlinked to chromosome 17 (FTDP-17), tauopathies, Pick's disease, traumatic brain injury (TBI),corticobasal degeneration, transmissible spongiform encephalopathy, Amyotrophic lateral sclerosis and amyloidosis. In one embodiment, the neurodegenerative disorder is selected from Parkinson’s disease (PD) and other Parkinsonian disorders (such as MSA, PSP, CBS), Alzheimer’s disease (AD),frontotemporal dementia (FTD), tauopathies (such as PSP and Pick’s disease), and traumaticbrain injury.In one embodiment, the neurodegenerative disorder is a proteinopathy (i.e. a class of diseaseswhich are caused by structurally abnormal proteins). In one embodiment, theneurodegenerative disorder is preferably a synucleinopathy, most preferably Parkinson'sdisease. DRI-C-P3835PCT Parkinson's Disease (PD) is characterized by muscle rigidity, tremor, bradykinesia progressing to akinesia, and is caused by progressive loss of dopaminergic neurons in the substantia nigra. PD is primarily a disease of an aging population and with a rapidly increasing aging population,the burden of PD will reach even broader proportions in the near future. Neurodegenerativedisorders also include other Parkinsonian disorders. Atypical Parkinsonian disorders are progressive diseases that present with some of the signs and symptoms of Parkinson’s disease, but that generally do not respond well to drug treatment with levodopa. They are alsoassociated with abnormal protein build-up within brain cells. Disorders considered aParkinsonian disorder include dementia with Lewy bodies, PSP, MSA and CBS.In one embodiment, the Parkinson's disease is prodromal Parkinson’s disease or earlyParkinson's disease.Prodromal Parkinson’s disease refers to the stage at which individuals do not fulfil diagnosticcriteria for PD (i.e. bradykinesia and at least 1 other motor sign) but do exhibit signs andsymptoms that indicate a higher than average risk of developing motor symptoms and adiagnosis of PD in the future. A number of prodromal symptoms in patients with PD have beenidentified. The most common symptoms associated with prodromal-PD include hyposmia,constipation, mood disorders, and REM sleep behaviour disorder (RBD). In one embodiment, the neurodegenerative disorder is preferably a tauopathy, most preferablyAlzheimer's disease.In one embodiment, the Alzheimer’s disease is mild cognitive impairment (MCI) or early AD.There are several types of neurological disorders related to Alzheimer’s disease. As cognitivedysfunction appears gradually in dementia including Alzheimer’s disease, there is a diseasestatus of pre-stage of dementia. This stage is called as mild cognitive impairment (MCI). MCI is defined as a condition characterized by newly acquired cognitive decline to an extent that is beyond that expected for age or educational background, yet not causing significant functional impairment, and not showing disturbance in daily life. METHODS OF TREATMENT According to a further aspect, there is provided a method of treating a neurodegenerativedisorder in a subject, which comprises the following steps: DRI-C-P3835PCT (i) detecting or measuring the combined biomarker described herein in a bodyfluid sample obtained from the subject;(ii) using the measurement in step (i) as indicative of the presence of saidneurodegenerative disorder in the subject; and(iii) administering a treatment if the subject is determined to have saidneurodegenerative disorder in step (ii).According to a further aspect, there is provided a method of treating a neurodegenerativedisorder in a subject in need thereof, which comprises the step of administering a treatmentto a subject identified as having a differing level or score of the combined biomarker describedherein in a body fluid sample obtained from said subject, when compared to the level or scoreof the combined biomarker in a body fluid sample obtained from a control subject.Treatments may be selected by those skilled in the art depending on the neurodegenerative disorder. In one embodiment, the treatment is selected from medication, supportive therapy (e.g. physiotherapy or speech and language therapy) or surgery. Suitable PD treatments will be readily recognised by the skilled person, and include those in development or that are yet to be developed but which will treat or ameliorate symptoms of PD. Suitable treatments include those that improve outcome and / or symptoms for patients.For example, the treatment being administered may be levodopa (for example, co-beneldopaor co-careldopa), dopamine agonists (for example, pramipexole, ropinirole or rotigotine),monoamine oxidase-B (MAO-B) inhibitors (for example, rasagiline, selegiline or safinamide),catechol-o-methyltransferase (COMT) inhibitors (for example, entacapone or opicapone),amantadine or anticholinergics (for example, procyclidine or trihexyphenidyl). Specific formsof these treatments may be required if symptoms are severe, such as non-oral therapies (for example apomorphine or co-careldopa) or skin patches (for example a rotigotine skin patch). Suitable AD treatments will be readily recognised by the skilled person, and include those in development or that are yet to be developed but which will treat or ameliorate symptoms of AD. Suitable treatments include those that improve outcome and / or symptoms for patients. For example, the treatment being administered may be a cholinesterase inhibitor (e.g. galantamine, rivastigmine or donepezil) which improve cognitive function, an N-methyl-D- aspartate (NMDA) antagonist (e.g. memantine) which ameliorate symptoms of cognitive impairment, an orexin antagonist (e.g. suvorexant) used to treat insomnia, some DRI-C-P3835PCT antipsychotics (e.g. brexpiprazole), or may be an immunotherapy which targets amyloid β to reduce amyloid plaques (e.g. lecanemab or aducanumab). The methods may comprise: (i) measuring the level or score of the combined biomarker described herein in abody fluid (e.g., blood, serum or plasma) sample obtained from the subject, optionally usingthe method of analysing protein complexes as described herein;(ii) identifying the subject as suffering from a neurodegenerative disorder basedon a higher level or score of the combined biomarker compared to a control; and(iii) administering a treatment to the subject.It will be understood that all embodiments described herein may be applied to all aspects ofthe invention. Other features and advantages of the present invention will be apparent fromthe description provided herein. It should be understood, however, that the description andthe specific examples while indicating preferred embodiments of the invention are given byway of illustration only, since various changes and modifications will become apparent to those skilled in the art. The present invention will now be illustrated by the following examples. EXAMPLES Example 1: Single-molecular array analysis The aim of this work was to develop a sensitive assay for the detection of Aβ, α-syn, and pTau aggregates including common post-translational modifications, based on the SIMOA platform. Methods: Protein aggregates / tau lysate preparation: Recombinant α-syn aggregates. Wild type α-syn samples were expressed, purified in E. coli and stored at -80°C as previously described (Cremades et al. Cell 149, 1048–1059 (2012)) and kindly provided by the Centre for Misfolding Diseases (CMD) at the University of Cambridge. To remove pre-aggregation seeds, the solution was centrifuged at 91000 g at 4°C for 1 h by an ultracentrifuge (OptimaTLX Ultracentrifuge, Beckman). The concentration of the supernatant was then determined byA280 (ε 280 = 5960 M −1 cm −1). The supernatant was then diluted to 70 µM in 1x PBS supplemented with 0.01% NaN3 (Merck, Cat. No.71290) and incubated at 37°C with shaking DRI-C-P3835PCT at 200 rpm for 12 h or 48 h. The aggregates were aliquoted (20 µL) to avoid multiple freeze- thaw cycles. The aliquots were then snap-frozen and stored at -80°C.In vitro Aβ42 one-week sonicated aggregates.Lyophilised monomeric recombinant Aβ42 peptide (Stratech, Cat. No. A-1170-2-RPE-1.0mg) was dissolved in PBS (pH = 7.4) at 200 μM on ice. The solution was quickly aliquoted and snap-frozen. To prepare recombinant Aβ42 fibrils, an aliquot was thawed and diluted to 4 μM in 1x PBS supplemented with 0.01% NaN3 (Merck, Cat. No.71290) and incubated at 37 °C under quiescent conditions for one week. The Aβ42 fibril was then sonicated as described previously (Corbett et al. Acta Neuropathol 139, 503–526 (2020)) with modification. The one- week aggregated Aβ42 aliquot was immersion sonicated in an ice water bath with a 3-mm- titanium probe (Sonicator microprobe 4422, Qsonica) mounted on a tip sonicator (Ultrasonic processor Q125, QSonica) at 20 kHz with 40% of power for 24×5-s bursts with 15-s rests between bursts. Thereafter, the sonicated aggregate was centrifuged, aliquoted (50 μL) and snap-frozen. The aliquots were stored at -80 °C until use. Preparation of cell-derived tau. HEK293 cells expressing tau P301S-Venus under the CMV promoter (pcDNA3) were maintained in DMEM supplemented with 10% FCS, 100 U / ml penicillin, 100 µg / ml streptomycin and grown at 37 °C and 5% CO2. The cells were seeded with 50 nM heparin- assembled recombinant 6xHis-tau P301S assemblies in the presence of 1% Lipofectamine2000 and a single clone was isolated (R1E5) that stably propagates tau P301S- Venus aggregates. Cells were lysed in lysis buffer (1x PBS, 1% w / v Triton X-100, 1xcOmplete™, EDTA-free Protease Inhibitor Cocktail mix, 1x PhosSTOP™ phosphataseinhibitor mix) on ice for 30 min. The lysate was then centrifuged at 14,000 × g for 15 min at4 °C and the clarified lysate was aliquoted and stored at -20 °C. The total tau concentrationwas determined through ELISA, which is an upper limit for the amount of tau aggregates and used this sample as calibration standard. By measuring the HEK cell lysate using the tau silica bead calibrant using HT7 antibodies, which bind pan-tau, for capture and detection, we found that 0.1 ng / mL total tau monomer corresponds to 5.8 nM tau aggregates so that the conversion factor from 1 ng / mL to nM is 58. We ensured that the Venus tag does not interfere with the 488nm dye-labelled beads by testing 750nm dye-labelled beads and determined the total tau aggregate concentration in the cell lysate using tau silica bead calibrant (data not shown). DRI-C-P3835PCT Calibration sample preparationIt is important to have calibration samples that can be included in each run in order to reducerun-run to variation. We therefore made silica nanoparticles coupled with a-synuclein, beta- amyloid or tau as calibration samples as described below. α-synuclein SiNaP α-synuclein SiNaPs were prepared following the protocol described by Herrmann andcolleagues (Herrmann et al. Clin Chim Acta 466, 152–159 (2017)). To 500 µL of carboxylatedsilica nanoparticles (cSiNaP) (particle size with 15-nm diameter), 11.47 µM indimethylformamide (DMF) and 500 µL of 18.2-MΩ cm water was added. The mixture wasthen centrifuged (10,000 g, room temperature, 1 h) and the pellet was resuspended with 500 µL of MES buffer (2-(N-morpholino)ethanesulfonic acid) buffer (10 mM, pH 5.7). Meanwhile, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) and sulfo-N-hydroxysuccinimide (sulfo-NHS,) were freshly dissolved in cold MES buffer (10 mM, pH 5.7) at 52.16 mM (10 mg / mL) and 92.11 mM (20 mg / mL), respectively. The cSiNaP was then diluted to 100 nM in MES buffer. EDC and sulfo-NHS were then introduced into the diluted cSiNaP suspension such that the mixture contained 400 µM EDC and 100 µM sulfo-NHS. The reaction mixturewas sonicated for 30 min and then centrifuged (10,000 g, room temperature, 1 h). The pellet,i.e. activated SiNaP, was resuspended in fresh 10 mM MES buffer to give 200 nM suspension. Meanwhile, the monomeric α-synuclein solution (kindly provided by the Centre for Misfolding Diseases (CMD) at the University of Cambridge) was then diluted in 10 mM MES buffer to give 20 µM solution. To 1 mL of the activated cSiNaP suspension, 1 mL of diluted α-synuclein solution was introduced. The reaction mixture was placed on a revolver rotator for overnight incubation at room temperature. Finally, it was centrifuged (10,000 g, 4 °C, 1 h) and the pellet was redispersed in 1 mL of 1:1 H2O:DMSO (v / v). The suspension was sonicated for 10 min and then centrifuged (5,000 g, 4 °C, 1 h). The α-synuclein-conjugated SiNaP was then redispersed in 400 µL of 1:1 H2O:DMSO (v / v) to give a 500 nM (based on the SiNaP) suspension, and stored at -20 °C until use. Aβ42 SiNaP Aβ42 SiNaPs were prepared following the protocol described by Hülsemann and colleagues (Hülsemann et al. J Alzheimers Dis 54, 79–88 (2016)). The carboxylated silica nanoparticles (cSiNaP) were buffer-exchanged and activated by EDC and sulfo-NHS as described above. The reaction mixture was then centrifuged (10,000g, room temperature, 1 h) and the resulting pellet, i.e. activated SiNaP, was resuspended in fresh 10 mM MES buffer to give 200 nMsuspension. Meanwhile, lyophilised monomeric recombinant Aβ42 peptide (Stratech, Cat. No. DRI-C-P3835PCTA-1170-2-RPE-1.0mg) was dissolved in PBS (pH = 7.4) at 200 μM on ice. An aliquot of Aβ42peptide solution was then diluted in 10 mM MES buffer to give 20 µM solution. To 1 mL of the activated SiNaP suspension, 1 mL of diluted Aβ42 solution was introduced. The reaction mixture was placed on a revolver rotator for overnight incubation at room temperature. Finally, it was centrifuged (10,000 g, 4 °C, 1 hour) and the pellet was redispersed in 1 mL of 1:1 H2O:HFIP (1,1,1,3,3,3-Hexafluoro-2-propanol) (v / v). The suspension was sonicated for 10 min and then centrifuged (5,000 g, 4 °C, 1 hour). The Aβ42-conjugated SiNaP was then redispersed in 200 μL of 1:1 H2O:DMSO (v / v), and stored at -20 °C until use. Tau SiNaP To the 30-nm triethoxylpropylaminosilane silica nanoparticles (nSiNaP, Merck, Cat. No. 791334, 16.59 µM in water, 500 µL), 500 µL of DMF was introduced. The mixture was firstly centrifuged (10,000 g, room temperature, 1 hour) and resuspended with 500 µL of DMF. Meanwhile, the NHS-activated carbonylacrylic reagent was dissolved in DMF to give a 1 M stock solution. N,N-diisopropylethylamine (DIPEA) was diluted in DMF to give a 1 M stock solution. To 5.6 μL of 1 M DIPEA solution, 96.4 μL of the bead suspension was introduced, followed by the addition of 5.6 μL of 1 M carbonylacrylic linker solution. The reaction wasincubated overnight at 37 °C with shaking at 200 rpm in dark. The reaction mixture wascentrifuged (15,000 g, room temperature, 15 min) and the pellet was resuspended in 500 μL of DMF. The suspension was then centrifuged at (15,000 g, room temperature, 15 min) and the pellet was resuspended with 96.4 μL of water. Meanwhile, a 10x Tris buffer (500 mM Tris, pH 8.5) was prepared. Tris(2-carboxyethyl)phosphine hydrochloride (TCEP) was dissolved in water to give a concentration of 100 mM and the pH was adjusted to 7-8. To the pellet suspension, 60 µL of 10x Tris buffer and 3.2 μL of TCEP solution were added, followed by the addition of 0.5 mL of RP hTAU solution (32 µM in 100 mM Tris, 150 mM NaCl and 1 mM EGTA). The reaction was incubated overnight at 37 °C with shaking at 200 rpm. Next, the reaction mixture was centrifuged (15,000 g, room temperature, 15 min) and the pellet was resuspended in 500 μL of 1:1 H2O:DMSO solution (v / v). The mixture was then sonicated for 10 min and centrifuged (15,000 g, room temperature, 15 min). The pellet was resuspended in 160 μL of 1:1 H2O:DMSO solution (v / v) to give 10 µM, and stored at -20 °C until use. Synthesis of NHS-activated carbonylacrylic reagent All reagents and solvents were purchased from commercial suppliers and used as received.THF was purified as reported by Pangborn et al. (Organometallics 15, 1518–1520 (1996)),solvent was pre-dried over sodium wire and then distilled from calcium hydride and lithium aluminium hydride. Merck Silica gel 60 was used for the flash column chromatography. DRI-C-P3835PCT Monitoring of reactions was performed using TLC Silica gel 60 F254 plates. Compounds were detected using shortwave (254 nm) UV lamp or by staining with an indicated solution prepared by known procedures. NMR spectra were recorded on Bruker 400-Avance III HD, AvanceDPX-400, 400-QNP Cryoprobe (400.1 MHz for 1H) in DMSO-d6 (referenced to the residualsolvent signal). Chemical shifts are given in ppm (δ-scale), coupling constants (J) in Hz. 2,5-Dioxopyrrolidin-1-yl (E)-4-oxo-4-phenylbut-2-enoate (2) A solution of 3-benzoylacrylic acid (1) (1 g, 5.68 mmol) and N-hydroxysuccinimide (690 mg, 6.0 mmol) in anhydrous THF (25 ml) was cooled to 0°C and N,N' dicyclohexylcarbodiimide (1.24 g, 6 mmol) was added with stirring. The reaction mixture was stirred at 0°C for 1 h and then it was kept in a freezer (-20°C) overnight. The formed N,N-dicyclohexylurea was removed by filtration, washed with ether and solvents were removed under reduced pressure. The crudeproduct 2 (1.084 g, 4.0 mmol, 70%) was isolated as a yellow solid after recrystallization formisopropanol (40 ml). Rf 0.93 (10% MeOH / DCM, UV). 1H NMR (400.1 MHz, DMSO-d6) δ 8.29 (d, J = 15.7 Hz, 1H, H3), 8.10–8.07 (m, 2H, H2”), 7.76–7.72 (m, 1H, H4”), 7.62–7.53 (m, 2H, H3”), 7.03 (d, J = 15.7 Hz, 1H, H2), 2.88 (s, 4H,H2’). 1H NMR data are in accordance with the previous reports (Jakubec & Berkeš,Tetrahedron: Asymmetry 21, 2807–2815 (2010)). Single-molecule Pull-down (SiMPull) Single-molecule Pull-down (SiMPull) experiments were performed as previously described(Böken et al. Angew. Chem. Int. Ed. Engl., e202317756 (2024)). Briefly, functionalisedcoverslips were incubated with NeutrAvidin, washed, incubated with biotinylated capture antibody (α-syn: SC211, Aβ: 6E10, tau: HT7). After a further wash, the diluted silica- nanoparticle calibrators were incubated for 1h at RT or overnight at 4 °C. Subsequently, the wells were washed, blocked with BSA and labelled detection antibody (α-syn: SC211, Aβ: 6E10, tau: HT7) was added, followed by a further wash. Imaging was performed on a home- DRI-C-P3835PCT built total internal reflection fluorescence (TIRF) microscope. Super-resolution imaging was performed either using STORM (Aβ and tau calibrators) or DNA-PAINT (α-syn calibrators). Single-molecular array magnetic bead coupling We selected two tau antibodies: the phospho-tau specific antibody AT8 (p-Ser202, p-Thr205) and the total tau antibody HT7 for detection of tau aggregates.4B12 was used for detection of α-synuclein aggregates and 6E10 was used for detection of Amyloid beta (Aβ) aggregates. The use of the same capture antibody for detection and capture ensures that monomers give no signal and the signal comes from dimers or larger protein complexes. This was confirmed by performing denaturation experiments on synthetic aggregates. Antibody-bead conjugation was performed as per manufacturer’s instructions (Quanterix). Briefly, paramagnetic carboxylated beads were vortexed for 30 sec and left on a rotator to mix gently for at least 10 min. The beads were then washed three times with wash buffer followed two times with conjugation buffer. EDC (0.3 mg / mL) was used to activate the beads by placing the mixture in a rotator at 2-8°C for 30 min. The beads were once again washed with conjugation buffer. Buffer exchange of 100 µg of antibody was performed with a 50 kDa Amicon Ultra Spin Column device to change the storage buffer of the antibody to conjugationbuffer. The concentrated antibody was recovered to ∼ 100 µL volume and the antibodyconcentration was measured by A280. The antibody was diluted to 0.2 mg / mL in 300 µL of ice cold bead conjugation buffer and used to resuspend the washed beads. The mixture was placed on a rotator at 2-8°C for 120 min. The antibody-coated beads were then washed twicewith wash buffer and antibody coating efficiency was determined by measuring the residueantibody concentration in the solution and supernatant of the first wash. Bead blocking buffer was used to block the beads with 45 min incubation on a rotator. Finally, the beads were washed once with wash buffer followed by two washes with diluent buffer, and stored as a pellet at 4°C until use. Antibodies The following antibodies were used in this study: SC211 (Santa Cruz, Cat. No. SC767), 4B12 (BioLegend, Cat. No. 807-808), 6E10 (BioLegend, Cat. No. 803007), HT7 (ThermoFisher Scientific, Cat. No. MN1000), AT8 (ThermoFisher Scientific, MN1020). Single-molecular array plate preparation A total volume of 100 µL of each sample, diluted with Detector / Sample Diluent to desired concentration, were added to a SIMOA 96-Well Plate (Quanterix). These samples included DRI-C-P3835PCT bead calibration samples over a range of different concentrations. Approximately 500k antibody-conjugated beads were added to each well and incubated on a shaker at 30°C and 800 rpm for 30 min (or 60, 120 min). All washing steps were performed using the automated 3-step-assay program on the SIMOA Microplate Washer. The assay wells were washed three times with wash buffer. To each well, 100 µL of biotinylated detector antibody (0.3 / 0.5 / 1 µg / mL, in Detector / Sample Diluent) was added and incubated on a shaker at 30°C and 800 rpm for 10 min (or 30 min) followed by three washes with wash buffer. SβG (streptavidin β - galactosidase) was diluted to a concentration of 150 pM (or 50 pM, 300 pM) with SβG Dilution Buffer and 100 µL of the solution was added to the assay wells. The microplate was once again incubated on a shaker at 30°C and 800 rpm for 10 min followed by three washed with wash buffer. Two final washes were performed with wash buffer and 1 min incubation on a shaker. Finally, the buffer in the assay wells was completely removed and the beads were left to dry for 10 min. Single-molecular array processingThe following steps were automated by using a Quanterix SR-X™ Instrument. The beads wereresuspended using pre-warmed RGP (resorufin β-D-galactopyranoside) substrate. Thenthese beads suspensions were transferred to a sample well (the “flow cell”) on the SIMOADisc. A low-power vacuum pulls the bead suspension into the disc channel, allowing the bead suspension to flow over an array of more than 200 thousand microwells, each large enough to hold a single bead. Oil was used to remove the excess beads on the surface of the array and seal the loaded wells. Then the wells were imaged. The wells containing beads with at least one immunocomplex attached gave out fluorescence signals, while the plain beads didnot. The fraction of beaded wells with enzyme activity (fON ) was then reported by the machine.Single-molecular array data analysisThe readout of SIMOA assays is presented in terms of the fraction of beaded wells withenzyme activity (fON). This is subsequently used to calculate the average enzyme per bead (AEB). When the fraction of beaded wells with enzyme activity (fON) is lower than 0.7 (i.e. withless than 70% active beads), AEB is calculated in digital mode, assuming Poisson statisticsfor the number of captured molecules per “on” bead. In this case, AEB is determined by: As for the wells with fON greater than 0.7, uncertainty rapidly grows to unacceptable levels forthe Poisson distribution, the AEB is then switched to analog mode based on the intensity of asingle enzyme, and calculated by: DRI-C-P3835PCT WHERE: We note however that for these assays, aggregates are being detected which may be bound by more than one enzyme. This means that the analog mode for calculating AEB cannot be used, and we revert to using digital mode. We avoid any sample or calibrant concentrations where fON > 0.9. Furthermore, while we use the term AEB (average enzyme per bead) for the purpose of consistency, in our case more than one enzyme can be bound per aggregate. After obtaining the AEB values at each calibration level, a four parameter logistic (4PL) curve was fitted (concentration of calibrators as x and AEB as y, and blanks were not included when establishing the calibration curve). The data points are weighted by 1 over during the fitting process. (4PL equation) The preliminary limit of detection (LoD) for each assay was determined by the parameter A with a set multiplier (normally 1.3) and fitted back to the curve to get the LoD in units of concentration. The lower limit of quantification (LLoQ) was the lowest valid calibration level with coefficient of variation (%CV) less than 25%. Denaturation protocol Aβ42 early oligomers. Aβ42 early oligomers were diluted in PBS to 500 nM with different concentrations of guanidine hydrochloride (GdnHCl, 6 M, 4 M, 2 M, 1 M, 0.5 M, 0.25 M and 0 M) from an 8 M guanidine hydrochloride solution (pH 8.5, Merck, Cat. No. G7294). The mixture was then heated to 80°C for 10 min. It was then immediately diluted to 0.5 nM with Detector / Sample Diluent (Quanterix, Cat. No.101359). The diluted mixture was then immediately either loaded into a Simoa 96- Well Plate (Quanterix, Cat. No.101457) or stored on ice until use. α-syn early oligomers. Recombinant 12 h α-syn aggregates were diluted in PBS to 17.5 nM with different concentrations of guanidine hydrochloride (GdnHCl, 6 M, 4 M, 2 M, 1 M, 0.5 M, 0.25 M and 0 M) from an 8 M guanidine hydrochloride solution (pH 8.5, Merck, Cat. No. G7294). The mixture DRI-C-P3835PCT was then heated to 80°C for 10 min. It was then immediately diluted to 0.2 nM with Detector / Sample Diluent (Quanterix, Cat. No.101359) and kept on ice. Assay validation For the validation of each assay, four plates were run across two days using calibrator samples as well as independently prepared quality control samples across the calibration range. The quality control samples were analysed against the calibration curve, and the obtained concentrations were compared with the nominal value to obtain the accuracy as a percentage of the nominal value. The accuracy was determined within a single plate (within-run accuracy) as well as across different plates (between-run accuracy). Information on serum samples Patients with early Alzheimer’s disease includes the patients who sought medical advice at a memory clinic for the first time and were diagnosed for AD based on the positive AD CSF biomarker profile. AD CSF biomarker profile was defined by a CSF Aβ42 / p-tau181 ratio < 10.25 (as measured by Lumipulse G600II, Fujirebio). The study protocol was approved by the regional ethics committee at the University of Gothenburg. Results: Establishing SIMOA assays for the selective detection of protein aggregates We set out to develop SIMOA aggregate assays to detect protein aggregates relevant to neurodegenerative diseases, including native and C-terminal truncated α-synuclein (α-syn), beta-amyloid (Aβ), tau, and phosphorylated tau (p-tau). For the specific detection of theseaggregates – and not monomers – we used the same monoclonal antibody for both captureand detection. This configuration required the presence of two or more identical epitopes within a single aggregate; capturing the aggregate would occupy one binding site and require a second site for binding of the detection antibody, ensuring that the detected species are, at a minimum, dimeric. The assay development process consisted of antibody pair selection, assay condition optimisation (detector concentration and SBG concentration), optimisation to achieve lower coefficient of variation at all calibration levels including adjusting the dynamic range, assay validation, and diluent optimisation for specific sample matrices. To achieve accurate quantification and ensure normalisation between runs, we first developed suitable calibrators for these assays. This is a challenging task since the calibrator needs to have a known concentration and be reproducible. Since the aggregation process of monomers is stochastic and the produced aggregates have an unstable, unknown concentration, in vitro DRI-C-P3835PCTaggregates are not suitable calibrators. To have a reliable aggregate mimic, we coupled α-syn,Aβ42, or tau monomers to silica nanoparticles. We used single-molecule and super-resolutionmicroscopy to check if the calibrators aggregate (Figures 1A-C). These experiments showedno significant aggregates of the coated silica nanoparticles making them suitable calibrators for our purposes. Since it is not possible to get a sample of tau in which every single monomer is phosphorylated at S202 and T205 (AT8), the beads could not be used for (p-)tau. To solve this issue, we used cell lysate from HEK cells which stably propagate tau aggregates that arehighly phosphorylated (Böken et al. Angew. Chem. Int. Ed. Engl., e202317756 (2024)). Thisallowed us to use the same sample for measurement of total tau aggregates and tau aggregates phosphorylated at S202 and T205 (AT8-positive). We then proceeded to select the antibody pairs for each assay. For the development of the α-syn assays, we selected the 4B12-4B12 and sc12767-sc12767 (SC211) antibody pairsbased on their target specificity (truncated and total, respectively) and limits of detection. It isknown that significant truncation of α-syn occurs during the pathogenesis of PD, increasing aggregation. Importantly, this truncation can remove the epitope detected by the SC211 antibody, which is closer to the C-terminus. Use of the 4B12 antibody, which has an epitope closer to the centre of the α-syn molecule, allows us to detect truncated α-syn along with full length α-syn. By detecting both we can estimate the concentration of truncated α-syn aggregates. For the tau assay, we selected two antibodies that are commonly used in the field: the Ser202 and Thr205 phosphorylated tau-specific antibody AT8 and the total tau antibody HT7. For the Aβ assay, we used the 6E10 antibody, which has a binding region within residues 3-8 of Aβ36. All five antibodies selected (4B12, SC211, 6E10, HT7, AT8) are monoclonal and have a single epitope, and as such only bind to a single epitope on each monomer. We ensured that using these antibody pairs we were able to detect the respective silica- nanoparticle and lysate calibrators explained above, generating a concentration-dependent signal which can be used as calibration curves for each assay (Figure 2A-D). To ensure the accuracy of our protein aggregate quantification assays, we evaluated specificity from two key perspectives. Firstly, the assay must be specific to the analyte of interest. While this specificity largely depends on the antibodies used, it can also be influenced by other reagents involved in the assay. To test this, we assessed the cross-reactivity between Aβ, α-syn, and tau aggregates by measuring the recombinant aggregate samples using mismatched SIMOA assays. The results showed negligible cross-reactivity, confirming high analyte-specificity (Figure 3A). Secondly, the assay must specifically detect aggregates rather than monomer. To evaluate this, we performed denaturation experiments of the aggregates DRI-C-P3835PCT with increasing concentrations of guanidinium chloride (GdnHCl), and a short heat treatment (85 °C for 10 min). Following this treatment, 99% of the signal disappeared showing that the assays are aggregate specific (Figure 3B). To further enhance assay performance, we optimised the sample diluent, detector, and SBG concentration for each assay individually, evaluating performance based on the signal-to- background ratio at various calibration levels (data not shown). Initially, we identified the optimal sample diluent by testing a range of commercially available diluents (Quanterix Sample Diluents A-E), alongside the standard sample diluent and, specifically for the tau aggregate assays, the tau 2.0 sample diluent. The standard diluent is phosphate buffer with saline. The Quanterix sample diluents are: A, phosphate buffer with bovine serum components, a heterophilic blocker, and a surfactant; B, phosphate buffer with protein stabilisers (bovine), a heterophilic blocker, and a high surfactant concentration; C, phosphate buffer with low concentration of protein stabilisers (bovine), a heterophilic blocker, and a surfactant; D, phosphate buffer with newborn calf serum, a heterophilic blocker, and a surfactant; E, Tris buffer with high pH, bovine serum components, a heterophilic blocker, and a surfactant. The Tau 2.0 diluent contains BSA and Calf serum and an antimicrobial. For the detector and SBG enzyme concentrations, we explored various combinations of their concentrations together to account for potential combined effects, ensuring the optimal interplay between these components. Using these optimised assay conditions, we achieved the following limits of detection (LoDs): 4.2 pM for 4B12 assay, 0.63 pM for SC211, 0.92 pM for 6E10, 17 pM for HT7, 37 pM for AT8. The optimal assay conditions and respective LoDs are shown in Table 1.Table 1: Optimised conditions and limits of detection for aggregate assays. * indicates assayconditions for serum sample specific assays. Target α-syn α-syn Aβ tau p-tauAntibody pair 4B12-4B12SC211- SC2116E10-6E10 HT7-HT7 AT8-AT8Epitope AA103-108 AA121-125 AA3-8 AA159-163pS202 + pT205 Sample diluent Diluent C Diluent C Homebrew Tau 2.0 Tau 2.0[Detector] 1 µg / mL 0.5 µg / mL 0.3 µg / mL0.3 µg / mL 0.3 µg / mL (1.2 µg / mL)* (1.2 µg / mL)* [SBG] 50 pM 50 pM 150 pM150 pM 150 pM (50 pM)* (50 pM)* DRI-C-P3835PCT Sample 60 min, 30 min, 30 min, 30°C, 800 30 30 min, 30°C, 30 min, 30°C, incubation °C, 800 30°C, 800 rpm rpm rpm 800 rpm 800 rpm LoD 4.2 pM 0.625 pM 0.92 pM 17 pM 37 pMTo confirm the reproducibility of the assays, we validated their accuracy and precision across using four technical replicates across two days using calibrator samples as well as independently prepared quality control samples across the calibration range. All assays had a coefficient of variation (CV) below the accepted 20% threshold throughout the working range. The accuracy of all assays laid between 80%-120% for all calibration samples (Figure 3C) as well as for independently prepared quality control samples (n = 5 technical replicates on each plate) at multiple concentrations selected in the dynamic range of the respective assay. SIMOA aggregate assays detect soluble aggregates in the human brain Once the assays were optimised, we applied them to post-mortem human brain homogenate samples to demonstrate their capabilities to soluble protein aggregates in relevant biologically complex samples. Given the critical role of these aggregates in AD, post-mortem brain homogenate from AD and age-matched control samples was tested. We first ensured that these assays detect aggregates in a concentration-dependent manner in a linear range. For this purpose, brain homogenate from 5 AD and 5 control samples were combined and testedacross a wide range of dilutions (α-syn 1:4 to 1:256, Aβ 1:6.25 to 1:400, tau: 1:2000 to1:64000, data not shown). We confirmed the linear working range of the assays for brain homogenate by interpolating the protein aggregate concentration from the standard curves and calculating the final concentration of the aggregates depending on the dilution factor, observing only little variation across the dilution range. This positive correlation of the brainhomogenate concentration and the readout confirms the detection of aggregates in thissample type. We then proceeded to test brain homogenate from 5 AD (frontal cortex, BA6 / 8, Braak Stage VI) and 5 age-matched controls (frontal cortex, BA6 / 8, Braak Stage 0; Figure 4A). Using the calibrator samples to calculate the aggregate concentration, all samples were above zero, showing the detection of aggregates in these samples. Notably, we saw a significant increase in tau and p-tau aggregates with AD (Figure 4B-G). The mean concentration of α-syn aggregates detected by SC211 was 109 pM and 248 pM (SC211 assay, Welch’s t-test, p = 0.42) and 107 pM and 88 pM for aggregates detected by 4B12 (Welch’s t-test, p = 0.69), respectively in control and AD brains (Figure 4B and C), with no significant differences DRI-C-P3835PCTbetween control and disease. The Aβ concentration was 3060 pM in control brain and 1272pM in AD (Welch’s t-test, p = 0.14, Figure 4D). This difference may reflect that there is ahigher number of small Aβ aggregates in control brain and there is a small number of largeaggregates in AD brain. The total tau (HT7) and AT8-positive aggregate concentration were and 6446 pM and 6372 pM respectively in AD brains, compared to 328 pM and 218 pM incontrol brain (Welch’s t-test, HT7: p = 0.023, AT8: p = 0.018, Figure 4E and F). Thus, therewere significantly increased levels of aggregated tau in AD brain. Overall, these results show that the dominant protein aggregate present in AD brain is tau. The ratio of AT8 / HT7 aggregates was ~1 in AD and < 0.5 in controls, showing that the majority of aggregates detected in AD were phosphorylated at S202 and T205 (Welch’s t-test, p < 0.0001, Figure 4G).SIMOA aggregate assays detect aggregates in human serumWe confirmed the assays are compatible with readily available and clinically relevant samples, such as human serum. The high concentration of albumin, as well as other proteins and lipids,creates a complex matrix that may affect the diffusion and detection of the aggregates inserum. To address this, the detector and SBG concentration was optimised for serum samplesspecifically for Aβ, pTau, and α-syn aggregates. Similar to the brain homogenate, we verifiedthe detection of aggregates in a linear range by testing a range of concentrations, observing a positive correlation between serum concentration and signal (data not shown). After furtheroptimising the assays for human serum, we analysed serum samples taken from patients froma memory clinic in Gothenburg, Sweden, who diagnosed with early-stage AD based on a positive CSF biomarker profile (n = 20). Patients who were negative for this biomarker profilewere used as the control group (n = 20). The results are shown in Table 2.Table 2. Results of aggregate measurements on AD and control serum. Values shown in unit of pM in format of mean (S.D.). Assay All subjects AD Control P value (t-test)SC211 24.0 (69.1) 3.8 (5.87) 44.2 (94.4) 0.124B12 229.8 (804.3) 387.2 (1111.8) 72.5 (199.3) 0.226E10 18.1 (58.1) 35.3 (79.4) 0.9(3.1) 0.061HT7 48.0 (45.6) 61.0 (55.5) 35.0 (29.0) 0.071AT8 105.7 (202.6) 187.9 (263.1) 23.5 (28.6) 0.0081While α-syn aggregate levels did not differ between AD and control (Figure 5A,B), there wasa trend for higher Aβ (Figure 5C) and total tau (Figure 5D) in the CSF biomarker positive DRI-C-P3835PCT cases accompanied by significantly higher levels of AT8-positive tau aggregates (Figure 5C). Moreover, we observed tenfold higher levels of total (C terminally truncated + full length α- syn) aggregates than full length only aggregates, suggesting that most of the α-syn aggregates in these samples are C-terminally truncated. The ratio of AT8-positive tau aggregates to total tau aggregates was 3.1 and 0.67 for AD and control serum respectively (Figure 5F), suggesting higher phosphorylation of tau in early AD.We then explored combining these measurements into a combined biomarker for AD to see ifthis could improve the diagnostic accuracy, as was done for PD. All the potential biomarkers evaluated, along with their performance are tabulated in Table 3. The ratios were calculated with fitted concentrations in unit of pM. If the numerator was measured at a concentration below the LoD, the ratio was considered as 0. While on the other hand, when the denominator was below the LoD, the ratio was considered as infinity. We found that the combined biomarker (SC211 / 6E10) + (HT7 / AT8) (i.e. (α-syn / Aβ) + (tau / p-tau)) gave good discrimination with an area under the curve in the ROC curve of 0.91, where a higher value of biomarker represents lower likelihood of AD.We also found that Aβ aggregates / (Aβ + α-synuclein + tau aggregates) gave a ROC curvewith an AUC of 0.81. Other combined biomarkers tested included: (Aβ + p-tau aggregates) / α-syn aggregates gave a ROC curve with an AUC of 0.84, and (Aβ + p-tau aggregates) / (α- syn aggregates + (p-tau aggregates / tau aggregates)) gave a ROC curve with an AUC also of 0.84. Table 3: Table for all combined biomarkers tested. Biomarker Unweighted Weighted Gender specificbiomarker ROC-AUC Weighted biomarker α β γ ROC-AUC Female MaleSC211 / 6E10 + HT7 / AT8 0.913 SC211 / 6E10 + α*(HT7 / AT8) 1 0.913 0.988 0.883SC211 / 6E10 0.805 0.894 0.717(6E10+AT8) / SC211 0.780 (6E10+α*AT8) / SC211 6E10:AT8 = 4083:1 0.842 0.838 0.708AT8 / SC211 0.771 0.838 0.7136E10 / SC211 0.764 0.775 0.7256E10 / (6E10+SC211+HT7) 0.760 6E10 / (6E10+α*SC211+β*HT7) 4.5 0.1 0.815 0.713 0.775(6E10+AT8) / SC211 +0.758 (α*6E10+β*AT8) / SC211 + 1000 0.2 7 0.842 0.800 0.708AT8 / HT7 γ*(AT8 / HT7) 6E10 0.756 0.731 0.783AT8 0.750 0.650 0.863SC211 / (6E10+SC211+AT8) 0.743 0.756 0.708SC211 / (6E10+AT8) 0.743 0.756 0.708SC211 / 6E10 + AT8 / HT7 0.743 0.863 0.621SC211 / AT8 0.740 0.756 0.7086E10 / (6E10+4B12+HT7) 0.735 0.700 0.7426E10 / SC211 + AT8 / HT7 0.734 0.750 0.717(6E10+AT8) / SC211 +0.733 0.694 0.708HT7 / AT8 6E10 / (6E10+SC211+HT7)0.705 0.625 0.758+ AT8 / HT7 DRI-C-P3835PCT 6E10 / HT7 0.700 0.675 0.700HT7 / 6E10 0.700 0.675 0.700AT8 / (6E10+SC211+AT8) 0.699 0.825 0.6336E10 / (6E10+4B12+HT7) +0.695 0.625 0.742AT8 / HT7 6E10 / (6E10+SC211+AT8)0.694 0.625 0.754+ AT8 / HT7 SC211 / (6E10+SC211+HT7) 0.693 0.656 0.675(6E10+HT7) / SC211 0.693 0.656 0.675SC211 / (6E10+HT7) 0.693 0.656 0.675SC211 / 4B12 0.685 0.644 0.6756E10 / (6E10+SC211+AT8) 0.681 0.725 0.646HT7 / SC211 0.680 0.656 0.650SC211 / HT7 0.680 0.656 0.6506E10 / (6E10+4B12+AT8) +0.680 0.625 0.717AT8 / HT7 6E10 / (6E10+4B12+AT8) +0.675 0.625 0.721HT7 / AT8 4B12 / SC211 0.670 0.525 0.7636E10 / 4B12 0.670 0.675 0.625AT8 / HT7 0.670 0.625 0.713HT7 / AT8 0.670 0.625 0.713SC211 0.665 0.631 0.6676E10 / (6E10+4B12+HT7) +0.663 0.613 0.704HT7 / AT8 4B12 / 6E10 0.660 0.775 0.5086E10 / (6E10+SC211+AT8)0.658 0.625 0.688+ HT7 / AT8 HT7 0.653 0.475 0.6926E10 / (6E10+4B12+AT8) 0.650 0.675 0.4256E10 / (6E10+SC211+HT7)0.625 0.613 0.654+ HT7 / AT8 6E10 / AT8 0.624 0.650 0.571AT8 / (6E10+4B12+AT8) 0.600 0.725 0.504AT8 / 4B12 0.596 0.713 0.4966E10 / SC211 + HT7 / AT8 0.580 0.544 0.6334B12 / AT8 0.551 0.713 0.5924B12 0.530 0.600 0.6084B12 / HT7 0.520 0.638 0.542HT7 / 4B12 0.520 0.638 0.542AT8 / 6E10 0.421 0.438 0.571Example 2: Brain-derived tau aggregates on SIMOASIMOA experiments were conducted as described in Example 1, comparing the performanceof two further anti-tau antibodies, 8B9 (Figure 6A-C) and 5H3 (Figure 6D-F), in measuring tau aggregate levels. The 5H3 antibody showed higher overall signal levels compared to 8B9. However, the 8B9 antibody provided better discrimination between Alzheimer’s disease (AD)and non-AD samples (“non-AD” were patients who presented with some cognitive symptomsand include healthy patients and non-AD neurodegenerative patients). Additionally, higher levels of brain-derived tau aggregates were detected in plasma compared to serum.Figure 7 shows the detection of (A) brain-derived and (B) total tau aggregates in AD patientscompared to non-AD patients. When brain-derived tau aggregate levels were normalised tototal tau aggregate levels for each patient, it enhanced the assay’s diagnostic performanceachieving an area under the curve (AUC) of 0.8194 (Figures 7C-D). DRI-C-P3835PCTExample 3: ASC speck on SIMOASIMOA experiments were conducted as described in Example 1, and run to detect ASC.Antibodies used in the three assays were set up as follows: AL177-AL177 (sandwich ofpolyclonal antibodies); AL177-Caspase1 (inflammasome complex); and TMS1-TMS1 (sandwich of monoclonal antibodies). Different buffers (the same as used in Example 1) were tested for a pooled human serum sample to evaluate their effectiveness in enhancing the assay signal and signal-to-noise ratio(S / N) (data not shown).THP-1 cells were stimulated with Nigericin to induce inflammasome formation, and media samples were collected at various time points post-treatment. Different assay setups were utilised to measure ASC speck and inflammasome formation in the media, representing apositive control for the development of the assays (Figure 8).The assays were then tested on plasma and serum samples from AD patients (Figure 9) andParkinson’s disease (PD) patients (Figure 10). ASC speck detection in biofluids was able todistinguish between AD and non-AD patients, and between PD and healthy controls. Discussion: Immune system dysregulation and neuroinflammation are major pathophysiological drivers ofdisease progression in AD (Heneka, M. T. et al. (2015)) and PD (Jewell, S. et al. (2022)). Weintroduce a new assay that has potential as an ultrasensitive biomarker of inflammation in the blood of people with AD and PD. We have developed quantitative, highly sensitive, and selective Simoa-based assays for detecting aggregates of α-synuclein (α-syn), beta-amyloid (Aβ) and tau with detection limits in the low picomolar range. We confirmed the specificity for detecting aggregates only (and not monomers) and showed that the assays are not cross-reacting with other protein aggregates. Additionally, our assays can detect key post-translational modifications, including C-terminally truncated α-syn and AT8-phosphorylated tau aggregates. We performed extensive bioanalytical validation to show the reproducibility and stability of all our assays. These assays have been optimised for use in a wide range of complex biological samples, including human serum, post-mortem brain tissue, as well as model systems such as cerebral DRI-C-P3835PCT organoid conditioned media and mouse models. The high sensitivity of our assays is crucial, as small, soluble aggregate levels in these samples are typically very low and often fall below the detection limits of other techniques. This sensitivity allows for the reliable detection of aggregates even in challenging biological matrices. This versatility makes our assays a valuable tool for studying disease mechanisms across various biological contexts. By applying these assays to different sample types, the assays can be used to gain insights into theaggregation processes and post-translational modifications occurring in vivo and in vitro,enhancing our understanding of neurodegenerative disease progression. We demonstrated the capabilities of our assays to detect soluble aggregates in biological samples by applying them to human brain tissue. Post-mortem brain homogenate from AD samples was first tested at different dilutions providing concentration-dependent readouts. This was a proof of principle for detection of all the aggregates in this sample type and helpeddetermining the linear range. Then we compared the AD brain homogenates with age- andsex-matched control samples. The decision of measuring all the aggregates in the same sample was made to allow their direct comparison. These assays can detect α-syn, Aβ and tau aggregates in human post-mortem brain samples which will enable them to be used in future studies providing novel insights into the molecular mechanisms underlying neurodegenerative diseases. This approach of detecting small soluble aggregates with high sensitivity and specificity also holds potential for investigating the efficacy of therapeutic interventions aimed at reducing or modifying protein aggregates in various neurodegenerative conditions. We then explored the application of our assays to human serum which is an easily accessible (non-invasive) biofluid that can be used for the diagnosis of dementia and track its progression. Serum samples from individuals who individuals who visited a memory clinic for the first time and showed a positive CSF biomarker profile were compared to samples from patients whoalso visited the memory clinic but showed a negative CSF biomarker profile. The assays' highsensitivity allowed us to use less than 150 µL of sample in total to test for all the aggregates, making them suitable for samples with limited availability and enabling the application of multiple assays to each patient. Similar to human brain homogenate, we showed a concentration-dependent readout for all aggregates showing the assays’ capability of detecting α-syn, Aβ and tau aggregates in human serum samples. Overall, cases classifiedas AD by the CSF biomarker profile, had significantly higher levels of AT8-positive tauaggregates and a strong trend for higher total tau (CI95 = -2.62, 54.65) and Aβ (CI95 = -2.83, DRI-C-P3835PCT 71.54) aggregate levels. Once we added Aβ, HT7 and AT8 for each patient the difference was significant (CI95= 70.61, 378.97). In conclusion, we have developed a robust and sensitive method for detecting α-syn, Aβ and tau aggregates, including post-translationally modified forms, in human brain homogenate and serum. 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Claims

DRI-C-P3835PCT CLAIMS1. A method for determining whether a subject has, or is at risk of developing, aneurodegenerative disorder, the method comprising analysing two or more types of protein complexes in a body fluid sample obtained from the subject by performing a single-molecular array detection method to quantify the level of the protein complexes present in the sample, wherein the single-molecular array detection method comprises: (i) contacting the sample with a plurality of beads comprising a capturebinding agent which specifically binds to the protein complex, (ii) applying a detection binding agent to detect the presence of the proteincomplex bound by the capture binding agent, (iii) individually isolating the beads into separate isolations,(iv) detecting the presence of the detection binding agent in the separateisolations to determine the number of separate isolations containing a protein complex bound by the capture binding agent and quantify the level of protein complexes present in the sample, wherein the single-molecular array detection method is performed for each type of protein complex.

2. The method of claim 1, wherein the one or more protein complexes comprise a proteinaggregate that forms during the development of neurodegenerative disease and / or ASC speck.

3. The method of claim 1 or claim 2 , wherein the protein complexes are selected fromAmyloid-β aggregates, tau aggregates, α-synuclein aggregates and TDP-43 aggregates.

4. The method of any one of claims 1 to 3, wherein the protein complex comprises morethan one type of protein, for example a co-aggregate that forms during the development of neurodegenerative disease.

5. The method of claim 4, wherein a second detection binding agent is used to detectanother protein present in the protein complex.

6. The method of any one of claims 1 to 5, wherein the single-molecular array detectionmethod is used to measure two or more types of protein complexes to produce a combinedbiomarker.DRI-C-P3835PCT7. The method of claim 6, wherein the combined biomarker comprises a post-translationally modified protein or a truncated protein.

8. The method of any one of claims 1 to 7, wherein the single-molecular array detectionmethod is used to measure a total level of a protein complex and a level of the protein complexwhich has been post-translationally modified or truncated, to produce a combined biomarker.

9. The method of claim 8, wherein the combined biomarker is the ratio of the total levelof the protein complex to the level of protein complex which has been post-translationallymodified or truncated.

10. The method of any one of claims 6 to 9, wherein the combined biomarker comprisesthe sum of the level of two or more protein aggregates that form during the development of neurodegenerative disease.

11. The method of any one of claims 6 to 10, wherein the combined biomarker isdetermined as a ratio.

12. The method of any one of claims 6 to 11, wherein the combined biomarker comprises:(i) the sum of the ratio of the level of α-synuclein aggregates to the level ofAmyloid-β aggregates, and the level of tau aggregates to the level of p-tau aggregates (i.e. (α-syn / Aβ) + (tau / p-tau)); (ii) the ratio of the level of p-tau aggregates to the level of tau aggregates(i.e. p-tau / tau);(iii) the ratio of the level of Amyloid-β aggregates to the sum of the level of Amyloid-β, α-synuclein and tau aggregates (i.e. Aβ aggregates / (Aβ + α-synuclein + tau aggregates)); (iv) the ratio of the sum of the level of Amyloid-β and p-tau aggregates to the levelof α-synuclein aggregates (i.e. (Aβ + p-tau aggregates) / α-syn aggregates); or(v) the ratio of the sum of the level of Amyloid-β and p-tau aggregates to the sumof the level of α-synuclein aggregates and the ratio of the level of p-tau aggregates to the levelof tau aggregates (i.e. (Aβ + p-tau aggregates) / (α-syn aggregates + (p-tau aggregates / tau aggregates))).DRI-C-P3835PCT13. The method of any one of claims 1 to 12, wherein the neurodegenerative disorder isselected from: Parkinson’s disease (PD) and other parkinsonian disorders, Alzheimer’s disease (AD), frontotemporal dementia (FTD), tauopathies, traumatic brain injury.

14. The method of claim 13, wherein the PD is prodromal PD or early PD, or wherein theAD is mild cognitive impairment (MCI) or early AD.

15. The method of any one of claims 1 to 14, wherein the method comprises comparingthe information obtained for the protein complexes to one or more controls.

16. The method of claim 16, wherein the level of protein complex increases compared tothe control.

17. The method of claim 16, wherein the level of protein complex decreases compared tothe control.

18. The method of any one of claims 1 to 17, wherein the detection binding agent islabelled with a fluorescent marker, such as a fluorescent dye, in particular a fluorescent dye with photophysical properties.

19. The method of any one of claims 1 to 18, wherein the capture binding agent anddetection binding agent are antibodies.

20. The method of any one of claims 1 to 19, wherein the body fluid sample is selectedfrom blood, serum, plasma, cerebrospinal fluid or saliva.

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