FIELD OF THE INVENTION

The present invention relates to methods for predicting progression of cognitive deterioration relating to the areas of dementias, cognitive disorders and/or affective disorders and/or behavioural dysfunction, Alzheimer's Disease and related dementias in patients with amyloid deposition in the brain by determining a measure of magnetic susceptibility and/or transverse relaxation in brain tissue. The invention is also applicable to monitoring progression of cognitive deterioration and stratifying an individual into one or more classes depending on the diagnosis or prognosis of the cognitive deterioration.

BACKGROUND

The already extensive burden of Alzheimer's disease (AD) and neurodegenerative disorders to Australia is projected to increase due to an aging population demographic and no effective treatments. There is an emerging consensus that disease-modifying treatments should be delivered during the pre-clinical phase of the disease, such as when amyloid β (Αβ) pathology begins to accumulate. Early detection of cognitive deterioration is therefore necessary for effectively treating these conditions. There is currently no clinically acceptable prognostic biomarker for AD and the associated conditions leading to AD such as cognitive deterioration.

AD brain pathology starts developing approximately two decades prior to the onset of cognitive symptoms. Consequently, anti-AD therapies may have the best chance of success when given in this preclinical period. There is a need to identify biomarkers that predict cognitive deterioration early. Amyloid PET imaging is the most advanced biomarker of geriatric cognitive deterioration. High Αβ burden (Αβ+), identified by PiB, flutemetamol, or florbetapir radioligands, predicts cognitive decline with an average effect size (difference between slopes) of ~0.5 on memory composite scores in cognitively normal (CN) subjects over 3+ years. Αβ imaging is a sensitive predictor (98%) of cognitive decline but studies have shown repeatedly a large prevalence (~20-30%) of cognitive unimpaired people over age 60 with already high Αβ burden in the brain. It is now clear that other factors are necessary to predict and monitor cognitive decline toward Alzheimer's dementia since Αβ alone cannot monitor the rate of decline.

Post-mortem studies have shown that tau deposition correlates more strongly than Αβ burden with cognitive impairment. Attempts have been made to diagnose or differentially diagnose AD by measuring the level of a target such as tau and Αβ in the patient whose level specifically increases or decreases in the cerebrospinal fluid ("CSF") of a dementia patient. Αβ and tau form the brain amyloid and tangle proteopathies of AD and have been the subjects of extensive biomarker research. The accumulation of cortical amyloid and hippocampal tau are pathognomonic of AD, but can also be substantial in people regarded as clinically normal. Post-mortem studies find brain tau accumulation in normal ageing, and while elevated CSF tau is one of the best available prognostic biomarkers, it is not yet clinically useful.

It is now understood that, on its own, the prognostic and diagnostic value of Αβ is limited, whether this is measured in biofluids or via Positron Emission Tomography (PET) imaging. Other parameters will be required along with Αβ to predict cognitive deterioration. The combination with other parameters is limitless. There are many biomarkers that associate with cognitive deterioration.

In light of the above, there is a need for an improved method of identifying those with a propensity for cognitive deterioration leading to neurological disorders such as AD or those displaying cognitive decline, particularly at the onset of the disease, which may assist in delaying disease progression. The ability to detect preclinical or early stage disease through reliable measurement of markers present in biological samples from a subject suspected of having AD would also allow treatment and management of the disease to begin earlier. The same tests can be used to monitor the progression of decline or the possible rate of decline without the need for expensive equipment, discomfort and side effects experienced in the present available methods of diagnosis and prognosis. A test which can provide assistance to clinicians in reaching an early stage prognosis prior to the portrayal of detectable clinical indicators and which would obviate the need for actual confirmatory brain imaging tests would be useful. With disease modifying therapies for neurological disorders undergoing clinical trials, there is a social and economic imperative to identify biomarkers and parameters that can detect features of the disease in at-risk individuals in the earliest possible stage, so therapies can be administered at a time when the disease burden is mild and it may prevent or delay functional and irreversible cognitive loss.

Accordingly, there is a desire to provide a simple and effective measure of cognitive deterioration in patients that can be used to diagnose, prognose, stratify or monitor a patient with a cognitive deterioration and that correlates with the cognitive deterioration in the patient. This early detection may assist in delaying the onset of cognitive deterioration if treated early and appropriately or to monitor progression of a patient undergoing drug therapy for cognitive deterioration.

SUMMARY OF THE INVENTION

Measuring cognitive deterioration before the onset of AD may enable early treatment with drugs that would delay disease progression.

Accordingly, in an aspect of the present invention there is provided a method for predicting or diagnosing cognitive deterioration in a patient with amyloid deposition in the brain, said method comprising determining a measure of magnetic susceptibility and/or transverse relaxation in brain tissue for the patient wherein the measure of magnetic susceptibility and/or transverse relaxation is an indication of cognitive deterioration.

The measure of magnetic susceptibility and/or transverse relaxation can be performed using any method which can measure magnetic properties of tissues. These may include QSM, T2 ^* T2, or NMR frequency. Preferably, the method used to measure magnetic susceptibility is QSM. Preferably, the method to measure transverse relaxation is T2 ^* Applicants have demonstrated a QSM value as an alternative/adjunct prognostic for cognitive deterioration. They show that the QSM value in patients with amyloid deposition in the brain can predict the trajectory and rate of cognitive decline in these patients. However, as QSM is a measure of magnetic susceptibility, any method available to the skilled addressee for measuring magnetic susceptibility may be used. Similarly, methods such as T2 ^* which measure the transverse relaxation speed of molecules may be used since molecules such as iron which may be present in tissues will also affect the transverse relaxation of tissue. Furthermore, relaxation maps of tissue, such as those obtained from T2 ^* T2, T1 , or T2' maps may also provide an indication of the presence of molecules such as iron in tissues of patients with amyloid deposition thereby enabling a prediction of cognitive deterioration.

The changes in magnetic susceptibility preferably the QSM values can additionally be used in assessing for any changes in cognitive deterioration of a patient. Accordingly, in the monitoring of the magnetic susceptibility or preferably QSM values, it is possible to monitor for the presence of cognitive deterioration over a period of time, or to track cognitive deterioration progression in a patient.

In another embodiment, there is provided a method for monitoring progression of cognitive deterioration in a patient with amyloid deposition in the brain, said method comprising determining a first measure of magnetic susceptibility and/or transverse relaxation from in in the patient at a first time point;

determining a second measure of magnetic susceptibility and/or transverse relaxation from the same patient at a second time point;

optionally comparing the measure of magnetic susceptibility and/or transverse relaxation from the first and second time points to a reference level;

determining a difference in the measure of magnetic susceptibility and/or transverse relaxation at each of the first and second time points;

deducing progression of cognitive deterioration from the difference in the measure of magnetic susceptibility and/or transverse relaxation from the first and second time points. The changes in the level of magnetic susceptibility or preferably QSM values and/or transverse relaxation in a patient with amyloid deposition in the brain can also be used to stratify a patient (i.e., sorting a patient with cognitive deterioration into different classes of the condition).

In another embodiment there is provided a method for stratifying a patient with amyloid deposition in the brain for cognitive deterioration, said method comprising determining a measure of magnetic susceptibility and/or transverse relaxation for the patient;

comparing the measure of magnetic susceptibility and/or transverse relaxation with a reference value previously defined as characteristic for patients diagnosed with a level of cognitive deterioration; and

sorting the patient into a class of cognitive deterioration based on the measure of magnetic susceptibility and/or transverse relaxation for the patient relative to the reference value.

BRIEF DESCRIPTION OF THE FIGURES

Figure 1 shows the Relationship between QSM and longitudinal cognitive outcomes in Αβ+ subjects. Visual representation of the effect of baseline QSM on longitudinal composites of cognitive performance. For display purposes, Αβ+ subjects were designated to a low or high QSM group, based on the QSM value (0.0064 ppb) that optimally separated HC from diseased participants. DETAILED DESCRIPTION OF THE INVENTION

Predicting a rate of cognitive deterioration before the onset of AD may enable early treatment intervention to delay disease progression. Anti-AD therapies given in the pre-clinical period will have the best chance of success. In some cases dementia or AD may not fully develop, but the patient displays symptoms of Mild Cognitive Impairment (MCI) or are cognitively normal elders who may eventually experience cognitive deterioration. Monitoring progression and predicting or diagnosing a trajectory of cognitive deterioration will be imperative for managing the cognitive deterioration over time. Accordingly, in an aspect of the present invention there is provided a method for predicting or diagnosing cognitive deterioration in a patient with amyloid deposition in the brain, said method comprising determining a measure of magnetic susceptibility and/or transverse relaxation in brain tissue for the patient wherein the measure of magnetic susceptibility and/or transverse relaxation is an indication of cognitive deterioration.

Αβ or amyloid alone or any measure of magnetic susceptibility or transverse relaxation alone has been shown to be insufficient as a marker for cognitive deterioration since there exist a large number of cognitively unimpaired people with high Αβ levels in the brain. Approximately 30% of Αβ carrying subjects do not have objective cognitive impairment, suggesting that amyloid is not sufficient to precipitate dementia, however amyloid acts in concert with other pathogenic factors to drive disease progression. The present invention demonstrates that measures of magnetic susceptibility such as QSM and/or transverse relaxation may also predict the trajectory of cognitive decline in Αβ carrying subjects depending on a measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation determined. These findings highlight the potential for a measure of magnetic susceptibility or preferably QSM and/or transverse relaxation to be used in combination with PET imaging for AD-prognostics. Repeated measures of magnetic susceptibility or preferably QSM-MRI scanning of Αβ carrying patients and/or measurements of transverse relaxation in these patients in the preclinical phase is likely to be cheaper and more powerful assay to predict near-term cognitive changes. For the purpose of brevity, some of the description contained herein will be made in the context of QSM as the preferred method of measuring magnetic susceptibility. It is considered however that the skilled addressee would be capable of understanding that the present invention may also include other ways of measuring magnetic susceptibility and/or transverse relaxation which is one measure of the magnetic properties of a material that may be contributed by iron present in the tissues. Other forms of measure including T2, T2 ^* or pattern of NMR frequencies can also be used.

Magnetic susceptibility is a measure of the magnetic properties of a material including tissue. The susceptibility indicates whether a material is attracted into or repelled out of a magnetic field. It can also be a measure the degree of magnetization of a material in response to an applied magnetic field. Hence, it often reflects iron levels in tissue where iron is the most abundant magnetic material in the tissue. Measuring magnetic susceptibility can be conducted by several methods available to the skilled addressee aiming to measure the magnetic properties of tissue. Methods such as QSM and MRI are the most common methods used. Preferably, QSM is used as it is a superior method for measuring magnetic susceptibility. Transverse relaxation (T2 or T2 ^* ) is a measure of the relaxation speed for a molecule from an excited state. The presence of other molecules such as iron will change T2 and T2 ^*

However, both measures such as QSM and T2/T2 ^* are a surrogate measure of the presence of iron in the brain.

The present invention relates to assessing, predicting or diagnosing cognitive deterioration as measured by magnetic susceptibility or preferably QSM and/or transverse relaxation as an indicator of the rate of decline in cognitive capacity. When a patient's cognitive capacity declines changes occur which give rise to a variety of symptoms associated with aging, such as forgetfulness, decreased ability to maintain focus, and decreased problem solving capability. Symptoms oftentimes progress into more serious conditions, such as dementia and depression, or even Alzheimer's disease.

As used herein, reference to cognitive deterioration includes mild cognitive impairment (MCI), MCI conversion to Alzheimer's Disease (AD), and AD. However, the invention also relates broadly to the areas of dementias, cognitive disorders and/or affective disorders and/or behavioural dysfunction, Alzheimer's Disease and related dementias associated with a decline in cognitive function. The term "cognitive deterioration" may be used interchangeably with "cognitive decline".

Mild cognitive impairment (MCI) is an intermediate stage between the expected cognitive decline of normal aging and the more serious decline of dementia. It can involve problems with memory, language, thinking and judgment that are greater than normal age-related changes. Mild cognitive impairment causes cognitive changes that are serious enough to be noticed by the individuals experiencing them or to other people, but the changes are not severe enough to interfere with daily life or independent function. However, underlying what appears to be MCI, there may be a growing incidence of cognitive deterioration that does not manifest until it is too late. Early detection allows for intervention therapies.

Currently, the clinical diagnosis in the areas of dementias, cognitive disorders and/or affective disorders and/or behavioural dysfunction, Alzheimer's Disease and related dementias generally requires an evaluation of medical history and physical examination to determine the extent of cognitive function including neurological, neuropsychological and psychiatric assessment including memory and/or psychological tests, assessment of language impairment and/or other focal cognitive deficits (such as apraxia, acalculia and left-right disorientation), assessment of impaired judgment and general problem-solving difficulties, assessment of personality changes ranging from progressive passivity to marked agitation, as well as various biological, radiological and electrophysiological tests, such as for instance measuring brain volume or activity measurements derived from neuroimaging modalities such as magnetic resonance imaging (MRI) or positron emission tomography (PET) of relevant brain regions.

In one embodiment the cognitive deterioration is determined by Pre-clinical Alzheimer's Cognitive Composite (PACC: MMSE, LMII, Digit Symbol &CVLT-II LDFR), Global Cognition (C10pt: LMII, CVLTFP, Clock), Disease Progression (C2CR: CDRsb and MMSE), or Verbal Episodic Memory (C3VerEM: LMII, CVLTFP, CLVTLDFR).

A risk of cognitive deterioration may be assessed relative to a cognitively normal (CN) patient which will provide a reference level. Patients who are at risk of cognitive deterioration and/or Alzheimer's Disease include those with family histories, genetic vulnerability and deficiency alleles. They may be vulnerable and carry genes which predispose them to a more rapid cognitive deterioration leading to dementia and AD. Being able to determine an onset of rapid decline will enable better management of the cognitive deterioration.

The term "cognitively normal (CN) patient" as used herein means a subject which has no significant cognitive impairment or impaired activities of daily living. Patients that are suspected of, or are at risk of cognitive deterioration may be compared against a CN patient. This includes patients that are cognitively normal but show changed levels of a marker indicative of a neurological disease such as amyloid loading in the brain (preferably determined by PET imaging). The characteristics of a CN patient may assist in providing a reference level or reference value to which deterioration from normal can be determined.

Applicants have demonstrated that a measure of magnetic susceptibility or preferably QSM in patients with amyloid deposition in the brain predicts a propensity for cognitive deterioration and a trajectory of cognitive deterioration in these patients which enables a simple assessment of the risk for cognitive deterioration. This was shown in their observation study of 106 participants who were cognitively appraised over a 6-year period. The study supported that elevated QSM predicted deteriorating cognitive performance in participants with a high amyloid load, whereas low QSM was associated with stable cognitive performance.

This effect may also be shown using transverse relaxation (T2/T2 ^* ). Each method provides an indication of the presence of molecules such as iron that may be present in the tissues.

Accordingly, these data support (1 ) the utility of a measure of magnetic susceptibility or preferably QSM and/or transverse relaxation as a prognostic test for cognitive impairment in AD, and (2) a possibility of therapeutically lowering brain iron levels to delay disease progression.

QSM provides a contrast mechanism in Magnetic Resonance Imaging (MRI) derived from phase processing of gradient echo acquisition, and is a relatively new MRI technique that has been validated with post mortem studies. It has been used for a number of applications including differentiating calcification from iron, standardized quantitative stratification of cerebral microbleeds, gadolinium quantification in contrast enhanced MRI, and direct monitoring of targeted theranostic drug biodistribution in nanomedicine. A QSM value may be obtained for patients and individuals that can be used to determine whether there is a change in cognitive deterioration or trajectory of cognitive deterioration. These values may be compared against a reference level such as from a cognitively normal individual or an internal sample taken the same individual. Alternatively, the QSM reference values can derive from diseased participants and heathy controls (HC).

Like any measure of magnetic susceptibility, QSM values may be stratified into categories such as, but not limited to high or low QSM values. A positive magnetic susceptibility or high QSM value may be indicative of a high iron loading in the neocortex. Conversely a negative magnetic susceptibility or low QSM value may indicate a low iron loading in the neocortex. Consequently, high or elevated QSM values or positive magnetic susceptibility values will indicate a trajectory for deteriorating cognitive performance in participants with an amyloid load, whereas low QSM or negative magnetic susceptibility may be associated with stable cognitive performance in patients with amyloid loading.

Hence the magnetic susceptibility or preferably QSM values can assist in assessing cognitive deterioration or a trajectory for cognitive deterioration since a stratified magnetic susceptibility or preferably QSM will allow for a prediction of the severity of deteriorating cognitive performance in participants with amyloid load. Preferably severe deterioration may be indicated by high QSM values and manageable deterioration or stable deterioration may be indicated by low QSM values.

The magnetic susceptibility or preferably QSM values will also enable a diagnosis of the cognitive deterioration in patients with amyloid loading as being deteriorating or stable cognitive performance. Similarly, changes in transverse relaxation or T2/T2 ^* may indicate changes excitability of molecules in the tissues of the brain caused by the presence of other molecules such as but not limited to iron content of the brain The terms "determining," "measuring," "evaluating," "assessing," and "assaying," as used herein, generally refer to any form of measurement. These terms include both quantitative and/or qualitative determinations, which require sample processing and transformation steps of the biological sample. Assessing may be relative or absolute. In one embodiment the measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation is an indication of a rate of cognitive deterioration.

The term "diagnosis" or "diagnosing" as used herein would be understood by one skilled in the art to refer to the process of attempting to determine or identify a possible disease or disorder, and to the opinion reached by this process.

The term "predicts" or "predicting" as used herein would be understood by one skilled in the art to refer to the process of anticipating, envisioning or foreseeing an outcome based on results obtained.

As used herein, a "reference value" or "reference level" may be used interchangeably and may be selected from the group comprising an absolute value; a relative value; a value that has an upper and/or lower limit; a range of values; an average value; a median value, a mean value, a shrunken centroid value, or a value as compared to a particular control or baseline value. Preferably it is a predetermined reference value obtained from a known sample prepared in parallel with the biological or test sample in question. It is to be understood that other statistical variables may be used in determining the reference value. A reference value can be based on an individual sample value, such as for example, a value obtained from a sample from the individual with cognitive deterioration, but at an earlier point in time, or a value obtained from a sample from a patient or another patient with the disorder other than the individual being tested, or a "normal" or "healthy" individual, that is an individual not diagnosed with cognitive deterioration otherwise a CN individual. The reference value can be based on a large number of reference samples, such as from AD patients or patients with cognitive deterioration, normal individuals or based on a pool of samples including or excluding the sample to be tested.

For diagnostic and prognostic methods, the "reference level" or "reference value" is typically a predetermined reference level, such as an average of levels obtained from a population that is or isn't afflicted with cognitive deterioration. In some instances, the predetermined reference level is derived from (e.g., is the mean or median of) levels obtained from an age-matched population. In some examples disclosed herein, the age-matched population comprises individuals with cognitive deterioration or neurodegenerative disease individuals.

For methods predicting or diagnosing cognitive deterioration or predicting or diagnosing a trajectory of cognitive deterioration, a reference level may also be considered as generally a predetermined level considered "normal" for the particular diagnosis (e.g., an average level for age-matched individuals not diagnosed with cognitive deterioration or an average level for age-matched individuals diagnosed with cognitive deterioration other than AD and/or healthy age-matched individuals), although reference levels which are determined contemporaneously (e.g., a reference value that is derived from a pool of samples including the sample being tested) are also contemplated.

A reference level may also be a measure of a constant internal control to standardize the measurements to decrease the variability between the tests. For example, the middle frontal white matter region of the brain may be used as a reference region for normalizing QSM regional values. All values would then be relative to the mean susceptibility value of this reference region.

Patients who can be tested and/or treated according to any of the methods of the present invention include those who present with cognitive dysfunction with a history of treated depression, cognitive dysfunction with a history of depression, cognitive dysfunction with bipolar disease or schizoaffective disorders, cognitive dysfunction with generalized anxiety disorder, cognitive dysfunction with attention deficit, ADHD disorder or both attention deficit and ADHD disorder, dyslexia, developmental delay, school adjustment reaction, Alzheimer's Disease, amnesic mild cognitive impairment, non-amnesic mild cognitive impairment, cognitive impairment with white matter disease on neuroimaging or by clinical examination, frontotemporal dementia, cognitive disorders in those under 65 years of age, those with serum homocysteine levels of less than 10 nmol/l, and those with high serum transferrin levels (uppermost population quartile). Importantly, the patient must present with amyloid deposition in the brain.

As used herein, the terms "individual," "subject," and "patient," generally refer to a human subject, unless indicated otherwise, e.g., in the context of a non-human mammal useful in an in vivo model (e.g., for testing drug toxicity), which generally refers to murines, simians, canines, felines, ungulates and the like (e.g., mice, rats, other rodents, rabbits, dogs, cats, swine, cattle, sheep, horses, primates, etc.).

A patient can also be confirmed as being positive for amyloid using imaging techniques including, PET and MRI, or with the assistance of diagnostic tools such as PiB when used with PET (otherwise referred to as PiB-PET). Preferably, the patient positive for amyloid is PiB positive. More preferably, the patient has a standard uptake value ratio (SUVR) which corresponds with high neocortical amyloid load (PiB positive). For instance, current practice regards a SUVR can reflect 1.5 as a high level in the brain and below 1 .5 may reflect low levels of neocortical amyloid load in the brain. A skilled person would be able to determine what is considered a high or low level of neocortical amyloid load. As would be appreciated by one of skill in the art, a patient can also be confirmed as being positive for a neurological disease by measuring amyloid beta and tau from the CSF.

Moreover, a positive diagnosis of cognitive deterioration in a patient can be validated or confirmed if warranted, such as determining the amyloid load or amyloid level or amyloid deposition to confirm the presence of high neocortical amyloid. The terms amyloid load or amyloid level, often used interchangeably, or presence of amyloid and amyloid fragments, refers to the concentration or level of cerebral amyloid beta (Αβ or amyloid-β) deposited in the brain, amyloid-beta peptide being the major constituent of (senile) plaques. The present invention relates to predicting cognitive decline in patients with amyloid deposition in the brain. The patients may already show signs of cognitive deterioration correlating with amyloid levels. Alternatively, the patients may have amyloid deposits and be cognitively unimpaired. For the latter group, the methods of the present invention are useful for predicting an outcome for cognitive deterioration. Depending on the measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation for these patients (being stratified as positive or negative magnetic susceptibility or high or low QSM and/or decrease transverse relaxation), the prognosis may be either deteriorating cognitive performance or stable cognitive performance or somewhere in between. In subjects characterised as negative for amyloid, neocortical QSM was not a predictive variable in mixed effects models of the same cognitive scales.

For determining amyloid in the brain the best validated of these amyloid-imaging agents is Pittsburgh Compound-B (PiB), which is an analogue of the amyloid-binding dye Thioflavin-T. PiB-Positron Emission Tomography (PiB-PET) studies in Alzheimer's disease have shown robust cortical binding of PiB with amyloid plaque. This provides an accurate detection marker, perhaps what could be considered the gold standard. Recently other compounds have been investigated based on the similar functionality of PiB to target amyloid beta, such as AV-45 (florpiramine F-18) (otherwise known as F-18 AV-45) produced by Avid Radiopharmaceuticals Pty Ltd (Philadelphia), Florbetaben, Florbetapir, Flutematamol and NAV4694.

There have been numerous studies that have correlated the PiB radio tracer signal or output with the level of amyloid-beta and this has led to the terminology of PiB positive and PiB negative. Typically the normalisation of the PiB output, or uptake of the tracer, occurs to allow inter- and intra-subject comparisons to be made. In clinical practice normalisation for the radioactive dose and the patient's mass or volume (otherwise known as the standard uptake value (SUV)) is performed. The normalisation also incorporates standardisation with the (usually) unaffected cerebellum to provide the standard uptake value ratio (SUVR). This has led to the determination of a threshold value to differentiate those with high neocortical load (PiB positive) from those with a low load (PiB negative). Preferably the amyloid deposition is determined using PET amyloid imaging. However, any method available to the skilled addressee may be used to determine amyloid deposition. Once detected, the patient may be stratified as being amyloid positive or amyloid negative or PiB positive or PiB negative. More preferably, the patient has a standard uptake value ratio (SUVR) which corresponds with high neocortical amyloid load (PiB positive). For instance, current practice regards a SUVR can reflect 1.5 as a high level in the brain and below 1 .5 may reflect low levels of neocortical amyloid load in the brain. A skilled person would be able to determine what is considered a high or low level of neocortical amyloid load.

More preferably, the patient with amyloid deposition is amyloid positive. Ideally, the patient has a SUVR of >1 .5 as measured using PET amyloid imaging in unit consistent with PiB. The 1.5 threshold can be adapted for other traces like AV-45 to provide the same Amyloid positivity classification.

In another embodiment the magnetic susceptibility or preferably QSM and/or transverse relaxation is determined from neocortex of the brain. Preferably, the magnetic susceptibility or preferably QSM and/or transverse relaxation is determined from multiple regions of the neocortex.

Hence, magnetic susceptibility or preferably QSM and/or transverse relaxation in the neocortex could be used to predict those amyloid positive subjects who are on the pathway toward disease progression, regardless of diagnosis.

In one embodiment, the QSM is determined from MRI data. MRI detects the levels of iron through variation in the magnetic susceptibility of the tissue and iron is the strongest biological contributor to this signal.

In another preferred embodiment the QSM and/or transverse relaxation is a measure of neocortical iron. Cortical iron accumulation is also a pathological feature of AD (reviewed in Ayton S, Lei P, Bush Al. The Journal of the American Society for Experimental NeuroTherapeutics. Oct 30 2014; 12(1 ): 109-120), and has the potential to propel neurodegeneration though oxidative damage, however the contribution of cortical iron to the development of clinical symptoms has yet to be established. It has recently been shown that elevated levels of CSF ferritin (reporting brain iron levels) predicted poorer cognition, and increased the risk of developing AD in a 7-year prospective study (Ayton S, Faux NG, Bush Al, Nature communications. 2015;6:6760; S A, Faux NG, Al B. JAMA neurology. 2016;Accepted Sept 9, 2016), which is consistent with a role for iron in contributing to disease progression. Over the last 20 years, Magnetic Resonance Imaging (MRI) has been used to measure brain iron content, revealing iron elevation in the ageing brain that is exaggerated in AD (Bartzokis G, Tishler TA. Cell Mol Biol (Noisy-le-grand). Jun 2000;46(4):821 -833; Bartzokis G, Sultzer D, Mintz J, et al. Biological psychiatry. Apr 1 1994;35(7):480-487; Schenck JF, Zimmerman EA, Li Z, et al. Topics in magnetic resonance imaging : TMRI. Feb 2006; 17(1 ):41 -50; van Rooden S, Doan NT, Versluis MJ, et al. Neurobiology of aging. Jan 2015;36(1 ):20-26; van Rooden S, Buijs M, van Vliet ME, et al. NMR in biomedicine. Dec 19 2014; van Rooden S, Versluis MJ, Liem MK, et al. The journal of the Alzheimer's Association. Jan 2014;10(1 ):e19-26)). In cross sectional studies, an inverse correlation exists between brain iron concentration and memory functions in individuals with subjective cognitive impaired (van Rooden S, Buijs M, van Vliet ME, et al. (2014)) and individuals with AD (van Rooden S, Versluis MJ, Liem MK, et al. (2014)), and recently it was shown that elevated iron in the basal ganglia predicted poorer cognitive outcomes (Daugherty AM, Haacke EM, Raz N. The Journal of neuroscience : the official journal of the Society for Neuroscience. Apr 29 2015;35(17):6731 -6743) and brain atrophy (Daugherty AM, Raz N. Neurolmage. Mar 2016; 128: 1 1 -20) in a longitudinal analysis of healthy older adults. There has not yet been a longitudinal study on the impact of iron measured by MRI in AD cohort studies, nor has there been a study that has investigated MRI-iron measures in combination with amyloid PET imaging.

Over the last 20 years, MRI has been used to measure neocortical iron content, revealing iron elevation in the ageing brain, which is exaggerated in AD. In cross sectional studies, an inverse correlation exists between neocortical iron concentration and memory functions in subjectively impaired individuals and individuals with AD, however there has not been a longitudinal study on the impact of iron measured by MRI as determined by QSM values in combination with amyloid PET imagery on cognitive deterioration outcomes. Applicants now show that that high QSM values correlate to deteriorating cognitive performance in patients with amyloid deposition.

In one preferred embodiment the QSM and/or transverse relaxation correlates to neocortical iron and may be an indicator of a level of neocortical iron. However, QSM and/or transverse relaxation does not measure iron directly. QSM measures the magnetic susceptibility of the tissue in which iron is the strongest biological contributor to this signal whereas transverse relaxation measures the speed at which the excited molecules relax. Therefore, these measures merely suggest or correlate to a level of iron in the tissue. Based on the finding that high neocortical iron content relative to a reference level as measured by QSM values, translates to increased cognitive deterioration, it is considered in the present invention that an increase in neocortical iron would translate to a difference between the patient and a reference level. This difference assists in predicting or diagnosing cognitive deterioration in patients with amyloid deposition in the brain.

In characterising the diagnostic capability of a measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation, one of skill in the art may calculate a diagnostic cut-off. This cut-off may be a value, level or range. The diagnostic cut-off should provide a value level or range that assists in the process of attempting to determine or identify cognitive deterioration or rate of cognitive deterioration.

In a preferred embodiment the amyloid positive subjects may be stratified into high and low QSM, based on a QSM value (0.0064 ppb) that optimally separates HC from diseased participants. Hence, a nominal cut-off value for the QSM may be determined from relative values obtained from HC or from other diseased individuals. Alternatively, a QSM value from an individual with low iron and/or showing no cognitive deterioration or being cognitively unimpaired may be used to define the cutoff points for QSM.

For example, the level of a measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation may be diagnostic for cognitive deterioration if the value is above the diagnostic cut-off. Alternatively, as would be appreciated by one of skill in the art, the measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation may be diagnostic for cognitive deterioration if the level is below the diagnostic cut-off.

The diagnostic cut-off for measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation can be derived using a number of statistical analysis software programs known to those skilled in the art. The statistical work may be conducted with R (version 3-2-4)22, using packages ggplot223, nlme24, lmerTest25. The conditions necessary to apply the regression models, normal distribution of the residuals, and the absence of multicollinearity may be determined as by the skilled addressee. Minimal models may be obtained via step down regression using Bayesian information criterion (BIC), ensuring that the central hypotheses are maintained. All hypothesis tests may be 2-sided, and significant differences may be inferred when p<0.05.

It would be contemplated that the use of measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation in the methods of the present invention could also be used in combination with other methods of clinical assessment of a neurological disease known in the art in providing a prognostic evaluation of the presence of a neurological disease.

It would be understood by one skilled in the art that clinical determinations for the presence of cognitive deterioration in combination with the assessment of the levels of measure of magnetic susceptibility or preferably QSM values and/or transverse relaxation (in conjunction with information regarding APOE genotype, CSF tau, Αβ and ApoE levels) would be considered to relate to assessments that include, but are not necessarily limited to, memory and/or psychological tests, assessment of language impairment and/or other focal cognitive deficits (such as apraxia, acalculia and left-right disorientation), assessment of impaired judgment and general problem- solving difficulties, assessment of personality changes ranging from progressive passivity to marked agitation. It would be contemplated that the methods of the present invention could also be used in combination with other methods of clinical assessment of a neurological disease known in the art in providing a prognostic evaluation of the presence of a neurological disease.

A difference in a measure of magnetic susceptibility or preferably QSM value and/or transverse relaxation between the patient and the reference level would indicate a change in cognitive deterioration. The degree of change can provide an indication of whether there is increase or decrease risk for cognitive deterioration or the severity of the cognitive deterioration. A small elevation may indicate a small risk whereas a high elevation is likely to indicate greater cognitive deterioration. An increasing elevation between the patient and the reference level will indicate an increased risk for cognitive deterioration.

In yet another aspect of the present invention there is provided a method for monitoring progression of cognitive deterioration in a patient with amyloid deposition in the brain, said method comprising

determining a first measure of magnetic susceptibility and/or transverse relaxation from in in the patient at a first time point;

determining a second measure of magnetic susceptibility and/or transverse relaxation from the same patient at a second time point;

optionally comparing the measure of magnetic susceptibility and/or transverse relaxation from the first and second time points to a reference level;

determining a difference in the measure of magnetic susceptibility and/or transverse relaxation at each of the first and second time points;

deducing progression of cognitive deterioration from the difference in the measure of magnetic susceptibility and/or transverse relaxation from the first and second time points.

In a preferred embodiment the progression in cognitive deterioration is a change in trajectory of the cognitive deterioration. The changes in the magnetic susceptibility or preferably QSM values and/or transverse relaxation can additionally be used in assessing for any changes in cognitive deterioration of a patient. Accordingly, in the monitoring of the magnetic susceptibility or preferably QSM values and/or transverse relaxation, it is possible to monitor for the presence of cognitive deterioration over a period of time, or to track cognitive deterioration progression in a patient.

Accordingly, changes in the level of magnetic susceptibility or preferably QSM values and/or transverse relaxation from a patient can be used to assess cognitive function and cognitive deterioration, to diagnose or aid in the prognosis or diagnosis of cognitive deterioration and/or to monitor progression toward AD in a patient (e.g., tracking progression in a patient and/or tracking the effect of medical or surgical therapy in the patient). For instance if the magnetic susceptibility or preferably QSM value increases over time, the rate at which the cognitive deterioration will occur will increase.

It may be contemplated to also relate to an altered level relative to a sample previously taken for the same mammal. Hence, there may not be a requirement to compare against a reference level such as from a CN sample. In this regard, a reference level may be the level of magnetic susceptibility or preferably QSM value or transverse relaxation at an earlier time point from the same patient.

It is contemplated that magnetic susceptibility or preferably QSM values and/or transverse relaxation can also be obtained from a patient at more than one time point. Such serial sampling would be considered feasible through the methods of the present invention related to monitoring progression of cognitive deterioration in a patient. Serial sampling can be performed on any desired timeline, such as monthly, quarterly (i.e., every three months), semi-annually, annually, biennially, or less frequently. The comparison between the measured levels and predetermined levels may be carried out each time a new sample is measured, or the data relating to levels may be held for less frequent analysis.

In another embodiment, the difference in magnetic susceptibility or preferably QSM values is an elevation between the first and second time points such that the magnetic susceptibility or preferably QSM value in the second time point is higher than the first time point relative to the reference level thereby indicating an increased progression or trajectory for cognitive deterioration. Applicants have shown that patients with comparatively low QSM value will not deteriorate in the foreseeable future. Conversely, an increase in QSM value predicts a more rapid deterioration. Little change in the QSM value would indicate stability of the cognitive deterioration. This will also be relevant to changes in magnetic susceptibility of the patient where the measure of magnetic susceptibility changes in a positive or negative way. Similarly, if the transverse relaxation is changed, such as if it were to decrease, this may indicate the presence of iron in the tissues.

The methods of the invention can additionally be used for monitoring the effect of therapy administered to a mammal, also called therapeutic monitoring, and patient management. Changes in the magnetic susceptibility or preferably QSM values and/or transverse relaxation can be used to evaluate the response of a patient to drug treatment. In this way, new treatment regimens can also be developed by examining the magnetic susceptibility or preferably QSM values and/or transverse relaxation in a patient following commencement of treatment.

The method of the present invention can thus assist in monitoring a clinical study, for example, for evaluation of a certain therapy for a neurological disease. For example, a chemical compound can be tested for its ability to change the magnetic susceptibility or preferably QSM values and/or transverse relaxation in a patient having cognitive deterioration to levels found in controls or CN patients. In a treated patient, a chemical compound can be tested for its ability to maintain the magnetic susceptibility or preferably QSM values and/or transverse relaxation at a level at or near the level seen in controls, HC or CN patients. In a further aspect of the present invention there is provided a method for stratifying a patient with amyloid deposition in the brain for cognitive deterioration, said method comprising

determining a measure of magnetic susceptibility and/or transverse relaxation for the patient; comparing the measure of magnetic susceptibility and/or transverse relaxation with a reference value previously defined as characteristic for patients diagnosed with a level of cognitive deterioration; and

sorting the patient into a class of cognitive deterioration based on the measure of magnetic susceptibility and/or transverse relaxation for the patient relative to the reference value.

The changes in the level of magnetic susceptibility or preferably QSM and/or transverse relaxation in a patient with amyloid deposition in the brain can accordingly be used to stratify a patient (i.e., sorting a patient with cognitive deterioration into different classes of the condition). It is considered that the stratifying of a patient typically refers to sorting of a patient into a different class or strata based on the features characteristic of cognitive deterioration. For example, stratifying patients with cognitive deterioration involves assigning the mammals on the basis of the severity of the deterioration or rate of deterioration. For example a high QSM will identify those patients with amyloid loading that will deteriorate faster than those that have a low QSM which may have a stable deterioration of cognitive deterioration.

Further, the assessment in the change of the levels of magnetic susceptibility or preferably QSM and/or transverse relaxation can be used as a manner of identifying a patient that may be at risk of cognitive deterioration. It would be considered that should a patient be identified as being likely to show cognitive deterioration, they may be further considered for potential therapeutic intervention to assess if the predisposition of cognitive deterioration can be arrested or attenuated. The effectiveness of the intervention in the progression or development cognitive deterioration may be made possible through the monitoring for the change in the magnetic susceptibility or preferably QSM values and/or transverse relaxation.

Where the terms "comprise", "comprises", "comprised" or "comprising" are used in this specification (including the claims) they are to be interpreted as specifying the presence of the stated features, integers, steps or components, but not precluding the presence of one or more other features, integers, steps or components, or group thereof. The present invention will now be more fully described by reference to the following non-limiting Examples.

EXAMPLES

Example 1 : In vivo mapping of brain iron to predict amyloid-related cognitive decline

Quantitative Susceptibility Mapping (QSM) was employed for brain-iron analysis in the Australian Imaging Biomarkers and Lifestyle (AIBL) cohort. QSM, derived from phase processing of gradient echo acquisition, is a relatively new MRI technique that has been validated with post mortem studies (Langkammer C, Schweser F, Krebs N, et al. Neurolmage. Sep 2012;62(3): 1593-1599; Sun H, Walsh AJ, Lebel RM, et al. Jan 15 2015; 105:486-492).

(a) Methods

(i) Study description and participants

Australian Imaging, Biomarkers and Lifestyle (AIBL), previously described in detail (Villemagne VL, Burnham S, Bourgeat P, et al. Lancet neurology. Apr 2013; 12(4):357-367), is a prospective cohort study that began in 2004, with participants assessed for cognitive function every 18 months. AIBL is a longitudinal (currently up to 6 years) clinical-observation study of aging and AD. Participants who met the criteria of Mild Cognitive Impaired (MCI) or AD were recruited from tertiary Memory Disorders Clinics or primary care physicians who specialise in dementia care. 'Healthy Control' (HC) participants were recruited from advertisements, and performed within normal limits on the AIBL neuropsychological test battery (Ellis KA, Bush Al, Darby D, et al. International psychogeriatrics / IPA. Aug 2009;21 (4):672- 687). MCI participants met the criteria for subjective and objective cognitive difficulties in the absence of manifest functional loss, whereas the AD participants met National Institute of Neurological and Communicative Disorders and Stroke- Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria (McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Neurology. Jul 1984;34(7):939-944) for probable AD. All participants underwent baseline amyloid-PET and QSM-MRI imaging, and underwent cognitive assessments every 18 months for up to 6 years. (ii) Ethics

Written informed consent was obtained from all AIBL participants. Study approval was obtained from the human research ethics committees of Austin Health, St Vincent's Hospital, Edith Cowan University, and Hollywood Private Hospital.

(Hi) PET Imaging

Amyloid PET scans were obtained using the 1 1 C-PiB ligand. Image acquisition was for 30 minutes, starting 40 minutes after injection of the radiotracer. PET images were processed using semi-automated region of interest method, as described elsewhere (Villemagne VL, Burnham S, Bourgeat P, et al. Lancet neurology. Apr 2013; 12(4):357-367). Standardised update values (SUV) for 1 1 C-PiB were calculated for all brain regions. A ratio of all regional SUV to the cerebellar cortex SUV was defined as the SUV ratio (SUVR), and a value above 1 .5 designated amyloid positivity (Villemagne VL, Burnham S, Bourgeat P, et al.. Lancet neurology. Apr 2013; 12(4):357-367).

(iv) MRI

All subjects underwent an anatomical T1 -weighted (T1W) and SWI. MRI data were acquired on a 3T Siemens TRIO scanner with a 12-channel head coil. The 3D SWI images used for QSM were acquired with 0.93x0.93mm in-plane resolution and 1 .75mm slice thickness, repetition time/echo time of 27/20msec, flip angle 20° and field of view 240x256, and 80 slices. The magnitude and phase images were stored for each head coil channel.

The T1W data were parcellated into 45 grey-matter (GM) regions by segmentation propagation of an atlas database which had been previously parcellated using the Automated Anatomical Labelling (AAL) (Ayton S, Faux NG, Bush Al, Nature communications. 2015;6:6760).

Several image processing steps were performed to compute QSM maps. First, phase offsets between each coil channel were removed by weighting the magnitude of the corresponding channel, and then combined to form a single-phase image. For QSM reconstruction the STI Suite software (version 2.2) was mainly used. A brain mask was generated from the bias-field corrected magnitude image using FSL's BET with the robust parameter. A Laplacian based method was used to unwrap the phase followed by background field elimination using vSHARP approach. Finally, dipole inversion using an iLSQR technique was performed to obtain the QSM image. In this study, the middle frontal white matter region was chosen as a reference region for normalizing QSM regional values. All susceptibility values are then relative to the mean susceptibility value of this reference region.

(v) Neuropsychological testing

The following statistically-derived composite cognitive scores (as previously described (Burnham SC, Raghavan N, Wilson W, et al. Journal of Alzheimer's disease : JAD. 2015;46(4): 1079-108)) were used as outcome variables in the analyses: Pre-clinical Alzheimer's Cognitive Composite (PACC: MMSE, LMII, Digit Symbol &CVLT-II LDFR), Global Cognition (C10pt: LMII, CVLTFP, Clock), Disease Progression (C2CR: CDRsb and MMSE), and Verbal Episodic Memory (C3VerEM: LMII, CVLTFP, CLVTLDFR).

(vi) Statistical analysis

All statistical work was conducted with R (version 3-2-4)22, using packages ggplot223, nlme24, lmerTest25. The conditions tested were necessary to apply the regression models, normal distribution of the residuals, and the absence of multicolinearity. All models satisfied these conditions. Minimal models were obtained via step down regression using Bayesian information criterion (BIC), ensuring that the central hypotheses were maintained. Where subjects prematurely left the study, their data was included in modelling to the point at which they left. All hypothesis tests were 2-sided, and significant differences were inferred when p<0.05.

(b) Results

QSM values were elevated in amyloid positive subjects in multiple regions of neocortex; an effect that was mediated by diagnostic category, suggesting that QSM is associated more with cognitive performance than amyloid deposition. In amyloid positive subjects, elevated neocortical QSM predicted deteriorating performance on multiple cognitive composites (Global Cognition: p=0.0002, Verbal Episodic Memory: p=0.0009, Disease Progression: p=0.0024, PACC: p=0.0293), regardless of diagnosis. Neocortical QSM was not associated with longitudinal cognitive performance in amyloid negative participants.

(i) Elevated Neocortical QSM in amyloid positive subjects is mediated by diagnosis

The AIBL study collected 106 cross-sectional QSM scans at baseline of 24 AD, 18 MCI and 64 HC participants and stratified the cohort according to amyloid deposition into amyloid positive (PiB-PET SUVR>1 .5; n=51 ) and amyloid negative (SUVR<1 .5; n=55; Table 1 ).

Table 1

In multiple regression models of QSM (controlling for age, sex, amyloid status, and APOE ε4), amyloid positive subjects had elevated QSM in neocortex (p=0.009), frontal lobe (p=0.007), temporal cortex (p=0.008) and amygdala (0.022;).

Adjusting these models additionally for diagnosis abolished the elevation of QSM in all these regions of amyloid positive subjects which suggests that iron does not accumulate with amyloid per se, however, QSM may be associated with impaired cognitive performance. (ii) QSM is negatively associated with longitudinal cognitive performance in Αβ+ participants

Amyloid deposition is evidence for the presence of AD, but the clinical syndrome of AD may take many years to emerge. QSM in the neocortex was tested to predict those amyloid positive subjects who are on the pathway toward disease progression, regardless of diagnosis. In mixed effects linear models of several cognitive composites (controlling for age, sex, APOE ε4, SUVR, years of education, diagnosis) higher neocortical QSM was associated with poorer clinical outcomes in amyloid positive subjects over a six-year period (Table 1 ). For graphical display of this effect, the amyloid positive subjects were stratified into high and low QSM, based on the QSM value (0.0064 ppb) that optimally separated HC from diseased participants (Figure 1 ). In subjects characterised as negative for amyloid, neocortical QSM was not a predictive variable in mixed effects models of the same cognitive scales (Table 1 ).

(c) Discussion

Approximately 30% of Αβ+ subjects do not have objective cognitive impairment (Pietrzak RH, Lim YY, Ames D, et al. Neurobiology of aging. Mar 2015;36(3): 1231 - 1238; Rowe CC, Ellis KA, Rimajova M, et al. Neurobiology of aging. Aug 2010;31 (8): 1275-1283; Aizenstein HJ, Nebes RD, Saxton JA, et al. Archives of neurology. Nov 2008;65(1 1 ): 1509-1517), suggesting that amyloid is not sufficient to precipitate dementia, however amyloid may act in concert with other pathogenic factors to drive disease progression. The current data reveal that neocortical QSM predicts the trajectory of cognitive decline in Αβ+ subjects, which, in agreement with previous work on CSF ferritin (Ayton S, Faux NG, Bush Al, Nature communications. 2015;6:6760; S A, Faux NG, Al B. JAMA neurology. 2016;Accepted Sept 9, 2016), supports a pathogenic role of elevated brain-iron in accelerating cognitive impairment.

These findings highlight the potential for QSM to be used in combination with PET imaging for AD-prognostics. Repeated QSM-MRI scanning of Αβ+ patients in the preclinical phase is likely to be cheaper and more powerful assay to predict near-term cognitive changes. These data also highlight iron as a therapeutic target for AD, since those Αβ+ subjects with the low QSM had stable cognition over the study period. Indeed an early phase II study of the iron chelator, desferrioxamine, demonstrated a 50% reduction in cognitive decline compared to placebo (Crapper McLachlan DR, Dalton AJ, Kruck TP, et al. Lancet. Jun 1 1991 ;337(8753): 1304- 1308). QSM could be used in combination with PET imaging to stratify subjects at risk of proximal cognitive decline. Therapeutically lowering brain iron might slow disease progression in AD.

Example 2: Assessing a risk of cognitive deterioration in a patient

In conducting the methods of the present invention, it is contemplated that a patient will be assessed for a level of cognitive ability. This level will set a base for determining whether they will over time deteriorate. They patient may already show signs of cognitive impairment after being initially assessed. The patient is also assessed for amyloid loading before performing QSM in the patient. If the patient is not amyloid positive as assessed using PET amyloid imaging and does not have a SUVR >1 .5, the patient is not progressed.

Having determined that the patient is amyloid positive, QSM is performed. The amyloid positive subjects are then stratified into high and low QSM, based on the QSM value (0.0064 ppb) that optimally separated HC from diseased participants.

A high or low QSM determines the trajectory for cognitive deterioration. Example 3: Monitoring cognitive deterioration in a patient

A patient is tested according to Example 2 at a first time point. A second test is conducted at another time point after the first time point. The difference between the patient QSM is assessed. The difference may then be compared to the difference from the first time point or with a reference level from a CN patient.

A degree of deterioration can be determined by assessing the cognitive function with the following statistically-derived composite cognitive scores (as previously described (Burnham SC, Raghavan N, Wilson W, et al. Journal of Alzheimer's disease : JAD. 2015;46(4): 1079-108)) as outcome variables for the analyses: Pre-clinical Alzheimer's Cognitive Composite (PACC: MMSE, LMII, Digit Symbol &CVLT-II LDFR), Global Cognition (C10pt: LMII, CVLTFP, Clock), Disease Progression (C2CR: CDRsb and MMSE), and Verbal Episodic Memory (C3VerEM: LMII, CVLTFP, CLVTLDFR).

While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific embodiment, method, and examples herein. The invention should therefore not be limited by the above described embodiment, method, and examples, but by all embodiments and methods within the scope and spirit of the invention as broadly described herein.

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