WO2009076581A1 - Fluctuations de la bêta-amyloïde en tant que biomarqueur pour la maladie d'alzheimer - Google Patents

Fluctuations de la bêta-amyloïde en tant que biomarqueur pour la maladie d'alzheimer Download PDF

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WO2009076581A1
WO2009076581A1 PCT/US2008/086529 US2008086529W WO2009076581A1 WO 2009076581 A1 WO2009076581 A1 WO 2009076581A1 US 2008086529 W US2008086529 W US 2008086529W WO 2009076581 A1 WO2009076581 A1 WO 2009076581A1
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subject
samples
disease
correlation
fluctuation
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PCT/US2008/086529
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Randall Bateman
David Holtzman
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Washington University In St. Louis
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    • C—CHEMISTRY; METALLURGY
    • C07—ORGANIC CHEMISTRY
    • C07K—PEPTIDES
    • C07K14/00—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof
    • C07K14/435—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans
    • C07K14/46—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans from vertebrates
    • C07K14/47—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans from vertebrates from mammals
    • C07K14/4701—Peptides having more than 20 amino acids; Gastrins; Somatostatins; Melanotropins; Derivatives thereof from animals; from humans from vertebrates from mammals not used
    • C07K14/4711—Alzheimer's disease; Amyloid plaque core protein

Definitions

  • the present invention generally relates to Alzheimer's disease.
  • the present invention provides biomarkers for Alzheimer's disease and methods of using the biomarkers to diagnose, monitor treatment, and/or identify individuals at risk for Alzheimer's disease.
  • AD Alzheimer's disease
  • AD is the most common cause of dementia and is an increasing public health problem. It is currently estimated to afflict 5 million people in the United States, with an expected increase to 13 million by the year 2050 (Hebert et al., 2003, Arch Neurol 60(8):1119-1122). AD leads to loss of memory, cognitive function, and ultimately independence. AD takes a heavy personal and financial toll on the patient and the family. Because of the severity and increasing prevalence of the disease in the population, it is urgent that better treatments be developed.
  • AD Alzheimer's disease
  • a ⁇ amyloid-beta
  • APP amyloid precursor protein
  • CDR Clinical Dementia Rating
  • the biomarker comprises either (a) the attenuation of amyloid-beta fluctuation over time in a subject, or (b) the attenuation of correlation between amyloid-beta species over time in the subject.
  • Another aspect of the invention encompasses a method for diagnosing Alzheimer's disease in a subject.
  • the method comprises either (a) determining the fluctuation of amyloid-beta over time in the subject, wherein an attenuated fluctuation indicates the diagnosis of Alzheimer's disease, or (b) determining the correlation between amyloid-beta species over time in the subject, wherein an attenuated correlation indicates the diagnosis of Alzheimer's disease.
  • a further aspect of the invention provides a method for determining whether a subject is at risk for Alzheimer's disease.
  • the method comprising either (a) determining the fluctuation of amyloid-beta over time in the subject, wherein an attenuated fluctuation indicates the subject is at risk for Alzheimer's disease, or (b) determining the correlation between amyloid-beta species over time in the subject, wherein an attenuated correlation indicates the subject is at risk for Alzheimer's disease.
  • FIG. 1 depicts a series of graphs illustrating that human CSF A ⁇ levels fluctuate over hours.
  • A-C The levels of human CSF A ⁇ i -X (triangle), A ⁇ 40 (square), and A ⁇ 42 (circle) over 36 hours are shown in three typical individual participants (A, B age 20 to 45, C age 46 to 80). A ⁇ levels had significant fluctuations, changing >50% within 6 hours, and >100% over 12 hours.
  • D-F Mean levels of A ⁇ i -X (D), A ⁇ i -40 (E), and A ⁇ i -42 (F) averaged across all participants at each sample time are shown as a percent of the average A ⁇ level.
  • a ⁇ levels demonstrate troughs at 0 and 25 hours with peaks at 14 and 23 hours.
  • Figure 2 depicts a series of graphs showing that CSF A ⁇ 40 , A ⁇ 42 , and A ⁇ i -X are correlated over time and mean levels vary by time of day.
  • the CSF A ⁇ i -X versus A ⁇ 40 and A ⁇ 42 , and A ⁇ 40 versus A ⁇ 42 are shown for three participants (A, B, and C).
  • a ⁇ 40 and A ⁇ 42 are correlated with A ⁇ i -X
  • a ⁇ 42 is correlated with A ⁇ 40 .
  • Linear regression of each indicates a strong correlation between each pair of human A ⁇ species assessed in CSF (p ⁇ 0.0001 ).
  • Figure 3 depicts a graph showing that the loss of correlation in the fluctuation of A ⁇ is predictive of those affected or at risk for AD versus normal controls.
  • Figure 4 depicts two graphs showing the fluctuations of A ⁇ in DAT participants (CDR >0) (B) and cognitively normal controls (A).
  • the present invention provides novel AD biomarkers present in the bodily fluid or tissue of a subject. These biomarkers correlate with CDR score, and therefore may allow a more accurate diagnosis or prognosis of AD in subjects that are at risk for AD, that show no clinical signs of AD, or that show minor clinical signs of AD. Furthermore, the biomarkers may allow the monitoring of AD, such that a comparison of biomarker levels allows an evaluation of disease progression in subjects that have been diagnosed with AD, or that do not yet show any clinical signs of AD. Moreover, the AD biomarkers of the invention may be used in concert with known AD biomarkers such that a more accurate diagnosis or prognosis of AD may be made.
  • One aspect of the invention encompasses biomarkers for AD.
  • One biomarker for AD comprises an attenuation of the fluctuation of A ⁇ over time in a subject.
  • Another biomarker for AD comprises an attenuation of the correlation between A ⁇ species over time in a subject.
  • a ⁇ refers to the level of A ⁇ in two or more samples from a subject.
  • a ⁇ may refer to A ⁇ polypeptides (e.g., A ⁇ i. x), A ⁇ 42 (A ⁇ i -42 ), A ⁇ 40 (A ⁇ i-40), or any combination thereof.
  • a ⁇ refers to A ⁇ 42 .
  • Methods of measuring the level of A ⁇ in a sample are known in the art. Generally speaking, one skilled in the art will consider the source and quantity of the sample when selecting a method of measuring the level of A ⁇ in a sample. For instance, an ELISA may be used to measure the level of A ⁇ in a sample. For more details, see the methods for Example 1.
  • a ⁇ may be measured in cerebral spinal fluid (CSF) samples, tissue samples, blood samples, microdialysis samples, or other samples that comprise A ⁇ and reflect physiological fluctuations in A ⁇ levels.
  • CSF cerebral spinal fluid
  • a ⁇ may be measured in CSF samples. Methods for collecting CSF samples are known in the art. For more details, see the methods for Example 1 below.
  • a ⁇ may be measured in blood samples.
  • a ⁇ may be measured in blood plasma samples. Methods for collecting blood samples are known in the art.
  • a ⁇ may be measured in tissue samples. Methods for collecting tissue samples, including brain tissue samples, are well known in the art.
  • a ⁇ may be measured in microdialysis samples. Methods for collecting microdialysis samples are well known in the art.
  • the amount of sample collected depends in part, on the type of sample being collected. Generally speaking, the amount collected will be enough to measure A ⁇ by the method selected.
  • a sample may be collected and tested from any animal known to suffer from Alzheimer's disease, including humans, or used as a disease model for Alzheimer's disease.
  • the subject may be a rodent. Examples of rodents include mice, rats, and guinea pigs.
  • the subject may be a primate. Examples of primates include monkeys, apes, and humans.
  • the subject may be a human.
  • the subject may have no clinical signs of AD.
  • the subject may have a CDR score of greater than 0.
  • the subject may have mild clinical signs of AD, for instance, corresponding to a CDR score of 0.5 or higher.
  • the subject may be at risk for AD.
  • the subject may have a CDR score of 0 but have amyloid plaques in the brain.
  • the subject may have been diagnosed with AD. (a) attenuation of the fluctuation of A ⁇
  • Fluctuation in A ⁇ refers to changes, variations, variability, or dynamics in the level of A ⁇ over time in a subject (or the ratio of A ⁇ over time in a subject). The changes may be reflected in increased levels or ratios, decreased levels or ratios, or changed patterns of fluctuation (e.g., sinusoidal vs. non-sinusoidal).
  • the level of A ⁇ fluctuates over time in a subject that is not afflicted with AD. Stated another way, the level of A ⁇ fluctuates over time in a subject with a clinical dementia rating (CDR) of 0 that lacks amyloid plaques in the brain. Consequently, in some embodiments, attenuation of the fluctuation of A ⁇ over time comprises a biomarker for diagnosing AD in a subject or for predicting whether a subject will develop AD. For instance, in one embodiment, attenuation of the fluctuation of A ⁇ over time may comprise a biomarker for AD in subjects who have neuropathologic AD but have not yet manifested clinical signs of AD.
  • One method to quantify the fluctuation of A ⁇ in a subject is to determine the level of A ⁇ in two or more samples from the subject over a given time period.
  • Another method to quantify the fluctuation of A ⁇ in the subject is to calculate the standard deviation of A ⁇ levels in two or more samples from the subject over a given time period.
  • Methods of calculating standard deviations are known in the art.
  • the level of A ⁇ and/or the standard deviation may be calculated from 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, or more samples from the subject.
  • the time interval between two consecutive samples may range from minutes to hours to days to months.
  • the time interval between two consecutive samples may be at least about 0.5, 1 , 2, 5, 10, 20, 30, 60, 120, 240, or more minutes.
  • the time interval between two consecutive samples may be at least about 3, 5, 10, 15, 20, 25, 30, or more hours.
  • the time interval between two consecutive samples may be at least about 1 , 2, 5, 10, 15, 20, 30, 60, 120, or more days.
  • the fluctuation is attenuated compared to the fluctuation in a subject with a CDR of 0 who lacks amyloid plaques in the brain.
  • the fluctuation is attenuated for a subject afflicted with AD.
  • the fluctuation is attenuated for a subject who is at risk for developing AD (i.e., who is developing amyloid plaques in the brain but is still clinically normal, with a CDR of 0).
  • the fluctuation may be attenuated in a subject who is likely to develop AD but has not yet shown clinical symptoms of the disease.
  • Attenuation means that the fluctuation is at least about 10% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain.
  • the fluctuation may be at least about 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain.
  • a ⁇ species in a subject who is not afflicted with AD refers to an A ⁇ polypeptide, or, in some embodiments, the total of all or some A ⁇ polypeptides. For instance, if the total level of A ⁇ increases in a subject, the level of A ⁇ 42 also increases. Consequently, in some embodiments, the attenuation of the correlation between A ⁇ 42 and total A ⁇ or A ⁇ 40 over time comprises a biomarker for AD in a subject. In other embodiments, the attenuation of correlation is a biomarker for a subject who is at risk for developing AD.
  • the attenuation of correlation is a biomarker for a subject who is likely to develop AD but has not yet shown clinical symptoms of the disease (e.g., a subject who is developing amyloid plaques in the brain, but is still clinically normal, with a CDR of 0).
  • the attenuation of correlation is a biomarker for a subject that has a CDR >0.
  • a ⁇ 42 and the level of other A ⁇ species, such as total A ⁇ or A ⁇ 40 over time in a subject This correlation may be measured using methods known in the art, as illustrated in Example 1.
  • the correlation between A ⁇ species is calculated from two or more samples from the subject over a time period.
  • the time interval between two consecutive samples may range from minutes to hours to days to months.
  • the time interval between two consecutive samples may be at least about 0.5, 1 , 2, 5, 10, 20, 30, 60, 120, 240, or more minutes.
  • the time interval between two consecutive samples may be at least about 3, 5, 10, 15, 20, 25, 30, or more hours.
  • the time interval between two consecutive samples may be at least about 1 , 2, 5, 10, 15, 20, 30, 60, or more days.
  • Attenuation means that the correlation is at least about 10% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain.
  • the correlation may be at least about 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, or 95% less than that seen in a subject with a CDR of 0 who lacks amyloid plaques in the brain.
  • Each of the biomarkers identified above may be used in concert with another biomarker for purposes including but not limited to diagnosis of AD, prognosis of AD, determining risk of AD, and monitoring treatment of AD. For instance, two or more, three or more, four or more, five or more, or six or more AD biomarkers may be used in concert. As explained above, there are several known biomarkers for AD. In one embodiment, at least one biomarker of the invention and one or more biomarkers from the group comprising ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert.
  • At least one biomarker of the invention and two or more biomarkers from the group comprising ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert.
  • at least one biomarker of the invention and three or more biomarkers from the group comprising ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert.
  • at lest one biomarker of the invention and ACT, ATIII, ZAG, CNDP1 , and tau may be used in concert as biomarkers for AD. //.
  • Another aspect of the invention encompasses methods for using the biomarkers of the invention.
  • one of the biomarkers detailed in section I above may be used in a method for diagnosing AD in a subject.
  • the method may comprise determining the fluctuation of A ⁇ over time in the subject, wherein an attenuated fluctuation indicates a diagnosis of AD.
  • the method may comprise determining the correlation of A ⁇ species over time in a subject, wherein an attenuated correlation indicates a diagnosis of AD. Determining the fluctuation or correlation over time comprises measuring A ⁇ in at least two samples from the subject.
  • one of the biomarkers detailed in section I above may be used in a method for determining whether a subject is at risk of developing AD.
  • the biomarkers may be used for assessing whether a subject is likely to develop AD but has not yet shown clinical symptoms of the disease.
  • the method may comprise determining the fluctuation of A ⁇ over time in the subject, wherein an attenuated fluctuation indicates the subject is at risk of developing AD.
  • the method may comprise determining the correlation of A ⁇ species over time in the subject, wherein an attenuated correlation indicates the subject is at risk of developing AD. Determining the fluctuation or correlation over time comprises measuring A ⁇ in at least two samples from the subject.
  • one of the biomarkers detailed in section I above may be used for monitoring AD.
  • the method may comprise determining the fluctuation of A ⁇ or determining the correlation of A ⁇ species in the subject over time after the diagnosis of AD.
  • the comparison of the biomarker at two or more time points may give an indication of disease progression. For example, no further attenuation of the fluctuation or correlation indicates that the disease has not progressed or worsened. Additionally, the comparison may serve to measure the rate of disease progression.
  • a biomarker detailed in section I above may be used for monitoring treatment of a subject having AD.
  • the method may comprise determining the fluctuation of A ⁇ or determining the correlation of A ⁇ species in the subject before and after the administration of the treatment.
  • a reduced attenuation of fluctuation or correlation after treatment indicates a positive response to the treatment.
  • the comparison may serve to measure the effectiveness of a chosen therapeutic treatment.
  • the therapeutic treatment for AD will comprise administration of a therapeutic agent.
  • suitable AD therapeutic agents include gamma-secretase inhibitors, beta-secretase inhibitors, alpha-secretase activators, RAGE inhibitors, small molecule inhibitors of A ⁇ production, small molecule inhibitors of A ⁇ polymerization, platinum-based inhibitors of A ⁇ production, platinum- based inhibitors of polymerization, agents that interfere with metal-protein interactions, proteins (such as, e.g., low-density lipoprotein receptor-related protein (LRP) or soluble LRP) that bind soluble A ⁇ , and antibodies that clear soluble A ⁇ and/or break down deposited A ⁇ .
  • proteins such as, e.g., low-density lipoprotein receptor-related protein (LRP) or soluble LRP
  • AD therapeutic agents include cholesterylester transfer protein (CETP) inhibitors, metalloprotease inhibitors, cholinesterase inhibitors, NMDA receptor antagonists, hormones, neuroprotective agents, and cell death inhibitors.
  • CETP cholesterylester transfer protein
  • the therapeutic agent will be administered to the subject in accord with known methods. Typically, the therapeutic agent will be administered orally, but other routes of administration such as parenteral or topical may also be used.
  • the amount of therapeutic agent that is administered to the subject can and will vary depending upon the type of agent, the subject, and the particular mode of administration.
  • suitable subjects include those detailed in section I above.
  • the subject is human.
  • a ⁇ amyloid- ⁇
  • the levels for A ⁇ i -X , A ⁇ 40 , and A ⁇ 42 varied by 50% or more over several hours and the maximum A ⁇ levels were greater than 200% the minimum values over the entire study.
  • a ⁇ 40 and A ⁇ 42 were correlated (p ⁇ 0.05) to A ⁇ 1-X in all samples
  • a ⁇ i -X there was a significant correlation of A ⁇ i -X to A ⁇ 40 and A ⁇ 42 , as well as A ⁇ 40 to A ⁇ 42 .
  • the A ⁇ species 40 and 42 were tightly correlated to each other in hourly measurements, and this likely indicates similar processes in the production and clearance of each from human CSF. The relationship may be altered in the presence of A ⁇ deposition in plaques, leading to a decreased level of A ⁇ 42 and a decreased ratio of A ⁇ 42 to A ⁇ 40 reported in studies (Sunderland et al., 2003, JAMA 289:2094-2103).
  • there was not a significant correlation of A ⁇ 42 to A ⁇ 40 or to A ⁇ i -X This may reflect a disturbance in clearance of A ⁇ 42 relative to A ⁇ 40 and may be a precursor or an indicator of AD pathology.
  • a ⁇ i -42 may be extremely highly correlated to Alzheimer pathology, as suggested by recent studies of A ⁇ i -42 and PET PIB, which is an A ⁇ plaque imaging technique (Fagan et al., 2006, Annals of Neurology 59(3):512-519).
  • PET PIB PET PIB
  • the variability of A ⁇ i -42 in cognitively normal participants (CDR 0) appears higher than in participants with DAT (CDR >0) ( Figure 4). Table 2 below summarizes the differences in variability between AD and controls.
  • the A ⁇ fluctuations are a biologic change in levels and not an artifact (e.g., a floor effect) of the assay, which has a sensitivity of 10 pg/ml (Bateman et al., 2007, Neurology 68(9):666-669). These fluctuations were demonstrated in young healthy controls and age matched older controls, but appear to be significantly decreased in participants with DAT.
  • a ⁇ levels increased from 0 to 14 hours, with peaks at 14 and 23 hours and troughs at 0 and 25 hours in the levels of A ⁇ i -X , A ⁇ 40 , and A ⁇ 42 . This may be time of day or activity dependent.
  • a ⁇ release is dependent on synaptic activity (Cirrito et al., 2005, Neuron 48:913; Kamenetz et al., 2003, Neuron, 37:925-937) and this may account for much of the observed variability in CSF levels.
  • a similar dynamic variability over hours in A ⁇ levels in brain interstitial fluid was observed, similar to that observed here in human CSF.

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Abstract

La présente invention concerne des biomarqueurs pour la maladie d'Alzheimer, ainsi que des procédés d'utilisation des biomarqueurs pour diagnostiquer la maladie d'Alzheimer, pour suivre la progression de la maladie d'Alzheimer, pour suivre le traitement de la maladie d'Alzheimer et/ou pour identifier des sujets à risque de développer la maladie d'Alzheimer.
PCT/US2008/086529 2007-12-12 2008-12-12 Fluctuations de la bêta-amyloïde en tant que biomarqueur pour la maladie d'alzheimer WO2009076581A1 (fr)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011133583A1 (fr) * 2010-04-19 2011-10-27 Functional Neuromodulation Inc. Stimulation cérébrale profonde de circuits mémoriels dans la maladie d'alzheimer
US10830775B2 (en) 2014-09-30 2020-11-10 Washington University Tau kinetic measurements
US11085935B2 (en) 2018-05-03 2021-08-10 Washington University Methods of treating based on site-specific tau phosphorylation

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
BATEMAN ET AL.: "Fluctuations of CSF amyloid-beta levels: Implications for a diagnostic and therapeutic biomarker.", NEUROLOGY, vol. 68, 27 February 2007 (2007-02-27), pages 666 - 669 *
FAGAN ET AL.: "Cerebrospinal fluid tau/beta-amyloid.42 ratio as a prediction of cognitive decline in nondemented older adults.", ARCHIVES OF NEUROLOGY, vol. 64, March 2007 (2007-03-01), pages 343 - 349 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011133583A1 (fr) * 2010-04-19 2011-10-27 Functional Neuromodulation Inc. Stimulation cérébrale profonde de circuits mémoriels dans la maladie d'alzheimer
US10830775B2 (en) 2014-09-30 2020-11-10 Washington University Tau kinetic measurements
US11085935B2 (en) 2018-05-03 2021-08-10 Washington University Methods of treating based on site-specific tau phosphorylation
US11402392B2 (en) 2018-05-03 2022-08-02 Washington University Methods of treating based on site-specific tau phosphorylation

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