# US 12,601,750 B2 · Diagnosing mild cognitive impairment (MCI), predicting alzheimer's disease (AD) dementia onset, and screening and monitoring agents for treating mci or preventing dementia onset

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- Number: US 12,601,750 B2
- Document ID: US12601750B2
- Status: Granted
- Kind: B2
- Application number: 18/763,515
- Filed: 2024-07-03
- Published: 2024-10-24
- Granted: 2026-04-14
- Earliest claimed: 2016-02-22
- Assignees: West Virginia University
- Applicants: West Virginia University
- Inventors: Florin V. Chirila; Daniel L. Alkon
- Web page: https://patentgrep.com/patent/US12601750B2

## CPC

- G01N 33/6896: {Neurological disorders, e.g. Alzheimer's disease}
- C12Q 1/485: {involving kinase}
- G01N 33/5041: {involving analysis of members of signalling pathways}
- G01N 33/5091: {for testing the pathological state of an organism}
- G01N 33/573: for enzymes or isoenzymes
- G16B 5/00: ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- G01N 2333/4709: Amyloid plaque core protein
- G01N 2333/912: transferring phosphorus containing groups, e.g. kinases (2.7)
- G01N 2333/91205: Phosphotransferases in general
- G01N 2333/9121: with an alcohol group as acceptor (2.7.1), e.g. general tyrosine, serine or threonine kinases
- G01N 2333/91215: with a definite EC number (2.7.1.-)
- G01N 2440/14: phosphorylation
- G01N 2500/10: involving cells
- G01N 2800/2814: Dementia; Cognitive disorders
- G01N 2800/2821: Alzheimer
- G01N 2800/50: Determining the risk of developing a disease
- G01N 2800/52: Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
- G01N 2800/56: Staging of a disease; Further complications associated with the disease
- G01N 2800/60: Complex ways of combining multiple protein biomarkers for diagnosis
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

Methods of detecting the signature of Alzheimer's disease before the clinical onset of the disease are disclosed, such as methods of diagnosing Mild Cognitive Impairment (MCI), monitoring the progress of MCI, and predicting the time to clinical onset of AD dementia. The methods use a Biomarker Severity Score, which corresponds to output signals of one or more biomarkers chosen from AD Index, Morphometric Imaging, and PKC Epsilon Biomarkers. Also disclosed are methods of screening for a compound useful for treating MCI or for preventing the clinical onset of AD dementia, as well as methods of evaluating or monitoring the therapeutic benefit of an agent for treating MCI or preventing the clinical onset of AD dementia.

## Claims

### Claim 1

A method for predicting the time to clinical onset of Alzheimer's disease (AD) dementia in a test subject having Mild Cognitive Impairment (MCI) comprising
(a) obtaining cells from the test subject;
(b) contacting a first portion of the cells with a Protein Kinase C (PKC) activator while leaving a second portion of the cells uncontacted with the PKC activator,
wherein the PKC activator is selected from the group consisting of bradykinin, a bryostatin, a bryolog, neristatin, 8-[2-(2-pentyl-cyclopropylmethyl)cyclopropyl]-octanoic acid (DCPLA), and esters of DCPLA;
(c) determining an output signal of AD Index Biomarker using the cells from the test subject by using levels of phosphorylated extracellular signal-regulated kinase 1 (pERK1) and phosphorylated extracellular signal-regulated kinase 2 (pERK2), wherein the output signal is determined by
calculating a first ratio of pERK1 to pERK2 in the first portion of the cells,
calculating a second ratio of pERK1 to pERK2 in the second portion of the cells, and
subtracting the second ratio from the first ratio to obtain the output signal of AD Index Biomarker;
(d) obtaining a graph of AD Index Biomarker values, the graph having plotted thereon:
first AD Index Biomarker values for cells obtained from AD-afflicted subjects and
second AD Index Biomarker values for cells obtained from age-matched control subjects,
wherein
the graph has as its x-axis age difference in years and has as its y-axis AD Index values from 0-100,
the graph includes an inflection point between the first AD Index Biomarker values and the second AD Index Biomarker values; and
the first AD Index Biomarker values and the second AD Index Biomarker values are obtained using levels of pERK1 and pERK2 in the cells obtained from AD-afflicted subjects and in the cells obtained from the age-matched control subjects, respectively; and
(e) plotting the output signal determined in step (c) on the graph obtained in step (d), and predicting the time to clinical onset of AD dementia in the test subject based on the position of the output signal determined in step (c) on the graph relative to the inflection point,
wherein
the age difference for each AD-afflicted subject is the difference in age between the time of clinical onset of AD and the age at the time of collecting cells, and
the age difference for each age-matched control subject is the difference in age between the age at the time of collecting cells from the age-matched control subject and the age of the oldest age-matched control subject at the time of collecting cells from that subject.

### Claim 2 (depends on 1)

The method of claim 1, wherein the PKC activator is bradykinin.

### Claim 3 (depends on 1)

The method of claim 1, further comprising monitoring the progression of MCI, comprising repeating steps (a) through (e) at one or more subsequent points in time, wherein the subject has progressed toward the clinical onset of AD dementia if the output signals determined in step (c) have increased over time.

### Claim 4 (depends on 1)

The method of claim 1, wherein the cells are peripheral cells.

### Claim 5 (depends on 4)

The method of claim 4, wherein the peripheral cells are skin fibroblast cells.

### Claim 6 (depends on 1)

The method of claim 1, wherein the test subject displays no phenotypic symptoms of AD.

### Claim 7 (depends on 1)

The method of claim 1, wherein the method further comprises determining an output signal of a Morphometric Imaging Biomarker using the cells from the test subject, wherein determining the output signal of the Morphometric Imaging Biomarker comprises:
(i) culturing one or more cells from the test subject for a time period sufficient to achieve cell aggregation;
(ii) determining the average area of cell aggregates (A) and dividing the average area by the number of aggregates (N) to obtain the average area per number of aggregates (A/N); and
(iii) calculating the natural logarithm of (A/N).

### Claim 8 (depends on 1)

The method of claim 1, wherein the method further comprises determining an output signal of a PKC Epsilon Biomarker using the cells from the test subject, wherein determining the output signal of the PKC Epsilon Biomarker comprises:
(i) determining the PKC level in one or more cells from the test subject;
(ii) contacting the one or more cells with an Aβ peptide;
(iii) determining the PKC epsilon level in the one or more cells in step (ii) after the contacting step; and
(iv) calculating the output signal as the ratio of the slope(S) and intercept (I), (S/I), of the change in PKCε level as a function of Aβ peptide concentration.

### Claim 9 (depends on 1)

The method of claim 1, wherein the PKC activator is a bryostatin selected from the group consisting of bryostatin-1, bryostatin-2, bryostatin-3, bryostatin-4, bryostatin-5, bryostatin-6, bryostatin-7, bryostatin-8, bryostatin-9, bryostatin-10, bryostatin-11, bryostatin-12, bryostatin-13, bryostatin-14, bryostatin-15, bryostatin-16, bryostatin-17, and bryostatin-18.