KR102555878B1 - Use of downregulated mirna for diagnosis and treatment - Google Patents

Abstract

The present invention relates to the use of miRNAs and/or activators thereof for diagnosing or treating cognitive disorders associated with reduced levels of miRNA (eg, miR-150) expression.

Description

Use for diagnosis and treatment of downregulated MIRNA {USE OF DOWNREGULATED MIRNA FOR DIAGNOSIS AND TREATMENT}

The present invention relates to miRNAs for the diagnosis and/or treatment of cognitive disorders such as Alzheimer's disease and Mild Cognitive Impairment (MCI).

As degenerative aging progresses, spontaneous memory loss may occur. However, persistent problems with cognitive function and memory may raise the suspicion of mild cognitive impairment (MCI). MCI refers to changes in cognitive abilities, including memory and thinking, that are more severe than the natural aging process. Also, MCI patients are more likely to progress to Alzheimer's disease (AD). AD is a progressive neurodegenerative disorder associated with the destruction of higher brain structures involved in memory and cognition. The disease leads to deficits in cognitive function, resulting in reduced memory, learning, language skills, and the ability to carry out deliberate or intentional actions. The total number of people with AD is expected to at least triple between 2000 and 2050, making AD a global public health problem. Clinical detection of AD remains elusive even for medical professionals, and diagnostic tests such as the Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) are commonly used to diagnose normal aging, MCI, and AD, but these diagnoses are difficult to recognize due to normal aging. It is insufficient to distinguish whether or not it is a disease group of deterioration. Clinical detection, management and treatment of AD remain inadequate. Thus, there remains an unmet need for effective methods of identifying and treating Alzheimer's disease.

The matters described as the above background art are only for improving understanding of the background of the present invention, and should not be taken as an admission that they correspond to prior art already known to those skilled in the art.

1. Grundman, M., Petersen, R. C., Ferris, S. H., Thomas, R. G., Aisen, P. S., Bennett, D. A., . . . Doody, R. (2004). Mild cognitive impairment can be distinguished from alzheimer disease and normal aging for clinical trials. Archives of Neurology, 61(1), 59-66. 2. Petersen, R. C., Doody, R., Kurz, A., Mohs, R. C., Morris, J. C., Rabins, P. V., . . . Winblad, B. (2001). Current concepts in mild cognitive impairment. Archives of Neurology, 58(12), 1985-1992. 3. Mattsson, N., Zetterberg, H., Hansson, O., Andreasen, N., Parnetti, L., Jonsson, M., . . . Ewers, M. (2009). CSF biomarkers and incipient alzheimer disease in patients with mild cognitive impairment. Jama, 302(4), 385-393. 4. Morris, J. C., Storandt, M., Miller, J. P., McKeel, D. W., Price, J. L., Rubin, E. H., & Berg, L. (2001). Mild cognitive impairment represents early-stage alzheimer disease. Archives of Neurology, 58(3), 397-405. 5. Vos, S. J., Van Rossum, I. A., Verhey, F., Knol, D. L., Soininen, H., Wahlund, L., . . . Frisoni, G. B. (2013). Prediction of alzheimer disease in subjects with amnestic and nonamnestic MCI. Neurology, 80(12), 1124-1132. 6. Alzheimer's Association. (2018). 2018 Alzheimer's disease facts and figures. Alzheimer's & Dementia, 14(3), 367-429. 7. Thies, W., & Bleiler, L. (2013). 2013 alzheimer's disease facts and figures alzheimer's association. Alzheimers & Dementia, 9(2), 208-245. 8. Lyketsos, C. G. (2006). Task force of american association for geriatric psychiatry. position statement of the american association for geriatric psychiatry regarding principles of care for patients with dementia resulting from alzheimer disease. Am J Geriatr Psychiatry, 14, 561-572. 9. Celsis, P. (2000). Age-related cognitive decline, mild cognitive impairment or preclinical alzheimer's disease? Annals of Medicine, 32(1), 6-14. 10. Coen, R. F., Robertson, D. A., Kenny, R. A., & King-Kallimanis, B. L. (2016). Strengths and limitations of the MoCA for assessing cognitive functioning: Findings from a large representative sample of irish older adults. Journal of Geriatric Psychiatry and Neurology, 29(1), 18-24. 11. Stewart, S., O'Riley, A., Edelstein, B., & Gould, C. (2012). A preliminary comparison of three cognitive screening instruments in long term care: The MMSE, SLUMS, and MoCA. Clinical Gerontologist, 35(1), 57-75. 12. Dolgin, E. (2018). Alzheimer's disease is getting easier to spot. Nature, 559 (7715), S10. 13. Catricala, S., Torti, M., & Ricevuti, G. (2012). Alzheimer disease and platelets: How's that relevant. Immunity & Aging, 9(1), 20. 14. Keshavan, A., Heslegrave, A., Zetterberg, H., & Schott, J. M. (2017). Blood biomarkers for alzheimer's disease: Much promise, cautious progress. Molecular Diagnosis & Therapy, 21(1), 13-22. 15. Voyle, N., Baker, D., Burnham, S. C., Covin, A., Zhang, Z., Sangurdekar, D. P., . . . Kiddle, S. (2015). Blood protein markers of neocortical amyloid-β burden: A candidate study using SOMAscan technology. Journal of Alzheimer's Disease, 46(4), 947-961. 16. Geekiyanage, H., Jicha, G. A., Nelson, P. T., & Chan, C. (2012). Blood serum miRNA: Non-invasive biomarkers for alzheimer's disease. Experimental Neurology, 235(2), 491-496. 17. Leidinger, P., Backes, C., Meder, B., Meese, E., & Keller, A. (2014). The human miRNA repertoire of different blood compounds. BMC Genomics, 15(1), 474. 18. Hebert, S. S., & De Strooper, B. (2009). Alterations of the microRNA network cause neurodegenerative disease. Trends in Neurosciences, 32(4), 199-206. 19. Junn, E., & Mouradian, M. M. (2012). MicroRNAs in neurodegenerative diseases and their therapeutic potential. Pharmacology & Therapeutics, 133(2), 142-150. 20. Nelson, P. T., Wang, W., & Rajeev, B. W. (2008). MicroRNAs (miRNAs) in neurodegenerative diseases. Brain Pathology, 18(1), 130-138. 21. Kondkar, A. A., Bray, M. S., Leal, S. M., Nagalla, S., Liu, D. J., Jin, Y., . . . Shaw, C. (2010). VAMP8/endobrevin is overexpressed in hyperreactive human platelets: Suggested role for platelet microRNA. Journal of Thrombosis and Haemostasis, 8(2), 369-378. 22. Landry, P., Plante, I., Ouellet, D. L., Perron, M. P., Rousseau, G., & Provost, P. (2009). Existence of a microRNA pathway in anucleate platelets. Nature Structural & Molecular Biology, 16(9), 961. 23. Nagalla, S., Shaw, C., Kong, X., Kondkar, A. A., Edelstein, L. C., Ma, L., . . . Yang, L. (2011). Platelet microRNA-mRNA coexpression profiles correlate with platelet reactivity. Blood, the Journal of the American Society of Hematology, 117(19), 5189-5197. 24. Sevush, S., Jy, W., Horstman, L. L., Mao, W., Kolodny, L., & Ahn, Y. S. (1998). Platelet activation in alzheimer disease. Archives of Neurology, 55(4), 530-536. 25. Catricala, S., Torti, M., & Ricevuti, G. (2012). Alzheimer disease and platelets: How's that relevant. Immunity & Aging, 9(1), 20. 26. Bissels, U., Wild, S., Tomiuk, S., Holste, A., Hafner, M., Tuschl, T., & Bosio, A. (2009). Absolute quantification of microRNAs by using a universal reference. RNA, 15(12), 2375-2384. 27. Dostal, D. E., Rothblum, K. N., & Baker, K. M. (1994). An improved method for absolute quantification of mRNA using multiplex polymerase chain reaction: Determination of renin and angiotensinogen mRNA levels in various tissues. Analytical Biochemistry, 223(2), 239-250. 28. Murray, M. J., Bell, E., Raby, K. L., Rijlaarsdam, M. A., Gillis, A. J., Looijenga, L. H., . . . Coleman, N. (2016). A pipeline to quantify serum and cerebrospinal fluid microRNAs for diagnosis and detection of relapse in pediatric malignant germ-cell tumors. British Journal of Cancer, 114(2), 151-162. 29. Rinnerthaler, G., Hackl, H., Gampenrieder, S. P., Hamacher, F., Hufnagl, C., Hauser-Kronberger, C., . . . Mlineritsch, B. (2016). miR-16-5p is a stably-expressed housekeeping microRNA in breast cancer tissues from primary tumors and from metastatic sites. International Journal of Molecular Sciences, 17(2), 156. 30. Griffiths-Jones, S., Hui, J. H., Marco, A., & Ronshaugen, M. (2011). MicroRNA evolution by arm switching. EMBO Reports, 12(2), 172-177. 31. Chen, L., Sun, H., Wang, C., Yang, Y., Zhang, M., & Wong, G. (2018). miRNA arm switching identifies novel tumor biomarkers. EBioMedicine, 38, 37-46. 32. Zhang, Z., Pi, J., Zou, D., Wang, X., Xu, J., Yu, S., . . . Zhao, H. (2019). microRNA arm-imbalance in part from complementary targets mediated decay promotes gastric cancer progression. Nature Communications, 10(1), 1-16. 33. Liu, C., Wang, J., Li, L., & Wang, P. (2014). MicroRNA-384 regulates both amyloid precursor protein and β-secretase expression and is a potential biomarker for alzheimer's disease. International Journal of Molecular Medicine, 34(1), 160-166. 34. Lugli, G., Cohen, A. M., Bennett, D. A., Shah, R. C., Fields, C. J., Hernandez, A. G., & Smalheiser, N. R. (2015). Plasma exosomal miRNAs in persons with and without alzheimer disease: Altered expression and prospects for biomarkers. PloS One, 10(10) 35. Riancho, J., Vαzquez-Higuera, J. L., Pozueta, A., Lage, C., Kazimierczak, M., Bravo, M., . . . Lleo, A. (2017). MicroRNA profile in patients with alzheimer's disease: Analysis of miR-9-5p and miR-598 in raw and exosome enriched cerebrospinal fluid samples. Journal of Alzheimer's Disease, 57(2), 483-491.

The present inventors have made diligent efforts to find useful methods for identifying cognitive disorders, including Alzheimer's disease. As a result, the present invention was completed by confirming that the reduced level of expression of miRNA such as miR-150 is closely related to cognitive impairment.

Accordingly, an object of the present invention is a method for providing information for identifying a subject suitable for treatment of cognitive disorder, comprising measuring the expression level of miRNA obtained from an isolated sample of the subject. , The miRNA is miR-873-5p, miR-215-5p, miR-642a-5p, miR-4731-5p, miR-95-3p, miR-150-3p, miR-150-5p, or miR-150 It is to provide a method of providing information, characterized in that it is a precursor or a combination thereof.

Another object of the present invention is to provide a miRNA selection method for determining whether a subject has cognitive impairment.

Another object of the present invention is to provide a kit for diagnosing cognitive impairment.

Another object of the present invention is to provide a pharmaceutical composition for the prevention or treatment of cognitive disorder for administration to a subject with cognitive disorder diagnosed using the information providing method or kit.

Other objects and advantages of the present invention will become more apparent from the following detailed description of the invention, claims and drawings.

According to one aspect of the present invention, information for identifying a subject suitable for treatment of cognitive disorder, comprising measuring the expression level of miRNA obtained from an isolated sample of the subject As a method of providing, the miRNAs are miR-873-5p, miR-215-5p, miR-642a-5p, miR-4731-5p, miR-95-3p, miR-150-3p, miR-150-5p, Or a miR-150 precursor or a combination thereof, characterized in that, provides a method of providing information.

As used herein, the term "subject", "subject" or "subject" refers to a mammal that is an object of identification, discrimination, classification, diagnosis, treatment, observation, or experiment, preferably humans, primates including chimpanzees, dogs, cats, etc. It is interpreted as meaning including mammals such as pets, livestock such as cattle, horses, sheep, and goats, and rodents such as mice and rats. In addition, "normal group" is also interpreted in this sense, and means an object that is not affected by the cognitive disorder to be detected.

Unless otherwise specified, the term “miRNA” herein is transcribed as a hairpin-shaped RNA precursor, cleaved by a dsRNA cleavage enzyme having RNase III cleavage activity, introduced into a protein complex called RISC, and inhibiting mRNA translation Involved in, generally about 10 to 30 bases of non-coding RNA is intended to be used. In addition, the miRNAs used herein include not only miRNAs represented by specific nucleotide sequences (SEQ ID NOs: 30 to 37 in Table 1), but also precursors of the miRNAs (pre-miRNA, pri-miRNA), biological functions equivalent to those Variants and derivatives of miRNAs, such as homologs (ie, homologs or orthologs), polymorphisms, etc., are also included. These precursors, homologues, mutants or derivatives can be specifically identified by miRBase release 20 (http://www.mirbase.org/), and nucleotide sequences that hybridize with the complementary sequence of the miRNA under stringent conditions miRNAs with In addition, the miRNA used herein may be a gene product of a miR gene, and such a gene product is a mature miRNA (e.g., non-coding 10 to 30 bases or 15 to 30 bases involved in translational inhibition of the above mRNA). RNA) or miRNA precursors (eg, pre-miRNA or pri-miRNA as above).

SEQ ID No. miRNAs Sequence 30 miR-873-5p GCAGGAACUUGUGAGUCUCCU 31 miR-215-5p AUGACCUAUGAAUUGACAGAC 32 miR-642a-5p GUCCCUCUCCAAAUGUGUCUUG 33 miR-4731-5p UGCUGGGGGCCACAUGAGUGUG 34 miR-95-3p UUCAACGGGUAUUUAUUGAGCA 35 miR-150-3p CUGGUACAGGCCUGGGGGACAG 36 miR-150-5p UCUCCCAACCCUUGUACCAGUG 37 miR-150 precursor CUCCCCAUGGCCCUGUCUCCCAACCCUUGUACCAGUGCUGGGCUCAGACCCUGGUACAGGCCUGGGGGACAGGGACCUGGGGAC

As used herein, the term "nucleic acid" is used for nucleic acids, including both RNA, DNA, and RNA/DNA (chimera). In addition, the DNA includes all of cDNA, genomic DNA, and synthetic DNA. In addition, the RNA includes all of total RNA, mRNA, rRNA, miRNA, siRNA, snoRNA, snRNA, non-coding RNA and synthetic RNA. In the present specification, "synthetic DNA" and "synthetic RNA" are artificially produced based on a predetermined base sequence (either a natural sequence or a non-natural sequence), for example, using an automatic nucleic acid synthesizer. refers to DNA and RNA. In this specification, "non-natural sequence" is intended to be used in a broad sense, and is different from the natural sequence, for example, a sequence containing substitution, deletion, insertion and / or addition of one or more nucleotides (i.e., , variant sequences), sequences comprising one or more modified nucleotides (ie, modified sequences), and the like. Also, in the present specification, polynucleotides are used interchangeably with nucleic acids.

As used herein, the term "cognitive disorder" or "cognitive disorder" refers to any disorder that affects mental functions, including impairments in memory, learning, cognition, perception, attention, communication, motor coordination, and intellectual abilities. .

In some aspects, the cognitive impairment is AD, MCI, amnesia, cortical basal syndrome, dementia, lewy body dementia, frontotemporal dementia, primary progressive aphasia, progressive nondegenerative aphasia, progressive supranuclear palsy, senescence, meaning dementia, severe cognitive impairment, subcortical dementia, vascular dementia, amyotrophic lateral sclerosis (ALS) and/or logopanic progressive aphasia.

According to a preferred embodiment of the present invention, the cognitive disorder is Alzheimer's disease (AD).

According to a preferred embodiment of the present invention, the cognitive impairment is mild cognitive impairment (Mild Cognitive Impairment, MCI).

In this specification, the term "identification" or "identification" refers to distinguishing a specific object from other objects using one or more characteristics, and includes detection, discrimination, separation, classification, and diagnosis. (diagnosis) is used in the meaning included.

As used herein, the term "diagnosis" is used to determine or predict whether a subject (subject) has, is suffering from, or is at risk of contracting or suffering from a disease (e.g., is genetically predisposed). It means a method that can be used, and as a result, a target suitable for treatment can be identified.

In some aspects, treatment can be therapeutic (eg, administered to a subject exhibiting one or more symptoms associated with a disease or disorder). In some aspects, treatment can be prophylactic (eg, administered to a subject at risk to prevent and/or reduce the development of a disease or disorder).

According to a preferred embodiment of the present invention, the subject with cognitive impairment has a reduced expression level of the miRNA compared to a normal case.

As described herein, one skilled in the art can make a diagnosis based on one or more diagnostic markers (e.g., miR-150-3p, miR-150-5p, or miR-150 precursors), wherein the diagnostic markers The presence, absence, amount, or change in amount indicates: the presence, severity, or absence of a disease or condition. In some aspects, an increase in the relative expression ratio of miR-150-3p/precursor and/or a decrease in the relative expression ratio of miR-150-5p/precursor (e.g., in a separate sample from the subject) is a cognitive impairment ( eg Alzheimer's disease).

According to a preferred embodiment of the present invention, the subject has an increase in the relative expression ratio of miR-150-3p/precursor, a decrease in the relative expression ratio of miR-150-5p/precursor, or a decrease in the relative expression ratio of miR-150-3p/miR-150-3p/miR-150- Indicates an increase in the relative expression ratio between 5p.

According to a preferred embodiment of the present invention, the relative expression ratio is as follows:

(a) The miR-150-3p/precursor relative expression ratio is 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more , an increase of 100% or more, 110% or more, 120% or more, 150% or more, or 200% or more;

(b) The miR-150-5p/precursor relative expression ratio is 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more , a reduction of at least 100%, at least 110%, at least 120%, at least 150%, or at least 200%; or

(c) the miR-150-3p/miR-150-5p relative expression ratio is 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more , an increase of 90% or more, 100% or more, 110% or more, 120% or more, 150% or more, or 200% or more.

According to a preferred embodiment of the present invention, the increase in the relative expression ratio of miR-150-3p/precursor, the decrease in the relative expression ratio of miR-150-5p/precursor, or between miR-150-3p/miR-150-5p An increase in the relative expression rate of β distinguishes normal cases from subjects with cognitive impairment.

According to a preferred embodiment of the present invention, the increase in the relative expression ratio of miR-150-3p/precursor, the decrease in the relative expression ratio of miR-150-5p/precursor, or between miR-150-3p/miR-150-5p An increase in the relative expression ratio of may indicate that cognitive impairment is progressing.

The term "diagnosis" as used herein does not imply the ability to determine with 100% accuracy the presence or absence of a particular disease or disorder or that a given process or outcome is more likely not to occur. Instead, those skilled in the art will understand that the term “diagnosis” refers to an increased probability that a particular disease or disorder exists in a subject.

In some aspects, the term “diagnosis” includes one or more diagnostic methods for identifying a subject having a cognitive disorder (eg, those described herein).

In the present specification, the term "sample", "sample" or "sample" is not limited as long as it is naturally or artificially separated from a subject (subject) and includes genetic information related to cognitive impairment of the subject, preferably blood separated outside the body. , It can be separated from plasma, serum, cerebrospinal fluid, urine, feces, cells, hair, etc., and more preferably, blood, plasma, serum, etc. separated outside the body can be used.

According to a preferred embodiment of the present invention, the sample is a blood sample.

According to a preferred embodiment of the present invention, the blood sample contains platelets.

The method of providing information for identifying a subject with cognitive impairment suitable for the treatment of cognitive impairment of the present invention may use a variety of well-known test methods, such as hybridization, immunoassay, or gene amplification. can and is not limited thereto.

The hybridization method confirms the presence of miRNA using a probe.

As used herein, the term “probe” refers to a natural or modified monomer or linear oligomer of linkages, including deoxyribonucleotides and ribonucleotides, capable of specifically hybridizing to a target nucleotide sequence, and naturally existing or artificially synthesized. The probe of the present invention is preferably single-stranded and is an oligodeoxyribonucleotide.

When the method of the present invention is carried out in a microarray method among hybridization methods, the above probe is used as a hybridizable array element and is immobilized on a substrate. Preferred substrates include rigid or semi-rigid supports such as membranes, filters, chips, slides, wafers, fibers, magnetic or non-magnetic beads, gels, tubing, plates, polymers, microparticles and capillaries. The hybridization array elements are arranged and immobilized on the substrate. This immobilization is carried out by chemical bonding methods or covalent bonding methods such as UV. For example, the hybridization array element may be bonded to a glass surface modified to include an epoxy compound or an aldehyde group, and may also be bonded to a polylysine-coated surface by UV. In addition, the hybridization array element may be coupled to a substrate through a linker (eg, ethylene glycol oligomer and diamine).

Meanwhile, sample DNA applied to the microarray of the present invention can be labeled and hybridized with array elements on the microarray. Hybridization conditions can be variously changed. In addition, the degree of hybridization may be detected and analyzed in various ways depending on the labeling substance.

The label of the probe may provide a signal allowing detection of hybridization, which may be linked to an oligonucleotide. Suitable labels include fluorophores (e.g., fluorescein, phycoerythrin, rhodamine, lissamine, and Cy3 and Cy5 (Pharmacia)), terminal deoxynucleotidyl transferase (TdT), chromophores, chemiluminescent provided, however, that magnetic particles, radioactive isotopes (P32 or S35), mass labels, electron dense particles, enzymes (alkaline phosphatase or horseradish peroxidase), cofactors, substrates for enzymes, heavy metals (e.g., gold), and Antibodies, streptavidin, biotin, digoxigenin and haptens with specific binding partners such as chelating groups, but are not limited thereto. Labeling is performed by various methods commonly practiced in the art, such as the nick translation method, the random priming method (Multiprime DNA labeling systems booklet, “Amersham” (1989)), and the kination method (Maxam & Gilbert, Methods in Enzymology, 65:499 (1986)). The label provides a signal that can be detected by fluorescence, radioactivity, chromometry, gravimetry, X-ray diffraction or absorption, magnetism, enzymatic activity, mass analysis, binding affinity, hybridization radiofrequency, nanocrystals.

Nucleic acid samples to be analyzed in the hybridization method can be prepared using RNA obtained from various biological samples (biosamples). Hybridization reaction-based analysis can also be performed by labeling the cDNA to be analyzed instead of the probe.

When using a probe, the probe is hybridized with the cDNA molecule. In the present invention, suitable hybridization conditions can be determined in a series of steps by an optimization procedure. This procedure is carried out as a series of procedures by those skilled in the art to establish a protocol for use in the laboratory. For example, conditions such as temperature, concentration of components, hybridization and washing time, buffer components and their pH and ionic strength depend on various factors such as probe length and GC amount and target nucleotide sequence. Detailed conditions for hybridization are described in Joseph Sambrook, et al., Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. (2001); and M.L.M. Anderson, Nucleic Acid Hybridization, Springer-Verlag New York Inc. N.Y. (1999).

After the hybridization reaction, a hybridization signal generated through the hybridization reaction is detected. Hybridization signals can be performed in various ways depending on the type of label attached to the probe, for example. For example, when a probe is labeled by an enzyme, hybridization can be confirmed by reacting a substrate of the enzyme with a hybridization reaction product. Enzyme/substrate combinations that can be used include peroxidases (e.g., horseradish peroxidase) with chloronaphthol, aminoethylcarbazole, diaminobenzidine, D-luciferin, lucigenin (bis-N-methylacridinium nitrate). rate), resorufin benzyl ether, luminol, amplex red reagent (10-acetyl-3,7-dihydroxyphenoxazine), HYR (p-phenylenediamine-HCl and pyrocatechol), TMB (tetramethylbenzidine), ABTS (2, 2'-Azine-di[3-ethylbenzthiazoline sulfonate]), o-phenylenediamine (OPD) and naphthol/pyronine; alkaline phosphatase with bromochloroindolyl phosphate (BCIP), nitro blue tetrazolium (NBT), naphthol-AS-B1-phosphate and ECF substrate; These include glucose oxidase, t-NBT (nitroblue tetrazolium), and m-PMS (phenzaine methosulfate). When the probe is labeled with gold particles, it can be detected by a silver staining method using silver nitrate.

When the hybridization signal to the miRNA sequence in the biological sample is up-regulated or down-regulated compared to the normal sample, cognitive disorder is diagnosed.

The method of providing information for identifying a cognitive disorder subject or diagnosing a cognitive disorder of the present invention may be performed by an immunoassay method. The immunoassay method includes radioimmunoassay, radioimmunoprecipitation, immunoprecipitation, enzyme-linked immunosorbent assay (ELISA), capture-ELISA, inhibition or hard material assay, sandwich assay, flow cytometry, immunofluorescence staining and immunophile including, but not limited to, chemical tablets. The immunoassay method is Enzyme Immunoassay, E. T. Maggio, ed., CRC Press, Boca Raton, Florida, 1980; Gaastra, W., Enzyme-linked immunosorbent assay (ELISA), in Methods in Molecular Biology, Vol. 1, Walker, J.M. ed., Humana Press, NJ, 1984; and Ed Harlow and David Lane, Using Antibodies: A Laboratory Manual, Cold Spring Harbor Laboratory Press, 1999, incorporated herein by reference.

The method of providing information for identifying a subject with cognitive disorder or diagnosing cognitive disorder of the present invention may be performed by a gene amplification method. Detection of miRNA using a gene amplification method can be performed using various methods known in the art, and in this case, miRNA primers or probes can be used.

In the case of using primers, a gene amplification reaction is performed to examine the expression level of the miRNA gene. Since the present invention analyzes the level of expression of the gene, the level of expression of the gene of the marker is determined by examining the amount of mRNA of the marker in a sample to be analyzed (eg, a blood sample including platelets). Therefore, in the present invention, in principle, a gene amplification reaction is performed using mRNA in a biological sample as a template and primers binding to mRNA or cDNA.

First, total RNA is isolated from a sample to obtain mRNA. Isolation of total RNA can be performed according to conventional methods known in the art (see: Sambrook, J. et al., Molecular Cloning. A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (2001); Tesniere, C. et al., PlantMol. Biol. Rep., 9:242 (1991) Ausubel, F.M. et al., Current Protocols in Molecular Biology, John Willey & Sons (1987) and Chomczynski, P. et al., Anal. Biochem. 162:156 (1987)). For example, total RNA in cells can be easily isolated using Trizol.

Then, cDNA is synthesized from the isolated mRNA, and this cDNA is amplified. Since the total RNA of the present invention is isolated from human samples, mRNA has a poly-A tail at the end, and cDNA can be easily synthesized using oligo dT primers and reverse transcriptase using this sequence characteristic ( References: PNAS USA, 85:8998 (1988) Libert F, et al., Science, 244:569 (1989) and Sambrook, J. et al., Molecular Cloning. A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (2001)). Subsequently, the synthesized cDNA is amplified through a gene amplification reaction. The primer used in the present invention is hybridized or annealed to one site of the template to form a double-stranded structure. Conditions of nucleic acid hybridization suitable for forming such a double-stranded structure are Joseph Sambrook, et al., Molecular Cloning, A Laboratory Manual, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y. (2001) and Haymes, B. D., et al., Nucleic Acid Hybridization, A Practical Approach, IRL Press, Washington, D.C. (1985).

A variety of DNA polymerases can be used for the amplification of the present invention, including the “Klenow” fragment of E. coli DNA polymerase I, thermostable DNA polymerase and bacteriophage T7 DNA polymerase. Polymerases are thermostable DNA polymerases available from various bacterial species, including Thermus aquaticus (Taq), Thermusthermophilus (Tth), Thermusfiliformis, Thermisflavus, Thermococcus literalis, and Pyrococcus furiosus (Pfu). When carrying out the polymerization reaction, it is preferable to provide the reaction vessel with components necessary for the reaction in excess. An excess of components required for the amplification reaction means an amount to the extent that the amplification reaction is not substantially limited by the concentration of the components. It is desirable to provide cofactors such as Mg ²⁺ , dATP, dCTP, dGTP and dTTP to the reaction mixture in such a way that the desired degree of amplification can be achieved. All enzymes used in the amplification reaction may be active under the same reaction conditions. In fact, the buffer allows all enzymes to approach optimal reaction conditions. Therefore, the amplification process of the present invention can be carried out in a single reactant without changing conditions such as addition of reactants.

In the present invention, annealing or hybridization is performed under stringent conditions enabling specific binding between the target nucleotide sequence and the primer. Stringent conditions for annealing are sequence-dependent and vary depending on environmental variables.

As used herein, the term “amplification reaction” refers to a reaction that amplifies a nucleic acid molecule. Various amplification reactions have been reported in the art, including polymerase chain reaction (hereinafter referred to as PCR) (U.S. Patent Nos. 4,683,195, 4,683,202, and 4,800,159), reverse transcription-polymerase chain reaction (hereinafter referred to as RT-PCR) (Sambrook et al., Molecular Cloning. A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (2001)), Miller, H. I. (WO 89/06700) and Davey, C. et al. (EP 329,822) method, ligase chain reaction chain reaction; LCR) (17, 18), Gap-LCR (WO 90/01069), repair chain reaction (EP 439,182), transcription-mediated amplification (TMA) (19) (WO 88/10315), self sustained sequence replication (20) (WO 90/06995), selective amplification of target polynucleotide sequences (U.S. Patent No. 6,410,276), including, but not limited to, consensus sequence primed polymerase chain reaction (CP-PCR) (US Pat. No. 4,437,975) and loop-mediated isothermal amplification (LAMP). don't Other amplification methods that may be used are described in U.S. Patent Nos. 5,242,794, 5,494,810, 4,988,617 and U.S. Patent No. 09/854,317. The gene amplification method of the present invention is performed according to the PCR (polymerase chain reaction) disclosed in US Patent Nos. 4,683,195, 4,683,202 and 4,800,159.

PCR is the most well-known nucleic acid amplification method, and many variations and applications thereof have been developed. For example, touchdown PCR, hot start PCR, nested PCR and booster PCR have been developed by modifying traditional PCR procedures to enhance the specificity or sensitivity of PCR. In addition, real-time PCR, differential display PCR (DD-PCR), rapid amplification of cDNA ends (RACE), multiplex PCR, inverse polymerase chain reaction chain reaction (IPCR), vectorette PCR, thermal asymmetric interlaced PCR (TAIL-PCR) and multiplex PCR have been developed for specific applications. For details on PCR, see McPherson, M.J., and Moller, S.G. PCR. BIOS Scientific Publishers, Springer-Verlag New York Berlin Heidelberg, N.Y. (2000), the teachings of which are incorporated herein by reference.

Primers used in the gene amplification method in the present invention may be oligonucleotides having a sequence complementary to the cDNA sequence of the miRNA. As used herein, the term “primer” refers to a single-strand capable of acting as a starting point for template-directed DNA synthesis under suitable conditions (ie, four different nucleoside triphosphates and polymerases) in a suitable buffer at a suitable temperature. It may mean an oligonucleotide. The suitable length of a primer will vary depending on various factors, such as temperature and use of the primer, but will typically be 15-30 nucleotides. Shorter primer molecules generally require lower temperatures to form a sufficiently stable hybrid complex with the template.

The sequence of the primer does not have to have a sequence completely complementary to a part of the sequence of the template, and it is sufficient to have sufficient complementarity within the range of hybridizing with the template to perform the specific function of the primer. Therefore, the primer set in the present invention does not have to have a sequence perfectly complementary to the cDNA sequence of the marker as a template, and it is sufficient to have sufficient complementarity within the range in which the primer can function as a primer by hybridizing to this sequence. Preferably, the primer used in the present invention has a sequence perfectly complementary to the cDNA sequence of the marker.

The design of such primers can be easily performed by those skilled in the art by referring to the cDNA sequence of the miRNA, for example, using a primer design program (eg, PRIMER 3 program).

The amplified cDNA of the marker can be analyzed by a suitable method to examine the expression level of the marker gene. For example, the expression level of the marker gene can be investigated by performing gel electrophoresis on the amplification reaction product described above and observing and analyzing the band formed as a result.

Through this amplification reaction, when the expression of the gene in the sample is higher or lower than that in the sample of the normal group, cognitive disorder can be diagnosed.

In the present specification, the miRNA is a biomolecule whose expression is reduced or increased in cognitive disorders. As used herein, the term "high expression (or overexpression)" or "up-regulation" refers to a case in which the expression level of a target nucleotide sequence or protein in a biological sample to be investigated is higher than that of a normal sample. . For example, expression analysis methods commonly used in the art, such as the RT-PCR method or the ELISA method (see Sambrook, J. et al., Molecular Cloning. A Laboratory Manual, 3rd ed. Cold Spring Harbor Press (2001)) When expression analysis is performed according to, it means a case where the expression is analyzed to be high. As used herein, the term “low expression”, “reduction of expression” or “down-regulation” refers to a case in which the expression level of a target nucleotide sequence or protein in a biological sample to be investigated is low compared to a normal sample do. For example, as a result of analysis according to the above-described diagnostic method, when the miRNA of the present invention is expressed at a higher or lower level by 10% or more compared to a normal sample, it is judged as “high expression” or “low expression” in the present invention, It is provided as information for determining cognitive impairment.

According to one embodiment of the present invention, the miRNA included in the identification or diagnosis method of the present invention is up-regulated or down-regulated in cognitively impaired patients compared to normal people, and 10% It was confirmed that it was up-regulated or down-regulated by more than 50%, preferably more than 50%.

According to a preferred embodiment of the present invention, the information providing method further comprises providing information on a cognitive disorder therapeutic agent to be administered to a subject with cognitive disorder.

According to a preferred embodiment of the present invention, the therapeutic agent for cognitive disorders is miR-150-3p, miR-150-5p, miR-150 precursor, miRNA activator activating miR-150-5p, miR-150-3p activator a miRNA activator that inhibits miR-485, a miRNA inhibitor that inhibits miR-485, aducanumab, galantamine, rivastigmine, donepezil, or memantine, or any of these that includes combinations.

Since the subject of the present invention has reduced expression of miR-150-3p, miR-150-5p, miR-150 precursor, etc., it is directly administered to the subject or an activator capable of activating the miRNA is administered to recognize the above. It can help treat the disorder.

According to a preferred embodiment of the present invention, the miR-485 is miR-485-3p.

According to a preferred embodiment of the present invention, the miR-485-3p includes 5'-GUCAUACACGGCUCUCCUCUCU-3' (SEQ ID NO: 1).

According to a preferred embodiment of the present invention, the miR-485 inhibitor is a sequence complementary to miR-485.

According to a preferred embodiment of the present invention, the miR-485 inhibitor is 5'-UGUAUGA-3' (SEQ ID NO: 2), 5'-GUGUAUGA-3' (SEQ ID NO: 3), 5'-CGUGUAUGA- 3' (SEQ ID NO: 4), 5'-CCGUGUAUGA-3' (SEQ ID NO: 5), 5'-GCCGUGUAUGA-3' (SEQ ID NO: 6), 5'-AGCCGUGUAUGA-3' (SEQ ID NO: 7), 5'-GAGCCGUGUAUGA-3' (SEQ ID NO: 8), 5'-AGAGCCGUGUAUGA-3' (SEQ ID NO: 9), 5'-GAGAGCCGUGUAUGA-3' (SEQ ID NO: 10), 5'-GGAGAGCCGUGUAUGA-3' (SEQ ID NO: 11), 5'-AGGAGAGCCGUGUAUGA-3' (SEQ ID NO: 12), 5'-GAGGAGAGCCGUGUAUGA-3' (SEQ ID NO: 13), 5'-AGAGGAGAGCCGUGUAUGA- 3' (SEQ ID NO: 14), 5'-GAGAGGAGAGCCGUGUAUGA-3' (SEQ ID NO: 15); 5'-UGUAUGAC-3' (SEQ ID NO: 16), 5'-GUGUAUGAC-3' (SEQ ID NO: 17), 5'-CGUGUAUGAC-3' (SEQ ID NO: 18), 5'-CCGUGUAUGAC- 3' (SEQ ID NO: 19), 5'-GCCGUGUAUGAC-3' (SEQ ID NO: 20), 5'-AGCCGUGUAUGAC-3' (SEQ ID NO: 21), 5'-GAGCCGUGUAUGAC-3' (SEQ ID NO: 22), 5'-AGAGCCGUGUAUGAC-3' (SEQ ID NO: 23), 5'-GAGAGCCGUGUAUGAC-3' (SEQ ID NO: 24), 5'-GGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 25), 5'-AGGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 26), 5'-GAGGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 27), 5'-AGAGGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 28), and It is selected from the group consisting of 3' (SEQ ID NO: 29).

According to another aspect of the present invention, the present invention provides a miRNA selection method for determining whether a subject has cognitive impairment, comprising the following steps:

(1) calculating a sequential score for one or more miRNAs extracted from a sample isolated from the subject (the sequential score identifies sequentially upregulated or downregulated miRNAs,

Sequential Score= {(1 - P1) x FC1} + {(1 - P2) x FC2};

P1 = p value of Student's t using expression in young normal group and old normal group,

FC1 = Log2 (senior normal group expression/young normal group expression),

P2 = p value of Student's t using expression in elderly normal and diseased groups,

FC2 = Log2 (disease expression/elderly normal expression)); and

(2) selecting one or more miRNAs with an increased sequential score, where an increased sequential score indicates increased expression of the miRNA.

According to another aspect of the present invention, the present invention provides a kit for diagnosing cognitive disorders, comprising the following components:

(a) miR-873-5p, miR-215-5p, miR-642a-5p, miR-4731-5p, miR-95-3p, miR-150-3p, miR-150-5p, miR-150 precursors and One or more miRNA amplification primers selected from the group consisting of combinations thereof; and

(b) Instructions for providing information for the identification of subjects suitable for treatment of cognitive impairment.

According to another aspect of the present invention, the present invention is a pharmaceutical composition for preventing or treating cognitive disorder for administration to a subject with cognitive disorder diagnosed using the information providing method or kit, wherein the The composition is miR-873-5p, miR-215-5p, miR-642a-5p, miR-4731-5p, miR-95-3p, miR-150-3p, miR-150-5p, miR-150 precursor or the above Provided is a pharmaceutical composition comprising a miRNA activator as an active ingredient.

The pharmaceutical composition according to the present invention may be administered orally or parenterally.

In the case of parenteral administration, such as intravenous injection, transdermal administration, subcutaneous injection, intramuscular injection, intravitreal injection, eye drop administration, intracerebroventricular injection, intrathecal injection (intrathecal injection), intraamniotic injection, intraarterial injection, intraarticular injection, intracardiac injection, intracavernous injection, intracerebral injection ( intracerebral injection), intracisternal injection, intracoronary injection, intracranial injection, intrathecal injection, epidural injection, intrahippocampal injection ), intranasal injection, intraosseous injection, intraperitoneal injection, intrathoracic injection, intraspinal injection, intrathoracic injection, intrathymic injection, intrauterine injection, intravaginal injection, intraventricular injection, intravesical injection, subconjunctival injection, intratumor It can be administered by intratumoral injection, local injection and intraperitoneal injection.

The pharmaceutical composition of the present invention may include a pharmaceutically acceptable carrier. As used herein, the term "pharmaceutically acceptable carrier" means a carrier or diluent that does not significantly stimulate living organisms and does not inhibit the biological activity and properties of the administered component. The pharmaceutically acceptable carrier in the present invention may be saline, sterile water, Ringer's solution, buffered saline, dextrose solution, maltodextrin solution, glycerol, ethanol, and one or a mixture of one or more of these components, If necessary, other conventional additives such as antioxidants, buffers, and bacteriostatic agents may be added, and formulated into an injection suitable for injection into tissues or organs. In addition, it may be formulated as an isotonic sterile solution or, in some cases, as a dry preparation (particularly a freeze-dried preparation) that can be an injectable solution by adding sterile water or physiological saline. In addition, a target organ-specific antibody or other ligand may be used in combination with the carrier so as to specifically act on the target organ. Suitable formulations known in the art may be used those disclosed in the literature (Remington's Pharmaceutical Science, Mack Publishing Company, Easton PA).

In addition, preferably, the composition of the present invention may further include fillers, excipients, disintegrants, binders, lubricants, and the like. In addition, the composition of the present invention can be formulated using methods known in the art to provide rapid, sustained or delayed release of the active ingredient after administration to a mammal.

In the present invention, "administration" means introducing the composition of the present invention to a patient by any suitable method, and the administration route of the composition of the present invention is administered through various oral or parenteral routes as long as it can reach the target tissue. It can be.

For example, the composition of the present invention can be administered by intramuscular or intraperitoneal injection in clinical administration.

For injection, it may preferably be formulated in a pharmacologically compatible buffer such as Hank's solution, Ringer's solution, or physiological saline buffer. For transmucosal administration, non-penetrating agents suitable for the barrier to be passed are used in the formulation. Such impermeable agents are generally known in the art.

Formulations for parenteral administration include sterilized aqueous solutions, non-aqueous solvents, suspensions, emulsions, and the like. Propylene glycol, polyethylene glycol, vegetable oils such as olive oil, and injectable esters such as ethyl oleate may be used as non-aqueous solvents and suspending agents.

As used herein, "effective amount" means an amount necessary to delay or completely stop the onset or progression of a specific disease to be treated, and includes the therapeutic agent for cognitive disorders or the miRNA and/or the pharmaceutical composition of the present invention. The effective amount of the miRNA activator refers to an amount required to achieve the effect of preventing, improving or treating cognitive disorders. Therefore, the effective amount depends on the type of disease, the severity of the disease, the type and amount of other components contained in the composition, and the patient's age, weight, general health condition, sex and diet, administration time, administration route, treatment period, concurrent use It can be adjusted according to various factors including the drug used. It is obvious to those skilled in the art that an appropriate total daily amount can be determined by a treating physician within the scope of sound medical judgment.

For purposes of this invention, a specific therapeutically effective amount for a particular patient is determined by the type and extent of the response to be achieved, the specific composition, including whether other agents are used as the case may be, the patient's age, weight, general health condition, and gender. And it is preferable to apply differently according to various factors including diet, administration time, administration route and secretion rate of the composition, treatment period, drugs used together with or concurrently used with the specific composition, and similar factors well known in the medical field.

As used herein, "treatment" refers to an approach for obtaining beneficial or desirable clinical results. For purposes of this invention, beneficial or desired clinical results include, but are not limited to, alleviation of symptoms, reduction of disease extent, stabilization of disease state (i.e., not worsening), delay or slowing of disease progression, disease state improvement or palliation and relief (partial or total), detectable or undetectable. "Treatment" can also mean prolonging the survival rate compared to the expected survival rate if not receiving the treatment. “Treatment” refers to both therapeutic treatment and prophylactic or prophylactic measures. The treatments include treatment required for disorders that have already occurred as well as disorders that are prevented. “Relieving” a disease means that the extent of the disease state and/or undesirable clinical signs are reduced and/or the time course of the disease is slowed or lengthened, compared to no treatment. do.

The features and advantages of the present invention are summarized as follows:

(i) The present invention provides a method for providing information for identifying a subject with cognitive impairment suitable for treatment of cognitive impairment, comprising measuring the expression level of miRNA obtained from an isolated sample of the subject.

(ii) The method of providing information for identification or diagnosis of the present invention effectively and accurately diagnoses or treats cognitive disorders (eg, AD) associated with reduced levels of miRNA (eg, miR-150) expression. It can be used as information for

Figure 1 shows the NGS (Next-Generation Sequencing) results of miRNAs extracted from platelet samples. 1A shows the raw read counts of 12 patient samples. 1B shows the number of adapter leads filtered and cut. 1C shows mapped read values for 12 patient samples. 1D shows the known read values for a sample of 12 patients. Figure 1e shows the number of miRNAs per sample. Figure 1f shows the average number of reads per sample. The first 5 bars represent normal young patients, the 6th to 8th bars represent normal elderly patients, the 9th to 11th bars represent Mild Cognitive Impairment (MCI) patients, and the 12th bar represents Alzheimer's disease patients.
2 shows the result of TMM (Trimmed means of M values) normalization processing. TMM normalization was performed after the NGS process. Bars 1 to 5 represent normal young people, bars 6 to 8 represent normal old people, bars 9 to 11 represent MCI, and bars 12 represent Alzheimer's disease. Figure 2a shows the number of reads per sample and 2b shows the normalized samples.
Figure 3 shows total miRNA expression for 12 patient samples. 3A shows a heatmap of the relative expression of 1,850 miRNAs from 12 patient samples. Relative expression is the Log2 value of dividing the TMM value of each miRNA by the mean value. Hierarchical sample clustering was used to analyze miRNAs. 3B shows a heatmap visualization of sample-to-sample correlation test results. Coefficient values are derived by two-tailed Pearson's correlation test. 3C shows PCA analysis performed using 1,850 miRNA expression values.
Figure 4 shows sequentially expressed miRNAs. Figure 4a shows 250 sequentially upregulated miRNAs (SUmiR) and sequentially downregulated (SDmiR). Dotted lines represent thresholds for SUmiR and SDmiR selection. Figure 4b shows a heatmap of the expression values of 13 SUmiRs and 7 SDmiRs. Relative expression is the Log2 value of dividing the TMM value of each miRNA by the mean value. For miRNA and sample clustering hierarchical clustering was used. The horizontal dotted line indicates the cut portion when the highest rank was cut as a result of miRNA clustering. The vertical dotted line represents the cut portion when it is cut to the highest order as a result of sample clustering. 4C shows two-dimensional principal component analysis (PCA). PCA was performed using 13 SUmiR and 7 SDmiR expression values.
Figure 5 shows the expression patterns of sequentially down-regulated miRNAs. Figure 5a shows the relative expression of seven SUmiRs. Figure 5b shows the relative expression patterns of miR-150-3p and miR-150-5p in normal young, normal elderly patients, and MCI and AD patients. Relative expression is the value of Log2 dividing the TMM value of miR-150 by the mean value. As a statistical test, an unpaired student's t test was performed. A single asterisk signifies a p-value <0.05. A double asterisk signifies a p-value <0.01. Results from P1 to P4 were p values of unpaired student's t test. P1 was the comparison result between the normal young group and the normal old group. P2 was the comparison result between normal and diseased groups. P3 was the comparison result between the normal elderly group and the diseased group. P4 was the comparison result between normal and diseased groups. Figure 5c shows the correlation between the expression of sequentially down-regulated miRNAs and the age of the patients.
P represents the p value generated by a two-tailed Pearson correlation test and CC represents the correlation coefficient value of the same test.
6 shows the expression patterns of sequentially expressed miRNAs in human brain. Figure 6a shows a heatmap of 6 matched miRNAs from 13 sequentially upregulated miRNAs and 7 sequentially downregulated miRNAs. Relative expression is the Log2 value of dividing the TMM value of each miRNA by the mean value. For miRNA and sample clustering hierarchical clustering was used. 6B shows the results of two-dimensional principal component analysis (PCA). PCA was performed using the expression values of 6 miRNCs matched at 13 SUmiRs and 7 SDmiRs. Figure 6c shows the putative expression pattern of the miR-150 precursor. The estimated expression is the sum of the expression values of the 3p and 5p strands of mature RNA. ¹ P is the p value of the unpaired student's t test result. 6d shows the utilization rates of 3p and 5p strands relative to the precursor miR-150. The left bar represents early AD and the right bar represents late AD. ¹ P is the p value of the unpaired student's t test result. Figure 6e shows the difference in the expression ratio of miR-150-3p to miR-150-5p. ¹ P is the p value of the unpaired student's t test result.
Figure 7 shows the expression pattern of matched SDmiR in brain tissue. Figure 7a shows the expression patterns of hsa-miR-150-3p and hsa-miR-150-5p in early (left column) and late (right column) stages of AD in brain tissue. Figure 7b shows the expression patterns of hsa-miR-642a-5p and hsa-miR-873-5p in AD early (left column) and late (right column) stages.
Figure 8 shows the expression patterns of precursor and mature forms of miR-150. Figure 8a shows the correlation analysis between the 3p and 5p strand mature miRNAs of the miR-150 precursor and the correlation analysis between each mature miRNA and age. The line in each plot represents the regression line of the logistic regression analysis results. ¹ P represents the p value generated by the two-tailed Pearson correlation test, and ² CC represents the correlation coefficient value of the same test. The calculation formula in the box on the right is a calculation formula using slope and intercept in logistic regression analysis. Figure 8b shows the utilization of 3p and 5p relative to the precursor. ¹ P is the p value of the unpaired student's t test result. Normal young patients are the first column from the left, normal elderly patients are the second column from the left, MCI patients are the third column from the left, and AD patients are the right column. Figure 8c shows the validation of the diagnostic method disclosed herein using the proportion of mature RNA of miR-150. "Normal All" in the box plot on the left is a group that includes normal sore throat and elderly people. ¹ P in the left box plot is the p value of the unpaired student's t test result. The ² AUC values in the ROC plot on the right represent the area under the curve. The dotted line in the left plot is the boundary line generated by the ROC analysis in the right figure and coincides with the diamond points in both plots. Figure 8d shows the predictions and expression patterns of miR-150 precursors. The estimated expression is the sum of the expression values of the 3p and 5p strands of mature RNA. ¹ P is the p value of the unpaired student's t test result. The line on the right plot represents the regression line of the logistic regression analysis results. ² P represents the p value generated from the two-tailed Pearson correlation test, and ³ CC represents the value of the correlation coefficient of the same test. 8E shows a comparison of 3p and 5p expression levels of miR-150 in 12 patient platelet samples. ¹ P is the p value of the unpaired student's t test result. The multiple at the bottom of each box represents the relative multiple assuming the average multiple of 3p strands is 1x. Figure 8f shows a comparison of the expression levels of 3p and 5p in various tissues from published data sets. P is the p value of the unpaired student's t test result. The multiple at the bottom of each box represents the relative multiple assuming the average multiple of 3p strands is 1x. 8G compares the expression of 3p and 5p in whole blood. P is the p value of the unpaired student's t test result. The bottom multiple of each box represents the relative multiple assuming the average multiple of 3p strands is 1x. Figure 8h compares the expression of 3p and 5p in the brain frontal cortex. P is the p value of the unpaired student's t test result. The multiple at the bottom of each box represents the relative multiple assuming the average multiple of 3p strands is 1x. Figure 8i compares the expression of 3p and 5p in plasma exosomes. P is the p value of the unpaired student's t test result. The multiple at the bottom of each box represents the relative multiple assuming the average multiple of 3p strands is 1x. Figure 8j shows the correlation between miR-150-5p and miR-150-3p expression in whole blood (GSE46579), brain frontal cortex (GSE48552) and plasma exosomes (GSE97644). ¹ P represents the p value generated by the two-tailed Pearson correlation test, and ² CC represents the correlation coefficient value of the same test.

Hereinafter, the present invention will be described in more detail through examples. These examples are only for explaining the present invention in more detail, and it will be apparent to those skilled in the art that the scope of the present invention is not limited by these examples according to the gist of the present invention. .

Example

Currently, diagnosing Alzheimer's disease (AD) is difficult even for medical professionals, and there are no clear biomarkers. Therefore, the present inventors searched for miRNAs as biomarkers that can be the basis for treatment and diagnosis of AD. The patient study group was classified as a young normal group, an elderly normal group, or an AD group. The present inventors developed a method for discovering sequentially expressed miRNAs in order to distinguish sequentially expressed miRNAs in the three groups.

As a result, the sequentially expressed miRNAs showed a high correlation with the patient's age, and most of them showed expression patterns that differentiated young, old, and AD. In particular, the miRNA expression we uncovered showed a similar pattern in the brains of AD patients. One set of selected miRNAs was derived from the same precursor: expression of miR-150 was disease- and age-specific downregulated in both the 3p and 5p forms, and the precursors also showed the same pattern. The present inventors named the above result triple matching. The miR-150 precursors also found had AD-specific miRNA-unbalanced properties.

The present inventors developed a new AD diagnosis method using triple matching and miRNA- imbalance. The triple matching and miRNA imbalance-based relative ratio diagnosis method developed by the present inventors will be very useful in solving the problem of absolute diagnosis quantification based on biomarker expression. In addition, the present inventors' research results suggest the possibility of a therapeutic target for Alzheimer's disease. In the present specification, methods for diagnosing Alzheimer's disease and diagnostic biomarkers are disclosed.

As we age, natural memory impairment can occur. However, persistent problems with cognitive function and memory may cast doubt on the possibility of mild cognitive impairment (MCI). MCI refers to more severe changes in cognitive abilities, including memory and thinking, than the natural aging process. People with MCI are more likely to develop Alzheimer's disease or other dementias than people without MCI (1, 2). Although the cause of MCI is unclear, it is often caused by pathological changes in the brain that occur in the early stages of dementia, including Alzheimer's disease (3, 4, 5). When nerve cells in the brain die or do not function normally, memory and behavioral changes occur, which is called dementia.

AD is the most common type of dementia, accounting for 60% to 80% of dementia cases (6). Although many studies have been done on Alzheimer's disease, little is known about the exact physiological causes (7). Because Alzheimer's disease is a degenerative brain disease, it progresses slowly, making it very difficult for even medical professionals to identify and confirm Alzheimer's disease in patients (8). In general, diagnostic tests such as the Mini-Mental State Examination and Montreal Cognitive Assessment (MoCA) are performed to diagnose normal aging, MCI and AD, but they are not sufficient to differentiate between normal aging-induced cognitive decline and disease groups ( 9, 10, 11).

Thus, AD is primarily identified by abnormal accumulation of amyloid beta detected via cerebrospinal fluid (CSF) samples or brain imaging using positron emission tomography (PET). However, PET and CSF analysis can be very expensive for patients. Amyloid PET scans cost over US$3,000 (12). Alzheimer's disease is known to be a brain tissue disorder, and biochemical changes in Alzheimer's disease patients have been shown to occur not only in the brain but also in blood vessels and blood cells. Therefore, there have been many recent studies to establish blood-based biomarkers of AD (13, 14, 15).

Among these possible AD biomarkers, miRNAs are small RNAs that play a role in regulating the expression of genes post-transcriptionally in a sequence-specific manner. In particular, miRNAs show great potential in terms of stability and ease of detection in blood (16, 17). Additionally, the role of biomarkers in neurodegenerative diseases, including descriptions of disease etiology, is attracting research attention (18, 19, 20). Platelets provide some of the majority of miRNAs in the body (21, 22, 23). They can synthesize pre-miRNAs into a variety of mature miRNAs that can be synthesized into proteins, and specific platelet miRNA levels are associated with platelet responsiveness (24). Certain miRNAs also indicate an early onset of AD and appear to reflect Alzheimer's progression. Thus, platelet-derived miRNAs can be biomarkers that affect Alzheimer's diagnosis (25).

Example 1. Sample summary and NGS processing results

To evaluate whether the platelet-derived miRNAs disclosed herein can serve as biomarkers for cognitive impairment (eg, AD), whole blood samples from 12 patients were divided into three groups: normal elderly group 3 number of people; 5 ordinary young people; and 4 diseased elderly groups (3 MCI patients and 1 AD patient) were collected (Table 2). Among the diseased elderly group, one patient (EX_0002_M) agreed to the use of human-derived material rather than personal information. The average ages of the normal young, normal elderly and diseased elderly groups were 41, 69 and 78 years, respectively. Of the 12 patients, 8 had the APOE4 genotype and 1 (BO_0002_N) had the E3/E4 type. The buffy coat layer was separated by centrifugation using Histopaque. After washing the separated buffy coat, it was reacted with glycophorin A microbeads (MACS Co.) and CD45 microbeads (MACS Co.) to obtain pure platelets from which red blood cells and leukocytes were removed using an MS column (MACS Co.) did

RNA was collected through ethanol precipitation after dissolving platelets using iNtRON easy-BLUE (iNtRON Biotechnology, Gyeonggi-do, Korea) and chloroform. After checking the RNA concentration with a nano drop, the rRNA ratio (28s/18s) was checked through QC. Each sample passed QC results with rRNA ratios between 0.3 and 1.1 (28S/18S) and RNA integrity values between 3.1 and 8.8 (Table 3).

Next-Generation Sequencing (NGS) generated over 10 million raw read counts per sample with approximately 200 to 500 read counts per known miRNA (Table 4, Figures 1a-f and 2a-b). 1,850 miRNAs were detected in 12 samples (Fig. 3a-c).

NGS was performed at Chunlab (Seoul, Korea) using a NovaSeq 6000 system (Illumina, San Diego, CA, USA). Data were processed using ‘Raw fastq’ for miRNA sequencing. Adapters were removed from each read and filtering was performed to leave only reads 15-30 nucleotides in length. After mapping to GRCh38, miRNA read counts were derived by quantification with mirbase ver.22. TMM normalization was performed because the total number of reads for each sample was different. All data are available as GSE147714 in Gene Expression Omnibus (GEO), https://www.ncbi.nlm.nih.gov/geo/.

Expression profiles were confirmed for each sample using all detected miRNAs. All samples were TMM normalized and fold change for each miRNA was calculated. As a result of clustering analysis based on miRNA expression patterns using three methods (hierarchical clustering, inter-sample correlation, and PCA), the expression of a total of 1,850 miRNAs was sufficient to find correlations between age and disease status of patients. didn't fit

Patient ID Group ^1DX Gender Age APOE type Amyloid PET Result ^2MMSE Global ³ CDRs Education Year BO_0001_N Normal_Young Normal Male 40 E3/E3 - - - 16 BO_0002_N Normal_Young Normal Male 41 E3/E4 - - - 16 BO_0003_N Normal_Young Normal Male 46 E3/E3 - - - 16 BO_0004_N Normal_Young Normal Male 40 E3/E3 - - - 16 BO_0005_N Normal_Young Normal Male 36 E3/E3 - - - 16 SJ_0032_N Normal_Old Normal Female 62 E3/E3 - - - - SJ_0033_N Normal_Old Normal Female 76 E3/E3 - - - - SJ_0036_N Normal_Old Normal Male 70 E3/E3 - - - - EX_0002_M Disease_Old MCI - - - - - - - SB_0104_M Disease_Old MCI Female 73 - Positive 25 0.5 6 SB_0105_M Disease_Old MCI Female 76 - Positive 19 0.5 6 SB_0029_A Disease_Old AD Male 84 - Positive 24 0.5 16

Clinical information of 12 patients. ¹ DX was a diagnosis result using cognitive function and various clinical results by a clinical specialist. ² MMSE is an abbreviation for mini mental state examination. ³ CDR is an abbreviation for clinical dementia rate. Hyphenation means missing information.

[Table 3]

ID Group Raw read count After filter and cut adapt Mapped GRCh38 Known miRNA read counts Non zero miRNAs Reads per miRNA BO_0001_N Normal_Young 11,794,978 4,267,182 4,245,758 338,835 768 441.2 BO_0002_N Normal_Young 13,315,978 3,118,947 3,104,263 228,741 694 329.6 BO_0003_N Normal_Young 10,641,441 3,826,716 3,805,537 298,170 747 399.2 BO_0004_N Normal_Young 8,738,756 3,230,156 3,198,192 227,087 811 280.0 BO_0005_N Normal_Young 11,199,807 4,172,066 4,147,416 329,436 760 433.5 SJ_0032_N Normal_Old 11,182,456 3,935,876 3,754,185 272,861 1,193 228.7 SJ_0033_N Normal_Old 12,346,051 4,054,194 4,019,792 304,608 837 363.9 SJ_0036_N Normal_Old 13,702,610 3,204,432 3,188,667 255,371 632 404.1 SB_0104_M MCI 11,928,177 5,447,668 5,330,368 399,518 942 424.1 SB_0105_M MCI 10,482,429 4,729,432 4,685,874 344,400 877 392.7 EX_0002_M MCI 11,525,457 4,825,533 4,732,836 326,091 1,035 315.1 SB_0029_A AD 12,655,617 4,639,797 4,603,990 362,504 796 455.4

Example 2. Sequentially expressed miRNAs

The present inventors confirmed whether miRNA biomarkers of cognitive impairment could be derived from the miRNA expression data described above by using a sequential score that represents the gradual up or down expression of miRNAs derived from NGS treatment as follows. :

Sequential Score = {(1 - P1) x FC1} + {(1 - P2) x FC2}

where P1 = p of Student's t using expression in normal young and normal old groups,

FC1 = Log2 (normal old expression/normal young expression),

P2 = p of Student's t using expression in normal old and disease groups, and

FC2 = Log2 (disease expression/normal old expression).

Among a total of 1,850 miRNAs, FC1 and FC2 were named positive or negative sequentially upregulated miRNAs (SUmiR) or sequentially downregulated miRNAs (SDmiR). 250 sequentially upregulated miRNAs and 63 sequentially downregulated miRNAs were found (Fig. 4a). A list of sequentially down-regulated miRNAs (SDmiRs) is shown in Table 5.

miRNAs P1 FC1 P2 FC2 Score hsa-miR-873-5p 0.0324 -3.5 0.8064 -0.42 -3.4679 hsa-miR-215-5p 0.0327 -2.31 0.4226 -2.11 -3.4528 hsa-miR-150-5p 0.1354 -1.26 0.032 -2.15 -3.1706 hsa-miR-642a-5p 0.3607 -1.71 0.4226 -2.23 -2.3808 hsa-miR-95-3p 0.1555 -2.58 0.8674 -0.27 -2.2146 hsa-miR-150-3p 0.2615 -2.09 0.246 -0.86 -2.1919 hsa-miR-4731-5p 0.7833 -0.39 0.4226 -3.59 -2.1574 hsa-miR-4772-3p 0.1143 -1.85 0.4397 -0.78 -2.0756 hsa-miR-135a-3p 0.7281 -0.72 0.4226 -3.06 -1.9626 hsa-miR-342-3p 0.2182 -0.84 0.0399 -1.32 -1.9240 hsa-miR-6757-5p 0.4855 -1.24 0.4226 -2.11 -1.8563 hsa-miR-541-5p 0.6231 -0.47 0.234 -2.16 -1.8317 hsa-miR-668-3p 0.4982 -0.99 0.4226 -2.23 -1.7844 hsa-miR-200b-5p 0.5505 -0.98 0.4226 -2.23 -1.7281 hsa-miR-6893-5p 0.3517 -2.26 0.8064 -0.42 -1.5465 hsa-miR-652-5p 0.5569 -0.63 0.3309 -1.73 -1.4367 hsa-let-7i-3p 0.5347 -0.73 0.3488 -1.61 -1.3881 hsa-miR-138-5p 0.7924 -0.47 0.4226 -2.23 -1.3852 hsa-miR-6758-5p 0.8502 -0.33 0.4226 -2.23 -1.3370 hsa-miR-342-5p 0.2202 -1.28 0.5796 -0.75 -1.3134 hsa-miR-2110 0.9776 -0.02 0.1319 -1.51 -1.3113 hsa-miR-204-3p 0.9016 -0.17 0.4226 -2.23 -1.3043 hsa-miR-3199 0.9238 -0.16 0.4226 -2.23 -1.2998 hsa-miR-193a-3p 0.8239 -0.3 0.4226 -2.11 -1.2711 hsa-miR-4777-3p 0.9072 -0.19 0.4226 -2.05 -1.2013 hsa-miR-3141 0.4257 -1.65 0.7369 -0.34 -1.0370 hsa-miR-3194-3p 0.6762 -0.55 0.5325 -1.67 -0.9588 hsa-miR-487a-5p 0.8297 -0.29 0.5162 -1.84 -0.9396 hsa-miR-5006-5p 0.7082 -0.41 0.2907 -1.12 -0.9141 hsa-miR-744-3p 0.1034 -0.92 0.7723 -0.2 -0.8704 hsa-miR-181a-2-3p 0.0105 -0.71 0.9422 -0.02 -0.7037 hsa-miR-149-3p 0.4315 -1.16 0.9169 -0.17 -0.6736 hsa-miR-6165 0.9815 -0.03 0.3885 -1.08 -0.6610 hsa-miR-211-5p 0.4702 -1.13 0.8674 -0.27 -0.6345 hsa-miR-3074-5p 0.9125 -0.11 0.4326 -1.03 -0.5940 hsa-miR-378i 0.3132 -0.75 0.9751 -0.03 -0.5158 hsa-miR-4747-3p 0.546 -0.96 0.8176 -0.4 -0.5088 hsa-miR-361-3p 0.3804 -0.68 0.7289 -0.28 -0.4972 hsa-miR-24-2-5p 0.3666 -0.59 0.6833 -0.34 -0.4814 hsa-miR-409-5p 0.3683 -0.74 0.8661 -0.09 -0.4795 hsa-miR-149-5p 0.8796 -0.25 0.6378 -1.08 -0.4213 hsa-miR-3940-3p 0.7457 -0.59 0.7162 -0.79 -0.3742 hsa-miR-134-5p 0.2682 -0.49 0.9686 -0.02 -0.3592 hsa-miR-29a-3p 0.375 -0.31 0.6196 -0.2 -0.2698 hsa-miR-486-3p 0.8207 -0.18 0.3403 -0.3 -0.2302 hsa-miR-708-3p 0.7992 -0.43 0.7612 -0.41 -0.1843 hsa-miR-11181-3p 0.7714 -0.41 0.8064 -0.42 -0.1750 hsa-miR-1229-5p 0.7795 -0.5 0.8269 -0.36 -0.1726 hsa-miR-766-5p 0.668 -0.37 0.8168 -0.27 -0.1723 hsa-miR-146a-5p 0.9189 -0.03 0.3713 -0.2 -0.1282 hsa-miR-30c-5p 0.4508 -0.2 0.9072 -0.05 -0.1145 hsa-miR-99a-5p 0.493 -0.2 0.8614 -0.04 -0.1069 hsa-miR-2467-3p 0.7976 -0.45 0.9169 -0.17 -0.1052 hsa-miR-4783-5p 0.9955 -0.01 0.6882 -0.33 -0.1029 hsa-miR-181b-2-3p 0.8325 -0.34 0.8597 -0.29 -0.0976 hsa-miR-148b-3p 0.5843 -0.19 0.9077 -0.05 -0.0836 hsa-miR-6745 0.7883 -0.36 0.9443 -0.11 -0.0823 hsa-miR-224-5p 0.7707 -0.3 0.9502 -0.04 -0.0708 hsa-miR-1180-3p 0.9266 -0.13 0.8419 -0.33 -0.0617 hsa-miR-19a-3p 0.9382 -0.03 0.6724 -0.16 -0.0543 hsa-miR-124-3p 0.9238 -0.16 0.8625 -0.29 -0.0521 hsa-miR-548ay-3p 0.9586 -0.08 0.8831 -0.24 -0.0314 hsa-miR-144-3p 0.9945 -0.01 0.8548 -0.15 -0.0218

In order to derive potential biomarkers with predictive values as biomarkers (eg, AD biomarkers), SUmiR and SDmiR showing the most extreme expression patterns were selected. Thresholds were arbitrarily determined for each set of miRNAs and the threshold for SUMiR was set to the top 5% (Fig. 4a). Accordingly, 13 SUmiRs were selected (Fig. 5a).

Example 3. Expression dynamics of the seven SDmiRs

7 miRNAs with extremely sequential expression patterns formed clusters of samples with the same characteristics (FIGS. 4b and 4c), unlike the previous clustering results using 1,850 miRNAs (FIG. 3). The expression of these 7 miRNAs distinguished the presence or absence of disease as well as distinguishing three groups of patients (except for one sample) by heatmap hierarchical clustering (Fig. 4b). In addition, seven miRNAs were clearly distinguished between the normal group (young and old) and the diseased patient group (MCI and AD) through principal component analysis (Fig. 4c).

Surprisingly, platelet-derived SDmiR showed a similar expression profile in human brain frontal cortex (Figs. 6a-e and 7a-b). The inventors of Lau et al. (2013), we identified the expression patterns of 20 miRNAs selected by our study in Alzheimer's disease-related tissues. Unfortunately, 6 out of 20 miRNAs were present in the 2 data sets. Nevertheless, these six consensus miRNAs showed different expression patterns according to early versus more advanced AD (Fig. 6a), and these results were more clearly confirmed by PCA (Fig. 6b).

The expression patterns of miR-150-3p and miR-150-5p in human brain were very similar to those in platelets, and both were statistically significant in brain tissue (Fig. 7a–b). In addition, miR-150-5p, which is commonly found in both platelets and brain tissue, showed a greater difference than miR-150-3p (Fig. 5b and Fig. 7a). Expression patterns of miR-150-3p and miR-150-5p differentiated the normal group from the diseased group (FIG. 5b). In addition, miR-150-5p not only highly correlated with age, but also had sufficient statistical significance to discriminate between diseases (Fig. 5c).

Example 4. Biomarkers for Alzheimer's disease and patient age

Most of the miRNAs belonging to the sequentially down-regulated miRNAs (SDmiRs) showed high correlation with patients' age (Fig. 5c), owing to the strategy of analyzing the sequentially expressed miRNA findings (Fig. 5c), but not all selected miRNAs represented only the patient's age. It wasn't. In an actual clinical diagnosis environment, since the elderly come to the hospital for diagnosis or treatment, biomarkers that distinguish normal from disease are more useful. Among SDmiR-Ex, miR-873-5p and miR-215-5p showed a high correlation with age, but their expression patterns did not differentiate between normal and diseased patients. However, miR-150-5p not only highly correlated with age, but also had sufficient statistical significance to discriminate between diseases (Figures 5a and c). In summary, it can be assumed that the platelet expression of miR-150-5p gradually changes with age, and this phenomenon is further amplified when cognitive impairment occurs.

Accordingly, miR-4449 and miR-6796 showed a very high association with age (Fig. 5c), but only miR-4449 expression patterns were distinguished between normal and diseased groups (Fig. 5B). In summary, it can be assumed that the platelet expression of miR-4449 gradually changes with age, and this phenomenon is further amplified when cognitive impairment occurs.

Example 5. Precursor and strand preference of miR-150

The present inventors were able to obtain interesting results while screening SDmiR-Ex. Among the miRNAs belonging to SDmiR, a set of miRNAs derived from the same precursor was found (Fig. 4a). In addition, the expression levels of these miRNAs (e.g., miR-150-3p and miR-150-5p) were highly positively correlated in various tissue types (Figures 8a and j). Concomitantly, 3p and 5p expression was highly correlated with patient's age in platelets (Fig. 8a).

The expression of the precursor form of miRNA was predicted using the sum of the two miRNA expression values (miR-150-5p and miR-150-3p), and the expression of the precursor was also statistically significant in each patient group, 150-3p and miR-150-3p. As at 150-5p, it was highly correlated with the patient's age (Fig. 8d). Differences in precursor miR-150 expression between patient groups were also the same in brain tissue from patients in Lau et al. In addition, 5p and 3p mature miRNAs derived from the same precursor showed biased expression due to "arm-switching" of the precursor. We found that the precursor miRNA-150 in platelets had a higher preference for the 5p strand than the 3p strand (FIG. 8e). We confirmed the biased results of using these 5p and 3p in several data sets (Fig. 8f-8i). In several tissue-based experiments, the 5p strand was favored and there was still a high 5p strand preference even within the same tissue data set using different key components and RNA extraction methods.

Example 6. Diagnosis using Alzheimer's specific arm switching

As described above, the present inventors can simultaneously screen patients and non-patients for the expression of miR-150-5p, miR-150-3p, and miR-150 precursors in platelets, and also if the precursor miR-150 is 5p stranded A preference for use was confirmed. In addition, differences between strands were found during analysis of the relationship between age and mature RNAs (e.g., miR-150-5p and miR-150-3p) derived from the same precursor (Fig. 8a). In the logistic regression analysis of each strand and age, the slope of the 5p strand (−0.066) was much steeper than that of the 3p strand (−0.047) (right side of Fig. 8a). In addition, when plotting the 3p and 5p strands for each sample, splitting patterns were identified on both sides based on the regression line (left side of Fig. 8a).

Based on these observations, we hypothesized that the strand preference of the miR-150 precursor may change as the disease progresses to Alzheimer's disease. The present inventors confirmed that the utilization rate of the 3p strand was significantly higher in diseased patients (p = 0.023) than in normal patients (FIG. 8b). It was also confirmed that the same pattern appeared in brain tissue (FIG. 6d).

For platelets, the ratio of 3p usage to 5p usage in the normal and diseased groups was significantly different (Fig. 8c). Although not significantly different (p = 0.101), the different ratios of 3p use and 5p use had similar patterns seen in the brain tissue of Lau's et al. (Fig. 6E). In conclusion, the ratio of miR-150-3p to miR-150-5p derived from the miR-150 precursor may be useful when platelet tissue is used for diagnosis of Alzheimer's disease.

All statistical analyzes were performed in R version 3.5.2 using an unpaired t test to test for statistical significance in differences between two groups. PCA (principal component analysis) was performed using R's basic command "prcomp", and area under the curve, sensitivity and specificity were measured using ROC (receiver operating characteristic) analysis. ROC analysis using “ROCR” and “pROC” was performed in R.

We used 4 types of public data, 3 of which were GEO data. Information on the GEO data set is shown in Table 6. Another data source is miRbase (http://www.mirbase.org/cgi-bin/get_read.pl?acc=MI0000479).

GEO accession number Origin and Tissue Number of samples GSE48552 Human brain, frontal cortex 12 GSE46579 Human whole blood 70 GSE97644 Plasma, Exosome 97

discussion

When researching and developing biomarkers, there are two ways to use external factors such as age. The first is to remove all substances (e.g. miRNAs) associated with external factors (e.g. age), and the second is to subdivide the sample groups by including the external factors. In the case of Alzheimer's disease, which is known as a degenerative brain disease, removing biomarkers related to external factors such as age excludes many potential biomarkers. Therefore, we conducted the study under the premise of an age-related sample group using the second strategy.

The normal group was divided into two groups according to age, and finally, the patients were divided into three groups: young normal, old normal, and diseased. In addition, a method was developed to discover miRNAs that are differently expressed according to the characteristics of the three groups. Specifically, we used the new method to calculate sequential scores and finally selected 20 miRNAs with very low or high scores. Some of these were age-only discriminating miRNAs (e.g. miR-10396a-3p) that could not confirm disease. However, some miRNAs have strong expression patterns that can distinguish the presence or absence of disease while distinguishing age groups (e.g., miR-150-5p).

A biomarker is an identifying substance that can differentiate a specific patient group. However, there are more considerations in the development of clinical diagnostic products. Measurement of biomarker quantities for diagnostic purposes, whether using single or multiple biomarkers, can only be successful after solving a significant problem, and most importantly the absolute quantification of these biomarkers.

Although many methods have been developed for absolute quantification, there are many limitations for practical use (26, 27). One of the best known and easiest methods is to use housekeeping miRNAs (28; 29), but since most of them show stable expression only in specific normal tissues, they are insufficient to respond to various tissues and various diseases. The 20 miRNA biomarkers discovered by the present inventors have the same problems in actual use.

Accordingly, the present inventors developed an Alzheimer's disease diagnosis method using a ratio rather than a quantitative biomarker. Fortunately, among the miRNAs we selected, there was a set of miRNAs derived from the same precursor. The precursors of miR-150, namely 3p and 5p mature miRNAs, had the ability to distinguish patients from non-patients while maintaining a high correlation with patient age. We called this triple-matched miRNA. The triple-matched miR-150 had the property of arm switching (30), using more and more of the 3p strand as Alzheimer's disease progressed. In addition, using miRNA combinations derived from the same precursor in experiments for actual diagnosis can better reduce errors due to various conditions of the sample and the skill level of the experimenter than using miRNA combinations derived from different precursors. For example, when sporadic expression changes of biomarkers occur due to unexpected changes in sample conditions, the amount of miRNA may deviate significantly from the reference value. However, measuring the proportion of miRNAs derived from the same precursor under the same circumstances showed much less variance compared to quantitative methods.

Attempts to develop miRNA biomarkers using miRNA imbalance have been noted several times in cancer-related studies (31, 32). However, the present inventors first developed a diagnostic method using miRNA imbalance in relation to Alzheimer's disease. In addition, we reanalyzed the brains of Alzheimer's patients and confirmed the miR-150 precursor and mature miRNA expression patterns. These results suggest that miRNAs have potential as therapeutic targets. Of course, miR-150 has been mentioned several times as a biomarker for Alzheimer's disease (33, 34, 45). However, application of the precursor miR150-imbalanced properties we found could contribute to the development of more effective Alzheimer's therapies.

Although the embodiments of the present invention have been described above, those skilled in the art can add, change, delete, or add components within the scope not departing from the spirit of the present invention described in the claims. The present invention can be variously modified and changed by the like, and this will also be said to be included within the scope of the present invention.

<110> BIORCHESTRA CO., LTD. KONYANG UNIVERSITY INDUSTRIAL COOPERATION GROUP <120> USE OF DOWNREGULATED MIRNA FOR DIAGNOSIS AND TREATMENT <130> HPC-9904 <150> KR 10-2020-0049292 <151> 2020-04-23 <160> 37 <170> KoPatentIn 3.0 <210> 1 <211> 22 <212> RNA <213> artificial sequence <220> <223> miR-485-3p <400> 1 gucauacacg gcucuccucu cu 22 <210> 2 <211> 7 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 2 uguauga 7 <210> 3 <211> 8 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 3 guguauga 8 <210> 4 <211> 9 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 4 cguguauga 9 <210> 5 <211> 10 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 5 ccguguauga 10 <210> 6 <211> 11 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 6 gccguguaug a 11 <210> 7 <211> 12 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 7 agccguguau ga 12 <210> 8 <211> 13 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 8 gagccgugua uga 13 <210> 9 <211> 14 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 9 agagccgugu auga 14 <210> 10 <211> 15 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 10 gagagccgug uauga 15 <210> 11 <211> 16 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 11 ggagagccgu guauga 16 <210> 12 <211> 17 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 12 aggagagccg uguauga 17 <210> 13 <211> 18 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 13 gaggagcc guguauga 18 <210> 14 <211> 19 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 14 agaggagagc cguguauga 19 <210> 15 <211> 20 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 15 gagaggagag ccguguauga 20 <210> 16 <211> 8 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 16 8 <210> 17 <211> 9 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 17 9 <210> 18 <211> 10 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 18 cguguaugac 10 <210> 19 <211> 11 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 19 ccguguauga c 11 <210> 20 <211> 12 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 20 gccguguaug ac 12 <210> 21 <211> 13 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 21 agccguguau gac 13 <210> 22 <211> 14 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 22 gagccgugua ugac 14 <210> 23 <211> 15 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 23 agagccgugu augac 15 <210> 24 <211> 16 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 24 gagagccgug uaugac 16 <210> 25 <211> 17 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 25 ggagagccgu guaugac 17 <210> 26 <211> 18 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 26 aggagagccg uguaugac 18 <210> 27 <211> 19 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 27 gaggagagcc guguaugac 19 <210> 28 <211> 20 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 28 agaggagagc cguguaugac 20 <210> 29 <211> 21 <212> RNA <213> artificial sequence <220> <223> miR-485-3p inhibitor <400> 29 gagaggagag ccguguauga c 21 <210> 30 <211> 21 <212> RNA <213> artificial sequence <220> <223> miR-873-5p <400> 30 gcaggaacuu gugagucucc u 21 <210> 31 <211> 21 <212> RNA <213> artificial sequence <220> <223> miR-215-5p <400> 31 augaccuaug aauugacaga c 21 <210> 32 <211> 22 <212> RNA <213> artificial sequence <220> <223> miR-642a-5p <400> 32 gucccucucc aaaugugucu ug 22 <210> 33 <211> 22 <212> RNA <213> artificial sequence <220> <223> miR-4731-5p <400> 33 ugcuggggggc cacaugagug ug 22 <210> 34 <211> 22 <212> RNA <213> artificial sequence <220> <223> miR-95-3p <400> 34 uucaacgggu auuuauugag ca 22 <210> 35 <211> 22 <212> RNA <213> artificial sequence <220> <223> miR-150-3p <400> 35 cugguacagg ccugggggac ag 22 <210> 36 <211> 22 <212> RNA <213> artificial sequence <220> <223> miR-150-5p <400> 36 ucucccaacc cuuguaccag ug 22 <210> 37 <211> 84 <212> RNA <213> artificial sequence <220> <223> miR-150 precursor <400> 37 cuccccaugg cccugucucc caacccuugu accagucug ggcucagacc cugguacagg 60 ccugggggac agggaccugg ggac 84

Claims (19)

Information for diagnosis of Mild Cognitive Impairment (MCI) or Alzheimer's disease (AD), comprising measuring the expression level of miR-150 obtained from an isolated sample of the subject As a method of providing, the expression level of miR-150 is increased in the relative expression ratio of miR-150-3p/precursor, decreased in the relative expression ratio of miR-150-5p/precursor, or miR-150-3p/miR-150- It represents the increase in the relative expression ratio between 5p,
The increase or decrease in the relative expression rate is characterized in that the expression rate is increased or decreased compared to the normal case, information providing method.
The method of claim 1, wherein the information providing method is selected from the group consisting of miR-873-5p, miR-215-5p, miR-642a-5p, miR-4731-5p, miR-95-3p and combinations thereof Characterized in that it further comprises the step of measuring the expression level of the miRNA, a method of providing information.
delete The method of claim 1, wherein the relative expression ratio has the following characteristics:
(a) The miR-150-3p/precursor relative expression ratio is 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more , an increase of 100% or more, 110% or more, 120% or more, 150% or more, or 200% or more;
(b) The miR-150-5p/precursor relative expression ratio is 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more , a reduction of at least 100%, at least 110%, at least 120%, at least 150%, or at least 200%; or
(c) the miR-150-3p/miR-150-5p relative expression ratio is 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more , an increase of 90% or more, 100% or more, 110% or more, 120% or more, 150% or more, or 200% or more.
The method of claim 1, wherein the relative expression ratio of miR-150-3p/precursor is increased, the relative expression ratio of miR-150-5p/precursor is decreased, or the relative expression between miR-150-3p/miR-150-5p is increased. The method of providing information, characterized in that the increase in the ratio distinguishes a normal case from a subject having mild cognitive impairment or Alzheimer's disease.
The method of claim 1, wherein the relative expression ratio of miR-150-3p/precursor is increased, the relative expression ratio of miR-150-5p/precursor is decreased, or the relative expression between miR-150-3p/miR-150-5p is increased. An increase in the ratio indicates that mild cognitive impairment or Alzheimer's disease is progressing.
delete delete The method of claim 1, wherein the sample is a blood sample.
10. The method of claim 9, wherein the blood sample contains platelets.
The method of claim 1, wherein the information providing method further comprises providing information on a cognitive disorder therapeutic agent to be administered to a subject with mild cognitive impairment or Alzheimer's disease. , The therapeutic agent is a miRNA inhibitor that inhibits miR-485-3p, aducanumab, galantamine, rivastigmine, donepezil, or memantine, or these Characterized in that it comprises a combination of, a method of providing information.
delete delete The method of claim 11, wherein the miR-485-3p comprises 5'-GUCAUACACGGCUCUCCUCUCU-3' (SEQ ID NO: 1).
The method of claim 11, wherein the miRNA inhibitor is a sequence complementary to miR-485-3p.
The method of claim 15, wherein the miRNA inhibitor is 5'-UGUAUGA-3' (SEQ ID NO: 2), 5'-GUGUAUGA-3' (SEQ ID NO: 3), 5'-CGUGUAUGA-3' (SEQ ID NO: 4), 5'-CCGUGUAUGA-3' (SEQ ID NO: 5), 5'-GCCGUGUAUGA-3' (SEQ ID NO: 6), 5'-AGCCGUGUAUGA-3' (SEQ ID NO: 7), 5'-GAGCCGUGUAUGA-3' (SEQ ID NO: 8), 5'-AGAGCCGUGUAUGA-3' (SEQ ID NO: 9), 5'-GAGAGCCGUGUAUGA-3' (SEQ ID NO: 10), 5'-GGAGAGCCGUGUAUGA- 3' (SEQ ID NO: 11), 5'-AGGAGAGCCGUGUAUGA-3' (SEQ ID NO: 12), 5'-GAGGAGAGCCGUGUAUGA-3' (SEQ ID NO: 13), 5'-AGAGGAGAGCCGUGUAUGA-3' (SEQ ID NO: 14), 5′-GAGAGGAGAGCCGUGUAUGA-3′ (SEQ ID NO: 15); 5'-UGUAUGAC-3' (SEQ ID NO: 16), 5'-GUGUAUGAC-3' (SEQ ID NO: 17), 5'-CGUGUAUGAC-3' (SEQ ID NO: 18), 5'-CCGUGUAUGAC- 3' (SEQ ID NO: 19), 5'-GCCGUGUAUGAC-3' (SEQ ID NO: 20), 5'-AGCCGUGUAUGAC-3' (SEQ ID NO: 21), 5'-GAGCCGUGUAUGAC-3' (SEQ ID NO: 22), 5'-AGAGCCGUGUAUGAC-3' (SEQ ID NO: 23), 5'-GAGAGCCGUGUAUGAC-3' (SEQ ID NO: 24), 5'-GGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 25), 5'-AGGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 26), 5'-GAGGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 27), 5'-AGAGGAGAGCCGUGUAUGAC-3' (SEQ ID NO: 28), and 3' (SEQ ID NO: 29), characterized in that selected from the group consisting of, providing information.
delete A kit for diagnosing mild cognitive impairment (MCI) or Alzheimer's disease (AD), comprising the following components:
(a) primers for amplifying miR-150-3p, miR-150-5p and miR-150 precursors; and
(b) Instructions for the provision of information in paragraph 1.
The method of claim 18, wherein the kit is one selected from the group consisting of miR-873-5p, miR-215-5p, miR-642a-5p, miR-4731-5p, miR-95-3p, and combinations thereof Characterized in that it further comprises a primer for miRNA amplification, the kit.

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