CN113151432A

CN113151432A - Novel targets for neurodegenerative disease detection and treatment

Info

Publication number: CN113151432A
Application number: CN202010290529.7A
Authority: CN
Inventors: 郁金泰; 徐伟; 韩思达; 谭兰; 董强; 谭琳
Original assignee: Individual
Current assignee: Individual
Priority date: 2020-04-14
Filing date: 2020-04-14
Publication date: 2021-07-23

Abstract

The invention provides a novel molecular target for detecting and treating neurodegenerative diseases, and corresponding diagnosis and treatment methods and corresponding kits. Specifically, the invention judges whether the expression level of PGRN is normal or not by detecting the expression level of FAM171A2 gene so as to assist in diagnosing the neurodegenerative disease. It is also an object of the present invention to provide a method for treating degenerative diseases of the nervous system by up-regulating the level of PGRN in the brain.

Description

Novel targets for neurodegenerative disease detection and treatment

Technical Field

The invention belongs to the fields of molecular biology, neuroscience and clinical neuroscience, and particularly provides a novel molecular target for detecting and treating neurodegenerative diseases, a corresponding diagnosis and treatment method and a corresponding kit.

Background

With the aging of the world population accelerating, the number of patients with nervous system degenerative diseases shows a rapid growth trend, such as dementia, parkinson's disease and the like. The former may suffer from memory impairment, aphasia, disuse, agnosia, impairment of visuospatial skills, dysfunction in execution, and personality and behavioral changes; the latter causes dyskinesia, such as paralysis agitans, bradykinesia, abnormal muscle rigidity, gait disorder in posture, etc. The etiology and pathogenesis of such diseases are often unclear, treatment is difficult, and patient longevity and quality of life are severely affected.

PGRN, a progranulin, is expressed in both the central nervous system and peripheral tissues. Lack of PGRN and prefrontal dementia (FTD)^[1]Alzheimer's Disease (AD)^[2]And Parkinson's Disease (PD)^[3]Is involved in the onset of disease. Animal experiments show that PGRN may influence neuroinflammation^[4]Autophagy^[5]And cell signaling. In animal models of AD and PD^[3,6]Over-expression of PGRN can reduce pathological protein deposition and its toxicity, delaying the progression of disease phenotype. Recent studies have shown that PGRN levels in cerebrospinal fluid gradually increase as AD progresses^[7]. These lines of evidence suggest that a reduction in PGRN levels may be one of the etiological factors of neurodegenerative diseases, and PGRN is expected to be a target for therapy and intervention.

There is increasing evidence that PGRN levels may be regulated by mutations in several genes^[8,9]. Among these mutations is the PGRN-encoding gene grn^[10]All one ofOutside the coding gene, e.g. sort1^[8]And psrc1^[9]Etc. GWAS has shown that these mutations can modulate PGRN levels in peripheral blood^[11]. However, there is currently no adequate research to explore the regulatory factors of cerebrospinal PGRN. The PGRN protein is related to the occurrence and development of various neurodegenerative diseases due to cerebrospinal fluid. Understanding the role of PGRN in disease development helps to improve our understanding of the pathogenesis of degenerative diseases, and thus search for effective therapeutic approaches.

However, there is currently no GWAS study to explore the regulatory factors of cerebrospinal fluid PGRN. Compared with peripheral blood PGRN, cerebrospinal fluid PGRN has different possible regulation mechanisms, and the side effects of PGRN on tumors and obesity in peripheral tissues are avoided. Therefore, GWAS is developed aiming at genetic regulatory factors of cerebrospinal fluid PGRN, the experimental subjects are 1362 non-dementia adults, and an independent site which is located on the FAM171A2 gene and has strong correlation with PGRN level change is successfully screened. We also used bioinformatics means to annotate the function of the mutation and further determine its relationship to neurodegenerative diseases.

Summary of The Invention

The invention aims to provide a method for auxiliary diagnosis and treatment of nervous system degenerative diseases. Specifically, the invention judges whether the expression level of PGRN is normal or not by detecting the expression level of FAM171A2 gene or detecting the genotype of single nucleotide polymorphism locus rs708384, so as to assist in diagnosing the nervous system degenerative disease. It is also an object of the present invention to provide a method for treating degenerative diseases of the nervous system by up-regulating the level of PGRN in the brain.

In one embodiment of the invention, a two-stage Genome Wide Association Study (GWAS) was conducted to screen for modulators of cerebrospinal fluid PGRN levels. Data in the ADNI database showed that mutation site rs708384 located in FAM171a2 gene was associated with decreased levels of cerebrospinal PGRN (p ═ 3.95 × 10¹²). This conclusion is also verified in another independent queue embodiment of the present invention. While the factor associated with decreased levels of cerebrospinal PGRN is also similar to Alzheimer's diseaseThe risk of developing diseases such as Parkinson's disease and prefrontal dementia is increased. Furthermore, in another embodiment of the present invention, the site may regulate the expression of FAM171a2 in multiple brain regions, also suggesting that the gene may have an important role in regulating PGRN production. In another specific embodiment of the present invention, c of rs708384 was verified>The a mutation up-regulates the expression of FAM171a 2. Whereas over-expressed FAM171a2 decreased PGRN production. In summary, evidence for genetic, molecular, and biological information has collectively shown that FAM171a2 gene is an important regulator of PGRN production.

In one embodiment of the invention, the invention provides a method of predicting or determining the level of Progranulin (PGRN) in an individual, the method comprising determining the level of one or more biomarkers in one or more samples obtained from the individual, wherein the one or more biomarkers comprise FAM171a 2. The method may further comprise determining the levels of one or more of the following biomarkers in a sample obtained from the individual: ITGA 2B.

In one embodiment of the present invention, the present invention provides a method of determining whether an individual is at risk for dysregulated levels of Preprogrammin (PGRN) levels, the method comprising determining the level of one or more biomarkers in one or more samples obtained from the individual, wherein the one or more biomarkers comprise FAM171a 2. The method may further comprise determining the levels of one or more of the following biomarkers in a sample obtained from the individual: ITGA 2B.

In one embodiment of the present invention, the present invention provides a method of determining whether an individual is at risk of developing a neurodegenerative disease, the method comprising determining the level of one or more biomarkers in one or more samples obtained from the individual, wherein the one or more biomarkers comprise FAM171a 2. The method may further comprise determining the levels of one or more of the following biomarkers in a sample obtained from the individual: ITGA 2B.

In one embodiment, the expression level of FAM171a2 is determined by determining the nucleotide type of the single nucleotide polymorphism site rs 708384. When the site is cytosine (wild type), the expression level of FAM171a2 is normal. When the site is adenine (mutant), the expression level of FAM171a2 is significantly up-regulated.

In one embodiment, the level of one or more biomarkers is compared to one or more reference values. In this case, the same analytical method is preferably used to determine each biomarker level in each sample and the corresponding reference value. The reference value may be based on, for example, the value (e.g., average) of one or more biomarkers in a population of individuals that have previously been determined to have a normal or deregulated PGRN level.

Accordingly, in one embodiment of the present invention, there is provided the use of an agent that specifically detects FAM171a2 and/or an agent that specifically detects ITGA2B in the manufacture of a kit for predicting or determining the level of PGRN in an individual. The present invention also provides a kit comprising a reagent specifically detecting FAM171a2 and/or a reagent specifically detecting ITGA 2B. Preferably, such reagents are primers and/or probes and/or guide RNAs and the corresponding methods are general PCR, RT-PCR, fluorescent real-time quantitative PCR, isothermal amplification, DNA/RNA imprinting, gene chips, nuclease cleavage, etc. Or preferably such agents are antibodies and/or specific binding proteins, and the corresponding methods are immunoblotting, ELISA, in situ hybridization, immunohistochemistry, etc.

Accordingly, in another embodiment of the present invention, there is provided the use of a reagent specifically detecting FAM171a2 and/or a reagent specifically detecting ITGA2B in the manufacture of a kit for determining whether an individual is at risk of a dysregulated level of a Progranulin (PGRN). The present invention also provides a kit comprising a reagent specifically detecting FAM171a2 and/or a reagent specifically detecting ITGA 2B. Preferably, such reagents are primers and/or probes and/or guide RNAs and the corresponding methods are general PCR, RT-PCR, fluorescent real-time quantitative PCR, isothermal amplification, DNA/RNA imprinting, gene chips, nuclease cleavage, etc. Or preferably such agents are antibodies and/or specific binding proteins, and the corresponding methods are immunoblotting, ELISA, in situ hybridization, immunohistochemistry, etc.

Accordingly, in another embodiment of the present invention, there is provided a use of a reagent specifically detecting FAM171a2 and/or a reagent specifically detecting ITGA2B in the manufacture of a kit for determining whether an individual is at risk of developing a neurodegenerative disease. The present invention also provides a kit comprising a reagent specifically detecting FAM171a2 and/or a reagent specifically detecting ITGA 2B. Preferably, such reagents are primers and/or probes and/or guide RNAs and the corresponding methods are general PCR, RT-PCR, fluorescent real-time quantitative PCR, isothermal amplification, DNA/RNA imprinting, gene chips, nuclease cleavage, etc. Or preferably such agents are antibodies and/or specific binding proteins, and the corresponding methods are immunoblotting, ELISA, in situ hybridization, immunohistochemistry, etc.

In a specific embodiment of the invention, the reagent for specifically detecting FAM171a2 is a primer pair capable of specifically amplifying FAM171a2 gene in a PCR reaction.

Furthermore, in one embodiment of the invention, PGRN levels are reduced by over-expressing FAM171a2 in the central nervous system. In another embodiment of the invention, the ability of microglia to phagocytose, clear, degrade abnormally deposited proteins is enhanced by inhibiting FAM171a2 expression in the central nervous system, increasing PGRN levels, and upregulating lysosomal enzyme activity in microglia. Thus, in one embodiment, the invention provides a method of treating a neurodegenerative disease characterized by inhibiting the expression of FAM171a2 in the central nervous system. In a specific embodiment, the expression of FAM171a2 is reduced by means of gene therapy. In another more specific embodiment, the gene therapy means is the in vivo transfer of siRNA, preferably naked siRNA, but also siRNA, or shRNA, or miRNA, or antisense oligonucleotide (ASO), preferably via a vector, or a nucleic acid construct that can be transcribed to produce these, or other viable nucleic acid forms; vectors such as plasmids, viruses, or other commonly used forms of vectors. In another more specific embodiment, the sequence of the siRNA is 5'-GCAAUGGCACUGGUGUAAUTT-3', or 5'-AUUACACCAGUGCCAUUGCTT-3'. In another more specific embodiment, the viral vector consists of any vector that is effective in the transfer of small RNAs into target cells, preferably the viral vector is a lentiviral vector, or preferably the viral vector is an adeno-associated viral vector, or preferably the viral vector is an adenoviral vector. In another more specific embodiment, the gene therapy means is gene editing, preferably the gene editing is by a Zinc Finger Nuclease (ZFN), TALE-effector (TALEN), CRISPR/Cas system or NgAgo system, preferably CRISPR/Cas9 system. In some embodiments, modification of the endogenous FAM171a2 gene by gene therapy means may comprise introduction of mutations such as: which reduces the expression of the endogenous FAM171a2 gene or results in degradation (e.g., by nonsense-mediated decay) of FAM171a2 transcript mRNA.

In a specific embodiment, the in vivo protein content of FAM171a2 is reduced. In a more specific embodiment, FAM171a2 is bound to reduce its level by an antagonist specific antibody. In another more specific embodiment, FAM171a2 is bound by a non-antibody specific binding protein/polypeptide to facilitate its degradation, thereby reducing its in vivo levels.

In another specific embodiment, the effect of reducing the expression of FAM171a2 molecules is actually achieved by transferring to the central nervous system an antisense nucleic acid to a strong promoter upstream of FAM171a2 gene, or an antisense nucleic acid or antibody to the corresponding transcription factor, or other known means or protocols that achieve similar effects. In some embodiments, the strong promoter upstream of FAM171a2 gene is subjected to gene therapy or gene modification to change from wild type to mutant, or to correct point mutation to wild type sequence, so as to achieve the effect of down-regulating the expression level of downstream FAM171a 2.

Further, the present invention provides a method for treating neurodegenerative diseases by restoring the phagocytic capacity of the central nervous system mononuclear-macrophage system (e.g., microglia) to abeta and other abnormally deposited proteins. In a specific embodiment, a transcriptional modulator capable of reducing the expression level of FAM171a2 gene is introduced into the body.

In another aspect of the present invention, there is provided a use of a substance that decreases the expression of FAM171a2 or inhibits the in vivo level of FAM171a2 in the preparation of a pharmaceutical composition for treating a degenerative disease of the nervous system, or for preventing or reducing the risk of developing a neurodegenerative disease, or for increasing the level of PGRN or for treating or preventing a disease caused by a deregulated level of PGRN. Preferably, the substance that reduces the expression of FAM171a2, or inhibits the in vivo level of FAM171a2, is a substance that reduces the expression of FAM171a2, or a substance that reduces the in vivo protein content of FAM171a2, by gene therapy as mentioned above, or an antisense nucleic acid to a strong promoter upstream of FAM171a2 gene, or an antisense nucleic acid or antibody to a corresponding transcription factor. More preferably, the substance is siRNA. More preferably, the siRNA has a sequence of 5'-GCAAUGGCACUGGUGUAAUTT-3', or 5'-AUUACACCAGUGCCAUUGCTT-3'.

The present invention first found the effect of the expression level of FAM171a2 on promoting the phagocytosis of abnormally accumulated proteins such as a β by microglia. The down-regulated PGRN expression caused by excessive FAM171A2 directly causes the decrease of the phagocytic capacity of microglia, and even under the physiological condition that the generation speed of certain abnormal accumulation proteins is not increased, the latter can not be eliminated, so that the abnormal accumulation proteins are accumulated in the central nervous system in a large amount, and further have toxic effect on nerves, and the neurodegenerative diseases are developed to a certain extent. Although the etiology of such diseases is very complex and difficult to be considered with a single cause or cause, if a significant down-regulation of PGRN expression in the central nervous system, such as cerebrospinal fluid, is detected, this may be strongly correlated with neurodegenerative diseases. And the regulation of the expression level of FAM171A2 and/or the up-regulation of PGRN expression may prevent or treat the neurodegenerative diseases.

Drawings

Figure 1 GWAS results and area plots associated with CSF PGRN levels. a. Manhattan plots (showing log 10(p value) for a single nucleotide polymorphism) and qq plots. And b, arranging the correlation results after the test. EMP 1-empirical p-value; EMP2 is the empirical family error rate after permutation-based correction. Region association results for the c GRN FAM171a2 ITGA2B region. d area after control of rs708384 correlates the results.

Figure 2 minor allele of rs708384 (a allele, MAF ═ 0.41) was significantly dose-dependent with cerebrospinal fluid PGRN levels.

FIG. 3. degree of variability in cerebrospinal PGRN levels explained by genetic variation. Chromosome 17 accounts for approximately 17.4% of cerebrospinal PGRN level variations. b most important loci are in linkage disequilibrium with rs 708384. SNPs in the c GRN region account for most, but not all, variations in cerebrospinal fluid PGRN. Analysis of the FAM171a2 and ITGA2B regions showed that these two regions account for 9.1% and 5.6% of the variation in cerebrospinal PGRN levels, respectively. Rs708384 has been shown to account for 9.1% variability. d Low to moderate LD between rs5848 and rs708384 in the CEU population (r)²0.6) and no locus in the LD of rs 5848. However, rs5848 and rs708384 have high LD (r) in the CHB population²＝0.8)。

FIG. 4. correlation of cerebrospinal fluid PGRN levels with rs708384 genotype in replicate cohorts.

Cerebrospinal fluid PGRN levels of AA, AC and CC genotypes of rs708384 were compared in a larger independent cohort of 930 non-dementia chinese participants to verify the most significant signals initially observed. The observation that decreased cerebrospinal fluid PGRN levels were significantly correlated with allele a (rs708384 mutation) dose, but not with age, gender, education, APOE4 genotype, baseline MMSE score, CV and rs5848 genotype.

FIG. 5 GO and pathway analysis.

a pathway classes with significant differences (p <0.001) are mainly associated with nervous system development, molecular trafficking, signal transduction, cell adhesion and response to stimuli. b four clusters are formed in the gene network. The most important genes (FAM171a2 and GRN) were clustered together. c FAM171a2 and GRN obtained the highest z-score. GADO prioritizes candidate genes using Z scores: genes with higher z scores are more likely to explain the phenotype.

FIG. 6 FAM171A2 was abundantly expressed on the brain vascular endothelium.

a b IHC staining of FAM171A2 in the cortex and hippocampus of mice. Arrows mark DAB staining around and around cerebral vessels. c IF staining of FAM171A2 and CD31 on mouse cortex. Their co-localization is marked with an asterisk. IF staining of FAM171a2 and CD31 on primary cerebral Vascular Endothelial Cells (VECs) in mice.

FIG. 7 rs708384 promotes expression of FAM171A2 and subsequently inhibits GRN/PGRN levels.

a structure of firefly luciferase reporter plasmid. The sequence containing rs708384 is marked with a red square. b plasmid (c a) with or without rs708384, including empty controls, expressed at different levels of firefly luciferase following transfection into HEK293 cells. The luminescence intensity was calibrated with renilla luciferase and the results were expressed as the ratio firefly/algal luciferase. c, d significant decreases in intracellular GRN were observed following overexpression of FAM171A 2. After overexpression of e FAM171A2, the supernatant PGRN decreased significantly.

FIG. 8. subgroup and sensitivity analysis.

In subgroup analysis, the minor allele (C) of rs708384 was associated with higher cerebrospinal fluid PGRN levels in different stratified populations divided by gender (male, p ═ 2.67 x 10-6; female, p ═ 1.76 x 10-6) and baseline diagnosis (HC, p ═ 0.01742; MCI, p ═ 1.36 x 10-11). Notably, the effect size of the HC population increased dramatically (HC beta-100.9, MCI beta-8.77 x 10-5) b sensitivity analyses were performed to further adjust for these confounders. There was no significant change in adjusted age and baseline diagnosis (p of rs708384 ═ 3.51X 10-12). After adjustment for rs5848, we also found a significant, although slightly lower, association of rs708384 with cerebrospinal PGRN levels (p ═ 8.28 × 10-5). After excluding 73 individuals who developed AD within three years since baseline, rs708384 was still the most significant SNP (n 359, p 4.73 × 10-10).

FIG. 9 differential expression analysis of GRN, FAM171A2 and ITGA 2B.

All results were adjusted for gender and sex. Entorhinal cortex dataset: GSE26927, GSE26972, GSE48350, GSE 5281; data set of hippocampus: GSE28146, GSE29378, GSE36980, GSE48350, GSE 5281; temporal cortical data set: GSE29652, GSE36980, GSE37263, GSE 5281; frontal cortex dataset: GSE12685, GSE36980, GSE5281, GSE53890, GSE66333

Figure 10 knock-down of FAM171a2 promotes GRN expression in cells.

Intracellular expression of a, b GRN. c efficiency of FAM171A2 siRNA and Overexpression (OE).

FIG. 11. correlation of rs708384 genotype with overall cognition and cerebrospinal fluid tau levels. The "AA" genotype of rs708384 is associated with higher cerebrospinal tau levels (a) and poorer overall cognitive levels (b & c) in HC populations.

Figure 12 MDS plots for samples of ADNI non-hispanic white species.

Unexpected duplications and cryptic correlations between samples were examined by proportional identity estimation of the scale reduction using paired whole genomes. In addition to the two outliers based on the second MDS component (at the bottom of the figure; IID 024_ S _4084 and 024_ S _2239), the samples appear to generally form tight clusters, indicating potential population substructures.

Detailed Description

Preferred features and embodiments of the invention will be described by way of non-limiting examples.

The practice of the present invention will employ, unless otherwise indicated, conventional techniques of chemistry, biochemistry, molecular biology, microbiology, and immunology, which are within the capabilities of a person of ordinary skill in the art. Such techniques are described in the literature. See: for example, Sambrook, j., Fritsch, e.f., and manitis, T. (1989) "Molecular Cloning: a Laboratory Manual ", second edition, Cold Spring Harbor Laboratory Press; ausubel, F.M. et al (1995and periodic suspensions) Current Protocols in Molecular Biology, Ch.9,13and 16, John Wiley & Sons; roe, B., Crabtree, J., and Kahn, A., 1996, "DNA Isolation and Sequencing: expression Techniques", John Wiley & Sons; polak, J.M. and McGee, J.O' D., 1990, "In Situ Hybridization: Principles and Practice," Oxford University Press; gait, M.J. (1984) Oligonucleotide Synthesis A Practical Approach, IRL Press; and Lilley, D.M.And and Dahlberg, J.E. (1992) Methods in Enzymology DNA Structures Part A: Synthesis and Physical Analysis of DNA, Academic Press. Each of these general texts is incorporated herein by reference.

Definition of

PGRN

Namely the progranulin. The human PGRN gene is located at 17q21.32 and is a secreted glycoprotein consisting of 593 amino acid residues, and the relative molecular mass of non-glycosylated PGRN is about 6.8X 10⁴And the glycosylated PGRN had a relative molecular mass of 8.8X 10⁴Left and right. The PGRN molecule contains a signal peptide and seven half-adaptor repeated domains, each consisting of 12 cysteines. Proteolytic hydrolysis of the highly conserved mature PGRN produces a set of relative molecular masses of approximately 6X 10³The granulin (Grn) polypeptides (Grn A-G) of (1). PGRN can exert its biological function by regulating MAPK, PI3K, caspase, Wnt and TNF signal pathways, and has the functions of growth factor and neurotrophic factor. In recent years, PGRN has been found to be involved in the pathological processes of various neurological diseases, such as those associated with various neurodegenerative diseases. Immunopositivity of PGRN in the brain of AD patients and animal models correlates with the distribution of amyloid plaques. PGRN can protect damage of dopaminergic neurons in brain of Parkinson's Disease (PD) animal model and the like. Since mature PGRN is a secretory protein, the PGRN can be highly expressed by microglia along with the development of diseases, so that the PGRN level in cerebrospinal fluid and serum can be increased, and the PGRN can be used as a potential diagnostic marker for nervous system diseases. Studies have shown that PGRN is highly expressed in brain tissue and cerebrospinal fluid of Multiple Sclerosis (MS) patients, and that PGRN concentration in cerebrospinal fluid is associated with activation of glial cells.

Neurodegenerative diseases

Neurodegenerative diseases refer to the following conditions, including: prefrontal dementia, alzheimer's disease, parkinson's disease, neuronal lipofuscin deposition, multiple sclerosis and amyotrophic lateral sclerosis. It may also refer to the following conditions, including: dentatorubral pallidoluysian atrophy (DRPLA), neuronal endonuclear hyaline inclusion body disease (NIHID), Lewy body dementia, Down syndrome, Hallervorden-Spatz disease, prion disease, dementia with silvery granules, cortical basal degeneration, dementia pugilistica, diffuse neurofibrillary tangles, GSS ' disease, Hallervorden-Spatz disease, Creutzfeldt-Jakob disease, Niemann-pick disease type 3, progressive supranuclear palsy, subacute sclerosing panencephalitis, spinocerebellar ataxia, Huntington's disease, pick's disease, and dentatorubral pallidoluysia. Neurodegenerative disorders are generally characterized by neurofibrillary tangles and/or amyloid peptide deposits in the brain.

"diagnosis" of a neurodegenerative disease or disorder refers to predicting symptoms associated with such disorders, such as impaired cognitive function, cumulative a β deposition, and neuronal cell death.

Alzheimer's Disease (AD)

Alzheimer's disease results from atrophy of brain regions. Although it is not known what causes atrophy, studies have found that amyloid plaques, neurofibrillary tangles and acetylcholine imbalances are present in the brain of alzheimer's patients. Vascular damage in the brain that can damage healthy neurons is also common in alzheimer's patients.

Alzheimer's disease is a progressive disorder affecting multiple brain functions. Early signs of disease often include minor memory problems, such as forgetting the name of the most recent activity or location or object. As the disease progresses, memory problems become more severe and may cause additional symptoms such as confusion, disorientation, difficulty in making decisions, speech disorders, and personality changes.

Vascular dementia

Vascular dementia results from a decrease in blood flow to the brain, which damages brain cells. Reduced blood flow can result from a variety of causes, including narrowing of the cerebral vasculature (subcortical vascular dementia), stroke (single infarct dementia), and multiple minor strokes (multi-infarct dementia). In addition, reduced blood flow may also be caused by alzheimer's disease, a combination of symptoms known as mixed dementia.

Early symptoms of vascular dementia include slow thinking, difficulty planning, difficulty speaking, attention and concentration problems, and behavioral changes. After a stable period of months or years, symptoms usually worsen gradually.

Parkinson's Disease (PD)

Parkinson's disease is a disorder of progressive damage to nerve cells in the substantia nigra. Nerve cells in this region of the brain produce dopamine, which acts as a messenger between the brain parts and the nervous system that controls body movement. These nerve cell injuries result in a reduction in the amount of dopamine produced in the brain, the resulting effect being to attenuate the function of the portion of the brain that controls movement.

Symptoms of parkinson's disease include tremor, bradykinesia, and muscle stiffness and inflexibility. Parkinson patients may also experience additional symptoms including depression, constipation, insomnia, olfactory deficits, and memory problems.

Amyotrophic Lateral Sclerosis (ALS)

Amyotrophic Lateral Sclerosis (ALS) affects motor neurons in the brain and spinal cord, leading to degeneration and death of this cell population. ALS patients eventually lose the ability to speak, move and breathe. Although the causal relationship of ALS is not yet known, specific mutations are associated with disease development and are a field of extensive study.

Multiple sclerosis

Multiple sclerosis is caused by an immune system attack on the myelin sheaths around neurons in the brain and spinal cord. This disease can lead to poor communication between neurons and axonal degeneration. MS appears to deteriorate in physical performance and also results in changes in vision, pain management, and speech ability. Although gender, race and environment are risk factors for the occurrence of MS, the exact cause is not known.

Prevention and treatment of

As used herein, "prevention" refers to all actions that suppress or delay the onset of a neurodegenerative disease by administering a drug according to the invention, and "treatment" refers to all actions that have been ameliorated or have been favorably altered by administering a drug to a subject having or suspected of having a neurodegenerative disease.

Expression level detection

The detection of the expression level of a gene encoding a protein by conventional molecular biology means can be generally classified into two categories. The first type is to detect the mRNA level of the gene. The second type is to detect the product protein obtained after the gene is expressed.

Over-or high-expression refers to a protein or nucleic acid that is transcribed or translated in a cell at a detectably higher level relative to a normal cell. The term includes overexpression due to transcription, post-transcriptional processing, translation, post-translational processing, cellular localization (e.g., organelles, cytoplasm, nucleus, cell surface), and RNA and protein stability (relative to normal cells). Overexpression can be detected using conventional techniques for detecting mRNA (i.e., RT-PCR, hybridization) or for detecting protein (i.e., ELISA, immunohistochemical techniques). Overexpression may be 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or higher than in normal cells. In some examples, overexpression is at a 1-fold, 2-fold, 3-fold, 4-fold, or higher level of transcription or translation relative to normal cells.

By low expression is meant a protein or nucleic acid that is transcribed or translated in the cell at a detectably lower level relative to a normal cell. The term includes low expression due to transcription, post-transcriptional processing, translation, post-translational processing, cellular localization (e.g., organelle, cytoplasm, nucleus, cell surface), and RNA and protein stability (relative to controls). Low expression can be detected using conventional techniques for detecting mRNA (i.e., RT-PCR, hybridization) or for detecting protein (i.e., ELISA, immunohistochemical techniques). Low expression can be 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or less lower than the control. In some examples, the low expression is a 1-fold, 2-fold, 3-fold, 4-fold or lower level of transcription or translation relative to a control.

Differential expression or differential expression generally refers to overexpression (upregulation) or underexpression (downregulation) of a protein or nucleic acid in one sample relative to at least one other sample. For the purposes of the present invention, a sample from an individual suspected of having a neurodegenerative disorder is typically compared to a sample from an individual known to have the disorder (positive control) or known to be negative for the disorder (negative control).

A "label" or "detectable moiety" is a component that can be detected spectrophotometrically, photochemically, biochemically, immunochemically, chemically, or by other physical means. For example, useful labels include 32P, fluorescent dyes, high electron density reagents, enzymes (e.g., enzymes commonly used in ELISA), biotin, digoxigenin (digoxigenin), or haptens and proteins that can be prepared to be detectable (e.g., by incorporating a radioactive marker into the peptide) or used to detect antibodies specifically reactive with the peptide. The label may be bound to a targeting molecule, such as an antibody or a nucleotide sequence for specific detection of a target compound.

Knockdown and suppression

An "inhibitor" is a compound that, for example, binds, partially blocks or completely blocks activity, reduces, prevents, delays activation, inactivates, desensitizes, or down regulates the activity or expression of a neurodegenerative biomarker. Inhibitors, activators, or modulators also include genetically modified neurodegenerative biomarkers, e.g., forms with altered activity, as well as naturally occurring and synthetic ligands, antagonists, agonists, antibodies, peptides, cyclic peptides, nucleic acids, antisense molecules, ribozymes, RNAi and siRNA molecules, small organic molecules, and the like.

Nucleic acids, nucleotides or polynucleotides

"nucleic acid," "nucleotide," or "polynucleotide" refers to deoxyribonucleotides or ribonucleotides, as well as polymers thereof in either single-or double-stranded form, and their complements. The term includes nucleic acids containing known nucleotide analogs or modified backbone residues or linkages, which are synthetic, naturally occurring, and non-naturally occurring, which have similar binding characteristics as the reference nucleic acid, and which are metabolized in a manner similar to the reference nucleotides. Examples of such analogs include, but are not limited to, phosphorothioate, phosphoramidate, methylphosphonate, chiral methylphosphonate, 2-O-methyl ribonucleotide, Peptide Nucleic Acid (PNA).

Small RNAs

Small RNAs refer to non-coding RNAs, which are typically less than about 200 nucleotides or less in length and have silencing or interfering functions. In other embodiments, the small RNA is about 175 nucleotides or less in length, about 150 nucleotides or less, about 125 nucleotides or less, about 100 nucleotides or less, or about 75 nucleotides or less. Such RNAs include microRNAs (miRNAs), small interfering RNAs (siRNAs), double-stranded RNAs (dsRNA), and short hairpin RNAs (shRNAs). The "small RNA" of the present disclosure should be capable of inhibiting or knocking down gene expression of a target gene, typically through a pathway that results in the destruction of the target gene mRNA.

Amino acids, peptides, polypeptides, proteins

"polypeptide," "peptide," and "protein" are used interchangeably herein to refer to a polymer of amino acid residues. The term applies to amino acid polymers: artificial chemical mimetics in which one or more amino acid residues is a corresponding naturally occurring amino acid are also suitable for use in naturally occurring amino acid polymers and non-naturally occurring amino acid polymers.

Amino acids refer to naturally occurring and synthetic amino acids, as well as amino acid analogs and amino acid mimetics that function in a manner similar to the naturally occurring amino acids. Naturally occurring amino acids are those encoded by the genetic code, as well as later modified amino acids, such as hydroxyproline, γ -carboxyglutamic acid, and O-phosphoserine. Amino acid analogs refer to compounds that have the same basic chemical structure as a naturally occurring amino acid, i.e., a carbon that is bound to a hydrogen, a carboxyl group, an amino group, and an R group, e.g., homoserine, norleucine, methionine sulfoxide, methionine methyl sulfonium. Such analogs have modified R groups (e.g., norleucine) or modified peptide backbones, but retain the same basic chemical structure as a naturally occurring amino acid. Amino acid mimetics refers to chemical compounds that differ in structure from the general chemical structure of an amino acid, but that function in a manner similar to a naturally occurring amino acid.

Antibodies

An antibody refers to a polypeptide comprising a framework region or fragment thereof from an immunoglobulin gene that specifically recognizes and binds an antigen. Recognized immunoglobulin genes include the kappa, lambda, alpha, gamma, delta, epsilon, and mu constant region genes, as well as numerous immunoglobulin variable region genes. Light chains are classified as either kappa or lambda. Heavy chains are classified as gamma, mu, alpha, delta, or epsilon, which in turn define the class of immunoglobulins, IgG, IgM, IgA, IgD, and IgE, respectively. Generally, the antigen binding region of an antibody is most important for specificity and affinity of binding. The antibodies may be polyclonal or monoclonal, derived from serum, hybridomas or recombinant clones, and may be chimeric, primatized or humanized.

Exemplary immunoglobulin (antibody) building blocks include tetramers. Each tetramer is composed of two identical pairs of polypeptide chains, each pair having one "light chain" (about 25kDa) and one "heavy chain" (about 50-70 kDa). The N-terminus of each chain defines a variable region of about 100 to 110 or more amino acids, primarily responsible for antigen recognition. The terms light chain variable region (VL) and heavy chain variable region (VH) refer to these light and heavy chains, respectively.

Antibodies exist, for example, as intact immunoglobulins or as a number of well-characterized fragments produced by digestion with various peptidases. Thus, for example, pepsin digests the antibody under the disulfide bond in the hinge region, thereby producing f (ab)' 2, which is a dimer of Fab, which itself is a light chain linked to VH-CH1 by a disulfide bond. F (ab) ' 2 can be reduced under mild conditions to disrupt the disulfide bonds in the hinge region, thereby converting the f (ab) ' 2 dimer to an Fab ' monomer. The Fab' monomer is essentially a Fab with a partial hinge region (see, e.g., Fundamental Immunology (Paul ed., 3d ed. 1993). although various antibody fragments have been defined based on digestion of whole antibodies, one skilled in the art will recognize that such fragments can be synthesized from new (de novo) chemically or by using recombinant DNA methods.

As used herein, "antibody" may also refer to any functional VH and VL pair (i.e., capable of specifically binding an epitope), each linked in various configurations to other polypeptides that can perform various functions, such as a receptor, receptor inhibitor, or stabilizer of the VH-VL complex.

When referring to proteins, nucleic acids, antibodies or small molecule compounds, the phrase "specifically (or selectively) binds" refers to a binding reaction that generally determines the presence or absence of a protein or nucleic acid (e.g., STAT3, TYK2, or modified forms thereof) in a heterogeneous population of proteins or nucleic acids and other biological agents. In the case of antibodies, the binding of a given antibody to a particular protein may be at least 2-fold over background, more typically 10-fold or more to 100-fold over background, under the specified immunoassay conditions. Specific binding to antibodies under such conditions requires those antibodies to be selected for their selectivity for a particular protein. For example, polyclonal antibodies can be screened to obtain only those that have a specific immune response to the selected antigen and no specific immune response to other proteins. This screening can be achieved by subtracting out antibodies that cross-react with other molecules. A variety of immunoassay formats can be used to select antibodies specifically immunoreactive with a particular protein. For example, solid phase ELISA immunoassays are routinely used to select Antibodies specifically immunoreactive with a protein (see, e.g., Harlow & Lane, Antibodies, a Laboratory Manual (1988), which describes formats and conditions useful for immunoassays to determine specific immunoreactivity).

Nucleotide-based assays

In some embodiments, the expression of FAM171a2 and/or ITGA2B is detected by real-time or quantitative PCR using RNA from a biological sample. RNA can be extracted by any method known to those skilled in the art, for example using Trizol and RNeasy. Real-time PCR may be performed by any method known to those skilled in the art, such as Taqman real-time PCR using an Applied Biosystem assay. Gene expression was calculated relative to pooled normal lung RNA and corrected for housekeeping genes. Suitable oligonucleotide primers are selected by those skilled in the art.

In one embodiment, the RNA biomarkers are detected using nucleic acid binding molecules such as probes, oligonucleotides, oligonucleotide arrays, and primers to detect differential RNA expression in patient samples. In one embodiment, RT-PCR is used according to standard methods known in the art. In another embodiment, nucleic acids and variants thereof can be detected using quantitative PCR assays (e.g., assays available from, for example, Applied Biosystems). In other embodiments, nucleic acids can be detected using a nucleic acid microarray. Analysis of the nucleic acid may be achieved using conventional techniques, such as northern analysis, or any other method based on hybridization to a nucleic acid sequence complementary to a portion of the marker-encoding sequence (e.g., bar-blot hybridization) is also included within the scope of the present invention. Reagents that bind to the selected nucleic acid biomarkers can be prepared according to methods known to those skilled in the art or purchased from commercial sources.

Applicable PCR amplification techniques are described, for example, in Ausubel et al and Innis et al. General Nucleic Acid Hybridization methods are described in Anderson, "Nucleic Acid Hybridization," BIOS Scientific Publishers, 1999. Amplification or hybridization of multiple nucleic acid sequences (e.g., genomic DNA, mRNA, or cDNA) can also be performed from mRNA or cDNA sequences arranged in a microarray. A general description of microarray Methods is given in Hardiman, "microarray Methods and Applications: nuts & Bolts, "DNA Press, 2003; and Baldi et al, "DNA microarray and Gene Expression: from Experiments to Data Analysis and Modeling, "Cambridge University Press, 2002.

Protein-based assays and immunoassays

In another embodiment, antibody reagents may be used in assays to detect the level of expression and/or activity of a neurodegeneration biomarker of the present invention in a biological sample using any of a variety of immunoassays known to those skilled in the art. General descriptions of Immunoassay techniques and procedures are found in Price and Newman, "Principles and Practice of immunologic analysis," 2nd Edition, Grove's diagnostics, 1997; and Gosling, "Immunoassays: a Practical Approach, "Oxford University Press, 2000. A variety of immunoassay techniques may be used, including competitive and non-competitive immunoassays. See, e.g., Self et al, curr, opin, biotechnol, 7: 60-65(1996). The term "immunoassay" encompasses techniques including, but not limited to, Enzyme Immunoassays (EIAs), such as enzyme amplified immunoassay technology (EMIT), enzyme-linked immunosorbent assays (ELISA), IgM antibody capture ELISA (mac ELISA), and Microparticle Enzyme Immunoassays (MEIA); capillary Electrophoresis Immunoassay (CEIA); radioimmunoassay (RIA); an immunoradiometric assay (IRMA); fluorescence Polarization Immunoassay (FPIA); and chemiluminescence assay (CL). Such immunoassays can be automated, if desired. Immunoassays can also be used in conjunction with laser-induced fluorescence. See, e.g., Schmalzing et al, electrophophoresis, 18: 2184-93 (1997); bao, j.chromatogr.b.biomed.sci., 699: 463-80(1997). Liposomal immunoassays, such as the flow injection liposome immunoassay and the liposome immunosensor, are also suitable for use in the present invention. See, e.g., Rongen et al, j.immunol.methods, 204: 105-133(1997). In addition, turbidimetric assays are also suitable for use in the methods of the invention, wherein the formation of protein/antibody complexes causes increased light scattering, which is converted to a peak velocity signal as a function of marker concentration. Turbidimetric assays are commercially available from Beckman Coulter (Brea, CA; Kit #449430) and can be performed using a Behring Nephelometer Analyzer (Fink et al, J.Clin.chem.Clin.biochem., 27: 261-.

Detectable moieties may be used in the assays described herein for direct or indirect detection. A variety of detectable moieties can be used, with the choice of label depending on the sensitivity required, ease of conjugation to the antibody, stability requirements, and available instrumentation and processing provisions (disposal provision). Suitable detectable moieties include, but are not limited to, radionucleotides, fluorescent dyes (e.g., Fluorescein Isothiocyanate (FITC), Oregon GreenTM, rhodamine, Texas red, tetramethylrhodamine isothiocyanate (TRITC), Cy3, Cy5, and the like), fluorescent markers (e.g., Green Fluorescent Protein (GFP), phycoerythrin, and the like), self-quenching fluorescent compounds activated by tumor-associated proteases, enzymes (e.g., luciferase, horseradish peroxidase, alkaline phosphatase, and the like), nanoparticles, biotin, digoxigenin, metals, and the like.

Chemiluminescent assays using nucleic acid-specific chemiluminescent antibodies are suitable for sensitive, nonradioactive detection of protein levels. Antibodies labeled with fluorophores are also suitable. Examples of fluorophores include, but are not limited to, DAPI, fluorescein, Hoechst 33258, R-phycocyanin, B-phycoerythrin, R-phycoerythrin, rhodamine, Texas red, and lissamine (lissamine). Indirect labels include various enzymes well known in the art, such as horseradish peroxidase (HRP), Alkaline Phosphatase (AP), beta-galactosidase, urease, and the like. The horseradish peroxidase detection system can be used with, for example, the chromogenic substrate Tetramethylbenzidine (TMB), which in the presence of hydrogen peroxide produces a soluble product that can be detected at 450 nm. The alkaline phosphatase detection system can be used with, for example, the chromogenic substrate p-nitrophenylphosphate, which produces a soluble product that is readily detectable at 450 nm. Similarly, a β -galactosidase detection system can be used with the chromogenic substrate o-nitrophenyl- β -D-galactopyranoside (ONPG), which produces a soluble product that is detectable at 410 nm. The urease detection system can be used with a substrate such as urea-bromocresol purple (Sigma Immunochemicals; St. Louis, Mo.).

The signal from the direct or indirect label can be analyzed, for example: detecting the color from the luminescent substrate using a spectrophotometer; detecting radiation using a radiation counter, e.g., detecting 125I using a gamma counter; or detecting fluorescence in the presence of light of a certain wavelength using a fluorometer. For detection of enzyme-linked antibodies, quantitative analysis can be performed using a spectrophotometer such as an EMAX Microplate Reader (Molecular Devices; Menlo Park, Calif.) according to the manufacturer's instructions. The assay of the invention can be automated or robotically operated, if desired, and can detect signals from multiple samples simultaneously.

The antibodies can be immobilized on a variety of solid supports, such as magnetic or chromatographic matrix particles, the surface of an assay plate (e.g., microtiter wells), pieces of solid substrate material or membranes (e.g., plastic, nylon, paper), and the like. The test strip (assay strip) may be prepared by coating the antibody or antibodies on an array on a solid support. Such strips can then be immersed in the test sample and rapidly processed through washing and detection steps to produce a detectable signal, such as a colored spot.

Useful physical forms include surfaces having a plurality of discrete, addressable locations for detecting a plurality of different markers. Such formats include microarrays and some capillary devices. See, e.g., Ng et al, j.cell mol.med., 6: 329-340(2002). In these embodiments, each discrete surface location may comprise an antibody to immobilize one or more markers for detection at each location. Alternatively, the surface may comprise one or more discrete particles (e.g. microparticles or nanoparticles) immobilised at discrete locations on the surface, wherein the microparticles comprise an antibody to immobilise one or more markers for detection.

Analysis can be performed in a variety of physical forms. For example, microtiter plates or automated equipment may be used to facilitate the processing of large numbers of test samples. Alternatively, a single sample format may be developed to facilitate diagnosis or prognosis in a real-time manner.

Alternatively, the antibody or nucleic acid probe of the present invention may be applied to a section of a patient biopsy sample immobilized on a microscope slide. Any of a variety of optical or fluorescent microscopy methods known in the art can be used to display the resulting antibody staining or in situ hybridization pattern.

In another form, various markers of the invention also provide images of reagents for in vivo imaging, such as labeled reagents, that detect the nucleic acids or encoded proteins of the biomarkers of the invention.

Compared with peripheral blood PGRN, the cerebrospinal fluid PGRN has different regulation mechanisms, and the tumor caused by the PGRN in peripheral tissues is avoided^[12,13]And obesity^[14]The side effects of (1).

In past studies, it has been reported that a locus outside the GRN gene can regulate blood PGRN levels^[8,9]. However, there is no GWAS reporting gene regulatory factors for cerebrospinal fluid PGRN. The present invention performed a genome-wide analysis of PGRN levels in cerebrospinal fluid and observed FAM171a2 gene and its significant association. Overall, evidence from genetic, molecular and bioinformatics aspects suggests that FAM171a2 is an important regulator of PGRN expression.

Currently, several independent studies have shown that defined genome-wide loci are truly specific signals, not class I errors. First, rs708384 exhibits a rather significant p-value and has been corrected by an empirical substitution-based approach. Moreover, these loci are directly genotyped, reducing the possibility of human input errors. Second, the correlations that have been found can be repeated and validated in larger independent samples. Third, both bioinformatics and in vitro experimental evidence show that rs708384 can modulate GRN and FAM171a2 gene expression. Fourth, FAM171a2 and GRN genes are closely linked and likely to function together in the brain. Finally, the genotype of rs708384 has relevance to the risk of developing neurodegenerative diseases and their cerebrospinal fluid biomarkers. These findings are consistent with recent studies suggesting that PGRN may increase the risk of developing AD by affecting tau rather than Α β lesions^[18]。

Recently, it has been reported that the expression of PGRN is up-regulated in AD patients^[7,19]Therefore, to excludeDue to the potential bias of case selection, we excluded subjects already suffering from dementia in this study. In addition, sensitivity analysis and subgroup analysis showed that the results obtained were significant in both the a β positive and negative groups^[20]. Interestingly, subgroup analysis showed that the effect of rs708384 on cerebrospinal fluid PGRN was greater in healthy control group compared to patients with mild cognitive impairment.

GRN and FAM171a2 share in common molecular pathways that may be involved in the regulation of cerebrospinal PGRN levels. The most prominent pathway among these is the L1CAM interaction. L1CAM is axon glycoprotein and has important effect on the occurrence and survival of nerves^[21]. Although past animal experiments showed that this molecule could alleviate AD pathology^[22]It is not clear how it interacts with PGRN to participate in the development of neurodegenerative diseases. GO analysis showed that the classification associated with FAM171a2 was mainly related to oxidative stress, neuronal transport systems, sensitivity to taste and hearing, and endocytosis. There are studies showing that all of the above mentioned biological processes are associated with neurodegenerative diseases, in particular AD, PD and FTD. Future studies should focus on the role played by PGRN in these processes and how these pathways influence the development of neurodegenerative diseases.

This study has several deficiencies. First, the evaluation queue is based on the Chinese Han nationality hospital queue, and has limited representativeness. In the future, verification is required in community queues of other races. Second, although rs5848 and rs708384 have only mild to moderate LD in the CEU population, they were also included in the study as important covariates in the GWAS phase, but genotypes were not detected. To exclude potential bias from input errors, we specified the genotype of rs5949 and added it as a covariate in the analysis of replicate samples. The results show that the effect of rs708384 on cerebrospinal fluid PGRN is not completely dependent on rs 5484. Third, our in vitro experiments confirmed the effect of rs708384 on FAM171a2 and also verified that FAM171a2 and GRN expression are closely related, but the specific mechanism remains to be studied. In subsequent studies, we planned to further investigate the mechanism by which FAM171a2 modulates PGRN. We will also investigate the role of FAM171a2 in various models of neurodegenerative diseases.

Detailed Description

Preferred features and embodiments of the present invention will now be described by way of non-limiting examples.

EXAMPLE 1 Experimental materials and methods used in the invention

GWAS inclusion standard

In the discoverability cohort, we included 432 (157 healthy controls, 275 mild cognitive impairment) non-hispanic, non-demented white individuals from the ADNI-GO/2 database. Table 1 summarizes the basic characteristics of these samples. Data for GWAS was derived from ADNI database (ADNI. The raw queue containing cerebrospinal fluid PGRN and GWAS data was total 508 inclusion subjects. We limited the analysis to non-hispanic whites (n-434) avoiding the risk of bias due to population stratification. We use PLINK software (beta6.4)^[23]Pairwise whole genome pedigree estimates were performed to verify unexpected duplicates and unknown correlations between samples. Genome-wide complex assay analysis (GCTA) for calculating basic information and determining ethnicity of samples^[24]. Two marginally included subjects were removed and 432 subjects were finally included (FIG. 12)

The study was approved by an institutional review board with all participants and written informed consent was obtained from all participants or authorized representatives.

Table 1 basic characteristics of GWAS samples

Table 1 notes: the detection of the significance of the differences between the two different diagnostic groups was done by a two-sample t-test or the mann whitney U-test (applicable to continuous variables) and the Pearson chi-square test with continuity correction (applicable to categorical variables). The results showed age (p ═ 1.38 × 10)^-6) The ratio of APOE4 carriers (p ═ 1.367) differed between the two diagnostic groups.

Gender (p-0.2171), PGRN level (p-0.9304) and PGRN measured coefficient of variation (p-0.2003) were not significantly different between groups.

Cerebrospinal fluid PGRN level measurement

Cerebrospinal PGRN detection by Mass Spectrometry platform (MSD)^[25]Enzyme-linked immunosorbent assay (ELISA) detection. All cerebrospinal fluid samples were randomly distributed on the platform and duplicate tests were set up. All antibodies or test plates were used with a single lot number to avoid variation between batches. The experiment was performed by an experienced operator and clinical information was blinded. The mean Coefficient of Variation (CV) within the batch was 2.2% (all replicate measures had a coefficient of variation of less than 15%); the mean inter-batch coefficient of variation was 4.21%. PGRN levels were available for analysis after correction batch to batch variation.

Genotype detection and input

ADNI-GO/2 sample genotypes were determined by a Human Omniexpress BeadChip (Illumina, Inc, San Diego, Calif.). Prior to the correlation study, all samples and genotypes were subjected to strict quality control, with the following criteria: SNPs response rate > 95%, individual response rate > 95%, minimum allele frequency > 0.2 and Hardy-Weinberg equilibrium detection p > 0.001. The original database contains 710618 gene type compilations including rs7412 and rs429358, these genotypes are measured by using APOE gene detection kit alone, in order to define APOE epsilon 2/epsilon 3/epsilon 4 subtype^[26]The methods are as conventionally used in the art. According to the standard procedure, information entry is done by Beagle software (version 5.0), referenced to HapMap GRCh 37. For Beagle R2 < 0.8, the response rate < 95%, the minimum allele frequency was less than 0.2 and SNPs with a Hardy-Weinberg equilibrium detection p <0.001 were removed. Finally, upon screening and command, 3262988 SNPs were co-input and determined for analysis.

Statistical method

As the PGRN value of cerebrospinal fluid is distributed in a skewed state (p is less than 0.05 by using a shapero-wilk test). The R language toolkit is used for data transformation to obtain data presenting normal distribution. Analysis of cerebrospinal fluid PGRN levels and Gene polygamy Using a Linear regression model in the PLINK v1.9 software with Gene model additionCorrelation of attitude. Stepwise linear regression analysis was used to test whether cerebrospinal fluid PGRN levels were affected by factors such as diagnosis, age, sex, education, APOE epsilon 4 allele, and PGRN measured coefficient of variation. Those factors with p < 0.2 were included as covariates. To correct for the confusion of genetic predictions that may lead to population stratification, the first three main components of the genetic relationship matrix between pairs of individuals are further included as covariates. Meeting biomarker criteria for AD in view of 30% of non-demented elderly^[27]A subset analysis of the pathological state of Α β (a positive vs. negative) was first performed according to the Α T N criteria, where a positive was defined as positive evidence of brain Α β deposition detected by PET (AV 45)>1.11) or cerebrospinal fluid (Abeta)<192pg/ml)^[28]. We further excluded those individuals who progressed to dementia within three years from baseline. Sensitivity analyses including rs5848(GRN, estimates), age and diagnosis as covariates were also performed, as studies have shown that PGRN levels are affected by these factors^[11,19]. Stratification analysis was performed according to gender and diagnosis was performed to check for stratification effects.

By exploring the specificity of the association with the most significant signal (SNP with the smallest P-value), it was examined whether the association was affected by other cerebrospinal proteins related to neurodegenerative diseases, including A β, P-tau181(P-tau), total tau (T-tau)^[29]Alpha synuclein (alpha SYN)^[30]Neurofilament light chain (NFL)^[31]And in myeloid cells 2(sTREM2)^[32]The secreted trigger receptor expressed above. The measured data for all these proteins were downloaded from ADNI: 1) the association of the most significant signals with these proteins was explored separately by univariate linear regression; 2) estimating the relation between the cerebrospinal fluid PGRN standardized level and other cerebrospinal fluid proteins by using the correlation coefficient of product moment of Pearson; 3) these cerebrospinal fluid proteins were included in the model as covariates, respectively. At R v3.5.1, PLINK v1.9^[23]GCTA v1.91.6beta^[33]And LocusZoom v1.3^[34]Statistical analysis and data visualization were performed.

Statistical significance after correction by Bonferroni was defined as p<5×10^-8And p <1×10^-5Considered to be an suggestive association. To determine other independent genetic signals, conditional analysis was performed by adding the most significant SNPs as covariates and testing the association of SNPs for all remaining regions. As an additional method to exclude possible false positive results, an empirical p-value was generated using the PLINK max (T) permutation test with 5,000 permutations to make multiple test corrections. The R software package "qqman" shows genome-wide associations. Scale elucidation for genome partitioning to estimate phenotypic variance using the algorithm GCTA^[35]。

Repetitive queue

As an independent repetitive cohort, non-demented elderly in northern han are from the alzheimer biomarker and lifestyle (CABLE) study in china, which has been approved by the institutional review board of the Qingdao city hospital. Since 2017, CABLE has been an ongoing large-scale study, mainly investigating risk factors and biomarkers of AD in Chinese Han population. CABLE aims to determine genetic and environmental modifiers of biomarkers for AD and their utility in early diagnosis. Study individuals were recruited in Qingdao urban hospitals in Shandong province, China.

All participants were han nationality aged between 40 and 90 years. Exclusion criteria included (1) central nervous system infection, head trauma, epilepsy, multiple sclerosis or other major nervous system disease; (2) major psychological disorders; (3) severe systemic diseases (e.g., malignant tumors); (4) family history of genetic diseases: all participants underwent clinical and neuropsychological assessments, biochemical tests and blood and cerebrospinal fluid sample collection, and demographic information and medical history was collected via structured questionnaires and electronic medical record systems.

The level of cerebrospinal fluid PGRN in CABLE was determined using a human Progranulin ELISA kit (Biovector laboratory research, Inc. of C. zech Reublic) on a microplate reader (Thermo scientific MK 3). Samples were diluted ten-fold and run in duplicate. Association of the most important loci (selection of the most significant SNPs in the discovery phase for validation. several sites were selected for Restriction Fragment Length Polymorphism (RFLP) technology for genotyping, including rs708384 (the most significant SNP used for validation), rs5848 (an important confounding factor in GRN), two loci associated with APOE4 status (rs7412 and rs429358), and three loci associated with blood PGRN of previous GWAS (rs660240, rs 47197 and rs 646776.) until 2019 for 10 months, eligibility measurements for PGRN and genotyping were performed on 930 non-dementia patients. data analysis by linear regression in R language, adjusted for age, cerebrospinal fluid, education, APOE4 status, coefficient of variation of baseline and PGRN measurements. We also examined whether the locus associated with blood PGRN also affects its level in cerebrospinal fluid.

Bioinformatics analysis

NCBI database Using Single nucleotide polymorphisms (dbSNP, GRCh37/hg19 program set, 105 th edition) http:// www.ncbi.nlm.nih.gov/SNP /)^[36]，SNPnexus(http://www.snp-nexus.org)^[37]And SNP and CNV annotation databases (SCAN) (http:// www.scandb.org/newonterface/index _ v1.html using HaploReg v4.1[ 38:// www.scandb.org/newonterface/index _ v1.html]RegulomeDBv1.1 (internal version 141 of dbSNP)^[39]And 1000genome Project (http:// www.internationalgenome.org /) examined potential regulatory functions. Linkage disequilibrium analysis was performed based on data from 1000genome research projects (EUR and CHB). The variants marked by the most significant SNPs were used for the following enhancer enrichment analysis and expression analysis.

Enhancer enrichment analysis was performed by HaploReg v4.1 to assess in which cell types the marker variants were significantly enriched. Using roadmap epigenomic data enhancers were defined by four different methods (including 15-State core model, 25-State model incorporating a putative epigenome, H3K4me1/H3K4me3 peak and H3K27ac/H3K9ac peak)^[40]. Using MAF in all populations>All 1000 genomic variants in 5% were binomially tested as background. A total of 28 blood cells and 13 brain cells were selected for this analysis.

To verify the enhancer enrichment fractionThe results of the analysis and characterization of these associations, expression analysis was performed to determine: 1) whether the expression level of the gene in which the important locus is located is correlated with the control status of AD cases. AD blood was studied by analyzing gene expression profiles from GEO using NCBI network tool GEO2R^[41]And the brain^[42]Differential expression of the genes identified in (a) (fig. 9). http:// www.ncbi.nlm.nih.gov/geo/geo2r /) and AlzData Web Server^[43](www.alzdata.org). After multiple test adjustment, the P value<0.05 was considered statistically significant; 2) whether SNPs associated with cerebrospinal PGRN also affect the expression levels of protein-coding Genes (GRNs) in brain and blood [44](ii) a 3) Whether important SNPs are correlated with expression levels or not is the number of candidate genes in each locus. To this end, quantitative signature loci were expressed (using multiple publicly available datasets in human Brain tissue (including Brain Expression GWAS eQTLs dataset)^[45]And Genotype Tissue Expression^[46]) And whole Blood (including Blood eQTL browser [47 ]]) The analysis is carried out, and a gene expression architecture browser is adopted^[48]NCBI molecular QTL browser [49]Search database and Framingham Heart research eQTL database federation^[49]. eQTL results were also searched from 1000genome projects; 4) public RNA sequence data (https:// genemtwork. nl) and GTEx expression data of 31499 samples were used to express data via a GEPIA web server^[50](http：//gepia.cancer-pku.cn/index.html)。

Characterization analysis and Path analysis of Gene Ontology (GO)

Association list GO annotator (ALIGATOR) method [51]For searching for Gene Ontology (GO) terms and KEGG pathways. If the SNP is within 1Mb and is at high LD (r)²> 0.8) and the index value is SNP (defined as p-value)<1.0×10^-4) They form a cluster. These SNPs were mapped to genes using the SNP annotation tool described above. SNPs are localized to the gene if they are located within 20kb of the gene. Genes were counted only once, regardless of how many SNPs mapped to the gene. Finally, 34 genes were included in total.

Using a protein assay representing evolutionary statistics (PANTHER) to represent the statistical test v9.052](www.go.pantherdb.org/org /) and representative Gene set Consensus Pathway Database (CPDB) analysis of Gene ontology Release 33 on biological representation [53](http:// cpdb. molgen. mpg. de /). Both used data from the gene ontology union (http:// www.geneontology.org) and calculated candidate genes against different backgrounds (18,043 genes for CPDB, 20,814 genes for PANTHER). Of the 34 genes analyzed, CPDB identified all genes, while panarter assigned at least one GO to 29 genes. The generated p-values were corrected using the FDR method in CPDB for multiple tests (p < 0.05). For PANTHER, the p-value after adjustment (six independent tests) using Bonferroni (p < 8.33X 10)^-3)。

In addition, we used sources of diverse sets of pathways, including the encyclopedia of genes and genomes in the Kyoto protocol (8/1/2018, https:// www.genome.jp/kegg: `^[54]，PANTHER v8.1)^[52]Reactomepathways, v65 (13.6.2018, https:// reactor. org /)^[55]Wikipathways (https:// www.wikipathways.org/index. php/Wikipathways) and priority and function assessment (PAFA, http:// 159.226). 67.237: 8080/pafa^[56]. Finally, the function of the gene network is predicted based on the functional richness of its common regulatory partners using the GeneNetwork Assisted Diagnostic Optimization (GADO) tool (www.genenetwork.nl).

In vitro experiments

1) Luciferase reporter plasmids and antibodies

The plasmid was purchased from gima pharmaceutical limited, shanghai, china. Briefly, we cloned an approximately 500bp region of intron 1 of FAM171a2 containing SNP rs708384 or the wild-type site and inserted the cloned fragment into a pGL3 promoter vector containing the SV40 promoter upstream of the firefly luciferase (luc) reporter gene. Empty pGL3 promoter vector was transferred as a system control. anti-FAM 171a2 antibody (ab121614, IHC and IF dilution ratio 1: 20). anti-FAM 171a2 antibody (Proteintech, 208361 AP, 1: 500 for western blot). anti-CD 31 antibody (ab 24690, IF dilution ratio 1: 250). anti-GRN antibody (ab108608, western blot dilution 1: 1000). Anti-beta-actin antibody (Affinity, AF7018, western blot dilution ratio 1: 1000).

2) FAM171A2 gene silencing and overexpression

In vitro silencing of FAM171a2 was achieved by siRNA (purchased from GenePharma Company Ltd, shanghai, china). The sequence is as follows: 5 'GCAAUGGCACUGGUGUAAUTT 3', 5 'AUUACACCAGUGCCAUUGCTT 3'. FAM171a2 overexpression plasmid was purchased from GenePharma. The pEX-3 vector was used for plasmid construction. Both FAM171a2 siRNA and plasmid were transferred to human umbilical vein endothelial cells by lipofectamine 2000. Silencing and overexpression effects were confirmed 48 hours after transfection.

3) Cell culture

Human umbilical vein endothelial cells we used were purchased from iCell, shanghai, china. This cell line immortalizes human primary umbilical vein endothelial cells by lentivirus transformation in 2018, and the cell purity has been confirmed by CD31 IF staining. The cells were cultured in ECM + 5% FBS + 1% endothelial growth factor + 1% penicillin/streptomycin (P/S). HEK293 cells were purchased from the institute of cell research, academy of sciences, china. Cells were cultured in DMEM + FBS + 1% P/S. The incubator was kept at 37 ℃ and 5% CO 2. Cells were plated at 1: 3 subculture until 80% confluency is reached.

4) Dual luciferase reporter assay

According to Promega Dual

The technical manual of the Reporter analysis system performs the analysis. Firefly and Renilla luciferase reporter plasmids (5: 1) were co-transferred into HEK293 cells by lipofectamine 2000. After 24 hours, the cells were homogenized with passive lysis buffer. Luciferase assay reagents II and Stop&

Reagents are added sequentially to the lysate. The luminous intensity was detected by a Synergy H1 multifunction detector and using a light module.

5) Immunohistochemistry

Mice were deeply anesthetized by intraperitoneal injection of sodium pentobarbital and perfused with normal saline, followed by injection of 4% w/v Paraformaldehyde (PFF). Coronal sections were taken of hippocampus and cortex using a cryomicrotome and 30 μm serial sections were collected. Sections were incubated for 1h in blocking buffer (0.01

% TX

100, 20% normal goat serum in PBS, pH 7.4) 7.4. Subsequently, sections were incubated overnight at 4 ℃ in rabbit anti-FAM 171a2 primary antibody, followed by incubation for 2h at room temperature in biotinylated secondary antibody. After 3 washes, sections were incubated in avidin biotin complex (ABC Standard, Vector Laboratories) and developed by using 0.025% 3,3' diaminobenzidine and 0.1% H2O 2. The sections were then stuck to a microslide and immersed in hematoxylin solution for 1 minute, followed by washing with deionized water. After treatment with ethanol and dimethyl benzene, the slices were mounted with neutral gum. The images were taken using an Olympus camera (DP 72; Olympus).

6) Immunofluorescence staining

The process is similar to immunohistochemistry. Brain sections were incubated with rabbit anti-FAM 171a2 antibody and mouse anti-CD 31 antibody and shaken overnight. After washing, the sections were immersed for 2 hours in goat anti-rabbit alexflur 488 and goat anti-mouse alexflur 647, then washed and observed with Olympus FV10 laser confocal microscope.

7) Western blot

30 μ g of protein was loaded into 10% SDS PAGE gel lanes. Transfer film (PVDF) conditions: a constant current of 250mA was continued for 90 minutes. Membranes were blocked with 5% BSA for 1 hour and incubated overnight in rabbit anti-GRN antibody. After washing, the membrane was incubated with HRP conjugated secondary antibody for 2 hours. The blot was visualized using a Super Signal West Pico chemiluminescent substrate (Thermo Fisher Scientific Inc.). The grayscale was measured by Image J software. All experiments were set up for 3 replicates. The final data is expressed as the ratio of the Relative Optical Density (ROD) of the target protein to the β -actin ROD.

8) Enzyme-linked immunosorbent assay

We used the R & D progranulin quantikine ELISA kit to detect the PGRN content of the supernatant. The experiments were performed according to the manual of the ELISA kit. Briefly, 50. mu.l of cell supernatant was added to each well and incubated at room temperature for 2 hours. After 4 washes, 200 μ l of human PGRN conjugate was added per well, at a wash rate of 400 μ l per well, and incubated at room temperature for 2 hours. 200ul of substrate solution was then added to each well and incubated for 30 minutes at room temperature. Finally, the reaction was stopped by 50. mu.l of stop solution per well. The OD of each sample was measured at 450nm over 30 minutes and corrected for by 540 nm. The PGRN content was calculated from OD according to the standard curve.

9) Statistics of

Data are presented as mean ± standard deviation. Differences were tested by one-way analysis of variance, Turkey post hoc analysis, and unpaired t-test using GraphPad Prism 8 software (version 8.0.2, GraphPad software, inc. P <0.01 is considered statistically significant.

Correlation between the most significant signals and neurodegenerative diseases

The impact of the most significant SNPs on the cognition, brain Α β deposition, FDG and volume/thickness of brain regions of interest (hippocampus, parahippocampus, posterior cingulate gyrus, anterior foetal, cuneiform, entorhinal cortex and mid-temporal lobe regions) was further explored using ADNI. Patients who developed AD in the first three years were excluded. A linear regression model was performed to determine the correlation with the above-mentioned indicator at baseline. A diagnostic-based subgroup analysis (HC vs MCI) was performed. The R package "lm" is used to perform the above analysis. In addition, AD is searched^[15]，PD^[16](http://www.pdgene.org/)、ALS^[57](http:// www.alsgene.org /) and FTD^[17 ^,58-61]Of the previous GWAS on the correlation of the most significant signal with the risk of neurodegenerative disease.

Data and material availability:

all ADNI data can be accessed via LONI image and data acquisition archive (IDA) and interested scientists can apply for access on ADNI website (https:// IDA. LONI. usc. edu/collaboot /)

Example 2 two-stage GWAS screening

The present application first analyzed the genetic information of 432 non-demented healthy individuals and their cerebrospinal fluid PGRN levels in the ADNI database. The results are as follows.

2.1 cerebrospinal fluid PGRN levels were affected by sex, education and APOE4 levels.

In the GWAS cohort, gender may significantly affect cerebrospinal fluid PGRN levels (p ═ 3.87 × 10⁵Beta-0.003 APOE epsilon 4 allele (p-0.08, beta-8.73 × 10)⁴) And the degree of education, also has potential impact. (p is 0.12 and beta is 1.77X 10)⁴). Age (p 0.48) and clinical diagnosis (healthy control vs mild cognitive impairment, p 0.21) had no significant effect on cerebrospinal PGRN levels.

2.2 some common mutations located in FAM171a2 were associated with altered levels of cerebrospinal PGRN.

The GWAS study included a total of 432 non-demented individuals (157 healthy controls and 275 mild cognitive impairment individuals). Age (p ═ 1.38 × 10)^-6) And APOE e4 allele frequency (p ═ 1.37 × 10^-6) The difference was significant between the two groups. Table 1 sex, education, APOE epsilon 4 allele and the first three major components were adjusted and no differences due to population stratification were found (λ ═ 1.012). In total, 18 single nucleotide polymorphisms (5 in FAM171a2 gene, 12 in ITGA2B gene, and rs5848 in GRN gene) of chromosome 17 were found to be significantly associated with cerebrospinal fluid PGRN levels. Of these, rs708384 located in FAM171a2 has the most significant correlation (p ═ 5.09 × 10)^-12). (Table 2 and FIG. 1a) rs708384, located in the transcription factor binding region (intron 1) of FAM171A2 gene, was also corrected empirically based on alignment and measured multiple times (empirical p ═ 0.0002) (FIG. 1b)

TABLE 2 significant correlation with cerebrospinal PGRN levels (p < 10)^-8) SNP site list of

Table 2 notes: SNP-single nucleotide polymorphism; NA is no data;

^#from the HaploRegv4.1 online database, rs708383 and rs708384 are completely linked mismatches (r)²＝1)。

^*The smaller the value, the variation is located at the baseThe greater the probability of a functional domain (http:// www.regulomedb.org/help # score)

^&P1 ═ P value of GWAS; p2-empirical P value; p3-empirical family error rate after correction based on permutations; empirical P value after P4 ═ rs 708384.

In addition to being located at the site of FAM171a2, 13 single nucleotide polymorphisms on the ITGA2B and GRN genes were also associated with cerebrospinal fluid PGRN levels (empirical p ═ 0.0002 was controlled at < 0.005 based on the empirical family error rate of substitutions). Notably, 8 loci and rs708384 present linkage mismatches (r)²Not less than 0.8). After rs708384 was set as the controlling factor, the correlation signals for all sites were significantly reduced (p > 0.1), indicating that the correlation for these sites is dominated by rs708384 (table 2, fig. 1c and 1 d). We also analyzed 149 suspected positive loci (92% of which are located on FAM171a2, ITGA2B, and GPATCH8 genes on chromosome 17), however, their differences were not significant after empirical correction based on substitutions (table e-1). In summary, rs708384 located on FAM171a2 gene is the most significantly different SNP, its minor allele (a allele, MAF 0.4074) is most closely related to the reduction in PGRN level in cerebrospinal fluid, and is dose-dependent (p 3.95 × 10)^-12) (FIG. 2).

TABLE e-1 loci likely to be associated with cerebrospinal fluid PGRN levels

Subgroups and sensitivity analysis

Subgroup analysis showed that minor allele (A) of rs708384 was associated with cerebrospinal fluid PG both within the class divided by gender and initial diagnosisReduced RN levels are associated (male, p ═ 2.67 × 10)^-6(ii) a Female, p ═ 1.76X 10^-6(ii) a Healthy control, p ═ 0.017; mild cognitive impairment, p ═ 1.36 × 10^-11). It is noted that the magnitude of the effect appears to be dynamically increased in healthy control population (beta value of 100.9 in healthy control population; beta value of 8.77 × 10 in mild cognitive impairment population)^-5) (FIG. 8A). Since cerebrospinal fluid PGRN levels are affected by age, diagnosis and rs5854 located at the GRN gene, it is necessary to further correct these confounders by sensitivity analysis. Age corrected and baseline diagnosis did not significantly affect outcome (p ═ 3.51 × 10^-12). After rs5848 correction, although the correlation between rs708384 and cerebrospinal PGRN levels decreased, it was still significant (p ═ 8.28 × 10^-5) (FIG. 8B). The initial diagnosis had little impact on outcome except for those patients who had recently suffered from AD within three years, and therefore rs708384 was still the most significant SNP (n 359, p 4.73 × 10)^-10) (FIG. 8C) furthermore, subgroup analysis based on A.beta.lesion stage showed that both groups had the same dose-dependence. (Abeta-negative group p < 5X 10)^-4(ii) a Abeta Positive group p ═ 1.07X 10^-7)。

rs708384 specificity associated with PGRN

We found by examination that other proteins associated with neurodegenerative diseases do not affect the currently observed association between the two. First, there was no significant change in significance following incorporation of cerebrospinal fluid A β 42, T-tau, P-tau, α -SYN, NFL or sTREM2 into the covariates. Secondly, no clear association between biomarkers such as Abeta 42 or P-tau and rs708384 was found (r)²The range of change in value is 0.04 to 0.1). Cerebrospinal PGRN levels and T-tau (p ═ 0.04, r ═ 0.1), α -SYN (p ═ 0.0003, r ═ 0.36), NFL (p ═ 0.03, r ═ 0.22) and sTREM2(p ═ 1.134 × 10)^-8And r ═ 0.27) only weakly. In addition, when the above proteins were taken alone as the intrinsic phenotype, no association with rs708384 was found. In summary, the above results show that our results are sufficiently specific. (Table e-2)

TABLE e-2 specificity of correlation with PGRN levels

Part of the variation in cerebrospinal PGRN levels that can be explained by gene mutations.

We also used genomic compartmentalization analysis to estimate the chromosomal and important gene, locus interpretable part of the variation in PGRN levels in CSF. All genotypes and encompassing mutations of chromosome 17 account for 17.4% of the variation in PGRN levels in cerebrospinal fluid (p < 0.05) (fig. 3 a). Notably, most of the significant sites and rs708384 have stronger LD (r)²≧ 0.8) (FIG. 3 b). SNPs on the GRN gene could account for only 13.3% of PGRN variations, suggesting that mutations other than the GRN gene also play a role. Rs808384 accounted for 9.1% variation with the smallest p-value (p ═ 2.6 × 10)^-10) (FIG. 3 c). Although there is no rs5848 genotype in the ADNI database, there are 1000 genome-related items of data that show only mild to moderate LD (r 5848 and rs708384 in the CEU population (r 708384)²0.6) (fig. 3 b). Nor is rs5848 present the LD locus.

Therefore, we reasonably conclude that the locus with significant association that has been observed so far is more likely to be affected by rs 708384.

Independent queue validation and meta analysis

We considered rs708384 to be the most relevant SNP to cerebrospinal fluid PGRN levels, and to verify authenticity we measured again cerebrospinal fluid PGRN levels and rs708384 genotype in another larger independent cohort. The cohort contained 930 non-demented northern chinese hans (table 3). In this cohort, subjects were included in the age range of 40 to 88 years (mean age 62.6 years, standard deviation 10.4 years) when cerebrospinal fluid was collected. The sex distribution is 380 men and 550 women, which are representative. The mean PGRN level in cerebrospinal fluid was 1739pg/ml (standard deviation 372 pg/ml). The average intra-batch coefficient of variation was 2.95% and the average inter-batch coefficient of variation was 3.82%. By verification, we reached the same conclusion as before, namely: including age, sex, education, APOE4 genotype, baseline MMSE score and coefficient of variationIn a linear regression model of the parameters, the a allele of rs708384 and the decrease in cerebrospinal fluid PGRN levels were significantly correlated. (p is 7.47X 10)^-9FIG. 4)

TABLE 3 summary of basic features of CABLE samples

To exclude the potential effect of rs5848 on the GRN gene, we also examined this genotype and incorporated it into covariates. One-way regression analysis showed a significant correlation between rs5848 and cerebrospinal PGRN levels (p < 0.005). However, after incorporation of rs708384 into the covariate, rs5848 is no longer significant (p ═ 0.88). After controlling rs5848, the correlation between rs708384 and cerebrospinal PGRN levels is still significant (p ═ 0.1). This may be due to the high but incomplete LD (r) of rs5848 and rs708384 in the Han population²0.8, fig. 3 d). More importantly, the additive model (AA vs CC) showed that the correlation of rs708384 was still significant (p < 0.05) after controlling rs5848 and other covariates (Table e-3). This indicates that the effect of rs708384 on cerebrospinal PGRN is not dependent on rs 5848. Biphasic meta analysis further supported the correlation of rs708384 and cerebrospinal fluid PGTN levels (p ═ 1.74 × 10^-18). Furthermore, we also examined the correlation between loci known to be associated with peripheral blood PGRN levels and cerebrospinal fluid PGTN levels, and found no significance, suggesting that PGRN exists in different gene regulatory mechanisms in cerebrospinal fluid and peripheral blood. (Table e-3)

Table e-3. correlation results in repetitive queues.

Table e-3 notes: all analyses were corrected for age, gender, education, APOE4 mutation, and baseline MMSE score.

^*Rs7082384 and Rs5848 were both added to the regression model

Functional annotation of the strongest signal in FAM171a2 gene.

The enhanced enrichment analysis showed that the rs708384 labeled mutations were significantly enriched in some brain regions (e.g., the middle hippocampus, the inferior temporal lobe and the prefrontal lobe) (Table e-4), suggesting that these mutations may be associated with gene regulation in these brain regions. In addition, we found that FAM171a2 was significantly differentially expressed in endothelial layers of AD patients (p ═ 0.004, fig. 9). Furthermore, eQTL analysis showed that some mutations in rs708384 and its markers could potentially affect GRN expression (Table e-6) in blood (Table e-5) and in some brain regions (pre-circulating cortex and prefrontal cortex). In addition to GRN, rs708384 is also associated with expression of FAM171a2, ITGA2B in various tissues, such as the prefrontal lobe (table e-7). All the above evidence shows that the rs708384 site located in the transcription factor binding region can regulate the expression and function of GRN and FAM171A2 genes. More interestingly, we found expression of GRN gene and FAM171a2 gene (p ═ 1.1 × 10^-17) In the brain (p ═ 5.3X 10)^-10) And peripheral blood (p ═ 3.1 × 10)^-6) All have significant correlation.

TABLE e-4 enrichment analysis of enhancers

Table e-4 notes: p <0.05 was considered to be significantly different. O, observed (observed); e, expected (expected); BLD, blood (blood); BRN, brain (brain).

TABLE e-5 marked variations and Gene expression in peripheral blood

Table e-5 notes: p <0.05 was considered significantly different. NA is unknown, z score is beta/standard error, beta is a regression coefficient based on the valid allele. Beta > or <0 indicates the up-or down-regulation of the gene expression, respectively, in which the allele is located. The data set is [1] http:// www.genenetwork.nl/bloodeqtlowser/[ 2] http:// cnsgenomics.com/shiny/CAGE/[3] https:// preview.n cbi.nlm.nih.gov/gap/estl/studies:/[ 1] https

TABLE e-6 marked variations and Gene expression in brain tissue

Table e-6 notes: cerebellum (cerebellum) TX parietal cortex (temporal cortex)

TABLE e-7. influence of Rs708384 and Rs5848 on FAM171A2-GRN-ITGA2B expression

FAM171a2 may co-occur with the GRN gene in several common pathways.

Both can yield many enriched categories: there were 96 classes in the PANTHER analysis and 107 classes in the CPDB analysis. A total of 34 significant classes appeared in both analyses (table e-8). These classes are generally involved in regulating nervous system development, molecular transport, signal transduction, cell-cell adhesion and stress response (FIG. 5 a). More importantly, gene network analysis revealed 31 most significant (p <0.001) classes, constituting 4 gene clusters. As expected, the most significant genes (GRN, FAM171a2 and ITGA2B) were enriched together (fig. 5 b). In addition to the above classification (p <0.001), the GO entries for this particular cluster include two new classifications: blood pressure regulation (p ═ 3.84 × 10)^-4) And interleukin-8 secretion (p ═ 4.2X 10)^-4)。

Among the 16 pathways with statistical differences (p < 0.05) (12 from REACTOME and 4 from KEGG), the mutual lease between L1 cell adhesion molecules (L1CAM) was the most significantly different pathway (REACTOME, p ═ 2.49X 10^-6). In this pathway, FAM171a2 and GRN genes also acquired the highest z-value (fig. 5 c). Interestingly, other prominent pathways were also associated primarily with cell-cell interactions (Table e-9).

TABLE e-8 GO classes that differ significantly in both PANTERER and CPDB analyses

TABLE e-9 pathway analysis

Example 3 FAM171A2 expression study

Before studying the function of this gene, it is necessary to define its localization in the brain. We therefore performed immunohistochemistry and immunofluorescence staining with mouse brain sections. In the cortex and hippocampus, regions running along or around the blood vessels we observed significant DAB staining (fig. 6a,6 b). In the corresponding brain regions, immunofluorescent staining of FAM171a2 was co-localized with CD31 (vascular endothelial cell marker) (fig. 6 c). We also observed FAM171a2 expression in mouse primary cerebrovascular endothelial cells. The above results indicate that FAM171a2 is relatively abundantly expressed on vascular endothelial cells.

Example 4 rs708384 can modulate the expression levels of FAM171A2 and GRN genes

We performed a dual luciferase reporter assay with HEK293 cells to confirm the regulation of FAM171a2 expression by rs 708384. Compared to the wild type, we observed a significant increase in the ratio of the reporter genes firefly luciferase to Renilla luciferase luminescence intensity after C mutation to A, indicating that the above mutation significantly increased the expression of FAM171A2 (FIG. 7 b).

Next, we examined the effect of increased FAM171a2 expression on PGRN levels. Following overexpression of FAM171a2 in human umbilical vein endothelial cells, we observed a significant decrease in intracellular GRN protein expression as well as in the levels of PGRN in the cell supernatant (fig. 7c d e), consistent with clinical data. Meanwhile, we observed an up-regulation of GRN expression in cells following FAM171a2 silencing (fig. 10a, b). These results show that increased FAM171a2 expression can reduce PGRN levels, while silencing can have the opposite effect.

Example 5 Effect of rs708384 on the phenotype of neurodegenerative diseases

A β is a marker present in cerebrospinal fluid that is associated with risk of neurological damage, cognitive function, brain structure/metabolism and neurodegenerative diseases (AD, PD, ALS and FTD etc.), therefore, we investigated whether rs708384 is associated with pathological manifestations of a β. The AA genotype of Rs708384 was associated with increased tau levels in cerebrospinal fluid (fig. 11a) and decreased overall cognitive function (fig. 11b, c). Rs708384 was not found to be associated with a β pathological manifestations, cerebrospinal p-tau levels and structural and metabolic features of brain regions of interest. It has been found that rs708384 can mark 10 r²A variant of not less than 0.8. In large-scale GWAS databases, these loci have significant associations with risk factors for AD, PD, LTD, etc. diseases, particularly the a allele is associated with an increased risk of developing these diseases (AD: p ═ 0.01, PD: p ═ 1.42 × 10-5, FTD: p ═ 0.04). No locus of rs708384 and its markers was found to be associated with risk of ALS onset. (Table e-10).

Table e-10: variants tagged with significant SNP markers and markers of neurodegenerative disease susceptibility

Table e-10 notes: significant associations with p <0.05 are shown in bold. Beta, the overall estimated magnitude of the effect allele; SE, total standard error of effect size estimation; p-value, meta analysis uses regression coefficients (β and standard error) to derive the p-value. Beta is a regression coefficient for the effect allele based on the addition model. Chromosome 17 position (GRCh 37); beta >0 and Beta <0 indicate that this effector allele increases and reduces the risk of AD, respectively. None of these variations was identified at the 1+2GWAS stage. IGAP first stage GWAS; the above loci are not found in phase two GWAS. # meta p values for PD, ALS and FTD in previous GWAS; (reference: Human Molecular Genetics,2008, Vol.17, No. 2336313642, doi:10.1093/hmg/ddn257)

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Claims

1. a method of determining whether an individual is at risk of having a dysregulated level of a Progranulin (PGRN), the method comprising determining the level of one or more biomarkers in one or more samples obtained from the individual, wherein the one or more biomarkers comprise FAM171a 2.

2. The method of claim 1, wherein said determining the level of one or more biomarkers in one or more samples obtained from said individual is effected by determining a polymorphic site thereof that affects the expression thereof, said one or more biomarkers comprising FAM171a 2.

3. The method according to claim 2, wherein the polymorphic site is the single nucleotide polymorphic site rs708384 of FAM171a2 gene.

4. The method of any preceding claim, wherein the method further comprises determining the level of one or more biomarkers in a sample obtained from the individual selected from the group consisting of: ITGA 2B.

5. The method of any preceding claim, wherein the level of FAM171a2 and/or ITGA2B is determined in one or more cerebrospinal fluid (CSF) and/or serum samples.

6. A method of treating or preventing a disease resulting from a deregulated PGRN level, said method comprising the steps of:

(a) determining whether an individual has or is at risk of developing a PGRN level imbalance according to the method of any one of claims 1-8; and

(b) knockdown and/or inhibition of the expression level of FAM171a2 in vivo.

7. A method of preventing or reducing the risk of developing a neurodegenerative disease, the method comprising the steps of:

(b) knockdown and/or inhibition of the expression level of FAM171a2 in vivo.

8. The method of claim 6 or 7, wherein the expression level of FAM171a2 is knocked down and/or inhibited in vivo by administering an siRNA specific for FAM171a2, wherein the sequence of the specific siRNA is 5'-GCAAUGGCACUGGUGUAAUTT-3', or 5'-AUUACACCAGUGCCAUUGCTT-3'.

9. A pharmaceutical composition comprising a substance that knockdown and/or inhibits the expression level of FAM171a2 in vivo.

10. The pharmaceutical composition according to claim 9, wherein the substance that knockdown and/or inhibits the expression level of FAM171a2 in vivo is a specific siRNA, shRNA against FAM171a2 gene, or a specific antibody against FAM171a2 protein.