Method and kit for detecting genetic factors related to the severity of COVID-19

Abstract

To provide novel methods and kits for detecting a genetic factor leading to serious conditions of COVID-19.SOLUTION: A method for detecting a genetic factor leading to serious conditions of COVID-19 includes detecting one or more single nucleotide polymorphisms in the region from the interleukin-17A gene locus to the interleukin-17F gene locus in a subject-derived DNA-containing sample. A kit for detecting a genetic factor leading to serious conditions of COVID-19 includes one or more nucleic acid probes or primers to detect one or more single nucleotide polymorphisms in the region from the interleukin-17A gene locus to the interleukin-17F gene locus.SELECTED DRAWING: None

Description

[Technical Field]

[0001] The present invention relates to a method and kit for detecting genetic factors that contribute to the worsening of COVID-19. [Background technology]

[0002] As of April 2021, the number of people infected with the novel coronavirus disease (COVID-19) caused by SARS-CoV-2 infection in Japan has exceeded 530,000, and the number of deaths has exceeded 9,600.

[0003] Genome-wide association studies (GWAS)-based genomic analyses are being conducted as part of international collaborative research to identify genetic factors involved in the onset and severity of COVID-19. The COVID-19 Host Genetics Initiative (COVID-19hg) is a multicenter collaborative research organization established for this purpose, with 50 research institutions or groups participating from around the world. COVID-19hg reported the results of an international meta-GWAS in a release dated January 18, 2021. The Japanese Coronavirus Task Force is also participating in COVID-19hg, and the international meta-GWAS includes 572 Japanese COVID-19 patients (155 of whom had severe COVID-19) and 1,705 healthy controls.

[0004] The latest international meta-GWAS comparing COVID-19 patients with healthy controls showed significant associations with nine genes: LZTFL1 (leucine zipper transcription factor like 1) gene, CCHCR1 (Coiled-coil alpha-herical rod protein 1) gene, FOXP4-AS1 (Forkhead box protein 4-antisense RNA 1) gene, ABO gene, TMEM65 (transmembrane protein 65) gene, OAS (2',5'-oligoadenylate synthetase) family genes, KANSL1 (KAT8 regulatory NSL complex subunit 1) gene, DPP9 (Dipeptidyl peptidase 9) gene, and IFNAR2 (Interferon alpha and beta receptor subunit 2) gene. Seven genes, including the LZTFL1 gene, CCHCR1 gene, FOXP4-AS1 gene, VSTM2A (V-set and transmembrane domain containing 2A) gene, OAS family genes, TAC4 (tachykinin 4) gene, DPP9 gene, and IFNAR2 gene, are significantly associated with severe COVID-19 patients compared to healthy individuals. However, an international meta-GWAS of severe COVID-19 patients versus mild COVID-19 patients has not found any significant single nucleotide polymorphisms (SNPs). Furthermore, it has been reported that a core haplotype exists in the 3p21.31 gene cluster, including the LZTFL1 gene, which is associated with the severity of COVID-19, and that this core haplotype originated in Neanderthals and was inherited by Homo sapiens (see, for example, Non-Patent Document 1). [Prior art documents] [Non-patent literature]

[0005] [Non-Patent Document 1] Zeberg H et al, “The major genetic risk factor for severe COVID-19 is inherited from Neanderthals.”, Nature, Vol. 587, pp. 610-612, 2020. Summary of the Invention [Problem to be solved by the invention]

[0006] Although a certain number of COVID-19 patients become severely ill and require oxygen inhalation or tracheal intubation, the genetic factors that contribute to the severity of COVID-19 in Japanese patients remain unclear. Furthermore, no genetic factors meeting genome-wide significance levels have been detected in an international meta-GWAS comparing severe and mild COVID-19 patients.

[0007] The present invention has been made in consideration of the above circumstances, and provides a novel method and kit for detecting genetic factors that contribute to the aggravation of COVID-19. [Means for solving the problem]

[0008] That is, the present invention includes the following aspects. (1) A method for detecting genetic factors that contribute to the severity of COVID-19, comprising: A method comprising detecting one or more single nucleotide polymorphisms present in the region from the interleukin-17A locus to the interleukin-17F locus in a DNA-containing sample from a subject. (2) The method according to (1), wherein the single nucleotide polymorphism is one or more selected from the group consisting of rs11962054, rs13192563, rs13192246, and rs9474169 in the NCBI SNP Database. (3) The method according to (1) or (2), further comprising detecting a single nucleotide polymorphism at one or more loci selected from the group consisting of the forkhead box protein 4-antisense RNA 1 locus and the interferon alpha and beta receptor subunit 2 locus in a DNA-containing sample derived from the subject. (4) A kit for detecting genetic factors that contribute to the worsening of COVID-19, A kit comprising one or more nucleic acid probes or primers for detecting one or more single nucleotide polymorphisms present in the region from the interleukin-17A locus to the interleukin-17F locus. (5) The kit according to (4), wherein the single nucleotide polymorphism is one or more selected from the group consisting of rs11962054, rs13192563, rs13192246, and rs9474169 in the NCBI SNP Database. (6) The kit according to (4) or (5), further comprising one or more nucleic acid probes or primers for detecting single nucleotide polymorphisms at one or more loci selected from the group consisting of the forkhead box protein 4-antisense RNA 1 locus and the interferon alpha and beta receptor subunit 2 locus. [Effects of the Invention]

[0009] The method and kit of the above aspect make it possible to simply and reliably detect genetic factors that contribute to the aggravation of COVID-19 in a subject. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a graph showing the age distribution of sCOVID-19 patients and mCOVID-19 patients in Example 1. [Figure 2A] FIG. 1 shows the results of GWAS in Japanese people, comparing all COVID-19 patients and healthy individuals in Example 1. [Figure 2B]FIG. 1 shows the results of an international meta-GWAS comparing all COVID-19 patients and healthy individuals in Example 2. [Figure 2C] FIG. 1 shows the results of an integrated analysis of Japanese GWAS and international meta-GWAS comparing all COVID-19 patients and healthy individuals in Example 2. [Figure 2D] 1 shows a LocusZoom plot of 400 kb around the major SNPs in three gene regions including FOXP4-AS1, ABO, and IFNAR2 in Example 1. [Figure 3A] FIG. 1 shows the results of GWAS in Japanese people comparing severe COVID-19 (sCOVID-19) patients and healthy individuals in Example 1. [Figure 3B] FIG. 1 shows the results of an international meta-GWAS comparing COVID-19 (sCOVID-19) patients and healthy individuals in Example 2. [Figure 3C] FIG. 1 shows the results of an integrated analysis of Japanese GWAS and international meta-GWAS comparing COVID-19 (sCOVID-19) patients and healthy individuals in Example 2. [Figure 3D] 1 is a LocusZoom plot of 400 kb around the major SNPs in two gene regions including FOXP4-AS1 and IFNAR2 in Example 2. [Figure 4A] FIG. 1 shows the results of GWAS in Japanese people comparing COVID-19 (sCOVID-19) patients and mild COVID-19 (mCOVID-19) patients in Example 1. [Figure 4B] FIG. 1 shows the results of an international meta-GWAS comparing COVID-19 (sCOVID-19) and mild COVID-19 (mCOVID-19) patients in Example 2. [Figure 4C] FIG. 1 shows the results of an integrated analysis of Japanese GWAS and international meta-GWAS comparing COVID-19 (sCOVID-19) patients and mild COVID-19 (mCOVID-19) patients in Example 2. [Figure 4D]1 is a LocusZoom plot of 400 kb around the major SNPs in the gene region containing ILF17A and ILF17F in Example 2. [Figure 5] eQTL data for three SNPs identified in a GWAS comparing severe and mild COVID-19 patients. DETAILED DESCRIPTION OF THE INVENTION

[0011] Details of a method and kit for detecting genetic factors contributing to the aggravation of COVID-19 according to one embodiment of the present invention (hereinafter sometimes abbreviated as "the method of this embodiment" and "the kit of this embodiment") are described below.

[0012] <covid-19> In this specification, Coronavirus disease 2019 (COVID-19) is an abbreviation for Coronavirus disease 2019, which is an infectious disease caused by the infection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). SARS-CoV-2 belongs to the genus Betacoronavirus and is thought to be genetically closely related to coronaviruses isolated from the genus Rhinolophus.

[0013] <Method for Detecting Genetic Factors Associated with the Progression of COVID-19> The method of this embodiment is a method for detecting genetic factors associated with the progression of COVID-19, including detecting one or more single nucleotide polymorphisms (SNPs) present in the region from the interleukin-17A (ILF17A) locus to the interleukin-17F (ILF17F) locus in a DNA-containing sample derived from a subject.

[0014] As shown in the examples described below, the inventors performed genome-wide SNP typing using the Japanese Screening Array (JSA) manufactured by Illumina on 503 COVID-19 patients registered in the biobank of the National Center for Global Health and Medicine and 1,276 Japanese healthy controls, and conducted a genome-wide association analysis (GWAS) to compare the patient group that became severely ill with the SARS-Cov-2 infection and the patient group that had mild symptoms. As a result, SNPs associated with the progression of COVID-19 were identified as SNPs present in the region from the ILF17A locus to the ILF17F locus. Examples of SNPs present in the region from the ILF17A locus to the ILF17F locus include, for example, the accession numbers rs11962054, rs13192563, rs13192246, rs9474169, etc. in the NCBI SNP Database. These SNPs may be individually targeted for detection, or two or more of them may be combined for detection.

[0015] Furthermore, as shown in the Examples below, the inventors integrated the statistical values ​​of the international meta-GWAS published by COVID-19hg with the statistical values ​​of the Japanese GWAS and found that the above-mentioned SNPs present in the region from the ILF17A locus to the ILF17F locus meet the genome-wide significance level, thereby completing the present invention.

[0016] According to the method of this embodiment, genetic factors that contribute to the aggravation of COVID-19 in a subject can be detected simply and reliably.

[0017] The DNA-containing sample derived from a subject is not particularly limited as long as it is collected from the subject's living body, and examples include, but are not limited to, blood, serum, plasma, urine, buffy coat, saliva, semen, thoracic exudate, cerebrospinal fluid, tears, sputum, mucus, lymph, ascites, pleural effusion, amniotic fluid, bladder washings, bronchoalveolar lavage fluid, hair, feces, cells or tissues collected directly from the living body, etc. It is preferable to extract DNA from these samples and use them as samples to be used for detection, as described below.

[0018] The DNA extraction method is not particularly limited, and can be performed using known methods. Examples include the phenol / chloroform method and the cetyltrimethylammonium bromide (CTAB) method. DNA extraction can also be performed using commercially available kits. Examples of such kits include the Wizard Genomic DNA Purification Kit (Promega).

[0019] Alternatively, the DNA may be cDNA synthesized by extracting mRNA and using the mRNA as a template. There are no particular limitations on the method for extracting mRNA, and it can be extracted using known methods. Examples include the guanidine isothiocyanate method. A commercially available kit may be used for mRNA extraction. Examples of such kits include the NucleoTrap (registered trademark) mRNA Kit (manufactured by Clontech). There are also no particular limitations on the method for synthesizing cDNA, and it can be synthesized using known methods. For example, cDNA can be synthesized from RNA by reverse transcriptase-polymerase chain reaction (RT-PCR) using a random primer or a polyT primer.

[0020] The SNPs present in the region from the ILF17A locus to the ILF17F locus can be detected using known SNP detection methods, such as direct sequencing, polymerase chain reaction (PCR), restriction fragment length polymorphism (RFLP), hybridization, TaqMan® PCR (hereinafter, the term "registered trademark" will be omitted), and mass spectrometry.

[0021] Direct sequencing is performed by cloning a region containing the SNP present in the region from the ILF17A locus to the ILF17F locus to be detected in a DNA-containing sample derived from the subject into a vector or amplifying it by PCR, and then determining the nucleotide sequence of the region. Cloning can be performed by screening a cDNA library using an appropriate probe. Alternatively, cloning can be performed by amplifying the SNP by PCR using appropriate primers and ligating it into an appropriate vector. Subcloning into another vector is also possible, but is not limited to these methods. Examples of vectors that can be used include commercially available plasmid vectors, viral vectors, artificial chromosome vectors, and cosmid vectors, such as pBlue-Script SK(+) (Stratagene), pGEM-T (Promega), pAmp (Gibco-BRL), p-Direct (Clontech), and pCR2.1-TOPO (Invitrogene). Nucleotide sequencing can be performed using known methods, including, but not limited to, manual sequencing using radioactive marker nucleotides and automated sequencing using dye terminators. Based on the base sequence thus obtained, it is determined whether or not the sample contains the above-mentioned SNP present in the region from the ILF17A locus to the ILF17F locus.

[0022] PCR is performed using oligonucleotide primers (hereinafter sometimes referred to as "primers for detecting SNPs in the region from the ILF17A locus to the ILF17F locus") that hybridize only to sequences containing the above-mentioned SNPs present in the region from the ILF17A locus to the ILF17F locus. As described above, since multiple SNPs exist in the region from the ILF17A locus to the ILF17F locus, the primers for detecting SNPs in the region from the ILF17A locus to the ILF17F locus may be primers capable of detecting all SNPs alone, or two or more primers capable of detecting each SNP may be used in combination. DNA from the sample is amplified using these primers. If the primers for detecting SNPs in the region from the ILF17A locus to the ILF17F locus generate a PCR product, the sample will contain one or more of the above-mentioned SNPs present in the region from the ILF17A locus to the ILF17F locus. If no PCR product is produced, it indicates that the sample does not contain the above SNP present in the region from the ILF17A locus to the ILF17F locus.

[0023] In the RFLP method, a region containing one or more of the SNPs present in the region from the ILF17A locus to the ILF17F locus to be detected is first amplified by PCR. The PCR product is then cleaved with a restriction enzyme appropriate for the region containing one or more of the SNPs present in the region from the ILF17A locus to the ILF17F locus. The PCR products digested with the restriction enzymes are separated by gel electrophoresis and visualized by ethidium bromide staining. The fragment lengths can be compared with molecular weight markers and, as a control, with the PCR product not treated with the restriction enzymes, to detect the presence of one or more of the SNPs present in the region from the ILF17A locus to the ILF17F locus in a sample.

[0024] The hybridization method determines the presence or absence of one or more of the above-mentioned SNPs present in the region from the ILF17A locus to the ILF17F locus in a sample based on the ability of sample-derived DNA to hybridize with complementary DNA molecules (e.g., oligonucleotide probes). This hybridization method can be performed using various hybridization and detection techniques, including known hybridization techniques such as colony hybridization, plaque hybridization, and Southern blotting. For detailed procedures for the hybridization method, see "Molecular Cloning, A Laboratory Manual 3rd ed." (Cold Spring Harbor Press (2001); particularly Sections 6-7), "Current Protocols in Molecular Biology" (John Wiley & Sons (1987-1997); particularly Sections 6.3-6.4), and "DNA Cloning 1: Core Techniques, A Practical Approach 2nd ed." (Oxford University (1995); for hybridization conditions, particularly Section 2.10). Hybridization can also be detected using a DNA chip. This method involves designing oligonucleotide probes specific to the SNPs present in the region from the ILF17A locus to the ILF17F locus, attaching them to a solid support, and then contacting a DNA sample derived from a specimen with the DNA chip to detect hybridization.

[0025] The TaqMan PCR method uses TaqMan probes specific to the SNPs present in the region from the ILF17A locus to the ILF17F locus and Taq polymerase to simultaneously detect SNPs and amplify the region containing the SNP. The TaqMan probe is an oligonucleotide of approximately 20 bases labeled with a fluorescent substance at the 5' end and a quencher at the 3' end, and is designed to hybridize to the target SNP site. Taq polymerase has 5'→3' nuclease activity. When the region containing the SNP site is amplified in the presence of these TaqMan probes and Taq polymerase using PCR primers designed to amplify the region containing the SNP site, the TaqMan probe hybridizes to the target SNP site in the template DNA in parallel with the amplification. When the extension reaction from the forward primer reaches the TaqMan probe hybridized to the template, the 5' to 3' nuclease activity of Taq polymerase cleaves the fluorescent substance attached to the 5' end of the TaqMan probe. As a result, the released fluorescent substance is no longer affected by the quencher and emits fluorescence. SNP detection is possible by measuring the fluorescence intensity.

[0026] Mass spectrometry-based SNP typing, for example, can be performed using MALDI-TOF / MS in combination with primer extension. This method allows for high-throughput analysis and involves the following steps: 1) PCR, 2) PCR product purification, 3) primer extension, 4) extension product purification, 5) mass spectrometry, and 6) genotyping. First, a region containing the target SNP site is amplified from genomic DNA by PCR. PCR primers are designed so that they do not overlap with the SNP site base. The primers are then purified by enzymatic removal using exonuclease and shrimp alkaline phosphatase or by ethanol precipitation. Next, a primer extension reaction is performed using a genotyping primer whose 3' end is directly adjacent to the SNP site. The PCR product is denatured at high temperature, and excess genotyping primer is added and annealed. ddNTPs and DNA polymerase are added to the reaction system, followed by thermal cycling to generate oligomers one base longer than the genotyping primer. The oligomers generated by this extension reaction are different for each allele depending on the design of the genotyping primer. The purified extension reaction products are subjected to mass spectrometry and analyzed from the mass spectrum.

[0027] Other detection methods include a high-throughput SNP typing method that applies single-molecule fluorescence analysis. For example, the MF20 / 10S (manufactured by Olympus) is a system that employs this method. Specifically, it uses a confocal laser optical system and a highly sensitive photodetector to measure and analyze the translational diffusion time at the single-molecule level of fluorescently labeled primers amplified by PCR using complementary and non-complementary primers in an ultra-small area of ​​approximately 1 femtoliter (1 / 1000 trillionth of a liter).

[0028] Another high-throughput typing method is the use of DNA chips, which have a variety of DNA probes arrayed and fixed on a substrate. Labeled DNA samples are hybridized on the chip, and fluorescent signals from the probes are detected.

[0029] The Snipper method is an example of an SNP typing method that uses gene amplification methods other than PCR. This method utilizes rolling circle amplification (RCA), a DNA amplification method in which DNA polymerase synthesizes complementary DNA strands while moving along a circular single-stranded DNA template. The probe is an oligo DNA between 80 and 90 bases long, containing sequences of 10 and 20 bases at both ends that are complementary to the 5' and 3' ends of the target SNP site, respectively, and is designed to anneal to the target DNA and form a circular form. The 3' end of the probe is also designed to be complementary to the target SNP site. If the 3' end of the probe is completely complementary to the target SNP site, the probe will circularize; however, if the 3' end of the probe is mismatched, the probe will not circularize. The probe also has a backbone sequence between 40 and 50 bases long and contains sequences complementary to two RCA amplification primers.

[0030] Other examples of SNP typing methods that utilize gene amplification methods other than PCR include typing methods that utilize the UCAN method and the LAMP method.

[0031] The UCAN method is an adaptation of the ICAN method, an isothermal gene amplification method developed by Takara Bio. The UCAN method uses a DNA-RNA-DNA chimeric oligonucleotide (DRD) as a primer precursor. This DRD primer precursor is modified at the 3' end to prevent DNA polymerase from replicating the template DNA, and is designed to allow the RNA portion to bind to the SNP site. When this DRD primer precursor is incubated with the template, the coexisting RNase H cleaves the RNA portion of the paired DRD primer only if the DRD primer and template are perfectly matched. This removes the modified DNA from the 3' end of the primer, creating a new one, allowing DNA polymerase to elongate the primer and amplify the template DNA. On the other hand, if the DRD primer and template DNA do not match, RNase H does not cleave the DRD primer, and DNA amplification does not occur. After the perfectly matched DRD primer precursor is cleaved by RNase H, the amplification reaction proceeds via the ICAN reaction mechanism.

[0032] The LAMP method is a gene isothermal amplification method developed by Eiken Chemical. It defines six regions of the target gene (F3c, F2c, F1c from the 3' end, and B3, B2, B1 from the 5' end) and amplifies them using four primers (FIP primer, F3 primer, BIP primer, B3 primer) for these six regions. For typing purposes, only the target SNP site (single base) is required between F1 and B1, and the FIP and BIP primers are designed so that the single base of the SNP is located at their 5' ends. If there is no SNP, DNA synthesis occurs from the dumbbell structure, which is the starting structure for the LAMP method, and the amplification reaction proceeds continuously. If there is an SNP, DNA synthesis from the dumbbell structure does not occur, and the amplification reaction does not proceed.

[0033] The Invader method does not use nucleic acid amplification, but instead uses two types of non-fluorescently labeled probes (allele probe and Invader probe), one type of fluorescently labeled probe (FRET probe), and the endonuclease cleavase. The allele probe has a sequence complementary to the template DNA from the SNP site at the 3' end, and a flap sequence unrelated to the template DNA at the 5' end of the probe. The Invader probe has a sequence complementary to the template DNA from the SNP site at the 5' end, with the base corresponding to the SNP site being an arbitrary base. The FRET probe has a sequence complementary to the flap sequence at the 3' end. The 5' end of the other probe is labeled with a fluorescent dye and a quencher, but the FRET probe is designed to form a double-stranded chain within the molecule and is usually quenched. When these probes are reacted with template DNA, the 3' end of the Invader probe (any base portion) invades the SNP site when the allele probe forms a double-stranded chain with the template DNA. Cleavase recognizes the structure where the base has invaded and cleaves the flap portion of the allele probe. Next, when this released flap binds to the complementary sequence of the FRET probe, the 3' end of the flap invades the intramolecular double-stranded portion of the FRET probe. As in the case of the allele probe and invader probe described above, cleavase recognizes the structure where the base of the flap has invaded the FRET probe and cleaves the fluorescent dye of the FRET probe. The fluorescent dye separates from the quencher, causing fluorescence. If the allele probe does not match the template DNA, the specific structure recognized by cleavase is not formed, and the flap is not cleaved.

[0034] When primers are used to detect SNPs, they are designed to be suitable for the region to be amplified and the typing method. For example, it is preferable that the primers be capable of completely amplifying the region, and the primer sequences can be designed based on the sequences near both ends of the region. Primer design techniques are well known in the art, and primers that can be used in the method of this embodiment are designed to satisfy conditions for specific annealing, for example, to have a length and base composition (melting temperature) that enable specific annealing. The length of the region to be amplified is not limited as long as it does not interfere with typing, and may be increased or decreased as appropriate depending on the detection method. Furthermore, while a portion of the amplified region contains an SNP site, the position of this site within the amplified region is not limited and may be positioned appropriately depending on the detection method (typing method). Therefore, when designing primers, the positional relationship between the primer and the SNP site can be freely designed according to the detection method, and primers can be designed taking into account the characteristics of the typing method as long as they hybridize to a region containing the SNP to be detected (e.g., a continuous region of 50 to 500 bases in length). The length of a primer that functions as a primer is preferably 10 to 100 bases, more preferably 15 to 50 bases, and even more preferably 15 to 30 bases. Furthermore, when designing a primer, it is preferable to confirm its melting temperature (Tm), which is the temperature at which 50% of any nucleic acid strand hybridizes with its complementary strand. In order for the template DNA and the primer to form a double strand and anneal, the annealing temperature must be optimized. However, a temperature that is too low is undesirable because it can cause nonspecific reactions. Known primer design software can be used to confirm the Tm.

[0035] When a probe is used to detect SNPs, it is designed so that the probe recognizes the SNP site. In designing the probe, the SNP site may be recognized at any location within the probe depending on the typing method, and may be recognized at the end of the probe depending on the typing method. When a polynucleotide for SNP detection is used as the probe, the length of the base sequence complementary to genomic DNA is usually 15 to 200 bases, preferably 15 to 100 bases, and more preferably 15 to 50 bases, but may be longer or shorter depending on the typing method.

[0036] In the method of this embodiment, if one or more of the above SNPs present in the region from the ILF17A locus to the ILF17F locus are detected in a sample, it indicates that COVID-19 caused by SARS-CoV-2 infection may become severe.

[0037] The method of this embodiment directly leads to improved accuracy in predicting the risk of severe COVID-19, making it possible to selectively administer vaccinations, treatments, and medications to cases at high risk of severe illness.

[0038] The presence of the above SNPs in the region from the ILF17A locus to the ILF17F locus may be either homozygous or heterozygous, but due to their association with the expression level of ILF17F, it is thought that being homozygous may increase the risk of developing severe COVID-19.

[0039] In the method of this embodiment, in addition to detecting the above-mentioned SNPs present in the region from the ILF17A locus to the ILF17F locus, other SNPs or haplotypes associated with the possibility of COVID-19 becoming severe may also be detected. By detecting these SNPs or haplotypes in combination with the detection of the above-mentioned SNPs present in the region from the ILF17A locus to the ILF17F locus, the possibility of COVID-19 becoming severe can be determined with higher accuracy, thereby increasing the reliability of the diagnosis.

[0040] Other SNPs associated with the likelihood of severe COVID-19 include the following: SNP in the LZTFL1 (leucine zipper transcription factor like 1) locus: Accession number rs35081325 in the NCBI SNP Database; SNP in the CCHCR1 (Coiled-coil alpha-herical rod protein 1) locus: Accession number rs111837807 in the NCBI SNP Database; SNP in the FOXP4-AS1 (Forkhead box protein 4-antisense RNA 1) locus: Accession number rs1853837 in the NCBI SNP Database; SNP in the VSTM2A (V-set and transmembrane domain containing 2A) locus: Accession number rs71525842 in the NCBI SNP Database; SNP in the OAS (2',5'-oligoadenylate synthetase) family gene locus: Accession number rs2269899 in the NCBI SNP Database; SNP in the TAC4 (tachykinin 4) locus: Accession number rs77534576 in the NCBI SNP Database; SNP in the DPP9 (Dipeptidyl peptidase 9) gene locus: Accession number rs2109069 in the NCBI SNP Database; SNPs in the IFNAR2 (Interferon alpha and beta receptor subunit 2) gene locus: NCBI SNP Database accession numbers rs2186317, rs62226132, rs62226152, rs4553897, rs12482556, rs11088247, rs2300370, rs2248420, rs2834154, rs6517153, rs17860142, rs3153, rs9636867, rs1131964, rs12482014, rs12482193, rs12482 060, rs17860165, rs17860169, rs1051393, rs9976829, rs2834157, rs2236756, rs2252639, rs2252650, rs22845 49, rs2284550, rs2284551, rs12053666, rs2073361, rs2834161, rs2834163, rs2834164, rs2834165, rs2236757.

[0041] These SNPs may be detected individually or in combination. If these SNPs are detected in a sample, it can be determined that the sample may be at risk of severe COVID-19. Among these, as shown in the Examples described below, SNPs in one or more loci selected from the group consisting of the FOXP4-AS1 locus and the IFNAR2 locus are preferred, since the association has been reproduced not only in an international meta-GWAS comparing severe COVID-19 patients and healthy individuals, but also in a GWAS in Japanese people.

[0042] In addition to the SNPs associated with the possibility of COVID-19 becoming severe as described above, SNPs associated with the possibility of developing COVID-19 (or susceptibility to SARS-CoV-2) may also be detected.

[0043] Examples of SNPs associated with the likelihood of developing COVID-19 (or susceptibility to SARS-CoV-2) include the following: SNP in the LZTFL1 locus: accession number rs35081325 in the NCBI SNP Database; SNP in CCHCR1 locus: Accession number rs111837807 in NCBI SNP Database; SNPs in the FOXP4-AS1 locus: Accession numbers rs2894439, rs9367106, rs12660421, rs1853837, rs55889968, rs12175265, rs1886814, rs4714474, rs9381074 in the NCBI SNP Database; SNP in the ABO locus: Accession number rs8176719 in the NCBI SNP Database; SNP in the TMEM65 (transmembrane protein 65) gene locus: Accession number rs72711165 in the NCBI SNP Database; SNP in OAS family locus: Accession number rs10774671 in NCBI SNP Database; SNP in the KANSL1 (KAT8 regulatory NSL complex subunit 1) locus: Accession number rs1819040 in the NCBI SNP Database; SNP in the DPP9 locus: Accession number rs2109069 in the NCBI SNP Database; SNPs in the IFNAR2 locus: Accession numbers rs2248420, rs17860142, rs3153, rs12482014, rs12482193, rs12482060, and rs17860165 in the NCBI SNP Database.

[0044] These SNPs may be detected individually or in combination. If these SNPs are detected in a sample, it can be determined that the sample is likely to develop COVID-19 (or is susceptible to SARS-CoV-2). Among these, as shown in the Examples described below, SNPs in one or more loci selected from the group consisting of the FOXP4-AS1 locus, the ABO locus, and the IFNAR2 locus are preferred, since the association has been reproduced not only in an international meta-GWAS comparing all COVID-19 patients with healthy individuals, but also in a GWAS in Japanese people.

[0045] For example, if the above-mentioned SNPs associated with the possibility of COVID-19 becoming severe and the above-mentioned SNPs associated with the possibility of COVID-19 onset (or susceptibility to SARS-CoV-2) are detected in a sample, it can be determined that the sample has the possibility of COVID-19 onset (or is susceptible to SARS-CoV-2) and the possibility of COVID-19 becoming severe.

[0046] Furthermore, for example, if a SNP associated with the possibility of the above-mentioned COVID-19 becoming severe is detected in a sample, but a SNP associated with the possibility of the above-mentioned COVID-19 onset (or susceptibility to SARS-CoV-2) is not detected, it can be determined that the sample has a low or no possibility of developing COVID-19 (or has little or no susceptibility to SARS-CoV-2), but that there is a possibility of the sample becoming severe if infected with SARS-CoV-2.

[0047] Furthermore, for example, if the above-mentioned SNPs related to the possibility of COVID-19 becoming severe are not detected in a sample, but the above-mentioned SNPs related to the possibility of COVID-19 onset (or susceptibility to SARS-CoV-2) are detected, it can be determined that the sample has the possibility of COVID-19 onset (or is susceptible to SARS-CoV-2), but that the possibility of COVID-19 becoming severe is low or not.

[0048] Also, for example, when neither the SNP related to the presence or absence of the possibility of severe COVID-19 progression described above nor the SNP related to the presence or absence of the possibility of COVID-19 onset (or susceptibility to SARS-CoV-2) described above is detected in a sample, it can be determined that the sample has a low or no possibility of COVID-19 onset (or has little or no susceptibility to SARS-CoV-2), and has a low or no possibility of severe COVID-19 progression.

[0049] <Kit for Detecting Genetic Factors of Severe COVID-19> The kit of this embodiment includes one or more nucleic acid probes or primers for detecting one or more SNPs present in the region from the IL17A locus to the IL17F locus. The kit of this embodiment is useful as a kit for examining the presence or absence of the possibility of severe COVID-19 progression. Examples of the one or more SNPs present in the region from the IL17A locus to the IL17F locus include those similar to those exemplified in the above "Method for Detecting Genetic Factors of Severe COVID-19 Progression". Also, for the nucleic acid probes or primers, those skilled in the art can appropriately prepare them using the methods described in the above "Method for Detecting Genetic Factors of Severe COVID-19 Progression" for detecting one or more SNPs present in the region from the IL17A locus to the IL17F locus.

[0050] In addition to the above nucleic acid probes or primers, the kit of this embodiment can further include reagents, positive controls, solvents and solutes commonly used in SNP typing. Examples of such reagents include deoxynucleotide triphosphates (dNTPs), DNA polymerase, etc. Examples of solvents and solutes include distilled water, pH buffer reagents, salts, proteins, surfactants, etc.

[0051] The nucleic acid probe or primer may contain a sequence unrelated to one or more SNPs present in the region from the IL17A locus to the IL17F locus. The nucleic acid probe or primer may be a chimera of DNA and RNA. The nucleic acid probe or primer may be labeled with a fluorescent substance, a binding affinity substance such as biotin or digoxin, an enzyme, a radioisotope, a luminescent substance, or the like. Examples of fluorescent substances include fluorescamine and fluorescein isothiocyanate. Examples of enzymes include peroxidase, alkaline phosphatase, malate dehydratase, α-glucosidase, α-galactosidase, and the like. Examples of radioisotopes include 125 I, 131 I, 3 H, 14 Examples of luminescent substances include luciferin, lucigenin, luminol, and luminol derivatives.

[0052] In addition to the nucleic acid probe or primer, the kit of this embodiment may also include a reference sample to serve as a comparison standard or for preparing a calibration curve, a detector, etc. Examples of detectors include those capable of detecting the label of the nucleic acid probe or primer, such as a spectrometer, a radiation detector, and a light scattering detector.

[0053] The kit of this embodiment may further include, in addition to nucleic acid probes or primers for detecting one or more SNPs present in the region from the IL17A locus to the IL17F locus, nucleic acid probes or primers for detecting other SNPs or haplotypes associated with the possibility of COVID-19 worsening. Examples of such SNPs and haplotypes include those exemplified in the above-mentioned "Method for detecting genetic factors contributing to the worsening of COVID-19." Furthermore, a person skilled in the art can appropriately prepare nucleic acid probes or primers for detecting these SNPs or haplotypes using the method described in the above-mentioned "Method for detecting genetic factors contributing to the worsening of COVID-19" for the method for detecting one or more SNPs present in the region from the IL17A locus to the IL17F locus.

[0054] The kit of this embodiment may further include, in addition to the nucleic acid probe or primer for detecting one or more SNPs present in the region from the IL17A locus to the IL17F locus, a nucleic acid probe or primer for detecting a SNP associated with the presence or absence of the possibility of developing COVID-19 (or susceptibility to SARS-CoV-2). Examples of such SNPs include those exemplified in the above-mentioned "Method for detecting genetic factors contributing to the worsening of COVID-19." Furthermore, a person skilled in the art can appropriately prepare nucleic acid probes or primers for detecting these SNPs using the method described in the above-mentioned "Method for detecting genetic factors contributing to the worsening of COVID-19" for the method for detecting one or more SNPs present in the region from the IL17A locus to the IL17F locus. [Example]

[0055] The present invention will be described below with reference to examples, but the present invention is not limited to the following examples.

[0056] <Materials and measurement methods> [COVID-19 patient and clinical data] Data from a total of 503 adult COVID-19 patients who were hospitalized at the National Center for Global Health and Medicine or treated at home or in accommodation facilities between January 30, 2020, and January 11, 2021 were used. The presence or absence of underlying medical conditions in COVID-19 patients was obtained from questionnaire-based clinical information. In this example, COVID-19 patients were divided into two groups: severe COVID-19 patients (sCOVID-19) and mild COVID-19 patients (mCOVID-19) according to the latest clinical guidelines from the Ministry of Health, Labor, and Welfare (December 25, 2020). Patients defined as having sCOVID-19 showed clinical signs of pneumonia (fever, cough, dyspnea, and rapid breathing) accompanied by any of the following symptoms: peripheral oxygen saturation (SpO2) ≤ 93% at room temperature, need for supplemental oxygen or a ventilator, and need for support with an extracorporeal membrane oxygenation (ECMO) device. Patients defined as having mCOVID-19 had any of the following signs and symptoms of COVID-19 (e.g., fever, cough, sore throat, fatigue, headache, muscle pain, nausea, vomiting, diarrhea, loss of taste and smell) but no shortness of breath, difficulty breathing, or abnormal chest imaging. These criteria are largely consistent with the international standards established by the NIH (https: / / www.covid19treatmentguidelines.nih.gov / ). Permission for this analysis was granted by the Ethics Office of the National Center for Global Health and Medicine, and written informed consent was obtained from all COVID-19 patients (NCGM-G-003472).

[0057] [Data from healthy Japanese subjects] Of 1,273 healthy Japanese adults, 419 (Tokyo healthy controls, THCs) who lived in the Tokyo area before the COVID-19 outbreak were collected and used extensively for genome analysis. Informed consent was obtained from all 419 individuals. The remaining 854 individuals were purchased as Pharma SNP Consortium (PSC) samples from the Japan Health Sciences Foundation (JHSF). Human immortalized B cell lines were generated from blood samples of approximately 1,000 Japanese volunteers and deposited at the Japan Collection of Research Bioresources (JCRB) / JHSF, Health Sciences Research Resources Bank (HSRRB).

[0058] [Genome-wide genotyping and filtered samples] All 1,776 genomic DNA samples from 503 Japanese COVID-19 patients and 1,273 Japanese healthy controls were genotyped using the Illumina Infinium Japanese Screening Array (JSA) according to the protocol. Of the 1,776 samples, 1,759 had a genotype call rate of over 97% for all SNPs, meeting the criteria for accuracy assessment of heterozygosity. Twenty-nine samples, including nine COVID-19 patients and 20 PSC healthy controls, were determined to be close relatives (PI ≥ 0.1) by homoeologous analysis and were excluded from further analysis. Seventy-five samples, including 32 COVID-19 patients, 19 THC healthy controls, and 24 PSC healthy controls, were detected as outliers (IQR = 1.5) in principal component analysis and were excluded from further analysis. Finally, 1,655 samples, including 462 COVID-19 patients and 1,193 healthy controls (400 THC individuals and 793 PSC individuals), formed the same cluster in principal component analysis using the first and second components. The average call rate for all SNPs in the 1,655 samples was 99.49% (97.25-99.73%).

[0059] [Genotype imputation and statistical analysis] Genotype imputation was performed on the filtered SNP array data using BEAGLE 5.1. Genotype data in VCF format were processed to match the reference panel using the conform-gt program, and then genotype imputation was performed using BEAGLE 5.1 ​​with default settings. The reference panel used for genotype imputation was created in-house. This panel consisted of 9,338 haplotypes from 4,669 individuals from diverse populations, including 2,493 individuals from the International 1000 Genomes, 820 individuals from the Human Genome Diversity Project, 278 individuals from the Simons Genome Diversity Project, 90 individuals from the Korean Personal Genome Diversity Project, and 1,026 individuals from Biobank Japan. The Biobank Japan data were approved restricted-access data from the NBDC Human Data Center (JGAS000114), while the other data were downloaded from public databases. Low-quality (DR2 < 0.5) variants (SNPs and insertion / deletion) were excluded, and variants with a genotype probability of less than 0.9, the standard value for genotype accuracy assessment, were considered missing values. Logistic regression was used for statistical analysis of variants and COVID-19 onset and severity. Variants with a minor allele frequency of less than 1% or a low genotype call rate (< 95%) were excluded from the analysis. Statistical analysis assumed additive genetic effects. Genome-wide association studies were performed using plink1.9.

[0060] [Integrated statistical analysis integrating Japanese GWAS and international meta-GWAS] To integrate the P values ​​of the Japanese GWAS with those of the international meta-GWAS, we used the Stouffer Z-score method in this analysis. In simple terms, the P value of a one-sided right-sided test was first calculated from the P value of the international meta-GWAS based on the direction of association detected in the Japanese GWAS. Then, the standard normal cumulative distribution function was used to calculate the Z score from the one-sided right-sided P value. Furthermore, the Z scores of the Japanese GWAS and the international meta-GWAS were integrated using the following formula:

[0061]

number

[0062] Z obtained from the above formula combined A two-sided P value was calculated for each SNP from: The beta coefficient (β) for each SNP was obtained as an inverse variance-weighted estimator using the formula below, and the standard deviation (SE) of β was obtained as the square root of the variance using the formula below.

[0063]

number

[0064]

number

[0065] [Example 1] (Detection of genetic factors associated with the worsening of COVID-19 in Japanese people) Clinical characteristics of 1.503 Japanese COVID-19 patients Of the 503 Japanese COVID-19 patients in this analysis, 19 patients recovered from COVID-19, but information on the severity of their illness was unavailable. Table 1 summarizes the age and gender, as well as the presence or absence of six underlying conditions (hypertension, dyslipidemia, type II diabetes mellitus (TIIDM), bronchial asthma, hyperuricemia, and obesity) in the 484 patients with information on their severity.

[0066] [Table 1]

[0067] Of the 109 severe COVID-19 (sCOVID-19) patients, 86 were male and 23 were female, with a mean age of 56.1 years, the youngest being 27 years old and the oldest being 88 years old. Among the 375 mild COVID-19 (mCOVID-19) patients, 178 were male and 197 were female, with a mean age of 44.8 years, the youngest being 20 years old and the oldest being 89 years old. Of the six underlying conditions, five were more common in sCOVID-19 patients than in mCOVID-19 patients. Hypertension accounted for 41.3% (45 of 109) of sCOVID-19 patients and 14.4% (54 of 375) of mCOVID-19 patients. Dyslipidemia accounted for 23.9% (26 / 109) of sCOVID-19 patients and 12.0% (45 / 375) of mCOVID-19 patients. TIIDM accounted for 22% (24 / 109) of sCOVID-19 patients and 5.6% (21 / 375) of mCOVID-19 patients. Hyperuricemia accounted for 19.3% (21 / 109) of sCOVID-19 patients and 5.3% (20 / 375) of mCOVID-19 patients. Obesity accounted for 15.6% (17 / 109) of sCOVID-19 patients and 3.7% (14 / 375) of mCOVID-19 patients. The opposite trend was observed for bronchial asthma; it accounted for 3.7% (4 / 109) of sCOVID-19 patients and 6.1% (23 / 375) of mCOVID-19 patients. In addition to age and gender, the frequency of six underlying diseases was compared between the two groups of sCOVID-19 and mCOVID-19 patients, and seven items, except for bronchial asthma, were statistically significant in univariate analysis (see Table 2 below; statistically significant P values ​​are shown in bold in Table 2). In multivariate analysis, in addition to age and gender, hyperuricemia and obesity showed a statistically significant association with P<0.05 (see Table 2 below).

[0068] [Table 2]

[0069] The age distribution of sCOVID-19 and mCOVID-19 patients is shown in Figure 1. These results suggest that older men with underlying medical conditions are at higher risk of developing sCOVID-19.

[0070] 2. GWAS using Japanese COVID-19 patients and healthy individuals A genome-wide association study (GWAS) using estimated genotypes from 462 Japanese COVID-19 patients and 1,193 healthy individuals was conducted with the following three comparisons: i) All COVID-19 patients and healthy individuals; ii) COVID-19 patients and healthy individuals; iii) sCOVID-19 patients and mCOVID-19 patients.

[0071] For comparisons i) and ii) above, regression analysis was performed using sex estimated from the genotypes of chromosomes X and Y, and for comparison iii) above, regression analysis was performed using estimated sex, age, and the presence or absence of six underlying diseases. The results of each GWAS analysis i) to iii) above are shown in Figures 2A, 3A, and 4A.

[0072] Although the SNP did not reach genome-wide significance (p = 5e-08), the top hit SNP identified in the comparison in i) above was rs796171020 on chromosome 6 (the closest gene is DDX39BP2) with a p value of 1.73e-07 and an odds ratio (OR) of 2.22 (see Figure 2A). From the comparison in ii) above, rs76954434 present on chromosome 13 (the closest gene is LINC00355) was identified with a P value of 7.81e-08 and an odds ratio (OR) of 10.4 (see Figure 3A). From the comparison in iii) above, rs376628389 present on chromosome 6 (the closest gene is IL17A) was identified with a P value of 5.72e-07 and an odds ratio (OR) of 2.59 (see FIG. 4A).

[0073] [Example 2] (Integrated analysis integrating Japanese GWAS and international meta-GWAS) Summary statistics for the international meta-GWAS were downloaded as the latest COVID-19 GWAS results from the public download site supported by the NHLBI Intramural Research Program and the NIHB Biowulf High-Performance Computing Cluster (https: / / grasp.nhlbi.nih.gov / COVID19GWASResults.aspx). To conduct an integrated analysis of Japanese GWAS comparing all COVID-19 patients with healthy controls, we downloaded the international meta-GWAS statistics (corresponding to the comparison in i above) conducted in COVID-19hg, which compared 7,885 hospitalized COVID-19 patients with 961,804 healthy controls. The results are shown in Figure 2B. Additionally, for the integrated analysis conducted in COVID-19hg comparing sCOVID-19 patients with healthy controls, we downloaded the international meta-GWAS statistics (corresponding to the comparison in ii above) comparing 4,336 COVID-19 patients with severe respiratory symptoms with 623,902 healthy controls. The results are shown in Figure 3B. We also downloaded the international meta-GWAS statistics (corresponding to the comparison in iii above) comparing 269 very severe respiratory COVID-19 patients with 688 non-hospitalized COVID-19 patients for a pooled analysis conducted in COVID-19hg comparing sCOVID-19 and mCOVID-19 patients. The results are shown in Figure 3B.

[0074] Because the number of samples in the international meta-GWAS was overwhelmingly larger than that in the Japanese GWAS, P values ​​were pooled using Stouffer's Z-score method (see "Integrated statistical analysis integrating Japanese GWAS and international meta-GWAS" in the "Materials and Measurement Methods" section above for details). Because this was not a meta-analysis of individual studies, we were unable to accurately estimate odds ratios (ORs). However, we investigated whether the associations of SNPs detected in the Japanese GWAS or the international meta-GWAS were replicated, and whether new SNPs meeting genome-wide significance levels were identified by integrating the two. The results of the analysis of each of the above GWASs (i) to (iii) above, integrating the Japanese GWAS and the international meta-GWAS, are shown in Figures 2C, 3C, and 4C.

[0075] As shown in Figure 2C, three genetic regions, including FOXP4-AS1, ABO, and IFNAR2, showed significant association in the integrated analysis. LocusZoom plots of 400 kb around the major SNPs in these three genetic regions are shown in Figure 2D. Summary statistics showing significant associations in the integrated GWAS are shown in Table 3 below.

[0076] [Table 3]

[0077] These three gene regions were originally detected in an international meta-GWAS, and the associations of these three gene regions were confirmed to be replicated in a Japanese GWAS. However, IFNAR2 was not significant in the Japanese GWAS due to the small sample size.

[0078] As shown in Figure 3C, significant associations were detected from two gene regions, including FOXP4-AS1 and IFNAR2. These were consistent with those detected by comparing all COVID-19 and healthy individuals. LocusZoom plots of 400 kb around the major SNPs in the two gene regions are shown in Figure 3D. Summary statistics showing significant associations in the integrated GWAS are presented in Tables 4-1 and 4-2 below.

[0079] [Table 4-1]

[0080] [Table 4-2]

[0081] Although FOXP4-AS1 was not significant in the original international meta-GWAS, it met genome-wide significance standards in an integrated analysis with the Japanese GWAS. Although the significant SNP in the FOXP4-AS1 gene, rs1853837, was not among the SNPs detected in the comparison of all COVID-19 patients with healthy controls, the same trend of a higher frequency of the risk allele in sCOVID-19 patients was observed. The IFNAR2 gene was originally significant in the international meta-GWAS, and the association was replicated in the Japanese GWAS.

[0082] Neither the international meta-GWAS nor the Japanese GWAS provided any SNPs that met genome-wide significance levels. However, the integrated analysis showed that a SNP in the gene region containing IL17A and IL17F met genome-wide significance levels (rs13192246, P = 1.42e-08), as shown in Figure 4C. All four SNPs that met genome-wide significance levels in the integrated analysis showed a high frequency of risk alleles in patients with severe COVID-19. A LocusZoom plot of 400 kb around the key SNPs in the gene region is shown in Figure 4D. Summary statistics showing significant associations in the integrated GWAS are shown in Table 5 below.

[0083] [Table 5]

[0084] [Consideration] The IL17A / IL17F gene region, which showed the lowest P value in a GWAS comparing severe and mild COVID-19 patients in Japanese people, met the genome-wide significance level in an integrated analysis with an international meta-GWAS. These results suggest that the association between COVID-19 severity and the IL17A / IL17F gene is not unique to Japanese people, but represents a new disease susceptibility gene detected by the integrated analysis with an international meta-GWAS.

[0085] Figure 5 shows the eQTL data for three SNPs identified in a GWAS comparing severe and mild COVID-19 patients. As shown in Figure 5, eQTL data using the Genotype-Tissue Expression (GTEx) database for three SNPs that met genome-wide significance levels in the IL17A / IL17F gene region showed that carrying risk alleles associated with COVID-19 severity significantly reduced IL17F mRNA expression levels.

[0086] However, the eQTL data only corresponded to expression levels in the testis. In the future, direct comparison of IL17F mRNA expression levels between patients with severe and mild COVID-19 is necessary. It is intriguing that the expression level of IL17F, which has been reported to be associated with the prevention of mucosal epithelial infection, may be significantly lower in patients with severe COVID-19.

[0087] IL-17 has been reported to be produced not only by the helper T cell subset Th17 but also by γδT cells and innate lymphoid cells, and is involved in various diseases such as multiple sclerosis, inflammatory bowel disease, and psoriasis.

[0088] Analysis of the functional differences between IL17A and IL17F using knockout mice has been reported. It has been revealed that IL17A, not IL17F, plays a major role in the development of autoimmune diseases such as arthritis and allergic inflammatory responses, and that IL17F is equivalent to IL17A or plays an important role in the defense of mucosal epithelia against Staphylococcus aureus and Citrobacter londentium infections.

[0089] Of the nine genes discovered in the international meta-GWAS comparing all COVID-19 patients and healthy controls, three genes, FOXP4-AS1, ABO, and IFNAR2, were replicated in the Japanese GWAS. While SNPs in these three gene regions met genome-wide significance standards in the integrated analysis, none of the SNPs in the IFNAR2 gene region were significant in the Japanese GWAS (P > 0.05). However, because the odds ratios (ORs) for each SNP were in the same direction as in the international meta-GWAS, the small number of cases suggests that the Japanese GWAS did not have sufficient power.

[0090] In the ABO gene region, only one SNP, rs8176719, was genome-wide significant (see Figure 2D). This SNP is a well-known deletion that determines blood type O, and it was shown that Japanese people with type O blood are less likely to develop COVID-19.

[0091] The association of six genes, including the LZTFL1 gene, which showed the lowest P value in the international meta-GWAS, was not replicated in the Japanese GWAS. Furthermore, the SNPs genotyped in the international meta-GWAS were not included in the Japanese GWAS. Although ORs cannot be directly compared, no SNPs had a P value of <0.01. The SNP rs796171020 near the DDX39BP2 gene, which had the lowest P value in the Japanese GWAS comparing all COVID-19 patients and healthy controls, did not meet the genome-wide significance level in the integrated analysis.

[0092] These results indicate that three of the nine genes found in the international meta-GWAS also play important roles in the research and development of COVID-19 in Japanese people.

[0093] The FOXP4-AS1 and IFNAR2 genes also met genome-wide significance levels in an integrated analysis comparing severe COVID-19 patients and healthy controls. In particular, although FOXP4-AS1 was not associated with severe COVID-19 in an international meta-GWAS, an integrated analysis with a Japanese GWAS revealed its association with severe COVID-19.

[0094] Although it was not possible to directly compare the SNPs from the international meta-GWAS with those from the Japanese GWAS using OR, there were no SNPs with P<0.01.

[0095] These results suggest that three genetic factors, including the IL17F gene newly identified in this analysis, are involved in the development of severe COVID-19 in Japanese people.

[0096] This analysis also revealed that the newly identified IL17F gene, associated with COVID-19 severity, is a common genetic factor across populations. Because all study samples were collected from Japanese COVID-19 patients upon discharge, it was not possible to determine whether IL17F could be used as a marker of disease severity. If a decrease in serum IL17F levels is confirmed, it is expected to become an effective and important serum marker for predicting the severity of COVID-19 patients. In the future, it is hoped that the effectiveness of IL17F as a diagnostic marker will be examined by collecting samples from COVID-19 patients upon hospitalization. [Industrial Applicability]

[0097] The method and kit of this embodiment make it possible to simply and reliably detect genetic factors that contribute to the worsening of COVID-19 in a subject.

Claims

1. A method for assisting in the detection of genetic factors contributing to the severity of COVID-19, comprising: detecting one or more single nucleotide polymorphisms present in a region from the interleukin-17A locus to the interleukin-17F locus in a DNA-containing sample derived from a subject; the single nucleotide polymorphism is one or more selected from the group consisting of NCBI SNP Database accession numbers rs11962054, rs13192563, rs13192246, and rs9474169; When the single nucleotide polymorphism is detected, it indicates that the subject is likely to develop severe COVID-19 caused by SARS-CoV-2 infection.

2. detecting a single nucleotide polymorphism at one or more loci selected from the group consisting of the forkhead box protein 4-antisense RNA 1 (FOXP4-AS1) locus and the interferon alpha and beta receptor subunit 2 (IFNAR2) locus in a DNA-containing sample derived from the subject; In the FOXP4-AS1 locus, a single nucleotide polymorphism associated with the likelihood of COVID-19 becoming severe is registered under the accession number rs1853837 in the NCBI SNP Database. In the FOXP4-AS1 locus, the single nucleotide polymorphism associated with the possibility of developing COVID-19 is one or more selected from the group consisting of NCBI SNP Database accession numbers rs2894439, rs9367106, rs12660421, rs1853837, rs55889968, rs12175265, rs1886814, rs4714474, and rs9381074; In the IFNAR2 locus, single nucleotide polymorphisms associated with the likelihood of severe COVID-19 disease are listed in the NCBI SNP Database under the following accession numbers: rs2186317, rs62226132, rs62226152, rs4553897, rs12482556, rs11088247, rs2300370, rs2248420, rs2834154, rs6517153, rs17860142, rs3153, rs9636867, rs1131964, rs12482014, rs12482193, rs12482060, and rs1786. 0165, rs17860169, rs1051393, rs9976829, rs2834157, rs2236756, rs2252639, rs2252650, rs2284549, rs2284550, rs2284551, rs12053666, rs2073361, rs2834161, rs2834163, rs2834164, rs2834165, and rs2236757; In the IFNAR2 locus, the single nucleotide polymorphism associated with the possibility of developing COVID-19 is one or more selected from the group consisting of NCBI SNP Database accession numbers rs2248420, rs17860142, rs3153, rs12482014, rs12482193, rs12482060, and rs17860165; When a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 and a single nucleotide polymorphism associated with the possibility of developing COVID-19 are detected, it indicates that the subject is at risk of developing COVID-19 due to SARS-CoV-2 infection and at risk of developing severe COVID-19, If a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 is detected, and if a single nucleotide polymorphism associated with the possibility of developing COVID-19 is not detected, this indicates that the subject has a low or no possibility of developing COVID-19 due to SARS-CoV-2 infection, but that if infected with SARS-CoV-2, COVID-19 may become severe; If a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 is not detected and a single nucleotide polymorphism associated with the possibility of developing COVID-19 is detected, it indicates that the subject is at risk of developing COVID-19 due to SARS-CoV-2 infection, but is at a low or no risk of developing severe COVID-19; The method of claim 1, wherein, when a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 is not detected and a single nucleotide polymorphism associated with the possibility of developing COVID-19 is also not detected, the subject is indicated to have a low or no possibility of developing COVID-19 due to SARS-CoV-2 infection and a low or no possibility of developing severe COVID-19.

3. A kit for detecting genetic factors that contribute to the worsening of COVID-19 in a subject, comprising: one or more nucleic acid probes or primers for detecting one or more single nucleotide polymorphisms present in the region from the interleukin-17A locus to the interleukin-17F locus; The kit, wherein the single nucleotide polymorphism is one or more selected from the group consisting of NCBI SNP Database accession numbers rs11962054, rs13192563, rs13192246, and rs9474169.

4. The method further comprises one or more nucleic acid probes or primers for detecting a single nucleotide polymorphism at one or more loci selected from the group consisting of the forkhead box protein 4-antisense RNA 1 (FOXP4-AS1) locus and the interferon alpha and beta receptor subunit 2 (IFNAR2) locus; In the FOXP4-AS1 locus, a single nucleotide polymorphism associated with the likelihood of COVID-19 becoming severe is registered under the accession number rs1853837 in the NCBI SNP Database. In the FOXP4-AS1 locus, the single nucleotide polymorphism associated with the possibility of developing COVID-19 is one or more selected from the group consisting of NCBI SNP Database accession numbers rs2894439, rs9367106, rs12660421, rs1853837, rs55889968, rs12175265, rs1886814, rs4714474, and rs9381074; In the IFNAR2 locus, single nucleotide polymorphisms associated with the likelihood of severe COVID-19 disease are listed in the NCBI SNP Database under the following accession numbers: rs2186317, rs62226132, rs62226152, rs4553897, rs12482556, rs11088247, rs2300370, rs2248420, rs2834154, rs6517153, rs17860142, rs3153, rs9636867, rs1131964, rs12482014, rs12482193, rs12482060, and rs1786. 0165, rs17860169, rs1051393, rs9976829, rs2834157, rs2236756, rs2252639, rs2252650, rs2284549, rs2284550, rs2284551, rs12053666, rs2073361, rs2834161, rs2834163, rs2834164, rs2834165, and rs2236757; In the IFNAR2 locus, the single nucleotide polymorphism associated with the possibility of developing COVID-19 is one or more selected from the group consisting of NCBI SNP Database accession numbers rs2248420, rs17860142, rs3153, rs12482014, rs12482193, rs12482060, and rs17860165; When a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 and a single nucleotide polymorphism associated with the possibility of developing COVID-19 are detected, it indicates that the subject is at risk of developing COVID-19 due to SARS-CoV-2 infection and at risk of developing severe COVID-19, If a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 is detected, and if a single nucleotide polymorphism associated with the possibility of developing COVID-19 is not detected, this indicates that the subject has a low or no possibility of developing COVID-19 due to SARS-CoV-2 infection, but that if infected with SARS-CoV-2, COVID-19 may become severe; If a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 is not detected and a single nucleotide polymorphism associated with the possibility of developing COVID-19 is detected, it indicates that the subject is at risk of developing COVID-19 due to SARS-CoV-2 infection, but is at a low or no risk of developing severe COVID-19; The kit according to claim 3, wherein, when a single nucleotide polymorphism associated with the possibility of developing severe COVID-19 and a single nucleotide polymorphism associated with the possibility of developing COVID-19 are not detected, the subject is indicated to have a low or no possibility of developing COVID-19 due to SARS-CoV-2 infection and a low or no possibility of developing severe COVID-19.

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