WO2014058254A1 - Composition for estimating risk of onset of systemic lupus erythematosus, comprising primer for detecting dna copy number variation in 1q25.1(rabgap1l) location, 6p21.32 (c4) location and 10.q21.3 location - Google Patents

Abstract

The present invention relates to a composition for estimating the risk of onset of systemic lupus erythematosus, and more particularly, to a composition which determines an examinee as having a high risk of onset of systemic lupus erythematosus when a DNA copy number variation has occurred in the C4 region, 1q25.1 region and 10q21.3 region. The composition of the present invention may estimate the risk of onset of systemic lupus erythematosus using the fact that the copy number variation in C4 location, 1q25.1 location and 10q21.3 location has a synergistic effect in the occurrence of systemic lupus erythematosus. The composition of the present invention enables a clinically friendly method that may reduce an error of an analysis which might be caused by a newly purchased device or by technological limitations, by using PCR which is generally performed in most laboratories of hospital. Furthermore, the composition of the present invention has the advantages of being performed on an examinee using a non-invasive method. Thus, the composition of the present invention may estimate the risk of onset of systemic lupus erythematosus at an early stage, and thus can be used in preventing an aggravated state or in delaying the occurrence of the disease.

Description

A composition for predicting the risk of developing systemic lupus erythematosus comprising primers for detecting DNA replication mutations at the RBGAP1L position, the 6P21.32 (C4) position, and the 1023.13 position.

The present invention relates to a composition for predicting the risk of developing systemic lupus erythematosus, and more specifically, to a systemic erythema when a DNA copy number mutation occurs at 1q25.1 (RABGAP1L) region, 6p21.32 (C4) region, and 10q21.3 region. It relates to a composition characterized in that it is seen as a high risk group for the development of reflective lupus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects several organs simultaneously, mainly in young women of childbearing age. In SLE, abnormal immune responses produce pathological autoantibodies and immune complexes accumulate in various organs resulting in inflammation and organ damage. The mechanism of SLE has not yet been fully established, but genetic factors are important because identical twins have a higher risk of developing them than fraternal twins and are closely related to family history.

SLE is a chronic disease that causes symptoms to improve and worsen over time. SLE patients are particularly prone to blood clotting and blood clots, which can cause coronary artery disease even at a young age, which increases the likelihood of developing angina or myocardial infarction. There is also a risk of stillbirth if you are pregnant. It is also vulnerable to respiratory infections such as influenza and pneumococci. Therefore, it is important to anticipate the risk of SLE in advance to delay or prevent the onset of disease, to reduce symptoms through proper treatment when the disease occurs, and to prevent damage to major organs such as the kidney, lung, and heart. Complications of SLE can be prevented by immunization against influenza and pneumococci and by controlling factors associated with atherosclerosis such as hypertension, blood sugar, and lipid metabolism disorders.

Recent genome-wise association studies (GWAS) have identified a number of SNPs identified in candidate genes such as HLA, IRF5, STAT4, TNFAIP3, PTPN22, BLK, BANK1, TNFSF4, ITGAM, KIAA1542, and PXK in relation to the risk of SLE in various ethnic groups. Has been reported. In addition to SNPs, DNA copy number variations (CNVs) have been shown to cause genetic disruption and gene rearrangement that affect protein expression and contribute to SLE development. For example, CNV in C4 and FCGR3B has been shown to increase the risk of SLE in Caucasians. However, there is little research on this in other peoples.

Based on this background, the present inventors studied new markers capable of early diagnosis of the risk of developing SLE. As a result, deletion variants at the 1q25.1 and 10q21.3 loci of the chromosome were found. If present, the risk of developing SLE is significantly increased, thereby completing the present invention.

The present invention has been made in the above background, composition for predicting the risk of developing systemic lupus erythematosus comprising primers for detecting DNA copy number mutations at positions 1q25.1, 6p21.32 (C4) and 10q21.3. It is intended to provide a kit.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problem, another task that is not mentioned will be clearly understood by those skilled in the art from the following description.

The present invention is a composition for predicting the development of Systemic Lupus Erythematosus, wherein the composition is DNA copy number variation of C4 position, 1q25.1 position and / or 10q21.3 position on the chromosome of the sample. Provided is a composition comprising a primer for detection.

The range of DNA copy number variations can be deletion-type (0 or 1 copy) and can be gain-type (> 2 copy), but is not limited thereto.

The RABGAPase activating protein 1-like (RABGAP1L) gene located at 1q25.1 encodes a GPTase-activating protein. The protein has a phosphotyrosine binding domain and is thought to be a tyrosine-kinase that acts in signaling, but it is not known whether it is involved in specific biological actions or etiology.

We found a 5.2 Kb deletion type CNVR located in intron 20 of the RABGAP1L gene in the course of the study, and this CNVR influenced the expression of this gene through selective splicing or posttranslational modification. I found that I could give. In the 10q21.3 position, a 8.3 Kb-sized deletion type CNVR was identified. The 10q21.3 region does not have a gene encoding it, but many GWAS studies have shown that untranslated sites are also involved in various phenotypes. It has also been reported that the nuclease accessible site (NAS) of CD34 + cells is related to the 10q21.3 position. NAS acts as a transcription factor binding site and is known to be involved in hematopoietic stem cell differentiation. Thus, deletion of this position may be involved in the bone marrow differentiation of CD34 + cells and the risk of developing SLE.

Among CNVs previously suggested to be related to SLE in the GWAS discovery step, CNV of C4 showed a significant correlation in the present invention.

On the other hand, the present invention was completed for Korean women, but such copy number variation is highly likely to occur regardless of ethnicity. For example, Yang et al.'S paper reported that Westerners reported a lower risk of developing SLE when the number of copies of C4 was small, and a higher risk of developing SLE when they were large, and the same result was observed for Han Chinese. However, these results were also found in the experiments of the present invention. Specifically, the higher the number of C4 copies, the lower the risk of development (OR = 0.40, 95% CI = 0.16-1.03, P = 0.057). Therefore, the specimen is not limited to Korean women but can be of any ethnicity.

In addition, the chromosome of the sample can be obtained from the cells of the sample derived from oral epithelium, hair, etc., the source of the cell is not limited thereto.

In one embodiment, the primer for detecting DNA copy number variation at position 1q25.1 is a primer pair for genomic quantitative PCR including DNA sequences of SEQ ID NOs: 1 and 2. It is done.

In another embodiment, the primer for detecting DNA copy number variation at position 10q21.3 is a primer pair for genomic quantitative PCR including DNA sequences of SEQ ID NOs: 3 and 4. It is done.

In another embodiment, the primer for detecting DNA copy number variation at position 1q25.1 includes deletion-typing comprising a DNA sequence selected from the group consisting of SEQ ID NOs: 5-8 Characterized in that it is a primer for PCR.

As another embodiment of the present invention, The primer for detecting DNA copy number variation at the 10q21.3 position is a primer for deletion-typing PCR including a DNA sequence selected from the group consisting of SEQ ID NOs: 9 to 12.

In another aspect, the present invention is a kit for predicting the risk of developing Systemic Lupus Erythematosus, wherein the kit is a DNA copy number variation (DNA copy number) at the C4 position, 1q25.1 position and / or 10q21.3 position on the chromosome of the sample. Variation) It provides a kit, characterized in that it comprises a primer (primer) for detection. The term 'kit' of the present invention refers to a set that can be commercialized into a configuration including a biomarker and all other materials necessary for various pretreatment and materials for analysis.

In one embodiment, the kit is characterized in that it comprises a primer comprising a DNA sequence selected from the group consisting of SEQ ID NO: 1 to 12.

The present invention

A) PCR was performed by adding a primer for detecting DNA copy number variation to the sample DNA sample at the 6p21.32 (C4), 1q25.1 and / or 10q21.3 positions on the chromosome of the sample. Performing; And

B) determining whether the sample has a DNA copy number variation at the C4, 1q25.1 and / or 10q21.3 positions from the PCR results performed above. It provides a method of providing information for predicting the risk of developing lupus.

In one embodiment of the present invention,

Of step A) Primer for detecting DNA copy number variation at position 1q25.1 and / or 10q21.3 is a primer for genomic quantitative PCR comprising a DNA sequence selected from the group consisting of SEQ ID NOs: 1-4. It features.

As another embodiment of the present invention,

DNA copy number variation detection, sizing and border primers of the 1q25.1 position and / or 10q21.3 position of step A) is selected from the group consisting of SEQ ID NOs: 5-12 It is characterized in that the primer for deletion-typing PCR containing a DNA sequence.

As another embodiment of the present invention,

The method works for individuals with deletions in all three positions 1q25.1 (RABGAP1L), 6p21.32 (C4) and 10q21.3 (OR = 5.52), and in two of three positions (OR = 1.78). ), The risk of developing systemic lupus erythematosus is diagnosed in the order of deletion in one of the three positions (OR = 1.43) and in the absence of deletion in all three positions (OR = 1). The OR according to the number of deletions showed a concentration-dependent increase (r ² = 0.965).

The compositions of the present invention make it possible to predict the risk of onset by having a replication number variation at the C4, 1q25.1 and 10q21.3 positions having a synergistic effect on the development of systemic lupus erythematosus and is common in most hospital laboratories. The use of PCR is a clinically friendly way to reduce errors in analysis that can occur due to new equipment purchases or technical limitations. In addition, the present invention has the advantage that can be performed in a non-invasive way to the test subject. Ultimately, the present invention is expected to be important for early prediction of the possibility of developing systemic lupus erythematosus and for preventing or slowing the progression of the condition.

1 is a diagram illustrating an analysis process ranging from genome-wide CNV discovery to independent replication.

FIG. 2 is a schematic diagram showing that a region containing a very small number of CNVs is not viewed as a CNVR.

Fig. 3 shows the allele intensity and qPCR confirmation results of RABGAP1L CNV at 1q25.1 .

4 shows ORs for SLEs of 1q25.2 (RABGAP1L) and 10q21.3 by the number of copies. In this figure, the number of copies refers to the number of copies detected by qPCR. Independent replication experiments show that the deletions in the 1q25.1 and 10q21.3 CNV regions are associated with lupus risk, whereas those with a relatively high number of copies show a lower lupus risk.

5 is a schematic diagram showing a strategy for determining deletion typing PCR and deletion-CNVR boundaries. White boxes indicate deleted areas. The blue arrow in the flanking region of the region where the deletion is expected to indicate a primer set to search for the deletion. Red arrows in the deleted sites indicate a set to distinguish between HOM and HET. The upper diagram shows the strategy diagram of two CNVRs, the middle diagram shows the results of electrophoresis of the deletion-typing PCR product according to each strategy, and the lower diagram shows the deletion breakpoint (pointed by arrow) through DNA sequencing. to be.

Figure 6 shows the distribution number distribution for the entire C4, C4A and C4B genes identified by qPCR. Black bars represent patient groups and gray bars represent controls.

7 shows the concentration dependent trend of OR for SLE sensitivity. The inventors expected that the greater the degree of deletion, the higher the risk of developing SLE than the criteria.

The present inventors attempted to identify CNV related to SLE by analyzing genome-wide CNV profiles of 400 Korean SLE patients and 200 healthy Koreans using SNP arrays. To this end, in the first stage, 18,266 CNVs were found through genome-wide CNV analysis. Based on this, 2544 CNVRs were defined, and correlation analysis was performed on 144 CNVRs with a frequency of 5% or more. Of the 144 common CNVRs, GWAS analysis revealed that 1q25.1, 8q23.3, and 10q21.3 were most relevant to SLE (OR = 2.28, P = 4.4 x 10 ^-3 ; OR = 0.37, P =, respectively). 5.2 × 10 ⁻⁴ , OR = 1.62, P = 0.039).

Designing primers specific for these three candidate CNVR regions and performing target-specific qPCR on a larger set of independent experimental-control groups than the one-step experimental-control set replicated the results of step 1, 1q25. CNV of 1 and deletion of 10q21.3 were replicated successfully (OR = 1.30, P = 0.038; OR = 1.90, P = 3.6 × 10 ^{−5, respectively} ).

In addition to the three candidate CNVR regions, CNVRs in the C4 gene region were found to be highly related to SLE during the GWAS discovery stage. Therefore, the independent verification of C4 using qPCR method showed that the risk of SLE was significantly higher (OR = 1.88, P = 0.01). ). Therefore, C4 CNVR was also included in the SLE risk prediction model. As a result, in all three sites, the risk of developing SLE was significantly higher than in all three sites (OR = 5.52, P = 3.9 x 10 ^-4 ).

Their relationship was again confirmed by deletion typing PCR. We designed specific primers that can directly identify the presence, size, and boundaries of deletions for two relevant CNVR regions that were successfully cloned by genomic qPCR method, and performed deletion-typing PCR. The exact size (5.2Kb for 1q25.1 and 8.3Kb for 10q24.3) and deletion breakpoints were identified. As with qPCR, the association between deletion of 1q25.1 and 10q21.3 and SLE risk was successfully replicated in replication experiments using deletion-typing PCR (OR = 1.38, P = 0.009, OR = 1.40, P = 0.011, respectively). .

Hereinafter, preferred examples are provided to aid in understanding the present invention. However, the following examples are merely provided to more easily understand the present invention, and the contents of the present invention are not limited by the following examples.

EXAMPLE

Example 1 Study Subject and Statistical Analysis Method

1-1. Study subject

All study subjects consisted of Korean ethnic groups.

For CNV-GWAS analysis, 400 SLE patients (all women, average age 31 ± 10.0 years) were recruited from the BAE lupus population of the rheumatoid disease department of Hanyang University Hospital (South Korea, Seoul). These patients are those who were diagnosed as SLE by the 1997 American College of Rheumatology classification criteria. As a control group, 200 people who were not SLE patients were recruited from the same hospital (all women, mean age 33 ± 9.2 years).

For independent replication, 564 patients and 511 controls (1075 total) were recruited from the same hospital.

This study was conducted with the approval of the institutional review board (CUMC11U199).

1-2. Statistical analysis

Statistical analysis was performed using Stata software (version 10.0; Stata Corporation, College station, TX) and SPSS for Windows (version 11.5; SPSS, Chicago, IL). P value of 0.05 or more was considered significant.

Example 2 Total Genome SNP Genotype Analysis

Genotype analysis of the entire genome SNP was performed using Illumina's Human 610s Quad-Bead Chip platform (including 620,901 SNP markers). The average number of probes per known CNV is 37.7. Approximately 750 ng of genomic DNA per sample was used for genotyping. The sample we used showed an average SNP call rate of 99.89 ± 0.16%. To minimize plate or batch effects, all procedures were performed in the same environment for the same period.

Example 3. Quality Verification and Replication Number Variation (CNV) Identification

Experimental data including signal intensity (log R ratio (LRR)) and allele intensity (B allele frequency) were obtained using Illumina GenomeStudio software.

3-1. Quality verification

First, the quality of this data was verified. Subjects were tested if the successful SNP call rate was less than 90%, if the LRR standard deviation was greater than 0.24, if the B conjugate frequency drift was greater than 0.01, and if the wave factor was less than 0.05. Excluded from the results.

3-2. CNV Extraction

We extracted CNV using the PennCNV algorithm as the default setting, based on the signal intensity (log R ratio (LRR)) and allele intensity (B allele frequency) data.

The PennCNV algorithm uses HMM, so there was no threshold on the minimum number of consecutive CNVs (CVVs), but all of the SNPs found in this process were more than three consecutive SNPs (3-1988). A different number of SNPs were found, with the average number of probes per CNV being 13.42, with a median of 7. The boundary of each CNV is determined by the length from the linear position of the first SNP probe to the last probe (hg18). General characteristics of CNV are shown in Table 1 below.

Table 1

Parameters	Case (n = 382)	Control (n = 191)	Total (n = 573)	Mann-WhitneyP-value
Total number of CNVs	12,287	5,979	18,266
Avg. CNVs per sample (Median)	30.8 (30)	30.2 (30)	30.6 (30)	0.906
Gain	13.4 (11)	12.0 (11)	12.9 (11)	0.153
Los	17.9 (17)	18.3 (18)	18.0 (18)	0.096
Avg. of Size (kb) (Median)	49.2 (20.4)	54.1 (21.1)	52.5 (21.0)	0.012
Gain	70.1 (30.1)	71.4 (29.3)	70.5 (29.8)	0.107
Los	42.4 (13.2)	34.8 (13.2)	39.8 (13.2)	0.548
Ratio (Loss / Gain)	1.4	1.5	1.4

The boundaries of each CNV were determined by the straight line distance from the first SNP probe to the last SNP probe (hg18).

First quartile -1.5 * IQR <N < third quartile +1.5 * Calculated according to the formula, samples containing too little or too many CNV were excluded from the experimental results. Where N is the number of CNVs detected in each sample and IQR is the inter-quartile range calculated from the CNV extraction set detected in 600 subjects. Finally, a total of 573 samples (382 patients and 191 controls) were included in the analysis.

Example 4 CNV Region Identification and Statistical Analysis

We generate CNV data for each probe and distinguish CNVs based on the number of replicates consisting of normal (2X), deletion (homozygous deletion = 0X; semijunction deletion = 1X), acquisition (≥3X). did. CNV was identified from 573 individuals and the CNV region (CNVR) was identified by combining the overlapping parts between CNVs using CNVRuler software as described in Redon et al. This method has the advantage of directly identifying the CNVR, but has the disadvantage that the size of the CNVR can be calculated larger than the actual one when there is a particularly large CNV among the CNVs included in the CNVR. In addition, even if all CNV extractions are included, if the frequency of the CNVR includes a singleton or a very rare CNV, the size of the CNVR may be larger than the actual size (see FIG. 2). To minimize this possibility, areas containing only a small number of CNVs (less than 10% of the total CNVs) were not viewed as CNVRs.

A total of 18,266 CNVs were identified in 573 samples. The median CNV number for an individual was 30 (range of 1-285) and the median size of CNV was 21.0 kb (range 14 bp-18 Mbp). Copy number-loss CNV was 1.4 times more frequent than copy number-gain CNV.

2,544 CNVRs were identified from 18,266 CNVs. Of those, 144 CNVR were present in over 5% of the individuals.

Table 2 below shows 144 CNVRs found in 5% or more individuals.

TABLE 2

CNVR	Chr	Start (bp)	End (bp)	Length (Kb)	G / L	RefSeq gene annotation
cnve1	One	1,610,720	1,626,497	15.7	G / L	MMP23A, CDK11B, CDK11A
cnve2	One	12,777,429	12,841,261	63.8	G / L	PRAMEF11, LOC649330, HNRNPCL1, PRAMEF2
cnve3	One	17,085,956	17,140,083	54.1	G / L	CROCC
cnve4	One	76,124,315	76,124,567	0.25	G / L	MSH4
cnve5	One	147,292,384	147,637,598	345.2	G / L	LOC388692, FCGR1C
cnve6	One	173064490	173068262	3.7	G / L	RABGAP1L
cnve7	One	246,837,884	246,852,068	14., 1	G / L	-
cnve8	2	24,456,463	24,459,556	3.1	L	-
cnve9	2	36,263,684	36,264,490	0.8	G / L	-
cnve10	2	41,092,148	41,101,972	9.8	G / L	-
cnve11	2	52,613,957	52,637,176	23.2	G / L	-
cnve12	2	89731562	89885025	153.4	G / L	-
cnve13	2	132,485,521	132,588,945	103.4	G / L	-
cnve14	3	1,652,400	1,666,090	13.7	L	-
cnve15	3	37,954,886	37,961,253	6.4	L	CTDSPL
cnve16	3	53,003,023	53,013,826	10.8	L	SFMBT1
cnve17	3	65,166,887	65,187,636	20.8	L	-
cnve18	3	90,421,209	90,576,572	155.4	G / L	-
cnve19	3	150,446,085	150,450,025	3.9	L	-
cnve20	3	163,699,360	163,712,278	12.9	G / L	-
cnve21	3	164,004,033	164,101,579	97.5	G / L	-
cnve22	3	191,220,845	191,221,750	0.9	G / L	LEPREL1
cnve23	4	8,980,214	9,097,760	117.5	G / L	DEFB131, LOC650293
cnve24	4	10,006,425	10,009,254	2.8	L	-
cnve25	4	20,982,707	20,984,915	2.2	L	KCNIP4
cnve26	4	34,469,747	34,499,424	29.7	L	-
cnve27	4	58,417,022	58,418,605	1.6	G / L	-
cnve28	4	63,352,170	63,367,714	15.5	G / L	-
cnve29	4	64,380,191	64,392,223	12	G / L	-
cnve30	4	69,064,675	69,163,188	98.5	G / L	UGT2B17
cnve31	4	70,164,518	70,257,471	92.9	G / L	UGT2B28
cnve32	4	115,398,433	115,401,739	3.3	G / L	-
cnve33	4	116,387,607	116,393,377	5.8	L	-
cnve34	4	122,504,713	122,508,095	3.4	L	QRFPR
cnve35	4	138,312,400	138,316,899	4.5	L	-
cnve36	4	162,083,343	162,146,977	63.6	G / L	-
cnve37	5	783,022	873,185	90.2	G / L	ZDHHC11
cnve38	5	27,462,485	27,462,654	0.17	G / L	-
cnve39	5	32,142,841	32,202,977	60.1	G	PDZD2, GOLPH3
cnve40	5	70,210,770	70,415,222	204.4	G / L	GTF2H2, GTF2H2B, GTF2H2D, GTF2H2C, SERF1B, SERF1A, SMN1, SMN2, NAIP, OCLN, LOC647859
cnve41	5	151,495,149	151,499,003	3.9	L	-
cnve42	5	180,327,250	180,363,775	36.5	G / L	BTNL3
cnve43	6	219,847	306,547	86.7	G / L	DUSP22
cnve44	6	29,965,065	30,003,207	38.1	G / L	HCG2P7, HCG4P6, HLA-H
cnve45	6	31388080	31406722	18.6	G / L	-
cnve46	6	31,445,794	31,449,319	3.5	G / L	-
cnve47	6	31,465,370	31,561,597	96.2	G / L	MICA, HCP5, HCG26, MICA
cnve48	6	31,979,464	31,986,474	7	L	C2
cnve49	6	32058245	32110823	52.6	G / L	STK19, STK19, TNXA, C4A, C4B
cnve50	6	32,563,460	32,600,286	36.8	G / L	HLA-DRB5
cnve51	6	32,608,853	32,629,229	20.4	G / L	HLA-DRB6
cnve52	6	32,630,503	32,666,924	36.4	G / L	HLA-DRB1, HLA-DRB6
cnve53	6	32,672,677	32,672,762	0.086	G / L	-
cnve54	6	32,746,293	32,756,221	9.9	G / L	-
cnve55	6	57,482,074	57,503,129	21.1	G	PRIM2
cnve56	6	62,241,860	62,281,216	39.4	G / L	-
cnve57	6	77,074,879	77,081,385	6.5	L	-
cnve58	6	79,029,649	79,090,197	60.5	L	-
cnve59	6	81,341,226	81,346,109	4.9	G / L	-
cnve60	6	162,655,871	162,659,755	3.9	G / L	PARK2
cnve61	6	169,248,365	169,262,485	14.1	L	-
cnve62	6	170,222,030	170,223,555	1.5	G / L	-
cnve63	7	136,005	164,003	27.9	G / L	-
cnve64	7	61,256,909	61,311,414	54.5	G / L	-
cnve65	7	101,931,221	102,109,692	178.5	G / L	POLR2J3, SPDYE2, SPDYE2L, POLR2J2, UPK3BL, RASA4
cnve66	7	141,419,097	141,441,259	22.2	G / L	MGAM
cnve67	8	3,773,951	3,777,675	3.7	G / L	CSMD1
cnve68	8	5,583,199	5,592,495	9.3	G / L	-
cnve69	8	7,242,915	7,459,302	216.4	G / L	DEFB families,
cnve70	8	7,683,445	7,830,417	146.9	G / L	DEFB families
cnve71	8	12,570,457	12,603,846	33.4	G / L	-
cnve72	8	15,447,307	15,455,979	8.7	L	TUSC3
cnve73	8	25,129,632	25,130,278	0.64	G / L	DOCK5
cnve74	8	39,356,825	39,497,557	140.7	G / L	ADAM3A, ADAM5P
cnve75	8	115704806	115711712	6.9	G / L	-
cnve76	9	4,516,796	4,519,671	2.9	L	SLC1A1
cnve77	9	11,398,647	11,398,865	0.22	G / L	-
cnve78	9	11,786,468	12,110,085	323.6	L	-
cnve79	9	43,515,795	43,730,292	214.5	G / L	FAM75A6
cnve80	9	44,708,655	44,779,627	70.9	G / L	-
cnve81	9	45,757,243	45,837,067	79.8	G / L	-
cnve82	9	66,345,398	66,759,835	414.4	G / L	LOC100133920
cnve83	9	140,149,899	140,225,046	75.1	G	TUBBP5
cnve84	10	38,740,240	38,953,282	213	G / L	LOC399744
cnve85	10	41679826	41702521	22.7	G / L	-
cnve86	10	58,575,075	58,606,559	31.5	L	-
cnve87	10	66980652	66983043	2.4	G / L	-
cnve88	10	81,478,475	81,492,542	14.1	G / L	-
cnve89	11	4,217,831	4,333,781	115.9	G / L	-
cnve90	11	5,856,461	5,891,679	35.2	G	OR52E4
cnve91	11	48,689,789	48,868,236	178.4	G / L	-
cnve92	11	48,886,497	48,918,267	31.8	G / L	-
cnve93	11	50,470,172	50,687,058	216.9	G / L	-
cnve94	11	54,649,547	54,738,983	89.4	G / L	-
cnve95	11	55,124,465	55,209,499	85	G / L	OR4S2, OR4P4, OR4C11, OR4C6
cnve96	11	99,152,896	99,160,002	7.1	L	CNTN5
cnve97	12	9,526,879	9,607,393	80.5	G / L	-
cnve98	12	11,398,341	11,438,799	40.5	G / L	PRB1, PRB2
cnve99	12	31,202,075	31,237,140	35.1	G / L	-
cnve100	12	33,192,424	33,197,122	4.7	L	-
cnve101	12	36,270,798	36,667,312	396.5	G / L	-
cnve102	13	18,209,780	18,299,097	89.3	G / L	-
cnve103	13	49,238,624	49,271,799	33.2	G / L	KPNA3
cnve104	13	56,648,172	56,722,157	73.9	G / L	-
cnve105	14	18,312,221	18,373,017	60.8	G / L	-
cnve106	14	19,255,839	19,493,705	237.9	G / L	OR4Q3, OR4M1, OR4N2, OR4K2, OR4K1, OR4K5
cnve107	14	40,679,974	40,738,084	58.1	L	-
cnve108	14	43,574,960	43,600,472	25.5	L	-
cnve109	14	105,099,614	105,259,090	159.5	G / L	-
cnve110	15	18,822,301	18,883,654	61.3	G / L	HERC2P3
cnve111	15	19,095,051	19,545,168	450.1	G / L	NF1P1, BCL8, LOC646214, POTEB, CXADRP2
cnve112	15	19,768,826	20,093,116	324.3	G / L	LOC727924, REREP3, OR4N3P, OR4N4, OR4M2
cnve113	15	22,134,751	22,284,089	149.3	G / L	-
cnve114	15	30,272,117	30,302,218	30.1	G / L	-
cnve115	15	32,459,510	32,595,161	135.7	G / L	MIR1233-1, MIR1233-2, GOLGA8A
cnve116	15	54,579,805	54,582,930	3.1	L	-
cnve117	16	16,519,474	16,713,816	194.3	G / L	-
cnve118	16	22,538,900	22,617,264	78.4	G / L	-
cnve119	16	27,147,411	27,147,520	0.11	G / L	NSMCE1
cnve120	16	32,404,517	32,511,911	107.4	G / L	-
cnve121	16	33,778,130	33,820,307	42.2	G / L	-
cnve122	16	54,390,068	54,420,550	30.5	G / L	CES1
cnve123	16	68,715,069	68,753,813	38.7	G	PDPR
cnve124	17	14,984,724	14,998,961	14.2	G / L	-
cnve125	17	31,462,326	31,567,477	105.2	G / L	CCL3L1, CCL4L1, CCL4L2, CCL3L3, TBC1D3B
cnve126	17	41,780,482	41,922,658	142.2	G / L	NSFP1, ARL17B
cnve127	18	14,170,547	14,271,864	101.3	G / L	-
cnve128	18	64,897,188	64,906,488	9.3	G / L	-
cnve129	19	20,404,485	20,507,068	102.6	L	-
cnve130	19	32,470,668	32,730,547	259.9	G / L	-
cnve131	19	33,903,241	33,903,289	0.05	G / L	-
cnve132	19	46,041,879	46,064,315	22.4	G / L	CYP2A6
cnve133	19	47,997,996	48,235,556	237.6	G / L	PSG6, PSG1, LOC100289650, PSG10, PSG7, PSG11
cnve134	19	58,023,726	58,050,701	26.9	G / L	ZNF468
cnve135	20	26,235,048	28,107,200	1,872	G / L	-
cnve136	21	9,730,102	9,870,617	140.5	G / L	-
cnve137	22	22,619,365	22,728,586	109.2	G / L	GSTTP1, DDTL, GSTT2B, DDT, GSTT2, LOC391322, GSTT1, GSTTP2
cnve138	22	49,129,839	49,130,879	One	G / L	PPP6R2
cnve139	X	16,305,623	16,306,395	0.8	G / L	-
cnve140	X	58406597	58580762	174.2	G / L	-
cnve141	X	61660428	61815821	155.4	G / L	-
cnve142	X	93,289,757	93,290,555	0.8	G / L	-
cnve143	X	110,851,010	110,851,339	0.33	G / L	ALG13
cnve144	X	145712954	145717285	4.3	G / L	-

Using these 144 CNVRs, logistic regression analysis was performed. This prevented the experimental results from appearing differently according to age groups and experimental groups. To solve the problem of T multiple comparison, a false discovery rate (FDR) method was used. CNVRs with P <0.05 and FDR <0.1 were considered significant. As a result, we found three CNVRs at 1q25.1, 8q23.3, and 10q21 that were most relevant to the risk of SLE. This is shown in Table 3 below.

TABLE 3

CNVRLocation	Start * (bp)	End * (bp)	Length (kb)	Type	Genes	GWAS Discovery 1 (382 cases vs 191controls)			Replication 2 (564 cases vs 511controls)			Replication 3 (564 cases vs 495controls)
						P	FDR	OR (95% CI)	P	FDR	OR (95% CI)	P	FDR	OR (95% CI)
1q25.1	173,06.490	173,068.26	3.8	Los	RABGAP1L	4.40E-03	0.024	2.28 (1.29-4.01)	0.038	0.057	1.30 (1.02-1.67)	0.009	0.011	1.38 (1.08-1.77)
8q23.3	115,704.81	115,711.71	6.9	Los	-	5.20E-04	0.044	0.37 (0.21-0.65)	0.23	0.23	0.85 (0.65-1.11)	ND	ND	ND
10q21.3	66,980.65	66,983.04	2.4	Los	-	0.039	0.066	1.62 (1.02-2.56)	3.60E-05	1.10E-04	1.90 (1.40-2.58)	0.011	0.011	1.40 (1.08-1.81)

* hg18;

¹ Principal component analysis was performed to adjust population stratification.

² Replication by qPCR;

³ Replication by deletion-typing PCR;

^† Adjusted for age; ND, not determined

The OR of CNVRs was calculated based on the 2n individuals. In replication by deletion typing PCR, OR was calculated based on ≧ 2n. Principal componet analysis (PCA) was performed to correct the effect of population distribution by age group. For regression analysis, the top two principal components derived from PCA analysis, PC1 and PC2, were used as covariates, and SNP-array batch information was also used as a covariate for regression analysis. FDR was calculated as the p-value of 144 CNVR.

Among the CNVR sites that have been identified as being related to SLE in addition to the three CNVRs described above, C4 (6p21.32) replication number deletion was more frequent in the SLE patient group, and acquisition type CNVRs were more likely to develop SLE. It has been shown to have a blocking effect. However, these results did not reach statistical significance (OR = 2.35, 95% CI = 0.64-8.57, P = 0.197 for loss; OR = 0.40, 95% CI = 0.16-1.03, P = 0.057 for gain) .

Example 5 Validation of CNVRs Associated with SLE Using genomic qPCR

We designed a specific primer set for amplification for genomic quantitative PCR (qPCR). This primer set was used to identify and replicate the CNVR found to be highly related to SLE during GWAS discovery.

All primers used in this study were experimentally confirmed to be suitable for quantifying the number of copies. Information on this is shown in Table 4 below.

Table 4

Chr	Start	End	AmpliconSize (bp)	Forward	Reverse	Efficiency (%)	R 2
One	173064505	173064592	88	AGGTCAAACATCACCTGCTCTGGA (SEQ ID NO: 1)	TAACGCCAACAGTGGTGCTCTAGT (SEQ ID NO: 2)	104.7	0.99
8	115705632	115705728	97	ACAAGACCATGTGGCCCTATGTGA	CAGCATCTTCTTGCCTAACAGCCT	90.3	0.993
10	66981511	66981683	173	ACCCAGCCTCAGGTATTCCTTTGT (SEQ ID NO: 3)	AGGATTCTGGTGGTGTGGCTAGAA (SEQ ID NO: 4)	91.7	0.998

Genomic qPCR was performed using a Viia 7 system (Life Technologies, Carlsbad, Calif.).

For qPCRs of 1q25.1 and 10q21.3, 20 μl of a reaction mixture containing 20 ng of genomic DNA, SYBR Premix Ex Taq ™ II (TaKaRaBio), 1 × ROX, and 10 pmol of primer were used. After performing 1 cycle for 30 seconds at 95 ℃, 45 cycle was performed by 5 seconds at 95 ℃, 10 seconds at 55 ℃, 30 seconds at 72 ℃.

For the C4 gene (C4A and C4B), the copy number was determined by performing genomic qPCR using two Taqman assays (Hs07226349_cn and Hs07226350_cn (Life Technologies)) designed specifically for C4 A and C4 B. A total of 10 μl of reaction mixture was used, including 10 ng of genomic DNA, TaqMan universal PCR master mix II (Life Technologies), C4A or C4B TaqMan probe, and RNaseP TaqMan probe. PCR conditions were carried out with 40 cycles of 1 cycle at 95 ℃ for 10 minutes, 15 seconds at 95 ℃ for 1 minute at 60 ℃.

PCR efficiency (Cr value) for the entire primer was determined by standard curve over serial 1: 5 dilution. The Ct value is determined by the number of PCR cycles required for the reference gene to reach the threshold of the standard curve. The copy number variation for each target was defined as 2 ^−ΔΔCT . Where ΔCt is the difference in threshold cycles for the values obtained from the reference gene (RNase P) and calibrator DNA (individual / calibrator) in the sample to be identified. The ratio data is then divided by the nearest integer. In summary, we divided 511 normal control samples into diploids and adjusted all measured 1q25.1 and 10q21.3 qPCR ratio values to two replicates. Adjusted ratio values were rounded to the nearest integer. The frequency distribution of these three CNVRs is shown in the table below (Table 5). The left column is the frequency distribution of CNVR GWAS discovery results, the middle column is the qPCR verification result, and the right column is the deletion typing PCR verification.

Table 5

From the SNP-array intensity signal, 92.8% of the CNV in the array was also detected in genomic qPCR. The allele intensity and qPCR identification results of RABGAP1L CNV at 1q25.1 are shown in FIG. 3.

3 is a genoplot image of the rs4480415 marker (173066744 position, hg18) obtained by Illumina GenomeStudio software. The signal strengths at these positions form six distinct clusters of 2X (A / A, A / B / B / B), 1X (A /-, B /-), and 0X (-/-), respectively. As a result, the number of replicas can be known. The figure in the center shows the signal strength ratio around the 1q25.1 region. 3 is a diagram confirming the estimated number of copies of the 1q25.1 region by genomic qPCR. The X axis represents the state of copy number by PennCNV, and the Y axis represents the estimated DNA copy number by qPCR.

Independent Cohort Validation Using Genomic qPCR The association of 10VR2 CNVR with CNVR across RABGAP1L at 1q25.1 was successfully replicated in the independent validation cohort (Table 3). However, the CNVR at position 8q23.3 did not replicate. We used 2n subjects as the basis for predicting the risk of developing SLE (OR = 1.30, 95% CI 1.02-1.67, P = 0.038), but OR decreased with increasing number of copies (r ² = 0.939). (Figure 4 left). Individuals with a deletion type CNVR at the 10q21.3 position also had a higher risk of developing SLE than those with 2n at replication (OR = 1.90, 95% CI 1.40-2.58, P = 3.6 x 10 ^-5 ). There was no consistent trend in OR in the context (r ² = 0.528) (Figure 4 right).

Since CNVR in the C4 gene was also found to be associated with the risk of SLE during GWAS discovery, this CNVR was also replicated independently (308 patient groups and 307 control groups). To determine the number of copies of C4, DNA of HeLa cells known to have diploid copies of this gene was set as a diploid control and adjusted accordingly. Based on individuals with 2n, individuals with a C4A replication deletion showed a significantly higher risk of developing SLE (OR = 1.83, 95% CI 0.19-0.49, P = 3.6 x 10 ^-6 ), and C4A Individuals with a copy number of had a significantly lower risk of developing SLE (OR = 0.30, 95% CI 1.15-3.06, P = 1.87 x ^10-6 ). However, C4B's CNVR was not associated with the risk of SLE. Individuals with total C4 (C4A + C4B) deletions also had a significantly higher risk of developing SLE than individuals with 4n (OR = 1.88, 95% CI 1.15-3.06, P = 0.01).

The frequency distribution of 6p21.32, a CNVR across C4, is shown in Table 6 below. The upper table of Table 6 shows CNV GWAS discovery results and the following table shows qPCR verification experiment results.

Table 6

Example 6 Confirmation of CNV Size and Boundary by Deletion-typing PCR

6-1. Check size and boundary of CNV

As a result of Example 5, the inventors performed deletion-typing PCR in order to confirm the exact size and boundary of CNV of the two regions (1q25.1 and 10q21.3) showing significant association with SLE. Amplicons of deleted alleles were sequenced using PCR-direct sequencing. In the case of the C4 region, the deletion-typing PCR design was not possible.

To determine the exact size and boundaries of 1q251. And 10q21.3, we devised a deletion typing PCR strategy. Primer sets were designed in the flanking sequence around the expected deletion site and in the deletion region. Specific information about this is shown in Table 7. PCR was performed under the following conditions. 20 μl of a reaction mixture containing 20 ng of genomic DNA, 0.4 unit of FX DNA polymerase (TOYOBO, Osaka, Japan), 2% DNSO, and 6 pmol of primer was prepared. PCR was performed for 1 cycle at 94 ° C for 2 minutes, at 98 ° C for 10 seconds and at 69 ° C for 1 minute / Kb. After the PCR reaction, 10 μl of the PCR product was electrophoresed on 0.5% agarose gel. The deleted alleles were sequenced by PCR-direct sequencing method.

TABLE 7

Target Region	Forward Primer (5´―3´)	Reverse Primer (5'-3 ')
1q25.1_Long	AAGCGTCACGTTCTCATTGTGGCA (SEQ ID NO: 5)	TCCCACCCATTCAAGCACTAAGGT (SEQ ID NO: 6)
1q25.1_Short	AAGCGTCACGTTCTCATTGTGGCA (SEQ ID NO: 7)	AGCTGCCAAGCAAGATTCACGTTC (SEQ ID NO: 8)
10q21.3_Long	GATGGTGGCAGCAAAGTCAACACA (SEQ ID NO: 9)	CATTCTGCCAAACATGAAGGGCCA (SEQ ID NO: 10)
10q23.1_Short	GATGGTGGCAGCAAAGTCAACACA (SEQ ID NO: 11)	TGACCAGGATACTGCAGATGGCAA (SEQ ID NO: 12)

In summary, the experiment strategy of FIG. 5 shows that if PCR is performed including a region of expected deletion, a PCR amplification product of the expected size appears in the absence of a deletion, whereas a PCR amplification product of which the length is reduced by that size appears. It is a principle.

The amplicon size of the total allele of the 1q25.1 region designed by the inventors was 9.4 Kb, and the predicted size of the deletion region at 1q25.1 based on the start-end position of the SNP. Was 3.8 Kb. Therefore, the magnitude of the amplification of the deletion allele was calculated to be 5.6 Kb. However, since the actual amplification size of the deleted allele was 4.2 Kb or less, the actual deletion size at 1q25.1 was calculated to be 5.2 Kb or less, not 3.8 Kb. Therefore, a person who shows only 9.4Kb bands can be interpreted as 2n (diploid), a person who shows only 4.2Kb bands can be interpreted as homozygous deletion (HOM), and a person who shows both 9.4Kb and 4.2Kb bands as heterozygous deletion (HET). do.

Likewise, the predicted size of the deletion region based on the start-end position of the SNP in the 10q21.3 region was 2.4 Kb and the amplification size of the designed allele was 11.6 Kb. Therefore, a 9.2 Kb-sized deletion typing PCR amplification product is expected, but the size of the amplification product of the deletion allele was 3.3 Kb or less, so the amplification size of the actual deletion allele in the 10q21.3 region was 8.3 Kb or less, not 2.4 Kb. Was calculated. Therefore, a person who shows only 11.6Kb band can be interpreted as 2n (diploid), a person who shows only 3.3 Kb band can be interpreted as homozygous deletion (HOM), and a person who shows 11.6 Kb and 3.3 Kb band at the same time can be interpreted as heterozygous deletion (HET). do.

We sequenced the amplifications of the deleted genes and identified the exact size and breakpoint of the deletion sequence.

5 disruption shows the results of electrophoresis of deletion-typing PCR products.

In the left side of FIG. 5, the region 1q25.1 includes Band 1, 9.4 Kb; Band 2, 4.2 Kb; Band 3, 2.3 Kb. In the right side of FIG. 5, the 10q21.3 region includes Band 1, 11.6 Kb; Band 2, 3.3 Kb; Band 3, 3.2 Kb. P1 and P2 mean primer sets 1 and 2, respectively.

5 bottom is an example of a DNA sequence showing deletion breakpoints (parts indicated by arrows) of 1q25.1 and 10q21.3.

6-2. Comparison of homozygous and heterozygous deletions

Although heterozygous samples must have two sizes of amplification (full size and size of deletion), full size amplification is preferred for small size PCR in both CNVRs. for small-sized PCR). Therefore, to distinguish homozygous and heterozygous deletions based on deletion mapping data, we sought to redesign the primers in the deleted sequences to test for the presence of short amplifications that represent the entire allele ( 5, Table 7). If the sample had a heterozygous deletion, the total allele would produce an amplified product of the expected size (2.3 Kb for 1q25.1, 3.2 Kb for 10q21.3), but not for the deletion allele. If the sample had a homozygous deletion, it was expected that no PCR amplification would be produced.

As a result, we interpreted the deletion type as follows. For 1q25.1 homozygous deletions are 4.2 Kb band positive, 9.4 Kb band negative, 2.3 Kb band negative, for heterozygous deletions are 4.2 Kb band positive, 2.3 Kb band positive, and the 9.4 Kb band is positive but may not appear. If there is more than one copy number variation, it is 9.4 Kb band positive, 2.3 Kb band positive, 3.2 Kb band negative, 4.2 Kb band negative. For 10q21.3, homozygous deletion will be 3.3 Kb band positive, 3.2 Kb band negative, 11.6 Kb band negative, heterozygous deletion will be 3.3 Kb band positive, 3.2 Kb band positive, and 11.6 Kb may be positive but may not appear. If there is more than one copy number variation, it will be 11.6 Kb band positive, 3.2 Kb band positive, 3.3 Kb band negative (FIG. 4).

This strategy was able to accurately distinguish between HOM, HET, ≧ 2n (FIGS. 4B and 4C). Replicates of deleted alleles were sequenced to determine the exact size of the deletion site and the deletion breakpoint.

We performed deletion typing PCR by applying the designed deletion typing PCR strategy to an independent validation cohort (564 cases and 495 controls) and found that less than 95% of the deletions identified by qPCR are consistent with the deletion typing PCR results. Said. Based on the deletion-typing PCR results, people with CNVR at 1q25.1 (HOM and HET) had a greater chance of developing SLE compared to ≥2n (OR = 1.38, 95% CI 1.08-1.77, P = 0.0009). ), The same was true for the deletion at 10q21.3 (OR = 1.40, 95% CI 1.08-1.81, P = 0.011) (Table 3). 1q24.1 or 10q21.3 HOMs showed a significantly higher risk of developing SLE compared to ≥2n (OR = 1.82, 95% CI 1.03-3.20, P = 0.039; OR = 1.46, 95% CI 1.01-2.10, P = 0.044). The meta-analysis of GWAS discovery and deletion typing PCR showed that CNVR correlation was more significant (OR = 1.51 for 1q24.1, 95% CI 1.20-1.89, P = 4 x 10 ^-4 ; 10q21). For .3, OR = 1.46, 95% CI 1.01-2.10, P = 8 × 10 ⁻⁴ ).

In addition, the present inventors wanted to know the effects of the deletion type CNVR occurring at the same time in three important positions in predicting the risk of developing SLE. Combining the results of deletion type PCR of RABGAP1L and 10q21.3 with qPCR results at C4, individuals with deletions in all three positions (8.1% of the patient group and 2.3% of the control group) in all three positions The risk of developing SLE was 5.5 times higher compared to individuals> 2n (10.7% of patients in this study and 16.6% of controls) (OR = 5.52, 95% CI 2.14-14.21, P = 3.9 x 10 ^-4 ). According to the number of deletions 1 to 3, OR showed a concentration-dependent increase (r ² = 0.965) (FIG. 7, Table 8).

Table 8

Type	Case (308)	Control (307)
Losses in all 3 loci	25 (8.1%)	7 (2.3%)
Losses in 2 loci	122 (39.6%)	106 (34.5%)
Los in 1 locus	126 (40.9%)	136 (44.3%)
≥2n in all 3 loci	33 (10.7%)	51 (16.6%)
ND	2 (0.6%)	7 (2.3%)

The foregoing description of the present invention is intended for illustration, and it will be understood by those skilled in the art that the present invention may be easily modified in other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, the embodiments described above are to be understood in all respects as illustrative and not restrictive.

The compositions of the present invention make it possible to predict the risk of onset by having a replication number variation at the C4, 1q25.1 and 10q21.3 positions having a synergistic effect on the development of systemic lupus erythematosus and is common in most hospital laboratories. By using the PCR that is performed as a new device or to reduce the error of analysis that may occur due to technical limitations, there is an advantage that can be performed in a non-invasive way to the subject. In other words, the present invention can be used to predict the possibility of developing systemic lupus erythematosus early to prevent the worsening of the condition or to delay the onset.

Claims (10)

1. A composition for predicting the risk of developing Systemic Lupus Erythematosus, the composition comprising a primer for detecting DNA copy number variation at the C4, 1q25.1 and / or 10q21.3 positions on a chromosome of a sample (primer), characterized in that the composition.
2. The method of claim 1,

   The primer for detecting DNA copy number variation at the 1q25.1 position is a pair of primers for genomic quantitative PCR (DNA) including DNA sequences of SEQ ID NOs: 1 and 2, Composition.
3. The method of claim 1,

   The primer for detecting DNA copy number variation at position 10q21.3 is a pair of primers for genomic quantitative PCR (DNA) including DNA sequences of SEQ ID NOs: 3 and 4, Composition.
4. The method of claim 1,

   The primer for detecting DNA copy number variation at position 1q25.1 is a primer for deletion-typing PCR including a DNA sequence selected from the group consisting of SEQ ID NOs: 5 to 8. Characterized in that the composition.
5. The method of claim 1,

   The primer for detecting DNA copy number variation at the 10q21.3 position is a primer for deletion-typing PCR including a DNA sequence selected from the group consisting of SEQ ID NOs: 9 to 12. Characterized in that the composition.
6. A kit for predicting the risk of developing Systemic Lupus Erythematosus, wherein the kit is a primer for detecting DNA copy number variation at 1q25.1 and / or 10q21.3 on a chromosome of a sample. A kit comprising:).
7. The method of claim 6,

   The primer is a kit, characterized in that the primer comprising a DNA sequence selected from the group consisting of SEQ ID NO: 1 to 12.
8. A) performing PCR by adding a primer for detecting DNA copy number variation to the sample DNA sample at the C4, 1q25.1 and / or 10q21.3 positions on the chromosome of the sample; And

   B) determining whether the sample has a DNA copy number variation at the C4, 1q25.1 and / or 10q21.3 positions from the PCR results performed above. How to provide information to predict the risk of developing lupus.
9. The method of claim 8,

   Of step A) Primers for detecting DNA copy number variation at positions 1q25.1 and / or 10q21.3 are genomic quantitative PCRs comprising DNA sequences selected from the group consisting of SEQ ID NOs: 1-4. Characterized in that the primer for PCR).
10. The method of claim 8,

    Of step A) A primer for detecting DNA copy number variation at the 1q25.1 position and / or the 10q21.3 position comprises a deletion typing PCR comprising a DNA sequence selected from the group consisting of SEQ ID NOs: 5-12. a primer for typing PCR).

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