METHOD FOR PREDICTING ORGAN TRANSPLANT REJECTION USING NEXT-GENERATION SEQUENCING

Abstract
A non-invasive method for organ transplant rejection prediction is described, involving measurement of the ratio between donor-specific nucleic acid sequences and recipient-specific nucleic acid sequences in a biological sample obtained from an organ transplant recipient. In specific implementations, the method includes analyzing a biological sample (e.g., blood) obtained from an organ transplant recipient to measure the ratio between donor-derived marker sequences and recipient-derived marker sequences, having three or more markers selected from the markers listed in Tables 1 to 10, and thereby predicting organ transplant rejection based on the ratio. Using next-generation sequencing (NGS) or digital base amplification in the disclosed method enables its application to minute amounts of a sample. The method is rapid, inexpensive, enables rapid data analysis, is applicable irrespective of organ type and race(s) of the donor and recipient, and can detect the probability of sequencing error.
Description
TECHNICAL FIELD

The present invention relates to a method of non-invasively predicting organ transplant rejection by measuring the ratio between donor-specific nucleic acid sequences and recipient-specific nucleic acid sequences in a biological sample obtained from an organ transplant recipient, and more particularly to a method of predicting organ transplant rejection based on the results of measuring the ratio between donor-derived marker sequences and recipient-derived marker sequences by analyzing a biological sample (e.g., blood) obtained from an organ transplant recipient.


BACKGROUND ART

Accurate and timely diagnosis of organ transplant rejection in an organ transplant recipient is essential for survival of the organ transplant recipient. However, methods for diagnosing organ transplant rejection, which are currently used, have many disadvantages. For example, gold standard for diagnosing heart transplant rejection is examining tissue at each time point with surgery for heart biopsy, however, this methods shows many problems including high costs, variability between tissue biopsy physicians, and severe patient discomfort (F. Saraiva et al., Transplant. Proc. Vol. 43, pp. 1908-1912, 2011).


In order to overcome such limitations, non-invasive methods have been used, such as a method for measuring gene expression signals which tend to increase when organ transplant rejection occurs, a method for measuring the level of immune proteins, and the like. However, these methods also pose limitations as they tend to produce high false positive results due to the complex cross-reactivity of various immune responses, and are based on tissue-specific gene expression signals.


In the late 1990s, cell-free donor-derived DNA (cfdDNA) was detected in the urine and blood of organ transplant recipients (J. Zhang et al., Clin. CHem. Vol. 45, pp. 1741-1746, 1999; Y. M. Lo et al., Lancet, Vol. 351, pp. 1329-1330, 1998). Based on this finding, methods for non-invasive diagnosis of organ transplant rejection have been proposed. For example, donor-specific DNA in a female recipient of organ from a male donor can be analyzed using various molecular and chemical assays that detect Y chromosome (T. K. Sigdel et al., Transplantation, Vol. 96, pp. 97-101, 2013). However, the cfdDNA is present in minute quantity, whereas the background DNA is present in abundance. Thus, a highly specific and sensitive method for analyzing this cfdDNA is required.


Next-generation sequencing (NGS) has the capacity of overcoming such limitations and is becoming more and more popular. The next-generation sequencing technique can produce huge amount of data within a short span of time, unlike the existing methods. Thus, this technique is both time and cost effective for individual genome sequencing. The next-generation sequencing technique also provides an unprecedented opportunity to detect disease-causing genes in Mendelian diseases, rare diseases, cancers and the like. Extraordinary progress has been made on genome sequencing platforms and the sequencing data analysis costs have gradually reduced. In the next-generation sequencing technique, DNA is extracted from a sample and mechanically fragmented, followed by size-specific library construction which is used for sequencing. Initial sequencing data are produced while repeating the association and dissociation of four complementary nucleotides with one base unit by using high-throughput sequencing system. Subsequently, bioinformatics-based analysis steps are performed which includes initial data trimming, mapping, genetic mutation identification, and mutation annotation. The analysis leads to the identification of genetic mutations that may affect diseases and various biological phenotypes. Thus, the next-generation sequencing technique contributes to the creation of new added values through the development and commercialization of new therapeutic agents. The next-generation sequencing technique can not only be used for DNA analysis, but also for RNA and methylation analysis. This includes whole-exome sequencing (WES) that captures and sequences only protein-encoding exome regions. This whole-exome sequencing technique is a method that produces sequences of the region encoding a protein having the most direct connection with the development of disease. This technique is widely used, because sequencing of only the exome region is more cost-effective as compared to sequencing of the whole genome. The modification of the whole-exome sequencing technique is popularly known as targeted sequencing. This sequencing technique has the capacity of detecting genetic mutation in the region of interest by using a designed probe. The probe captures only the genetic region of interest, which in turn is used for the detection of genetic mutation in the major oncogene of interest. This technique is relatively easy to perform and can be achieved by significantly lower costs. This sequencing technique is referred to as targeted sequencing.


It is a well-known fact that the use of this next-generation sequencing technique makes it possible to analyze all nucleic acids present in a sample, and thus is highly useful for the analysis of cfdDNA that is present in a desired sample at a very low concentration. For example, Iwijin De Vlaminck et al. performed the analysis of 565 samples obtained from 65 heart transplant patients over time which indicated that the level of cfdDNA in the samples from the recipients were elevated when organ transplant rejection appeared (Iwijin De Vlaminck et al., Sci. Transl. Med. Vol. 6, 241ra77, 2014).


However, this method has limitations; it requires considerable amount of time and cost as it analyzes whole genome data.


Accordingly, the present inventors have made extensive efforts to solve the above-described problems, and as a result, have found that, when markers shown in Table 1 to 10 below are amplified to a size of less than 200 bp and used in next-generation sequencing, cfDNA in a sample can be used intact and, at the same time, analysis sensitivity and accuracy are maintained and analysis time and cost are significantly decreased, thereby completing the present invention.


DISCLOSURE OF INVENTION
Technical Problem

It is an object of the present invention to provide a method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification


Another object of the present invention is to provide a computer system comprising a computer readable medium encoded with a plurality of instructions for controlling a computing system to perform an operation of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by use of next-generation sequencing (NGS) or digital base amplification.


Technical Solution

To achieve the above object, the present invention provides a method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification, the method comprising the steps of:


non-invasively obtaining a biological sample, which contains donor-derived and recipient-derived cell-free nucleic acid molecules, from a recipient who received an organ from a donor;


amplifying three or more marker sequences, selected from marker sequences shown in Tables 1 to 10, in cell-free nucleic acid molecules isolated from the biological sample;


analyzing the amplified sequences by next-generation sequencing (NGS) or digital base amplification;


based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences; and


comparing the ratio with one or more cutoff values.


The present invention also provides a method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification, the method comprising the steps of:


non-invasively obtaining a biological sample, which contains donor-derived and recipient-derived cell-free nucleic acid molecules, from a recipient who received an organ from a donor;


amplifying three or more marker sequences, selected from marker sequences shown in Tables 1 to 10, in cell-free nucleic acid molecules isolated from the biological sample;


analyzing the amplified sequences by next-generation sequencing (NGS) or digital base amplification;


based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences; and


measuring the ratio over time, and predicting whether the recipient will have transplant rejection, graft dysfunction or organ failure when the ratio each of the donor-derived marker sequences increases.


The present invention also provides a computer system comprising a computer readable medium encoded with a plurality of instructions for controlling a computing system to perform an operation of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by use of next-generation sequencing (NGS) or digital base amplification,


wherein the biological sample contains donor-derived and recipient-derived cell-free nucleic acid molecules from a recipient who received an organ from a donor, and


wherein the operation comprises the steps of:


receiving data obtained by analyzing three or more marker sequences, selected from markers shown in Tables 1 to 10, in the cell-free nucleic acid molecules isolated from the biological sample, by use of next-generation sequencing (NGS) or digital base amplification;


based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences;


comparing the ratio with one or more cutoff values; and


based on the comparison, predicting whether or not organ transplant rejection in the recipient will be present.





BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.



FIG. 1 is a conceptual view depicting a method for the prediction of organ transplant rejection by next-generation sequencing (NGS). As shown in FIG. 1, a biological sample (e.g., blood) is collected non-invasively from a patient, and circulating cell-free DNA is isolated from the biological sample. A selected marker set in the sample is amplified by multiplexed PCR and analyzed by short read length next generation sequencing to count the ratio between marker alleles, thereby predicting organ transplant rejection.



FIG. 2 illustrates that when a single marker is amplified using a designed primer and analyzed, NGS can be very quickly performed because a target SNP site is located immediately following the primer.



FIGS. 3A-3C show the results obtained by mixing DNAs to artificially make organ transplantation conditions for 2023 markers selected from markers shown in Table 1 to 10, and measuring the percentages of donor-derived SNP markers in a transplant recipient.



FIGS. 4A-4B show the results of measuring each SNP marker in a sample comprising artificially mixed DNAs.





ADVANTAGEOUS EFFECTS

The method of prediction of organ transplant rejection by next-generation sequencing (NGS) or digital base amplification according to the present invention is applicable even for minute amount of sample. This method is rapid, inexpensive, enables rapid data analysis, and is applicable irrespective of the types of organs and races in the world, Also it can detect the probability of the sequencing error. Thus, the method of the present invention is vital for non-invasive prediction of organ transplant rejection.


BEST MODE FOR CARRYING OUT THE INVENTION

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention pertains. Generally, the nomenclature used herein and the experiment methods, which will be described below, are those well-known and commonly employed in the art.


As used herein, the term “next-generation sequencing (NGS)” means a technique in which the whole genome is fragmented and the fragments are sequenced in a high-throughput manner. The term includes the technologies of Agilent, Illumina, Roche and Life Technologies. In a broad sense, the term includes third-generation sequencing technologies such as Pacificbio, Nanopore Technology and the like, and also the fourth-generation sequencing technologies.


As used herein, the term “organ transplant rejection” includes both acute and chronic transplant rejections. “Acute transplant rejection (AR)” occurs when the donor's organ is considered exogenous by the recipient's immune system. “Acute transplant rejection” implies that the recipient's immune cells penetrate a transplanted organ, resulting in destruction of the transplant organ. Acute transplant rejection occurs very rapidly, and it generally occurs within weeks after organ transplantation surgery. Generally, acute transplant rejection can be inhibited or suppressed by immunosuppressants such as rampamycin, cyclosprin A, anti-CD4 monoclonal antibody and the like. “Chronic transplant rejection (CR)” generally occurs within several months or years after organ transplantation. Organ fibrosis that occurs in all kinds of chronic transplant rejection is a common phenomenon that reduces the function of each organ. For example, chronic transplant rejection in a transplanted lung occurs leads to fibrotic reaction which destroys the airways leading to pneumonia (bronchiolitis obliterans). Furthermore, when chronic transplant rejection occurs in a transplanted heart, it will result in fibrotic atherosclerosis. Similarly, the chronic transplant rejection in a transplanted kidney leads to obstructive nephropathy, nephrosclerosis, tubulointerstitial nephropathy or the like. Chronic transplant rejection also results in ischemic insult, denervation of a transplanted organ, hyperlipidemia and hypertension symptoms associated with immunosuppressants.


As used herein, the term “biological sample” refers to any sample that is obtained from a recipient and contains one or more nucleic acid molecule(s) of interest.


The term “nucleic acid” or “polynucleotide” refers to a deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) and a polymer thereof in either single- or double-stranded form. Unless specifically limited, the term encompasses nucleic acids containing known analogs of natural nucleotides that have similar binding properties as the reference nucleic acid and are metabolized in a manner similar to naturally occurring nucleotides. Unless otherwise indicated, a particular nucleic acid sequence also implicitly encompasses conservatively modified variants thereof (e.g., degenerate codon substitutions), alleles, orthologs, SNPs, and complementary sequences as well as the sequence explicitly indicated. Specifically, degenerate codon substitutions may be achieved by generating sequences in which the third position of one or more selected (or all) codons is substituted with mixed-base and/or deoxyinosine residues (Batzer et al., Nucleic Acid Res. 19:5081 (1991); Ohtsuka et al., J. Biol. Chem. 260:2605-2608 (1985); and Rossolini et al, Mol. Cell. Probes 8:91-98 (1994)). The term nucleic acid is used interchangeably with gene, cDNA, mRNA, small noncoding RNA, micro RNA (miRNA), Piwi-interacting RNA, and short hairpin RNA (shRNA) encoded by a gene or locus.


As used herein, the term “single nucleotide polymorphism (SNP)” refers to a single nucleotide difference between a plurality of individuals within a single species. For example, when an rs7988514 marker present in chromosome 13 of a transplant donor is C/G and the marker in a transplant recipient is T/A, the method of the present invention can be used to analyze the ratio of the donor-derived marker in the blood of the recipient to thereby predict organ transplant rejection.


The term “cutoff value” as used herein means a numerical value whose value is used to arbitrate between two or more states (e.g. normal state and organ transplant rejection state) of classification for a biological sample. For example, if the ratio of a donor-derived marker in the blood of a recipient is greater than the cutoff value, the recipient is classified as being in the organ transplant rejection state; or if the ratio of the donor-derived marker in the blood of the recipient is less than the cutoff value, the recipient is classified as being in the normal state.


In the present invention, it was found that when a biological sample collected from a recipient is analyzed by short read length next-generation sequencing or digital base amplification by using at least three markers selected from the list of markers shown in Tables 1 to 10 (FIG. 1), organ transplant rejection in the biological sample can be quickly predicted with high accuracy.


Therefore, in one aspect, the present invention is directed to a method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification, the method comprising the steps of:


non-invasively obtaining a biological sample, which contains donor-derived and recipient-derived cell-free nucleic acid molecules, from a recipient who received an organ from a donor;


amplifying three or more marker sequences, selected from marker sequences shown in Tables 1 to 10, in cell-free nucleic acid molecules isolated from the biological sample;


analyzing the amplified sequences by next-generation sequencing (NGS) or digital base amplification;


based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences; and


comparing the ratio with one or more cutoff values.


In the present invention, the marker sequences listed in Tables 1 to 10 can be used as single nucleotide polymorphism (SNP) markers which are bi-allelic, are in agreement with the a Hardy-Weinberg distribution and have a minor allele frequency of 0.4 or greater.


In the present invention, the marker numbers (rs numbers) listed in Tables 1 to 10 may have reference SNP numbers that can be searched in dbSNP database (http://www.ncbi.nlm.nih.gov/snp) of NCBI.









TABLE 1







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs1000160
rs1483303
rs2296122
rs3773445
rs6565831
rs899968
rs9978408


rs1000501
rs1491658
rs2296348
rs377685
rs6565969
rs904654
rs9979609


rs1002460
rs1495816
rs2297256
rs378108
rs6565990
rs906629
rs9980589


rs1003092
rs1495965
rs2297291
rs3786203
rs6566067
rs912441
rs9980734


rs10035179
rs1498553
rs2298437
rs3786355
rs6566186
rs912697
rs9980852


rs10048391
rs1501230
rs2298583
rs3787732
rs6566286
rs914163
rs9980934


rs10048862
rs1501233
rs2318993
rs3788190
rs6566554
rs914231
rs9981016


rs10049125
rs1501871
rs2320747
rs3788200
rs6566669
rs914232
rs9982310


rs10057967
rs1506008
rs232374
rs378872
rs6566675
rs914532
rs9982473


rs1006757
rs1508494
rs232381
rs3795494
rs6566862
rs915800
rs9983057


rs10069510
rs1511151
rs2328975
rs379605
rs6567221
rs915876
rs9983351


rs1007300
rs1512473
rs2329327
rs3802981
rs6579927
rs918823
rs9983568


rs10074004
rs1518036
rs2330396
rs3803196
rs659897
rs924895
rs9984531


rs10075717
rs1519126
rs2330572
rs3805015
rs660207
rs926130
rs9985011


rs10078065
rs1526589
rs2332023
rs3806
rs660236
rs928299
rs9985019


rs10083274
rs1530330
rs2332026
rs3809346
rs660622
rs9285110
rs9985057


rs10085762
rs153119
rs2332240
rs3810590
rs660811
rs9285254
rs999104


rs1009823
rs153283
rs233616
rs3817
rs661100
rs9285297


rs10098835
rs1532846
rs233621
rs3819177
rs661293
rs9292170


rs1010392
rs1533434
rs2337483
rs3826616
rs662792
rs9300377


rs1010559
rs1535904
rs234787
rs3844038
rs6650458
rs9300518


rs1013059
rs1536780
rs235310
rs384901
rs6650723
rs9300569


rs10140137
rs1536807
rs235329
rs3850193
rs665479
rs9300647


rs1014209
rs1542578
rs236043
rs3853682
rs6662560
rs9300921


rs1014604
rs1545310
rs2362839
rs385501
rs6678950
rs9301149


rs1015820
rs1549060
rs2366188
rs3856791
rs6680365
rs9301441


rs10158288
rs1553108
rs2388919
rs3864997
rs671441
rs9301695


rs10164030
rs1553295
rs2390878
rs3865418
rs673220
rs930189


rs1018676
rs1554936
rs2390998
rs3865419
rs674929
rs9303869


rs10210
rs1556817
rs239340
rs3866900
rs6762432
rs9303900


rs10222177
rs1560669
rs2395891
rs386838
rs6769917
rs9304336
















TABLE 2







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs1058396
rs1682914
rs2571764
rs4268850
rs703505
rs946228
rs10915584


rs10742709
rs1690551
rs2575177
rs428424
rs7062
rs946231
rs10935501


rs10744938
rs169332
rs2576036
rs4284535
rs706466
rs949741
rs1757889


rs1075906
rs16943649
rs2576038
rs4284740
rs7067226
rs949931
rs17591231


rs1077550
rs16950864
rs2581732
rs429133
rs7067297
rs950408
rs277665


rs10780042
rs16951141
rs2585481
rs430043
rs7099777
rs9506275
rs2779134


rs10781417
rs16951664
rs2585495
rs4306614
rs7139787
rs9506919
rs445593


rs10790400
rs16978368
rs2586776
rs431864
rs7139997
rs9507577
rs4456612


rs1079139
rs16980558
rs2586778
rs4319623
rs7140005
rs9507631
rs7234111


rs1079174
rs16980586
rs2586779
rs432294
rs714831
rs950772
rs7234383


rs10799636
rs16980588
rs2587428
rs4329028
rs716117
rs9508080
rs9521192


rs10840837
rs17041964
rs25876
rs4346468
rs716510
rs9508327
rs952134


rs10851201
rs17069898
rs2591518
rs4346469
rs7186326
rs9508716
rs10903035


rs10853392
rs17070149
rs2628125
rs4349043
rs7206898
rs9509249
rs10915311


rs10853603
rs17071467
rs2641114
rs4349054
rs721247
rs9509441
rs1754514


rs10854400
rs17080696
rs2641962
rs435081
rs7226953
rs9509516
rs17550441


rs10856953
rs17084208
rs2687899
rs4372773
rs7226979
rs9510334
rs2776341


rs10858469
rs170962
rs269286
rs4375553
rs7227268
rs9510340
rs2776344


rs10866988
rs17184424
rs2699323
rs4380323
rs7228099
rs9510597
rs4452046


rs10869149
rs1720839
rs271374
rs438064
rs7228812
rs9510775
rs4454841


rs10869157
rs17232531
rs271397
rs4383238
rs7229278
rs9512046
rs7233802


rs10870724
rs17248234
rs2729429
rs4384683
rs7229644
rs9512063
rs7233985


rs10870932
rs1725235
rs2736084
rs4389803
rs7229967
rs9514560
rs9520400


rs10871180
rs17307670
rs273696
rs439146
rs722998
rs9514663
rs9521146


rs10871550
rs17326281
rs273701
rs4398676
rs7230288
rs9515124


rs10871620
rs1734848
rs2747740
rs4402665
rs7230661
rs9515621


rs10871641
rs17351137
rs275948
rs4402842
rs7230860
rs9515774


rs10871815
rs17363863
rs2762171
rs4407150
rs7231029
rs9516644


rs10875612
rs174047
rs2764618
rs4409964
rs7231046
rs9516904


rs10880836
rs1748124
rs2765327
rs4428160
rs7231112
rs9518743


rs10889256
rs17513940
rs2774494
rs4430618
rs7231366
rs9518903


rs10889523
rs17518254
rs2775138
rs4440160
rs7232672
rs9518972


rs10899035
rs17533
rs2775537
rs444435
rs7233515
rs9520132
















TABLE 3







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs10937406
rs17591266
rs2780746
rs446716
rs7234990
rs9521472
rs11151454


rs10937408
rs17686332
rs2782462
rs4468699
rs7235005
rs9521488
rs11151514


rs10942130
rs17711702
rs2783084
rs448247
rs7235160
rs9521801
rs1790428


rs10955093
rs1772587
rs2786712
rs448503
rs7235654
rs9521832
rs1790584


rs10955174
rs17740268
rs2793734
rs4495668
rs7235891
rs9521853
rs2825610


rs10955420
rs1774918
rs2793736
rs4497518
rs7235930
rs9522262
rs2825688


rs10972552
rs17754863
rs2794243
rs4508511
rs7235989
rs9523648
rs466448


rs1102617
rs17765723
rs2794247
rs4510132
rs7236090
rs9524400
rs467140


rs1105513
rs17781378
rs2803220
rs451826
rs7236427
rs9525095
rs7277441


rs1105856
rs1778797
rs2803348
rs4520729
rs7236653
rs9525149
rs7277926


rs11069237
rs17794801
rs2807441
rs4522508
rs7237517
rs9525158
rs9532436


rs11071215
rs1779843
rs2821796
rs4525375
rs7237577
rs9525300
rs9533146


rs11080646
rs17800754
rs2822618
rs4539677
rs7237747
rs9525641
rs11151426


rs11081004
rs17804894
rs2822648
rs4544336
rs7237774
rs9525643
rs11151452


rs11081037
rs1783099
rs2822661
rs455508
rs7239234
rs9526222
rs1788648


rs11081555
rs1783305
rs2822809
rs455921
rs723940
rs9526312
rs1788658


rs11082705
rs1783395
rs2822965
rs4573787
rs7240004
rs9526400
rs2825583


rs11083008
rs1783404
rs2822973
rs4576968
rs7240257
rs9526792
rs2825608


rs11083386
rs17836226
rs2822975
rs458029
rs7240294
rs9527084
rs4661514


rs1108522
rs1785739
rs2823145
rs4583369
rs7240363
rs9527138
rs466277


rs11088040
rs1785745
rs2823152
rs4588087
rs7240404
rs9527905
rs7276176


rs11088302
rs1786388
rs2823169
rs4588273
rs7240429
rs9528696
rs7277076


rs11088405
rs1786427
rs2823795
rs4611350
rs7241051
rs9528931
rs9531615


rs11088861
rs1786648
rs2823809
rs4613170
rs7241461
rs9529287
rs9532420


rs11096435
rs1787013
rs2823983
rs4617713
rs7241510
rs9529809


rs11096453
rs1787186
rs2824133
rs461853
rs7241718
rs9529814


rs1111937
rs1787292
rs2824238
rs4628
rs7242966
rs9530505


rs11135235
rs1787301
rs2824376
rs4638449
rs7243620
rs9530604


rs1114342
rs1787337
rs2824762
rs4650520
rs7244347
rs9530721


rs11148802
rs1787435
rs2825516
rs4653036
rs7245332
rs9530981


rs11150946
rs1787557
rs2825560
rs465353
rs725040
rs953109


rs11151009
rs1787577
rs2825576
rs465446
rs7260507
rs9531243


rs11151180
rs1788002
rs2825578
rs4661295
rs7275842
rs9531587
















TABLE 4







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs11151657
rs1790649
rs2825824
rs4677496
rs7278004
rs9533177
rs11662474


rs11151684
rs1790875
rs2826117
rs4685212
rs7278137
rs9533397
rs11662612


rs11151698
rs1792668
rs2826259
rs4686407
rs7278676
rs9533738
rs1890306


rs11151892
rs1792674
rs2826390
rs4687889
rs7279020
rs9534174
rs1891132


rs11152060
rs1792687
rs2826392
rs468837
rs7279626
rs9534262
rs2828798


rs11152170
rs1806487
rs2826395
rs468849
rs7280367
rs9534330
rs2828800


rs11152242
rs1807783
rs2826396
rs469303
rs7280538
rs9534515
rs4799055


rs11152264
rs1808693
rs2826399
rs469353
rs7280591
rs9534596
rs4799198


rs11164166
rs1810129
rs2826506
rs470490
rs7280941
rs9534638
rs732569


rs11167694
rs1817141
rs2826718
rs4747351
rs7281206
rs9535880
rs7326426


rs11208377
rs1819894
rs2826721
rs4750494
rs7281674
rs9536346
rs9545554


rs1125807
rs1826318
rs2826737
rs4757240
rs728174
rs9536415
rs9545559


rs1143914
rs1829651
rs2826803
rs4761518
rs7281853
rs9538268
rs11661072


rs1145560
rs1830926
rs2826807
rs4770032
rs7282582
rs9538278
rs11661849


rs1146888
rs1832265
rs2826949
rs4770463
rs7282876
rs9539175
rs1888469


rs1152991
rs1833277
rs2826959
rs4770597
rs7283077
rs9539877
rs1888514


rs1153294
rs1833304
rs2827038
rs4770601
rs7283399
rs9539893
rs2828506


rs1153295
rs1833486
rs2827433
rs4770771
rs729809
rs9540071
rs2828793


rs1156026
rs1834545
rs2827527
rs4771157
rs7304820
rs9540450
rs4798412


rs115750
rs1834547
rs2827528
rs4771638
rs7310809
rs9540451
rs4798479


rs11595762
rs1851043
rs2827530
rs4771695
rs7317338
rs9540627
rs7325068


rs11617291
rs1854100
rs2827874
rs4771833
rs7317341
rs9540642
rs7325529


rs11617562
rs1855259
rs2827965
rs4771904
rs7317430
rs9541479
rs9545224


rs11617606
rs1864469
rs2827987
rs4772278
rs7319926
rs9541813
rs9545244


rs11618168
rs1866337
rs2828001
rs4772857
rs7319976
rs9542105


rs11619265
rs1866986
rs2828023
rs4772937
rs7320145
rs9542137


rs11619462
rs1870592
rs2828055
rs4773212
rs7321115
rs9542383


rs11620473
rs1874864
rs2828061
rs4773395
rs7321584
rs9542852


rs11659206
rs1874921
rs2828089
rs4773402
rs7322458
rs9542951


rs11659463
rs1876583
rs2828151
rs4773838
rs7322868
rs9542969


rs11659969
rs188446
rs2828155
rs4784207
rs7323182
rs9543171


rs11660213
rs1886969
rs2828263
rs4784376
rs7323558
rs9544749


rs11660737
rs1887718
rs2828500
rs4796869
rs7324970
rs9544845
















TABLE 5







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs11664190
rs1891948
rs2828802
rs4799910
rs7326820
rs9545852
rs12184876


rs11664478
rs189204
rs2829066
rs4800786
rs7326944
rs9545853
rs12185460


rs11664727
rs1892681
rs2829115
rs4800967
rs7327180
rs9545861
rs1970678


rs11665106
rs1893455
rs2829214
rs4800970
rs7327256
rs9545903
rs1972415


rs11665385
rs1893654
rs2829432
rs4800973
rs7327729
rs9546633
rs2833935


rs11701849
rs1893657
rs2829445
rs4816597
rs7329520
rs9546677
rs2834208


rs11701901
rs1893673
rs2829614
rs4816610
rs7330025
rs9547087
rs4886217


rs11702340
rs1895076
rs2829674
rs4816681
rs7331003
rs9547646
rs4890312


rs1176270
rs1898165
rs2829887
rs4817097
rs7331794
rs9548869
rs9561936


rs1183856
rs1904177
rs2830048
rs4817371
rs7332180
rs9548880
rs9561953


rs11839815
rs1908593
rs2830194
rs4817609
rs7333280
rs9548930
rs1217618


rs11872146
rs1910660
rs2830424
rs4817685
rs7333503
rs9549172
rs1218307


rs11872403
rs191482
rs2830437
rs4817890
rs7333648
rs9549293
rs195700


rs11872509
rs1920083
rs2830604
rs4817891
rs733398
rs9551135
rs1970668


rs11872828
rs1923732
rs2830643
rs4818015
rs7334111
rs9551233
rs2833846


rs11873161
rs1923771
rs2830811
rs4818108
rs7334546
rs9551406
rs2833916


rs11876001
rs1923886
rs2830841
rs4818144
rs7334805
rs9552733
rs4885878


rs11876772
rs1924417
rs2830856
rs4818160
rs7335163
rs9552874
rs4885880


rs11877050
rs1925857
rs2831057
rs4818179
rs7335426
rs9553022
rs735862


rs11877617
rs1926264
rs2831350
rs4818561
rs7335836
rs9553390
rs736081


rs11910048
rs1926614
rs2831378
rs4819090
rs7335944
rs9554579
rs9561532


rs11910807
rs1926616
rs2831699
rs4819128
rs7336089
rs9554641
rs9561935


rs11910832
rs1927014
rs2831702
rs4819130
rs733610
rs9555119


rs11919425
rs1927807
rs2831706
rs4819201
rs7336348
rs9555266


rs11939712
rs1927830
rs2831755
rs4835587
rs7336658
rs9555581


rs11948061
rs1930586
rs2832155
rs483712
rs7337326
rs9555714


rs11959584
rs1932917
rs2832236
rs4841972
rs7337382
rs9556425


rs11960564
rs1933187
rs2832916
rs4845953
rs7337528
rs9560166


rs12018498
rs1937443
rs2833117
rs486285
rs7337915
rs9560339


rs12020398
rs1942399
rs2833123
rs487812
rs7338544
rs9560797


rs12037545
rs1942531
rs2833153
rs4884402
rs7339162
rs9560800


rs12136961
rs1942803
rs2833523
rs4884905
rs7339250
rs9560807


rs12149
rs1949593
rs2833636
rs4884906
rs734747
rs9561254
















TABLE 6







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs12185828
rs1972598
rs2834295
rs4890333
rs742276
rs9562045
rs12584118


rs12287199
rs1972917
rs2834297
rs4890698
rs743446
rs9562457
rs12584427


rs1231048
rs1979613
rs2834337
rs4890876
rs7441242
rs9562501
rs2027667


rs12326252
rs1980080
rs2834339
rs4891097
rs747781
rs9562637
rs2031446


rs12327010
rs1980942
rs2834694
rs4891098
rs748607
rs9563028
rs2836404


rs1236411
rs1980950
rs2834709
rs4891160
rs7504436
rs9563770
rs2836488


rs12420519
rs1981084
rs2834712
rs4891325
rs7504842
rs9564167
rs4941643


rs12427782
rs1981390
rs2834756
rs4891576
rs7509953
rs9564355
rs4941715


rs12428610
rs1982837
rs2834782
rs4891734
rs7544781
rs9564535
rs7735484


rs12428798
rs1986899
rs2834796
rs4907464
rs754777
rs9564577
rs7799930


rs12454023
rs1988657
rs2834884
rs4907552
rs756040
rs9564626
rs9574824


rs12454180
rs1991753
rs2834908
rs4910359
rs760345
rs9564747
rs9574897


rs12454706
rs1993355
rs2835035
rs4911045
rs7614
rs9564791
rs12583161


rs12455429
rs199667
rs2835043
rs4920104
rs7616178
rs9565398
rs12583202


rs12456484
rs1997353
rs2835103
rs4920520
rs7618973
rs9565654
rs2026744


rs12457067
rs1998956
rs2835104
rs492338
rs762173
rs9565661
rs2027605


rs12457191
rs2000416
rs2835121
rs492346
rs762227
rs9565968
rs2836338


rs12458066
rs2000490
rs2835169
rs492597
rs7624098
rs9566836
rs2836358


rs12458637
rs2000833
rs2835293
rs4927236
rs7624366
rs9567448
rs4941183


rs12458713
rs2004000
rs2835349
rs492781
rs762438
rs9567700
rs4941388


rs12482086
rs2005187
rs2835567
rs4939701
rs7626725
rs9568497
rs7728402


rs12482146
rs2006089
rs2835695
rs4939702
rs7633784
rs9568684
rs7733022


rs12482714
rs200680
rs2835704
rs4939735
rs7634577
rs9568713
rs9573927


rs12482786
rs2009879
rs2835722
rs4940009
rs7639145
rs9569550
rs9574740


rs12483578
rs2012898
rs2835723
rs4940235
rs7639867
rs9570226


rs12490235
rs2012982
rs2835735
rs4940498
rs7651989
rs9570290


rs12513430
rs2013669
rs2835790
rs4940563
rs765557
rs9570447


rs12514412
rs2014509
rs2835802
rs4940615
rs7661729
rs9571811


rs1253809
rs2014678
rs2835823
rs4940791
rs7702862
rs9571821


rs1253811
rs2018093
rs2835955
rs4940955
rs7711972
rs9572020


rs12561781
rs2019006
rs2835965
rs4940957
rs7716283
rs9572196


rs12565445
rs2025951
rs2835971
rs4940960
rs7717101
rs9572308


rs125810
rs2026263
rs2835975
rs4941085
rs7721965
rs9573824
















TABLE 7







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs12585235
rs2031546
rs2836656
rs4941939
rs7807853
rs9574898
rs12960453


rs12586094
rs2032313
rs2836661
rs4942060
rs7822979
rs9574900
rs12961253


rs12604515
rs203332
rs2836706
rs4942169
rs7831906
rs9575364
rs2104632


rs12604519
rs2037920
rs2836837
rs4942242
rs7856187
rs9575369
rs2111299


rs12605543
rs2037921
rs2836840
rs4942416
rs786018
rs9575372
rs2837751


rs12605917
rs2039056
rs2836842
rs4942486
rs7914609
rs9579214
rs2837801


rs12605932
rs2039281
rs2836943
rs4942642
rs794185
rs9581121
rs525776


rs12606001
rs2039622
rs2836956
rs4942769
rs7967526
rs9583190
rs526057


rs12626853
rs2043428
rs2836958
rs4942830
rs797517
rs9583537
rs7997078


rs12626876
rs2044800
rs2836975
rs4942931
rs7981995
rs9583996
rs7997881


rs12627315
rs2046845
rs2836980
rs4943119
rs7982563
rs958687
rs977660


rs12627610
rs2051121
rs2836985
rs4943694
rs7982833
rs9592665
rs9783885


rs12627745
rs2051189
rs2837129
rs4943696
rs7983168
rs9593922
rs12959212


rs12630707
rs2051382
rs2837302
rs4949256
rs7983218
rs9597134
rs12960451


rs12637291
rs2057529
rs2837381
rs495737
rs7984225
rs9600079
rs2099255


rs12659620
rs2058276
rs2837393
rs496627
rs7984261
rs9601268
rs2100750


rs12724092
rs2059757
rs2837395
rs4986223
rs7984523
rs9601567
rs2837738


rs1274749
rs2060816
rs2837399
rs4989135
rs7984835
rs9604328
rs2837747


rs12756081
rs2063222
rs2837403
rs499416
rs7986681
rs9617452
rs522505


rs1276034
rs2065280
rs2837411
rs4998815
rs7988095
rs962267
rs524566


rs12763013
rs2065288
rs2837490
rs500910
rs7988209
rs9634593
rs7995700


rs128365
rs2067741
rs2837494
rs501062
rs7989235
rs9636883
rs7996275


rs1284419
rs2068051
rs2837512
rs5023173
rs798963
rs9636977
rs970705


rs12858753
rs2070535
rs2837529
rs508151
rs7989798
rs9637300
rs975336


rs12859190
rs2071754
rs2837553
rs509215
rs7990298
rs9646522


rs12864209
rs2073425
rs2837592
rs509741
rs7992072
rs9646629


rs12876644
rs2076237
rs2837637
rs512699
rs7992416
rs9647139


rs12925084
rs208932
rs2837655
rs513775
rs7993087
rs9647235


rs12936110
rs2090036
rs2837701
rs514556
rs7993804
rs9647276


rs12953319
rs2094186
rs2837705
rs514669
rs7994585
rs9652107


rs12955787
rs2096507
rs2837712
rs515391
rs7994654
rs9675925


rs12957246
rs2096905
rs2837717
rs515551
rs7995283
rs9676063


rs12957256
rs2097096
rs2837736
rs515920
rs7995306
rs968906
















TABLE 8







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs12961631
rs2113462
rs2837865
rs532095
rs7997893
rs9785659
rs1326056


rs12961741
rs2115980
rs2838004
rs532625
rs7997966
rs9785716
rs13275667


rs12961750
rs2116378
rs2838081
rs535923
rs7998641
rs9785897
rs2187091


rs12962651
rs211962
rs2838104
rs536419
rs7999126
rs9786101
rs2188584


rs12963212
rs2120204
rs2838125
rs537435
rs7999812
rs9786111
rs2849977


rs12963466
rs212315
rs2838304
rs545723
rs8000390
rs9786121
rs2850125


rs12965753
rs2136681
rs2838361
rs550801
rs8001960
rs9786140
rs608382


rs12966281
rs2137492
rs2838438
rs556046
rs8002541
rs9786194
rs608713


rs12966492
rs214054
rs2838441
rs558700
rs803815
rs9786276
rs8091446


rs12967515
rs214341
rs2838568
rs559372
rs8083067
rs9786291
rs8091825


rs12967616
rs2146442
rs2838724
rs560169
rs8083437
rs9786386
rs9909561


rs12968141
rs2148443
rs2838799
rs561418
rs8083682
rs9786773
rs991045


rs12968648
rs2149436
rs2838806
rs569216
rs8084206
rs9786824
rs1325798


rs12969413
rs2150419
rs2838813
rs575936
rs8084711
rs9786876
rs1325968


rs12969725
rs2151277
rs2838815
rs5761308
rs8084792
rs9786885
rs2183557


rs12971228
rs2154487
rs2838820
rs5764891
rs8085054
rs9788296
rs2186557


rs13046156
rs2154549
rs2838887
rs576808
rs8085056
rs9789153
rs2849697


rs13046342
rs2154550
rs2838890
rs578835
rs8085222
rs9805596
rs2849865


rs1304747
rs2154723
rs2838893
rs581394
rs8086286
rs9805694
rs607127


rs13049234
rs2155797
rs2839287
rs582547
rs8086449
rs9805804
rs6072085


rs13049853
rs2156187
rs2839377
rs582853
rs8086752
rs9813365
rs8091123


rs13050660
rs2156384
rs2839386
rs585632
rs8086807
rs9818400
rs8091380


rs13052088
rs2156650
rs2839392
rs591173
rs8087052
rs982328
rs9891988


rs13087163
rs2160043
rs2839468
rs591498
rs8087127
rs9828270
rs990557


rs13152923
rs2161775
rs2839470
rs593340
rs8087403
rs9835007


rs13159598
rs2166029
rs2839508
rs595106
rs8087551
rs9837159


rs13162651
rs2174524
rs2839520
rs596778
rs8087849
rs9845467


rs13163878
rs2174571
rs2842906
rs599551
rs8088596
rs984659


rs13168731
rs2174896
rs28468602
rs599881
rs8088779
rs985035


rs13178296
rs2178841
rs2848957
rs6014601
rs8088832
rs985198


rs13200025
rs2178848
rs2848958
rs602212
rs8089359
rs9853755


rs1323556
rs2181753
rs2848961
rs6047745
rs8089613
rs9861671


rs1325453
rs2182957
rs2849253
rs607020
rs8090831
rs9869577
















TABLE 9







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs1328368
rs2198683
rs2850542
rs6108022
rs8092218
rs993930
rs1378492


rs1328926
rs220128
rs2852146
rs612573
rs8092926
rs9944568
rs1378800


rs13304168
rs220149
rs2861624
rs6137476
rs8094161
rs9945284
rs2246422


rs13304202
rs220171
rs28649411
rs614290
rs8094280
rs9945648
rs2247021


rs1331948
rs220268
rs287355
rs616669
rs8095071
rs9945969
rs3121808


rs1331951
rs2203754
rs2873580
rs619542
rs8095250
rs9947210
rs3127637


rs1333023
rs2205533
rs2878293
rs625028
rs8095514
rs9947426
rs6492589


rs1333027
rs2206747
rs2878901
rs625090
rs8095747
rs9947829
rs6506138


rs1333072
rs2211681
rs2885243
rs626519
rs8096263
rs9948368
rs8131559


rs1334384
rs2211845
rs2887596
rs627527
rs8096542
rs9948679
rs8132424


rs1335282
rs2211869
rs2892463
rs628221
rs8096605
rs9948733
rs9959180


rs1335787
rs2211938
rs2897977
rs630706
rs8096830
rs9948841
rs9959555


rs1335788
rs2211973
rs2901821
rs6311
rs8097023
rs9948974
rs1370079


rs13380936
rs2212624
rs2921452
rs632324
rs8097306
rs9949020
rs1377341


rs13381153
rs2212626
rs293105
rs632678
rs8097433
rs9949323
rs2245411


rs13381188
rs2212809
rs2933307
rs632683
rs8097467
rs9949565
rs2246122


rs1340312
rs2212828
rs2941782
rs632986
rs8097792
rs9949574
rs3106603


rs1340333
rs2217442
rs2946523
rs634293
rs8097822
rs9949868
rs3118045


rs1340562
rs2222370
rs2953258
rs634760
rs8098182
rs9949882
rs6492379


rs13433508
rs2222999
rs2953261
rs639862
rs8098925
rs9950906
rs6492586


rs1345492
rs2223079
rs2969931
rs640254
rs8099616
rs9951809
rs8130781


rs1348466
rs2226356
rs2993502
rs641366
rs8099832
rs9951893
rs8131481


rs1349094
rs2226358
rs2997116
rs6426721
rs8127266
rs9952107
rs9958812


rs1349936
rs2226798
rs3011522
rs6439686
rs8127332
rs9952148
rs9958938


rs13503
rs2226859
rs3014944
rs6442180
rs8127569
rs9952357


rs1351407
rs2236483
rs3015419
rs645539
rs8127634
rs9952908


rs13554
rs2236944
rs3019879
rs645699
rs8128478
rs9953136


rs1358368
rs2241585
rs304838
rs6469456
rs8128523
rs9954012


rs1361029
rs2242661
rs306395
rs6483561
rs8128650
rs9954208


rs1361768
rs2242752
rs3091601
rs6490683
rs8129332
rs9954439


rs1364416
rs2242753
rs3096835
rs6490713
rs8129919
rs9955860


rs1365251
rs2243936
rs3101866
rs6490946
rs8130292
rs9957425


rs1369348
rs2244188
rs3106556
rs6491350
rs8130587
rs9957591
















TABLE 10







Markers used in the present invention













Marker number
Marker number
Marker number
Marker number
Marker number
Marker number
Marker number





rs1379823
rs2247221
rs3171532
rs6506332
rs8132865
rs9959597
rs1472406


rs1380332
rs2248218
rs326046
rs6506837
rs8132870
rs9959723
rs1473279


rs1382394
rs2249360
rs328125
rs6507196
rs8133195
rs9960454
rs1474092


rs1385338
rs2250226
rs329027
rs6507440
rs8134612
rs9961499
rs1478526


rs1389561
rs2250494
rs331018
rs6507719
rs8134986
rs9963406
rs2284636


rs1390431
rs2250926
rs331020
rs6507783
rs8181861
rs9963983
rs2287434


rs1412819
rs2251085
rs334458
rs6507967
rs8184900
rs9964749
rs2289152


rs1412822
rs2251210
rs336214
rs6508168
rs825977
rs9964911
rs229441


rs1413021
rs2252046
rs336279
rs6508266
rs844974
rs9964940
rs375484


rs1413158
rs2252776
rs340966
rs6508351
rs844975
rs9965174
rs375886


rs1413435
rs2252828
rs341237
rs6508502
rs844978
rs9965410
rs3760582


rs1415019
rs225383
rs341499
rs651029
rs844986
rs9965900
rs377191


rs1417313
rs225396
rs341506
rs651407
rs844990
rs9966050
rs6562599


rs1417907
rs2254368
rs347128
rs6516794
rs844999
rs9966798
rs6562888


rs1421182
rs2255059
rs349714
rs6516819
rs845015
rs9967142
rs6563329


rs1424406
rs2255332
rs352247
rs6517605
rs845017
rs9967277
rs6565830


rs1430378
rs2256000
rs35379414
rs6518100
rs845018
rs9967440
rs892430


rs1430381
rs2256417
rs355708
rs6518252
rs845022
rs9967534
rs894050


rs1437650
rs2269145
rs367841
rs652539
rs845024
rs996906
rs896036


rs1442134
rs2269161
rs369906
rs6550169
rs845969
rs9974136
rs898484


rs1445728
rs2269173
rs372883
rs6550215
rs857569
rs997416
rs9976426


rs1446770
rs2274328
rs373037
rs655209
rs858044
rs9974225
rs9977055


rs1447740
rs2274403
rs3736867
rs6555064
rs863075
rs9974317
rs9977610


rs1451940
rs2274463
rs3736972
rs6561105
rs864674
rs9974879
rs9977815


rs1452670
rs2274774
rs3737893
rs6561326
rs875625
rs9974970


rs1455514
rs2276218
rs3742188
rs6561605
rs876165
rs9975304


rs1455872
rs2277798
rs3744877
rs6561644
rs877786
rs9975452


rs1464236
rs2279962
rs3744998
rs6561709
rs877856
rs9975831


rs1465509
rs2281767
rs3746897
rs6561727
rs878971
rs997587


rs1467756
rs2284214
rs3746924
rs6561900
rs883868
rs9976123


rs1471171
rs2284514
rs3751405
rs6561924
rs888789
rs9976168









In the present invention, the biological sample may be blood, plasma, serum, urine, or saliva.


In the present invention, the marker sequences may have genotypes as shown in Table 11 below for each SNP site, and thus any SNP combination (red) cannot provide information useful for prediction of organ transplant rejection, and any SNP combinations (yellow and green) can provide useful information which is entirely determined according to a random distribution of donor-specific and recipient-specific SNP genes.









TABLE 11







Donor/recipient SNP combinations predicted by


analysis using selected marker set










recipient












Donor
X:X
X:Y
Y:Y















X:X
N
MI
HI
HI
Highly Informative


X:Y
HI
NI
HI
MI
Moderately Informative


Y:Y
HI
MI
NI
NI
No Informative









For example, when an SNP marker combination having a minor allele frequency of 45% is used in the analysis, the ratio between each of donor-specific alleles and each of recipient-specific alleles, calculated by the Hardy-Weinberg equilibrium, is represented in Table 12 below.









TABLE 12







Allele ratios predicted by analysis using an SNP marker


combination having a minor allele frequency of 45%











X = 55%
X:X





Y = 45%
(30%)
X:Y (49%)
Y:Y (21%)















X:X (30%)
9.0%
14.7%
6.3%
HIGH
37.6%


X:Y (49%)
14.7%
24.0%
10.3%
MEDIUM
25.0%


Y:Y (21%)
6.3%
10.3%
4.4%
LOW
37.4%









In the present invention, the step of amplifying the marker sequences may further comprise amplifying all of the markers shown in Tables 1 to 10.


In the present invention, the ratio between the marker sequences might imply the ratio between the amount of each donor-derived marker sequence and the amount of each recipient-derived marker sequence, selected from the list of markers shown in Tables 1 to 10.


The NGS platform that is used in the present invention is optimized for analysis of sequence fragments having a size of 100 bp. Essential factors to be taken into consideration while making a choice of the NGS platform includes the read-length that is readable at the same time, basic error rate, analysis speed, and reaction efficiency.


In the present invention, it was shown that when the markers listed in Tables 1 to 10 were amplified in order to optimize the above-described factors, a desired SNP site was within 35 bp from the starting point of sequencing, and the average length of amplified marker sequences were 70 bp (FIG. 2).


Therefore, in the present invention, the amplified marker sequences in the biological sample may be less than 200 bp in length.


The markers that are used in the present invention are bi-allelic SNP sites which are the markers whose positions and expected nucleotide sequences are all known. Thus, when the nucleotide at any position differs from a known nucleotide (for example, A is read in place of the correct nucleotide G/T), it can be counted as an error.


By analyzing 2023 markers as represented in FIGS. 3A-3B, it was inferred that an error rate could be easily calculated.


In the present invention, the ratio between the marker sequences may be calculated along with a sequencing error rate.


In the present invention, the cutoff values may be reference values established from a normal biological sample.


Meanwhile, it was found that organ transplant rejection can be predicted by observing a time-dependent change in the amount of donor-derived DNA in a recipient who received an organ.


In another example of the present invention, biological samples were obtained from a recipient, who received an organ, before and immediately after organ transplantation, and then were obtained at certain time intervals after organ transplantation.


The obtained biological samples were analyzed, and as a result, it was observed that the ratio of donor-derived SNP markers were increased when organ transplant rejection occurred.


Therefore, in another aspect, the present invention is directed to a method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification, the method comprising the steps of:


non-invasively obtaining a biological sample, which contains donor-derived and recipient-derived cell-free nucleic acid molecules, from a recipient who received an organ from a donor;


amplifying three or more marker sequences, selected from marker sequences shown in Tables 1 to 10, in cell-free nucleic acid molecules isolated from the biological sample;


analyzing the amplified sequences by next-generation sequencing (NGS) or digital base amplification;


based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences; and


measuring the ratio over time, and predicting whether the recipient will have transplant rejection, graft dysfunction or organ failure when the ratio each of the donor-derived marker sequences increases.


In the present invention, the biological sample may be blood, plasma, serum, urine, or saliva.


In the present invention, the step of amplifying the marker sequences further comprises amplifying all of the markers listed in Tables 1 to 10.


In the present invention, the ratio between the marker sequences might imply the ratio between the amount of each donor-derived marker sequence and the amount of each recipient-derived marker sequence, selected from the markers shown in Tables 1 to 10.


In the present invention, the ratio between the marker sequences may be calculated along with a sequencing error rate.


In the present invention, the amplified marker sequences in the biological sample might be less than 200 bp in length.


In the present invention, the ratio measurement time may be selected from the group consisting of before organ transplantation, immediately after organ transplantation, and one day, two days, one week, one month, two months, three months, one year, two years, and 10 years after organ transplantation.


The present invention is also directed to a computer system comprising a computer readable medium encoded with a plurality of instructions for controlling a computing system to perform an operation of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by use of next-generation sequencing (NGS) or digital base amplification,


wherein the biological sample contains donor-derived and recipient-derived cell-free nucleic acid molecules from a recipient who received an organ from a donor, and


the operation comprises the steps of:


receiving data obtained by analyzing three or more marker sequences, selected from markers shown in Tables 1 to 10, in the cell-free nucleic acid molecules isolated from the biological sample, by use of next-generation sequencing (NGS) or digital base amplification;


based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences;


comparing the ratio with one or more cutoff values; and


based on the comparison, predicting whether or not organ transplant rejection in the recipient will be present.


EXAMPLES

Hereinafter, the present invention will be described in further detail with reference to examples. It will be obvious to a person having ordinary skill in the art that these examples are for illustrative purposes only and are not to be construed to limit the scope of the present invention. Thus, the substantial scope of the present invention will be defined by the appended claims and equivalents thereof.


Example 1: Prediction of Organ Transplant Rejection in Artificially Generated Organ Transplant Recipients

1.1: Pretreatment for Preparation and Analysis of Artificial DNA Samples from Organ Transplant Recipients


Male DNA (donor) was mixed with female DNA (recipient) such that the percentage of the male DNA in the female DNA would be 0%, 0.625%, 1.25%, 2.5%, 5% or 10%, thereby preparing artificial organ transplant patient genomic DNA samples.


To perform a TruSeq Custom Amplicon (TSCA) assay (Illumina, USA) using 100 ng of each gDNA, Custom Amplicon was prepared. A heat block was adjusted to 95° C., and 5 μl of each of DNA and CAT (Custom Amplicon Oligo Tube) was added to a 1.7-ml tube. As control reagents, 5 μl of each of ACD1 and ACP1 was also prepared. 40 μl of OHS1 (Oligo Hybridization for Sequencing Reagent 1) was added to each tube and mixed well using a pipette, and each tube was maintained at 95° C. for 1 min, and subjected to oligo hybridization at 40° C. for 80 min subsequently. following this, the temperature was lowered and 45 μl of SW1 (stringent wash 1) reagent was added to an FPU (Filter Plate Unit) plate membrane, followed by centrifugation at 2,400×g and 20° C. for 10 min. The sample tube was subjected to hybridization, spun-down, and the sample was transferred to the FPU plate using a pipette, and then centrifuged at 2,400×g and 20° C. for 2 min. This was followed by the washing of the sample twice with 45 μl of SW1 reagent, and addition of 45 μl of UB1 (Universal Buffer 1) reagent. Subsequently, centrifugation was performed under the same conditions to remove unreacted unbound oligo.


For extension-ligation of hybridized oligo, 45 μl of ELM3 (extension-ligation mix 3) was added to the sample covered with a foil and incubated in an incubator at 37° C. for 45 min. After completion of the incubation, the foil was removed, and the sample was centrifuged at 2,400×g for 2 min. Then, 25 μl of 50 mM NaOH was added to the sample which was then pipetted 5 to 6 times using a pipette and incubated at room temperature for 5 minutes. During the incubation, a PMM2/TDP1 (PCR Master Mix 2/TruSeq DNA Polymerase 1) mixture was added to the PCR tube containing P5 and P7 index. After completion of the incubation, 20 μl of DNA diluted in NaOH was added, thereby preparing a total of 50 μl of a PCR amplification sample. The prepared sample was subjected to PCR reaction under the following conditions:


<PCR Conditions>


−95° C., 3 min


−28 cycles


95° C., 30 sec


66° C., 30 sec


72° C., 60 sec


−72° C., 5 min


−Hold at 10° C.


After completion of the PCR cycles, the sample was analyzed using a QIAxcel system for confirmation. The sample was then purified using 60 μl of beads and suspended in 30 μl of resuspension buffer (RS).


1.2: Analysis of Artificial DNA Sample from Organ Transplant Recipient


It was observed that the sample could be sequenced using a sequencing system and the corresponding markers could be counted, making it possible to monitor organ transplant rejection through an algorithm and a pipeline (FIGS. 3A-3C and 4A-4B).


Allele counts corresponding to the SNP markers identified using next-generation sequencing were graphically shown. On the X-axis, reference allele or major allele counts were expressed, and on the Y-axis, alternate allele or minor allele counts were expressed as log 2 values (FIGS. 3A-3C). Particularly, because the selected SNP markers were SNPs located at chromosome 13, 18 and 21, these markers were indicated by blue (●), green (▪) and red (x), respectively (FIGS. 3A-3C).


As represented in Table 13 below, the mixed DNAs may show a total of 9 phenotypes.









TABLE 13







Phenotypes of mixed (organ transplant patient) DNAs












M F
AA
Aa
aa







AA
AAAA
AAAa
AAaa



Aa
AaAA
AaAa
Aaaa



aa
aaAA
aaAa
aaaa










The phenotypes of the artificially prepared DNA may appear as AA, Aa, aA and aa, and thus have the possibility of eight distributions (AAaa and aaAA are regarded as the same phenotype). It could be seen that, as the donor-derived DNA increased, the AaAA and Aaaa distributions increased at a constant rate (FIGS. 3A-3C).


As represented in FIGS. 3A-3C, the distribution of the donor-derived biomarkers changes depending on the degree of mixing of the biomarkers. When this distribution is quantitatively measured and calculated, small amounts of the donor-derived genes present in the recipient's blood can be detected or measured, and when the amount of the donor-derived gene mutation is measured and observed, organ transplant rejection in the recipient can be predicted or observed.


In addition, as represented in Table 14 below, when two DNAs were mixed in different amounts were and were actually measured by next-generation sequencing, the amounts of the mixed DNAs could be accurately measured even when present in minute amounts by quantitatively analyzing biomarkers using next-generation sequencing.









TABLE 14







Experimental Ratio and SNP Counting-Based Ratio of Mixed DNAs














Background (0%)
10%
5%
2.50%
1.25%
0.63%

















Fraction Homo
0.001395983
0.221443
0.123786
0.063688
0.035009
0.015802


Fraction Hetero
0.001495645
0.110112
0.060944
0.032425
0.017551
0.010921


Actual Fraction

22.08%
12.28%
6.43%
3.51%
1.88%









In this context, when bases corresponding to AA and aa of artificially mixed donor-derived DNA are counted, values as listed in Table 14 above can be obtained. Although there is a difference of about 2 folds between the experimental value of mixed DNA and the value measured by analysis, this difference may have appeared because the measured DNA amount is not an absolute amount.


As shown in FIGS. 4A-4B, although markers differ from each other, the use of several markers makes it possible to accurately measure or observe organ transplant rejection.


When the method of the present invention is actually applied to patients, donor-derived DNA can be expressed as a numerical value at varying time points, and organ transplant rejection can be monitored.


Although the present invention has been described in detail with reference to the specific features, it will be apparent to those skilled in the art that this description is only for a preferred embodiment and does not limit the scope of the present invention. Thus, the substantial scope of the present invention will be defined by the appended claims and equivalents thereof.


INDUSTRIAL APPLICABILITY

The method of the present invention is useful for non-invasive prediction and monitoring of organ transplant rejection, and thus it has a high industrial applicability.

Claims
  • 1. A method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification, the method comprising the steps of: obtaining a biological sample non-invasively, which contains donor-derived and recipient-derived cell-free nucleic acid molecules, from a recipient who received an organ from a donor;amplifying three or more marker sequences, selected from marker sequences shown in Tables 1 to 10, in cell-free nucleic acid molecules isolated from the biological sample;analyzing the amplified sequences by next-generation sequencing (NGS) or digital base amplification;based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences; andcomparing the ratio with one or more cutoff values.
  • 2. The method of claim 1, wherein the biological sample is blood, plasma, serum, urine, or saliva.
  • 3. The method of claim 1, wherein the step of amplifying the marker sequences further comprises amplifying all of the markers shown listed in Tables 1 to 10.
  • 4. The method of claim 1, wherein the ratio between the marker sequences is the ratio between the amount of each donor-derived marker sequence and the amount of each recipient-derived marker sequence, selected from the markers shown in Tables 1 to 10.
  • 5. The method of claim 1, wherein the ratio between the marker sequences is calculated along with a sequencing error rate.
  • 6. The method of claim 1, wherein the amplified marker sequences in the biological sample are less than 200 bp in length.
  • 7. The method of claim 1, wherein the cutoff values are reference values established from a normal biological sample.
  • 8. A method of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by next-generation sequencing (NGS) or digital base amplification, the method comprising the steps of: obtaining a biological sample non-invasively, which contains donor-derived and recipient-derived cell-free nucleic acid molecules, from a recipient who received an organ from a donor;amplifying three or more marker sequences, selected from marker sequences shown in Tables 1 to 10, in cell-free nucleic acid molecules isolated from the biological sample;analyzing the amplified sequences by next-generation sequencing (NGS) or digital base amplification;based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences; andmeasuring the ratio over time, and predicting whether the recipient will have transplant rejection, graft dysfunction or organ failure when the ratio each of the donor-derived marker sequences increases.
  • 9. The method of claim 8, wherein the biological sample is blood, plasma, serum, urine, or saliva.
  • 10. The method of claim 8, wherein the step of amplifying the marker sequences further comprises amplifying all of the markers shown in Tables 1 to 10.
  • 11. The method of claim 8, wherein the ratio between the marker sequences is the ratio between the amount of each donor-derived marker sequence and the amount of each recipient-derived marker sequence, selected from the markers shown in Tables 1 to 10.
  • 12. The method of claim 8, wherein the ratio between the marker sequences is calculated along with a sequencing error rate.
  • 13. The method of claim 8, wherein the amplified marker sequences in the biological sample are less than 200 bp in length.
  • 14. The method of claim 8, wherein the ratio measurement time is selected from the group consisting of before organ transplantation, immediately after organ transplantation, and one day, two days, one week, one month, two months, three months, one year, two years, and 10 years after organ transplantation.
  • 15. A computer system comprising a computer readable medium encoded with a plurality of instructions for controlling a computing system to perform an operation of predicting organ transplant rejection in a biological sample, obtained from a recipient who received an organ from a donor, by use of next-generation sequencing (NGS) or digital base amplification, wherein the biological sample contains donor-derived and recipient-derived cell-free nucleic acid molecules from a recipient who received an organ from a donor, andwherein the operation comprises the steps of:receiving data obtained by analyzing three or more marker sequences, selected from markers shown in Tables 1 to 10, in the cell-free nucleic acid molecules isolated from the biological sample, by use of next-generation sequencing (NGS) or digital base amplification;based on the analysis of the sequences, determining the ratio between each of the donor-derived marker sequences and each of the recipient-derived marker sequences;comparing the ratio with one or more cutoff values; andbased on the comparison, predicting whether or not organ transplant rejection in the recipient will be present.
Priority Claims (1)
Number Date Country Kind
10-2015-0052649 Apr 2015 KR national
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a U.S. national phase under the provisions of 35 U.S.C. § 371 of International Patent Application No. PCT/KR2015/005905 filed Jun. 11, 2015, which in turn claims priority of Korean Patent Application No. 10-2015-0052649 filed Apr. 14, 2015. The disclosures of all such applications are hereby incorporated herein by reference in their respective entireties, for all purposes.

PCT Information
Filing Document Filing Date Country Kind
PCT/KR2015/005905 6/11/2015 WO 00