CN114292907A - Biomarkers and diagnostic and therapeutic methods for recurrent implantation failure - Google Patents

Abstract

The present invention relates to methods of luteal phase support therapy for repeated implantation failure, and methods and biomarkers for predicting responsiveness of luteal phase support therapy in patients with repeated implantation failure.

Description

Biomarkers and diagnostic and therapeutic methods for recurrent implantation failure

Technical Field

The invention relates to the technical field of in vitro fertilization-embryo implantation. More particularly, the present invention relates to methods of luteal phase support therapy for recurrent implantation failures, and methods and biomarkers for predicting responsiveness of luteal phase support therapy in patients with recurrent implantation failures.

Background

Recurrent Implantation Failure (RIF) is a specific disease type in the area of assisted reproduction therapy (Bashiri A, Halper KI, Orviet R. Current Implantation Failure-update overview on Biology, diagnosis, treatment and future directions. reproduction Biology and Endocrinology 2018; 16: 121). In general, patients who have undergone more than three consecutive cycles of high quality embryo transfer without acquiring clinical pregnancy are considered to have failed repeated implantation. The incidence of RIF in vitro fertilization-embryo transfer (IVF-ET) is 10-15%. The etiology of RIF is 1/3 related to embryo quality, and 2/3 is related to maternal factors. Current clinical strategies for RIF include: improve embryo quality and endometrial receptivity. Methods of improving endometrial receptivity include hormonal medications (estrogen, progesterone and bromocriptine), adjuvant medications (vitamin D, aspirin, low molecular weight heparin, antimicrobials, and antibiotics), immunotherapy (prednisone, active immunity, passive immunity, and granulocyte colony stimulating factor G-CSF), assisted reproductive therapy (endometrial window phase detection), surgery (hysteroscopy and laparoscopy), traditional chinese medicine, stem cell therapy, and physiological therapy, among others. Although these methods may treat some RIF patients; however, there are still some RIF patients who do not get a solution to the fertility problem.

In vitro fertilization-embryo transfer, corpus luteum support has been proposed for application to fresh and freeze-thaw embryo transfer cycles. It is generally believed that reaching a certain level of luteal mid-luteal serum progesterone (P) is critical to achieving successful implantation. For this reason, two luteal support strategies have been proposed, one conventional luteal support strategy being exogenous supplementation of progestin and estrogen drugs; another luteal support strategy is to potentiate the hormone (progesterone and estrogen) production of the corpus luteum by exogenous LH-active drugs (e.g., LH or HCG). In IVF-EF patients in the fresh embryo transfer period, luteal phase insufficiency of the patients often occurs due to the use of ovulation-promoting drugs and other reasons; for such patients, it has been demonstrated that supplementation with progesterone with luteal support can lead to a clear clinical therapeutic improvement effect. However, the effectiveness of corpus luteum support remains controversial in the art, depending on the particular corpus luteum support drug and regimen used and the patient's condition for a particular application. For HCG, use of luteinizing drugs is made, for example, Ludwig M et al report that supplementation of HCG in addition to conventional progesterone luteinizing does not bring about an effectiveness superior to progesterone alone in the fresh embryo transfer cycle (Ludwig M, FinaS, KatalinicA, StrikD, KowalcekI, SchwartzP, et al.Prospective, random to evaluation of the success rates using G, genetic promoter a combination of bone for viral phase support. acta terricia et al Scandinavica 2001; 80: 574-82.). Similarly, Linden et al report that Meta analysis shows that progesterone in combination with HCG for a fresh embryo transfer cycle is luteally supported with no statistical difference in live productivity and sustained pregnancy rates compared to progesterone alone (Luteal phase support for assisted pregnancy cycles (Review), Cochrane Database of Systematic Reviews 2015, Issue 7.art. 009154.). Currently, for RIF patients, studies are still limited for different luteal support regimens and their suitability in different RIF patient populations; moreover, with the introduction of an accurate personalized corpus luteum support treatment concept, it is necessary to determine biomarkers indicative of treatment regimen responsiveness and to select a targeted treatment regimen based on the biomarkers for a particular corpus luteum treatment regimen.

In recent years, functional enrichment studies based on microarray chips and differentially expressed genes have been proposed for the study of the etiology and therapeutic responsiveness of complex diseases. In the field of RIF disease, it has also been proposed to stage endometrial capacity conditions in RIF patients using functional enrichment studies, as well as to perform analyses of implantation window-associated genetic profiles. For example, Ercan Bastu et al (functional Marker Pathways in the endometeric thin mass blood recovery expression failure, reproduction Sciences,2018, p1-12), compared RIF patients with fertile individuals, identified and proposed 9 KEGG biological Pathways that may be associated with endometrial receptivity of RIF patients in the natural cycle, including cyclic nodal rhythm, pathway in cancer, protelomer, completion and aggregation cassettes, circulation cycle, adherens junction, immunological system and injection, cell cycle, and Renin-system. Similarly, Koot et al (An end gene expression signature, transcription expression failure after IVF, Sci. Rep.2016; 6:19411) also propose the use of differentially expressed gene microarrays and functional enrichment analysis in RIF prediction. However, these differentially expressed gene-based assays typically require taking endometrial biopsies from the patient at specific time points of the cycle; and the analysis result also changes along with the change of the biopsy time, so that the method has certain application limitation.

In view of the foregoing, there are limitations to current diagnostic and therapeutic methods for RIF for unknown reasons. There is a need in the art for new methods of differentiating RIF patients and improving RIF therapy and diagnosis.

Summary of The Invention

By clinical studies exploring the correlation of Luteinizing Hormone (LH) levels with RIF patients, the present inventors propose a new luteal support method suitable for patients with RIF disease with specific low LH serum levels. Further, the inventors performed whole genome exon sequencing and functional enrichment analysis of variant genes; and on the basis of the correlation between the luteal phase support treatment responsiveness and the genetic variation on a specific biological pathway.

In conjunction with the above intensive studies at molecular, genetic and clinical levels, the present inventors have also proposed a new RIF disease subtype, "subclinical hypopituitarism" recurrent implantation failure, whose patients with RIF have diagnostic specific biological pathway genetic alterations and/or optionally, diagnostic low LH levels of luteal phase D2 and exhibit good clinical responsiveness to luteal support regimens for HCG supplementation after transplantation.

Accordingly, in one aspect, the invention provides a method of diagnosing or classifying a RIF patient comprising detecting a variation in a characteristic biological pathway-associated gene, and/or LH serum level at day D2 of luteal phase, in the patient. In a further aspect, the present invention provides a method of luteal phase support comprising the step of further supplementing a luteal generation-associated active drug, in particular HCG, based on the administration of progesterone and/or estrogen for luteal phase support in RIF patients having a variation in characteristic biological pathway-associated genes and/or a D2 day LH serum level below a certain threshold, preferably, the method improves the clinical pregnancy rate and/or the live birth rate of the patients. In yet another aspect, the invention provides a method of predicting responsiveness of a RIF patient to luteal support therapy supplemented with HCG, comprising detecting a variation in a characteristic biological pathway-associated gene of the patient, and/or LH serum levels at D2 day of luteal phase.

In still another aspect, the invention also provides biomarkers and combinations thereof that can be used to diagnose or classify RIF patients, and biomarkers and combinations thereof that can be used to predict responsiveness of RIF patients to treatment with HCG supplemented luteal support methods. In yet another aspect, the invention also provides the use of said biomarkers and combinations thereof in the preparation of kits for use in the diagnostic or prognostic methods of the invention.

Brief Description of Drawings

FIG. 1 shows the measured cyclic changes of luteinizing hormone LH in some patients with IVF-ET due to tubal problems.

Figure 2 shows the measured cyclic changes in luteinizing hormone LH in some patients with repeat implantation failure.

Figure 3 shows the quality control of the sequencing data for all samples of example 3.

Figure 4 shows the results of case group pathway analysis enrichment. The pathways ECM-receptor interaction and extracellular matrix organization enriched in the case group are descriptions of one pathway in two different databases, KEGG and GO-BP.

Figure 5 shows the control pathway analysis enrichment results.

FIG. 6 shows the 27 genes associated with the major KEGG/GO enrichment pathway (ECM-receptor interaction/extracellular matrix organization; PI3K-Akt signaling pathway, and Focal attachment) in the case group.

FIG. 7 shows the statistics of the enrichment of treatment response-associated genes in case and control samples based on pathway enrichment analysis.

Figure 8 shows the major pathway-associated gene enrichment statistics for 10 case group samples.

FIG. 9 shows the characteristic biological pathways and pathway-associated genes of the present invention.

Figure 10 shows a list of characteristic pathway SNPs identified in HCG luteal phase support therapy-responsive patients.

Detailed Description

Before the present invention is described in detail, it is to be understood that this invention is not limited to the particular methodology and experimental conditions set forth herein as such may vary. In addition, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.

Definition of

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. For the purposes of the present invention, the following terms are defined below.

The term "about," when used in conjunction with a numerical value, is intended to encompass a numerical value within a range having a lower limit that is 5% less than the stated numerical value and an upper limit that is 5% greater than the stated numerical value.

The term "and/or" when used to connect two or more selectable items should be understood to mean either one of the selectable items or any two or more of the selectable items.

As used herein, the term "comprising" or "comprises" is intended to mean including the stated elements, integers or steps, but not excluding any other elements, integers or steps. When the term "comprising" or "includes" is used herein, unless otherwise specified, it also encompasses the presence of stated elements, integers or steps.

In this context, D0 refers to the endometrial inversion day, the ovulation day in the case of the natural cycle and the ovulation-promoting cycle; in the case of the artificial cycle, the day of administration of the endometrial transforming drug. Correspondingly, D2 refers to day 2 after D0. Ovulation monitoring in the present invention may be carried out by any known method, for example, the development of follicles may be detected by transvaginal ultrasound every day from day 8 to 10 of menstruation until disappearance of the dominant follicles is found, which is regarded as ovulation.

Herein, clinical pregnancy is defined as: an abdominal B-ultrasonic examination was performed 30 to 35 days after the transplantation, and a gestational sac was observed.

In this context, live birth is defined as: one or more live births were delivered after 20 weeks of gestation.

Pathway-associated genes are defined herein as: annotating genes on at least one of the following biological pathways and/or biological processes according to KEGG and GO:

KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)。

in some embodiments of the methods, compositions, kits and/or uses according to the invention, the pathway-associated gene is selected from: KEGG notes genes under hsa04510, hsa04511, hsa04512, and/or GO _ BP _ DIRECT notes under GO: 0030198.

In some embodiments, the pathway-associated gene is selected from the group consisting of the genes annotated under KEGG pathway hsa04512, e.g., COL1, COL2, COL4, COL6, COL9, LAMA _2, LAMA _5, LAMA, LAMB, LAMC, CHAD, RELN, THBS2, FN, SPP, VTN, TNC, tenascin C, ibf, IBSP, AGRN, HSPG, ITGA, ITGB, itsdgb, ITGB, CD, DAG, COL, SV, CD GP, GP1BA, ITGA, CD GP1, CD GP, hmbb, CD 24.

In some embodiments, the pathway-associated gene is selected from the group consisting of GO _ BP _ DIRECT annotated genes under GO:0030198, e.g., PECAM1, ITGB2, APP, FBN1, CD44, NCAN, SPOCK2, COL16A1, LAMB2, B4GALT1, DAG1, SLC39A8, JAM2, ITGA8, IBSP, COL28A1, ADAMTS18, ITGB 18, LAMB 18, ITGA 18, ITGA 18, ITGA 18, PDGFB 36GAE, ITGB 18, MP3672, NF 18, PTK 18, LAMC 18, TGFBI, SOX 18, CCN 18, ITGAM, VIEGFL, NPT, TNF, ITGB 18, BSEGFG 18, EGGFX 18, TFF 18, FBC 72, TFGA 18, TFC 72, TFC 18, CADG 18, GAC 72, CADG 18, GAMMA 18, CADG 18, GAMMA 18, 36IDGAMDCGN 18, 36IDGAMDGAMDGAMDGAMDGAMDGAMMA 18, 36IDGAMDGAMDGAMDGAMDGAMDGAMDGAMDGAMDGAMDGAMDGAMMA, 18, 36FAN, 18, 36FAN, 18, 36FAN, 18, ICAM2, COL4A6, ITGA11, COL6A3, COL6a2, COL6a1, ITGAX, ITGAL, MMP24, SPP1, COL19a1, ICAM4, ITGB1, ADAM12, COL18a1, COL15a1, COL24A, ADAM19, LAMA4, KDR, ITGA2, COL17a1, COL5a1, BCAN, COL5A3, LAMC3, DNAJB6, SPINK5, DDR2, COL9A3, ERCC 2.

In some embodiments, the pathway-associated gene is selected from the group consisting of the genes annotated under KEGG pathway hsa04510, e.g., COL1, COL2, COL4, COL6, COL9, LAMA _2, LAMA _5, LAMA, LAMB, LAMB, LAMC, LAMC, LAMC, CHAD, RELN, THBS, THBS2, FN, SPP, VTN, TN, VWF, IBSP, ITGA, ITGA, ITGA2, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGAV, ITGB, ITGB, ITGB, ITGB, ITGB, ITGB, ITGB, PDGFA, PDGFB, PDGFC _ D, MYFB, EGF, VEGFA, VEGFB, PGF, VEGFC _ D, HGF, PDGFRAF, PDGFRA, PDGFR, IGF1, IGF, TLRP, PRRG _ CKRB, PRC _ PSC _ 12, PRC _ PSC, PRC _ PSK, PRC _ PSC, PSK, PRC _ 12, PRC _ PSC, PSC _ 12, PSC _ PSC, PSC _ 12, PSC _ PSC, PSC _ C, PSC _ 12, PSC _ PSC, PSC _ C _ 12, PSC _ 12, PSC _ PSC, PSC _ C, PSC _ 12, PSC _ C, PSC _ PSC, PSC _ 12, PSC _ PSC, PSC _ 12, PSC _ 12, PSC _ 12, PSC _ P, PSC _ 12, PSC _ PSC, PSC _ PSC, PSC _ 12, PSC _ P, PSC _ 12, PSC _ PSC, PSC _ PSC, PSC _ C, PSC _ C _ P, PSC _ P, PTEN, VAV, RAC1, RAC2, RAC3, PAK1, PAK2, PAK3, PAK4, PAK5, PAK6, CDC42, BCAR1, CRK, DOCK1, rapgof 1, RAP1A, RAP1B, JNK, JUN, BRAF, CAV1, CAV2, CAV3, FYN, SHC1, SHC2, SHC3, SHC4, GRB2, SOS, HRAS, RAF1, MAP2K1, ERK, ELK1, CCND1, CCND2, CCND3, BIRC2_3, XIAP, BAD, BCL2.

In some embodiments, the pathway-related gene is selected from the group consisting of the genes annotated under KEGG pathway hsa04511, e.g., EGF, TGFA, EREG, AREG, FGF, NGFA, NGFB, BDNF, NTF, INS, IGF, PDGFA, PDGFB, PDGFC _ D, CSF, KITLG, FLT3LG, VEGFA, VEGFB, PGF, VEGFC _ D, HGF, ANGPT, EFNA, EGFR, ERBB, FGFR, NGFR, IGF1, PDGFRA, PDGFRB, CSF1, KIT, FLT, KDR, MET, TEK, EPHA, GRB, SOS, HRAS, KRAS, epof, CSF, ralk 2, ralk, MAP2, slr, slb, slr, slb, slr, slb, slr, sl, LAMA, LAMB, LAMB, LAMB, LAMB, LAMC, LAMC, LAMC, CHAD, RELN, THBS, THBS2, FN, SPP, VTN, TN, VWF, IBSP, ITGA, ITGA, ITGA2, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGB, ITGB, ITGB, ITGB, ITGB, ITGB, PTK, PIK 3_ B _ D, PIK3R _2_3, F2, CHRM, CHRM, LPAR, LPAR, HSP, LPAR, LPAR, GNB, GNB, GNB, GNG, GNG, GNG, GNG, GNG, GNG, GNG, PGG, PIK3, PIK3, PTK 6, PTCR, PCK, PSK, PCK, PTCR 2, PCK 6, PCK 2, PCK 2, PCK 2, PCK 2, PCK 2, PCK 2, PCK, CCNE, FOXO3, RBL2, TNFSF6, BCL2L11, ywlab _ Q _ Z, ywrae, ywnag _ H, BAD, BCL2L1, BCL2, CASP9, CREB1, ATF2, ATF4, CREB3(CREB3L4), CREB5, ATF6B, MCL1, RXRA, NR4a1, IKBKG, IKBKA, IKBKB, RELA, NFKB1, MYB, MDM2, TP 53.

In some embodiments of the methods, compositions, kits and/or uses according to the invention, the pathway-associated gene is selected from one or a combination of the genes of KEGG pathways hsa04510, hsa04511, hsa04512, and/or GO BP DIRECT biological process GO:0030198 listed in fig. 9.

As used herein, the term "marker" or "biomarker" refers to a biomolecule, or a portion/fragment of a biomolecule, the alteration and/or presence of which has an association with a particular biological condition or state. In some embodiments, the markers of the invention are gene markers, encompassing all biologically relevant forms of the identified genes and their encoded proteins, including, for example, genetic variations (e.g., missense mutations), gene expression levels, and mutant forms and/or protein expression levels and/or activities of the respective encoded proteins. In some embodiments, a gene marker is a sequence variation in an exon of a gene, and/or a corresponding amino acid change in a protein resulting from the variation. In some embodiments, the detection of the biomarker molecule may be the detection of a fragment or portion thereof. The portion may be, for example, a fragment of a gene or a fragment of a protein, e.g., a gene fragment comprising 5-30 nucleotides, or a protein fragment comprising 5-30 amino acids.

The term "marker panel" or "biomarker panel", as used herein, refers to a combination, such as a composition, array or collection, comprising one or more biomarkers (e.g., genetic markers). In some embodiments, the number of biomarkers used in the marker panel depends on the detection sensitivity and specificity for a particular biomarker magnitude combination. Sensitivity and specificity demonstrate the ability to correctly classify subjects based on the magnitude of the biomarkers detected in the biological sample. In some embodiments, in the methods of the invention, e.g., diagnostic and prognostic methods, the sensitivity of the diagnostic or prognostic methods reaches 70%, 80% or more, e.g., 90% or more, for the biomarker panel used. In some embodiments, the specificity of the diagnostic or prognostic methods reaches 70%, 80% or more, e.g., 90% or more, for the biomarker panel used in the methods of the invention, e.g., diagnostic and prognostic methods.

The term "genetic variation" refers to a change, including but not limited to a deletion, insertion, and/or substitution, in the sequence encoding the gene relative to the canonical sequence of the gene. The term "canonical sequence" refers herein to the sequence that occurs most frequently in humans, for example, the sequence of the human reference genome (GRCh37/hg 19). Preferably, the genetic variation results in an allele frequency in the human population of no greater than 0.03, such as no greater than 0.02, no greater than 0.01, such as an allele frequency of no greater than 0.01 according to the GnomAD database.

The term "missense mutation" refers to a genetic sequence variation that can result in an amino acid sequence change or a functional RNA base sequence change of a polypeptide product. In some preferred embodiments, the genetic variation of the invention comprises a missense mutation, preferably the missense mutation does not result in complete inactivation of the protein encoded by the gene, but affects the biological activity of the protein encoded by the gene. In one embodiment, the missense mutation is a deleterious missense mutation. In this context, a deleterious missense mutation is a mutation that affects a structural and/or functional change in the product encoded by a gene (e.g., a polypeptide product); however, the mutation does not result in complete inactivation of the protein. In one embodiment, the deleterious missense mutation is one predicted by SIFT and/or Polyphen-2 software.

The term "array" or "microarray" refers to an ordered arrangement of hybridizable array elements, preferably polynucleotide probes (e.g., oligonucleotides), on a substrate. The substrate may be a solid substrate such as a glass slide or a semi-solid substrate such as a nitrocellulose membrane.

The term "diagnosis" is used herein to refer to the identification or classification of a molecular or pathological state, disease or condition. For example, "diagnosis" may refer to the classification of a particular subtype of RIF, for example by histopathological criteria (e.g., D2 serum LH levels) and/or by molecular characteristics (e.g., a particular genetic variation or combination of specific genetic variations, expression of a protein encoded by the gene, or pattern of variant gene enrichment).

The term "aiding diagnosis" is used herein to refer to a method of aiding in making a clinical decision regarding the presence or nature or responsiveness of a particular type of symptom or condition of RIF or treatment responsiveness. In some embodiments, the invention also provides, for example, methods of aiding in the diagnosis of a RIF subtype or methods of aiding in the diagnosis of treatment responsiveness of a RIF patient, which can include measuring genetic variation of a particular gene or combination of genes, or an enrichment pattern of a particular genetic variation, in a biological sample from an individual.

The term "detecting" in relation to a biomarker, as used herein, encompasses any manner of detection, including direct and indirect detection.

The term "predicting therapeutic responsiveness" is used herein to refer to the likelihood that a patient will respond favorably or adversely to a drug or group of drugs. In one embodiment, the prediction relates to the extent of said response. In one embodiment, the prediction involves: whether and/or likely that a patient will obtain an improvement in clinical outcome, e.g., clinical pregnancy rate, live birth rate, etc., following treatment, e.g., treatment with a particular therapeutic agent.

As used herein, "reference sample", "control sample" refers to a sample obtained from a source known or believed to not have a disease or condition to be identified with the methods or compositions of the invention. For example, a "reference" may be a population consisting of a majority of individuals blindly selected from patients who have failed repeated implantation without luteal support treatment supplemented with HCG and/or without detection of luteal phase LH levels. Alternatively, a "reference" may be a subject that has not been diagnosed as RIF, or may be a subject of RIF due to embryo mass, or may be an IVF-ET subject with organic lesions such as fallopian tube problems.

As used herein, the term "sample" refers to a composition obtained or suspected of comprising a cellular entity and/or other molecular entity (in the context of the present invention, in particular a nucleic acid to be detected, such as a whole exon nucleic acid sequence, or a biomarker nucleic acid to be detected, or a fragment thereof) to be characterized and/or identified, e.g., characterized and/or identified based on physical, biochemical, chemical and/or physiological characteristics, from a subject of interest.

The term "luteinizing activity-related drug", as used herein, refers to a drug having luteinizing biotin-like action, such as LH, HCG, including recombinantly produced or isolated and purified forms, such as recombinant LH, urogenic HCG and recombinant HCG.

The term "progestin drug" as used herein refers to progestins useful in fertility-related treatments, including natural or synthetic progestins. Conventional progestin drugs include, for example, but are not limited to, intramuscular progestins, such as pregnenolone 17 α -hydroxycaproate; vaginal progestins such as progesterone sustained release gels and micronized progesterone capsules; progesterone, such as dydrogesterone, is administered orally.

The term "estrogenic drug" as used herein refers to estrogenic drugs that may be used in fertility-related therapies, including, but not limited to, estradiol valerate and micronized estradiol, which may be administered orally, vaginally, and transdermally.

Various aspects of the invention are described in further detail below.

The present invention is based, at least in part, on the definition of a unique new disease subtype of recurrent abortion failure (RIF), also referred to herein as the subclinical hypopituitarism RIF subtype. This disease subtype is characterized by: variation of characteristic biological pathway-associated genes, and/or LH serum levels at D2 days of luteal phase. The invention also provides biomarkers associated with the diagnosis and classification of the subtype, and methods of neoxanthin support suitable for improvement in the clinical outcome of embryo transfer for the subtype, and methods and biomarkers for predicting patient responsiveness to the luteal phase support therapy.

I. The disease subtypes and characteristic biological pathway related genetic variations thereof of the present invention

Combining gene level and clinical level studies, the present inventors propose a new disease subtype of recurrent implantation failure-subclinical recurrent implantation failure with hypopituitarism. This disease subtype has characteristic biological pathway-associated genetic variation and exhibits favorable clinical pregnancy responsiveness to HCG-supplemented luteal phase support therapy, and preferably, also has one or more, preferably all, of the following characteristics:

(1) there is no clear reason for repeated implantation failure;

(2) no apparent organic pituitary damage;

(3) mild hypopituitarism symptoms;

(4) the serum LH level at D2 days of luteal phase is less than or equal to 5 IU/L.

Thus, in one aspect, the present invention provides methods and compositions that can characterize (including, but not limited to, diagnose and/or classify) subclinical hypopituitarism recurrent implantation failures, and/or predict a patient's responsiveness to luteal phase support therapy supplemented with HCG, by screening biological samples from subjects for variations in characteristic biological pathway-associated genes as biomarkers.

Variant gene screening

Variant gene screening of the present invention includes detection of nucleotide variations on the genome and/or exome of a subject. Such genetic variations include, but are not limited to, polymorphisms, splice variants, mutations, and the like. A variety of variant gene screening techniques are known in the art, including, but not limited to, whole genome sequencing, target region sequencing, whole exome sequencing, SNP array hybridization, and the like. In addition, it is known in the art that variant genes can also be screened by detecting a change (e.g., a decrease) in biological activity/function of the product (e.g., protein) encoded by the gene. All of these techniques may be applied to the present invention. Also, as will be appreciated by those skilled in the art, the present invention is not limited to a particular variation screening technique.

In some embodiments of the invention, the protein coding sequences in the genome of the subject are preferably analyzed by Whole Exome Sequencing (WES). Using this technique, disease-associated genetic abnormalities located predominantly in exon regions can be probed. WES will produce high throughput results. There are a variety of technical means in the art that can be applied to the analysis of sequencing data to allow the detection of nucleotide variations and nucleotide polymorphisms. The data obtained by these methods can be combined and further applied to, for example, diagnosis and classification of disease subtypes.

Both of the two major second generation sequencing (NGS) methods available today can be used in the present invention to perform WES, i.e., DNA amplification based sequencing (e.g., available from Illumina, Ion Torrent) and single molecule real-time sequencing (available from Pacific Biosciences, Oxford Nanopore). Tissue samples for sequencing may be freshly cryopreserved, formaldehyde-fixed and paraffin-embedded, or liquid-based samples (e.g., blood samples). Kits for isolating nucleic acid from each of these samples are commercially available. Exome can be captured by array-based or magnetic bead-based means. To achieve sufficient sequencing coverage depth, the target region may also be captured appropriately. After WES sequencing data is obtained, data processing is typically performed to control data quality, pruning out low quality reads. Thereafter, reads can be mapped to selected reference genomes, genetic variations identified and annotated. In one embodiment, genetic variations, including, but not limited to, frameshift, stop-gain, and stop-loss mutations and missense mutations, are identified by WES techniques. In a preferred embodiment, missense mutations that result in amino acid changes are identified in the compositions and methods of the invention. Tools that can be used to identify single nucleotide variations in the WES data include, but are not limited to, varScan2, mutec, Strelka, Platypus, FreeBayes, SomaticSniper. Any of these methods and combinations thereof are suitable for use in the genetic variation detection of the present invention.

Identification of deleterious missense mutations

The present inventors found that, in the RIF disease subtypes of the present invention, in line with their subclinical manifestations, the genetic variations detected in the analysis of variant gene function enrichment in cases and controls were mainly missense mutations that did not result in gene inactivation but affected protein biological activity, i.e., deleterious missense mutations.

Thus, in some preferred embodiments of the invention, in the compositions and methods of the invention, deleterious missense mutations in pathway-associated genes are detected as biomarkers. Deleterious missense mutations can be identified by a variety of software known in the art, such as SIFT and PolyPhen-2 software.

Functional annotation of variant genes

Herein, after screening for variant genes in a subject, in some embodiments, functional annotations, including KEGG biological pathways and GO biological process annotations, may be performed on the detected variant genes in the subject using the KEGG and GO databases, optionally further performing a functional enrichment analysis on the detected variant genes, and comparing to a reference sample.

KEGG (Kyoto Encyclopedia of Genes and genomes) notes

KEGG is a database for the analysis of gene function systems that links genomic information to more ordered biological functional information. The KEGG database includes three databases, a GENE database, a PATHWAY database and a LIGAND database. The GENES database stores genome information, is a collection of gene catalogues, covers completely sequenced genomes and partial sequenced genomes, and has real-time updated gene function annotations. The PATHWAY database stores more ordered information on biological functions including graphical representations of cellular biological processes such as metabolism, membrane trafficking, signaling, cell cycle, etc. KEGG also provides a list of ortholog groups as a complement to the PATHWAY database, providing information about conserved sub-PATHWAYs (PATHWAY motifs) that are often encoded by multiple genes coupled at locations on the chromosome that are useful for prediction of gene function. The third database of KEGG is LIGAND, which provides information about compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for genome map browsing, two genome map comparison, and manipulation of expression profiles, and provides computational tools for sequence comparison, pattern comparison, and path computation. The KEGG database is available at http:// www.genome.jp/KEGG/to the public.

In some embodiments of methods and compositions according to the invention, RIF patients having a RIF disease subtype of the invention and/or exhibiting therapeutic responsiveness to supplementation with HCG corpus luteum support exhibit one or more genetic variations in the extracellular matrix (ECM) -receptor interaction KEGG pathway. The ECM-receptor interaction KEGG pathway is described under entry hsa 04512.

In some embodiments, therefore, in the compositions and methods, e.g., diagnostic and prognostic methods, the detected gene markers comprise 1 or more genes, e.g., 1,2,3,4,5,6,7,8,9,10,15,20,25,30,35,40,45,50,55,60, or 65 or more genes, annotated on the ECM-receptor interaction KEGG pathway according to KEGG. In some embodiments, the gene may be selected from: genes listed in the list of complementary ortholog cohorts of KEGG database entries hsa0451, such as genes COL1, COL2, COL4, COL6, COL9, LAMA _2, LAMA _5, LAMA, LAMB, LAMC, CHAD, RELN, THBS, FN, SPP, VTN, VWF, IBSP, agnn, HSPG, ITGA2, ITGA, ITGAV, ITGB, CD, SDC, DAG, SV, CD, GP1BA, GP1, GP, DAG, CD, hmr, COL 24. In a preferred embodiment, the biomarker of the invention comprises an EC-receptor interaction pathway gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, and COL6a 6.

In some embodiments of the methods and compositions according to the invention, RIF patients having a RIF disease subtype of the invention and/or exhibiting therapeutic responsiveness to supplementation with HCG corpus luteum support exhibit one or more genetic variations in the KEGG pathway PI3K-Akt signaling pathway. The PI3K-Akt signaling pathway is described under entry hsa 04511.

In some embodiments, therefore, in the compositions and methods, e.g., diagnostic and prognostic methods, the detected gene markers comprise 1 or more genes, e.g., 1,2,3,4,5,6,7,8,9,10,15,20,25,30,35,40,45,50,55,60, or 65 or more genes, annotated under the PI3K-Akt signaling pathway according to KEGG. In some embodiments, the gene may be selected from: genes listed in the group list of complementary orthologs of KEGG database entries hsa04511, such as the genes EGF, TGFA, EREG, AREG, FGF, FGF, FGF, FGF, FGF, FGF, FGF, NGFA, NGFB, BDNF, NTF, NTF, INS, IGF, IGF, PDGFA, PDGFB, PDGFC _ D, CSF, KITLG, FLT3LG, VEGFA, VEGFB, PGF, VEGFC _ D, HGF, ANGPT, ANGPT, ANGPT, EFNA, EGFR, ERBB, ERBB, ERBB, FGFR, FGFR, FGFR, NGFR, IGF1, PDGFRA, PDGFRB, CSF1, KIT, FLT, FLT, KDR, MET, TEK, EPHA, GRB, SOS, HRRKA, KRAS, NRAS, RAF, EPAS 2K, CSF 2, LARG 4, LARG, LAMA, LAMB, LAMB, LAMB, LAMB, LAMC, LAMC, LAMC, CHAD, RELN, THBS, THBS2, FN, SPP, VTN, TN, VWF, IBSP, ITGA, ITGA, ITGA2, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGB, ITGB, ITGB, ITGB, ITGB, ITGB, PTK, PIK 3_ B _ D, PIK3R _2_3, F2, CHRM, CHRM, LPAR, LPAR, HSP, LPAR, LPAR, GNB, GNB, GNB, GNG, GNG, GNG, GNG, GNG, GNG, GNG, PGG, PIK3, PIK3, PTK 6, PTCR, PCK, PSK, PCK, PTCR 2, PCK 6, PCK 2, PCK 2, PCK 2, PCK 2, PCK 2, PCK 2, PCK, CCNE, FOXO3, RBL2, TNFSF6, BCL2L11, ywlab _ Q _ Z, ywrae, ywnag _ H, BAD, BCL2L1, BCL2, CASP9, CREB1, ATF2, ATF4, CREB3(CREB3L4), CREB5, ATF6B, MCL1, RXRA, NR4a1, IKBKG, IKBKA, IKBKB, RELA, NFKB1, MYB, MDM2, TP 53. In a preferred embodiment, the biomarker of the invention comprises a PI3K-Akt signaling pathway gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, and LPAR 6.

In some embodiments of methods and compositions according to the invention, RIF patients having a RIF disease subtype of the invention and/or exhibiting therapeutic responsiveness to supplementation with HCG corpus luteum support exhibit one or more genetic variations on KEGG pathway focus adhision. The FOCAL ADHENSION pathway is described under entry hsa 04510.

In some embodiments, therefore, in the compositions and methods, e.g., diagnostic and prognostic methods, the gene markers detected comprise 1 or more genes, e.g., 1,2,3,4,5,6,7,8,9,10,15,20,25,30,35,40,45,50,55,60, or 65 or more genes, annotated on the FOCAL adhision pathway according to KEGG. In some embodiments, the gene may be selected from: genes listed in the list of the group of complementary orthologues of KEGG database entry hsa0450, such as, for example, genes COL1, COL2, COL4, COL6, COL9, LAMA _2, LAMA _5, LAMA, LAMB, LAMB, LAMB, LAMC, LAMC, LAMC, CHAD, RELN, THBS, THBS2, FN, SPP, VTN, TN, VWF, IBSP, ITGA, ITGA, ITGA2, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGAV, ITGB, ITGB, ITGB, ITGB, ITGB, ITGB, PDGFA, PDGFB, PDGFC, EGF, IGF, VEGFA, VEGFB, VEGFF, VEGFC _ D, LPF, PDGFRA, PDGFRB, IGF1, PDGFRR, TLFB, PDGFB, PDGFC, PPP, PGMYKC, VEGFR, PCKC, PCAK, PPP, PCAK, GAP, LAMB, LAMB, LAMB, LAMC, LAMC, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGA, ITGAV, TPGB, PCFB, PCK 12, PCK 2, PCK, PTEN, VAV, RAC1, RAC2, RAC3, PAK1, PAK2, PAK3, PAK4, PAK5, PAK6, CDC42, BCAR1, CRK, DOCK1, rapgof 1, RAP1A, RAP1B, JNK, JUN, BRAF, CAV1, CAV2, CAV3, FYN, SHC1, SHC2, SHC3, SHC4, GRB2, SOS, HRAS, RAF1, MAP2K1, ERK, ELK1, CCND1, CCND2, CCND3, BIRC2_3, XIAP, BAD, BCL2. In a preferred embodiment, the biomarker of the invention comprises a FOCAL ADHESION pathway gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, SHC4 and MYL 12A.

Gene Ontology

Gene Ontology is abbreviated as GO. GO annotations can be divided into three major classes: GO _ MF Molecular Function (Molecular Function), GO _ BP bioprocess (biological process) and GO _ CC cell component (cellular component). Through these three major classes, GO describes one gene. For example, in one GO annotation, the gene product "cytochrome c" can be described by molecular function (oxidoreductase activity), biological process (oxidative phosphorylation), and molecular composition (mitochondrial matrix).

In this context, the GO functional enrichment analysis may be to count the number or composition of genes or proteins (e.g., mutated genes or proteins encoded thereby) at any and/or combination of the three levels of Molecular Function (Molecular Function), biological process (biological process) and cellular component (cellular component). In addition, a specific GO Term can be further selected, and the number of genes or proteins directly corresponding to the Term is counted.

In some embodiments of methods and compositions according to the invention, RIF patients having a RIF disease subtype of the invention and/or exhibiting therapeutic responsiveness to supplementation with HCG corpus luteum support exhibit one or more genetic variations in the GO BP DIRECT extracellular matrix tissue (extracellular matrix organization) biological process. In the GO database, extracellular matrix tissue biology processes are described under entry GO: 0030198.

Thus, in some embodiments, in the compositions and methods, e.g., diagnostic and prognostic methods, the detected gene markers comprise 1 or more genes, e.g., 1,2,3,4,5,6,7,8,9,10,15,20,25,30,35,40,45,50,55,60, or 65 or more genes, annotated on the extracellular matrix tissue biological process GO:0030198 according to GO _ BP _ DIRECT. In some embodiments, the genes are also annotated on one or more of GO:0005576 (extracellular region), GO:0062023 (collagen-containing extracellular gene), GO:0007155 (Cell adhesion).

In some embodiments, the genetic markers detected comprise a gene having a GO _ BP _ DIRECT extracellular matrix tissue annotation and are selected from, e.g., PECAM1, ITGB2, APP, FBN1, CD44, NCAN, SPOCK2, COL16a1, LAMB2, B4GALT1, DAG1, SLC39a8, ITGB2, ITGA8, IBSP, COL28a1, ACAN, ADAMTS18, ITGB6, LAMB3, ITGA9, ITGA5, PDGFB, itgagne, ITGB5, MPZL3, NF1, PTK 1, lam 1, tgi, SOX 1, CCN1, gam, NPNT, egft 1, TNF, ITGB1, BSG, xf1, fgflg 1, fgflw 72, fgvcfln 1, favg 72, fagg 1, fagg 1, fagg 1, 36, COL13A1, CD47, COL8A1, HSD17B12, SMOC2, ICAM2, COL4A6, ITGA11, COL6A3, COL6A2, COL6A1, ITGAX, ITGAL, MMP24, SPP1, COL19A1, ICAM4, ITGB1, ADAM12, COL18A1, COL15A1, ADAM19, LAMA4, KDR, ITGA2, COL17A1, COL5A1, BCAN, COL5A3, LAMC3, DNAJB6, SPINK5, DDR2, COL9A3, ERCC 2. In a preferred embodiment, the biomarker of the invention comprises a gene with GO _ BP _ DIRECT extracellular matrix tissue annotation selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, and COL9 A3.

In some embodiments, in the compositions and methods, e.g., diagnostic and prognostic methods, of the invention, the gene markers detected comprise a combination of genes from one or more of (a) - (d):

(a) having a KEGG _ PATHWAY: an extracellular matrix-receptor interaction pathway (hsa04512) annotated gene, such as the gene under the hsa04512 classification shown in figure 9;

(b) genes with GO _ BP _ DIRECT extracellular matrix tissue (GO:0030198) annotation, such as the genes shown in FIG. 9 under the GO:0030198 classification;

(c) genes annotated with the KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa04511), such as the genes under the hsa04511 classification shown in FIG. 9;

(d) genes annotated with KEGG _ PATHWAY: Focal addition (hsa04510), such as the genes under the hsa04510 classification shown in FIG. 9.

Preferably, the gene marker detected comprises the N gene from (a) or (b); optionally, further comprising M genes from (c) and/(d). N may be an integer selected from 2 to 300, 2 to 200,2 to 150, 2 to 100, 2 to 50, or 2-40, or 2-30, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5. M may be an integer selected from 2 to 300, 2 to 200,2 to 150, 2 to 100, 2 to 50, or 2-40, or 2-30, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5.

In preferred embodiments, in the compositions and methods of the invention, e.g., diagnostic and prognostic methods, the gene markers detected comprise one or any combination of the following pathway-associated genes: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A. In some embodiments, the gene marker detected comprises a gene marker combination consisting of N pathway-associated genes, wherein N is an integer selected from 2 to 27, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5. In other embodiments, the genetic markers detected comprise LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9A3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A.

The biomarkers of the invention

In a further aspect, the invention provides markers or marker combinations useful for characterizing, classifying, and diagnosing the "subclinical hypopituitarismatic recurrent implantation failure disease subtypes of the present invention, as well as for predicting the responsiveness of a patient with recurrent implantation failure to luteal phase support therapy supplemented with HCG, as well as compositions or products (e.g., microarray chips) comprising reagents for their detection, and their corresponding use in the diagnostic and prognostic methods of the present invention.

Thus, in one aspect, the invention provides an isolated biomarker or marker combination comprising or consisting of one or more pathway-associated genes, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

(a) KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

(b) GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

(c) KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

(d)KEGG_PATHWAY:Focal Adhesion(hsa04510)，

in some embodiments, the isolated biomarker panel comprises N of the pathway-associated gene biomarkers shown in figure 9. In some preferred embodiments, the isolated biomarker panel comprises N markers selected from the group of biomarkers listed in class hsa04512 and GO:0030198 shown in figure 9; optionally, M markers selected from the group of biomarkers listed in classes hsa04511 and hsa04510 as shown in figure 9 are also included. N may be an integer selected from 2 to 300, 2 to 200,2 to 150, 2 to 100, 2 to 50, or 2-40, or 2-30, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5. M may be an integer selected from 2 to 300, 2 to 200,2 to 150, 2 to 100, 2 to 50, or 2-40, or 2-30, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5.

In a preferred embodiment, the biomarker or combination of markers consists of N pathway-associated genes in LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9A3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A. N may be an integer selected from 2 to 27, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5.

In some embodiments, the biomarker combinations of the present invention comprise at least 1 or at least two isolated biomarkers selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a 6.

In some embodiments, the biomarker combinations of the present invention comprise at least 1 or at least two isolated biomarkers selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, and COL9 A3.

In some embodiments, the biomarker combinations of the present invention comprise at least 1 or at least two isolated biomarkers selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR 6.

In some embodiments, the biomarker combinations of the present invention comprise at least 1 or at least two isolated biomarkers selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, SHC4, MYL 12A.

In some embodiments, the biomarker combinations of the present invention may be used to characterize, diagnose, or classify "subclinical hypopituitarism" repeat implantation failure patients.

In some embodiments, the biomarker combinations of the present invention can be used to predict the therapeutic responsiveness of a patient with repeated implant failure to a luteal phase support therapy. In some embodiments, the corpus luteum support treatment comprises: following embryo implantation, luteinizing activity-related drugs, especially LH or LH substitutes, preferably HCG, are used. In some preferred embodiments, the luteinizing activity-related drug is intramuscular HCG, preferably the luteinizing activity-related drug is administered after implantation of the embryo, preferably the drug is used in combination with a drug that modulates estrogen and/or progestin (e.g., a progestin drug and/or an estrogen drug). Preferably, HCG is administered at a dose of 100-.

In some embodiments, in the compositions and methods of the invention, the biomarkers of the invention can be further combined with other markers indicative of the condition of the individual. In some preferred embodiments, the combination is with serum LH levels of luteal phase D2. D2 serum LH levels in a subject can be measured using any method known in the art. In a preferred embodiment, D2 serum LH levels are less than 5IU/L, such as less than 4IU/L,3IU/L,2IU/L, or less than 1IU/L in patients with the disease subtypes of the invention, or in patients with the therapeutic responsiveness of the invention. IU refers to the international unit of LH.

Detection of biomarkers

In the compositions and methods of the invention, e.g., diagnostic and prognostic methods, information for a genetic marker of the invention is detected in a sample from a subject. In some embodiments, the detecting comprises determining and comparing genetic variation in the genetic markers between the subject sample and a reference. In some embodiments, genetic variation is achieved by detecting genetic markers at the nucleic acid level, e.g., sequencing, microarray hybridization, SNP detection, and the like. In other embodiments, genetic variation is achieved by detecting the protein encoded by the gene of the genetic marker at the protein level, e.g., detection of the encoded protein in structure (e.g., amino acid sequence), expression level, and/or function or activity, to indicate whether a genetic variation associated with a disease subtype and/or treatment responsiveness in the subject is present in the gene.

Various methods are known in the art for detecting genetic variations at the nucleic acid and protein levels. These methods are all suitable for use in the present invention. Such methods include, but are not limited to, nucleic acid sequencing, Polymerase Chain Reaction (PCR), mass spectrometry-based analytical methods, antibody-based analytical methods, and combinations of any two or more thereof.

In some embodiments, RNA encoded by a gene of the gene marker is detected. Detection of RNA may be performed by one or a combination of sequencing, microarray, SAGE, blotting, RT-PCR or quantitative PCR, preferably by microarray. In other embodiments, the protein product encoded by the gene of the gene marker is detected. The detection of the protein can be determined by ELISA, mass spectrometry, blotting, or immunochemistry, preferably by ELISA.

The sample for detection of the gene marker of the present invention may be a nucleic acid or a sample containing a nucleic acid according to any of the methods described herein. The nucleic acid may be RNA transcribed from genomic DNA or cDNA generated from RNA. The nucleic acid may be derived from a suitable biological sample of a cell, tissue, body fluid, etc. of the subject. Prior to performing detection of the nucleic acid, in some embodiments, it may include obtaining a copy of the nucleic acid, e.g., a copy resulting from amplification. Amplification may be desirable in certain situations, for example, to facilitate obtaining a desired amount of material for detecting variations. The amplicons can then be subjected to variation detection methods, such as genetic variation detection methods known in the art and described herein, e.g., probe hybridization, and the like.

The sample for detection of the gene marker of the present invention may be a protein/polypeptide/peptide encoded by the gene marker or a sample comprising the protein/polypeptide/peptide according to any of the methods described herein. In some embodiments, prior to detecting the protein/polypeptide/peptide, purification or isolation of the protein/polypeptide/peptide from the sample may be included.

In some embodiments, the detection and/or quantification of one or more biomarkers includes an assay method utilizing a capture reagent. Examples of capture reagents can include, but are not limited to, oligonucleotides, antibodies, antibody fragments, nucleic acid-based protein conjugates, small molecules, and the like. In some embodiments, the capture reagent is an oligonucleotide, polynucleotide, or nucleic acid molecule that hybridizes to a biomarker gene. In some embodiments, the capture reagent is a probe contained in a microarray and the assay method comprises microarray hybridization. In other embodiments, the capture reagent is an antibody and the assay method can be an immunoassay, such as a Western blot, an Enzyme Immunoassay (EIA), an enzyme-linked immunosorbent assay (ELISA), and a Radioimmunoassay (RIA). Solid matrices for capture detection may include, but are not limited to, 96-well plates, nitrocellulose membranes, microbeads, microparticles.

In a preferred embodiment, a microarray is used to detect variations in the genes of the biomarkers of the invention. Microarrays typically use thousands of nucleic acid probes arrayed to hybridize, for example, to cDNA or cRNA samples under high stringency conditions. Probe target hybridization is typically detected and quantified by detecting fluorophore, silver, or chemiluminescent labeled targets, thereby determining the relative abundance of nucleic acid sequences in the target. In a typical microarray, probes are attached to a solid surface by covalent bonds to a chemical substrate (via an epoxy silane, amino silane, lysine, polyacrylamide, or others). The solid surface is, for example, glass, silicon wafer or micro beads. A variety of microarrays are commercially available, including, for example, microarrays manufactured by Affymetrix, Inc.

In another preferred embodiment, the detection method is used to detect the protein encoded by the biomarker of the invention to detect the presence or absence of a protein sequence change indicative of a genetic variation. In one embodiment, the detection method is an ELISA-based method. In one embodiment, the ELISA may be a direct ELISA, an indirect ELISA, a multiplex ELISA, an ELISPOT technique, a sandwich ELISA, a competitive ELISA, or other similar techniques known in the art. Typically, the ELISA is performed using an antibody, but can be performed using any capture reagent that specifically binds to a biomarker of the invention or an expression product thereof.

Many protein biochips can be used in the present invention. These include, for example, but are not limited to, protein chips produced by Packard BioScience Company (Meriden Conn.), Zyomyx (Hayward, Calif.) and Pholos (Lexington, Mass.). Typically, protein chips comprise a substrate having a surface. A capture reagent or adsorbent is attached to the surface of the substrate. The surface often comprises a plurality of addressable locations, each location having a capture agent bound thereto. These capture agents may be biomolecules, such as polypeptides or nucleic acids or small molecules, which capture the biomarkers of the invention in a specific manner.

To facilitate detection, a detectable label can be used in any of the methods described herein for directly or indirectly detecting a biomarker of the invention. A variety of detectable labels may be used. The detectable label can be selected based on the sensitivity desired for detection, the feasibility of conjugation to the capture agent, the detection instrumentation available, and the like. Suitable detectable labels include, but are not limited to, fluorescent dyes, chemiluminescent dyes, enzymes, nanoparticles, biotin, digoxigenin, metals, radioisotopes, and the like.

Biological samples suitable for the present invention include, but are not limited to, blood, serum, and other body fluids or biopsies. Biological samples can be obtained using methods known to those skilled in the art. In some cases, the biological sample is blood, plasma, serum, or Peripheral Blood Mononuclear Cells (PBMCs). By screening such samples, a simple early diagnosis of diseases such as RIF can be achieved. In addition, the progress of treatment can also be readily monitored by testing such samples for variations in the target nucleic acid (or encoded polypeptide).

Upon determining that a subject or tissue or cell sample comprises a variant gene function enrichment pattern disclosed herein, and/or a biomarker or combination of markers indicative of a disease subtype of the invention, administration of an effective amount of a suitable corpus luteum supporting therapeutic agent (including a luteal producing drug) may be contemplated to improve the embryo transfer clinical outcome of the subject, e.g., clinical pregnancy, fetal liveness.

The diagnostic and prognostic methods of the invention

Based on the detection of variation of the characteristic biological pathway-associated genes of the invention, and/or based on the biomarkers of the invention and their detection, the invention also provides methods for diagnosing and classifying disease subtypes of the invention, and methods for predicting treatment responsiveness in patients with recurrent implantation failures.

Accordingly, in one aspect, the invention provides a method for diagnosing or classifying a subject as a subclinical hypopituitarism recurrent implantation failure disease subtype, the method comprising detecting genetic variation information of a subject in a biological sample obtained from the subject, wherein a subject is diagnosed or classified as a subclinical hypopituitarism recurrent implantation failure if the subject exhibits variation in one or more KEGG biological pathways or GO biological processes having one or more pathway-associated genes (preferably at least 2,3, and more preferably at least 4 or 5 genes) in a subclinical hypopituitarism recurrent implantation failure:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)。

in some embodiments, the diagnostic methods of the invention comprise: detecting information from one or more (e.g., 10-30, or 30-100, 150- > 500) pathway-associated genes in a biological sample from a subject, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

wherein, if the information indicates that one or more (preferably two, 3, more preferably at least 4 or 5) of the pathway-associated genes is mutated, the subject is diagnosed or classified as the disease subtype,

preferably, at least one (preferably at least two or 3) of said mutated pathway-associated genes is annotated according to KEGG and GO on a KEGG biological pathway or GO biological process selected from the group consisting of:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

more preferably, the genes are annotated according to KEGG and GO on KEGG _ pathway extracellular matrix-receptor interaction pathway and/or GO _ BP _ DIRECT extracellular matrix tissue, and on KEGG _ pathway PI3K-Akt signaling pathway and Focal addition.

In some preferred embodiments, the diagnostic/classification method comprises: detecting in a biological sample from a subject one or any combination of pathway-associated genes selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A; wherein, when information indicative of a genetic variation in the one or more pathway-associated genes (preferably at least 2 or 3, and more preferably at least 4 or 5 genes) is detected in the biological sample of the subject, the subject is diagnosed or classified as the disease subtype.

In some preferred embodiments, a subject diagnosed with the disease subtype according to the methods of the invention has a variation in at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

In further preferred embodiments, a subject diagnosed with said disease subtype according to the method of the invention shows an enrichment of the variant gene in said KEGG biological pathway or GO biological process compared to a reference, preferably said enrichment shows that the subject has a more pathway-associated gene variation than the reference on said biological pathway or biological process, preferably a more pathway-associated gene variation of at least 2,3 or 4 more than the reference.

In any of the embodiments according to the foregoing diagnostic methods, the subject may have no definite cause of repeat implantation failure and no apparent pituitary organic lesions, but exhibit mild hypopituitarism symptoms.

In any of the embodiments of the diagnostic method according to the preceding description, the diagnostic method further comprises measuring the subject's serum level at luteal phase D2, preferably in the morning. Preferably, patients diagnosed with a disease subtype of the invention also have a daily serum LH level of D2 luteal phase of less than or equal to 5IU/L, more preferably less than 3IU/L,2IU/L, or 1 IU/L.

In another aspect, the invention provides a method for predicting whether a subject with Repeated Implantation Failure (RIF) is suitable for treatment with a luteal support therapy, or for predicting the responsiveness of a subject with Repeated Implantation Failure (RIF) to a luteal support therapy, wherein the luteal support therapy comprises administering a luteal generating activity-related drug, such as LH and/or HCG, preferably HCG,

wherein the method comprises: detecting genetic variation information of a subject in a biological sample obtained from the subject, wherein if a subject exhibits a variation in at least one or more KEGG biological pathways or GO biological processes selected from the group consisting of at least 2,3, and more preferably at least 4 or 5 genes having one or more pathway-associated genes (preferably at least 2,3, and more preferably at least 4 or 5 genes), the subject is indicated as being eligible for, or likely to respond therapeutically to, the corpus luteum supporting therapeutic agent:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)。

in some embodiments of the prediction method of the present invention, the prediction method comprises: detecting information from one or more pathway-associated genes in a biological sample from a subject, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

wherein if the information indicates a variation in one or more (preferably two, 3, more preferably at least 4 or 5) of the pathway-associated genes, the subject is predicted to be eligible for, or likely to respond therapeutically to, the luteal phase-supportive therapeutic agent,

preferably, at least one (preferably at least two or 3) of said mutated pathway-associated genes is annotated according to KEGG and GO on a KEGG biological pathway or GO biological process selected from the group consisting of:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

more preferably, the genes are annotated according to KEGG and GO on KEGG _ pathway extracellular matrix-receptor interaction pathway and/or GO _ BP _ DIRECT extracellular matrix tissue, and on KEGG _ pathway PI3K-Akt signaling pathway and Focal addition.

In some embodiments of the prediction method of the present invention, the prediction method comprises: detecting in a biological sample from a subject one or any combination of pathway-associated genes selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A; wherein, when information is detected in a biological sample of a subject that indicates a genetic variation in the one or more pathway-associated genes (preferably at least 2 or 3, and more preferably at least 4 or 5 genes), then the subject is predicted to be eligible for, or likely to respond therapeutically to, the luteal phase-supporting therapeutic agent.

Preferably, a subject predicted to be eligible to receive the treatment or likely to respond therapeutically to the treatment has a variation in at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

In some embodiments of the prediction method according to the invention, the method comprises: predicting that the subject is suitable for, or likely to respond therapeutically to, the corpus luteum supporting therapeutic agent if the subject exhibits an enrichment of a variant gene in the KEGG biological pathway or GO biological process as compared to a reference, preferably the enrichment is exhibited by the subject having more pathway-associated gene variation, preferably at least 1, at least 2,3, or 4 more pathway-associated gene variation, over the biological pathway or biological process as compared to the reference.

In any embodiment of the method of prediction according to the invention, the subject may be free of a clear cause of repeated implantation failure and no apparent pituitary organic lesions, but exhibit mild hypopituitarism symptoms.

In any embodiment of the prediction method according to the present invention, preferably, the method further comprises detecting the D2 day luteal serum LH level of the subject. Preferably, subjects with therapeutic responsiveness are predicted to have D2 serum LH levels of less than 5IU/L, more preferably less than 3IU/L,2IU/L, or 1IU/L D2 serum LH levels.

In any of the above methods, in some embodiments, the genetic variation is a missense mutation, preferably the variation does not result in gene inactivation but affects the biological activity of a protein encoded by the gene, preferably the mutation has an allele frequency in a normal healthy population

<0.01。

In any of the above methods, in some embodiments, the biological sample is selected from blood, serum, and other bodily fluids or biopsies.

In any of the above methods, in some embodiments, the genetic variation information is measured using a PCR method or a microarray chip.

In any of the above methods, in some embodiments, the genetic variation information is obtained using a sequencing method, preferably an exon sequencing method.

In any of the above methods, in some embodiments, the genetic variation information is obtained by detecting a biological activity of a protein encoded by the gene, preferably the biological activity is a decreased biological activity.

In any of the above methods, in some embodiments, the measuring comprises detecting the mutein encoded by the variant gene using an immunoassay, such as an ELISA assay.

In any of the above methods, in some embodiments, the corpus luteum support treatment comprises: on the basis of the supplementation with a progestin and/or estrogen drug, a luteinization-related active drug, such as LH or HCG, more preferably, HCG, is further supplemented after the date of endometrial transformation, preferably after embryo implantation. Preferably the luteal phase support therapy further comprises adjusting the amount of progestin and/or estrogen drug administered during the luteal phase support therapy based on the level of progestin and/or estrogen in the patient. Preferably, HCG is administered at a dose of 100-800IU or 200-500IU,

more preferably, the patient is given daily intramuscular injections of 500IU HCG starting every other day after transplantation.

In the diagnostic and prognostic methods of the present invention, in other embodiments, machine learning-based classifiers may also be employed to make the diagnosis and prognosis. Machine learning algorithms suitable for use with the present invention include, but are not limited to, linear discriminant analysis, support vector machines, recursive feature elimination, microarray prediction analysis, logistic regression, CART, FlexTree, LART, random forest, and the like. Thus, in some embodiments, the diagnostic and prognostic methods of the present invention comprise the steps of:

-determining in vitro variations in a plurality of target nucleic acids in a sample of a plurality of known sub-clinical hypopituitary repeat implantation failure patients (preferably, said patients having luteal phase D2 serum LH level <5IU/L) to construct a training data set;

-training a classifier, such as a random forest classifier, using a training data set;

-determining a plurality of variations of the nucleic acid of interest from an in vitro sample of the subject, using a trained classifier, to predict, determine or assess the likelihood of the subject being classified as a RIF disease subtype of the invention, or responding to a luteal phase support therapy of the invention.

The classification and prediction may be set as a threshold, i.e. a threshold for determining the probability that a sample belongs to a given class, according to a trained machine learning model. The probability threshold may be at least 50%, or at least 60%, or at least 70%, or at least 80% or higher. Classification or prediction can also be made by comparing a data set obtained from a subject to a reference data set to determine whether there is a statistically significant difference between the two. If there is a significant difference, the subject is classified as belonging to a category other than the reference. If there is no significant difference, the subject is classified as belonging to the same category as the reference.

Through biomarker combination and machine learning, in some embodiments, the diagnostic/classification and prediction methods of the present invention can be provided with high specificity and high sensitivity.

In any of the diagnostic and prognostic methods described above, detecting variation in the plurality of biomarkers may comprise detecting genetic variation in the N biomarkers listed in figure 9. In some embodiments, N may be an integer selected from N from 2 to 50, or from 2 to 40, or from 2 to 30, or from 2 to 25, or from 2 to 20, or from 2 to 15, or from 2 to 10, or from 2 to 5. In some embodiments, N is an integer selected from 3 to 50, or 3-40, or 3-30, or 3-25, or 3-20, or 3-15, or 3-10, or 3-5. In some embodiments, N is an integer selected from 4 to 50, or 4 to 40, or 4 to 30, or 4 to 25, or 4 to 20, or 4 to 15, or 4 to 10, or 4 to 5. In some embodiments, N is an integer selected from 5 to 50, or 5-40, or 5-30, or 5-25, or 5-20, or 5-15, or 5-10. In some embodiments, N is an integer selected from 6 to 50, or 6-40, or 6-30, or 6-25, or 6-20, or 6-15, or 6-10. It will be apparent to those skilled in the art that N may also be selected from similar or larger numerical ranges.

In a preferred embodiment, a plurality of biomarker variants are detected, said biomarker panel consisting of N pathway-associated genes selected from LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9A3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A. N may be an integer selected from 2 to 27, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5.

In any of the diagnostic and prognostic methods described above, preferably the genetic variation in the biomarker is a missense mutation, particularly a deleterious missense mutation that affects protein structure and/or function, such as predicted by SIFT and PolyPhen-2 software. In some embodiments, detection of missense mutations includes detecting nucleotide mutations on a nucleic acid sequence, including, for example, SNPs, SNVs, insertions and/or deletions, and the like. In some embodiments, in any of the diagnostic and prognostic methods described above, detecting a genetic variation in a biomarker comprises detecting 1 or more SNVs (single nucleotide variations) listed in figure 10 of the present invention, e.g., 2 to 50, or 2-40, or 2-30, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5 SNVs. Detection of SNV can be performed by microarray hybridization, sequencing, and the like. The SNV can also be detected by detecting changes in the amino acid sequence of the protein encoded by the SNV. The SNV can also be detected by detecting the activity of a protein encoded by a gene comprising the SNV. In some preferred embodiments, in the compositions and methods of the invention, one or more SNVs selected from the group consisting of: rs375041472, rs2276331, rs117194484, rs749258477, rs201006742, rs532783486, rs533178276, rs140413590, rs745335790, rs200254355, rs187465892, rs770208004, rs768170625, rs769085031, rs759512073, rs113055208, rs145852498, rs147773336, rs779870630, rs200796753, rs529211517, rs201251711, rs140368397, rs 7446427, rs 688285, rs139813458, rs 7519524, rs754641652, rs199896561, and an SNV on LPAR6, such as a C to T mutation on chromosome 13 position 48986219 (the SNV results in an amino acid change: LPAR6: NM _001162498: exon 49 1: R341114A: 341114Q: 114Q). In still other preferred embodiments, in the compositions and methods of the invention, one or more SNVs selected from the group consisting of: rs375041472, rs2276331, rs117194484, rs749258477, rs201006742, rs532783486, rs533178276, rs745335790, rs200254355, rs187465892, rs770208004, rs768170625, rs769085031, rs759512073, rs145852498, rs147773336, rs779870630, rs200796753, rs 529211511517, rs201251711, rs140368397, rs749946427, rs181688285, rs 147811393458, rs754919524, rs 75464141466561, rs199896561, and a C to T mutation at position 48986219 on SNV chromosome 13.

Methods of luteal phase-supporting RIF treatment of the invention

In long-term clinical practice, the inventors found that some RIF patients had significantly low LH serum hormone levels at day 2 of the luteal phase (D2). That is, in these RIF patients, in addition to the generally known abnormalities in estrogen and progestin in the post-ovulatory luteal phase, LH also exhibits abnormalities (in the blood of patients drawn at 8 a.m.). However, clinical examination revealed that these patients had no significant pituitary organic lesions.

By working to develop clinical treatment regimens for such RIF patients, the inventors discovered that: in such patient populations, further supplementation of HCG, based on the use of progestin and estrogen drugs for conventional luteal support, can effectively improve the clinical outcome of the patients, including clinical pregnancy rates and live yields. Further gene level studies have shown that individuals who exhibit therapeutic responsiveness have characteristic genetic variations in biological pathways.

Thus, the present inventors propose a novel method of luteal phase support therapy, which comprises, in patients with characteristic genetic variation of the biological pathway and/or with repeated implantation failure of luteal phase D2 with LH levels of less than 5IU/L, further supplementing with drugs associated with luteal generating activity after embryo transfer, based on administration of progestin and estrogen for luteal phase support therapy.

Thus, in a further aspect, the invention provides a method of providing luteal phase support therapy to a patient with recurrent implantation failure, said method comprising administering to said patient, at the date of endometrial transformation, preferably after implantation of an embryo, an effective amount of a luteal phase activity related drug, such as HCG and/or LH, preferably HCG,

wherein the patient exhibits a variation in at least one or more KEGG biological pathways or GO biological processes having one or more pathway-associated genes (preferably at least 2,3, and more preferably at least 4 or 5 genes) selected from:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)；

preferably, at least one (preferably at least two or 3) of said mutated pathway-associated genes is annotated according to KEGG and GO on a KEGG biological pathway or GO biological process selected from the group consisting of:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

more preferably, the genes are annotated according to KEGG and GO on KEGG _ pathway extracellular matrix-receptor interaction pathway and/or GO _ BP _ DIRECT extracellular matrix tissue, and on KEGG _ pathway PI3K-Akt signaling pathway and Focal addition.

In the corpus luteum supporting treatment method of the present invention, in some preferred embodiments, the patient has a genetic variation in one or a combination of the following pathway-associated genes: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A.

In the corpus luteum supporting treatment methods of the present invention, in some preferred embodiments, the patient has a genetic variation on a genome comprising at least 2, at least 3, or more preferably at least 4 or 5 pathway genes, and more preferably, the combination of genes comprises at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

In the corpus luteum supporting treatment methods of the present invention, in some preferred embodiments, the patient's corpus luteum stage D2 serum level is ≦ 5IU/L, e.g., less than 4IU/L, or 3IU/L, or 2IU/L, or less than 1 IU/L.

In any of the foregoing embodiments of the corpus luteum supporting treatment method, preferably the genetic variation is a missense mutation, preferably the variation does not result in gene inactivation but affects the biological activity of a protein encoded by the gene, preferably the mutation has an allele frequency in a normal healthy population of < 0.01.

In one embodiment, RIF patients also have abnormal estrogen and progestin levels. In other embodiments, the luteal phase support treatment method further comprises: progesterone and/or estrogen drugs are administered for hormone level adjustment in a patient based on the patient's luteinizing phase progesterone, estrogen, and luteinizing hormone levels from the date of endometrial conversion, in reference to a standard hormone profile for normal pregnancy.

Preferably, in some embodiments, the methods of the invention result in improved clinical outcome in said RIF patients. In some embodiments, the improved clinical outcome is improved clinical pregnancy rate. In other embodiments, the improved clinical outcome is improved live productivity. In still other embodiments, the improved clinical outcome comprises improved clinical pregnancy rates and improved live birth rates. In still other embodiments, the methods of the invention do not result in increased multiple pregnancy rates, miscarriage rates, and/or ectopic pregnancy rates.

Thus, in some embodiments, the present invention also provides a method for improving embryo implantation clinical outcome, e.g., clinical pregnancy rate and/or survival rate, in a repeat implantation failure patient, wherein the repeat implantation failure patient is diagnosed or classified as a subclinical hypopituitarism repeat implantation failure of the present invention according to the methods of the present invention, optionally the patient further has a luteal phase D2 serum LH level of less than or equal to 5IU/L, the method comprising: on the basis of conventional luteal support treatments of progesterone and/or estrogens, luteal activity-related drugs are further supplemented after embryo implantation. Preferably, the method of the invention of supplementing a luteinizing activity-related drug results in an improvement in clinical outcome in said patient compared to a conventional method of not supplementing a luteinizing activity-related drug.

In a preferred embodiment, the supplemented luteinising activity-related drug is a LH and/or HCG drug, preferably HCG. Luteinizing hormone LH is high in market price and low in active ingredient content at present, and the direct addition of exogenous LH to supplement LH causes economic burden to patients and is poor in effect. HCG is chorionic gonadotropin, a drug with luteinizing hormone-like action. Considering that the α -subunit of LH acts on the same receptor in a similar structure to HCG, the possibility of luteal support with exogenous HCG instead of exogenous LH has been proposed. However, the presence of HCG interferes with the detection of HCG at day 7 post-implantation, which is detrimental to the confirmation of biochemical pregnancy. Therefore, designing an economical and practical corpus luteum support solution using HCG is also a problem to be solved.

In one embodiment, therefore, the invention provides a method of luteal support treatment for HCG supplemented RIF patients. This method solves the above problems. In this method of luteal phase support therapy of the invention, HCG is used, preferably intramuscular HCG, after implantation of the embryo, and preferably said HCG is administered at a dose of 100-.

Normal human has estrogen E2 level not less than 100pg/ml at day 2 after ovulation, progestogen P level not less than 10ng/ml, and luteinizing hormone level not less than 6Miu/ml at day 5. To treat patients with subclinical pituitary insufficiency that have failed the recurrent implants of the present invention, in some embodiments, the methods of the present luteal phase support therapy also include: hormone-modifying therapy is initiated by reference to a standard hormone profile during the embryo implantation cycle, e.g., from the date of endometrial transformation, based on the level of each hormone in the patient's own luteal phase. For example, in some embodiments, after luteal phase D2, hormone (HCG, E2, LH and P) levels are measured periodically and compared to set normal values, exogenous hormonal drugs (e.g., estradiol and/or progesterone) are applied and the corresponding estrogen and/or progestin are supplemented to bring the corresponding hormone levels to the set normal standards.

In some embodiments of the foregoing methods of treatment, the patient has a biological pathway-associated genetic variation characteristic of a disease subtype of the invention described herein (e.g., the foregoing KEGG PATHWAY and GO pathway-associated genes), or has a genetic variation of one or more biomarkers characteristic of a disease subtype of the invention described herein (e.g., the foregoing genetic variation in a biomarker of the invention), wherein preferably the genetic variation is a missense mutation.

In some embodiments of the foregoing methods of treatment, the method is for improving endometrial receptivity of the RIF patient, and/or for improving clinical pregnancy and/or the likelihood of delivering a live fetus in the RIF patient.

In some embodiments of the foregoing methods of treatment, in said method embryo transfer is freeze-thaw embryo transfer or fresh cycle transfer, preferably freeze-thaw embryo transfer.

In some embodiments of the foregoing methods of treatment, the method comprises regularly checking for the hormone LH and supplementation HCG in the luteal phase of the patient.

In some embodiments of the foregoing methods of treatment, the RIF patient initiates endometrial conversion via a natural cycle, an artificial cycle, or an ovulation-promoting cycle prior to transplantation. In a preferred embodiment, RIF patients undergo freeze-thaw embryo transfer after natural cycle ovulation. In another preferred embodiment, RIF patients are subjected to freeze-thaw embryo transfer after the ovulation induction period. In yet another preferred embodiment, RIF patients undergo freeze-thaw embryo transfer after endometrial transformation in a row cycle.

In one embodiment of the foregoing method of treatment, the method of treatment further comprises: the hormone levels, including LH, P, E2 and HCG levels, of the patient are monitored prior to implantation and during the embryo implantation cycle.

V. the products of the invention and their use

In one embodiment, the invention provides a composition comprising reagents for detecting a biomarker or combination of markers of the invention. In another embodiment, the invention provides a kit comprising a composition of the invention. In another embodiment, the invention provides the use of said composition for the preparation of a kit for use in the diagnostic and/or prognostic method of the invention. In yet another embodiment, the present invention provides a microarray comprising a combination of reagents for detecting a combination of markers of the invention.

In some embodiments, the compositions, kits, microarrays of the invention can be used to detect genetic variations of the N biomarkers listed in any of the embodiments of the inventive biomarkers above. N may be an integer selected from N2 to 50, or 2-40, or 2-30, or 2-25, or 2-20, or 2-15, or 2-10, or 2-5. In some embodiments, N is an integer selected from 3 to 50, or 3-40, or 3-30, or 3-25, or 3-20, or 3-15, or 3-10, or 3-5. In some embodiments, N is an integer selected from 4 to 50, or 4 to 40, or 4 to 30, or 4 to 25, or 4 to 20, or 4 to 15, or 4 to 10, or 4 to 5. In some embodiments, N is an integer selected from 5 to 50, or 5-40, or 5-30, or 5-25, or 5-20, or 5-15, or 5-10. In some embodiments, N is an integer selected from 6 to 50, or 6-40, or 6-30, or 6-25, or 6-20, or 6-15, or 6-10. It will be apparent to those skilled in the art that N may also be selected from similar or larger numerical ranges. Accordingly, in some embodiments, the compositions, kits, microarrays of the invention comprise one or more reagents for detecting the N biomarkers.

In still other embodiments, the kits of the invention comprise one or more reagents for detecting a biomarker, and optionally, a container for holding a biological sample isolated from a subject; and instructions for performing biomarker detection and/or performing the diagnostic and/or prognostic methods of the present invention. The plurality of reagents may be packaged in separate containers. In addition, the kit may also contain one or more control reference samples, and optionally the detection time required for performing the detection (e.g., microarray detection or immunoassay). In some embodiments, the reagent may be an antibody, or a nucleic acid probe, or a protein microarray chip, or a nucleic acid microarray chip that binds to the marker.

In one embodiment, the kit of the invention may also comprise reagents for detecting the activity of a product encoded by a biomarker to quantitatively or qualitatively indicate whether there is a variation in the biomarker that results in a change in the structure/activity of the product.

In some embodiments, the invention provides a composition for diagnosing or classifying a RIF patient or for predicting the therapeutic responsiveness of a RIF patient to luteal phase support supplemented with a drug associated with luteal generating activity, wherein the composition comprises a reagent or combination of reagents for detecting information on a biomarker panel,

wherein the biomarker panel consists of a plurality of pathway-associated genes, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

for example, the biomarker panel consists of at least 2, at least 5, at least 10, at least 15, or all of LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9A3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL12A,

preferably, the detection provides information on a variation, preferably a missense mutation, of the pathway-associated gene,

preferably, the reagent is a polynucleotide for detecting the genetic variation, and/or a reagent (e.g., an antibody) for detecting the amount and/or activity of a mutein encoded by the genetic variation.

In some preferred embodiments, the composition is in the form of a microarray chip comprising a polynucleotide agent or combination of agents for providing information on the set of biomarkers, preferably a polynucleotide that hybridizes to a missense mutation site (e.g., a SNP) of the pathway gene.

In some embodiments, the invention also provides a kit, wherein the kit comprises a diagnostic/prognostic composition or a microarray chip of the invention.

In still further embodiments, the invention also provides the use of a diagnostic/prognostic composition of the invention, a microarray chip of the invention, or a kit of the invention, in the manufacture of a product for diagnosing or classifying a RIF patient, or for predicting the therapeutic responsiveness of a RIF patient to corpus luteum support supplemented with a medicament associated with luteal generating activity.

The following abbreviations are used in the examples.

LH: luteinizing hormone;

FSH, follicle stimulating hormone;

progesterone (also known as progesterone);

e2: estradiol;

HCG: chorionic gonadotropin;

IVF-ET: in vitro fertilization-embryo transfer;

FET: freezing and thawing embryo transplantation;

RIF: failure of repeated implantation;

m1,2,5,8,11,13,18 day 1,2,5,8,11,13,18 day of menstrual cycle

D0: the endometrial conversion day is the ovulation day in the natural cycle and the ovulation induction cycle; the day of administration of the endometrial transformation drug is initiated in the artificial cycle.

D2: day 2 as counted from date D0 of endometrial transformation.

BMI: body mass index.

Examples

Example 1

To investigate the relationship between luteinizing hormone and RIF, the serum level cycling of luteinizing hormone LH in RIF patients was examined and compared to LH level cycling in other IVF patients.

In previous studies, patients with secondary infertility due to fallopian tube factors alone, aged 25-36 years (mean 27.5 + -2.4) and no hormonal use during three months, were selected for whom no history of fetal arrest was observed, and day 3 and day 5 LH values after ovulation were determined. The mean level of LH at day D3 for this patient population was 7.63. + -. 3.49 mIU/ml; the mean LH level at D5 days was 6.67. + -. 4.53mIU/ml, showing no luteal phase low LH levels. In this example, patients who underwent IVF-ET due to the single oviduct factor were selected as controls for this purpose.

Briefly, in this example, patients with a history of RIF were selected as the test group; patients who underwent IVF-ET due to the single oviduct factor were also selected as a control group. The ovarian follicle development was examined by transvaginal ultrasound daily on day 8 of menstruation for the day of ovulation (day D0). Peripheral blood was drawn at 8 am on days 2,5,8,11,13 of the menstrual cycle (M) (i.e., M2, M5, M8, M11, M13, where day 1 of the menstrual cycle is M1), and on day 2 post-ovulation (D2, where day of ovulation is D0) for luteinizing hormone LH levels in serum. Thus, the LH cycle variation of the selected patients is monitored and graphed.

As a result, some RIF patients showed luteal phase low LH levels relative to the control group.

In tables 1 and 2 below and in fig. 1 and 2, respectively, the detected periodic changes in LH levels (LH units: mIU/ml) are exemplarily shown in some RIF patients and some patients undergoing IVF due to tubal problems.

TABLE 1 cyclical variation of LH in patients with repeated implantation failure

M2, day 2 of menstrual period; d2: day 2 after ovulation

TABLE 2 cyclical changes in LH in patients with IVF of fallopian tube problems

M2, day 2 of menstrual period; d2: day 2 after ovulation

Clinical observations have shown that these RIF patients with luteal phase low LH serum levels share common features: no apparent pituitary organic changes and no detectable cause of specific repeated implantation failure; in addition to having known abnormalities in luteal estrogen and progesterone levels, the LH levels at day D2 of the luteal phase also exhibit abnormalities. Luteinizing Hormone (LH) is a glycoprotein gonadotropin secreted by adenohypophysis cells and previous studies have shown that LH, in addition to affecting ovarian steroid hormone production through the corpus luteum, can act directly on the uterus. Abnormal D2 serum levels of LH in these RIF patients suggest: there may be some functional impairment of the pituitary gland in patients and thus subclinical hypopituitarism and further multiple adverse effects on embryo implantation and pregnancy.

Example 2

Neoxanthin support treatment regimens supplemented with LH functional analogue HCG were given for repeated implantation failures with luteal phase low LH serum levels and retrospective observational studies were performed on the patients' relevant clinical treatment responsiveness. In this retrospective observation study, serum LH levels <5IU/L at D2 day of luteal phase were taken as one of the entry conditions based on previous observations of dynamic LH levels in RIF patients and in oviduct factor IVF patients.

Patients who entered the study were all from the sixth medical center of the general hospital of the people's liberation military in China; and sign an informed consent. All clinical studies were approved by the institutional ethics committee prior to performance.

A total of 84 patients were enrolled. The general health status of the patient is good, and the patient has no history of immunity, chromosome abnormality and repeated abortion; and has the following features: (1) according to the consensus of experts in genetics diagnosis/screening technology before embryo implantation (Chinese medicine genetics impurities, 2018,35(2):151-155), a diagnosis with a history of RIF was made, (2) the age was ≥ 35 and <45, of which 29 patients had ages ≥ 35 and <38,11 were ≥ 38 and <40,25 were ≥ 40 and <43, and 29 were ≥ 40 and < 45; (3) the serum LH level at D2 day of luteal phase is less than or equal to 5 IU/L. None of these patients in the cohort were examined to exhibit organic pituitary damage and had normal basal Follicle Stimulating Hormone (FSH), Luteinizing Hormone (LH) and progesterone (P) levels.

Patients were divided into observation and control groups depending on the luteal phase support protocol used.

Observation groupCorpus luteum support protocol of (a): RIF patients (including natural, artificial, and ovulation cycles) used from the date of endometrial conversion (i.e., day D0) finmolton (yellow tablets), qinin, aspirin, and prednisone. The dosages were as follows: 1 tablet of Fenmolong (yellow tablet), three times a day, orally administered (PO); qining 2 tablets, 2 times daily, administered vaginally (PV); 1 aspirin tablet, 3 times daily, PO; prednisone 5mg, 1 time daily, PO. On day D2, the levels of three hormones (estradiol E2, luteinizing hormone LH, and progesterone P) were determined; and adjusting the dosage of the progestogen and the estrogenic agent based on the measured estrogen and progesterone levels.

The patient was given daily intramuscular injections of 500IU HCG, the remainder of the drug as before, on the next day after transplantation. On day 7 post-transplantation, HCG, E2, LH and P levels were evaluated.

Pregnancy was confirmed if HCG >50 mIU/mL. Thereafter, four hormones (HCG, E2, LH, and P) were tested every other day to determine the doubling status of HCG in time. The dosage of estrogen and progesterone drugs was adjusted and the hormones were checked weekly for stability and increased frequency of follow-up when the hormones were unstable. At 30-35 days post-transplantation, patients underwent vaginal ultrasound for intrauterine pregnancy and embryonic development. Abdominal ultrasound was performed on day 49 to examine fetal development, allowing for a gradual reduction in the administration of estrogen, progesterone and HCG as appropriate. By 12 weeks, all medications were stopped. The obstetrical examination is carried out, and the follow-up period is 1 year.

If 5. ltoreq. HCG. ltoreq.50 mIU/mL, the drug HCG is continued to be administered and the four hormones (HCG, E2, LH, and P) are detected every other day. If the pregnancy is confirmed, fetal containment is performed. If the HCG value does not double, the drug is terminated.

If HCG is less than or equal to 5mIU/mL, the patient is determined to be non-pregnant and drug administration is terminated.

Control groupCorpus luteum support protocol of (a): the same as the observation group except that HCG was not administered.

In this study, both the transplantation in the observation and control groups were freeze-thaw cycle transplants, which avoided ovarian hyperstimulation syndrome (OHSS). In addition, the alpha subunits of LH and HCG are similar in structure and act on the same receptor; therefore, exogenous HCG can be substituted for exogenous LH to make up for deficient LH. HCG half-life was 25 hours; blood HCG values after intramuscular injection of 500IU of HCG will not exceed 80mIU/mL (in practice it is observed that most are within 50 mIU/mL). Thus, a small daily dose of 500IU injected intramuscularly does not affect the observation of doubling of HCG due to early pregnancy. Thus, pregnancy can be confirmed when HCG actually measured is 50mIU/mL or more.

Record of clinical outcome

The following clinical outcomes were recorded for both groups: biochemical pregnancy, ectopic pregnancy, clinical pregnancy, multiple pregnancy, abortion and live birth. Since the observation group used HCG, no comparison was made for the biochemical pregnancy outcome of the two groups. Clinical pregnancy is defined as: an abdominal B-ultrasonic examination was performed 30 to 35 days after the transplantation, and a gestational sac was observed. Live birth is defined as: one or more live births were delivered after 20 weeks of gestation.

Statistical analysis

Statistical analysis of the data was performed using SPSS version 21.0. Quantitative data conforming to normal distribution are expressed as mean ± standard deviation, and two independent sample t-tests are performed for comparison. Quantitative data that did not fit a normal distribution were expressed as median, P25 and P75, and a rank-sum test was performed for comparison. Qualitative data are expressed as percentages and the rank-sum test is used for comparison. P <0.05 was considered statistically significant.

As a result:

table 3 lists the patient characteristics and treatment cycles for the observed and control groups. Table 4 lists the pregnancy outcome comparisons between the two groups. No relevant side reactions were detected in the study.

TABLE 3 comparison of patient characteristics and treatment periods between groups

Note that the observation group: luteal support for HCG was supplemented every other day after transplantation; control group conventional corpus luteum support without HCG supplementation P <0.05 was considered a statistically significant difference.

TABLE 4 comparison of pregnancy outcomes between groups

Note that the observation group: luteal support for HCG was supplemented every other day after transplantation; control group, conventional corpus luteum support without HCG supplementation; p <0.05 was considered as a statistically significant difference

As shown in table 4, no significant difference in ectopic pregnancy rate, multiple pregnancy rate and miscarriage rate was detected between the observation group and the control group (P > 0.05). However, the observed and control groups showed statistically significant differences (P <0.05) in clinical pregnancy rate (51.2% vs. 29.3%, RR ═ 1.907, 95% CI: 1.106-3.289) and live birth rate (46.5% vs. 24.4%, RR ═ 1.906, 95% CI: 1.019-3.570).

Example 3

The genetic basis of HCG luteal supporting therapeutic responsiveness in RIF patients was examined by whole genome exon sequencing and functional enrichment analysis.

In this study, 10 patients were randomly selected as a case group from among RIF patients who had successfully obtained clinical pregnancy using the HCG supplementation luteal phase support treatment protocol described in example 2. Meanwhile, 10 RIF patients who were not measured for LH hormone level and were not treated with HCG supplementation for luteal support were randomly selected as a control group. All patients in the study were from the sixth medical center of the general hospital of the people's liberation military in China; and sign an informed consent. A comparison of patient characteristics for the case and control groups is shown in table 5.

TABLE 5 comparison of the general demographic characteristics of the patients between groups

Note that P <0.05 was considered a statistically significant difference.

Gene level analysis

Whole genome exon sequencing

Genomic DNA was extracted from peripheral blood using DNeasy blood & tissue kit (Qiagen, Hilden, Germany). The quality and quantity of extracted DNA was measured using a Qubit DNA analysis kit and a Qubit 3.0 fluorometer. >0.6 μ g total DNA from the sample was used for library construction. Human full Exon region DNA was efficiently enriched using the Agilent SureSelect Human All Exon region V6 kit, root manufacturer's instructions, to generate sequencing libraries. The Qubit 2.0 was used for the initial amplification of the library, and the insert size (180-280 bp) in the library was detected using NGS 3K/Caliper. The library concentration (3nM) was accurately quantified using qPCR method to ensure quality. Whole exome sequencing was performed using Novaseq6000(Illumina) at 150bp read-ends according to the effective concentration of the library. The data output requirement is 10Gbp per sample.

Processing and analysis of sequencing results

Raw sequencing data were obtained by Bioinformatics. The raw data was filtered, the sequencing error rate was checked, the ratio of Phred values Q20 and Q30, the amount of raw data, and the mapping rate were evaluated to assess whether the data met the criteria (average ratio of Q20 bases > 90%, average ratio of Q30 bases > 80%, average error rate < 0.1%). The quality of the data from all samples is summarized in fig. 3. The cleaned data were aligned to a reference genome (GRCh37/hg19) by Burrows-Wheeler Alignment (BWA) to generate initial Alignment in BAM format. SAMtols [ Li H, Durbin R.fast and acid short read alignment with Burrows-Wheeler transform was used.

Bioinformatics (Oxford, England) 2009; 25:1754-60] data sorting was performed and Sambambamba markdup (de-duplication) was performed and the results used to calculate sequencing coverage and depth. Typically, sequencing reads of a sample reach > 95% of the mapping rate (mapping rate) and the sequencing depth of the base (read depth) >10X, in which case the single nucleotide polymorphism SNP detected at that base position is more reliable. The sequencing results from all samples were examined, and the Coverage of exon target regions (Coverage _ of _ target _ region) reached more than 99%, and at least more than 95% of the target regions covered by sequencing had a sequencing depth of at least 10 × (Fraction _ of _ target _ covered _ with _ at _ least _10 ×).

Screening of genetic variants and prediction of association with disease treatment responsiveness

Genetic variation screening

The high quality sequences obtained above were aligned with the reference genome of human (GRCh37/hg19) to obtain the genetic variation information in the samples. Statistical analysis and KEGG and GO annotation of the detected variant genes were performed.

The detected variants were screened for based on the following principles:

1) the consequences of variation are frameshift (frameshift mutation), stop-gain (stop codon gain mutation), and stop-loss (stop codon loss mutation);

2) missense mutations predicted to be harmful by SIFT and PolyPhen-2 software [ Kumar P, Henikoff S, Ng pc.predictioning the effects of coding non-syntony variants on protein functions using the SIFT algorithms. nature protocols 2009; 4:1073-81. ];

3) allele frequency was <0.01 based on GnomAD database.

Functional enrichment analysis

DAVID bioinformatics resources [ Huang da W, Sherman BT, Lempicki RA. bioinformatics information tools: pages aware the comprehensive functional analysis of large gene tests. nucleic acids research 2009; 37:1-13], and performing function enrichment analysis on the genes screened according to the principle.

The function of the Genes examined was investigated using the KEGG (Kyoto encyclopedia of Genes and Genes) pathway and the Biological Processes (BP), Molecular Functions (MF) and Cell Components (CC) terminals of Gene Ontology (GO). Statistical significance (P-value) was obtained using a modified Fisher's exact test and Benjamini's multiple test calibration.

As a result:

multiple genes with potentially deleterious mutations were detected in both 10 randomly selected treatment-responsive case group RIF patients and 10 randomly selected control group RIF patients enrolled in the study.

The function enrichment analysis was performed on the selected variant genes in the case group and the control group, respectively. Figure 4 shows the results of case group pathway analysis enrichment. Figure 5 shows the results of control pathway assay enrichment. As shown in the figure results, the genes in the case group formed significant enrichments on the following 3 pathways: ECM-receptor associated action pathways; a PI3K-Akt signaling pathway; and a Focal attachment pathway; in sharp contrast, none of these pathways appeared in the significantly enriched pathway list of the control group.

The 27 genes identified in the case group that were associated with the three major enrichment pathways described above are shown in table 6 below, with 17 genes associated with the extracellular gene pathway and 10 genes annotated to the three pathways simultaneously according to KEGG/GO. The association of each gene with the pathway is also shown in fig. 6.

Table 6: pathways of interaction with ECM-receptors detected in the case group; a PI3K-Akt signaling pathway; 27 genes related to the Focal attachment pathway

The mutations detected in these genes are mainly missense mutations, which alter specific amino acids of the protein, but do not lead to protein inactivation, and do not belong to loss-of-function mutations, such as frameshift mutations, stop codon gain/loss mutations. These findings are consistent with the subclinical phenotype of the pituitary observed in this study.

The distribution of the 27 genes associated with the three pathways was examined in the case group and control group samples. As a result, as shown in FIG. 7, of the 27 related genes, the remaining genes appeared only in the case group samples, except that 3 genes (COL13A1, COL24A1he LAMC2) appeared not only in the case group samples but also in the 4 control samples (WJ02/YHF09, TY08, LMY 06). The results of this analysis matched those of the previous case and control group for pathway enrichment analysis. For the 4 control samples presenting the three-way related genes, considering that the control patient individuals included in the group were blindly selected from the group of RIF patients who had not been previously tested for LH hormone levels and treated for HCG supplementation, the presence of the three-way related genes in these individuals may be predictive of these RIF individuals that would produce a beneficial clinical response in HCG supplementation with luteal support therapy.

In addition, the distribution of the 27 three-pathway-associated genes in each case sample was examined. Results as shown in fig. 8, all but 1 case sample showed variation in at least one pathway-associated gene, with 7 cases involving ECM-receptor interaction/extracellular matrix organization pathway molecules associated with extracellular matrix, and 2 cases involving PI3K and/or FOCAL attachment pathway molecules.

Taken together, the above results demonstrate that three pathways, the ECM-receptor interaction pathway, were obtained in a functional enrichment assay by case-control studies; a PI3K-Akt signaling pathway; and the Focal attachment pathway, and 27 pathway genes, are involved in the responsiveness of sub-clinical RIF case patients to HCG supplementation. It can be predicted that individuals with missense genetic variations on these pathways, particularly RIF patients with missense genetic variations on the ECM-receptor interaction pathway, will likely have beneficial clinical responsiveness to the HCG supplementation luteal treatment of the invention, e.g., improved in clinical pregnancy/live birth rates. Therefore, for RIF patients with such genetic variations, it would be advantageous to perform luteal phase regular hormone examination and HCG supplementation.

Based on the above findings of gene level studies and clinical studies, the present inventors have proposed a new subtype of RIF disease, i.e., repeated implantation failure of "subclinical hypopituitarism". This disease subtype is characterized by characteristic biological pathway-associated genetic variation, and low levels (≦ 5IU/L) of luteinizing phase D2 serum luteinizing hormone LH levels; and exhibit favorable therapeutic responsiveness to HCG supplementation in terms of pregnancy rate and/or live birth rate. Based on the above findings of gene level studies and clinical studies, the present inventors have proposed a technical solution of the present invention.

Some embodiments of the invention

1. A method for diagnosing or classifying a subject as a subclinical hypopituitarism recurrent implantation failure disease subtype, the method comprising detecting genetic variation information of a subject in a biological sample obtained from the subject, wherein a subject is diagnosed or classified as a subclinical hypopituitarism recurrent implantation failure if the subject exhibits variation in one or more pathway-associated genes (preferably at least 2,3, and more preferably at least 4 or 5 genes) in at least one or more KEGG or GO biological processes selected from the group consisting of:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)。

2. the method of embodiment 1, wherein the method comprises: detecting information from one or more pathway-associated genes in a biological sample from a subject, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

wherein, if the information indicates that one or more (preferably two, 3, more preferably at least 4 or 5) of the pathway-associated genes is mutated, the subject is diagnosed or classified as the disease subtype,

preferably, at least one (preferably at least two or 3) of said mutated pathway-associated genes is annotated according to KEGG and GO on a KEGG biological pathway or GO biological process selected from the group consisting of:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

and more preferably, said at least one gene is annotated according to KEGG and GO on KEGG _ pathway extracellular matrix-receptor interaction pathway and/or GO _ BP _ DIRECT extracellular matrix tissue, and on KEGG _ pathway PI3K-Akt signaling pathway and Foc al addition.

3. The method according to embodiment 2, wherein one or any combination of pathway-associated genes selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A; wherein, when information indicative of a genetic variation in the one or more pathway-associated genes (preferably at least 2 or 3, and more preferably at least 4 or 5 genes) is detected in the biological sample of the subject, the subject is diagnosed or classified as the disease subtype.

4. The method according to embodiment 3, wherein the subject diagnosed with the disease subtype has a variation in at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, CO L13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

5. A method according to any one of the preceding embodiments, wherein the subject exhibits an enrichment of a variant gene in said KEGG biological pathway or GO biological process as compared to a reference, preferably said enrichment exhibits a variation in a pathway-associated gene in the subject that is greater than the reference, preferably at least 2,3 or 4 more pathway-associated genes than the reference.

6. The method according to any one of the preceding embodiments, wherein the subject has no definite cause of repeat implantation failure and no apparent pituitary organic lesions, but exhibits mild symptoms of hypopituitarism.

7. The method according to any one of the preceding embodiments, wherein the subject has a daily serum LH level at luteal phase D2 of less than or equal to 5IU/L, more preferably less than 3IU/L,2IU/L, or 1 IU/L.

8. A method for predicting whether a subject with Repeated Implantation Failure (RIF) is eligible for treatment with a luteal phase support therapeutic agent, or for predicting the responsiveness of a subject with Repeated Implantation Failure (RIF) to treatment with a luteal phase support, wherein the luteal phase support comprises administering a luteal phase production activity-related drug, such as LH and/or HCG, preferably HCG,

wherein the method comprises: detecting genetic variation information of a subject in a biological sample obtained from the subject, wherein if a subject exhibits a variation in at least one or more KEGG biological pathways or GO biological processes selected from the group consisting of at least 2,3, and more preferably at least 4 or 5 genes having one or more pathway-associated genes (preferably at least 2,3, and more preferably at least 4 or 5 genes), the subject is indicated as being eligible for, or likely to respond therapeutically to, the corpus luteum supporting therapeutic agent:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)。

9. the method according to embodiment 8, wherein the method comprises: detecting information from one or more pathway-associated genes in a biological sample from a subject, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

wherein if the information indicates a variation in one or more (preferably two, 3, more preferably at least 4 or 5) of the pathway-associated genes, the subject is predicted to be eligible for, or likely to respond therapeutically to, the luteal phase-supportive therapeutic agent,

preferably, at least one (preferably at least two or 3) of said mutated pathway-associated genes is annotated according to KEGG and GO on a KEGG biological pathway or GO biological process selected from the group consisting of:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

and more preferably, the at least one gene is annotated according to KEGG and GO on KEGG _ pathway extracellular matrix-receptor interaction pathway and/or GO _ BP _ DIRECT extracellular matrix tissue, and on KEGG _ pathway PI3K-Akt signaling pathway and Foc al addition.

10. The method according to embodiment 9, wherein one or any combination of pathway-associated genes selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A; wherein, when information is detected in a biological sample of a subject that indicates a genetic variation in the one or more pathway-associated genes (preferably at least 2 or 3, and more preferably at least 4 or 5 genes), then the subject is predicted to be eligible for, or likely to respond therapeutically to, the luteal phase-supporting therapeutic agent.

11. The method of embodiment 10, wherein the subject predicted to be eligible to receive the treatment or likely to respond therapeutically to the treatment has a variation in at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITG a9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

12. The method according to any one of the preceding embodiments 8-11, wherein the subject is predicted to be suitable for, or likely to respond therapeutically to, the luteal phase-supporting therapeutic agent if the subject exhibits an enrichment of a variant gene in the KEG biological pathway or GO biological process as compared to a reference, preferably the enrichment exhibits a greater variation in a pathway-associated gene in the subject than in the reference, preferably at least 1, at least 2,3 or 4 more variations in a pathway-associated gene in the biological pathway or biological process as compared to the reference.

13. The method according to any one of the preceding embodiments 8-12, wherein the subject has no definite cause of repeated implantation failure and no apparent pituitary organic lesions, but exhibits mild hypopituitarism symptoms.

14. The method according to any one of the preceding embodiments 8-13, wherein the method further comprises detecting D2 day serum LH levels in the luteal phase of the subject, preferably the subject has a D2 serum LH level of less than 5IU/L, more preferably a D2 serum LH level of less than 3IU/L,2IU/L, or 1 IU/L.

15. The method according to any one of the preceding embodiments, wherein the genetic variation is a missense mutation, preferably the variation does not result in gene inactivation but affects the biological activity of a protein encoded by the gene, preferably the mutation has an allele frequency in a normal healthy population of < 0.01.

16. The method according to any one of the preceding embodiments, wherein the biological sample is selected from the group consisting of blood, serum, and other body fluids or biopsies.

17. The method according to any one of the preceding embodiments, wherein the genetic variation information is measured using a PCR method or a microarray chip.

18. The method according to any one of the preceding embodiments, wherein the genetic variation information is obtained using a sequencing method, preferably an exon sequencing method.

19. The method according to any one of the preceding embodiments, wherein the genetic variation information is obtained by detecting a biological activity of a protein encoded by the gene, preferably the biological activity is a reduced biological activity.

20. The method according to any one of the preceding embodiments, wherein the measuring comprises detecting the mutein encoded by the variant gene using an immunoassay, such as an ELISA assay.

21. The method according to any one of the preceding embodiments 8-20, wherein the luteal phase support treatment comprises: administering HCG after embryo implantation, more preferably, intramuscular HCG, preferably the luteal support therapy further comprises supplementation with a progesterone and/or estradiol drug, and optionally adjusting the amount of said drug administered according to the patient's progestin and/or estrogen levels;

preferably, HCG is administered at a dose of 100-800IU or 200-500IU,

more preferably, the patient is given daily intramuscular injections of 500IU HCG starting every other day after transplantation.

22. A method of providing luteal phase support therapy to a patient with recurrent implantation failure, said method comprising administering to said patient, after the date of endometrial transformation, preferably after implantation of an embryo, an effective amount of a luteal phase generating activity related drug, such as HCG and/or LH, preferably HCG,

wherein the patient exhibits a variation in at least one or more KEGG biological pathways or GO biological processes having one or more pathway-associated genes (preferably at least 2,3, and more preferably at least 4 or 5 genes) selected from:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)；

preferably, the subject has a variation in at least one or more genes in at least one or more KEGG biological pathways or GO biological processes selected from:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

more preferably, the subject has a variation in at least one or more genes annotated to the KEGG _ path extracellular matrix-receptor interaction PATHWAY and/or to the GO _ BP _ DIRECT extracellular matrix tissue according to KEGG and GO, and to the PI3K-Akt signaling PATHWAY and Focal addition.

23. The method according to embodiment 22, wherein the patient has a genetic variation in one or a combination of pathway-associated genes: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A;

preferably, the patient has genetic variation across a genome comprising at least 2, at least 3, or more preferably at least 4 or 5 pathway genes, more preferably the combination of genes comprises at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

24. The method according to any one of embodiments 22-23, wherein the patient has a luteal phase D2 serum level of ≦ 5IU/L, e.g., less than 4IU/L, or 3IU/L, or 2IU/L, or less than 1 IU/L.

25. The method according to any one of embodiments 22 to 24, wherein said genetic variation is a missense mutation, preferably said variation does not result in gene inactivation but affects the biological activity of a protein encoded by the gene, preferably said mutation has an allele frequency in a normal healthy population of < 0.01.

26. The method according to any one of embodiments 22 to 25, wherein said method is for improving the clinical pregnancy and/or the likelihood of delivering a live fetus in said RIF patient.

27. The method according to any one of embodiments 22-26, wherein the method comprises: administering HCG after embryo implantation, more preferably, intramuscular HCG, preferably the luteal support therapy further comprises supplementation with a progesterone and/or estradiol drug, and optionally adjusting the amount of said drug administered according to the patient's progestin and/or estrogen levels;

preferably, HCG is administered at a dose of 100-800IU or 200-500IU,

more preferably, the patient is given daily intramuscular injections of 500IU HCG starting every other day after transplantation.

28. The method according to any one of embodiments 22-27, wherein embryo transfer is a freeze-thaw cycle transfer or a fresh cycle transfer, preferably a freeze-thaw cycle transfer,

preferably, the patient is subjected to embryo transfer, especially freeze-thaw embryo transfer, after ovulation in the natural cycle or after application of an ovulation promoting protocol or after an artificial cycle.

29. The method according to any one of embodiments 22-28, wherein said method comprises monitoring the hormone levels, including LH, P, E2 and HCG levels, of the patient prior to implantation and during the embryo implantation cycle.

30. A composition for diagnosing or classifying a RIF patient or for predicting the therapeutic responsiveness of a RIF patient to corpus luteum support supplemented with a medicament associated with luteal generating activity, wherein the composition comprises a reagent or combination of reagents for detecting information of a biomarker panel,

wherein the biomarker panel consists of a plurality of pathway-associated genes, wherein the pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

for example, the biomarker panel consists of at least 2, at least 5, at least 10, at least 15, or all of LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9A3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL12A,

preferably, the detection provides information on a variation, preferably a missense mutation, of the pathway-associated gene, e.g.the pathway-associated gene described in embodiments 8-11,

preferably, the reagent is a polynucleotide for detecting the genetic variation, and/or a reagent (e.g., an antibody) for detecting the amount and/or activity of a mutein encoded by the genetic variation.

31. The composition of embodiment 30, wherein said composition is in the form of a microarray chip comprising a polynucleotide agent or combination of agents for providing information on said set of biomarkers, preferably said polynucleotide agent is a polynucleotide that hybridizes to a missense mutation site (e.g., a SNP) of said pathway gene.

32. A kit, wherein the kit comprises the composition of embodiment 30 or 31.

33. Use of the composition of embodiment 30, the microarray chip of embodiment 31, or the kit of embodiment 32 in the manufacture of a product for diagnosing or classifying a RIF patient, or for predicting the therapeutic responsiveness of a RIF patient to corpus luteum support supplemented with a luteal generating activity-related drug.

Claims (13)

1. Use of a reagent or combination of reagents for detecting information of a biomarker panel in the manufacture of a kit for diagnosing or classifying a subject as a subclinical hypopituitarism recurrent implantation failure disease subtype,

wherein the biomarker panel consists of a plurality of pathway-associated genes, wherein the plurality of pathway-associated genes are selected from the group consisting of: annotating genes on at least one or more of the following biological pathways or biological processes according to KEGG and GO:

-KEGG _ path: an extracellular matrix-receptor interaction pathway (hsa 04512);

-GO _ BP _ DIRECT extracellular matrix organization (GO: 0030198);

-KEGG _ PATHWAY: PI3K-Akt signaling PATHWAY (hsa 04511);

-KEGG_PATHWAY:Focal Adhesion(hsa04510)，

preferably, the biomarker panel consists of at least 2, at least 5, at least 10, at least 15, or all of LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9A3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL12A,

wherein the detection provides information on a variation, preferably a missense mutation, of the pathway-associated gene,

preferably, the reagent or combination of reagents is used for detecting the gene variation of polynucleotides, and/or for detecting the gene variation encoded by the mutant protein amount and/or activity of reagents (such as antibodies),

wherein the diagnosing or classifying comprises detecting variation information of the plurality of pathway-associated genes of the subject in a biological sample obtained from the subject, wherein the subject is diagnosed or classified as a subclinical hypopituitarism recurrent implantation failure if the subject exhibits variation in at least 2,3, and more preferably at least 4 or 5 of the plurality of pathway-associated genes,

preferably, wherein the subject exhibits an enrichment of a variant gene in said KEGG biological pathway or GO biological process as compared to a reference, preferably said enrichment exhibits a variation in a pathway-associated gene in the subject that is greater than the reference, preferably at least 2,3 or 4 more than the reference.

2. The use of claim 1, wherein, if said information indicates that one or more (preferably two, 3, more preferably at least 4 or 5) of said plurality of pathway-related genes is mutated, and at least one (preferably at least two or 3) of said mutated pathway-related genes is annotated according to KEGG and GO on a KEGG biological pathway or GO biological process selected from the group consisting of:

-KEGG _ path: extracellular matrix-receptor interaction pathways;

-GO _ BP _ DIRECT extracellular matrix organization;

and more preferably, said at least one gene is annotated according to KEGG and GO on the KEGG-pathway extracellular matrix-receptor interaction pathway and/or GO _ BP _ DIRECT extracellular matrix tissue, and on the KEGG-pathway PI3K-Akt signaling pathway and Foc al addition,

the subject is diagnosed or classified as having the disease subtype.

3. Use according to claim 2, wherein the biomarker panel consists of the following pathway-associated genes: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6A6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9a3, PHLPP2, IFNA4, CRTC2, CSF3R, CSF1, GYS1, CREB3L4, LPAR6, SHC4, and MYL 12A; wherein a subject is diagnosed or classified as the disease subtype when information detected in a biological sample of the subject indicates information of genetic variation in the one or more pathway-associated genes (preferably at least 2 or 3, and more preferably at least 4 or 5 genes),

preferably, wherein the subject diagnosed with said disease subtype has a variation in at least one gene selected from the group consisting of: LAMA5, LAMA2, ITGB4, ITGA11, SPP1, TNC, ITGA9, COL24A, COL6a6, COL18A, COL13a1, NID2, ACAN, CDH1, ERCC2, COL9 A3.

4. Use according to any one of the preceding claims, wherein the subject has no definite cause of repeated implantation failure and no apparent pituitary organic lesions, but exhibits mild hypopituitarism symptoms, and/or the subject has a D2 day serum LH level at luteal phase of less than or equal to 5IU/L,3IU/L,2IU/L, or 1 IU/L.

5. Use of a reagent or combination of reagents for detecting information of a biomarker panel in the manufacture of a kit for predicting whether a subject with Repeated Implantation Failure (RIF) is eligible for treatment with a luteal phase support therapeutic, or for predicting the responsiveness of a subject with Repeated Implantation Failure (RIF) to treatment with a luteal phase support, wherein the luteal phase support comprises administration of a luteal phase production activity-related drug, such as LH and/or HCG, preferably HCG,

wherein the biomarker panel consists of a plurality of pathway-associated genes as defined in any one of claims 1 to 4,

wherein the detection provides information on a variation, preferably a missense mutation, of the pathway-associated gene,

preferably, the reagent or combination of reagents is used for detecting the gene variation of polynucleotides, and/or for detecting the gene variation encoded by the mutant protein amount and/or activity of reagents (such as antibodies),

wherein, if the subject exhibits a variation in at least 2,3, and more preferably at least 4 or 5 genes of said plurality of pathway-associated genes, then the subject is indicated as being eligible for, or likely to respond therapeutically to, said luteal phase supporting therapeutic agent,

preferably, the subject has no definite cause of recurrent implantation failure and no apparent pituitary organic lesions, but exhibits mild hypopituitarism symptoms, and/or the subject has a D2 day serum LH level at luteal phase of less than or equal to 5IU/L,3IU/L,2IU/L, or 1 IU/L.

6. Use of a luteinising activity-related drug in the manufacture of a medicament for improving the clinical pregnancy and/or likelihood of delivering a live foetus in a patient with recurrent implantation failure, wherein the patient is administered an effective amount of the luteinising activity-related drug, e.g. HCG and/or LH, preferably HCG, at the date of endometrial conversion, preferably after implantation of an embryo, to provide a luteinising therapy,

preferably, wherein the patient has a luteal phase D2 serum level of ≦ 5IU/L, e.g., less than 4IU/L, or 3IU/L, or 2IU/L, or less than 1 IU/L;

still more preferably, wherein said patient exhibits a genetic variation, preferably a missense mutation, in at least one pathway gene (preferably at least 2 or 3, and more preferably at least 4 or 5 genes) in a biomarker panel consisting of a plurality of pathway-associated genes as defined in any of claims 1 to 4,

still preferably, the subject has no definite cause of repeat implantation failure and no apparent pituitary organic lesions, but exhibits mild hypopituitarism symptoms.

7. Use according to any of the preceding claims, wherein the genetic variation is a missense mutation, preferably the variation does not lead to gene inactivation but affects the biological activity of a protein encoded by the gene, preferably the mutation has an allele frequency in a normal healthy population of < 0.01.

8. Use according to any one of the preceding claims, wherein the biological sample is selected from blood, serum, and other body fluids or biopsies.

9. Use according to any one of the preceding claims, wherein

The genetic variation information is measured using a PCR method or a microarray chip, or

The genetic variation information is obtained using a sequencing method, preferably an exon sequencing method, or

The information on the genetic variation is obtained by detecting the biological activity of the protein encoded by the gene, preferably the biological activity is reduced, or

The measuring comprises detecting the mutant protein encoded by the variant gene using an immunoassay, such as an ELISA assay.

10. Use according to any one of the preceding claims, wherein the luteal phase support treatment comprises: administering HCG after embryo implantation, more preferably, intramuscular HCG, preferably the luteal support therapy further comprises supplementation with a progesterone and/or estradiol drug, and optionally adjusting the amount of said drug administered according to the patient's progestin and/or estrogen levels;

preferably, HCG is administered at a dose of 100-800IU or 200-500IU,

more preferably, starting every other day after transplantation, the patient is given daily intramuscular injections of 500IU HCG,

preferably, wherein the method comprises monitoring the hormone levels, including LH, P, E2 and HCG levels, of the patient prior to implantation and during the embryo implantation cycle.

11. Method according to any of the preceding claims, wherein embryo transfer is a freeze-thaw cycle transfer or a fresh cycle transfer, preferably a freeze-thaw cycle transfer, preferably the patient is embryo transferred after ovulation in the natural cycle or after application of an ovulation-promoting protocol or after an artificial cycle, in particular a freeze-thaw embryo transfer is performed.

12. A composition or a kit comprising said composition for diagnosing or classifying a RIF patient or for predicting the therapeutic responsiveness of a RIF patient to luteal phase support supplemented with a luteal phase generating activity related drug,

wherein the composition comprises a reagent or combination of reagents for detecting information of a biomarker panel as defined in any one of claims 1 to 4,

preferably, wherein the composition is in the form of a microarray chip, comprising a polynucleotide agent or combination of agents for providing information of the biomarker panel, preferably the polynucleotide agent is a polynucleotide that hybridizes to a missense mutation site (e.g., a SNP) of the pathway gene.

13. Use of a composition or microarray chip or kit according to claim 12 for the preparation of a product for diagnosing or classifying a RIF patient, or for predicting the therapeutic responsiveness of a RIF patient to corpus luteum support supplemented with a luteal generating activity-related drug.

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