Biomarker for evaluating spermatogenesis of pituitary stem disruption syndrome and application of biomarker

Abstract

The invention belongs to the technical field of biological detection, and particularly relates to a biomarker for evaluating spermatogenesis of pituitary stem disruption syndrome and application of the biomarker. The biomarker comprises C9JFR7, B4E1B2, and Q9NPF0, and is characterized in that the biomarker comprises C9JFR7, B4E1B2, the invention provides a novel molecular marker for evaluating spermatogenesis of the PSIS, whether spermatogenesis of PSIS patients succeeds or not can be accurately diagnosed in a laboratory level by quantitatively detecting the content of the biomarker, the compliance of the patients is improved, clear spermatogenesis judgment is given to guide clinical treatment and an assisted reproductive technology, and the application prospect is wide. The fertility of the patient is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of biological detection, and specifically relates to biomarkers for evaluating spermatogenesis in pituitary stalk interruption syndrome and their applications. Background Art

[0002] Pituitary stalk interruption syndrome (PSIS) is a rare congenital pituitary anatomical defect, characterized by a significantly thinned or absent pituitary stalk, hypoplasia of the anterior pituitary lobe, and ectopia of the posterior pituitary lobe, resulting in a series of clinical symptoms caused by the inability of hormones secreted by the hypothalamus to be transported to the posterior pituitary lobe through the pituitary stalk. Due to the thin or interrupted pituitary stalk, hormones secreted by the hypothalamus cannot act on the anterior pituitary lobe through the pituitary portal system, and at the same time, hypoplasia of the adenohypophysis leads to a decrease in the number of pituitary cells. Therefore, the clinical manifestations of PSIS patients are most commonly pituitary hormone deficiencies (isolated or combined), growth hormone deficiency (GHD), followed by gonadal hormone deficiencies, which may lead to dysplasia of sexual organs and absence of secondary sexual characteristics. In addition, some patients may have deficiencies in thyroid hormones and adrenal cortical hormones.

[0003] Infertility is a major problem that needs to be urgently solved in adult PSIS patients, which not only affects family harmony and happiness but also causes a social and economic burden. Gonadotropin therapy can successfully induce spermatogenesis, but the spermatogenesis induction protocol for PSIS has a long course, inconvenient pump treatment or frequent injections, and the lack of objective spermatogenesis markers to predict the curative effect will greatly reduce the compliance of spermatogenesis treatment. For individuals with a small number of sperm, the computer-aided sperm counting system cannot give a clear judgment on spermatogenesis. And currently, there is no objective, sensitive, accurate, and non-invasive biomarker for early predicting the spermatogenesis curative effect of PSIS.

[0004] Therefore, it is very necessary to use efficacy markers to evaluate the spermatogenesis treatment effect of PSIS patients to guide clinical treatment and assisted reproductive technology and effectively improve the fertility of patients. Summary of the Invention

[0005] The primary object of the present invention is to provide a biomarker for evaluating spermatogenesis in pituitary stalk interruption syndrome and its applications, so as to be able to evaluate the spermatogenesis treatment effect of PSIS patients and thus improve the fertility of patients.

[0006] Therefore, the present invention provides the following technical solutions.

[0007] The first aspect of the present invention provides a biomarker for evaluating spermatogenesis in pituitary stalk interruption syndrome, and the biomarker includes C9JFR7, B4E1B2, and Q9NPF0.

[0008] In a preferred embodiment of the present invention, the biomarker further includes any one, two, three, or all of E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2, and B3KXY9.

[0009] The second aspect of the present invention provides the use of a reagent for quantitatively detecting the biomarker as described above in the preparation of a kit or a detection device for evaluating spermatogenesis in pituitary stalk interruption syndrome.

[0010] In a preferred embodiment of the present invention, the reagent is an antibody against the biomarker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatographic analysis.

[0011] The third aspect of the present invention provides a kit for evaluating spermatogenesis in pituitary stalk interruption syndrome, including a reagent for detecting the biomarker as described above. Optionally, the detection is for quantitatively detecting the level of the biomarker in the semen of a subject.

[0012] In a preferred embodiment of the present invention, the reagent is an antibody against the biomarker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatographic analysis.

[0013] In a preferred embodiment of the present invention, the kit is an ELISA kit.

[0014] The fourth aspect of the present invention provides the application of the biomarker as described above in the evaluation of spermatogenesis in pituitary stalk interruption syndrome for non-disease diagnosis or treatment purposes.

[0015] The fifth aspect of the present invention provides the use of the biomarker as described above as a biomarker for spermatogenesis in pituitary stalk interruption syndrome in the preparation of a preparation for evaluating spermatogenesis in pituitary stalk interruption syndrome.

[0016] The sixth aspect of the present invention provides a method for evaluating whether a drug can be used for spermatogenesis in pituitary stalk interruption syndrome, including using the biomarker as described above as a biomarker to evaluate the spermatogenic effect of the drug.

[0017] The seventh aspect of the present invention provides a method for screening compounds that can promote spermatogenesis in pituitary stalk interruption syndrome, including using the biomarker as described above as a biomarker to evaluate the spermatogenic effect of the compounds.

[0018] By means of the above technical solutions, the present invention has at least the following advantages:

[0019] The present invention provides novel molecular markers that can be used to evaluate spermatogenesis in pituitary stalk interruption syndrome. By quantitatively detecting the content of the biomarkers, it is possible to accurately diagnose whether spermatogenesis is successful in PSIS patients at the laboratory level, improve patient compliance, give a clear judgment on spermatogenesis to guide clinical treatment and assisted reproductive technology, and improve the fertility of patients.

[0020] The biomarkers provided by the present invention for evaluating spermatogenesis in pituitary stalk interruption syndrome are any one or a combination of two or more of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2, and B3KXY9. By comparing their levels in semen with those in normal semen, it is possible to highly accurately diagnose whether spermatogenesis is successful in PSIS patients.

[0021] The above description is only an overview of the technical solution of the present invention. In order to be able to more clearly understand the technical means of the present invention and implement it in accordance with the content of the description, the following will detail the preferred embodiments of the present invention as follows. Brief Description of the Drawings

[0022] Figure 1 It is a variable importance ranking graph obtained by evaluating and ranking important variables using the random forest machine learning method;

[0023] Figure 2 It is a biomarker variable importance screening graph;

[0024] Figure 3 It is a box plot of the abundance of each selected protein between the SF group and the SS group;

[0025] Figure 4 It is the ROC curve of each of the ten biomarkers;

[0026] Figure 5 It is a sample dimensionality reduction graph of the biomarkers C9JFR7, B4E1B2, and Q9NPF0;

[0027] Figure 6 It is a visualization graph of the confusion matrix of the biomarkers C9JFR7, B4E1B2, and Q9NPF0;

[0028] Figure 7 It is the ROC curve graph of the biomarkers C9JFR7, B4E1B2, and Q9NPF0;

[0029] Figure 8It is a heatmap showing the correlation between the expression of biomarker proteins and the clinical characteristics of the disease. Among them, c: the group with failed spermatogenesis treatment for KS; t: the group with successful spermatogenesis treatment for KS; TV: the testicular size after the patient's treatment (clinically considered: the larger the testis, the stronger the spermatogenic ability); SC: Sperm count; SCT: Sperm concentration. Detailed implementation manners

[0030] In order to make the technical means, creative features, achieved purposes and effects of the present invention easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0031] Infertility is a major problem that adult patients with pituitary stalk interruption syndrome (PSIS) urgently need to solve, which not only affects the harmony and happiness of the family, but also causes social and economic burdens. Gonadotropin therapy can successfully induce spermatogenesis, but there are many problems such as a long treatment cycle and uncertain treatment efficacy. And currently, there is no objective, sensitive, accurate, non-invasive biomarker for early predicting the spermatogenic efficacy of PSIS.

[0032] The present invention provides corresponding biomarkers for this phenomenon, which include C9JFR7, B4E1B2 and Q9NPF0.

[0033] Preferably, the biomarker further includes any one, two, three or all of E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9.

[0034] It should be noted that C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 in the present invention are all known proteins in the human body. They can be queried through public protein databases, and the ID and amino acid sequence information of each protein are shown as follows.

[0035] 1. C9JFR7 (CYCS)

[0036] >tr|C9JFR7|C9JFR7_HUMAN Cytochrome c(Fragment)OS=Homo sapiens OX=9606GN=CYCS PE=1SV=1;

[0037] SEQ ID NO:1

[0038] MGDVEKGKKIFIMKCSQCHTVEKGGKHKTGPNLHGLFGRKTGQAPGYSYTAANKNKGIIWGEDTLMEYLENPKKYIPGTKMIFVGIKKKEERADLIAYLKK

[0039] 2.B4E1B2(Serotransferrin)

[0040] >tr|B4E1B2|B4E1B2_HUMAN Serotransferrin OS=Homo sapiens OX=9606 PE=2 SV=1

[0041] SEQ ID NO:2

[0042] MRLAVGALLVCAVLGLCLAVPDKTVRWCAVSEHEATKCQSFRDHMKSVIPSDGPSVACVKKASYLDCIRAIAANEADAVTLDAGLVYDAYLAPNNLKPVVAEFYGSKEDPQTFYYAVAVVKKDSGFQMNQLRGKKSCHTGLGRSAGWNIPNFFSGSCAPCADGTDFPQLCQLCPGCGCSTLNQYFGYSGAFKCLKDGAGDVAFVKHSTIFENLANKADRDQYELLCLDNTRKPVDEYKDCHLAQVPSHTVVARSMGGKEDLIWELLNQAQEHFGKDKSKEFQLFSSPHGKDLLFKDSAHGFLKVPPRMDAKMYLGYEYVTAIRNLREGTCPEAPTDECKPVKWCALSHHERLKCDEWSVNSVGKIECVSAETTEDCIAKIMNGEADAMSLDGGFVYIAGKCGLVPVLAENYNKSDNCEDTPEAGYFAVAVVKKSASDLTWDNLKGKKSCHTAVGRTAGWNIPMGLLYNKINHCRFDEFFSEGCAPGSKKDSSLCKLCMGSGLNLCEPNNKEGYYGYTGAFRCLVEKGDVAFVKHQTVPQNTGGKNPDPWAKNLNEKDYELLCLDGTRKSVEEYANCHLARAPNHAVVTRKDKEACVHKILRQQQHLFGSNVTDCSGNFCLFRSETKDLLFRDDTVCLAKLHDRNTYEKYLGEEYVKAVGNLRKCSTSSLLEACTFRRP

[0043] 3. Q9NPF0 (CD320 antigen)

[0044] >sp|Q9NPF0|CD320_HUMAN CD320 antigen OS=Homo sapiens OX=9606 GN=CD320 PE=1 SV=1

[0045] SEQ ID NO:3

[0046] MSGGWMAQVGAWRTGALGLALLLLLGLGLGLEAAASPLSTPTSAQAAGPSSGSCPPTKFQCRTSGLCVPLTWRCDRDLDCSDGSDEEECRIEPCTQKGQCPPPPGLPCPCTGVSDCSGGTDKKLRNCSRLACLAGELRCTLSDDCIPLTWRCDGHPDCPDSSDELGCGTNEILPEGDATTMGPPVTLESVTSLRNATTMGPPVTLESVPSVGNATSSSAGDQSGSPTAYGVIAAAAVLSASLVTATLLLLSWLRAQERLRPLGLLVAMKESLLLSEQKTSLP

[0047] 4.E9PAR0(FKBP11)

[0048] >tr|E9PAR0|E9PAR0_HUMAN peptidylprolyl isomerase OS=Homo sapiens OX=9606 GN=FKBP11 PE=1 SV=1

[0049] SEQ ID NO:4

[0050] MCVGEKRRAIIPSHLAYGKRGFPPSVPADAVVQYDVELIALIRANYWLKLVKGILPLVGMAMVPALLGLIGYHLYRKANRPKVSKKKLKEEKRNKSKKK

[0051] 5.A0A8I5KXD3(PPEF1)

[0052] >tr|A0A8I5KXD3|A0A8I5KXD3_HUMAN Serine / threonine-protein phosphataseOS=Homo sapiens OX=9606GN=PPEF1PE=1SV=1

[0053] SEQ ID NO:5

[0054] MRDRWDYVDSIDVPDSYNGPRLQFPLTCTDIDLLLEAFKEQQILHAHYVLEVLFETKKVLKQMPNFTHIQTSPSKEVTICGDLHGKLDDLFLIFYKNGLPSERNPYVFNGDFVDRGKNSIEILMILCVSFLVYPNDLHLNRGNHEDFMMNLRYGFTKEILHKYKLHGKRILQILEEFYAWLPIGTIVDNEILVIHGGISETTDLNLLHRVERNKMKSVLIPPTETNRDHDTDSKHNKVGVTFNAHGRIKTNGSPTEHLTEHEWEQIIDILWSDPRGKNGCFPNTCRGGGCYFGPDVTSKILNKYQLKMLIRSHECKPEGYEICHDGKVVTIFSASNYYEEGSNRGAYIKLCSGTTPRFFQYQVTKATCFQPLRQRVDTMENSAIKILRERVISRKSDLTRAFQLQDHRKSGKLSVSQWAFCMENILGLNLPWRSLSSNLVNIDQNGNVEYMSSFQNIRIEKPVQEAHSTLVETLYRYRSDLEIIFNAIDTDHSGLISVEEFRAMWKLFSSHYNVHIDDSQVNKLANIMDLNKDGSIDFNEFLKAFYVVHRYEDLMKPDVTNLG

[0055] 6.Q9Y230(RuvB-like 2)

[0056] >sp|Q9Y230|RUVB2_HUMAN RuvB-like 2 OS=Homo sapiens OX=9606 GN=RUVBL2 PE=1 SV=3

[0057] SEQ ID NO:6

[0058] MATVTATTKVPEIRDVTRIERIGAHSHIRGLGLDDALEPRQASQGMVGQLAARRAAGVVLEMIREGKIAGRAVLIAGQPGTGKTAIAMGMAQALGPDTPFTAIAGSEIFSLEMSKTEALTQAFRRSIGVRIKEETEIIEGEVVEIQIDRPATGTGSKVGKLTLKTTEMETIYDLGTKMIESLTKDKVQAGDVITIDKATGKISKLGRSFTRARDYDAMGSQTKFVQCPDGELQKRKEVVHTVSLHEIDVINSRTQGFLALFSGDTGEIKSEVREQINAKVAEWREEGKAEIIPGVLFIDEVHMLDIESFSFLNRALESDMAPVLIMATNRGITRIRGTSYQSPHGIPIDLLDRLLIVSTTPYSEKDTKQILRIRCEEEDVEMSEDAYTVLTRIGLETSLRYAIQLITAASLVCRKRKGTEVQVDDIKRVYSLFLDESRSTQYMKEYQDAFLFNELKGETMDTS

[0059] 7.B3KQF0(SEC63)

[0060] >tr|B3KQF0|B3KQF0_HUMAN cDNA FLJ90354 fis,clone NT2RP2003390,highlysimilar to Translocation protein SEC63 homolog OS=Homo sapiens OX=9606 PE=2 SV=1

[0061] SEQ ID NO:7

[0062] MAGQQFQYDDSGNTFFYFLTSFVGLIVIPATYYLWPRDQNAEQIRLKNIREVYGRCMWYRLRLLKPQPNIIPTVKKIVLLAGWALFLFLAYKVSKTDREYQEYNPYEVLNLDPGATVAEIKKQYRLLSLKYHPDKGGDEVMFMRIAKAYAALTDEESRKNWEEFGNPDGPQATSFGIALPAWIVDQKNSILVLLVYGLAFMVILPVVVGSWWYRSIRYSGDQILIRTTQIYTYFVYKTRNMDMKRLIMVLAGASEFDPQYNKDATSRPTDNILIPQLIREIGSINLKKNEPPLTCPYSLKARVLLLSHLARMKIPETLEEDQQFMLKKCPALLQEMVNVICQLIVMARNREEREFRAPTLASLENCMKLSQMAVQGLQQFKSPLLQLPHIEEDNLRRVSNHKKYEIKTIQDLVSLKESDRHTLLHFLEDEKYEEVMAVLGSFPYVTMDIKSQVLDDEDSNNITVGSLVTVLVKLTRQTMAEVFEKEQSICAAEEQPAEDGQGETNKNRTKGGWQQKSKGPKKTAKSKKKKPLKKKPTPVLLPQSKQQKQKQANGVVGNEAAVKEDEEEVSDKGSDSEEEETNRDSQSEKDDGSDRDSDREQDEKQNKDDEAEWQELQQSIQRKERALLETKSKITHPVYSLYFPEEKQEWWWLYIADRKEQTLISMPYHVCTLKDTEEVELKFPAPGKPGNYQYTVFLRSDSYMGLDQIKPLKLEVHEAKPVPENHPQWDTAIEGDEDQEDSEGFEDSFEEEEEEEEDDD

[0063] 8.A8K878(MANF)

[0064] >tr|A8K878|A8K878_HUMAN cDNA FLJ77177,highly similar to Homo sapiensarginine - rich,mutated in early stage tumors(ARMET),mRNA OS=Homo sapiens OX=9606 PE=1 SV=1

[0065] SEQ ID NO:8

[0066] MRRMRRMWATQGLAVALALSVLPGSRALRPGDCEVCISYLGRFYQDLKDRDVTFSPATIENELIKFCREARGKENRLCYYIGATDDAATKIINEVSKPLAHHIPVEKICEKLKKKDSQICELKYDKQIDLSTVDLKKLRVKELKKILDDWGETCKGCAEKSDYIRKINELMPKYAPKAASARTDL

[0067] 9.Q9UJT2(TSKS)

[0068] >sp|Q9UJT2|TSKS_HUMAN Testis-specific serine kinase substrate OS=Homo sapiens OX=9606 GN=TSKS PE=1 SV=3

[0069] SEQ ID NO:9

[0070] MASVVVKTIWQSKEIHEAGDTPTGVESCSQLVPEAPRRVTSRAKGIPKKKKAVSFHGVEPQMSHQPMHWCLNLKRSSACTNVSLLNLAAMEPTDSTGTDSTVEDLSGQLTLAGPPASPTLPWDPDDADITEILSGVNSGLVRAKDSITSLKEKTNRVNQHVQSLQSECSVLSENLERRRQEAEELEGYCIQLKENCWKVTRSVEDAEIKTNVLKQNSALLEEKLRYLQQQLQDETPRRQEAELQEPEEKQEPEEKQEPEEKQKPEAGLSWNSLGPAATSQGCPGPPGSPDKPSRPHGLVPAGWGMGPRAGEGPYVSEQELQKLFTGIEELRREVSSLTARWHQEEGAVQEALRLLGGLGGRVDGFLGQWERAQREQAQTARDLQELRGRADELCTMVERSAVSVASLRSELEGLGPLKPILEEFGRQFQNSRRGPDLSMNLDRSHQGNCARCASQGSQLSTESLQQLLDRALTSLVDEVKQRGLTPACPSCQRLHKKILELERQALAKHVRAEALSSTLRLAQDEALRAKNLLLTDKMKPEEKMATLDHLHLKMCSLHDHLSNLPLEGSTGTMGGGSSAGTPPKQGGSAPEQ

[0071] 10.B3KXY9 (Hexokinase-1, Hexokinase-1)

[0072] >tr|B3KXY9|B3KXY9_HUMAN Hexokinase-1 OS=Homo sapiens OX=9606 PE=2 SV=1

[0073] SEQ ID NO:10

[0074] MGQICQRESRQGLAMLPRLFLNPWRQVILLPQPPKVLGLQATAAEKPKLHLLAESEIDKYLYAMRLSDETLIDIMTRFRKEMKNGLSRDFNPTATVKMLPTFVRPIPDGSEKGDFIALDLGGSSFRILRVQVNHEKNQNVHMESEVYDTPENIVHGSGSQLFDHVAECLGDFMEKRKIKDKKLPVGFTFSFPCQQSKIDEAILITWTKRFKASGVEGADVVKLLNKAIKKRGDYDANIVAVVNDTVGTMMTCGYDDQHCEVGLIIGTGTNACYMEELRHIDLVEGDEGRMCINTEWGAFGDDGSLEDIRTEFDREIDRGSLNPGKQLFEKMVSGMYLGELVRLILVKMAKEGLLFEGRITPELLTRGKFNTSDVSAIEKNKEGLHNAKEILTRLGVEPSDDDCVSVQHVCTIVSFRSANLVAATLGAILNRLRDNKGTPRLRTTVGVDGSLYKTHPQYSRRFHKTLRRLVPDSDVRFLLSESGSGKGAAMVTAVAYRLAEQHRQIEETLAHFHLTKDMLLEVKKRMRAEMELGLRKQTHNNAVVKMLPSFVRRTPDGTENGDFLALDLGGTNFRVLLVKIRSGKKRTVEMHNKIYAIPIEIMQGTGEELFDHIVSCISDFLDYMGIKGPRMPLGFTFSFPCQQTSLDAGILITWTKGFKATDCVGHDVVTLLRDAIKRREEFDLDVVAVVNDTVGTMMTCAYGEPTCEVGLIVGTGSNACYMEEMKNVEMVEGDQGQMCINMEWGAFGDNGCLDDIRTHYDRLVDEYSLNAGKQRYEKMISGMYLGEIVRNILIDFTKKGFLFRGQISETLKTRGIFETKFLSQIESDRLALLQVRAILQQLGLNSTCDDSILVKTVCGVVSRRAAQLCGAGMAAVVDKIRENRGLDRLNVTVGVDGTLYKLHPHFSRIMHQTVKELSPKCNVSFLLSEDGSGKGAALITAVGVRLRTEASS。

[0075] It should be noted that among the above-mentioned biomarkers, any one of them can be used alone as a basis for evaluating the spermatogenesis ability of patients with pituitary stalk interruption syndrome after spermatogenesis induction or spermatogenesis treatment. However, due to the possibility of misjudgment of a single biomarker, in order to improve the accuracy and reliability of diagnosis, a more preferred solution is to combine these ten biomarkers as biomarkers for evaluating the spermatogenesis ability of patients with pituitary stalk interruption syndrome after spermatogenesis induction or spermatogenesis treatment.

[0076] In an embodiment of the present invention, there is provided a use of a reagent for quantitatively detecting the above-mentioned biomarker in the preparation of a kit or a detection device for evaluating spermatogenesis in pituitary stalk interruption syndrome.

[0077] In a specific embodiment of the present invention, the reagents contained in the kit can be set according to the detection means of each biomarker. This means that for the ten different biomarkers C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2, and B3KXY9, specific methods and reagents suitable for their detection can be selected.

[0078] Since these ten biomarkers are all known substances, there are already extensive and reliable detection methods in the prior art. For example, immunological methods such as enzyme-linked immunosorbent assay (ELISA), immunofluorescence analysis, etc. can be used to detect the content of these biomarkers. Molecular biology techniques such as polymerase chain reaction (PCR), in situ hybridization, etc. can also be used to detect the gene expression levels of these biomarkers. In addition, mass spectrometry analysis and other means can also be used.

[0079] Based on the rich experience and mature methods of the prior art, the most suitable method can be selected to detect the above-mentioned biomarkers with reference to the existing detection means and reagents. Then, according to the selected detection method, a corresponding diagnostic kit or detection device can be designed according to the standards and procedures of the prior art.

[0080] ELISA is a commonly used method for detecting biomarkers. It uses specific antibodies to bind to the biomarkers to be detected, and then generates a measurable signal through the reaction of enzymes. The ELISA method has high sensitivity and specificity and can be applied to the detection of single biomarkers or multiple biomarkers.

[0081] Immunofluorescence analysis uses fluorescently labeled antibodies to bind to the biomarkers to be detected, and detects the intensity of the fluorescent signal through a fluorescence microscope or a fluorometer to quantitatively analyze the amount of the biomarkers present.

[0082] Mass spectrometry can perform accurate quantitative analysis of biomarkers, including methods such as proton nuclear magnetic resonance (NMR) and mass spectrometry (MS), which can provide very precise molecular structure and relative content information.

[0083] The PCR technique can be used to detect the transcribed RNA of biomarkers. The RNA or its fragment to be detected is amplified by PCR, and then quantitative analysis is carried out by methods such as gel electrophoresis or real-time fluorescence quantitative PCR.

[0084] Protein chip technology can detect multiple biomarkers simultaneously. By immobilizing a variety of antibodies on the chip surface and then binding them to the proteins in the sample to be detected (such as tissue), the biomarkers are finally detected through signals of fluorescence or radioactive labeling.

[0085] Exemplarily, considering the detection efficiency and convenience, the kit can be an ELISA kit.

[0086] In another embodiment of the present invention, there is provided an application of the above-mentioned biomarker in the spermatogenesis induction or spermatogenesis ability after spermatogenesis treatment of patients with pituitary stalk interruption syndrome for non-prognostic assessment, pathological diagnosis or treatment purposes. The spermatogenesis ability after spermatogenesis induction or spermatogenesis treatment of patients with pituitary stalk interruption syndrome for non-prognostic assessment, pathological diagnosis or treatment purposes can be for purposes such as scientific research, non-medical commercial detection or testing.

[0087] For example, biomarkers for evaluating the spermatogenesis ability after spermatogenesis induction or spermatogenesis treatment of patients with pituitary stalk interruption syndrome can be used to study the disease occurrence mechanism, pathophysiological process and potential therapeutic targets. By analyzing the changes of these biomarkers in the disease process, the development mechanism of the disease can be deeply understood, providing a deeper understanding for the prevention and treatment of the disease.

[0088] Biomarkers also play an important role in the drug R & D process. They can be used as indicators for evaluating drug efficacy, helping researchers evaluate the safety and effectiveness of new drugs. By monitoring the impact of drugs on biomarkers, potential drug toxicity and adverse reactions can be detected early, and the adjustment and optimization of drug dosage can be guided.

[0089] Biomarkers can also be used in individual health management and preventive medicine. By regularly monitoring specific biomarkers, changes in individual health status can be detected in a timely manner, the risk of diseases can be predicted, and corresponding health management measures can be taken, such as adjusting lifestyle, eating habits or drug treatment, to maintain health and delay the progression of diseases.

[0090] Biomarkers can be used to evaluate the impact of lifestyle on health. By monitoring changes in these markers, the impact of different lifestyles on health can be assessed, and individuals can be guided to adopt appropriate lifestyle intervention measures, such as weight loss, smoking cessation, increased physical activity, etc., thereby improving health status and reducing disease risk.

[0091] In another embodiment of the present invention, a method for screening biomarkers is provided, specifically including:

[0092] (1) Extract the sample and use it for proteomic analysis; the sample is semen after spermatogenesis treatment (double stimulation / pump treatment) for PSIS disease;

[0093] (2) According to the main differential results, combined with the protein database, calibrate the protein id;

[0094] (3) Use the subject sample characteristics to analyze the differential proteins, and use the random forest machine learning method to evaluate and rank the important variables to screen spermatogenesis efficacy biomarkers.

[0095] (4) Use ROC curve, confusion matrix visualization, sample dimensionality reduction map, etc. to verify whether the biomarker can effectively judge spermatogenesis in PSIS patients.

[0096] The present invention also provides a method for evaluating the spermatogenesis induction or spermatogenesis ability after spermatogenesis treatment in patients with pituitary stalk interruption syndrome. The key to this method is to detect the levels of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 in the semen of subjects with pituitary stalk interruption syndrome.

[0097] First, the implementation of this method involves sample collection and processing. Samples are extracted from the semen of the subject, and this process needs to follow strict standard operating procedures to ensure the quality and integrity of the samples.

[0098] Secondly, for the obtained semen samples, appropriate techniques and reagents can be selected to detect the levels of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 in the semen. These detection methods can be immunological techniques, such as ELISA, immunofluorescence analysis, etc., or molecular biology techniques, such as PCR, in situ hybridization, etc., or mass spectrometry means, etc. Through these methods, the content level of a certain biomarker in the semen of the subject can be accurately quantified.

[0099] After obtaining the test results of the biomarker, it is necessary to compare and analyze them with the relevant data in normal subjects. Based on these comparison results, the spermatogenic ability of the subject after spermatogenesis induction or spermatogenesis treatment can be judged. If the level of a certain biomarker or biomarker combination is significantly close to the normal range, it can be inferred that the subject has a relatively high probability of improved spermatogenic ability.

[0100] The reliability and accuracy of this method depend on the sensitivity and specificity of the selected detection method, as well as the determination of the reference range or threshold. Therefore, when implementing this method, it is necessary to strictly control the experimental conditions and, in combination with clinical practice experience and data analysis, interpret and diagnose the results.

[0101] The present invention provides a method for pre-evaluating whether a drug can be used to evaluate the spermatogenic ability of a patient with pituitary stalk interruption syndrome after spermatogenesis induction or spermatogenesis treatment, which includes using C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 as biomarkers to evaluate the effect of the drug, so as to achieve the purpose of precision medicine.

[0102] The implementation of this method needs to start from experimental design and sample collection. In the design stage of a study or clinical trial, it is necessary to clarify the drug, treatment plan and evaluation indicators to be evaluated. At the same time, it is necessary to determine the selection criteria for the subjects and collect corresponding biological samples, such as semen samples, for subsequent experimental analysis.

[0103] After obtaining the biological sample, appropriate techniques and reagents can be used to detect the level of the selected biomarker. These detection methods can be immunological techniques, such as ELISA, immunofluorescence analysis, etc., or molecular biology techniques, such as PCR, in situ hybridization, etc., or mass spectrometry analysis. Through these methods, the content level of the biomarker in the biological sample of the subject can be accurately quantified.

[0104] Next, the drug or treatment plan needs to be applied to the subject and the treatment is carried out according to the predetermined plan. During the treatment process, it is necessary to regularly monitor the biological samples of the subject and repeatedly detect the level of the selected biomarker. This can timely understand the treatment effect of the drug and whether the expected treatment goal has been achieved.

[0105] Finally, based on the obtained test results, the therapeutic effect of the drug can be evaluated and determined. If the level of the selected biomarker has changed significantly and there is an obvious difference compared with that before treatment, it can be inferred that the drug may have the potential to improve the spermatogenic ability of the subject after spermatogenic induction or spermatogenic treatment. On the contrary, if the change in the biomarker level is not obvious or does not reach the expected effect, it may be necessary to re-evaluate the treatment plan or try other treatment strategies.

[0106] The present invention provides a method for screening compounds that can improve the spermatogenic ability of patients with pituitary stalk interruption syndrome after spermatogenic induction or spermatogenic treatment, which includes using C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 as biomarkers to evaluate the effect of the compound, so as to achieve the purpose of precision medicine.

[0107] First, the implementation of this method requires the establishment of a suitable experimental system and model. A cell line or animal model of pituitary stalk interruption syndrome can be used to simulate the physiological process of pituitary stalk interruption syndrome and evaluate the effect of the compound on it.

[0108] Secondly, select suitable biomarkers for evaluating the effect of the compound. C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 can reflect the biological process and pathological state of pituitary stalk interruption syndrome as biomarkers. Therefore, they can be used as biomarkers for screening the effect of the compound to evaluate the intervention effect of the compound on the spermatogenic ability of pituitary stalk interruption syndrome.

[0109] Next, conduct a screening experiment of the compound. Add the compound to be screened into cells or animals, and observe its effect on C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 in the semen of patients with pituitary stalk interruption syndrome. Appropriate techniques and reagents can be used to detect the levels of these biomarkers, such as immunological techniques and molecular biological techniques, etc. According to the test results, the potential therapeutic effect of the compound on the spermatogenic ability of pituitary stalk interruption syndrome can be preliminarily evaluated.

[0110] After obtaining the preliminary screening results, further verification and confirmation experiments can be carried out. By using a more refined and strict experimental design and operation process, the effect of the compound on the biomarker level can be verified, and its therapeutic effect on the spermatogenic ability of pituitary stalk interruption syndrome can be further evaluated.

[0111] Finally, based on the experimental results, further research and development are carried out on the compounds with potential therapeutic effects. Their pharmacological properties, toxic and side effects, pharmacokinetics and other drug attributes can be further evaluated, and preclinical studies and clinical trials can be conducted.

[0112] The following specific example of the present invention further demonstrates the selection principle, process and effect of the above-mentioned biomarkers, so as to facilitate those skilled in the art to understand the essence of the present invention.

[0113] In the following examples, the following are involved and used:

[0114] 1. Instruments

[0115] Vortex-Genie 2 type vortex mixer, SI Company, USA; Centrifuge 5424R type high-speed refrigerated centrifuge, Eppendorf Company, Germany; ABS-MS-078 type constant temperature mixer, Hefei Aibensen Scientific Instrument Co., Ltd.; Spectra Max plus384 type microplate reader, Molecular Devices Company, USA; LNG-T98 type freeze centrifugal concentration dryer, Taicang Huamei Biochemical Instrument Factory; LNG-T88 type desktop rapid centrifugal concentration dryer, Taicang Huamei Biochemical Instrument Factory; Tanon-3500R type automatic digital gel image analysis system, Shanghai Tianneng Technology Co., Ltd.; EPS-300 type digital display regulated power supply and constant current electrophoresis instrument, Shanghai Tianneng Technology Co., Ltd.; EASY-nLC 1200 type high performance liquid chromatograph, Fisher Company, USA; timsTOF Pro type tandem mass spectrometer, Bruker Company, Germany; MS105DU type analytical balance, Mettler Toledo Company, USA; Fielda-650D type ultrasonic cell disruptor, Jiangsu Bofield Intelligent Technology Co., Ltd.

[0116] 2. Reagents

[0117] Ammonia water (Sigma Company); IAM iodoacetamide (Sigma Company); Triethylammonium bicarbonate buffer (TEAB) (Sigma Company); Coomassie brilliant blue staining solution (Beyotime Company); Chromatographic pure chloroform (Wokai Company); Chromatographic pure pyridine (Aladdin Company); Chromatographic pure water (Fisher Company); Mass spectrometry grade Modified Trypsin protease (Promega Company), Pierce TMBCA Protein Assay Kit (Fisher); NUPAGE 10% BT GEL 1.0MM 12W (Fisher); Protease Inhibitor (Bimake); Protein Ladder (Pre-stained) (Fisher); Bond-Breaker TM TCEP Solution (Fisher); LC / MS Grade Water (Fisher); LC / MS Grade Acetonitrile (Fisher); LC / MS Grade Methanol (Fisher); LC / MS Grade Formic Acid (Fisher); LC / MS Grade Isopropanol (Fisher).

[0118] Example 1: Screening of Biomarkers

[0119] 1. Sample Source

[0120] PSIS diagnostic criteria: Meeting the typical magnetic resonance "triad" manifestations (pituitary stalk interruption / thinning, hypoplasia of the adenohypophysis, and ectopia / absence of the neurohypophysis) and having anterior pituitary hormone deficiency (including at least growth hormone deficiency and hypogonadotropic hypogonadism).

[0121] Specific inclusion criteria: (1) Male patients over 18 years old; (2) Meeting the PSIS diagnosis: Meeting the typical magnetic resonance "triad" manifestations (pituitary stalk interruption / thinning, hypoplasia of the adenohypophysis, and ectopia / absence of the neurohypophysis) and having anterior pituitary hormone deficiency (including at least growth hormone deficiency and hypogonadotropic hypogonadism); (3) Normal posterior pituitary function; (4) Strong desire for fertility and regular use of gonadotropin therapy.

[0122] Specific exclusion criteria: (1) Having received gonadotropin or GnRH pulsatile pump therapy before treatment; (2) Having received mhGH therapy within 1 year before treatment; (3) Less than 3 months of gonadotropin therapy; (4) Poor compliance; (5) Lost to follow-up or incomplete data.

[0123] Based on the above inclusion and exclusion criteria, all the samples screened in this invention are from patients in the outpatient department of the Endocrinology Department of Peking Union Medical College Hospital. All patients received dual gonadotropin / pump treatment for ≥6 months. Dual gonadotropin treatment refers to the treatment with gonadotropin + chorionic gonadotropin, and pump treatment refers to the continuous subcutaneous pulsatile infusion of gonadotropin-releasing hormone. Semen (plasma) samples of 20 patients with successful spermatogenesis treatment (successful spermatogenesis is defined as at least 1 motile sperm observed in the submitted semen sample under a microscope) and 7 patients with failed spermatogenesis treatment (failed spermatogenesis is defined as no motile sperm observed in the submitted semen sample under a microscope) were collected. All experiments related to clinical specimens were approved by the Ethics Committee of Peking Union Medical College Hospital. The demographic and clinical characteristics of all patients are shown in Table 1.

[0124] Table 1 Clinical characteristics of patients

[0125]

[0126]

[0127] Note: FSH: follicle-stimulating hormone; LH: luteinizing hormone; T: testosterone; E2: estradiol; PRL: prolactin; FT3: estradiol; FT4: prolactin; IGF1: insulin-like growth factor; * indicates P<0.05.

[0128] 2. Grouping

[0129] Since PSIS is a rare disease and the sample size is small, which is not suitable for sub-datasets. To make up for this deficiency, in this embodiment, the dataset is randomly divided into 10 subsets, and each data subset is used as the validation set in turn, and the other parts are used as the training set. After multiple training and validation evaluations, the performance differences of the model are obtained, so as to continuously optimize the model.

[0130] 3. Sample collection

[0131] For semen samples, patients are required to abstain from sexual intercourse for 2-7 days and then collect semen samples by masturbation. Sperm-related parameters are measured using computer-aided sperm analysis (SSA-II sperm automatic detection and analysis system, Beijing Suijia, China). Referring to the WHO "Laboratory Manual for the Examination and Processing of Human Semen" (5th Edition)

[201] , sperm motility is divided into rapid forward motility, slow forward motility, non-forward motility, and immotility (grades a, b, c, or d). The total sperm motility (%) is defined as WHO grades a + b + c, and the sperm forward motility rate (%) is WHO grades a + b.

[0132] 4. Sample processing

[0133] 4.1 Protein extraction

[0134] Take out all the samples in the frozen state and transfer them to MP oscillation tubes; add an appropriate amount of protein lysate (8M urea + 1% SDS, containing protease inhibitors); use a high-throughput tissue grinder to oscillate 3 times, 40s each time; lyse on ice for 30min, vortex and mix for 5 - 10s every 5 minutes during this period; centrifuge at 4℃, 12 000g for 30min, and collect the supernatant; then determine the protein content by the BCA method and operate strictly according to the BCA reagent instruction manual. After protein quantification, perform SDS-PAGE electrophoresis.

[0135] 4.2 Protease digestion

[0136] Take 100μg of protein sample, supplement the lysate, and add 100mM triethylammonium bicarbonate buffer (TEAB) at a final concentration; add tris(2-carboxyethyl)phosphine (TCEP) at a final concentration of 10mM and react at 37℃ for 60min; add iodoacetamide at a final concentration of 40mM and react in the dark at room temperature for 40min; add pre-cooled acetone (acetone: sample v:v = 6:1) to each tube and precipitate at -20℃ for 4h; centrifuge at 10 000g for 20min and take the precipitate; dissolve the sample thoroughly with 100μL of 100mM TEAB; add Trypsin at a mass ratio of 1:50 (enzyme: protein) and digest overnight at 37℃.

[0137] 4.3 Peptide desalting and quantification

[0138] After trypsin digestion, dry the peptides with a vacuum pump; dissolve the dried peptides after enzymatic digestion with 0.1% trifluoroacetic acid (TFA); desalt the peptides with HLB and dry with a vacuum concentrator; use the Thermo Fisher Scientific peptide quantification kit (product number 23275) to quantify the peptides.

[0139] 4.4 DIA mass spectrometry detection

[0140] After the samples are digested with trypsin, take an equal amount of peptides and dry them with a vacuum centrifugal concentrator; dissolve the peptides with 0.1% TFA, desalt them with HLB, and dry with a vacuum concentrator; use the Thermo Fisher Scientific (product number: 23275) peptide quantification kit to quantify the peptides.

[0141] Peptide separation was performed using a Vanquish Neo (Thermo) chromatograph. The analytical column was ES906 (150 μm × 15 cm, Thermo, USA). Mobile phase A was water (2% acetonitrile + 0.1% formic acid), mobile phase B was water (80% acetonitrile + 0.1% formic acid), the chromatographic gradient was 60 SPD, and the flow rate was 500 nL / min. The data acquisition software was Thermo Xcalibur 4.7 (Thermo, USA).

[0142] The sample after nano-scale high performance liquid chromatography separation was analyzed by an Orbitrap Astral mass spectrometer (Thermo).

[0143] The Orbitrap Astral mass spectrometer (Thermo) was operated in the DIA mode. The detection mode was positive ion, the ion source voltage was set at 1.5 kV, and the MS scan range (m / z) was 100 - 1700.

[0144] 4.5 DIA data analysis

[0145] The DIA raw data was imported into the Spectronaut TM 18 software system for database searching and analysis. Six peptides were selected for each protein and three sub-ions were selected for each peptide for quantitative analysis. The parameters were as follows: Protein FDR ≤ 0.01, Peptide FDR ≤ 0.01, Peptide Confidence ≥ 99%, XIC width ≤ 75 ppm. Shared peptides and modified peptides were excluded, and the quantitative results were obtained by calculating the peak area adduct.

[0146] 4.6 Bioinformatics analysis

[0147] All data was uploaded to the Majorbio Cloud Platform (cloud.majorbio.com) for analysis. The t.test function in R language was used to calculate the significance P value of the difference between groups and the fold change (FC). Proteins with a significance test p < 0.05 and a fold change greater than 2 times were differentially expressed proteins. The GO database (gene ontology, http: / / geneontology.org / ) was selected to perform GO annotation analysis and functional clustering analysis on all differentially expressed proteins from three aspects: biological process, cellular component, and molecular function; the KEGG (Kyoto encyclopedia of gene and genomes, http: / / www.genome.jp / kegg / / ) pathway database was used to analyze the metabolic pathways involved in the differentially expressed proteins. Protein-protein interaction analysis was performed using String v11.5.

[0148] 5. Results and Analysis

[0149] The variable importance ranking graph obtained by evaluating and ranking important variables using the random forest machine learning method is as shown Figure 1 below. Among them, the top ten substances are: C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2, B3KXY9. These ten substances can be preliminarily used as spermatogenesis efficacy markers.

[0150] By using proteomics technology to detect the protein expression levels of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2, B3KXY9 in the semen (plasma) of the subjects, the results are shown in Tables 2 and 3.

[0151] Table 2

[0152]

[0153] Table 3

[0154] Sample Number c t TV SC SCT SM A_451Z 1 0 5.5 0 0 0 A_658 1 0 6 0 0 0 A_669 1 0 12 0 0 0 A_684 1 0 12 0 0 0 A_712 1 0 2 0 0 0 A_717 1 0 6 0 0 0 A_723 1 0 5 0 0 0 A_308 0 1 12 40.61 15.62 63.3 A_309 0 1 8 43.76 15.63 22.33 A_392 0 1 15 96.87 44.03 11.3 A_420 0 1 12 4.77 2.17 23.41 A_428 0 1 12 39.22 8.17 38.6 A_429 0 1 12 5.55 1.79 22 A_431 0 1 10 36.11 25.79 15.41 A_439 0 1 12 113.95 26.5 28.31 A_451J 0 1 18 207.54 37.06 47.19 A_493 0 1 5 8.53 2.37 40.54 A_523 0 1 10 137.96 34.49 54.42 A_600 0 1 12 185.27 39.42 60.93 A_608 0 1 14 10.69 3.96 37.84 A_613 0 1 4 18.93 6.31 61.02 A_614 0 1 4 26.82 29.8 38.28 A_661 0 1 18 74.17 15.18 54.54 A_662 0 1 4 40.74 9.26 25.74 A_673 0 1 11 67.71 22.57 71.56 A_678 0 1 15 123.88 28.81 66.34 A_682 0 1 18 219.72 91.55 66.82 A_691 0 1 10 45.32 14.62 72.6 A_705 0 1 16.5 220.75 45.99 91.6 A_718 0 1 15 839.51 270.81 79.1

[0155] Note: SF: Spermatogenesis treatment failure group; SS: Spermatogenesis treatment success group; TV: Testicular size after treatment (clinically considered: the larger the testis, the stronger the spermatogenic ability); SC: Sperm count; SCT: Sperm concentration; Sm: Sperm motility.

[0156] As Figure 2 shown, the box plot shows the abundance of each selected protein between the SF group and the SS group.

[0157] As Figure 3 shown, from the box plot of the 10 markers, it can be seen that there are significant differences in the expression levels of the 10 markers between the SS group and the SF group.

[0158] As Figure 4 shown, from the ROC curves of the 10 markers, the AUC values of the 10 markers are AUC Q9NPF0 = 0.944, AUC Q9UJT2 = 0.913, AUC E9PAR0 = 0.901, AUC C9JFR7 = 0.988, AUC B4E1B2 = 0.919, AUC B3KXY9 = 0.938, AUCB3KQF0 = 0.913, AUC A8K878 = 0.938, AUC A0A8I5KXD3 = 0.913, AUC Q9Y230 = 0.888, which can be used as a biomarker.

[0159] Based on the above, the biomarkers determined for evaluating the spermatogenesis ability after spermatogenesis induction or spermatogenesis treatment in patients with pituitary stalk interruption syndrome are C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9. And an increase in the levels of the above biomarkers indicates an improvement in the spermatogenesis ability after spermatogenesis induction or spermatogenesis treatment in patients with pituitary stalk interruption syndrome.

[0160] Example 2: Verification of Biomarkers

[0161] Since PSIS is a rare disease and the sample size is small and not suitable for diversification, to make up for this deficiency, in this example, the dataset is randomly divided into 10 subsets, and each data subset is used as the validation set in turn, and the other parts are used as the training set. After multiple training and validation evaluations, the performance differences of the model are obtained, so as to continuously optimize the model.

[0162] All experiments related to clinical specimens were approved by the Ethics Committee of Peking Union Medical College Hospital. The collected semen samples of the subjects were directly placed into cryotubes, and the cryotubes were placed in a -80 °C refrigerator for storage and transported with dry ice. The method described in Example 1 was used to process the samples in the validation set. At the same time, sample dimensionality reduction plots, confusion matrix visualization, and ROC curves were used to verify whether the 10 biomarkers screened in Example 1 could effectively judge whether PSIS patients had spermatogenesis. The results are shown in Figures 5 - 8 . Comprehensive Figures 5 - 8 The results show that the AUC is 1, indicating good detection effect.

[0163] Example 3: ELISA Kit for Detecting the Spermatogenesis Ability after Spermatogenesis Induction or Spermatogenesis Treatment in Patients with Pituitary Stalk Interruption Syndrome

[0164] This example provides an ELISA kit for detecting the spermatogenesis ability after spermatogenesis induction or spermatogenesis treatment in patients with pituitary stalk interruption syndrome. The design of the kit aims to detect the content levels of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9 in the semen samples of the subjects, so as to achieve accurate diagnosis of the spermatogenesis ability after spermatogenesis induction or spermatogenesis treatment in patients with pituitary stalk interruption syndrome.

[0165] 1.1 Composition of the Kit:

[0166] (1) ELISA analysis of C9JFR7:

[0167] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting C9JFR7.

[0168] It is used to detect the content level of C9JFR7 in the semen samples of subjects and perform quantitative analysis according to the standard curve.

[0169] (2) ELISA analysis of B4E1B2:

[0170] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting B4E1B2.

[0171] It is used to detect the content level of B4E1B2 in the semen samples of subjects and perform quantitative analysis according to the standard curve.

[0172] (3) ELISA analysis of Q9NPF0:

[0173] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting Q9NPF0.

[0174] It is used to detect the content level of Q9NPF0 in the semen samples of subjects and perform quantitative analysis according to the standard curve.

[0175] (4) ELISA analysis of E9PAR0:

[0176] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting E9PAR0.

[0177] It is used to detect the content level of E9PAR0 in the semen samples of subjects and perform quantitative analysis according to the standard curve.

[0178] (5) ELISA analysis of A0A8I5KXD3:

[0179] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting A0A8I5KXD3.

[0180] It is used to detect the content level of A0A8I5KXD3 in the semen samples of subjects and perform quantitative analysis according to the standard curve.

[0181] (6) ELISA analysis of Q9Y230:

[0182] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting Q9Y230.

[0183] To detect the content level of Q9Y230 in the semen sample of a subject and perform quantitative analysis according to the standard curve.

[0184] (7) ELISA analysis of B3KQF0:

[0185] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting B3KQF0.

[0186] To detect the content level of B3KQF0 in the semen sample of a subject and perform quantitative analysis according to the standard curve.

[0187] (8) ELISA analysis of A8K878:

[0188] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting A8K878.

[0189] To detect the content level of A8K878 in the semen sample of a subject and perform quantitative analysis according to the standard curve.

[0190] (9) ELISA analysis of Q9UJT2:

[0191] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting Q9UJT2.

[0192] To detect the content level of Q9UJT2 in the semen sample of a subject and perform quantitative analysis according to the standard curve.

[0193] (10) ELISA analysis of B3KXY9:

[0194] It includes reagents and materials such as antibodies, standards, substrates, washing buffers, etc. for detecting B3KXY9.

[0195] To detect the content level of B3KXY9 in the semen sample of a subject and perform quantitative analysis according to the standard curve.

[0196] 1.2 The detection process can be as follows:

[0197] Take out the semen sample of the subject and perform specimen processing and pretreatment steps according to the kit instructions.

[0198] Add the pretreated sample into the respective ELISA plate wells and specifically react with the antibodies of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9.

[0199] Use the washing buffer to wash the plate wells to remove unbound substances.

[0200] Add the substrate and carry out the reaction under appropriate conditions to produce a measurable color.

[0201] Use an enzyme-labeled instrument to measure the absorbance of the reaction product, and calculate the contents of C9JFR7, B4E1B2, Q9NPF0, E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2, and B3KXY9 in the sample according to the standard curve.

[0202] According to the content levels of each biomarker and in combination with the preset diagnostic criteria, evaluate the changes in spermatogenic ability of the subject after spermatogenesis induction or spermatogenesis treatment.

[0203] As described above, it is only a preferred embodiment of the present invention and does not impose any form of limitation on the present invention. Although the present invention has been disclosed above with the preferred embodiment, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications within the scope of the technical solution of the present invention to form equivalent embodiments of equivalent changes. However, as long as it does not depart from the content of the technical solution of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A biomarker for evaluating spermatogenesis in pituitary stalk interruption syndrome, characterized in that: The biomarkers include C9JFR7, B4E1B2 and Q9NPF0.

2. The biomarker according to claim 1, characterized in that: The biomarkers also include any one, two, three or all of E9PAR0, A0A8I5KXD3, Q9Y230, B3KQF0, A8K878, Q9UJT2 and B3KXY9.

3. Use of a reagent for quantitatively detecting the biomarker according to claim 1 or 2 in the preparation of a kit or a detection device for evaluating spermatogenesis in pituitary stalk interruption syndrome.

4. The use according to claim 3, characterized in that The reagent is an antibody to the biomarker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatography analysis.

5. A kit for evaluating spermatogenesis in pituitary stalk interruption syndrome, characterized in that: Comprising reagents for detecting the biomarkers as claimed in claim 1 or 2, optionally, the detection is a quantitative detection of the level of the biomarkers in the semen of the subject.

6. The kit according to claim 5, characterized in that The reagent is an antibody to the biomarker, a primer for PCR, a reagent for mass spectrometry analysis, or a reagent for chromatography analysis.

7. Use of the biomarker as claimed in claim 1 or 2 in evaluating spermatogenesis in pituitary stalk interruption syndrome for non-disease diagnosis or treatment purposes.

8. Use of the biomarker according to claim 1 or 2 as a biomarker for spermatogenesis in pituitary stalk interruption syndrome in the preparation of a preparation for evaluating spermatogenesis in pituitary stalk interruption syndrome.

9. A method for evaluating whether a drug can be used for spermatogenesis in pituitary stalk interruption syndrome, characterized in that: The method comprises using the biomarker as described in claim 1 or 2 as a biomarker to evaluate the spermatogenic effect of the drug.

10. A method for screening a compound capable of promoting spermatogenesis in pituitary stalk interruption syndrome, characterized in that: The method comprises using the biomarker as described in claim 1 or 2 as a biomarker to evaluate the spermatogenic effect of the compound.

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