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CN113834889B - Pituitary stem blocking syndrome biomarker, and determination method and application thereof - Google Patents

Pituitary stem blocking syndrome biomarker, and determination method and application thereof Download PDF

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CN113834889B
CN113834889B CN202111147889.2A CN202111147889A CN113834889B CN 113834889 B CN113834889 B CN 113834889B CN 202111147889 A CN202111147889 A CN 202111147889A CN 113834889 B CN113834889 B CN 113834889B
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pituitary
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CN113834889A (en
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李永哲
郭野
李小刚
伍学焱
茅江峰
王曦
李昊隆
晏颂欣
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Peking Union Medical College Hospital Chinese Academy of Medical Sciences
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
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Abstract

The invention provides a pituitary stalk blocking syndrome biomarker which is one or more selected from pregnenolone sulfate, L-saccharin, MG (18:2 (9Z, 12Z)/0:0/0:0), heneicosanoic acid, glyceryl monostearate, hydroxy phenyllactic acid, D-xylo-ate, inositol, D-aspartic acid and PA (18:1_22:6). Also provides a determination method of the marker and application of the marker in preparation of a pituitary stem blocking syndrome diagnosis kit and/or reagent. The invention creatively provides a concept of diagnosing the pituitary stem blocking syndrome through the biomarker, provides the pituitary stem blocking syndrome biomarker, a specific determination method and application thereof, provides more choices and supports for the diagnosis of the pituitary stem blocking syndrome and the research thereof, has low cost and easy operation, and can be rapidly detected in batches.

Description

Pituitary stem blocking syndrome biomarker, and determination method and application thereof
Technical Field
The invention belongs to the field of biological identification, and particularly relates to a pituitary stem blocking syndrome biomarker, a determination method and application thereof.
Background
The pituitary shaft blocking syndrome (pituitary stalk interruption syndrome, PSIS) is a clinical syndrome in which hypothalamic secreted hormones cannot be transported to the posterior pituitary via the pituitary shaft and cannot act on the anterior pituitary via the pituitary portal system due to hypophysis deficiency or thinning. PSIS patients present with varying degrees of pituitary hormone deficiency. The retardation of growth and the deficiency of puberty are the main clinical manifestations. Early discovery, early diagnosis, and early treatment are critical to improving the symptoms of hormonal deficiency in patients, especially the development of height and gonads; if the diagnosis and treatment time is delayed, the growth and development are affected, and even the personality and the social psychology of the patient are seriously affected. Diagnosis of PSIS is difficult, the only imaging method that can be diagnosed is magnetic resonance imaging (Magnetic Resonance Imaging, MRI), but MRI diagnosis has the disadvantages of being expensive, difficult to operate, and not capable of rapid mass detection, and thus, there is a great clinical need for specific metabolites/markers associated with PSIS.
Disclosure of Invention
In order to solve the technical problems, the invention provides a pituitary shaft blocking syndrome biomarker. Meanwhile, the extraction method and the determination method of the marker are also provided. Also provided are uses of the biomarker in preparing a pituitary shaft blocking syndrome diagnostic kit and/or reagent. The invention creatively provides a concept of diagnosing the pituitary stem blocking syndrome through the biomarker, provides the pituitary stem blocking syndrome biomarker, a specific determination method and application thereof, provides more choices and supports for the diagnosis of the pituitary stem blocking syndrome and the research thereof, has low cost and easy operation, and can be rapidly detected in batches.
In order to achieve the above purpose, the present invention adopts the following technical scheme: a pituitary shaft blocking syndrome biomarker selected from one or more of pregnenolone sulfate, L-saccharin, MG (18:2 (9 z,12 z)/0:0/0:0), heneicosanoic acid (Heneicosanoic acid), glyceryl monostearate (1-Stearoyl-rac-glycol), hydroxy phenyllactic acid (Hydroxyphenyllactic acid), D-xylo-iso (D-Lyxose), inositol (myo-biositol), D-Aspartic acid (D-Aspartic acid), PA (18:1_22:6).
Preferably, the markers are derived from body fluids, such as semen, plasma, urine, and the like.
On the other hand, the invention provides a method for determining the marker, which comprises the following steps:
(1) Extracting a seminal plasma sample and performing metabolic analysis to determine the metabolic difference foreign bodies of PSIS patients and other types of male infertility patients;
(2) Extracting the seminal plasma sample and using the extracted sample for lipid analysis to determine main differential lipid types;
(3) The primary differential lipid species, combined with the multi-level mass spectrum information retrieval metabolite database, can preliminarily determine PSIS biomarkers;
(4) Significantly different metabolites were selected using subject work signature (ROC) analysis, and diagnostic panel models were optimized using multivariate exploratory ROC analysis, verifying whether the determined biomarkers could distinguish PSIS from other male infertility.
Preferably, in step (1), the concentrate sample is extracted with methanol/acetonitrile.
Preferably, in step (1), a pre-chilled methanol/acetonitrile/water solution (2:2:1, v/v) is mixed with 10 μl of sample and sonicated for 30 minutes. The sample was centrifuged at 14000g for 20 minutes at 4℃to obtain a supernatant. Then dried in a vacuum centrifuge and redissolved in 100. Mu.L acetonitrile/water (1:1, v/v). The samples were then centrifuged at 14000g for 15 minutes and the supernatant was used for metabonomic analysis.
Preferably, in step (2), 240. Mu.L of pre-chilled methanol, 200. Mu.L of water and 20. Mu.L of internal lipid standard mixture are homogenized with the concentrate sample; 800. Mu.L MTBE was added and sonicated for 20 minutes; then, the sample was centrifuged at 14000g for 15 minutes to obtain a supernatant; after drying under nitrogen, the sample was redissolved in 200 μl of 90% isopropanol/acetonitrile solution and centrifuged at 14000g for 15 min. The final supernatant was used for lipidomic analysis.
Either of the above-described schemes is preferred, in that the whole process of step (2) is carried out at a low temperature.
Preferably, in either of the above schemes, in steps (1) and (2), equal amounts of the supernatant of the refiner's pulp sample are mixed to prepare a Quality Control (QC) sample for determining instrument status and evaluating system stability throughout the experiment.
In either of the above embodiments, it is preferable that in both steps (1) and (2), the metabonomic analysis is performed using ultra high performance liquid chromatography-high resolution tandem mass spectrometry (UHPLC-HRMS/MS) analysis technique.
In any of the above schemes, preferably, in the steps (1) and (2), during the analysis of metabolome and lipidomic analysis, an ESI ion source is adopted and is scanned in positive and negative ion modes respectively, so as to obtain an overall metabolism profile of each sample and high-resolution primary and secondary mass spectrum information of each metabolite chromatographic peak in the overall metabolism profile; and performing main component analysis (PCA) on metabolites of the two groups of samples at three time points between the groups and in the groups, performing pattern recognition on the data, searching main metabolites causing differences between the groups and in the groups through load diagram and variable importance analysis, and searching a metabolite database according to multi-level mass spectrum information to perform structural identification of target metabolites.
In another aspect, the invention provides the use of a biomarker in the preparation of a PSIS diagnostic kit and/or reagent.
Preferably, the biomarker is any of the aforementioned markers.
The invention creatively provides a concept of diagnosing PSIS through the biomarker, provides a PSIS biomarker and a specific determination method and application thereof, provides more choices and supports for PSIS diagnosis and research thereof, has low cost and easy operation, and can be rapidly detected in batches.
Drawings
FIG. 1 is a non-target metabolome heat map of metabolites of PSIS patients and healthy controls with normal semen parameters.
FIG. 2 is a lipidomic thermogram of metabolites of PSIS patients and healthy controls with normal semen parameters.
FIG. 3 is a graph showing the combined diagnosis of PSIS vs HC pregnenolone and L-yeast amino acid for ROC.
FIG. 4 is a graph showing the combined diagnosis of PSIS vs nCHH pregnenolone and L-yeast amino acid for ROC.
FIG. 5 is a graph showing the combined diagnosis of PSIS vs VC pregnenolone and L-yeast amino acid for ROC.
Detailed Description
For a more complete and clear understanding of the present invention, reference is now made to the following descriptions taken in conjunction with the accompanying drawings.
The raw material information used in the invention is as follows: chromatographic grade ammonium fluoride, 2-propanol, ammonium acetate, formic acid, ammonium hydroxide, ammonium formate, acetonitrile, methyl tert-butyl ether (MTBE) were purchased from Sigma Aldrich; mass spectrum grade methanol was purchased from Thermo Fisher; the Q-Exactive Plus Orbitrap LC-MS/MS system is from Thermo Scientific; AB Triple TOF 6600 from AB Sciex (ma, usa); nexera LC-30A liquid chromatography System from SHIMADZU; ACQUITY UPLC BEH amide column (1.7 μm,2.1 mm. Times.100 mm) and ACQUITY UPLC CSH C column (1.7 μm,2.1 mm. Times.100 mm, from Waters Corporation (Milford, massachusetts, U.S.A.).
The case information in the present invention is as follows: male infertility patient: idiopathic hypogonadotropin hypogonadism (nCHH), varicocele (VC), pituitary shaft blocking syndrome (pituitary stalk interruption syndrome, PSIS) are all derived from male infertility patients diagnosed by beijing co-ordinates and hospital outpatient. Healthy control group is derived from Beijing co-ordination and clinic health physical examination crowd. All subjects and control groups met strictly the diagnostic criteria accepted by the international or professional society.
Example 1
This example provides PSIS diagnostic biomarkers that are pregnenolone sulfate and L-holo
Saccharin.
21 PSIS patients (BD group), 23 nCHH patients (HH group), 20 varicocele patients (VC group), and 23 healthy controls with normal semen parameters (HC group) were recruited from beijing synergetic hospitals. Diagnostic criteria include: (a) growth hormone deficiency; (b) Pituitary stalk loss or triad of thin, hypophysis and/or ectopic neural pituitary Magnetic Resonance Imaging (MRI). All patients and HC selected are Han population. Semen samples were produced by masturbation after a period of no less than 3 days of abstinence. The basic information of all participants is listed in table 1.
All PSIS patients had abnormal performance (100%). Their average age was 24.6±4.9 years. Many patients have semen that is not liquefied(10/21) and concentrate semen (9/21). The testis volume of PSIS patients is smaller (PSIS group 5.9+ -2.6 ml vs HC group 13.5+ -3.1 ml), sperm count is lower (PSIS group 20.4+ -29.4×10) 6 vs HC 229.4+ -118.6x10 6 ) Sperm concentration (PSIS group 8.7±13.2×10 6 96.1+ -55.2.10 per mL vs HC group 6 /mL) and sperm motility (PSIS group 33.9.+ -. 28.1% vs HC group 69.7.+ -. 12.3%). Luteinizing Hormone (LH) in PSIS patients (PSIS group 0.38+ -0.59 IU/L vs HC group 3.59+ -1.57 IU/L), serum Follicle Stimulating Hormone (FSH) (PSIS group 1.29+ -1.47 IU/L vs HC group 6.43+ -4.34 IU/L) and testosterone (T) (PSIS group 1.85+ -1.03 ng/mL vs. HC group 8.4+ -12.7 ng/mL) (Table 1).
TABLE 1 basic information of all participants
Abbreviations in the table: FSH, follicle stimulating hormone; LH, luteinizing hormone; t, testosterone; e2, estradiol; PRL, prolactin; FT3, estradiol; FT4, prolactin; IGF1, insulin-like growth factor.
The PSIS diagnostic biomarker of this example was determined by the following method.
First, the seminal plasma sample was extracted with methanol/acetonitrile. Briefly, a pre-chilled methanol/acetonitrile/water solution (2:2:1, v/v) was mixed with 10 μl of sample and sonicated for 30 minutes. The sample was centrifuged at 14000g for 20 minutes at 4℃to obtain a supernatant. Then dried in a vacuum centrifuge and redissolved in 100. Mu.L acetonitrile/water (1:1, v/v). The samples were then centrifuged at 14000g for 15 minutes and the supernatant was used for metabonomic analysis.
Next, 240. Mu.L of pre-chilled methanol, 200. Mu.L of water and 20. Mu.L of internal lipid standard mixture were homogenized with the concentrate sample. 800. Mu.L MTBE was added and sonicated for 20 minutes. The sample was then centrifuged at 14000g for 15 minutes to give a supernatant. After drying under nitrogen, the sample was redissolved in 200 μl of 90% isopropanol/acetonitrile solution and centrifuged at 14000g for 15 min. The final supernatant was used for lipidomic analysis. The whole process is carried out at low temperature.
During both of the above analyses, equal amounts of the supernatant of the refiner's pulp sample were mixed to prepare Quality Control (QC) samples. QC samples were used to determine instrument status and evaluate system stability throughout the experiment.
Quadrupole time of flight 6600 (AB Sciex) was used for metabonomics data acquisition. The lipidomic data acquisition was performed using the Q-Exactive Plus Orbitrap LC-MS/MS system (Thermo Scientific).
Metabonomics raw MS data were processed using ProteoWizard and XCMS software. The lipidomic raw MS data were processed using lipid searches, including peak identification, peak extraction, and lipid identification (secondary identification).
Data for normal distribution are expressed as mean (SD). Statistical analysis was performed using R packets. The univariate level t-test was used to measure the significance of the metabolites, with p-values <0.05 considered significant (significantly different). MetaboAnalyst 5.0 (Xia Lab@McGill Sweden) was used for chemometrics, clustering and biomarker analysis.
Metabonomics and lipidomic characteristics of PSIS patients were analyzed using the UPLC-MS method. In metabolomic profiling, many metabolites were altered (fig. 1, table 2). Many lipids, such as Triacylglycerols (TG), sphingomyelins (SM), phosphatidylethanolamine (PE), phosphatidylcholine (PC), and ceramides (Cer) were reduced in PSIS patients (fig. 2). Thus, based on the primary differential lipid species, in combination with the multi-level mass spectrometry information retrieval of the metabolite database, it can be initially determined that the PSIS biomarker can be PS.
TABLE 2 metabonomics results of PSIS group BD relative to control group HC
Similarly, BD vs nCHH, it could be initially determined that PSIS biomarkers could be L-saccharin.
In this example, pregnenolone Sulfate (PS) and L-saccharin were combined as potential biomarkers of PSIS.
Significantly different metabolites were selected using subject work characteristic (ROC) analysis. And the diagnostic panel model was optimized using multivariate exploratory ROC analysis, verifying whether the determined biomarkers Pregnenolone Sulfate (PS) and L-saccharin can distinguish PSIS from other male infertility.
As shown in fig. 3-5, by combining Pregnenolone Sulfate (PS) and L-saccharin, excellent differentiation was achieved: PSIS and HC (AUC=0.927, 95% Cl: 0.81-1); PSIS and nCHH (AUC=0.951, 95% Cl: 0.844-1); PSIS and VC (AUC=0.921, 95% Cl: 0.812-1). The results indicate that Pregnenolone Sulfate (PS) and L-saccharin are potential biomarkers for diagnosing PSIS.
The biomarkers pregnenolone sulfate and L-saccharin can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 2
Unlike example 1, BD vs nCHH, based on the major differential lipid species, combined with multi-level mass spectrometry information retrieval of the metabolite database, can initially determine that the PSIS biomarker can also be MG (18:2 (9 z,12 z)/0:0/0:0). The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 3
Unlike example 1, BD vs VC, based on the primary differential lipid species, in combination with multi-level mass spectrometry information retrieval of the metabolite database, can initially determine that the PSIS biomarker may also be eicosanoic acid. The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 4
Unlike example 1, BD vs nCHH, based on the major differential lipid species, in combination with multi-level mass spectrometry information retrieval of the metabolite database, can determine that the PSIS biomarker can also be glycerol monostearate. The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 5
Unlike example 1, BD vs HC, based on the major differential lipid species, in combination with multi-level mass spectrometry information retrieval of the metabolite database, can determine that the PSIS biomarker can also be hydroxyphenyllactic acid. The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 6
Unlike example 1, BD vs VC, based on the primary differential lipid species, in combination with multi-level mass spectrometry information retrieval of the metabolite database, can determine that the PSIS biomarker can also be D-xylo-iso. The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 7
Unlike example 1, BD vs HC, based on the major differential lipid species, in combination with multi-level mass spectrometry information retrieval of the metabolite database, can determine that the PSIS biomarker can also be inositol. The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 8
Unlike example 1, BD vs VC, based on the primary differential lipid species, in combination with multi-level mass spectrometry information retrieval of the metabolite database, can determine that the PSIS biomarker can also be D-aspartic acid. The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
Example 9
Unlike example 1, BD vs nCHH, based on the major differential lipid species, combined with multi-level mass spectrometry information retrieval of the metabolite database, can determine that the PSIS biomarker can also be PA (18:1_22:6). The PSIS can be distinguished from other types of male infertility patients by ROC validation. The marker can be used for preparing a PSIS diagnostic kit and/or a reagent.
The AUC (area under the curve) in examples 2-9 is shown in Table 3, and by AUC values, it can be seen that MG (18:2 (9Z, 12Z)/0:0/0:0), heneicosanoic acid, glycerol monostearate, hydroxy phenyllactic acid, D-xylo-iso-Inositol, myo-Inositol, D-aspartic acid, PA (18:1_22:6) can be used as potential markers for PSIS.
TABLE 3 AUC of ROC curves for PSIS vs. different marker small molecules
Example 10
Unlike example 1, the samples were from plasma. The extraction method and the determination method are the same as in example 1, and the final results are also substantially the same.
Example 11
Unlike example 1, the sample was derived from urine. The extraction method and the determination method are the same as in example 1, and the final results are also substantially the same.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (7)

1. Use of a biomarker in the preparation of a kit and/or a reagent for diagnosing pituitary shaft blocking syndrome, wherein the biomarker is selected from one or more of pregnenolone sulfate, L-saccharin, MG (18:2 (9 z,12 z)/0:0/0:0), heneicosanoic acid, glycerol monostearate, hydroxy phenyllactic acid, D-xylosose, inositol, D-aspartic acid, PA (18:1_22:6), the method for determining the biomarker comprising the steps of:
(1) Extracting the sample and performing metabolic analysis to determine the metabolic difference and foreign bodies between the pituitary shaft blocking syndrome patient and other types of male infertility patients; the sample is body fluid, and is one of semen, blood plasma or urine;
(2) Extracting the sample and using the sample for lipid analysis to determine the main differential lipid species;
(3) Searching a metabolite database according to main differential lipid types and combining multi-stage mass spectrum information to preliminarily determine pituitary stem blocking syndrome biomarkers;
(4) Significantly different metabolites were selected using subject work profiling and diagnostic panel models were optimized using multivariate exploratory ROC analysis, verifying whether the determined biomarkers could distinguish pituitary shaft blocking syndrome from other male infertility.
2. The use according to claim 1, characterized in that: in step (1), the seminal plasma sample is extracted with methanol/acetonitrile.
3. The use according to claim 2, characterized in that: in step (1), pre-chilled methanol/acetonitrile/water solution (2:2:1, v/v) was mixed with 10 μl of sample and sonicated for 30 minutes; centrifuging the sample at 14000g for 20 minutes at 4 ℃ to obtain a supernatant; then dried in a vacuum centrifuge and redissolved in 100. Mu.L acetonitrile/water (1:1, v/v); the samples were then centrifuged at 14000g for 15 minutes and the supernatant was used for metabonomic analysis.
4. A use according to claim 3, characterized in that: in step (2), 240 μl of pre-chilled methanol, 200 μl of water, and 20 μl of internal lipid standard mixture are homogenized with the seminal plasma sample; 800. Mu.L MTBE was added and sonicated for 20 minutes; then, the sample was centrifuged at 14000g for 15 minutes to obtain a supernatant; after drying under nitrogen, the sample was redissolved in 200 μl of 90% isopropanol/acetonitrile solution and centrifuged at 14000g for 15 min; the final supernatant was used for lipidomic analysis.
5. The use according to claim 4, characterized in that: the whole process of the step (2) is carried out at a low temperature.
6. The use according to claim 5, characterized in that: in steps (1) and (2), equal amounts of supernatant from the refiner's plasma sample are mixed to prepare a quality control sample for determining instrument status and evaluating system stability throughout the experiment.
7. The use according to claim 6, characterized in that: in the steps (1) and (2), the metabonomics analysis is carried out by adopting an ultra-high performance liquid chromatography-high resolution tandem mass spectrometry technology; in the steps (1) and (2), during metabolome and lipidomic analysis, an ESI ion source is adopted and is scanned in positive and negative ion modes respectively, so that an overall metabolism profile of each sample and high-resolution primary and secondary mass spectrum information of each metabolite chromatographic peak are obtained; and (3) performing main component analysis of metabolites at three time points between groups and in the groups on the two groups of samples, performing pattern recognition on the data, searching main metabolites causing differences between the groups and in the groups through load diagram and variable importance analysis, searching a metabolite database according to multi-level mass spectrum information, performing structural identification of target metabolites, and determining pituitary handle blocking syndrome biomarkers.
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