CN114196748B - Early-stage acute pancreatitis prediction biomarker, prediction model and construction method thereof - Google Patents
Early-stage acute pancreatitis prediction biomarker, prediction model and construction method thereof Download PDFInfo
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Abstract
The invention provides an early-stage acute pancreatitis prediction biomarker, a prediction model and a construction method thereof, wherein the obvious correlation between three differential expression exosome mic-RNAs markers and acute pancreatitis is obtained by analyzing the expression levels of exosome microRNAs-Novel 1, novel2 and Novel3 of acute pancreatitis patients, and a prediction model C is constructed micRNA = (-9.552) +0.025 x novel1+2.033 x novel2+2.384 x novel3; the Novel1, the Novel2 and the Novel3 are the relative expression amounts of the secretion microRNAs in the serum of the sample to be tested, are used for prognosis evaluation and early screening of patients suffering from acute pancreatitis, and are beneficial to providing more accurate prognosis and diagnosis information for the patients.
Description
Technical Field
The invention relates to the technical field of biology, relates to the technical field of disease prediction, and in particular relates to an acute pancreatitis early-stage prediction biomarker, a prediction model and a construction method thereof.
Background
Acute pancreatitis is a disease that seriously threatens human health and life, and the incidence rate is on the rise. Acute pancreatitis can be defined as both the type of mild acute pancreatitis (Mild acute pancreatitis, MAP) and severe acute pancreatitis (Severe acute pancreatitis, SAP) according to its clinical characteristics. Although these types of mechanisms of occurrence and development share common features from a pathophysiological perspective, including recruitment and activation of neutrophils, production of various cytokines and vascular actives, and activation of related signaling pathways, the course and severity of two acute pancreatitis (Acute pancreatitis, AP) are diametrically opposed. More than 20% of acute pancreatitis APs can gradually become malignant to SAP with severe complications such as pancreatic necrosis, systemic Inflammatory Response Syndrome (SIRS) and even multiple organ dysfunction syndrome (Multiple organ dysfunction syndrome, MODS), with an overall mortality of about 40%. Thus, if SAP patients can be predicted early, more aggressive medical support is given early in the disease, which is significant for improving SAP disease outcome. Although some clinical practice guidelines currently suggest the use of scoring systems to predict the severity of AP onset, such as the Ranson scoring system, the acute physiological and chronic health detection (APACHE) system, and the bedside index of AP severity (bispa). These scoring systems are not only complex to operate, but the prediction efficiency is still further improved. In addition, scholars have suggested using clinical parameters such as CRP, PCT, blood Urea Nitrogen (BUN), creatinine (SCr) and the like to predict the severity of acute pancreatitis. But it appears to be undesirable from a clinical practice point of view, and therefore more effective early predictive molecular markers remain to be discovered.
The exosomes are usually circular or oval in shape and have lipid membranes. Exosomes may carry a variety of proteins, nucleic acids, including long coding RNAs (long non-coding RNAs, lncRNAs), circular RNAs (circular RNAs), smiling RNAs (micro RNAs), and mRNAs, among others. During extracellular circulation, exosomes can be taken up by other cells, which in turn regulate various functions of the cells, such as autophagy, cellular homeostasis, via the proteins, nucleic acids they carry. microRNAs are endogenous non-coding RNAs, and can regulate the expression level of genes after transcription, thereby regulating the occurrence and development of diseases.
Disclosure of Invention
Aiming at the problems in the background technology, the invention provides an acute pancreatitis early-stage prediction biomarker, a prediction model and a construction method thereof, wherein the obvious correlation between three differential expression exosome mic-RNAs markers and acute pancreatitis is obtained by analyzing the expression levels of the exosome microRNAs-Novel 1, novel2 and Novel3 of acute pancreatitis patients, and the prediction model is constructed for prognosis evaluation and early screening of the acute pancreatitis patients, so that more accurate prognosis and diagnosis information can be provided for the patients.
In order to achieve the above purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides an early-stage acute pancreatitis predictive molecular marker comprising any one or a combination of at least two of exocrine micrornas-Novel 1, micrornas-Novel 2, or micrornas-Novel 3;
the microRNAs-Novel 1 has a sequence shown in SEQ ID NO.1 in a sequence table:
the microRNAs-Novel 2 has a sequence shown as SEQ ID NO.2 in a sequence table;
the microRNAs-Novel 3 has a sequence shown as SEQ ID NO.3 in the sequence table.
In a second aspect, the present invention provides an early-stage predictive model of acute pancreatitis, the predictive model being: c (C) micRNA = (-9.552) +0.025 x novel1+2.033 x novel2+2.384 x novel3; the Novel1, the Novel2 and the Novel3 are the relative expression amounts of the secretion microRNAs-Novel 1, the microRNAs-Novel 2 and the microRNAs-Novel 3 in serum of a sample to be detected respectively.
In a third aspect, the present invention provides a method for constructing an early-stage predictive model of acute pancreatitis according to the second aspect, the method comprising the steps of:
(1) Separating and screening serum sample seeds of acute pancreatitis patients to obtain serum exosomes;
(2) Further extracting and identifying three microRNAs, namely Novel1, novel2 and Novel3, in qualified exosomes, and detecting the relative expression quantity of the three microRNAs by using an RT-qPCR method;
(3) And modeling the three differential expressed microRNAs by adopting two logistic regression, and constructing a prediction model equation according to a multi-factor logistic regression result.
In a fourth aspect, the present invention provides the use of an acute pancreatitis early-stage predictive molecular marker as described in the first aspect for preparing an acute pancreatitis diagnostic reagent.
Compared with the prior art, the invention has the following advantages:
(1) The markers exocrine microRNAs-Novel 1, microRNAs-Novel 2 and microRNAs-Novel 3 have obvious correlation with acute pancreatitis, and the three differential expressed microRNAs are used as biomarkers for early prediction of SAP, have very good efficacy in early prediction of SAP disease condition in single detection or combined detection, and are more obvious in combined detection.
(2) The differential relative expression quantity of exocrine microRNAs-Novel 1, microRNAs-Novel 2 or microRNAs-Novel 3 is used as a variable to construct a prediction model C micRNA As a prediction model of acute pancreatitis, the probability of the AP patient developing into SAP is determined according to a well-established fitting curve, so that a high-risk patient is captured early, more positive intervention is given early, and the specificity and accuracy of early diagnosis of severe acute pancreatitis can be greatly improved.
Drawings
FIG. 1A shows basic information of three types of microRNAs; FIG. 1B shows the sequence structure of three kinds of microRNAs.
Fig. 2A exosome morphology under transmission microscopy (arrow shows exosomes); figure 2B exosome size distribution.
FIG. 3A is a box plot of the relative expression levels of Novel1 in Non-SAP and SAP groups; FIG. 3B is a box plot of the relative expression levels of Novel2 at Non-SAP and SAP groups; FIG. 3C is a box plot of the relative expression levels of Novel3 in Non-SAP and SAP groups.
Fig. 4C micRNA Comparison of the model with the ability of three microRNAs to predict alone and to predict the Ranson score.
Detailed Description
The following describes specific embodiments of the present invention in detail. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
Specific examples:
the present team collected plasma samples of 4 SAPs and 4 healthy subjects in previous studies and found large amounts of micro RNAs (micrornas) from plasma exosomes. Three differentially expressed micrornas were identified in the exosomes of SAP patients compared to healthy controls, respectively down-regulated Novel1, up-regulated Novel2, 3, and it was speculated that these three differentially expressed micrornas would be promising as biomarkers for early prediction of SAP. The basic information of these three microRNAs is shown in FIG. 1.
The microRNAs-Novel 1 has a sequence shown in SEQ ID NO.1 in a sequence table:
CAGGGCUGGGCUGGAAUUUUAAGAAAGGUGGCCAAGGUGGGGUUUGCU；
the microRNAs-Novel 2 has a sequence shown in SEQ ID NO.2 in a sequence table:
UUUCAUGUUCUCACUCAUGUAUGAUAGCUAAAAACGUUGAUCUCAUAGAGGGAGAGAAUGGAAUA；
the microRNAs-Novel 3 has a sequence shown as SEQ ID NO.3 in the sequence table.
AGCGGGGCUGGUGGCAUUUUGUUUCCAGUUCUGCACU。
Therefore, by further collecting blood plasma of SAP patients, three kinds of microRNAs are found to have good efficacy in early prediction of SAP illness state in single detection or combined detection after extracting and detecting microRNAs in exosomes, and the three kinds of microRNAs are more remarkable in combined detection.
1. AP patient data is collected.
Inclusion criteria: (1) AP diagnostics meet the international consensus of atlanta revised in 2012; (2) comprising the required clinical parameters: sex, height, weight, blood fat, 5 indexes (age, blood sugar, aspartate aminotransferase, lactate dehydrogenase, white blood cell count) required by a Ranson scoring system, 6 indexes (blood calcium, oxygen partial pressure, alkali deficiency, blood urea nitrogen, hematocrit, body fluid loss amount) of 48 hours of admission, and the like; (3) three differentially expressed microRNAs were detected in plasma exosomes within 24h after admission; (4) the study was enrolled and informed consent was signed.
Exclusion criteria: AP that has been treated prior to admission; the AP attack distance admission time is more than 48 hours; acute exacerbation phase of chronic pancreatitis; serious heart, lung, kidney diseases, rheumatic immune system diseases, metabolic diseases and other basic diseases; a history of trauma within one month; incomplete clinical data; excluding patients who need surgical treatment one month before and after admission; patients with malignant tumor and the like; patients with special medical history such as immunosuppressant, hormone, etc. can take the medicine for a long time.
The enrolled patients were divided into Non-SAP groups and SAP groups, wherein SAP met one of the following conditions: there are localized complications such as pancreatic necrosis, pancreatic abscess, pseudocyst, etc.; organ failure; CT classification class II or above. The remaining inclusion objects included the Non-SAP group.
2. Constructing a predictive model
The specific method comprises the following steps: the fasting venous blood of 108 AP patients on the day of admission was collected, 4mL was withdrawn respectively, and centrifuged at a centrifugation radius of 6cm and 3000r/min for 12min, and the supernatant was collected. The total miRNA in the supernatant is extracted by using a miRcute miRNA extraction and separation kit (product number: DP501, TIANGEN), and the above process is especially clean, so that the miRNA is prevented from being polluted by RNase in the air, and the miRNA is decomposed, so that the detection accuracy is affected. The total miRNA extracted was then reverse transcribed into cDNA using the miRNA first strand cDNA synthesis kit (stem-loop method) (cat. No.: MR101-01, vazyme), and qPCR was performed using ChamQ Universal SYBR qPCR Master Mix (cat. No.: Q711-02, vazyme) to detect the relative expression levels of each miRNA (specific primers used in the qPCR process are shown in Table 1). Meanwhile, U6 is used as an internal reference gene. By 2 -ΔΔCt Method for calculating miRNAExpression level.
Table 1 primer sequences for qPCR detection of three miRNA lines
Serum exosomes are obtained by separating and screening serum sample seeds of acute pancreatitis patients, the result of a transmission microscope is shown in fig. 2 (A), the exosomes are round particles with double-layer membrane structures, the diameter of most examples is in the range of 30-150nm, and the size identification result of the exosomes in the study is shown in fig. 2 (B).
Then further extracting and identifying three microRNAs of Novel1, novel2 and Novel3 in qualified exosomes, and detecting their relative expression amounts by RT-qPCR method, and obtaining the result (2) -ΔΔCt ) The box diagram is presented as shown in fig. 3.
Two-term logistic regression modeling is adopted for the three differential expression microRNAs, and a prediction equation C is constructed according to the multi-factor logistic regression result micRNA ＝(-9.552)+0.025*Novel1+2.033*Novel2+2.384*Novel3。
The severity of AP was predicted early by the relative expression levels of three microRNAs, novel1, novel2, novel3, whose ROC curve is shown in FIG. 4.
3. Conclusion(s)
The markers exocrine microRNAs-Novel 1, microRNAs-Novel 2 and microRNAs-Novel 3 have obvious correlation with acute pancreatitis, and the three differential expressed microRNAs are used as biomarkers for early prediction of SAP, have very good efficacy in early prediction of SAP disease condition in single detection or combined detection, and are more obvious in combined detection.
The differential relative expression quantity of exocrine microRNAs-Novel 1, microRNAs-Novel 2 or microRNAs-Novel 3 is used as a variable, a prediction model CmicRNA is constructed as a prediction model of acute pancreatitis, and the probability of an AP patient developing into SAP is determined according to a well-established fitting curve, so that a high-risk patient is captured early, more positive intervention is given early, and the early diagnosis specificity and accuracy of severe acute pancreatitis can be greatly improved.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made therein without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
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<120> an acute pancreatitis early-stage prediction biomarker, a prediction model and a construction method thereof
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Claims (1)
1. An acute pancreatitis early-stage prediction molecular marker combination, which is characterized by comprising exosomes of microRNAs-Novel 1, microRNAs-Novel 2 and microRNAs-Novel 3;
the microRNAs-Novel 1 is shown in a sequence table SEQ ID NO. 1;
the microRNAs-Novel 2 is shown in a sequence table SEQ ID NO. 2;
the microRNAs-Novel 3 is shown in a sequence table SEQ ID NO. 3.
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| JP2006226795A (en) * | 2005-02-16 | 2006-08-31 | Tokyo Univ Of Science | Diagnostic marker of acute pancreatitis |
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