KR101361546B1 - Computer readable medium recorded computer program to perform method for estimating reason for Hereditary Skeletal Muscle Channelopathy - Google Patents
Computer readable medium recorded computer program to perform method for estimating reason for Hereditary Skeletal Muscle Channelopathy Download PDFInfo
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Abstract
A computer readable recording medium containing a computer program and an apparatus for executing the same are provided. The computer program included in this recording medium can perform the method of predicting the cause of hereditary skeletal muscle ion channel disease by determining the cause gene of hereditary skeletal muscle ion channel disease by using symptom information of accidental paralysis and myotonia. The cause of the disease can be predicted quickly and accurately. Therefore, the user can determine the cause of hereditary skeletal muscle ion pathway disease by examining only some genes among various cause genes, and can identify the cause of hereditary skeletal muscle ion pathway disease in a short time at low cost.
Description
The present invention relates to a computer-readable recording medium and a device for executing the same. More particularly, the present invention relates to a computer-readable recording medium and a device for executing the same. will be.
Functional abnormalities of potassium ion channel genes have been identified in patients with familial hypokalemia. Familial hypokalemic periodic paralysis is an autosomal dominant hereditary disease characterized by reversible loosening muscle paralysis accompanied by intermittent hypokalemia.
This is a kind of symptom of typical ion channel disease (or ion channel disease), but as with most channel diseases, it is still difficult and complicated to identify the exact pathogenesis.
However, we have recently identified the effects of mutations in the sodium ion and calcium ion channel genes that are known to be the cause of familial hypokalemia and other genes that may be related.
This suggests a new pathogenesis of the disease, revealing that functional abnormalities of potassium ion channel genes, which are closely related to the disease, are actually occurring in patients.
This is a very important data for understanding the pathogenesis of various ion channel diseases including familial hypokalemia.
As such, Hereditary Skeletal Muscle Channelopathy occurs due to genetic defects in skeletal muscle ion channel proteins.
However, gene mutations in ion channel proteins that are responsible for hereditary skeletal muscle ion channel diseases have a large amount of phenotypes (clinical symptoms), and their phenotypes and genotypes are so diverse that it is necessary to search for the genes that are responsible for time and time. There is a costly issue.
Accordingly, there is a need for a method for easily predicting a gene which is a cause of hereditary skeletal muscle ion channel disease.
The present invention has been made to solve the above problems, an object of the present invention, Hereditary Skeletal Muscle Channelopathy using the symptoms information of episodic paralysis and myotonia (Myeronia): The present invention provides a computer-readable recording medium containing a computer program for performing a method for predicting the cause of hereditary skeletal muscle ion pathway disease for determining the cause gene of HSMC) and a device for executing the same.
According to an embodiment of the present invention, a computer-readable recording medium may include: selecting at least one of episodic paralysis and myotonia; If the accidental paralysis is selected, receiving first symptom information corresponding to accidental paralysis; If the myotonia is selected, receiving second symptom information corresponding to myotonia; And determining the cause gene of Hereditary Skeletal Muscle Channelopathy (HSMC) using the first symptom information and the second symptom information. The computer program for this is stored.
In the determining of the cause gene, at least one of the ion channel genes SCN4A, CACNA1S, CLCNS, and KCNJ2 may be determined as the cause gene.
The first symptom information input step may include at least one of hyperkalemia, dysmorphism, electrocardiogram (EKG abnormality), stiffness, myalgia, and myotonia. It can also be entered as symptom information.
The causal gene determination step may include determining a causative gene as SCN4A when the first symptom information is at least one of hyperkalemia, stiffness, myalgia, and myotonia, and the first symptom information may be dysentery. Alternatively, the cause gene may be determined as KCNJ2 in case of abnormal ECG, and the cause gene may be determined as CACNA1S when all of the inputted first symptom information is not applicable.
The second symptom information input step may include at least one of recessive inheritance, paramytonia, warm-up, period paralysis, and facial myoyonia. May be input as the second symptom information.
The causal gene determination step may include determining the causative gene as SCN4A when the second symptom information is at least one of dystonia, periodic paralysis, and facial myotonia. The cause gene may be determined as CLCN1 if at least one or both of recessive genetics and warm up are not applicable.
The determining of the cause gene may include determining
In the determining of the cause gene, when the cause gene is determined to be SCN4A, if the second symptom information is inputted as periodic paralysis,
In the determining of the cause gene, when the cause gene is determined as SCN4A, the first symptom information corresponds to muscular dystrophy, the second symptom information corresponds to dystonia, or potassium ion (K + ) concentration is normal. (3.5 mEq / L or more and 5 mEq / L or less),
In addition, the causal gene determination step, when the causal gene is determined SCN4A, when the potassium ion (K + ) concentration is greater than 5mEq / L, exon 19,24 (domain 3,4 (D3, D4) of SCN4A) Exon 19,24) may be determined as the primary cause gene, and
And, the causal gene determination step, when the causal gene is determined as SCN4A, when the potassium ion (K + ) concentration is less than 3.5mEq / L, exons of
In the causal gene determination step, when the causal gene is determined to be CACNA1S, exon 11,30 of CACNA1S is determined as the causal gene, and when there is no mutation in the causal gene, the entire gene of CACNA1S is searched. May be determined.
In the determining of the cause gene, when the cause gene is determined as CLCN1, when there is no mutation in the gene of CLCN1, SCN4A may be determined as the second cause gene.
On the other hand, according to an embodiment of the present invention, the apparatus for predicting the cause of the inherited skeletal muscle ion pathway disease executes the computer program recorded on the above-described recording medium.
According to various embodiments of the present invention, a computer program for performing a method of predicting the cause of hereditary skeletal muscle ion pathway disease that determines the cause gene of the hereditary skeletal muscle ion pathway disease using symptom information of accidental paralysis and myotonia It is possible to provide a recording medium and a device for performing the same, and thus it is possible to quickly and accurately predict the causative gene of hereditary skeletal muscle ion channel disease. Therefore, the user can determine the cause of hereditary skeletal muscle ion pathway disease by examining only some genes among various cause genes, and can identify the cause of hereditary skeletal muscle ion pathway disease in a short time at low cost.
1 is a flowchart provided to explain a method for predicting the cause of hereditary skeletal muscle ion channel disease according to an embodiment of the present invention;
2 is a flowchart provided to explain a process of determining a cause gene by the HSMC cause prediction program when a user selects an accidental paralysis according to an embodiment of the present invention;
3 is a flowchart provided to explain a process of determining a cause gene by a HSMC cause prediction program when a user selects myotonia according to an embodiment of the present invention;
4 is a flowchart provided to explain a process of determining a cause gene when the cause gene is determined to be SCN4A according to an embodiment of the present invention;
5 is a diagram illustrating a first screen on which an HSMC cause prediction program is executed according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating an inspection method recommendation screen of an HSMC cause prediction program according to an embodiment of the present invention. FIG.
Hereinafter, the present invention will be described in detail with reference to the drawings.
In the present embodiment, a method for predicting the cause of hereditary skeletal muscle ion channel disease predicting the genetic defect of the ion channel protein causing the hereditary skeletal muscle channel pathway (HSMC) through simple clinical symptom input will be described. The genetic skeletal muscle ion channel disease cause prediction method to be described below may be implemented as a computer program of the genetic skeletal muscle ion channel disease cause prediction program (hereinafter, HSMC cause predictive program). The HSMC cause predictive program is executed in a genetic skeletal muscle ion pathway disease predictor (hereinafter, referred to as HSMC cause predictor) composed of a personal computer or a server.
1 is a flowchart provided to explain a method for predicting the cause of hereditary skeletal muscle ion channel disease according to an embodiment of the present invention.
HSMC cause prediction program is selected by the user at least one of the episodic paralysis (Episodic paralysis) and myotonia (Myotonia) (S110). Accidental paralysis and myotonia may be chosen either one or both. The HSMC cause prediction program displays a selection screen for selecting accidental paralysis and myotonia as the basic symptoms on the screen, and the user inputs the basic symptoms through the selection screen. Here, the basic symptom represents a representative symptom in HSMC, and represents at least one of accidental paralysis and myotonia.
If accidental paralysis is selected, the HSMC cause prediction program receives first symptom information corresponding to accidental paralysis from the user (S120). Here, the first symptom information may be at least one of hyperkalemia, dysmorphism, EKG abnormality, stiffness, myalgia, and myotonia. The HSMC cause prediction program displays a selection screen for selecting first symptom information on a screen in a questionnaire form or a questionnaire form, and the user inputs the first symptom information through the selection screen.
In addition, when myotonia is selected, the HSMC cause prediction program receives the second symptom information corresponding to the myotonia from the user (S130). Here, the second symptom information may be at least one of recessive inheritance, paramytonia, warm-up, period paralysis, and facial myoyonia. The HSMC cause prediction program displays a selection screen for selecting second symptom information on a screen in a questionnaire form or a questionnaire form, and the user inputs second symptom information through the selection screen.
Thereafter, the HSMC cause prediction program determines the cause gene of hereditary skeletal muscle ion pathway disease using the inputted first symptom information and second symptom information (S140). Here, the causative gene includes at least one of the ion channel genes SCN4A, CACNA1S, CLCN1, and KCNJ2. Here, SCN4A represents the human skeletal muscle sodium channel Na v 1.4 gene. In addition, CACNA1S represents a calcium channel Ca V 1.1 gene. CLCN1 also represents the human skeletal muscle chloride channel CIC-1 gene. KCNJ2 represents an Inward-rectifier potassium ion channel K ir 2.1 gene.
As such, the HSMC cause prediction program determines the cause gene and displays it on the screen (S150). Through this, the HSMC cause prediction program determines the cause gene for examining the cause of HSMC to the doctor or patient and recommends as an HSMC cause test method.
In this case, the HSMC cause prediction program may recommend the entire search for the gene in the cause gene according to the type of the cause gene, or may determine and recommend a specific domain and exon within the cause gene. In addition, the HSMC cause prediction program may prioritize and recommend a plurality of specific domains and exons in a cause gene.
As such, the detailed process of determining the cause gene by the HSMC cause prediction program will be described in detail below with reference to FIGS. 2 to 4.
2 is a flowchart provided to explain a process of determining a cause gene by an HSMC cause prediction program when a user selects an accidental paralysis according to an embodiment of the present invention.
First, the HSMC cause predictive program is selected by the user as the primary symptoms of accidental paralysis (S112).
Thereafter, the HSMC cause prediction program receives first symptom information corresponding to accidental paralysis from the user (S122). The first symptom information may be at least one of hyperkalemia, dysmorphism, EKG abnormality, stiffness, myalgia, and myotonia.
If the first symptom information input is hyperkalemia (S210-Y), the HSMC cause prediction program determines the cause gene as SCN4A (S250). Then, the HSMC cause prediction program determines the cause gene in the cause gene SCN4A according to the process shown in FIG. 4 (S252). 4 will be described in detail later.
In addition, when the first symptom information input is dysplasia or electrocardiogram abnormality (S220-Y), the HSMC cause prediction program determines the cause gene as KCNJ2 (S270). Then, the HSMC cause prediction program is determined to search the entire gene in the cause gene KCNJ2 (S272). In other words, the HSMC cause prediction program recommends the entire gene search in KCNJ2 as the HSMC cause test method.
And, if the first symptom information input is stiffness or muscle pain (S230-Y), the HSMC cause prediction program determines the cause gene as SCN4A (S250). Then, the HSMC cause prediction program determines the cause gene in the cause gene SCN4A according to the process shown in FIG. 4 (S252). 4 will be described in detail later.
In addition, when the inputted first symptom information is myotonia (S240-Y), the HSMC cause prediction program determines the cause gene as SCN4A (S250). The HSMC cause prediction program determines a cause gene in SCN4A according to the process shown in FIG. 4 (S252). 4 will be described in detail later.
On the other hand, if the first symptom information does not correspond to any of hyperkalemia, dysmorphism, EKG abnormality, stiffness, myalgia, myotonia, HSMC cause prediction program determines the cause gene to CACNA1S (S260). The HSMC cause prediction program determines the cause genes as exons 11 and 30 in CACNA1S (S262). In addition, the HSMC cause prediction program determines to search the entire gene in CACNA1S when there are no mutations in exons 11 and 30 in CACNA1S (S272). In other words, the HSMC cause prediction program recommends exon 11 and 30 tests in CACNA1S as the first priority and the entire CACNA1S gene search as the second priority.
Through this process, the HSMC cause prediction program determines the cause gene when the user selects accidental paralysis.
Hereinafter, a case in which the user selects myotonia will be described with reference to FIG. 3. 3 is a flowchart provided to explain a process of determining a cause gene by the HSMC cause prediction program when a user selects myotonia according to an embodiment of the present invention.
Once, the HSMC cause prediction program is selected by the user as myastheniasis (S114).
Thereafter, the HSMC cause predictive program receives input of the second symptom information corresponding to myotonia from the user (S132). Here, the second symptom information may be at least one of recessive inheritance, paramytonia, warm-up, period paralysis, and facial myoyonia.
If the inputted second symptom information is a recessive genetic (S310-Y), the HSMC cause prediction program determines the cause gene as CLCN1 (S370). Then, the HSMC cause prediction program is determined to search the entire gene in CLCN1 (S372). In addition, if there is no mutation in the HSMC cause prediction program, the cause gene is determined to be SCN4A in second order (S360). That is, the HSMC cause prediction program recommends the first search for all genes in CLCN1 as the HSMC cause test method, and the second test recommends the gene test according to FIG. 4 of the SCN4A gene.
In addition, when the inputted second symptom information is dysplasia or ECG abnormalities (S320-Y), the HSMC cause prediction program determines the cause gene as SCN4A (S360). The HSMC cause prediction program determines a cause gene in SCN4A according to the process shown in FIG. 4 (S362). 4 will be described in detail later.
If the inputted second symptom information is warm-up (S330-Y), the HSMC cause prediction program determines the cause gene as CLCN1 (S370). Then, the HSMC cause prediction program is determined to search the entire gene in CLCN1 (S372). In addition, if there is no mutation in the HSMC cause prediction program, the cause gene is determined to be SCN4A in second order (S360). That is, the HSMC cause prediction program recommends the first search for all genes in CLCN1 as the HSMC cause test method, and the second test recommends the gene test according to FIG. 4 of the SCN4A gene.
In addition, when the inputted second symptom information is periodic paralysis (S340-Y), the HSMC cause prediction program determines the cause gene as SCN4A (S360). The HSMC cause prediction program determines a cause gene in SCN4A according to the process shown in FIG. 4 (S362). 4 will be described in detail later.
In addition, when the inputted second symptom information is facial muscle tone (S350-Y), the HSMC cause prediction program determines the cause gene as SCN4A (S360). The HSMC cause prediction program determines a cause gene in SCN4A according to the process shown in FIG. 4 (S362). 4 will be described in detail later.
On the other hand, the second symptom information does not correspond to any of recessive inheritance, paramytonia, warm-up, periodic paralysis, and facial myoyonia. In case (S350-N), the HSMC cause prediction program determines the cause gene as CLCN1 (S370). Then, the HSMC cause prediction program is determined to search the entire gene in CLCN1 (S372). In addition, if there is no mutation in the HSMC cause prediction program, the cause gene is determined to be SCN4A in second order (S360). That is, the HSMC cause prediction program recommends the first search for all genes in CLCN1 as the HSMC cause test method, and the second test recommends the gene test according to FIG. 4 of the SCN4A gene.
Through this process, the HSMC cause prediction program determines the cause gene when the user selects accidental paralysis as a basic symptom.
Hereinafter, a process of determining the cause gene when the cause gene is determined as SCN4A will be described in detail with reference to FIG. 4. 4 is a flowchart provided to explain a process of determining a cause gene when the cause gene is determined to be SCN4A according to an embodiment of the present invention.
When the cause gene is determined to be SCN4A through step S250 of FIG. 2 or step S360 of FIG. 3, the HSMC cause prediction program uses the base symptom, first symptom information, and second symptom information input by the user to identify the cause gene. The decision will be made in detail.
Specifically, the HSMC cause prediction program checks whether both accidental paralysis and myotonia are selected as basic symptoms (S410). In addition, when both the primary paralysis and myotonia are selected as the basic symptoms, the HSMC cause prediction program determines
That is, in the above-described case, the HSMC cause prediction program recommends the
In addition, the HSMC cause prediction program checks whether the second symptom information is input as periodic paralysis (S420). If the second symptom information is input as periodic paralysis, the HSMC cause prediction program determines
That is, in the above-described case, the HSMC cause prediction program recommends the
In addition, the HSMC cause predictive program inputs the first symptom information to myotonia, the second symptom information to dystonia, or the potassium ion (K + ) concentration is normal (3.5 mEq / L or more and 5 mEq / L or less). Check whether it is (S430). HSMC Cause Prediction Program if the first symptom information corresponds to myotonia, the second symptom information corresponds to dystonia, or potassium ion (K + ) concentration is normal (more than 3.5 mEq / L and less than 5 mEq / L)
That is, in the above-described case, the HSMC cause prediction program recommends the
In addition, the HSMC cause prediction program checks whether the input potassium ion (K + ) concentration is greater than 5 mEq / L (S440). If the input potassium ion (K + ) concentration is above 5 mEq / L, the HSMC cause prediction program uses exon 19,24 (Exon 19,24) of domain 3,4 (D3, D4) of SCN4A as the primary cause gene. In operation S442,
That is, in the above-described case, the HSMC cause prediction program recommends the exon 19,24 (Exon 19,24) test of domains 3,4 (D3, D4) of SCN4A as the HSMC cause test method, and the
In addition, HSMC cause prediction program checks whether the input potassium ion (K + ) concentration is less than 3.5mEq / L (S450). If the input potassium ion (K + ) concentration is less than 3.5 mEq / L, the HSMC cause prediction program is based on the
That is, in the above-described case, the HSMC cause predictive program is an HSMC cause test method, and
Through this process, the HSMC cause prediction program determines the cause gene in detail and recommends a test method when the cause gene is determined as SCN4A. The HSMC Cause Prediction Program will also be able to recommend a variety of genetic tests through priorities.
Hereinafter, a screen executed by the HSMC cause predictive program in an HSMC cause predictor (computer, server, mobile device, etc.) will be described with reference to FIGS. 5 and 6. The HSMC cause estimating program is executed by the server, and the user may access the server through a personal PC and execute the HSMC cause estimating program. In addition, the HSMC cause predictive program may be installed and executed directly on a personal PC. In addition, the HSMC cause predictive program may be executed in various types of HSMC cause predictive devices (eg, mobile devices, etc.).
5 is a diagram illustrating a first screen on which an HSMC cause prediction program is executed according to an embodiment of the present invention. When the 'START' button is selected in FIG. 5, the HSMC cause prediction program is executed, and the user can input the basic symptom, the first symptom information, and the second symptom information through a question displayed on the screen.
FIG. 6 is a diagram illustrating an inspection method recommendation screen of an HSMC cause prediction program according to an embodiment of the present invention. FIG. The screen of FIG. 6 is a screen displayed after all of the basic symptom, the first symptom information, and the second symptom information are input by the user.
In the case of Figure 6, the patient is a case where the potassium ion (K + ) concentration is greater than 5mEq / L. Accordingly, when confirming "Conclusion" at the bottom of FIG. 6, the HSMC cause prediction program scans the exon 19,24 (Exon 19,24) of the domain 3,4 (D3, D4) of SCN4A by the HSMC
As such, doctors and patients can easily predict the cause genes that cause HSMC by inputting information about some symptoms of the patient by using the HSMC cause predictive apparatus, which executes the HSMC cause predictive program. Accordingly, diagnosis and cause analysis of HSMC can be performed more simply and inexpensively.
Needless to say, the technical idea of the present invention can also be applied to a computer-readable recording medium having a computer program for performing the function of the power control device 30 according to the present embodiment. In addition, the technical idea according to various embodiments of the present invention may be embodied in computer-readable code form recorded on a computer-readable recording medium. The computer-readable recording medium is any data storage device that can be read by a computer and can store data. For example, the computer-readable recording medium may be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical disk, a hard disk drive, or the like. In addition, the computer readable code or program stored in the computer readable recording medium may be transmitted through a network connected between the computers.
While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention.
Claims (14)
If the accidental paralysis is selected, receiving first symptom information corresponding to accidental paralysis;
If the myotonia is selected, receiving second symptom information corresponding to myotonia; And
And determining the causative gene of Hereditary Skeletal Muscle Channelopathy (HSMC) using the first symptom information and the second symptom information.
The causal gene determination step,
A computer-readable recording medium containing a computer program for performing a method for predicting the cause of hereditary skeletal muscle ion channel disease, which determines at least one of ion channel genes SCN4A, CACNA1S, CLCN1, and KCNJ2 as the causal gene.
The first symptom information input step,
Computer for receiving at least one of hyperkalemia, dysmorphism, EKG abnormality, stiffness, myalgia, and myotonia as first symptom information Recordable media that can be read by
The causal gene determination step,
If the first symptom information input is at least one of hyperkalemia, stiffness, muscle pain, and myotonia, the cause gene is determined as SCN4A,
If the first symptom information input is dysplasia or ECG abnormality, the cause gene is determined as KCNJ2,
The computer-readable recording medium of claim 1, wherein the causal gene is determined as CACNA1S when the first symptom information does not correspond to all the information.
The second symptom information input step,
Receive at least one of recessive inheritance, Paramytonia, Warm-up, Periodic paralysis, and Facial myoyonia as second symptom information. Computer-readable recording media.
The causal gene determination step,
If the second symptom information input is at least one of dystonia, periodic paralysis, and facial myotonia, the cause gene is determined as SCN4A,
And the cause gene is determined as CLCN1 when the input second symptom information corresponds to or does not correspond to at least one of recessive genetics and warm-up.
The causal gene determination step,
When the causal gene is determined to be SCN4A,
And if both accidental paralysis and myotonia are selected, exon 24 of domain 4 (D4) of SCN4A is determined as a causal gene.
The causal gene determination step,
When the causal gene is determined to be SCN4A,
If the second symptom information is entered as periodic paralysis, exon 13,19 of domain 2,3 (D2, D3) of SCN4A is determined as the first cause gene, and exon of domain 4 (D4) is determined. A computer-readable recording medium, characterized in that 24 (Exon 24) is determined as the second-order cause gene.
The causal gene determination step,
When the causal gene is determined to be SCN4A,
If the first symptom information corresponds to myotonia, the second symptom information corresponds to dystonia, or potassium ion (K + ) concentration is normal (3.5 mEq / L or more and 5 mEq / L or less), domain 3- of SCN4A The exon 22 of the 4 linker (D3-D4 linker) is determined to be the primary cause gene, and the exons 5,9,24 (Exon 5,9,24) of domains 1,4 (D1, D4) are ranked 2nd. Computer-readable recording medium, characterized in that determined by the cause gene.
The causal gene determination step,
When the causal gene is determined to be SCN4A,
If the potassium ion (K + ) concentration is greater than 5 mEq / L, exon 19,24 of domain 3,4 (D3, D4) of SCN4A is determined as the primary cause gene and domain 2 (D2) A computer-readable recording medium, characterized in that the exon 13 of (Exon 13) is determined as the second cause gene.
The causal gene determination step,
When the causal gene is determined to be SCN4A,
When the potassium ion (K + ) concentration is less than 3.5 mEq / L, exon 5,9,13,19 (Exon 5,9,13,19) of domains 1,2,3 (D1, D2, D3) of SCN4A A computer-readable recording medium, characterized in that it is determined by the primary cause gene.
The causal gene determination step,
When the causal gene is determined to be CACNA1S,
The exon 11,30 (Exon 11,30) of CACNA1S as a causal gene, and if there is no mutation in the causal gene, the computer-readable recording medium, characterized in that for determining the entire gene search of CACNA1S.
The causal gene determination step,
When the causal gene is determined to be CLCN1,
The computer-readable recording medium of claim 1, wherein if there is no mutation in the gene of CLCN1, SCN4A is determined as the second-order cause gene.
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| KR20110060142A (en) * | 2009-11-30 | 2011-06-08 | 한국 한의학 연구원 | Discriminant apparatus for obesity syndrome differentiation and discriminan method for obesity syndrome differentiation |
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| KR20140007540A (en) | 2014-01-20 |
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