WO2023237800A1 - Método de obtención de datos útiles para la predicción del riesgo de un sujeto de sufrir fibrosis - Google Patents
Método de obtención de datos útiles para la predicción del riesgo de un sujeto de sufrir fibrosis Download PDFInfo
- Publication number
- WO2023237800A1 WO2023237800A1 PCT/ES2023/070378 ES2023070378W WO2023237800A1 WO 2023237800 A1 WO2023237800 A1 WO 2023237800A1 ES 2023070378 W ES2023070378 W ES 2023070378W WO 2023237800 A1 WO2023237800 A1 WO 2023237800A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- gene
- seq
- subject
- genetic
- fibrosis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/156—Polymorphic or mutational markers
Definitions
- the present invention is related to an in vitro method for obtaining data useful for predicting a subject's risk of suffering from fibrosis, falling within the field of Personalized Medicine. Specifically, this method is based on the analysis of a series of genetic polymorphisms, as well as other environmental data of the subject, which together are useful and allow the prediction of the risk of a subject developing fibrosis.
- Fibrosis in general terms refers to an abnormal growth and accumulation of components of the extracellular matrix, which causes hardening or fibrosing of tissue, resulting in a partial or total loss of function of the affected tissue or organ. Fibrotic disease comprises a wide range of clinical pathologies that are estimated to be responsible for 45% of all deaths in the developed world.
- Fibrotic pathologies can affect a large number of different organs and tissues, however, it is believed that their generation pathways are common in any organ.
- fibrotic pathology can occur after a surgical intervention. This condition, called postsurgical fibrosis, is characterized by an excessive proliferation of fibrotic and scar tissue generated after a surgical intervention in a patient, forming more fibrous tissue than necessary, which which usually has a negative impact on their quality of life.
- Fibrosis appears very frequently at the joint level, which leads to the development of arthrofibrosis, with the consequent hardening or pathological stiffening of a joint due to an exaggerated fibrotic response.
- the appearance of fibrosis is a complication to take into account in joint surgical interventions due to its incidence: ranging between 1 and 15% of patients affected in knee arthroplasties, and between 4 and 38%. in anterior cruciate ligament reconstruction.
- Patent application EP2428583A1 describes a method for determining the progress of the healing process of a subject, which comprises determining the level of expression of at least one gene selected from the genes TFAP2A, EGFR, ILIA, IL1 B, IL6, IL10 , IL18, CD44, TNFRSF1A, HSPD1, MYC, CTGF, MMP7, MMP2, MMP9, MMP25, TGFA, TGFB2, EREG, FN1, HBEGF, NF1, SRC, EGF4, CDKN2A, PLAU, SPP1, ITGB2, BAX, MET and PPAR , or a functionally equivalent variant of said genes, in a sample from said subject.
- ES2422874B1 an in vitro method is described for the prognosis and/or diagnosis of severe liver fibrosis that is characterized by the detection of a series of genetic polymorphisms and the determination of clinical variables.
- CA2805267A1 a method is described that comprises measuring the level of cadherin-11 in a sample obtained from a subject, and its comparison with control values, where a level of cadherin-11 in the sample obtained from the subject greater than the control value indicates fibrosis or risk of developing fibrosis.
- the present invention discloses a method for obtaining data useful in vitro to predict the risk of a subject of suffering from a fibrosis process.
- the inventors are based on the use of environmental variables (degree of obesity, use or not of platelet-rich plasma, and additionally data related to the variables, area susceptible to fibrosis and/or sex of the subject) together with genetic variables that include the analysis of one or several genetic polymorphisms of the MMP3, NEDD4, SMAD4 genes, as well as their combinations with polymorphisms of the IL6R, CTGF, IL-6, BMP4 genes, the application of an algorithm that takes into account
- the above variables allow us to obtain a value of a subject's risk of generating fibrosis.
- the algorithm of the invention takes into account genetic and environmental variables jointly, which allow calculating a specific risk value for each subject.
- the present invention thus provides an innovative approach in the area of Personalized Medicine with multiple associated advantages: it allows obtaining useful data to know a patient's risk of suffering from fibrosis with high sensitivity and specificity; It allows decisions or preventive measures to be taken that can avoid said condition, which in the event that the patient is going to undergo surgery, can in turn facilitate a correct recovery and/or future interventions to eliminate the fibrosis generated. In addition, it may also be useful when guiding the application of certain preventive treatments based on the risk identified in the patient, such as, for example, adjusting the diet or applying preoperative physiotherapy, oral pharmacology or alternative surgical techniques, which avoid the generation of fibrosis. Likewise, it allows us to know a patient's risk of suffering from post-surgical fibrosis before undergoing surgery. Method of invention
- the present invention refers to an in vitro method for obtaining data useful for predicting the risk of suffering from fibrosis of a subject, hereinafter "the method of the invention", which comprises the following steps:
- (b) collect data from the subject on at least one environmental variable, selected from the list that consists of: use or non-use of platelet-rich plasma in the treatment of the subject and degree of obesity;
- step (c) assign a p value to the genetic polymorphisms analyzed in step (a) according to Table 3, and assign a value to the data collected from the subject in step (b) according to Table 3;
- Po 3.256 pix is the sum of all p values assigned in step (c).
- in vitro refers to the method of the invention being carried out outside the subject's body.
- fibrosis refers to a process typical of vascularized connective tissue, in which plasma and circulating and resident cells of the connective tissue participate, highlighting mediators of inflammation, granulocytes, macrophages, platelets and endothelial cells, in addition to fibroblasts and myofibroblasts among others.
- fibrosis is characterized by the proliferation of fibroblasts, cells abundant in the connective tissue that secretes compounds such as collagen and proteoglycans.
- myofibroblasts also play a very important role during inflammation, repair and healing. As used here, it refers to a pathological increase in connective tissue in some organ or tissue.
- healing refers to a natural process that the body of a subject who has suffered a wound has to regenerate the tissues involved in it. In this process, a series of complex biochemical phenomena are carried out that take place to repair the damage caused by the wound.
- the healing process of the present invention refers to, but is not limited to, any type of healing of a wound caused in the human body, including wounds from post-surgical processes.
- keloids refers to pathological scars produced by an aberrant and overly exuberant wound healing response. Keloids are raised scars that extend beyond the margins of an original wound and invade the normal skin surrounding the wound site. Keloids may continue to grow over time and may not subside spontaneously. It can be considered that a keloid lesion is made up of several different parts that can present very different biological activity from each other.
- the central part of a mature keloid lesion (the intra-lesional portion) is largely acellular, while the peripheral part of the lesion (the peh-lesional portion) is relatively more cellular and is the site of greatest angiogenic activity.
- the phrase "predict the risk of suffering from fibrosis in a subject” refers to determining or predicting the probability of a subject to suffer from said condition.
- obtaining data useful for this prediction comprises the application of an algorithm that takes into account environmental and genetic variables, in particular, genetic polymorphisms.
- the algorithm of the method of the invention is considered predictive when the AUCROC (AUC-Area UnderCurve or area under the curve; ROC-Receiver Operating Characteristic) is greater than 0.5.
- AUCROC AUC-Area UnderCurve or area under the curve; ROC-Receiver Operating Characteristic
- the AUCROC is defined as the probability of correctly classifying a pair of case and control individuals, selected at random from the population, through the results or values obtained when applying the algorithm.
- the AUCROC by convention is between 0.5 and 1: the closer the ALICROC value of a variable is to 1, the more precise and predictive it is considered.
- the sensitivity of the diagnostic test is the probability of obtaining a positive result when the individual has the disease or condition, in the present invention, fibrosis.
- the specificity of a test indicates the probability of obtaining a negative result when the individual does not have the disease or condition, in the present invention, does not develop or suffer from fibrosis.
- subject in the present invention refers to any individual susceptible to suffering from fibrosis, or to any individual who is interested in knowing the risk of suffering from said condition.
- patient or “subject” are used interchangeably herein.
- fibrosis can affect any organ or tissue of the subject.
- the fibrosis affects a joint. More preferably, the fibrosis affects a joint, where the joint is selected from the list consisting of knee, ankle, hip, shoulder and elbow.
- the method of the invention also allows predicting a subject's risk of suffering from post-surgical fibrosis prior to undergoing surgery.
- the subject is to undergo surgery.
- the surgery to which the subject is to undergo is performed on a joint.
- joints include, but are not limited to, knee, ankle, hip, shoulder and elbow.
- the joint is selected from the list consisting of knee, ankle, hip, shoulder and elbow.
- the fibrosis is postsurgical fibrosis.
- post-surgical fibrosis refers to the process of fibrosis in response to surgery (or surgical intervention, terms used interchangeably in the present document) that includes a secondary healing process. As used here, it is used to refer to a condition that includes excessive secondary scarring produced after a surgical intervention, forming more fibrous tissue than necessary causing unwanted effects that can complicate the patient's recovery. Examples of unwanted effects related to said post-surgical fibrosis include, but are not limited to, the compression of a nerve due to the excessive scar, which causes pain to the patient, affecting the patient's recovery and quality of life, or the restriction in the range of movement of a joint after surgical intervention.
- post-surgical fibrosis mostly appears at the joint level, which leads to the development of arthrofibrosis, with the consequent hardening or pathological stiffening of a joint due to an exaggerated fibrotic response. This can arise in large joints such as shoulders, elbows, hips and knees, and generally causes loss of function and immobility of these joints.
- postsurgical fibrosis occurs in a joint.
- the joint is selected from the list consisting of shoulder, elbow, hip and knee.
- a first step of the method of the invention comprises analyzing in a biological sample isolated from the subject, at least one genetic polymorphism selected from the list consisting of rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene, rs12456284 of the gene SMAD4, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms;
- genetic polymorphism refers to a variation in the nucleotide sequence of the deoxyribonucleic acid (DNA) chain that has at least a frequency of 1% in individuals in a population. Genetic polymorphisms can be variations of one or more nucleotides. Single nucleotide polymorphisms, or SNPs, generally give rise to two alleles.
- polynucleotide refers to a polymeric form of nucleotides of any length, which may or may not be chemically or biochemically modified.
- the genetic polymorphism rs679620 of the MMP3 gene refers to a SNP located at position 102842889 of chromosome 11 of homo sapiens (GenBank accession number of the sequence of chromosome 11 of homo sap/ens:NC_000011.10). Genotypes can be homozygous for adenine (A:A), heterozygous adenine:guanine (A:G) or homozygous for guanine (G:G).
- the genetic polymorphism rs8032158 of the NEDD4 gene refers to a SNP located at position 55902679 of chromosome 15 of homo sapiens (GenBank accession number of the sequence of chromosome 15 of homo sapiens. NC_000015.10). Genotypes can be homozygous for cytosine (C:C), heterozygous cytosine:thymine (C:T) or homozygous for thymine (T:T).
- the genetic polymorphism rs12456284 of the SMAD4 gene refers to a SNP located at position 51083598 of chromosome 18 of homo sapiens (GenBank accession number of the sequence of chromosome 18 of homo sapiens. NC_000018.10). Genotypes can be homozygous for adenine (A:A), heterozygous adenine:guanine (A:G) or homozygous for guanine (G:G).
- step (a) comprises analyzing at least two genetic polymorphisms selected from the list consisting of rs679620 of the gene MMP3 rs8032158 of the NEDD4 gene, rs12456284 of the SMAD4 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- step (a) comprises analyzing the genetic polymorphism rs12456284 of the SMAD4 gene and the genetic polymorphism rs679620 of the MMP3 gene.
- step (a) comprises analyzing the genetic polymorphism rs8032158 of the NEDD4 gene and the genetic polymorphism rs12456284 of the SMAD4 gene.
- step (a) comprises analyzing the genetic polymorphism rs8032158 of the NEDD4 gene and the genetic polymorphism rs679620 of the MMP3 gene.
- step (a) comprises analyzing at least three genetic polymorphisms selected from the list consisting of rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene, rs12456284 of the SMAD4 gene. , and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- step (a) comprises analyzing three genetic polymorphisms selected from the list consisting of rs8032158 of the NEDD4 gene, rs12456284 of the SMAD4 gene, rs679620 of the MMP3 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- the genetic polymorphisms are rs8032158 of the NEDD4 gene, rs12456284 of the SMAD4 gene and rs679620 of the MMP3 gene.
- step (a) of the method of the invention may comprise analyzing at least one genetic polymorphism selected from the list consisting of, rs2228145 of the IL6R gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the gene BMP4, and/or any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- the genetic polymorphism rs2228145 of the IL6R gene refers to a SNP located at position 154454494 of chromosome 1 of homo sapiens (GenBank accession number of the sequence of chromosome 1 of homo sapiens. NC_000001.11). Genotypes can be homozygous for adenine (A:A), heterozygous adenine:cytosine (A:C) or homozygous for cytosine (C:C).
- the genetic polymorphism rs9493150 of the CTGF gene refers to a SNP located at position 131952851 of chromosome 6 of homo sapiens (GenBank accession number of the sequence of chromosome 6 of homo sapiens. NC_000006.12). Genotypes can be homozygous for cytosine (C:C), heterozygous cytosine:guanine (C:G) or homozygous for guanine (G:G).
- the genetic polymorphism rs1800796 of the IL-6 gene refers to a SNP located at position 22726627 of chromosome 7 of homo sapiens (GenBank accession number of the sequence of chromosome 7 of homo sapiens. NC_000007.14). Genotypes can be homozygous for cytosine (C:C), heterozygous cytosine:guanine (C:G) or homozygous for guanine (G:G).
- the genetic polymorphism rs17563 of the BMP4 gene refers to a SNP located at position 53950804 of chromosome 14 of homo sapiens (GenBank accession number of the sequence of chromosome 14 of homo sapiens. NC_000014.9). Genotypes can be homozygous for cytosine (C:C), heterozygous cytosine:thymine (C:T) or homozygous for thymine (T:T).
- step (a) further comprises analyzing at least one genetic polymorphism selected from the list consisting of rs2228145 of the IL6R gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- step (a) further comprises analyzing at least two, at least three, at least four, genetic polymorphisms selected from the list that consists of rs2228145 of the IL6R gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms, including any combination thereof.
- step (a) comprises analyzing at least 7 genetic polymorphisms selected from a list consisting of rs2228145 of the IL6R gene, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms, including any combination of the same..
- step (a) comprises analyzing the genetic polymorphisms rs2228145 of the IL6R gene, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the gene IL-6, rs17563 of the BMP4 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene.
- polymorphisms of the invention is used to refer to at least one genetic polymorphism selected from among the polymorphisms rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene, rs12456284 of the SMAD4 gene, any other polymorphism that is in disequilibrium of linkage with said genetic polymorphisms, and/or to any combination of one or more of the previous genetic polymorphisms with at least one genetic polymorphism selected from among rs2228145 of the IL6R gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, and rs17563 of the BMP4 gene, including any other polymorphism that is in linkage disequilibrium with them
- the genetic polymorphisms are SNPs, so the terms polymorphisms of the invention and SNPs of the invention can be used interchangeably throughout the document.
- the genetic polymorphisms that can be analyzed as part of the method of the present invention, and that are useful in predicting a subject's risk of suffering from fibrosis, are shown in Table 1.
- Table 1 Genetic polymorphisms that can be included as genotypic variables within the prediction model.
- linkage disequilibrium refers to the property of some genes or DNA markers of not segregating independently, that is, they have a recombination frequency of less than 50%. This is usually due to the fact that the two loci involved are located on the same chromosome, which makes it impossible to transfer them to the progeny in a random manner with the separation of the chromosomes in anaphase. In the present invention, it refers to those genetic polymorphisms that, due to their physical proximity on a chromosome, occur together more frequently than would be expected by chance.
- a genetic polymorphism that is in linkage disequilibrium with another presents the same capacity or gives equivalent information, in the present invention, relative to the prediction of a subject's risk of suffering from fibrosis, since by the definition itself, both are inherited. on the whole.
- a measure of linkage disequilibrium between two genetic markers is defined like “r 2 ”.
- Two genetic polymorphisms that have not been separated by recombination (total linkage disequilibrium), show an r 2 1.
- the polymorphisms that are in linkage disequilibrium with the genetic polymorphisms rs2228145 of the IL6R gene, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, rs8032158 of the NEDD4 gene and /or rs12456284 of the SMAD4 gene preferably have a linkage disequilibrium measurement r 2 > 0.8, more preferably a linkage disequilibrium measurement r 2 > 0.9.
- the analysis of the polymorphisms of the invention can be carried out by any method known to the person skilled in the art for this purpose. For example, it can be carried out using genotyping kits, sequencing or by PCR amplification (polymerase chain reaction) and subsequent analysis with restriction enzymes or by real-time PCR.
- Genotyping kits may contain oligonucleotides labeled with fluorophores and may require hybridization of these with a biological sample isolated from a subject.
- the analysis of the polymorphisms of the invention in step (a) is carried out by any method known to the person skilled in the art for this purpose.
- it is carried out by amplification, more preferably PCR amplification, and/or sequencing.
- the analysis of the polymorphisms of the invention in step (a) is carried out using a genotyping kit.
- the analysis of the polymorphisms of the invention in step (a) comprises the use of probes and/or primers that detect and/or amplify said polymorphisms.
- the primers and/or probes comprise, or consist of, the nucleotide sequences: SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO : 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13 , SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, and/or any combination thereof.
- sequences SEQ ID NO: 1 and SEQ ID NO: 2 correspond to the sequences of the primers necessary to amplify the rs2228145 polymorphism of the IL6R gene.
- sequences SEQ ID NO: 3 and SEQ ID NO: 4 correspond to the sequences of the probes necessary to specifically detect the rs2228145 polymorphism of the IL6R gene.
- sequences SEQ ID NO: 5 and SEQ ID NO: 6 correspond to the sequences of the primers necessary to amplify the rs679620 polymorphism of the MMP3 gene.
- sequences SEQ ID NO: 7 and SEQ ID NO: 8 correspond to the sequences of the probes necessary to specifically detect the rs679620 polymorphism of the MMP3 gene.
- sequences SEQ ID NO: 9 and 10 correspond to the sequences of the primers necessary to amplify the rs9493150 polymorphism of the CTGF gene.
- sequences SEQ ID NO: 11 and SEQ ID NO: 12 correspond to the sequences of the probes necessary to specifically detect the rs9493150 polymorphism of the CTGF gene.
- sequences SEQ ID NO: 13 and SEQ ID NO: 14 correspond to the sequences of the primers necessary to amplify the rs1800796 polymorphism of the IL-6 gene.
- sequences SEQ ID NO: 15 and SEQ ID NO: 16 correspond to the sequences of the probes necessary to specifically detect the rs1800796 polymorphism of the IL-6 gene.
- sequences SEQ ID NO: 17 and SEQ ID NO: 18 correspond to the sequences of the primers necessary to amplify the rs17563 polymorphism of the BMP4 gene.
- sequences SEQ ID NO: 19 and SEQ ID NO: 20 correspond to the sequences of the probes necessary to specifically detect the rs17563 polymorphism of the BMP4 gene.
- sequences SEQ ID NO: 21 and SEQ ID NO: 22 correspond to the sequences of the primers necessary to amplify the rs8032158 polymorphism of the NEDD4 gene.
- sequences SEQ ID NO: 23 and SEQ ID NO: 24 correspond to the sequences of the probes necessary to specifically detect the rs8032158 polymorphism of the NEDD4 gene.
- sequences SEQ ID NO: 25 and SEQ ID NO: 26 correspond to the sequences of the primers necessary to amplify the rs12456284 polymorphism of the SMAD4 gene.
- sequences SEQ ID NO: 27 and SEQ ID NO: 28 correspond to the sequences of the probes necessary to specifically detect the rs12456284 polymorphism of the SMAD4 gene.
- the analysis of the polymorphisms carried out in step (a) comprises the use of probes that detect the polymorphisms of the invention.
- the probes that detect said polymorphisms are selected from the list consisting of: SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 11, SEQ ID NO : 12, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 27, SEQ ID NO: 28 , and any combination of them.
- the analysis of the polymorphisms of the invention in step (a) comprises the use of hybridization probes labeled with fluorophores.
- sequencing refers to the determination of the nucleotides of a template nucleic acid and their order.
- amplification refers to the increase in the number of copies of a template nucleic acid, where this can be carried out using fluorescent probes. In a preferred embodiment, amplification takes place by real-time PCR.
- template nucleic acid refers to a single-stranded or double-stranded nucleic acid molecule that is to be amplified or sequenced.
- the increase in the number of copies of a template nucleic acid is carried out by synthesis of complementary DNA using conditions that allow it.
- the conditions that allow the synthesis of complementary DNA refer to the conditions in which the incorporation of nucleotides into a nascent DNA can take place through base complementarity with the template nucleic acid.
- the conditions under which sequencing or amplification is performed generally include (a) contacting a template nucleic acid with a polymerase in a mixture further comprising a primer, a divalent cation, (e.g., Mg 2+ ), and nucleotides, generally, dNTPs and, at least, one ddNTP, and (b) subjecting said mixture to a temperature sufficient for the polymerase to initiate the incorporation of the nucleotides into the primer through base complementarity with the template nucleic acid, and give rise to a population of complementary DNA molecules of different sizes.
- the separation of said population of complementary DNA molecules generally by electrophoresis, allows the nucleotide sequence to be determined.
- primer refers to an oligonucleotide capable of acting as a starting point for DNA synthesis when hybridized with the template nucleic acid.
- the primer is a deoxyrhbose oligonucleotide.
- the Primers may be prepared by any suitable method, including, for example, but not limited to, cloning and restriction of appropriate sequences and direct chemical synthesis. Primers can be designed to hybridize to specific nucleotide sequences in the template nucleic acid (specific primers) or can be synthesized at random (arbitrary primers).
- telomere sequence refers to a primer whose sequence is complementary to a specific nucleotide sequence in the template nucleic acid to be amplified or sequenced.
- arbitrary primer refers to a primer whose sequence is synthesized at random and that is used to initiate DNA synthesis at random positions of the template nucleic acid that is to be amplified or sequenced. A population of different arbitrary primers is often used.
- arbitrary primers refers to a set of primers whose sequence is synthesized at random and that is used to initiate DNA synthesis at random positions of the template nucleic acid that is to be amplified or sequenced.
- hybridization refers to the pairing of two complementary single-stranded DNA molecules to give a double-stranded molecule.
- complementarity is 100%. That is, in the region of complementarity each nucleotide of one of the two nucleic acid molecules can form hydrogen bonds with a nucleotide present in the other nucleic acid molecule.
- those with ordinary experience in the field will recognize that two nucleic acid molecules possessing a region with less than 100% complementarity can also hybridize.
- nucleotide refers to an organic molecule formed by the covalent bonding of a pentose, a nitrogenous base and a phosphate group.
- nucleotide includes deoxyribonucleoside triphosphates such as, for example, but not limited to, dATP, dCTP, dITP, dllTP, dGTP, dTTP, or derivatives thereof.
- nucleotide also includes dideoxyribonucleoside triphosphates (ddNTPs), such as, for example, ddATP, ddCTP, ddGTP, ddITP, ddTTP or derivatives thereof.
- a "nucleotide” or a “primer” can be labeled or labeling using techniques well known in the state of the art.
- Tags detected include, for example, radioactive isotopes, fluorescent tags, chemiluminescent tags, bioluminescent tags or enzymatic tags.
- biological sample in the present invention refers to any sample that allows DNA to be obtained from the individual from whom said sample has been obtained, and includes, but is not limited to, tissues and/or biological fluids of an individual, obtained by any method. known by an expert in the field that serves this purpose.
- the biological sample comes from any tissue susceptible to DNA extraction.
- the biological sample could be, for example, but not limited to, a tissue or fluid sample, such as blood, plasma, serum, oral mucosa, bronchoalveolar lavage, lymph or ascites fluid.
- the biological sample is selected from the list consisting of tissue, oral mucosa, blood, plasma, serum and lymph.
- the biological sample may be, for example, but not limited to, fresh, frozen, fixed or fixed and paraffin embedded.
- the algorithm used in the method of the invention which is useful and allows predicting a subject's risk of suffering from fibrosis, is based on the use of genomic variables together with environmental variables of each subject. To do this, therefore, it is necessary to collect data related to said environmental variables of the subject.
- a second stage of the method of the invention comprises collecting data from the subject on at least one environmental variable selected from the list that consists of: use or non-use of platelet-rich plasma in the treatment of the subject and degree of obesity.
- step (b) comprises collecting data from the subject on two environmental variables, where the environmental variables are use or non-use of plasma rich in platelets in the treatment of the subject and degree of obesity.
- stage (b) of the method of The invention may further comprise collecting data from the subject on at least one environmental variable selected from the list consisting of area of the body susceptible to fibrosis and sex of the subject, which are environmental variables that may also be useful in predicting the risk of fibrosis. a subject to suffer from fibrosis.
- step (b) further comprises collecting data from the subject on at least one environmental variable selected from the list consisting of area of the body susceptible to suffering from fibrosis and sex of the subject.
- step (b) comprises collecting data from the subject on the environmental variables, use or non-use of platelet-rich plasma in the treatment of the subject. , degree of obesity, area of the body susceptible to fibrosis and sex of the subject.
- collected data from the subject refers to the collection and/or recording of data related to environmental variables. As understood by an expert in the field, said data collection can be carried out using any methodology or protocol followed by health professionals.
- Table 2 shows the subject data that can be collected in step (b) of the method of the invention.
- Table 2 Subject data that can be collected in stage (b) of the method, and their respective environmental variables.
- the left column shows the environmental variables, while the right column shows each of the possible data to be collected from the subject for each variable.
- the data collected from the environmental variable degree of obesity is BMI ⁇ 30, BMI >30, percentage of fat mass > 25% (men), or percentage of fat mass > 33% (women).
- the data collected from the environmental variable use or non-use of platelet-rich plasma in the treatment of the subject is use or non-use.
- the data collected from the environmental variable sex of the subject is male or female.
- step (b) comprises collecting data from the subject, where the data comprises:
- the body susceptible to fibrosis, where the area of the body is selected from the list consisting of hip, shoulder, knee, ankle or other, including the term “other”, any other part, tissue or organ of the subject's body ;
- the degree of obesity comprises a body mass index of the subject greater than 30 or less than or equal to 30; and/or a percentage of fat mass greater than 25% or less than or equal to 25% in men, or a percentage of fat mass greater than 33% or less than or equal to 33% in women.
- area of the body susceptible to fibrosis is understood as the location, tissue, organ or part of the body of the subject that may be susceptible to fibrosis.
- one of the possible data collected from the subject in step (b) of the method of the invention is whether the area of the body, location or tissue susceptible to suffering fibrosis is hip, shoulder, knee, ankle or another , including the term “other” any other part, tissue or organ of the subject's body.
- the phrase “other part of the body” refers to any organ, tissue, or area of the subject's body other than hip, shoulder, knee, ankle.
- the area of the body susceptible to fibrosis is the tissue or organ of the subject where the surgery is performed.
- Another possible data collected from the subject in this step (b) of the method of the invention is whether the sex of the subject is male or female.
- platelet-rich plasma is type 13-00-11/24-00-11 as described in Kon E., et al., Expert Opin Biol Ther. , 20 (12):1447-1460 (2020).
- stage (b) of the method of the invention another of the possible data collected from the subject has to do with the degree of obesity of the subject, understanding this as a body mass index greater than 30 (BMI ⁇ 30), or less or equal to 30 (BMI ⁇ 30) or a percentage of fat mass greater than 25% in men or less than or equal to 25%, and greater than 33% in women or less than or equal to 33%.
- body mass index or BMI
- Body fat percentage can be calculated through bioelectrical impedance or by skinfolds using plycometry.
- Step (c) of the method of the invention assign a value B to the polymorphisms and data of the subject
- the method of the invention takes into account genetic variables and environmental variables of each subject.
- a value, in the present invention p-value is assigned to the polymorphisms analyzed in stage (a), and to the data collected from the subject in stage (b) of the method of the invention. .
- stage (c) comprises assigning a value to the genetic polymorphisms analyzed in stage (a) according to Table 3, and assigning a value p to the data collected from the subject in stage (b) according to Table 3.
- a p value is assigned for each polymorphism, according to the genotype of the subject. If From the data collected from the subject in step (b) of the method, a p value is assigned for each data collected.
- step (d) comprises calculating a P value of risk of suffering from fibrosis, by applying the algorithm:
- Pix is the sum of all p values assigned in step (c),
- This algorithm hereinafter the algorithm of the invention, relates the risk of a subject to suffering from fibrosis, according to the genetic polymorphisms previously analyzed and data on the environmental variables previously collected from the subject, through Pix.
- Pix is the sum of all the p values assigned in stage (c) to each of the variables: a p value is assigned to each polymorphism analyzed in stage (a) of the method of the invention, depending on the genotype. according to Table 3; To each data collected from the subject in step (b) of the method of the invention, a p value is also assigned according to Table 3. The sum of all the p values constitutes the Pix value included in the algorithm of the invention.
- the application of the algorithm of the invention makes it possible to calculate the P value of a subject's risk of suffering from fibrosis.
- the "P value of risk of suffering fibrosis” also called, “specific risk value of generating fibrosis", or “P value” simply, terms used interchangeably in the present invention
- the calculated value is as much as one, and can also be interpreted in terms of percentage, multiplying the calculated value by 100.
- the method of the invention allows predicting a subject's risk of suffering from fibrosis.
- the implementation of the method of the invention is based, in addition to the collection of environmental data related to the subject, on the analysis of genetic polymorphisms, the polymorphisms of the invention.
- the means used for the analysis of said genetic polymorphisms may be part of a kit.
- kits hereinafter the "kit of the invention” which comprises the means for analyzing in vitro in a biological sample isolated from a subject, at least three genetic polymorphisms selected from the list consisting of rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene, rs12456284 of the SMAD4 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- the kit of the invention may further comprise the means for analyzing in vitro at least one genetic polymorphism selected from the list consisting of rs2228145 of the IL6R gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene. , and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- the kit of the invention further comprises the means for analyzing in vitro in the biological sample isolated from the subject, at least one genetic polymorphism selected from the list consisting of rs2228145 of the IL6R gene, rs9493150 of the CTGF gene. , rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, and any other polymorphism that is in linkage disequilibrium with said genetic polymorphisms.
- the kit of the invention comprises the means for analyzing in vitro in a biological sample isolated from the subject, the genetic polymorphisms rs2228145 of the IL6R gene, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene.
- the biological sample comes from any tissue susceptible to DNA extraction.
- the biological sample could be, for example, but not limited to, a tissue or fluid sample, such as blood, plasma, serum, oral mucosa, bronchoalveolar lavage, lymph, or ascites fluid.
- the biological sample is selected from the list consisting of tissue, oral mucosa, blood, plasma, serum and lymph.
- kits for analyzing genetic polymorphisms in vitro are understood to mean all those reagents necessary to analyze the polymorphisms of the invention in vitro (primers, probes, buffers, enzymes, coenzymes, substrates).
- the kits can include all the supports and containers necessary for their start-up and optimization (plastic tubes, plates, reagents, etc.).
- the kits may also contain other molecules, genes, proteins or probes of interest, which serve as positive and negative controls.
- genetic polymorphisms can be analyzed by techniques and methods known in the state of the art, including techniques and methods different from those presented here. These methods and techniques have been explained in the previous inventive aspect, and both they and their preferred embodiments are applicable to the kit of the invention.
- the means for analyzing in vitro the polymorphisms of the invention comprise the reagents necessary to carry out the amplification technique, preferably POR, and/or sequencing.
- the means for analyzing in vitro the polymorphisms of the invention comprise primers and/or probes that specifically detect said genetic polymorphisms.
- the primers and/or probes comprise, or consist of, the nucleotide sequences: SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 13, SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 21, SEQ ID NO: 22, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, and/or any combination of them.
- the means comprise probes that specifically detect the polymorphisms of the invention.
- the probes that detect said polymorphisms are selected from the list consisting of: SEQ ID NO: 3, SEQ ID NO: 4, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 11, SEQ ID NO: 12, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 20, SEQ ID NO: 23, SEQ ID NO: 24, SEQ ID NO: 27, SEQ ID NO : 28, and any combination of them.
- kits further comprise instructions for carrying out the analysis of the polymorphisms of the invention and/or the method of the invention.
- These instructions may be present in the aforementioned kits in a variety of forms, one or more of which may be present in the kit.
- One way in which these instructions may be present is as printed information on a suitable medium or substrate, e.g. e.g., a sheet or sheets of paper on which the information is printed, on the kit packaging, on a package insert, etc.
- Another medium would be a computer-readable medium, for example, a CD, USB, etc., on which the information has been recorded.
- Another medium that may be present is a website address that can be used over the Internet to access information at a remote site. Any convenient media may be present in the kits.
- the kit of the invention which comprises the means for analyzing the polymorphisms of the invention in vitro, has utility in the method of the invention.
- the invention relates to the use of the kit of the invention in the method of the invention.
- kit and use of the kit of the invention have been explained for the method of the invention, and both they and their preferred embodiments are also applicable for the kit of the invention and its use in the method of the invention.
- ROC curve graph of the prediction model taking into account as variables the genetic polymorphisms rs2228145 of the IL6R gene, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, rs8032158 of the gene NEDD4 and rs12456284 of the SMAD4 gene, and the environmental variables use or non-use of platelet-rich plasma in the treatment of the subject, degree of obesity, area of the body susceptible to fibrosis, and sex of the subject, in which each point on the graph shows a possible cut-off point for the model in which it reports on its specific sensitivity at that point (Y-axis) with respect to its 1-specificity (X-axis). Diagonally on the graph (from 0.0 to 1.1) the diagonal reference line or non-discrimination line is represented. The diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the rs8032158 polymorphism of the NEDD4 gene as a genetic variable and the use or not of platelet-rich plasma as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the rs12456284 polymorphism of the SMAD4 gene as a genetic variable and the use or not of platelet-rich plasma as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the rs679620 polymorphism of the MMP3 gene as a genetic variable and the use or not of platelet-rich plasma as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the rs8032158 polymorphism of the NEDD4 gene as a genetic variable and the degree of obesity as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the rs12456284 polymorphism of the SMAD4 gene as a genetic variable and the degree of obesity as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the rs679620 polymorphism of the MMP3 gene as a genetic variable and the degree of obesity as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account as a genetic variable the genetic polymorphisms rs12456284 of the SMAD4 gene and rs679620 of the MMP3 gene, and as an environmental variable the use or not of platelet-rich plasma.
- the Diagonal segments are generated by ties.
- Fig. 9 ROC curve graph of the prediction model taking into account as a genetic variable the genetic polymorphisms rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene, and as an environmental variable the use or not of platelet-rich plasma.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account as genetic variable the genetic polymorphisms rs8032158 of the NEDD4 gene and rs679620 of the MMP3 gene. and as an environmental variable the use or not of platelet-rich plasma.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the genetic polymorphisms rs12456284 of the SMAD4 gene and rs679620 of the MMP3 gene as a genetic variable, and the degree of obesity as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the genetic polymorphisms rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene as a genetic variable, and the degree of obesity as an environmental variable.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account the genetic polymorphisms rs8032158 of the NEDD4 gene and rs679620 of the MMP3 gene as a genetic variable, and the degree of obesity as an environmental variable.
- the diagonal segments are generated by ties.
- Fig. 14 ROC curve graph of the algorithm prediction model taking into account as a genetic variable the genetic polymorphisms rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene and as an environmental variable the use or not of platelet-rich plasma.
- the diagonal segments are generated by ties.
- ROC curve graph of the prediction model taking into account as a genetic variable the genetic polymorphisms rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene and as an environmental variable the degree of obesity.
- the diagonal segments are generated by ties.
- the resulting DNA samples were analyzed by SNP genotyping analysis (polymorphisms rs2228145 of the IL6R gene, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, rs8032158 of the NEDD4 gene and rs1245628 4 of the SMAD4 gene) using the Biomark HD system methodology (Fluidigm). Patients were categorized taking into account the following environmental factors:
- platelet-rich plasma is type 13-00-11/24-00-11 as described in Kon E., et al., Expert Opin Biol Ther. , 20 (12):1447- 1460 (2020).
- BMI (Kg/m 2 ) Weight (Kg)/(Height (m)) 2 .
- Po 3.256 ix is the sum of all the values assigned according to Table 3, previously shown in this document.
- ROC analysis taking into account the rs2228145 IL6R, rs679620 of the MMP3 gene, rs9493150 of the CTGF gene, rs1800796 of the IL-6 gene, rs17563 of the BMP4 gene, rs8032158 of the NEDD4 gene v rs12456284 of the SMAD4 gene, v environmental variables use or non-use of pest-rich plasma in the treatment of the subject, degree of obesity, area of the body susceptible to fibrosis and sex of the subject.
- ROC analysis was performed (Fig. 1), establishing the risk of 50.90% of suffering from fibrosis as a cut-off point to classify the subject or patient in question as having high or low risk of developing fibrosis.
- the P value calculated for the subject is greater than 0.509, the subject is classified as having a high risk of suffering from fibrosis, while if the P value is less than 0.509, the subject is classified as having a low risk of suffering from fibrosis.
- said value is clearly lower than the selected cut-off point of 0.509, therefore, said patient has a low risk of developing fibrosis.
- the model showed sensitivity values of: 74.8% and specificity of 73.6%.
- sensitivity values of: 74.8% and specificity of 73.6%.
- Table 5 a classification table of “Observed” patients versus “Predicted” by the model (with .00 being no fibrosis and 1.00 being fibrosis) (Table 5).
- Table 6 provides the value of the area under the curve for the model, with an AUC (area under the curve) of 0.818 and its 95% confidence interval (95% CI) was 0.766-0.871.
- ROC analyzes were carried out taking into account a smaller number of variables, demonstrating that they are also useful in predicting a subject's risk of suffering from fibrosis, such as and as shown by the results obtained and summarized in Table 7, Table 8 and Table 9.
- Table 7 Summary of the results obtained by the ROC analysis (2 variables) depending on the genetic and environmental variables taken into account when applying the algorithm.
- Fig. 2 shows the ROC curve when applying the algorithm taking into account the rs8032158 polymorphism of the NEDD4 gene as a genetic variable and the use or not of platelet-rich plasma as an environmental variable.
- Fig. 3 shows the ROC curve when applying the algorithm taking into account the rs12456284 polymorphism of the SMAD4 gene as a genetic variable and the use or not of platelet-rich plasma as an environmental variable.
- Fig. 4 shows the ROC curve when applying the algorithm taking into account the rs679620 polymorphism of the MMP3 gene as a genetic variable and the use or not of platelet-rich plasma as an environmental variable.
- Fig. 5 shows the ROC curve when applying the algorithm taking into account the rs8032158 polymorphism of the NEDD4 gene as a genetic variable and the degree of obesity as an environmental variable.
- Fig. 6 shows the ROC curve when applying the algorithm taking into account the rs12456284 polymorphism of the SMAD4 gene as a genetic variable and the degree of obesity as an environmental variable.
- Fig. 7 shows the ROC curve when applying the algorithm taking into account the rs679620 polymorphism of the MMP3 gene as a genetic variable and the degree of obesity as an environmental variable.
- Table 8 Summary of the results obtained by the ROC analysis (3 variables) depending on the genetic and environmental variables taken into account when applying the algorithm.
- Fig. 8 shows the ROC curve when applying the algorithm taking into account as a genetic variable the genetic polymorphisms rs12456284 of the SMAD4 gene and rs679620 of the MMP3 gene, and as an environmental variable the use or not of platelet-rich plasma.
- Fig. 9 shows the ROC curve when applying the algorithm taking into account as a genetic variable the genetic polymorphisms rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene, and as an environmental variable the use or not of platelet-rich plasma.
- Fig. 10 shows the ROC curve when applying the algorithm taking into account as genetic variables the genetic polymorphisms rs8032158 of the NEDD4 gene and rs679620 of the MMP3 gene. and as an environmental variable the use or not of platelet-rich plasma.
- Fig. 11 shows the ROC curve when applying the algorithm taking into account as a genetic variable the genetic polymorphisms rs12456284 of the SMAD4 gene and rs679620 of the MMP3 gene, and as an environmental variable the degree of obesity.
- Fig. 12 shows the ROC curve when applying the algorithm taking into account as a genetic variable the genetic polymorphisms rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene, and as an environmental variable the degree of obesity.
- Fig. 13 shows the ROC curve when applying the algorithm taking into account as a genetic variable the genetic polymorphisms rs8032158 of the NEDD4 gene and rs679620 of the MMP3 gene, and as an environmental variable the degree of obesity.
- Table 9 Summary of the results obtained by the ROC analysis (4 variables) depending on the genetic and environmental variables taken into account when applying the algorithm.
- Fig. 14 shows the ROC curve when applying the algorithm taking into account as a genetic variable the genetic polymorphisms rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene and as an environmental variable the use or not of platelet-rich plasma.
- Fig. 15 shows the ROC curve when applying the algorithm taking into account as a variable genetics the genetic polymorphisms rs679620 of the MMP3 gene, rs8032158 of the NEDD4 gene and rs12456284 of the SMAD4 gene and as an environmental variable the degree of obesity.
Landscapes
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- Organic Chemistry (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Genetics & Genomics (AREA)
- Analytical Chemistry (AREA)
- Public Health (AREA)
- Pathology (AREA)
- Zoology (AREA)
- Wood Science & Technology (AREA)
- Physics & Mathematics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Biomedical Technology (AREA)
- Biotechnology (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- General Engineering & Computer Science (AREA)
- Biochemistry (AREA)
- Immunology (AREA)
- Microbiology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Theoretical Computer Science (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
Description
Claims
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP23742348.8A EP4538391A1 (en) | 2022-06-07 | 2023-06-07 | Method for obtaining useful data for the prediction of risk of fibrosis in a subject |
| US18/872,910 US20250349436A1 (en) | 2022-06-07 | 2023-06-07 | Method for obtaining useful data for the prediction of risk of fibrosis in a subject |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| ES202230497A ES2957479B2 (es) | 2022-06-07 | 2022-06-07 | Metodo de obtencion de datos utiles para la prediccion del riesgo de un sujeto de sufrir fibrosis |
| ESP202230497 | 2022-06-07 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2023237800A1 true WO2023237800A1 (es) | 2023-12-14 |
Family
ID=87377828
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/ES2023/070378 Ceased WO2023237800A1 (es) | 2022-06-07 | 2023-06-07 | Método de obtención de datos útiles para la predicción del riesgo de un sujeto de sufrir fibrosis |
Country Status (4)
| Country | Link |
|---|---|
| US (1) | US20250349436A1 (es) |
| EP (1) | EP4538391A1 (es) |
| ES (1) | ES2957479B2 (es) |
| WO (1) | WO2023237800A1 (es) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2805267A1 (en) | 2010-05-04 | 2011-11-10 | The Brigham And Women's Hospital, Inc. | Detection and treatment of fibrosis |
| EP2428583A1 (en) | 2010-09-10 | 2012-03-14 | Bioftalmik, S.L. | Method of prognosis for the success of filtering surgery and for determining the progress of cicatrization |
| ES2422874B1 (es) | 2012-03-12 | 2014-07-15 | Universidad Autnoma De Madrid | Método in vitro de pronóstico de fibrosis hepática grave |
| EP3425056A1 (en) * | 2017-07-07 | 2019-01-09 | Genepred Biotechnologies | Method for prognosing fibrosis progression |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7141380B2 (en) * | 2000-04-28 | 2006-11-28 | Michael Volker | Assessment of liver fibrosis scoring with serum marker algorithms |
| CN107099581B (zh) * | 2012-03-27 | 2021-07-13 | 弗·哈夫曼-拉罗切有限公司 | 预测、诊断和治疗特发性肺纤维化的方法 |
| US10939868B2 (en) * | 2014-07-18 | 2021-03-09 | Western Sydney Local Health District | Method of predicting rapid progression of fibrosis and therapy and reagents therefor |
-
2022
- 2022-06-07 ES ES202230497A patent/ES2957479B2/es active Active
-
2023
- 2023-06-07 US US18/872,910 patent/US20250349436A1/en active Pending
- 2023-06-07 EP EP23742348.8A patent/EP4538391A1/en active Pending
- 2023-06-07 WO PCT/ES2023/070378 patent/WO2023237800A1/es not_active Ceased
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2805267A1 (en) | 2010-05-04 | 2011-11-10 | The Brigham And Women's Hospital, Inc. | Detection and treatment of fibrosis |
| EP2428583A1 (en) | 2010-09-10 | 2012-03-14 | Bioftalmik, S.L. | Method of prognosis for the success of filtering surgery and for determining the progress of cicatrization |
| ES2422874B1 (es) | 2012-03-12 | 2014-07-15 | Universidad Autnoma De Madrid | Método in vitro de pronóstico de fibrosis hepática grave |
| EP3425056A1 (en) * | 2017-07-07 | 2019-01-09 | Genepred Biotechnologies | Method for prognosing fibrosis progression |
Non-Patent Citations (4)
| Title |
|---|
| "GenBank", Database accession no. NC_000007.14 |
| DAGNEAUX LOUIS ET AL: "Human Fibrosis: Is There Evidence for a Genetic Predisposition in Musculoskeletal Tissues?", THE JOURNAL OF ARTHROPLASTY, ELSEVIER, AMSTERDAM, NL, vol. 35, no. 11, 4 June 2020 (2020-06-04), pages 3343 - 3352, XP086292548, ISSN: 0883-5403, [retrieved on 20200604], DOI: 10.1016/J.ARTH.2020.05.070 * |
| KON E. ET AL., EXPERT OPIN BIOL THER., vol. 20, no. 12, 2020, pages 1447 - 1460 |
| NAKASHIMA MITSUKO ET AL: "A genome-wide association study identifies four susceptibility loci for keloid in the Japanese population", NATURE GENETICS, NATURE PUBLISHING GROUP US, NEW YORK, vol. 42, no. 9, 31 August 2010 (2010-08-31), pages 768, XP009530513, ISSN: 1061-4036, [retrieved on 20100815], DOI: 10.1038/NG.645 * |
Also Published As
| Publication number | Publication date |
|---|---|
| US20250349436A1 (en) | 2025-11-13 |
| ES2957479B2 (es) | 2025-07-28 |
| ES2957479A1 (es) | 2024-01-19 |
| EP4538391A1 (en) | 2025-04-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| ES2955026T3 (es) | Detección no invasiva de aneuploidía fetal en embarazos por ovodonación | |
| ES2453108T3 (es) | Nuevos polimorfismos de un único nucleótido y combinaciones de polimorfismos nuevos y conocidos para determinar la expresión específica de alelo del gen IGF2 | |
| ES2321845T3 (es) | Asociacion de polimorfismos de nucleotidos individuales en el ppar gamma, con la osteoporosis. | |
| KR101545258B1 (ko) | 운동 민감도 예측용 바이오마커 | |
| ES2660818T3 (es) | Marcadores genéticos para predecir la capacidad de respuesta a un compuesto de FGF-18 | |
| TW202012639A (zh) | 使用病原體核酸負荷確定個體是否患有癌症病況的系統及方法 | |
| WO2017112738A1 (en) | Methods for measuring microsatellite instability | |
| US20070065865A1 (en) | Polymorphisms Associated with Coronary Artery Disease | |
| KR101761801B1 (ko) | 코 표현형 판단용 조성물 | |
| ES2957479B2 (es) | Metodo de obtencion de datos utiles para la prediccion del riesgo de un sujeto de sufrir fibrosis | |
| ES2340459B1 (es) | Metodo para diagnosticar o determinar la predisposicion genetica a desarrollar miocardiopatia hipertrofica. | |
| ES2984296B2 (es) | Método de obtención de datos útiles para la predicción de la respuesta de un sujeto al tratamiento con plasma rico en plaquetas | |
| ES2611759B1 (es) | Uso de variantes alélicas (SNPs) en la región 6p21.33 para el diagnóstico, pronóstico y tratamiento de la Enfermedad de Ménière. | |
| JP5368101B2 (ja) | Pde4d対立遺伝子変異体と脳卒中との関連 | |
| ES2422874B1 (es) | Método in vitro de pronóstico de fibrosis hepática grave | |
| KR101795920B1 (ko) | 폐암 환자의 생존 예측용 slc5a10 다형성 마커 및 이를 이용한 폐암 생존 예후의 예측 방법 | |
| KR101673148B1 (ko) | 운동 민감도 예측용 바이오마커 | |
| KR102214804B1 (ko) | Pna 프로브를 이용한 성별 판별 및 클라인펠터 증후군의 진단 방법 | |
| KR102579423B1 (ko) | 단일염기다형성을 이용한 교정 치료 기간 예측용 조성물 및 이를 이용한 방법 | |
| KR102720023B1 (ko) | 바이설파이트 변환 평가용 키트 및 이를 이용한 평가 방법 | |
| RU2352641C1 (ru) | Способ диагностики наследственной предрасположенности к тромбофилии | |
| KR101673162B1 (ko) | 운동 민감도 예측용 바이오마커 | |
| CN103882110A (zh) | 一种检测强直性脊柱炎易感性的试剂 | |
| Dierks et al. | Fine mapping of a quantitative trait locus of equine osteochondrosis on chromosome 2 | |
| HK1127788B (en) | Association of pde4d allelic variants with stroke |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 23742348 Country of ref document: EP Kind code of ref document: A1 |
|
| WWE | Wipo information: entry into national phase |
Ref document number: 2023742348 Country of ref document: EP |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| ENP | Entry into the national phase |
Ref document number: 2023742348 Country of ref document: EP Effective date: 20250107 |
|
| WWP | Wipo information: published in national office |
Ref document number: 2023742348 Country of ref document: EP |
|
| WWP | Wipo information: published in national office |
Ref document number: 18872910 Country of ref document: US |











