# US 10,308,985 B2 · Methods for diagnosing risk of renal allograft fibrosis and rejection > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,308,985 B2 - Document ID: US10308985B2 - Status: Granted - Kind: B2 - Application number: 15/320,208 - Filed: 2015-06-26 - Published: 2017-06-01 - Granted: 2019-06-04 - Earliest claimed: 2014-06-26 - Assignees: Icahn School of Medicine at Mount Sinai - Applicants: Icahn School of Medicine at Mount Sinai - Inventors: Barbara Murphy; Weijia Zhang - Web page: https://patentgrep.com/patent/US10308985B2 ## CPC - C12Q 1/6883: for diseases caused by alterations of genetic material - A61K 31/343: condensed with a carbocyclic ring, e.g. coumaran, bufuralol, befunolol, clobenfurol, amiodarone - A61K 31/436: the heterocyclic ring system containing a six-membered ring having oxygen as a ring hetero atom, e.g. rapamycin - A61K 31/4412: having oxo groups directly attached to the heterocyclic ring - A61K 31/52: Purines, e.g. adenine - A61K 31/5377: not condensed and containing further heterocyclic rings, e.g. timolol - A61K 31/573: substituted in position 21, e.g. cortisone, dexamethasone, prednisone or aldosterone - A61K 38/13: Cyclosporins - A61K 38/1774: {Immunoglobulin superfamily (e.g. CD2, CD4, CD8, ICAM molecules, B7 molecules, Fc-receptors, MHC-molecules)} - A61K 38/18: Growth factors; Growth regulators - A61K 38/1875: {Bone morphogenic factor; Osteogenins; Osteogenic factor; Bone-inducing factor} - A61K 38/2221: {Relaxins} - C07K 14/70521: {CD28, CD152} - C07K 2319/30: Non-immunoglobulin-derived peptide or protein having an immunoglobulin constant or Fc region, or a fragment thereof, attached thereto - C12Q 2600/118: Prognosis of disease development - C12Q 2600/158: Expression markers - C12Q 2600/178: miRNA, siRNA or ncRNA - G01N 2800/245: Transplantation related diseases, e.g. graft versus host disease - G01N 2800/347: Renal failures; Glomerular diseases; Tubulointerstitial diseases, e.g. nephritic syndrome, glomerulonephritis; Renovascular diseases, e.g. renal artery occlusion, nephropathy - G01N 2800/52: Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis - C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES - A61K: PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES (devices or methods specially adapted for bringing pharmaceutical products into particular physical or administering forms A61J3/00; chemical aspects of, or use of materials for deodorisation of air, for disinfection or sterilisation, or for bandages, dressings, absorbent pads or surgical articles A61L; soap compositions C11D) - C07K: PEPTIDES (peptides in foodstuffs A23; obtaining protein compositions for foodstuffs, working-up proteins for foodstuffs A23J; preparations for medicinal purposes A61K; peptides containing beta-lactam rings C07D; cyclic dipeptides not having in their molecule any other peptide link than those which form their ring, e.g. piperazine-2,5-diones, C07D; ergot alkaloids of the cyclic peptide type C07D519/02; macromolecular compounds having statistically distributed amino acid units in their molecules, i.e. when the preparation does not provide for a specific; but for a random sequence of the amino acid units, homopolyamides and block copolyamides derived from amino acids C08G69/00; macromolecular products derived from proteins C08H1/00; preparation of glue or gelatine C09H; single cell proteins, enzymes C12N; genetic engineering processes for obtaining peptides C12N15/00; compositions for measuring or testing processes involving enzymes C12Q; investigation or analysis of biological material G01N33/00) - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) ## Abstract Disclosed herein is a method for diagnosing a renal allograft recipient's risk for developing fibrosis of the allograft and allograft loss. The method includes determining the expression levels of certain microRNAs, which have been determined to be predictive of an allograft recipient's risk. Also disclosed herein is a method of treating a renal allograft recipient to inhibit fibrosis of the allograft and allograft loss, as well as kits for use in the methods disclosed herein. ## Claims ### Claim 1 A method for diagnosing and treating a renal allograft recipient at risk for developing fibrosis of the allograft and allograft loss, the method comprising: (a) determining the expression levels of said microRNAs in a blood sample using Nanostring analysis, wherein the microRNAs are hsa-mir-128, hsa-mir-29b-3p, hsa-mir-302b-3p, and hsa-mir-192-5p; (b) determining the expression levels of said microRNAs in a control sample using Nanostring analysis for each microRNA; (c) diagnosing the recipient as being at risk for developing fibrosis of the allograft and allograft loss if the expression levels of said miRNA samples are altered relative to a control level for each microRNA, and (d) treating the allograft recipient by administering an effective amount of a drug for treating fibrosis of the allograft and allograft loss. ### Claim 2 (depends on 1) The method of claim 1, further comprising diagnosing the recipient as being at high risk for developing fibrosis of the allograft and allograft loss if the expression levels of hsa-miR-128 and hsa-miR-302b-3p are increased relative to a control level for each microRNA, and the expression levels of hsa-miR-29b-3p and hsa-miR-192-5p are decreased relative to the control level for each microRNA based on the probability score cutoff determined from the training set; wherein said drug is an anti-rejection drug. ### Claim 3 (depends on 1) The method of claim 1, wherein determining the expression levels comprise isolating mRNA from the blood sample; synthesizing cDNA from the mRNA; and measuring the expression levels of microRNAs hsa-mir-128, hsa-mir-29b-3p, hsa-mir-302b-3p, and hsa-mir-192-5p from the sample. ### Claim 4 (depends on 1) The method of claim 1, wherein diagnosing the recipient's risk comprises calculating the recipient's risk by applying the expression levels determined in the recipient's sample to a penalized logistic regression fitting model. ### Claim 5 (depends on 4) The method of claim 4, wherein the penalized logistic regression fitting model from which the risk will be calculated utilizes the formula: log ⁢ ⁢ p ⁡ ( x ) 1 - p ⁡ ( x ) = β 0 + * ⁢ β 1 * ⁢ g 1 + β i * ⁢ g i + … + β 4 * ⁢ g 4 where (p(x) is the probability of developing fibrosis, β*i is penalized coefficiency and gi is the expression value of miRNA i. ### Claim 6 (depends on 2) The method of claim 2 wherein the anti-rejection drug is selected from the group consisting of cyclosporine and Belatacept. ### Claim 7 (depends on 6) The method of claim 6, which comprises administering between 4 and 6 mg/kg bodyweight/day of cyclosporine to the allograft recipient. ### Claim 8 (depends on 2) The method of claim 2, wherein the anti-rejection drug is an immunosuppressive or anti-proliferative agent. ### Claim 9 (depends on 8) The method of claim 8, wherein the immunosuppressive agent is a member selected from the group consisting of a mycophenolate mofetil (MMF), sirolimus, prednisone, Mycophenolate Mofetil, Mycophenolate Sodium and Azathioprine. ### Claim 10 (depends on 1) The method of claim 1, wherein determining the expression levels of miRNAs hsa-mir-128, hsa-mir-29b-3p, hsa-mir-302b-3p, and hsa-mir-192-5p comprises performing an assay selected from the group consisting of qPCR, microarray, and Nanostring analysis. ### Claim 11 (depends on 4) The method of claim 4, wherein the Nanostring analysis comprises annealing the cDNA comprising the microRNAs to barcode probes specific for the microRNAs, immobilizing the cDNA, and quantifying the probes bound to the cDNA by digital analyzer. ### Claim 12 (depends on 1) The method of claim 1, further comprising modifying the immunosuppression regimen of an allograft recipient diagnosed as being at high risk for fibrosis of the allograft and allograft loss. ### Claim 13 (depends on 12) The method of claim 12, wherein modifying the immunosuppression regimen comprises administering to the recipient an anti-rejection drug selected from the group consisting of Belatacept, rapamycin and Mycophenolate Mofetil. ### Claim 14 (depends on 12) The method of claim 12, wherein modifying the immunosuppression regimen comprises administering to the recipient an anti-fibrosis drug selected from the group consisting of Pirfenidone, relaxin, Bone morphogenetic protein 7 (BMP-7) and Hepatic growth factor (HGF) 6. ### Claim 15 (depends on 1) The method of claim 1 further comprising diagnosing the recipient as being at low risk for developing fibrosis of the allograft and allograft loss if the expression levels of hsa-miR-128 and hsa-miR-302b-3p are decreased relative to the control level for each microRNA, and the expression levels of hsa-miR-29b-3p and hsa-miR-192-5p are increased relative to the control level for each microRNA based on the probability score cutoff determined from the training set and wherein said drug is an anti-fibrotic agent. ### Claim 16 (depends on 15) The method of claim 15, further comprising administering an anti-fibrotic agent to the allograft recipient if the recipient is diagnosed as being at low risk for developing fibrosis of the allograft and allograft loss. ### Claim 17 (depends on 16) The method of claim 16, wherein the anti-fibrotic agent is selected from the group consisting of Pirfenidone, relaxin, Bone morphogenetic protein 7 (BMP-7) and Hepatic growth factor (HGF) 6. ### Claim 18 (depends on 1) The method of claim 1 wherein said anti-rejection drug is rapamycin. ### Claim 19 (depends on 15) The method of claim 15, further comprising calculating the probability score of fibrosis risk for said recipient using the equation: log ⁢ ⁢ p ⁡ ( x ) 1 - p ⁡ ( x ) = β 0 + * ⁢ β 1 * ⁢ g 1 + β i * ⁢ g i + … + β 4 * ⁢ g 4 where (p(x) is the probability of developing fibrosis, β*i is penalized coefficiency and gi is the expression value of miRNA i.