Biomarkers for the diagnosis and treatment of fibrotic lung disease
US-2020171024-A1 · Jun 4, 2020 · US
US12396991B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12396991-B2 |
| Application number | US-202217930488-A |
| Country | US |
| Kind code | B2 |
| Filing date | Sep 8, 2022 |
| Priority date | Jun 26, 2017 |
| Publication date | Aug 26, 2025 |
| Grant date | Aug 26, 2025 |
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The present disclosure provides a method of treating a fibrotic lung disease in a subject comprising administering to the subject an effective amount of a therapeutic agent, wherein the subject is asymptomatic and wherein the subject is at risk of developing the fibrotic lung disease.
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What is claimed is: 1. A method of treating a fibrotic lung disease in an asymptomatic human subject within an at-risk population, wherein the fibrotic lung disease is familial interstitial pneumonia (FIP), pulmonary fibrosis, idiopathic pulmonary fibrosis (IPF), interstitial lung disease (ILD), an interstitial lung abnormality (ILA), an asymptomatic ILA, fibrotic interstitial lung disease (FILD), or rheumatoid arthritis-associated interstitial lung disease (RA-ILD), and wherein the subject has a blood relative with a fibrotic lung disease selected from the group consisting of familial interstitial pneumonia (FIP), pre-clinical pulmonary disease, pulmonary fibrosis, idiopathic pulmonary fibrosis (IPF), an interstitial lung abnormality (ILA), an asymptomatic ILA, interstitial lung disease (ILD), fibrotic interstitial lung disease (FILD) and rheumatoid arthritis-associated interstitial lung disease (RA-ILD), the method comprising: a) identifying pre-clinical pulmonary fibrosis (PrePF) in the subject by use of quantitative high resolution computed tomography (qHRCT) comprising the use of a convolutional neural network to quantify the extent of fibrosis in the subject and wherein the convolutional neural network architecture classifies image regions using pixel and texture features extracted by multiple convolutional layers at different scales; b) determining that the subject has the T allele of the MUC5B rs35705950 polymorphism; c) administering a therapeutic agent in an amount effective for the treatment of fibrotic lung disease to the subject, wherein the therapeutic agent: (i) prevents the onset or development of a sign or symptom of the fibrotic lung disease; (ii) delays the onset or development of a sign or symptom of the fibrotic lung disease when compared to the expected onset of the sign or symptom in the absence of treatment with the therapeutic agent; or (iii) agent reduces the severity of a sign or symptom of the fibrotic lung disease when compared to the expected severity of the sign or symptom in the absence of treatment with the therapeutic agent. 2. The method of claim 1 , wherein the subject presents radiographic Usual Interstitial Pneumonia (UIP). 3. The method of claim 1 , wherein the subject is greater than 40 years in age. 4. The method of claim 1 , wherein the blood relative is a sibling. 5. The method of claim 1 , wherein the MUC5B rs35705950 polymorphism is encoded by a sequence comprising SEQ ID NO: 7. 6. The method of claim 1 , wherein the therapeutic agent comprises a N-acetylcysteine, pirfenidone, or nintedanib. 7. The method of claim 1 , wherein PrePF is identified in the subject when a fibrosis score in the subject is above a predetermined cutoff value.
Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism · CPC title
having a carbocyclic group directly attached to the heterocyclic ring, e.g. cyproheptadine · CPC title
Alpha-amino acids, e.g. alanine or edetic acid [EDTA] (betaine A61K31/205; proline A61K31/401; tryptophan A61K31/405; histidine A61K31/4172; peptides not degraded to individual amino acids A61K38/00) · CPC title
Polymorphic or mutational markers · CPC title
for diseases caused by alterations of genetic material · CPC title
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