Treatment of pulmonary diseases based on interleukin-33 (IL-33) polygenic risk score stratification

Abstract

The present invention provides methods of treating a subject with a pulmonary disease that is likely to respond to an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, or an IL-13 receptor antagonist based on the subject's IL-33 asthma polygenic risk score.

Description

[Technical field]

[0001] Sequence Listing Reference This application contains a Sequence Listing, which has been submitted electronically as an XML file 14 kilobytes in size, entitled 381203560SEQ, created on November 9, 2022. The Sequence Listing is incorporated herein by reference.

[0002] Field The present invention relates to the field of therapeutic treatment of pulmonary diseases. More specifically, the present disclosure relates to methods of increasing the efficacy of interleukin-33 (IL-33) antagonist, interleukin-4 receptor alpha antagonist, and / or interleukin-13 receptor antagonist therapy in subjects with pulmonary diseases by identifying subjects likely to respond to an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist. [Background technology]

[0003] Asthma is an inflammatory disease of the airways of the lungs. The condition is characterized by a variety of recurrent symptoms, reversible airflow obstruction, and easily provoked bronchospasm. Diagnosis of asthma may include pulmonary function testing with spirometry, including assessment of forced expiratory volume in 1 second (FEV1), peak expiratory flow, and annual exacerbation rate. Treatment of asthma involves the administration of immediate or long-term effective medications. Salbutamol and albuterol are the mainstay of immediate-acting medications, while inhaled corticosteroids (ICS) have been the cornerstone of long-term treatment for many years. Recently, antibodies such as mepolizumab, dupilumab, and omalizumab have been used in connection with certain types of asthma. However, it is difficult to predict whether a particular subject will respond to a particular antibody therapy. It is also difficult to predict prospectively the annual exacerbation rate or loss of asthma control (LOAC).

[0004] Chronic obstructive pulmonary disease (COPD) is characterized, in part, by symptoms of airflow limitation, emphysema, and chronic bronchitis. COPD is often exacerbated by daily activities, which makes daily tasks difficult. Tobacco smoke is the main risk factor, but other factors include pollution, genetics, and exposure to dust and chemicals in the workplace. Diagnosis of COPD often involves spirometry, including measuring the patient's FEV1 value. Current treatments include smoking cessation, short-acting bronchodilators, phosphodiesterase 4 inhibitors, corticosteroids, and, in severe cases, antibiotics. However, it is difficult to predict whether a patient will respond to a particular treatment. Summary of the Invention

[0005] The present disclosure provides a method of treating a subject suffering from or at risk of developing a pulmonary disease such as asthma and COPD, the method comprising administering an IL-33 antagonist to the subject if the subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS) is greater than a threshold IL-33 asthma PRS, or administering an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist to the subject if the subject's IL-33 asthma PRS is less than a threshold IL-33 asthma PRS, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma.

[0006] The disclosure also provides a method of treating a subject suffering from or at risk of developing a pulmonary disease such as asthma and COPD, the method comprising administering to the subject an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist, and administering more than a standard amount of a composition for treating an asthma exacerbation if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma.

[0007] The disclosure also provides a method of determining whether a subject should be administered an interleukin-4 receptor alpha antagonist, an interleukin-13 receptor antagonist, and / or an IL-33 antagonist for the treatment of a pulmonary disease such as asthma and COPD, the method comprising determining, or having determined, the subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), where the IL-33 asthma PRS is a weighted sum of multiple genetic variants near or within the IL-33 and IL1RL1 genes associated with asthma. and determining, or having determined, whether the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS; if the subject's IL-33 asthma PRS is equal to or greater than the threshold IL-33 asthma PRS, then the subject should be administered an IL-33 antagonist; or if the subject's IL-33 asthma PRS is less than the threshold IL-33 asthma PRS, then the subject should be administered an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist.

[0008] The disclosure also provides a method of determining whether a subject suffering from asthma should be administered more than a standard amount of a composition for treating an asthma exacerbation, the method comprising determining or having determined the subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), where the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, then the subject should be administered more than a standard amount of a composition for treating an asthma exacerbation.

[0009] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate certain features of the present disclosure. The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. [Brief description of the drawings]

[0010] [Figure 1A] We show significant genetic associations with annual asthma exacerbation rates. Specifically, quartiles of IL33 PRS are associated with patient response to efficacy of dupilumab treatment. [Figure 1B] We show significant genetic associations with annual asthma exacerbation rates. Specifically, quartiles of IL33 PRS are associated with patient response to efficacy of dupilumab treatment. [Figure 2A] The multiple primary endpoint measures of change in FEV1 are shown. Genetic effects are not significant for those in the same treatment group. [Figure 2B] The multiple primary endpoint measures of change in FEV1 are shown. Genetic effects are not significant for those in the same treatment group. [Diagram 3] When comparing dupilumab-treated and placebo groups, subjects in the higher quartiles of IL33 PRS (75 and 100 groups) show a significantly associated lower response efficacy to dupilumab. [Figure 4A] Figure 2 shows that IL-33 asthma PRS determined using the LDpred method was not associated with change in FEV1 at week 12 in dupilumab-treated mixed race American patients. [Figure 4B] Figure 2 shows that IL-33 asthma PRS determined using the LDpred method was not associated with change in FEV1 at week 12 in dupilumab-treated mixed race American patients. [Diagram 5] Figure 2 shows that the IL-33 asthma PRS determined using the LDpred method showed a trend towards a decreased risk of loss of asthma control (LOAC) in itepekimab monotreated European subjects. [Figure 6] 13 shows that the IL-33 asthma PRS demonstrated a trend towards reduced risk of LOAC in itepekimab monotreated European and mixed race American subjects. [Figure 7A]Figure 2 shows that the IL-33 asthma PRS determined using the LDpred method was significantly associated with asthma in GHS_GSA European subjects. [Figure 7B] Figure 2 shows that the IL-33 asthma PRS determined using the LDpred method was significantly associated with asthma in GHS_GSA European subjects. [Figure 8A] Figure 2 shows that the IL-33 asthma PRS determined using the LDpred method was significantly associated with eosinophil count in GHS_GSA European subjects. [Figure 8B] Figure 2 shows that the IL-33 asthma PRS determined using the LDpred method was significantly associated with eosinophil count in GHS_GSA European subjects. [Figure 9-1] We show that 11 of 543 variants in the IL-33 asthma PRS determined by LDpred training were disease- or trait-associated variants in HGMD. [Figure 9-2] We show that 11 of 543 variants in the IL-33 asthma PRS determined by LDpred training were disease- or trait-associated variants in HGMD. [Figure 10A] We show that the IL-33 asthma polygenic risk score for mixed race American subjects (IL-33AMR asthma PRS), determined using the LDpred method, was significantly associated with asthma risk in mixed race American subjects in Mexico City. [Figure 10B] We show that the IL-33 asthma polygenic risk score for mixed race American subjects (IL-33AMR asthma PRS), determined using the LDpred method, was significantly associated with asthma risk in mixed race American subjects in Mexico City. [Figure 11] We show that 6 of 205 variants in the IL-33AMR asthma PRS determined by LDpred training were associated with HGMD disease or trait. [Figure 12A] We describe the IL-33 asthma PRS determined with LDpred training in a clinical trial of itepekimab-treated mixed European and mixed race American subjects. [Figure 12B] We describe the IL-33 asthma PRS determined with LDpred training in a clinical trial of itepekimab-treated mixed European and mixed race American subjects. [Figure 13] Figure 1 shows that the IL-33 asthma PRS trends toward a decreased risk of LOAC in itepekimab monotreated European and mixed American subjects. [Figure 14] We show that the IL-33 asthma PRS was associated with increased baseline basophil counts in European subjects in clinical trials named DRI12544 and EFC13579. [Figure 15] 1 shows that the IL-33 asthma PRS was significantly associated with increased asthma exacerbations in dupilumab-treated European subjects in clinical trials named DRI12544 and EFC13579. [Figure 16A] 1 shows the combined IL-33 asthma PRS determined with LDpred training for European and mixed American subjects in clinical trials named DRI12544 and EFC13579. [Figure 16B] 1 shows the combined IL-33 asthma PRS determined with LDpred training for European and mixed American subjects in clinical trials named DRI12544 and EFC13579. [Figure 17A] Patients with IL-33 Asthma PRS scores in the top 25% responded less effectively to dupilumab compared with patients with lower IL-33 Asthma PRS scores who were treated with dupilumab; the patients were mixed European and mixed American subjects in trials named DRI12544 and EFC13579. [Figure 17B] Patients with IL-33 Asthma PRS scores in the top 25% responded less effectively to dupilumab compared with patients with lower IL-33 Asthma PRS scores who were treated with dupilumab; the patients were mixed European and mixed American subjects in trials named DRI12544 and EFC13579. [Figure 18A]Patients with IL-33 Asthma PRS scores in the bottom quartile of dupilumab had the greatest increase in FEV1 compared to placebo; (0.3-0.14) indicates the greatest difference compared to other quartiles. [Figure 18B] Patients with IL-33 Asthma PRS scores in the bottom quartile of dupilumab had the greatest increase in FEV1 compared to placebo; (0.3-0.14) indicates the greatest difference compared to other quartiles. [Figure 19A] FIG. 1 shows the relationship between change in IL-33 asthma PRS and FVC at week 12 in European and Mixed American subjects. [Figure 19B] FIG. 1 shows the relationship between change in IL-33 asthma PRS and FVC at week 12 in European and Mixed American subjects. [Figure 20A] FIG. 1 shows no association between IL-33 asthma PRS and the proportion of GHS_GSA European subjects with asthma exacerbations. [Figure 20B] 1 shows the lack of association between IL-33 asthma PRS and proportion of subjects taking asthma medications. [Figure 21] Figure 1 shows the relationship between the IL-33 Asthma PRS and the proportion of GHS_GSA European patients with COPD. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Genetic factors play an important role in the risk of developing disease and can potentially affect how an individual responds to drug treatment. A polygenic risk score (PRS) combines information from multiple genetic variants obtained from disease association studies to create a single composite quantitative measure for each individual that reflects the genetic risk of disease. Individuals with a higher number of risk alleles for a particular disease will have a higher PRS than individuals with a lower number of alleles for the same particular disease. Risk can be assessed at some threshold, for example, percentiles, standard deviation units of population distribution, or absolute values. The present disclosure generally relates to the unexpected finding that stratification of subjects by IL-33 asthma PRS is useful for identifying subjects likely to respond to IL-33 antagonists, interleukin-4 receptor alpha antagonists, and / or interleukin-13 receptor antagonists in the treatment of lung diseases, such as asthma and COPD.

[0012] Various terms relating to aspects of the present disclosure are used throughout the specification and claims. Such terms are to be given their ordinary meaning in the art unless otherwise indicated. Other specifically defined terms are to be interpreted in a manner consistent with the definitions provided herein.

[0013] Unless otherwise expressly stated, it is in no way intended that the methods or aspects described herein be interpreted as requiring that their steps be performed in a particular order. Accordingly, it is in no way intended that a method claim be inferred in any respect unless the claims or specification specifically state that the steps are limited to a particular order. This applies to all possible unexpressed grounds for interpretation, including matters of logic, obvious meanings derived from grammatical constructions or punctuation with respect to the arrangement or operational flow of the steps, or the number or type of aspects described herein.

[0014] As used in this document, the singular forms "a," "an," and "the" include plural referents unless the context clearly indicates otherwise. As used herein, the term "about" means that the numerical values ​​described are approximate and that small variations will not significantly affect the practice of the disclosed embodiments. When numerical values ​​are used, unless otherwise indicated, the term "about" means that the numerical values ​​can vary by ±10% and still be within the scope of the disclosed embodiments.

[0015] As used herein, the term "subject" includes any animal, including mammals. Mammals include, but are not limited to, farm animals (e.g., horses, cattle, pigs), pets (e.g., dogs, cats), laboratory animals (e.g., mice, rats, rabbits), and non-human primates (e.g., apes and monkeys). In some embodiments, the subject is a human. In some embodiments, the subject is a patient under the care of a physician.

[0016] The present disclosure generally relates to methods and compositions for treating subjects suffering from or at risk of developing a pulmonary disease, such as asthma and COPD. In some embodiments, the pulmonary disease comprises asthma. In some embodiments, the pulmonary disease comprises COPD.

[0017] Without being limited to a particular theory, it is believed that the IL-33 asthma PRS calculated according to the methods presented herein allows for the identification of subjects likely to respond to an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist. Moreover, surprisingly and unexpectedly, the IL-33 asthma PRS is also predictive of a subject's response to an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist.

[0018] In some embodiments, subjects treatable by the methods of the present disclosure have had asthma within the past 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 months. Subjects treatable by the methods of the present invention include subjects who have been hospitalized for asthma-related symptoms, as well as subjects who are currently hospitalized.

[0019] In some embodiments, subjects treatable by the methods of the present disclosure have had COPD within the past 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, or 18 months. Subjects treatable by the methods of the present invention include subjects who have been hospitalized for COPD-related symptoms, as well as subjects who are currently hospitalized.

[0020] In some embodiments, subjects may be selected based on an IL-33 asthma PRS, where the IL-33 asthma PRS comprises the sum or weighted sum of multiple genetic variants associated with asthma or COPD and is calculated using at least about 2, at least about 3, at least about 4, at least about 5, at least about 10, at least about 20, at least about 30, at least about 40, at least about 50, at least about 60, at least about 70, at least about 80, at least about 100, at least about 120, at least about 150, at least about 200, at least about 250, at least about 300, at least about 400, at least about 500, at least about 1,000, at least about 2,000, at least about 3,000, at least about 4,000, at least about 5,000, at least about 6,000, at least about 7,000, at least about 8,000, at least about 9,000, or at least about 10,000 genetic variants. If the subject has an IL-33 asthma PRS that is equal to or greater than the threshold IL-33 asthma PRS, the subject should be administered an IL-33 antagonist. Alternatively, if the subject has an IL-33 asthma PRS that is less than the threshold IL-33 asthma PRS, the subject should be administered an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist. In some embodiments, the sum of the multiple genetic variants associated with asthma is a weighted sum of the multiple genetic variants associated with asthma. In some embodiments, the genetic variant is selected from any one or more of the variants listed in Table 1 (Variant D according to the GRCh38 / hg38 human genome assembly coordinates).

[0021] [Table 1-1]

[0022] [Table 1-2]

[0023] [Table 1-3]

[0024]

Table 1-4

[0025]

Table 1-5

[0026]

Table 1-6

[0027]

Table 1-7

[0028]

Table 1-8

[0029]

Table 1-9

[0030]

Table 1-10

[0031]

Table 1-11

[0032]

Table 1-12

[0033]

Table 1-13

[0034] [Table 1-14]

[0035] [Table 1-15]

[0036] [Table 1-16]

[0037] In some embodiments, the genetic variant is selected from any one or more of the variants listed in Table 2, which is a subset of the variants in Table 1 (variant IDs according to GRCh38 / hg38 human genome assembly coordinates).

[0038] [Table 2]

[0039] Risk assessment using multiple genetic variants provides the advantage of improved predictive power. In some embodiments, one or more of the genetic variants are single nucleotide polymorphisms (SNPs). In some embodiments, one or more of the genetic variants are insertions. In some embodiments, one or more of the genetic variants are deletions. In some embodiments, one or more of the genetic variants are structural variants. In some embodiments, one or more of the genetic variants are copy number variations. In any embodiment described herein, the presence or absence or amount of any genetic variant described herein can be replaced by the presence or absence or expression level of any particular mRNA molecule.

[0040] In some embodiments, the disclosure provides a method of determining an IL-33 asthma PRS in a subject, the method comprising: detecting at least about 2 genetic variants, at least about 5 genetic variants, at least about 10 genetic variants, at least about 15 genetic variants, at least about 20 genetic variants, at least about 30 genetic variants, at least about 40 genetic variants, at least about 50 genetic variants, at least about 60 genetic variants, at least about 70 genetic variants, at least about 100 genetic variants, at least about 200 genetic variants, at least about 300 genetic variants, at least about 40 ...50 genetic variants, at least about 60 genetic variants, at least about 70 genetic variants, at least about 100 genetic variants, at least about 200 genetic variants, at least about 300 genetic variants, at least about 400 genetic variants, at least about 50 genetic variants, at least about 50 genetic variants, at least about 60 genetic variants, at least The method includes determining whether at least about 1,000 genetic variants, at least about 2,000 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, or at least about 10,000 genetic variants are present in the subject's biological sample. The presence of the risk allele increases the subject's IL-33 asthma PRS.

[0041] In some embodiments, the disclosure provides a method of determining an IL-33 asthma PRS in a subject, the method comprising identifying whether one or more genetic variants associated with risk of developing asthma are present in a biological sample from a subject, and calculating an IL-33 asthma PRS for the subject based on the identified genetic variants (wherein the IL-33 asthma PRS is calculated, for example, by summing, e.g., aggregating, the risk scores (or weighted risk scores) associated with each identified genetic variant). The number of identified genetic variants may be at least about 2 genetic variants, at least about 5 genetic variants, at least about 10 genetic variants, at least about 15 genetic variants, at least about 20 genetic variants, at least about 30 genetic variants, at least about 40 genetic variants, at least about 50 genetic variants, at least about 95 genetic variants, at least about 100 genetic variants, at least about 200 genetic variants, at least about 3 ... At least about 500 genetic variants, at least about 1,000 genetic variants, at least about 2,000 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, or at least about 10,000 genetic variants.In some embodiments, the disclosure provides a method of determining an IL-33 asthma PRS in a subject comprising identifying whether genetic variants associated with risk of developing asthma are present in a biological sample from the subject, wherein the identification process identifies at least about 2 genetic variants, at least about 5 genetic variants, at least about 10 genetic variants, at least about 15 genetic variants, at least about 20 genetic variants, at least about 30 genetic variants, at least about 40 genetic variants, at least about 50 genetic variants, at least about 95 genetic variants, at least about 100 genetic variants, at least about 15 ... At least about 100 genetic variants, at least about 200 genetic variants, at least about 500 genetic variants, at least about 1,000 genetic variants, at least about 2,000 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, or at least about 10,000 genetic variants.

[0042] As an exemplary method, the IL-33 asthma PRS can be determined, for example, from data obtained from a GWAS of disease risk. For example, in a representative hypothetical GWAS, the GWAS may identify four genetic variants associated with the disease. Each genetic variant may be associated with one or more genes. Values ​​such as odds ratios can be calculated for each individual genetic variant. The IL-33 asthma PRS of a particular subject can be determined by multiplying the log value of the individual odds ratios of each variant by the number effect allele (the number of copies of the genetic variant in the genome, i.e., 0, 1, or 2), and then summing the resulting values. This type of determination can be described in Table 3.

[0043] [Table 3]

[0044] Therefore, the IL-33 asthma PRS of a subject is the sum of the individual values ​​in the last column of the table, taking into account any number of genetic variants associated with a particular disease.This simplified methodology for determining the IL-33 asthma PRS of a subject is for illustrative purposes only and is not to be construed as limiting in any way.The IL-33 asthma PRS of the above table is a weighted score, since each genetic variant may carry out different weighting depending on the specific odds ratio and number effect allele value.

[0045] In some embodiments, the disclosure provides a method of assigning an asthma risk group to a subject, the method comprising: determining whether a genetic variant is present in a biological sample from a subject; calculating an IL-33 asthma PRS for the subject based on the identified genetic variant; and assigning the subject to a risk group based on the IL-33 asthma PRS. A threshold PRS can be determined for each tier. In some embodiments, the tiers can be expressed in percentiles. As a non-limiting example, the IL-33 asthma PRS can be divided into quintiles, e.g., top quintile, upper middle quintile, middle quintile, lower middle quintile, and bottom quintile, with the top quintile of IL-33 asthma PRS corresponding to the highest genetic risk group and the bottom quintile of IL-33 asthma PRS corresponding to the lowest genetic risk group. The number of genetic variants identified can be at least about 2 genetic variants, at least about 5 genetic variants, at least about 10 genetic variants, at least about 15 genetic variants, at least about 20 genetic variants, at least about 30 genetic variants, at least about 40 genetic variants, at least about 50 genetic variants, at least about 95 genetic variants, at least about 100 genetic variants, at least about 200 genetic variants, at least about 500 genetic variants, at least about 1,000 genetic variants, at least about 2,000 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, or at least about 10,000 genetic variants associated with asthma.

[0046] In some embodiments, the disclosure provides a method of selecting a subject or candidate for administration of an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist, the method comprising ...13 receptor antagonist, The method includes identifying whether at least about 1,000 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, or at least about 10,000 genetic variants are present in a biological sample from the subject or candidate; calculating an IL-33 asthma PRS for the subject or candidate based on the identified genetic variants; and selecting the subject or candidate for administration of an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist.

[0047] In some embodiments, the disclosure provides a method of selecting a subject or candidate for administration of an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist, the method comprising: detecting at least about 2 genetic variants, at least about 5 genetic variants, at least about 10 genetic variants, at least about 15 genetic variants, at least about 20 genetic variants, at least about 30 genetic variants, at least about 40 genetic variants, at least about 50 genetic variants, at least about 95 genetic variants, at least about 100 genetic variants, at least about 200 genetic variants, at least about 500 genetic variants, at least about 1,000 genetic variants, at least about 2,000 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, at least about 10,000 genetic variants, at least about 15 ... determining whether at least about 0 genetic variants, at least about 3,000 genetic variants, at least about 4,000 genetic variants, at least about 5,000 genetic variants, at least about 6,000 genetic variants, at least about 7,000 genetic variants, at least about 8,000 genetic variants, at least about 9,000 genetic variants, or at least about 10,000 genetic variants are present in a biological sample from each subject or candidate of the population of subjects or candidates; calculating an IL-33 asthma PRS for each subject or candidate based on the identified genetic variants; and selecting subjects or candidates for administration of an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist.

[0048] In some embodiments, the number of identified genetic variants is at least four genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least five genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least ten genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least twenty genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least thirty genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least forty genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least fifty genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least seventy genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least one hundred genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least five hundred genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 1,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 2,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 3,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 4,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 5,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 6,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 7,000 genetic variants associated with asthma.In some embodiments, the number of identified genetic variants is at least 8,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 9,000 genetic variants associated with asthma. In some embodiments, the number of identified genetic variants is at least 10,000 genetic variants associated with asthma.

[0049] In some embodiments, the risk assessment comprises a maximum weighted IL-33 asthma PRS score, including but not limited to the top 50%, 55%, 60%, 70%, 80%, 90%, or 95% of the IL-33 asthma PRS scores of the subject population. In some embodiments of the present disclosure, the threshold PRS is a value within the top 50%, 55%, 60%, 70%, 80%, 90%, or 95% percentile of the PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the top 50% percentile of the PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the top 55% percentile of the PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the top 60% percentile of the PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the top 65% percentile of the PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the top 70% percentile of the PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the upper 75% percentile of PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the upper 80% percentile of PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the upper 85% percentile of PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the upper 90% percentile of PRS values. In some embodiments of the present disclosure, the threshold PRS is a value within the upper 95% percentile of PRS values.

[0050] In some embodiments, the identified genetic variants include the highest risk genetic variants or genetic variants in the top 10%, top 20%, top 30%, top 40%, or top 50% of weighted risk scores. In some embodiments, the identified genetic variants include the highest risk genetic variants or genetic variants in the top 10% of weighted risk scores. In some embodiments, the identified genetic variants include the highest risk genetic variants or genetic variants in the top 20% of weighted risk scores. In some embodiments, the identified genetic variants include the highest risk genetic variants or genetic variants in the top 30% of weighted risk scores. In some embodiments, the identified genetic variants include the highest risk genetic variants or genetic variants in the top 40% of weighted risk scores. In some embodiments, the identified genetic variants include the highest risk genetic variants or genetic variants in the top 50% of weighted risk scores.

[0051] In some embodiments, the identified genetic variants comprise genetic variants associated with asthma in the top 10%, top 20%, top 30%, top 40%, or top 50% of the p-value range. In some embodiments, the identified genetic variants comprise genetic variants associated with asthma in the top 10% of the p-value range. In some embodiments, the identified genetic variants comprise genetic variants associated with asthma in the top 20% of the p-value range. In some embodiments, the identified genetic variants comprise genetic variants associated with asthma in the top 30% of the p-value range. In some embodiments, the identified genetic variants comprise genetic variants associated with asthma in the top 40% of the p-value range. In some embodiments, the identified genetic variants comprise genetic variants associated with asthma in the top 50% of the p-value range.

[0052] In some embodiments, each of the identified genetic variants has a p-value of about 10 -1 , about 10 -2 , about 10 -3 , about 10-4 , about 10 -5 , about 10 -6 , about 10 -7 , about 10 -8 , about 10 -9 , about 10 -10 , about 10 -11 , about 10 -12 , about 10 -13 , about 10 -14 , or about 10 -15 In some embodiments, the identified genetic variants include those associated with the IL-33 gene that have a p-value of 5×10 or less. -8 The present invention includes genetic variants associated with the IL-33 gene that are less than 50%.

[0053] In some embodiments, the identified genetic variants have a mean of about 1.0 or more, about 1.5 or more, about 1.75 or more, about 2.0 or more, about 2.25 or more, or about 2.75 or more for the upper half of the distribution (up to 50%); about 1.5 or more, about 1.75 or more, about 2.0 or more, about 2.25 or more, about 2.5 or more, or about 2.75 or more for the upper quarter of the distribution (up to 55%); about 1.0 or more, about 1.5 or more, about 1.75 or more, about 2.0 or more, about 2.25 or more, or about 2.75 or more for up to 60% of the distribution; about 1.0 or more, about 1.5 or more, about 1.75 or more, about 2.0 or more for up to 70% of the distribution, or about 2.25 or more; or about 2.75 or more; up to 80% of the distribution; up to 90% of the distribution; or up to 95% of the distribution; or an odds ratio (OR) of about 1.0 or more, about 1.5 or more, about 1.75 or more, about 2.0 or more, about 2.25 or more, or about 2.75 or more for the remainder of the reference population. In some embodiments, the odds ratio (OR) may range from about 1.0 to about 1.5, about 1.5 to about 2.0, about 2.0 to about 2.5, about 2.5 to about 3.0, about 3.0 to about 3.5, about 3.5 to about 4.0, about 4.0 to about 4.5, about 4.5 to about 5.0, about 5.0 to about 5.5, about 5.5 to about 6.0, about 6.0 to about 6.5, or about 6.5 to about 7.0. In some embodiments, high risk subjects include subjects with an IL-33 asthma PRS score in the top decile, quintile, or tertile of a reference population.

[0054] In some embodiments, the identified genetic variants include genetic variants with the highest genetic variant performance in a reference population. In some embodiments, the genetic variant performance is calculated with respect to asthma risk based on statistical significance, strength of association, and / or probability distribution.

[0055] In some embodiments, the genetic variant score is calculated using any PRS calculation method. In some embodiments, the genetic variant score is calculated using a PRS calculation method such as the LDpred method (or its variants and / or versions). LDpred is a Bayesian approach that calculates the posterior average effect for all variants based on a prior (effect size in a prior genome-wide association study) and subsequent shrinkage based on linkage disequilibrium. LDpred creates a PRS using genome-wide polymorphisms with weights obtained from a set of summary statistics of genome-wide association studies (GWAS). See Vilhjalmsson et al., Am. J. Hum. Genet., 2015, 97, 576-92. In some embodiments, alternative approaches to calculate gene variant scores may be used, including SBayesR (Lloyd-Jones, LR, World Wide Web at biorxiv.org / content / biorxiv / early / 2019 / 01 / 17 / 522961.full.pdf), Pruning and Thresholding (P&T) (Purcell, Nature, 2009, 460, 748-752), and Conditional Joint Analysis (COJO) (Yang et al., Nat. Genet., 2012, 44, 369-375). SBayesR is a Bayesian approach similar to LDpred, but can be more flexible in posterior mean effects. Pruning and thresholding (P&T) is based on a minimum p-value threshold (the p-value associated with the variant in the source data file) and the r 2 A threshold (a measure of linkage disequilibrium (LD)) must be specified. P&T identifies the variant with the smallest p-value in each region and then calculates the p-value for the specified r 2 Greater than r 2All other variants in the region with a value are "lumped" under that variant. In a PRS, the index variant represents all variants in the clump (only the index variant is included in the PRS, all others are excluded). COJO is conceptually similar to P&T, but after conditioning on the index variant, it incorporates additional variants in a particular LD block into the score if they are shown to contribute independently to disease risk.

[0056] In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.0001 to about 0.5. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.5. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.1. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.05. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.01. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.005. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.001. In some embodiments, the genetic variant performance is calculated using the LDpred method and has a p value of about 0.0005. In some embodiments, the genetic variant performance is calculated using the LDpred method and the p value is about 0.0001.

[0057] In some embodiments, the method further comprises the initial step of obtaining a biological sample from the subject. As used herein, a "biological sample" may contain whole cells, live cells, and / or cell debris. A biological sample may contain (or be derived from) a "body fluid." The present disclosure encompasses embodiments in which the body fluid is selected from amniotic fluid, aqueous humor, vitreous humor, bile, serum, breast milk, cerebrospinal fluid, earwax (ear wax), chyle, chyme, endolymph, perilymph, exudate, feces, vaginal fluid, gastric acid, gastric juice, lymph, mucus (including nasal drip and phlegm), pericardial fluid, peritoneal fluid, pleural fluid, pus, catarrhal secretions, saliva, sebum (skin oil), semen, sputum, synovial fluid, sweat, tears, urine, vaginal secretions, vomit, and mixtures of one or more thereof. Biological samples include cell cultures, body fluids, and cell cultures derived from body fluids. Body fluids may be obtained from a mammal, for example, by venipuncture, or other collection or sampling procedures.

[0058] In any of the embodiments described herein, the IL-33 Asthma PRS endpoint can be an increase in annualized exacerbation rate. In any of the embodiments described herein, the IL-33 Asthma PRS endpoint can be loss of asthma control. In any of the embodiments described herein, the IL-33 Asthma PRS endpoint can be Asthma Control Questionnaire-5 (ACQ-5).

[0059] The present disclosure provides a method of treating a subject suffering from or at risk of developing asthma, the method comprising administering an IL-33 antagonist to the subject if the subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS) is greater than a threshold IL-33 asthma PRS, or administering an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist to the subject if the subject's IL-33 asthma PRS is less than a threshold IL-33 asthma PRS, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or within the IL-33 and IL1RL1 genes associated with asthma.

[0060] The invention also provides a method of treating a subject suffering from asthma or at risk of developing asthma, the method comprising administering to the subject an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist, and administering more than a standard amount of a composition for treating an asthma exacerbation if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or within the IL-33 and IL1RL1 genes associated with asthma.

[0061] The disclosure also provides a method of determining whether a subject should be administered an interleukin-4 receptor alpha antagonist, an interleukin-13 receptor antagonist, and / or an interleukin-33 (IL-33) antagonist for the treatment of asthma (or a method of classifying a subject suffering from asthma; or a method of selecting a subject suffering from asthma for treatment with an interleukin-4 receptor alpha antagonist / interleukin-13 receptor antagonist or treatment with an anti-IL-33 receptor antagonist; or a method of improving the efficacy of an asthma treatment), the method comprising: determining the subject's IL-33 Asthma Polygenic Risk Score (IL-33 Asthma PRS); and determining whether the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS; if the subject's IL-33 asthma PRS is equal to or greater than the threshold IL-33 asthma PRS, then the subject should be administered an IL-33 antagonist; or if the subject's IL-33 asthma PRS is less than the threshold IL-33 asthma PRS, then the subject should be administered an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist. In some embodiments, the method further comprises prescribing an interleukin-4 receptor alpha antagonist, an interleukin-13 receptor antagonist, and / or an interleukin-33 (IL-33) antagonist.

[0062] The disclosure also provides a method of determining whether a subject suffering from asthma should be administered more than a standard amount of a composition for treating an asthma exacerbation (or a method of classifying a subject suffering from asthma; or a method of selecting a subject suffering from asthma for treatment with an interleukin-4 receptor alpha antagonist / interleukin-13 receptor antagonist; or a method of improving the efficacy of an asthma treatment), the method comprising determining or having determined a subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), the IL-33 asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, then the subject should be administered more than a standard amount of an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist and a composition for treating an asthma exacerbation. In some embodiments, the method further comprises administering an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist.

[0063] The disclosure also provides a method of determining whether a subject suffering from asthma should be administered more than a standard amount of a composition for treating loss of asthma control (or a method of classifying a subject who has lost asthma control; or a method of selecting a subject who has lost asthma control for treatment with a composition for treating loss of asthma control; or a method of improving the efficacy of an asthma treatment), the method comprising determining or having determined a subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), the IL-33 asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, the subject should be administered more than a standard amount of a composition for treating loss of asthma control. In some embodiments, the method further comprises prescribing the composition for treating loss of asthma control.

[0064] The disclosure also provides a method of determining whether a subject suffering from asthma should be administered more than a standard amount of a composition for treating asthma (or a method of classifying a subject suffering from asthma; or a method of selecting a subject suffering from asthma for treatment with a composition for treating loss of asthma control; or a method of improving the efficacy of an asthma treatment), the method comprising determining or having determined a subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), the IL-33 asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, the subject should be administered more than a standard amount of a composition for treating loss of asthma control. In some embodiments, the method further comprises prescribing the composition for treating loss of asthma control.

[0065] The disclosure also provides a method of determining whether a subject suffering from a pulmonary disease should be administered more than a standard amount of a composition that reduces eosinophil count (or a method of classifying a subject suffering from a pulmonary disease; or a method of selecting a subject suffering from a pulmonary disease for treatment with a composition that reduces eosinophil count; or a method of improving the efficacy of a pulmonary disease treatment), the method comprising determining or having determined the subject's IL-33 Asthma Polygenic Risk Score (IL-33 Asthma PRS), the IL-33 Asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 Asthma PRS is equal to or greater than a threshold IL-33 Asthma PRS, the subject should be administered a composition that reduces eosinophil count. In some embodiments, the method further comprises prescribing the composition that reduces eosinophil count.

[0066] The disclosure also provides a method of determining whether a subject suffering from a pulmonary disease should be administered more than a standard amount of a composition for treating the pulmonary disease (or a method of classifying a subject suffering from a pulmonary disease; or a method of selecting a subject suffering from a pulmonary disease for treatment with an asthma risk reducing composition; or a method of improving the efficacy of a pulmonary disease treatment), the method comprising determining or having determined a subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), the IL-33 asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, the subject should be administered more than a standard amount of the asthma risk reducing composition. In some embodiments, the method further comprises prescribing the asthma risk reducing composition.

[0067] The disclosure also provides a method of determining whether a subject suffering from a pulmonary disease should be administered more than a standard amount of a composition that increases FEV1 values ​​(or a method of classifying a subject suffering from a pulmonary disease; or a method of selecting a subject suffering from a pulmonary disease for treatment with a composition that increases FEV1 values; or a method of improving the efficacy of a pulmonary disease treatment), the method comprising determining or having determined the subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), the IL-33 asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, the subject should be administered more than a standard amount of a composition that increases FEV1 values. In some embodiments, the method further comprises prescribing the composition that increases FEV1 values.

[0068] The disclosure also provides a method of determining whether a subject suffering from a pulmonary disease should be administered more than a standard amount of a composition that reduces baseline basophil count (or a method of classifying a subject suffering from a pulmonary disease; or a method of selecting a subject suffering from a pulmonary disease for treatment with a composition that reduces baseline basophil count; or a method of improving the efficacy of a pulmonary disease treatment), the method comprising determining or having determined the subject's IL-33 Asthma Polygenic Risk Score (IL-33 Asthma PRS), the IL-33 Asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 Asthma PRS is equal to or greater than a threshold IL-33 Asthma PRS, the subject should be administered more than a standard amount of a composition that reduces baseline basophil count. In some embodiments, the method further comprises prescribing a composition that reduces baseline basophil count.

[0069] The invention also provides a method of determining whether a subject suffering from a pulmonary disease should be administered more than a standard amount of a composition for increasing forced vital capacity (FVC) value (or a method of classifying a subject suffering from a pulmonary disease; or a method of selecting a subject suffering from a pulmonary disease for treatment with a composition that increases FVC value; or a method of improving the efficacy of a pulmonary disease treatment), the method comprising determining or having determined a subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS), the IL-33 asthma PRS comprising a weighted sum of multiple genetic variants near or in the IL-33 and IL1RL1 genes associated with asthma; if the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, the subject should be administered more than a standard amount of a composition that increases FVC value. In some embodiments, the method further comprises prescribing a composition that increases FVC value.

[0070] In some embodiments, any of the methods described herein can be used to select a population of subjects or candidates for a clinical trial, e.g., a clinical trial to determine whether a particular treatment or treatment regimen is effective against a pulmonary disease, e.g., asthma or COPD. In some embodiments, the selected candidates or subjects are divided into subgroups based on the genetic variants identified for each subject or candidate, and the method is used to determine whether a particular treatment or treatment regimen is effective for subjects with the identified genetic variants or groups of identified genetic variants. For example, the methods described herein can be used to determine the susceptibility of a subject population to a particular treatment or treatment regimen, and the subject population is selected based on the genetic variants identified in the subjects.

[0071] In some embodiments, the method is used to select a population of subjects or candidates for a clinical trial, for example, a clinical trial to determine whether a particular treatment or treatment plan is effective against a pulmonary disease, for example, asthma or COPD. In some embodiments, the desired risk group is a population that includes high-risk subjects or candidates. In some embodiments, the selected population of subjects or candidates are responders, i.e., the subjects or candidates respond to the treatment or treatment plan.

[0072] In some embodiments, subjects are selected based solely on the IL-33 asthma PRS. For example, if the subject or candidate's IL-33 asthma PRS exceeds a pre-determined threshold, the subject is selected for treatment initiation or the candidate is included in a clinical trial. In some embodiments, the threshold for treatment initiation or admission to a clinical trial is determined relatively. For example, in some embodiments, the threshold IL-33 asthma PRS score is in the top 50% of the reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 40% of the reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 30% of the reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 25% of the reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 20% of the reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 15% of the reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 10% (decile) within a reference population. In some embodiments, the threshold IL-33 asthma PRS score is in the top 5% within a reference population.

[0073] In any of the embodiments described herein, subjects with an IL-33 Asthma PRS score in the top 5%, top 10%, top 15%, top 20%, top 25%, or top 30% of the reference population can be administered any of the IL-33 antagonists described herein, such as itepekimab. In any of the embodiments described herein, subjects with an IL-33 Asthma PRS score in the bottom 5%, bottom 10%, bottom 15%, bottom 20%, bottom 25%, or bottom 30% of the reference population can be administered any of the interleukin-4 receptor alpha antagonists and / or interleukin-13 receptor antagonists described herein, such as dupilumab. In any of the embodiments described herein, subjects with an IL-33 Asthma PRS score in the top 30% to bottom 30% of the reference population may be administered a combination of any of the IL-33 antagonists described herein and any of the interleukin-4 receptor alpha antagonists and / or interleukin-13 receptor antagonists described herein.

[0074] In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 100 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 200 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 500 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 1,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 3,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 5,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 7,500 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 10,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 12,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 15,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 20,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 30,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 50,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 70,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 100,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 200,000 subjects.In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 300,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 400,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 500,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 600,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 700,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 800,000 subjects. In some embodiments, the reference population for determining a relative IL-33 asthma PRS score is at least about 900,000 subjects. In some embodiments, the reference population for determining the relative IL-33 asthma PRS score is at least about 1,000,000 subjects.

[0075] In some embodiments, the reference population is not limited to any particular ancestral group in any way. In some embodiments, the reference population is enriched for members of ancestral groups. In some embodiments, the ancestral group is self-reported. In some embodiments, the ancestral group is assigned based on genetic testing of ancestry. In some embodiments, the ancestral group is derived from a principal components analysis of ancestry. In some embodiments, the ancestral group is European. In some embodiments, the ancestral group is Eastern European. In some embodiments, the ancestral group is Western European. In some embodiments, the ancestral group is African. In some embodiments, the ancestral group is mixed American. In some embodiments, the ancestral group is East Asian. In some embodiments, the ancestral group is South Asian. In some embodiments, the ancestral group is a mixture of any two or more of European, African, mixed American, East Asian, and South Asian populations.

[0076] In some embodiments, the method further includes initiating a treatment for the subject, which may include ICS, leukotriene modifiers, long-acting muscarinic antagonists (LAMA), long-acting beta agonists (LABA), theophylline, combination inhalers containing both a corticosteroid and a LABA, e.g., albuterol, short-acting beta agonists such as albuterol, ipratropium, oral corticosteroids (OCS), intravenous corticosteroids, allergy injections, allergy medications, omalizumab, mepolizumab, benralizumab, reslizumab, dupilumab, and itepekimab, or any combination thereof.

[0077] Examples of therapeutic agents useful in the treatment of asthma include, but are not limited to, ICS, leukotriene modifiers, long-acting beta agonists (LABAs), theophylline, combination inhalers containing both corticosteroids and LABAs, short-acting beta agonists such as albuterol, ipratropium, oral corticosteroids, intravenous corticosteroids, allergy injections, allergy medications, omalizumab, mepolizumab, benralizumab, reslizumab, dupilumab, and itepekimab, or any combination thereof. Standard amounts of these agents are determined by a physician according to label guidelines.

[0078] Initiating treatment may include devising a treatment plan based on the risk group corresponding to the calculated IL-33 asthma PRS for the subject. In some embodiments, the IL-33 asthma PRS predicts the effectiveness of treatment or the subject's response to a therapeutic regimen. Thus, treatment can be determined or adjusted depending on the IL-33 asthma PRS.

[0079] In some embodiments, initiating treatment involves modifying a dosage or regimen of a treatment already being received by a subject with asthma or COPD based on the calculated IL-33 asthma PRS for the subject. In some embodiments, initiating treatment involves replacing one therapeutic agent with another based on the IL-33 asthma PRS. In some embodiments, initiating treatment involves starting a regimen of a therapeutic agent in addition to a therapeutic agent already being received by the subject. In some embodiments, initiating treatment involves starting administration of a therapeutic regimen to a previously untreated asthma or COPD subject.

[0080] In some embodiments, the therapeutic agent is an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist. In some embodiments, the IL-33 asthma PRS is predictive of the efficacy of treatment or a subject's response to treatment with an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist. Thus, depending on the calculated IL-33 asthma PRS for a subject, IL-33 antagonist, interleukin-4 receptor alpha antagonist, and / or interleukin-13 receptor antagonist treatment can be determined or adjusted.

[0081] As used herein, the term "antagonist" means that a given compound is capable of inhibiting the activity of a respective protein or other substance in a cell, at least to a certain extent. This can be achieved by the direct interaction of the compound with a given protein or substance ("direct inhibition"), or by the interaction of the compound with other proteins or other substances inside or outside the cell, which leads to at least partial inhibition of the activity of the protein or substance ("indirect inhibition"). Inhibition of protein activity can also be achieved by suppressing the expression of the target protein. Techniques for inhibiting protein expression include, but are not limited to, antisense inhibition, siRNA-mediated inhibition, miRNA-mediated inhibition, ribozyme-mediated inhibition, DNA-directed RNA interference (DdRNAi), RNA-directed DNA methylation, transcription activator-like effector nuclease (TALEN)-mediated inhibition, zinc finger nuclease-mediated inhibition, aptamer-mediated inhibition, and CRISPR-mediated inhibition.

[0082] As used herein, "antisense inhibition" refers to the reduction of target nucleic acid levels in the presence of an oligonucleotide complementary to a target nucleic acid compared to the target nucleic acid levels in the absence of the oligonucleotide.

[0083] In some embodiments, the IL-33 antagonist, the interleukin-4 receptor alpha antagonist, and / or the interleukin-13 receptor antagonist is a small molecule.

[0084] In some embodiments, the IL-33 antagonist, the interleukin-4 receptor alpha antagonist, and / or the interleukin-13 receptor antagonist is a siRNA.

[0085] In some embodiments, the IL-33 antagonist is an anti-IL-33 antibody or an antigen-binding portion thereof. In some embodiments, the IL-33 antagonist is an anti-IL-33 receptor antagonist. In some embodiments, the interleukin-4 receptor alpha antagonist is an anti-interleukin-4 receptor alpha antibody or an antigen-binding fragment thereof. In some embodiments, the anti-interleukin-4 receptor alpha antagonist is an anti-interleukin-4 antibody or an antigen-binding fragment thereof. In some embodiments, the interleukin-13 receptor antagonist is an anti-IL-13 receptor antibody. In some embodiments, the interleukin-13 receptor antagonist is an anti-interleukin-13 antibody or an antigen-binding fragment thereof.

[0086] The term "antibody" as used herein is intended to refer to an immunoglobulin molecule comprising four polypeptide chains, two heavy (H) and two light (L) chains inter-connected by disulfide bonds, as well as multimers thereof (e.g., IgM). Each heavy chain contains a heavy chain variable region (herein referred to as HCVR or V H The heavy chain constant region is made up of three domains: H 1. C H 2, and C H Each light chain comprises a light chain variable region (herein, LCVR or V L The light chain constant region comprises one domain (C L 1) is included. H Area and V L The regions can be further subdivided into regions of hypervariability called complementarity determining regions (CDRs) and more conserved regions called framework regions (FRs). H and V Lis composed of three CDRs and four FRs, which are arranged from the amino terminus to the carboxy terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3, FR4. In different embodiments, the FRs of an anti-IL-33 antibody (or an antigen-binding fragment thereof) or an anti-interleukin-4 receptor alpha (or an antigen-binding portion thereof) may be identical to a human germline sequence or may be naturally or artificially modified. An amino acid consensus sequence may be defined based on a comparative analysis of two or more CDRs.

[0087] The term "antibody" as used herein also includes antigen-binding fragments of complete antibody molecules. As used herein, the terms "antigen-binding portion" of an antibody, "antigen-binding fragment of an antibody" and the like include naturally occurring, enzymatically derived, synthetic, or genetically engineered polypeptides or glycoproteins that specifically bind to an antigen to form a complex. Antigen-binding fragments of antibodies can be derived from complete antibody molecules, for example, using any suitable standard technique, such as proteolytic digestion or recombinant genetic engineering techniques, including the manipulation and expression of DNA encoding the variable domains of the antibody and, optionally, the constant domains. Such DNA can be obtained, for example, from commercial sources, DNA libraries (including, for example, phage antibody libraries), or can be synthesized. The DNA can be sequenced and manipulated, for example, using chemical or molecular biology techniques, to place one or more variable and / or constant domains in a suitable configuration, or to introduce codons, create cysteine ​​residues, modify, add, or delete amino acids.

[0088] Interleukin-4 receptor alpha antagonists include, but are not limited to, dupilumab and pitrakinra. Interleukin-13 receptor antagonists include, but are not limited to, dupilumab, tralokinumab, pitrakinra, and lebrikizumab. The standard dosage of dupilumab for adults and adolescents (age 12 and older) is i) an initial dose of 400 mg (two 200 mg injections), followed by 200 mg every other week, or ii) an initial dose of 600 mg (two 300 mg injections), followed by 300 mg every other week, or iii) for patients with moderate to severe atopic dermatitis who require concurrent oral corticosteroids or for whom dupilumab is indicated, an initial dose of 600 mg, followed by 300 mg every other week. In some embodiments, the interleukin-4 receptor alpha antagonist is not an interleukin-13 receptor antagonist. In some embodiments, the interleukin-13 receptor antagonist is not an IL4R alpha antagonist. In some embodiments, the interleukin-4 receptor alpha antagonist and / or the interleukin-13 receptor antagonist are separate antagonists. When the interleukin-4 receptor alpha antagonist and / or the interleukin-13 receptor antagonist are separate antagonists, the first separate antagonist is an interleukin-4 receptor alpha antagonist but not an interleukin-13 receptor antagonist, and the second separate antagonist is an interleukin-13 receptor antagonist but not an interleukin-4 receptor alpha antagonist, i.e., two separate antagonists are administered.

[0089] In some embodiments, the interleukin-4 receptor alpha antagonist specifically binds human IL-4Rα and comprises a heavy chain variable region (HCVR) comprising SEQ ID NO:1 and a light chain variable region (LCVR) comprising SEQ ID NO:2, a heavy chain complementarity determining region 1 (HCDR1) comprising SEQ ID NO:3, an HCDR2 comprising SEQ ID NO:4, an HCDR3 comprising SEQ ID NO:5, a light chain complementarity determining region 1 (LCDR1) comprising SEQ ID NO:6, an LCDR2 comprising SEQ ID NO:7, and an LCDR3 comprising SEQ ID NO:8. The full length heavy chain of dupilumab is set forth as SEQ ID NO:9, and the full length light chain is set forth as SEQ ID NO:10. Human anti-IL-4R antibodies can be generated as described in U.S. Patent No. 7,608,693.

[0090] In some embodiments, the IL-33 antagonist comprises itepekimab. In some embodiments, the interleukin-4 receptor alpha antagonist is dupilumab. In some embodiments, the interleukin-13 receptor antagonist is dupilumab. In some embodiments, the interleukin-4 receptor alpha antagonist and the interleukin-13 receptor antagonist are dupilumab.

[0091] In the context of the methods disclosed herein, the additional therapeutically active ingredient(s), e.g., any of the agents listed above or derivatives thereof, may be administered immediately prior to, simultaneously with, or immediately following administration of an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist; (for purposes of this disclosure, such administration regimes will be considered administration of an IL-33 antagonist, an interleukin-4 receptor alpha antagonist, and / or an interleukin-13 receptor antagonist "in combination" with the additional therapeutically active ingredient). In some embodiments, the additional therapeutically active ingredient is considered to be administered "in combination with" the IL-33 antagonist, interleukin-4 receptor alpha antagonist, and / or interleukin-13 receptor antagonist, despite the fact that the additional therapeutically active ingredient and the IL-33 antagonist, interleukin-4 receptor alpha antagonist, and / or interleukin-13 receptor antagonist are administered by different routes. Methods of the invention include pharmaceutical compositions and methods of use thereof in which the IL-33 antagonist, interleukin-4 receptor alpha antagonist, and / or interleukin-13 receptor antagonist are co-formulated with one or more additional therapeutically active ingredient(s) described herein.

[0092] As used herein, the terms "treat," "treatment," or "treating" refer to the administration of a therapeutic agent for prophylactic and / or therapeutic purposes. Examples of therapeutic agents useful in the treatment of pulmonary diseases include, but are not limited to, ICS, leukotriene modifiers, long-acting beta agonists (LABAs), theophylline, combination inhalers containing both a corticosteroid and a LABA, short-acting beta agonists such as albuterol, ipratropium, oral corticosteroids, intravenous corticosteroids, allergy injections, allergy meds, omalizumab, mepolizumab, benralizumab, reslizumab, dupilumab, and itepekimab, or any combination thereof.

[0093] As used herein, "therapeutic treatment" refers to the administration of a therapeutic agent to a subject with a pulmonary disease. As used herein, the terms "prophylactic treatment" or "prevention" refer to administration to a subject not currently or previously suffering from at least one pulmonary disease.

[0094] As used herein, the term "pulmonary disease" refers to, but is not limited to, asthma, COPD, chronic bronchitis, emphysema, acute bronchitis, cystic fibrosis, bacterial lung infections, tuberculosis infections, pneumonia, tuberculosis (including but not limited to, caused by Mycobacterium tuberculosis), pulmonary edema, lung cancer, acute respiratory distress syndrome (ARDS) (including but not limited to, ARDS associated with COVID), pneumoconiosis, lung injury (caused by chemical, biological, or radionuclide (CBRN) agents), black lung disease (associated with exposure to coal dust), and asbestosis (associated with exposure to asbestos).

[0095] In some embodiments, the asthma can be, but is not limited to, mild asthma, moderate asthma, severe asthma, eosinophilic asthma with or without alterations in immunoglobulin E levels, or oral corticosteroid-dependent asthma.

[0096] In some embodiments, the asthma exacerbation can be an annual asthma exacerbation. Examples of compounds for treating acute asthma exacerbations include, but are not limited to, increasing the dose of oral or inhaled corticosteroids. Examples of compounds for preventing acute asthma exacerbations include, but are not limited to, inhaled corticosteroids (including in combination with long-acting beta agonists), oral corticosteroids, dupilumab, mepolizumab, benralizumab, reslizumab, omalizumab, tezepelumab, and azithromycin.

[0097] Examples of compounds that treat loss of asthma control include, but are not limited to, any available asthma therapy, such as ICS, leukotriene modifiers, LABAs, LAMAs, theophylline, combination inhalers containing both a corticosteroid and a LABA, short acting beta agonists such as albuterol, ipratropium, OCS, intravenous corticosteroids, allergy injections, allergy medications, omalizumab, mepolizumab, benralizumab, reslizumab, dupilumab, and itepekimab, or any combination thereof.

[0098] Examples of compounds that reduce eosinophil count include, but are not limited to, OCS, mepolizumab, benralizumab, reslizumab, omalizumab, and tezepelumab, or any combination thereof.

[0099] Examples of compounds that increase FEV1 values ​​include, but are not limited to, OCS, ICS, LABA, LAMA, short-acting muscarinic antagonists (SAMA), short-acting beta agonists (SABA), anti-leukotrienes (e.g., montelukast), theophylline, dupilumab, tezepelumab, omalizumab, mepolizumab, benralizumab, and reslizumab, or any combination thereof.

[0100] All patent documents, websites, other publications, accession numbers, etc., cited above or below, are incorporated by reference in their entirety for all purposes to the same extent as if each individual item was specifically and individually indicated to be so incorporated by reference. Where different versions of a sequence at different times are associated with an accession number, it refers to the version associated with the accession number at the effective filing date of this application. The effective filing date refers to the actual filing date or, if applicable, the filing date of the priority application that references the accession number, whichever is earlier. Similarly, where different versions of a publication, website, etc. are published at different times, it refers to the version last published at the effective filing date of the application, unless otherwise indicated. Any feature, step, element, embodiment, or aspect of the present disclosure may be used in combination with any other feature, step, element, embodiment, or aspect, unless otherwise indicated. The present disclosure has been described in detail by illustration and example for purposes of clarity and understanding, but it will be apparent that certain changes and modifications may be practiced within the scope of the appended claims.

[0101] The following examples are provided to more fully describe the embodiments. They are intended to illustrate, not limit, the claimed embodiments. The following examples provide those skilled in the art with disclosures and descriptions of how the compounds, compositions, articles, devices, and / or methods described herein are made and evaluated, and are intended to be purely illustrative and are not intended to limit the scope of any claims. Efforts have been made to ensure accuracy with respect to numbers (e.g., amounts, temperatures, etc.), but some errors and deviations may be accounted for. Unless otherwise indicated, parts are parts by weight, temperature is in ° C. or is at ambient temperature, and pressure is at or near atmospheric pressure. EXAMPLES

[0102] Example 1: Generation of a polygenic risk score Dataset: A pathway-specific asthma PRS was generated for a European population. The PRS consisted of 543 variants near or within the IL-33 and IL1RL1 genes. The LDpred method was used to estimate the contribution of individual SNPs from the asthma GWAS. Additionally, a pathway-specific asthma PRS was generated for an admixed American population. It included 205 variants near or within the IL-33 and IL1RL1 genes. The LDpred method was used to estimate the contribution of individual SNPs from the asthma GWAS.

[0103] PRS Algorithm Selection: We used the LDpred approach to generate polygenic risk scores. LDpred is a Bayesian approach to PRS development that calculates the posterior mean effect (adjusted effect size) of all variants based on prior and LD information from a reference panel. Heuristically, effect sizes generated from LDpred differ from P&T in that LDpred jointly models the effect size and variance of each marker and incorporates LD structure when shrinking effect sizes. The adjustment or shrinkage of variant weights is based not only on the magnitude of the association of the variant with the disease but also on the linkage disequilibrium (LD) between the variants. In the LDpred approach, data from 1000 Genomes phase 3 version 5 was used for the LD reference panel.

[0104] PRS calculation: From the LDpred approach, we generated a set of variants and their respective weights. For LDpred, the variant weights were the adjusted log odds ratios (posterior means). After generating the weights, the process of calculating and normalizing the scores was the same. For a set of M variants, j=1...,i=1...N patients, the PRS for patient j was calculated as follows:

[0105]

number

[0106] (In the formula, B iis the log odds ratio for variant i, and x ij where is the number of risk alleles carried in patient j at variant i (for imputed variants, the allele dosage of variant i). Scores were standardized to approximately N(0,1) by subtracting the mean PRS and dividing by the PRS standard deviation within each ancestral group.

[0107] PRS algorithm testing and validation: For each set of LDpred tuning parameters, the PRS was calculated and logistic regression was performed with the composite endpoint as the dependent variable and PRS, age, sex, and ancestry covariates as independent variables. For each model, odds ratios (OR) and areas under the curve (AUC) per PRS standard deviation (SD) were reported.

[0108] Choosing a threshold to define high risk: High genetic risk was defined as patients within the 25th, 50th, 75th, and 100th percentiles of the distribution of polygenic risk scores. This threshold was selected in a post-hoc analysis, which evaluated high genetic risk thresholds in the 25th, 50th, 75th, and 100th percentile ranges.

[0109] Statistical analysis: Baseline disease and medical history characteristics were analyzed to assess the distribution of asthma risk factors by genetic risk status (high (above percentile threshold) vs low (below percentile threshold)). Continuous baseline characteristics were compared using t-tests, and binary or categorical characteristics were tested using chi-square or Fisher's exact tests.

[0110] result: IL-33 asthma PRS determined using the LDpred method is significantly associated with higher annualized exacerbation rates in dupilumab-treated European patients. Both graphs in Figure 1 show the association between IL-33 asthma PRS and annualized exacerbation rates. In particular, panel A shows the genetic influence in patients undergoing the same treatment. The X-axis is the IL33 PRS score divided into quartiles and ranked from lowest to highest, and the Y-axis is the annualized exacerbation rate. In the dupilumab-treated group, those with higher IL33 PRS had higher exacerbation rates. The p-value is 0.41. This is also significant when comparing those in the top quartile with those in the remaining or lowest quartile, suggesting that those in the highest quartile of IL33 PRS are not benefiting as much as those in the lowest quartile of IL33 PRS. In particular, panel B shows a comparison of treatment effects according to quartile of IL33 PRS. In the quartiles of IL33 PRS, dupilumab-treated patients had significantly lower exacerbation rates. No differences were seen between the dupilumab and placebo groups in the highest quartile of IL33 PRS.

[0111] IL-33 Asthma PRS determined using LDpred was not associated with change in pre-bronchodilator FEV1 at week 12 in dupilumab-treated European patients, but patients with lower IL-33 Asthma PRS scores showed the greatest clinical benefit when compared to placebo-treated patients. In the study disclosed herein, other primary endpoints were change in FEV1 change (Figure 2). In particular, panel A shows that when comparing treatment effects, dupilumab treatment significantly increased FEV1 values ​​in patients with lower IL33 PRS quartiles, but not in those with higher PRS quartiles.

[0112] IL-33 asthma PRS, determined using the LDpred method, tended to be associated with higher annualized exacerbation rates in dupilumab-treated mixed race American patients. Figure 3 shows that subjects in the higher quartiles of IL33 PRS (75 and 100 groups) were significantly associated with less effective response to dupilumab when comparing dupilumab-treated and placebo groups.

[0113] IL-33 Asthma PRS measured using the LDpred method was not associated with change in FEV1 at week 12 in dupilumab-treated mixed race American patients, but patients with lower IL-33 Asthma PRS scores had the greatest clinical benefit when compared to placebo-treated patients. Figure 4 shows the distribution of variants by sample. In the graph in Panel A, IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, and the numbers in each bar are the change in FEV1 at week 12. In the graph in Panel B, IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, and the numbers at the bottom of each bar indicate the number of patients in each group and the change in FEV1 at week 12.

[0114] The IL-33 Asthma PRS determined using the LDpred method showed a trend towards a reduced risk of LOAC in itepekimab monotreated European subjects. In 148 European samples, the IL33 Asthma PRS for European patients was applied (Figure 5). The IL-33 Asthma PRS was divided into quartiles and ranked from lowest to highest, the number at the bottom of each bar is the number of subjects in each group, and the number on each bar is the percentage of subjects with LOAC. It was found that the IL-33 Asthma PRS tended to be associated with reduced LOAC (p-value=0.055). When comparing the lowest quartile with the other quartiles, it was observed that patients with higher IL-33 Asthma PRS values ​​had less LOAC compared to the lowest quartile. The variation of the IL-33 Asthma PRS by treatment regimen was not significant. However, this may be due to the small number of samples in this study. Figure 5 shows the trend in the itepekimab monotherapy group. Patients with higher IL33PRS scores showed fewer LOAC events.

[0115] IL-33 asthma PRS showed a trend towards a decreased risk of LOAC in European and mixed race American subjects treated with itepekimab monotherapy. The IL-33 asthma PRS of the remaining 50 mixed race American samples in the itepekimab trial was applied and combined with that of the European subjects (Figure 6). The IL-33 asthma PRS was divided into quartiles and ranked from lowest to highest, the number at the bottom of each bar is the number of subjects in each group, and the number on each bar is the percentage of subjects with LOAC. Also, asthma patients with higher IL-33-asthma PRS had less LOAC than patients in the lowest quartile of the itepekimab monotherapy group. The findings suggested that asthma patients with higher IL-33 asthma PRS may benefit more from itepekimab treatment. In the placebo group, IL-33 asthma PRS tended to be associated with increased LOAC. This suggested that placebo asthma patients with a high IL33 asthma PRS suffered more LOAC. Figure 6 shows that in the itepekimab monotherapy group, asthma patients with a high IL33 PRS had less LOAC than those in the lowest quartile. This suggests that asthma patients with a high IL33-based genetic risk may benefit more from itepekimab treatment. In the placebo group, IL33 PRS tended to be associated with increased LOAC, suggesting that asthma patients in the higher quartiles of IL33 PRS suffered more LOAC.

[0116] The IL-33 asthma PRS determined using the LDpred method was significantly associated with asthma in GHS_GSA European subjects. The GHS_GSA population is a cohort of the Geisinger Health System. The IL-33 asthma PRS was strongly associated with asthma risk (p-value = 4.18 × 10 -30) (FIG. 7). In the graph in Panel A, the IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, the numbers below each bar are the number of subjects in each group, and the numbers in each bar are the percentage of asthma subjects. In the graph in Panel B, the IL-33 Asthma PRS percentiles and the vertical axis are the odds ratios of the percentage of asthma subjects. FIG. 7 shows the validated IL33 Asthma PRS correlated with asthma risk. The IL33 Asthma PRS determined by LDpred was significantly associated with asthma in GUS-GSA European subjects.

[0117] The IL-33 asthma PRS determined using the LDpred method was significantly associated with eosinophil count in GHS_GSA European subjects. The IL-33 asthma PRS measured using the LDpred method also showed a significant association with eosinophil count (p-value = 1.73 × 10 -40 ) (FIG. 8). In the graph in panel A, the numbers "25", "50", "75", and "100" are the IL-33 Asthma PRS divided into quartiles and ranked from lowest to highest, the numbers "13102", "13102", "13104", and "13101" are the number of subjects in each group, and the numbers within each bar are the eosinophil counts. In the graph in panel B, the IL-33 Asthma PRS percentiles and the vertical axis are the relative difference in eosinophil counts. FIG. 8 shows that the IL33 PRS by the Ldpred method also shows a significant positive correlation with eosinophil counts.

[0118] Of the 543 variants in the IL-33 asthma PRS determined by LDpred training, 11 were disease or trait associated variants in HGMD. Variants in the IL-33 asthma PRS and interleukin-1 receptor ligand were found in the HGMD database and are associated with disease traits (Figure 9). The results of the analysis of the 543 variants are shown in Figure 9. The IL-33 asthma PRS and interleukin-1 receptor ligand were generated.

[0119] The IL-33 Asthma Polygenic Risk Score (IL-33AMR Asthma PRS) for Mixed-race American subjects determined using the LDpred methodology was significantly associated with asthma risk in Mixed-race American subjects in Mexico City. The graph shown in FIG. 10 shows how the IL-33 Asthma PRS for Mixed-race American patients predicts asthma risk in Mixed-race American patients in Mexico City. In the graph in Panel A, the IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, the numbers at the bottom of each bar are the number of subjects in each group, and the numbers in each bar are the percentage of asthmatic subjects. In the graph in Panel B, the IL-33 Asthma PRS percentiles and the vertical axis are the odds ratios for the percentage of asthmatic subjects. A highly significant association was observed. The results of this study were applied to the IL-33 Asthma PRS in clinical samples, combining both European and Mixed-race American samples to increase power. The plot in Figure 10 shows how the IL33 AMR asthma PRS acts on MCPS predicament asthma risk, with a highly significant association. This IL33 AMR PRS can be applied to clinical samples and combined with both EUR and AMR samples to increase power.

[0120] Six of the 205 variants in the IL-33 AMR asthma PRS determined by LDpred training were associated with HGMD disease or traits. Variants in the AMR IL-33 asthma PRS and interleukin-1 receptor ligand were found in the HGMD database and are associated with disease traits (Figure 11). The results of the analysis of 543 variants are shown in Figure 9. The IL-33 asthma PRS and interleukin-1 receptor ligand were generated. Figure 11 shows the IL33 PRS and IL4R PRS in clinical samples, and indicates that the IL4R PRS did not show a significant association with the efficacy endpoint.

[0121] In a clinical trial of itepekimab-treated mixed European and mixed American subjects, the IL-33 asthma PRS was determined by LDpred training. Figure 12 shows information on the number of variants and datasets used to generate the PRS (Panel A) and the distribution of PRS scores across samples for the European and mixed American subsets (Panel B).

[0122] The IL-33 Asthma PRS showed a trend towards a decreased risk of LOAC in itepekimab monotreated European and mixed race American subjects. The IL-33 Asthma PRS of mixed race American subjects was applied to 50 mixed race American samples from the itepekimab trial and combined with those of European subjects (Figure 13). The IL-33 Asthma PRS was divided into quartiles and ranked from lowest to highest, the number at the bottom of each bar is the number of subjects in each group, and the number on each bar is the percentage of subjects with LOAC. It was also observed that asthma patients with a high IL-33 Asthma PRS had less LOAC than those in the lowest quartile in the itepekimab monotherapy group. This finding suggests that asthma patients with high IL-33-based genetic risk may benefit more from itepekimab treatment. In the placebo group, the IL-33 Asthma PRS was observed to trend towards an increased LOAC. The findings suggest that asthma patients with high IL-33 PRS suffer from more LOAC.

[0123] The IL-33 asthma PRS was associated with increased baseline basophil counts in European subjects in trials named DRI12544 and EFC13579. The findings were significant with a p-value of 0.008 (Figure 14).

[0124] IL-33 Asthma PRS was significantly associated with increased asthma exacerbations in dupilumab-treated European subjects in trials named DRI12544 and EFC13579. Higher IL-33 Asthma PRS was associated with significantly increased asthma exacerbations in dupilumab-treated patients (Figure 15). IL-33 Asthma PRS was also associated with reduced changes in exotoxin 3 levels in the placebo group.

[0125] Mixed IL-33 asthma PRS determined with LDpred training for European and Mixed American subjects in trials named DRI12544 and EFC13579. Figure 16 shows information on the number of variants and datasets used to generate the PRS (Panel A) and the distribution of PRS scores across samples of European and Mixed American subjects (Panel B).

[0126] The IL-33 Asthma PRS was significantly associated with increased asthma exacerbation rates in dupilumab-treated mixed European and mixed American subjects in trials named DRI12544 and EFC13579. The European and mixed American samples were scored separately for each IL-33 Asthma PRS. The scores were then combined and regression analysis was performed on asthma exacerbation rates (Figure 17). In the graph in panel A, the IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, and the numbers within each bar are the annualized exacerbation rates. In the graph in panel B, the IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, and the numbers below each bar are the number of subjects in each group, and the vertical axis is the annualized exacerbation rate. These findings were replicated in European subjects, where the IL-33 Asthma PRS was significantly associated with increased exacerbations in the dupilumab group. Furthermore, based on IL-33 asthma PRS quartiles, the effect associated with dupilumab was significant for the 25th, 50th, and 75th quartiles, but not for the highest quartile. This suggests that the benefit of dupilumab comes primarily from asthma patients with low IL33 asthma PRS scores to dupilumab. Figure 17 shows that patients with IL-33 asthma PRS scores in the top 25% responded less effectively to dupilumab compared to patients with low IL-33 asthma PRS scores and treated with dupilumab.

[0127] IL-33 Asthma PRS was significantly associated with increased change in FEV1 at week 12 in mixed European and mixed American subjects on placebo in the trials named DRI12544 and EFC13579. IL-33 Asthma PRS was regressed against change in FEV1 at week 12 for the mixed European and mixed American sample. With increasing sample size, a significant association was observed between higher IL-33 Asthma PRS and increased FEV1 in the placebo group. This indicates that asthmatics with higher IL33 PRS benefited more from LABA or inhaled corticosteroids (graph in panel A of FIG. 18). In the graph in panel A, IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, and the number on each bar is the change in FEV1 at week 12. In the graph in Panel B, IL-33 Asthma PRS are divided into quartiles and ranked from lowest to highest, the numbers below each bar are the number of subjects in each group, and the vertical axis is the change in FEV1 at week 12. The graph in Panel B shows a replication of the findings in European patients, with patients with IL-33 Asthma PRS in the 25th and 50th quartiles having a more pronounced dupilumab response in terms of change in FEV1. Figure 18 shows that patients with IL-33 Asthma PRS scores in the bottom 25% of the dupilumab group had the greatest increase in FEV1 values ​​compared to the placebo group.

[0128] There was an association between the change in IL-33 Asthma PRS and FVC at week 12 in European and mixed American subjects. Figure 19 shows the distribution of variants by sample. In the graph in Panel A, IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, and the number in each bar is the change in FEV1 at week 12. In the graph in Panel B, IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, the number under each bar is the number of subjects in each group, and the vertical axis is the change in FEV1 at week 12. Patients with IL-33 Asthma PRS scores in the top 25% respond less effectively to dupilumab compared to patients with lower IL-33 Asthma PRS scores and treated with dupilumab.

[0129] There was an association between the IL-33 Asthma PRS and the proportion of subjects with asthma exacerbations in GHS_GSA European subjects. The data shown in the graph in Panel A of Figure 20 demonstrates this finding. Panel A shows no association between the IL-33 Asthma PRS and the proportion of subjects with asthma exacerbations in GHS_GSA European subjects, and Panel B shows no association between the IL-33 Asthma PRS and the proportion of asthma subjects taking medication. In the graph in Panel A, the IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, the number at the bottom of each bar is the number of subjects in each group, and the number in each bar is the proportion of subjects with asthma exacerbations. There is an association between the IL-33 Asthma PRS and the proportion of asthma subjects taking medication. The data shown in the graph in Panel B of Figure 20 demonstrates this finding. In the graph in Panel B, IL-33 Asthma PRS are divided into quartiles and ranked from lowest to highest, the number below each bar is the number of subjects in each group, and the number within each bar is the percentage of asthma subjects taking medication. Figure 20 shows that patients with IL-33 Asthma PRS scores in the bottom 25% of the dupilumab group had the greatest increases in FEV1 values ​​compared to the placebo group.

[0130] There was an association between the IL-33 Asthma PRS and the proportion of patients with Chronic Obstructive Pulmonary Disease (COPD) in GHS_GSA European patients. The graph shown in Figure 21 illustrates this result. The p-value was 7.75e-03. In this graph, the IL-33 Asthma PRS is divided into quartiles and ranked from lowest to highest, the numbers below each bar are the number of subjects in each group, and the numbers within each bar are the proportion of subjects with COPD.

[0131] GWAS data from individuals of European and mixed American ancestry were used to develop the PRS in this study. Polygenic risk scores for non-European populations will likely be improved over time as GWAS data become available for more diverse populations.

[0132] In addition to those described herein, various modifications of the described subject matter will be apparent to those skilled in the art from the above description. Such modifications are also intended to fall within the scope of the appended claims. Each reference described in this application (including, but not limited to, journal articles, U.S. and non-U.S. patents, patent application publications, international patent application publications, gene bank accession numbers, etc.) is incorporated herein by reference in its entirety.

Claims

1. 1. A composition for treating a subject suffering from or at risk of developing asthma, said composition comprising: an IL-33 antagonist if the subject's IL-33 asthma polygenic risk score (IL-33 asthma PRS) is equal to or greater than a threshold IL-33 asthma PRS; or If the subject's IL-33 asthma PRS is less than a threshold IL-33 asthma PRS, an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist. Including, The composition, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or within the IL-33 and IL1RL1 genes associated with asthma.

2. 1. A method for assisting in determining whether a subject should be administered an interleukin-4 receptor alpha antagonist, an interleukin-13 receptor antagonist, and / or an interleukin-33 (IL-33) antagonist for the treatment of asthma, the method comprising: determining or having determined an IL-33 asthma polygenic risk score (IL-33 asthma PRS) for the subject, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or within the IL-33 and IL1RL1 genes associated with asthma, and further wherein the method comprises: Determining whether the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS, or having determined Including, the subject's IL-33 asthma PRS being equal to or greater than the threshold IL-33 asthma PRS indicates that the subject should be administered the IL-33 antagonist; or The method, wherein the subject's IL-33 asthma PRS being less than the threshold IL-33 asthma PRS indicates that the subject should be administered the interleukin-4 receptor alpha antagonist and / or the interleukin-13 receptor antagonist.

3. 1. A method for assisting in determining whether a subject suffering from asthma should be administered more than a standard amount of a composition for treating an asthma exacerbation, comprising: determining or having determined an IL-33 asthma polygenic risk score (IL-33 asthma PRS) for the subject, wherein the IL-33 asthma PRS comprises a weighted sum of multiple genetic variants near or within the IL-33 and IL1RL1 genes associated with asthma, and further wherein the method comprises: The method, wherein the subject's IL-33 asthma PRS is equal to or greater than a threshold IL-33 asthma PRS indicates that the subject should be administered an interleukin-4 receptor alpha antagonist and / or an interleukin-13 receptor antagonist and a composition for treating asthma exacerbations in a standard or greater amount.

4. The composition of claim 1, wherein the interleukin-4 receptor alpha antagonist and / or the interleukin-13 receptor antagonist is dupilumab.

5. The composition of claim 1 or 4, wherein the IL-33 antagonist is itepekimab.

6. 10. The composition of claim 1 or 4, wherein the threshold IL-33 asthma PRS is in the top 50% within a reference population.

7. The composition of claim 1 or 4, wherein the IL-33 asthma PRS endpoint is an increase in annualized exacerbation rate.

8. 10. The composition of claim 1 or 4, wherein the endpoint of the IL-33 asthma PRS is loss of asthma control.

9. The composition of claim 1 or 4, wherein the reference population comprises at least 100 subjects.

10. The composition of claim 1 or 4, wherein the reference population is enriched for members of an ancestral group.

11. 11. The composition of claim 10, wherein the ancestral group comprises a European ancestral group, an African ancestral group, a mixed American ancestral group, an East Asian ancestral group, or a South Asian ancestral group.

12. 10. The composition of claim 1 or 4, wherein the plurality of genetic variants comprises single nucleotide polymorphisms (SNPs), insertions, deletions, structural variants, or copy number variations.

13. 10. The composition of claim 1 or 4, wherein the plurality of genetic variants is determined by calculating genetic variant performance in the reference population and selecting the best-performing genetic variant.

14. 10. The composition of claim 1 or 4, wherein the IL-33 asthma PRS is calculated using the LDpred method.

15. 10. The composition of claim 1 or 4, wherein the IL-33 asthma PRS is calculated using a pruning and thresholding method.

16. 10. The composition of claim 1 or 4, wherein the plurality of genetic variants comprises at least two genetic variants.

17. 10. The composition of claim 1 or 4, wherein the subject is receiving or is currently receiving dupilumab.

18. The method described in claim 2 or 3, wherein the interleukin-4 receptor alpha antagonist and / or the interleukin-13 receptor antagonist is dupilumab.

19. The method described in claim 2 or 3, wherein the IL-33 antagonist is itepekimab.

20. The method described in claim 2 or 3, wherein the threshold IL-33 asthma PRS is in the top 50% within a reference population.

21. The method described in claim 2 or 3, wherein the endpoint of the IL-33 asthma PRS is an increase in annual exacerbation rate.

22. The method described in claim 2 or 3, wherein the endpoint of the IL-33 asthma PRS is loss of asthma control.

23. The method described in claim 2 or 3, wherein the reference population includes at least 100 subjects.

24. The method described in claim 2 or 3, wherein the reference population is enriched for members of an ancestral group.

25. The method of claim 24, wherein the ancestral groups include European ancestry, African ancestry, Mixed American ancestry, East Asian ancestry, or South Asian ancestry.

26. The method of claim 2 or 3, wherein the multiple genetic variants include single nucleotide polymorphisms (SNPs), insertions, deletions, structural variants, or copy number variations.

27. ​​The method described in claim 2 or 3, wherein the multiple genetic variants are determined by calculating genetic variant performance in the reference population and selecting the genetic variant with the best performance.

28. The method described in claim 2 or 3, wherein the IL-33 asthma PRS is calculated using the LDpred method.

29. The method described in claim 2 or 3, wherein the IL-33 asthma PRS is calculated using a pruning and thresholding method.

30. The method described in claim 2 or 3, wherein the multiple gene variants include at least two gene variants.

31. The method of claim 2 or 3, wherein the subject has been or is currently being administered dupilumab.

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