Methods to diagnose and treat acute respiratory infections

Abstract

The present disclosure provides methods for determining the etiology of an acute respiratory infection in a subject and methods of treating the subject based on the determination, as well as systems useful for performing the determination using a biological sample from the subject.

1 . A method for making acute respiratory illness classifiers for a platform, wherein the classifiers comprise a bacterial ARI classifier, a viral ARI classifier and a non-infectious illness classifier for the platform, said method comprising:
 (a) obtaining biological samples from a plurality of subjects known to be suffering from a bacterial acute respiratory infection;   (b) obtaining biological samples from a plurality of subjects known to be suffering from a viral acute respiratory infection;   (c) obtaining biological samples from a plurality of subjects known to be suffering from a non-infectious illness;   (d) measuring on said platform the gene expression levels of a plurality of genes (e.g., all expressed genes or transcriptome, or a subset thereof) in each of said biological samples from steps (a), (b) and (c);   (e) normalizing the gene expression levels obtained in step (d) to generate normalized gene expression values; and   (f) generating a bacterial ARI classifier, a viral ARI classifier and a non-infectious illness classifier for the platform based upon said normalized gene expression values,   to thereby make the acute respiratory illness classifiers for the platform.   
     
     
         2 . The method of  claim 1 , wherein said measuring comprises or is preceded by one or more steps of: purifying cells from said sample, breaking the cells of said sample, and isolating RNA from said sample. 
     
     
         3 . The method of  claim 1 , wherein said measuring comprises semi-quantitative PCR and/or nucleic acid probe hybridization. 
     
     
         4 . The method of  claim 1 , wherein said platform comprises an array platform, a thermal cycler platform (e.g., multiplexed and/or real-time PCR platform), a hybridization and multi-signal coded (e.g., fluorescence) detector platform, a nucleic acid mass spectrometry platform, a nucleic acid sequencing platform, or a combination thereof. 
     
     
         5 . The method of  claim 1 , wherein said generating comprises iteratively:
 (i) assigning a weight for each normalized gene expression value, entering the weight and expression value for each gene into a classifier (e.g., a linear regression classifier) equation and determining a score for outcome for each of the plurality of subjects, then   (ii) determining the accuracy of classification for each outcome across the plurality of subjects, and then   (iii) adjusting the weight until accuracy of classification is optimized,   to provide said bacterial ARI classifier, viral ARI classifier and non-infectious illness classifier for the platform,   wherein genes having a non-zero weight are included in the respective classifier,   and optionally uploading components of each classifier (genes, weights and/or etiology threshold value) onto one or more databases.   
     
     
         6 . The method of  claim 5 , wherein the classifier is a linear regression classifier and said generating comprises converting a score of said classifier to a probability. 
     
     
         7 . The method according to  claim 1  further comprising validating said ARI classifier against a known dataset comprising at least two relevant clinical attributes. 
     
     
         8 . A bacterial ARI classifier made according to the method of  claim 1 , wherein the bacterial ARI classifier comprises expression levels of 5, 10, 20, 30 or 50, to 80, 100, 150 or 200 of the genes (measurable, e.g., with oligonucleotide probes homologous to said genes) listed as part of a viral ARI classifier in Table 1, Table 2, Table 9, Table 10 and/or Table 12. 
     
     
         9 . A viral ARI classifier made according to the method of  claim 1 , wherein the viral classifier comprises expression levels of 5, 10, 20, 30 or 50, to 80, 100, 150 or 200 of the genes (measurable, e.g., with oligonucleotide probes homologous to said genes) listed as part of a viral ARI classifier in Table 1, Table 2, Table 9, Table 10 and/or Table 12. 
     
     
         10 . A non-infectious illness classifier made according to the method of  claim 1 , said non-infectious classifier comprises expression levels of 5, 10, 20, 30 or 50, to 80, 100, 150 or 200 of the genes (measurable, e.g., with oligonucleotide probes homologous to said genes) listed as part of a non-infectious illness classifier in Table 1, Table 2, Table 9, Table 10 and/or Table 12. 
     
     
         11 . A method for determining an etiology of an acute respiratory illness in a subject suffering therefrom, or at risk thereof, selected from bacterial, viral and/or non-infectious, comprising:
 (a) obtaining a biological sample from the subject;   (b) measuring on a platform gene expression levels of a pre-defined set of genes (i.e., signature) in said biological sample;   (c) normalizing the gene expression levels to generate normalized gene expression values;   (d) entering the normalized gene expression values into one or more acute respiratory illness classifiers selected from a bacterial acute respiratory infection (ARI) classifier, a viral ARI classifier and a non-infectious illness classifier, said classifier(s) comprising pre-defined weighting values (i.e., coefficients) for each of the genes of the pre-defined set of genes for the platform, optionally wherein said classifier(s) are retrieved from one or more databases; and   (e) calculating an etiology probability for one or more of a bacterial ARI, viral ARI and non-infectious illness based upon said normalized gene expression values and said classifier(s),   to thereby determine whether the acute respiratory illness in the subject is bacterial in origin, viral in origin, non-infectious in origin, or some combination thereof.   
     
     
         12 . The method of  claim 11 , further comprising:
 (f) comparing the probability to pre-defined thresholds, cut-off values, or ranges of values (e.g., a confidence interval) that indicate likelihood of infection.   
     
     
         13 . The method of  claim 11 , wherein the subject is suffering from acute respiratory illness symptoms. 
     
     
         14 . The method of  claim 11 , wherein said subject is suspected of having a bacterial infection or a viral infection. 
     
     
         15 . The method of  claim 11 , wherein, if the sample does not indicate a likelihood of bacterial ARI, further comprises repeating steps (d) and (e) using only the viral classifier and/or non-infectious classifier, to determine whether the acute respiratory illness in the subject is viral in origin, non-infectious in origin, or a combination thereof. 
     
     
         16 . The method of  claim 11 , wherein, if the sample does not indicate a likelihood of viral ARI, further comprises repeating steps (d) and (e) using only the bacterial classifier and/or non-infectious classifier, to determine whether the acute respiratory illness in the subject is bacterial in origin, non-infectious in origin, or a combination thereof. 
     
     
         17 . The method of  claim 11 , wherein, if the sample does not indicate a likelihood of non-infectious illness, further comprises repeating steps (d) and (e) using only the bacterial classifier and/or viral classifier, to determine whether the acute respiratory illness in the subject is bacterial in origin, viral in origin, or a combination thereof. 
     
     
         18 . The method of  claim 11  in which the method further comprises generating a report assigning the subject a score indicating the probability of the etiology of the acute respiratory illness. 
     
     
         19 . The method as in  claim 11  in which the pre-defined set of genes comprises from 30 to 200 genes. 
     
     
         20 . The method according to  claim 11  in which the pre-defined set of genes comprises from 30 to 200 genes listed in Table 1, Table 2, Table 9, Table 10 and/or Table 12. 
     
     
         21 . The method as in  claim 11  in which the biological sample comprises is selected from the group consisting of peripheral blood, sputum, nasopharyngeal swab, nasopharyngeal wash, bronchoalveolar lavage, endotracheal aspirate, and combinations thereof. 
     
     
         22 . The method as in  claim 11  in which the biological sample is a peripheral blood sample. 
     
     
         23 . The method of  claim 11 , wherein the bacterial acute respiratory infection (ARI) classifier, viral ARI classifier and non-infectious illness classifier are obtained by a method of any one of  claims 1 - 7   
     
     
         24 . A method of treating an acute respiratory illness in a subject comprising administering to said subject an appropriate treatment regimen based on an etiology determined by a method of  claim 11 . 
     
     
         25 . The method according to  claim 24 , wherein the appropriate treatment regimen comprises an antibacterial therapy when the etiology is determined to comprise a bacterial ARI. 
     
     
         26 . The method according to  claim 24 , wherein the appropriate treatment regimen comprises an antiviral therapy when the etiology is determined comprise a viral ARI. 
     
     
         27 . A method of monitoring response to a vaccine or a drug in a subject suffering from or at risk of an acute respiratory illness selected from bacterial, viral and/or non-infectious, comprising determining a host response of said subject, said determining carried out by a method of  claim 11 . 
     
     
         28 . The method of  claim 27 , wherein the drug is an antibacterial drug or an antiviral drug. 
     
     
         29 . A system for determining an etiology of an acute respiratory illness in a subject selected from bacterial, viral and/or non-infectious, comprising:
 at least one processor;   a sample input circuit configured to receive a biological sample from the subject;   a sample analysis circuit coupled to the at least one processor and configured to determine gene expression levels of the biological sample;   an input/output circuit coupled to the at least one processor;   a storage circuit coupled to the at least one processor and configured to store data, parameters, and/or classifiers; and   a memory coupled to the processor and comprising computer readable program code embodied in the memory that when executed by the at least one processor causes the at least one processor to perform operations comprising:   controlling/performing measurement via the sample analysis circuit of gene expression levels of a pre-defined set of genes (i.e., signature) in said biological sample;   normalizing the gene expression levels to generate normalized gene expression values;   retrieving from the storage circuit a bacterial acute respiratory infection (ARI) classifier, a viral ARI classifier and a non-infectious illness classifier, said classifier(s) comprising pre-defined weighting values (i.e., coefficients) for each of the genes of the pre-defined set of genes;   entering the normalized gene expression values into one or more acute respiratory illness classifiers selected from the bacterial acute respiratory infection (ARI) classifier, the viral ARI classifier and the non-infectious illness classifier;   calculating an etiology probability for one or more of a bacterial ARI, viral ARI and non-infectious illness based upon said classifier(s); and   controlling output via the input/output circuit of a determination whether the acute respiratory illness in the subject is bacterial in origin, viral in origin, non-infectious in origin, or some combination thereof.   
     
     
         30 . The system of  claim 29 , where said system comprises computer readable code to transform quantitative, or semi-quantitative, detection of gene expression to a cumulative score or probability of the etiology of the ARI. 
     
     
         31 . The system of  claim 29 , wherein said system comprises an array platform, a thermal cycler platform (e.g., multiplexed and/or real-time PCR platform), a hybridization and multi-signal coded (e.g., fluorescence) detector platform, a nucleic acid mass spectrometry platform, a nucleic acid sequencing platform, or a combination thereof. 
     
     
         32 . The system of  claim 29 , wherein the pre-defined set of genes comprises from 30 to 200 genes. 
     
     
         33 . The system of  claim 29 , wherein the pre-defined set of genes comprises from 30 to 200 genes listed in Table 1, Table 2, Table 9, Table 10 and/or Table 12.