Methods for profiling and quantitating cell-free rna

Abstract

The invention generally relates to methods for assessing the health of a tissue by characterizing circulating nucleic acids in a biological sample. According to certain embodiments, methods for assessing the health of a tissue include the steps of detecting a sample level of RNA in a biological sample, comparing the sample level of RNA to a reference level of RNA specific to the tissue, determining whether a difference exists between the sample level and the reference level, and characterizing the tissue as abnormal if a difference is detected.

What is claimed is: 
     
         1 . A method of assessing the health of a tissue, the method comprising
 detecting a sample level of RNA in a biological sample;   comparing the sample level of RNA to a reference level of RNA specific to the tissue;   determining whether a difference exists between the sample level and the reference level; and   characterizing the tissue as abnormal if a difference is detected.   
     
     
         2 . The method of  claim 1 , further comprising the step of monitoring the tissue for disease progression. 
     
     
         3 . The method of  claim 1 , wherein the reference level corresponds to the state of the tissue at a time-point. 
     
     
         4 . The method of  claim 1 , wherein the reference level is a level of RNA specific to the tissue in a healthy state. 
     
     
         5 . The method of  claim 1 , wherein the biological sample is blood, a blood fraction, saliva, sputum, urine, semen, transvaginal fluid, cerebrospinal fluid, stool, a cell or a tissue biopsy. 
     
     
         6 . The method of  claim 5 , wherein the biological sample is blood. 
     
     
         7 . The method of  claim 6 , wherein the RNA is cell-free RNA. 
     
     
         8 . The method of  claim 1 , wherein the detecting step is performed via a sequencing technique, a microarray technique, or both. 
     
     
         9 . The method of  claim 8 , wherein the sequencing technique is whole transcriptome shotgun sequencing. 
     
     
         10 . The method of  claim 1 , wherein said reference level is determined by a computer-generated database. 
     
     
         11 . The method of  claim 1 , wherein the tissue is selected from the group consisting of: whole blood, bone marrow, hypothalamus, smooth muscle, lung, thymus, lymph node, and thyroid. 
     
     
         12 . A method of assessing health of a tissue, the method comprising characterizing the tissue as abnormal if a specified level of RNA is present in the blood. 
     
     
         13 . The method of  claim 12 , wherein the tissue is selected from the group consisting of:
 whole blood, bone marrow, hypothalamus, smooth muscle, lung, thymus, lymph node, and thyroid.   
     
     
         14 . The method of  claim 12 , further comprising
 detecting a level of RNA in a blood sample;   comparing the sample level of RNA to a reference level of RNA specific to a tissue;   determining whether a difference exists between the sample level and the reference level, and   characterizing the tissue as abnormal if the sample level and the reference level are the same.   
     
     
         15 . The method of  claim 14 , wherein the reference level is indicative of a disease or a condition. 
     
     
         16 . The method of  claim 12 , wherein the RNA is cell-free RNA. 
     
     
         17 . The method of  claim 12 , wherein the detecting step is performed via a sequencing technique, a microarray technique, or both. 
     
     
         18 . The method of  claim 17 , wherein the sequencing technique is whole transcriptome shotgun sequencing. 
     
     
         19 . The method of  claim 14 , wherein said reference level is determined by a computer-generated database. 
     
     
         20 . A method for detecting differential transcript levels from a biological sample comprising a mixture of genetic material from different genomic sources, the method comprising the steps of:
 a) obtaining a plurality of biological samples over different time-points, each sample containing a mixture of genetic material from different genomic sources;   b) amplifying a plurality of RNA transcripts from the plurality of biological samples to obtain a plurality of amplified samples, each containing a mixture of amplified RNA transcripts from different genomic sources;   c) detecting the levels of one or more of the RNA transcripts from each of the amplified samples; and   d) conducting an analysis that compares the levels of one or more of the RNA transcripts between each of the amplified samples to determine a differential profile for one or more of the detected RNA transcripts across the different time-points.   
     
     
         21 . The method of  claim 20 , wherein the biological sample is blood, a blood fraction, saliva, sputum, urine, semen, transvaginal fluid, cerebrospinal fluid, stool, a cell or a tissue biopsy. 
     
     
         22 . The method of  claim 21 , wherein the biological sample is blood. 
     
     
         23 . The method of  claim 22 , wherein the blood is peripheral blood derived from a pregnant woman, or a fraction thereof. 
     
     
         24 . The method of  claim 20 , wherein the different genomic sources are derived from a pregnant female and a fetus. 
     
     
         25 . The method of  claim 20 , wherein the detecting step is performed via a sequencing technique, a microarray technique, or both. 
     
     
         26 . The method of  claim 25 , wherein the sequencing technique is whole transcriptome shotgun sequencing. 
     
     
         27 . The method of  claim 25 , wherein the differential profile of one or more RNA transcripts is indicative of a disease or a condition. 
     
     
         28 . The method of  claim 27 , wherein the disease or condition is preterm pregnancy. 
     
     
         29 . The method of  claim 27 , wherein the disease or condition is a pathological pregnancy. 
     
     
         30 . The method of  claim 27 , wherein the differential profile includes one or more genes selected from the group consisting PVALB, CLCN3, ITGA2B, LTV1, HIST1H4B, TREML1, NPTN, LSM2, SCGB1C1, NOP10, MFSD1, MALAT1, GDI1, HIST1H1C, HIST1H4H, CD226, ITM2B, MLLT6, ANO6, and ITGB3.