Methods of monitoring conditions by sequence analysis
There is a need for improved methods for determining the diagnosis and prognosis of patients with conditions, including autoimmune disease and cancer. Provided herein are methods for using DNA sequencing to identify personalized biomarkers in patients with autoimmune disease and other conditions. Identified biomarkers can be used to determine the disease state for a subject with an autoimmune disease or other condition.
1. A method for quantitatively measuring clonotypes correlating to a disease state of a subject wherein the disease is a cancer, wherein the method comprises:
(a) identifying a sequence and level of the clonotype correlated with the disease in the subject, comprising
(1) generating and comparing a first clonotype profile from a first sample taken from the subject and a second clonotype profile from a second sample taken from the subject, wherein the first sample and the second sample each comprises T-cells and/or B-cells from the subject and are taken at different times from the subject, wherein each clonotype profile is generated by a method comprising:
(i) isolating genomic DNA from the first and second samples;
(ii) amplifying from said isolated genomic DNA recombined DNA sequences of the T-cells and/or B-cells in a multiplex PCR, comprising hybridizing to the genomic DNA a plurality of primers; wherein the regions to be amplified comprise V, D, and/or J segments of an immunoglobulin and/or a T-cell or B-cell receptor gene;
(iii) spatially isolating individual molecules of the amplified sequences on a solid substrate, wherein the solid substrate is a glass slide; and
(iv) sequencing said amplified individual molecules to produce the clonotype profile by sequencing by synthesis using reversibly terminated labeled nucleotides;
(2) comparing the generated first and second clonotype profiles to identify the presence and level of the clonotype correlated with the disease in the subject; and
(b) producing a quantitative profile of clonotyes identified in step (a)(2) that correlate with the disease in the subject, wherein the profile comprises sequences and levels of said clonotypes.
2. The method of claim 1 , wherein each of the clonotype profiles comprises at least 1000 sequence reads, wherein each read is about 30 base pairs to about 300 base pairs, so that different clonotypes of said sample are determined from such sequence reads with a confidence of at least 99.9 percent.
3. The method of claim 1 , wherein the step (a)(1) further comprises minimizing errors introduced by amplification and/or by sequencing, comprising combining sequence reads together to more accurately determine the frequency of individual molecules.
4. The method of claim 1 , wherein the region to be amplified comprises V, D, and/or J segments of an immunoglobulin gene.
5. The method of claim 1 , wherein the region to be amplified comprises V, D, and/or J segments of a T cell receptor gene.
6. The method of claim 4 , wherein the immunoglobulin gene is an IgH gene.
7. The method of claim 6 , wherein the primers bind to a V segment and a J segment of the IgH gene.
8. The method of claim 4 , wherein the immunoglobulin gene is an IgK gene.
9. The method of claim 8 , wherein the primers bind to a V segment and a J segment of the IgK gene.
10. The method of claim 4 , wherein the immunoglobulin gene is an IgL gene.
11. The method of claim 10 , wherein the primers bind to a V segment and a J segment of the IgL gene.
12. The method of claim 5 , wherein the T cell receptor gene is a T-cell receptor gamma (TRG) gene.
13. The method of claim 12 , wherein the primers bind to a V segment and a J segment of a T-cell receptor gamma (TRG) gene.
14. The method of claim 5 , wherein the T-cell receptor gene is a T-cell receptor beta (TRB) gene.
15. The method of claim 14 , wherein the primers bind to a V segment and a J segment of a T-cell receptor beta (TRB) gene.
16. The method of claim 1 , wherein step b) further comprises determining the state of disease in the subject, comprising predicting the disease state using the set of factors which include one or more of the number of the number of positive clonotypes, the level of a positive clonotype, the rate of change of a clonotype, the level of a clonotype at episode peak, and the level of a clonotype at an inactive disease state.