1. Sample peptides: -Class 1:1,2,3… -Class 2:1,2,3… -Class 3:1,2,3… SCX/RP-HPLC Collect 100 fractions on MALDI plates MALDI-TOF MS for each sample LC fraction -- m/.z --abundance MASS-Conductor ® SSA ® Machine learning feature discovery and classification Biomarker panels MSMS protein ID Prospective validation with quantitative mass spec (MRM) Figure 1

2. Class A Class B Class C A B HPLC Fractions LC-MALDI intensity HPLC fraction 13 (m/z 1200 ~ 1500)LC-MALDI intensity Figure 2

3. Pool individual urine samples Split into 4 identical samples 1 2 3 4 Spin Freeze @ -20ºC Thaw Process Spin Freeze @ -20ºC Thaw Process Spin Freeze @ -20ºC Thaw Process Spin Freeze @ -20ºC Thaw Process RT 4 hrs Figure 3A

4. 122 t > 3 72 t < -3 S/F/T vs. F/T/SRT/S/F/T vs. RT/F/T/S 14825196 -3 < t < 3t < -3 14762 -3 < t < 3 t > 3 83 0 MW/10000 2 4 2 3 0 1 # X 100 Randomize Feature set 20 X P (Two-Tailed) = 0.013 Figure 3B

5. Transit B Pool 5 individual urine samples Split into 6 identical samples 1 2 3 4 5 6 Day 1 Process Day 2 Process R.T. Day 3Day 4Day 5 Process R.T. Process R.T. Process R.T. Receive FEDEX Process 5 X Figure 1

6. Day 2 vs. Day 1 Day 3 vs. Day 1 Day 4 vs. Day 1Day 5 vs. Day 1FEDEX vs. Day 1 Density 0.00.20.40.60.81.00.00.20.40.60.81.00.00.20.40.60.81.00.00.20.40.60.81.00.00.20.40.60.81.0 Tukey HSD P value between sub groups 0 2 4 6 8 10 12 Figure 3 B

7. 15516728 t > 3 Day 2 vs. 1 -3 < t < 3 t < -3 Day 3 vs. 1 -3 < t < 3 33 t > 3t < -3 553 Day 4 vs. 1 -3 < t < 3 38 t > 3t < -3 163251469 Day 5 vs. 1 -3 < t < 3 149 t < -3 15298 t > 3 761 FEDEX vs. day 1 -3 < t < 3 173 t < -3 15982 t > 3 1216565339 MW/1000 1 3 Figure 4 B

8. Distribution of CV of each feature Distribution of  CV of each feature 1.0 0.5 2.0 1.5 0.0 Day 1Day 2Day 3Day 4Day 5FEDEXDay 2 - Day 1 Day 3 - Day 1 Day 4 - Day 1 Day 5 - Day 1 FEDEX - Day 1 0.0 2.0 1.0 -2.0 Figure 5 B

9. 1. THP 982.59 VLNLGPITR 2. THP1047.48 SGSVIDQSRV 3. THP1211.66 DQSRVLNLGPI 4. THP1225.69 SRVLNLGPITR 5. THP1324.76 IDQSRVLNLGPI 6. THP1423.83 VIDQSRVLNLGPI 7. THP1468.82 DQSRVLNLGPITR 8. THP1510.87 SVIDQSRVLNLGPI 9. THP1567.91 GSVIDQSRVLNLGPI 10. THP1581.91 IDQSRVLNLGPITR 11. THP1654.91 SGSVIDQSRVLNLGPI 12. THP1680.98 VIDQSRVLNLGPITR 13. THP1755.96 SGSVIDQSRVLNLGPIT 14. THP1768.01 SVIDQSRVLNLGPITR 15. THP1912.07 SGSVIDQSRVLNLGPITR 16. THP2040.16 SGSVIDQSRVLNLGPITRK Figure 7 A

10. Signal/100000 2 0 4 THP 1680.98THP 1912.07THP 1423.83 Figure 7 B

11. PR Enbrel CR Anakinra CRPR CR EnbrelAnakinra A B C Figure X

12. S/F/T vs. F/T/SRT/S/F/T vs. RT/F/T/S Density 0.00.20.40.60.81.00.00.20.40.60.81.0 Tukey HSD P value between sub groups 0 2 4 6 8 10 12 Total # of feature: 15030

13. Urine peptide biomarkers: the discovery process Sample peptides: -Class 1:1,2,3… -Class 2:1,2,3… -Class 3:1,2,3… SCX/RP-HPLC Collect 100 fractions on MALDI plates MALDI-TOF MS for each sample LC fraction -- m/.z --abundance MASS-Conductor ® Machine learning feature discovery and classification Biomarker panels MSMS protein ID Prospective validation with quantitative mass spec (MRM)

14. Allograft Acute Rejection Urine Biomarker Discovery Peak finding Peak alignment Peak indexing Supervised Data mining Feature selection Training Testing LCMS Data reduction Unsupervised Data mining 2D - Clustering QuantitativeLCMS Validation 1234

15. Permutation based FDR analysis of the biomarker signature

16. Proposed Underlying Mechanisms of Urine Naturally Occurring Peptide Biomarkers