BIOMARKERS AND METHODS FOR ASSESSING PSORIATIC ARTHRITIS DISEASE ACTIVITY
Provided herein are biomarkers and methods for generating scores useful for assessing psoriatic arthritis (PsA) disease activity in subjects previously diagnosed with PsA. The invention also provides predictive model methods based on the biomarkers, as well as computer systems, software embodiments of the models for scoring and optionally classifying samples, and methods of recommending optimal therapeutic regimens.
1 . A method for predicting one or more clinical assessments of disease activity in a subject previously diagnosed with an inflammatory disorder, the method comprising:
(a) performing at least one immunoassay on a sample from the subject to generate a dataset comprising quantitative data comprising at least four markers selected from chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); interleukin 6 (interferon, beta 2) (IL6); leptin (LEP); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid Al (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A); vascular cell adhesion molecule 1 (VCAM1); or, vascular endothelial growth factor A (VEGFA); and
(b) applying an algorithm to said dataset to determine a disease activity score, wherein said disease activity score predicts one or more clinical assessments of disease activity.
2 . The method of claim 1 , wherein the inflammatory disorder is psoriatic arthritis.
3 . The method of claim 1 , wherein performance of the at least one immunoassay comprises:
obtaining the blood sample, wherein the blood sample comprises the protein markers;
contacting the blood sample with a plurality of distinct reagents;
generating a plurality of distinct complexes between the reagents and markers; and
detecting the complexes to generate the data.
4 . The method of claim 1 , wherein the at least four protein markers comprise at least five, six, seven, eight, nine, ten, or eleven, markers selected from CHI3L1, CRP, EGF, IL6, LEP, MMP1, MMP3, RETN, SAA1, TNFRSF1A, VCAM1, or VEGFA.
5 . The method of claim 1 , wherein the at least four protein markers comprise at most 12, 25, 50, 100, 250, or 500 protein markers.
6 . The method of claim 1 , wherein the CHI3L1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001267.2, wherein the CRP is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000558.2, wherein the EGF is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001954.2, wherein the IL6 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000591.1, wherein the LEP is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000221.1, wherein the MMP1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_002412.1, wherein the MMP3 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_002413.1, wherein the RETN is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_065148.1, wherein the SAA1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000322.2, wherein the TNFRSF1A is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001056.1, wherein the VCAM1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001069.1, and wherein the VEGFA is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001020539.2.
7 . The method of claim 1 , wherein the one or more clinical assessments of disease activity comprise one or more DAS28 score components.
8 . The method of claim 7 , wherein the one or more DAS28 score components is selected from the group consisting of tender joint count (TJC), swollen joint count (SJC), and patient global health assessment (PGHA).
9 . The method of claim 1 , wherein the disease activity score predicts one or more clinical measures of disease activity with a higher correlation coefficient than the correlation coefficient of CRP alone.
10 . The method of claim 1 , wherein the algorithm comprises the formula:
MBDA
Score
=
(
(
0.56
×
sqrt
(
predicted
TJC
)
+
0.28
×
sqrt
(
predicted
SJC
)
+
0.36
×
log
(
CRP
/
106
+
1
)
+
(
0.14
×
predicted
PGHA
)
+
0.96
)
×
10.53
)
+
1
,
wherein PTJC is predicted, PSJC=predicted swollen joint count, and PPGHA=predicted PGHA,
wherein PTJC is calculated according to the formula:
-
3
8
.
5
6
4
+
(
3.997
*
SAA
11
/
10
)
+
(
17.331
*
IL
6
1
/
10
)
+
(
4.665
*
CHI
3
L
11
/
10
)
-
(
15.236
*
EGF
1
/
10
)
+
(
2.651
*
TNFRSF
1
A
1
/
10
)
+
(
2.641
*
LEP
1
/
10
)
+
(
4.026
*
VEGFA
1
/
10
)
-
(
1.47
*
VCAM
11
/
10
)
;
wherein PSJC is calculated according to the formula:
-
2
5
.
4
4
4
+
(
4.051
*
(
SAA
11
/
10
)
+
(
16.154
*
IL
61
/
10
)
-
(
11.847
*
EGF
1
/
10
)
+
(
3.091
*
CHI
3
L
11
/
10
)
+
(
0.353
*
TNFRSF
1
A
1
/
10
)
;
and
wherein PPGHA is calculated according to the formula:
-
1
3
.
4
8
9
+
(
5.474
*
IL
61
/
10
)
+
(
0.486
*
SAA
11
/
10
)
+
(
2.246
*
MMP
11
/
10
)
+
(
1.684
*
LEP
1
/
10
)
+
(
4.14
*
TNFRSF
1
A
1
/
10
)
+
(
2.292
*
VEGFA
1
/
10
)
-
(
1.898
*
EGF
1
/
10
)
+
(
0.028
*
MMP
3
1
/
10
)
-
(
2.892
*
VCAM
11
/
10
)
-
(
0.506
*
RETN
1
/
10
)
.
11 . A system for scoring a sample, said system comprising:
a storage memory for storing a dataset associated with a sample obtained from a subject previously diagnosed with psoriatic arthritis (PsA), wherein said dataset comprising quantitative data for at least four markers selected from chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1); C-reactive protein, pentraxin-related (CRP);
epidermal growth factor (beta-urogastrone) (EGF); interleukin 6 (interferon, beta 2) (IL6);
leptin (LEP); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid Al (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A); vascular cell adhesion molecule 1 (VCAM1); or, vascular endothelial growth factor A (VEGFA); and
a processor communicatively coupled to the storage memory, the processor configured to apply an algorithm to the dataset to determine a disease activity score wherein said disease activity score provides a quantitative measure of PsA disease activity in the subject and wherein the algorithm is trained using data representing the at least four markers in samples from subjects having a known PsA disease activity.
12 . The system of claim 11 , wherein the at least four protein markers comprise at least five, six, seven, eight, nine, ten, or eleven markers selected from CHI3L1, CRP, EGF, IL6, LEP, MMP1, MMP3, RETN, SAA1, TNFRSF1A, VCAM1, or VEGFA.
13 . The system of claim 11 , wherein the at least four protein markers comprise at most 12, 25, 50, 100, 250, or 500 protein markers.
14 . The system of claim 11 , wherein the CHI3L1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001267.2, wherein the CRP is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000558.2, wherein the EGF is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001954.2, wherein the IL6 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000591.1, wherein the LEP is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000221.1, wherein the MMP1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_002412.1, wherein the MMP3 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_002413.1, wherein the RETN is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_065148.1, wherein the SAA1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000322.2, wherein the TNFRSF1A is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001056.1, wherein the VCAM1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001069.1, and wherein the VEGFA is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001020539.2.
15 . A method for generating protein level data for a subject comprising:
performing at least one immunoassay on a blood sample from the subject to generate a dataset comprising protein level data for at least four protein markers, wherein the at least four protein markers comprise at least four markers selected from chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); interleukin 6 (interferon, beta 2) (IL6); leptin (LEP); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A); vascular cell adhesion molecule 1 (VCAM1); or, vascular endothelial growth factor A (VEGFA); and wherein the subject has been previously diagnosed with psoriatic arthritis (PsA).
16 . The method of claim 15 , wherein performance of the at least one immunoassay comprises:
obtaining the blood sample, wherein the blood sample comprises the protein markers;
contacting the blood sample with a plurality of distinct reagents;
generating a plurality of distinct complexes between the reagents and markers; and
detecting the complexes to generate the data.
17 . The method of claim 15 , wherein the at least four protein markers comprise at least five, six, seven, eight, nine, ten, or eleven, markers selected from CHI3L1, CRP, EGF, IL6, LEP, MMP1, MMP3, RETN, SAA1, TNFRSF1A, VCAM1, or VEGFA.
18 . The method of claim 15 , wherein the at least four protein markers comprise at most 12, 25, 50, 100, 250, or 500 protein markers.
19 . The method of claim 15 , wherein the CHI3L1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001267.2, wherein the CRP is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000558.2, wherein the EGF is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001954.2, wherein the IL6 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000591.1, wherein the LEP is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000221.1, wherein the MMP1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_002412.1, wherein the MMP3 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_002413.1, wherein the RETN is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_065148.1, wherein the SAA1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_000322.2, wherein the TNFRSF1A is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001056.1, wherein the VCAM1 is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001069.1, and wherein the VEGFA is at least 90% identical to the amino acid sequence of NCBI RefSeq NP_001020539.2.