Back

Bistable attractor dynamics in difficult-to-treat rheumatic disease: a multi-axis ODE framework with cross-disease transcriptomic evidence

jung, s.; jeong, h.; jeon, C. H.

2026-04-06 systems biology
10.64898/2026.04.02.716225 bioRxiv
Show abstract

Difficult-to-treat (D2T) rheumatic disease affects approximately 12% of rheumatoid arthritis patients and resists sequential biologic therapy, yet no mechanistic model explains this refractoriness as a system-level phenomenon. Here we present the 3-Axis Integrative Framework (3-AIF), a six-variable ordinary differential equation system integrating mucosal tolerance, energy-gated neuroimmune danger sensing, and integrated stress response pathways coupled through Hill-function metabolic gating. Stability analysis reveals bistable dynamics with two co-existing attractors separated by a saddle point. Bifurcation analysis demonstrates fold catastrophe with hysteresis: recovery requires greater therapeutic effort than disease prevention. Sensitivity analysis identifies three dominant parameters mapping to neuroimmune activation, energy drain, and recovery capacity. Cross-disease transcriptomic consistency analysis across six public datasets (n=310, five rheumatic diseases, four tissue types) reveals compartment-specific axis dysregulation -- circulating cells show integrated stress response activation while target tissues show pathway exhaustion -- and disease-specific axis dominance patterns consistent with model predictions.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nature Communications
4913 papers in training set
Top 12%
14.0%
2
Cell Systems
167 papers in training set
Top 1%
9.8%
3
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 6%
9.8%
4
npj Systems Biology and Applications
99 papers in training set
Top 0.1%
9.8%
5
Journal of The Royal Society Interface
189 papers in training set
Top 0.6%
6.2%
6
eLife
5422 papers in training set
Top 15%
6.1%
50% of probability mass above
7
iScience
1063 papers in training set
Top 3%
4.2%
8
PLOS Computational Biology
1633 papers in training set
Top 9%
3.9%
9
Cell Reports
1338 papers in training set
Top 16%
3.5%
10
Advanced Science
249 papers in training set
Top 6%
3.5%
11
Science Advances
1098 papers in training set
Top 7%
3.5%
12
Scientific Reports
3102 papers in training set
Top 52%
2.0%
13
Communications Biology
886 papers in training set
Top 10%
1.6%
14
Bulletin of Mathematical Biology
84 papers in training set
Top 1%
1.3%
15
Molecular Systems Biology
142 papers in training set
Top 1%
1.2%
16
Nature Medicine
117 papers in training set
Top 3%
1.1%
17
Development
440 papers in training set
Top 3%
0.9%
18
JCI Insight
241 papers in training set
Top 7%
0.8%
19
Royal Society Open Science
193 papers in training set
Top 5%
0.8%
20
PLOS ONE
4510 papers in training set
Top 67%
0.8%
21
Developmental Cell
168 papers in training set
Top 12%
0.7%
22
npj Digital Medicine
97 papers in training set
Top 4%
0.6%
23
Mathematical Biosciences
42 papers in training set
Top 1%
0.6%
24
Computational and Structural Biotechnology Journal
216 papers in training set
Top 11%
0.6%