| 1b | Discussion | |
|---|---|---|
| IL-1b | IL-1B is just sufficient as a marker indicative of NLRP3 activation. I just don't see how much additional value from Casp-1. Assay is already available (MSD ELISA). It seems that your blood-based BM-based patient stratification strategy is centered on IL-1b. Could you help me understand what the rationale behind why we choose IL-1b (ie not NLRP3 or caspase-1)? |
As the mediator of pyroptosis and one of the major products of Casp-1, IL-1B can be a biomarker indicative of pharmacodynamics and modulation of pathology. We can get multiple birds with this one stone while NLRP3 and Casp-1 have a limited utility just as indicator of inflammasome activation. These would be, if any, a back-up biomarker. We don't need many back-up plans, given finite money and time. Another practical aspect is that we cant compare any data of ASC, NLRP3 or Casp-1 etc. because historical data is poor in quality and quantity in comparison with such a classic marker like IL-1B. |
| Question | |
|---|---|
| clinical | Biological hypothesis? Risk factor for spreading? Or for DA neuronal loss? Does Jaya attend regular team meeting? High level clinical plan? TAU endorsement? |
| PET | Progress? Who is leading? |
| CSF | Assay 다 되어 있나, for CSF & blood? [NLRP3, ASC, caspase-1, ] VS [IL-1b] |
| Patient selection | Screening 이니, 당연히 blood 를 쓸건데, [robustness of blood BM] Correlation of BM (IL-1b) between blood and CNS? Blood 에서의 origin 은 ? 뭘쓰나? [NLRP3, ASC, caspase-1, ] VS [IL-1b] Correlation with DatsCAN, ? Natural HX STUDY 계획했나? KOL 그 했나? HIGH risk group: 뭐가 다른가? Rapid progression? Tx response? II-IB 와 NLRP3 quantitative correlation? How to decide cut off point? 우리 약이 activated NLRP3 에만 결합하나? |
| IL-1b high level 의 source? It can just be variability on the same level of NLRP3 activation, not the truly overactivated NLRP3. So we should look at correlation NLRP3 - IL-1b - clinical severity (근데 이 부문에서 다른 cause 들 rule out 해야 할 텐데, but PD 환자들은 모두 다른 원인이 있는 것이니, PD 환자에서 비교하면 IL-1b 와 다른 원인을 비교하는 것임 ie lysosome) , so should we do it in isogenic iPS? |
Stratification strategy on neuroinflammation
Postmortem study
| In vitro ? | ||||
|---|---|---|---|---|
| If a large ES | No subpopulation strategy | |||
| If a small ES | Subpopulation strategy | DR impact | Correlation with TH | |
| Tractibility (measurable BM) | Correlation with MBM | |||
| Correlation with microglial imaging | X | |||
| Pharmacologic effect (Responder subpopulation relevance) | BzATP ? | It also potently blocked nigericin induced LDH) release with an IC50 of 1.7 nM, demonstrating that it is cytoprotective by specifically blocking NLRP3-pyroptotic cell death. |
RNA-Seq (Daria)
(Inline Takeda slide titled “Inflammasome gene expression in blood to stratify patients: baseline gene expression”; preserved as body_r03 evidence.)
- We have analyzed a large blood RNA-seq AMP-PD dataset: PPMI 816 cases/617 controls; PDBP 780 cases/504 controls.
- Compared PD case (including LRRK2, SNCA, GBA mutants) and control at baseline time point (M0 recruitment).
- Significance of inflammasome genes in data-driven approach: what portion of inflammasome genes are in DEGs (controls vs case)? The inflammasome genes are not significantly over-represented within DEGs: time(0, 6, 12, 24, 36m) = p-val (0.6, 0.11, 0.15, 0.7, 0.3).
- We have used K-means (k=3) clustering to identify subset of samples with inflammasome-related gene expression pattern in PPMI and PDBP datasets.
- We checked whether these clusters are associated with clinical parameters (MDS UPDRS III) associated to motor function.
- Conclusion: We could identify 3 clusters of patients with different expression of inflammasome genes at baseline in PPMI dataset (shown below), these clusters were also associated to motor abnormalities. These clusters are not reproducible across other timepoints.
PPMI sample clusters (heatmap, distribution of MDS-UPDRS III codes was significantly different (p<0.05) in patients from cluster X in comparison to other two; codes listed: code_upd2303b_rigidity_rt_upper_extremity, code_upd2303b_left_leg_agile, code_upd23010_consistency_of_rest_tremor, code_upd23hy_hoehn_and_yahr_stage; *Please, see clarification on Slide #3.)
Heatmap of inflammasome-related DEGs (case vs control, nominal p-val<0.05) from PPMI dataset: the genes have 3 expression patterns hence the clusters in y-axis; the samples have 3 expression pattern hence the clusters in the x-axis.
Daria Prilutsky: no association at the DNA level was found, so we looked currently at the RNA level and saw that patients can be clustered based on inflammasome gene expression (not only NLRP3, 72 inflammasome genes)
(Inline Takeda slide titled “Inflammasome gene expression in blood to stratify patients: longitudinal gene expression”; preserved as body_r03 evidence.)
- Expression of inflammasome-related genes at different time points. Gene was included in the heatmap if it was DE in cases vs controls (nominal p< 0.05) at least at one timepoint.
- Value = Log2(case/control); Red = upregulated in cases versus controls; Blue = downregulated in cases versus controls.
- We have selected IL1B as an example to demonstrate differences between case to control. IL1B gene expression is higher in cases vs control across multiple time points (except t=24 months).
- Time axis ticks: 0, 6, 12, 24, 36 months.
Computational Biology — Daria Prilutsky, Naif Zaman
C5aR1 (Woodruff, Univ of Queensland)
| a-syn | complement system activation (cell type?) | generate C5a (a complement fragment) | Binding to C5aR1 | Microglia activation? | activates ERK pathway (→ ↑pERK){Cao, 2012 #1687} | ↑ NLRP3 assembly (↑ ASC, ↑ Procaspase 1 → caspase 1) | ProIL-1b → IL-1b, il-18 → ↑ secretion of IL-1 from microglia | DA | aSyn | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| human | Post mortem | Woodruff) Activation of the complement system has been observed in PD, with early complement fragments (js no specific mention of C5a!) upregulated in regions of cell death in post-mortem tissue from PD patients. | 2018 Gordon abstract) C5aR1 expression on (activated) microglia (quantitative... | data not shown) | |||||||
| NCNP has shown CSF C5 reduction in PD patient samples, may worthwhile to consider additional PD patient tissue evaluation | |||||||||||
| CSF | (inline CSF bar chart: Healthy ~0.4 vs PD ~1.0 ng/ml, axis "C5a (ng/ml)"; preserved as body_r04 evidence) | ||||||||||
| serum | (inline Serum bar chart: Healthy ~25 vs PD ~38 ng/ml, axis "C5a (ng/ml)"; preserved as body_r05 evidence) | ||||||||||
| PBMC | |||||||||||
| Additional Computational Biology analysis in PPMI/PDBP data set has shown the correlation between C5aR1 vs. suggested molecules ... 202011 | |||||||||||
| aSyn overexpression | 20201116 pdf p11: aSyn overexpression → ↑ C5a in SN | 2018 Gordon abstract) aSyn overexpression → ↑ aSyn (...) | |||||||||
Uncertain Spans
| location | transcription | uncertainty |
|---|---|---|
| C5aR1 post-mortem cell | Woodruff) Activation of the complement system has been observed in PD, with early complement fragments (js no specific mention of C5a!) upregulated in regions of cell death in post-mortem tissue from PD patients. | The “(js no specific mention of C5a!)” parenthetical is preserved; “js” likely abbreviates “just” or “just”. |
| RNA-Seq slide bullets | time(0, 6, 12, 24, 36m) = p-val (0.6, 0.11, 0.15, 0.7, 0.3) | The list separator and decimal punctuation are faint. |
| C5aR1 CSF / serum bar charts | numeric Healthy/PD values | Approximate y-axis values are read from the chart; the exact tick spacing is small. |
| Stratification table In vitro cell | It also potently blocked nigericin induced LDH) release with an IC50 of 1.7 nM | The trailing parenthesis after LDH is faint. |