What molecular mechanisms mediate SPP1-induced microglial phagocytic activation and synaptic targeting?¶
Notebook ID: nb-SDA-2026-04-15-gap-pubmed-20260406-062118-e3613755 · Analysis: SDA-2026-04-15-gap-pubmed-20260406-062118-e3613755 · Generated: 2026-04-21T18:43:35
Research question¶
The study shows SPP1 from perivascular cells drives microglial synaptic engulfment, but the specific receptors, signaling pathways, and molecular cascades linking SPP1 to phagocytic gene expression remain undefined. Understanding this mechanism is critical for developing targeted therapeutics that could modulate pathological synaptic loss.
Gap type: unexplained_observation Source paper: Perivascular cells induce microglial phagocytic states and synaptic engulfment via SPP1 in mouse models of Alzheimer's disease. (2023, Nat Neurosci, PMID:36747024)
Approach¶
This notebook is generated programmatically from real Forge tool calls and SciDEX debate data. Forge tools used: PubMed Search, MyGene, STRING PPI, Reactome pathways, Enrichr.
Debate Summary¶
Quality score: 0.95 · Rounds: 5
1. Target gene annotations (MyGene)¶
In [1]:
import pandas as pd
ann_rows = [{'gene': 'NLRP3', 'name': 'NLR family pyrin domain containing 3', 'summary': 'This gene encodes a pyrin-like protein containing a pyrin domain, a nucleotide-binding site (NBS) domain, and a leucine-'}, {'gene': 'SPP1', 'name': 'secreted phosphoprotein 1', 'summary': 'The protein encoded by this gene is involved in the attachment of osteoclasts to the mineralized bone matrix. The encode'}]
pd.DataFrame(ann_rows)
| gene | name | summary | |
|---|---|---|---|
| 0 | NLRP3 | NLR family pyrin domain containing 3 | This gene encodes a pyrin-like protein contain... |
| 1 | SPP1 | secreted phosphoprotein 1 | The protein encoded by this gene is involved i... |
2. GO Biological Process enrichment (Enrichr)¶
In [2]:
go_bp = [{'rank': 1, 'term': 'Cellular Response To Lipid (GO:0071396)', 'p_value': 0.00012939152458165337, 'odds_ratio': 39544.0, 'genes': ['SPP1', 'NLRP3']}, {'rank': 2, 'term': 'Response To Testosterone (GO:0033574)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['SPP1']}, {'rank': 3, 'term': 'Positive Regulation Of T-helper 2 Cell Differentiation (GO:0045630)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['NLRP3']}, {'rank': 4, 'term': 'Osmosensory Signaling Pathway (GO:0007231)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['NLRP3']}, {'rank': 5, 'term': 'Regulation Of Type 2 Immune Response (GO:0002828)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['NLRP3']}, {'rank': 6, 'term': 'Negative Regulation Of Acute Inflammatory Response (GO:0002674)', 'p_value': 0.000599909243874975, 'odds_ratio': 3998.6, 'genes': ['NLRP3']}, {'rank': 7, 'term': 'Positive Regulation Of T-helper 2 Cell Cytokine Production (GO:2000553)', 'p_value': 0.0006998773712248138, 'odds_ratio': 3332.0, 'genes': ['NLRP3']}, {'rank': 8, 'term': 'Regulation Of T-helper 2 Cell Differentiation (GO:0045628)', 'p_value': 0.0006998773712248138, 'odds_ratio': 3332.0, 'genes': ['NLRP3']}, {'rank': 9, 'term': 'Response To Vitamin (GO:0033273)', 'p_value': 0.0007998405838081707, 'odds_ratio': 2855.8571428571427, 'genes': ['SPP1']}, {'rank': 10, 'term': 'Response To Vitamin D (GO:0033280)', 'p_value': 0.0007998405838081707, 'odds_ratio': 2855.8571428571427, 'genes': ['SPP1']}]
go_df = pd.DataFrame(go_bp)[['term','p_value','odds_ratio','genes']]
go_df['p_value'] = go_df['p_value'].apply(lambda p: f'{p:.2e}')
go_df['odds_ratio'] = go_df['odds_ratio'].round(1)
go_df['term'] = go_df['term'].str[:60]
go_df['n_hits'] = go_df['genes'].apply(len)
go_df['genes'] = go_df['genes'].apply(lambda g: ', '.join(g))
go_df[['term','n_hits','p_value','odds_ratio','genes']]
| term | n_hits | p_value | odds_ratio | genes | |
|---|---|---|---|---|---|
| 0 | Cellular Response To Lipid (GO:0071396) | 2 | 1.29e-04 | 39544.0 | SPP1, NLRP3 |
| 1 | Response To Testosterone (GO:0033574) | 1 | 5.00e-04 | 4998.5 | SPP1 |
| 2 | Positive Regulation Of T-helper 2 Cell Differe... | 1 | 5.00e-04 | 4998.5 | NLRP3 |
| 3 | Osmosensory Signaling Pathway (GO:0007231) | 1 | 5.00e-04 | 4998.5 | NLRP3 |
| 4 | Regulation Of Type 2 Immune Response (GO:0002828) | 1 | 5.00e-04 | 4998.5 | NLRP3 |
| 5 | Negative Regulation Of Acute Inflammatory Resp... | 1 | 6.00e-04 | 3998.6 | NLRP3 |
| 6 | Positive Regulation Of T-helper 2 Cell Cytokin... | 1 | 7.00e-04 | 3332.0 | NLRP3 |
| 7 | Regulation Of T-helper 2 Cell Differentiation ... | 1 | 7.00e-04 | 3332.0 | NLRP3 |
| 8 | Response To Vitamin (GO:0033273) | 1 | 8.00e-04 | 2855.9 | SPP1 |
| 9 | Response To Vitamin D (GO:0033280) | 1 | 8.00e-04 | 2855.9 | SPP1 |
In [3]:
import matplotlib.pyplot as plt
import numpy as np
go_bp = [{'rank': 1, 'term': 'Cellular Response To Lipid (GO:0071396)', 'p_value': 0.00012939152458165337, 'odds_ratio': 39544.0, 'genes': ['SPP1', 'NLRP3']}, {'rank': 2, 'term': 'Response To Testosterone (GO:0033574)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['SPP1']}, {'rank': 3, 'term': 'Positive Regulation Of T-helper 2 Cell Differentiation (GO:0045630)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['NLRP3']}, {'rank': 4, 'term': 'Osmosensory Signaling Pathway (GO:0007231)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['NLRP3']}, {'rank': 5, 'term': 'Regulation Of Type 2 Immune Response (GO:0002828)', 'p_value': 0.0004999362185987752, 'odds_ratio': 4998.5, 'genes': ['NLRP3']}, {'rank': 6, 'term': 'Negative Regulation Of Acute Inflammatory Response (GO:0002674)', 'p_value': 0.000599909243874975, 'odds_ratio': 3998.6, 'genes': ['NLRP3']}, {'rank': 7, 'term': 'Positive Regulation Of T-helper 2 Cell Cytokine Production (GO:2000553)', 'p_value': 0.0006998773712248138, 'odds_ratio': 3332.0, 'genes': ['NLRP3']}, {'rank': 8, 'term': 'Regulation Of T-helper 2 Cell Differentiation (GO:0045628)', 'p_value': 0.0006998773712248138, 'odds_ratio': 3332.0, 'genes': ['NLRP3']}]
terms = [t['term'][:45] for t in go_bp][::-1]
neglogp = [-np.log10(max(t['p_value'], 1e-300)) for t in go_bp][::-1]
fig, ax = plt.subplots(figsize=(9, 4.5))
ax.barh(terms, neglogp, color='#4fc3f7')
ax.set_xlabel('-log10(p-value)')
ax.set_title('Top GO:BP enrichment (Enrichr)')
ax.grid(axis='x', alpha=0.3)
plt.tight_layout(); plt.show()
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3. STRING protein interaction network¶
In [4]:
print('No STRING PPI data available')
No STRING PPI data available
4. Reactome pathway footprint¶
In [5]:
pw_rows = [{'gene': 'NLRP3', 'n_pathways': 6, 'top_pathway': 'Metalloprotease DUBs'}, {'gene': 'SPP1', 'n_pathways': 1, 'top_pathway': 'Sphingolipid catabolism'}]
pd.DataFrame(pw_rows).sort_values('n_pathways', ascending=False)
| gene | n_pathways | top_pathway | |
|---|---|---|---|
| 0 | NLRP3 | 6 | Metalloprotease DUBs |
| 1 | SPP1 | 1 | Sphingolipid catabolism |
5. Hypothesis ranking (7 hypotheses)¶
In [6]:
hyp_data = [('Temporal SPP1 Inhibition During Critical Windows', 0.728), ('Temporal NLRP3 Inhibition During SPP1-Driven Microglial', 0.551), ('Astrocytic SPP1 Modulation Through STAT3-Dependent Tran', 0.551), ('Temporal NLRP3 Inhibition via SPP1-Mediated Mitophagy E', 0.496), ('Astrocytic SPP1 Modulation via STAT3-Dependent Transcri', 0.459), ('Mitochondrial Damage-Triggered SPP1 Inflammasome Coupli', 0.453), ('Astrocytic SPP1 Modulation for Neuroinflammatory Resolu', 0.447)]
titles = [h[0] for h in hyp_data][::-1]
scores = [h[1] for h in hyp_data][::-1]
fig, ax = plt.subplots(figsize=(10, max(8, len(titles)*0.4)))
colors = ['#ef5350' if s >= 0.6 else '#ffa726' if s >= 0.5 else '#66bb6a' for s in scores]
ax.barh(range(len(titles)), scores, color=colors)
ax.set_yticks(range(len(titles))); ax.set_yticklabels(titles, fontsize=7)
ax.set_xlabel('Composite Score'); ax.set_title('What molecular mechanisms mediate SPP1-induced microglial phagocytic activation and synaptic targeting?')
ax.grid(axis='x', alpha=0.3)
plt.tight_layout(); plt.show()
In [7]:
labels = ['Temporal SPP1 Inhibition During Critical', 'Temporal NLRP3 Inhibition During SPP1-Dr', 'Astrocytic SPP1 Modulation Through STAT3', 'Temporal NLRP3 Inhibition via SPP1-Media', 'Astrocytic SPP1 Modulation via STAT3-Dep', 'Mitochondrial Damage-Triggered SPP1 Infl', 'Astrocytic SPP1 Modulation for Neuroinfl']
matrix = np.array([[0.75, 0.7, 0.8, 0.85, 0.0, 0.75, 0.7, 0.75, 0.7], [0.0, 0.0, 0.0, 0.85, 0.0, 0.75, 0.7, 0.75, 0.7], [0.0, 0.0, 0.0, 0.85, 0.0, 0.75, 0.7, 0.75, 0.7], [0.5, 0.4, 0.58, 0.8, 0.58, 0.25, 0.64, 0.65, 0.5], [0.5, 0.33, 0.53, 0.8, 0.53, 0.25, 0.64, 0.35, 0.5], [0.5, 0.4, 0.47, 0.8, 0.47, 0.25, 0.64, 0.35, 0.5], [0.5, 0.33, 0.47, 0.8, 0.47, 0.25, 0.64, 0.35, 0.5]])
dims = ['novelty_score', 'feasibility_score', 'impact_score', 'mechanistic_plausibility_score', 'clinical_relevance_score', 'data_availability_score', 'reproducibility_score', 'druggability_score', 'safety_profile_score']
if matrix.size:
fig, ax = plt.subplots(figsize=(10, 5))
im = ax.imshow(matrix, cmap='RdYlGn', aspect='auto', vmin=0, vmax=1)
ax.set_xticks(range(len(dims)))
ax.set_xticklabels([d.replace('_score','').replace('_',' ').title() for d in dims],
rotation=45, ha='right', fontsize=8)
ax.set_yticks(range(len(labels))); ax.set_yticklabels(labels, fontsize=7)
ax.set_title('Score dimensions — hypotheses')
plt.colorbar(im, ax=ax, shrink=0.8)
plt.tight_layout(); plt.show()
else:
print('No score data available')
6. PubMed literature per hypothesis¶
Hypothesis 1: Temporal SPP1 Inhibition During Critical Windows¶
Target genes: SPP1 · Composite score: 0.728
Temporal SPP1 Inhibition During Critical Windows: Mechanistic Framework and Therapeutic Rationale¶
Hypothesis Summary¶
Temporal SPP1 (Secreted Phosphoprotein 1, also known as Osteopontin) neutralization represents a precision-immunology strategy for intercepting neurodegeneration during mechani
In [8]:
lit_data = [{'year': '2024', 'journal': 'Cancer Discov', 'title': 'Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon C', 'pmid': '38552005'}, {'year': '2024', 'journal': 'Bone Res', 'title': 'Osteopontin deficiency promotes cartilaginous endplate degeneration by enhancing', 'pmid': '39242551'}, {'year': '2021', 'journal': 'J Cell Physiol', 'title': 'NLRP3 is involved in long bone edification and the maturation of osteogenic cell', 'pmid': '33319921'}, {'year': '2024', 'journal': 'Clinics (Sao Paulo)', 'title': 'Xuebijing improves inflammation and pyroptosis of acute lung injury by up-regula', 'pmid': '38325020'}, {'year': '2024', 'journal': 'World J Psychiatry', 'title': 'Botulinum toxin type A-targeted SPP1 contributes to neuropathic pain by the acti', 'pmid': '39165552'}]
if lit_data:
df = pd.DataFrame(lit_data)
print(f'{len(lit_data)} PubMed results')
display(df)
else:
print('No PubMed results')
5 PubMed results
| year | journal | title | pmid | |
|---|---|---|---|---|
| 0 | 2024 | Cancer Discov | Spatially Segregated Macrophage Populations Pr... | 38552005 |
| 1 | 2024 | Bone Res | Osteopontin deficiency promotes cartilaginous ... | 39242551 |
| 2 | 2021 | J Cell Physiol | NLRP3 is involved in long bone edification and... | 33319921 |
| 3 | 2024 | Clinics (Sao Paulo) | Xuebijing improves inflammation and pyroptosis... | 38325020 |
| 4 | 2024 | World J Psychiatry | Botulinum toxin type A-targeted SPP1 contribut... | 39165552 |
Hypothesis 2: Temporal NLRP3 Inhibition During SPP1-Driven Microglial Activation Win¶
Target genes: NLRP3 · Composite score: 0.551
This hypothesis proposes that SPP1-mediated microglial activation creates discrete temporal windows during which NLRP3 inflammasome hyperactivation becomes the dominant driver of neurodegeneration. During these critical periods, SPP1 signaling through CD44 and integrin receptors not only recruits mi
In [9]:
lit_data = [{'year': '2024', 'journal': 'Cancer Discov', 'title': 'Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon C', 'pmid': '38552005'}, {'year': '2024', 'journal': 'Bone Res', 'title': 'Osteopontin deficiency promotes cartilaginous endplate degeneration by enhancing', 'pmid': '39242551'}, {'year': '2021', 'journal': 'J Cell Physiol', 'title': 'NLRP3 is involved in long bone edification and the maturation of osteogenic cell', 'pmid': '33319921'}, {'year': '2024', 'journal': 'Clinics (Sao Paulo)', 'title': 'Xuebijing improves inflammation and pyroptosis of acute lung injury by up-regula', 'pmid': '38325020'}, {'year': '2024', 'journal': 'World J Psychiatry', 'title': 'Botulinum toxin type A-targeted SPP1 contributes to neuropathic pain by the acti', 'pmid': '39165552'}]
if lit_data:
df = pd.DataFrame(lit_data)
print(f'{len(lit_data)} PubMed results')
display(df)
else:
print('No PubMed results')
5 PubMed results
| year | journal | title | pmid | |
|---|---|---|---|---|
| 0 | 2024 | Cancer Discov | Spatially Segregated Macrophage Populations Pr... | 38552005 |
| 1 | 2024 | Bone Res | Osteopontin deficiency promotes cartilaginous ... | 39242551 |
| 2 | 2021 | J Cell Physiol | NLRP3 is involved in long bone edification and... | 33319921 |
| 3 | 2024 | Clinics (Sao Paulo) | Xuebijing improves inflammation and pyroptosis... | 38325020 |
| 4 | 2024 | World J Psychiatry | Botulinum toxin type A-targeted SPP1 contribut... | 39165552 |
Hypothesis 3: Astrocytic SPP1 Modulation Through STAT3-Dependent Transcriptional Con¶
Target genes: SPP1 · Composite score: 0.551
Reactive astrocytes, rather than microglia, represent the primary pathogenic source of SPP1 in neuroinflammation through STAT3-dependent transcriptional upregulation. Under neuroinflammatory conditions, astrocytes transition from a homeostatic to reactive state characterized by massive SPP1 overprod
In [10]:
print('No PubMed results for hypothesis h-var-e607efdac0')
No PubMed results for hypothesis h-var-e607efdac0
Hypothesis 4: Temporal NLRP3 Inhibition via SPP1-Mediated Mitophagy Enhancement Duri¶
Target genes: NLRP3 · Composite score: 0.496
This hypothesis proposes that time-restricted enhancement of mitophagy specifically during SPP1-driven microglial activation windows will prevent NLRP3 inflammasome hyperactivation and interrupt the pathological transition from protective to neurotoxic microglial phenotypes. SPP1 upregulation serves
In [11]:
lit_data = [{'year': '2024', 'journal': 'Cancer Discov', 'title': 'Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon C', 'pmid': '38552005'}, {'year': '2024', 'journal': 'Bone Res', 'title': 'Osteopontin deficiency promotes cartilaginous endplate degeneration by enhancing', 'pmid': '39242551'}, {'year': '2021', 'journal': 'J Cell Physiol', 'title': 'NLRP3 is involved in long bone edification and the maturation of osteogenic cell', 'pmid': '33319921'}, {'year': '2024', 'journal': 'Clinics (Sao Paulo)', 'title': 'Xuebijing improves inflammation and pyroptosis of acute lung injury by up-regula', 'pmid': '38325020'}, {'year': '2024', 'journal': 'World J Psychiatry', 'title': 'Botulinum toxin type A-targeted SPP1 contributes to neuropathic pain by the acti', 'pmid': '39165552'}]
if lit_data:
df = pd.DataFrame(lit_data)
print(f'{len(lit_data)} PubMed results')
display(df)
else:
print('No PubMed results')
5 PubMed results
| year | journal | title | pmid | |
|---|---|---|---|---|
| 0 | 2024 | Cancer Discov | Spatially Segregated Macrophage Populations Pr... | 38552005 |
| 1 | 2024 | Bone Res | Osteopontin deficiency promotes cartilaginous ... | 39242551 |
| 2 | 2021 | J Cell Physiol | NLRP3 is involved in long bone edification and... | 33319921 |
| 3 | 2024 | Clinics (Sao Paulo) | Xuebijing improves inflammation and pyroptosis... | 38325020 |
| 4 | 2024 | World J Psychiatry | Botulinum toxin type A-targeted SPP1 contribut... | 39165552 |
Hypothesis 5: Astrocytic SPP1 Modulation via STAT3-Dependent Transcriptional Control¶
Target genes: SPP1 · Composite score: 0.459
Astrocytic SPP1 (Secreted Phosphoprotein 1) expression represents a critical upstream regulator of neuroinflammatory cascades through STAT3-dependent transcriptional mechanisms. Unlike microglial SPP1, which primarily functions in immune recruitment, astrocyte-derived SPP1 acts as a paracrine coordi
In [12]:
lit_data = [{'year': '2024', 'journal': 'Cancer Discov', 'title': 'Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon C', 'pmid': '38552005'}, {'year': '2024', 'journal': 'Bone Res', 'title': 'Osteopontin deficiency promotes cartilaginous endplate degeneration by enhancing', 'pmid': '39242551'}, {'year': '2021', 'journal': 'J Cell Physiol', 'title': 'NLRP3 is involved in long bone edification and the maturation of osteogenic cell', 'pmid': '33319921'}, {'year': '2024', 'journal': 'Clinics (Sao Paulo)', 'title': 'Xuebijing improves inflammation and pyroptosis of acute lung injury by up-regula', 'pmid': '38325020'}, {'year': '2024', 'journal': 'World J Psychiatry', 'title': 'Botulinum toxin type A-targeted SPP1 contributes to neuropathic pain by the acti', 'pmid': '39165552'}]
if lit_data:
df = pd.DataFrame(lit_data)
print(f'{len(lit_data)} PubMed results')
display(df)
else:
print('No PubMed results')
5 PubMed results
| year | journal | title | pmid | |
|---|---|---|---|---|
| 0 | 2024 | Cancer Discov | Spatially Segregated Macrophage Populations Pr... | 38552005 |
| 1 | 2024 | Bone Res | Osteopontin deficiency promotes cartilaginous ... | 39242551 |
| 2 | 2021 | J Cell Physiol | NLRP3 is involved in long bone edification and... | 33319921 |
| 3 | 2024 | Clinics (Sao Paulo) | Xuebijing improves inflammation and pyroptosis... | 38325020 |
| 4 | 2024 | World J Psychiatry | Botulinum toxin type A-targeted SPP1 contribut... | 39165552 |
Hypothesis 6: Mitochondrial Damage-Triggered SPP1 Inflammasome Coupling¶
Target genes: SPP1 · Composite score: 0.453
This hypothesis proposes that mitochondrial dysfunction in microglia creates a pathological coupling between SPP1 secretion and NLRP3 inflammasome activation, establishing a self-perpetuating cycle of neurodegeneration. Specifically, damaged mitochondria release damage-associated molecular patterns
In [13]:
print('No PubMed results for hypothesis h-var-6856106f48')
No PubMed results for hypothesis h-var-6856106f48
Hypothesis 7: Astrocytic SPP1 Modulation for Neuroinflammatory Resolution¶
Target genes: SPP1 · Composite score: 0.447
Astrocytic SPP1 upregulation represents a previously underexplored driver of chronic neuroinflammation that can be therapeutically targeted through astrocyte-specific gene delivery systems. While microglial SPP1 has received extensive attention, emerging evidence indicates that reactive astrocytes b
In [14]:
lit_data = [{'year': '2024', 'journal': 'Cancer Discov', 'title': 'Spatially Segregated Macrophage Populations Predict Distinct Outcomes in Colon C', 'pmid': '38552005'}, {'year': '2024', 'journal': 'Bone Res', 'title': 'Osteopontin deficiency promotes cartilaginous endplate degeneration by enhancing', 'pmid': '39242551'}, {'year': '2021', 'journal': 'J Cell Physiol', 'title': 'NLRP3 is involved in long bone edification and the maturation of osteogenic cell', 'pmid': '33319921'}, {'year': '2024', 'journal': 'Clinics (Sao Paulo)', 'title': 'Xuebijing improves inflammation and pyroptosis of acute lung injury by up-regula', 'pmid': '38325020'}, {'year': '2024', 'journal': 'World J Psychiatry', 'title': 'Botulinum toxin type A-targeted SPP1 contributes to neuropathic pain by the acti', 'pmid': '39165552'}]
if lit_data:
df = pd.DataFrame(lit_data)
print(f'{len(lit_data)} PubMed results')
display(df)
else:
print('No PubMed results')
5 PubMed results
| year | journal | title | pmid | |
|---|---|---|---|---|
| 0 | 2024 | Cancer Discov | Spatially Segregated Macrophage Populations Pr... | 38552005 |
| 1 | 2024 | Bone Res | Osteopontin deficiency promotes cartilaginous ... | 39242551 |
| 2 | 2021 | J Cell Physiol | NLRP3 is involved in long bone edification and... | 33319921 |
| 3 | 2024 | Clinics (Sao Paulo) | Xuebijing improves inflammation and pyroptosis... | 38325020 |
| 4 | 2024 | World J Psychiatry | Botulinum toxin type A-targeted SPP1 contribut... | 39165552 |
7. Knowledge graph edges (3 total)¶
In [15]:
edge_data = [{'source': 'h-655c7f33', 'relation': 'targets', 'target': 'SPP1', 'strength': 0.5}, {'source': 'SPP1', 'relation': 'associated_with', 'target': 'neuroinflammation', 'strength': 0.4}, {'source': 'SPP1', 'relation': 'involved_in', 'target': 'osteopontin___immune_cell_migr', 'strength': 0.4}]
if edge_data:
pd.DataFrame(edge_data).head(25)
else:
print('No KG edge data available')
Caveats¶
This notebook uses real Forge tool calls from live APIs:
- Enrichment is against curated gene-set libraries (Enrichr)
- STRING/Reactome/HPA/MyGene reflect curated knowledge
- PubMed literature is search-relevance ranked, not systematic review