PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia
Open accessPublished version of a preprint
Abstract
, the underlying disease mechanisms remain largely unclear. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Here, using our approach for identifying functional GWAS risk variants showing allele-specific open chromatin, we systematically identified putative causal LOAD-risk variants in human induced pluripotent stem (iPS)-cell-derived neurons, astrocytes and microglia, and linked a PICALM LOAD-risk allele to a microglial-specific role of PICALM in lipid droplet (LD) accumulation. Allele-specific open-chromatin mapping revealed functional risk variants for 26 LOAD-risk loci, mostly specific to microglia. At the microglial-specific PICALM locus, the LOAD-risk allele of the single-nucleotide polymorphism rs10792832 reduced transcription factor (PU.1) binding and PICALM expression, impairing the uptake of amyloid beta (Aβ) and myelin debris. Notably, microglia carrying the PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation. Genetic and pharmacological perturbations of microglia further established a causal link between reduced PICALM expression, LD accumulation and phagocytosis deficits. Our work elucidates the selective LOAD vulnerability in microglia at the PICALM locus through detrimental LD accumulation, providing a neurobiological basis that can be exploited for developing clinical interventions.
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TL;DR
Using allele-specific open chromatin mapping in human iPS-cell-derived brain cell types, this study identifies functional late-onset Alzheimer's disease (LOAD) risk variants for 26 loci, mostly microglia-specific, and links the PICALM risk allele of rs10792832 to reduced PU.1 binding, reduced PICALM expression, lipid droplet accumulation and impaired phagocytosis in microglia.
Key findings
- ASoC mapping identified functional LOAD-risk variants for 26 loci, with 20 loci (38 ASoC/LOAD-risk SNPs) accounted for by iMGs; iMG open-chromatin regions were strongly enriched for LOAD heritability (enrichment fold = 13.6, P = 2.1 × 10⁻¹⁵) and iMG ASoC SNPs showed the strongest LOAD GWAS enrichment (35-fold, P = 1.04 × 10⁻³³).
- The LOAD-risk allele G of rs10792832 disrupted a PU.1 binding motif, retaining about 40% of allele A's PU.1 binding, and reduced PICALM expression by about 50% in iMGs (but not iAst cells); lower PICALM expression was associated with the risk allele G in AD patients (P = 0.004).
- Risk-allele iMGs showed 40–50% decreased Aβ–pHrodo phagocytosis and ~50% reduced myelin phagocytosis in PICALM-KO C20 cells; PICALM-CRISPRa rescued the phagocytic deficit.
- Risk-allele iMGs showed a twofold to sevenfold increase in lipid droplets, a ~twofold increase in total triacylglycerols (32 of 55 altered lipid species were TGs, 5.6-fold enrichment, P < 2.6 × 10⁻¹⁶), >2-fold increase in ROS, threefold more peroxidated lipids, and 2.7–4.2-fold more lysosomes (4.3–5.7-fold for lysosome–LD colocalization).
Methods
- ATAC–seq and allele-specific open chromatin (ASoC) mapping in human iPS-cell-derived microglia (iMG, n = 38), astrocytes (iAst, n = 18), and glutamatergic, GABAergic and dopaminergic neurons (62 iPS cell lines total), integrated with hMG caQTL/eQTL, ABC enhancer–promoter linkage and LOAD GWAS data.
- CRISPR–Cas9 editing of rs10792832 (G/G→A/A) in two non-AD donor iPS lines (CD04, CD09), plus CRISPRa (PICALM overexpression), CRISPRoff (knockdown) and PICALM knockout in the C20 hMG line; assays included ChIP for PU.1, RNA-seq, lipidomics (LC–MS/MS), phagocytosis (Aβ- and myelin-pHrodo), LD/ROS/lysosome staining and flow cytometry.
- Statistical analysis used linear mixed models, one-way ANOVA with Dunnett's or Tukey's correction, two-sided binomial tests for ASoC, and Benjamini–Hochberg FDR correction.
Limitations
- The authors acknowledge a lack of strong correlation between the magnitude of PICALM alteration and its functional effects in CRISPR-engineered iMGs, possibly due to differentiation variability and nonlinear gene–phenotype relationships; they cannot formally exclude a long-range cis-effect of the risk variant on genes other than PICALM.
- The authors note PICALM expression in AD patients may be influenced by cell type, MG state and disease stage, and that effects seen in iMGs may also occur in other myeloid cells/macrophages, warranting further investigation.
- The authors note that although impaired phagocytosis implies a neuroprotective role in clearing Aβ or damaged myelin, MG phagocytosis in vivo may also be detrimental through excessive synaptic pruning.
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Claims the paper makes
64 of 77 cited sources checked · 31 supported · 0 flagged · accuracy not yet measured
- Study design and conductown data§ Mapping functional LOAD-risk variants
The iMG and iAst cells were epigenetically similar to hMGs and other reported iMGs and Ast cells.
“Our iMG and iAst cells were epigenetically similar to hMGs6 and other reported iMGs22 and Ast (hAst)6 cells (Extended Data Fig. 1i).”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [6] Kosoy, R. et al. Genetics of the human microglia regulome refines Alzheimer’s disease risk loci. Nat. Genet. 54, 1145–1154 (2022). source
The Results section, “Chromatin accessibility and gene expression in microglia” (page unavailable), confirms that this paper generated chromatin-accessibility data from primary human microglia, supporting its use as an hMG comparator. The cited paper does not establish that the citing authors’ iMG or iAst cells were epigenetically similar to those cells, and our copy does not identify an hAst epigenetic dataset from this paper. The comparison with other reported iMGs is attached to citation 22, not this source. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [22] Novikova, G. et al. Integration of Alzheimer’s disease genetics and myeloid genomics identifies disease risk regulatory elements and genes. Nat. Commun. 12, 1610 (2021). source
- Findingown data§ 100 bp
Lower PICALM expression was found in disease-associated MGs (DAMs) and LD-accumulating MGs (LDAMs) versus homeostatic MGs (P = 0.016).
“Moreover, by recapitulating snRNA-seq analysis of AD brain MG states19, we found lower PICALM expression in disease-associated MGs (DAMs) and LD-accumulating MGs (LDAMs) (versus homeostatic MGs) (P = 0.016) (Extended Data Fig. 4c).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
- Premisecitation§ 0 2 4 6
ATP6AP2 encodes a protein essential for lysosomal degradative functions.
“ATP6AP2, one of the most downregulated genes in risk-allele iMGs (Fig. 4b and Supplementary Table 13), encodes a protein that is essential for lysosomal degradative functions; Atp6ap2-mutant mice show increased triglycerides and LD in fat body cells48.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [48] Hirose, T. et al. ATP6AP2 variant impairs CNS development and neuronal survival to cause fulminant neurodegeneration. J. Clin. Invest. 129, 2145–2162 (2019). source
- Findingown data§ 0 2 4 6
Three known LD suppressor genes (SLC33A1, MCOLN1 and GRN) all exhibit reduced expression in LOAD-risk-allele iMGs.
“Notably, three known LD suppressor genes (SLC33A1, MCOLN1 and GRN)10 all exhibited reduced expression in LOAD-risk-allele iMGs (Fig. 5d), two of which are related to lysosomal function: MCOLN1 is a ROS sensor in lysosomes regulating autophagy49, and GRN encodes the lysosomal protein progranulin related to neurodegenerative diseases50.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
In Results (CRISPR-Cas9 screen; page unavailable), the source identifies SLC33A1 and GRN as negative regulators of lipid-droplet formation: disrupting either increased lipid droplets in BV2 cells. The cited paper does not identify MCOLN1 as a lipid-droplet suppressor, so it supports only two of the three genes named. The reduced expression in LOAD-risk-allele iMGs is attributed to the citing paper’s Fig. 5d, not to this source. (LLM, conf=0.86)
Experimental — accuracy not yet measured
- Findingown data§ 0 2 4 6
Blocking LD formation with TrC influences ROS levels in iMGs.
“As seen in mouse microglia10, we further confirmed that LD accumulation influences ROS levels in iMGs by using TrC to block LD formation (Extended Data Fig. 7f–i).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
- Findingown data§ 0 2 4 6
TrC treatment of LOAD-risk-allele iMGs shifts the proportions of cells with varying BODIPY/pHrodo combinations to resemble non-risk iMGs.
“Like in mouse microglia10, there was an inverse relationship between BODIPY+ and Aβ–pHrodo+ signals in iMGs, and TrC treatment of the LOAD-risk-allele iMGs shifted the proportions of cells with varying BODIPY/pHrodo combinations to resemble non-risk iMGs (Extended Data Fig. 12d).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
- Interpretationown data§ 0 2 4 6
The results align with previously reported TG increases in LDAMs and APOE4-associated LDs.
“Our results align with previously reported TG increases in LDAMs10 and APOE4-associated LDs19, further supporting our observed PICALM-risk-allele-associated LD accumulation in iMGs.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
The Results section, “Microglia accumulate lipid droplets in the aging brain” (page unavailable), reports more lipid droplets in aged microglia, while the Discussion, “LDAM in neurodegeneration” (page unavailable), says triacylglycerides (TG) are a major component of LDAM lipid droplets. Our copy does not directly report a TG increase in LDAMs relative to other microglia. The APOE4-associated finding has a separate citation in the citing sentence and is not attributed to this source. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 45 90 135 180
Treating iMGs with triacsin C effectively decreased BODIPY-labelled LDs.
“Treating iMGs with triacsin C (TrC), an inhibitor of long-chain acyl-CoA synthetase that reduces LD formation10,18,19,39,40, effectively decreased BODIPY-labelled LDs (Extended Data Fig. 7e–i).”
Quote in the paperSubstantial claim3 of 5 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
- cites [18] Victor, M. B. et al. Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity. Cell Stem Cell 29, 1197–1212 (2022). source
- cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
- cites [39] Namatame, I., Tomoda, H., Arai, H., Inoue, K. & Omura, S. Complete inhibition of mouse macrophage-derived foam cell formation by triacsin C. J. Biochem. 125, 319–327 (1999). source
- cites [40] Khatchadourian, A., Bourque, S. D., Richard, V. R., Titorenko, V. I. & Maysinger, D. Dynamics and regulation of lipid droplet formation in lipopolysaccharide (LPS)-stimulated microglia. Biochim. Biophys. Acta 1821, 607–617 (2012). source
- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Premisecitation§ 0 2 4 6
Atp6ap2-mutant mice show increased triglycerides and LD in fat body cells.
“Atp6ap2-mutant mice show increased triglycerides and LD in fat body cells48.”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [48] Hirose, T. et al. ATP6AP2 variant impairs CNS development and neuronal survival to cause fulminant neurodegeneration. J. Clin. Invest. 129, 2145–2162 (2019). source
The Results (pp. 5–7) describe Atp6ap2-mutant mice with enlarged lysosomes and accumulated autophagy-related structures in cortical and hippocampal cells. Searches for triglycerides, lipid droplets, and fat body cells found no passage addressing the claimed increases. (LLM, conf=0.75)
Experimental — accuracy not yet measured
- Interpretationown data§ Discussion
De novo cholesterol and fatty acid synthesis in LOAD-risk-allele iMGs may contribute to LD accumulation.
“The de novo cholesterol and fatty acid synthesis in LOAD-risk-allele iMGs may contribute to LD accumulation: genes in the cholesterol-biosynthesis pathway, including TFs (such as SREBP) that regulate lipids synthesis35, were all upregulated (Fig. 4b and Supplementary Fig. 8).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [35] Rong, S. et al. Expression of SREBP-1c requires SREBP-2-mediated generation of a sterol ligand for LXR in livers of mice. eLife https://doi.org/10.7554/eLife.25015 (2017). source
- Interpretationcitation§ Discussion
Our findings with PICALM further strengthen the notion of a causal role of LDs in mediating LOAD genetic risk factors.
“Nonetheless, given that the APOE4 allele was recently found to induce LD accumulation in MGs and impair neuronal function18,19, our findings with PICALM further strengthen the notion of a causal role of LDs in mediating LOAD genetic risk factors, providing potential mechanistic targets for AD treatments.”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [18] Victor, M. B. et al. Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity. Cell Stem Cell 29, 1197–1212 (2022). source
- cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
- Findingown data§ Discussion
Genes in the cholesterol-biosynthesis pathway, including TFs such as SREBP that regulate lipid synthesis, are all upregulated in LOAD-risk-allele iMGs.
“The de novo cholesterol and fatty acid synthesis in LOAD-risk-allele iMGs may contribute to LD accumulation: genes in the cholesterol-biosynthesis pathway, including TFs (such as SREBP) that regulate lipids synthesis35, were all upregulated (Fig. 4b and Supplementary Fig. 8).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [35] Rong, S. et al. Expression of SREBP-1c requires SREBP-2-mediated generation of a sterol ligand for LXR in livers of mice. eLife https://doi.org/10.7554/eLife.25015 (2017). source
- Study design and conductcitation§ Discussion
There is a lack of strong correlation between the magnitude of PICALM alteration and its functional effects in CRISPR-engineered iMGs.
“We acknowledge a lack of strong correlation between the magnitude of PICALM alteration and its functional effects in CRISPR-engineered iMGs, probably due to technical variations in iMG differentiation and/or the nonlinear relationship between gene expression and cellular phenotypes due to epistasis and systems buffering54,55.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [54] Green, R. M. et al. Developmental nonlinearity drives phenotypic robustness. Nat. Commun. 8, 1970 (2017). source
The Introduction describes nonlinear relationships in which variation in gene expression can be buffered before it affects phenotype, supporting the proposed explanation in general. But the paper studies Fgf8 and craniofacial morphology, not PICALM in CRISPR-engineered iMGs; its Discussion also describes developmental nonlinearity as a cause, rather than a consequence, of epistasis. The iMG correlation is the citing authors’ own observation, not a finding attributed to this source. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [55] Lotfollahi, M. et al. Predicting cellular responses to complex perturbations in high-throughput screens. Mol. Syst. Biol. 19, e11517 (2023). source
The Results section on combinatorial genetic perturbations discusses epistatic interactions, but not PICALM, CRISPR-engineered iMGs, or a correlation between alteration magnitude and functional effects. Searches for PICALM, iMGs, and gene-expression–phenotype correlation found no passage addressing the specific observation attributed to this paper. (LLM, conf=0.76)
Experimental — accuracy not yet measured
- Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM expression is lower in DAM and LDAM microglial cell clusters than in other microglial states.
“Note lower PICALM expression in DAM and LDAM cell clusters.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
The ‘Lipid-associated ACSL1+ microglia in AD’ section distinguishes DAM and LDAM clusters, but does not report PICALM expression in either cluster. A search of our copy for ‘PICALM’ found no passage establishing the claimed comparison; page numbers were not available. (LLM, conf=0.73)
Experimental — accuracy not yet measured
- Findingown data§ 1 2 3 4 5 6 7
PICALM-CRISPRa fully rescued the Aβ-pHrodo phagocytic deficit of risk-allele iMGs.
“PICALM-CRISPRa fully rescued the Aβ–pHrodo phagocytic deficit of risk-allele iMGs (Fig. 3a and Extended Data Fig. 5a).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 100 bp
PICALM expression was confirmed in IBA1+ MGs in the post-mortem human brain.
“We first confirmed PICALM expression in IBA1+ MGs in the post-mortem human brain (Extended Data Fig. 4a).”
Quote in the paperSubstantial claim - Findingown data§ 1 2 3 4 5 6 7
PICALM-CRISPRoff reduced iMG capacity for phagocytosis of myelin-pHrodo and Aβ-pHrodo compared with non-risk-allele iMGs.
“We found that PICALM-CRISPRoff reduced iMG capacity for phagocytosis of myelin-pHrodo and Aβ–pHrodo compared with the non-risk-allele iMGs (Extended Data Fig. 5h–l).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 100 bp
The LOAD-risk allele of rs10792832 reduces PU.1 binding at the SNP site.
“We found that the risk allele G decreased PU.1 binding at the SNP site (Extended Data Fig. 3i).”
- Also stated in: § 100 bp · plain
“the risk allele G retained about 40% of the PU.1-binding ability of allele A.”
Quote in the paperSubstantial claim - Also stated in: § 100 bp · plain
- Findingown data§ 100 bp
iMGs from a second clone of each iPS cell line also exhibited a similar allelic difference in phagocytic activity.
“iMGs from a second clone of each iPS cell line also exhibited similar allelic difference in phagocytic activity (Extended Data Fig. 5b,c).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ Abstract
Microglia carrying the PICALM risk allele show transcriptional enrichment of pathways for cholesterol synthesis and LD formation.
“microglia carrying the PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation.”
Quote in the paperSubstantial claim - Findingown data§ Mapping functional LOAD-risk variants
The authors identified between 202,019 and 267,119 open-chromatin regions (OCRs) for each cell type.
“We identified between 202,019 and 267,119 open-chromatin regions (OCRs) for each cell type.”
Quote in the paperNot a substantial claim - Findingown data§ 100 bp
13 ASoC/LOAD-risk SNPs of 9 risk loci could be assigned to a target gene.
“We found that 13 ASoC/LOAD-risk SNPs of 9 risk loci could be assigned to a target gene (Extended Data Fig. 2l)”
Quote in the paperSubstantial claim - Findingown data§ 100 bp
There was no difference in brain microglial PICALM protein levels between patients with AD and controls in a small ROSMAP cohort.
“Although we did not find a difference in brain microglial PICALM protein levels between patients with AD and controls in a small ROSMAP cohort (Extended Data Fig. 4d–g and Supplementary Table 11)”
Quote in the paperSubstantial claim - Findingown data§ Introduction
Using the ASoC approach, the authors systematically identified functional LOAD-risk variants in human iPS-cell-derived microglia, astrocytes and neurons.
“Here, using the ASoC approach, we systematically identified functional LOAD-risk variants in human iPS-cell-derived MGs (iMGs), astrocytes (iAst) and neurons.”
- Also stated in: § Abstract · hedged
“we systematically identified putative causal LOAD-risk variants in human induced pluripotent stem (iPS)-cell-derived neurons, astrocytes and microglia”
Quote in the paperSubstantial claim - Also stated in: § Abstract · hedged
- Findingown data§ Mapping functional LOAD-risk variants
ASoC SNPs in iMGs were near genes involved in immune activation and phagocytosis.
“As expected, ASoC SNPs in iMGs were near genes involved in immune activation and phagocytosis (Supplementary Fig. 3d,e).”
Quote in the paperNot a substantial claim - Findingown data§ Mapping functional LOAD-risk variants
iMG ASoC SNPs were highly enriched for hMG chromatin accessibility QTLs (caQTL) and eQTLs.
“iMG ASoC SNPs were highly enriched for hMG chromatin accessibility QTLs (caQTL) and eQTLs (Supplementary Tables 2 and 8 and Supplementary Fig. 3f–h)”
Quote in the paperSubstantial claim - Findingown data§ 100 bp
At the mRNA level, patients with AD showed a reduction in PICALM in the grey matter.
“At the mRNA level, patients with AD showed a reduction in PICALM in the grey matter (Extended Data Fig. 4b and Supplementary Table 11).”
Quote in the paperSubstantial claim - Findingown data§ Abstract
Allele-specific open-chromatin mapping revealed functional risk variants for 26 LOAD-risk loci, mostly specific to microglia.
“Allele-specific open-chromatin mapping revealed functional risk variants for 26 LOAD-risk loci, mostly specific to microglia.”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
The ratio of peroxidated to non-peroxidated lipids in risk-allele iMGs is higher than in non-risk iMGs.
“The ratio of peroxidated to non-peroxidated lipids in risk-allele iMGs was also higher than in non-risk iMGs (Extended Data Fig. 11e).”
Quote in the paperSubstantial claim - Findingown data§ 1 2 3 4 5 6 7
Differential expression analysis identified 257 upregulated and 244 downregulated genes (FDR < 0.05) in LOAD-risk-allele iMGs.
“We identified 257 upregulated and 244 downregulated genes (false-discovery rate (FDR) < 0.05) in the LOAD-risk-allele iMGs (Fig. 4b and Supplementary Table 13).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
ATP6AP2 is one of the most downregulated genes in risk-allele iMGs.
“Notably, ATP6AP2, one of the most downregulated genes in risk-allele iMGs (Fig. 4b and Supplementary Table 13), encodes a protein that is essential for lysosomal degradative functions; Atp6ap2-mutant mice show increased triglycerides and LD in fat body cells48.”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
Risk-allele iMGs have a 2.7-4.2-fold increase of lysosomes.
“We found that risk-allele iMGs had a 2.7–4.2-fold increase of lysosomes, and an even larger increase (4.3 to 5.7-fold) of lysosomes that colocalized with LDs (LysoTracker+BODIPY+) (Fig. 5f,g).”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
Only 2.4-3.2% of iMGs were BODIPY+Aβ-pHrodo+ across all conditions.
“We observed that only 2.4–3.2% of iMGs were BODIPY+Aβ–pHrodo+ across all conditions and an increase in BODIPY+ cells in risk-allele iMGs was proportionally accompanied by a decrease in BODIPY−Aβ–pHrodo+ iMGs (Extended Data Fig. 8c).”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
LOAD-risk-allele iMGs exhibit threefold more peroxidated lipids compared with non-risk iMGs.
“The LOAD-risk-allele iMGs exhibited threefold more peroxidated lipids compared with non-risk iMGs (Extended Data Fig. 11b–d).”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
Downregulated lysosomal genes in LOAD-risk-allele iMGs share VAMP1, CD74, TCRIG1 with mouse LDAMs.
“which shared some downregulated lysosomal genes (VAMP1, CD74, TCRIG1) with mouse LDAMs (Figs. 4d and 5d and Supplementary Fig. 7c).”
Quote in the paperSubstantial claim - Findingown data§ 1 2 3 4 5 6 7
More than half of the top 20 differentially expressed genes (DEGs) were related to lipid metabolism.
“Notably, more than half of the top 20 differentially expressed genes (DEGs) were related to lipid metabolism (for example, DHCR7, HPGD, FDFT1, HMGCR, PLBD1, IMPA2, MTMR1, RETN, ATP6AP2, LRP5 and CRABP2) (Fig. 4b, Extended Data Fig. 6a–d, Supplementary Fig. 7b and Supplementary Table 13).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
An increase in BODIPY+ cells in risk-allele iMGs is proportionally accompanied by a decrease in BODIPY−Aβ-pHrodo+ iMGs.
“an increase in BODIPY+ cells in risk-allele iMGs was proportionally accompanied by a decrease in BODIPY−Aβ–pHrodo+ iMGs (Extended Data Fig. 8c).”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
LOAD-risk-allele iMGs have a greater than twofold increase in CellROX staining compared with non-risk iMGs.
“We observed that LOAD-risk-allele iMGs had a greater than twofold increase in CellROX staining (Extended Data Fig. 7f–i), with largely colocalized CellROX and LD staining (Extended Data Fig. 7e).”
Quote in the paperSubstantial claim - Findingown data§ Discussion
Integrative analyses of chromatin accessibility in iPS-cell-derived major brain cell types, brain QTLs, chromatin interactions (ABC) and LOAD GWAS data identified functional LOAD-risk variants that account for about one-third of the known LOAD GWAS risk loci.
“Our integrative analyses of chromatin accessibility in iPS-cell-derived major brain cell types, brain QTLs, chromatin interactions (ABC) and LOAD GWAS data identified functional LOAD-risk variants that account for about one-third of the known LOAD GWAS risk loci, providing a rich resource for prioritizing functional LOAD-risk variants/genes for biological follow-up.”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
CellROX and LD staining are largely colocalized in LOAD-risk-allele iMGs.
“with largely colocalized CellROX and LD staining (Extended Data Fig. 7e).”
Quote in the paperSubstantial claim - Findingown data§ 0 45 90 135 180
PICALM-CRISPRa iMGs fully restored LD levels to the levels of non-risk iMGs.
“PICALM-CRISPRa iMGs fully restored LD levels to the levels of those of non-risk iMGs (Extended Data Fig. 8b).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 1 2 3 4 5 6 7
All genes in the activated cholesterol-biosynthesis pathway were upregulated in LOAD-risk-allele iMGs.
“All genes in the activated cholesterol-biosynthesis pathway were upregulated (Supplementary Figs. 7b and 8) in LOAD-risk-allele iMGs.”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
iAst cells with PICALM-CRISPRoff exhibited around a 50% reduction in BODIPY-labelled LD and Red-C12-labelled lipids.
“iAst cells with PICALM-CRISPRoff exhibited around a 50% reduction in BODIPY-labelled LD and Red-C12-labelled lipids (Extended Data Fig. 10h–l).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
LOAD-risk-allele iMGs show reduced phagocytosis of Aβ and myelin.
“LOAD-risk-allele iMGs showed reduced phagocytosis of Aβ and myelin (Extended Data Fig. 12).”
Quote in the paperSubstantial claim - Findingown data§ 1 2 3 4 5 6 7
PICALM-KO cells exhibited reduced (about 50%) phagocytosis of myelin-pHrodo compared with WT cells.
“However, PICALM-KO cells exhibited reduced (about 50%) phagocytosis of myelin-pHrodo compared with the wild-type (WT) cells (Fig. 3f,g)”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 45 90 135 180
iMGs carrying the LOAD-risk allele showed stronger filipin fluorescence than non-risk-allele iMGs.
“We found stronger filipin fluorescence in iMGs carrying the LOAD-risk (versus non-risk) allele.”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
Reduced expression of ATP6AP2, VAMP1 and CD74 in LOAD-risk-allele iMGs was confirmed independently by immunofluorescence staining.
“The reduced expression of ATP6AP2, VAMP1 and CD74 in LOAD-risk-allele iMGs was further confirmed independently by immunofluorescence staining (Extended Data Fig. 6c,d).”
Quote in the paperNot a substantial claim - Findingown data§ 0 45 90 135 180
The authors observed a twofold to sevenfold increase in LDs in iMGs carrying the PICALM risk allele.
“We observed a twofold to sevenfold increase in LDs in iMGs carrying the PICALM risk allele (Fig. 5a,b and Extended Data Fig. 7c,d).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
In a lipid-transfer assay, similar levels of Red-C12 staining were observed between iMGs with the LOAD-risk and non-risk alleles.
“We observed similar levels of Red-C12 staining between iMGs with the LOAD-risk and non-risk alleles (Extended Data Fig. 10e–g).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
Independent LD staining using LipidTOX produced similar results.
“Independent LD staining using LipidTOX produced similar results (Extended Data Fig. 9f–j).”
Quote in the paperNot a substantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 45 90 135 180
The LD accumulation in PICALM risk-allele iMGs was independently confirmed by flow cytometry analysis of BODIPY+ iMGs and by staining for the LD-associated protein PLIN2.
“The LD accumulation in PICALM risk-allele iMGs was independently confirmed by flow cytometry analysis of BODIPY+ iMGs (Extended Data Fig. 7j,k) and by staining for the LD-associated protein PLIN2 (Extended Data Fig. 7l–n).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Findingown data§ 0 2 4 6
Colocalization analysis of LD and phagocytosed myelin in iMGs yielded similar results.
“Colocalization analysis of LD and phagocytosed myelin in iMGs yielded similar results (Extended Data Fig. 12h).”
Quote in the paperNot a substantial claim - Findingown data§ 0 2 4 6
Risk-allele iMGs have a 4.3 to 5.7-fold increase of lysosomes that colocalized with LDs (LysoTracker+BODIPY+).
“an even larger increase (4.3 to 5.7-fold) of lysosomes that colocalized with LDs (LysoTracker+BODIPY+) (Fig. 5f,g).”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
Downregulated genes in LOAD-risk-allele iMGs are enriched for lysosomal GO terms.
“Moreover, the downregulated genes in LOAD-risk-allele iMGs were enriched for the lysosomal GO terms (Supplementary Fig. 7a), which shared some downregulated lysosomal genes (VAMP1, CD74, TCRIG1) with mouse LDAMs (Figs. 4d and 5d and Supplementary Fig. 7c).”
Quote in the paperSubstantial claim - Findingown data§ 0 2 4 6
TrC treatment itself does not significantly increase phagocytosis of non-risk iMGs.
“note that TrC treatment itself did not significantly increase phagocytosis of non-risk iMGs; Supplementary Fig. 9”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
19 LOAD risk loci with 38 GWAS risk SNPs are also ASoC SNPs in iMG.
“(l) Circos plot depicting 19 LOAD risk loci with 38 GWAS risk SNPs also ASoC SNPs in iMG.”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The rs10792832-flanking OCR peak identified in iMG is present in brain microglia but not in other brain cell types.
“Note the rs10792832-flanking peak (highlighted in the vertical yellow box) identified in our iMG is only present in brain microglia but not in other cell types.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [24] Xiong, X. et al. Epigenomic dissection of Alzheimer’s disease pinpoints causal variants and reveals epigenome erosion. Cell 186, 4422–4437 (2023). source
- Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
LOAD GWAS risk loci with functional LOAD risk SNPs showing ASoCs are predominantly in iMG (19 of 26 loci).
“Note the LOAD GWAS risk loci with functional LOAD risk SNPs showing ASoCs are predominantly in iMG (19/26 loci).”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
Aβ-pHrodo+/BODIPY+ iMG are rare.
“Note the Aβ-pHrodo+/BODIPY+ iMG are rare”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
CRISPRoff-induced reduction of PICALM in iMG occurs for both CD04 and CD09 lines.
“qPCR results show CRISPRoff-induced reduction of PICALM in iMG for both lines.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
Peroxidized LD density and area are increased in iMG carrying the LOAD risk-allele vs non-risk.
“(c) and (d) Increased LD (C11-BODIPY green fluorescence) density and area in iMG carrying the LOAD risk-allele (vs. non-risk).”
Quote in the paperSubstantial claim- Rests on an assumption: C11-BODIPY fluorescence shift from red to green indicates lipid peroxidation/ROS.
- Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
Lysosomal abnormality is associated with LD increase.
“Lysosomal abnormality ties to LD increase”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
iMG carrying the LOAD risk-allele of rs10792832 show increased lipid peroxidation.
“Extended Data Fig. 11 | iMG carrying the LOAD risk-allele of rs10792832 show increased lipid peroxidation.”
Quote in the paperSubstantial claim- Rests on an assumption: C11-BODIPY fluorescence shift from red to green indicates lipid peroxidation/ROS.
- Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
LOAD risk-allele iMG show increased lipid droplet (BODIPY+) size and fluorescence intensity compared to non-risk iMG.
“Quantification of LD staining shows increased LD (BODIPY+) size and fluorescence intensity in LOAD risk-allele iMG (vs. non-risk), respectively.”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
Among the top 20 increased lipid species in risk iMG vs non-risk iMG, most are triglycerides.
“The top 20 increased lipid species are highlighted, most of which are TG.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
TrC treatment rescues the LD in iMG carrying the LOAD risk-allele to a level similar to that in iMG with the non-risk allele.
“(c) TrC treatment rescues the LD in iMG carrying the LOAD risk-allele to a level similar to that in MG with the non-risk allele.”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
Peroxidized LD density and area are reduced in iMG treated with TrC.
“Note the peroxidized LD density and area are reduced in iMG treated with TrC.”
Quote in the paperSubstantial claim- Rests on an assumption: C11-BODIPY fluorescence shift from red to green indicates lipid peroxidation/ROS.
- Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM expression in microglia of AD and non-AD controls does not differ significantly when stratified by Braak stage or CERAD score.
“Quantification of PICALM expression in MG of AD and non-AD controls stratified by Braak Stage (0-5) (left) and by CERAD score (0 = control; 1-2, probable or possible AD; and 3, definitely AD) (right). Not significant in one-way ANOVA.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The PICALM risk allele increases ROS in iMGs.
“PICALM risk allele increases ROS in iMGs”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
In brain microglia, the rs10792832 locus shows significantly more ATAC-seq reads for allele A than for allele G (allele-specific chromatin accessibility).
“The adjacent ATAC-seq read pileup plot (right) for rs10792832 shows significantly more ATAC-reads of allele A than allele G (i.e., ASoC) in brain microglia.”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
In risk-allele iMG, lipid species are increased vs non-risk iMG at FDR < 0.05.
“for the lipid species increased in risk-allele iMG (vs. non-risk iMG) at FDR < 0.05.”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM expression in microglia of AD and non-AD controls is not significantly different.
“Quantification of PICALM expression in MG of AD and non-AD controls. AD, n = 15 with the diagnosis of “definitely AD” with a CERAD score of 3; the rest include control (n = 16), probable AD and possible AD (n = 9) (Supplementary Table 11). The grey background dots represent individual MG. ns, not significant in the two-sided unpaired Student's t-test.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The allele A of rs10792832 exhibits higher Sanger sequencing peaks for PU.1 ChIP-seq PCR products of iMG from two iPSC lines heterozygous for rs10792832.
“The allele A of rs10792832 exhibits higher Sanger sequencing peaks for PU.1 ChIP-seq PCR products of iMG from two iPSC lines heterozygous for rs10792832.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM expression is reduced in the grey matter of AD patients' postmortem brains (n=20) compared to controls (n=19).
“Reduced PICALM expression in the grey matter of AD patients' postmortem brains (n = 20) compared to controls (n = 19).”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM-deficit iMGs accumulate lipid droplets.
“LD accumulation in PICALM-deficit iMGs”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The LOAD risk-allele G of rs10792832 shows reduced PU.1 binding in qPCR of ChIP products.
“The LOAD risk-allele G of rs10792832 shows reduced PU.1 binding in qPCR of ChIP products.”
Quote in the paperSubstantial claim- Rests on an assumption: rs10792832 allele G is a LOAD risk allele for Alzheimer's disease.
- Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM-CRISPRa rescues the LD accumulation in iMG carrying the LOAD risk-allele to a level similar to that in iMG carrying the non-risk allele for both CD04 and CD09.
“(b) PICALM-CRISPRa rescues the LD accumulation in iMG carrying the LOAD risk-allele to a level similar to that in MG carrying the non-risk allele for both CD04 and CD09.”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The LOAD-risk allele of PICALM reduces PICALM expression.
“LOAD-risk allele reduces PICALM expression”
Quote in the paperSubstantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The risk allele of rs10792832 does not affect PICALM expression in iAst.
“qPCR result showing that the risk allele of rs10792832 does not affect PICALM expression in iAst.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM expression is reduced in risk-allele iMG compared with non-risk iMG by qPCR.
“qPCR shows reduced PICALM expression in risk-allele iMG.”
Quote in the paperNot a substantial claim - Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM-deficit iMGs have dysregulated lipid genes.
“Dysregulated lipid genes in PICALM-deficit iMGs”
Quote in the paperSubstantial claim - Interpretationcitation§ 100 bp
The LOAD-risk allele may have context-dependent effects (MG state, cell type and AD stage) on PICALM expression.
“suggesting possible context-dependent effects (MG state, cell type and AD stage) of the LOAD-risk allele on PICALM expression.”
Quote in the paperSubstantial claim - Interpretationown data§ Abstract
Genetic and pharmacological perturbations of microglia established a causal link between reduced PICALM expression, LD accumulation and phagocytosis deficits.
“Genetic and pharmacological perturbations of microglia further established a causal link between reduced PICALM expression, LD accumulation and phagocytosis deficits.”
Quote in the paperSubstantial claim- Rests on an assumption: The role of PICALM in LD formation in microglia and its link to the LOAD-risk allele was not demonstrated before this study.
- Interpretationown data§ 100 bp
Together, these data provide compelling evidence that the LOAD-risk allele of rs10792832 reduces PICALM expression specifically in MGs by disrupting PU.1 binding.
“Together, these data provide compelling evidence that the LOAD-risk allele of rs10792832 reduces PICALM expression specifically in MGs by disrupting PU.1 binding.”
Quote in the paperSubstantial claim - Interpretationown data§ 0 2 4 6
There is a potential link between altered lysosomal dynamics and LD accumulation in iMGs carrying the LOAD-risk allele of PICALM.
“Together, these data suggest a potential link between altered lysosomal dynamics and LD accumulation in iMGs carrying the LOAD-risk allele of PICALM (Extended Data Fig. 11f).”
Quote in the paperSubstantial claim - Interpretationown data§ 0 2 4 6
iMGs carrying the LOAD-risk allele of PICALM are in a stress state.
“These results indicate a stress state in iMGs carrying the LOAD-risk allele of PICALM.”
Quote in the paperSubstantial claim - Interpretationown data§ 1 2 3 4 5 6 7
These results suggest that impaired MG phagocytosis of fragmented myelin and Aβ aggregates could be a causal mechanism for the LOAD-risk allele at the PICALM locus.
“These results suggest that impaired MG phagocytosis of fragmented myelin and Aβ aggregates could be a causal mechanism for the LOAD-risk allele at the PICALM locus.”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Interpretationown data§ 0 2 4 6
These findings also support that reduced PICALM expression by the LOAD-risk-allele leads to MG-specific LD accumulation.
“These findings also support that reduced PICALM expression by the LOAD-risk-allele leads to MG-specific LD accumulation.”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Interpretationown data§ 1 2 3 4 5 6 7
These results support a direct link between reduced PICALM expression and iMG phagocytosis.
“These results support a direct link between reduced PICALM expression and iMG phagocytosis.”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
- Interpretationown data§ 0 2 4 6
PICALM-risk-allele-induced LD accumulation in iMGs impairs phagocytosis.
“Collectively, these results support the notion that the PICALM-risk-allele-induced LD accumulation in iMGs impairs phagocytosis.”
Quote in the paperSubstantial claim - Interpretationreasoning§ Discussion
The impaired phagocytosis in PICALM-risk-allele iMGs implies a neuroprotective role of phagocytosis in clearing Aβ or damaged myelin.
“Finally, the impaired phagocytosis in PICALM-risk-allele iMGs implies a neuroprotective role of phagocytosis in clearing Aβ or damaged myelin, but MG phagocytosis in vivo may also be detrimental through excessive synaptic pruning57.”
Quote in the paperSubstantial claim - Interpretationreasoning§ Discussion
PICALM also regulates MG lipid/cholesterol homeostasis, independent of interactions with neurons.
“Our study indicates that PICALM also regulates MG lipid/cholesterol homeostasis, independent of interactions with neurons.”
Quote in the paperSubstantial claim - Interpretationown data§ Discussion
Lipid processing in PICALM-risk-allele iMGs may be exacerbated by lysosomal dysregulation.
“Lipid processing in PICALM-risk-allele iMGs may be exacerbated by lysosomal dysregulation (Fig. 5d–g).”
Quote in the paperNot a substantial claim - Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The PICALM risk allele impairs iMG phagocytosis.
“PICALM risk allele impairs iMG phagocytosis”
Quote in the paperSubstantial claim - Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The PICALM Alzheimer's risk allele causes aberrant lipid droplets in microglia.
“PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia”
Quote in the paperSubstantial claim - Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
TrC treatment rescues the phagocytosis deficit in iMG carrying the LOAD risk-allele by mainly converting BODIPY+ iMG to phagocytic cells without LD (Aβ-pHrodo+/BODIPY-).
“Note that TrC treatment rescues the phagocytosis deficit in iMG carrying the LOAD risk-allele by mainly converting BODIPY+ iMG to phagocytic cells without LD (Aβ-pHrodo+/BODIPY-).”
Quote in the paperSubstantial claim - Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The LOAD risk-allele of PICALM impairs microglial phagocytosis.
“The LOAD risk-allele of PICALM impairs MG phagocytosis.”
Quote in the paperSubstantial claim- Rests on an assumption: rs10792832 allele G is a LOAD risk allele for Alzheimer's disease.
- Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
LD accumulation impairs iMG phagocytosis.
“LD accumulation impairs iMG phagocytosis”
- Also stated in: § 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based · plain
“Extended Data Fig. 12 | LD accumulation impairs iMG phagocytosis.”
Quote in the paperSubstantial claim - Also stated in: § 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based · plain
- Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
PICALM-CRISPRa rescues the phagocytosis deficit in LOAD risk-allele iMG by mainly converting BODIPY+ iMG to phagocytic cells without LD (Aβ-pHrodo+/BODIPY−).
“PICALM-CRISPRa rescues the phagocytosis deficit in LOAD risk-allele iMG by mainly converting BODIPY+ iMG to phagocytic cells without LD (Aβ-pHrodo+/BODIPY−).”
Quote in the paperSubstantial claim - Study design and conductown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
CRISPR-engineered isogenic iMG show high and comparable purity for TREM2, CD45, and PU.1.
“IF staining of the CRISPR-engineered isogenic iMG (left panels) shows high and comparable purity (TREM2+/CD45+/PU.1+) (right panel).”
Quote in the paperSubstantial claim - Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
Transferred Red-C12 partially contributes to LD formation in iAst.
“Note the partial overlap of Red-C12 and BODIPY staining, suggesting the transferred Red-C12 partially contributes to LD formation in iAst.”
Quote in the paperNot a substantial claim- Rests on an assumption: The LOAD risk-allele of PICALM does not affect its expression in iAst.
- Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-based
The PICALM Alzheimer's risk allele causes aberrant lipid droplet accumulation in microglia.
“LOAD risk-allele of PICALM causes LD accumulation in iMG.”
Quote in the paperSubstantial claim- Rests on an assumption: rs10792832 allele G is a LOAD risk allele for Alzheimer's disease.
- Classified as probably not a substantial claim. 57
- May combine two claims. 26
- The quote only partly states this claim. 3
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 100 bpThe functional linkage between rs6733839 and BIN1 has been well established.
“including the two loci with the strongest associations with LOAD: the BIN1 locus for which the functional linkage between rs6733839 and BIN1 has been well established7,23”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [7] Yang, X. et al. Functional characterization of Alzheimer’s disease genetic variants in microglia. Nat. Genet. 55, 1735–1744 (2023). source
The Results section ('AD variants affect multiple target genes in microglia'; page unavailable) reports that perturbing a candidate regulatory element at the BIN1 locus significantly affects nearby gene expression. That supports a functional link at the locus, but the copy does not identify rs6733839 as the responsible variant or establish its specific functional linkage to BIN1. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites [23] Nott, A. et al. Brain cell type-specific enhancer–promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019). source
The paper’s BIN1 enhancer discussion (indexed under Abstract; no page supplied) places rs6733839 in a microglia-specific enhancer linked to the BIN1 promoter and reports that deleting the enhancer sharply reduced BIN1 expression in microglia. That establishes a functional link between the enhancer and BIN1, but the paper does not test the effect of rs6733839 itself; it calls for further investigation of the risk allele’s function. Thus, saying the variant’s functional linkage is well established overstates this source. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ IntroductionAPOE4 impairs neuron-glia lipid metabolism.
“APOE4, the strongest genetic risk factor for LOAD, impairs neuron–glia lipid metabolism14,16”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [14] Qi, G. et al. ApoE4 impairs neuron-astrocyte coupling of fatty acid metabolism. Cell Rep. 34, 108572 (2021). source
- cites [16] Liu, L., MacKenzie, K. R., Putluri, N., Maletić-Savatić, M. & Bellen, H. J. The glia-neuron lactate shuttle and elevated ROS promote lipid synthesis in neurons and lipid droplet accumulation in Glia via APOE/D. Cell Metab. 26, 719–737 (2017). source
May combine two claims.
Findingcitation§ 100 bprs10792832 lies within a predicted binding site of PU.1, with the risk allele G predicted to disrupt PU.1's consensus binding motif.
“The PICALM SNP rs10792832 lies within a predicted binding site of PU.1, a key myeloid-specific TF encoded by a strong LOAD-risk gene, SPI13,28, with the risk allele G predicted to disrupt PU.1's consensus binding motif (Fig. 2d).”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [3] Bellenguez, C. et al. New insights into the genetic etiology of Alzheimer’s disease and related dementias. Nat. Genet. 54, 412–436 (2022). source
The GWAS meta-analysis table lists Alzheimer’s-associated PICALM and SPI1 loci, but the passages from our copy do not identify rs10792832 or address PU.1 binding at that variant. Searches for rs10792832, PU.1, and the predicted motif disruption found no passage establishing the claim. (LLM, conf=0.73)
Experimental — accuracy not yet measured - cites [28] Andrews, S. J. et al. The complex genetic architecture of Alzheimer’s disease: novel insights and future directions. eBioMedicine https://doi.org/10.1016/j.ebiom.2023.104511 (2023). source
The ‘Alzheimer's disease gene prioritization’ section (page unavailable) says that AD risk variants affect PU.1 binding at microglial regulatory elements. It does not identify rs10792832, place it in a predicted PU.1 binding site, or say that its G allele disrupts the consensus motif. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 100 bpThe directional effect of the AD risk allele of rs10792832 on PICALM expression was consistent with other hMG eQTL findings.
“The directional effect of the AD risk allele of rs10792832 on PICALM expression was consistent with other hMG eQTL findings8,9,25.”
Quote in the paperNot a substantial claim3 of 3 sources checked- cites [8] Lopes, K. P. et al. Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies. Nat. Genet. 54, 4–17 (2022). source
The Results sections on genetic regulatory effects and disease loci identify PICALM as an AD-associated microglial eQTL and report that PICALM colocalization was shared with a previously published microglial dataset. They do not identify rs10792832 or state the direction of its AD risk allele’s effect on PICALM expression, so the specific directional-consistency claim is not established. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [9] Bryois, J. et al. Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nat. Neurosci. 25, 1104–1112 (2022). source
The 'Brain cell type eQTLs mediate brain disease associations' section reports a microglial PICALM co-localization signal and associates increased PICALM expression with decreased AD risk. The 'Mapping of risk variants to cell type regulatory elements' section identifies rs10792832 at a microglia-specific enhancer connected to PICALM, but our copy does not establish the expression effect of that particular risk allele or compare its direction with other human microglia eQTL findings. The indexed passages provide section labels but no specific page for these statements. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites [25] Jang, B. et al. SingleBrain: a meta-analysis of single-nucleus eQTLs linking genetic risk to brain disorders. Preprint at medRxiv https://doi.org/10.1101/2025.03.06.25323424 (2025). source
The Results section discusses AD-associated microglial eQTLs, but the passages found do not mention rs10792832 or PICALM. Searches for both terms and for a directional comparison with other human microglial eQTL findings found no passage that addresses the claim. (LLM, conf=0.72)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ IntroductionAPOE4-associated glial LD accumulation modulates neuron function and brain memory.
“and the APOE4-associated glial LD accumulation modulates neuron function and brain memory17–19.”
Quote in the paperNot a substantial claim3 of 3 sources checked- cites [17] Blanchard, J. W. et al. APOE4 impairs myelination via cholesterol dysregulation in oligodendrocytes. Nature 611, 769–779 (2022). source
The Introduction (page unavailable) reports increased lipid droplets in APOE4 oligodendroglia and reduced droplets, improved myelination, and improved learning and memory after treatment in APOE4 mice. The Discussion links cholesterol dysregulation to impaired myelination and cognition, but the paper does not establish that lipid-droplet accumulation itself modulates neuronal function or memory; the intervention also changes cholesterol transport. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites [18] Victor, M. B. et al. Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity. Cell Stem Cell 29, 1197–1212 (2022). source
The Results sections on microglial energetics and lipid-content modulation report increased lipid droplets in APOE4 microglia and show that their conditioned media reduced neuronal bursts; reducing the droplets preserved neuronal activity. The Discussion section on neuronal excitability only proposes a possible detriment to neural computations critical for learning and memory. It does not establish an effect on memory itself. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
The ‘ACSL1 and triglycerides increase after fAβ challenge’ section reports greater lipid-droplet accumulation in APOE4/4 microglia. The ‘LD+ iMG induce pTau and apoptosis in neurons’ section reports that conditioned media from lipid-droplet-high microglia induced Tau phosphorylation and caspase activation in cultured neurons, supporting an effect on neurons. Our copy does not report an effect on brain memory; the neuronal effects were also observed with APOE3/3 microglia, so they are not shown to be unique to APOE4. (LLM, conf=0.88)
Experimental — accuracy not yet measured
Classified as probably not a substantial claim.
Premisecitation§ 100 bpPICALM has a role in clathrin-mediated endocytosis in non-MG cells.
“and the role of PICALM in clathrin-mediated endocytosis in non-MG cells31,32”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [31] Ando, K. et al. PICALM and Alzheimer’s disease: an update and perspectives. Cells https://doi.org/10.3390/cells11243994 (2022). source
- cites [32] Zhang, B. et al. Synaptic vesicle size and number are regulated by a clathrin adaptor protein required for endocytosis. Neuron 21, 1465–1475 (1998). source
The Results passage on the Drosophila lap gene (page not provided) identifies LAP as an AP180-family protein with a human homolog, and the paper reports that loss of LAP impairs synaptic-vesicle endocytosis. It does not directly establish a role for human PICALM in clathrin-mediated endocytosis in non-MG cells; that part is an extrapolation from the homolog studied. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Classified as probably not a substantial claim.
Premisecitation§ IntroductionLipid droplets (LDs) have important roles in ageing and Alzheimer's disease (AD).
“Moreover, LDs—cellular organelles containing lipids such as glycerolipids and cholesterol—were recently found to have important roles in ageing and Alzheimer's disease (AD)10–15.”
Quote in the paperSubstantial claim5 of 6 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
The Results and Discussion describe lipid-droplet-accumulating microglia in the aging brain, including impaired phagocytosis (Discussion, ‘Role of lipid droplets in the LDAM functional phenotype’; page unavailable). The Introduction notes historical observations of lipid-filled glial cells in dementia, but our copy does not establish an important role for lipid droplets in Alzheimer’s disease specifically. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites [11] Lindner, K. et al. Isoform- and cell-state-specific lipidation of ApoE in astrocytes. Cell Rep. 38, 110435 (2022). source
The Discussion links lipid-droplet accumulation in astrocytes to aging and describes a possible connection to late-onset AD. But the Limitations of the study says its proposed effects on brain aging and AD remain speculative, so this source does not establish that lipid droplets have important roles in both. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites [12] Sienski, G. et al. APOE4 disrupts intracellular lipid homeostasis in human iPSC-derived glia. Sci. Transl. Med. https://doi.org/10.1126/scitranslmed.aaz4564 (2021). source
- cites [13] Moulton, M. J. et al. Neuronal ROS-induced glial lipid droplet formation is altered by loss of Alzheimer’s disease-associated genes. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2112095118 (2021). source
- cites [14] Qi, G. et al. ApoE4 impairs neuron-astrocyte coupling of fatty acid metabolism. Cell Rep. 34, 108572 (2021). source
- cites [15] Zhao, X., Zhang, S., Sanders, A. R. & Duan, J. Brain lipids and lipid droplet dysregulation in Alzheimer’s disease and neuropsychiatric disorders. Complex Psychiatry 9, 154–171 (2023). source
Classified as probably not a substantial claim.
Premisecitation§ 100 bpMG phagocytosis is important in AD.
“Considering the importance of MG phagocytosis in AD29,30”
Quote in the paperSubstantial claim1 of 2 sources checked- cites [29] Romero-Molina, C., Garretti, F., Andrews, S. J., Marcora, E. & Goate, A. M. Microglial efferocytosis: diving into the Alzheimer’s disease gene pool. Neuron 110, 3513–3533 (2022). source
- cites [30] Salter, M. W. & Stevens, B. Microglia emerge as central players in brain disease. Nat. Med. 23, 1018–1027 (2017). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ IntroductionGWAS analyses have identified 75 genome-wide significant loci for LOAD.
“GWAS analyses have identified 75 genome-wide significant (P < 5 × 10−8) loci for LOAD1–3.”
Quote in the paperNot a substantial claim3 of 3 sources checked- cites [1] Lambert, J. C. et al. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease. Nat. Genet. 45, 1452–1458 (2013). source
The Abstract supports that GWAS identified genome-wide significant LOAD loci using P < 5 × 10−8. It reports 19 such loci in the combined analysis, in addition to APOE, not 75; this source does not support the cited total. (LLM, conf=0.90)
Experimental — accuracy not yet measured - cites [2] Jansen, I. E. et al. Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk. Nat. Genet. 51, 404–413 (2019). source
The Results section (Genome-wide meta-analysis for AD status; page unavailable) reports genome-wide significant associations in 29 distinct loci, supporting the general point that GWAS identified loci associated with Alzheimer’s disease. It does not support the attributed total of 75 loci; the sentence also cites other sources, which are not assessed here. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites [3] Bellenguez, C. et al. New insights into the genetic etiology of Alzheimer’s disease and related dementias. Nat. Genet. 54, 412–436 (2022). source
The Discussion reports 75 independent loci for Alzheimer’s disease and related dementias (ADD), and the GWAS meta-analysis specifies a genome-wide significance threshold of P ≤ 5 × 10−8. The paper does not establish that all 75 loci are specifically for late-onset Alzheimer’s disease (LOAD); its analysis also includes proxy cases of dementia. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
Premisecitation§ 0 45 90 135 180Filipin only stains free (unesterified) cholesterol, and cellular cholesterol accumulation is associated with excess LD.
“Although filipin only stains free (unesterified) cholesterol, cellular cholesterol accumulation is associated with excess LD10,37,38.”
Quote in the paperSubstantial claim3 of 3 sources checked- cites [10] Marschallinger, J. et al. Lipid-droplet-accumulating microglia represent a dysfunctional and proinflammatory state in the aging brain. Nat. Neurosci. 23, 194–208 (2020). source
The Introduction describes lipid droplets as storing lipids that can include cholesterol, but does not establish that cellular cholesterol accumulation is associated with excess lipid droplets. The Discussion (‘What causes lipid droplet formation in LDAM?’; page unavailable) reports low cholesteryl ester in these droplets and suggests demyelination does not contribute to their formation. A search for filipin and free or unesterified cholesterol found no passage addressing the staining claim. (LLM, conf=0.74)
Experimental — accuracy not yet measured - cites [37] Olzmann, J. A. & Carvalho, P. Dynamics and functions of lipid droplets. Nat. Rev. Mol. Cell Biol. 20, 137–155 (2019). source
The ‘Neutral lipid synthesis and lens formation’ section says cholesterol can be esterified into a lipid-droplet component and that sterol esters can trigger droplet formation. This supports a connection between cholesterol storage and lipid droplets, but it does not establish that cellular cholesterol accumulation is associated with excess droplets. Our copy also does not address what filipin stains. (LLM, conf=0.77)
Experimental — accuracy not yet measured - cites [38] Tcw, J. et al. Cholesterol and matrisome pathways dysregulated in astrocytes and microglia. Cell 185, 2213–2233 (2022). source
The Results section ('Impaired cholesterol trafficking in APOE4 astrocytes and microglia'; page unavailable) identifies filipin as a measure of intracellular free cholesterol, supporting the first part of the claim. The Discussion mentions lipid-droplet accumulation only while describing another study's finding about choline deficiency and unsaturated fatty acids; it does not establish an association between cellular cholesterol accumulation and excess lipid droplets. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 0 45 90 135 180Cholesterol esters, derived from cellular cholesterol, are often stored in LDs along with triacylglycerols (TGs).
“Cholesterol esters, derived from cellular cholesterol, are often stored in LDs along with triacylglycerols (TGs)37.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [37] Olzmann, J. A. & Carvalho, P. Dynamics and functions of lipid droplets. Nat. Rev. Mol. Cell Biol. 20, 137–155 (2019). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ DiscussionPICALM's role in lipid/cholesterol metabolism has been reported in Drosophila glia and HEK293 cells.
“its role in lipid/cholesterol metabolism has been reported in Drosophila glia and HEK293 cells13,36”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites [13] Moulton, M. J. et al. Neuronal ROS-induced glial lipid droplet formation is altered by loss of Alzheimer’s disease-associated genes. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2112095118 (2021). source
- cites [36] Mercer, J. L. et al. Modulation of PICALM levels perturbs cellular cholesterol homeostasis. PLoS ONE 10, e0129776 (2015). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 0 45 90 135 180PICALM has been shown to be involved in lipid/cholesterol metabolism in Drosophila glia and HEK293 cells.
“Although PICALM has been shown to be involved in lipid/cholesterol metabolism in Drosophila glia and HEK293 cells13,36”
Quote in the paperNot a substantial claim1 of 2 sources checked- cites [13] Moulton, M. J. et al. Neuronal ROS-induced glial lipid droplet formation is altered by loss of Alzheimer’s disease-associated genes. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2112095118 (2021). source
- cites [36] Mercer, J. L. et al. Modulation of PICALM levels perturbs cellular cholesterol homeostasis. PLoS ONE 10, e0129776 (2015). source
Classified as probably not a substantial claim. May combine two claims.
Premisecitation§ 0 2 4 6MCOLN1 is a ROS sensor in lysosomes regulating autophagy.
“MCOLN1 is a ROS sensor in lysosomes regulating autophagy49”
Quote in the paperSubstantial claim1 of 1 sources checked- cites [49] Zhang, X. et al. MCOLN1 is a ROS sensor in lysosomes that regulates autophagy. Nat. Commun. 7, 12109 (2016). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ DiscussionThere is a reported genetic interaction between the PICALM risk-allele and APOE4.
“Given the reported genetic interaction between the PICALM risk-allele and APOE419,58, it will be interesting to empirically examine possible epistasis between these two AD risk factors.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
The section on ACSL1 and triglycerides after fAβ challenge reports APOE4-dependent lipid-droplet accumulation, not a genetic interaction with PICALM. A search of our copy for “PICALM” found no passage addressing that interaction. (LLM, conf=0.75)
Experimental — accuracy not yet measured - cites [58] Jun, G. et al. Meta-analysis confirms CR1, CLU, and PICALM as alzheimer disease risk loci and reveals interactions with APOE genotypes. Arch. Neurol. 67, 1473–1484 (2010). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitation§ MethodsNone of the donors had large copy-number variants (>100 kb).
“All donors were also analysed for copy-number variants, and none had large copy-number variants (>100 kb)61”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [61] Levinson, D. F. et al. Copy number variants in schizophrenia: confirmation of five previous findings and new evidence for 3q29 microdeletions and VIPR2 duplications. Am. J. Psychiatry 168, 302–316 (2011). source
The Methods (GWAS Assay and Detection of CNVs; Analysis of CNV Association) describe testing samples for CNVs, including variants larger than 100 kb. The Results instead report large CNVs in the paper’s own subjects; the paper does not establish that none of the citing study’s donors had them. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Classified as probably not a substantial claim. May combine two claims.
Premisecitation§ DiscussionThe APOE4 allele was recently found to induce LD accumulation in MGs and impair neuronal function.
“given that the APOE4 allele was recently found to induce LD accumulation in MGs and impair neuronal function18,19”
Quote in the paperSubstantial claim2 of 2 sources checked- cites [18] Victor, M. B. et al. Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity. Cell Stem Cell 29, 1197–1212 (2022). source
- cites [19] Haney, M. S. et al. APOE4/4 is linked to damaging lipid droplets in Alzheimer’s disease microglia. Nature 628, 154–161 (2024). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitation§ MethodsWASP calibration was performed on raw BAM files to eliminate allelic bias towards reference alleles during alignment.
“To further eliminate allelic bias towards reference alleles during the alignment step, we performed WASP (v.0.3.4) calibration on the generated raw BAM files68.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [68] van de Geijn, B., McVicker, G., Gilad, Y. & Pritchard, J. K. WASP: allele-specific software for robust molecular quantitative trait locus discovery. Nat. Methods 12, 1061–1063 (2015). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ DiscussionMG phagocytosis in vivo may also be detrimental through excessive synaptic pruning.
“MG phagocytosis in vivo may also be detrimental through excessive synaptic pruning57.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [57] Hong, S. et al. Complement and microglia mediate early synapse loss in Alzheimer mouse models. Science 352, 712–716 (2016). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitation§ MethodseSNP-karyotyping was performed for all cell lines used to eliminate potential chromosomal abnormalities.
“eSNP-karyotyping was performed for all cell lines used to eliminate potential chromosomal abnormalities, as previously described20,21.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [20] Zhang, S. et al. Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants. Science 369, 561–565 (2020). source
The paper’s passage describing the 20 iPSC lines and their assays (section labeled Abstract, page unavailable) does not say they underwent eSNP-karyotyping. Searches for eSNP-karyotyping and chromosomal-abnormality screening found only a reference to a separate chromosomal-aberration assay, not a statement that this procedure was performed on all cell lines. (LLM, conf=0.72)
Experimental — accuracy not yet measured - cites [21] Zhang, S. et al. Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons. Cell Genom. 3, 100399 (2023). source
The STAR★Methods section on experimental models describes checks of pluripotency and CRISPR off-target editing, but does not say that eSNP-karyotyping was performed on all cell lines or used to screen for chromosomal abnormalities. Searches for eSNP-karyotyping, karyotyping, and chromosomal abnormalities found no passage addressing that procedure. (LLM, conf=0.76)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationcitation§ DiscussionPICALM expression in patients with AD may also be influenced by cell type, MG state and disease stage.
“Although our study indicates a reduced PICALM expression in LOAD-risk-allele iMGs, PICALM expression in patients with AD may also be influenced by cell type, MG state and disease stage31,56.”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites [31] Ando, K. et al. PICALM and Alzheimer’s disease: an update and perspectives. Cells https://doi.org/10.3390/cells11243994 (2022). source
Section 3.3.1 says PICALM expression is dysregulated during AD progression, while section 3.4 and Discussion section 4.1 describe differing expression across cell types in AD brains. Section 3.4 also reports microglial PICALM upregulation correlated with AD pathology, but the cited paper does not establish that microglial state itself influences PICALM expression. (LLM, conf=0.82)
Experimental — accuracy not yet measured - cites [56] Baig, S. et al. Distribution and expression of picalm in Alzheimer disease. J. Neuropathol. Exp. Neurol. 69, 1071–1077 (2010). source
The Results and Discussion report that picalm is concentrated in endothelial cells, with relatively little in glial cells, supporting a cell-type distinction. The Discussion also speculates that changes in expression may relate to the stage of disease spread. The paper does not address microglial (MG) state, so that part of the claim is unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measured
May combine two claims.
Interpretationown data§ DiscussionMany LDs in iMGs are peroxidated, suggesting that ROS may also occur first and the peroxidized lipids are sequestered in LDs.
“However, many LDs in iMGs were also peroxidated (Extended Data Fig. 11b–e), suggesting that ROS may also occur first and the peroxidized lipids are sequestered in LDs16,42,52.”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites [16] Liu, L., MacKenzie, K. R., Putluri, N., Maletić-Savatić, M. & Bellen, H. J. The glia-neuron lactate shuttle and elevated ROS promote lipid synthesis in neurons and lipid droplet accumulation in Glia via APOE/D. Cell Metab. 26, 719–737 (2017). source
- cites [42] Liu, L. et al. Glial lipid droplets and ROS induced by mitochondrial defects promote neurodegeneration. Cell 160, 177–190 (2015). source
The Results sections on increased ROS and lipid peroxidation report that ROS may promote glial lipid-droplet accumulation and that accumulated lipids are peroxidated. They do not establish the proposed sequence in which lipids are peroxidated first and then sequestered in droplets. The observation about iMGs is the citing authors’ own result, not a finding attributed to this source. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites [52] Sies, H. & Jones, D. P. Reactive oxygen species (ROS) as pleiotropic physiological signalling agents. Nat. Rev. Mol. Cell Biol. 21, 363–383 (2020). source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitation§ MethodsAll ROSMAP participants enrolled without known dementia and agreed to detailed clinical evaluation and brain donation at death.
“All ROSMAP partici- pants enrolled without known dementia and agreed to detailed clinical evaluation and brain donation at death.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites [62] Bennett, D. A. et al. Religious Orders Study and Rush Memory and Aging Project. J. Alzheimers Dis. 64, S161–S189 (2018). source
May combine two claims. The quote only partly states this claim.
Findingown data§ 1 2 3 4 5 6 7The LOAD-risk allele of rs10792832 impairs the uptake of amyloid beta (Aβ) and myelin debris in microglia.
“However, PICALM-KO cells exhibited reduced (about 50%) phagocytosis of myelin-pHrodo compared with the wild-type (WT) cells (Fig. 3f,g)”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
May combine two claims.
Findingown data§ 100 bpThe LOAD-risk allele of rs10792832 reduces PICALM expression by about 50% in iMGs but not in iAst cells.
“We found that the risk allele reduced PICALM expression by about 50% (Fig. 2b,c and Extended Data Fig. 3e) in iMGs but not in iAst cells (Extended Data Fig. 3f).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
May combine two claims.
Findingown data§ Mapping functional LOAD-risk variantsThe authors confirmed cell-type-specific OCRs of MG (for example, SPI1) and Ast (for example, VIM) cells, and clear separation of iMG and iAst cells from neuronal samples.
“We confirmed cell-type-specific OCRs of MG (for example, SPI1) and Ast (for example, VIM) cells, and clear separation of iMG and iAst cells from neuronal samples (Extended Data Fig. 1f–i).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ Mapping functional LOAD-risk variantsThe authors identified between 15,693 and 72,291 ASoC SNPs, a large proportion of which were cell type specific.
“We identified between 15,693 and 72,291 ASoC SNPs, a large proportion of which were cell type specific (Extended Data Fig. 2a, Supplementary Tables 2–6 and Supplementary Fig. 3a).”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ 1 2 3 4 5 6 7Loss of PICALM did not perturb the Golgi apparatus (Giantin), the distribution of early endosomes (EEA1), AP-4 containing secretory and endocytic vesicles or the internalization of transferrin and cholera toxin through endocytosis.
“The loss of PICALM did not perturb the Golgi apparatus (Giantin), the distribution of early endosomes (EEA1), AP-4 containing secretory and endocytic vesicles or the internalization of transferrin and cholera toxin through endocytosis (Supplementary Fig. 6).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ 0 2 4 6Among the 55 lipid species altered in risk-allele iMGs versus non-risk (FDR < 0.05), 32 were TGs (5.6-fold enrichment, Fisher's exact test, P < 2.6 × 10−16) and all were increased.
“Among the 55 lipid species altered in risk-allele iMGs (versus non-risk) (FDR < 0.05), 32 were TGs (5.6-fold enrichment, Fisher's exact test, P < 2.6 × 10−16) and all were increased (Extended Data Fig. 10a,b and Supplementary Table 17).”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedATAC-seq fragment size distribution plots show periodical nucleosome-free region patterns that are similar between samples and different iPSC-derived cell types.
“(c) ATAC-seq fragment size distribution plots show periodical nucleosome-free region patterns that are similar between samples and different iPSC-derived cell types.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basediMG-specific OCR peaks were found for the known MG-specific gene SPI1 (PU.1), and VIM peaks were much stronger in iAs than in other cell types.
“(f) iMG-specific OCR peaks for a known MG-specific gene SPI1 (also known as PU.1) and much stronger peaks for VIM in iAs than in other cell types.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedCytochalasin D (10 μM) nearly completely inhibits phagocytosis.
“Cytochalasin D (10 µM) nearly completely inhibits phagocytosis.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basediMG carrying the LOAD risk-allele show increased lipid droplet and CellRox density and area compared to non-risk iMG.
“Quantification of (e) shows increased LD and CellRox density and area in iMG carrying LOAD risk-allele (vs. non-risk).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedFor genomic PCR products of the same heterozygous samples, the two alleles of rs10792832 have equal Sanger sequencing peak heights.
“Note the equal peak height of the two alleles for genomic PCR products (sequenced by using primers for on-target editing confirmation) of the same heterozygous samples as in the top panels.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basediMG with PICALM-CRISPRoff show increased LD accumulation vs non-risk allele, mimicking the effect of the PICALM risk allele.
“Note iMG with PICALM-CRISPRoff also show increased LD accumulation (vs. non-risk allele), mimicking the effect of the PICALM risk allele.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basediMG carrying the LOAD risk-allele show increased LD area, density per cell, size, and fluorescence intensity vs non-risk for both CD04 and CD09.
“(b) to (e) Increased LD (BODIPY+) area, density per cell, size, and fluorescence intensity in iMG carrying the LOAD risk-allele (vs. non-risk) for both CD04 and CD09 lines.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Premisenone given§ IntroductionAssociation-based mapping approaches do not directly implicate functional or causal variants.
“However, such association-based mapping approaches do not directly implicate functional or causal variants.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ DiscussionPICALM is known to be expressed in brain MGs.
“While PICALM is known to be expressed in brain MGs51, and its role in lipid/cholesterol metabolism has been reported in Drosophila glia and HEK293 cells13,36, our work demonstrates a human-MG-specific role for PICALM in regulating LD accumulation and phagocytosis, which potentially contribute to LOAD pathophysiology.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [51] Ando, K. et al. Clathrin adaptor CALM/PICALM is associated with neurofibrillary tangles and is cleaved in Alzheimer’s brains. Acta Neuropathol. 125, 861–878 (2013). source
Classified as probably not a substantial claim.
Premisecitation§ 0 2 4 6PICALM has been shown to promote neuron-astrocyte lipid transfer in Drosophila and rat astrocytes.
“PICALM has been shown to promote neuron–astrocyte lipid transfer in Drosophila and rat astrocytes13.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [13] Moulton, M. J. et al. Neuronal ROS-induced glial lipid droplet formation is altered by loss of Alzheimer’s disease-associated genes. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2112095118 (2021). source
May combine two claims.
Interpretationown data§ 0 2 4 6These results indicate cell-type-specific effects of PICALM on lipid transfer and LD formation in MG and Ast cells, warranting further studies.
“These results indicate cell-type-specific effects of PICALM on lipid transfer and LD formation in two very different types of glial cells, MG and Ast cells, warranting further studies.”
Quote in the paperSubstantial claim- Rests on an assumption: The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ 0 2 4 6GRN encodes the lysosomal protein progranulin related to neurodegenerative diseases.
“GRN encodes the lysosomal protein progranulin related to neurodegenerative diseases50.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [50] Simon, M. J., Logan, T., DeVos, S. L. & Di Paolo, G. Lysosomal functions of progranulin and implications for treatment of frontotemporal dementia. Trends Cell Biol. 33, 324–339 (2023). source
May combine two claims.
Interpretationown data§ DiscussionThe study mechanistically links the putative LOAD causal SNP at the PICALM locus to its MG-specific effect on PICALM expression, resulting in LD accumulation in iMGs partially through lysosomal dysregulation.
“Moreover, we mechanistically link the putative LOAD causal SNP at the PICALM locus to its MG-specific effect on PICALM expression, resulting in LD accumulation in iMGs partially through lysosomal dysregulation (Extended Data Fig. 11f).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ DiscussionIn Drosophila and rat astrocytes, PICALM is required for storing peroxidated lipids sourced from neurons.
“In Drosophila and rat astrocytes, PICALM is required for storing peroxidated lipids sourced from neurons13.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [13] Moulton, M. J. et al. Neuronal ROS-induced glial lipid droplet formation is altered by loss of Alzheimer’s disease-associated genes. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.2112095118 (2021). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsThe integrated density of pHrodo-myelin within each cell was measured from five random fields of view per biological replicate.
“within each cell was measured from five random fields of view”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsAll lipids were normalized to the peak area of an internal standard with the same head group as the target lipids.
“All lipids were normalized to the peak area of an internal standard with the same”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsLipidomics data were acquired in two technical replicates for each sample.
“with lipidomics data acquired in two technical”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsAll analysed ATAC-seq samples passed standard quality control based on the characteristic nucleosomal periodicity of the insert fragment size distribution and high signal-to-noise ratio around transcription start sites (TSSs).
“All analysed ATAC–seq samples passed standard quality control based on the characteristic nucleosomal periodicity of the insert fragment size distribution and high signal-to-noise ratio around transcription start sites (TSSs).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsThe samples from two different iMG differentiations were analysed.
“The samples from two different iMG differentiations”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsFor comparisons involving more than two groups, possible random effects from experimental rounds were accounted for when applicable.
“while accounting for any possible random effects from experimental rounds when applicable.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsPluripotency of CRISPR-Cas9-edited human iPS cell lines was confirmed by staining with pluripotency marker antibodies OCT4, NANOG and SSEA4.
“To confirm the pluripotency of CRISPR–Cas9-edited human iPS cell lines, the cells were stained with pluripotency marker antibodies: rabbit anti-OCT4 (ab181557, Abcam, 1:250), goat anti-NANOG (AF1997-SP, R&D Systems, 1:50) and mouse anti-SSEA4 (ab16287, Abcam, 1:250).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ DiscussionIn glia, the main sources of ROS include peroxisomes and mitochondria that perform lipid β-oxidation.
“In glia, the main sources of ROS include peroxisomes and mitochondria that perform lipid β-oxidation52.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [52] Sies, H. & Jones, D. P. Reactive oxygen species (ROS) as pleiotropic physiological signalling agents. Nat. Rev. Mol. Cell Biol. 21, 363–383 (2020). source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsBenjamini-Hochberg correction was applied to all qualified ASoC SNPs in the ATAC-seq analysis of ASoC SNPs.
“the Benjamini–Hochberg correction was applied”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.
Study design and conductnone given§ MethodsFive random fields of view per biological replicate were acquired for quantification of BODIPY+ droplets.
“Five random fields of view (per biological replicate) were acquired for”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown data§ DiscussionPICALM has a human-MG-specific role in regulating LD accumulation and phagocytosis, which potentially contribute to LOAD pathophysiology.
“our work demonstrates a human-MG-specific role for PICALM in regulating LD accumulation and phagocytosis, which potentially contribute to LOAD pathophysiology.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsCell line ID (CD04 and CD09) was considered as a coefficient in generalized linear models to further remove line-specific effects.
“When constructing the generalized linear models, we considered cell line ID (CD04 and CD09) as a coefficient to further remove line-specific effects.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsAll cell cultures used in the study were confirmed to be mycoplasma-free using a PCR detection kit.
“All cell cul- tures were confirmed to be mycoplasma-free using the PCR detection kit (ab289834, Abcam).”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationreasoning§ DiscussionThe lipids are peroxidated and sequestered in LDs, which are initially protective against ROS elevation.
“(2) the lipids are peroxidated and sequestered in LDs, which are initially protective against ROS elevation;”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoning§ MethodsOnly SNPs with corresponding rs# records found in dbSNP v154 were retained to reduce bias introduced by acquired or de novo mutations during cell growth.
“To reduce bias introduced by any acquired (or de novo) mutations during cell growth, only SNPs with corresponding rs# records found in dbSNP v154 were retained.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoning§ MethodsThe human iPS cell lines used for ATAC-seq were generated using the Sendai virus method and are integration-free.
“The human iPS cell lines were generated using the Sendai virus method to ensure that they are integration-free”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoning§ MethodsFor two-group comparisons, an LMM was used to account for potential random effects from different experimental rounds and clones.
“otherwise, we used the R packages lme4 and lmerTest to fit data into an LMM”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationreasoning§ DiscussionOngoing lipid build-up causes cellular stress, further elevating ROS and LD levels.
“(3) ongoing lipid build-up causes cellular stress, further elevating ROS and LD levels;”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsThe median values from each biological replicate were used for statistical analysis of myelin phagocytosis.
“the median values from each replicate were”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductnone given§ MethodsThe purity of selected CRISPR-Cas9-edited iPS cell clones was confirmed for on-target editing and the absence of off-target editing.
“The purity of the selected clones was confirmed for on-target editing and the absence of off-target editing (see below).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsFor quantification of PICALM in IBA1+ microglia, all processing was conducted by a researcher blinded to individual diagnoses.
“For quantification of PICALM in IBA1+ microglia, all processing was conducted by a researcher blinded to individual diagnoses.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsSanger sequencing was used to verify editing in resistant colonies.
“Resistant colonies were collected 14 days after transfection and a small amount of DNA from each colony was used for Sanger sequencing to verify editing.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsNo obvious mapping bias to reference alleles was confirmed by visualizing volcano plots of allelic read-depth ratios against −log2[P] values.
“We confirmed there was no obvious mapping bias to reference alleles by visualizing the volcano plots that graph the allelic read-depth ratios against −log2[P] values in scatter plots.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsPrimers were designed to amplify regions corresponding to the four top-ranking predicted off-targets to check on-target and off-target editing.
“Primers were designed to amplify regions corresponding to the four top-ranking predicted off-targets to check on-target and off-target editing.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.
Study design and conductnone given§ MethodsThe median values from each biological replicate were used for statistical analysis of LD staining.
“and the median values from each biological replicate”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ MethodsBenjamini-Hochberg procedure was used to adjust P values accounting for multiple testing in RNA-seq DEG analysis.
“the Benjamini–Hochberg procedure was used to adjust P values”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Study design and conductnone given§ DiscussionWe cannot formally exclude a possible long-range cis-effect of the AD-risk variant on genes other than PICALM.
“However, we cannot formally exclude a possible long-range cis-effect of the AD-risk variant on genes other than PICALM.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone given§ MethodsThe images were acquired in a manner that the operator was blinded to the sample and genotype identification.
“The images were acquired in a manner that the operator was”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone given§ MethodsComBat-seq was applied to remove batch effects between the two experiments (rounds of iMG differentiation).
“The ComBat-seq function from the R package sva was applied to remove batch effects between the two experiments (that is, rounds of iMG differentiation).”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown data§ DiscussionPartial loss of PICALM in MGs exacerbates ROS levels, leading to increased lipid/cholesterol synthesis due to increased SREBP.
“We therefore propose a model that connects the PICALM risk allele to LD accumulation and phagocytosis deficits (Extended Data Fig. 11f): (1) partial loss of PICALM in MGs exacerbates ROS levels (Extended Data Fig. 7e), leading to increased lipid/cholesterol synthesis due to increased SREBP;”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedPICALM knockdown or knockout causes LD accumulation.
“Extended Data Fig. 9 | PICALM knockdown (KD) or knockout (KO) causes LD accumulation.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedThe LOAD GWAS SNP risk allele is linked to reduced PICALM expression, lysosomal dysfunction, LD accumulation, LD peroxidation, cellular ROX level, and phagocytosis deficits in iMG.
“(f) Mechanistic insight on the link between the LOAD GWAS SNP risk allele and the reduced PICALM expression, lysosomal dysfunction, LD accumulation, LD peroxidation, cellular ROX level, and phagocytosis deficits in iMG.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedSelected DE genes were validated by qPCR and IF staining.
“Validation of the selected DE genes by qPCR and IF staining.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown data§ 77. Nunez, J. K. et al. Genome-wide programmable transcriptional memory by CRISPR-basedPU.1 antibody was validated in PMP cells from which iMG were further differentiated.
“PU.1 antibody validation in PMP cells from which iMG were further differentiated.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
The functional link between rs10792832 and PICALM was unknown before this study.
“and the PICALM locus with an unknown functional link between rs10792832 and its target gene PICALM (Fig. 1c,d and Extended Data Fig. 2l).”
The paper relies on this without support.
The role of PICALM in LD formation in microglia and its link to the LOAD-risk allele was not demonstrated before this study.
“its potential role in LD formation in MGs, especially its link to the LOAD-risk allele, has not been demonstrated.”
The paper relies on this without support.
The CRISPR-edited iPS cell lines differ from the non-risk lines only at rs10792832 and not at off-target sites.
“iMGs from a second clone of each iPS cell line also exhibited similar allelic difference in phagocytic activity”
The paper relies on this without support.
Around 70% of ASoC SNPs are in distal enhancers and are likely to be functional.
“Given that around 70% of ASoC SNPs are in distal enhancers and are likely to be functional, our study presents a framework for prioritizing functional non-coding risk variants through combinatorial analyses of whether a SNP is predicted to alter TF-binding sites and/or is a brain eQTL.”
The authors state this as an assumption.
A functional common GWAS SNP does not display monoallelic chromatin accessibility.
“with the assumption that a functional common GWAS SNP does not display monoallelic chromatin accessibility”
The paper relies on this without support.
rs10792832 allele G is a LOAD risk allele for Alzheimer's disease.
“The LOAD risk-allele G of rs10792832 shows reduced PU.1 binding in qPCR of ChIP products.”
The paper relies on this without support.
C11-BODIPY fluorescence shift from red to green indicates lipid peroxidation/ROS.
“(a) The schematics show C11-BODIPY (581/591), a fluorescent lipid peroxidation sensor, shifts its fluorescence from red to green in the presence of ROS.”
The paper relies on this without support.
The LOAD risk-allele of PICALM does not affect its expression in iAst.
“over the genetic background of non-risk allele since the LOAD risk-allele of PICALM does not affect its expression in iAst”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Altered lipid droplet biology has been linked to both brain aging and neurodegenerative diseases.
“Altered lipid droplet biology has been linked to both brain aging and neurodegenerative diseases10–24.”
From APOE genotypes differentially remodel the astrocytic lipid droplet proteome to shape lipid droplet dynamics (2026) · cites this paper as [11]
Lipid droplets have been associated with AD risk genes beyond APOE (PICALM and INPP5D in microglia and ABCA7 in neurons), suggesting convergent biology across risk genes.
“Interestingly, lipid droplets have now been associated with AD risk genes beyond APOE (PICALM and INPP5D in microglia and ABCA7 in neurons), suggesting convergent biology across risk genes11,31,32.”
From APOE genotypes differentially remodel the astrocytic lipid droplet proteome to shape lipid droplet dynamics (2026) · cites this paper as [11]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Cytochalasin D concentration differs by 1,000-fold for C20 assay
MajorThe Fig. 3 caption gives 10 μM cytochalasin D for the C20-cell phagocytosis control, while the C20-cell assay method gives 10 nM.
“Cytochalasin D (10 µM) was used to show the specificity of phagocytosis.”
“Negative controls were treated with cytochalasin D (10 nM, Invitrogen).”
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“10a,b and Supplementary Table 17).”
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“Considering the importance of MG phagocytosis in AD 29,30 and the role of PICALM in clathrin-mediated endocytosis in non-MG cells 31,32 , we hypothesized that the LOAD-risk allele of rs10792832 influences iMG phagocytosis by reducing PICALM expression.”
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Cholesterol and matrisome pathways dysregulated in astrocytes and microglia
TCW, J., Qian, L., Pipalia, N. H., Chao, M. J., Liang, S. A., Shi, Y., Jain, B. R., Bertelsen, S. E., Kapoor, M., Marcora, E., et al. (2022) · Cell · doi:10.1016/j.cell.2022.05.017 · Cited by 411 · cited 4× · see citing works
“Although filipin only stains free (unesterified) cholesterol, cellular cholesterol accumulation is associated with excess LD 10,37,38 .”
InfluentialApoE4 Impairs Neuron-Astrocyte Coupling of Fatty Acid Metabolism
Qi, G., Mi, Y., Shi, X., Gu, H., Brinton, R. D., & Yin, F. (2021) · Cell Reports · doi:10.1016/j.celrep.2020.108572 · Cited by 379 · see citing works
The complex genetic architecture of Alzheimer's disease: novel insights and future directions
Andrews, S. J., Renton, A. E., Fulton-Howard, B., Podlesny-Drabiniok, A., Marcora, E., & Goate, A. M. (2023) · eBioMedicine · doi:10.1016/j.ebiom.2023.104511 · Cited by 377 · cited 1× · see citing works
“The PICALM SNP rs10792832 lies within a predicted binding site of PU.1, a key myeloid-specific TF encoded by a strong LOAD-risk gene, SPI1 3,28 , with the risk allele G predicted to disrupt PU.1’s consensus binding motif (Fig.”
Generation of pure GABAergic neurons by transcription factor programming
Yang, N., Chanda, S., Marro, S., Ng, Y.-H., Janas, J. A., Haag, D., Ang, C. E., Tang, Y., Flores, Q., Mall, M., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4291 · Cited by 341 · see citing works
<i>APOE4</i> disrupts intracellular lipid homeostasis in human iPSC-derived glia
Sienski, G., Narayan, P., Bonner, J. M., Kory, N., Boland, S., Arczewska, A. A., Ralvenius, W. T., Akay, L., Lockshin, E., He, L., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.aaz4564 · Cited by 336 · see citing works
Lipid accumulation induced by APOE4 impairs microglial surveillance of neuronal-network activity
Victor, M. B., Leary, N., Luna, X., Meharena, H. S., Scannail, A. N., Bozzelli, P. L., Samaan, G., Murdock, M. H., von Maydell, D., Effenberger, A. H., et al. (2022) · Cell Stem Cell · doi:10.1016/j.stem.2022.07.005 · Cited by 316 · see citing works
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Predicting cellular responses to complex perturbations in high‐throughput screens
Lotfollahi, M., Klimovskaia Susmelj, A., De Donno, C., Hetzel, L., Ji, Y., Ibarra, I. L., Srivatsan, S. R., Naghipourfar, M., Daza, R. M., Martin, B., et al. (2023) · Molecular Systems Biology · doi:10.15252/msb.202211517 · Cited by 307 · cited 1× · see citing works
“…correlation between the magnitude of PICALM alteration and its functional effects in CRISPR-engineered iMGs, probably due to technical variations in iMG differentiation and/or the nonlinear relationship between gene expression and cellular phenotypes due to epistasis and systems buffering 54,55 .”
PICALM modulates autophagy activity and tau accumulation
Moreau, K., Fleming, A., Imarisio, S., Lopez Ramirez, A., Mercer, J. L., Jimenez-Sanchez, M., Bento, C. F., Puri, C., Zavodszky, E., Siddiqi, F., et al. (2014) · Nature Communications · doi:10.1038/ncomms5998 · Cited by 281 · see citing works
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“The downregulated genes were enriched for Gene Ontology (GO) terms (such as MHC class II protein complex, antigen presentation and clathrin-coated endocytic vesicle membranes) that are important for MG phagocytosis 34 (Supplementary Table 15 and Supplementary Fig.”
Direct lysosome-based autophagy of lipid droplets in hepatocytes
Schulze, R. J., Krueger, E. W., Weller, S. G., Johnson, K. M., Casey, C. A., Schott, M. B., & McNiven, M. A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2011442117 · Cited by 245 · cited 1× · see citing works
“Given the link between lysosome-based autophagy and LD breakdown 47 , we predicted that LD accumulation in PICALM LOAD-risk-allele iMGs may result from compromised lysosomal function.”
Tian, Y., Chang, J. C., Fan, E. Y., Flajolet, M., & Greengard, P. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1315110110 · Cited by 233 · cited 1× · see citing works
“PICALM also has a role in autophagy and lysosomal function in some non-brain cell lines 44–46 .”
Novikova, G., Kapoor, M., TCW, J., Abud, E. M., Efthymiou, A. G., Chen, S. X., Cheng, H., Fullard, J. F., Bendl, J., Liu, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-21823-y · Cited by 214 · cited 3× · see citing works
“210,833 peaks from the previous studies 6,22 were used for PCA.”
InfluentialA Map of Transcriptional Heterogeneity and Regulatory Variation in Human Microglia
Young, A. M. H., Kumasaka, N., Calvert, F., Hammond, T. R., Knights, A., Panousis, N., Park, J. S., Schwartzentruber, J., Liu, J., Kundu, K., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00875-2 · Cited by 213 · see citing works
Epigenomic dissection of Alzheimer’s disease pinpoints causal variants and reveals epigenome erosion
Xiong, X., James, B. T., Boix, C. A., Park, Y. P., Galani, K., Victor, M. B., Sun, N., Hou, L., Ho, L.-L., Mantero, J., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.040 · Cited by 205 · cited 1× · see citing works
“Except for our iMG, data of all other cell types are from a snATAC-seq study 24 and reanalysed by using 10x Genomics Cell Ranger ARC 2.0.2.”
InfluentialFunctional Studies of Missense TREM2 Mutations in Human Stem Cell-Derived Microglia
Brownjohn, P. W., Smith, J., Solanki, R., Lohmann, E., Houlden, H., Hardy, J., Dietmann, S., & Livesey, F. J. (2018) · Stem Cell Reports · doi:10.1016/j.stemcr.2018.03.003 · Cited by 193 · cited 1× · see citing works
“Data were plotted and analysed using Prism 10 (GraphPad). iMG differentiation from human iPS cells iMGs were generated from human iPS cell lines as described in our previous study 63 using the Brownjohn’s method 64 .”
Moulton, M. J., Barish, S., Ralhan, I., Chang, J., Goodman, L. D., Harland, J. G., Marcogliese, P. C., Johansson, J. O., Ioannou, M. S., & Bellen, H. J. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2112095118 · Cited by 180 · see citing works
Self-citationGenetics of the human microglia regulome refines Alzheimer’s disease risk loci
Kosoy, R., Fullard, J. F., Zeng, B., Bendl, J., Dong, P., Rahman, S., Kleopoulos, S. P., Shao, Z., Girdhar, K., Humphrey, J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01149-1 · Cited by 168 · see citing works
Self-citationDynamics and regulation of lipid droplet formation in lipopolysaccharide (LPS)-stimulated microglia
Khatchadourian, A., Bourque, S. D., Richard, V. R., Titorenko, V. I., & Maysinger, D. (2012) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/j.bbalip.2012.01.007 · Cited by 143 · cited 2× · see citing works
“Treating iMGs with triacsin C (TrC), an inhibitor of long-chain acyl-CoA synthetase that reduces LD formation 10,18,19,39,40 , effectively decreased BODIPY-labelled LDs (Extended Data Fig.”
Ando, K., Brion, J.-P., Stygelbout, V., Suain, V., Authelet, M., Dedecker, R., Chanut, A., Lacor, P., Lavaur, J., Sazdovitch, V., et al. (2013) · Acta Neuropathologica · doi:10.1007/s00401-013-1111-z · Cited by 136 · cited 1× · see citing works
“While PICALM is known to be expressed in brain MGs 51 , and its role in lipid/cholesterol metabolism has been reported in Drosophila glia and HEK293 cells 13,36 , our work demonstrates a human-MG-specific role for PICALM in regulating LD accumulation and phagocytosis, which potentially contribute…”
Rong, S., Cortés, V. A., Rashid, S., Anderson, N. N., McDonald, J. G., Liang, G., Moon, Y.-A., Hammer, R. E., & Horton, J. D. (2017) · eLife · doi:10.7554/elife.25015 · Cited by 134 · cited 3× · see citing works
“8 and Supplementary Table 16), activated pathways were linked to lipid metabolism, such as cholesterol biosynthesis and gene activation by SREBF (encoding SREBP) 35 .”
Dileep, V., Boix, C. A., Mathys, H., Marco, A., Welch, G. M., Meharena, H. S., Loon, A., Jeloka, R., Peng, Z., Bennett, D. A., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.038 · Cited by 130 · see citing works
Self-citationAllele-specific open chromatin in human iPSC neurons elucidates functional disease variants
Zhang, S., Zhang, H., Zhou, Y., Qiao, M., Zhao, S., Kozlova, A., Shi, J., Sanders, A. R., Wang, G., Luo, K., et al. (2020) · Science · doi:10.1126/science.aay3983 · Cited by 127 · cited 8× · see citing works
“…identify functional LOAD GWAS risk variants, we performed an assay for transposase-accessible chromatin using sequencing (ATAC–seq) and ascertained the allelic imbalance of chromatin accessibility (that is, ASoC) 20,21 at heterozygous LOAD-risk single-nucleotide polymorphism (SNP) sites (Fig.”
InfluentialSelf-citationDistribution and Expression of Picalm in Alzheimer Disease
Baig, S., Joseph, S. A., Tayler, H., Abraham, R., Owen, M. J., Williams, J., Kehoe, P. G., & Love, S. (2010) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e3181f52e01 · Cited by 115 · cited 1× · see citing works
“Although our study indicates a reduced PICALM expression in LOAD-risk-allele iMGs, PICALM expression in patients with AD may also be influenced by cell type, MG state and disease stage 31,56 .”
Microglial efferocytosis: Diving into the Alzheimer’s disease gene pool
Romero-Molina, C., Garretti, F., Andrews, S. J., Marcora, E., & Goate, A. M. (2022) · Neuron · doi:10.1016/j.neuron.2022.10.015 · Cited by 111 · cited 1× · see citing works
“Considering the importance of MG phagocytosis in AD 29,30 and the role of PICALM in clathrin-mediated endocytosis in non-MG cells 31,32 , we hypothesized that the LOAD-risk allele of rs10792832 influences iMG phagocytosis by reducing PICALM expression.”
Developmental nonlinearity drives phenotypic robustness
Green, R. M., Fish, J. L., Young, N. M., Smith, F. J., Roberts, B., Dolan, K., Choi, I., Leach, C. L., Gordon, P., Cheverud, J. M., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-02037-7 · Cited by 106 · cited 1× · see citing works
“…correlation between the magnitude of PICALM alteration and its functional effects in CRISPR-engineered iMGs, probably due to technical variations in iMG differentiation and/or the nonlinear relationship between gene expression and cellular phenotypes due to epistasis and systems buffering 54,55 .”
PICALM and Alzheimer’s Disease: An Update and Perspectives
Ando, K., Nagaraj, S., Küçükali, F., de Fisenne, M.-A., Kosa, A.-C., Doeraene, E., Lopez Gutierrez, L., Brion, J.-P., & Leroy, K. (2022) · Cells · doi:10.3390/cells11243994 · Cited by 104 · cited 2× · see citing works
“Although our study indicates a reduced PICALM expression in LOAD-risk-allele iMGs, PICALM expression in patients with AD may also be influenced by cell type, MG state and disease stage 31,56 .”
Wen, X. (2016) · The Annals of Applied Statistics · doi:10.1214/16-aoas952 · Cited by 101 · cited 1× · see citing works
“Bayesian hierarchical model (TORUS) was applied to perform an SNP-based enrichment analysis to explore whether ASoC SNPs are enriched in any of the diseases 73 as previously described 20 .”
Lysosomal functions of progranulin and implications for treatment of frontotemporal dementia
Simon, M. J., Logan, T., DeVos, S. L., & Di Paolo, G. (2023) · Trends in Cell Biology · doi:10.1016/j.tcb.2022.09.006 · Cited by 94 · cited 1× · see citing works
“5d), two of which are related to lysosomal function: MCOLN1 is a ROS sensor in lysosomes regulating autophagy 49 , and GRN encodes the lysosomal protein progranulin related to neurodegenerative diseases 50 .”
Ho, S., Hartley, B. J., Flaherty, E. K., Rajarajan, P., Abdelaal, R., Obiorah, I., Barretto, N., Muhammad, H., Phatnani, H. P., Akbarian, S., et al. (2017) · Stem Cell Reports · doi:10.1016/j.stemcr.2017.06.012 · Cited by 86 · see citing works
Isoform- and cell-state-specific lipidation of ApoE in astrocytes
Lindner, K., Beckenbauer, K., van Ek, L. C., Titeca, K., de Leeuw, S. M., Awwad, K., Hanke, F., Korepanova, A. V., Rybin, V., van der Kam, E. L., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110435 · Cited by 84 · see citing works
Dubreuil, M. M., Morgens, D. W., Okumoto, K., Honsho, M., Contrepois, K., Lee‐McMullen, B., Traber, G. M., Sood, R. S., Dixon, S. J., Snyder, M. P., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.01.013 · Cited by 77 · cited 1× · see citing works
“Notably, PICALM and some other clathrin adaptor proteins are reported to protect against ROS production partially through iron regulation 53 .”
Complete Inhibition of Mouse Macrophage-Derived Foam Cell Formation by Triacsin C
Namatame, I., Tomoda, H., Arai, H., Inoue, K., & Omura, S. (1999) · Journal of Biochemistry · doi:10.1093/oxfordjournals.jbchem.a022289 · Cited by 74 · cited 2× · see citing works
“Treating iMGs with triacsin C (TrC), an inhibitor of long-chain acyl-CoA synthetase that reduces LD formation 10,18,19,39,40 , effectively decreased BODIPY-labelled LDs (Extended Data Fig.”
Comparative analysis of human microglial models for studies of HIV replication and pathogenesis
Mohammad, A., Hammonds, J. E., Pujato, M. A., Mayhew, C. N., Roskin, K. M., & Spearman, P. W. (2020) · Retrovirology · doi:10.1186/s12977-020-00544-y · Cited by 72 · see citing works
Functional characterization of Alzheimer’s disease genetic variants in microglia
Yang, X., Wen, J., Yang, H., Jones, I. R., Zhu, X., Liu, W., Li, B., Clelland, C. D., Luo, W., Wong, M. Y., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01506-8 · Cited by 71 · see citing works
Reducing microglial lipid load enhances β amyloid phagocytosis in an Alzheimer’s disease mouse model
Wu, X., Miller, J. A., Lee, B. T. K., Wang, Y., & Ruedl, C. (2025) · Science Advances · doi:10.1126/sciadv.adq6038 · Cited by 67 · cited 2× · see citing works
“We next conducted a phagocytosis assay for LOAD-risk-allele iMGs in the presence or absence of the LD blocker (TrC) 10,18,19,39,40 to confirm whether LD accumulation impairs phagocytosis as seen in mouse microglia 10,43 .”
Analysis of chromosomal aberrations and recombination by allelic bias in RNA-Seq
Weissbein, U., Schachter, M., Egli, D., & Benvenisty, N. (2016) · Nature Communications · doi:10.1038/ncomms12144 · Cited by 64 · see citing works
Deriving dopaminergic neurons for clinical use. A practical approach
Gonzalez, R., Garitaonandia, I., Abramihina, T., Wambua, G. K., Ostrowska, A., Brock, M., Noskov, A., Boscolo, F. S., Craw, J. S., Laurent, L. C., et al. (2013) · Scientific Reports · doi:10.1038/srep01463 · Cited by 56 · see citing works
ATP6AP2 variant impairs CNS development and neuronal survival to cause fulminant neurodegeneration
Hirose, T., Cabrera-Socorro, A., Chitayat, D., Lemonnier, T., Féraud, O., Cifuentes-Diaz, C., Gervasi, N., Mombereau, C., Ghosh, T., Stoica, L., et al. (2019) · Journal of Clinical Investigation · doi:10.1172/jci79990 · Cited by 55 · cited 1× · see citing works
“4b and Supplementary Table 13), encodes a protein that is essential for lysosomal degradative functions; Atp6ap2-mutant mice show increased triglycerides and LD in fat body cells 48 .”
Brain Lipids and Lipid Droplet Dysregulation in Alzheimer’s Disease and Neuropsychiatric Disorders
Zhao, X., Zhang, S., Sanders, A. R., & Duan, J. (2023) · Complex Psychiatry · doi:10.1159/000535131 · Cited by 54 · see citing works
Self-citationZhang, S., Zhang, H., Forrest, M. P., Zhou, Y., Sun, X., Bagchi, V. A., Kozlova, A., Santos, M. D., Piguel, N. H., Dionisio, L. E., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100399 · Cited by 26 · cited 6× · see citing works
“…identify functional LOAD GWAS risk variants, we performed an assay for transposase-accessible chromatin using sequencing (ATAC–seq) and ascertained the allelic imbalance of chromatin accessibility (that is, ASoC) 20,21 at heterozygous LOAD-risk single-nucleotide polymorphism (SNP) sites (Fig.”
InfluentialSelf-citationModulation of PICALM Levels Perturbs Cellular Cholesterol Homeostasis
Mercer, J. L., Argus, J. P., Crabtree, D. M., Keenan, M. M., Wilks, M. Q., Chi, J.-T. A., Bensinger, S. J., Lavau, C. P., & Wechsler, D. S. (2015) · PLOS ONE · doi:10.1371/journal.pone.0129776 · Cited by 17 · cited 2× · see citing works
“Although PICALM has been shown to be involved in lipid/cholesterol metabolism in Drosophila glia and HEK293 cells 13,36 , its potential role in LD formation in MGs, especially its link to the LOAD-risk allele, has not been demonstrated.”
Butler, R. R., Kozlova, A., Zhang, H., Zhang, S., Streit, M., Sanders, A. R., Laudański, K., Pang, Z. P., Gejman, P. V., & Duan, J. (2019) · Complex Psychiatry · doi:10.1159/000501935 · Cited by 16 · cited 1× · see citing works
“Data were plotted and analysed using Prism 10 (GraphPad). iMG differentiation from human iPS cells iMGs were generated from human iPS cell lines as described in our previous study 63 using the Brownjohn’s method 64 .”
Self-citationHigh-resolution mass spectrometric analysis of cardiolipin profiles in Barth syndrome
Byeon, S. K., Ramarajan, M. G., Madugundu, A. K., et al. (2021) · Mitochondrion · doi:10.1016/j.mito.2021.07.003 · Cited by 15 · see citing works
Self-citationSingleBrain: A Meta-Analysis of Single-Nucleus eQTLs Linking Genetic Risk to Brain Disorders
Jang, B., Kailash, B., Tokolyi, A., Cuddleston, W. H., Ravi, A., Jung, S.-H., Naito, T., Kim, B., Kim, M. S., Cho, M., et al. (2025) · doi:10.1101/2025.03.06.25323424 · Cited by 11 · cited 1× · see citing works
“The directional effect of the AD risk allele of rs10792832 on PICALM expression was consistent with other hMG eQTL findings 8,9,25 .”
PICALM regulates cathepsin D processing and lysosomal function
Hattersley, K. J., Carosi, J. M., Hein, L. K., Bensalem, J., & Sargeant, T. J. (2021) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2021.07.024 · Cited by 10 · see citing works
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Self-citationUsing CRISPR-ERA Webserver for sgRNA Design
Liu, H., Wang, X., & Qi, L. S. (2017) · BIO-PROTOCOL · doi:10.21769/bioprotoc.2522 · Cited by 3 · see citing works
Jang, B., Won, H.-H., & Raj, T. (2025) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.14907598 · Cited by 3 · see citing works
Summary statistics of cell-type specific cis-eQTLs in eight brain cell-types
Bryois, J. (2021) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.5543734 · Cited by 1 · see citing works
Alzheimer's disease risk allele of PICALM causes detrimental lipid droplets in microglia
Zhang, S. (2025) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.14853786 · Cited by 1 · see citing works
Self-citationendeneon/PICALM_Kozlova: 1.0.0 for review purpose Zenodo push
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WASP: allele-specific software for robust discovery of molecular quantitative trait loci
van de Geijn, B., McVicker, G., Gilad, Y., et al. (2014) · doi:10.1101/011221
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Neuroinflammation in Alzheimer disease
Heneka, M. T., van der Flier, W. M., Jessen, F., Hoozemanns, J., Thal, D. R., Boche, D., Brosseron, F., Teunissen, C., Zetterberg, H., Jacobs, A. H., et al. (2025) · Nature Reviews Immunology · doi:10.1038/s41577-024-01104-7 · Cited by 638 · see citing works
He, S., Xu, Z., & Han, X. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00803-6 · Cited by 62 · see citing works
Microglial phagocytosis in Alzheimer disease
Brown, G. C., St George-Hyslop, P., Paolicelli, R. C., & Lemke, G. (2026) · Nature Reviews Neurology · doi:10.1038/s41582-025-01162-y · Cited by 36 · see citing works
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Self-citationLipid metabolism and metabolites: emerging roles in systemic physiology and metabolic diseases
Xu, J., Lu, D., & Huang, X. (2026) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2026.01.006 · Cited by 10 · see citing works
Transcriptional regulation of disease-relevant microglial activation programs
McQuade, A., Mishra, R., Hagan, V., Liang, W., Colias, P. J., Castillo, V. C., Gonzalez, B., Lubin, J. P., Haage, V. C., Marshe, V. S., et al. (2026) · Neuron · doi:10.1016/j.neuron.2026.07.001 · Cited by 6 · see citing works
Haskell, A. K., Kulas, J. A., Carter, W., Javens‐Wolfe, J., Hinkel, R. D., Moussaif, M., Smiley, J. S., Lazaro, O., Robertson, S., Palkowitz, A. D., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71117 · Cited by 6 · see citing works
“68 We found that treatment of iMG with myelin debris had potent effects on the transcription of several lipid homeostasis genes.”
Cellular mechanisms of brain lipid metabolism in health and disease
Petrelli, F., Gilardi, C., Igelbüscher, C. M., Panfilova, D., Rey, A., Paolicelli, R. C., & Knobloch, M. (2026) · Nature Cell Biology · doi:10.1038/s41556-026-01880-5 · Cited by 7 · see citing works
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Paterson, T., Rohrs, J. A., Hohman, T. J., Mapstone, M. E., Meikle, P. J., Kaddurah‐Daouk, R., Levey, A. I., Hood, L., Initiative, A. D. N., & Funk, C. C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.23.604835 · Cited by 3 · see citing works
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The Interplay Between Immunometabolism and Neuroinflammation in Alzheimer’s Disease
Crescenzo, T. D., Papiri, G., Membrino, V., Alia, S., Cecati, M., Campagna, R., Silvestrini, M., Luzzi, S., & Vignini, A. (2026) · Biomolecules · doi:10.3390/biom16050656 · Cited by 3 · see citing works
“…handling by phagocytosis is thought to play an important role in late-onset AD pathogenesis; in a recent study, mutations in the phosphatidylinositol-binding clathrin assembly protein (PICALM) gene, which regulates microglial debris clearance, have been associated with a causal role in AD [40].”
Single-cell multiomics of neuron activation reveals context-specific genetics of brain disorders
Liang, L., Zhang, S., Wang, Z., Zhang, H., Li, C., Thapa, C., Oh, E., Sirkin, D., Sun, X., Barishman, A., et al. (2026) · Science · doi:10.1126/science.adw3949 · Cited by 3 · see citing works
Self-citationVázquez‐Rosa, E., Shin, M., Chaubey, K., Barker, S., Corella, S. G., Chakraborty, S., Tripathi, S. J., Yu, Y., Hyung, J., Dashora, H. R., et al. (2026) · Redox Biology · doi:10.1016/j.redox.2026.104052 · Cited by 2 · see citing works
“Lipid droplet (LD) accumulation in microglia impairs phagocytosis [48] and is linked to neurodegeneration [49].”
Endocytic scaffolds at the crossroads of Alzheimer’s disease and neuronal aging
Shergill, J. K., & Tehran, D. A. (2026) · Biological Chemistry · doi:10.1515/hsz-2025-0250 · Cited by 2 · see citing works
“More recently, a LOAD-associated PICALM allele that lowers CALM expression in microglia has been shown to drive aberrant lipid droplet accumulation, reduce uptake of A β and myelin debris, and impair phagocytic capacity (Kozlova et al. 2025) (Figure 2).”
Epigenetic noise in the aging brain: tuning neuronal vulnerability to neurodegeneration
Yin, X., Zhang, H., Zhang, R., Xue, J., & Hou, Y. (2026) · Trends in Neurosciences · doi:10.1016/j.tins.2026.04.006 · Cited by 3 · see citing works
Self-citationHu, P., Guo, S., Ren, Y., Zhao, R., Su, L., Cheng, J., & Tian, X. (2026) · ACS Sensors · doi:10.1021/acssensors.6c01055 · Cited by 2 · see citing works
Cary, G. A., Ganesh, S. S. A., Heath, L. M., Leal, K., Kampmann, M., Longo, F. M., Butler, R. R., Levey, A. I., Carter, G. W., & Wiley, J. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71403 · Cited by 2 · see citing works
Zhao, X., Li, Y., Zhang, S., Sudwarts, A., Zhang, H., Kozlova, A., Moulton, M. J., Goodman, L. D., Pang, Z. P., Sanders, A. R., et al. (2024) · medRxiv · doi:10.1101/2024.08.14.24312009 · Cited by 2 · see citing works
Self-citationscTWAS: a powerful statistical framework for single-cell transcriptome-wide association studies
Lin, Z., & Su, C. (2026) · Nature Communications · doi:10.1038/s41467-026-70374-7 · Cited by 2 · see citing works
“These include genes located in established AD GWAS loci, whosefunctionalroles in immune pathways or in microgliaaresupportedbypriorliterature(e.g., PICALM 79 , HLA-DRB1 80 , EPHA1-AS1 78 , PTK2B 81 , BIN1 82 ).”
Ruthirakuhan, M. T., Taha, A. Y., & Swardfager, W. (2026) · Journal of Neurochemistry · doi:10.1111/jnc.70492 · Cited by 1 · see citing works
Localized PD-1 CAR T therapy reprograms neuroinflammation
Shalita, R., Yehuda, M. B., Gur, C., Frid, Y., McGrath, S., Suhler, R., Bolokan, L., Eisenberg, V., Sharet-Eshed, R., Shlomi-Loubaton, S., et al. (2026) · Cell · doi:10.1016/j.cell.2026.06.036 · Cited by 1 · see citing works
Single-cell multiomics of neuron activation reveals context-specific genetics of brain disordersPreprint
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Self-citationRodríguez-Nunez, I., Bartley, S. C., Taylor, J. W., Johnston, S. Q., Rogers, B. B., Meadows, S. K., Newberry, K. M., Cochran, J. N., & Myers, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.30.657077 · Cited by 1 · see citing works
Kim, M. J., Blumenfeld, J. R., Li, Y., Yip, O., Yao, L., Ancheta, S., Leon, S. D., Platow, Z., Liang, Z., Shostak, D. M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.04.692390 · Cited by 1 · see citing works
Progranulin deficiency induces lipid droplet accumulation in microglia via a STAT3-GPAT3 axisPreprint
Li, J., Shi, Y., Guan, H., Lü, Y., Yi, T., Li, W., Wang, Y., Guo, Y., Li, B., & Zhu, C. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.17.700052 · Cited by 1 · see citing works
Thapa, C., Oh, E., Sirkin, D., Lahey, J., de León‐Guerrero, S. D., McCarroll, A., Gowda, P., Zhang, H., Barishman, A., Peyton, L., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.27.708613 · Cited by 1 · see citing works
Self-citationRevealing the nervous system requirements of Alzheimer’s disease risk genes in DrosophilaPreprint
Deger, J., Hannan, S. B., Gu, M., Strohlein, C. E., Goodman, L. D., Pasupuleti, S., Shaik, Z., Ma, L., Li, Y., Li, J., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.24.666383
Self-citationSherman, E., Qiu, K., Roberts, R., Shichman, L., Li, S., Sun, H., Ide, L., Tucker, A., Lee, S., Gniadzik, W., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.17.683162
Revealing the nervous system requirements of Alzheimer disease risk genes in Drosophila
Deger, J., Hannan, S. B., Gu, M., Strohlein, C. E., Goodman, L. D., Pasupuleti, S., Shaik, Z., Ma, L., Li, Y., Li, J., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.10.003 · Cited by 1 · see citing works
“31,81,91,102 The T2A-GAL4 / Kozak-GAL4 reagents generated as part of this study will accelerate such future investigations.”
Self-citationPCSK9 and High-Fat Diet Synergistically Induce Neurovascular Dysfunction and NeuroinflammationPreprint
Zhang, M., Letian, A., Mohl, G. A., Kroke, B., Arkelius, K., Clelland, C. D., Goldberg, E. L., & Singhal, N. S. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.29.685380
Lakhani, C. M., Cavalca, G., Liu, A., Nidumbur, R., Feng, R., Raj, T., Jager, P. L. D., Wang, G., & Knowles, D. A. (2025) · medRxiv · doi:10.64898/2025.12.03.25341562
Zhou, X., Zhang, Y., Sun, L., Kwok, C. K., & Zhang, J. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.20.700564
“Of note, the PICALM isoform has been identified as medically relevant 44,45 , which can cause abnormal lipid droplets during endocytosis due to compromised lysosomal function 46 .”
Ando, K., Lopez‐Gutierrez, L., Mansour, S., Yilmaz, Z., Dauphinot, L., Verheijen, J., Fontaine, G., Quintanilla‐Sánchez, C., Aydin, E., Doeraene, E., et al. (2026) · Cells · doi:10.3390/cells15030235
“Microglia carrying the non-protective allele exhibited reduced PICALM expression, lipid droplet accumulation, and phagocytosis deficits [63].”
InfluentialNasciben, L. B., Wang, L., Xu, W., Ramírez, A. M., Moura, S., Lu, L., Liu, X., Rajabli, F., Celis, K., Gearing, M., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.14.705927
“Consistent with the microglia - specific regulatory mechanism suggested by PU.1 occupancy (Kozlova et al., 2025), carriers of the risk allele (G) showed reduced PICALM expression, whereas the rs10792832 A/A displayed the highest expression.”
Self-citationZeng, H.-X., Li, G., Zeng, Q.-G., Zhang, Q., Liu, L., & Zeng, X.-W. (2026) · Environment & Health · doi:10.1021/envhealth.5c00701
“33 Similarly, circbabo(5,6,7,8S) was reported to regulate lipid droplet accumulation and maintain neuronal integrity through the TGF-β /ROS/JNK/SREBP signaling axis in Drosophila .”
Kim, Y. D., Vaidya, B., Kim, J., Bitar, S., Shajan, F. J., Verma, A. K., Yalamanchili, H. K., Singh, S., & Zoghbi, H. Y. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.20.726454
APOE4 and INPP5D converge on membrane mechanics to regulate endocytosis in human astrocytesPreprint
Gevorgyan, A. S., Gordon, L. M., Combs, C. A., Lita, A., Yang, L. G., Cuní‐López, C., Root, J. T., Larion, M., Taraska, J. W., & Narayan, P. S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.22.726347
Polania-Sandoval, C. A., Chandran, J., Meschia, J. F., et al. (2026) · JVS Vascular Science · doi:10.1016/j.jvssci.2026.100421
Self-citationRogers, B. B., Anderson, A. G., Rodríguez-Nunez, I., Bartley, S. C., Johnston, S. Q., Taylor, J. W., Meadows, S. K., Newberry, K. M., Myers, R., & Cochran, J. N. (2026) · iScience · doi:10.1016/j.isci.2026.116412 · Cited by 1 · see citing works
“73,86 Consistent with these motif-level observations, our cCRE-gene linkage analyses recapitulated regulatory architecture at established AD risk loci in microglia.”
Wang, P.-J., Yang, X., Ji, L., Shi, J., Cai, X., Sun, P., Liu, H.-X., Jiang, F., & Yang, F. (2026) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2026.1858299
“…numerous risk variants implicating not merely A β and Tau metabolism, but also lipid transport and innate immune pathways (Jansen et al., 2019; Kozlova et al., 2025; Kunkle et al., 2019; Novikova et al., 2021; Schwartzentruber et al., 2021), suggesting that metabolic-immune dysregulation…”
Jiang, T., Xu, X., Yu, Y., Zhu, C., Ma, C., Tang, Y., Min, L., Tan, M., Bai, J., Feng, Z., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.07.02.736008
Wang, C., Yun, Q. I., Zhang, Z., Zhao, H., Lin, F., & Cao, H. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1877167
Zou, Y., Ou, Y., Zhao, H., Chen, G., Chen, Z., Li, Y., & Jiang, J. (2026) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2026.119841 · Cited by 1 · see citing works
Oxidative stress and inflammation in neurodegenerative disorders
Jomová, K., Alomar, S. Y., Valko, R., Nepovimová, E., Kuča, K., & Valko, M. (2026) · Archives of Toxicology · doi:10.1007/s00204-026-04518-5 · Cited by 1 · see citing works
Song, M., Bu, N., Wei, L., & Chen, J. (2026) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2026.1945478
“…PICALM-dependent lipid handling, and prolonged myelin loading were similarly associated with persistent intracellular lipid, inflammatory myelin-laden phagocytes, or foam-cell-like dysfunction (Xia et al., 2025; Haidar et al., 2022; Loix et al., 2022; Kozlova et al., 2025; Ziaee et al., 2026).”
Li, J., Yue, D., Xie, W., Xiong, Z., & Wang, X. (2026) · Gene · doi:10.1016/j.gene.2026.150397
Huang, L., Cheng, P., Liu, G., Xiang, Y., Hong, Z., & Le, W. (2026) · MedComm · doi:10.1002/mco2.71017
“Additionally, other genes that increase the risk of AD including triggering receptor expressed on TREM2, clusterin (CLU), and phosphatidylinositol-binding clathrin assembly protein (PICALM), all of which also affect the integrity of the myelin sheath [ 71–73 ].”
Lysosomes as chemical and metabolic organizers of central nervous system injury and repair
Zhao, T., Huang, H., Wang, Y., Zhong, Y., Zhong, Z., Xue, D., Zhu, W., & Xu, K. (2026) · Frontiers in Chemistry · doi:10.3389/fchem.2026.1891677
“After TBI, microglia and astrocytes are involved in the handling of synaptic fragments, myelin debris and dead cells, but impaired autophagy–lysosome flux may prolong neuroinflammation and secondary injury (Bano et al., 2025; Sarkar and Lipinski, 2024; Zhang et al., 2025).”
Yang, S., Wu, D., Li, Y., et al. (2026) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2026.154628
Zhang, Z., Ning, Y., Wu, Z., Sun, J., & Gao, F. (2026) · Analytical Chemistry · doi:10.1021/acs.analchem.6c04279
From Amyloid Exposure to Genetic Causality: Converging hiPSC-Based Models of Alzheimer’s Disease
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Thapa, C., Oh, E. K., Sirkin, D., Lahey, J., de León-Guerrerro, S. D., McCarroll, A., Gowda, P., Zhang, H.-W., Barishman, A., Peyton, L., et al. (2026) · Stem Cell Reports · doi:10.1016/j.stemcr.2026.103120
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Li, S., Lu, J., Zeng, K., Lu, X., Zhang, J., Feng, S., Liang, C., Cai, Y., Yao, S., Huang, Q., et al. (2026) · Alzheimer's & Dementia · doi:10.1002/alz.71812
- Authors
- Kozlova, A., Zhang, S., Sudwarts, A., Zhang, H., Smirnou, S., Byeon, S. K., Thapa, C., Sun, X., Stephenson, K., Zhao, X., Jamison, B., Ponnusamy, M., He, X., Schneider, J. A., Pandey, A., Bennett, D. A., Pang, Z. P., Sanders, A. R., Bellen, H. J., Thinakaran, G., & Duan, J.
- Affiliations
- Endeavor Health (US)
- University of South Florida (US)
- Mayo Clinic (US)
- University of Chicago (US)
- Rush University Medical Center (US)
- Rutgers, The State University of New Jersey (US)
- Baylor College of Medicine (US)
- Corresponding author
- Thinakaran, Gopal
- Duan, Jubao
- ORCID
- Venue
- Nature
- Published
- 2025-09-03
- Volume
- 646
- Issue
- 8087
- Pages
- 1178-1186
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC11142308
- OpenAlex
- W4413946395
- Semantic Scholar
- 9ecf72980121fc7b9b3948e5c2d369f93c859949
- Cited by
- 53
- References
- 85
- Citations by year
- 2026: 38 · 2025: 12 · 2024: 3
- FWCI
- 14.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, cc-by-nc-nd)
- Research Square (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion, cc-by)
- Europe PMC (PubMed Central) (submittedVersion, cc-by-nc-nd)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- Funders
- BrightFocus Foundation
- University of Miami
- National Institutes of Health (5r01ag015819-21, R01 AG063175, R01MH106575, R01MH116281)
- Goizueta Business School, Emory University
- National Institute on Aging (P30 AG072975, U01 AG072439, R01AG063175, U01AG061356, R01 AG081374, R01 AG017917, U01AG046152, P30AG010161, RF1AG079141, R01AG073260, R01AG079141, R01-AG015819)
- National Institute of Mental Health (R01MH116281, R01 MH106575)
- National Cancer Institute (U01CA271410, P30CA015083)
- Topics
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- PICALM, Alzheimer's disease, microglia, lipid droplets, amyloid-beta uptake, cholesterol biosynthesis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-16.
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