Plcg2M28L Interacts With High Fat/High Sugar Diet to Accelerate Alzheimer’s Disease-Relevant Phenotypes in Mice
Open accessPublished version of a preprint
Abstract
Obesity is recognized as a significant risk factor for Alzheimer’s disease (AD). Studies have supported the notion that obesity accelerates AD-related pathophysiology in mouse models of AD. The majority of studies, to date, have focused on the use of early-onset AD models. Here, we evaluate the impact of genetic risk factors on late-onset AD (LOAD) in mice fed with a high fat/high sugar diet (HFD). We focused on three mouse models created through the IU/JAX/PITT MODEL-AD Center. These included a combined risk model with APOE4 and a variant in triggering receptor expressed on myeloid cells 2 ( Trem2 R47H ). We have termed this model, LOAD1. Additional variants including the M28L variant in phospholipase C Gamma 2 ( Plcg2 M28L ) and the 677C > T variant in methylenetetrahydrofolate reductase ( Mthfr 677C > T ) were engineered by CRISPR onto LOAD1 to generate LOAD1. Plcg2 M28L and LOAD1. Mthfr 677C > T . At 2 months of age, animals were placed on an HFD that induces obesity or a control diet (CD), until 12 months of age. Throughout the study, blood was collected to assess the levels of cholesterol and glucose. Positron emission tomography/computed tomography (PET/CT) was completed prior to sacrifice to image for glucose utilization and brain perfusion. After the completion of the study, blood and brains were collected for analysis. As expected, animals fed a HFD, showed a significant increase in body weight compared to those fed a CD. Glucose increased as a function of HFD in females only with cholesterol increasing in both sexes. Interestingly, LOAD1. Plcg2 M28L demonstrated an increase in microglia density and alterations in regional brain glucose and perfusion on HFD. These changes were not observed in LOAD1 or LOAD1. Mthfr 677C > T animals fed with HFD. Furthermore, LOAD1. Plcg2 M28L but not LOAD1. Mthfr 677C > T or LOAD1 animals showed transcriptomics correlations with human AD modules. Our results show that HFD affects the brain in a genotype-specific manner. Further insight into this process may have significant implications for the development of lifestyle interventions for the treatment of AD.
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Written from the paper’s full text.
TL;DR
In mice carrying late-onset Alzheimer’s disease (LOAD) risk variants, a 10-month high fat/high sugar diet (HFD) produced genotype-specific brain changes, with LOAD1.Plcg2M28L showing the strongest AD-relevant phenotypes. HFD interacted with Plcg2M28L to increase microglial density, alter brain glucose/perfusion, and align brain transcriptomes with human AD inflammatory modules, while LOAD1.Mthfr677C>T did not show these interactions.
Key findings
- HFD from 2 to 12 months increased body weight regardless of genotype; cholesterol was elevated at 8 and 12 months in all HFD strains (p < 0.0001 at JAX and IU), while glucose increased with HFD in females only. Fasting glucose exceeded 240 mg/dL only in LOAD1 HFD and LOAD1.Plcg2M28L HFD mice.
- LOAD1.Plcg2M28L females on HFD showed increased IBA1+ microglial density in cortex compared with LOAD1.Plcg2M28L on control diet; this was not seen in LOAD1.Mthfr677C>T. Brain IL-1β increased in HFD-fed LOAD1 mice, whereas LOAD1.Plcg2M28L mice had reduced brain IL-1β and IFN-γ regardless of diet and elevated plasma TNF-α in HFD males only.
- The HFD × Plcg2M28L interaction positively correlated with human AD immune-related AMP-AD modules (Consensus Cluster B) and with inflammatory LOAD subtypes across ROSMAP, MSBB, and Mayo cohorts; no significant correlation was observed for HFD × Mthfr677C>T. PET/CT showed HFD mice overall had increased brain glucose uptake and perfusion versus control diet; 15 of 27 regions explained 80% of variance in glycolysis and 13 of 27 in blood flow.
- No neuronal loss was detected, and LOAD1.Plcg2M28L HFD mice still lacked amyloid-beta plaques.
Methods
- Three congenic C57BL/6J strains were used: LOAD1 (APOE4/Trem2R47H), LOAD1.Plcg2M28L, and LOAD1.Mthfr677C>T. At 2 months, mice were randomized to control diet (6% fat) or HFD (45% fat, ResearchDiet D12451i) until 12 months; n = 10 per sex/genotype/diet unless specified, with NanoString n = 6 and PET n = 10 per sex/genotype/age.
- Outcomes included longitudinal body weight, fasting blood glucose and cholesterol at 8 and 12 months, terminal PET/CT with 18F-FDG and 64Cu-PTSM plus autoradiography, brain histology (NeuN, Iba1), cytokine panel assay, and NanoString Mouse AD panel transcriptomics.
- Analyses used mixed ANOVA for repeated measures, two-way ANOVA with Tukey’s post hoc tests, multiple regression for NanoString effects, Pearson correlations with human AMP-AD modules and LOAD subtypes, KEGG/GSEA, and PCA for imaging regions.
Limitations
- Stated: the study was not designed to determine whether diet effects are reversible; the 45% fat HFD is somewhat extreme; B6 mice do not develop overt type 2 diabetes and detailed type 2 diabetic phenotypes were not assessed, so the authors cannot rule out that the HFD × Plcg2M28L interaction is due to differential type 2 diabetes susceptibility; the mice lack amyloid-beta plaques and neuronal loss, requiring additional perturbations or aging; findings need support from human and cell-based models given reported human/mouse microglia differences.
- Evident: blood glucose levels differed between JAX and IU despite efforts to standardize housing, and microglia density data were not based on stereological analyses, which the paper notes makes them suggestive. PET/CT was not performed in LOAD1.Mthfr677C>T because no inflammatory transcriptomic interaction was found.
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Claims the paper makes
30 of 47 cited sources checked · 14 supported · 3 flagged · accuracy not yet measured
- Premisecitation
Transcriptomic analyses of brain tissue from LOAD1.Plcg2M28L or LOAD1.Mthfr677C>T mice revealed increased alignment to brain transcriptomes from human patients with AD compared to B6 or LOAD1 controls.
“Transcriptomic analyses of the brain tissue from LOAD1.Plcg2M28L or LOAD1.Mthfr677C > T mice revealed increased alignment to brain transcriptomes from human patients with AD compared to B6 or LOAD1 controls (Preuss et al., 2020).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Preuss et al., 2020 source
The Results section describes comparing brain transcriptomes from APOE4 KI, Trem2*R47H, and combined-variant mice with human AD co-expression modules, including comparisons with B6 controls. Searches for LOAD1.Plcg2M28L and LOAD1.Mthfr677C>T found no passage reporting analyses of those mice or their increased alignment relative to B6 or LOAD1 controls. No page numbers were available in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measured
- Premisecitation
LOAD1 mice provided a sensitized background for assessing additional genetic and environmental risk factors.
“Therefore, these mice provided a sensitized background for assessing additional genetic and environmental risk factors (Kotredes et al., 2021).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Kotredes et al., 2021 source
- Premisecitation
In LOAD1 mice and controls aged 24 months, age but not genotype was the major factor driving changes.
“LOAD1 mice and controls were aged 24 months and data showed age but not genotype was the major factor-driving changes in LOAD1 mice (Kotredes et al., 2021).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Kotredes et al., 2021 source
- Premisecitation
Addition of a high fat/high sugar diet exacerbates Alzheimer's disease phenotypes in mouse models relevant to early-onset AD.
“Also, the addition of an HFD exacerbated AD phenotypes in mouse models relevant to early-onset AD (Knight et al., 2014; Jones et al., 2019; Bracko et al., 2020; Robison et al., 2020; Jones et al., 2021).”
Quote in the paperSubstantial claim3 of 3 sources checked- cites Knight et al., 2014 source
The Discussion (page unavailable) reports that a high-fat diet worsened memory deficits in 3xTgAD mice, supporting the high-fat-diet part of the citing sentence. The Methods describe the diet as high-fat, not high-fat/high-sugar; the quoted claim’s added sugar qualifier is unsupported. The Discussion also reports no increase in amyloid or tau deposition, so the exacerbation shown is cognitive rather than neuropathological. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites Jones et al., 2019 source
The Discussion (page unavailable) reports that high-fat diets worsened cognitive deficits or AD pathology in some AD mouse models, which supports the general point. But this paper studied APOE knock-in mice, not an early-onset AD model, and found no robust diet-related behavioral effects in its own experiment. The cited passages also do not establish a high-sugar diet. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites Bracko et al., 2020 source
The Discussion reports that a high-fat diet increased amyloid pathology, inflammation, and behavioral deficits in APP/PS1 mice. The Methods describe the diet as high-fat but do not establish the claim’s additional “high sugar” characterization; the verbatim citing sentence itself says only “HFD.” (LLM, conf=0.84)
Experimental — accuracy not yet measured
- Premisecitation
Neuronal cell loss was not observed in LOAD1 mice, even at 24 months of age.
“Neuronal cell loss was also not observed in LOAD1 mice, even at 24 months of age (Kotredes et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Kotredes et al., 2021 source
- Findingcitation
The direction of the changes correlated with gene expression changes observed in human AD based on the AMP-AD modules.
“The direction of the changes correlated with gene expression changes observed in human AD based on the AMP-AD modules (Preuss et al., 2020).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Preuss et al., 2020 source
- Findingown data
Female LOAD1 animals had an increase in plasma IL-1β in response to an HFD that was not observed in males.
“Female LOAD1 animals had an increase in plasma IL-1β in response to an HFD that was not observed in males.”
Quote in the paperNot a substantial claim - Findingown data
The effect of HFD on fasting blood glucose was more striking in female mice from IU (p < 0.0001) compared to female mice from JAX (p = 0.165).
“The effect was more striking in female mice from IU (p < 0.0001) compared to female mice from JAX (p = 0.165).”
Quote in the paperNot a substantial claim - Findingown data
Animals fed a high fat/high sugar diet (HFD) showed a significant increase in body weight compared to those fed a control diet (CD).
“As expected, animals fed a HFD, showed a significant increase in body weight compared to those fed a CD.”
Quote in the paperSubstantial claim - Findingown data
The same changes in brain IL-1β were not observed in LOAD1.Mthfr677C > T animals.
“however, the same changes were not observed in the LOAD1.Mthfr677C > T animals.”
Quote in the paperNot a substantial claim - Findingown data
Increased IBA1+ cells were found in the cortex of female LOAD1.Plcg2M28L mice fed on HFD compared to LOAD1.Plcg2M28L on CD.
“When analyzing the number of IBA1+ cells in the brain, compared to LOAD1 mice either on the CD or HFD, we found increased IBA1+ cells in the cortex of female LOAD1.Plcg2M28L mice fed on HFD compared to LOAD1.Plcg2M28L on CD (Figure 3 and Supplementary Figure 1).”
Quote in the paperSubstantial claim - Findingown data
In LOAD1.Plcg2M28L mice, brain IL-1β and IFN-γ were significantly reduced regardless of diet.
“In LOAD1.Plcg2M28L, we found significant reductions in several proinflammatory cytokines (IL-1β, IFN-γ) in the brain regardless of diet”
Quote in the paperNot a substantial claim - Findingown data
We did not see a difference in IBA1+ cells in LOAD1.Mthfr677C > T mice.
“Interestingly, we did not see a difference in LOAD1.Mthfr677C > T mice (Figure 3)”
Quote in the paperSubstantial claim - Findingown data
Brain IL-1β was increased in HFD-fed LOAD1 animals.
“Analysis of cytokines in the brain revealed increases of IL-1β in HFD fed-LOAD1 animals (Figure 4A)”
Quote in the paperSubstantial claim - Findingown data
Glucose increased as a function of HFD in females only.
“Glucose increased as a function of HFD in females only”
Quote in the paperNot a substantial claim - Findingown data
No changes in IFN-γ were observed in the LOAD1.Mthfr677C > T study.
“No changes in IFN-γ were observed in the LOAD1. Mthfr677C > T study.”
Quote in the paperNot a substantial claim - Findingown data
Fasting serum cholesterol levels were consistently elevated at both 8 and 12 months of age in all strains fed with an HFD compared to those fed with CD independent of genotype and sex.
“Fasting serum cholesterol levels were consistently elevated at both 8 and 12 months of age in all strains fed with an HFD compared to those fed with CD independent of genotype and sex (p > 0.0001 at JAX, p > 0.0001 at IU; Figures 1F–G).”
Quote in the paperNot a substantial claim - Findingown data
LOAD1.Plcg2M28L but not LOAD1.Mthfr677C>T or LOAD1 animals showed transcriptomics correlations with human AD modules.
“Furthermore, LOAD1.Plcg2M28L but not LOAD1.Mthfr677C > T or LOAD1 animals showed transcriptomics correlations with human AD modules.”
Quote in the paperSubstantial claim - Findingown data
Fasting blood glucose levels only exceeded 240 mg/dL in mice fed with LOAD1 HFD and LOAD1.Plcg2M28L HFD.
“Fasting blood glucose levels only exceeded 240 mg/dL (a level that previous studies consider B6 mice to be diabetic (Xiang et al., 2021) in mice fed with LOAD1 HFD and LOAD1.Plcg2M28L HFD.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Xiang et al., 2021 source
- Findingown data
Mice fed on HFD gained more weight compared to those fed on CD, irrespective of genotype.
“Mice fed on HFD gained more weight compared to those fed on CD, irrespective of genotype (Figures 1B,C).”
Quote in the paperNot a substantial claim - Findingown data
HFD had a significant effect on fasting blood glucose in female mice but not male mice in both studies.
“In both studies, there was a significant effect of HFD in female, but not male mice fed on HFD.”
Quote in the paperNot a substantial claim - Findingown data
Cholesterol increased in both sexes as a function of HFD.
“with cholesterol increasing in both sexes.”
Quote in the paperNot a substantial claim - Findingown data
A significant increase in TNF-a was observed in LOAD1 males but not in females.
“In addition, a significant increase in TNF-a was observed in LOAD1 males but not in females (Figure 4C).”
Quote in the paperNot a substantial claim - Findingown data
In both LOAD1.MthfrC677T and LOAD1.Plcg2M28L animals, there was no quantitative difference in the density of neurons in either genotype when comparing the CD to the HFD.
“In both LOAD1.MthfrC677T and LOAD1.Plcg2M28L animals, there was no quantitative difference in the density of neurons in either genotype when comparing the CD to the HFD (Figure 2).”
Quote in the paperSubstantial claim - Findingown data
In the plasma of LOAD1.Plcg2M28L mice, there was a significant increase in TNF-a in mice fed on HFD.
“In contrast, in the plasma of LOAD1.Plcg2M28L mice, we found a significant increase in TNF-a (Figure 4I) in mice fed on HFD.”
Quote in the paperSubstantial claim - Findingown data
The reductions in brain IL-1β and IFN-γ in LOAD1.Plcg2M28L mice were inversely correlated with plasma levels.
“which was inversely correlated with plasma (Figures 4D–F).”
Quote in the paperNot a substantial claim - Findingown data
Interaction between Plcg2M28L and HFD displayed significant positive correlation with immune-related modules in Consensus Cluster B.
“while interaction between Plcg2M28L and HFD displayed significant positive correlation (p < 0.05)”
Quote in the paperSubstantial claim - Findingown data
Neuronal loss was not detected in LOAD1.Plcg2M28L mice on an HFD, at least in the brain regions assessed up to 12 months of age.
“Also, neuronal loss was not detected in LOAD1.Plcg2M28L mice on an HFD, at least in the brain regions assessed up to 12 months of age, suggesting additional pathways/processes need to be perturbed likely in combination with extended aging to further align these models to human LOAD.”
Quote in the paperSubstantial claim - Findingown data
A total of 99 genes were extracted that exhibited directional coherence for interaction between HFD and Plcg2M28L in mice and change in expression in AMP-AD modules in Consensus Cluster A.
“A total of 99 genes were extracted that exhibited directional coherence for interaction between HFD and Plcg2M28L in mice and change in expression in AMP-AD modules in Consensus Cluster A, such as Aldh2, Aldh6a1, Aldh7a1, lamb2, Rab31, and Sox9 (Supplementary File 3).”
Quote in the paperSubstantial claim - Findingown data
HFD mice showed overall increased perfusion compared to CD mice.
“Interestingly, an HFD mice showed overall increased perfusion compared to CD mice.”
Quote in the paperNot a substantial claim - Findingown data
The effect of the Mthfr677C > T variant showed a significant positive correlation with the inflammatory subtypes across all three cohorts.
“The effect of the Mthfr677C > T variant showed a significant positive correlation (p < 0.05) with the inflammatory subtypes across all three cohorts”
Quote in the paperNot a substantial claim - Findingown data
We identified a total of 192 genes that exhibit a directional coherence between interaction with HFD and Plcg2M28L in mice and a change in the expression in immune-associated AMP-AD modules in Consensus Cluster B.
“We identified a total of 192 genes that exhibit a directional coherence between interaction with HFD and Plcg2M28L in mice and a change in the expression in immune-associated AMP-AD modules in Consensus Cluster B, including microglia-related genes, such as Trem2, Tyrobp, Cldn5, and C1qc (Figure 5E and Supplementary File S3).”
Quote in the paperSubstantial claim - Findingown data
In LOAD1 and LOAD1.Mthfr677C>T animals, TNF-α and IL-1β were upregulated in LOAD1 animals fed HFD, but not in LOAD1.Plcg2M28L animals.
“In the LOAD1 and LOAD1. Mthfr677C > T animals, TNF-a and IL-1b were upregulated in LOAD1 animals fed HFD, but not the LOAD1.Plcg2M28L animals.”
Quote in the paperSubstantial claim - Findingown data
PCA analysis for blood flow determined 13 of the 27 brain regions explained 80 percent of the variance in blood flow in all mice and all conditions.
“Utilizing PCA analysis again for blood flow analysis, 13 of the 27 brain regions explained 80 percent of the variance in blood flow in all mice and all conditions (Figures 6D,E).”
Quote in the paperNot a substantial claim - Findingown data
An interaction between Plcg2M28L and HFD exhibited significant positive correlation with extracellular matrix organization-related module in Consensus Cluster A and neuronal system-associated modules in Consensus Cluster C.
“In addition, an interaction between Plcg2M28L and HFD also exhibited significant positive correlation (p < 0.05) with extracellular matrix organization- related module in Consensus Cluster A and neuronal system-associated modules in Consensus Cluster C (Figure 5A).”
Quote in the paperSubstantial claim - Findingown data
PCA comparing sex, genotype, and age determined 15 of the 27 brain regions that explained 80 percent of the variance in brain glycolysis in all mice and all conditions.
“PCA comparing sex, genotype, and age determined 15 of the 27 brain regions that explained 80 percent of the variance in brain glycolysis in all mice and all conditions (Figures 6B,C).”
Quote in the paperNot a substantial claim - Findingown data
No significant correlation was observed for interaction between HFD and Mthfr677C > T risk variant.
“while no significant correlation was observed for interaction between HFD and Mthfr677C > T risk variant (Figure 5B).”
Quote in the paperNot a substantial claim - Findingown data
The interaction between HFD and Plcg2M28L risk variant showed a strong significant positive correlation with the inflammatory subtypes across all three cohorts.
“Notably, the interaction between HFD and Plcg2M28L risk variant showed a strong significant positive correlation (p < 0.05) with the inflammatory subtypes across all three cohorts”
Quote in the paperSubstantial claim - Findingown data
The Plcg2M28L:HFD interaction resulted in changes in the expression of genes enriched for inflammatory pathways.
“These analyses indicated Plcg2M28L:HFD (interaction) resulted in changes in the expression of genes enriched for inflammatory pathways.”
Quote in the paperSubstantial claim - Findingown data
Genes that showed directional coherence for the interaction between HFD and Plcg2M28L in mice and human co-expression modules in Consensus Cluster A were enriched for "Regulation of actin cytoskeleton," "fatty acid degradation," and multiple "metabolism" associated pathways.
“Genes that showed directional coherence for the interaction between HFD and Plcg2M28L in mice and human co-expression modules in Consensus Cluster A were enriched for “Regulation of actin cytoskeleton,” “fatty acid degradation,” and multiple “metabolism” associated pathways (Figure 5C).”
Quote in the paperSubstantial claim - Findingown data
We observed clear discrimination between genetic variants with and without interaction with HFD along the first principal component (accounting for around 59% of total variation).
“We observed clear discrimination between genetic variants with and without interaction with HFD along the first principal component (accounting for around 59% of total variation) (Supplementary Figure 2D).”
Quote in the paperNot a substantial claim - Findingown data
The GSEA identified upregulation of Alzheimer's disease, focal adhesion pathways in presence of each perturbation except Mthfr677C > T.
“The GSEA identified upregulation of Alzheimer’s disease, focal adhesion pathways in presence of each perturbation except Mthfr677C > T (Supplementary Figure 2).”
Quote in the paperNot a substantial claim - Findingreasoning
LOAD1.Plcg2M28L mice fed HFD still lack amyloid-beta plaques.
“Despite the increased alignment at the gene expression of LOAD1.Plcg2M28L on an HFD to human LOAD compared to strain-matched mice fed on CD, LOAD1.Plcg2M28L mice fed on HFD still lack amyloid-beta plaques.”
Quote in the paperSubstantial claim- Rests on an assumption: Mice require mutations or engineering of the human sequence to drive plaque deposition, and neither is present in these mice.
- Findingown data
Plcg2M28L displayed significant negative correlation with immune-related modules in Consensus Cluster B.
“Furthermore, Plcg2M28L displayed significant negative correlation (p < 0.05) with immune-related modules in Consensus Cluster B”
Quote in the paperNot a substantial claim - Findingown data
PCA using gene set enrichment score (NES) revealed HFD as the main effect in mice.
“Moreover, PCA using gene set enrichment score (NES) revealed HFD as the main effect in mice.”
Quote in the paperNot a substantial claim - Findingown data
In the present study, alterations in several peripheral cytokines including IL-1β, IFN-γ, and TNF-α were found in only the LOAD1.Plcg2M28L animals.
“In the present study, we found alterations in several peripheral cytokines including IL-1β, IFN-γ, and TNF-α in only the LOAD1.Plcg2M28L animals.”
Quote in the paperSubstantial claim - Findingown data
For both male and female mice, we observed a significant positive correlation between some of the immune-related modules in Consensus Cluster B and interaction between Plcg2M28L and HFD.
“For both male and female mice, we observed a significant positive correlation between some of the immune-related modules in Consensus Cluster B and interaction between Plcg2M28L and HFD (Supplementary Figures 2A,B).”
Quote in the paperSubstantial claim - Findingown data
Genes that showed directional coherence for interaction between HFD and Plcg2M28L in mice and human co-expression modules in Consensus Cluster B were enriched for multiple KEGG pathways, such as "Tight junction," "Hippo signaling pathway," "Lysosome," and "phagocytosis" pathways.
“Genes that showed directional coherence for interaction between HFD and Plcg2M28L in mice and human co-expression modules in Consensus Cluster B were enriched for multiple KEGG pathways, such as “Tight junction,” “Hippo signaling pathway,” “Lysosome,” and “phagocytosis” pathways (Figure 5D).”
Quote in the paperSubstantial claim - Findingown data
The effect of Plcg2M28L and HFD showed a significant positive correlation with the non-inflammatory subtype B in the ROSMAP and MSBB cohorts.
“while the effect of Plcg2M28L and HFD showed a significant positive correlation (p < 0.05) with the non-inflammatory subtype B in the ROSMAP and MSBB cohorts (Figure 4B).”
Quote in the paperSubstantial claim - Findingown data
HFD mice show overall increased glucose uptake compared to CD mice.
“Interestingly, an HFD mice show overall increased glucose uptake compared to CD mice.”
Quote in the paperNot a substantial claim - Findingown data
TNF-α, IL-1β, and IFN-γ were downregulated in LOAD1.Plcg2M28L female brains, regardless of diet.
“However, TNF-α, IL-1β, and IFN-γ were downregulated in LOAD1.Plcg2M28L female brains, regardless of the diet.”
Quote in the paperSubstantial claim - Findingown data
Plcg2M28L displayed significant positive correlation with neuronal system-associated modules in Consensus Cluster C.
“Moreover, Plcg2M28L displayed significant positive correlation (p < 0.05) with neuronal system-associated modules in Consensus Cluster C (Figure 5A).”
Quote in the paperNot a substantial claim - Findingown data
Increases in microglial number were observed in female LOAD1.Plcg2M28L mice only in the hippocampus of HFD animals.
“Although we observed increases in the microglial number in female LOAD1.Plcg2M28L mice, this was only in the hippocampus of HFD animals, suggesting a potential compensatory effect.”
Quote in the paperNot a substantial claim - Findingown data
LOAD1.Plcg2M28L on HFD showed increased alignment at gene expression to human LOAD compared to strain-matched mice fed CD.
“Despite the increased alignment at the gene expression of LOAD1.Plcg2M28L on an HFD to human LOAD compared to strain-matched mice fed on CD, LOAD1.Plcg2M28L mice fed on HFD still lack amyloid-beta plaques.”
Quote in the paperSubstantial claim - Findingown data
In the present study, alterations in FDG activity were observed in multiple brain areas in LOAD1.Plcg2M28L mice.
“In the present study, we observed alterations in FDG activity in multiple brain areas in LOAD1.Plcg2M28L mice.”
Quote in the paperSubstantial claim - Findingown data
Both risk variants, Mthfr677C > T and Plcg2M28L, exhibited significant positive correlations with cell cycle and myelination-associated modules in Consensus Cluster D and cellular stress-response associated modules in Consensus Cluster E.
“Both risk variants, Mthfr677C > T and Plcg2M28L exhibited significant positive correlations (p < 0.05) with cell cycle and myelination-associated modules in Consensus Cluster D and cellular stress-response associated modules in Consensus Cluster E (Figure 4A).”
Quote in the paperSubstantial claim - Findingown data
In the present study, transcriptomic changes were observed in the neuroinflammation module.
“In the present study, transcriptomic changes were observed in the neuroinflammation module, indicative of alterations in the microglial function.”
Quote in the paperSubstantial claim - Findingown data
The interaction between Mthfr677C>T and HFD did not result in gene expression changes relating to inflammation.
“Interestingly, the interaction between Mthfr677C > T and HFD did not result in gene expression changes relating to inflammation and therefore PET/CT was not performed in LOAD1.Mthfr677C > T mice.”
Quote in the paperSubstantial claim - Interpretationown data
The HFD-induced neuroinflammatory reaction is specific to the LOAD1.Plcg2M28L genotype.
“suggesting an HFD-induced neuroinflammatory reaction that is specific to the LOAD1.Plcg2M28L genotype.”
Quote in the paperSubstantial claim- Rests on an assumption: The second hallmark of LOAD is neuroinflammation, particularly microglia activation.
- Rests on an assumption: In our previous study, LOAD1 mice did not show microglia activation.
- Interpretationown data
The effects of HFD were most severe in the presence of Plcg2M28L.
“In particular, the effects of the HFD were most severe in the presence of Plcg2M28L.”
Quote in the paperSubstantial claim - Interpretationown data
The effects of HFD consumption to midlife were not uniform across all models but dependent on specific genetic risk factors.
“Results showed that the effects of consumption of HFD to midlife were not uniform across all models but dependent on specific genetic risk factors.”
Quote in the paperSubstantial claim - Interpretationown data
HFD affects the brain in a genotype-specific manner.
“Our results show that HFD affects the brain in a genotype-specific manner.”
Quote in the paperSubstantial claim - Interpretationown data
The transcriptomic changes in the neuroinflammation module are indicative of alterations in microglial function.
“In the present study, transcriptomic changes were observed in the neuroinflammation module, indicative of alterations in the microglial function.”
Quote in the paperSubstantial claim- Rests on an assumption: Many inflammation genes, including Csf1, Tgfbr2, Fcer1g, Trem2, and Tyrobp, are expressed by microglia.
- Interpretationreasoning
The interaction between Plcg2M28L and HFD is driven by changes in microglial function.
“However, unlike Plcg2M28L, a function for MTHFR in microglia has not been reported, further suggesting the interaction between Plcg2M28L and HFD is driven by changes in microglial function.”
Quote in the paperSubstantial claim- Rests on an assumption: Many inflammation genes, including Csf1, Tgfbr2, Fcer1g, Trem2, and Tyrobp, are expressed by microglia.
- Rests on an assumption: PLCG2 is a critical signaling element for various immune receptors and a key regulatory hub gene for immune signaling.
- Rests on an assumption: The HFD used in this study creates a more inflammatory environment in the brain, causing microglia activation.
- Rests on an assumption: A function for MTHFR in microglia has not been reported.
- Interpretationown data
Several regions that showed increased glucose metabolism and increased blood perfusion in a genotype-dependent manner are involved in memory and behavior.
“Several regions that showed increased glucose metabolism and increased blood perfusion in a genotype-dependent manner are involved in memory and behavior.”
Quote in the paperSubstantial claim - Interpretationown data
We observed AD relevant phenotypes in mice for an interaction between HFD and Plcg2M28L risk variant.
“Overall, we observed AD relevant phenotypes in mice for an interaction between HFD and Plcg2M28L risk variant.”
Quote in the paperSubstantial claim- Rests on an assumption: A hallmark of LOAD and other dementias is the loss of neurons, particularly in the cortex and hippocampus.
- Rests on an assumption: The second hallmark of LOAD is neuroinflammation, particularly microglia activation.
- Premisecitation
In patients with AD, increases in glucose uptake were observed with an increase in microglial activity using TSPO-PET.
“In patients with AD, glucose uptake was measured using FDG-PET, and increases in glucose uptake were observed with an increase in the microglial activity (utilizing TSPO-PET) (Xiang et al., 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Xiang et al., 2021 source
- Interpretationreasoning
There is a difference in the peripheral and central immune responses to an HFD.
“suggesting that there is a difference in the peripheral and central immune responses to an HFD.”
Quote in the paperNot a substantial claim - Interpretationown data
Interaction with HFD increased neuroinflammation in mice carrying the Plcg2M28L risk variant.
“suggesting interaction with HFD increased neuroinflammation in mice carrying the Plcg2M28L risk variant (Figure 5A).”
Quote in the paperSubstantial claim- Rests on an assumption: The second hallmark of LOAD is neuroinflammation, particularly microglia activation.
- Interpretationreasoning
The present study suggests that FDG-PET may provide evidence for the microglial state in vivo.
“The present study suggests that FDG-PET may provide evidence for the microglial state in vivo.”
Quote in the paperSubstantial claim - Interpretationown data
These data support a functional consequence of the observed interaction between HFD and Plcg2M28L by IHC and transcriptomics.
“These data support a functional consequence of the observed interaction between HFD and Plcg2M28L by IHC and transcriptomics.”
Quote in the paperSubstantial claim - Interpretationown data
Mice homozygous for the Plcg2M28L risk variant on a LOAD1 background showed more extreme AD phenotypes compared to either LOAD1 mice or LOAD1 mice homozygous for Mthfr677C > T.
“The results supported our hypothesis, with mice homozygous for the Plcg2M28L risk variant on a LOAD1 background showing more extreme AD phenotypes compared to either LOAD1 mice or LOAD1 mice homozygous for Mthfr677C > T.”
Quote in the paperSubstantial claim- Rests on an assumption: A hallmark of LOAD and other dementias is the loss of neurons, particularly in the cortex and hippocampus.
- Rests on an assumption: The second hallmark of LOAD is neuroinflammation, particularly microglia activation.
- Interpretationown data
The mechanisms driving the interaction between HFD and Plcg2M28L may be due to a combination of peripheral and central factors, likely involving microglia responses, that conspire to increase the alignment of brain transcriptomes to human LOAD.
“Taken together, these data suggest the mechanisms driving the interaction between HFD and Plcg2M28L may be due to a combination of peripheral and central factors (likely involving microglia responses) that conspire to increase the alignment of brain transcriptomes to human LOAD.”
Quote in the paperSubstantial claim- Rests on an assumption: Many inflammation genes, including Csf1, Tgfbr2, Fcer1g, Trem2, and Tyrobp, are expressed by microglia.
- Rests on an assumption: PLCG2 is a critical signaling element for various immune receptors and a key regulatory hub gene for immune signaling.
- Rests on an assumption: The HFD used in this study creates a more inflammatory environment in the brain, causing microglia activation.
- Interpretationown data
The interactions observed here that correlate with LOAD in the human population suggest that the effects of an HFD are genotype-specific.
“The interactions we have observed here that correlate with LOAD in the human population suggest that the effects of an HFD are genotype-specific and further investigation is needed to resolve the mechanistic interactions between genetics and diet.”
Quote in the paperSubstantial claim
- May combine two claims. 19
- Classified as probably not a substantial claim. 37
May combine two claims.
Study design and conductcitationAll strains were validated using brain RNA-seq to confirm no off-target effects and no alterations in target transcript isoforms or expression levels.
“All strains were validated using brain RNA-seq to confirm no off-target effects and no alterations in target transcript isoforms/expression levels (Kotredes et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Kotredes et al., 2021 source
The paper reports brain RNA-seq in Materials and Methods (RNA-Sequencing Experimental Design), but it does not say that this confirmed an absence of off-target effects. More decisively, the Discussion reports that the Trem2*R47H mutation created a novel splice site and reduced Trem2 transcript levels by approximately 20%—the opposite of the claimed absence of changes in target isoforms or expression. Page numbers are not available in our copy. (LLM, conf=0.93)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPrevious HFD studies have been associated with increased microglial activity in wild-type mice.
“Previous HFD studies have been associated with increased microglial activity in wild-type mice (Rivera et al., 2013; Wanrooy et al., 2018).”
Quote in the paperNot a substantial claim2 of 2 sources checked- cites Rivera et al., 2013 source
The Results (Figure 9; page unavailable) report significantly more Iba1-positive microglial cells in the hippocampi of HFD-fed rats, supporting the association with increased microglial activity. The cited study examined rats, not wild-type mice, so it does not support that population-specific part of the claim. (LLM, conf=0.88)
Experimental — accuracy not yet measured - cites Wanrooy et al., 2018 source
The Results section (“Hyperglycemia increases microglia numbers and activates astrocytes”; page unavailable) reports increased hippocampal microglia in mice given STZ on a control diet, but not in either high-fat-diet group. The paper therefore does not support citing its HFD findings as evidence of increased microglial activity in wild-type mice; its measured outcome was microglial number rather than activity. (LLM, conf=0.78)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationAlthough APOE4 and TREM2R47H are strong genetic risk factors for LOAD in humans, TREM2R47H may be reducing the effect of the APOE4 variant when present together.
“However, data now suggest that although APOE4 and TREM2R47H are strong genetic risk factors for LOAD in humans, TREM2R47H may be reducing the effect of the APOE4 variant when present together (Kotredes et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Kotredes et al., 2021 source
The Discussion states the opposite direction of effect: APOEε4 suppresses effects associated with Trem2*R47H, including its transcriptional and inflammatory responses in the mouse models. The paper also reports emerging evidence that APOEε4 carriers may not have increased AD risk from Trem2*R47H; it does not say Trem2*R47H reduces the effect of APOEε4. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationMetabolic syndrome increases the risk for Type 2 diabetes, cardiovascular disease, and Alzheimer's disease.
“Metabolic syndrome increases the risk for Type 2 diabetes and cardiovascular disease, and AD (Kivipelto et al., 2001; Luchsinger et al., 2004; Cordain et al., 2005; Whitmer et al., 2008).”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Kivipelto et al., 2001 source
- cites Luchsinger et al., 2004 source
- cites Cordain et al., 2005 source
The Glycemic load and Glycemic index sections link metabolic syndrome and insulin resistance with coronary heart disease and type 2 diabetes. The paper does not address Alzheimer’s disease in the passages found, so it does not support that part of the claim. Page numbers were not available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Classified as probably not a substantial claim. May combine two claims.
PremisecitationEarly dysregulation of inflammation in APOE4 brains could predispose to CNS damage from various insults, including diet, and later results in increased CNS damage normally associated with the APOE4 genotype.
“A second study concluded that early dysregulation of inflammation in APOE4 brains could predispose to CNS damage from various insults, including diet, and later results in the increased CNS damage normally associated with the APOE4 genotype (Jones et al., 2021).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Jones et al., 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Interpretationown dataThese data are consistent with the induction of diet-induced obesity (DIO) that has been previously reported for B6 mice.
“These data are consistent with the induction of diet-induced obesity (DIO) that has been previously reported for B6 mice (Wanrooy et al., 2018).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Wanrooy et al., 2018 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMany individuals are likely to develop LOAD due to a combination of genetic and environmental factors.
“Studies also suggest that genetic factors may only contribute between 50 and 70% of the risk for LOAD, meaning many individuals are likely to develop LOAD due to a combination of genetic and environmental factors (Kawahara et al., 2017; Sarkar et al., 2019; Rahman et al., 2020; Kim et al., 2021).”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Kawahara et al., 2017 source
- cites Sarkar et al., 2019 source
The Introduction (page unavailable) says that Alzheimer’s disease has a multifactorial etiology and links environmental metal exposure to AD. It does not specifically address late-onset Alzheimer’s disease (LOAD), establish a combined genetic-and-environmental risk for individuals, or give the cited 50–70% genetic-risk estimate. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites Rahman et al., 2020 source
Classified as probably not a substantial claim.
PremisecitationObesity increases the risk for late-onset Alzheimer's disease (LOAD) and other dementias.
“Studies have shown that diet, obesity, cardiovascular diseases, hypertension, physical activity, diabetes, educational attainment, smoking, and traumatic brain injury increase the risk for LOAD and other dementias (Ebbert et al., 2014; Baumgart et al., 2015; Xu et al., 2015; Wajman et al., 2018).”
Quote in the paperSubstantial claim2 of 3 sources checked- cites Ebbert et al., 2014 source
The Introduction and Abstract > Methods describe genetic risk alleles and LOAD prediction, not obesity. A search for obesity, body mass index, and lifestyle risk factors found no passage in our copy linking obesity to LOAD or other dementias. (LLM, conf=0.72)
Experimental — accuracy not yet measured - cites Baumgart et al., 2015 source
Section 3.2, “Mid-life obesity,” reports that mid-life obesity is associated with increased dementia risk. The claim omits that age qualifier and states an increase in risk more definitively than the paper does: the same section notes that obesity in later life may be associated with reduced risk, while Section 2 describes evidence for modifiable factors and dementia as inconclusive. (LLM, conf=0.87)
Experimental — accuracy not yet measured - cites Xu et al., 2015
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Classified as probably not a substantial claim.
PremisecitationChronic inflammation greatly increases the risk for LOAD.
“Chronic inflammation has been shown to greatly increase the risk for LOAD (Furman et al., 2019).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Furman et al., 2019 source
The section “Systemic chronic inflammation and non-communicable disease risk” lists neurodegenerative diseases among the risks associated with systemic chronic inflammation. It also reports lower Alzheimer’s disease risk among rheumatoid arthritis patients treated with etanercept. Neither passage establishes that chronic inflammation greatly increases the risk of late-onset Alzheimer’s disease (LOAD) specifically; page numbers are not available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationBehavioral deficits were not observed due to HFD, suggesting that metabolic responses to HFD are dependent on both sex and APOE genotype.
“Behavioral deficits were not observed due to HFD, suggesting that metabolic responses to HFD are dependent on both sex and APOE genotype.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Jones et al., 2019 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationPET images were corrected for radionuclide decay, tissue attenuation, detector dead-time loss, and photon scatter.
“In all cases, images were corrected for radionuclide decay, tissue attenuation, detector dead-time loss, and photon scatter according to the manufacturer’s methods (Krishnamoorthy et al., 2018).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Krishnamoorthy et al., 2018 source
In Materials and Methods (NEMA NU-4 evaluation; page unavailable), the paper says CT data were used for PET attenuation and scatter corrections and that images were reconstructed with all available PET data corrections. Scanner Calibrations (page unavailable) describes a dead-time correction. Our copy does not explicitly identify radionuclide-decay correction or establish that the citing study applied every listed correction in all cases. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationWith HFD, male APOE4 mice were more susceptible to metabolic disturbances, including glucose intolerance, compared to APOE3 mice.
“In one study, Jones et al. (2019) found that with HFD, male APOE4 mice were more susceptible to metabolic disturbances, including glucose intolerance when compared to APOE3 mice.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Jones et al., 2019 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationGenetic factors may contribute only between 50 and 70% of the risk for LOAD.
“Studies also suggest that genetic factors may only contribute between 50 and 70% of the risk for LOAD, meaning many individuals are likely to develop LOAD due to a combination of genetic and environmental factors (Kawahara et al., 2017; Sarkar et al., 2019; Rahman et al., 2020; Kim et al., 2021).”
Quote in the paperNot a substantial claim1 of 3 sources checked- cites Kawahara et al., 2017 source
- cites Sarkar et al., 2019 source
The Introduction (page not provided) says that the etiology of Alzheimer’s disease is multifactorial, which supports the broad point that factors beyond genetics may be involved. It does not give a 50–70% estimate for genetic risk or specifically address late-onset Alzheimer’s disease (LOAD); searches for those terms found no supporting passage. (LLM, conf=0.83)
Experimental — accuracy not yet measured - cites Rahman et al., 2020 source
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationB6 mice homozygous or heterozygous for Mthfr677C>T show reduced enzyme activity in both the liver and brain, elevated levels of homocysteine, cerebral blood flow deficits, reduced collagen 4 in the brain, and neurovascular damage by electron microscopy.
“Supporting a role for MTHFR in the cerebrovascular function, B6 mice homozygous or heterozygous for Mthfr677C > T show reduced enzyme activity in both the liver and brain, elevated levels of homocysteine, cerebral blood flow deficits, reduced collagen 4 in the brain, and neurovascular damage by electron microscopy (Reagan et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Reagan et al., 2021 source
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationE4FAD (APOE4+5xFAD) mice show increased amyloid deposition, specifically more compact plaques, compared to E3FAD (APOE3+5xFAD) mice.
“Previous studies support this, with E4FAD (APOE4+5xFAD) mice showing increased amyloid deposition, specifically more compact plaques, compared to E3FAD (APOE3+5xFAD) mice (Youmans et al., 2012).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Youmans et al., 2012 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationReduced PLCG2 gene expression drives distinct transcriptional phenotypes of microglia in the presence of amyloid pathology.
“A previous study has reported that reduced PLCG2 gene expression alters microglial phenotypes in 5XFAD mice, affects plaque pathology, and drives distinct transcriptional phenotypes of microglia in the presence of amyloid pathology (Tsai et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Tsai et al., 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe role of PLCG2 has not yet been comprehensively explored.
“However, the role of PLCG2 has not yet been comprehensively explored (Tsai et al., 2021; Maguire et al., 2021).”
Quote in the paperNot a substantial claim2 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationReduced PLCG2 gene expression alters microglial phenotypes in 5XFAD mice.
“A previous study has reported that reduced PLCG2 gene expression alters microglial phenotypes in 5XFAD mice, affects plaque pathology, and drives distinct transcriptional phenotypes of microglia in the presence of amyloid pathology (Tsai et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Tsai et al., 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationReduced PLCG2 gene expression affects plaque pathology in 5XFAD mice.
“A previous study has reported that reduced PLCG2 gene expression alters microglial phenotypes in 5XFAD mice, affects plaque pathology, and drives distinct transcriptional phenotypes of microglia in the presence of amyloid pathology (Tsai et al., 2021).”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Tsai et al., 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataBlood glucose levels were slightly lower in all mice housed at JAX compared to IU.
“In general, blood glucose levels were slightly lower in all mice housed at JAX (Figure 1D) compared to IU (Figure 1E) which may be due to differences in environment, despite efforts to standardize housing conditions.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataLOAD1.Plcg2M28L mice demonstrated an increase in microglia density and alterations in regional brain glucose and perfusion on HFD.
“Interestingly, LOAD1.Plcg2M28L demonstrated an increase in microglia density and alterations in regional brain glucose and perfusion on HFD.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe increase in microglia density and alterations in regional brain glucose and perfusion were not observed in LOAD1 or LOAD1.Mthfr677C>T animals fed HFD.
“These changes were not observed in LOAD1 or LOAD1.Mthfr677C > T animals fed with HFD.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataMultiple immune-related pathways were upregulated and synaptic associated pathways, such as GABAergic synapse, and axon guidance were downregulated in the presence of HFD and interaction between HFD and Plcg2M28L.
“Multiple immune-related pathways were upregulated and synaptic associated pathways, such as GABAergic synapse, and axon guidance were downregulated in the presence of HFD and interaction between HFD and Plcg2M28L (Supplementary Figure 1).”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThis study revealed an increase in microgliosis in the hippocampus of LOAD1.Plcg2M28L mice, but not in LOAD1.Mthfr677C>T.
“Consistent with the transcriptomic changes, this study revealed an increase in microgliosis in the hippocampus of LOAD1.Plcg2M28L mice, but not in LOAD1.Mthfr677C > T.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataIn LOAD1.Plcg2M28L mice, plasma IL-1β was reduced in males and plasma IFN-γ was reduced in females.
“However, there was a reduction in IL-1β (LOAD1.Plcg2M28L males) and IFN-γ (LOAD1.Plcg2M28L females)”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe effects were stronger in females as we observed a significant positive correlation with immune modules associated with the PHG brain region in females, which was not significant in male mice.
“However, the effects were stronger in females as we observed a significant positive correlation (p < 0.05) with immune modules associated with the PHG brain region as well in females, which was not significant (p > 0.05) in male mice.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataThe second principal component accounts for 25% of the total variance and separated Mthfr677C > T and interaction between HFD and Plcg2M28L factors from other factors.
“The second principal component accounts for 25% of the total variance and separated Mthfr677C > T and interaction between HFD and Plcg2M28L factors from other factors (Supplementary Figure 2).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Findingown dataSome of those changes were observed in this study.
“Some of those changes were observed in this study (Figure 1).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataAutoradiography provided secondary confirmation of the in vivo PET images.
“To provide secondary confirmation of the in vivo PET images, and to quantify tracer uptake regionally, the brains were extracted post rapid decapitation, gross sectioned along the midline, slowly frozen on dry ice, then embedded in cryomolds with optimal cutting temperature (OCT) compound (Tissue-Tek).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoningThese data are not collected based on stereological analyses and are therefore suggestive of a reduced density of IBA1+ cells.
“These data are not collected based on stereological analyses and are therefore suggestive of a reduced density of IBA1+ cells.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenUnless specified, n = 10 for each sex, genotype, and diet were used.
“Unless specified, n = 10 for each sex, genotype, and diet were used.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductown dataExperimental cohorts were randomized into two groups at 2 months of age.
“At 2 months of age (mos), experimental cohorts were randomized into two groups: Group 1 continued on CD ad libitum and Group 2 was provided with ResearchDiet® feed D12451i (45% of high fat; 35% of carbohydrates, HFD3) ad libitum.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataPathways were determined to be significant after multiple testing corrections (FDR adjusted p < 0.05).
“Pathways were determined to be significant after multiple testing corrections (FDR adjusted p < 0.05).”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThese data suggest HFD-induced features of some metabolic syndrome, potentially in a sex-specific manner, but independent of genotype.
“Collectively, these data suggest HFD-induced features of some metabolic syndrome, potentially in a sex-specific manner, but independent of genotype.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenWhere possible, all housing and procedures were standardized and aligned across sites.
“Where possible, all housing and procedures were standardized and aligned across sites.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductcitationPET and CT images were co-registered using a mutual information-based normalized entropy algorithm and mapped to stereotactic mouse brain coordinates.
“Post-acquisition, all PET and CT images were co-registered using a mutual information-based normalized entropy algorithm (Studholme et al., 1998) with 12 degrees of freedom and mapped to stereotactic mouse brain coordinates (Franklin and Paxinos, 2013).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Studholme et al., 1998 source
- cites Franklin and Paxinos, 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataFindings were confirmed using autoradiography.
“Findings were confirmed using autoradiography.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenA detailed assessment of Type 2 diabetic phenotypes was not performed here.
“However, a detailed assessment of Type 2 diabetic phenotypes was not performed here.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenOur study was not designed to determine whether the changes are reversible.
“However, our study was not designed to determine whether the changes are reversible.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationRecent in vivo imaging studies have suggested that microglia displayed higher glucose uptake than neurons and astrocytes.
“Recent in vivo imaging studies have suggested that microglia displayed higher glucose uptake than neurons and astrocytes (Xiang et al., 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Xiang et al., 2021 source
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationVariations in MTHFR, particularly the Mthfr677C>T variant, are associated with cardiovascular diseases, AD, and vascular dementia.
“Variations in MTHFR, particularly the Mthfr677C > T variant, are associated with cardiovascular diseases, AD, and vascular dementia (Liu et al., 2010; Liew and Gupta, 2015; Rai, 2017).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S2 (checkable).
Interpretationown dataAdditional pathways/processes need to be perturbed, likely in combination with extended aging, to further align these models to human LOAD.
“Also, neuronal loss was not detected in LOAD1.Plcg2M28L mice on an HFD, at least in the brain regions assessed up to 12 months of age, suggesting additional pathways/processes need to be perturbed likely in combination with extended aging to further align these models to human LOAD.”
Quote in the paperNot a substantial claim- Rests on an assumption: Mice require mutations or engineering of the human sequence to drive plaque deposition, and neither is present in these mice.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningWe cannot rule out that the interaction between HFD and Plcg2M28L observed in the brain is due to increased susceptibility to Type 2 diabetes in LOAD1.Plcg2M28L compared to the other strains tested.
“Therefore, although we suggest not likely, we cannot rule out the interaction between HFD and Plcg2M28L observed in the brain is due to increased susceptibility to Type 2 diabetes in LOAD1.Plcg2M28L compared to the other strains tested.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataThis is the first study to show that specific LOAD risk variants interact with HFD to exacerbate LOAD phenotypes whereas others do not.
“To our knowledge, this is the first study to show that specific LOAD risk variants interact with HFD to exacerbate LOAD phenotypes whereas others do not.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationMODEL-AD has created a new Trem2R47H allele (Trem2*R47H HSS) that incorporates a human splice site and restores Trem2 expression to normal levels, at least in young wild type B6 mice.
“MODEL-AD has created a new Trem2R47H allele (Trem2*R47H HSS) that incorporates a human splice site (HSS) and restores Trem2 expression to normal levels, at least in young wild type B6 mice (JAX#33781).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites JAX#33781
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationReduced expression levels of Trem2 in Trem2R47H mice are caused by a cryptic splice site that results in an aberrant splice form.
“This may be due in part to the reduced expression levels of Trem2 in Trem2R47H mice caused by a cryptic splice site that results in an aberrant splice form (JAX#27918).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites JAX#27918
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
Study design and conductown dataDespite all mice carrying the APOE4 and Trem2R47H variants, linear modeling identified the specific effects of the Plcg2M28L and Mthfr677C>T variants and the Plcg2M28L:HFD and Mthfr677C>T:HFD interactions.
“Despite the fact that all mice carried the APOE4 and Trem2R47H variants, linear modeling identified the specific effects of the Plcg2M28L and Mthfr677C > T variants and the Plcg2M28L:HFD and Mthfr677C > T:HFD interactions.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningCombining genetic and environmental risk factors (e.g., HFD) leads to better translational and preclinical models of LOAD.
“In summary, combining genetic and environmental risk factors (e.g., HFD) leads to better translational and preclinical models of LOAD.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
The majority of studies to date have focused on the use of early-onset AD models.
“The majority of studies, to date, have focused on the use of early-onset AD models.”
The paper relies on this without support.
No single LOAD-associated variant is sufficient to cause AD.
“Importantly, unlike relatively rare cases of familial AD (fAD), which are predominantly caused by mutations in APP or one APP processing gene, no single LOAD-associated variant is sufficient to cause AD.”
The paper relies on this without support.
Combinations of genetic risk factors are required to develop LOAD.
“It is anticipated that combinations of genetic risk factors are required to develop LOAD.”
The paper relies on this without support.
LOAD1, LOAD1.Plcg2M28L, and LOAD1.Mthfr677C>T did not natively recapitulate all phenotypes relevant to LOAD.
“Despite carrying multiple genetic risk variants for LOAD, LOAD1, LOAD1.Plcg2M28L, and LOAD1.Mthfr677C > T did not natively recapitulate all phenotypes relevant to LOAD, making these strains ideal to test the effects of environmental risk factors, such as diet.”
The paper relies on this without support.
The effects of a western-like diet in the context of multiple genetic risk factors for LOAD have not been studied.
“However, the effects of a western-like diet in the context of multiple genetic risk factors for LOAD have not been studied.”
The paper relies on this without support.
APOE4 is the greatest genetic risk factor for LOAD.
“The E4 allele of apolipoprotein E (APOE4) is the greatest genetic risk factor but with variations in many other genes, including triggering receptor expressed on myeloid cells 2 (TREM2), also contribute to risk.”
The paper relies on this without support.
Variations in many other genes, including TREM2, also contribute to LOAD risk.
“The E4 allele of apolipoprotein E (APOE4) is the greatest genetic risk factor but with variations in many other genes, including triggering receptor expressed on myeloid cells 2 (TREM2), also contribute to risk.”
The paper relies on this without support.
A hallmark of LOAD and other dementias is the loss of neurons, particularly in the cortex and hippocampus.
“A hallmark of LOAD and other dementias is the loss of neurons, particularly in the cortex and hippocampus.”
The paper relies on this without support.
The cortical and hippocampal neuronal cell loss is largely absent in the most widely used mouse models of fAD and LOAD.
“However, the cortical and hippocampal neuronal cell loss is largely absent in the most widely used mouse models of fAD and LOAD.”
The paper relies on this without support.
The second hallmark of LOAD is neuroinflammation, particularly microglia activation.
“The second hallmark of LOAD is neuroinflammation, particularly microglia activation.”
The paper relies on this without support.
In our previous study, LOAD1 mice did not show microglia activation.
“In our previous study, LOAD1 mice did not show microglia activation.”
The paper relies on this without support.
Late-onset AD is a complex disorder that is caused by a combination of genetic and environmental risk factors.
“Late-onset AD is a complex disorder that is caused by a combination of genetic and environmental risk factors.”
The paper relies on this without support.
The specific combinations of genetic and environmental factors that increase the risk for LOAD are not well understood.
“However, the specific combinations of genetic and environmental factors that increase the risk for LOAD are not well understood.”
The paper relies on this without support.
It is likely that these vary between individuals, making predictions of risk for LOAD based on their genetics and exposures imprecise.
“In fact, it is likely that these vary between individuals, making predictions of risk for LOAD based on their genetics and exposures imprecise.”
The paper relies on this without support.
Many inflammation genes, including Csf1, Tgfbr2, Fcer1g, Trem2, and Tyrobp, are expressed by microglia.
“Many of these “inflammation” genes are expressed by microglia including Csf1, Tgfbr2, Fcer1g, Trem2, and Tyrobp.”
The paper relies on this without support.
PLCG2 is a critical signaling element for various immune receptors and a key regulatory hub gene for immune signaling.
“PLCG2 is a critical signaling element for various immune receptors and is a key regulatory hub gene for immune signaling.”
The paper relies on this without support.
The HFD used in this study creates a more inflammatory environment in the brain, causing microglia activation.
“The HFD used here is reported to create a more inflammatory environment in the brain, causing microglia activation.”
The paper relies on this without support.
MTHFR is a key enzyme in the folate/methionine/homocysteine pathway.
“MTHFR is a key enzyme in the folate/methionine/homocysteine pathway.”
The paper relies on this without support.
In humans, MTHFR677C>T reduces liver enzyme activity, resulting in decreased enzyme function.
“In humans, MTHFR677C > T reduces liver enzyme activity resulting in a decrease in enzyme function.”
The paper relies on this without support.
Increases in homocysteine increase the risk for vascular inflammation and dysregulation.
“Common effects of this include increases in homocysteine which is reported to increase the risk for vascular inflammation and dysregulation.”
The paper relies on this without support.
MTHFR is expressed in multiple cells in the brain, particularly vascular-related cells such as endothelial and vascular smooth muscle cells.
“The MTHFR is also expressed in multiple cells in the brain, particularly in vascular-related cells, such as endothelial and vascular smooth muscle cells.”
The paper relies on this without support.
A function for MTHFR in microglia has not been reported.
“However, unlike Plcg2M28L, a function for MTHFR in microglia has not been reported”
The paper relies on this without support.
Mice require mutations or engineering of the human sequence to drive plaque deposition, and neither is present in these mice.
“This is not surprising as mice require mutations or engineering of the human sequence to drive plaque deposition, neither of which are present in these mice.”
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?
PLCG2M28L confers increased risk for AD.
“Conversely, the partial loss‐of‐function M28L variant (PLCG2M28L) confers increased risk for AD. 19 , 20”
From Alzheimer's disease–associated PLCG2 variants alter microglial state and function in human induced pluripotent stem cell–derived microglia‐like cells (2025) · cites this paper as [20]
The Introduction identifies Plcg2M28L as an additional genetic risk factor for late-onset AD, supporting the risk claim. But the citing sentence also calls M28L a partial loss-of-function variant, whereas the Introduction says its precise effects have not yet been elucidated; this copy does not support that characterization. No page numbers are available in the indexed passages. (LLM, conf=0.86)
Experimental — accuracy not yet measuredPLCG2M28L modulates phagocytic capability and alters inflammatory responses.
“PLCG2M28L, though less studied, has been shown to modulate phagocytic capability and alter inflammatory responses. 19 , 20”
From Alzheimer's disease–associated PLCG2 variants alter microglial state and function in human induced pluripotent stem cell–derived microglia‐like cells (2025) · cites this paper as [20]
The Results section reports altered brain and plasma cytokines in LOAD1.Plcg2M28L mice, supporting the inflammatory-response part of the claim. It also reports enrichment of phagocytosis-related gene pathways, but does not show that the variant changes phagocytic capability itself; the Introduction says the precise effects of M28L had not yet been elucidated. (LLM, conf=0.86)
Experimental — accuracy not yet measuredExpression of PLCγ2 M28L in the mouse brain led to a transcriptomic profile that correlated with human AD modules and led to increased microglia density when fed a high fat diet.
“Expression of PLCγ2 M28L in the mouse brain led to a transcriptomic profile that correlated with human AD modules and led to increased microglia density when fed with a high fat diet (17).”
From Multi-omics analyses reveal novel effects of PLCγ2 deficiency in the mouse brain (2023) · cites this paper as [17]
The Results section reports that Plcg2M28L and its interaction with a high-fat diet correlated with human AD gene-expression modules. It also reports increased microglial density in high-fat-fed female LOAD1.Plcg2M28L mice, but the claim omits the sex restriction and implies a general increase across the mouse brain. The Results specify the cortex, while the Discussion describes the increase as limited to the hippocampus; our copy does not resolve that discrepancy. No page numbers are provided. (LLM, conf=0.85)
Experimental — accuracy not yet measuredThe loss-of-function PLCG2M28L variant confers resistance to the Bruton Tyrosine Kinase inhibitor ibrutinib, worsens Aβ pathology, and increases risk of AD.
“Conversely, the loss‐of‐function PLCG2M28L variant confers resistance to the Bruton Tyrosine Kinase inhibitor ibrutinib, worsens Aβ pathology, and increases risk of AD.”
From PLCG2 modulates TREM2 expression and signaling in response to Alzheimer's disease pathology (2025) · cites this paper as [29]
The Introduction and Methods describe Plcg2M28L as an AD risk variant, but the Introduction says its precise effects have not been elucidated. The Discussion states that the studied mice lacked amyloid-beta plaques, rather than showing worsened Aβ pathology. No passage found in our copy supports loss of function or resistance to ibrutinib. (LLM, conf=0.88)
Experimental — accuracy not yet measuredPLCG2 loss-of-function has recently been associated with worsened AD pathology.
“Likewise, PLCG2 loss‐of‐function has recently been associated with worsened AD pathology. 12 , 27 , 29”
From PLCG2 modulates TREM2 expression and signaling in response to Alzheimer's disease pathology (2025) · cites this paper as [29]
The Discussion reports more extreme AD-relevant phenotypes in mice carrying Plcg2M28L on a LOAD1 background when exposed to a high-fat/high-sugar diet. It describes loss of function for this variant as predicted, not established. Thus the paper supports a qualified association in this mouse model, but not the broader claim that PLCG2 loss of function generally worsens AD pathology. (LLM, conf=0.86)
Experimental — accuracy not yet measured
M28L is predicted to be a loss-of-function variant.
“The phospholipase C-γ−2 (PLCγ2) P522R protective variant is a functional hypermorph (12–16), while it is predicted that M28L is a loss-of-function variant (17).”
From Multi-omics analyses reveal novel effects of PLCγ2 deficiency in the mouse brain (2023) · cites this paper as [17]
The Introduction (page unavailable) says the precise effects of M28L have not yet been elucidated, but does not say whether it is predicted to be loss-of-function. Searches for a loss-of-function prediction and reduced M28L activity found no passage addressing that prediction; the Discussion discusses reduced PLCG2 expression, not a predicted effect of M28L. (LLM, conf=0.75)
Experimental — accuracy not yet measured
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.
JAX glucose result is called significant despite p = 0.165
MajorThe results say the HFD effect on glucose was significant in females in both studies, but give p = 0.165 for the JAX females. The paper defines significance as p < 0.05.
“In both studies, there was a significant effect of HFD in female, but not male mice fed on HFD. The effect was more striking in female mice from IU (p < 0.0001) compared to female mice from JAX (p = 0.165).”
“For these studies, p < 0.05 was considered significant.”
Increased IBA1+ cell count is described as reduced density
MinorThe same results passage reports increased IBA1+ cells in the cortex, then describes the data as suggestive of reduced IBA1+ cell density.
“we found increased IBA1+ cells in the cortex of female LOAD1.Plcg2M28L mice fed on HFD compared to LOAD1.Plcg2M28L on CD (Figure 3 and Supplementary Figure 1).”
“These data are not collected based on stereological analyses and are therefore suggestive of a reduced density of IBA1+ cells.”
Bilateral region count yields 28, not 27, regions
MinorThe image-analysis methods say 56 bilateral regions were paired to yield 27 unique volumes. Pairing 56 regions yields 28 volumes; the passage also lists 28 named regions.
Reported 27 · recomputed 28
“Post-registration, 56 bilateral regions were extracted via brain atlas and averaged to yield 27 unique volumes of interest”
Terminal blood collection is called non-anesthetized and anesthetized
MinorThe results describe the mice as non-anesthetized for blood samples at both 8 and 12 months. The methods say mice were anesthetized for the terminal, 12-month blood collection.
“Blood samples were collected from fasting, non-anesthetized mice at 8 (mid stage) and 12 (end stage) months of age”
“again at the terminal timepoint of 12 months of age where mice were anesthetized, and blood was extracted through a left ventricle cardiac puncture”
Regression intercept is assigned to males despite a male indicator
MinorThe model says sex (male) is included as a regression term, making the reference category female. It then identifies the intercept as the average expression for reference male mice.
“Where the sum is over sex (male), HFD, genetic variants (Mthfr677C > T, Plcg2M28L), and interaction terms between HFD and each variant (HFD*Mthfr677C > T, HFD*Plcg2M28L).”
“The values, β0 and ε represent the average expression level for the reference LOAD1 male mice on the standard chow diet and residual, respectively.”
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“GSEA identified upregulation of Alzheimer’s disease, focal adhesion pathways in presence of each perturbation except Mthfr677C>T (Supplementary Figure 1).”
MethodInfluentialclusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
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MethodFrom inflammation to sickness and depression: when the immune system subjugates the brain
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BackgroundObesity and inflammation: the linking mechanism and the complications
Ellulu, M. S., Patimah, I., Khaza’ai, H., Rahmat, A., & Abed, Y. (2017) · Archives of Medical Science · doi:10.5114/aoms.2016.58928 · Cited by 1,982 · cited 1× · see citing works
“Obesity can cause a wide range of changes including increased inflammation in both the periphery and the brain (Ellulu et al., 2017; Chan et al., 2019).”
BackgroundBaumgart, M., Snyder, H. M., Carrillo, M. C., Fazio, S., Kim, H., & Johns, H. (2015) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2015.05.016 · Cited by 1,660 · cited 1× · see citing works
“Studies have shown that diet, obesity, cardiovascular diseases, hypertension, physical activity, diabetes, educational attainment, smoking, and traumatic brain injury increase the risk for LOAD and other dementias (Ebbert et al., 2014; Baumgart et al., 2015; Xu et al., 2015; Wajman et al., 2018).”
BackgroundKivipelto, M., Helkala, E.-L., Laakso, M. P., Hänninen, T., Hallikainen, M., Alhainen, K., Soininen, H., Tuomilehto, J., & Nissinen, A. (2001) · BMJ · doi:10.1136/bmj.322.7300.1447 · Cited by 1,618 · see citing works
Role of pro-inflammatory cytokines released from microglia in Alzheimer's disease.
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“Inflammation is characterized, in part by increased production of cytokines, such as IL1b and the activation of myeloid cells, including microglia in the brain (Wang et al., 2015).”
BackgroundPaxinos and Franklin's the Mouse Brain in Stereotaxic Coordinates
Paxinos, G., & Franklin, K. B. J. (2012) · Cited by 1,267 · see citing works
Diet-Induced Type II Diabetes in C57BL/6J Mice
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“B6 mice are considered diabetic with a fasting glucose over 240 mg/dl[26].”
BackgroundDiabetes, a New Mutation in the Mouse
Hummel, K. P., Dickie, M. M., & Coleman, D. L. (1966) · Science · doi:10.1126/science.153.3740.1127 · Cited by 990 · cited 1× · see citing works
“Additionally, data in animals revealed that insensitivity of the leptin receptor [48] upregulated the transcriptional activity of interleukin-6 (IL-6), TNF-α, and IL-1β in the hippocampus compared to control [49].”
BackgroundCentral obesity and increased risk of dementia more than three decades later
Whitmer, R. A., Gustafson, D. R., Barrett-Connor, E., Haan, M. N., Gunderson, E. P., & Yaffe, K. (2008) · Neurology · doi:10.1212/01.wnl.0000306313.89165.ef · Cited by 803 · cited 1× · see citing works
“Metabolic syndrome increases the risk for Type 2 diabetes and cardiovascular disease, and AD (Kivipelto et al., 2001; Luchsinger et al., 2004; Cordain et al., 2005; Whitmer et al., 2008).”
BackgroundStreit, W. J., Braak, H., Xue, Q.-S., & Bechmann, I. (2009) · Acta Neuropathologica · doi:10.1007/s00401-009-0556-6 · Cited by 727 · cited 1× · see citing works
“, human iPSC-derived microglia), given some reports that indicate differences in microglia responses between humans and mice (Streit et al., 2009; Navarro et al., 2018; Streit et al., 2018; Olah et al., 2020).”
BackgroundSingle cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease
Olah, M., Menon, V., Habib, N., Taga, M. F., Ma, Y., Yung, C. J., Cimpean, M., Khairallah, A., Coronas-Samano, G., Sankowski, R., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19737-2 · Cited by 722 · cited 1× · see citing works
“, human iPSC-derived microglia), given some reports that indicate differences in microglia responses between humans and mice (Streit et al., 2009; Navarro et al., 2018; Streit et al., 2018; Olah et al., 2020).”
BackgroundStudholme, C., Hill, D., & Hawkes, D. J. (1997) · Medical Physics · doi:10.1118/1.598130 · Cited by 675 · cited 1× · see citing works
“All PET and MRI images were co-registered using a ridgedbody mutual information-based normalized entropy algorithm (Studholme et al., 1997) with 12 degrees of freedom and mapped to stereotactic mouse brain coordinates (Franklin and Paxinos, 2013) using MIM 7.”
MethodAdipokine dysregulation and adipose tissue inflammation in human obesity
Unamuno, X., Gómez‐Ambrosi, J., Rodríguez, A., Becerril, S., Frühbeck, G., & Catalán, V. (2018) · European Journal of Clinical Investigation · doi:10.1111/eci.12997 · Cited by 610 · see citing works
A multi-omic atlas of the human frontal cortex for aging and Alzheimer’s disease research
De Jager, P. L., Ma, Y., McCabe, C., Xu, J., Vardarajan, B. N., Felsky, D., Klein, H.-U., White, C. C., Peters, M. A., Lodgson, B., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.142 · Cited by 598 · see citing works
Meta-analysis of modifiable risk factors for Alzheimer's disease
Xu, W., Tan, L., Wang, H.-F., Jiang, T., Tan, M.-S., Tan, L., Zhao, Q.-F., Li, J.-Q., Wang, J., & Yu, J.-T. (2015) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2015-310548 · Cited by 573 · cited 1× · see citing works
“Studies have shown that diet, obesity, cardiovascular diseases, hypertension physical activity, diabetes, educational attainment, smoking, and traumatic brain injury increase risk for LOAD and other dementias [5-8].”
BackgroundMostafavi, S., Gaiteri, C., Sullivan, S. E., White, C. C., Tasaki, S., Xu, J., Taga, M., Klein, H.-U., Patrick, E., Komashko, V., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0154-9 · Cited by 509 · cited 1× · see citing works
“9 assessment of the relevance of mouse models to the molecular changes observed in human LOAD[28-31].”
BackgroundWang, M., Beckmann, N. D., Roussos, P., Wang, E., Zhou, X., Wang, Q., Ming, C., Neff, R., Ma, W., Fullard, J. F., et al. (2018) · Scientific Data · doi:10.1038/sdata.2018.185 · Cited by 502 · cited 3× · see citing works
“org/ hippocampus due to their relevance to LOAD neuropathology across independent human cohorts (ROS/MAP, Mount Sinai Brain Bank, and Mayo Clinic) and stratified patients into different molecular subtypes based on gene co-expression profiles using iterative WGCNA (Allen et al., 2016; De Jager et al., 2018; Wang et al.…”
BackgroundMethodCollins, S., Martin, T. L., Surwit, R. S., & Robidoux, J. (2004) · Physiology & Behavior · doi:10.1016/j.physbeh.2004.02.006 · Cited by 486 · cited 1× · see citing works
“In addition, B6 mice do not develop overt type 2 diabetes when fed with an HFD, but they are a model for early stages of the disease with phenotypes that include obesity, mildly elevated non-fasting blood glucose, increased serum glucose, glucose intolerance with advancing age and elevated triglycerides, glucose, HDL,…”
BackgroundLiew, S.-C., & Gupta, E. D. (2015) · European Journal of Medical Genetics · doi:10.1016/j.ejmg.2014.10.004 · Cited by 466 · see citing works
Allen, M., Carrasquillo, M. M., Funk, C., Heavner, B. D., Zou, F., Younkin, C. S., Burgess, J. D., Chai, H.-S., Crook, J., Eddy, J. A., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.89 · Cited by 439 · cited 4× · see citing works
“org/ hippocampus due to their relevance to LOAD neuropathology across independent human cohorts (ROS/MAP, Mount Sinai Brain Bank, and Mayo Clinic) and stratified patients into different molecular subtypes based on gene co-expression profiles using iterative WGCNA (Allen et al., 2016; De Jager et al., 2018; Wang et al.…”
BackgroundMethodInfluentialOblak, A. L., Lin, P. B., Kotredes, K. P., Pandey, R. S., Garceau, D., Williams, H. M., Uyar, A., O’Rourke, R., O’Rourke, S., Ingraham, C., et al. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.713726 · Cited by 325 · see citing works
Self-citationWan, Y.-W., Al-Ouran, R., Mangleburg, C. G., Perumal, T. M., Lee, T. V., Allison, K., Swarup, V., Funk, C. C., Gaiteri, C., Allen, M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107908 · Cited by 295 · cited 5× · see citing works
“Here, we correlated the effect of each mouse perturbation (sex, HFD, genetic variants, and interaction between variants and HFD) with 30 human AMP-AD co-expression modules (Wan et al., 2020).”
BackgroundMethodInfluentialSelf-citationXiang, X., Wind, K., Wiedemann, T., Blume, T., Shi, Y., Briel, N., Beyer, L., Biechele, G., Eckenweber, F., Zatcepin, A., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abe5640 · Cited by 268 · cited 4× · see citing works
“Fasting blood glucose levels only exceeded 240 mg/dL (a level that previous studies consider B6 mice to be diabetic (Xiang et al., 2021) in mice fed with LOAD1 HFD and LOAD1.”
BackgroundMethodInfluentialDinel, A., André, C., Aubert, A., Ferreira, G., Layé, S., & Castanon, N. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024325 · Cited by 264 · cited 1× · see citing works
“Additionally, data in animals revealed that insensitivity of the leptin receptor [48] upregulated the transcriptional activity of interleukin-6 (IL-6), TNF-α, and IL-1β in the hippocampus compared to control [49].”
BackgroundAPOE4-specific Changes in Aβ Accumulation in a New Transgenic Mouse Model of Alzheimer Disease
Youmans, K. L., Tai, L. M., Nwabuisi-Heath, E., Jungbauer, L., Kanekiyo, T., Gan, M., Kim, J., Eimer, W. A., Estus, S., Rebeck, G. W., et al. (2012) · Journal of Biological Chemistry · doi:10.1074/jbc.m112.407957 · Cited by 259 · cited 1× · see citing works
“Previous studies support this, with E4FAD (APOE4+5xFAD) mice showing increased amyloid deposition, specifically more compact plaques, compared to E3FAD (APOE3+5xFAD) mice (Youmans et al., 2012).”
The role of TREM2 in Alzheimer's disease and other neurodegenerative disorders
Carmona, S., Zahs, K., Wu, E., Dakin, K., Bras, J., & Guerreiro, R. (2018) · The Lancet Neurology · doi:10.1016/s1474-4422(18)30232-1 · Cited by 244 · cited 2× · see citing works
“Although the precise effects of the M28L variant have not yet been elucidated, like TREM2, PLCG2 is expressed by microglia and plays a role in amyloid clearance (Carmona et al., 2018).”
BackgroundKnight, E. M., Martins, I. V. A., Gümüsgöz, S., Allan, S. M., & Lawrence, C. B. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.02.010 · Cited by 232 · see citing works
Central and Peripheral Inflammation Link Metabolic Syndrome and Major Depressive Disorder
Chan, K. L., Cathomas, F., & Russo, S. J. (2019) · Physiology · doi:10.1152/physiol.00047.2018 · Cited by 227 · cited 2× · see citing works
“Obesity can cause a wide range of changes including increased inflammation in both the periphery and the brain (Ellulu et al., 2017; Chan et al., 2019).”
BackgroundBrain Barrier Breakdown as a Cause and Consequence of Neuroinflammation in Sepsis
Danielski, L. G., Giustina, A. D., Badawy, M., Barichello, T., Quevedo, J., Dal-Pizzol, F., & Petronilho, F. (2018) · Molecular Neurobiology · doi:10.1007/s12035-016-0356-7 · Cited by 182 · cited 1× · see citing works
“Increased blood-brain barrier permeability that allows proinflammatory proteins into the brain can initiate neuroinflammation and stimulate neurodegeneration [46].”
BackgroundPlasma homocysteine levels and risk of Alzheimer disease
Luchsinger, J. A., Tang, M. X., Shea, S., Miller, J., Green, R., & Mayeux, R. (2004) · Neurology · doi:10.1212/01.wnl.0000129504.60409.88 · Cited by 171 · see citing works
Sarkar, S., Rokad, D., Malovic, E., Luo, J., Harischandra, D. S., Jin, H., Anantharam, V., Huang, X., Lewis, M., Kanthasamy, A., et al. (2019) · Science Signaling · doi:10.1126/scisignal.aat9900 · Cited by 171 · cited 1× · see citing works
“Studies also suggest that genetic factors may only contribute between 50 and 70% of the risk for LOAD, meaning many individuals are likely to develop LOAD due to a combination of genetic and environmental factors (Kawahara et al., 2017; Sarkar et al., 2019; Rahman et al., 2020; Kim et al., 2021).”
BackgroundKrishnamoorthy, S., Blankemeyer, E., Mollet, P., Surti, S., Van Holen, R., & Karp, J. S. (2018) · Physics in Medicine & Biology · doi:10.1088/1361-6560/aacec3 · Cited by 141 · cited 2× · see citing works
“In all cases, images were corrected for radionuclide decay, tissue attenuation, detector dead-time loss, and photon scatter according to the manufacturer’s methods[56].”
MethodTerrito, P. R., Meyer, J. A., Peters, J. S., Riley, A. K., McCarthy, B. P., Gao, M., Wang, M., Green, M. A., Zheng, Q., & Hutchins, G. D. (2016) · Journal of Nuclear Medicine · doi:10.2967/jnumed.116.181354 · Cited by 138 · see citing works
Self-citationNavarro, G., Borroto‐Escuela, D. O., Angelats, E., Etayo, I., Reyes‐Resina, I., Pulido-Salgado, M., Rodriguez-Perez, A. I., Canela, E. I., Saura, J., Lanciego, J. L., et al. (2017) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2017.08.015 · Cited by 127 · see citing works
Emerging risk of environmental factors: insight mechanisms of Alzheimer’s diseases.
Rahman, M. A., Rahman, M. S., Uddin, M. J., Mamum-Or-Rashid, A. N. M., Pang, M.-G., & Rhim, H. (2020) · Environmental Science and Pollution Research · doi:10.1007/s11356-020-08243-z · Cited by 115 · see citing works
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“Therefore, to further align mouse studies to the human situation, alternative diets should be tested, such as a recently developed western diet that incorporates 16% of fat that was designed to model the more common diet consumed in the western world (Graham et al., 2016; Yang et al., 2019).”
BackgroundSelf-citationThe AD Knowledge Portal: A Repository for Multi‐Omic Data on Alzheimer's Disease and Aging
Greenwood, A. K., Montgomery, K. S., Kauer, N., Woo, K. H., Leanza, Z. J., Poehlman, W. L., Gockley, J., Sieberts, S. K., Bradic, L., Logsdon, B. A., et al. (2020) · Current Protocols in Human Genetics · doi:10.1002/cphg.105 · Cited by 102 · cited 5× · see citing works
“More details on strain creation are provided on the AD Knowledge Portal.”
MethodInfluentialReproducibility of 18F-FDG microPET Studies in Mouse Tumor Xenografts
Dandekar, M., Tseng, J. R., & Gambhir, S. S. (2007) · Journal of Nuclear Medicine · doi:10.2967/jnumed.106.036608 · Cited by 99 · cited 1× · see citing works
“Finally, to quantify regional changes, voxels of interest (VOIs) for 27 brain (54 bilateral) regions were extracted and analyzed for standardized uptake value ratios (SUVRs) according to published methods (Dandekar et al., 2007).”
MethodMicroglial activation occurs late during preclinical Alzheimer's disease
Streit, W. J., Braak, H., Del Tredici, K., Leyh, J., Lier, J., Khoshbouei, H., Eisenlöffel, C., Müller, W., & Bechmann, I. (2018) · Glia · doi:10.1002/glia.23510 · Cited by 98 · cited 1× · see citing works
“, human iPSC-derived microglia), given some reports that indicate differences in microglia responses between humans and mice (Streit et al., 2009; Navarro et al., 2018; Streit et al., 2018; Olah et al., 2020).”
Background<title>Normalized entropy measure for multimodality image alignment</title>
Studholme, C., Hawkes, D. J., & Hill, D. L. (1998) · SPIE Proceedings · doi:10.1117/12.310835 · Cited by 91 · cited 1× · see citing works
“Post-acquisition, all PET and CT images were co-registered using a mutual information-based normalized entropy algorithm (Studholme et al., 1998) with 12 degrees of freedom and mapped to stereotactic mouse brain coordinates (Franklin and Paxinos, 2013).”
MethodRai, V. (2017) · Molecular Neurobiology · doi:10.1007/s12035-016-9722-8 · Cited by 88 · cited 2× · see citing works
“Variations in MTHFR, particularly the Mthfr677C > T variant, are associated with cardiovascular diseases, AD, and vascular dementia (Liu et al., 2010; Liew and Gupta, 2015; Rai, 2017).”
BackgroundBracko, O., Vinarcsik, L. K., Cruz Hernández, J. C., Ruiz-Uribe, N. E., Haft-Javaherian, M., Falkenhain, K., Ramanauskaite, E. M., Ali, M., Mohapatra, A., Swallow, M. A., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-65908-y · Cited by 85 · cited 1× · see citing works
“Also, the addition of a HFD exacerbated AD phenotypes in mouse models relevant to early-onset AD[21-25].”
BackgroundKawahara, M., Kato-Negishi, M., & Tanaka, K. (2017) · Metallomics · doi:10.1039/c7mt00046d · Cited by 80 · see citing works
Robison, L. S., Gannon, O. J., Thomas, M. A., Salinero, A. E., Abi‐Ghanem, C., Poitelon, Y., Belin, S., & Zuloaga, K. L. (2020) · Journal of Neuroinflammation · doi:10.1186/s12974-020-01956-5 · Cited by 78 · cited 1× · see citing works
“Also, the addition of an HFD exacerbated AD phenotypes in mouse models relevant to early-onset AD (Knight et al., 2014; Jones et al., 2019; Bracko et al., 2020; Robison et al., 2020; Jones et al., 2021).”
BackgroundGreen, M. A. (1987) · International Journal of Radiation Applications and Instrumentation Part B Nuclear Medicine and Biology · doi:10.1016/0883-2897(87)90162-0 · Cited by 70 · cited 7× · see citing works
“Following the terminal 64Cu-PTSM scans, brains were subjected to autoradiographic analysis (F-G).”
BackgroundInfluentialAgatston, A. S. (2003) · Medical Entomology and Zoology · Cited by 69 · see citing works
Uncovering Disease Mechanisms in a Novel Mouse Model Expressing Humanized APOEε4 and Trem2*R47H
Kotredes, K. P., Oblak, A., Pandey, R. S., Lin, P. B.-C., Garceau, D., Williams, H., Uyar, A., O’Rourke, R., O’Rourke, S., Ingraham, C., et al. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.735524 · Cited by 66 · cited 5× · see citing works
“Neuronal cell loss was also not observed in LOAD1 mice, even at 24 months of age [10].”
BackgroundInfluentialSelf-citationRivera, P., Pérez-Martín, M., Pavón, F. J., Serrano, A., Crespillo, A., Cifuentes, M., López-Ávalos, M.-D., Grondona, J. M., Vida, M., Fernández-Llebrez, P., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0064750 · Cited by 65 · cited 1× · see citing works
“Previous HFD studies have been associated with increased microglial activity in wild-type mice (Rivera et al., 2013; Wanrooy et al., 2018).”
BackgroundWanrooy, B. J., Kumar, K. P., Wen, S. W., Qin, C. X., Ritchie, R. H., & Wong, C. H. Y. (2018) · Journal of Neuroinflammation · doi:10.1186/s12974-018-1329-8 · Cited by 63 · cited 2× · see citing works
“These data are consistent with the induction of diet-induced obesity (DIO) that has been previously reported for B6 mice (Wanrooy et al., 2018).”
BackgroundResultA novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease
the MODEL-AD Consortium, Preuss, C., Pandey, R., Piazza, E., Fine, A., Uyar, A., Perumal, T., Garceau, D., Kotredes, K. P., Williams, H., et al. (2020) · Molecular Neurodegeneration · doi:10.1186/s13024-020-00412-5 · Cited by 63 · cited 11× · see citing works
“The direction of the changes correlated with gene expression changes observed in human AD based on the AMP-AD modules (Preuss et al., 2020).”
BackgroundMethodInfluentialSelf-citationAssociation Between theMTHFRGene and Alzheimer's Disease: A Meta-Analysis
Ye, H., Zhao, H., Kong, Y., & Ye, M. (2011) · International Journal of Neuroscience · doi:10.3109/00207454.2011.578778 · Cited by 57 · cited 1× · see citing works
“These included the M28L variant in phospholipase C Gamma 2 (Plcg2M28L)[11, 12] and the 677C>T variant in methylenehydrofolate reductase (Mthfr677C>T)[12, 13].”
BackgroundPopulation-based analysis of Alzheimer’s disease risk alleles implicates genetic interactions.
Ebbert, M. T. W., Ridge, P. G., Wilson, A. R., Sharp, A. R., Bailey, M., Norton, M. C., Tschanz, J. T., Munger, R. G., Corcoran, C. D., & Kauwe, J. S. K. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2013.07.008 · Cited by 57 · cited 1× · see citing works
“Studies have shown that diet, obesity, cardiovascular diseases, hypertension physical activity, diabetes, educational attainment, smoking, and traumatic brain injury increase risk for LOAD and other dementias [5-8].”
BackgroundAssociation of MTHFR Gene Polymorphism C677T With Susceptibility to Late-Onset Alzheimer's Disease
Wang, B., Jin, F., Kan, R., et al. (2005) · Journal of Molecular Neuroscience · doi:10.1385/jmn:27:1:023 · Cited by 55 · cited 1× · see citing works
“, 2021) and the 677C > T variant in methylenetetrahydrofolate reductase (Mthfr677C > T) (Wang et al., 2005; Chan et al., 2019).”
BackgroundMetabolic disturbances of a high-fat diet are dependent on APOE genotype and sex.
Jones, N. S., Watson, K. Q., & Rebeck, G. W. (2019) · eneuro · doi:10.1523/eneuro.0267-19.2019 · Cited by 54 · see citing works
Liu, H., Yang, M., Li, G.-M., Qiu, Y., Zheng, J., Du, X., Wang, J.-L., & Liu, R.-W. (2010) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2010.04.001 · Cited by 51 · see citing works
Milind, N., Preuß, C., Haber, A., Ananda, G., Mukherjee, S., Cai, J., Shapley, S. M., Tyler, A. L., Logsdon, B. A., Crane, P. K., et al. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008775 · Cited by 50 · cited 1× · see citing works
“11 Next, to identify variants that resemble the inflammatory and non-inflammatory subtypes in human patients, we correlated the effect of each variant (sex, HFD, genetic variants and interaction between variants and HFD) with inflammatory and non-inflammatory subtypes associated with LOAD in the ROSMAP, MSBB and Mayo…”
BackgroundSelf-citationWajman, J. R., Mansur, L. L., & Yassuda, M. S. (2018) · Current Aging Science · doi:10.2174/1874609811666181003160225 · Cited by 41 · cited 1× · see citing works
“Studies have shown that diet, obesity, cardiovascular diseases, hypertension, physical activity, diabetes, educational attainment, smoking, and traumatic brain injury increase the risk for LOAD and other dementias (Ebbert et al., 2014; Baumgart et al., 2015; Xu et al., 2015; Wajman et al., 2018).”
BackgroundMaguire, E., Menzies, G. E., Phillips, T., Sasner, M., Williams, H. M., Czubala, M. A., Evans, N., Cope, E. L., Sims, R., Howell, G. R., et al. (2021) · The EMBO Journal · doi:10.15252/embj.2020105603 · Cited by 41 · see citing works
Self-citationYang, H. S., Graham, L. C., Reagan, A. M., Grabowska, W. A., Schott, W. H., & Howell, G. R. (2019) · Journal of Neuroinflammation · doi:10.1186/s12974-019-1527-z · Cited by 39 · cited 1× · see citing works
“common diet consumed in the western world [37, 38] .”
BackgroundSelf-citationInvestigation of copper-PTSM as a PET tracer for tumor blood flow
Mathias, C. J., Welch, M. J., Perry, D. J., et al. (1991) · International Journal of Radiation Applications and Instrumentation Part B Nuclear Medicine and Biology · doi:10.1016/0883-2897(91)90022-d · Cited by 38 · cited 1× · see citing works
“To measure regional blood flow, copper-pyruvaldehyde-bis(N4methylthiosemicarbazone) (64Cu-PTSM)[54], which has a very high first pass (>75%) extraction[55], and glutathione reductase redox trapping of copper[55], was administered via tail vein in awake subjects and was given a 2 min uptake period prior to imaging.”
MethodPandey, R. S., Graham, L., Uyar, A., Preuss, C., Howell, G. R., & Carter, G. W. (2019) · Molecular Neurodegeneration · doi:10.1186/s13024-019-0351-3 · Cited by 37 · cited 2× · see citing works
“, 2020) and the effect of each mouse perturbation (sex, HFD, Mthfr677C > T , Plcg2M28L, and interaction terms HFD∗Mthfr677C > T , HFD∗Plcg2M28L) as measured above for each gene in NanoString panel (Pandey et al., 2019; Preuss et al., 2020) using cor.”
MethodSelf-citationKim, J., Woo, S., Kim, S., Jang, H., Kim, J. P., Kim, J., Kang, S. H., Na, D. L., Chin, J., Apostolova, L. G., et al. (2021) · Alzheimer s Research & Therapy · doi:10.1186/s13195-021-00857-w · Cited by 30 · see citing works
Schuster, F., Huber, G., Stölting, I., et al. (2018) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-018-2178-0 · Cited by 29 · cited 1× · see citing works
“Hippocampal injury is found in HFD-fed animals in response to increased blood-brain barrier permeability [44] due to circulating proinflammatory adipokines and reactive glial cytokine”
BackgroundJones, N. S., Watson, K. Q., & Rebeck, G. W. (2021) · Journal of Neuroinflammation · doi:10.1186/s12974-021-02256-2 · Cited by 26 · cited 2× · see citing works
“A second study concluded that early dysregulation of inflammation in APOE4 brains could predispose to CNS damages from various insults, including diet, and later result in the increased CNS damage normally associated with the APOE4 genotype [25].”
BackgroundHernandez, D., Egan, S. E., Yulug, I. G., & Fisher, E. M. C. (1994) · Genomics · doi:10.1006/geno.1994.1533 · Cited by 22 · cited 1× · see citing works
“PLCG2 plays a crucial role in signal transduction between tyrosine kinases and downstream events, protein kinase C activation, and intracellular calcium release (Hernandez et al., 1994).”
BackgroundReagan, A. M., Christensen, K. E., Graham, L. C., Bedwell, A. A., Eldridge, K., Speedy, R., Figueiredo, L. L., Persohn, S. A., Bottiglieri, T., Nho, K. T., et al. (2022) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x221122644 · Cited by 21 · see citing works
Self-citationReagan, A. M., Christensen, K. E., Graham, L. C., Bedwell, A. A., Eldridge, K., Speedy, R., Figueiredo, L. L., Persohn, S. C., Bottiglieri, T., Sasner, M., et al. (2021) · doi:10.1101/2021.12.16.472805 · Cited by 21
Self-citationGraham, L. C., Kocalis, H. E., Soto, I., & Howell, G. R. (2020) · eNeuro · doi:10.1523/eneuro.0057-20.2020 · Cited by 18 · cited 1× · see citing works
“For instance, a study showed a diet-induced myelin breakdown in aging B6 mice that were dependent on the complement cascade (Graham et al., 2020).”
BackgroundSelf-citationWan, Y., Al-Ouran, R., Mangleburg, C. G., Lee, T. V., Allison, K., Neuner, S., Kaczorowski, C., Phillip, V., Howell, G. R., Martini-Stoica, H., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/506873 · Cited by 5 · cited 2× · see citing works
“Here, we correlated the effect of each mouse perturbation (sex, HFD, genetic variants and interaction between variants and HFD) with 30 human AMP-AD co-expression modules [28].”
BackgroundMethodSelf-citationTsai, A. P., Lin, P. B., Dong, C., Moutinho, M., Liu, Y., Bissel, S. J., Oblak, A. L., Nho, K., Lamb, B. T., & Landreth, G. E. (2021) · Alzheimer's & Dementia · doi:10.1002/alz.058740 · Cited by 1 · cited 3× · see citing works
“However, the role of PLCG2 has not yet been comprehensively explored (Tsai et al., 2021; Maguire et al., 2021).”
BackgroundInfluentialSelf-citation
Flagged first, then by citations
Research works printed but not linked: 3
- Franklin, 2013, Paxinos and Franklin’s The Mouse Brain In Stereotaxic Coordinates, 1
- Hartwig, 2015, The Whole30
- 2022, Adult Obesity Facts.
Cited by
Sorted by citations
Updates on mouse models of Alzheimer’s disease
Zhong, M. Z., Peng, T., Duarte, M. L., Wang, M., & Cai, D. (2024) · Molecular Neurodegeneration · doi:10.1186/s13024-024-00712-0 · Cited by 189 · see citing works
Tsai, A. P., Dong, C., Lin, P. B.-C., Oblak, A. L., Viana Di Prisco, G., Wang, N., Hajicek, N., Carr, A. J., Lendy, E. K., Hahn, O., et al. (2023) · Immunity · doi:10.1016/j.immuni.2023.08.008 · Cited by 71 · see citing works
Self-citationKotredes, K. P., Pandey, R. S., Persohn, S. A., Elderidge, K., Burton, C. P., Miner, E. W., Haynes, K. A., dos Santos, D. F. D. S., Williams, S. G., Heaton, N., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13828 · Cited by 38 · see citing works
Self-citationEvans, A. K., Defensor, E. B., & Shamloo, M. (2022) · Frontiers in Pharmacology · doi:10.3389/fphar.2022.1030609 · Cited by 36 · see citing works
“In terms of biological risk factors, functional studies have identified AD risk-related genes (e.g., TREM2, CD33) linked to the neuroimmune system (Griciuc and Tanzi, 2021) and proteomic changes implicating an altered metabolome (Johnson et al., 2022).”
BackgroundInfluentialValentin‐Escalera, J., Leclerc, M., & Calon, F. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-230118 · Cited by 35 · see citing works
PLCG2 modulates TREM2 expression and signaling in response to Alzheimer's disease pathology
Messenger, E. J., Baar, S. A., Bedford, L. M., Tsai, A. P., Lin, P. B., Ferguson, C. A., Xu, G., Wallace, A., Landreth, G. E., Lamb, B. T., et al. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70231 · Cited by 16 · see citing works
“27–29 Similarly,studiesof PLCG2 haploinsufficiency in mice have revealed that reduced PLCG2 expression impairs expression of inflammation-associated genes.”
Self-citationInvestigating the Interplay between Cardiovascular and Neurodegenerative Disease
Cousineau, J., Dawe, A. M., & Alpaugh, M. (2024) · Biology · doi:10.3390/biology13100764 · Cited by 15 · see citing works
“Herein, researchers found increased microglia activation in the female LOAD1/ plcg2 mouse cortex [407].”
BackgroundIn vivo validation of late‐onset Alzheimer's disease genetic risk factors
Sasner, M., Preuß, C., Pandey, R. S., Uyar, A., Garceau, D. T., Kotredes, K. P., Williams, H. M., Oblak, A. L., Lin, P. B., Perkins, B. M., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13840 · Cited by 11 · see citing works
Self-citationBedford, L. M., Tutrow, K. D., Hooper, K., Messenger, E. J., Hernandez, M., Lamb, B. T., Meyer, J. S., Richardson, T. I., & Bissel, S. J. (2025) · Alzheimer's & Dementia · doi:10.1002/alz.70772 · Cited by 8 · see citing works
Self-citationShin, Y.-C., Plummer-Medeiros, A. M., Mungenast, A., Choi, H.-W., TenDyke, K., Zhu, X., Shepard, J., Sanders, K., Zhuang, N., Hu, L., et al. (2024) · Science Advances · doi:10.1126/sciadv.adn6037 · Cited by 7 · see citing works
PLCG2 across human disease: genetic variants, signaling mechanisms, and clinical implications
Jiang, P., Wang, M., Zhang, C., Li, X., Wang, Z. Q., Guo, Y., Zhang, J., Yan, W., & Xi, X. (2026) · Journal of Translational Medicine · doi:10.1186/s12967-025-07632-7 · Cited by 6 · see citing works
“Dietary factors, such as a high-fat, high-sugar diet, may also interact with the PLCG2^M28L^ variant to accelerate the onset of AD-related phenotypes [20].”
Kloske, C. M., Mahinrad, S., Barnum, C. J., Batista, A. F., Bradshaw, E. M., Butts, B., Carrillo, M. C., Chakrabarty, P., Chen, X., Craft, S., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14291 · Cited by 6 · see citing works
“85 These models are comprehensively characterized with all the models and data available without licensing restrictions, and data can be used for the evaluation of potential therapeutics.”
Self-citationIdentification of Potential Diagnostic Biomarkers of Carotid Atherosclerosis in Obese Populations
Wu, X., Pan, J., Pan, X., Kang, J., Ren, J., Huang, Y., Gong, L., & Li, Y. (2025) · Journal of Inflammation Research · doi:10.2147/jir.s504480 · Cited by 5 · see citing works
Multi-omics analyses reveal novel effects of PLCγ2 deficiency in the mouse brain
Hopp, S. C., Rogers, J. G., Smith, S., Campos, G., Miller, H., Barannikov, S., Kuri, E. G., Wang, H., Han, X., Bieniek, K. F., et al. (2023) · doi:10.1101/2023.12.06.570499 · Cited by 4 · see citing works
“Expression of PLCγ2 M28L in the mouse brain led to a transcriptomic profile that correlated with human AD modules and led to increased microglia density when fed with a high fat diet (17).”
BackgroundGuan, Y., Cheng, C. H., Bellomo, L. I., Narain, S., Bigornia, S., Garelnabi, M., Scott, T. M., Ordovás, J. M., Tucker, K. L., Bhadelia, R. A., et al. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1285333 · Cited by 4 · see citing works
Chie, J. A. K. C., Persohn, S. A., Simcox, O. R., Collins, A., Salama, P., & Territo, P. R. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71496 · Cited by 1 · see citing works
Self-citationFrom consortia discovery to biotech creation: An innovative approach to next‐gen Alzheimer's drugs
Giardina, S. F., Culver, A. E., Ahmed, C., Mirescu, C., Oblak, A. L., Brosch, J. R., Clayton, B., Dage, J. L., Lamb, B. T., Richardson, T. I., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71165 · Cited by 2 · see citing works
“13 Both academic and industry partners can leverage these outputs to explore nonclinical therapeutic potential in MODEL-AD systems (often in direct partnership) and bolster confidence in downstream discovery investments.”
Self-citationOblak, A. L., Sasner, M., Carter, G. W., Howell, G. R., Rizzo, S. J. S., Leal, K., Territo, P. R., & Lamb, B. T. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71741 · Cited by 1 · see citing works
Self-citationGutierrez-Kuri, E., Marie Garcia-Rogers, J. L., Perez, J., Smith, S., Kenwood, M. R., Archuleta, K. S., Xiao, Y., Campos, G., Barannikov, S., Wang, H., et al. (2026) · doi:10.64898/2026.07.13.738356
APOE Polymorphism and Brain Imaging
Obenaus, A., & Territo, P. R. (2025) · Springer eBooks · doi:10.1007/978-3-031-52641-1_69-1
Self-citationPLCG2 signaling and genetic resilience in Alzheimer’s disease
Tsai, A. P., Martin, A. K., Mi, A., Yeh, A. E., Ramirez Lopez, E., & Wyss-Coray, T. (2026) · Molecular Neurodegeneration · doi:10.1186/s13024-026-00935-3
Self-citationUnderstanding the contribution of toxicant exposures to Alzheimer’s disease and related dementias
Howell, G. R., Territo, P. R., Aylor, D. L., & Goldstein, L. E. (2026) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2026.103192
Self-citationKotredes, K. P., Pandey, R. S., Reagan, A. M., Sarica, Z., O’Rourke, R., Herrick, S., Davis, A., Garceau, D. T., Sasner, M., Carter, G. W., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.08.25.746973
Self-citationKotredes, K. P., Pandey, R. S., Reagan, A. M., Sarica, Z., O’Rourke, R., Herrick, S., Davis, A., Garceau, D., Sasner, M., Carter, G. W., et al. (2026) · Research Square · doi:10.21203/rs.3.rs-11166891/v1
Self-citation
- Authors
- Oblak, A. L., Kotredes, K. P., Pandey, R. S., Reagan, A. M., Ingraham, C., Perkins, B., Lloyd, C., Baker, D., Lin, P. B., Soni, D. M., Tsai, A. P., Persohn, S. A., Bedwell, A. A., Eldridge, K., Speedy, R., Meyer, J. A., Peters, J. S., Figueiredo, L. L., Sasner, M., Territo, P. R., Sukoff Rizzo, S. J., Carter, G. W., Lamb, B. T., & Howell, G. R.
- Affiliations
- Indiana University Indianapolis (US)
- Jackson Laboratory (US)
- Indiana University School of Medicine
- Corresponding author
- Oblak, Adrian L.
- Howell, Gareth R.
- ORCID
- Venue
- Frontiers in Aging Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2022-06-24
- Volume
- 14
- Pages
- 886575-886575
- ISSN
- 1663-4365 (ISSN-L)
- PMC
- PMC9263289
- OpenAlex
- W4283460059
- Semantic Scholar
- 6a5aab1c31a9bb811afe93337b9a73943d5ccf96
- Cited by
- 23
- References
- 75
- Citations by year
- 2026: 8 · 2025: 4 · 2024: 7 · 2023: 3 · 2022: 1
- FWCI
- 1.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Aging Neuroscience (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- IUScholarWorks (Indiana University) (submittedVersion, cc-by)
- PubMed Central (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (U54AG054345, K01AG054753)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, late-onset Alzheimer's disease, high-fat high-sugar diet, obesity, APOE ε4, genetic risk factors, brain glucose metabolism, cerebral perfusion, cholesterol, glucose, lifestyle intervention
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