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Thompson, Matthew D.; Knee, Kathleen; Golden, Charles J.

doi:10.1023/a:1025627106073

Cited by 34 publications

(5 citation statements)

References 33 publications

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“…This data will allow models to account for neuron groups in specific brain regions, subcellular heterogeneity within cells, and the inclusion of less abundant glial cells. For example, higher-resolution models may provide insight into metabolic changes that occur in specific cell populations, such as the structures closely related to the olfactory system, which are affected in the early stages of Alzheimer’s disease37.…”

Section: Discussionmentioning

confidence: 99%

Large-scale in silico modeling of metabolic interactions between cell types in the human brain

et al. 2010

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A workflow is presented that integrates gene expression data, proteomic data, and literature-based manual curation to construct multicellular, tissue-specific models of human brain energy metabolism that recapitulate metabolic interactions between astrocytes and various neuron types. Three analyses are applied for gene identification, analysis of omics data, and analysis of physiological states. First, we identify glutamate decarboxylase as a target that may contribute to cell-type and regional specificity in Alzheimer’s disease. Second, the decreased metabolic rate seen in affected brain regions in Alzheimer’s disease is consistent with a suppression of central metabolic gene expression in histopathologically normal neurons. Third, we identify pathways in cholinergic neurons that couple mitochondrial metabolism and cytosolic acetylcholine production, and subsequently find that cholinergic neurotransmission accounts for ∼3% of brain neurotransmission. Constraint-based modeling can thus contribute to the study and analysis of multicellular metabolic processes in human tissues, and provide detailed mechanistic insight into high-throughput data analysis.

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Section: Discussionmentioning

confidence: 99%

Large-scale in silico modeling of metabolic interactions between cell types in the human brain

et al. 2010

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“…The olfactory bulb is a network highly sensitive to AD pathology [1-10,15,20,23], and it is one of the first brain structures to accumulate Aβ; it shows functional deterioration even before other neural networks involved in cognitive performance, such as the hippocampus and the cholinergic nuclei [15,82]. As the brain becomes older, it becomes more sensitive to several insults.…”

Section: Discussionmentioning

confidence: 99%

“…In recent decades, it has been demonstrated that at very early stages, Alzheimer’s patients find it difficult to detect, discriminate, and identify odors [1-6]. Such dysfunction has been correlated with early pathological findings such as sparse accumulation of amyloid beta protein (Aβ) in the olfactory bulb (OB) [7-11].…”

Section: Introductionmentioning

confidence: 99%

Amyloid Beta Inhibits Olfactory Bulb Activity and the Ability to Smell

2013

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Early olfactory dysfunction has been consistently reported in both Alzheimer’s disease (AD) and in transgenic mice that reproduce some features of this disease. In AD transgenic mice, alteration in olfaction has been associated with increased levels of soluble amyloid beta protein (Aβ) as well as with alterations in the oscillatory network activity recorded in the olfactory bulb (OB) and in the piriform cortex. However, since AD is a multifactorial disease and transgenic mice suffer a variety of adaptive changes, it is still unknown if soluble Aβ, by itself, is responsible for OB dysfunction both at electrophysiological and behavioral levels. Thus, here we tested whether or not Aβ directly affects OB network activity in vitro in slices obtained from mice and rats and if it affects olfactory ability in these rodents. Our results show that Aβ decreases, in a concentration- and time-dependent manner, the network activity of OB slices at clinically relevant concentrations (low nM) and in a reversible manner. Moreover, we found that intrabulbar injection of Aβ decreases the olfactory ability of rodents two weeks after application, an effect that is not related to alterations in motor performance or motivation to seek food and that correlates with the presence of Aβ deposits. Our results indicate that Aβ disrupts, at clinically relevant concentrations, the network activity of the OB in vitro and can trigger a disruption in olfaction. These findings open the possibility of exploring the cellular mechanisms involved in early pathological AD as an approach to reduce or halt its progress.

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“…Olfactory dysfunction is regarded as an early warning sign of Parkinson’s disease (Louis et al, 2008, Mollenhauer et al, 2013, Ross et al, 2012), Alzheimer’s Disease (Murphy et al, 1990, Thompson et al, 1998, Wang et al, 2010), and cognitive decline (Royall et al, 2002, Seo et al, 2009, Sohrabi et al, 2012, Swan and Carmelli, 2002). Given that lead, pesticides like DDT and other environmental exposures also show associations with these diseases (Richardson et al, 2014, Richardson et al, 2009, Weisskopf et al, 2010), and are known to be rhinotoxic in occupationally exposed populations and animal models (Sunderman, 2001), it is plausible that environmental exposures such as lead could also be related to olfactory dysfunction.…”

Section: Introductionmentioning

confidence: 99%

Cumulative lead exposure is associated with reduced olfactory recognition performance in elderly men: The Normative Aging Study

Grashow

Sparrow

et al. 2015

NeuroToxicology

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Introduction Olfactory dysfunction has been identified as an early warning sign for Alzheimer’s disease, Parkinson’s disease, dementia and more. A few occupational and environmental exposures have also been associated with reduced olfactory function, although the effects of long term environmental exposure to lead on olfactory dysfunction have not been explored. Here we performed olfactory recognition testing in elderly men in a community-dwelling cohort and examined the association with cumulative lead exposure, as assessed by lead in tibial and patellar bone. Methods Olfactory recognition was measured in 165 men from the Normative Aging Study (NAS) who had previously taken part in bone lead measurements using K-X-Ray fluorescence (KXRF). Olfactory recognition was measured using the University of Pennsylvania Smell Identification Test (UPSIT). Associations between olfactory recognition, global cognition and cumulative lead exposure were estimated using linear regression, with additional adjustment for age, smoking, and functional polymorphism status for hemochromatosis (HFE), transferrin (TfC2), glutathione-s-transferase Pi1 (GSTP1) and apolipoprotein E (APOE) genotypes. Sensitivity analyses explored olfactory recognition in men with high global cognitive function as measured using the Mini-Mental Status Exam (MMSE). Results The average age of the NAS participants at the time of olfactory recognition testing was 80.3 (standard deviation or SD = 5.7) years. Mean tibia lead was 16.3 (SD = 12.0) μg/g bone, mean patella lead was 22.4 (SD = 14.4) μg/g bone, and mean UPSIT score was 26.9 out of 40 (SD = 7.0). Consistent with previous findings, age at olfaction testing was negatively associated with UPSIT score. Tibia (but not patella) bone lead was negatively associated with olfaction recognition (per 15 μg/g tibia lead: β = −1.57; 95% CI: −2.93, −0.22; p = 0.02) in models adjusted for smoking and age. Additional adjustment for education did not significantly change results. Of all the genes explored, only the presence of one or more HFE variant alleles was significantly associated with olfaction recognition (HFE β = 2.26; 95% CI: 0.09, 4.43; p = 0.04). In a model containing the HFE term and a lead term, the tibia lead parameter estimate dropped by 21% (per 15 μg/g tibia lead: β = −1.25; 95% CI: −2.64, 0.14; p = 0.08) while the HFE term dropped 15% (β = 1.91; 95% CI: −0.28, 4.10; p=0.09). None of the other gene terms were associated with olfactory recognition in this cohort, nor were any gene-lead interaction terms significant. Additional sensitivity analysis in men with MMSE scores of 25 or higher (n = 149) showed a similar but slightly attenuated association between lead and olfactory recognition (per 15 μg/g tibia lead β = −1.39; 95% CI: −3.00, 0.22; p = 0.09) Conclusion Cumulative exposure to lead is associated with reduced olfactory recognition in a cohort of elderly men. The association was similar but not significant in men with better cognitive function as measured by the MMSE. Iron metabolism gene sta...

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Untitled

Cited by 34 publications

References 33 publications

Large-scale in silico modeling of metabolic interactions between cell types in the human brain

Large-scale in silico modeling of metabolic interactions between cell types in the human brain

Amyloid Beta Inhibits Olfactory Bulb Activity and the Ability to Smell

Cumulative lead exposure is associated with reduced olfactory recognition performance in elderly men: The Normative Aging Study

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