Toward an Alzheimer's disease diagnosis via high‐resolution blood gene expression

Fehlbaum-Beurdeley, Pascale; Prado, Anne Charlotte Jarrige-Le; Pallares, Diego; Carriere, Jennifer; Guihal, Caroline; Soucaille, Cyril; Rouet, Fabien; Drouin, Dominique; Sol, Olivier; Jordan, Heather; Wu, Darong; Ling, Lei; Einstein, Richard; Schweighoffer, Fabien; Bracco, Laurent

doi:10.1016/j.jalz.2009.07.001

Cited by 72 publications

(62 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We and others have previously shown that disease biomarkers to classify AD with dementia from cognitively healthy individuals are present in blood [16,23,35] and an algorithm based on the gene expression of a selected set of genes can be used to identify those with an AD dementia [34][35][36]. We have now further extended these findings to also include AD in the pre-dementia stage of the disease.…”

Section: Discussionmentioning

confidence: 80%

“…Several independent studies have indicated that a blood-based test could be used for diagnostic profiling in neurological diseases [16][17][18][19][20][21][22][23][24]. Lönneborg [21] summarized in 2008 that of several studies that investigated plasma A␤ levels in AD; one study showed an increase in A␤ levels [25] and the majority of studies found no significant differences between AD and controls [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prediction of Mild Cognitive Impairment that Evolves into Alzheimer's Disease Dementia within Two Years using a Gene Expression Signature in Blood: A Pilot Study

Roed

Grave

Lindahl

et al. 2013

JAD

View full text Add to dashboard Cite

Background: The focus on Alzheimer's disease (AD) is shifting from dementia to the prodromal stage of the disorder, to a large extent due to increasing efforts in trying to develop disease modifying treatment for the disorder. For development of diseasemodifying drugs, a reliable and accurate test for identification of mild cognitive impairment (MCI) due to AD is essential. Objective: In the present study, MCI progressing to AD will be predicted using blood-based gene expression. Material and Methods: Gene expression analysis using qPCR was performed on blood RNA from a cohort of patients with amnestic MCI (aMCI; n = 66). Within the aMCI cohort, patients progressing to AD within 1 to 2 years were grouped as MCI converters (n = 34) and the patients remaining at the MCI stage after 2 years were grouped as stable MCI (n = 32). AD and control populations were also included in the study. Results: Multivariate statistical method partial least square regression was used to develop predictive models which later were tested using leave-one-out cross validation. Gene expression signatures that identified aMCI subjects that progressed to AD within 2 years with a prediction accuracy of 74%-77% were identified for the complete dataset and subsets thereof. Conclusion:The present pilot study demonstrates for the first time that MCI that evolves into AD dementia within 2 years may be predicted by analyzing gene expression in blood. Further studies will be needed to validate this gene signature as a potential test for AD in the predementia stage.

show abstract

Section: Discussionmentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Prediction of Mild Cognitive Impairment that Evolves into Alzheimer's Disease Dementia within Two Years using a Gene Expression Signature in Blood: A Pilot Study

Roed

Grave

Lindahl

et al. 2013

JAD

View full text Add to dashboard Cite

show abstract

“…Fehlbaum-Beurdeley et al [31] verified 133 genes in blood cells whose expression pattern may distinguish AD patients from controls. These genes were involved in five major pathways occurring in macrophages and lymphocytes, such as to the transforming growth factor-beta signaling, oxidative stress, cytoskeletal organization, inflammatory and immune responses, lipid-raft, cholesterol homeostasis and the ubiquitin proteasome system.…”

Section: Discussionmentioning

confidence: 99%

Ribosomal Genes Activity in Aged Down Syndrome Subjects

Goncalves¹,

Ávalos²,

Chen³

et al. 2011

TOGERIMJ

View full text Add to dashboard Cite

Abstract:Objective: We aimed to investigate whether rRNA 28S/18S levels decrease with aging in Down Syndrome (DS) individuals and whether these decreased levels are tissue-specific. Methods:We investigated mature rRNA 28S/18S levels by Northern Blotting in blood cells from 21 younger and 21 older DS individuals in comparison to 42 age-sex-matched controls. We also investigated these levels in oral mucosa and in blood cells from the same DS individuals.Results: All DS subjects showed no clinical signs of dementia at the time of the study. We did not detect differences in rRNA 28S/18S levels among DS and control groups concerning either aging process or cell types.Conclusions: Aging process in DS individuals was not characterized by reduced rDNA transcriptional activity and did not indicate a preclinical marker of AD in older DS subjects.

show abstract

“…"signatures" in blood, detectable using microarrays [51,52]. Notably, melanoma also has a characteristic signature in blood due to reduced interferon signaling (which is not necessarily melanoma-specific, however) [53].…”

Section: Skinomics In Our Futurementioning

confidence: 99%

SKINOMICS: Transcriptional Profiling in Dermatology and Skin Biology

Blumenberg¹

2015

Encyclopedia of Metagenomics

View full text Add to dashboard Cite

Recent years witnessed the birth of bioinformatics technologies, which greatly advanced biological research. These 'omics' technologies address comprehensively the entire genome, transcriptome, proteome, microbiome etc. A large impetus in development of bioinformatics was the introduction of DNA microarrays for transcriptional profiling. Because of its accessibility, skin was among the first organs analyzed using DNA microarrays, and dermatology among the first medical disciplines to embrace the approach. Here, DNA microarray methodologies and their application in dermatology and skin biology are reviewed. The most studied disease has been, unsurprisingly, melanoma; markers of melanoma progression, metastatic potential and even melanoma markers in blood have been detected. The basal and squamous cell carcinomas have also been intensely studied. Psoriasis has been comprehensively explored using DNA microarrays, transcriptional changes correlated with genomic markers and several signaling pathways important in psoriasis have been identified. Atopic dermatitis, wound healing, keloids etc. have been analyzed using microarrays. Noninvasive skin sampling for microarray studies has been developed. Simultaneously, epidermal keratinocytes have been the subject of many skin biology studies because they respond to a rich variety of inflammatory and immunomodulating cytokines, hormones, vitamins, UV light, toxins and physical injury. The transcriptional changes occurring during epidermal differentiation and cornification have been identified and characterized. Recent studies identified the genes specifically expressed in human epidermal stem cells. As dermatology advances toward personalized medicine, microarrays and related 'omics' techniques will be directly applicable to the personalized dermatology practice of the future.

show abstract

Toward an Alzheimer's disease diagnosis via high‐resolution blood gene expression

Cited by 72 publications

References 66 publications

Prediction of Mild Cognitive Impairment that Evolves into Alzheimer's Disease Dementia within Two Years using a Gene Expression Signature in Blood: A Pilot Study

Prediction of Mild Cognitive Impairment that Evolves into Alzheimer's Disease Dementia within Two Years using a Gene Expression Signature in Blood: A Pilot Study

Ribosomal Genes Activity in Aged Down Syndrome Subjects

SKINOMICS: Transcriptional Profiling in Dermatology and Skin Biology

Contact Info

Product

Resources

About