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Biomedical subjects

Aron C Eklund

Publications and source records attributed to Aron C Eklund.

7 recordsLinked to original sources
PubMed2007

Molecular markers of early Parkinson's disease based on gene expression in blood.

Parkinson's disease (PD) progresses relentlessly and affects five million people worldwide. Laboratory tests for PD are critically needed for developing treatments designed to slow or prevent progression of the disease. We performed a transcriptome-wide scan in 105 individuals to interrogate the molecular processes perturbed in cellular blood of patients with early-stage PD. The molecular multigene marker here identified is associated with risk of PD in 66 samples of the training set comprising healthy and disease controls [third tertile cross-validated odds ratio of 5.7 (P for trend 0.005)]. It is further validated in 39 independent test samples [third tertile odds ratio of 5.1 (P for trend 0.04)]. Insights into disease-linked processes detectable in peripheral blood are offered by 22 unique genes differentially expressed in patients with PD versus healthy individuals. These include the co-chaperone ST13, which stabilizes heat-shock protein 70, a modifier of alpha-synuclein misfolding and toxicity. ST13 messenger RNA copies are lower in patients with PD (mean +/- SE 0.59 +/- 0.05) than in controls (0.96 +/- 0.09) (P = 0.002) in two independent populations. Thus, gene expression signals measured in blood can facilitate the development of biomarkers for PD.

Biomarkers↗
PubMed2006

A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers.

We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors.

Aneuploidy↗
PubMed2006

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.

Equipment Design↗
PubMed2005

Reliability and reproducibility issues in DNA microarray measurements.

DNA microarrays enable researchers to monitor the expression of thousands of genes simultaneously. However, the current technology has several limitations. Here we discuss problems related to the sensitivity, accuracy, specificity and reproducibility of microarray results. The existing data suggest that for relatively abundant transcripts the existence and direction (but not the magnitude) of expression changes can be reliably detected. However, accurate measurements of absolute expression levels and the reliable detection of low abundance genes are difficult to achieve. The main problems seem to be the sub-optimal design or choice of probes and some incorrect probe annotations. Well-designed data-analysis approaches can rectify some of these problems.

Animals↗
PubMed2005

Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements.

BACKGROUND: Comparison of data produced on different microarray platforms often shows surprising discordance. It is not clear whether this discrepancy is caused by noisy data or by improper probe matching between platforms. We investigated whether the significant level of inconsistency between results produced by alternative gene expression microarray platforms could be reduced by stringent sequence matching of microarray probes. We mapped the short oligo probes of the Affymetrix platform onto cDNA clones of the Stanford microarray platform. Affymetrix probes were reassigned to redefined probe sets if they mapped to the same cDNA clone sequence, regardless of the original manufacturer-defined grouping. The NCI-60 gene expression profiles produced by Affymetrix HuFL platform were recalculated using these redefined probe sets and compared to previously published cDNA measurements of the same panel of RNA samples. RESULTS: The redefined probe sets displayed a substantially higher level of cross-platform consistency at the level of gene correlation, cell line correlation and unsupervised hierarchical clustering. The same strategy allowed an almost complete correspondence of breast cancer subtype classification between Affymetrix gene chip and cDNA microarray derived gene expression data, and gave an increased level of similarity between normal lung derived gene expression profiles using the two technologies. In total, two Affymetrix gene-chip platforms were remapped to three cDNA platforms in the various cross-platform analyses, resulting in improved concordance in each case. CONCLUSION: We have shown that probes which target overlapping transcript sequence regions on cDNA microarrays and Affymetrix gene-chips exhibit a greater level of concordance than the corresponding Unigene or sequence matched features. This method will be useful for the integrated analysis of gene expression data generated by multiple disparate measurement platforms.

Breast Neoplasms↗
PubMed2003

Spatiotemporal patterns of gene expression during fetal monkey brain development.

Human DNA microarrays are used to study the spatiotemporal patterns of gene expression during the course of fetal monkey brain development. The 444 most dynamically expressed genes in four major brain areas are reported at five different fetal ages. The spatiotemporal profiles of gene expression show both regional specificity as well as waves of gene expression across the developing brain. These patterns of expression are used to identify statistically significant clusters of co-regulated genes. This study demonstrates for the first time in the primate the relevance, timing, and spatial locations of expression for many developmental genes identified in other animals and provides clues to the functions of many unknowns. Two different microarray platforms are used to provide high-throughput cross validation of the most important gene expression changes. These results may lead to new understanding of brain development and new strategies for treating and repairing disorders of brain function.

Animals↗