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. Author manuscript; available in PMC: 2011 Jun 1.
Published in final edited form as: Clin Lipidol. 2010 Aug 1;51(4):555–573. doi: 10.2217/CLP.10.37

Figure 1. Expression of apolipoproteins APO-A1, -A2, -A4 and -A5 during development of the human prefrontal cortex.

Figure 1

(A) Expression of APOA1. (B) Expression of APOA2. (C) Expression of APOA4. (D) Expression of APOA5. Data are derived from an Affymetrix GeneChip (HG-U133_Plus_2) microarray study conducted by Harris et al. [8] and accessible at the National Center for Biotechnology Information Gene Expression Omnibus database [7,303]. Fresh-frozen post-mortem prefrontal cortex tissue (Brodman area 46) was obtained from 44 individuals varying from 0 to 49 years of age. RNA was extracted from these samples and hybridized to HG133plus2.0 GeneChips. The data were used to examine patterns of gene expression over the course of human postnatal developmental and aging. Seven developmental periods are defined as neonate (<3 months: black), infant (3 months to <1 year: green), toddler (1 year to <5 years: red), school age (5 years to <13 years: dark blue), teenage (13 years to <20 years: light blue), young adult (20 years to <26 years: yellow) and adult (35 years to <50 years: purple). Data are plotted for both sexes (males: circles; females: triangles). Gene expression values that are less than 60 are below the limit of reliable detection, and genes with expression values in this range are, therefore, considered not to be expressed in the brain. The p-values shown were calculated as follows. Affymetrix Microarray Suite (MAS5.0) was used for image processing and data acquisition. The Bioconductor package was used to compute normalized expression values from the Affymetrix.cel files. Statistical analysis was performed using R and Bioconductor soft ware (Free Software Foundation, Boston, MA, USA). Probe sets that met the criteria of being 50% present in at least one of the age subgroups were retained in the analysis (33,210 probe sets retained; 61% of total number). Differential gene expression across chronological age was analyzed by linear regression comparing age (log scale) with gene expression (log scale) as the dependent variable. Statistical models in Supplementary Affymetrix Microarray Suite (MAS 5.0) was used for image processing and data acquisition.