Detailed Experimental Procedures

Detailed experimental Procedures Reagents. Murine Dkk1 cDNA and the pPrP vector were gifted by C. Niehrs (Heidelberg) and D. Borchelt (Johns Hopkins) respectively. Recombinant Dkk proteins, anti-mDkk1 antibody (MAB1765) and mDkk1 ELISA were from R&D systems (Abingdon, UK) and were each used at 800 ng/ml an empirically derived dose which blocks recombinant maximal Wnt3a activation of the TOPflash reporter gene; JNK inhibitors, Merck Chemicals Ltd (Nottm, UK); A25-35 and A35-25 peptides, Bachem (Weil am Rhein, Germany) and A1-42 from Dr. David Teplow (UCLA, California, USA). All other reagents have been described previously 1. Microarray hybridization and analysis. Total RNA was isolated from primary neurons, processed and hybridised to murine U74v2.0 or rat U230v2.0 microarrays as described 2. Raw data were transferred to a R v 2.6.0 environment (http://www.r- project.org/) and analysed using BioConductor (http://www.bioconductor.org/). Data were normalized by RMA. Empirical Bayes moderated t-statistics test was used to identify differentially expressed probe sets and q-values calculated using the FDR method of Benjamini and Hochberg 3. The method of Storey and Tibshirani was used to correct for multiple testing. The statistical probability of the same five genes appearing in the top eight of the A and Dkk1 gene lists after ranking by fold change was determined by performing a hypergeometric distribution calculation. A test for similarities in the ordering of the ranked gene lists was performed using the OrderedLists software package within the Bioconductor R environment. (http://www.bioconductor.org/packages/release/bioc/html/OrderedList.html). Cell survival assays. LDH. LDH assay was performed according to the manufacturer’s instructions (Promega, Poole, UK). Values are percentage of maximum LDH release following addition of Triton-X100. Cell viability. Following treatment medium was removed, cellular and cytoplasmic membranes lysed with detergent buffer generating a suspension of single, intact nuclei 4, which were counted using a haemocytometer. Broken or damaged nuclei were excluded. Dual staining. Calcein-AM is taken up by living cells and emits at 515 nm. Ethidium homodimer III can only intercalate with the DNA through disrupted membranes in dying cells and emits at 620 nm. Neurons on coverslips were treated, washed, fixed (4% paraformaldehyde), blocked (0.5% BSA), stained with 2 μM calcein-AM and 4 μM ethidium homodimer III (PromoCell, GmbH, Germany) and imaged by fluorescence microscopy. Transgenic mouse generation. The murine DKK1 ORF was amplified by PCR and cloned into the pPrP vector containing the promoter exons 1, 2 and 3 of mouse PrP and verified by sequencing. Transgenic mice were generated by microinjection into pronuclei of C57BL/6J x CBA/Ca embryos, and a DKK1 mouse line established. Transgenic animals were identified by PCR using primers 5’TATGAGGGCGGGAACAAGTA3’ and 5’GTCTGATGATCGGAGGCAGA3’, giving a 396 bp diagnostic amplicon. Contextual Fear Conditioning. Animals were group housed until 12-14 months of age. 2 weeks prior to, and during conditioning animals were individually housed. All experiments were carried out in accordance with United Kingdom Animals (Scientific Procedures) Act, 1986. For contextual fear conditioning, mice were placed into the conditioning chamber for a 2 min exploratory period, presented with an 80 dB sound for 30 s and a 0.20 mA foot shock (US) for the final 2 s followed by 30 s silence, repeated 5 times. After the final US, the mice were left in the chamber for 30 s and placed back in the home cages. 24 h post-training animals were reintroduced to the chamber and freezing behaviour, defined as the absence of all movement except that required for breathing, was recorded for 5 min using StartFear Software (Panlab, Harvard Apparatus).

Bioinformatic analyses. Gene set association of DKK1 responsive genes. To test whether Dkk1-responsive genes were associated with AD in man, we selected the top fifty genes (Dkk1 gene set) from the rat neuronal microarray analysis after ranking by p value of change. The human orthologous of the Dkk1 gene set were obtained from the Rat Genome Database (RGD) and transcripts matching human Entrez IDs were extracted from two human brain gene expression data sets 6, 7. All microarray data sets were downloaded from the Gene Expression Omnibus (GEO) database. The first data set (GSE15222) contains expression data from cortical regions of 176 late-onset AD (LOAD) patients and 187 neurologically normal controls 7. Illumina Human Refseq-8 Expression BeadChip arrays were used in this study and expression profiles of 25 genes from the Dkk1 gene set were extracted after rank invariant normalization. The log10 transformed expression values were adjusted for age, gender, cortical region, apolipoprotein E (APOE) allele dosage, and postmortem interval, date of hybridization, and site using linear regression. Dkk1 gene set association was tested using the globaltest method 8. In the model, a logistic regression model was fitted using disease status as the response, and residuals of the genes from the regression as predictor variables. In the second data set (GSE5281), neurons were collected by laser-capture microdissection from six different brain regions: Entorhinal cortex (13 controls, 10 AD), Hippocampus (13 controls, 10 AD), Mid temporal gyrus (11 controls, 23 AD), Posterior frontal gyrus (13 controls, 9 AD), Superior frontal gyrus (13 controls, 10 AD), and Primary visual cortex (11 controls, 9 AD) 6. The Robust Multichip Average (RMA) method was used to obtain the gene expression profiles from the raw data (Affymetrix .CEL files). Forty four genes of the Dkk1 gene set were reliably detected in this study and the association test with disease status was performed using the global test method. To evaluate the DKK1 gene set association with Down’s syndrome (DS), we used a gene expression data set (GSE5390) from dorsolateral prefrontal cortex of seven DS patients and eight controls 9. Normalized expression values of 38 genes of the Dkk1 gene set were obtained using the RMA method and tested for the global association with DS as described above. KEGG Pathway analyses. A total of 138,894 interactions (edges) between 13,562 proteins (nodes) were downloaded from the human subset of the I2D dataset (Interologous Interaction Database) 10. Cytoscape 11 was used to construct a protein- protein interaction network from this dataset. After mapping Dkk1 gene names onto human UniProt Ids, we were able to map transcript fold changes and p-values with 8129 (60%) of these proteins. The jActiveModules plug-in 12 was used to identify sub- networks based on the significance of their aggregate changes in expression. We adjusted the score for size and used regional scoring with a search depth of 1 and max depth from start nodes of 2, using the top 50, 100, 1000 significantly responsive genes as seeds for identifying the modules. We then identified KEGG pathways that were significantly over represented within the highest scoring sub-network using the DAVID knowledgebase 13. Multiple testing was corrected for by the method of Benjamini and Hochberg 3.

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