Additional file 1: of TMEM106B haplotypes have distinct gene expression patterns in aged brain

Table S1. Tissue samples available and selected for inclusion in this study. Table S2. DEGS in TCX. Positive fold change represents higher gene expression in SS than TT. Negative fold change represents lower gene expression in SS than TT. Table S3. DEGS in CER. Positive fold change represents higher gene expression in SS than TT. Negative fold change represents lower gene expression in SS than TT. Table S4. Overlapping genes between TCX and CER based on top 500 genes with |FC| ≥ 1.2 ranked by unadjusted p value. Table S5. Enrichment of modules for their respective DEG signatures. Table S6. Significant modules identified in the TCX and CER matched cases. Table S7. Significant modules identified in separate disease groups in TCX and CER. Table S8. Significant modules identified in the TCX and CER controls. (DOCX 54 kb

Additional file 3: of Identification of missing variants by combining multiple analytic pipelines

Table S3. The percentage of known and novel variants in BWA-unique, Novo-unique and shared variants. (DOCX 13 kb

Additional file 2: of Identification of missing variants by combining multiple analytic pipelines

Table S2. The composition of Tier 1, 2 and 3 variants in BWA-unique, Novo-unique and shared variants. (DOCX 13 kb

Additional file 1: of Identification of missing variants by combining multiple analytic pipelines

Table S1. The genomic location and GC content of BWA-unique, Novo-unique and shared variants. (DOCX 14 kb

Additional file 4: of Identification of missing variants by combining multiple analytic pipelines

Table S4. The genomic location and GC content of multi-unique, single-unique and shared variants. (DOCX 14 kb

Additional file 7: of Identification of missing variants by combining multiple analytic pipelines

Table S7. The full list of variants identified in APP, PSEN1 and PSEN2 by each workflow. (XLSX 14 kb

Additional file 5: of Identification of missing variants by combining multiple analytic pipelines

Table S5. The composition of Tier 1, 2 and 3 variants in multi-unique, single-unique and shared variants. (DOCX 14 kb

Additional file 6: of Identification of missing variants by combining multiple analytic pipelines

Table S6. The percentage of known and novel variants in multi-unique, single-unique and shared variants. (DOCX 13 kb

LRRTM3 Interacts with APP and BACE1 and Has Variants Associating with Late-Onset Alzheimer’s Disease (LOAD)

<div><p>Leucine rich repeat transmembrane protein 3 (LRRTM3) is member of a synaptic protein family. <i>LRRTM3</i> is a nested gene within α-T catenin (<i>CTNNA3</i>) and resides at the linkage peak for late-onset Alzheimer’s disease (LOAD) risk and plasma amyloid β (Aβ) levels. <i>In-vitro</i> knock-down of <i>LRRTM3</i> was previously shown to decrease secreted Aβ, although the mechanism of this is unclear. In SH-SY5Y cells overexpressing APP and transiently transfected with LRRTM3 alone or with BACE1, we showed that LRRTM3 co-localizes with both APP and BACE1 in early endosomes, where BACE1 processing of APP occurs. Additionally, LRRTM3 co-localizes with APP in primary neuronal cultures from Tg2576 mice transduced with LRRTM3-expressing adeno-associated virus. Moreover, LRRTM3 co-immunoprecipitates with both endogenous APP and overexpressed BACE1, in HEK293T cells transfected with LRRTM3. SH-SY5Y cells with knock-down of <i>LRRTM3</i> had lower <i>BACE1</i> and higher <i>CTNNA3</i> mRNA levels, but no change in <i>APP</i>. Brain mRNA levels of <i>LRRTM3</i> showed significant correlations with <i>BACE1</i>, <i>CTNNA3</i> and <i>APP</i> in ∼400 humans, but not in <i>LRRTM3</i> knock-out mice. Finally, we assessed 69 single nucleotide polymorphisms (SNPs) within and flanking <i>LRRTM3</i> in 1,567 LOADs and 2,082 controls and identified 8 SNPs within a linkage disequilibrium block encompassing 5′UTR-Intron 1 of <i>LRRTM3</i> that formed multilocus genotypes (MLG) with suggestive global association with LOAD risk (p = 0.06), and significant individual MLGs. These 8 SNPs were genotyped in an independent series (1,258 LOADs and 718 controls) and had significant global and individual MLG associations in the combined dataset (p = 0.02–0.05). Collectively, these results suggest that protein interactions between LRRTM3, APP and BACE1, as well as complex associations between mRNA levels of <i>LRRTM3, CTNNA3, APP</i> and <i>BACE1</i> in humans might influence APP metabolism and ultimately risk of AD.</p></div

Expression levels of genes in brains of <i>Lrrtm3</i> knock-out, heterozygote and wild type mice.

<p>Bar graphs depicting mean gene expression levels and error bars representing the standard deviations obtained from the averages of 3 animals per genotypic group where expression levels from each mouse brain is assessed in quadruplicate. Expression values are obtained by the delta Ct method, where geometric mean of HPRT and GAPDH is utilized as the control gene expression values. Average expression values (2?(-delta Ct))x100 were plotted on the y-axis. The three mouse genotypic groups are color-coded as shown in the inset. The genes with expression level measurements are shown in groups, with gene names depicted on the x-axis.</p