Genomic atlas of the proteome from brain, CSF and plasma prioritizes proteins implicated in neurological disorders.

Understanding the tissue-specific genetic controls of protein levels is essential to uncover mechanisms of post-transcriptional gene regulation. In this study, we generated a genomic atlas of protein levels in three tissues relevant to neurological disorders (brain, cerebrospinal fluid and plasma) by profiling thousands of proteins from participants with and without Alzheimer's disease. We identified 274, 127 and 32 protein quantitative trait loci (pQTLs) for cerebrospinal fluid, plasma and brain, respectively. cis-pQTLs were more likely to be tissue shared, but trans-pQTLs tended to be tissue specific. Between 48.0% and 76.6% of pQTLs did not co-localize with expression, splicing, DNA methylation or histone acetylation QTLs. Using Mendelian randomization, we nominated proteins implicated in neurological diseases, including Alzheimer's disease, Parkinson's disease and stroke. This first multi-tissue study will be instrumental to map signals from genome-wide association studies onto functional genes, to discover pathways and to identify drug targets for neurological diseases.

Expression and splicing of ABC and SLC transporters in the human blood-brain barrier measured with RNAseq.

The blood-brain barrier (BBB) expresses numerous membrane transporters that supply needed nutrients to the central nervous system (CNS), consisting mostly of solute carriers (SLC transporters), or remove unwanted substrates via extrusion pumps through the action of ATP binding cassette (ABC) transporters. Previous work has identified many BBB transporters using hybridization arrays or qRT-PCR, using targeted probes. Here we have performed next-generation sequencing of the transcriptome (RNAseq) extracted from cerebral cortex tissues and brain microvessel endothelial cells (BMEC) obtained from two donors. The same RNA samples had previously been measured for transporter expression using qRT-PCR (Geier et al., 2013), yielding similar expression levels for overlapping mRNAs (R=0.66, p<0.001). RNAseq confirms a number of transporters highly enriched in BMECs (e.g., ABCB1, ABCG2, SLCO2B1, and SLC47A1), but also detects novel BMEC transporters. Multiple splice isoforms detected by RNAseq are either robustly enriched or depleted in BMECs, indicating differential RNA processing in the BBB. The Complete RNAseq data are publically available (GSE94064).

Regulation of cholesteryl ester transfer protein expression by upstream polymorphisms: reduced expression associated with rs247616.

BACKGROUND: Cholesteryl ester transfer protein (CETP) is involved in reverse cholesterol transport by exchanging cholesteryl esters for triglycerides between high-density lipoprotein and low-density lipoprotein particles, effectively decreasing high-density lipoprotein cholesterol levels. Variants within a large haplotype block upstream of CETP (rs247616, rs173539) have been shown to be significantly associated with reduced expression; however, the underlying mechanism has not been identified. METHODS: We analyzed the linkage structure of our top candidate single-nucleotide polymorphism (SNP), rs247616, and assessed each SNP of the haplotype block for potential interactions with transcription factor binding sites. We then used a reporter gene assay to assess the effect of three SNPs (rs247616, rs173539, and rs1723150) on expression in vitro. RESULTS: Several variants in the upstream haplotype, including rs247616, rs173539, and rs1723150, disrupt or generate transcription factor binding sites. In reporter gene assays, rs247616 and rs173539 were found to significantly affected expression in HepG2 cells, whereas rs17231506 had no effect. rs247616 decreased expression by 1.7-fold (P<0.0001), whereas rs173539 increased expression by 2.2-fold (P=0.0006). CONCLUSION: SNPs rs247616 and rs173539 are in high linkage disequilibrium (R=0.96, D'=1.00) and have the potential to regulate CETP expression. Although opposing effects suggest that regulation of CETP expression could vary between tissues, the minor allele of rs247616 and SNPs in high linkage with it were found to be associated with reduced expression across all tissues.

Allele-specific imbalance mapping at human orthologs of mouse susceptibility to colon cancer (Scc) loci.

Colorectal cancer (CRC) can be classified into different types. Chromosomal instable (CIN) colon cancers are thought to be the most common type of colon cancer. The risk of developing a CIN-related CRC is due in part to inherited risk factors. Genome-wide association studies have yielded over 40 single nucleotide polymorphisms (SNPs) associated with CRC risk, but these only account for a subset of risk alleles. Some of this missing heritability may be due to gene-gene interactions. We developed a strategy to identify interacting candidate genes/loci for CRC risk that utilizes both linkage and RNA-seq data from mouse models in combination with allele-specific imbalance (ASI) studies in human tumors. We applied our strategy to three previously identified CRC susceptibility loci in the mouse that show evidence of genetic interaction: Scc4, Scc5 and Scc13. 525 SNPs from genes showing differential expression in the mouse and/or a previous role in cancer from the literature were evaluated for allele-specific imbalance in 194 paired human normal/tumor DNAs from CIN-related CRCs. One hundred three SNPs showing suggestive evidence of ASI (31 variants with uncorrected p values < 0.05) were genotyped in a validation set of 296 paired DNAs. Two variants in SNX10 (SCC13) showed significant evidence of allelic selection after multiple comparisons testing. Future studies will evaluate the role of these variants in combination with interacting genetic partners in colon cancer risk in mouse and humans.

Genetic variants affecting alternative splicing of human cholesteryl ester transfer protein.

Cholesteryl ester transfer protein (CETP) plays an important role in reverse cholesterol transport, with decreased CETP activity increasing HDL levels. Formation of an alternative splice form lacking exon 9 (Δ9-CETP) has been associated with two single nucleotide polymorphisms (SNPs) in high linkage disequilibrium with each other, namely rs9930761 T>C located in intron 8 in a putative splicing branch site and rs5883 C>T in a possible exonic splicing enhancer (ESE) site in exon 9. To assess the relative effect of rs9930761 and rs5883 on splicing, mini-gene constructs spanning CETP exons 8 to 10, carrying all four possible allele combinations, were transfected into HEK293 and HepG2 cells. The minor T allele of rs5883 enhanced splicing significantly in both cell lines whereas the minor C allele of rs9930761 did not. In combination, the two alleles did not yield greater splicing than the rs5883 T allele alone in HepG2 cells. These results indicate that the genetic effect on CETP splicing is largely attributable to rs5883. We also confirm that Δ9-CETP protein is expressed in the liver but fails to circulate in the blood.

Statin pharmacogenomics: pursuing biomarkers for predicting clinical outcomes.

Indicated for treating hyperlipidemias and for the prevention of cardiovascular disease (CVD), statins rank among the most commonly prescribed drug classes. While statins are considered to be highly effective in preventing atherosclerotic events, a substantial portion of treated patients still progress to overt CVD. Genetic factors are thought to contribute substantially to treatment outcome. Several candidate genes have been associated with statin dose requirements and treatment outcomes, but a clinically relevant pharmacogenomics test to guide statin therapy has not yet emerged. Here we define basic pharmacogenomics terminology, present strong candidate genes (CETP, HMGCR, SLCO1B1, ABCB1, and CYP3A4/5), and discuss the challenges in developing much-needed statin pharmacogenomics biomarkers for predicting treatment outcomes.

Whole transcriptome RNA-Seq allelic expression in human brain.

BACKGROUND: Measuring allelic RNA expression ratios is a powerful approach for detecting cis-acting regulatory variants, RNA editing, loss of heterozygosity in cancer, copy number variation, and allele-specific epigenetic gene silencing. Whole transcriptome RNA sequencing (RNA-Seq) has emerged as a genome-wide tool for identifying allelic expression imbalance (AEI), but numerous factors bias allelic RNA ratio measurements. Here, we compare RNA-Seq allelic ratios measured in nine different human brain regions with a highly sensitive and accurate SNaPshot measure of allelic RNA ratios, identifying factors affecting reliable allelic ratio measurement. Accounting for these factors, we subsequently surveyed the variability of RNA editing across brain regions and across individuals. RESULTS: We find that RNA-Seq allelic ratios from standard alignment methods correlate poorly with SNaPshot, but applying alternative alignment strategies and correcting for observed biases significantly improves correlations. Deploying these methods on a transcriptome-wide basis in nine brain regions from a single individual, we identified genes with AEI across all regions (SLC1A3, NHP2L1) and many others with region-specific AEI. In dorsolateral prefrontal cortex (DLPFC) tissues from 14 individuals, we found evidence for frequent regulatory variants affecting RNA expression in tens to hundreds of genes, depending on stringency for assigning AEI. Further, we find that the extent and variability of RNA editing is similar across brain regions and across individuals. CONCLUSIONS: These results identify critical factors affecting allelic ratios measured by RNA-Seq and provide a foundation for using this technology to screen allelic RNA expression on a transcriptome-wide basis. Using this technology as a screening tool reveals tens to hundreds of genes harboring frequent functional variants affecting RNA expression in the human brain. With respect to RNA editing, the similarities within and between individuals leads us to conclude that this post-transcriptional process is under heavy regulatory influence to maintain an optimal degree of editing for normal biological function.