Differential microRNA response to a high-cholesterol, high-fat diet in livers of low and high LDL-C baboons

ABSTRACT: BACKGROUND: Dysregulation of microRNA (miRNA) expression has been implicated in molecular geneticevents leading to the progression and development of atherosclerosis. We hypothesized thatmiRNA expression profiles differ between baboons with low and high serum low-densitylipoprotein cholesterol (LDL-C) concentrations in response to diet, and that a subset of thesemiRNAs regulate genes relevant to dyslipidemia and risk of atherosclerosis. RESULTS: Using Next Generation Illumina sequencing methods, we sequenced hepatic small RNAlibraries from baboons differing in their LDL-C response to a high-cholesterol, high-fat(HCHF) challenge diet (low LDL-C, n = 3; high LDL-C, n = 3), resulting in 517 baboonmiRNAs: 490 were identical to human miRNAs and 27 were novel. We compared miRNAexpression profiles from liver biopsies collected before and after the challenge diet andobserved that HCHF diet elicited expression of more miRNAs compared to baseline (chow)diet for both low and high LDL-C baboons. Eighteen miRNAs exhibited differentialexpression in response to HCHF diet in high LDL-C baboons compared to 10 miRNAs in low LDL-C baboons. We used TargetScan/Base tools to predict putative miRNA targets;miRNAs expressed in high LDL-C baboons had significantly more gene targets thanmiRNAs expressed in low LDL-C responders. Further, we identified miRNA isomers andother non-coding RNAs that were differentially expressed in response to the challenge diet inboth high LDL-C and low LDL-C baboons. CONCLUSIONS: We sequenced and annotated baboon liver miRNAs from low LDL-C and high LDL-Cresponders using high coverage Next Gen sequencing methods, determined expressionchanges in response to a HCHF diet challenge, and predicted target genes regulated by thedifferentially expressed miRNAs. The identified miRNAs will enrich the database for noncodingsmall RNAs including the extent of variation in these sequences. Further, weidentified other small non-coding RNAs differentially expressed in response to diet. Ourdiscovery of differentially expressed baboon miRNAs in response to a HCHF diet challengethat differ by LDL-C phenotype is a fundamental step in understating the role of non-codingRNAs in dyslipidemia.     

Massive analysis of cDNA Ends (MACE) and miRNA expression profiling identifies proatherogenic pathways in chronic kidney disease

Epigenetic dysregulation contributes to the high cardiovascular disease burden in chronic kidney disease (CKD) patients. Although microRNAs (miRNAs) are central epigenetic regulators, which substantially affect the development and progression of cardiovascular disease (CVD), no data on miRNA dysregulation in CKD-associated CVD are available until now. We now performed high-throughput miRNA sequencing of peripheral blood mononuclear cells from ten clinically stable hemodialysis (HD) patients and ten healthy controls, which allowed us to identify 182 differentially expressed miRNAs (e.g., miR-21, miR-26b, miR-146b, miR-155). To test biological relevance, we aimed to connect miRNA dysregulation to differential gene expression. Genome-wide gene expression profiling by MACE (Massive Analysis of cDNA Ends) identified 80 genes to be differentially expressed between HD patients and controls, which could be linked to cardiovascular disease (e.g., KLF6, DUSP6, KLF4), to infection / immune disease (e.g., ZFP36, SOCS3, JUND), and to distinct proatherogenic pathways such as the Toll-like receptor signaling pathway (e.g., IL1B, MYD88, TICAM2), the MAPK signaling pathway (e.g., DUSP1, FOS, HSPA1A), and the chemokine signaling pathway (e.g., RHOA, PAK1, CXCL5). Formal interaction network analysis proved biological relevance of miRNA dysregulation, as 68 differentially expressed miRNAs could be connected to 47 reciprocally expressed target genes. Our study is the first comprehensive miRNA analysis in CKD that links dysregulated miRNA expression with differential expression of genes connected to inflammation and CVD. After recent animal data suggested that targeting miRNAs is beneficial in experimental CVD, our data may now spur further research in the field of CKD-associated human CVD.     

Genotype-by-diet effects on co-variation in Lp-PLA2 activity and LDL-cholesterol concentration in baboons fed an atherogenic diet

Both lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) activity, a biomarker of inflammation, and concentration of its primary associated lipoprotein, LDL, are correlated with adverse coronary outcomes. We previously reported a quantitative trait locus (QTL) corresponding to HSA2p24.3-p23.2 with pleiotropic effects on Lp-PLA(2) activity and LDL-cholesterol (LDL-C) concentration in baboons fed a basal diet. Here, our goal was to locate pleiotropic QTLs influencing both traits in the same baboons fed a high-cholesterol, high-fat (HCHF) diet, and to assess whether shared genetic effects on these traits differ between diets. We assayed Lp-PLA(2) activity and LDL-C concentration in 683 baboons fed the HCHF diet. We used a bivariate maximum likelihood-based variance components approach in whole-genome linkage screens to locate a QTL [logarithm of odds (LOD) = 3.13, genome-wide P = 0.019] corresponding to HSA19q12-q13.2 with pleiotropic effects on Lp-PLA(2) activity and LDL-C levels in the HCHF diet. We additionally found significant evidence of genetic variance in response to diet for Lp-PLA(2) activity (P = 0.0017) and for LDL-C concentration (P = 0.00001), revealing a contribution of genotype-by-diet interaction to covariation in these two traits. We conclude that the pleiotropic QTLs detected at 2p24.3-p23.2 and 19q12-q13.2 on the basal and HCHF diets, respectively, exert diet-specific effects on covariation in Lp-PLA(2) activity and LDL-C concentration.     

Whole-genome sequencing identifies potential candidate genes for reproductive traits in pigs

Reproductive performance is a complex quantitative trait, that is determined by multiple genes, regulatory pathways and environmental factors. A list of major genes with large effect have been detected, although multiple QTLs are identified. To identify candidate genes for pig prolificacy, whole genome variants from five high- and five low-prolificacy Yorkshire sows were collected using whole-genome resequencing. A total of 13,955,609 SNPs and 2,666,366 indels were detected across the genome. Common differential SNPs and indels were identified between the two groups of sows. Genes encoding components of the TGF-beta signaling pathway were enriched with the variations, including BMP5, BMP6, BMP7, ACVR1, INHBA, ZFYVE9, TGFBR2, DCN, ID4, BAMBI, and ACVR2A. Several differential variants within these genes related to reproductive traits were identified to be associated with litter size. A comparison of selective regions and published QTL data suggests that NEDD9, SLC39A11, SNCA, and UNC5D are candidate genes for reproduction traits.     

The Impact of 3′UTR Variants on Differential Expression of Candidate Cancer Susceptibility Genes

Variants in regulatory regions are predicted to play an important role in disease susceptibility of common diseases. Polymorphisms mapping to microRNA (miRNA) binding sites have been shown to disrupt the ability of miRNAs to target genes resulting in differential mRNA and protein expression. Skin tumor susceptibility 5 (Skts5) was identified as a locus conferring susceptibility to chemically-induced skin cancer in NIH/Ola by SPRET/Outbred F1 backcrosses. To determine if polymorphisms between the strains which mapped to putative miRNA binding sites in the 3′ untranslated region (3′UTR) of genes at Skts5 influenced expression, we conducted a systematic evaluation of 3′UTRs of candidate genes across this locus. Nine genes had polymorphisms in their 3′UTRs which fit the linkage data and eight of these contained polymorphisms suspected to interfere with or introduce miRNA binding. 3′UTRs of six genes, Bcap29, Dgkb, Hbp1, Pik3cg, Twistnb, and Tspan13 differentially affected luciferase expression, but did not appear to be differentially regulated by the evaluated miRNAs predicted to bind to only one of the two isoforms. 3′UTRs from four additional genes chosen from the locus that fit less stringent criteria were evaluated. Ifrd1 and Etv1 showed differences and contained polymorphisms predicted to disrupt or create miRNA binding sites but showed no difference in regulation by the miRNAs tested. In summary, multiple 3′UTRs with putative functional variants between susceptible and resistant strains of mice influenced differential expression independent of predicted miRNA binding.     

Identification of differentially expressed genes related to metabolic syndrome induced with high-fat diet in E3 rats

Understanding the genes differentially expressing in aberrant organs of metabolic syndrome (MetS) facilitates the uncovering of molecular mechanisms and the identification of novel therapeutic targets for the disease. This study aimed to identify differentially expressed genes related to MetS in livers of E3 rats with high-fat-diet-induced metabolic syndrome (HFD-MetS). E3 rats were fed with high-fat diet for 24 weeks to induce MetS. Then, suppression subtractive hybridization (SSH) technology was used to identify the genes differentially expressed between HFD-MetS and control E3 rat livers. Twenty positive recombinant clones were chosen randomly from forward subtractive library and sent to sequence. BLAST analysis in GenBank database was used to determine the property of each cDNA fragment. In total, 11 annotated genes, 3 ESTs, and 2 novel gene fragments were identified by SSH technology. The expression of four genes (Alb, Pip4k2a, Scd1, and Tf) known to be associated with MetS and other five genes (Eif1, Rnase4, Rps12, Rup2, and Tmsb4) unknown to be relevant to MetS was significantly up-regulated in the livers of HFD-MetS E3 rats compared with control rats using real-time quantitative PCR (RT-qPCR). By analyzing the correlations between the expression of these nine genes and serum concentrations of TG, Tch, HDL-C, and LDL-C, we found that there were significant positive correlations between TG and the expression of five genes (Alb, Eif1, Pip4k2a, Rps12, and Tmsb4x), Tch and three genes (Rnase4, Scd1, and Tmsb4x), and LDL-C and two genes (Rnase4 and Scd1), as well there were significant negative correlations between HDL-C and the expression of three genes (Rup2, Scd1, and Tf). This study provides important clues for unraveling the molecular mechanisms of MetS.     

Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci

Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.     

Integrative Analysis of Somatic Mutations Altering MicroRNA Targeting in Cancer Genomes

Determining the functional impact of somatic mutations is crucial to understanding tumorigenesis and metastasis. Recent sequences of several cancers have provided comprehensive lists of somatic mutations across entire genomes, enabling investigation of the functional impact of somatic mutations in non-coding regions. Here, we study somatic mutations in 3′UTRs of genes that have been identified in four cancers and computationally predict how they may alter miRNA targeting, potentially resulting in dysregulation of the expression of the genes harboring these mutations. We find that somatic mutations create or disrupt putative miRNA target sites in the 3′UTRs of many genes, including several genes, such as MITF, EPHA3, TAL1, SCG3, and GSDMA, which have been previously associated with cancer. We also integrate the somatic mutations with germline mutations and results of association studies. Specifically, we identify putative miRNA target sites in the 3′UTRs of BMPR1B, KLK3, and SPRY4 that are disrupted by both somatic and germline mutations and, also, are in linkage disequilibrium blocks with high scoring markers from cancer association studies. The somatic mutation in BMPR1B is located in a target site of miR-125b; germline mutations in this target site have previously been both shown to disrupt regulation of BMPR1B by miR-125b and linked with cancer.     

Activin Signaling in Microsatellite Stable Colon Cancers Is Disrupted by a Combination of Genetic and Epigenetic Mechanisms

Background

Activin receptor 2 (ACVR2) is commonly mutated in microsatellite unstable (MSI) colon cancers, leading to protein loss, signaling disruption, and larger tumors. Here, we examined activin signaling disruption in microsatellite stable (MSS) colon cancers.

Methods

Fifty-one population-based MSS colon cancers were assessed for ACVR1, ACVR2 and pSMAD2 protein. Consensus mutation-prone portions of ACVR2 were sequenced in primary cancers and all exons in colon cancer cell lines. Loss of heterozygosity (LOH) was evaluated for ACVR2 and ACVR1, and ACVR2 promoter methylation by methylation-specific PCR and bisulfite sequencing and chromosomal instability (CIN) phenotype via fluorescent LOH analysis of 3 duplicate markers. ACVR2 promoter methylation and ACVR2 expression were assessed in colon cancer cell lines via qPCR and IP-Western blots. Re-expression of ACVR2 after demethylation with 5-aza-2′-deoxycytidine (5-Aza) was determined. An additional 26 MSS colon cancers were assessed for ACVR2 loss and its mechanism, and ACVR2 loss in all tested cancers correlated with clinicopathological criteria.

Results

Of 51 MSS colon tumors, 7(14%) lost ACVR2, 2 (4%) ACVR1, and 5(10%) pSMAD2 expression. No somatic ACVR2 mutations were detected. Loss of ACVR2 expression was associated with LOH at ACVR2 (p<0.001) and ACVR2 promoter hypermethylation (p<0.05). ACVR2 LOH, but not promoter hypermethylation, correlated with CIN status. In colon cancer cell lines with fully methylated ACVR2 promoter, loss of ACVR2 mRNA and protein expression was restored with 5-Aza treatment. Loss of ACVR2 was associated with an increase in primary colon cancer volume (p<0.05).

Conclusions

Only a small percentage of MSS colon cancers lose expression of activin signaling members. ACVR2 loss occurs through LOH and ACVR2 promoter hypermethylation, revealing distinct mechanisms for ACVR2 inactivation in both MSI and MSS subtypes of colon cancer.     

Testing allele homogeneity: the problem of nested hypotheses

Background

Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas).

Results

We identified four genes with SNPs that showed the strongest and most consistent associations with LDL-C and CAD: EBF1, PPP2R2B, SPOCK1, and PRELID2. The most significant results for association of SNPs with LDL-C were: EBF1, rs6865969, p = 0.01; PPP2R2B, rs2125443, p = 0.005; SPOCK1, rs17600115, p = 0.003; and PRELID2, rs10074645, p = 0.0002). The most significant results for CAD were EBF1, rs6865969, p = 0.007; PPP2R2B, rs7736604, p = 0.0003; SPOCK1, rs17170899, p = 0.004; and PRELID2, rs7713855, p = 0.003.

Conclusion

Using an intermediate disease-related quantitative trait of LDL-C we have identified four novel CAD genes, EBF1, PRELID2, SPOCK1, and PPP2R2B. These four genes should be further examined in future functional studies as candidate susceptibility loci for cardiovascular disease mediated through LDL-cholesterol pathways.