StemCellNet: an interactive platform for network-oriented investigations in stem cell biology.

Stem cells are characterized by their potential for self-renewal and their capacity to differentiate into mature cells. These two key features emerge through the interplay of various factors within complex molecular networks. To provide researchers with a dedicated tool to investigate these networks, we have developed StemCellNet, a versatile web server for interactive network analysis and visualization. It rapidly generates focused networks based on a large collection of physical and regulatory interactions identified in human and murine stem cells. The StemCellNet web-interface has various easy-to-use tools for selection and prioritization of network components, as well as for integration of expression data provided by the user. As a unique feature, the networks generated can be screened against a compendium of stemness-associated genes. StemCellNet can also indicate novel candidate genes by evaluating their connectivity patterns. Finally, an optional dataset of generic interactions, which provides large coverage of the human and mouse proteome, extends the versatility of StemCellNet to other biomedical research areas in which stem cells play important roles, such as in degenerative diseases or cancer. The StemCellNet web server is freely accessible at http://stemcellnet.sysbiolab.eu.

FUT2: filling the gap between genes and environment in Behçet's disease?

OBJECTIVES: To identify new susceptibility loci for Behçet's disease (BD), we performed a genome-wide association study (GWAS) using DNA pooling. METHODS: Two replicate pools of 292 Iranian BD cases and of 294 age- and sex-matched controls were allelotyped in quadruplicate on the Affymetrix Genome-Wide Human SNP Array 6.0. Of the 51 top markers, 47 were technically validated through individually genotyping. Replication of validated single nucleotide polymorphisms (SNPs) was performed in an independent Iranian dataset (684 cases and 532 controls). RESULTS: In addition to the well-established HLA-B locus, rs7528842 in a gene desert on chromosome 1p21.2, and rs632111 at the 3'UTR of FUT2 were associated in both the discovery and replication datasets (individually and in combination). However, only the FUT2 SNP was associated in a previous GWAS for BD in Turkish people. Fine-mapping of FUT2 in the full Iranian dataset showed additional associations in five coding SNPs (2.97E-06

Colocalised Genetic Associations Reveal Alternative Splicing Variants as Candidate Causal Links for Breast Cancer Risk in 10 Loci.

Genome-wide association studies (GWASs) have revealed numerous loci associated with breast cancer risk, yet the precise causal variants, their impact on molecular mechanisms, and the affected genes often remain elusive. We hypothesised that specific variants exert their influence by affecting cis-regulatory alternative splice elements. An analysis of splicing quantitative trait loci (sQTL) in healthy breast tissue from female individuals identified multiple variants linked to alterations in splicing ratios. Through colocalisation analysis, we pinpointed 43 variants within twelve genes that serve as candidate causal links between sQTL and GWAS findings. In silico splice analysis highlighted a potential mechanism for three genes-FDPS, SGCE, and MRPL11-where variants in proximity to or on the splice site modulate usage, resulting in alternative splice transcripts. Further in vitro/vivo studies are imperative to fully understand how these identified changes contribute to breast oncogenesis. Moreover, investigating their potential as biomarkers for breast cancer risk could enhance screening strategies and early detection methods for breast cancer.

Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis.

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.

Association study of IL10 and IL23R-IL12RB2 in Iranian patients with Behçet's disease.

OBJECTIVE: Independent replication of the findings from genome-wide association studies (GWAS) remains the gold standard for results validation. Our aim was to test the association of Behçet's disease (BD) with the interleukin-10 gene (IL10) and the IL-23 receptor-IL-12 receptor ß2 (IL23R-IL12RB2) locus, each of which has been previously identified as a risk factor for BD in 2 different GWAS. METHODS: Six haplotype-tagging single-nucleotide polymorphisms (SNPs) in IL10 and 42 in IL23R-IL12RB2 were genotyped in 973 Iranian patients with BD and 637 non-BD controls. Population stratification was assessed using a panel of 86 ancestry-informative markers. RESULTS: Subtle evidence of population stratification was found in our data set. In IL10, rs1518111 was nominally associated with BD before and after adjustment for population stratification (odds ratio [OR] for T allele 1.20, 95% confidence interval [95% CI] 1.02-1.40, unadjusted P [P(unadj) ] = 2.53 × 10(-2) ; adjusted P [P(adj) ] = 1.43 × 10(-2) ), and rs1554286 demonstrated a trend toward association (P(unadj) = 6.14 × 10(-2) ; P(adj) = 3.21 × 10(-2) ). Six SNPs in IL23R-IL12RB2 were found to be associated with BD after Bonferroni correction for multiple testing, the most significant of which were rs17375018 (OR for G allele 1.51, 95% CI 1.27-1.78, P(unadj) = 1.93 × 10(-6) ), rs7517847 (OR for T allele 1.48, 95% CI 1.26-1.74, P(unadj) = 1.23 × 10(-6) ), and rs924080 (OR for T allele 1.29, 95% CI 1.20-1.39, P = 1.78 × 10(-5) ). SNPs rs10489629, rs1343151, and rs1495965 were also significantly associated with BD in all tests performed. Results of meta-analyses of our data combined with data from other populations further confirmed the role of rs1518111, rs17375018, rs7517847, and rs924080 in the risk of BD, but no epistatic interactions between IL10 and IL23R-IL12RB2 were detected. Results of imputation analysis highlighted the importance of IL23R regulatory regions in the susceptibility to BD. CONCLUSION: These findings independently confirm, extend, and refine the association of BD with IL10 and IL23R-IL12RB2. These associations warrant further validation and investigation in patients with BD, as they may have implications for the development of novel therapies (e.g., immunosuppressive therapy targeted at IL-23p19).

Germline allelic expression of genes at 17q22 locus associates with risk of breast cancer.

INTRODUCTION: Translation of genome-wide association study (GWAS) findings into preventive approaches is challenged by the identification of the causal risk variants and the understanding of the biological mechanisms by which they act. We present using allelic expression (AE) ratios to perform quantitative case-control analysis as a novel approach to identify risk associations, causal regulatory variants, and target genes. METHODS: Using the breast cancer (BC) risk locus 17q22 to validate this approach, we measured AE ratios in normal breast tissue samples from controls and cases, as well as from unmatched blood samples. Then we used in-silico and in-vitro analysis to map and functionally characterised candidate causal variants. RESULTS: We found a significant shift in the AE patterns of STXBP4 (rs2628315) and COX11 (rs17817901) in the normal breast tissue of cases and healthy controls. Preferential expression of the G-rs2628315 and A-rs17817901 alleles, more often observed in cases, was associated with an increased risk for BC. Analysis of blood samples from cases and controls found a similar association. Furthermore, we identified two putative cis-regulatory variants - rs17817901 and rs8066588 - that affect a miRNA and a transcription factor binding site, respectively. CONCLUSION: We propose causal variants and target genes for the 17q22 BC risk locus and show that using AE ratios in case-control association studies is helpful in identifying risk and mapping causal variants.

Allelic expression imbalance of PIK3CA mutations is frequent in breast cancer and prognostically significant.

PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor-positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found a frequent allelic expression imbalance between the missense mutant and wild-type PIK3CA alleles in breast tumors from the METABRIC (70.2%) and the TCGA (60.1%) projects. When considering the mechanisms controlling allelic expression, 27.7% and 11.8% of tumors showed imbalance due to regulatory variants in cis, in the two studies respectively. Furthermore, preferential expression of the mutant allele due to cis-regulatory variation is associated with poor prognosis in the METABRIC tumors (P = 0.031). Interestingly, ER-, PR-, and HER2+ tumors showed significant preferential expression of the mutated allele in both datasets. Our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying patients of poorer prognosis, and those with low expression of the mutated allele, who will unlikely benefit from PI3K inhibitors. Furthermore, our work proposes a model of differential regulation of a critical cancer-promoting gene in breast cancer.

Apoptosis-associated microRNAs are modulated in mouse, rat and human neural differentiation.

BACKGROUND: MicroRNAs (miRs or miRNAs) regulate several biological processes in the cell. However, evidence for miRNAs that control the differentiation program of specific neural cell types has been elusive. Recently, we have shown that apoptosis-associated factors, such as p53 and caspases participate in the differentiation process of mouse neural stem (NS) cells. To identify apoptosis-associated miRNAs that might play a role in neuronal development, we performed global miRNA expression profiling experiments in NS cells. Next, we characterized the expression of proapoptotic miRNAs, including miR-16, let-7a and miR-34a in distinct models of neural differentiation, including mouse embryonic stem cells, PC12 and NT2N cells. In addition, the expression of antiapoptotic miR-19a and 20a was also evaluated. RESULTS: The expression of miR-16, let-7a and miR-34a was consistently upregulated in neural differentiation models. In contrast, expression of miR-19a and miR-20a was downregulated in mouse NS cell differentiation. Importantly, differential expression of specific apoptosis-related miRNAs was not associated with increased cell death. Overexpression of miR-34a increased the proportion of postmitotic neurons of mouse NS cells. CONCLUSIONS: In conclusion, the identification of miR-16, let-7a and miR-34a, whose expression patterns are conserved in mouse, rat and human neural differentiation, implicates these specific miRNAs in mammalian neuronal development. The results provide new insights into the regulation of neuronal differentiation by apoptosis-associated miRNAs.

Kalirin: a novel genetic risk factor for ischemic stroke.

Cerebrovascular and cardiovascular diseases are the leading causes of death and disability worldwide. They are complex disorders resulting from the interplay of genetic and environmental factors, and may share several susceptibility genes. Several recent studies have implicated variants of the Kalirin (KALRN) gene with susceptibility to cardiovascular and metabolic phenotypes, but no studies have yet been performed in stroke patients. KALRN is involved, among others, in the inhibition of inducible nitric oxide synthase, in the regulation of ischemic signal transduction, and in neuronal morphogenesis, plasticity, and stability. The goal of the present study was to determine whether SNPs in the KALRN region on 3q13, which includes the Ropporin gene (ROPN1), predispose to ischemic stroke (IS) in a cohort of Portuguese patients and controls. We genotyped 34 tagging SNPs in the KALRN and ROPN1 chromosomal region on 565 IS patients and 517 unrelated controls, and performed genotype imputation for 405 markers on chromosome 3. We tested the single-marker association of these SNPs with IS. One SNP (rs4499545) in the ROPN1-KALRN intergenic region and two SNPs in KALRN (rs17286604 and rs11712619) showed significant (P < 0.05) allelic and genotypic (unadjusted and adjusted for hypertension, diabetes, and ever smoking) association with IS risk. Thirty-two imputed SNPs also showed an association at P < 0.05, and actual genotyping of three of these polymorphisms (rs7620580, rs6438833, and rs11712039) validated their association. Furthermore, rs11712039 was associated with IS (0.001 < P < 0.01) in a recent well-powered genomewide association study (Ikram et al. 2009). These studies suggest that variants in the KALRN gene region constitute risk factors for stroke and that KALRN may represent a common risk factor for vascular diseases.

Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk.

Most breast cancer (BC) risk-associated single-nucleotide polymorphisms (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting microRNA (miRNA) genes and/or miRNA binding. To test this, we adapted two miRNA-binding prediction algorithms-TargetScan and miRanda-to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant ( P ≤ 5 × 10 - 8 ) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3'-untranslated regions of putative miRNA target genes were predicted to alter miRNA::mRNA (messenger RNA) pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and reinforce the role of miRNA-mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.