Tomi Pastinen

Bone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study

Summary Background Osteoporosis is diagnosed by the measurement of bone mineral density, which is a highly heritable and multifactorial trait. We aimed to identify genetic loci that are associated with bone mineral density. Methods In this genome-wide association study, we identified the most promising of 314 075 single nucleotide polymorphisms (SNPs) in 2094 women in a UK study. We then tested these SNPs for replication in 6463 people from three other cohorts in western Europe. We also investigated allelic expression in lymphoblast cell lines. We tested the association between the replicated SNPs and osteoporotic fractures with data from two studies. Findings We identified genome-wide evidence for an association between bone mineral density and two SNPs (p<5×10−8). The SNPs were rs4355801, on chromosome 8, near to the TNFRSF11B (osteoprotegerin) gene, and rs3736228, on chromosome 11 in the LRP5 (lipoprotein-receptor-related protein) gene. A non-synonymous SNP in the LRP5 gene was associated with decreased bone mineral density (rs3736228, p=6·3×10−12 for lumbar spine and p=1·9×10−4 for femoral neck) and an increased risk of both osteoporotic fractures (odds ratio [OR] 1·3, 95% CI 1·09–1·52, p=0·002) and osteoporosis (OR 1·3, 1·08–1·63, p=0·008). Three SNPs near the TNFRSF11B gene were associated with decreased bone mineral density (top SNP, rs4355801: p=7·6×10−10 for lumbar spine and p=3·3×10−8 for femoral neck) and increased risk of osteoporosis (OR 1·2, 95% CI 1·01–1·42, p=0·038). For carriers of the risk allele at rs4355801, expression of TNFRSF11B in lymphoblast cell lines was halved (p=3·0×10−6). 1883 (22%) of 8557 people were at least heterozygous for these risk alleles, and these alleles had a cumulative association with bone mineral density (trend p=2·3×10−17). The presence of both risk alleles increased the risk of osteoporotic fractures (OR 1·3, 1·08–1·63, p=0·006) and this effect was independent of bone mineral density. Interpretation Two gene variants of key biological proteins increase the risk of osteoporosis and osteoporotic fracture. The combined effect of these risk alleles on fractures is similar to that of most well-replicated environmental risk factors, and they are present in more than one in five white people, suggesting a potential role in screening. Funding Wellcome Trust, European Commission, NWO Investments, Arthritis Research Campaign, Chronic Disease Research Foundation, Canadian Institutes of Health Research, European Society for Clinical and Economic Aspects of Osteoporosis, Genome Canada, Genome Quebéc, Canada Research Chairs, National Health and Medical Research Council of Australia, and European Union.

Twenty bone-mineral-density loci identified by large-scale meta-analysis of genome-wide association studies

Bone mineral density (BMD) is a heritable complex trait used in the clinical diagnosis of osteoporosis and the assessment of fracture risk. We performed meta-analysis of five genome-wide association studies of femoral neck and lumbar spine BMD in 19,195 subjects of Northern European descent. We identified 20 BMD loci that reached genome-wide significance (GWS; P < 5 × 10−8), of which 13 map to regions not previously associated with this trait: 1p31.3 (GPR177), 2p21 (SPTBN1), 3p22 (CTNNB1), 4q21.1 (MEPE), 5q14 (MEF2C), 7p14 (STARD3NL), 7q21.3 (FLJ42280), 11p11.2 (LRP4, ARHGAP1, F2), 11p14.1 (DCDC5), 11p15 (SOX6), 16q24 (FOXL1), 17q21 (HDAC5) and 17q12 (CRHR1). The meta-analysis also confirmed at GWS level seven known BMD loci on 1p36 (ZBTB40), 6q25 (ESR1), 8q24 (TNFRSF11B), 11q13.4 (LRP5), 12q13 (SP7), 13q14 (TNFSF11) and 18q21 (TNFRSF11A). The many SNPs associated with BMD map to genes in signaling pathways with relevance to bone metabolism and highlight the complex genetic architecture that underlies osteoporosis and variation in BMD.

Genome-wide allele-specific analysis: insights into regulatory variation

Functional genomics is rapidly progressing towards the elucidation of elements that are crucial for the cis-regulatory control of gene expression, and population-based studies of disease and gene expression traits are yielding widespread evidence of the influence of non-coding variants on trait variance. Recently, genome-wide allele-specific approaches that harness high-throughput sequencing technology have started to allow direct evaluation of how these cis-regulatory polymorphisms control gene expression and affect chromatin states. The emerging data is providing exciting opportunities for comprehensive characterization of the allele-specific events that govern human gene regulation.

Use of genome-wide association studies for drug repositioning

1. Weaver, T., Maurer, J. & Hayashizaki, Y. Nat. Rev. Genet. 5, 861–866 (2004). 2. Fan, M., Tsai, J., Chen, B., Fan, K. & LaBaer, J. Science 307, 1877 (2005). 3. Campbell, E.G. et al. J. Am. Med. Assoc. 287, 473– 480 (2002). control of reagents by the institution, they can often cause long delays for the researcher looking to obtain these reagents. Addgene has streamlined the technology transfer process by (i) using the universal biological material transfer agreement (UBMTA) as the basis for all transfers, (ii) making the agreements as consistent as possible across all institutions and (iii) allowing for electronic signatures from institutions that both contribute and request materials. This system has been used for >80,000 orders from >2,500 institutions worldwide. As more technology transfer offices have adapted to this system, the time required for MTA approval has been halved, with the median time now <36 h. Moving forward, it would be more efficient for institutions to implement a similar electronic MTA system for all academic resource transfers. Ultimately, BRCs like Addgene will be important for guiding academic laboratories into a new age of high-throughput research and corporate funding. We are seeing a paradigm shift in the pharmaceutical industry toward greater collaborations with academia self-sustaining and does not rely on outside funding. The most popular plasmids in the collection are empty backbones created for specific gene expression or knockdown experiments, control plasmids, and constructs used for generating lentiviruses and retroviruses. A quick look at Addgene’s most requested plasmids, according to laboratory (Table 1), reveals a collection of vectors that can be used in various applications across multiple disciplines. If a BRC like Addgene were not archiving and distributing these valuable reagents, they would be far less accessible to the scientific community3. Indeed, many researchers, especially those outside the discipline of the contributing laboratory, might not even realize that some of these powerful tools exist. Addgene has become a global repository, sending out approximately half of its requests to scientists outside the United States. Addgene now distributes genomic resources for large-scale projects, such as the Zinc Finger Consortium (http://www. zincfingers.org/), the Structural Genomics Consortium (http://www.thesgc.org/) and the Center for Genomic Engineering (http:// www.cge.umn.edu/). Moving forward, Addgene hopes to collaborate with additional groups to help support their archival and distribution efforts. In addition to archiving and distributing a physical reagent, Addgene also plays a crucial role by archiving information about these reagents and making it accessible to all potential users through an online database. Addgene’s website receives an average of 35,000 page views per weekday. Having clone information available helps with reproducibility and future use, especially because checking the accuracy of this information is often an onerous task for many laboratories. Similar to other BRCs, Addgene can handle large volumes of samples and data, which facilitates the development of efficient, large-scale processes for standardizing quality control and maintaining comprehensive databases of information. Currently, Addgene sequences key regions of all incoming constructs, which helps maintain a standardized bar for accuracy throughout the repository. Addgene has developed one of the first electronic material transfer agreement (MTA) systems, which has helped expedite the MTA process. Over the past few decades, there has been an increase in the use of MTAs for transferring reagents between academic and nonprofit organizations. Although MTAs may be a practical means of maintaining Use of genome-wide association studies for drug repositioning

Allele-Specific Chromatin Remodeling in the ZPBP2/GSDMB/ORMDL3 Locus Associated with the Risk of Asthma and Autoimmune Disease

Common SNPs in the chromosome 17q12-q21 region alter the risk for asthma, type 1 diabetes, primary biliary cirrhosis, and Crohn disease. Previous reports by us and others have linked the disease-associated genetic variants with changes in expression of GSDMB and ORMDL3 transcripts in human lymphoblastoid cell lines (LCLs). The variants also alter regulation of other transcripts, and this domain-wide cis-regulatory effect suggests a mechanism involving long-range chromatin interactions. Here, we further dissect the disease-linked haplotype and identify putative causal DNA variants via a combination of genetic and functional analyses. First, high-throughput resequencing of the region and genotyping of potential candidate variants were performed. Next, additional mapping of allelic expression differences in Yoruba HapMap LCLs allowed us to fine-map the basis of the cis-regulatory differences to a handful of candidate functional variants. Functional assays identified allele-specific differences in nucleosome distribution, an allele-specific association with the insulator protein CTCF, as well as a weak promoter activity for rs12936231. Overall, this study shows a common disease allele linked to changes in CTCF binding and nucleosome occupancy leading to altered domain-wide cis-regulation. Finally, a strong association between asthma and cis-regulatory haplotypes was observed in three independent family-based cohorts (p = 1.78 x 10(-8)). This study demonstrates the requirement of multiple parallel allele-specific tools for the investigation of noncoding disease variants and functional fine-mapping of human disease-associated haplotypes.

Global patterns of cis variation in human cells revealed by high-density allelic expression analysis.

Cis-acting variants altering gene expression are a source of phenotypic differences. The cis-acting components of expression variation can be identified through the mapping of differences in allelic expression (AE), which is the measure of relative expression between two allelic transcripts. We generated a map of AE associated SNPs using quantitative measurements of AE on Illumina Human1M BeadChips. In 53 lymphoblastoid cell lines derived from donors of European descent, we identified common cis variants affecting 30% (2935/9751) of the measured RefSeq transcripts at 0.001 permutation significance. The pervasive influence of cis-regulatory variants, which explain 50% of population variation in AE, extend to full-length transcripts and their isoforms as well as to unannotated transcripts. These strong effects facilitate fine mapping of cis-regulatory SNPs, as demonstrated by dissection of heritable control of transcripts in the systemic lupus erythematosus–associated C8orf13-BLK region in chromosome 8. The dense collection of associations will facilitate large-scale isolation of cis-regulatory SNPs.

A risk haplotype of STAT4 for systemic lupus erythematosus is over-expressed, correlates with anti-dsDNA and shows additive effects with two risk alleles of IRF5

Systemic lupus erythematosus (SLE) is the prototype autoimmune disease where genes regulated by type I interferon (IFN) are over-expressed and contribute to the disease pathogenesis. Because signal transducer and activator of transcription 4 (STAT4) plays a key role in the type I IFN receptor signaling, we performed a candidate gene study of a comprehensive set of single nucleotide polymorphism (SNPs) in STAT4 in Swedish patients with SLE. We found that 10 out of 53 analyzed SNPs in STAT4 were associated with SLE, with the strongest signal of association (P = 7.1 × 10−8) for two perfectly linked SNPs rs10181656 and rs7582694. The risk alleles of these 10 SNPs form a common risk haplotype for SLE (P = 1.7 × 10−5). According to conditional logistic regression analysis the SNP rs10181656 or rs7582694 accounts for all of the observed association signal. By quantitative analysis of the allelic expression of STAT4 we found that the risk allele of STAT4 was over-expressed in primary human cells of mesenchymal origin, but not in B-cells, and that the risk allele of STAT4 was over-expressed (P = 8.4 × 10−5) in cells carrying the risk haplotype for SLE compared with cells with a non-risk haplotype. The risk allele of the SNP rs7582694 in STAT4 correlated to production of anti-dsDNA (double-stranded DNA) antibodies and displayed a multiplicatively increased, 1.82-fold risk of SLE with two independent risk alleles of the IRF5 (interferon regulatory factor 5) gene.

Genome-wide association study identifies variants at 9p21 and 22q13 associated with development of cutaneous nevi

A high melanocytic nevi count is the strongest known risk factor for cutaneous melanoma. We conducted a genome-wide association study for nevus count using 297,108 SNPs in 1,524 twins, with validation in an independent cohort of 4,107 individuals. We identified strongly associated variants in MTAP, a gene adjacent to the familial melanoma susceptibility locus CDKN2A on 9p21 (rs4636294, combined P = 3.4 × 10−15), as well as in PLA2G6 on 22q13.1 (rs2284063, combined P = 3.4 × 10−8). In addition, variants in these two loci showed association with melanoma risk in 3,131 melanoma cases from two independent studies, including rs10757257 at 9p21, combined P = 3.4 × 10−8, OR = 1.23 (95% CI = 1.15–1.30) and rs132985 at 22q13.1, combined P = 2.6 × 10−7, OR = 1.23 (95% CI = 1.15–1.30). This provides the first report of common variants associated to nevus number and demonstrates association of these variants with melanoma susceptibility.

An Integration of Genome-Wide Association Study and Gene Expression Profiling to Prioritize the Discovery of Novel Susceptibility Loci for Osteoporosis-Related Traits

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6×10−8), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6×10−13; SOX6, p = 6.4×10−10) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation.

The study of eQTL variations by RNA-seq: from SNPs to phenotypes

Common DNA variants alter the expression levels and patterns of many human genes. Loci responsible for this genetic control are known as expression quantitative trait loci (eQTLs). The resulting variation of gene expression across individuals has been postulated to be a determinant of phenotypic variation and susceptibility to complex disease. In the past, the application of expression microarray and genetic variation data to study populations enabled the rapid identification of eQTLs in model organisms and humans. Now, a new technology promises to revolutionize the field. Massively parallel RNA sequencing (RNA-seq) provides unprecedented resolution, allowing us to accurately monitor not only the expression output of each genomic locus but also reconstruct and quantify alternatively spliced transcripts. RNA-seq also provides new insights into the regulatory mechanisms underlying eQTLs. Here, we discuss the major advances introduced by RNA-seq and summarize current progress towards understanding the role of eQTLs in determining human phenotypic diversity.