Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

Serum bilirubin concentration is modified by UGT1A1 Haplotypes and influences risk of type-2 diabetes in the Norfolk Island Genetic Isolate

Background Located in the Pacific Ocean between Australia and New Zealand, the unique population isolate of Norfolk Island has been shown to exhibit increased prevalence of metabolic disorders (type-2 diabetes, cardiovascular disease) compared to mainland Australia. We investigated this well-established genetic isolate, utilising its unique genomic structure to increase the ability to detect related genetic markers. A pedigree-based genome-wide association study of 16 routinely collected blood-based clinical traits in 382 Norfolk Island individuals was performed. Results A striking association peak was located at chromosome 2q37.1 for both total bilirubin and direct bilirubin, with 29 SNPs reaching statistical significance (P < 1.84 × 10−7). Strong linkage disequilibrium was observed across a 200 kb region spanning the UDP-glucuronosyltransferase family, including UGT1A1, an enzyme known to metabolise bilirubin. Given the epidemiological literature suggesting negative association between CVD-risk and serum bilirubin we further explored potential associations using stepwise multivariate regression, revealing significant association between direct bilirubin concentration and type-2 diabetes risk. In the Norfolk Island cohort increased direct bilirubin was associated with a 28 % reduction in type-2 diabetes risk (OR: 0.72, 95 % CI: 0.57-0.91, P = 0.005). When adjusted for genotypic effects the overall model was validated, with the adjusted model predicting a 30 % reduction in type-2 diabetes risk with increasing direct bilirubin concentrations (OR: 0.70, 95 % CI: 0.53-0.89, P = 0.0001). Conclusions In summary, a pedigree-based GWAS of blood-based clinical traits in the Norfolk Island population has identified variants within the UDPGT family directly associated with serum bilirubin levels, which is in turn implicated with reduced risk of developing type-2 diabetes within this population.

The influence of OLR1 and PCSK9 gene polymorphisms on ischemic stroke: Evidence from a meta-analysis

It has been reported that both OLR1 and PCSK9 genes are related to various vascular diseases such as atherosclerosis, cardiovascular disease, peripheral artery disease and stroke, in particular ischemic stroke. The prevalence of PCSK9 rs505151 and OLR1 rs11053646 variants in ischemic stroke were 0.005 and 0.116, respectively. However, to date, association between OLR1 rs11053646 and PCSK9 rs505151 polymorphisms and the risk of ischemic stroke remains unclear and inconclusive. Therefore, this first meta-analysis was carried out to clarify the presumed influence of genetic polymorphisms on ischemic stroke, by analyzing the complete coverage of all relevant studies. All eligible case-control and cohort studies that met the search term were retrieved in multiple scientific databases. Data of interest such as demographic data and genotyping methods were extracted from each study, and the meta-analysis was performed using RevMan 5.3 and Metafor R 3.2.1. The pooled odd ratios (ORs) and 95% confidence intervals (CIs) were calculated using both fixed- and random-effect models. A total of seven case-control studies encompassing 1897 ischemic stroke cases and 2119 healthy controls were critically evaluated. Pooled results from the genetic models indicated that OLR1 rs11053646 dominant (OR=1.33. 95%CI:1.11-1.58) and co-dominant models (OR=1.24, 95%CI:1.02-1.51) were significantly associated with ischemic stroke. For PCSK9 rs505151 polymorphism, the OR of co-dominant model (OR=1.36, 95%CI:1.01-1.58) was found to be higher among ischemic stroke patients. In conclusion, the current meta-analysis highlighted that variant allele of OLR1 rs11053646 G>C and PCSK9 rs505151 A>G may contribute to the susceptibility risk of ischemic stroke.

Sustainable housing development through integrated strata utility and transport infrastructure

A comprehensive study was conducted on potential systems of integrated building utilities and transport power solutions that can simultaneously contain rising electricity, hot water and personal transport costs for apartment residents. The research developed the Commuter Energy and Building Utilities System (CEBUS) and quantified the economic, social and environmental benefits of incorporating such a system in future apartment developments. A decision support tool was produced to assist the exploration of the CEBUS design variants. A set of implementation guidelines for CEBUS was also developed for the property development industry.

Genome-wide association study of prostate cancer-specific survival

BACKGROUND: Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. METHODS: We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. Top findings were assessed for replication in a Norwegian cohort (CONOR). RESULTS: We observed no significant association between genetic variants and prostate cancer survival. CONCLUSIONS: Common genetic variants with large impact on prostate cancer survival were not observed in this study. IMPACT: Future studies should be designed for identification of rare variants with large effect sizes or common variants with small effect sizes.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

The effects of height and BMI on prostate cancer incidence and mortality: A Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium

Background Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. Methods We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. Results The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). Conclusions We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.

Improving the selectivity of engineered protease inhibitors: Optimizing the P2 prime residue using a versatile cyclic peptide library

Standard mechanism inhibitors are attractive design templates for engineering reversible serine protease inhibitors. When optimizing interactions between the inhibitor and target protease, many studies focus on the nonprimed segment of the inhibitor's binding loop (encompassing the contact β-strand). However, there are currently few methods for screening residues on the primed segment. Here, we designed a synthetic inhibitor library (based on sunflower trypsin inhibitor-1) for characterizing the P2′ specificity of various serine proteases. Screening the library against 13 different proteases revealed unique P2′ preferences for trypsin, chymotrypsin, matriptase, plasmin, thrombin, four kallikrein-related peptidases, and several clotting factors. Using this information to modify existing engineered inhibitors yielded new variants that showed considerably improved selectivity, reaching up to 7000-fold selectivity over certain off-target proteases. Our study demonstrates the importance of the P2′ residue in standard mechanism inhibition and unveils a new approach for screening P2′ substitutions that will benefit future inhibitor engineering studies.

Engineered protease inhibitors based on sunflower trypsin inhibitor-1 (SFTI-1) provide insights into the role of sequence and conformation in Laskowski mechanism inhibition

Laskowski inhibitors regulate serine proteases by an intriguing mode of action that involves deceiving the protease into synthesizing a peptide bond. Studies exploring naturally occurring Laskowski inhibitors have uncovered several structural features that convey the inhibitor's resistance to hydrolysis and exceptional binding affinity. However, in the context of Laskowski inhibitor engineering, the way that various modifications intended to fine-tune an inhibitor's potency and selectivity impact on its association and dissociation rates remains unclear. This information is important as Laskowski inhibitors are becoming increasingly used as design templates to develop new protease inhibitors for pharmaceutical applications. In this study, we used the cyclic peptide, sunflower trypsin inhibitor-1 (SFTI-1), as a model system to explore how the inhibitor's sequence and structure relate to its binding kinetics and function. Using enzyme assays, MD simulations and NMR spectroscopy to study SFTI variants with diverse sequence and backbone modifications, we show that the geometry of the binding loop mainly influences the inhibitor's potency by modulating the association rate, such that variants lacking a favourable conformation show dramatic losses in activity. Additionally, we show that the inhibitor's sequence (including both the binding loop and its scaffolding) influences its potency and selectivity by modulating both the association and the dissociation rates. These findings provide new insights into protease inhibitor function and design that we apply by engineering novel inhibitors for classical serine proteases, trypsin and chymotrypsin and two kallikrein-related peptidases (KLK5 and KLK14) that are implicated in various cancers and skin diseases.

KAT5 (Tip60) is a potential therapeutic target in malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a rare aggressive cancer of the pleura. Asbestos exposure (through inhalation) is the most well established risk factor for mesothelioma. The current standard of care for patients suffering from MPM is a combination of cisplatin and pemetrexed (or alternatively cisplatin and raltitrexed). Most patients, however, die within 24 months of diagnosis. New therapies are therefore urgently required for this disease. Lysine acetyltransferases (KATs) including KAT5 have been linked with the development of cisplatin resistance. This gene may therefore be altered in MPM and could represent a novel candidate target for intervention. Using RT-PCR screening the expression of all known KAT5 variants was found to be markedly increased in malignant tumors compared to benign pleura. When separated according to histological subtype, KAT5 was significantly overexpressed in both the sarcomatoid and biphasic subgroups for all transcript variants. A panel of MPM cell lines including the normal pleural cells LP9 and Met5A was screened for expression of KAT5 variants. Treatment of cells with a small molecule inhibitor of KAT5 (MG-149) caused significant inhibition of cellular proliferation (p<0.0001), induction of apoptosis and was accompanied by significant induction of pro-inflammatory cytokines/chemokines.