Alteration of the C-terminal ligand specificity of the Erbin PDZ domain by allosteric mutational effects

Modulation of protein binding specificity is important for basic biology and for applied science. Here we explore how binding specificity is conveyed in PDZ (postsynaptic density protein-95/discs large/zonula occludens-1) domains, small interaction modules that recognize various proteins by binding to an extended C terminus. Our goal was to engineer variants of the Erbin PDZ domain with altered specificity for the most C-terminal position (position 0) where a Val is strongly preferred by the wild-type domain. We constructed a library of PDZ domains by randomizing residues in direct contact with position 0 and in a loop that is close to but does not contact position 0. We used phage display to select for PDZ variants that bind to 19 peptide ligands differing only at position 0. To verify that each obtained PDZ domain exhibited the correct binding specificity, we selected peptide ligands for each domain. Despite intensive efforts, we were only able to evolve Erbin PDZ domain variants with selectivity for the aliphatic C-terminal side chains Val, Ile and Leu. Interestingly, many PDZ domains with these three distinct specificities contained identical amino acids at positions that directly contact position 0 but differed in the loop that does not contact position 0. Computational modeling of the selected PDZ domains shows how slight conformational changes in the loop region propagate to the binding site and result in different binding specificities. Our results demonstrate that second-sphere residues could be crucial in determining protein binding specificity.

Improved linear cryptanalysis of reduced-round SIMON-32 and SIMON-48

In this paper we analyse two variants of SIMON family of light-weight block ciphers against variants of linear cryptanalysis and present the best linear cryptanalytic results on these variants of reduced-round SIMON to date. We propose a time-memory trade-off method that finds differential/linear trails for any permutation allowing low Hamming weight differential/linear trails. Our method combines low Hamming weight trails found by the correlation matrix representing the target permutation with heavy Hamming weight trails found using a Mixed Integer Programming model representing the target differential/linear trail. Our method enables us to find a 17-round linear approximation for SIMON-48 which is the best current linear approximation for SIMON-48. Using only the correlation matrix method, we are able to find a 14-round linear approximation for SIMON-32 which is also the current best linear approximation for SIMON-32. The presented linear approximations allow us to mount a 23-round key recovery attack on SIMON-32 and a 24-round Key recovery attack on SIMON-48/96 which are the current best results on SIMON-32 and SIMON-48. In addition we have an attack on 24 rounds of SIMON-32 with marginal complexity.

Polymorphisms in a desaturase 2 ortholog associate with cuticular hydrocarbon and male mating success variation in a natural population of Drosophila serrata

Elucidating the nature of genetic variation underlying both sexually selected traits and the fitness components of sexual selection is essential to understanding the broader consequences of sexual selection as an evolutionary process. To date, there have been relatively few attempts to connect the genetic variance in sexually selected traits with segregating DNA sequence polymorphisms. We set out to address this in a well-characterized sexual selection system - the cuticular hydrocarbons (CHCs) of Drosophila serrata - using an indirect association study design that allowed simultaneous estimation of the genetic variance in CHCs, sexual fitness and single nucleotide polymorphism (SNP) effects in an outbred population. We cloned and sequenced an ortholog of the D. melanogaster desaturase 2 gene, previously shown to affect CHC biosynthesis in D. melanogaster, and associated 36 SNPs with minor allele frequencies > 0.02 with variance in CHCs and sexual fitness. Three SNPs had significant multivariate associations with CHC phenotype (q-value < 0.05). At these loci, minor alleles had multivariate effects on CHCs that were weakly associated with the multivariate direction of sexual selection operating on these traits. Two of these SNPs had pleiotropic associations with male mating success, suggesting these variants may underlie responses to sexual selection due to this locus. There were 15 significant male mating success associations (q-value < 0.1), and interestingly, we detected a nonrandom pattern in the relationship between allele frequency and direction of effect on male mating success. The minor-frequency allele usually reduced male mating success, suggesting a positive association between male mating success and total fitness at this locus.

Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: A Mendelian randomisation analysis

Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1α and IL-1β); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0·22 SD (95% CI 0·18–0·25; 12·5%; p=9·3 × 10−33), concentrations of interleukin 6 decreased by 0·02 SD (−0·04 to −0·01; −1·7%; p=3·5 × 10−3), and concentrations of C-reactive protein decreased by 0·03 SD (−0·04 to −0·02; −3·4%; p=7·7 × 10−14). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1·15 (1·08–1·22; p=1·8 × 10−6) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1·03 (1·02–1·04; p=3·9 × 10−10). Per-allele odds ratios were 0·97 (0·95–0·99; p=9·9 × 10−4) for rheumatoid arthritis, 0·99 (0·97–1·01; p=0·47) for type 2 diabetes, 1·00 (0·98–1·02; p=0·92) for ischaemic stroke, and 1·08 (1·04–1·12; p=1·8 × 10−5) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1α/β inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Funding UK Medical Research Council, British Heart Foundation, UK National Institute for Health Research, National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council, and European Commission Framework Programme 7.

Genetics of rheumatoid arthritis contributes to biology and drug discovery

A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)1. Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating ~10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2, 3, 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation5, cis-acting expression quantitative trait loci6 and pathway analyses7, 8, 9—as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes—to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Major histocompatibility complex associations of ankylosing spondylitis are complex and involve further epistasis with ERAP1

Ankylosing spondylitis (AS) is a common, highly heritable, inflammatory arthritis for which HLA-B*27 is the major genetic risk factor, although its role in the aetiology of AS remains elusive. To better understand the genetic basis of the MHC susceptibility loci, we genotyped 7,264 MHC SNPs in 22,647 AS cases and controls of European descent. We impute SNPs, classical HLA alleles and amino-acid residues within HLA proteins, and tested these for association to AS status. Here we show that in addition to effects due to HLA-B*27 alleles, several other HLA-B alleles also affect susceptibility. After controlling for the associated haplotypes in HLA-B, we observe independent associations with variants in the HLA-A, HLA-DPB1 and HLA-DRB1 loci. We also demonstrate that the ERAP1 SNP rs30187 association is not restricted only to carriers of HLA-B*27 but also found in HLA-B*40:01 carriers independently of HLA-B*27 genotype.

Tumor-associated mutations inO6-methylguanine DNA-methyltransferase (MGMT) reduce DNA repair functionality

MGMT is the primary vehicle for cellular removal of alkyl lesions from the O-6 position of guanine and the O-4 position of thymine. While key to the maintenance of genomic integrity, MGMT also removes damage induced by alkylating chemotherapies, inhibiting the efficacy of cancer treatment. Germline variants of human MGMT are well-characterized, but somatic variants found in tumors were, prior to this work, uncharacterized. We found that MGMT G132R, from a human esophageal tumor, and MGMT G156C, from a human colorectal cancer cell line, are unable to rescue methyltransferase-deficient Escherichia coli as well as wild type (WT) human MGMT after treatment with a methylating agent. Using pre-steady state kinetics, we biochemically characterized these variants as having a reduced rate constant. G132R binds DNA containing an O6-methylguanine lesion half as tightly as WT MGMT, while G156C has a 40-fold decrease in binding affinity for the same damaged DNA versus WT. Mammalian cells expressing either G132R or G156C are more sensitive to methylating agents than mammalian cells expressing WT MGMT. G132R is slightly resistant to O6-benzylguanine, an inhibitor of MGMT in clinical trials, while G156C is almost completely resistant to this inhibitor. The impared functionality of expressed variants G132R and G156C suggests that the presence of somatic variants of MGMT in a tumor could impact chemotherapeutic outcomes.

Single nucleotide polymorphisms in clinics: Fantasy or reality for cancer?

Single nucleotide polymorphisms (SNPs) have been classically used for dissecting various human complex disorders using candidate gene studies. During the last decade, large scale SNP analysis i.e. genome-wide association studies (GWAS) have provided an agnostic approach to identify possible genetic loci associated with heterogeneous disease such as cancer susceptibility, prognosis of survival or drug response. Further, the advent of new technologies, including microarray based genotyping as well as high throughput next generation sequencing has opened new avenues for SNPs to be used in clinical practice. It is speculated that the utility of SNPs to understand the mechanisms, biology of variable drug response and ultimately treatment individualization based on the individual’s genome composition will be indispensable in the near future. In the current review, we discuss the advantages and disadvantages of the clinical utility of genetic variants in disease risk-prediction, prognosis, clinical outcome and pharmacogenomics. The lessons and challenges for the utility of SNP based biomarkers are also discussed, including the need for additional functional validation studies.

Meta-analysis of genome-wide studies identifies MEF2C SNPs associated with bone mineral density at forearm

Background Forearm fractures affect 1.7 million individuals worldwide each year and most occur earlier in life than hip fractures. While the heritability of forearm bone mineral density (BMD) and fracture is high, their genetic determinants are largely unknown. Aim To identify genetic variants associated with forearm BMD and forearm fractures. Methods BMD at distal radius, measured by dualenergy x-ray absorptiometry, was tested for association with common genetic variants. We conducted a metaanalysis of genome-wide association studies for BMD in 5866 subjects of European descent and then selected the variants for replication in 715 Mexican American samples. Gene-based association was carried out to supplement the single-nucleotide polymorphism (SNP) association test. We then tested the BMD-associated SNPs for association with forearm fracture in 2023 cases and 3740 controls. Results We found that five SNPs in the introns of MEF2C were associated with forearm BMD at a genome-wide significance level (p<5×10-8) in meta-analysis (lead SNP, rs11951031[T] -0.20 SDs per allele, p=9.01×10-9). The gene-based association test suggested an association between MEF2C and forearm BMD ( p=0.003). The association between MEF2C variants and risk of fracture did not achieve statistical significance (SNP rs12521522[A]: OR=1.14 (95% CI 0.92 to 1.35), p=0.14). Meta-analysis also revealed two genome-wide suggestive loci at CTNNA2 and 6q23.2. Conclusions These findings demonstrate that variants at MEF2C were associated with forearm BMD, implicating this gene in the determination of BMD at forearm.

Mosaic PPM1D mutations are associated with predisposition to breast and ovarian cancer

Improved sequencing technologies offer unprecedented opportunities for investigating the role of rare genetic variation in common disease. However, there are considerable challenges with respect to study design, data analysis and replication. Using pooled next-generation sequencing of 507 genes implicated in the repair of DNA in 1,150 samples, an analytical strategy focused on protein-truncating variants (PTVs) and a large-scale sequencing case-control replication experiment in 13,642 individuals, here we show that rare PTVs in the p53-inducible protein phosphatase PPM1D are associated with predisposition to breast cancer and ovarian cancer. PPM1D PTV mutations were present in 25 out of 7,781 cases versus 1 out of 5,861 controls (P = 1.12 × 10-5), including 18 mutations in 6,912 individuals with breast cancer (P = 2.42 × 10-4) and 12 mutations in 1,121 individuals with ovarian cancer (P = 3.10 × 10-9). Notably, all of the identified PPM1D PTVs were mosaic in lymphocyte DNA and clustered within a 370-base-pair region in the final exon of the gene, carboxy-terminal to the phosphatase catalytic domain. Functional studies demonstrate that the mutations result in enhanced suppression of p53 in response to ionizing radiation exposure, suggesting that the mutant alleles encode hyperactive PPM1D isoforms. Thus, although the mutations cause premature protein truncation, they do not result in the simple loss-of-function effect typically associated with this class of variant, but instead probably have a gain-of-function effect. Our results have implications for the detection and management of breast and ovarian cancer risk. More generally, these data provide new insights into the role of rare and of mosaic genetic variants in common conditions, and the use of sequencing in their identification.

A new regulatory variant in the interleukin-6 receptor gene associates with asthma risk

The main genetic determinant of soluble interleukin 6 receptor (sIL-6R) levels is the missense variant rs2228145 that maps to the cleavage site of IL-6R. For each Ala allele, sIL-6R serum levels increase by ∼20 ng ml -1 and asthma risk by 1.09-fold. However, this variant does not explain the total heritability for sIL-6R levels. Additional independent variants in IL6R may therefore contribute to variation in sIL-6R levels and influence asthma risk. We imputed 471 variants in IL6R and tested these for association with sIL-6R serum levels in 360 individuals. An intronic variant (rs12083537) was associated with sIL-6R levels independently of rs4129267 (P=0.0005), a proxy single-nucleotide polymorphism for rs2228145. A significant and consistent association for rs12083537 was observed in a replication panel of 354 individuals (P=0.033). Each rs12083537:A allele increased sIL-6R serum levels by 2.4 ng ml -1. Analysis of mRNA levels in two cohorts did not identify significant associations between rs12083537 and IL6R transcription levels. On the other hand, results from 16 705 asthmatics and 30 809 controls showed that the rs12083537:A allele increased asthma risk by 1.04-fold (P=0.0419). Genetic risk scores based on IL6R regulatory variants may prove useful in explaining variation in clinical response to tocilizumab, an anti-IL-6R monoclonal antibody.

Genome-wide association studies

Genome-wide association studies (GWAS) are a powerful hypothesis-free tool for the dissection of susceptibility to common heritable human diseases, including osteoporosis. To date, more than 2000 loci for common human diseases have been identified by GWAS. Success using the GWAS model depends on genetic risk being determined by shared stretches of DNA carried with different frequencies in cases and controls, inherited from ancient ancestors, termed the “common disease–common variant” hypothesis. Not all disease risk is caused by common variants, however, and thus GWAS will not detect all variants involved. Successful GWAS performance requires careful quality control, especially as the effect sizes under study are modest, and there are multiple potential sources of error. Conservative interpretation, use of stringent significance thresholds, and replication in independent cohorts are required to ensure results are robust. Despite these challenging parameters, much has been learnt from GWAS and, as the approach matures and is modified to identify a wider range of variants, significantly more will be learnt about the etiopathogenesis of common diseases such as osteoporosis.

Genome-wide association study to identify genetic determinants of severe asthma

Background: The genetic basis for developing asthma has been extensively studied. However, association studies to date have mostly focused on mild to moderate disease and genetic risk factors for severe asthma remain unclear. Objective: To identify common genetic variants affecting susceptibility to severe asthma. Methods: A genome-wide association study was undertaken in 933 European ancestry individuals with severe asthma based on Global Initiative for Asthma (GINA) criteria 3 or above and 3346 clean controls. After standard quality control measures, the association of 480 889 genotyped single nucleotide polymorphisms (SNPs) was tested. To improve the resolution of the association signals identified, non-genotyped SNPs were imputed in these regions using a dense reference panel of SNP genotypes from the 1000 Genomes Project. Then replication of SNPs of interest was undertaken in a further 231 cases and 1345 controls and a meta-analysis was performed to combine the results across studies. Results: An association was confirmed in subjects with severe asthma of loci previously identified for association with mild to moderate asthma. The strongest evidence was seen for the ORMDL3/GSDMB locus on chromosome 17q12-21 (rs4794820, p=1.03×10 (-8)following meta-analysis) meeting genome-wide significance. Strong evidence was also found for the IL1RL1/IL18R1 locus on 2q12 (rs9807989, p=5.59×10 (-8) following meta-analysis) just below this threshold. No novel loci for susceptibility to severe asthma met strict criteria for genome-wide significance. Conclusions: The largest genome-wide association study of severe asthma to date was carried out and strong evidence found for the association of two previously identified asthma susceptibility loci in patients with severe disease. A number of novel regions with suggestive evidence were also identified warranting further study.

Fine mapping and replication of genetic risk Loci in primary sclerosing cholangitis

Background and aims. Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by progressive inflammation and fibrosis of the bile ducts eventually leading to biliary cirrhosis. Recent genetic studies in PSC have identified associations at 2q13, 2q35, 3p21, 4q27, 13q31 and suggestive association at 10p15. The aim of this study was to further characterize and refine the genetic architecture of PSC. Methods. We analyzed previously reported associated SNPs at four of these non-HLA loci and 59 SNPs tagging the IL-2/IL-21 (4q27) and IL2RA (10p15) loci in 992 UK PSC cases and 5162 healthy UK controls. Results. The most associated SNPs identified were rs3197999 (3p21 (MST1), p = 1.9 × 10 -6, OR A vs G = 1.28, 95% CI (1.16-1.42)); rs4147359 (10p15 (IL2RA), p = 2.6 × 10 -4, OR A vs G = 1.20, 95% CI (1.09-1.33)) and rs12511287 (4q27 (IL-2/IL-21), p = 3.0 × 10 -4, OR A vs T = 1.21, 95% CI (1.09-1.35)). In addition, we performed a meta-analysis for selected SNPs using published summary statistics from recent studies. We observed genome-wide significance for rs3197999 (3p21 (MST1), P combined = 3.8 × 10 -12) and rs4147359 (10p15 (IL2RA), P combined = 1.5 × 10 -8). Conclusion. We have for the first time confirmed the association of PSC with genetic variants at 10p15 (IL2RA) locus at genome-wide significance and replicated the associations at MST1 and IL-2/IL-21 loci in a large homogeneous UK population. These results strongly implicate the role of IL-2/IL2RA pathway in PSC and provide further confirmation of MST1 association. © Informa Healthcare.

Using genome-Wwide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.