Partial Opening of Cytochrome P450cam (CYP101A1) Is Driven by Allostery and Putidaredoxin Binding.

Cytochrome P450cam (CYP101A1) catalyzes the regio- and stereo-specific 5-exo-hydroxylation of camphor via a multistep catalytic cycle that involves two-electron transfer steps, with an absolute requirement that the second electron be donated by the ferrodoxin, putidaredoxin (Pdx). Whether P450cam, once camphor has bound to the active site and the substrate entry channel has closed, opens up upon Pdx binding, during the second electron transfer step, or it remains closed is still a matter of debate. A potential allosteric site for camphor binding has been identified and postulated to play a role in the binding of Pdx. Here, we have revisited paramagnetic NMR spectroscopy data and determined a heterogeneous ensemble of structures that explains the data, provides a complete representation of the P450cam/Pdx complex in solution, and reconciles alternative hypotheses. The allosteric camphor binding site is always present, and the conformational changes induced by camphor binding to this site facilitates Pdx binding. We also determined that the state to which Pdx binds comprises an ensemble of structures that have features of both the open and closed state. These results demonstrate that there is a finely balanced interaction between allosteric camphor binding and the binding of Pdx at high camphor concentrations.

Statistical method for modeling sequencing data from different technologies in longitudinal studies with application to Huntington disease.

Advancement of gene expression measurements in longitudinal studies enables the identification of genes associated with disease severity over time. However, problems arise when the technology used to measure gene expression differs between time points. Observed differences between the results obtained at different time points can be caused by technical differences. Modeling the two measurements jointly over time might provide insight into the causes of these different results. Our work is motivated by a study of gene expression data of blood samples from Huntington disease patients, which were obtained using two different sequencing technologies. At time point 1, DeepSAGE technology was used to measure the gene expression, with a subsample also measured using RNA-Seq technology. At time point 2, all samples were measured using RNA-Seq technology. Significant associations between gene expression measured by DeepSAGE and disease severity using data from the first time point could not be replicated by the RNA-Seq data from the second time point. We modeled the relationship between the two sequencing technologies using the data from the overlapping samples. We used linear mixed models with either DeepSAGE or RNA-Seq measurements as the dependent variable and disease severity as the independent variable. In conclusion, (1) for one out of 14 genes, the initial significant result could be replicated with both technologies using data from both time points; (2) statistical efficiency is lost due to disagreement between the two technologies, measurement error when predicting gene expressions, and the need to include additional parameters to account for possible differences.

Estimating Constraints for Protection Factors from HDX-MS Data.

Hydrogen/deuterium exchange monitored by mass spectrometry is a promising technique for rapidly fingerprinting structural and dynamical properties of proteins. The time-dependent change in the mass of any fragment of the polypeptide chain depends uniquely on the rate of exchange of its amide hydrogens, but determining the latter from the former is generally not possible. Here, we show that, if time-resolved measurements are available for a number of overlapping peptides that cover the whole sequence, rate constants for each amide hydrogen exchange (or equivalently, their protection factors) may be extracted and the uniqueness of the solutions obtained depending on the degree of peptide overlap. However, in most cases, the solution is not unique, and multiple alternatives must be considered. We provide a statistical method that clusters the solutions to further reduce their number. Such analysis always provides meaningful constraints on protection factors and can be used in situations in which obtaining more refined experimental data is impractical. It also provides a systematic way to improve data collection strategies to obtain unambiguous information at single-residue level (e.g., for assessing protein structure predictions at atomistic level).

An alternative approach to establishing unbiased colorectal cancer risk estimation in Lynch syndrome.

PURPOSE: Biallelic pathogenic variants in the mismatch repair (MMR) genes cause a recessive childhood cancer predisposition syndrome known as constitutional mismatch repair deficiency (CMMRD). Family members with a heterozygous MMR variant have Lynch syndrome. We aimed at estimating cancer risk in these heterozygous carriers as a novel approach to avoid complicated statistical methods to correct for ascertainment bias. METHODS: Cumulative colorectal cancer incidence was estimated in a cohort of PMS2- and MSH6-associated families, ascertained by the CMMRD phenotype of the index, by using mutation probabilities based on kinship coefficients as analytical weights in a proportional hazard regression on the cause-specific hazards. Confidence intervals (CIs) were obtained by bootstrapping at the family level. RESULTS: The estimated cumulative colorectal cancer risk at age 70 years for heterozygous PMS2 variant carriers was 8.7% (95% CI 4.3-12.7%) for both sexes combined, and 9.9% (95% CI 4.9-15.3%) for men and 5.9% (95% CI 1.6-11.1%) for women separately. For heterozygous MSH6 variant carriers these estimates are 11.8% (95% CI 4.5-22.7%) for both sexes combined, 10.0% (95% CI 1.83-24.5%) for men and 11.7% (95% CI 2.10-26.5%) for women. CONCLUSION: Our findings are consistent with previous reports that used more complex statistical methods to correct for ascertainment bias. These results underline the need for MMR gene-specific surveillance protocols for Lynch syndrome.

The mixed model for the analysis of a repeated-measurement multivariate count data.

Clustered overdispersed multivariate count data are challenging to model due to the presence of correlation within and between samples. Typically, the first source of correlation needs to be addressed but its quantification is of less interest. Here, we focus on the correlation between time points. In addition, the effects of covariates on the multivariate counts distribution need to be assessed. To fulfill these requirements, a regression model based on the Dirichlet-multinomial distribution for association between covariates and the categorical counts is extended by using random effects to deal with the additional clustering. This model is the Dirichlet-multinomial mixed regression model. Alternatively, a negative binomial regression mixed model can be deployed where the corresponding likelihood is conditioned on the total count. It appears that these two approaches are equivalent when the total count is fixed and independent of the random effects. We consider both subject-specific and categorical-specific random effects. However, the latter has a larger computational burden when the number of categories increases. Our work is motivated by microbiome data sets obtained by sequencing of the amplicon of the bacterial 16S rRNA gene. These data have a compositional structure and are typically overdispersed. The microbiome data set is from an epidemiological study carried out in a helminth-endemic area in Indonesia. The conclusions are as follows: time has no statistically significant effect on microbiome composition, the correlation between subjects is statistically significant, and treatment has a significant effect on the microbiome composition only in infected subjects who remained infected.

Human Plasma N-glycosylation as Analyzed by Matrix-Assisted Laser Desorption/Ionization-Fourier Transform Ion Cyclotron Resonance-MS Associates with Markers of Inflammation and Metabolic Health.

Glycosylation is an abundant co- and post-translational protein modification of importance to protein processing and activity. Although not template-defined, glycosylation does reflect the biological state of an organism and is a high-potential biomarker for disease and patient stratification. However, to interpret a complex but informative sample like the total plasma N-glycome, it is important to establish its baseline association with plasma protein levels and systemic processes. Thus far, large-scale studies (n >200) of the total plasma N-glycome have been performed with methods of chromatographic and electrophoretic separation, which, although being informative, are limited in resolving the structural complexity of plasma N-glycans. MS has the opportunity to contribute additional information on, among others, antennarity, sialylation, and the identity of high-mannose type species.Here, we have used matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance (FTICR)-MS to study the total plasma N-glycome of 2144 healthy middle-aged individuals from the Leiden Longevity Study, to allow association analysis with markers of metabolic health and inflammation. To achieve this, N-glycans were enzymatically released from their protein backbones, labeled at the reducing end with 2-aminobenzoic acid, and following purification analyzed by negative ion mode intermediate pressure MALDI-FTICR-MS. In doing so, we achieved the relative quantification of 61 glycan compositions, ranging from Hex4HexNAc2 to Hex7HexNAc6dHex1Neu5Ac4, as well as that of 39 glycosylation traits derived thereof. Next to confirming known associations of glycosylation with age and sex by MALDI-FTICR-MS, we report novel associations with C-reactive protein (CRP), interleukin 6 (IL-6), body mass index (BMI), leptin, adiponectin, HDL cholesterol, triglycerides (TG), insulin, gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), and smoking. Overall, the bisection, galactosylation, and sialylation of diantennary species, the sialylation of tetraantennary species, and the size of high-mannose species proved to be important plasma characteristics associated with inflammation and metabolic health.

Community deworming alleviates geohelminth-induced immune hyporesponsiveness.

In cross-sectional studies, chronic helminth infections have been associated with immunological hyporesponsiveness that can affect responses to unrelated antigens. To study the immunological effects of deworming, we conducted a cluster-randomized, double-blind, placebo-controlled trial in Indonesia and assigned 954 households to receive albendazole or placebo once every 3 mo for 2 y. Helminth-specific and nonspecific whole-blood cytokine responses were assessed in 1,059 subjects of all ages, whereas phenotyping of regulatory molecules was undertaken in 121 school-aged children. All measurements were performed before and at 9 and 21 mo after initiation of treatment. Anthelmintic treatment resulted in significant increases in proinflammatory cytokine responses to Plasmodium falciparum-infected red blood cells (PfRBCs) and mitogen, with the largest effect on TNF responses to PfRBCs at 9 mo-estimate [95% confidence interval], 0.37 [0.21-0.53], P value over time (Ptime) < 0.0001. Although the frequency of regulatory T cells did not change after treatment, there was a significant decline in the expression of the inhibitory molecule cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) on CD4+ T cells of albendazole-treated individuals, -0.060 [-0.107 to -0.013] and -0.057 [-0.105 to -0.008] at 9 and 21 mo, respectively; Ptime = 0.017. This trial shows the capacity of helminths to up-regulate inhibitory molecules and to suppress proinflammatory immune responses in humans. This could help to explain the inferior immunological responses to vaccines and lower prevalence of inflammatory diseases in low- compared with high-income countries.

Powerful testing via hierarchical linkage disequilibrium in haplotype association studies.

Marginal tests based on individual SNPs are routinely used in genetic association studies. Studies have shown that haplotype-based methods may provide more power in disease mapping than methods based on single markers when, for example, multiple disease-susceptibility variants occur within the same gene. A limitation of haplotype-based methods is that the number of parameters increases exponentially with the number of SNPs, inducing a commensurate increase in the degrees of freedom and weakening the power to detect associations. To address this limitation, we introduce a hierarchical linkage disequilibrium model for disease mapping, based on a reparametrization of the multinomial haplotype distribution, where every parameter corresponds to the cumulant of each possible subset of a set of loci. This hierarchy present in the parameters enables us to employ flexible testing strategies over a range of parameter sets: from standard single SNP analyses through the full haplotype distribution tests, reducing degrees of freedom and increasing the power to detect associations. We show via extensive simulations that our approach maintains the type I error at nominal level and has increased power under many realistic scenarios, as compared to single SNP and standard haplotype-based studies. To evaluate the performance of our proposed methodology in real data, we analyze genome-wide data from the Wellcome Trust Case-Control Consortium.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Effect of Anthelmintic Treatment on Insulin Resistance: A Cluster-Randomized, Placebo-Controlled Trial in Indonesia.

Background: Emerging evidence suggests that helminth infections are associated with lower insulin resistance (IR). Current deworming programs might remove this helminth-associated protective effect. Therefore, we evaluated the anthelmintic treatment effect on changes in IR. Methods: We conducted a double-blind, household-cluster-randomized, placebo-controlled clinical trial on Flores island, Indonesia, an area endemic for soil-transmitted helminths (STHs). All subjects received 4 rounds of albendazole or matching placebo with 3-month intervals, for 3 consecutive days. The primary outcome was the change in homeostatic model assessment of IR in those aged >16 years. An intention-to-treat analysis was performed involving all subjects and ad hoc in the helminth-infected subjects. Results: We examined 797 (in 329 households) and 872 (in 353 households) subjects, who were assigned randomly into the albendazole and placebo arms, respectively. Albendazole was associated with a significant reduction in STH prevalence, total immunoglobulin E (IgE), and eosinophil count. Whereas albendazole had no effect on IR (estimated treatment effect, 0.006 [95% confidence interval, -.010 to .021]; P = .48) at the community level, it was associated with a significant increase in IR (estimated treatment effect, 0.031 [95% confidence interval, .004 to .059]; P = .04) (P value for interaction = .01) among helminth-infected subjects as detected by microscopy. Pathway analysis suggested that this might in part be due to an increased body mass index or a reduced eosinophil count. Conclusions: Anthelmintic treatment reduces STH prevalence, total IgE, and eosinophil count but has no effect on IR at the community level. In helminth-infected subjects, treatment significantly increases IR, highlighting the need for metabolic health monitoring with ongoing deworming programs. Clinical Trials Registration: ISRCTN 75636394.

Secondary phenotype analysis in ascertained family designs: application to the Leiden longevity study.

The case-control design is often used to test associations between the case-control status and genetic variants. In addition to this primary phenotype, a number of additional traits, known as secondary phenotypes, are routinely recorded, and typically, associations between genetic factors and these secondary traits are studied too. Analysing secondary phenotypes in case-control studies may lead to biased genetic effect estimates, especially when the marker tested is associated with the primary phenotype and when the primary and secondary phenotypes tested are correlated. Several methods have been proposed in the literature to overcome the problem, but they are limited to case-control studies and not directly applicable to more complex designs, such as the multiple-cases family studies. A proper secondary phenotype analysis, in this case, is complicated by the within families correlations on top of the biased sampling design. We propose a novel approach to accommodate the ascertainment process while explicitly modelling the familial relationships. Our approach pairs existing methods for mixed-effects models with the retrospective likelihood framework and uses a multivariate probit model to capture the association between the mixed type primary and secondary phenotypes. To examine the efficiency and bias of the estimates, we performed simulations under several scenarios for the association between the primary phenotype, secondary phenotype and genetic markers. We will illustrate the method by analysing the association between triglyceride levels and glucose (secondary phenotypes) and genetic markers from the Leiden Longevity Study, a multiple-cases family study that investigates longevity. © 2017 The Authors. Statistics in Medicine Published by JohnWiley & Sons Ltd.

Vitamin D receptor polymorphisms and growth until adulthood after very premature birth.

The accretion of bone mass is often impaired in preterm infants, which may contribute to postnatal growth failure. We tested the effects of the vitamin D receptor single-nucleotide polymorphisms (SNPs) c1521g, Fok1, Bsm1, and Taq1 on linear growth up until adulthood in 341 subjects born very prematurely (i.e., <32 weeks of gestation) from the Dutch Project On Preterm and Small-for-gestational-age infants cohort. The GG genotype of the c1521g SNP was associated with a 0.36 [95 % confidence interval (CI), 0.02-0.69] SD taller adult stature and the ff genotype of the Fok1 SNP with a 0.38 SD (95 % CI, 0.02-0.75) taller adult stature. Interaction between these genotypes on stature was observed from the age of 1 year onward (albeit nonsignificantly before the age of 5 years), with adult height being 1.54 (95 % CI, 0.44-2.63) SD taller in subjects carrying both genotypes. The Bsm1 and Taq1 variants were both associated with faster catch-up growth until 2 years of age. Statistical correction for potential confounders did not change our results. We conclude that homozygosity for the minor alleles of both c1521g and Fok1 is associated with a taller adult stature in subjects born very prematurely. The minor alleles of Bsm1 and Taq1 are associated with faster catch-up growth in infancy.

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers.

Glycosylation of immunoglobulin G (IgG) influences IgG effector function by modulating binding to Fc receptors. To identify genetic loci associated with IgG glycosylation, we quantitated N-linked IgG glycans using two approaches. After isolating IgG from human plasma, we performed 77 quantitative measurements of N-glycosylation using ultra-performance liquid chromatography (UPLC) in 2,247 individuals from four European discovery populations. In parallel, we measured IgG N-glycans using MALDI-TOF mass spectrometry (MS) in a replication cohort of 1,848 Europeans. Meta-analysis of genome-wide association study (GWAS) results identified 9 genome-wide significant loci (P<2.27 × 10(-9)) in the discovery analysis and two of the same loci (B4GALT1 and MGAT3) in the replication cohort. Four loci contained genes encoding glycosyltransferases (ST6GAL1, B4GALT1, FUT8, and MGAT3), while the remaining 5 contained genes that have not been previously implicated in protein glycosylation (IKZF1, IL6ST-ANKRD55, ABCF2-SMARCD3, SUV420H1, and SMARCB1-DERL3). However, most of them have been strongly associated with autoimmune and inflammatory conditions (e.g., systemic lupus erythematosus, rheumatoid arthritis, ulcerative colitis, Crohn's disease, diabetes type 1, multiple sclerosis, Graves' disease, celiac disease, nodular sclerosis) and/or haematological cancers (acute lymphoblastic leukaemia, Hodgkin lymphoma, and multiple myeloma). Follow-up functional experiments in haplodeficient Ikzf1 knock-out mice showed the same general pattern of changes in IgG glycosylation as identified in the meta-analysis. As IKZF1 was associated with multiple IgG N-glycan traits, we explored biomarker potential of affected N-glycans in 101 cases with SLE and 183 matched controls and demonstrated substantial discriminative power in a ROC-curve analysis (area under the curve = 0.842). Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. The results may also provide an explanation for the reported pleiotropy and antagonistic effects of loci involved in autoimmune diseases and haematological cancer.

A meta-analysis of thyroid-related traits reveals novel loci and gender-specific differences in the regulation of thyroid function.

Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism.

Correlations between immune response and vascularization qRT-PCR gene expression clusters in squamous cervical cancer.

BACKGROUND: The tumour microenvironment comprises a network of immune response and vascularization factors. From this network, we identified immunological and vascularization gene expression clusters and the correlations between the clusters. We subsequently determined which factors were correlated with patient survival in cervical carcinoma. METHODS: The expression of 42 genes was investigated in 52 fresh frozen squamous cervical cancer samples by qRT-PCR. Weighted gene co-expression network analysis and mixed-model analyses were performed to identify gene expression clusters. Correlations and survival analyses were further studied at expression cluster and single gene level. RESULTS: We identified four immune response clusters: 'T cells' (CD3E/CD8A/TBX21/IFNG/FOXP3/IDO1), 'Macrophages' (CD4/CD14/CD163), 'Th2' (IL4/IL5/IL13/IL12) and 'Inflammation' (IL6/IL1B/IL8/IL23/IL10/ARG1) and two vascularization clusters: 'Angiogenesis' (VEGFA/FLT1/ANGPT2/ PGF/ICAM1) and 'Vessel maturation' (PECAM1/VCAM1/ANGPT1/SELE/KDR/LGALS9). The 'T cells' module was correlated with all modules except for 'Inflammation', while 'Inflammation' was most significantly correlated with 'Angiogenesis' (p < 0.001). High expression of the 'T cells' cluster was correlated with earlier TNM stage (p = 0.007). High CD3E expression was correlated with improved disease-specific survival (p = 0.022), while high VEGFA expression was correlated with poor disease-specific survival (p = 0.032). Independent predictors of poor disease-specific survival were IL6 (hazard ratio = 2.3, p = 0.011) and a high IL6/IL17 ratio combined with low IL5 expression (hazard ratio = 4.2, p = 0.010). CONCLUSIONS: 'Inflammation' marker IL6, especially in combination with low levels of IL5 and IL17, was correlated with poor survival. This suggests that IL6 promotes tumour growth, which may be suppressed by a Th17 and Th2 response. Measuring IL6, IL5 and IL17 expression may improve the accuracy of predicting prognosis in cervical cancer.

Cluster headache and the hypocretin receptor 2 reconsidered: a genetic association study and meta-analysis.

BACKGROUND: Cluster headache is a severe neurological disorder with a complex genetic background. A missense single nucleotide polymorphism (rs2653349; p.Ile308Val) in the HCRTR2 gene that encodes the hypocretin receptor 2 is the only genetic factor that is reported to be associated with cluster headache in different studies. However, as there are conflicting results between studies, we re-evaluated its role in cluster headache. METHODS: We performed a genetic association analysis for rs2653349 in our large Leiden University Cluster headache Analysis (LUCA) program study population. Systematic selection of the literature yielded three additional studies comprising five study populations, which were included in our meta-analysis. Data were extracted according to predefined criteria. RESULTS: A total of 575 cluster headache patients from our LUCA study and 874 controls were genotyped for HCRTR2 SNP rs2653349 but no significant association with cluster headache was found (odds ratio 0.91 (95% confidence intervals 0.75-1.10), p = 0.319). In contrast, the meta-analysis that included in total 1167 cluster headache cases and 1618 controls from the six study populations, which were part of four different studies, showed association of the single nucleotide polymorphism with cluster headache (random effect odds ratio 0.69 (95% confidence intervals 0.53-0.90), p = 0.006). The association became weaker, as the odds ratio increased to 0.80, when the meta-analysis was repeated without the initial single South European study with the largest effect size. CONCLUSIONS: Although we did not find evidence for association of rs2653349 in our LUCA study, which is the largest investigated study population thus far, our meta-analysis provides genetic evidence for a role of HCRTR2 in cluster headache. Regardless, we feel that the association should be interpreted with caution as meta-analyses with individual populations that have limited power have diminished validity.

Helminth infections and type 2 diabetes: a cluster-randomized placebo controlled SUGARSPIN trial in Nangapanda, Flores, Indonesia.

BACKGROUND: Insulin resistance is a strong predictor of the development of type 2 diabetes mellitus. Chronic helminth infections might protect against insulin resistance via a caloric restriction state and indirectly via T-helper-2 polarization of the immune system. Therefore the elimination of helminths might remove this beneficial effect on insulin resistance. METHODS/DESIGN: To determine whether soil-transmitted helminth infections are associated with a better whole-body insulin sensitivity and whether this protection is reversible by anthelmintic treatment, a household-based cluster-randomized, double blind, placebo-controlled trial was conducted in the area of Nangapanda on Flores Island, Indonesia, an area endemic for soil-transmitted helminth infections. The trial incorporates three monthly treatment with albendazole or matching placebo for one year, whereby each treatment round consists of three consecutive days of supervised drug intake. The presence of soil-transmitted helminths will be evaluated in faeces using microscopy and/or PCR. The primary outcome of the study will be changes in insulin resistance as assessed by HOMA-IR, while the secondary outcomes will be changes in body mass index, waist circumference, fasting blood glucose, 2 h-glucose levels after oral glucose tolerance test, HbA1c, serum lipid levels, immunological parameters, and efficacy of anthelmintic treatment. DISCUSSION: The study will provide data on the effect of helminth infections on insulin resistance. It will assess the relationship between helminth infection status and immune responses as well as metabolic parameters, allowing the establishment of a link between inflammation and whole-body metabolic homeostasis. In addition, it will give information on anthelmintic treatment efficacy and effectiveness. TRIAL REGISTRATION: This study has been approved by the ethical committee of Faculty of Medicine Universitas Indonesia (ref: 549/H2.F1/ETIK/2013), and has been filed by the ethics committee of Leiden University Medical Center, clinical trial number: ISRCTN75636394. The study is reported in accordance with the CONSORT guidelines for cluster-randomised trials.

Identification of a genetic variant for joint damage progression in autoantibody-positive rheumatoid arthritis.

BACKGROUND: Joint destruction is a hallmark of autoantibody-positive rheumatoid arthritis (RA), though the severity is highly variable between patients. The processes underlying these interindividual differences are incompletely understood. METHODS: We performed a genome-wide association study on the radiological progression rate in 384 autoantibody-positive patients with RA. In stage-II 1557 X-rays of 301 Dutch autoantibody-positive patients with RA were studied and in stage-III 861 X-rays of 742 North American autoantibody-positive patients with RA. Sperm-Associated Antigen 16 (SPAG16) expression in RA synovium and fibroblast-like synoviocytes (FLS) was examined using Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) and immunohistochemistry. FLS secrete metalloproteinases that degrade cartilage and bone. SPAG16 genotypes were related to matrix metalloproteinase (MMP)-3 and MMP-1 expression by FLS in vitro and MMP-3 production ex vivo. RESULTS: A cluster of single nucleotide polymorphisms (SNPs) at 2q34, located at SPAG16, associated with the radiological progression rate; rs7607479 reached genome-wide significance. A protective role of rs7607479 was replicated in European and North American patients with RA. Per minor allele, patients had a 0.78-fold (95% CI 0.67 to 0.91) progression rate over 7 years. mRNA and protein expression of SPAG16 in RA synovium and FLS was verified. FLS carrying the minor allele secreted less MMP-3 (p=1.60×10(-2)). Furthermore, patients with RA carrying the minor allele had lower serum levels of MMP-3 (p=4.28×10(-2)). In a multivariate analysis on rs7607479 and MMP-3, only MMP-3 associated with progression (p=2.77×10(-4)), suggesting that the association between SPAG16-rs7607479 and joint damage is mediated via an effect on MMP-3 secretion. CONCLUSIONS: Genetic and functional analyses indicate that SPAG16 influences MMP-3 regulation and protects against joint destruction in autoantibody-positive RA. These findings could enhance risk stratification in autoantibody-positive RA.

Combining family and twin data in association studies to estimate the noninherited maternal antigens effect.

It is hypothesized that certain alleles can have a protective effect not only when inherited by the offspring but also as noninherited maternal antigens (NIMA). To estimate the NIMA effect, large samples of families are needed. When large samples are not available, we propose a combined approach to estimate the NIMA effect from ascertained nuclear families and twin pairs. We develop a likelihood-based approach allowing for several ascertainment schemes, to accommodate for the outcome-dependent sampling scheme, and a family-specific random term, to take into account the correlation between family members. We estimate the parameters using maximum likelihood based on the combined joint likelihood (CJL) approach. Simulations show that the CJL is more efficient for estimating the NIMA odds ratios as compared to a families-only approach. To illustrate our approach, we used data from a family and a twin study from the United Kingdom on rheumatoid arthritis, and confirmed the protective NIMA effect, with an odds ratio of 0.477 (95% CI 0.264-0.864).

Identification of new susceptibility loci for osteoarthritis (arcOGEN): a genome-wide association study.

BACKGROUND: Osteoarthritis is the most common form of arthritis worldwide and is a major cause of pain and disability in elderly people. The health economic burden of osteoarthritis is increasing commensurate with obesity prevalence and longevity. Osteoarthritis has a strong genetic component but the success of previous genetic studies has been restricted due to insufficient sample sizes and phenotype heterogeneity. METHODS: We undertook a large genome-wide association study (GWAS) in 7410 unrelated and retrospectively and prospectively selected patients with severe osteoarthritis in the arcOGEN study, 80% of whom had undergone total joint replacement, and 11,009 unrelated controls from the UK. We replicated the most promising signals in an independent set of up to 7473 cases and 42,938 controls, from studies in Iceland, Estonia, the Netherlands, and the UK. All patients and controls were of European descent. FINDINGS: We identified five genome-wide significant loci (binomial test p≤5·0×10(-8)) for association with osteoarthritis and three loci just below this threshold. The strongest association was on chromosome 3 with rs6976 (odds ratio 1·12 [95% CI 1·08-1·16]; p=7·24×10(-11)), which is in perfect linkage disequilibrium with rs11177. This SNP encodes a missense polymorphism within the nucleostemin-encoding gene GNL3. Levels of nucleostemin were raised in chondrocytes from patients with osteoarthritis in functional studies. Other significant loci were on chromosome 9 close to ASTN2, chromosome 6 between FILIP1 and SENP6, chromosome 12 close to KLHDC5 and PTHLH, and in another region of chromosome 12 close to CHST11. One of the signals close to genome-wide significance was within the FTO gene, which is involved in regulation of bodyweight-a strong risk factor for osteoarthritis. All risk variants were common in frequency and exerted small effects. INTERPRETATION: Our findings provide insight into the genetics of arthritis and identify new pathways that might be amenable to future therapeutic intervention. FUNDING: arcOGEN was funded by a special purpose grant from Arthritis Research UK.