Smoking induces sex-specific changes in the small airway proteome.

INTRODUCTION: Cigarette smoke triggers many cellular and signaling responses in the lung and the resulting inflammation plays a central role in smoke-related lung diseases, such as COPD. We explored the effects of smoking on the small airway proteome in samples obtained by collection of exhaled particles with the aim to identify specific proteins dysregulated by smoking. METHODS: Exhaled particles were obtained from 38 current smokers, 47 former smokers and 22 healthy controls with the PExA method. 120 ng of sample was collected from individual subjects and analyzed with the SOMAscan proteomics platform. General linear model-based statistics were performed. RESULTS: Two hundred and three proteins were detected in at least half of 107 total samples. Active smoking exerted a significant impact on the protein composition of respiratory tract lining fluid (RTLF), with 81 proteins altered in current smokers compared to never smokers (p < 0.05, q < 0.124). Among the proteins most clearly discriminating between current and never smokers were sRAGE, FSTL3, SPOCK2 and protein S, all of them being less abundant in current smokers. Analysis stratified for sex unveiled sex differences with more pronounced proteomic alterations due to active smoking in females than males. Proteins whose abundance was altered by active smoking in women were to a larger extent related to the complement system. The small airway protein profile of former smokers appeared to be more similar to that observed in never smokers. CONCLUSIONS: The study shows that smoking has a strong impact on protein expression in the small airways, and that smoking affects men and women differently, suggesting PExA sampling combined with high sensitivity protein analysis offers a promising platform for early detection of COPD and identification of novel COPD drug targets.

Leveraging Human Genetics to Estimate Clinical Risk Reductions Achievable by Inhibiting Factor XI.

Background and Purpose- Coagulation factor XI (FXI) is a novel target for antithrombotic therapy addressed by various therapeutic modalities currently in clinical development. The expected magnitude of thrombotic event reduction mediated by targeting FXI is unclear. Methods- We analyzed the association of 2 common genetic variants, which alter levels of FXI, with a range of human phenotypes. We combined variants into a genetic score standardized to a 30% increase in relative activated partial thromboplastin time, equivalent to what can be achieved with pharmacological FXI reduction. Using data from 371 695 participants in the United Kingdom Biobank and 2 large-scale genome-wide association studies, we examined the effect of this FXI score on thrombotic and bleeding end points. Results- Genetic disposition to lower FXI levels was associated with reduced risks of venous thrombosis (odds ratio, 95% CI; P value; odds ratio=0.1, 0.07-0.14; P=3×10-43) and ischemic stroke (odds ratio=0.47, 0.36-0.61; P=2×10-8) but not with major bleeding (odds ratio=0.7, 0.45-1.04; P=0.0739). The observed relative risk reductions were consistent within a range of subgroups that were at high risk for thrombosis. Consistently, we observed higher absolute risk reductions conferred by genetically lower FXI levels in high-risk subgroups, such as patients with atrial fibrillation. Conclusions- Human genetic data suggest that pharmacological inhibition of FXI may achieve considerable reductions in ischemic stroke risk without clear evidence for an associated risk of major bleeding. The quantitative framework developed can be used to support the estimation of achievable risk reductions with pharmacological modulation of FXI.

Copy number variants encompassing Mendelian disease genes in a large multigenerational family segregating bipolar disorder.

BACKGROUND: Bipolar affective disorder (BP) is a common, highly heritable psychiatric disorder characterized by periods of depression and mania. Using dense SNP genotype data, we characterized CNVs in 388 members of an Old Order Amish Pedigree with bipolar disorder. We identified CNV regions arising from common ancestral mutations by utilizing the pedigree information. By combining this analysis with whole genome sequence data in the same individuals, we also explored the role of compound heterozygosity. RESULTS: Here we describe 541 inherited CNV regions, of which 268 are rare in a control population of European origin but present in a large number of Amish individuals. In addition, we highlight a set of CNVs found at higher frequencies in BP individuals, and within genes known to play a role in human development and disease. As in prior reports, we find no evidence for an increased burden of CNVs in BP individuals, but we report a trend towards a higher burden of CNVs in known Mendelian disease loci in bipolar individuals (BPI and BPII, p = 0.06). CONCLUSIONS: We conclude that CNVs may be contributing factors in the phenotypic presentation of mood disorders and co-morbid medical conditions in this family. These results reinforce the hypothesis of a complex genetic architecture underlying BP disorder, and suggest that the role of CNVs should continue to be investigated in BP data sets.

A population-based study of KCNH7 p.Arg394His and bipolar spectrum disorder.

We conducted blinded psychiatric assessments of 26 Amish subjects (52 ± 11 years) from four families with prevalent bipolar spectrum disorder, identified 10 potentially pathogenic alleles by exome sequencing, tested association of these alleles with clinical diagnoses in the larger Amish Study of Major Affective Disorder (ASMAD) cohort, and studied mutant potassium channels in neurons. Fourteen of 26 Amish had bipolar spectrum disorder. The only candidate allele shared among them was rs78247304, a non-synonymous variant of KCNH7 (c.1181G>A, p.Arg394His). KCNH7 c.1181G>A and nine other potentially pathogenic variants were subsequently tested within the ASMAD cohort, which consisted of 340 subjects grouped into controls subjects and affected subjects from overlapping clinical categories (bipolar 1 disorder, bipolar spectrum disorder and any major affective disorder). KCNH7 c.1181G>A had the highest enrichment among individuals with bipolar spectrum disorder (χ(2) = 7.3) and the strongest family-based association with bipolar 1 (P = 0.021), bipolar spectrum (P = 0.031) and any major affective disorder (P = 0.016). In vitro, the p.Arg394His substitution allowed normal expression, trafficking, assembly and localization of HERG3/Kv11.3 channels, but altered the steady-state voltage dependence and kinetics of activation in neuronal cells. Although our genome-wide statistical results do not alone prove association, cumulative evidence from multiple independent sources (parallel genome-wide study cohorts, pharmacological studies of HERG-type potassium channels, electrophysiological data) implicates neuronal HERG3/Kv11.3 potassium channels in the pathophysiology of bipolar spectrum disorder. Such a finding, if corroborated by future studies, has implications for mental health services among the Amish, as well as development of drugs that specifically target HERG3/Kv11.3.

Genomic view of bipolar disorder revealed by whole genome sequencing in a genetic isolate.

Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable effort to elucidate the genetic underpinnings of bipolar disorder, causative genetic risk factors remain elusive. We conducted a comprehensive genomic analysis of bipolar disorder in a large Old Order Amish pedigree. Microsatellite genotypes and high-density SNP-array genotypes of 388 family members were combined with whole genome sequence data for 50 of these subjects, comprising 18 parent-child trios. This study design permitted evaluation of candidate variants within the context of haplotype structure by resolving the phase in sequenced parent-child trios and by imputation of variants into multiple unsequenced siblings. Non-parametric and parametric linkage analysis of the entire pedigree as well as on smaller clusters of families identified several nominally significant linkage peaks, each of which included dozens of predicted deleterious variants. Close inspection of exonic and regulatory variants in genes under the linkage peaks using family-based association tests revealed additional credible candidate genes for functional studies and further replication in population-based cohorts. However, despite the in-depth genomic characterization of this unique, large and multigenerational pedigree from a genetic isolate, there was no convergence of evidence implicating a particular set of risk loci or common pathways. The striking haplotype and locus heterogeneity we observed has profound implications for the design of studies of bipolar and other related disorders.

From mouse to human: evolutionary genomics analysis of human orthologs of essential genes.

Understanding the core set of genes that are necessary for basic developmental functions is one of the central goals in biology. Studies in model organisms identified a significant fraction of essential genes through the analysis of null-mutations that lead to lethality. Recent large-scale next-generation sequencing efforts have provided unprecedented data on genetic variation in human. However, evolutionary and genomic characteristics of human essential genes have never been directly studied on a genome-wide scale. Here we use detailed phenotypic resources available for the mouse and deep genomics sequencing data from human populations to characterize patterns of genetic variation and mutational burden in a set of 2,472 human orthologs of known essential genes in the mouse. Consistent with the action of strong, purifying selection, these genes exhibit comparatively reduced levels of sequence variation, skew in allele frequency towards more rare, and exhibit increased conservation across the primate and rodent lineages relative to the remainder of genes in the genome. In individual genomes we observed ~12 rare mutations within essential genes predicted to be damaging. Consistent with the hypothesis that mutations in essential genes are risk factors for neurodevelopmental disease, we show that de novo variants in patients with Autism Spectrum Disorder are more likely to occur in this collection of genes. While incomplete, our set of human orthologs shows characteristics fully consistent with essential function in human and thus provides a resource to inform and facilitate interpretation of sequence data in studies of human disease.

PyMix--the python mixture package--a tool for clustering of heterogeneous biological data.

BACKGROUND: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers. This makes clustering challenging. Mixtures are versatile and powerful statistical models which perform robustly for clustering in the presence of noise and have been successfully applied in a wide range of applications. RESULTS: PyMix - the Python mixture package implements algorithms and data structures for clustering with basic and advanced mixture models. The advanced models include context-specific independence mixtures, mixtures of dependence trees and semi-supervised learning. PyMix is licenced under the GNU General Public licence (GPL). PyMix has been successfully used for the analysis of biological sequence, complex disease and gene expression data. CONCLUSIONS: PyMix is a useful tool for cluster analysis of biological data. Due to the general nature of the framework, PyMix can be applied to a wide range of applications and data sets.

Partially-supervised protein subclass discovery with simultaneous annotation of functional residues.

BACKGROUND: The study of functional subfamilies of protein domain families and the identification of the residues which determine substrate specificity is an important question in the analysis of protein domains. One way to address this question is the use of clustering methods for protein sequence data and approaches to predict functional residues based on such clusterings. The locations of putative functional residues in known protein structures provide insights into how different substrate specificities are reflected on the protein structure level. RESULTS: We have developed an extension of the context-specific independence mixture model clustering framework which allows for the integration of experimental data. As these are usually known only for a few proteins, our algorithm implements a partially-supervised learning approach. We discover domain subfamilies and predict functional residues for four protein domain families: phosphatases, pyridoxal dependent decarboxylases, WW and SH3 domains to demonstrate the usefulness of our approach. CONCLUSION: The partially-supervised clustering revealed biologically meaningful subfamilies even for highly heterogeneous domains and the predicted functional residues provide insights into the basis of the different substrate specificities.

Incomplete and inaccurate vocal imitation after knockdown of FoxP2 in songbird basal ganglia nucleus Area X.

The gene encoding the forkhead box transcription factor, FOXP2, is essential for developing the full articulatory power of human language. Mutations of FOXP2 cause developmental verbal dyspraxia (DVD), a speech and language disorder that compromises the fluent production of words and the correct use and comprehension of grammar. FOXP2 patients have structural and functional abnormalities in the striatum of the basal ganglia, which also express high levels of FOXP2. Since human speech and learned vocalizations in songbirds bear behavioral and neural parallels, songbirds provide a genuine model for investigating the basic principles of speech and its pathologies. In zebra finch Area X, a basal ganglia structure necessary for song learning, FoxP2 expression increases during the time when song learning occurs. Here, we used lentivirus-mediated RNA interference (RNAi) to reduce FoxP2 levels in Area X during song development. Knockdown of FoxP2 resulted in an incomplete and inaccurate imitation of tutor song. Inaccurate vocal imitation was already evident early during song ontogeny and persisted into adulthood. The acoustic structure and the duration of adult song syllables were abnormally variable, similar to word production in children with DVD. Our findings provide the first example of a functional gene analysis in songbirds and suggest that normal auditory-guided vocal motor learning requires FoxP2.

Context-specific independence mixture modeling for positional weight matrices.

MOTIVATION: A positional weight matrix (PWM) is a statistical representation of the binding pattern of a transcription factor estimated from known binding site sequences. Previous studies showed that for factors which bind to divergent binding sites, mixtures of multiple PWMs increase performance. However, estimating a conventional mixture distribution for each position will in many cases cause overfitting. RESULTS: We propose a context-specific independence (CSI) mixture model and a learning algorithm based on a Bayesian approach. The CSI model adjusts complexity to fit the amount of variation observed on the sequence level in each position of a site. This not only yields a more parsimonious description of binding patterns, which improves parameter estimates, it also increases robustness as the model automatically adapts the number of components to fit the data. Evaluation of the CSI model on simulated data showed favorable results compared to conventional mixtures. We demonstrate its adaptive properties in a classical model selection setup. The increased parsimony of the CSI model was shown for the transcription factor Leu3 where two binding-energy subgroups were distinguished equally well as with a conventional mixture but requiring 30% less parameters. Analysis of the human-mouse conservation of predicted binding sites of 64 JASPAR TFs showed that CSI was as good or better than a conventional mixture for 89% of the TFs and for 70% for a single PWM model. AVAILABILITY: http://algorithmics.molgen.mpg.de/mixture.

Low-dose hyperradiosensitivity of human glioblastoma cell lines in vitro does not translate into improved outcome of ultrafractionated radiotherapy in vivo.

PURPOSE: Low dose hyperradiosensitivity (HRS) has been observed in HGL21- and T98G human glioblastoma cells in vitro. The present study investigates whether these effects translate into improved outcome of ultrafractionated irradiation (UF) in vivo. MATERIAL AND METHODS: T98G or HGL21 were transplanted on the hind leg of nude mice. Tumours were irradiated with UF (3 fractions of 0.4 Gy per day, interval 4 h, 7 days per week) or with conventional fractionation (CF; 1 fraction of 1.68 Gy per day, 5 days per week) over 2 or 4 weeks in HGL21 and 2,4 or 6 weeks in T98G. In HGL21, graded top-up doses under clamped hypoxia were applied after 4 weeks of fractionated irradiation. Additional groups of animals were irradiated with single doses under clamp hypoxic conditions with or without whole body irradiation (WBI) before tumour transplantation. Experimental endpoints were growth delay (time to 5-fold starting volume, GD(V5)) and local tumour control. RESULTS: In T98G tumours median relative GD(V5) was 1.2 [95% C.I. 0.96; 8] in the CF and 0.8 [0.7; 1.02] in the UF arm (p = 0.009) indicating that ultrafractionation is less efficient than conventional fractionation. The TCD50 value of 33.5 Gy [22; 45] after UF was higher than TCD50 of 23.6 Gy [16; 31] after CF (p = 0.15). In HGL21 the median relative GD(V5) was not significantly different between CF and UF. The top-up TCD50 value of 16.1 Gy [95% C.I. 9; 23 Gy] after CF was significantly lower than the corresponding value of 33.2 Gy [23; 44] after UF irradiation (p = 0.007), indicating a higher efficacy of CF compared to UF. CONCLUSION: The results on human T98G and HGL21 glioblastoma do not support the hypothesis that HRS in vitro translates into improved outcome of ultrafractionated irradiation in vivo.

MACAT--microarray chromosome analysis tool.

UNLABELLED: By linking differential gene expression to the chromosomal localization of genes, one can investigate microarray data for characteristic patterns of expression phenomena involving sizeable parts of specific chromosomes. We have implemented a statistical approach for identifying significantly differentially expressed chromosome regions. We demonstrate the applicability of the approach on a publicly available data set on acute lymphocytic leukemia. AVAILABILITY: The R-package MACAT can be obtained from http://www.compdiag.molgen.mpg.de/software/macat.shtml SUPPLEMENTARY INFORMATION: http://www.compdiag.molgen.mpg.de/software/macat.shtml.