A reliable measure of similarity based on dependency for short time series: an application to gene expression networks

Background  

Microarray techniques have become an important tool to the investigation of genetic relationships and the assignment of different phenotypes. Since microarrays are still very expensive, most of the experiments are performed with small samples. This paper introduces a method to quantify dependency between data series composed of few sample points. The method is used to construct gene co-expression subnetworks of highly significant edges.     

Effects of 3-beta-diol, an androgen metabolite with intrinsic estrogen-like effects, in modulating the aquaporin-9 expression in the rat efferent ductules

Background  

Fluid homeostasis is critical for normal function of the male reproductive tract and aquaporins (AQP) play an important role in maintenance of this water and ion balance. Several AQPs have been identified in the male, but their regulation is not fully comprehended. Hormonal regulation of AQPs appears to be dependent on the steroid in the reproductive tract region. AQP9 displays unique hormonal regulation in the efferent ductules and epididymis, as it is regulated by both estrogen and dihydrotestosterone (DHT) in the efferent ductules, but only by DHT in the initial segment epididymis. Recent data have shown that a metabolite of DHT, 5-alpha-androstane-3-beta-17-beta-diol (3-beta-diol), once considered inactive, is also present in high concentrations in the male and indeed has biological activity. 3-beta-diol does not bind to the androgen receptor, but rather to estrogen receptors ER-alpha and ER-beta, with higher affinity for ER-beta. The existence of this estrogenic DHT metabolite has raised the possibility that estradiol may not be the only estrogen to play a major role in the male reproductive system. Considering that both ER-alpha and ER-beta are highly expressed in efferent ductules, we hypothesized that the DHT regulation of AQP9 could be due to the 3-beta-diol metabolite.     

Heritability of cardiovascular and personality traits in 6,148 Sardinians

In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14–102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits.     

Gene expression in skin and lymphoblastoid cells: Refined statistical method reveals extensive overlap in cis-eQTL signals

Psoriasis, an immune-mediated, inflammatory disease of the skin and joints, provides an ideal system for expression quantitative trait locus (eQTL) analysis, because it has a strong genetic basis and disease-relevant tissue (skin) is readily accessible. To better understand the role of genetic variants regulating cutaneous gene expression, we identified 841 cis-acting eQTLs using RNA extracted from skin biopsies of 53 psoriatic individuals and 57 healthy controls. We found substantial overlap between cis-eQTLs of normal control, uninvolved psoriatic, and lesional psoriatic skin. Consistent with recent studies and with the idea that control of gene expression can mediate relationships between genetic variants and disease risk, we found that eQTL SNPs are more likely to be associated with psoriasis than are randomly selected SNPs. To explore the tissue specificity of these eQTLs and hence to quantify the benefits of studying eQTLs in different tissues, we developed a refined statistical method for estimating eQTL overlap and used it to compare skin eQTLs to a published panel of lymphoblastoid cell line (LCL) eQTLs. Our method accounts for the fact that most eQTL studies are likely to miss some true eQTLs as a result of power limitations and shows that ～70% of cis-eQTLs in LCLs are shared with skin, as compared with the naive estimate of < 50% sharing. Our results provide a useful method for estimating the overlap between various eQTL studies and provide a catalog of cis-eQTLs in skin that can facilitate efforts to understand the functional impact of identified susceptibility variants on psoriasis and other skin traits.     

Aggravation of myocardial dysfunction by injurious mechanical ventilation in LPS-induced pneumonia in rats

Background

Mechanical ventilation (MV) may cause ventilator-induced lung injury (VILI) and may thereby contribute to fatal multiple organ failure. We tested the hypothesis that injurious MV of lipopolysaccharide (LPS) pre-injured lungs induces myocardial inflammation and further dysfunction ex vivo, through calcium (Ca²⁺)-dependent mechanism.

Materials and methods

N = 35 male anesthetized and paralyzed male Wistar rats were randomized to intratracheal instillation of 2 mg/kg LPS or nothing and subsequent MV with lung-protective settings (low tidal volume (V_t) of 6 mL/kg and 5 cmH₂O positive end-expiratory pressure (PEEP)) or injurious ventilation (high V_t of 19 mL/kg and 1 cmH₂O PEEP) for 4 hours. Myocardial function ex vivo was evaluated in a Langendorff setup and Ca²⁺ exposure. Key mediators were determined in lung and heart at the mRNA level.

Results

Instillation of LPS and high V_t MV impaired gas exchange and, particularly when combined, increased pulmonary wet/dry ratio; heat shock protein (HSP)70 mRNA expression also increased by the interaction between LPS and high V_t MV. For the heart, C-X-C motif ligand (CXCL)1 and Toll-like receptor (TLR)2 mRNA expression increased, and ventricular (LV) systolic pressure, LV developed pressure, LV +dP/dt_max and contractile responses to increasing Ca²⁺ exposure ex vivo decreased by LPS. High V_t ventilation aggravated the effects of LPS on myocardial inflammation and dysfunction but not on Ca²⁺ responses.

Conclusions

Injurious MV by high V_t aggravates the effects of intratracheal instillation of LPS on myocardial dysfunction, possibly through enhancing myocardial inflammation via pulmonary release of HSP70 stimulating cardiac TLR2, not involving Ca²⁺ handling and sensitivity.     

Pervasive sharing of genetic effects in autoimmune disease

Genome-wide association (GWA) studies have identified numerous, replicable, genetic associations between common single nucleotide polymorphisms (SNPs) and risk of common autoimmune and inflammatory (immune-mediated) diseases, some of which are shared between two diseases. Along with epidemiological and clinical evidence, this suggests that some genetic risk factors may be shared across diseases-as is the case with alleles in the Major Histocompatibility Locus. In this work we evaluate the extent of this sharing for 107 immune disease-risk SNPs in seven diseases: celiac disease, Crohn's disease, multiple sclerosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes. We have developed a novel statistic for Cross Phenotype Meta-Analysis (CPMA) which detects association of a SNP to multiple, but not necessarily all, phenotypes. With it, we find evidence that 47/107 (44%) immune-mediated disease risk SNPs are associated to multiple-but not all-immune-mediated diseases (SNP-wise P(CPMA)<0.01). We also show that distinct groups of interacting proteins are encoded near SNPs which predispose to the same subsets of diseases; we propose these as the mechanistic basis of shared disease risk. We are thus able to leverage genetic data across diseases to construct biological hypotheses about the underlying mechanism of pathogenesis.     

Impact of hypoxia and long-term cultivation on the genomic stability and mitochondrial performance of ex vivo expanded human stem/stromal cells

Recent studies have described the occurrence of chromosomal abnormalities and mitochondrial dysfunction in human stem/stromal cells (SCs), particularly after extensive passaging in vitro and/or expansion under low oxygen tensions. To deepen this knowledge we investigated the influence of hypoxia (2% O(2)) and prolonged passaging (>P10) of human bone marrow stromal cells (BMSCs) and adipose-derived stromal cells (ASCs) on the expression of genes involved in DNA repair and cell-cycle regulation pathways, as well as on the occurrence of microsatellite instability and changes in telomere length. Our results show that hypoxic conditions induce an immediate and concerted down-regulation of genes involved in DNA repair and damage response pathways (MLH1, RAD51, BRCA1, and Ku80), concomitantly with the occurrence of microsatellite instability while maintaining telomere length. We further searched for mutations occurring in the mitochondrial genome, and monitored changes in intracellular ATP content, membrane potential and mitochondrial DNA content. Hypoxia led to a simultaneous decrease in ATP content and in the number of mitochondrial genomes, whereas the opposite effect was observed after prolonged passaging. Moreover, we show that neither hypoxia nor prolonged passaging significantly affected the integrity of the mitochondrial genome. Ultimately, we present evidence on how hypoxia selectively impacts the cellular response of BMSCs and ASCs, thus pointing for the need to optimize oxygen tension according to the cell source.     

Murine Borrelia arthritis is highly dependent on ASC and caspase-1, but independent of NLRP3

Introduction

The protein platform called the NOD-like-receptor -family member (NLRP)-3 inflammasome needs to be activated to process intracellular caspase-1. Active caspase-1 is able to cleave pro-Interleukin (IL)-1β, resulting in bioactive IL-1β. IL-1β is a potent proinflammatory cytokine, and thought to play a key role in the pathogenesis of Lyme arthritis, a common manifestation of Borrelia burgdorferi infection. The precise pathways through which B. burgdorferi recognition leads to inflammasome activation and processing of IL-1β in Lyme arthritis has not been elucidated. In the present study, we investigated the contribution of several pattern recognition receptors and inflammasome components in a novel murine model of Lyme arthritis.

Methods

Lyme arthritis was elicited by live B. burgdorferi, injected intra-articularly in knee joints of mice. To identify the relevant pathway components, the model was applied to wild-type, NLRP3-/-, ASC-/-, caspase-1-/-, NOD1-/-, NOD2-/-, and RICK-/- mice. As a control, TLR2-/-, Myd88-/- and IL-1R-/- mice were used. Peritoneal macrophages and bone marrow-derived macrophages were used for in vitro cytokine production and inflammasome activation studies. Joint inflammation was analyzed in synovial specimens and whole knee joints. Mann-Whitney U tests were used to detect statistical differences.

Results

We demonstrate that ASC/caspase-1-driven IL-1β is crucial for induction of B. burgdorferi-induced murine Lyme arthritis. In addition, we show that B. burgdorferi-induced murine Lyme arthritis is less dependent on NOD1/NOD2/RICK pathways while the TLR2-MyD88 pathway is crucial.

Conclusions

Murine Lyme arthritis is strongly dependent on IL-1 production, and B. burgdorferi induces inflammasome-mediated caspase-1 activation. Next to that, murine Lyme arthritis is ASC- and caspase-1-dependent, but NLRP3, NOD1, NOD2, and RICK independent. Also, caspase-1 activation by B. burgdorferi is dependent on TLR2 and MyD88. Based on present results indicating that IL-1 is one of the major mediators in Lyme arthritis, there is a rationale to propose that neutralizing IL-1 activity may also have beneficial effects in chronic Lyme arthritis.     

A Likelihood-Based Framework for Variant Calling and De Novo Mutation Detection in Families

Family samples, which can be enriched for rare causal variants by focusing on families with multiple extreme individuals and which facilitate detection of de novo mutation events, provide an attractive resource for next-generation sequencing studies. Here, we describe, implement, and evaluate a likelihood-based framework for analysis of next generation sequence data in family samples. Our framework is able to identify variant sites accurately and to assign individual genotypes, and can handle de novo mutation events, increasing the sensitivity and specificity of variant calling and de novo mutation detection. Through simulations we show explicit modeling of family relationships is especially useful for analyses of low-frequency variants and that genotype accuracy increases with the number of individuals sequenced per family. Compared with the standard approach of ignoring relatedness, our methods identify and accurately genotype more variants, and have high specificity for detecting de novo mutation events. The improvement in accuracy using our methods over the standard approach is particularly pronounced for low-frequency variants. Furthermore the family-aware calling framework dramatically reduces Mendelian inconsistencies and is beneficial for family-based analysis. We hope our framework and software will facilitate continuing efforts to identify genetic factors underlying human diseases.