Linkage disequilibrium in young genetically isolated Dutch population

The design and feasibility of genetic studies of complex diseases are critically dependent on the extent and distribution of linkage disequilibrium (LD) across the genome and between different populations. We have examined genomewide and region-specific LD in a young genetically isolated population identified in the Netherlands by genotyping approximately 800 Short Tandem Repeat markers distributed genomewide across 58 individuals. Several regions were an

The Cluster Variation Method for Efficient Linkage Analysis on Extended Pedigrees

BACKGROUND: Computing exact multipoint LOD scores for extended pedigrees rapidly becomes infeasible as the number of markers and untyped individuals increase. When markers are excluded from the computation, significant power may be lost. Therefore accurate approximate methods which take into account all markers are desirable. METHODS: We present a novel method for efficient estimation of LOD scores on extended pedigrees. Our approach is based on the Cluster Variation Method, which deterministically estimates likelihoods by performing exact computations on tractable subsets of variables (clusters) of a Bayesian network. First a distribution over inheritances on the marker loci is approximated with the Cluster Variation Method. Then this distribution is used to estimate the LOD score for each location of the trait locus. RESULTS: First we demonstrate that significant power may be lost if markers are ignored in the multi-point analysis. On a set of pedigrees where exact computation is possible we compare the estimates of the LOD scores obtained with our method to the exact LOD scores. Secondly, we compare our method to a state of the art MCMC sampler. When both methods are given equal computation time, our method is more efficient. Finally, we show that CVM scales to large problem instances. CONCLUSION: We conclude that the Cluster Variation Method is as accurate as MCMC and generally is more efficient. Our method is a promising alternative to approaches based on MCMC sampling

Pentachlorophenol Induction of the Pseudomonas aeruginosa mexAB-oprM Efflux Operon: Involvement of Repressors NalC and MexR and the Antirepressor ArmR

Pentachlorophenol (PCP) induced expression of the NalC repressor-regulated PA3720-armR operon and the MexR repressor-controlled mexAB-oprM multidrug efflux operon of Pseudomonas aeruginosa. PCP's induction of PA3720-armR resulted from its direct modulation of NalC, the repressor's binding to PA3720-armR promoter-containing DNA as seen in electromobility shift assays (EMSAs) being obviated in the presence of this agent. The NalC binding site was localized to an inverted repeat (IR) sequence upstream of PA3720-armR and overlapping a promoter region whose transcription start site was mapped. While modulation of MexR by the ArmR anti-repressor explains the upregulation of mexAB-oprM in nalC mutants hyperexpressing PA3720-armR, the induction of mexAB-oprM expression by PCP is not wholly explainable by PCP induction of PA3720-armR and subsequent ArmR modulation of MexR, inasmuch as armR deletion mutants still showed PCP-inducible mexAB-oprM expression. PCP failed, however, to induce mexAB-oprM in a mexR deletion strain, indicating that MexR was required for this, although PCP did not modulate MexR binding to mexAB-oprM promoter-containing DNA in vitro. One possibility is that MexR responds to PCP-generated in vivo effector molecules in controlling mexAB-oprM expression in response to PCP. PCP is an unlikely effector and substrate for NalC and MexAB-OprM - its impact on NalC binding to the PA3720-armR promoter DNA occurred only at high µM levels - suggesting that it mimics an intended phenolic effector/substrate(s). In this regard, plants are an abundant source of phenolic antimicrobial compounds and, so, MexAB-OprM may function to protect P. aeruginosa from plant antimicrobials that it encounters in nature

Haplotype association analyses in resources of mixed structure using Monte Carlo testing

<p>Abstract</p> <p>Background</p> <p>Genomewide association studies have resulted in a great many genomic regions that are likely to harbor disease genes. Thorough interrogation of these specific regions is the logical next step, including regional haplotype studies to identify risk haplotypes upon which the underlying critical variants lie. Pedigrees ascertained for disease can be powerful for genetic analysis due to the cases being enriched for genetic disease. Here we present a Monte Carlo based method to perform haplotype association analysis. Our method, hapMC, allows for the analysis of full-length and sub-haplotypes, including imputation of missing data, in resources of nuclear families, general pedigrees, case-control data or mixtures thereof. Both traditional association statistics and transmission/disequilibrium statistics can be performed. The method includes a phasing algorithm that can be used in large pedigrees and optional use of pseudocontrols.</p> <p>Results</p> <p>Our new phasing algorithm substantially outperformed the standard expectation-maximization algorithm that is ignorant of pedigree structure, and hence is preferable for resources that include pedigree structure. Through simulation we show that our Monte Carlo procedure maintains the correct type 1 error rates for all resource types. Power comparisons suggest that transmission-disequilibrium statistics are superior for performing association in resources of only nuclear families. For mixed structure resources, however, the newly implemented pseudocontrol approach appears to be the best choice. Results also indicated the value of large high-risk pedigrees for association analysis, which, in the simulations considered, were comparable in power to case-control resources of the same sample size.</p> <p>Conclusions</p> <p>We propose hapMC as a valuable new tool to perform haplotype association analyses, particularly for resources of mixed structure. The availability of meta-association and haplotype-mining modules in our suite of Monte Carlo haplotype procedures adds further value to the approach.</p

Effects of mental health self-efficacy on outcomes of a mobile phone and web intervention for mild-to-moderate depression, anxiety and stress: secondary analysis of a randomised controlled trial.

Background: Online psychotherapy is clinically effective yet why, how, and for whom the effects are greatest remain largely unknown. In the present study, we examined whether mental health self-efficacy (MHSE), a construct derived from Bandura’s Social Learning Theory (SLT), influenced symptom and functional outcomes of a new mobile phone and web-based psychotherapy intervention for people with mild-to-moderate depression, anxiety and stress. Methods: STUDY I: Data from 49 people with symptoms of depression, anxiety and/or stress in the mild-to-moderate range were used to examine the reliability and construct validity of a new measure of MHSE, the Mental Health Self-efficacy Scale (MHSES). STUDY II: We conducted a secondary analysis of data from a recently completed randomised controlled trial (N = 720) to evaluate whether MHSE effected post-intervention outcomes, as measured by the Depression, Anxiety and Stress Scales (DASS) and Work and Social Adjustment Scale (WSAS), for people with symptoms in the mild-to-moderate range. Results: STUDY I: The data established that the MHSES comprised a unitary factor, with acceptable internal reliability (Cronbach’s alpha = .89) and construct validity. STUDY II: The intervention group showed significantly greater improvement in MHSE at post-intervention relative to the control conditions (p’s < = .000). MHSE mediated the effects of the intervention on anxiety and stress symptoms. Furthermore, people with low pre-treatment MHSE reported the greatest post-intervention gains in depression, anxiety and overall distress. No effects were found for MHSE on work and social functioning. Conclusion: Mental health self-efficacy influences symptom outcomes of a self-guided mobile phone and web-based psychotherapeutic intervention and may itself be a worthwhile target to increase the effectiveness and efficiency of online treatment programs

Achievement motives and emotional processes in children during problem-solving: Two experimental studies of their relation to performance in different achievement goal conditions

In two studies, the influence of key emotional and motivational factors on performance in different achievement goal-type situations is examined. In study 1, based on 314 sixth-graders, two types of goal situations were induced; performance and mastery. The goals were examined with respect to important antecedents (e.g., motive dispositions) and several consequences (e.g., performance, satisfaction, pleasant affect, worry, and emotionality). The results showed that the motive to achieve success (Ms) produced positive affects, satisfaction, and increased performance, whereas the motive to avoid failure (Mf) produced worries and performance reduction. In study 2, based on 331 sixth-graders, three types of goal situations were induced; performance–approach, performance–avoidance, and mastery goals. The findings revealed that the most important single factors positively related to performance were Ms and mastery–goal situation. In addition, high Ms pupils performed better under mastery condition than under performance condition. Finally, avoidance-goal situation accentuate the negative effects of high Mf on performance

Genetic linkage analysis in the age of whole-genome sequencing

For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of genome-wide association studies (GWASs). However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches. Here, we review the principles of linkage analysis and provide practical guidelines for carrying out linkage studies using WGS data

Linkage study of fibrinogen levels: the Strong Heart Family Study

<p>Abstract</p> <p>Background</p> <p>The pathogenesis of atherosclerosis involves both hemostatic and inflammatory mechanisms. Fibrinogen is associated with both risk of thrombosis and inflammation. A recent meta-analysis showed that risk of coronary heart disease may increase 1.8 fold for 1 g/L of increased fibrinogen, independent of traditional risk factors. It is known that fibrinogen levels may be influenced by demographic, environmental and genetic factors. Epidemiologic and candidate gene studies are available; but few genome-wide linkage studies have been conducted, particularly in minority populations. The Strong Heart Study has demonstrated an increased incidence of cardiovascular disease in the American Indian population, and therefore represents an important source for genetic-epidemiological investigations.</p> <p>Methods</p> <p>The Strong Heart Family Study enrolled over 3,600 American Indian participants in large, multi-generational families, ascertained from an ongoing population-based study in the same communities. Fibrinogen was determined using standard technique in a central laboratory and extensive additional phenotypic measures were obtained. Participants were genotyped for 382 short tandem repeat markers distributed throughout the genome; and results were analyzed using a variance decomposition method, as implemented in the SOLAR 2.0 program.</p> <p>Results</p> <p>Data from 3535 participants were included and after step-wise, linear regression analysis, two models were selected for investigation. Basic demographic adjustments constituted model 1, while model 2 considered waist circumference, diabetes mellitus and postmenopausal status as additional covariates. Five LOD scores between 1.82 and 3.02 were identified, with the maximally adjusted model showing the highest score on chromosome 7 at 28 cM. Genes for two key components of the inflammatory response, i.e. interleukin-6 and "signal transducer and activator of transcription 3" (<it>STAT3</it>), were identified within 2 and 8 Mb of this 1 LOD drop interval respectively. A LOD score of 1.82 on chromosome 17 between 68 and 93 cM is supported by reports from two other populations with LOD scores of 1.4 and 1.95.</p> <p>Conclusion</p> <p>In a minority population with a high prevalence of cardiovascular disease, strong evidence for a novel genetic determinant of fibrinogen levels is found on chromosome 7 at 28 cM. Four other loci, some of which have been suggested by previous studies, were also identified.</p

Astrocyte-Derived Tissue Transglutaminase Interacts with Fibronectin: A Role in Astrocyte Adhesion and Migration?

An important neuropathological feature of neuroinflammatory processes that occur during e.g. Multiple Sclerosis (MS) is the formation of an astroglial scar. Astroglial scar formation is facilitated by the interaction between astrocytes and extracellular matrix proteins (ECM) such as fibronectin. Since there is evidence indicating that glial scars strongly inhibit both axon growth and (re)myelination in brain lesions, it is important to understand the factors that contribute to the interaction between astrocytes and ECM proteins. Tissue Transglutaminase (TG2) is a multifunctional enzyme with an ubiquitous tissue distribution, being clearly present within the brain. It has been shown that inflammatory cytokines can enhance TG2 activity. In addition, TG2 can mediate cell adhesion and migration and it binds fibronectin with high affinity. We therefore hypothesized that TG2 is involved in astrocyte-fibronectin interactions. Our studies using primary rat astrocytes show that intracellular and cell surface expression and activity of TG2 is increased after treatment with pro-inflammatory cytokines. Astrocyte-derived TG2 interacts with fibronectin and is involved in astrocyte adhesion onto and migration across fibronectin. TG2 is involved in stimulating focal adhesion formation which is necessary for the interaction of astrocytes with ECM proteins. We conclude that astrocyte-derived TG2 contributes to the interaction between astrocytes and fibronectin. It might thereby regulate ECM remodeling and possibly glial scarring