Novel Machado-Joseph disease-modifying genes and pathways identified by whole-exome sequencing

Machado-Joseph disease (MJD/SCA3) is a neurodegenerative polyglutamine disorder exhibiting a wide spectrum of phenotypes. The abnormal size of the (CAG)n at ATXN3 explains ~55% of the age at onset variance, suggesting the involvement of other factors, namely genetic modifiers, whose identification remains limited. Our aim was to find novel genetic modifiers, analyse their epistatic effects and identify disease-modifying pathways contributing to MJD variable expressivity. We performed whole-exome sequencing in a discovery sample of four age at onset-concordant and four discordant first-degree relative pairs of Azorean patients, to identify candidate variants which genotypes differed for each discordant pair but were shared in each concordant pair. Variants identified by this approach were then tested in an independent multi-origin cohort of 282 MJD patients. Whole-exome sequencing identified 233 candidate variants, from which 82 variants in 53 genes were prioritized for downstream analysis. Eighteen disease-modifying pathways were identified; two of the most enriched pathways were relevant for the nervous system, namely the neuregulin signaling and the agrin interactions at neuromuscular junction. Variants at PARD3, NFKB1, CHD5, ACTG1, CFAP57, DLGAP2, ITGB1, DIDO1 and CERS4 modulate age at onset in MJD, with those identified in CFAP57, ACTG1 and DIDO1 showing consistent effects across cohorts of different geographical origins. Network analyses of the nine novel MJD modifiers highlighted several important molecular interactions, including genes/proteins previously related with MJD pathogenesis, namely between ACTG1/APOE and VCP/ITGB1. We describe novel pathways, modifiers, and their interaction partners, providing a broad molecular portrait of age at onset modulation to be further exploited as new disease-modifying targets for MJD and related diseases

How citation boosts promote scientific paradigm shifts and Nobel Prizes

Nobel Prizes are commonly seen to be among the most prestigious achievements of our times. Based on mining several million citations, we quantitatively analyze the processes driving paradigm shifts in science. We find that groundbreaking discoveries of Nobel Prize Laureates and other famous scientists are not only acknowledged by many citations of their landmark papers. Surprisingly, they also boost the citation rates of their previous publications. Given that innovations must outcompete the rich-gets-richer effect for scientific citations, it turns out that they can make their way only through citation cascades. A quantitative analysis reveals how and why they happen. Science appears to behave like a self-organized critical system, in which citation cascades of all sizes occur, from continuous scientific progress all the way up to scientific revolutions, which change the way we see our world. Measuring the "boosting effect" of landmark papers, our analysis reveals how new ideas and new players can make their way and finally triumph in a world dominated by established paradigms. The underlying "boost factor" is also useful to discover scientific breakthroughs and talents much earlier than through classical citation analysis, which by now has become a widespread method to measure scientific excellence, influencing scientific careers and the distribution of research funds. Our findings reveal patterns of collective social behavior, which are also interesting from an attention economics perspective. Understanding the origin of scientific authority may therefore ultimately help to explain, how social influence comes about and why the value of goods depends so strongly on the attention they attract.Comment: 6 pages, 6 figure

Peer mentorship to promote effective pain management in adolescents: study protocol for a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>This protocol is for a study of a new program to improve outcomes in children suffering from chronic pain disorders, such as fibromyalgia, recurrent headache, or recurrent abdominal pain. Although teaching active pain self-management skills through cognitive-behavioral therapy (CBT) or a complementary program such as hypnotherapy or yoga has been shown to improve pain and functioning, children with low expectations of skill-building programs may lack motivation to comply with therapists' recommendations. This study will develop and test a new manualized peer-mentorship program which will provide modeling and reinforcement by peers to other adolescents with chronic pain (the mentored participants). The mentorship program will encourage mentored participants to engage in therapies that promote the learning of pain self-management skills and to support the mentored participants' practice of these skills. The study will examine the feasibility of this intervention for both mentors and mentored participants, and will assess the preliminary effectiveness of this program on mentored participants' pain and functional disability.</p> <p>Methods</p> <p>This protocol will recruit adolescents ages 12-17 with chronic pain and randomly assign them to either peer mentorship or a treatment-as-usual control group. Mentored participants will be matched with peer mentors of similar age (ages 14-18) who have actively participated in various treatment modalities through the UCLA Pediatric Pain Program and have learned to function successfully with a chronic pain disorder. The mentors will present information to mentored participants in a supervised and monitored telephone interaction for 2 months to encourage participation in skill-building programs. The control group will receive usual care but without the mentorship intervention. Mentored and control subjects' pain and functioning will be assessed at 2 months (end of intervention for mentored participants) and at 4 month follow-up to see if improvements persist. Measures of treatment adherence, pain, disability, and anxiety and depression will be assessed throughout study participation. Qualitative interviews for mentors, mentored participants, and control subjects will also be administered.</p> <p>Trial registration</p> <p>ClinicalTrials.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT01118988">NCT01118988</a>.</p

Epistatic interaction of ERAP1 and HLA-B in Behçet disease: a replication study in the Spanish population

Behçet's disease (BD) is a multifactorial disorder associated with the HLA region. Recently, the ERAP1 gene has been proposed as a susceptibility locus with a recessive model and with epistatic interaction with HLA-B51. ERAP1 trims peptides in the endoplasmic reticulum to optimize their length for MHC-I binding. Polymorphisms in this gene have been related with the susceptibility to other immune-mediated diseases associated to HLA class I. Our aim was, the replication in the Spanish population of the association described in the Turkish population between ERAP1 (rs17482078) and BD. Additionally, in order to improve the understanding of this association we analyzed four additional SNPs (rs27044, rs10050860, rs30187 and rs2287987) associated with other diseases related to HLA class I and the haplotype blocks in this gene region. According to our results, frequencies of the homozygous genotypes for the minor alleles of all the SNPs were increased among patients and the OR values were higher in the subgroup of patients with the HLA-B risk factors, although differences were not statistically significant. Moreover, the presence of the same mutation in both chromosomes increased the OR values from 4.51 to 10.72 in individuals carrying the HLA-B risk factors. Therefore, although they were not statistically significant, our data were consistent with an association between ERAP1 and BD as well as with an epistatic interaction between ERAP1 and HLA-B in the Spanish population

Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci

<p>Abstract</p> <p>Background</p> <p>Genes of the Major Histocompatibility Complex (MHC) are very popular genetic markers among evolutionary biologists because of their potential role in pathogen confrontation and sexual selection. However, MHC genotyping still remains challenging and time-consuming in spite of substantial methodological advances. Although computational haplotype inference has brought into focus interesting alternatives, high heterozygosity, extensive genetic variation and population admixture are known to cause inaccuracies. We have investigated the role of sample size, genetic polymorphism and genetic structuring on the performance of the popular Bayesian PHASE algorithm. To cover this aim, we took advantage of a large database of known genotypes (using traditional laboratory-based techniques) at single MHC class I (N = 56 individuals and 50 alleles) and MHC class II B (N = 103 individuals and 62 alleles) loci in the lesser kestrel <it>Falco naumanni</it>.</p> <p>Findings</p> <p>Analyses carried out over real MHC genotypes showed that the accuracy of gametic phase reconstruction improved with sample size as a result of the reduction in the allele to individual ratio. We then simulated different data sets introducing variations in this parameter to define an optimal ratio.</p> <p>Conclusions</p> <p>Our results demonstrate a critical influence of the allele to individual ratio on PHASE performance. We found that a minimum allele to individual ratio (1:2) yielded 100% accuracy for both MHC loci. Sampling effort is therefore a crucial step to obtain reliable MHC haplotype reconstructions and must be accomplished accordingly to the degree of MHC polymorphism. We expect our findings provide a foothold into the design of straightforward and cost-effective genotyping strategies of those MHC loci from which locus-specific primers are available.</p

Damage and protection cost curves for coastal floods within the 600 largest European cities

The economic assessment of the impacts of storm surges and sea-level rise in coastal cities requires high-level information on the damage and protection costs associated with varying flood heights. We provide a systematically and consistently calculated dataset of macroscale damage and protection cost curves for the 600 largest European coastal cities opening the perspective for a wide range of applications. Offering the first comprehensive dataset to include the costs of dike protection, we provide the underpinning information to run comparative assessments of costs and benefits of coastal adaptation. Aggregate cost curves for coastal flooding at the city-level are commonly regarded as by-products of impact assessments and are generally not published as a standalone dataset. Hence, our work also aims at initiating a more critical discussion on the availability and derivation of cost curves