The influenza pandemic preparedness planning tool InfluSim

BACKGROUND: Planning public health responses against pandemic influenza relies on predictive models by which the impact of different intervention strategies can be evaluated. Research has to date rather focused on producing predictions for certain localities or under specific conditions, than on designing a publicly available planning tool which can be applied by public health administrations. Here, we provide such a tool which is reproducible by an explicitly formulated structure and designed to operate with an optimal combination of the competing requirements of precision, realism and generality. RESULTS: InfluSim is a deterministic compartment model based on a system of over 1,000 differential equations which extend the classic SEIR model by clinical and demographic parameters relevant for pandemic preparedness planning. It allows for producing time courses and cumulative numbers of influenza cases, outpatient visits, applied antiviral treatment doses, hospitalizations, deaths and work days lost due to sickness, all of which may be associated with economic aspects. The software is programmed in Java, operates platform independent and can be executed on regular desktop computers. CONCLUSION: InfluSim is an online available software which efficiently assists public health planners in designing optimal interventions against pandemic influenza. It can reproduce the infection dynamics of pandemic influenza like complex computer simulations while offering at the same time reproducibility, higher computational performance and better operability

Power analysis for genome-wide association studies

Abstract Background Genome-wide association studies are a promising new tool for deciphering the genetics of complex diseases. To choose the proper sample size and genotyping platform for such studies, power calculations that take into account genetic model, tag SNP selection, and the population of interest are required. Results The power of genome-wide association studies can be computed using a set of tag SNPs and a large number of genotyped SNPs in a representative population, such as available through the HapMap project. As expected, power increases with increasing sample size and effect size. Power also depends on the tag SNPs selected. In some cases, more power is obtained by genotyping more individuals at fewer SNPs than fewer individuals at more SNPs. Conclusion Genome-wide association studies should be designed thoughtfully, with the choice of genotyping platform and sample size being determined from careful power calculations.</p

Testing an Emerging Paradigm in Migration Ecology Shows Surprising Differences in Efficiency between Flight Modes

To maximize fitness, flying animals should maximize flight speed while minimizing energetic expenditure. Soaring speeds of large-bodied birds are determined by flight routes and tradeoffs between minimizing time and energetic costs. Large raptors migrating in eastern North America predominantly glide between thermals that provide lift or soar along slopes or ridgelines using orographic lift (slope soaring). It is usually assumed that slope soaring is faster than thermal gliding because forward progress is constant compared to interrupted progress when birds pause to regain altitude in thermals. We tested this slope-soaring hypothesis using high-frequency GPS-GSM telemetry devices to track golden eagles during northbound migration. In contrast to expectations, flight speed was slower when slope soaring and eagles also were diverted from their migratory path, incurring possible energetic costs and reducing speed of progress towards a migratory endpoint. When gliding between thermals, eagles stayed on track and fast gliding speeds compensated for lack of progress during thermal soaring. When thermals were not available, eagles minimized migration time, not energy, by choosing energetically expensive slope soaring instead of waiting for thermals to develop. Sites suited to slope soaring include ridges preferred for wind-energy generation, thus avian risk of collision with wind turbines is associated with evolutionary trade-offs required to maximize fitness of time-minimizing migratory raptors

A Genome-Wide Scan of Ashkenazi Jewish Crohn's Disease Suggests Novel Susceptibility Loci

Crohn's disease (CD) is a complex disorder resulting from the interaction of intestinal microbiota with the host immune system in genetically susceptible individuals. The largest meta-analysis of genome-wide association to date identified 71 CD–susceptibility loci in individuals of European ancestry. An important epidemiological feature of CD is that it is 2–4 times more prevalent among individuals of Ashkenazi Jewish (AJ) descent compared to non-Jewish Europeans (NJ). To explore genetic variation associated with CD in AJs, we conducted a genome-wide association study (GWAS) by combining raw genotype data across 10 AJ cohorts consisting of 907 cases and 2,345 controls in the discovery stage, followed up by a replication study in 971 cases and 2,124 controls. We confirmed genome-wide significant associations of 9 known CD loci in AJs and replicated 3 additional loci with strong signal (p<5×10−6). Novel signals detected among AJs were mapped to chromosomes 5q21.1 (rs7705924, combined p = 2×10−8; combined odds ratio OR = 1.48), 2p15 (rs6545946, p = 7×10−9; OR = 1.16), 8q21.11 (rs12677663, p = 2×10−8; OR = 1.15), 10q26.3 (rs10734105, p = 3×10−8; OR = 1.27), and 11q12.1 (rs11229030, p = 8×10−9; OR = 1.15), implicating biologically plausible candidate genes, including RPL7, CPAMD8, PRG2, and PRG3. In all, the 16 replicated and newly discovered loci, in addition to the three coding NOD2 variants, accounted for 11.2% of the total genetic variance for CD risk in the AJ population. This study demonstrates the complementary value of genetic studies in the Ashkenazim

Genome-Wide Interaction-Based Association Analysis Identified Multiple New Susceptibility Loci for Common Diseases

Genome-wide interaction-based association (GWIBA) analysis has the potential to identify novel susceptibility loci. These interaction effects could be missed with the prevailing approaches in genome-wide association studies (GWAS). However, no convincing loci have been discovered exclusively from GWIBA methods, and the intensive computation involved is a major barrier for application. Here, we developed a fast, multi-thread/parallel program named “pair-wise interaction-based association mapping” (PIAM) for exhaustive two-locus searches. With this program, we performed a complete GWIBA analysis on seven diseases with stringent control for false positives, and we validated the results for three of these diseases. We identified one pair-wise interaction between a previously identified locus, C1orf106, and one new locus, TEC, that was specific for Crohn's disease, with a Bonferroni corrected P<0.05 (P = 0.039). This interaction was replicated with a pair of proxy linked loci (P = 0.013) on an independent dataset. Five other interactions had corrected P<0.5. We identified the allelic effect of a locus close to SLC7A13 for coronary artery disease. This was replicated with a linked locus on an independent dataset (P = 1.09×10−7). Through a local validation analysis that evaluated association signals, rather than locus-based associations, we found that several other regions showed association/interaction signals with nominal P<0.05. In conclusion, this study demonstrated that the GWIBA approach was successful for identifying novel loci, and the results provide new insights into the genetic architecture of common diseases. In addition, our PIAM program was capable of handling very large GWAS datasets that are likely to be produced in the future

D1 Dopamine Receptor Signaling Is Modulated by the R7 RGS Protein EAT-16 and the R7 Binding Protein RSBP-1 in Caenoerhabditis elegans Motor Neurons

Dopamine signaling modulates voluntary movement and reward-driven behaviors by acting through G protein-coupled receptors in striatal neurons, and defects in dopamine signaling underlie Parkinson's disease and drug addiction. Despite the importance of understanding how dopamine modifies the activity of striatal neurons to control basal ganglia output, the molecular mechanisms that control dopamine signaling remain largely unclear. Dopamine signaling also controls locomotion behavior in Caenorhabditis elegans. To better understand how dopamine acts in the brain we performed a large-scale dsRNA interference screen in C. elegans for genes required for endogenous dopamine signaling and identified six genes (eat-16, rsbp-1, unc-43, flp-1, grk-1, and cat-1) required for dopamine-mediated behavior. We then used a combination of mutant analysis and cell-specific transgenic rescue experiments to investigate the functional interaction between the proteins encoded by two of these genes, eat-16 and rsbp-1, within single cell types and to examine their role in the modulation of dopamine receptor signaling. We found that EAT-16 and RSBP-1 act together to modulate dopamine signaling and that while they are coexpressed with both D1-like and D2-like dopamine receptors, they do not modulate D2 receptor signaling. Instead, EAT-16 and RSBP-1 act together to selectively inhibit D1 dopamine receptor signaling in cholinergic motor neurons to modulate locomotion behavior

Exclusion of a major role for the PTEN tumour-suppressor gene in breast carcinomas

PTEN is a novel tumour-suppressor gene located on chromosomal band 10q23.3. This region displays frequent loss of heterozygosity (LOH) in a variety of human neoplasms including breast carcinomas. The detection of PTEN mutations in Cowden disease and in breast carcinoma cell lines suggests that PTEN may be involved in mammary carcinogenesis. We here report a mutational analysis of tumour specimens from 103 primary breast carcinomas and constitutive DNA from 25 breast cancer families. The entire coding region of PTEN was screened by single-strand conformation polymorphism (SSCP) analysis and direct sequencing using intron-based primers. No germline mutations could be identified in the breast cancer families and only one sporadic carcinoma carried a PTEN mutation at one allele. In addition, all sporadic tumours were analysed for homozygous deletions by differential polymerase chain reaction (PCR) and for allelic loss using the microsatellite markers D10S215, D10S564 and D10S573. No homozygous deletions were detected and only 10 out of 94 informative tumours showed allelic loss in the PTEN region. These results suggest that PTEN does not play a major role in breast cancer formation. 1999 Cancer Research Campaig

VANG-1 and PRKL-1 Cooperate to Negatively Regulate Neurite Formation in Caenorhabditis elegans

Neuritogenesis is a critical early step in the development and maturation of neurons and neuronal circuits. While extracellular directional cues are known to specify the site and orientation of nascent neurite formation in vivo, little is known about the genetic pathways that block inappropriate neurite emergence in order to maintain proper neuronal polarity. Here we report that the Caenorhabditis elegans orthologues of Van Gogh (vang-1), Prickle (prkl-1), and Dishevelled (dsh-1), core components of planar cell polarity (PCP) signaling, are required in a subset of peripheral motor neurons to restrict neurite emergence to a specific organ axis. In loss-of-function mutants, neurons display supernumerary neurites that extend inappropriately along the orthogonal anteroposterior (A/P) body axis. We show that autonomous and non-autonomous gene activities are required early and persistently to inhibit the formation or consolidation of growth cone protrusions directed away from organ precursor cells. Furthermore, prkl-1 overexpression is sufficient to suppress neurite formation and reorient neuronal polarity in a vang-1– and dsh-1–dependent manner. Our findings suggest a novel role for a PCP–like pathway in maintaining polarized neuronal morphology by inhibiting neuronal responses to extrinsic or intrinsic cues that would otherwise promote extraneous neurite formation

Worldwide population differentiation at disease-associated SNPs

<p>Abstract</p> <p>Background</p> <p>Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).</p> <p>Methods</p> <p>We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.</p> <p>Results</p> <p>On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.</p> <p>Conclusion</p> <p>Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.</p