Neither Replication nor Simulation Supports a Role for the Axon Guidance Pathway in the Genetics of Parkinson's Disease

Susceptibility to sporadic Parkinson's disease (PD) is thought to be influenced by both genetic and environmental factors and their interaction with each other. Statistical models including multiple variants in axon guidance pathway genes have recently been purported to be capable of predicting PD risk, survival free of the disease and age at disease onset; however the specific models have not undergone independent validation. Here we tested the best proposed risk panel of 23 single nucleotide polymorphisms (SNPs) in two PD sample sets, with a total of 525 cases and 518 controls. By single marker analysis, only one marker was significantly associated with PD risk in one of our sample sets (rs6692804: P = 0.03). Multi-marker analysis using the reported model found a mild association in one sample set (two sided P = 0.049, odds ratio for each score change = 1.07) but no significance in the other (two sided P = 0.98, odds ratio = 1), a stark contrast to the reported strong association with PD risk (P = 4.64×10−38, odds ratio as high as 90.8). Following a procedure similar to that used to build the reported model, simulated multi-marker models containing SNPs from randomly chosen genes in a genome wide PD dataset produced P-values that were highly significant and indistinguishable from similar models where disease status was permuted (3.13×10−23 to 4.90×10−64), demonstrating the potential for overfitting in the model building process. Together, these results challenge the robustness of the reported panel of genetic markers to predict PD risk in particular and a role of the axon guidance pathway in PD genetics in general

A Large-Scale Rheumatoid Arthritis Genetic Study Identifies Association at Chromosome 9q33.2

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease affecting both joints and extra-articular tissues. Although some genetic risk factors for RA are well-established, most notably HLA-DRB1 and PTPN22, these markers do not fully account for the observed heritability. To identify additional susceptibility loci, we carried out a multi-tiered, case-control association study, genotyping 25,966 putative functional SNPs in 475 white North American RA patients and 475 matched controls. Significant markers were genotyped in two additional, independent, white case-control sample sets (661 cases/1322 controls from North America and 596 cases/705 controls from The Netherlands) identifying a SNP, rs1953126, on chromosome 9q33.2 that was significantly associated with RA (ORcommon = 1.28, trend Pcomb = 1.45E-06). Through a comprehensive fine-scale-mapping SNP-selection procedure, 137 additional SNPs in a 668 kb region from MEGF9 to STOM on 9q33.2 were chosen for follow-up genotyping in a staged-approach. Significant single marker results (Pcomb<0.01) spanned a large 525 kb region from FBXW2 to GSN. However, a variety of analyses identified SNPs in a 70 kb region extending from the third intron of PHF19 across TRAF1 into the TRAF1-C5 intergenic region, but excluding the C5 coding region, as the most interesting (trend Pcomb: 1.45E-06 → 5.41E-09). The observed association patterns for these SNPs had heightened statistical significance and a higher degree of consistency across sample sets. In addition, the allele frequencies for these SNPs displayed reduced variability between control groups when compared to other SNPs. Lastly, in combination with the other two known genetic risk factors, HLA-DRB1 and PTPN22, the variants reported here generate more than a 45-fold RA-risk differential

A new tool called DISSECT for analyzing large genomic datasets using a Big Data approach

Large-scale genetic and genomic data are increasingly available and the major bottleneck in their analysis is a lack of sufficiently scalable computational tools. To address this problem in the context of complex traits analysis, we present DISSECT. DISSECT is a new and freely available software that is able to exploit the distributed-memory parallel computational architectures of compute clusters, to perform a wide range of genomic and epidemiologic analyses, which currently can only be carried out on reduced sample sizes or under restricted conditions. We demonstrate the usefulness of our new tool by addressing the challenge of predicting phenotypes from genotype data in human populations using mixed-linear model analysis. We analyse simulated traits from 470,000 individuals genotyped for 590,004 SNPs in ∼4 h using the combined computational power of 8,400 processor cores. We find that prediction accuracies in excess of 80% of the theoretical maximum could be achieved with large sample sizes

Genome-wide scan reveals association of psoriasis with IL-23 and NF-κB pathways

Psoriasis is a common immune-mediated disorder that affects the skin, nails and joints. To identify psoriasis susceptibility loci, we genotyped 438,670 SNPs in 1,409 psoriasis cases and 1,436 controls of European ancestry. We followed up 21 promising SNPs in 5,048 psoriasis cases and 5,041 controls. Our results provide strong support for the association of at least seven genetic loci and psoriasis (each with combined P less than 5 × 10−8). Loci with confirmed association include HLA-C, three genes involved in IL-23 signaling (IL23A, IL23R, IL12B), two genes that act downstream of TNF-α and regulate NF-κB signaling (TNIP1, TNFAIP3) and two genes involved in the modulation of Th2 immune responses (IL4, IL13). Although the proteins encoded in these loci are known to interact biologically, we found no evidence for epistasis between associated SNPs. Our results expand the catalog of genetic loci implicated in psoriasis susceptibility and suggest priority targets for study in other auto-immune disorders

Improving the resilience in IP networks

Quality of service issues of IP networks are mostly related to guaranteeing bandwidth for flows. However, many interactive real-time applications also require this bandwidth in an uninterrupted fashion. The paper describes how multipath routing and local failure reaction can be employed to provide uninterrupted QoS to applications. We show how multipath route sets can be found in reasonably meshed networks and how multipath routing can be used to save on the spare capacity required in case of link failures

Association of ABCA1 with late-onset Alzheimer's disease is not observed in a case-control study

Genetic association of ABCA1 or the ATP-binding cassette A1 transporter with late-onset Alzheimer's disease (LOAD) has recently been proposed for a haplotype comprised of three single nucleotide polymorphisms (SNPs). We have genotyped these and other ABCA1 SNPs in a LOAD case-control series of 796 individuals (419 cases versus 377 controls) collected at Washington University. While our sample series is larger and thus presumably has greater power than any of the series used to implicate ABCA1, we were unable to replicate the published association, using either single markers or multiple marker haplotypes. Further, we did not observe significant and replicated association of other ABCA1 SNPs we examined with the disease, thus these ABCA1 variants do not appear to influence the risk of LOAD in this study