Seasonal Stability Tests in gretl. An Application to International Tourism Data

The seasonal stability tests of Canova & Hansen (1995) (CH) provide a method complementary to that of Hylleberg et al. (1990) for testing for seasonal unit roots. But the distribution of the CH tests are unknown in small samples. We present a method to numerically compute critical values and P-values for the CH tests for any sample size and any seasonal periodicity. In fact this method is applicable to the types of seasonality which are commonly in use, but also to any other.

A colorectal cancer genome-wide association study in a Spanish cohort identifies two variants associated with colorectal cancer risk at 1p33 and 8p12

Background: Colorectal cancer (CRC) is a disease of complex aetiology, with much of the expected inherited risk being due to several common low risk variants. Genome-Wide Association Studies (GWAS) have identified 20 CRC risk variants. Nevertheless, these have only been able to explain part of the missing heritability. Moreover, these signals have only been inspected in populations of Northern European origin. Results: Thus, we followed the same approach in a Spanish cohort of 881 cases and 667 controls. Sixty-four variants at 24 loci were found to be associated with CRC at p-values <10-5. We therefore evaluated the 24 loci in another Spanish replication cohort (1481 cases and 1850 controls). Two of these SNPs, rs12080929 at 1p33 (P-replication=0.042; P-pooled=5.523x10(-03); OR (CI95%)=0.866(0.782-0.959)) and rs11987193 at 8p12 (P-replication=0.039; P-pooled=6.985x10(-5); OR (CI95%)=0.786(0.705-0.878)) were replicated in the second Phase, although they did not reach genome-wide statistical significance. Conclusions: We have performed the first CRC GWAS in a Southern European population and by these means we were able to identify two new susceptibility variants at 1p33 and 8p12 loci. These two SNPs are located near the SLC5A9 and DUSP4 loci, respectively, which could be good functional candidates for the association signals. We therefore believe that these two markers constitute good candidates for CRC susceptibility loci and should be further evaluated in other larger datasets. Moreover, we highlight that were these two SNPs true susceptibility variants, they would constitute a decrease in the CRC missing heritability fraction.

Altered expression of Alzheimer's disease-related genes in the cerebellum of autistic patients: a model for disrupted brain connectome and therapy

Autism and Alzheimer's disease (AD) are, respectively, neurodevelopmental and degenerative diseases with an increasing epidemiological burden. The AD-associated amyloid-beta precursor protein-alpha has been shown to be elevated in severe autism, leading to the 'anabolic hypothesis' of its etiology. Here we performed a focused microarray analysis of genes belonging to NOTCH and WNT signaling cascades, as well as genes related to AD and apoptosis pathways in cerebellar samples from autistic individuals, to provide further evidence for pathological relevance of these cascades for autism. By using the limma package from R and false discovery rate, we demonstrated that 31% (116 out of 374) of the genes belonging to these pathways displayed significant changes in expression (corrected P-values <0.05), with mitochondria- related genes being the most downregulated. We also found upregulation of GRIN1, the channel-forming subunit of NMDA glutamate receptors, and MAP3K1, known activator of the JNK and ERK pathways with anti-apoptotic effect. Expression of PSEN2 (presinilin 2) and APBB1 (or F65) were significantly lower when compared with control samples. Based on these results, we propose a model of NMDA glutamate receptor-mediated ERK activation of alpha-secretase activity and mitochondrial adaptation to apoptosis that may explain the early brain overgrowth and disruption of synaptic plasticity and connectome in autism. Finally, systems pharmacology analyses of the model that integrates all these genes together (NOWADA) highlighted magnesium (Mg2+) and rapamycin as most efficient drugs to target this network model in silico. Their potential therapeutic application, in the context of autism, is therefore discussed.

Avances en algoritmos de estimación de distribuciones. Alternativas en el aprendizaje y representación de problemas

131 p.: graf.

Contributions to learning Bayesian network models from weakly supervised data: Application to Assisted Reproductive Technologies and Software Defect Classification

162 p.