Methylation alterations are not a major cause of PTTG1 missregulation

Background: On its physiological cellular context, PTTG1 controls sister chromatid segregation during mitosis. Within its crosstalk to the cellular arrest machinery, relies a checkpoint of integrity for which gained the over name of securin. PTTG1 was found to promote malignant transformation in 3T3 fibroblasts, and further found to be overexpressed in different tumor types. More recently, PTTG1 has been also related to different processes such as DNA repair and found to trans-activate different cellular pathways involving c-myc, bax or p53, among others. PTTG1 over-expression has been correlated to a worse prognosis in thyroid, lung, colorectal cancer patients, and it can not be excluded that this effect may also occur in other tumor types. Despite the clinical relevance and the increasing molecular characterization of PTTG1, the reason for its up-regulation remains unclear. Method: We analysed PTTG1 differential expression in PC-3, DU-145 and LNCaP tumor cell lines, cultured in the presence of the methyl-transferase inhibitor 5-Aza-2'-deoxycytidine. We also tested whether the CpG island mapping PTTG1 proximal promoter evidenced a differential methylation pattern in differentiated thyroid cancer biopsies concordant to their PTTG1 immunohistochemistry status. Finally, we performed whole-genome LOH studies using Affymetix 50 K microarray technology and FRET analysis to search for allelic imbalances comprising the PTTG1 locus. Conclusion: Our data suggest that neither methylation alterations nor LOH are involved in PTTG1 over-expression. These data, together with those previously reported, point towards a post-transcriptional level of missregulation associated to PTTG1 over-expression.This project was funded by The Fundación de Investigación Biomédica Mutua Madrileña Automovilista. Neocodex have been partially funded by the Ministerio de Educación y Ciencia of Spain (FIT-010000-2004-69, PTQ04-1-0006, PTQ2003-0549, PTQ2003-0546 and PTQ2003-0783). MAJ was also supported by SAF2005- 07713-C03-03 and CS by FIS 06/757

A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis

<p>Abstract</p> <p>Background</p> <p>The difficulty in elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Some of these genetic effects may interact in complex ways, proving undetectable by current single-locus methodology.</p> <p>Results</p> <p>We have developed an analysis tool called Hypothesis Free Clinical Cloning (HFCC) to search for genome-wide epistasis in a case-control design. HFCC combines a relatively fast computing algorithm for genome-wide epistasis detection, with the flexibility to test a variety of different epistatic models in multi-locus combinations. HFCC has good power to detect multi-locus interactions simulated under a variety of genetic models and noise conditions. Most importantly, HFCC can accomplish exhaustive genome-wide epistasis search with large datasets as demonstrated with a 400,000 SNP set typed on a cohort of Parkinson's disease patients and controls.</p> <p>Conclusion</p> <p>With the current availability of genetic studies with large numbers of individuals and genetic markers, HFCC can have a great impact in the identification of epistatic effects that escape the standard single-locus association analyses.</p

A novel Alzheimer disease locus located near the gene encoding tau protein

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordAPOE ε4, the most significant genetic risk factor for Alzheimer disease (AD), may mask effects of other loci. We re-analyzed genome-wide association study (GWAS) data from the International Genomics of Alzheimer's Project (IGAP) Consortium in APOE ε4+ (10 352 cases and 9207 controls) and APOE ε4- (7184 cases and 26 968 controls) subgroups as well as in the total sample testing for interaction between a single-nucleotide polymorphism (SNP) and APOE ε4 status. Suggestive associations (P<1 × 10-4) in stage 1 were evaluated in an independent sample (stage 2) containing 4203 subjects (APOE ε4+: 1250 cases and 536 controls; APOE ε4-: 718 cases and 1699 controls). Among APOE ε4- subjects, novel genome-wide significant (GWS) association was observed with 17 SNPs (all between KANSL1 and LRRC37A on chromosome 17 near MAPT) in a meta-analysis of the stage 1 and stage 2 data sets (best SNP, rs2732703, P=5·8 × 10-9). Conditional analysis revealed that rs2732703 accounted for association signals in the entire 100-kilobase region that includes MAPT. Except for previously identified AD loci showing stronger association in APOE ε4+ subjects (CR1 and CLU) or APOE ε4- subjects (MS4A6A/MS4A4A/MS4A6E), no other SNPs were significantly associated with AD in a specific APOE genotype subgroup. In addition, the finding in the stage 1 sample that AD risk is significantly influenced by the interaction of APOE with rs1595014 in TMEM106B (P=1·6 × 10-7) is noteworthy, because TMEM106B variants have previously been associated with risk of frontotemporal dementia. Expression quantitative trait locus analysis revealed that rs113986870, one of the GWS SNPs near rs2732703, is significantly associated with four KANSL1 probes that target transcription of the first translated exon and an untranslated exon in hippocampus (P≤1.3 × 10-8), frontal cortex (P≤1.3 × 10-9) and temporal cortex (P≤1.2 × 10-11). Rs113986870 is also strongly associated with a MAPT probe that targets transcription of alternatively spliced exon 3 in frontal cortex (P=9.2 × 10-6) and temporal cortex (P=2.6 × 10-6). Our APOE-stratified GWAS is the first to show GWS association for AD with SNPs in the chromosome 17q21.31 region. Replication of this finding in independent samples is needed to verify that SNPs in this region have significantly stronger effects on AD risk in persons lacking APOE ε4 compared with persons carrying this allele, and if this is found to hold, further examination of this region and studies aimed at deciphering the mechanism(s) are warranted

Methylation alterations are not a major cause of PTTG1 missregulation

Background: On its physiological cellular context, PTTG1 controls sister chromatid segregation during mitosis. Within its crosstalk to the cellular arrest machinery, relies a checkpoint of integrity for which gained the over name of securin. PTTG1 was found to promote malignant transformation in 3T3 fibroblasts, and further found to be overexpressed in different tumor types. More recently, PTTG1 has been also related to different processes such as DNA repair and found to trans-activate different cellular pathways involving c-myc, bax or p53, among others. PTTG1 over-expression has been correlated to a worse prognosis in thyroid, lung, colorectal cancer patients, and it can not be excluded that this effect may also occur in other tumor types. Despite the clinical relevance and the increasing molecular characterization of PTTG1, the reason for its up-regulation remains unclear. Method: We analysed PTTG1 differential expression in PC-3, DU-145 and LNCaP tumor cell lines, cultured in the presence of the methyl-transferase inhibitor 5-Aza-2'-deoxycytidine. We also tested whether the CpG island mapping PTTG1 proximal promoter evidenced a differential methylation pattern in differentiated thyroid cancer biopsies concordant to their PTTG1 immunohistochemistry status. Finally, we performed whole-genome LOH studies using Affymetix 50 K microarray technology and FRET analysis to search for allelic imbalances comprising the PTTG1 locus. Conclusion: Our data suggest that neither methylation alterations nor LOH are involved in PTTG1 over-expression. These data, together with those previously reported, point towards a post-transcriptional level of missregulation associated to PTTG1 over-expression

A method for detecting epistasis in genome-wide studies using case-control multi-locus association analysis

Background: The difficulty in elucidating the genetic basis of complex diseases roots in the many factors that can affect the development of a disease. Some of these genetic effects may interact in complex ways, proving undetectable by current single-locus methodology. Results: We have developed an analysis tool called Hypothesis Free Clinical Cloning (HFCC) to search for genome-wide epistasis in a case-control design. HFCC combines a relatively fast computing algorithm for genome-wide epistasis detection, with the flexibility to test a variety of different epistatic models in multi-locus combinations. HFCC has good power to detect multi-locus interactions simulated under a variety of genetic models and noise conditions. Most importantly, HFCC can accomplish exhaustive genome-wide epistasis search with large datasets as demonstrated with a 400,000 SNP set typed on a cohort of Parkinson's disease patients and controls. Conclusion: With the current availability of genetic studies with large numbers of individuals and genetic markers, HFCC can have a great impact in the identification of epistatic effects that escape the standard single-locus association analyses

Genetic analysis of caveolin-1 and eNOS genes in colorectal cancer.

Journal Article; Research Support, Non-U.S. Gov't;Caveolae are involved in physical compartmentalization between different groups of signaling events. Its main component, CAV1, modulates different pathways in cellular physiology. The emerging evidence pointing to the role of CAV1 in cancer led us to study whether different alleles of this gene are associated with colorectal cancer (CRC). Since one of the most characterized enzymes regulated by CAV1 is eNOS, we decided to include both genes in this study. We analyzed five SNPs in 360 unrelated CRC patients and 550 controls from the general population. Two of these SNPs were located within eNOS and three within the CAV1 gene. Although haplotype distribution was not associated with CRC, haplotype TiA (CAV1) was associated with familiar forms of CRC (p<0.05). This was especially evident in CRC antecedents and nuclear forms of CRC. If both CG (eNOS) and TiA (CAV1) haplotypes were taken together, this association increased in significance. Thus, we propose that CAV1, either alone or together with eNOS alleles, might modify CRC heritability.This study was supported by Ministerio de Ciencia y Tecnologia (the Spanish Ministry of Science and Technology) PROFIT 010000-2004-69.Ye

Exploratory analysis of seven Alzheimer's disease genes: disease progression

The relationships between GWAS-identified and replicated genetic variants associated to Alzheimer’s disease (AD) risk and disease progression or therapeutic responses in AD patients are almost unexplored. 701 AD patients with at least three different cognitive evaluations and genotypic information for APOE and six GWAS-significant SNPs were selected for this study. Mean differences in GDS and MMSE were evaluated using non-parametric tests, GLM and mixed models for repeated measurements. Each chart was also reviewed for evidence of treatment with any cholinesterase inhibitor (AChEI), memantine or both. Relationships between therapeutic protocols, genetic markers and progression were explored using stratified analysis looking for specific effects on progression in each therapeutic category separately. Neither calculation rendered a Bonferroni-corrected statistically significant difference in any genetic marker. Mixed model results suggested differences in the average point in MMSE test for patients carrying PICALM GA or AA genotype compared to GG carriers at the end of the follow up (MMSE mean difference= −0.57 C.I.95%[−1.145−0.009], p=0.047). This observations remained unaltered after covariate adjustments although did not achieve predefined multiple testing significance threshold. PICALM SNP also displayed a significant effect protecting against rapid progression during pharmacogenetics assays although it observed effect displayed heterogeneity among AD therapeutic protocols (p=0.039). None of studied genetic markers was convincingly linked to AD progression or drug response. However, by using different statistical approaches, PICALM rs3851179 marker displayed consistent but weak effects on disease progression phenotypes