Molecular and behavioural abnormalities in the FUS‐tg mice mimic frontotemporal lobar degeneration: Effects of old and new anti‐inflammatory therapies

Genetic mutations in FUS, a DNA/RNA‐binding protein, are associated with inherited forms of frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). A novel transgenic FUS[1‐359]‐tg mouse line recapitulates core hallmarks of human ALS in the spinal cord, including neuroinflammation and neurodegeneration, ensuing muscle atrophy and paralysis, as well as brain pathomorphological signs of FTLD. However, a question whether FUS[1‐359]‐tg mouse displays behavioural and brain pro‐inflammatory changes characteristic for the FTLD syndrome was not addressed. Here, we studied emotional, social and cognitive behaviours, brain markers of inflammation and plasticity of pre‐symptomatic FUS[1‐359]‐tg male mice, a potential FTLD model. These animals displayed aberrant behaviours and altered brain expression of inflammatory markers and related pathways that are reminiscent to the FTLD‐like syndrome. FTLD‐related behavioural and molecular Journal of Cellular and Molecular Medicine features were studied in the pre‐symptomatic FUS[1‐359]‐tg mice that received standard or new ALS treatments, which have been reported to counteract the ALS‐like syndrome in the mutants. We used anti‐ALS drug riluzole (8 mg/kg/d), or anti‐inflammatory drug, a selective blocker of cyclooxygenase‐2 (celecoxib, 30 mg/kg/d) for 3 weeks, or a single intracerebroventricular (i.c.v.) infusion of human stem cells (Neuro‐Cells, 500 000‐CD34⁺), which showed anti‐inflammatory properties. Signs of elevated anxiety, depressive‐like behaviour, cognitive deficits and abnormal social behaviour were less marked in FUS‐tg–treated animals. Applied treatments have normalized protein expression of interleukin‐1β (IL‐1β) in the prefrontal cortex and the hippocampus, and of Iba‐1 and GSK‐3β in the hippocampus. Thus, the pre‐symptomatic FUS[1‐359]‐tg mice demonstrate FTLD‐like abnormalities that are attenuated by standard and new ALS treatments, including Neuro‐Cell preparation.     

Beyond comparing means: the usefulness of analyzing interindividual variation in gene expression for identifying genes associated with cancer development

Identifying genes associated with cancer development is typically accomplished by comparing mean expression values in normal and tumor tissues, which identifies differentially expressed (DE) genes. Interindividual variation (IV) in gene expression is indirectly included in DE gene identification because given the same absolute differences in means, genes with lower variance tend to have lower p-values. We explored the direct use of IV in gene expression to identify candidate genes associated with cancer development. We focused on prostate (PCa) and lung (LC) cancers and compared IV in the expression level of genes shown to be cancer related with that in all other genes in the human genome. Compared with all those other genes, cancer-related genes tended to have greater IV in normal tissues and a greater increase in IV during the transition from normal to tumorous tissue. Genes without significantly different mean expression values between tumor and normal tissues but with greater IV in tumor than in normal tissue (note: the DE-based approach completely ignores those genes) had stronger associations with clinically important features like Gleason score in PCa or tumor histology in LC than all other genes were. Our results suggest that analyzing IV in gene expression level is useful in identifying novel candidate genes associated with cancer development.     

Shifting paradigm of association studies: value of rare single-nucleotide polymorphisms

Currently, single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) of >5% are preferentially used in case-control association studies of common human diseases. Recent technological developments enable inexpensive and accurate genotyping of a large number of SNPs in thousands of cases and controls, which can provide adequate statistical power to analyze SNPs with MAF <5%. Our purpose was to determine whether evaluating rare SNPs in case-control association studies could help identify causal SNPs for common diseases. We suggest that slightly deleterious SNPs (sdSNPs) subjected to weak purifying selection are major players in genetic control of susceptibility to common diseases. We compared the distribution of MAFs of synonymous SNPs with that of nonsynonymous SNPs (1) predicted to be benign, (2) predicted to be possibly damaging, and (3) predicted to be probably damaging by PolyPhen. Our sources of data were the International HapMap Project, ENCODE, and the SeattleSNPs project. We found that the MAF distribution of possibly and probably damaging SNPs was shifted toward rare SNPs compared with the MAF distribution of benign and synonymous SNPs that are not likely to be functional. We also found an inverse relationship between MAF and the proportion of nsSNPs predicted to be protein disturbing. On the basis of this relationship, we estimated the joint probability that a SNP is functional and would be detected as significant in a case-control study. Our analysis suggests that including rare SNPs in genotyping platforms will advance identification of causal SNPs in case-control association studies, particularly as sample sizes increase.     

Derived SNP alleles are used more frequently than ancestral alleles as risk-associated variants in common human diseases

Evolutionary aspects of the genetic architecture of common human diseases remain enigmatic. The results of more than 200 genome-wide association studies published to date were compiled in a catalog (). We used cataloged data to determine whether derived (mutant) alleles are associated with higher risk of human disease more frequently than ancestral alleles. We placed all allelic variants into ten categories of population frequency (0%-100%) in 10% increments. We then analyzed the relationship between allelic frequency, evolutionary status of the polymorphic site (ancestral versus derived), and disease risk status (risk versus protection). Given the same population frequency, derived alleles are more likely to be risk associated than ancestral alleles, as are rarer alleles. The common interpretation of this association is that negative selection prevents fixation of the risk variants. However, disease stratification as early or late onset suggests that weak selection against risk-associated alleles is unlikely a major factor shaping genetic architecture of common diseases. Our results clearly suggest that the duration of existence of an allele in a population is more important. Alleles existing longer tend to show weaker linkage disequilibrium with neighboring alleles, including the causal alleles, and are less likely to tag a SNP-disease association.     

Variation in the relative length of chromosomes in mammalian karyotypes. Hypothesis of equalizing selection

A hypothesis on the selective neutrality of relative lengths of karyotype chromosomes was tested. Idiograms expected based on an assumption of selective neutrality of chromosome lengths were compared with actual idiograms in more than a hundred mammalian species. The observed idiograms differed from those expected in a similar manner: in the observed idiograms, the longest chromosomes were shorter, and the shortest were longer than expected. It is suggested that karyotype chromosome variation is limited by selection against chromosome rearrangements that produce very long or very short chromosomes. An analysis of reciprocal translocations in the mouse and Drosophila showed that translocations generating chromosomes of extreme lengths were more deleterious than those generating normal-sized chromosomes. A working hypothesis was advanced stating that within-karyotype variation of chromosome lengths is accounted for by two factors: chromosome rearrangements and natural selection. Chromosome rearrangements tend to randomize relative chromosome lengths in a karyotype, whereas natural selection acts to equalize them.     

Genetic susceptibility for lung cancer: interactions with gender and smoking history and impact on early detection policies

OBJECTIVES: To identify a subgroup of former, current and never smokers (males and females) at high risk for developing lung cancer, based on their genetic susceptibility profiles, to estimate their lifetime probabilities of the disease, and to assess the potential mortality reduction that could be achieved by screening the high-risk group. METHODS: Case-control data (764 cases and 677 matched controls), on two assays of DNA damage and repair (mutagen susceptibility and DNA repair capacity, DRC) in different smoking categories were used to obtain estimates of susceptibility using the formula of total probability. The estimates were inserted into a model of lung cancer natural history and detection by screening to assess mortality reduction due to screening of high-risk individuals. RESULTS: The high-risk group was defined as that 12.5% of the population who were above the third quartile for bleomycin sensitivity and below the median for DRC. High-risk male current, former, and never smokers had lifetime probabilities for developing lung cancer of 38, 21, and 5%, respectively. Females had lower probabilities to develop lung cancer: 15, 8, and 1.5% for high-risk current, former, and never smokers, respectively. Screening of high-risk smokers (12.5% of all smokers) reduced overall mortality by 7% compared to 30% reduction if all smokers were screened. Analogous results were obtained for former and never smokers. CONCLUSIONS: Genetic susceptibility constitutes an important factor in the selection of a high-risk group for early lung cancer detection.     

Allelic Spectra of Risk SNPs Are Different for Environment/Lifestyle Dependent versus Independent Diseases

Genome-wide association studies (GWAS) have generated sufficient data to assess the role of selection in shaping allelic diversity of disease-associated SNPs. Negative selection against disease risk variants is expected to reduce their frequencies making them overrepresented in the group of minor (<50%) alleles. Indeed, we found that the overall proportion of risk alleles was higher among alleles with frequency <50% (minor alleles) compared to that in the group of major alleles. We hypothesized that negative selection may have different effects on environment (or lifestyle)-dependent versus environment (or lifestyle)-independent diseases. We used an environment/lifestyle index (ELI) to assess influence of environmental/lifestyle factors on disease etiology. ELI was defined as the number of publications mentioning “environment” or “lifestyle” AND disease per 1,000 disease-mentioning publications. We found that the frequency distributions of the risk alleles for the diseases with strong environmental/lifestyle components follow the distribution expected under a selectively neutral model, while frequency distributions of the risk alleles for the diseases with weak environmental/lifestyle influences is shifted to the lower values indicating effects of negative selection. We hypothesized that previously selectively neutral variants become risk alleles when environment changes. The hypothesis of ancestrally neutral, currently disadvantageous risk-associated alleles predicts that the distribution of risk alleles for the environment/lifestyle dependent diseases will follow a neutral model since natural selection has not had enough time to influence allele frequencies. The results of our analysis suggest that prediction of SNP functionality based on the level of evolutionary conservation may not be useful for SNPs associated with environment/lifestyle dependent diseases.     

GWAS Meets Microarray: Are the Results of Genome-Wide Association Studies and Gene-Expression Profiling Consistent? Prostate Cancer as an Example

Background

Genome-wide association studies (GWASs) and global profiling of gene expression (microarrays) are two major technological breakthroughs that allow hypothesis-free identification of candidate genes associated with tumorigenesis. It is not obvious whether there is a consistency between the candidate genes identified by GWAS (GWAS genes) and those identified by profiling gene expression (microarray genes).

Methodology/Principal Findings

We used the Cancer Genetic Markers Susceptibility database to retrieve single nucleotide polymorphisms from candidate genes for prostate cancer. In addition, we conducted a large meta-analysis of gene expression data in normal prostate and prostate tumor tissue. We identified 13,905 genes that were interrogated by both GWASs and microarrays. On the basis of P values from GWASs, we selected 1,649 most significantly associated genes for functional annotation by the Database for Annotation, Visualization and Integrated Discovery. We also conducted functional annotation analysis using same number of the top genes identified in the meta-analysis of the gene expression data. We found that genes involved in cell adhesion were overrepresented among both the GWAS and microarray genes.

Conclusions/Significance

We conclude that the results of these analyses suggest that combining GWAS and microarray data would be a more effective approach than analyzing individual datasets and can help to refine the identification of candidate genes and functions associated with tumor development.     

Genetic structure, subdivision, and population differentiation in Stankewiczii pine Pinus stankewiczii (Sukacz.) Fomin from Mountain Crimea

In order to analyze the genetic structure, subdivision and differentiation within and between two small isolated populations of the Crimea relict endemic, Pinus stankewiczii (Sukacz.) Fomin, electrophoretic analysis of the isozyme variation at nine enzymatic systems was carried out using 183 oldest trees. It was demonstrated that in populations of P. stankewiczii, 80% of the genes were in polymorphic state. Each tree was heterozygous at 19.1% loci, and at 21.6% loci in artificial 50-year-old plantation. The genetic structure of two populations was less differentiated (DN = 0.006), compared to their individual localities (DN = 0.008-0.009). Within-population subdivision of the diffusely dispersed populations was higher (FST-GST = 1.8-2.0%) than that of the populations themselves (0.8%).