Gene finding in genetically isolated populations

The struggle to identify susceptibility genes for complex disorders has stimulated geneticists to develop new approaches. One approach that has gained considerable interest is to focus on genetically isolated populations rather than on the general population. There remains much controversy and theoretical debate over the feasibility and advantages of such populations, but recent results speak in favor of the feasibility of this approach, and will be reviewed here

High content screening in neurodegenerative diseases

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency(1-4). Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation(5). For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known(6, 7). As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity(8). This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention. High-throughput screening (HTS) is an ideal methodology to address these issues(9-12). but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties(13, 14). This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS)(4, 15-17). HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. HCS has many advantages over HTS(18, 19), but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing(20) and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism(21). Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets

Common variants underlying cognitive ability: further evidence for association between the SNAP-25 gene and cognition using a family-based study in two independent Dutch cohorts.

The synaptosomal associated protein of 25 kDa (SNAP-25) gene, located on chromosome 20 p12-12p11.2 encodes a presynaptic terminal protein. SNAP-25 is differentially expressed in the brain, and primarily present in the neocortex, hippocampus, anterior thalamic nuclei, substantia nigra and cerebellar granular cells. Recently, a family-based genetic association was reported between variation in intelligence quotient (IQ) phenotypes and two intronic variants on the SNAP-25 gene. The present study is a follow-up association study in two Dutch cohorts of 371 children (mean age 12.4 years) and 391 adults (mean age 36.2 years). It examines the complete genomic region of the SNAP-25 gene to narrow down the location of causative genetic variant underlying the association. Two new variants in intron 1 (rs363043 and rs353016), close to the two previous reported variants (rs363039 and rs363050) showed association with variation in IQ phenotypes across both cohorts. All four single nucleotide polymorphisms were located in intron 1, within a region of about 13.8 kbp, and are known to affect transcription factor-binding sites. Contrary to what is expected in monogenic traits, subtle changes are postulated to influence the phenotypic outcome of complex (common) traits. As a result, functional polymorphisms in (non)coding regulatory sequences may affect spatial and temporal regulation of gene expression underlying normal cognitive variation. © 2007 The Authors

Genome-Wide Prediction of Functional Gene-Gene Interactions Inferred from Patterns of Genetic Differentiation in Mice and Men.

The human genome encodes a limited number of genes yet contributes to individual differences in a vast array of heritable traits. A possible explanation for the capacity our genome to generate this virtually unlimited range of phenotypic variation in complex traits is to assume functional interactions between genes. Therefore we searched two mammalian genomes to identify potential epistatic interactions by looking for co-adapted genes marked by excess two-locus genetic differentiation between populations/lineages using publicly available SNP genotype data. The practical motivation for this effort is to reduce the number of pair-wise tests that need to be performed in genome-wide association studies aimed at detecting GxG interactions, by focusing on pairs predicted to be more likely to jointly affect variation in complex traits. Hence, this approach generates a list of candidate interactions that can be empirically tested. In both the mouse and human data we observed two-locus genetic differentiation in excess of what can be expected from chance alone based on simulations. In an attempt to validate our hypothesis that pairs of genes showing excess genetic divergence represent potential functional interactions, we selected a small set of gene combinations postulated to be interacting based on our analyses and looked for a combined effect of the selected genes on variation in complex traits in both mice and man. In both cases the individual effect of the genes were not significant, instead we observed marginally significant interaction effects. These results show that genome wide searches for gene-gene interactions based on population genetic data are feasible and can generate interesting candidate gene pairs to be further tested for their contribution to phenotypic variation in complex traits

The SNAP-25 gene is associated with cognitive ability: evidence from a family-based study in two independent Dutch cohorts

The synaptosomal-associated protein of 25 kDa (SNAP-25) gene plays an integral role in synaptic transmission, and is differentially expressed in the mammalian brain in the neocortex, hippocampus, anterior thalamic nuclei, substantia nigra and cerebellar granular cells. Recent studies have suggested a possible involvement of SNAP-25 in learning and memory, both of which are key components of human intelligence. In addition, the SNAP-25 gene lies in a linkage area implicated previously in human intelligence. In two independent family-based Dutch samples of 391 (mean age 12.4 years) and 276 (mean age 37.3 years) subjects, respectively, we genotyped 12 single-nucleotide polymorphisms (SNPs) in the SNAP-25 gene on 20p12-20p11.2. From all individuals, standardized intelligence measures were available. Using a family-based association test, a strong association was found between three SNPs in the SNAP-25 gene and intelligence, two of which showed association in both independent samples. The strongest, replicated association was found between SNP rs363050 and performance IQ (PIQ), where the A allele was associated with an increase of 2.84 PIQ points (P=0.0002). Variance in this SNP accounts for 3.4 % of the phenotypic variance in PIQ. © 2006 Nature Publishing Group All rights reserved

N-acetyltransferase 2 polymorphism in Parkinson's disease. The Rotterdam study

The N-acetyltransferase-2 gene (NAT-2) has been associated with Parkinson's disease. The genotype associated with slow acetylation has been reported to be increased in patients with Parkinson's disease. Three mutant alleles M1, M2, and M3 of NAT-2 were investigated in 80 patients with idiopathic Parkinson's disease and 161 age matched randomly selected controls from a prospective population based cohort study. The allelic frequencies and genotypic distributions in patients were very similar to those found in controls. In controls the frequency of the wild type allele increased significantly with age suggesting that the mutant alleles are associated with an increased risk of mortality. These findings suggest that NAT-2 polymorphism is not a major genetic determinant of idiopathic Parkinson's disease, but may be a determinant of mortality in the general population