Whole genome association analysis shows that ACE is a risk factor for Alzheimer's disease and fails to replicate most candidates from Meta-analysis

For late onset Alzheimer's disease (LOAD), the only confirmed, genetic association is with the apolipoprotein E (APOE) locus on chromosome 19. Meta-analysis is often employed to sort the true associations from the false positives. LOAD research has the advantage of a continuously updated meta-analysis of candidate gene association studies in the web-based AlzGene database. The top 30 AlzGene loci on May 1(st), 2007 were investigated in our whole genome association data set consisting of 1411 LOAD cases and neuropathoiogicaiiy verified controls genotyped at 312,316 SNPs using the Affymetrix 500K Mapping Platform. Of the 30 "top AlzGenes", 32 SNPs in 24 genes had odds ratios (OR) whose 95% confidence intervals that did not include 1. Of these 32 SNPs, six were part of the Affymetrix 500K Mapping panel and another ten had proxies on the Affymetrix array that had >80% power to detect an association with α=0.001. Two of these 16 SNPs showed significant association with LOAD in our sample series. One was rs4420638 at the APOE locus (uncorrected p-value=4.58E-37) and the other was rs4293, located in the angiotensin converting enzyme (ACE) locus (uncorrected p-value=0.014). Since this result was nominally significant, but did not survive multiple testing correction for 16 independent tests, this association at rs4293 was verified in a geographically distinct German cohort (p-value=0.03). We present the results of our ACE replication aiongwith a discussion of the statistical limitations of multiple test corrections in whole genome studies.

Genetic control of human brain transcript expression in Alzheimer disease

We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We have now analyzed additional samples with a confirmed pathologic diagnosis of late-onset Alzheimer disease (LOAD; final n = 188 controls, 176 cases). Nine percent of the cortical transcripts that we analyzed had expression profiles correlated with their genotypes in the combined cohort, and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate-gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power for discovering risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease.

Genome-wide association analysis reveals putative Alzheimer's disease susceptibility loci in addition to APOE

Alzheimer's disease (AD) is a genetically complex and heterogeneous disorder. To date four genes have been established to either cause early-onset autosomal-dominant AD (APP, PSEN1, and PSEN2(1-4)) or to increase susceptibility for late-onset AD (APOE5). However, the heritability of late-onset AD is as high as 80%, (6) and much of the phenotypic variance remains unexplained to date. We performed a genome-wide association (GWA) analysis using 484,522 single-nucleotide polymorphisms (SNPs) on a large (1,376 samples from 410 families) sample of AD families of self-reported European descent. We identified five SNPs showing either significant or marginally significant genome-wide association with a multivariate phenotype combining affection status and onset age. One of these signals (p = 5.7 x 10(-14)) was elicited by SNP rs4420638 and probably reflects APOE-epsilon4, which maps 11 kb proximal (r2 = 0.78). The other four signals were tested in three additional independent AD family samples composed of nearly 2700 individuals from almost 900 families. Two of these SNPs showed significant association in the replication samples (combined p values 0.007 and 0.00002). The SNP (rs11159647, on chromosome 14q31) with the strongest association signal also showed evidence of association with the same allele in GWA data generated in an independent sample of approximately 1,400 AD cases and controls (p = 0.04). Although the precise identity of the underlying locus(i) remains elusive, our study provides compelling evidence for the existence of at least one previously undescribed AD gene that, like APOE-epsilon4, primarily acts as a modifier of onset age.

Evidence for an association between KIBRA and late-onset Alzheimer's disease

We recently reported evidence for an association between the individual variation in normal human episodic memory and a common variant of the KIBRA gene, KIBRA rs17070145 (T-allele). Since memory impairment is a cardinal clinical feature of Alzheimer's disease (AD), we investigated the possibility of an association between the KIBRA gene and AD using data from neuronal gene expression, brain imaging studies, and genetic association tests. KIBRA was significantly over-expressed and three of its four known binding partners under-expressed in AD-affected hippocampal, posterior cingulate and temporal cortex regions (P<0.010, corrected) in a study of laser-capture microdissected neurons. Using positron emission tomography in a cohort of cognitively normal, late-middle-aged persons genotyped for KIBRA rs17070145, KIBRA T non-carriers exhibited lower glucose metabolism than did carriers in posterior cingulate and precuneus brain regions (P<0.001, uncorrected). Lastly, non-carriers of the KIBRA rs17070145 T-allele had increased risk of late-onset AD in an association study of 702 neuropathologically verified expired subjects (P=0.034; OR=1.29) and in a combined analysis of 1026 additional living and expired subjects (P=0.039; OR=1.26). Our findings suggest that KIBRA is associated with both individual variation in normal episodic memory and predisposition to AD.

A survey of genetic human cortical gene expression

It is widely assumed that genetic differences in gene expression underpin much of the difference among individuals and many of the quantitative traits of interest to geneticists. Despite this, there has been little work on genetic variability in human gene expression and almost none in the human brain, because tools for assessing this genetic variability have not been available. Now, with whole-genome SNP genotyping arrays and whole-transcriptome expression arrays, such experiments have become feasible. We have carried out whole-genome genotyping and expression analysis on a series of 193 neuropathologically normal human brain samples using the Affymetrix GeneChip Human Mapping 500K Array Set and Illumina HumanRefseq-8 Expression BeadChip platforms. Here we present data showing that 58% of the transcriptome is cortically expressed in at least 5% of our samples and that of these cortically expressed transcripts, 21% have expression profiles that correlate with their genotype. These genetic-expression effects should be useful in determining the underlying biology of associations with common diseases of the human brain and in guiding the analysis of the genomic regions involved in the control of normal gene expression.

GAB2 alleles modify Alzheimer's risk in APOE epsilon4 carriers

The apolipoprotein E (APOE) epsilon4 allele is the best established genetic risk factor for late-onset Alzheimer's disease (LOAD). We conducted genome-wide surveys of 502,627 single-nucleotide polymorphisms (SNPs) to characterize and confirm other LOAD susceptibility genes. In epsilon4 carriers from neuropathologically verified discovery, neuropathologically verified replication, and clinically characterized replication cohorts of 1411 cases and controls, LOAD was associated with six SNPs from the GRB-associated binding protein 2 (GAB2) gene and a common haplotype encompassing the entire GAB2 gene. SNP rs2373115 (p = 9 x 10(-11)) was associated with an odds ratio of 4.06 (confidence interval 2.81-14.69), which interacts with APOE epsilon4 to further modify risk. GAB2 was overexpressed in pathologically vulnerable neurons; the Gab2 protein was detected in neurons, tangle-bearing neurons, and dystrophic neuritis; and interference with GAB2 gene expression increased tau phosphorylation. Our findings suggest that GAB2 modifies LOAD risk in APOE epsilon4 carriers and influences Alzheimer's neuropathology.

SNP-based chromosomal copy number ascertainment following multiple displacement whole-genome amplification

Whole genome amplification by multiple displacement amplification (MDA) offers investigators using precious genomic DNA samples a high fidelity method for amplifying nanogram quantities of DNA several thousandfold. This becomes especially important for the modemrn day genomics researcher who more and more commonly is applying today's genome scanning technologies to patient cohort samples collected years ago that are irrecoverable and invariably in short supply. We present evidence here that MDA-prepared genomic DNA includes artifacts of chromosomal copy number that resemble copy number polymorphisms (CNPs) upon analysis of the DNA on the Affymetrix 10K GeneChip. The study of CNPs in both health and disease is a rapidly growing area of research, however our current understanding of the relevance of CNPs is incomplete. Our data indicate that utilization of whole genome-amplified samples for analysis heavily reliant on accurate copy number retention could be confounded if the genomic DNA sample was subjected to MDA. We recommend that small amounts of patient cohort DNA stocks be set aside and not subjected to whole genome amplification in order to facilitate the unbiased determination of chromosomal copy numbers when desired.

Phenotypic definition of Chiari type I malformation coupled with high-density SNP genome screen shows significant evidence for linkage to regions on chromosomes 9 and 15

Chiari type I malformation (CMI; OMIM 118420) is narrowly defined when the tonsils of the cerebellum extend below the foramen magnum, leading to a variety of neurological symptoms. It is widely thought that a small posterior fossa (PF) volume, relative to the total cranial volume leads to a cramped cerebellum and herniation of the tonsils into the top of the spinal column. In a collection of magnetic resonance imagings (MRIs) from affected individuals and their family members, we measured correlations between ten cranial morphologies and estimated their heritability in these families. Correlations between bones delineating the PF and significant heritability of PF volume (0.955, P = 0.003) support the cramped PF theory and a genetic basis for this condition. In a collection of 23 families with 71 affected individuals, we performed a genome wide linkage screen of over 10,000 SNPs across the genome to identify regions of linkage to CMI. Two-point LOD scores on chromosome 15 reached 3.3 and multipoint scores in this region identified a 13 cM region with LOD scores over 1 (15q21.1-22.3). This region contains a biologically plausible gene for CMI, fibrillin-1, which is a major gene in Marfan syndrome and has been linked to Shprintzen-Goldberg syndrome, of which CMI is a distinguishing characteristic. Multipoint LOD scores on chromosome 9 maximized at 3.05, identifying a 40 cM region with LOD scores over 1 (9q21.33-33.1) and a tighter region with multipoint LOD scores over 2 that was only 8.5 cM. This linkage evidence supports a genetic role in Chiari malformation and justifies further exploration with fine mapping and investigation of candidate genes in these regions.

High-density single nucleotide polymorphism screen in a large multiplex neural tube defect family refines linkage to loci at 7p21.1-pter and 2q33.1-q35

BACKGROUND

Neural tube defects (NTDs) are considered complex, with both genetic and environmental factors implicated. To date, no major causative genes have been identified in humans despite several investigations. The first genomewide screen in NTDs demonstrated evidence of linkage to chromosomes 7 and 10. This screen included 44 multiplex families and consisted of 402 microsatellite markers spaced approximately 10 cM apart. Further investigation of the genomic screen data identified a single large multiplex family, pedigree 8776, as primarily driving the linkage results on chromosome 7.

METHODS

To investigate this family more thoroughly, a high-density single nucleotide polymorphism (SNP) screen was performed. Two-point and multipoint linkage analyses were performed using both parametric and nonparametric methods.

RESULTS

For both the microsatellite and SNP markers, linkage analysis suggested the involvement of a locus or loci proximal to the telomeric regions of chromosomes 2q and 7p, with both regions generating a LOD* score of 3.0 using a nonparametric identity by descent relative sharing method.

CONCLUSIONS

The regions with the strongest evidence for linkage map proximal to the telomeres on these two chromosomes. In addition to mutations and/or variants in a major gene, these loci may harbor a microdeletion and/or translocation; potentially, polygenic factors may also be involved. This single family may be promising for narrowing the search for NTD susceptibility genes.

SNiPer: improved SNP genotype calling for Affymetrix 10K GeneChip microarray data

BACKGROUND

High throughput microarray-based single nucleotide polymorphism (SNP) genotyping has revolutionized the way genome-wide linkage scans and association analyses are performed. One of the key features of the array-based GeneChip Mapping 10K Array from Affymetrix is the automated SNP calling algorithm. The Affymetrix algorithm was trained on a database of ethnically diverse DNA samples to create SNP call zones that are used as static models to make genotype calls for experimental data. We describe here the implementation of clustering algorithms on large training datasets resulting in improved SNP call rates on the 10K GeneChip.

RESULTS

A database of 948 individuals genotyped on the GeneChip Mapping 10K 2.0 Array was used to identify 822 SNPs that were called consistently less than 75% of the time. These SNPs represent on average 8.25% of the total SNPs on each chromosome with chromosome 19, the most gene-rich chromosome, containing the highest proportion of poor performers (18.7%). To remedy this, we created SNiPer, a new application which uses two clustering algorithms to yield increased call rates and equivalent concordance to Affymetrix called genotypes. We include a training set for these algorithms based on individual genotypes for 705 samples. SNiPer has the capability to be retrained for lab-specific training sets. SNiPer is freely available for download at http://www.tgen.org/neurogenomics/data.

CONCLUSION

The correct calling of poor performing SNPs may prove to be key in future linkage studies performed on the 10K GeneChip. It would prove particularly invaluable for those diseases that map to chromosome 19, known to contain a high proportion of poorly performing SNPs. Our results illustrate that SNiPer can be used to increase call rates on the 10K GeneChip without sacrificing accuracy, thereby increasing the amount of valid data generated.

Identification of disease causing loci using an array-based genotyping approach on pooled DNA

BACKGROUND

Pooling genomic DNA samples within clinical classes of disease followed by genotyping on whole-genome SNP microarrays, allows for rapid and inexpensive genome-wide association studies. Key to the success of these studies is the accuracy of the allelic frequency calculations, the ability to identify false-positives arising from assay variability and the ability to better resolve association signals through analysis of neighbouring SNPs.

RESULTS

We report the accuracy of allelic frequency measurements on pooled genomic DNA samples by comparing these measurements to the known allelic frequencies as determined by individual genotyping. We describe modifications to the calculation of k-correction factors from relative allele signal (RAS) values that remove biases and result in more accurate allelic frequency predictions. Our results show that the least accurate SNPs, those most likely to give false-positives in an association study, are identifiable by comparing their frequencies to both those from a known database of individual genotypes and those of the pooled replicates. In a disease with a previously identified genetic mutation, we demonstrate that one can identify the disease locus through the comparison of the predicted allelic frequencies in case and control pools. Furthermore, we demonstrate improved resolution of association signals using the mean of individual test-statistics for consecutive SNPs windowed across the genome. A database of k-correction factors for predicting allelic frequencies for each SNP, derived from several thousand individually genotyped samples, is provided. Lastly, a Perl script for calculating RAS values for the Affymetrix platform is provided.

CONCLUSION

Our results illustrate that pooling of DNA samples is an effective initial strategy to identify a genetic locus. However, it is important to eliminate inaccurate SNPs prior to analysis by comparing them to a database of individually genotyped samples as well as by comparing them to replicates of the pool. Lastly, detection of association signals can be improved by incorporating data from neighbouring SNPs.

The Autism Genome Project

Autism is a complex neurodevelopmental disorder with a broad spectrum of symptoms and varying severity. Currently, no biological diagnosis exists. Although there has been a significant increase in autism genetics research recently, validated susceptibility genes for the most common, sporadic forms of autistic disorder, as well as familial autism, have yet to be identified. The identification of autism-susceptibility genes will not only assist in the identification and/or development of better medications that can help improve the health and neurodevelopment of children with autism, but will also allow for better perinatal diagnosis. The Autism Genome Project (AGP) is a large-scale, collaborative genetics research project initiated by the National Alliance for Autism Research and the National Institutes of Health, and is aimed at sifting through the human genome in search of autism-susceptibility genes. Phase I of the AGP will consist of genome-wide scans utilizing both SNP array and microsatellite technologies. Linkage analysis will subsequently be performed on approximately 1500 pedigrees as will downstream fine-mapping and sequencing of the critical linkage intervals. Ultimately, the vision will be to identify the exact nucleotide variants within genes which give rise to predisposition. The AGP intends to move the field of autism clinical management forward by answering questions about the causal mechanisms underlying the pathophysiology of autism. From this knowledge, therapeutic targets for drug treatments, and ultimately, a newborn screening diagnostic that would allow for early intervention, can begin to be developed.

Genome-wide SNP arrays as a diagnostic tool: Clinical description, genetic mapping, and molecular characterization of Salla disease in an Old Order Mennonite population

An Old Order Mennonite child was evaluated for gross motor delay, truncal ataxia, and slow linear growth. The diagnostic evaluation, which included sub-specialty consultations, neuroimaging, and metabolic testing, was long, costly, and did not yield a diagnosis. Recognition of a similarly affected second cousin prompted a genome-wide homozygosity mapping study using high-density single nucleotide polymorphism (SNP) arrays. SNP genotypes from two affected individuals and their parents were used to localize the disease locus to a 14.9 Mb region on chromosome 6. This region contained 55 genes, including SLC17A5, the gene encoding the lysosomal N-acetylneuraminic acid transport protein. Direct sequencing of SLC17A5 in the proband revealed homozygosity for the 115C --> T (R39C) sequence variant, the common cause of Salla disease in Finland. Three additional affected Mennonite individuals, ages 8 months to 50 years, were subsequently identified by directed molecular genetic testing. This small-scale mapping study was rapid, inexpensive, and analytically simple. In families with shared genetic heritage, genome-wide SNP arrays with relatively high marker density allow disease gene mapping studies to be incorporated into routine diagnostic evaluations.

Mapping of sudden infant death with dysgenesis of the testes syndrome (SIDDT) by a SNP genome scan and identification of TSPYL loss of function

We have identified a lethal phenotype characterized by sudden infant death (from cardiac and respiratory arrest) with dysgenesis of the testes in males [Online Mendelian Inheritance in Man (OMIM) accession no. 608800]. Twenty-one affected individuals with this autosomal recessive syndrome were ascertained in nine separate sibships among the Old Order Amish. High-density single-nucleotide polymorphism (SNP) genotyping arrays containing 11,555 single-nucleotide polymorphisms evenly distributed across the human genome were used to map the disease locus. A genome-wide autozygosity scan localized the disease gene to a 3.6-Mb interval on chromosome 6q22.1-q22.31. This interval contained 27 genes, including two testis-specific Y-like genes (TSPYL and TSPYL4) of unknown function. Sequence analysis of the TSPYL gene in affected individuals identified a homozygous frameshift mutation (457_458insG) at codon 153, resulting in truncation of translation at codon 169. Truncation leads to loss of a peptide domain with strong homology to the nucleosome assembly protein family. GFP-fusion expression constructs were constructed and illustrated loss of nuclear localization of truncated TSPYL, suggesting loss of a nuclear localization patch in addition to loss of the nucleosome assembly domain. These results shed light on the pathogenesis of a disorder of sexual differentiation and brainstem-mediated sudden death, as well as give insight into a mechanism of transcriptional regulation.