Mariet Allen

Brain Expression Genome-Wide Association Study (eGWAS) Identifies Human Disease-Associated Variants

Genetic variants that modify brain gene expression may also influence risk for human diseases. We measured expression levels of 24,526 transcripts in brain samples from the cerebellum and temporal cortex of autopsied subjects with Alzheimers disease (AD, cerebellar n = 197, temporal cortex n = 202) and with other brain pathologies (non–AD, cerebellar n = 177, temporal cortex n = 197). We conducted an expression genome-wide association study (eGWAS) using 213,528 cisSNPs within ±100 kb of the tested transcripts. We identified 2,980 cerebellar cisSNP/transcript level associations (2,596 unique cisSNPs) significant in both ADs and non–ADs (q<0.05, p = 7.70×10−5–1.67×10−82). Of these, 2,089 were also significant in the temporal cortex (p = 1.85×10−5–1.70×10−141). The top cerebellar cisSNPs had 2.4-fold enrichment for human disease-associated variants (p<10−6). We identified novel cisSNP/transcript associations for human disease-associated variants, including progressive supranuclear palsy SLCO1A2/rs11568563, Parkinsons disease (PD) MMRN1/rs6532197, Pagets disease OPTN/rs1561570; and we confirmed others, including PD MAPT/rs242557, systemic lupus erythematosus and ulcerative colitis IRF5/rs4728142, and type 1 diabetes mellitus RPS26/rs1701704. In our eGWAS, there was 2.9–3.3 fold enrichment (p<10−6) of significant cisSNPs with suggestive AD–risk association (p<10−3) in the Alzheimers Disease Genetics Consortium GWAS. These results demonstrate the significant contributions of genetic factors to human brain gene expression, which are reliably detected across different brain regions and pathologies. The significant enrichment of brain cisSNPs among disease-associated variants advocates gene expression changes as a mechanism for many central nervous system (CNS) and non–CNS diseases. Combined assessment of expression and disease GWAS may provide complementary information in discovery of human disease variants with functional implications. Our findings have implications for the design and interpretation of eGWAS in general and the use of brain expression quantitative trait loci in the study of human disease genetics.

Novel late-onset Alzheimer disease loci variants associate with brain gene expression

Objective: Recent genome-wide association studies (GWAS) of late-onset Alzheimer disease (LOAD) identified 9 novel risk loci. Discovery of functional variants within genes at these loci is required to confirm their role in Alzheimer disease (AD). Single nucleotide polymorphisms that influence gene expression (eSNPs) constitute an important class of functional variants. We therefore investigated the influence of the novel LOAD risk loci on human brain gene expression. Methods: We measured gene expression levels in the cerebellum and temporal cortex of autopsied AD subjects and those with other brain pathologies (∼400 total subjects). To determine whether any of the novel LOAD risk variants are eSNPs, we tested their cis-association with expression of 6 nearby LOAD candidate genes detectable in human brain (ABCA7, BIN1, CLU, MS4A4A, MS4A6A, PICALM) and an additional 13 genes ±100 kb of these SNPs. To identify additional eSNPs that influence brain gene expression levels of the novel candidate LOAD genes, we identified SNPs ±100 kb of their location and tested for cis-associations. Results: CLU rs11136000 (p = 7.81 × 10−4) and MS4A4A rs2304933/rs2304935 (p = 1.48 × 10−4–1.86 × 10−4) significantly influence temporal cortex expression levels of these genes. The LOAD-protective CLU and risky MS4A4A locus alleles associate with higher brain levels of these genes. There are other cis-variants that significantly influence brain expression of CLU and ABCA7 (p = 4.01 × 10−5–9.09 × 10−9), some of which also associate with AD risk (p = 2.64 × 10−2–6.25 × 10−5). Conclusions: CLU and MS4A4A eSNPs may at least partly explain the LOAD risk association at these loci. CLU and ABCA7 may harbor additional strong eSNPs. These results have implications in the search for functional variants at the novel LOAD risk loci.

Association of MAPT haplotypes with Alzheimer’s disease risk and MAPT brain gene expression levels

IntroductionMAPT encodes for tau, the predominant component of neurofibrillary tangles that are neuropathological hallmarks of Alzheimer’s disease (AD). Genetic association of MAPT variants with late-onset AD (LOAD) risk has been inconsistent, although insufficient power and incomplete assessment of MAPT haplotypes may account for this.MethodsWe examined the association of MAPT haplotypes with LOAD risk in more than 20,000 subjects (n-cases = 9,814, n-controls = 11,550) from Mayo Clinic (n-cases = 2,052, n-controls = 3,406) and the Alzheimer’s Disease Genetics Consortium (ADGC, n-cases = 7,762, n-controls = 8,144). We also assessed associations with brain MAPT gene expression levels measured in the cerebellum (n = 197) and temporal cortex (n = 202) of LOAD subjects. Six single nucleotide polymorphisms (SNPs) which tag MAPT haplotypes with frequencies greater than 1% were evaluated.ResultsH2-haplotype tagging rs8070723-G allele associated with reduced risk of LOAD (odds ratio, OR = 0.90, 95% confidence interval, CI = 0.85-0.95, p = 5.2E-05) with consistent results in the Mayo (OR = 0.81, p = 7.0E-04) and ADGC (OR = 0.89, p = 1.26E-04) cohorts. rs3785883-A allele was also nominally significantly associated with LOAD risk (OR = 1.06, 95% CI = 1.01-1.13, p = 0.034). Haplotype analysis revealed significant global association with LOAD risk in the combined cohort (p = 0.033), with significant association of the H2 haplotype with reduced risk of LOAD as expected (p = 1.53E-04) and suggestive association with additional haplotypes. MAPT SNPs and haplotypes also associated with brain MAPT levels in the cerebellum and temporal cortex of AD subjects with the strongest associations observed for the H2 haplotype and reduced brain MAPT levels (β = -0.16 to -0.20, p = 1.0E-03 to 3.0E-03).ConclusionsThese results confirm the previously reported MAPT H2 associations with LOAD risk in two large series, that this haplotype has the strongest effect on brain MAPT expression amongst those tested and identify additional haplotypes with suggestive associations, which require replication in independent series. These biologically congruent results provide compelling evidence to screen the MAPT region for regulatory variants which confer LOAD risk by influencing its brain gene expression.

Concordant association of insulin degrading enzyme gene (IDE) variants with IDE mRNA, Abeta, and Alzheimer's disease.

Background The insulin-degrading enzyme gene (IDE) is a strong functional and positional candidate for late onset Alzheimers disease (LOAD). Methodology/Principal Findings We examined conserved regions of IDE and its 10 kb flanks in 269 AD cases and 252 controls thereby identifying 17 putative functional polymorphisms. These variants formed eleven haplotypes that were tagged with ten variants. Four of these showed significant association with IDE transcript levels in samples from 194 LOAD cerebella. The strongest, rs6583817, which has not previously been reported, showed unequivocal association (p = 1.5×10−8, fold-increase = 2.12,); the eleven haplotypes were also significantly associated with transcript levels (global p = 0.003). Using an in vitro dual luciferase reporter assay, we found that rs6583817 increases reporter gene expression in Be(2)-C (p = 0.006) and HepG2 (p = 0.02) cell lines. Furthermore, using data from a recent genome-wide association study of two Croatian isolated populations (n = 1,879), we identified a proxy for rs6583817 that associated significantly with decreased plasma Aβ40 levels (ß = −0.124, p = 0.011) and total measured plasma Aβ levels (b = −0.130, p = 0.009). Finally, rs6583817 was associated with decreased risk of LOAD in 3,891 AD cases and 3,605 controls. (OR = 0.87, p = 0.03), and the eleven IDE haplotypes (global p = 0.02) also showed significant association. Conclusions Thus, a previously unreported variant unequivocally associated with increased IDE expression was also associated with reduced plasma Aß40 and decreased LOAD susceptibility. Genetic association between LOAD and IDE has been difficult to replicate. Our findings suggest that targeted testing of expression SNPs (eSNPs) strongly associated with altered transcript levels in autopsy brain samples may be a powerful way to identify genetic associations with LOAD that would otherwise be difficult to detect.

Late-onset Alzheimer's risk variants in memory decline, incident mild cognitive impairment, and Alzheimer's disease.

We tested association of nine late-onset Alzheimers disease (LOAD) risk variants from genome-wide association studies (GWAS) with memory and progression to mild cognitive impairment (MCI) or LOAD (MCI/LOAD) in older Caucasians, cognitively normal at baseline and longitudinally evaluated at Mayo Clinic Rochester and Jacksonville (n>2000). Each variant was tested both individually and collectively using a weighted risk score. APOE-e4 associated with worse baseline memory and increased decline with highly significant overall effect on memory. CLU-rs11136000-G associated with worse baseline memory and incident MCI/LOAD. MS4A6A-rs610932-C associated with increased incident MCI/LOAD and suggestively with lower baseline memory. ABCA7-rs3764650-C and EPHA1-rs11767557-A associated with increased rates of memory decline in subjects with a final diagnosis of MCI/LOAD. PICALM-rs3851179-G had an unexpected protective effect on incident MCI/LOAD. Only APOE-inclusive risk scores associated with worse memory and incident MCI/LOAD. The collective influence of the nine top LOAD GWAS variants on memory decline and progression to MCI/LOAD appears limited. Discovery of biologically functional variants at these loci may uncover stronger effects on memory and incident disease.

Glutathione S-transferase omega genes in Alzheimer and Parkinson disease risk, age-at- diagnosis and brain gene expression: an association study with mechanistic implications

BackgroundGlutathione S-transferase omega-1 and 2 genes (GSTO1, GSTO2), residing within an Alzheimer and Parkinson disease (AD and PD) linkage region, have diverse functions including mitigation of oxidative stress and may underlie the pathophysiology of both diseases. GSTO polymorphisms were previously reported to associate with risk and age-at-onset of these diseases, although inconsistent follow-up study designs make interpretation of results difficult. We assessed two previously reported SNPs, GSTO1 rs4925 and GSTO2 rs156697, in AD (3,493 ADs vs. 4,617 controls) and PD (678 PDs vs. 712 controls) for association with disease risk (case-controls), age-at-diagnosis (cases) and brain gene expression levels (autopsied subjects).ResultsWe found that rs156697 minor allele associates with significantly increased risk (odds ratio = 1.14, p = 0.038) in the older ADs with age-at-diagnosis > 80 years. The minor allele of GSTO1 rs4925 associates with decreased risk in familial PD (odds ratio = 0.78, p = 0.034). There was no other association with disease risk or age-at-diagnosis. The minor alleles of both GSTO SNPs associate with lower brain levels of GSTO2 (p = 4.7 × 10-11-1.9 × 10-27), but not GSTO1. Pathway analysis of significant genes in our brain expression GWAS, identified significant enrichment for glutathione metabolism genes (p = 0.003).ConclusionThese results suggest that GSTO locus variants may lower brain GSTO2 levels and consequently confer AD risk in older age. Other glutathione metabolism genes should be assessed for their effects on AD and other chronic, neurologic diseases.

Gene expression levels as endophenotypes in genome-wide association studies of Alzheimer disease

Background: Late-onset Alzheimer disease (LOAD) is a common disorder with a substantial genetic component. We postulate that many disease susceptibility variants act by altering gene expression levels. Methods: We measured messenger RNA (mRNA) expression levels of 12 LOAD candidate genes in the cerebella of 200 subjects with LOAD. Using the genotypes from our LOAD genome-wide association study for the cis-single nucleotide polymorphisms (SNPs) (n = 619) of these 12 LOAD candidate genes, we tested for associations with expression levels as endophenotypes. The strongest expression cis-SNP was tested for AD association in 7 independent case-control series (2,280 AD and 2,396 controls). Results: We identified 3 SNPs that associated significantly with IDE (insulin degrading enzyme) expression levels. A single copy of the minor allele for each significant SNP was associated with ∼twofold higher IDE expression levels. The most significant SNP, rs7910977, is 4.2 kb beyond the 3′ end of IDE. The association observed with this SNP was significant even at the genome-wide level (p = 2.7 × 10−8). Furthermore, the minor allele of rs7910977 associated significantly (p = 0.0046) with reduced LOAD risk (OR = 0.81 with a 95% CI of 0.70-0.94), as expected biologically from its association with elevated IDE expression. Conclusions: These results provide strong evidence that IDE is a late-onset Alzheimer disease (LOAD) gene with variants that modify risk of LOAD by influencing IDE expression. They also suggest that the use of expression levels as endophenotypes in genome-wide association studies may provide a powerful approach for the identification of disease susceptibility alleles.

Evaluation of memory endophenotypes for association with CLU, CR1, and PICALM variants in black and white subjects

Genetic variants at the CLU, CR1, and PICALM loci associate with risk for late‐onset Alzheimers disease (LOAD) in genomewide association studies. In this study, our aim was to determine whether the LOAD risk variants at these three loci influence memory endophenotypes in black and white subjects.

Human whole genome genotype and transcriptome data for Alzheimer's and other neurodegenerative diseases.

Previous genome-wide association studies (GWAS), conducted by our group and others, have identified loci that harbor risk variants for neurodegenerative diseases, including Alzheimers disease (AD). Human disease variants are enriched for polymorphisms that affect gene expression, including some that are known to associate with expression changes in the brain. Postulating that many variants confer risk to neurodegenerative disease via transcriptional regulatory mechanisms, we have analyzed gene expression levels in the brain tissue of subjects with AD and related diseases. Herein, we describe our collective datasets comprised of GWAS data from 2,099 subjects; microarray gene expression data from 773 brain samples, 186 of which also have RNAseq; and an independent cohort of 556 brain samples with RNAseq. We expect that these datasets, which are available to all qualified researchers, will enable investigators to explore and identify transcriptional mechanisms contributing to neurodegenerative diseases.

Late-onset Alzheimer disease risk variants mark brain regulatory loci

Objective: To investigate the top late-onset Alzheimer disease (LOAD) risk loci detected or confirmed by the International Genomics of Alzheimers Project for association with brain gene expression levels to identify variants that influence Alzheimer disease (AD) risk through gene expression regulation. Methods: Expression levels from the cerebellum (CER) and temporal cortex (TCX) were obtained using Illumina whole-genome cDNA-mediated annealing, selection, extension, and ligation assay (WG-DASL) for ∼400 autopsied patients (∼200 with AD and ∼200 with non-AD pathologies). We tested 12 significant LOAD genome-wide association study (GWAS) index single nucleotide polymorphisms (SNPs) for cis association with levels of 34 genes within ±100 kb. We also evaluated brain levels of 14 LOAD GWAS candidate genes for association with 1,899 cis-SNPs. Significant associations were validated in a subset of TCX samples using next-generation RNA sequencing (RNAseq). Results: We identified strong associations of brain CR1, HLA-DRB1, and PILRB levels with LOAD GWAS index SNPs. We also detected other strong cis-SNPs for LOAD candidate genes MEF2C, ZCWPW1, and SLC24A4. MEF2C and SLC24A4, but not ZCWPW1 cis-SNPs, also associate with LOAD risk, independent of the index SNPs. The TCX expression associations could be validated with RNAseq for CR1, HLA-DRB1, ZCWPW1, and SLC24A4. Conclusions: Our results suggest that some LOAD GWAS variants mark brain regulatory loci, nominate genes under regulation by LOAD risk variants, and annotate these variants for their brain regulatory effects.