Here, we leverage a unique collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We find that the level of methylation at 71 of the 415,848 interrogated CpGs is significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validate 11 of the differentially methylated regions in an independent set of 117 subjects. Further, we functionally validate these CpG associations and identify the nearby genes whose RNA expression is altered in AD: ANK1, CDH23, DIP2A, RHBDF2, RPL13, RNF34, SERPINF1 and SERPINF2. Our analyses suggest that these DNA methylation changes may have a role in the onset of AD since (1) they are seen in presymptomatic subjects and (2) six of the validated genes connect to a known AD susceptibility gene network.

Previous genome-wide association studies (GWAS), conducted by our group and others, have identified loci that harbor risk variants for neurodegenerative diseases, including Alzheimer's 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.

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 Alzheimer's 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, Parkinson's disease (PD) MMRN1/rs6532197, Paget's 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 Alzheimer's 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.

Downregulation of myelination networks may underlie both PSP and AD pathophysiology, but may be more pronounced in PSP. These data also highlight conservation of transcriptional networks across brain regions and the influence of cell type changes on these networks.

By analyzing late onset Alzheimer's disease (LOAD) in a genome wide association study (313,504 SNPs, 3 series, 844 cases/1,255 controls) and evaluating the 25 SNPs with most significant allelic association in 4 additional series (1,547 cases/1,209 controls), we identified a SNP (rs5984894) on Xq21.3 in PCDH11X that is strongly associated with LOAD in American Caucasians. Analysis of rs5984894 by multivariable logistic regression adjusted for sex gave global P values of 5.7×10 -5 in stage I, 4.8×10 -6 in stage II, and 3.9×10 -12 in the combined data. Odds ratios were 1.75 (95% CI 1.42-2.16) for female homozygotes (P=2.0×10 -7 ) and 1.26 (95% CI 1.05-1.51) for female heterozygotes (P=0.01) compared to female non-carriers. For male hemizygotes (P=0.07) compared to male non-carriers the odds ratio was 1.18 (95% CI 0.99-1.41).Late onset Alzheimer's disease (LOAD) is a neurodegenerative disease characterized by large numbers of senile plaques and neurofibrillary tangles in the brain. LOAD is the most common cause of dementia in the elderly, affecting approximately 10% of those aged 65 years or older 1 . Multiple rare mutations in the genes encoding the amyloid ß protein precursor, presenilin 1, and presenilin 2 cause an early onset familial form of AD with autosomal dominant inheritance, but the only well established susceptibility allele for LOAD is the APOE ε4, To whom correspondence should be address: younkin.steven@mayo.edu. Author Contributions: M.M.C. spearheaded and participated in all aspects of this study, and drafted the manuscript along with Steven G. Younkin who is the lead investigator of this study. F.Z., S.L.W., L.M. and L.P.W. participated in the SEQUENOM genotyping. F.Z., L.M., L.H.Y. and G.D.B. were responsible for DNA sample preparation and quality control. L.M. also generated all DNA replica plates. Samuel G. Younkin and C.S.Y were instrumental in data management and analysis. N.E.T. participated in critical revisions of the manuscript. V.S.P and J.E.C. provided statistical expertise. N.R.G. and R.C.P. are the neurologists who diagnosed and provided samples for the Mayo Clinic Jacksonville (JS) and Mayo Clinic Rochester (RS) series, respectively. D.W.D. is the pathologist who diagnosed and provided brain samples for the autopsy-confirmed (AUT) series.URLs. PLINK, http://pngu.mgh.harvard.edu/purcell/plink/ Accession codes. RefSeq: PCDH11X mRNA isoform a precursor, NM_014522.1; PCDH11X mRNA isoform b precursor, NM_032967.1; PCDH11X mRNA isoform c, NM_032968.2; PCDH11X mRNA isoform d precursor, NM_032969.2. Entrez Gene: PCDH11X, 27328; PCDH11Y, 83259. sexually dimorphic traits 9 . To explore this possibility, we analyzed rs5984894 by multivariable logistic regression with sex as a covariate (Table 2). Using this approach, which specifically models each carrier group, the global P value in the combined series improved substantially to 3.9×10 -12 as compared to 3.8×10 -8 for allelic association (Supplementary Table 3) and 2.2×10 -7 using the Mantel-Haenszel method (Table 1). In the combined se...