Leonard C. Schalkwyk

Functional annotation of the human brain methylome identifies tissue-specific epigenetic variation across brain and blood

BackgroundDynamic changes to the epigenome play a critical role in establishing and maintaining cellular phenotype during differentiation, but little is known about the normal methylomic differences that occur between functionally distinct areas of the brain. We characterized intra- and inter-individual methylomic variation across whole blood and multiple regions of the brain from multiple donors.ResultsDistinct tissue-specific patterns of DNA methylation were identified, with a highly significant over-representation of tissue-specific differentially methylated regions (TS-DMRs) observed at intragenic CpG islands and low CG density promoters. A large proportion of TS-DMRs were located near genes that are differentially expressed across brain regions. TS-DMRs were significantly enriched near genes involved in functional pathways related to neurodevelopment and neuronal differentiation, including BDNF, BMP4, CACNA1A, CACA1AF, EOMES, NGFR, NUMBL, PCDH9, SLIT1, SLITRK1 and SHANK3. Although between-tissue variation in DNA methylation was found to greatly exceed between-individual differences within any one tissue, we found that some inter-individual variation was reflected across brain and blood, indicating that peripheral tissues may have some utility in epidemiological studies of complex neurobiological phenotypes.ConclusionsThis study reinforces the importance of DNA methylation in regulating cellular phenotype across tissues, and highlights genomic patterns of epigenetic variation across functionally distinct regions of the brain, providing a resource for the epigenetics and neuroscience research communities.

Disease-associated epigenetic changes in monozygotic twins discordant for schizophrenia and bipolar disorder

Studies of the major psychoses, schizophrenia (SZ) and bipolar disorder (BD), have traditionally focused on genetic and environmental risk factors, although more recent work has highlighted an additional role for epigenetic processes in mediating susceptibility. Since monozygotic (MZ) twins share a common DNA sequence, their study represents an ideal design for investigating the contribution of epigenetic factors to disease etiology. We performed a genome-wide analysis of DNA methylation on peripheral blood DNA samples obtained from a unique sample of MZ twin pairs discordant for major psychosis. Numerous loci demonstrated disease-associated DNA methylation differences between twins discordant for SZ and BD individually, and together as a combined major psychosis group. Pathway analysis of our top loci highlighted a significant enrichment of epigenetic changes in biological networks and pathways directly relevant to psychiatric disorder and neurodevelopment. The top psychosis-associated, differentially methylated region, significantly hypomethylated in affected twins, was located in the promoter of ST6GALNAC1 overlapping a previously reported rare genomic duplication observed in SZ. The mean DNA methylation difference at this locus was 6%, but there was considerable heterogeneity between families, with some twin pairs showing a 20% difference in methylation. We subsequently assessed this region in an independent sample of postmortem brain tissue from affected individuals and controls, finding marked hypomethylation (>25%) in a subset of psychosis patients. Overall, our data provide further evidence to support a role for DNA methylation differences in mediating phenotypic differences between MZ twins and in the etiology of both SZ and BD.

The nature and identification of quantitative trait loci: a community’s view

This white paper by eighty members of the Complex Trait Consortium presents a communitys view on the approaches and statistical analyses that are needed for the identification of genetic loci that determine quantitative traits. Quantitative trait loci (QTLs) can be identified in several ways, but is there a definitive test of whether a candidate locus actually corresponds to a specific QTL?

A data-driven approach to preprocessing Illumina 450K methylation array data

BackgroundAs the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets.ResultsThe standard index of DNA methylation at any specific CpG site is β = M/(M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas (βs) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive.ConclusionsCareful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data.

Moderation of breastfeeding effects on the IQ by genetic variation in fatty acid metabolism

Childrens intellectual development is influenced by both genetic inheritance and environmental experiences. Breastfeeding is one of the earliest such postnatal experiences. Breastfed children attain higher IQ scores than children not fed breast milk, presumably because of the fatty acids uniquely available in breast milk. Here we show that the association between breastfeeding and IQ is moderated by a genetic variant in FADS2, a gene involved in the genetic control of fatty acid pathways. We confirmed this gene–environment interaction in two birth cohorts, and we ruled out alternative explanations of the finding involving gene–exposure correlation, intrauterine growth, social class, and maternal cognitive ability, as well as maternal genotype effects on breastfeeding and breast milk. The finding shows that environmental exposures can be used to uncover novel candidate genes in complex phenotypes. It also shows that genes may work via the environment to shape the IQ, helping to close the nature versus nurture debate.

Alzheimer's disease: early alterations in brain DNA methylation at ANK1 , BIN1 , RHBDF2 and other loci

We used a collection of 708 prospectively collected autopsied brains to assess the methylation state of the brains DNA in relation to Alzheimers disease (AD). We found that the level of methylation at 71 of the 415,848 interrogated CpGs was significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validated 11 of the differentially methylated regions in an independent set of 117 subjects. Furthermore, we functionally validated these CpG associations and identified the nearby genes whose RNA expression was altered in AD: ANK1, CDH23, DIP2A, RHBDF2, RPL13, SERPINF1 and SERPINF2. Our analyses suggest that these DNA methylation changes may have a role in the onset of AD given that we observed them in presymptomatic subjects and that six of the validated genes connect to a known AD susceptibility gene network.

Genetic analysis of the mouse brain proteome

Proteome analysis is a fundamental step in systematic functional genomics. Here we have resolved 8,767 proteins from the mouse brain proteome by large-gel two-dimensional electrophoresis. We detected 1,324 polymorphic proteins from the European collaborative interspecific backcross. Of these, we mapped 665 proteins genetically and identified 466 proteins by mass spectrometry. Qualitatively polymorphic proteins, to 96%, reflect changes in conformation and/or mass. Quantitatively polymorphic proteins show a high frequency (73%) of allele-specific transmission in codominant heterozygotes. Variations in protein isoforms and protein quantity often mapped to chromosomal positions different from that of the structural gene, indicating that single proteins may act as polygenic traits. Genetic analysis of proteomes may detect the types of polymorphism that are most relevant in disease-association studies.

Allelic Skewing of DNA Methylation Is Widespread across the Genome

DNA methylation is assumed to be complementary on both alleles across the genome, although there are exceptions, notably in regions subject to genomic imprinting. We present a genome-wide survey of the degree of allelic skewing of DNA methylation with the aim of identifying previously unreported differentially methylated regions (DMRs) associated primarily with genomic imprinting or DNA sequence variation acting in cis. We used SNP microarrays to quantitatively assess allele-specific DNA methylation (ASM) in amplicons covering 7.6% of the human genome following cleavage with a cocktail of methylation-sensitive restriction enzymes (MSREs). Selected findings were verified using bisulfite-mapping and gene-expression analyses, subsequently tested in a second tissue from the same individuals, and replicated in DNA obtained from 30 parent-child trios. Our approach detected clear examples of ASM in the vicinity of known imprinted loci, highlighting the validity of the method. In total, 2,704 (1.5%) of our 183,605 informative and stringently filtered SNPs demonstrate an average relative allele score (RAS) change > or =0.10 following MSRE digestion. In agreement with previous reports, the majority of ASM ( approximately 90%) appears to be cis in nature, and several examples of tissue-specific ASM were identified. Our data show that ASM is a widespread phenomenon, with >35,000 such sites potentially occurring across the genome, and that a spectrum of ASM is likely, with heterogeneity between individuals and across tissues. These findings impact our understanding about the origin of individual phenotypic differences and have implications for genetic studies of complex disease.

High resolution cosmid and P1 maps spanning the 14 Mb genome of the fission yeast S. pombe

Gridded on high density filters, a P1 genomic library of 17-fold coverage and a cosmid library of 8 genome equivalents, both made from S. pombe strain 972h-, were ordered by hybridizing genetic markers and individual clones from the two libraries. Yeast artificial chromosome (YAC) clones covering the entire genome were used to subdivide the libraries, and hybridization of short oligonucleotides and DNA pools made from randomly selected cosmids provided further mapping information. Restriction digests were generated as an independent confirmation of the clone order. The high resolution clone map was aligned to the genetic map and the physical Notl and YAC maps. The usefulness of the various mapping techniques and cloning procedures could be assessed upon the different data sets.

Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder characterized by progressive neuropathology and cognitive decline. We describe a cross-tissue analysis of methylomic variation in AD using samples from three independent human post-mortem brain cohorts. We identify a differentially methylated region in the ankyrin 1 (ANK1) gene that is associated with neuropathology in the entorhinal cortex, a primary site of AD manifestation. This region was confirmed as significantly hypermethylated in two other cortical regions (superior temporal gyrus and prefrontal cortex) but not in the cerebellum, a region largely protected from neurodegeneration in AD, nor whole blood obtained pre-mortem, from the same individuals. Neuropathology-associated ANK1 hypermethylation was subsequently confirmed in cortical samples from three independent brain cohorts. This study represents the first epigenome-wide association study (EWAS) of AD employing a sequential replication design across multiple tissues, and highlights the power of this approach for identifying methylomic variation associated with complex disease.Alzheimers disease (AD) is a chronic neurodegenerative disorder that is characterized by progressive neuropathology and cognitive decline. We performed a cross-tissue analysis of methylomic variation in AD using samples from four independent human post-mortem brain cohorts. We identified a differentially methylated region in the ankyrin 1 (ANK1) gene that was associated with neuropathology in the entorhinal cortex, a primary site of AD manifestation. This region was confirmed as being substantially hypermethylated in two other cortical regions (superior temporal gyrus and prefrontal cortex), but not in the cerebellum, a region largely protected from neurodegeneration in AD, or whole blood obtained pre-mortem from the same individuals. Neuropathology-associated ANK1 hypermethylation was subsequently confirmed in cortical samples from three independent brain cohorts. This study represents, to the best of our knowledge, the first epigenome-wide association study of AD employing a sequential replication design across multiple tissues and highlights the power of this approach for identifying methylomic variation associated with complex disease.