Epigenetics and psychiatric illness Riccardo Marioni Chancellor’s Fellow Centre for Genomic and Experimental Medicine University of Edinburgh riccardo.marioni@ed.ac.uk Centre for Genomic & Experimental Medicine MRC Institute of Genetics & Molecular Medicine at the University of Edinburgh www.ed.ac.uk/cgem

Learning Objectives Describe DNA methylation, how it is measured, and how it varies by tissue type. Explain the analysis protocol for an epigenome-wide association study and interpret EWAS output. Recognise the strengths and weaknesses of various epigenetic clock measures and other biomarkers of ageing. Describe the difference between polygenic and polyepigenic prediction of quantitiative traits List the pros and cons of looking at blood-based epigenetic markers of brain-related traits.

Introduction to dna methylation

DNA Methylation An epigenetic mark Involved in gene regulation Occurs across the genome Addition of methyl group to C nucleotide (CpG) Changes over time Interested in the proportion of methylated DNA molecules at each CpG site

Technical details Bisulphite conversion of DNA Two chemistries Methylated locus C → C Non-methylated locus C → U → T Two chemistries 135,000 probes from Infinium I array One probe methylated locus, one for non-methylated 350,000 probes from Infinium II array One probe for both loci, different colours for meth/non-meth Bibikova et al. Genomics, 2011; 98(4): 288-295

Beta-values & M-values 2

Tissue Issue Cell composition … eosinophil DNA Molecule Host cell Methylated 1 Eosinophil Yes 2 Neutrophil No 3 … basophil monocyte neutrophil lymphocyte

Quality Control exclude samples with detection p-values <0.01 for <95% of probes exclude probes with detection p-values >0.01 in >5% of samples. Tend not to remove X and Y probes or cross-reactive or polymorphic probes.

Genetics Epigenetics Cognitive Function Health

Epigenome wide association studies (EWAS)

EWAS ~450,000 CpGs CpG ~ Trait + Age + Sex + WBCs + (1 | Technical Covariates) CpG ~ Trait + Age + Sex + WBCs + smoking + BMI + (1 | Technical Covariates) Cause and effect?

Smoking EWAS Zeilinger et al. Plos One 2013; 8(5): e63812

Smoking EWAS Joehanes*, Just,* Marioni* et al. Circ Card Gen 2016

Alcohol EWAS Methylation signatures built from LASSO regression in one cohort, used to predict heavy from non-drinkers in independent cohorts Liu,* Marioni* et al. Mol Psychiat 2016

BMI EWAS Dick et al. Three hits in blood 479 people, whole bld Replication in 339 people 2nd replication in 1,789 people Replication in adipose tissue (n=635) and skin (n=395) GEx for hits Three hits in blood One replicated in adipose tissue Inverse association with GEx Dick et al. Lancet 2014; 383(9933): 1990-98

BMI Mendelson*, Marioni* et al. PLoS Med 2017

EPIGENETIC CLOCK

Epigenetic Clock http://labs.genetics.ucla.edu/horvath/dnamage/

Methylation Age Elastic net regression on 450k probes Paper N subjects Tissue Chip N probes Correlation with age Hannum 656 19 - 101 Whole Blood Illumina 450k 71 0.96 Horvath 8,000 (from 82 datasets) Mean 43 51 types Illumina 27k and 450k 353 Elastic net regression on 450k probes Hannum et al. Molecular Cell 2013, 49(2): 359-367 Horvath Genome Biol 2013, 14(10): R115

Epigenetic age predicts all-cause mortality High Δage Low Δage High Δage Low Δage Marioni et al. Genome Biol 2015

Epigenetic clock and longevity Horvath et al. Aging, 2015; 7(5): 294-306

Other epigenetic clock correlates Obesity (specific to liver) Down Syndrome Alzheimer’s disease pathology HIV Frailty Prenatal and early life factors Horvath et al. PNAS 2014 Horvath et al. Aging Cell 2015 Levine et al. Aging 2015 Gross et al. Mol Cell 2016 Breitling et al Clin Epigenetics 2016 Simpkin et al. Hum Mol Gen 2016

Cognitive and physical fitness & the epigenetic clock Cross-sectional but not longitudinal associations gf Grip Strength FEV1 6m walk speed Marioni et al. Int J Epidemiol 2015

Other clocks: telomere length Lapham et al. Genetics 2015

Biological Clocks in Parallel Marioni et al. Int J Epidemiol 2016

Biological Clocks in Parallel Does the epigenetic clock correlate with telomere length? Do changes in the epigenetic clock associate with concurrent changes in telomere length? Do both biological clocks correlate with age independently? Do both biological clocks associate with mortality risk independently?

Polygenic and polyepigenic Prediction

EWAS/GWAS predictions of BMI Methylation and genetic profile scores created using EWAS/GWAS hits Scores then used as predictors of BMI in other cohorts Shah, Bonder, Marioni et al. AJHG, 2015

Models Model 1: trait ~ GWAS_score Model 2: trait ~ EWAS_score Model 3: trait ~ GWAS_score + EWAS_score Model 4: trait ~ GWAS_score * EWAS_score

Polygenic Scores GWAS from large discovery cohort or meta-analysis Use βs to create weighted score in independent cohort Genetic Score = β1*SNP1 + β2*SNP2 + ... SNP Beta SE P SNP1 β1 SE1 P1 SNP2 β2 SE2 P2 ....

Polygenic Scores SNP list Effect sizes Prediction cohort GIANT 2014 LBC Lifelines

Polygenic Scores EWAS Scores 9 CpGs in LBC (n=1,366) 5 CpGs in Lifelines (n=752) CpG list Effect sizes Prediction cohort Lifelines (n=5) Lifelines LBC LBC (n=9)

Cross cohort predictors

EWAS/GWAS height prediction

Epigenetic prediction of AD Evidence for a blood-based DNA methylation signature for AD Are there EWAS signals and epigenetic clock differences in those at high genetic risk of AD? APOE AD PGS Lunnon et al. Nature Neurosc 2014

Longitudinal modelling Novel genetic loci Are these SNPs eQTLs or methQTLs? Does expression or methylation at these sites change over time? Novel epigenetic loci Are these CpGs under genetic control? Are they linked to gene expression? Do they change with age? Do they correlate with changes in other markers of decline – brain atrophy or cognitive decline?

Lothian Birth Cohort 1936 (n=1,091) Exponential increase in AD risk over 8th decade Methylation at 70,73,76,79 MRI at 73,76,79 LCL expression at 70,76 WGS on all participants Telomeres at 70,73,76,79 Inflammasomics at 70 Lipidomics at 73

MethQTLs 57,070 cis hits 1,985 trans hits McRae et al. In preparation