1. Epigenetics and psychiatric illness
Riccardo Marioni
Chancellor’s Fellow
Centre for Genomic and Experimental Medicine
University of Edinburgh
Centre for Genomic & Experimental Medicine
MRC Institute of Genetics & Molecular Medicine
at the University of Edinburgh

2. 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.

3. Introduction to dna methylation

4. 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

5. 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):

6. Beta-values & M-values2

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

8. 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.

9. Genetics
Epigenetics
Cognitive Function
Health

10. Epigenome wide association studies (EWAS)

11. 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?

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

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

14. 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

15. 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):

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

17. EPIGENETIC CLOCK

18. Epigenetic Clock

19. Methylation Age Elastic net regression on 450k probes Paper N subjects
Tissue
Chip
N probes
Correlation with age
Hannum
656
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):
Horvath Genome Biol 2013, 14(10): R115

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

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

23. 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 Horvath et al. Aging Cell 2015
Levine et al. Aging Gross et al. Mol Cell 2016
Breitling et al Clin Epigenetics 2016 Simpkin et al. Hum Mol Gen 2016

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

25. Other clocks: telomere length
Lapham et al. Genetics 2015

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

27. 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?

28. Polygenic and polyepigenic Prediction

29. 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

30. 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

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

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

33. 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)

34. Cross cohort predictors

35. EWAS/GWAS height prediction

36. 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

37. 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?

38. 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

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