An overview of DNA methylation for population based research and a few new data resources for conducting analyses.

1. An introduction to population based
data for studies of DNA methylation
Stanford Center for Population Health Sciences
Seminar Series
March 22, 2019
David Rehkopf
Associate Professor
Stanford University School of Medicine

2. Six Questions addressed in this talk
1) What is DNA methylation?
2) What are the suspected causes and consequences
of DNA methylation?
3) Why might population health scientists be
interested in studying DNA methylation?
4) What are the standard approaches to analysis of
DNA methylation data?
5) What can epidemiology, demography and social
sciences contribute to understanding the role of
DNA methylation?
6) What population based datasets are currently
(2019) available for analysis of DNA methylation?

3. Q1. What is DNA methylation?

5. Methylation and the human genome
3,234,000,000 base pairs
CpG 28,000,000
[NB: 42% of genome is CG, .21*.21 is 4.4%]

9. Illumina EPIC
array
850,000 CpGs

11. Q2. What are the suspected causes
and consequences of DNA
methylation?

17. Q3. Why might population health
scientists be interested in studying
DNA methylation?

18. Reasons to study DNA methylation
1. Because it’s there
2. Prediction of future disease
3. Biological pathway from the
environment to disease
4. As an intermediate outcome to
disease and mortality

19. Q4. What are the standard approaches
to analysis of DNA methylation data?

20. Collaborators
Lisa McEwen Michael Kobor
Andres Cardenas Simone Ecker Nicole Gadish

21. Kilometers
0 50
NICARAGUA
PANAMA
CARIBBEAN
PACIFIC OCEAN
Nicoya
RR=.82
San Vito
RR=.66
NOTES: Each point is a voting location. Points are proportional to population size. Canton limits shown.

22. 1. CpG site specific regression

24. 2. Variability

25. 3. Summary methylation score

26. 26

28. Q5. What can epidemiology,
demography and social sciences
contribute to understanding the role of
DNA methylation?

29. Contributions to move the literature
forward
1) Generalizability, representative samples
2) Replication in multiple samples
3) Attention to identification strategies
4) Appropriate statistical mediation analysis

30. Q6. What population based datasets
are currently (2019) available for
analysis of DNA methylation?

31. Costa Rica (CRELES)
National Health and Nutrition
Examination Survey (NHANES)
Health and Retirement Study (HRS)
Danish National Birth Cohort (DBC)
Women’s Health Initiative (WHI)

32. Costa Rica (CRELES study)
n=500 (now) + 500 (late 2019)

33. Costa Rica (CRELES study)
Costa Rica Longevity and Health Aging Study
Probabilistic sample of adults age 60 and over selected
from the 2000 Census database
Different sampling fractions by age: 1941-1945: 1.1%, 1900
or earlier 100%
2 waves of data from 2005 and 2007
N=2827 total, 85% response rate, of those 95% blood
90 minute in person interview (24% proxy) collecting
individual and household data on social, economic,
functional status and health outcomes.
Blood draw (fasting next morning), urine and biomarker
assays.
Linked to national mortality database.

35. Life expectancy at age 80
0 2 4 6 8 10 12
Remaining years of life expectancy at age 80
Netherlands
Denmark
Finland
Norway
England & Wales
Sweden
Italy
Spain
Switzerland
France
United States
Iceland
Japan
Costa Rica
Sources: Human Mortality Data Base (HMD); CCP: http://ccp.ucr.ac.cr/observa/CRindicadores/TVcompletas.html
Males Females

36. Rosero Bixby and Dow PNAS 2015

37. Rosero Bixby and Dow PNAS 2015

38. NHANES 1999-2002 (n=2641) (late 2019)
MPI with Dr. Needham at U. Michigan
Large, nationally representative sample with
socioeconomic and racial/ethnic diversity
DNA methylation from 566 African-American, 898
Hispanic, 1,071 white, and 79 other race
individuals aged 50+ from NHANES 1999-2002.
Mortality follow-up
Links to Medicare claims data
Exact location data (RDC)

39. NHANES

42. Health and Retirement Study (n=4100)
(mid 2019)
Health and Retirement Study (1992 to present)
Longitudinal Panel data, nationally representative
Baseline survey 1992, age 50+ and spouses
New samples in 1998, 2004, 2010
Biological samples taken in 2006 and 2008
Over representation of non-whites in methylation
sample
Information on early life location and history of
residence since age 50.
Linked to mortality and medical claims data. 42

43. T1 T
2
Danish National Birth Cohort (n=78 x 2)
78 Danish women
DNAm (EPIC) from these women at two
time points
Meta data of moms and children during
and after pregnancy
– anthropometric measurements
– physical health
– mental health
– social economic status
Red = DNAm data
Blue = meta data

44. Women’s Health Initiative (n~2500)
MPI with Dr. Assimes

45. Other studies
~100ng of DNA ~$350

46. Costa Rica (CRELES)
National Health and Nutrition
Examination Survey (NHANES)
Health and Retirement Study (HRS)
Danish National Birth Cohort (DBC)
Women’s Health Initiative (WHI)

47. Thank you.
47
drehkopf@stanford.edu
@drehkopf
Funding:
NIA (K01 AG047280, R21 MD013296,
R01 HD091262, R01 MD011721)
CEDA, UC Berkeley (P30AG012839)
Canadian Institutes of Health Research