Prenatal Socioeconomic Position in Relation to Genome-wide DNA
Methylation
Golareh Agha, PhDHarvard School of Public Health
Department of Environmental Health
Disclosure: no conflicts of interest
Early life origins of cardiovascular risk
• Maternal famine
• Impaired fetal development
• Early life socioeconomic position
Cardiovascular risk factors and
disease
• Barker DJ, Winter PD, Osmond C, Margetts B, Simmonds SJ. Weight in infancy and death from ischaemic heart disease. Lancet. Sep 9 1989;2(8663):577-580
• Roseboom T, de Rooij S, Painter R. The Dutch famine and its long-term consequences for adult health. Early Hum Dev. Aug 2006;82(8):485-491
• Galobardes B, Smith GD, Lynch JW. Systematic review of the influence of childhood socioeconomic circumstances on risk for cardiovascular disease in adulthood. Ann Epidemiol. 2006;16(2):91-104.
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Early life origins of adiposity
• In utero exposure to famine
• Early life socioeconomic position
ADIPOSITYEpigenetic Mechanisms?
• Stein AD, Kahn HS, Rundle A, Zybert PA, van der Pal-de Bruin K, Lumey LH. Anthropometric measures in middle age after exposure to famine during gestation: evidence from the Dutch famine. Am J Clin Nutr. Mar 2007;85(3):869-876.
• Ravelli AC, van Der Meulen JH, Osmond C, Barker DJ, Bleker OP. Obesity at the age of 50 y in men and women exposed to famine prenatally. Am J Clin Nutr. Nov 1999;70(5):811-816.
• Senese LC, Almeida ND, Fath AK, Smith BT, Loucks EB. Associations between childhood socioeconomic position and adulthood obesity. Epidemiologic reviews. 2009;31:21-51.
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Epigenetics Mechanisms by which gene expression is regulated in our
bodies. DNA METHYLATION:
• Whereby the addition or removal of methyl group (CH3) to CpGdinucleotides in our DNA sequences leads to changes in gene expression
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• DNA methylation plays a major role during fetal development, where it orchestrates tissue-specific gene expression patterns that drive cellular differentiation in the developing organism
– differentiation in the developing organism
DNA methylation
http://epigenie.com/epigenetics/epigenetic-regulation/5
Early life exposures and DNA methylation
Animal studies Alterations of maternal diet (e.g. protein
restriction or high-fat feeding have led to: • DNA methylation changes in offspring (both globally
and in metabolic and appetite regulatory genes• Abnormalities in appetite regulation, development of
adiposity, insulin resistance
Human studies In utero exposure to famine associated with:
• DNA methylation changes in IGF2 gene and others• Increased BMI and waist circumference
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Objective
• To examine whether a comprehensive measure of socioeconomic position, assessed prenatally, is associated with DNA methylation profiles in adipose tissue and blood tissue in adulthood.
Early life socioeconomic disadvantage
Adulthood adiposity
DNA methylation profiles in
ADIPOSE? In BLOOD?
The Longitudinal Effects on Aging Perinatal(LEAP) Project
Originated from the Collaborative PerinatalProject (CPP)• ~60,000 pregnant women were recruited in 1958-
1965 across the US• Regular assessments on mothers and offspring
were performed until offspring age 7 years
For LEAP: Providence-born offspring of CPP participants were sampled• 400 participants enrolled
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In Utero Birth Age
1-4 Age 7 Age 44-50
• Gestational diabetes • Blood pressure• Smoking• Socio-economic index
• Birth weight• Fetal length• Placental
morphology
• Weight/ Height
• Cognitive function
• Parental bonding
• Blood pressure
• Weight/Height
• Cognitive function
• Parental SEP
• Subcutaneous adipose tissue/ blood tissue
• DEXA measures
• Carotid IMT• Lipids• CRP
Collaborative Perinatal Project (n=~60,000)
Assessments on Providence-born
offspring:LEAP (n=400)
The Longitudinal Effects on Aging Perinatal(LEAP) project
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MethodsStudy sample
• 106 participants (68 women, 38 men), aged 44-50 yrs
Prenatal socioeconomic Index (SEI) :• Assessed prenatally as a composite numerical score (range 0-10),
using a weighted percentile of both parents’ educational attainment, occupation, and income relative to the US population in 1965*
• Mean (range) in study sample: 4.5 (0.5-9.3)
Covariates of interest• Race - 72 white; 34 non-white• Current smoking - 40%• Maternal smoking: max # cigs/day during pregnancy –
mean(range) = 11 (0-50)
*Myrianthopoulos, N.C. and K.S. French, An application of the U.S. Bureau of the Census socioeconomic index to a large, diversified patient population. Soc Sci Med, 1968. 2(3): p. 283-99. 10
Methods
Tissue samples: Blood
• Peripheral blood leukocytes extracted from buffy coats Subcutaneous adipose tissue
• collected from the upper outer quadrant of the buttock
DNA methylation profiling: DNA extracted from adipose tissue samples and
peripheral blood buffy coats DNA bisulfite converted and analyzed using the
Infinium 450K array
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Statistical analysesEpigenome-wide (EWAS) analyses CpG-by-CpG analyses in combination with
omnibus tests for significance via permutation testing• Provide omnibus p-values for overall
association between prenatal SEI and genome-wide DNA methylation
EWAS analyses in blood also adjusted for blood cell type composition• Removes ‘confounding by cell type
composition’12
Statistical Analyses
Gene-specific analysesApplied selection criteria to select genes with DNA methylation levels most significantly related to prenatal SEI
“Top genes of interest”:Genes with ≥ 2 gene regions having a median CpG-specific nominal p value <0.001, with respect to association with prenatal SEI
Gene Region nCpG Signs medPvalKIF21A TSS200 1 + 3.13E-06TMEM114 3'UTR 1 - 3.78E-06ACPP TSS200 1 + 9.29E-06ECM2 5'UTR 1 - 1.60E-05PCYT1A 3'UTR 1 - 2.28E-05GIPC1 3'UTR 1 - 3.24E-05CLEC5A 1stExon 1 + 3.59E-05CLEC5A 5'UTR 1 + 3.59E-05PRR15L 3'UTR 1 + 3.70E-05C17orf49 3'UTR 1 - 4.53E-05MIR1259 Body 1 + 6.17E-05SNORD12BBody 1 + 6.17E-05ALDH4A1 3'UTR 1 - 6.31E-05ITM2C 3'UTR 1 + 6.46E-05DTX3 TSS1500 1 - 6.78E-05BCL2L1 3'UTR 1 - 7.35E-05ACY3 Body 1 + 7.47E-05
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Kyoto Encyclopedia of Genes and Genomes (KEGG)-defined biological pathway analyses Explored whether DNA methylation in certain
biological pathways may be important in relation to prenatal SEI• Do CpGs mapped to genes in particular a priori
defined biological pathways show differential methylation with respect to prenatal SEI?
Statistical Analyses
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tertile 1 tertile 2 tertile 3 P for trend
Women (N=68)White, no(%) 8 (40) 13 (68) 22 (81) 0.006Adulthood ducation, mean years (SD) 13.1 (2.2) 12.3 (2.1) 14.6 (2.6) 0.04Current smoker, no (%) 9 (47) 8 (42) 7 (26) 0.12BMI, mean kg/m2 (SD) 33.7 (8.1) 30.7 (8.1) 29.0 (7.6) 0.05Maternal pre-pregnancy BMI, mean kg/m2 (SD) 26.2(6.1) 24.5 (6.6) 21.9 (3.9) 0.02Maternal max # cigs/day, mean (SD) 9.0 (10.2) 13.8 (12.8) 10.6 (12.4) 0.66
Men (N=38)White, no(%) 8 (62) 9 (82) 8 (80) 0.29Education, mean years (SD) 12.2 (4.9) 11.9 (3.9) 14.9 (2.3) 0.11Current smoker, no (%) 6 (46) 6 (55) 0 (0) 0.03BMI, mean kg/m2 (SD) 33.5 (5.7) 32.8 (5.0) 30.9 (6.0) 0.29Maternal pre-pregnancy BMI, mean kg/m2 (SD) 24.7 (4.6) 22.2 (3.4) 22.4 (2.7) 0.16Maternal max # cigs/day, mean (SD) 10.1 (11.6) 9.5 (12.7) 8.4 (8.4) 0.72
Pooled (N=106)Women, no(%) 19 (59) 19 (63) 27 (73) 0.23White, no(%) 16 (50) 22 (73) 31 (81) 0.006Education, mean years (SD) 12.7 (3.5) 12.2 (2.9) 14.6 (2.5) 0.008Current smoker, no (%) 15 (47) 14 (47) 7 (19) 0.01BMI, mean kg/m2 (SD) 33.6 (7.2) 31.5 (7.1) 29.5 (7.2) 0.02Maternal pre-pregnancy BMI, mean kg/m2) 25.5 (5.4) 23.6 (5.7) 22.1 (3.6) 0.006Maternal max # cigs/day, mean (SD) 9.4 (10.6) 12.2 (12.7) 10.0 (11.4) 0.85
Descriptive Characteristics of LEAP Participants According to Tertiles of Prenatal Socioeconomic Index
Prenatal Socioeconomic Index
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Prenatal Socioeconomic Index in Relation to Adulthood Genome-wide DNA Methylation
ADIPOSE BLOODOmnibus p-values for
overall associationOmnibus p-values for
overall association based on minimum p-value test statistic
based on minimum p-value test statistic
Prenatal socioeconomic index
Women (N=68)Unadjusted 0.003 0.230Adjusted for race, current smoking 0.002 0.685Adjusted for race, maternal smoking 0.012 0.850
Men (N=38)Unadjusted 0.126 0.861Adjusted for race, current smoking 0.567 0.518Adjusted for race, maternal smoking 0.462 0.396
Pooled (N=106)Unadjusted 0.030 0.125Adjusted for race, sex, current smoking 0.459 0.176Adjusted for race, sex, maternal smoking 0.511 0.297
Gene and pathway analyses in adipose
AQP7 C19orf59 RAPGEF2CLEC1A RAPGEF2 CETPCLEC5A SLAMF8 TNFSF14
Encodes a pro-thrombotic and pro-inflammatory cytokine
Shown to play a crucial role in adipose tissue inflammatory response
Has been related to atherogenesis, obesity, metabolic disorder
Leukocyte transendothelialmigration Notch signaling pathway GnRH signaling pathway
PPAR signaling pathway Jak-STAT signaling pathway Chemokine signaling pathway
MAPK signaling pathway B cell receptor signaling pathway Insulin signaling pathway
Calcium signaling pathway B cell receptor signaling pathway
Cytokine-cytokine receptor interaction
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Prenatal socioeconomic index associated with DNA methylation profile in adipose tissue of women, but not men. • Findings in line with sex-specific associations observed
between early life adversity (e.g. famine, low SEP) and adulthood adiposity
Many significant genes and biological pathways related to immune and inflammatory responses• Obesity-related Adipose tissue inflammation
No associations observed in blood• Tissue-specificity is important in DNAm studies!
Conclusions; reflecting on the findings
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Literature – social stress and adversity is:• Associated with diseases involving both up-regulated
inflammatory response (e.g. atherosclerosis) and down-regulated immune function (greater susceptibility to viral infections)
• Occurs through a “pro-inflammatory/anti-antiviral” bodily response that involves inflammatory and immune-related genes
• Such stress responses experienced in early life can become ‘biologically programmed’ to persist across decades
• Can lead to inflammatory-related Cardiometabolicoutcomes, e.g. obesity
Potential Mechanisms?
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Strengths & LimitationsLimitations Small sample size (especially among men) DNA methylation measured at one time point in
adulthood Assessing visceral adipose tissue DNA methylation would
be most interesting
Strengths Comprehensive measure of early life prenatal
socioeconomic position, assessed prospectively at a time critical for epigenetic effects
Adipose tissue and blood DNA methylation assessed Comprehensive statistical analyses (permutation-based
EWAS, cell-mixture adjustment in blood)
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Acknowledgements• Brown University School of Public Health
– Dr. Eric B. Loucks– Dr. Charles B. Eaton– Dr. Karl T. Kelsey– Dr. Stephen L. Buka
• College of Public Health and Human Sciences, Oregon State University– Dr. E. Andrés Houseman
• Funding source: NIH/NIA grant 1RC2AG036666
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n = 1237 (88%) Eligible (i.e. exam 7 data available, met distance criteria)
n = 400 ENROLLED (77%) (i.e. did not refuse and able to schedule visit)
CPP (N~60,000) NEFS = Boston + PVD-born pptsof CPP (N~17,000)
n = 1098 (89%) Located
n = 796 (72%) Eligible for assessment (i.e. not too ill, distance confirmed to be within range
n = 522(66%) Contacted
N= 3,151 PVD-born, survived till age 7, eligible for adult FU (i.e. not adopted, deceased, had maternal race Black or White
Select all Blacks and random samples of Whites
Select a random sample of Blacks and Whites
Select all Blacks and random sample of Whites
n = 1400 LEAP Released Sample
SGA NGA LGA
316 had adequate samples, 68 refused, 16 had inadequate
biopsy specimens. Subsample of 108 selected, prioritizing
samples with adequate adipose tissue yield, and aiming to preserve the
oversampling for SGA/LGA and ace/ethnicity
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whole sample (n=400) Epigen Subsample (n=106)Women, n(%) 227 (57%) 68 (63%)Maternal age at pregnancy, mean (SD) 24.7 (6.4) 25.6 (7.0)Maternal pre-preg BMI, mean kg (SD) 23.2 (4.8) 23.4 (4.9)Maternal max # cigs/day during pregnancy, mean (SD) 10.5 (12.2) 11.2 (12.3)LGA, no (%) 81 (20.2) 21 (19.8)SGA, no (%) 93 (23.3) 30 (28.3)Current smoking, no (%) 146 (36.6) 36 (40.0)Ever smoking, no (%) 244 (61.6) 61 (57.6)< HS, no (%) 95 (24.2) 23 (21.9)BMI, mean Kg (SD) 30.3 (7.9) 31.4 (7.9)White, no (%) 251 (63.1) 72 (67.9)Prenatal SEI, mean (SD); range 4.5 (2.0); 0.5-9.3 4.6 (2.2); 0.5-9.3
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Linear Regression Analyses for Associations of Prenatal Socioeconomic Index with Adulthood Adiposity in the LEAP project
Women: Sex-, race-adjusted Multivariable-adjusted†
β (CI) β (CI)
Android fat mass* -1.56 (-2.5,-0.6) -1.62(-2.67,-0.59)
Android: gynoid fat ratio -0.03 (-0.04,-0.01) -0.02 (-0.04,-0.01)
Trunk:limb fat ratio* -0.03(-0.04,-0.02) -0.02 (-0.03,-0.01)
Men: Sex-, race-adjusted Multivariable-adjusted†
β (CI) β (CI)
Android fat mass* 0.02 (-1.16,1.19) -0.03 (-1.23,1.17)
Android: gynoid fat ratio 0.02 (0,0.03) 0.01 (0,0.03)
Trunk:limb fat ratio* 0.01 (0, 0.03) 0.01 (0,0.03)† Models adjusted for age and race, maternal: age, smoking, marital status, and pre-pregnancy BMI
*in order to satisfy assumptions of normal linear regression, the square root of android fat and trunk:limb fat ratio were used as analytic variables, so that the beta coefficients represent increase in square root (android fat mass) and square root (android:gynoid fat ratio) for every unit increase in socioeconomic index
Adjustment for blood cell mixture(Houseman et. al., BMC Bioinformatics 2012)
1) The effect of phenotype on distribution of leukocytes was estimated• Using DNA methylation measurements at 100 select DMRs as a
surrogate for leukocyte distribution• The coefficients of phenotype-methylation association
combined with reference mean methylation estimates measured from isolated leukocytes of specific cell type to obtain estimated associations between phenotype and percent composition of individual cell types.
2) Methylation values then adjusted for leukocyte composition • For each CpG, effects of leukocyte composition on chip-adjusted
average-beta DNA methylation were determined by a linear regression, and the linear effect subsequently subtracted from the corresponding beta values to obtain adjusted beta values
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Gene Symbo
AQP7 0.0005 - 0.0005 - 0.1119 .
ATP1A2 0.0009 .- 0.0706 .... 0.0161 . 0.0009 .- 0.1605 .... 0.2819 .
CETP 0.0009 -- 0.0007 .- 0.0064 . 0.0009 -- 0.4120 ... 0.0073 .
CLEC1A 0.0008 .- 0.3757 .. 0.0008 .- 0.3093 . 0.9801 .
CLEC5A 0.0000 + 0.0000 + 0.0602 .
COX7A1 0.0004 - 0.8133 .. 0.0128 . 0.0004 - 0.0008 .-
EVI2A 0.0008 + 0.1632 . 0.0160 . 0.0006 + 0.2450 .
KLHL38 0.0164 -. 0.0010 + 0.4924 .. 0.0519 ... 0.0008 -
MMRN2 0.0003 - 0.0188 .... 0.0104 .. 0.0003 - 0.2861 .........- 0.3316 .
MYL2 0.0006 - 0.3058 ... 0.0006 - 0.3835 ..
RAB13 0.0004 - 0.5365 ... 0.4328 .. 0.0004 - 0.2534 .
RAPGEF2 0.0008 - 0.0041 .. 0.0008 - 0.4207 .... 0.0111 .
SLAMF8 0.0005 + 0.1360 ... 0.0009 + 0.0005 + 0.1203 .. 0.9836 .
SLC38A4 0.0131 ..- 0.0162 . 0.0003 -.- 0.0005 - 0.2689 ... 0.9868 .
TNFSF14 0.0008 + 0.8994 . 0.0008 + 0.0155 . 0.6016 .
VAT1 0.3864 . 0.0006 + 0.5207 .... 0.4578 .. 0.1922 .. 0.0007 -
Adipose Tissue DNA Methylation in Top Genes Associated with Prenatal Socioeconomic Index in Women
Gene region-specific median p-value (direction of association for each CpG)b
5'UTR TSS1500 TSS200 1ST EXON BODY 3'UTR
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Sexual dimorphism in the ‘early life programming’ of adulthood adiposity?
There is sexual dimorphism in the expression of genes, in a tissue-specific manner
Evidence from Animal Models: Sex differences in genes associated with metabolic function
Studies show sex-specific function of the placenta• In mice: Maternal high-fat diet led to striking changes
in DNAm and gene expression of female placenta but not male (Gallou-Kabani et al., PLoS One 2010)
• In humans: complication of asthma during pregnancy led to sex differences in placental cytokine expression, growth factor pathways, and placental response to cortisol (Clifton, Placenta 2010)
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Adipose tissue is responsive to sex hormones Body composition is sexually dimorphic Body fat distribution is affected by differences
in sex hormones
Wells JC. Sexual dimorphism of body composition. Best practice & research. Clinical endocrinology & metabolism. Sep 2007;21(3):415-430.
Hassan M, Latif N, Yacoub M. Adipose tissue: friend or foe? Nat Rev Cardiol. Dec 2012;9(12):689-702.
Sexual dimorphism in the ‘early life programming’ of adulthood adiposity?
