| Literature DB >> 25115650 |
Alison G Paquette1, Barry M Lester2, Devin C Koestler3, Corina Lesseur1, David A Armstrong1, Carmen J Marsit4.
Abstract
Adverse maternal environments can lead to increased fetal exposure to maternal cortisol, which can cause infant neurobehavioral deficits. The placenta regulates fetal cortisol exposure and response, and placental DNA methylation can influence this function. FK506 binding protein (FKBP5) is a negative regulator of cortisol response, FKBP5 methylation has been linked to brain morphology and mental disorder risk, and genetic variation of FKBP5 was associated with post-traumatic stress disorder in adults. We hypothesized that placental FKBP5 methylation and genetic variation contribute to gene expression control, and are associated with infant neurodevelopmental outcomes assessed using the Neonatal Intensive Care Unit (NICU) Network Neurobehavioral Scales (NNNS). In 509 infants enrolled in the Rhode Island Child Health Study, placental FKBP5 methylation was measured at intron 7 using quantitative bisulfite pyrosequencing. Placental FKBP5 mRNA was measured in a subset of 61 infants by quantitative PCR, and the SNP rs1360780 was genotyped using a quantitative allelic discrimination assay. Relationships between methylation, expression and NNNS scores were examined using linear models adjusted for confounding variables, then logistic models were created to determine the influence of methylation on membership in high risk groups of infants. FKBP5 methylation was negatively associated with expression (P = 0.08, r = -0.22); infants with the TT genotype had higher expression than individuals with CC and CT genotypes (P = 0.06), and those with CC genotype displayed a negative relationship between methylation and expression (P = 0.06, r = -0.43). Infants in the highest quartile of FKBP5 methylation had increased risk of NNNS high arousal compared to infants in the lowest quartile (OR 2.22, CI 1.07-4.61). TT genotype infants had increased odds of high NNNS stress abstinence (OR 1.98, CI 0.92-4.26). Placental FKBP5 methylation reduces expression in a genotype specific fashion, and genetic variation supersedes this effect. These genetic and epigenetic differences in expression may alter the placenta's ability to modulate cortisol response and exposure, leading to altered neurobehavioral outcomes.Entities:
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Year: 2014 PMID: 25115650 PMCID: PMC4130612 DOI: 10.1371/journal.pone.0104913
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Infant Clinical and Demographic Information and relation to FKBP5 methylation.
| N | % | Mean | Std Dev. | Mean | P | |
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| 509 | 29.32 | 5.53 | |||
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| Yes | 22 | 4.3 | 87.89 | |||
| No | 481 | 94.5 | 87.12 | |||
| NA | 6 | 1.2 | ||||
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| 509 | 39.01 | 0.95 | 0.32 | ||
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| LGA | 132 | 25.9 | 86.74 | |||
| AGA | 275 | 54 | 87.06 | |||
| SGA | 102 | 20 | 87.9 | |||
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| Female | 258 | 50.7 | 86.82 | |||
| Male | 251 | 49.3 | 87.47 | |||
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| CC | 231 | 45.4 | 86.9 | |||
| CT | 235 | 46.2 | 87.11 | |||
| TT | 35 | 6.9 | 88.25 | |||
| NA | 8 | 1.6 | ||||
Figure 1Methylation and Genotype are associated with FKBP5 Expression.
Gene expression results were quantified in a subset (N = 61) of all placentas sequenced A.Gene expression as quantified as FKBP5/SDHA counts stratified by genotype, divided by the mean value of the average of the CC group (P = 0.07, ANOVA, Tukey test CT vs. CC, P = 0.53. CC vs TT P = 0.41, TT vs CT P = 0.05) B. Correlation of FKBP5/SDHA counts vs. FKBP5 Intron 7 Methylation (r = −0.22, P = 0.08). C–E. Correlation of FKBP5/SHDA counts vs. FKBP5 Intron 7 methylation stratified by genotype.*P≤0.1 ** = P≤0.05.
Linear regression model of FKBP5 methylation, rs1360780 Genotype and NNNS outcomes.
| Unadjusted | Adjusted | |||||
| Estimate | Std.Error |
| Estimate | Std.Error |
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| Methylation | −0.03 | 0.02 | 0.21 | −0.04 | 0.02 | 0.12 |
| CC |
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| CT | 0.24 | 0.17 | 0.15 | 0.23 | 0.17 | 0.18 |
| TT | 0.55 | 0.33 | 0.10 | 0.64 | 0.33 | 0.05 |
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| Methylation | 0.01 | 0.02 | 0.43 | 0.01 | 0.02 | 0.44 |
| CC |
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| CT | 0.06 | 0.13 | 0.64 | 0.04 | 0.13 | 0.78 |
| TT | 0.34 | 0.25 | 0.18 | 0.37 | 0.26 | 0.16 |
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| Methylation | 0.00 | 0.00 | 0.55 | 0.00 | 0.00 | 0.53 |
| CC |
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| CT | 0.03 | 0.02 | 0.16 | 0.03 | 0.02 | 0.15 |
| TT | 0.04 | 0.04 | 0.41 | 0.03 | 0.04 | 0.45 |
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| Methylation | 0.00 | 0.01 | 0.73 | 0.00 | 0.01 | 0.60 |
| CC |
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| CT | −0.01 | 0.06 | 0.81 | −0.01 | 0.06 | 0.91 |
| TT | −0.16 | 0.12 | 0.18 | −0.15 | 0.12 | 0.21 |
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| Methylation | 0.02 | 0.01 | 0.03 |
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| CC |
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| CT | −0.02 | 0.07 | 0.81 | −0.01 | 0.07 | 0.84 |
| TT | 0.17 | 0.15 | 0.23 | 0.15 | 0.14 | 0.29 |
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| Methylation | 0.00 | 0.00 | 0.17 | 0.00 | 0.00 | 0.19 |
| CC |
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| CT | 0.00 | 0.01 | 0.83 | 0.00 | 0.01 | 0.75 |
| TT | 0.03 | 0.01 | 0.03 |
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*Also adjusted for birth weight group, maternal age, gender and random effect of conversion plate.
Logistic regression model of FKBP5 methylation quartiles and 95th percentile arousal and stress abstinence scores.
| Arousal>5.14 | Stress Abstinence>0.2 | ||||||||||
| N (%) lowArousal | N (%) high Arousal | Unadjusted (OR, CI) | Adjusted (OR, CI) | N (%) low Stress Abstinence | N (%) high Stress Abstinence | Unadjusted (OR, CI) | Adjusted (OR, CI) | ||||
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| 1st Quartile | 112 (88) | 15 (12) |
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| 88 (69) | 39 (31) |
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| 2st Quartile | 105 (83) | 22 (17) | 1.57(0.77, 3.19) | 1.46 (0.71, 3.03) | 74 (58) | 53 (42) | 1.63 (0.95, 2.79) | 1.62(0.94,2.8) | |||
| 3st Quartile | 106 (83) | 21 (17) | 1.48(0.72, 3.03) | 1.52 (0.73,3.19) | 73 (57) | 54 (43) | 1.41 (0.82, 2.44) | 1.34 (0.77, 2.33) | |||
| 4st Quartile | 103 (80) | 25 (20) | 1.83 (0.91, 3.68) | 2.22(1.07,4.61) | 79 (62) | 49 (38) | 1.23 (0.71,2.13) | 1.23(0.7, 2.17) | |||
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| AGA | 231 (84) | 44 (16) |
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| 173 (63) | 102 (37) |
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| LGA | 102 (77) | 30 (23) | 1.57(0.93, 2.64) | 1.76 (1.01,3.04) | 88 (67) | 44 (33) | 1.06 (0.67,1.69) | 1.05 (0.65,1.69) | |||
| SGA | 93 (91) | 9 (9) | 0.5 (0.23, 1.07) | 0.44(0.2,0.96) | 53 (52) | 49 (48) | 1.23 (0.76, 2.01) | 1.17 (0.71, 1.94) | |||
| Maternal Age | 1 (0.96, 1.04) | 0.98 (0.94, 1.03) | 0.98 (0.94,1.01) | 0.97 (0.94,1.01) | |||||||
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| CC | 193 (84) | 38 (16) |
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| 149 (65) | 82 (35) |
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| CT | 199 (85) | 36 (15) | 0.92 (0.56, 1.51) | 0.93 (0.55, 1.55) | 143 (61) | 92 (39) | 1.08(0.72, 1.62) | 1.1 (0.73, 1.65) | |||
| TT | 28 (80) | 7 (20) | 1.27 (0.52, 3.12) | 1.2 (0.46, 3.11) | 17 (49) | 18 (51) | 2.01(0.95, 4.26) | 1.98(0.92,4.26) | |||
| Female | 207 (80) | 51 (20) |
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| 152 (59) | 106 (41) |
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| Male | 219 (87) | 32 (13) | 0.59 (0.37, 0.96) | 0.52 (0.31, 0.85) | 162 (65) | 89 (35) | 0.81 (0.55, 1.18) | 0.77 (0.52, 1.14) | |||