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Proc Natl Acad Sci U S A. May 17, 2011; 108(20): 8189–8193.
Published online May 16, 2011. doi:  10.1073/pnas.1014129108
PMCID: PMC3100926
Social Sciences, Genetics

Role of mother's genes and environment in postpartum depression

Abstract

Most studies of human molecular genetics and social environment interactions on health have relied heavily on the classic diathesis-stress model that treats genetic variations and environments as being either “risky” or “protective.” The biological susceptibility model posits that some individuals have greater genetic reactivity to stress, leading to worse outcomes in poor environments, but better outcomes in rich environments. Using a nontruncated measure of a chronic environmental stressor—socioeconomic status—measured by education, and two polymorphisms (5-HTTLPR and STin2 VNTR) of the serotonin transporter gene (5-HTT), we find strong evidence that some women are genetically more reactive to the environment, resulting in a crossover of risks of postpartum depression for the most reactive groups. We discuss how our approach and findings provide a framework for understanding some of the confusion in the gene-environment interaction literature on stress, 5-HTT, and depression.

Keywords: fertility, gene–environment interplay

Studies of human molecular genetics and social environment interactions have increased dramatically during the past decade. In particular, several studies have examined the interaction between the serotonin transporter gene (5-HTT, SERT, SLC6A4; link ID, 6532; 17q11.1-q12) and stressful life events on depression, with mixed results (13). All these studies rely on the classic diathesis-stress model that treats genetic variations and environments as being either “risky” or “protective” (4). More recently, researchers have proposed a “genetic plasticity” or “biological susceptibility” model, which posits that some genotypes are highly susceptible to environmental influences (“orchids”), whereas others are not (“dandelions”) (47). This model suggests a possible crossover effect, with those with genetic susceptibility having more negative outcomes than those without genetic susceptibility when the environment is “unfavorable” and better outcomes when the environment is “favorable.”

We use this crossover model to examine depression in the first year after the birth of a child: postpartum depression (PPD). PPD is common in the United States [10–20%; (8, 9)]. Maternal depression has negative effects on mother's physical health, relationships, and parenting, which also influences her children's health and social outcomes (9, 10). We measure PPD by using the 12-month Diagnostic and Statistical Manual for Mental Disorders (DSM-IV) diagnosis of major depressive episodes from the Composite International Diagnostic Interview–Short Form (CIDI-SF), version 1.0 (11). The measure is a count of number of depressive symptoms ranging from 0 to 7, with a major depression episode defined as the experience of three or more symptoms during a 2-week or longer period of dysphoria or anhedonia. In general, PPD occurs in the first few months after the birth of the child, but it can occur from as early as 2 wk after birth and as late as 1 y after the birth (8, 9, 12). In our sample of 1,206 mothers, 17% reported PPD by using the CIDI-SF, which is well within the standard range (8).

Most studies of the interaction between genotype and environment on depression have focused on the existence of severe negative experiences (i.e., child abuse, loss of a job), rather than on a range of both positive and negative experiences or more stable environmental conditions [i.e., education, permanent income (15)]. Ongoing negative conditions may result in a chronically stressful environment, often defined as occurring when an individual's resources are threatened beyond his or her ability to guard against or recover from a loss of resources (13), and there is some evidence that interactions of stress and the 5-HTTLPR polymorphism are more consistent for chronic rather than acute stressors (3). In this article, socioeconomic status (SES) is the environmental measure and is primarily measured by education. SES is relatively stable, includes both positive and negative environmental conditions, and is associated with lifetime stress (14). Women of low SES have poorer coping styles, greater exposure to stress, and weaker social support, and are approximately twice as likely as those of high SES to have depression (1517). We present data on mothers’ education at the time of the child's birth in Fig. 1.

Fig. 1.
Distributions of 5-HTTLPR and STin2 polymorphisms, their combination, and education. Genotype frequencies after removing any rare alleles (i.e., X, XX for 5-HTTLPR and 9 or 14 for STin2). Fig. S1 stratifies the alleles by race. The distributions of alleles ...

Previous studies of gene–environment interaction (G×E) have focused on one polymorphism of the 5-HTT gene, specifically 5HTTLPR (13); yet other polymorphisms of the 5-HTT gene are also associated with mental health (e.g., STin2 VNTR, G56A, rs25531, and I425V) but have not been examined in the G×E framework (1822). Further, combinations of polymorphisms have not been examined, possibly limiting the range of biological susceptibility to environmental influence if one polymorphism does not sufficiently explain the variation in gene function. Thus, we use two well examined polymorphisms of the 5-HTT gene: (i) a functional polymorphism (5-HTTLPR) in the 5′ regulatory region and (ii) a 17-bp variable-number tandem repeat (VNTR) in the second intron region (called STin2 VNTR). For the 5-HTTLPR polymorphism, the most common alleles are the short (S) 14-repeat and long (L) 16-repeat of a 23-bp incomplete repeat, but other less common repeats are also found in various populations (1820). Compared with the L allele, the S allele of the 5-HTTLPR polymorphism has been shown to be associated with higher rates of mental health problems, including depression (1,3,1820). For the STin2 polymorphism, the two most common alleles are the 10 and 12 repeat. Compared with the 10-repeat allele, the 12-repeat allele has been shown to be associated with higher rates of mental health problems (1820) (Fig. 1).

The serotonergic system may be under particular stress during peripartum and postpartum periods as a result of reductions of tryptophan (a metabolite of serotonin), inducing increased rates of depression (23, 24). Two studies have found that both the 5-HTTLPR and STin2 polymorphisms of the 5-HTT gene are associated with variations in PPD (25, 26). However, both these studies measured PPD in the first several weeks after birth and no G×E effect was examined. We construct a measure of the count of the number of “vulnerable” or “reactive” alleles (i.e., S and 12) with the anticipation that a larger number of reactive alleles is associated with an increase in the effect of SES on depression. We hypothesize that multiple measures of the same gene will provide a more robust interaction between gene and environment on the phenotype, perhaps being a better measure of gene function (Fig. 1).

This study uses data from the Fragile Families and Child Wellbeing Study (FFCWS) (27). The FFCWS is based on a stratified, multistage, probability sample of children born in large US cities between February 1998 and September 2000, with an oversample of children born to unmarried parents (three quarters unwed, one quarter wed). Baseline interviews with mothers and fathers were conducted within 72 h of the child's birth, and subsequent interviews were conducted when the focal child was 1, 3, 5, and 9 y old. Saliva DNA samples were taken at the age-9 follow-up, by using the Oragene DNA sample collection kit (DNA Genotek). Genotypes for both 5-HTTLPR and STin2 were obtained by PCR followed by gel electrophoresis (details provided in SI Materials and Methods). Our current analytic sample uses data from seven cities for a total of 1,206 mothers. The population-based sampling strategy avoids many of the selection biases that accompany the clinical and convenience samples used thus far to study depression G×E effect. FFCWS also has more variable population characteristics in terms of maternal education and race/ethnicity than previous studies (Table S1). Because of the complex survey design of the FFCWS, we adjust the SEs to account for clustering by hospital and city (27). The full models control for race—to reduce the concern of population stratification—as well as other variables related to PPD measured at the birth of the child (mother's age; if married to the father; tobacco, alcohol, and drug use during pregnancy; if child had low birth weight; if father injured mother during pregnancy; safety of the neighborhood; amount of social support; if mother was an immigrant) (8, 15). To avoid collinearity problems with the intercept we standardize (i.e., mean-center) all environmental measures.

Results

Table S2 shows the results of the interactive effects of SES (years of education) and number of reactive 5-HTT alleles (S or 12) on mother's risk of depression in the first year after birth of a child. The main effect of SES should be interpreted as the effect of SES for those with zero reactive alleles (i.e., genotype 10.10/LL), and is insignificant. The main effect of genes—which can be interpreted as the effect of the number of reactive alleles when mothers’ SES is set at the mean—is also insignificant. The estimate for the interaction between the count of reactive 5-HTT alleles and SES is strong and significant. This coefficient can be interpreted as the added effect of SES for each additional reactive 5-HTT allele. For mothers with zero reactive alleles, SES has no significant effect on PPD but for mothers with three or four reactive alleles, SES has a significant negative effect on PPD. Whereas, in low SES situations, mothers with three or four alleles have higher PPD rates than other mothers, in high SES situations, their PPD risk is lower.

Our findings are consistent with previous work that shows that negative life events in combination with a reactive 5-HTT allele has a negative effect on depression (1, 3). We extend this work, however, by showing that the genetic effect changes direction when the environment becomes much more positive. In other words, whereas the S or 12 homozygotes are positively associated with PPD in unfavorable environments, they are negatively associated with PPD in favorable environments. As seen in Fig. 2, our finding provides some support for the biological susceptibility hypothesis in that the orchids (i.e., dashed line, three or four alleles) are the most responsive to the environment, whereas the dandelions (solid line, zero or one alleles) appear uninfluenced by the environment, at least with respect to PPD (5, 6).

Fig. 2.
Probability of PPD across SES by the number of reactive 5-HTT alleles. G×E model does not constrain the SES to be related across allele types. For simplicity, we combine zero and one alleles into one group and three and four alleles into a second ...

It is also useful to consider the different 5-HTT alleles separately. We find that both 5-HTTLPR and STin2 have similar interactions with SES and the alleles for each polymorphism have additive effects. To do this, we decompose the base model into two models (i.e., 5-HTTLPR × SES and STin2 × SES) and we do not constrain the alleles to have additive effects. Results of the two decomposition models (Table S3 and Fig. 3) are informative and parallel our base model. For 5-HTTLPR, both the L homozygotes and LS heterozygotes have similar levels of PPD and only a slight, insignificant, and negative effect of education for both groups. However, the S homozygotes start with much higher levels of PPD at low educational attainment, but quickly decrease so that for those S homozygotes with college degrees the rate of PPD is very close to 5%. The results of the STin2 are similar in that the reactive 12/12 homozygotes appear to have a strong interaction with SES—whereby education significantly decreases PPD for that genotype. The less reactive 10/12 and 10/10 genotypes have no significant effect of SES on PPD.

Fig. 3.
Probability of PPD across education by the two polymorphisms of the 5-HTT gene. Decomposes the G×E effects related to the two 5-HTT polymorphisms. (A) People with a homozygote S genotype in the 5-HTTLPR polymorphism have a 12% decrease in PPD ...

Another issue with the genetic coding is that we excluded rare alleles such as the extra-long allele (X) in 5-HTTLPR and the nine-repeat allele in STin2 as a result of their rarity in the population. Table S4 shows that, when the X allele is treated as an L allele (5-HTTLPR) and the nine-repeat allele as a 10-repeat allele (STin2), the results are consistent with the base model. Table S4 also provides a brief examination of synthetic haplotypes that is consistent with the base model's conclusions.

We examined the linearity assumption of SES by allowing SES to have a quadratic effect on PPD. Fig. S2 shows that the assumption of a linear effect of education appears reasonable. We also examined the interaction of 5-HTT and current income, which is another common measure of SES (28). Results in Table S5 suggest that, although current income does interact with 5-HTT (at least for 5-HTTLPR), it is only borderline significant. Of course, household income is not just a characteristic of the mother and may be lower or more variable in the years surrounding a birth than in other years. A more permanent indicator of income (multiple years or asset wealth) might be a better measure of ongoing economic security (28). However, another indicator of SES is the circumstances of the mothers’ families of origin. Grandparent education (or mother's parents’ education) was available. The interaction between mother's 5-HTT genotype and her family-of-origin parental education was significant (the correlation, r, between mother's education and her parent's education was 0.40). It is possible that SES may be constantly interacting with genes to promote depression—or, in this case, PPD (29). It is also possible that earlier life SES modifies genetic expression, thus changing mothers’ depression levels for the rest of her life (30). When we include measures of both mother's education and grandparent's education, the coefficient for the mother's education does not change, suggesting that the interaction is primarily a result of the mother's own SES and not solely of SES in the family of origin (Table S6). This suggests that the heritable part of SES (and thus the genetic markers associated with such heritability) is not the dominant source of the observed interactions. As SES is strongly correlated across generations, a further possible concern is that the 5-HTT gene influences SES (i.e., G×E correlation). For these particular polymorphisms, however, we see little evidence of a correlation with SES (via education or income; Table S7).

We also tested the model by the race/ethnicity of the mother. We ran separate models for white, black, and Hispanic subjects (Table S8), and the findings were descriptively similar across groups.

Discussion

The present study is unique in that the environmental condition examined included both negative (e.g., less than high school education) and positive (e.g., college degree) indicators. In addition, the more negative environmental condition (i.e., low education) is not a low-frequency event, as are the conditions measured in previous studies. Our results may suggest an explanation for the failure in some studies to replicate the G×E interaction for depression. Depending on sample composition, especially if the distribution of environmental conditions is truncated, a study might have been examining a G×E interaction in only one part of the distribution (1, 3). If the sample were disadvantaged, an interaction might have been observed for negative events. If the sample were primarily drawn from the middle of the distribution, an interaction would not be revealed. Of fundamental significance to future studies, collapsing the middle and the high end of the environmental distribution would result in a masking of the positive associations of gene reactivity and a high resource environment.

In contrast to previous studies, we examined two polymorphisms of the 5-HTT gene. Our findings were strongest when both were included in the model. It is possible that inclusion of additional polymorphisms of 5-HTT, as well as other genes related to the serotonergic system, would make the interaction even more pronounced (in part because of better measurement of genetic reactivity). This may be particularly true for alleles that may modify other genetic polymorphic effects, such as the possible effect of rs25531 on the L allele of 5-HTTLPR (22). Interestingly, the framework of biological susceptibility to environmental influence provides a clear and concise method for integrating multiple polymorphisms of many genes, without including multiple interaction terms (7).

More work is needed to elucidate the biological mechanisms for the observed interaction. The function of the 5-HTTLPR polymorphism has been subject to considerable research, but less is known about the STin2 polymorphism (13). As the 5-HTTLPR is GC-rich and is in the promoter-enhancer region of the 5-HTT gene, it is possible that epigenetic signals play some part in the emergence of the interaction and social signal transduction might act differentially on the polymorphisms of this gene (29, 30). However, STin2 is found in the second intron region and therefore has a less clear pathway to interact with the environment, although this polymorphism has been reported to affect transcriptional activity of the 5-HTT gene (31).

In conclusion, we find evidence of significant gene-environment interplay between both polymorphisms (5-HTTLPR and STin2 VNTR) of the serotonin transporter gene (5-HTT) and SES on depression in the first year after the birth of the child. More crucially, we find evidence that some people are genetically more or less reactive to the environment, resulting in a crossover of risks of PPD for the most reactive groups.

Materials and Methods

We used data gathered during three waves of the FFCWS. This study follows a cohort of 4,898 children born in 20 large US cities between 1998 and 2000. The study interviewed parents at the time of the child's birth and again at 1 y, 3 y, 5 y, and 9 y after the birth. Our analyses are based on the subset of the 4,898 mothers who: (i) responded to the wave 2 (age 1 y) CIDI-SF (n = 4,362; 89% retention rate), (ii) provided usable saliva during wave 5 (age 9 y; n = 2,591; 81% of eligible wave 5 participants), and (iii) were living in the seven of the 20 cities where DNA genotyping was completed (n = 2,327). This leaves us with an analytic sample of 1,206 mothers. Attrition rates were higher among nonwhite subjects, and respondents with lower SES (32). We obtained the saliva sample from the mothers using the Oragene DNA collection kit (DNA Genotek) during the wave 5 (age 9 y) in-home interview (June 2007 to April 2010). Samples were retained at room temperature until DNA extraction (at the laboratory of D.N., Princeton University, Princeton, NJ) according to the protocol supplied by the manufacturer. Following extraction, DNA was quantified and evaluated for quality by measuring UV absorption at 260 and 280 nm.

Our outcome, PPD, comes from the 12-month DSM-IV diagnosis of major depressive episodes from the CIDI-SF, version 1.0 (11). Mothers were asked if, at some time during the past year (in this case in the first year after birth), they had feelings of depression or were unable to enjoy things that were normally pleasurable. Those who indicated experiencing one of these two conditions for at least a 2-week period were asked additional questions (regarding, e.g., losing interest in things, feeling tired, experiencing a change in weight of at least 10 pounds, having trouble sleeping, having trouble concentrating, feeling worthless, or thinking about death), and those who responded affirmatively to three or more of these questions were coded as 1 or 0, with 1 representing someone who experienced a major depressive episode during the first year postpartum (i.e., had PPD), and 0 representing someone who did not have PPD. Although limitations to the CIDI-SF exist, most researchers confirm that it is a reliable measurement tool to diagnose depression (33).

There are some considerations in our use of the CIDI-SF depression measure. First, it is measured by using a series of questions designed to measure major depression broadly and not specifically PPD. Thus, instead of treating PPD like its own distinct mental illness, we treated it as a subset of depression. Other studies of PPD have found the Edinburgh Postnatal Depression Scale (EPDS) to be better validated for PPD (34). Also, the EPDS measure is more continuous, thus allowing for greater variance and greater detection of interactions. Future G×E PPD research should improve the measurement of PPD—possibly by using the EPDS—which may result in better estimates of the G×E effect. Second, the CIDI-SF measure may conflate PPD with non–childbearing-related depression within the first year after birth. Third, because PPD often occurs in the first 2 to 3 mo after having the child, women may fail to recall the depressive episode several months later. Nevertheless, it is important to note that our sample estimates of PPD are within the expected range. Also, considering some studies have found PPD to occur as late as 1 y, more short-term studies of PPD would miss the late occurrences of PPD (12).

Mothers’ DNA samples were analyzed for the 5-HTTLPR length polymorphism by PCR followed by gel electrophoresis to distinguish the short (14-repeat, a 375-bp fragment,) and long (16-repeat, a 419-bp fragment) allele forms. Much less frequently occurring (<1% of the sample) longer alleles [20 repeats (×) and 28 repeats (××)] were removed from the main analysis of the sample. Additional tests including these rare, longer alleles were conducted (Table S4). PCR was performed with the following primers: forward, 5′-ATG CCA GCA CCT AAC CCCT AAT GT-3′; reverse, 5′-GGA CCG CAA GGT GGG CGG GA-3′. PCR was carried out on a PTC-225 DNA engine (MJ Research), using the following cycling conditions: 2-min denaturing step at 95 °C, followed by 35 cycles of 94 °C for 30 s, 66 °C for 30 s, and 72 °C for 40 s, and a final extension phase of 72 °C for 5 min. Reactions were performed in 10× PCR Buffer (Denville Scientific), containing 15 mM MgCl2, 500 ng of genomic DNA, 5 pmol of each primer, 0.3 mM dNTPs, and 1 U Taq polymerase (Denville Scientific). PCR products were separated on a 2.0% agarose gel (Denville Scientific) supplemented with ethidium bromide (0.03%) and visualized by UV illumination.

The STin 2 VNTR polymorphism is a 17-bp VNTR in the intron 2 region of the 5-HTT gene. The two main alleles of the STin2 are the 10 repeats and 12 repeats (31, 35). We again used PCR followed by gel electrophoresis to distinguish between repeats. Forward primer was 5′-GTC AGT ATC ACA GGC TGC GAG -3′; reverse primer was 5′-TGT TCC TAG TCT TAC GCC AGT G-3′. PCR was carried out on a PTC-225 DNA engine (MJ Research) with the following cycling conditions: 2-min denaturing step at 95 °C, followed by 32 cycles of 95 °C for 30 s, 63.2 °C for 30 s (with touch-down −0.1 °C) and 72 °C for 30 s, and a final extension phase of 72 °C for 5 min. Reactions were performed in 10× PCR Buffer (Denville Scientific), containing 15 mM MgCl2, 500 ng of genomic DNA, 5 pmol of each primer, 0.3 mM dNTPs, and 1 UTaq polymerase (Denville Scientific). PCR products were separated on a 2. 0% agarose gel (Denville Scientific) supplemented with ethidium bromide (0.03%) and visualized by UV illumination. Fifteen mothers had the rare 9 repeat and were excluded from the sample for the main analyses, but included in subsequent examinations (Table S4).

SI Materials and Methods provides additional details of study methods.

Supplementary Material

Supporting Information:

Acknowledgments

This study was supported by Eunice Kennedy Shriver National Institute of Child Health and Human Development Grants R01HD36916, R01HD39135, and R01HD40421, as well as a consortium of private foundations that supported the Fragile Families and Child Wellbeing Study.

Footnotes

The authors declare no conflict of interest.

*This Direct Submission article had a prearranged editor.

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1014129108/-/DCSupplemental.

References

1. Caspi A, Hariri AR, Holmes A, Uher R, Moffitt TE. Genetic sensitivity to the environment: The case of the serotonin transporter gene and its implications for studying complex diseases and traits. Am J Psychiatry. 2010;167:509–527. [PMC free article] [PubMed]
2. Risch N, et al. Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: A meta-analysis. JAMA. 2009;301:2462–2471. [PMC free article] [PubMed]
3. Karg K, Burmeister M, Shedden K, Sen S. The serotonin transporter variant (5-HTTLPR), stress, and depression meta-analysis revisited: evidence of genetic moderation. Arch Gen Psychiatry. 2011 10.1001/archgenpsychiatry.2010.189. [PMC free article] [PubMed]
4. Belsky J, Pluess M. Beyond diathesis stress: Differential susceptibility to environmental influences. Psychol Bull. 2009;135:885–908. [PubMed]
5. Boyce WT, Ellis BJ. Biological sensitivity to context: I. An evolutionary-developmental theory of the origins and functions of stress reactivity. Dev Psychopathol. 2005;17:271–301. [PubMed]
6. Ellis BJ, Boyce WT. Biological sensitivity to context. Curr Dir Psychol Sci. 2008;17:183–187.
7. Belsky J, et al. Vulnerability genes or plasticity genes? Mol Psychiatry. 2009;14:746–754. [PMC free article] [PubMed]
8. O'Hara MW, Swain AM. Rates and risks of postpartum depression – a meta analysis. Int Rev Psychiatry. 1996;8:37–54.
9. Kendall-Tackett KA. Depression in New Mothers: Causes, Consequences and Treatment Alternatives. Binghamton, NY: Haworth Press; 2005.
10. Kiernan KE, Mensah FK. Poverty, maternal depression, family status and children's cognitive and behavioural development in early childhood: A longitudinal study. J Soc Policy. 2009;38:569–588.
11. Kessler RC, Andrew G, Mroczek D, Ustun TB, Wittchen HU. The world health organization composite international diagnostic interview short form (CIDI-SF) Int J Methods Psychiatr Res. 1998;7:171–185.
12. Paulson JF, Bazemore SD. Prenatal and postpartum depression in fathers and its association with maternal depression: A meta-analysis. JAMA. 2010;303:1961–1969. [PubMed]
13. Hobfoll SE. Conservation of resources. A new attempt at conceptualizing stress. Am Psychol. 1989;44:513–524. [PubMed]
14. Adler NE, Newman K. Socioeconomic disparities in health: Pathways and policies. Health Aff (Millwood) 2002;21:60–76. [PubMed]
15. Beck CT. Predictors of postpartum depression: An update. Nurs Res. 2001;50:275–285. [PubMed]
16. Lorant V, et al. Socioeconomic inequalities in depression: A meta-analysis. Am J Epidemiol. 2003;157:98–112. [PubMed]
17. Goyal D, Gay C, Lee KA. How much does low socioeconomic status increase the risk of prenatal and postpartum depressive symptoms in first-time mothers? Womens Health Issues. 2010;20:96–104. [PMC free article] [PubMed]
18. Fan JB, Sklar P. Meta-analysis reveals association between serotonin transporter gene STin2 VNTR polymorphism and schizophrenia. Mol Psychiatry. 2005;10:928–938, 891. [PubMed]
19. Li D, He L. Meta-analysis supports association between serotonin transporter (5-HTT) and suicidal behavior. Mol Psychiatry. 2007;12:47–54. [PubMed]
20. Kohen R, et al. Association of serotonin transporter gene polymorphisms with poststroke depression. Arch Gen Psychiatry. 2008;65:1296–1302. [PMC free article] [PubMed]
21. Praschak-Rieder N, et al. Novel 5-HTTLPR allele associates with higher serotonin transporter binding in putamen: A [(11)C] DASB positron emission tomography study. Biol Psychiatry. 2007;62:327–331. [PubMed]
22. Delorme R, et al. Support for the association between the rare functional variant I425V of the serotonin transporter gene and susceptibility to obsessive compulsive disorder. Mol Psychiatry. 2005;10:1059–1061. [PMC free article] [PubMed]
23. Baïlara KM, et al. Decreased brain tryptophan availability as a partial determinant of post-partum blues. Psychoneuroendocrinology. 2006;31:407–413. [PubMed]
24. Maes M, Ombelet W, Verkerk R, Bosmans E, Scharpé S. Effects of pregnancy and delivery on the availability of plasma tryptophan to the brain: Relationships to delivery-induced immune activation and early post-partum anxiety and depression. Psychol Med. 2001;31:847–858. [PubMed]
25. Sanjuan J, et al. Mood changes after delivery: Role of the serotonin transporter gene. Br J Psychiatry. 2008;193:383–388. [PubMed]
26. Doornbos B, et al. The development of peripartum depressive symptoms is associated with gene polymorphisms of MAOA, 5-HTT and COMT. Prog Neuropsychopharmacol Biol Psychiatry. 2009;33:1250–1254. [PubMed]
27. Reichman NE, Teitler JO, Garfinkel I, McLanahan SS. Fragile families: Sample and design. Child Youth Serv. 2001;23:303–326.
28. Blau P, Duncan OD. The American Occupational Structure. New York: Wiley; 1967.
29. Cole SW. Social regulation of human gene expression. Curr Dir Psychol Sci. 2009;18:132–137. [PMC free article] [PubMed]
30. Miller GE, et al. Low early-life social class leaves a biological residue manifested by decreased glucocorticoid and increased proinflammatory signaling. Proc Natl Acad Sci USA. 2009;106:14716–14721. [PMC free article] [PubMed]
31. MacKenzie A, Quinn J. A serotonin transporter gene intron 2 polymorphic region, correlated with affective disorders, has allele-dependent differential enhancer-like properties in the mouse embryo. Proc Natl Acad Sci USA. 1999;96:15251–15255. [PMC free article] [PubMed]
32. Cooper CE, McLanahan SS, Meadows SO, Brooks-Gunn J. Family structure transitions and maternal parenting stress. J Marriage Fam. 2009;71:558–574. [PMC free article] [PubMed]
33. Aalto-Setälä TL, et al. Major depressive episode among young adults: CIDI-SF versus SCAN consensus diagnoses. Psychol Med. 2002;32:1309–1314. [PubMed]
34. Cox JL, Holden JM, Sagovsky R. Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale. Br J Psychiatry. 1987;150:782–786. [PubMed]
35. Hranilovic D, et al. Serotonin transporter promoter and intron 2 polymorphisms: Relationship between allelic variants and gene expression. Biol Psychiatry. 2004;55:1090–1094. [PubMed]

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