Conceived and designed the experiments: C. Kappen JMS. Performed the experiments: C. Kruger JM. Analyzed the data: C. Kruger C. Kappen. Contributed reagents/materials/analysis tools: JMS. Wrote the paper: C. Kappen. Designed the software used in analysis: JMS.
The authors have declared that no competing interests exist.
Unfavorable maternal diet during pregnancy can predispose the offspring to diseases later in life, such as hypertension, metabolic syndrome, and obesity. However, the molecular basis for this phenomenon of “developmental programming” is poorly understood. We have recently shown that a diet nutritionally optimized for pregnancy can nevertheless be harmful in the context of diabetic pregnancy in the mouse, associated with a high incidence of neural tube defects and intrauterine growth restriction. We hypothesized that placental abnormalities may contribute to impaired fetal growth in these pregnancies, and therefore investigated the role of maternal diet in the placenta. LabDiet 5015 diet was associated with reduced placental growth, commencing at midgestation, when compared to pregnancies in which the diabetic dam was fed LabDiet 5001 maintenance chow. Furthermore, by quantitative RT-PCR we identify 34 genes whose expression in placenta at midgestation is modulated by diet, diabetes, or both, establishing biomarkers for gene-environment interactions in the placenta. These results implicate maternal diet as an important factor in pregnancy complications and suggest that the early phases of placenta development could be a critical time window for developmental origins of adult disease.
Maternal diet has long been known to be a key determinant for pregnancy success. Both undernutrition and malnutrition are harmful to development of the conceptus, increasing risk for spontaneous abortions, congenital malformations, and intrauterine growth restriction
Unfavorable maternal diet, as reflected in abnormal birth weight, is believed to predispose the offspring to diseases later in life, such as hypertension, metabolic syndrome, and obesity
Indeed, as we reported previously, placental growth was also reduced in pregnancies affected by maternal hyperglycemia
In order to investigate the effects of maternal diet on the placenta in diabetic pregnancies, we used the well-established STZ-induced diabetes FVB mouse model
Placentas were isolated at various time points; the dissected material consisted of both embryo-derived and maternal portions. Only placentas were used that were associated with morphologically normal embryos. Wet weight was determined immediately after dissection. n = number of placenta samples. Error bars show standard deviations from the means. A: Comparison of placenta weights between control and diabetic pregnancies where all dams were fed chow diet. B: Comparison of placenta weights between control and diabetic pregnancies where all dams were fed breeder diet. C, D: Replotted data from A and B to facilitate comparison by diet. *: p<0.05; **: p<0.005; ***: p<0.0005. In diabetic dams fed chow diet, placenta weights were indistinguishable from controls by the end of pregnancy, while in diabetic dams fed breeder diet, placentas were consistently smaller than controls after midgestation.
When the dams were fed chow diet, differences between normal and diabetic placentas were observed at midgestation (E9.5, E10.5), and at the end of pregnancy (E18.5). Although statistically significant, the magnitude of weight differences was small: under 10% (recalculated to the normal weight average), and directions of change -i.e. increase/decrease- were not consistent between time points (
The breeder diet has little effect on placenta growth in normal pregnancies, although, compared to chow, significantly higher placental weights were observed at E9.5 (14.8% increased weight) and on E12.5 (13% increased weight) (
This conclusion is further supported when we consider placenta weights relative to maternal weight during pregnancy (
Pregnant females were weighed on the day the copulation plug was detected (E0.5), and before sacrifice. Weight gain was calculated as the difference between weight on E18.5 and E0.5. Bar diagrams depict means and standard deviations. A: On chow diet, diabetic dams gain less weight (p = 5.69x10−6 versus non-diabetic dams). B: On breeder diet, diabetic dams also gain less weight (p = 1.5x10−4 versus non-diabetic dams on breeder diet). C, D: Replotted data from A and B to facilitate comparison by diet. Differences between group means in C and D, respectively, are not statistically significant.
The relationship of placenta size to maternal weight is depicted in
For each pregnant dam, her weight at sacrifice (timepoints from E9.5 to E18.5) was plotted along the X-axis, and the weights of placentas associated with morphologically normal embryos from her pregnancy were plotted along the Y-axis. Polynomial distributions were fitted to the data for A: Control dams fed chow diet; B: Control dams fed breeder diet; C: Diabetic dams fed chow diet: and D: Diabetic dams fed breeder diet. E: Comparison of the polynomial curves shows that the distribution of placenta weights during the pregnancy is very similar for all groups, except for the group of diabetic dams that were fed breeder diet. F: Comparison of polynomial distributions when the data are plotted by day of placenta isolation. Again, the results for diabetic dams on breeder diet reveal a specific interaction between diet and diabetes on placenta growth.
We previously published that, under conditions of maternal diabetes, placental gene expression is dysregulated by E10.5, labyrinth and junctional layer are reduced, and spongiotrophoblast migration is aberrant
For each experimental group, gene expression levels were determined by quantitative real-time PCR (see
The results revealed multiple modes in which diet and diabetes affected gene expression in the placenta at E10.5:
Finally, the group comprised of
It is noteworthy that, even though the selection of genes investigated here was not random, almost all possible responses, based upon statistical significance of changes, were reflected in our data: with comparisons between 4 conditions, 16 response patterns are theoretically possible (see
Comparison | Chow vs. Breeder | Chow vs. Breeder | Normal vs. Diabetic | Normal vs. Diabetic | |
Condition | Normal | Diabetic | Chow | Breeder diet | |
Pattern # | Gene Names | ||||
1 | − | − | − | − | |
2 |
|
− | − | − | Usp24, Adamts6, Thbs2, Frem1 |
3 | − |
|
− | − | Csf2rb |
4 | − | − |
|
− | |
5 | − | − | − |
|
|
6 |
|
|
− | − | Tm9sf1, Ermp1, Ptgs2 |
7 | − |
|
|
− | Atoh8, Mpzl2, Pcsk5, Spink8, Tpbpb |
8 | − | − |
|
|
Lpl |
9 |
|
− | − |
|
Crct1, Mmp1a |
10 |
|
− |
|
− | Ptges2 |
11 | − |
|
− |
|
9130005N14R, Il17b, Thsd4 |
12 |
|
|
|
− | |
13 | − |
|
|
|
Tgfßi |
14 |
|
− |
|
|
Ankrd2, Pappa2, Pla2g5, Prl5a1, Slc6a4 |
15 |
|
|
− |
|
Kcnk2, Mmp13, Hpgd, Cyp1a1, |
16 |
|
|
|
|
Mmp15, Rassf4, Pfpl, Spi16 |
Comparisons were made for each gene between placentas from chow- and breeder diet-fed normal dams, between placentas from chow and breeder diet-fed diabetic dams, between placentas from normal and diabetic dams fed chow, and between placentas from normal and diabetic dams on breeder diet. Statistical significance by two-tailed t-test for any one comparison is indicated as "+" for comparisons where P is <0.05 (significant), and "−" for P>0.05 (not significant). The response pattern for each gene was determined by virtue of the distribution of significances in these 4 comparisons. vs. = versus.
This is also evident when the magnitude of changes is considered.
The “fold-change” results for each group and gene were clustered in Cluster 3 and plotted in TreeView as a heat map, with blue representing increased and yellow decreased expression, with black representing no change. The genes most indicative of exposure to diet or diabetes are highlighted by brackets (red for diabetes, black for diet). C: chow diet; B: breeder diet; CD: chow diet, diabetic; BD: breeder diet, diabetic.
We then attempted to determine the “strength” of effects of diet and diabetes on gene expression, and potential interactions of both conditions, by performing 2-factor ANOVA statistical tests. These revealed statistically significant interactions between both modalities for only a fraction (11 of 34 = 32.3%) of the genes (
Interaction | p-value | Diet | p-value | Diabetes | p-value | |
Gene name | ||||||
9130005N14R |
|
|
0.54 | 0.6800 | 10.24 | 0.0800 |
Adamts6 | 4.41 | 0.2591 |
|
|
0.59 | 0.6751 |
Ankrd2 |
|
|
0.22 | 0.7049 |
|
|
Atoh8 | 2.17 | 0.4048 | 12.28 | 0.0563 |
|
|
Crct1 | 8.99 | 0.0730 |
|
|
|
|
Csf2rb | 13.59 | 0.0790 | 6.50 | 0.2160 | 0.32 | 0.7790 |
Cyp1a1 |
|
|
0.26 | 0.6977 |
|
|
Ermp1 | 0.45 | 0.5561 |
|
|
1.88 | 0.2470 |
Frem1 | 0.36 | 0.7392 |
|
|
0.79 | 0.6203 |
Hpgd | 2.77 | 0.2400 |
|
|
|
|
Il17b |
|
|
5.00 | 0.1527 |
|
|
Kcnk2 | 5.77 | 0.0618 |
|
|
|
|
Lpl | 3.98 | 0.1660 | 0.04 | 0.8904 |
|
|
Mmp13 |
|
|
|
|
1.27 | 0.2054 |
Mmp1a | 4.65 | 0.1549 | 0.82 | 0.5420 |
|
|
Mpzl2 |
|
|
2.06 | 0.4491 | 1.06 | 0.5866 |
MT2-Mmp | 0.21 | 0.7556 |
|
|
|
|
Pappa2 | 1.30 | 0.1800 |
|
|
|
|
Pcsk5 | 1.07 | 0.5650 |
|
|
|
|
Pfpl |
|
|
|
|
|
|
Pla2g5 | 0.92 | 0.4501 | 1.49 | 0.3380 |
|
|
Prl5a1 |
|
|
4.20 | 0.0805 |
|
|
Ptges2 | 7.57 | 0.1308 |
|
|
|
|
Ptgs2 | 0.10 | 0.8405 |
|
|
|
|
Rassf4 |
|
|
2.37 | 0.3243 | 1.75 | 0.3958 |
Slc6a4 | 1.39 | 0.3485 |
|
|
|
|
Spi16 | 0.75 | 0.4013 |
|
|
|
|
Spink8 | 0.15 | 0.8126 |
|
|
|
|
Tgfbi | 2.92 | 0.2169 |
|
|
|
|
Thbs2 | 0.51 | 0.6974 |
|
|
10.93 | 0.0840 |
Thsd4 |
|
|
3.48 | 0.2932 | 9.89 | 0.0838 |
Tm9sf1 | 0.07 | 0.8660 |
|
|
0.00 | 0.9949 |
Tpbpb |
|
|
1.89 | 0.4606 |
|
|
Usp24 | 0.64 | 0.6553 |
|
|
3.36 | 0.3109 |
Statistical significance was evaluated by two-way repeated measures ANOVA, followed by post-hoc Bonferroni correction for multiple testing. Significance where P<0.05 is indicated by bold font.
Although statistical interaction of exposure conditions was not detected for 23 genes, 12 of these genes were nonetheless regulated by
The patterns of interactions in response to the environmental factors diet and diabetes are schematically depicted in
The influence (color) or lack thereof (empty field) of each factor, and their interaction was taken from
We here report that maternal diet affects placental growth and gene expression in diabetic pregnancies. In the context of maternal diabetes, the diet recommended specifically for breeding and lactating mice was associated with reduced fetal size
Litter size is known to be inversely correlated to placenta size
Gene symbol | Accession # | Forward primer – sequence | Position | Reverse primer – sequnce | Position | Exon-exon boundary | AE |
9130005 N14Rik | NM_026667 |
|
1438–1457 |
|
1555–1527 | yes | 1.89 |
Adamts6 | NM_001081020 |
|
2138–2160 |
|
2226–2201 | yes | 1.90 |
Ankrd2 | NM_020033 |
|
644–666 |
|
718–696 | yes | 1.93 |
Atoh8 | NM_153778 |
|
1356–1372 |
|
1459–1440 | yes | 1.96 |
Crct1 | NM_028798 |
|
4–26 |
|
91–69 | yes | 1.88 |
Csf2rb | NM_007780 |
|
1615–1635 |
|
1717–1696 | yes | 1.91 |
Cyp1a1 | NM_009992 |
|
1222–1252 |
|
1336–1319 | yes | 1.86 |
Ermp1 | NM_001081213 |
|
1704–1725 |
|
1833–1810 | yes | 1.95 |
Frem1 | NM_177863 |
|
5834–5851 |
|
5973–5953 | yes | 1.91 |
Hpgd | NM_008278 |
|
369–395 |
|
453–429 | yes | 1.90 |
Il17b | NM_019508 |
|
287–312 |
|
375–356 | yes | 1.97 |
Kcnk2 | NM_010607 |
|
778–801 |
|
861–835 | yes | 1.89 |
Lpl | NM_008509 |
|
958–979 |
|
1043–1223 | yes | 1.88 |
Mmp1a | NM_032006 |
|
941–963 |
|
1013–988 | yes | 1.95 |
Mmp13 | NM_008607 |
|
478–501 |
|
595–575 | yes | 1.84 |
Mmp15 | NM_008609 |
|
2085–2110 |
|
2192–2174 | yes | 1.89 |
Mpzl2 | NM_007962 |
|
728–747 |
|
815–791 | yes | 1.92 |
Pappa | NM_021362 |
|
10045–10067 |
|
10130–10107 | no | 1.93 |
Pcsk5 | NM_001163144 |
|
2303–2322 |
|
2384–2366 | yes | 1.89 |
Pfpl | NM_019540 |
|
2583–2605 |
|
2699–2674 | no | 1.89 |
Pla2g5 | NM_001122954 |
|
460–479 |
|
541–521 | yes | 1.88 |
Prl5a1 | NM_023746 |
|
346–368 |
|
418–397 | yes | 1.89 |
Ptges2 | NM_133783 |
|
1228–1248 |
|
1298–1275 | yes | 1.90 |
Ptgs2 | NM_011198 |
|
1285–1306 |
|
1410–1392 | yes | 1.86 |
Rassf4 | NM_178045 |
|
667–686 |
|
786–764 | yes | 1.89 |
Slc6a4 | NM_010484 |
|
1813–1830 |
|
1893–1872 | yes | 1.83 |
Spi16 | U96702 |
|
363–381 |
|
434–412 | no | 1.95 |
Spink8 | NM_183136 |
|
171–190 |
|
243–226 | yes | 1.98 |
Tgfbi | NM_009369 |
|
1930–1949 |
|
2040–2020 | yes | 1.69 |
Thbs2 | NM_011581 |
|
3693–3712 |
|
3800–3778 | yes | 1.81 |
Thsd4 | NM_172444 |
|
450–468 |
|
587–566 | no | 1.97 |
Tm9sf1 | NM_028780 |
|
1461–1480 |
|
1552–1529 | yes | 1.95 |
Tpbpb | NM_026429 |
|
406–425 |
|
487–464 | yes | 1.88 |
Usp24 | NM_183225 |
|
2972–3000 |
|
3087–3061 | yes | 1.80 |
Primer sequences and positions on the reference sequence are given. Where possible, primers were designed to span an exon-exon junction so as to avoid amplification from potentially contaminating DNA. Amplification efficiencies were calculated from the actual PCR runs as described before.
Interestingly, maternal glucose levels were higher at the start of pregnancy when diabetic dams consumed breeder diet, averaging 349.65±97.79 mg/dL compared to 306.23±81.81 mg/dL in diabetic dams consuming the chow diet. By the time of sacrifice, maternal glucose levels exceeded the upper limit of the meter (600 mg/dL) in 9 out of 53 dams on chow diet, and in 29 out of 45 dams on breeder diet (we therefore cannot estimate average levels for the whole group); measurable blood glucose levels in the remaining dams were 457.50±90.61 mg/dL in chow-fed (n = 26), and 506±82.13 mg/dL in breeder diet-fed diabetic dams (n = 16), respectively (difference is not statistically significant). Also, if we consider the difference between pre-pregnancy glucose levels and those at sacrifice
The gene expression profiles indicate that breeder diet does not simply exacerbate the detrimental effects of maternal diabetes, but that it has distinct effects. While gene expression is clearly misregulated in diabetic placentas, the different diets influence the magnitude and direction of changes, and exert their effects on specific sub-sets of genes. Except for Tgfßi and Il17ß, where gene expression levels in diabetic placentas could be interpreted to correlate with blood glucose levels (magnitude of change is greater in the breeder diet-fed group than in the chow-fed), all other patterns are indicative of interaction of diet and diabetic state, in additive manner, and often also in opposite directions (see
Less clear at the moment is how these molecular alterations translate into reduced placental growth. We have previously shown that spongiotrophoblast growth is reduced under conditions of diabetic pregnancy, and the labyrinth also remains smaller
It is noteworthy that our -admittedly short- list of 33 diet-responsive genes does not overlap with the gene repertoire changes reported for placentas from protein restricted FVB dams at E17.5
The molecular mechanisms through which diet affects the regulation of genes with altered expression levels are unknown. To date, regulatory elements that confer placenta-specific expression have not been identified for any of the diet targets our work uncovered. Similarly, it is unknown whether microRNAs or other epigenetic mechanisms may be involved. Changes in cellular composition, namely increased frequency of cells expressing the respective gene, appear to be responsible for the increased expression of the
Both the chow, as well as the breeder diet, are formulated to be replete for minerals and micronutrients, but they differ in macronutrient composition. In particular, protein content is higher in the chow diet, while fat is enriched in the breeder diet. From our results, it appears that placental cells can detect this difference, likely through nutrient sensing mechanisms
Taken together, our results demonstrate that maternal diet modulates placental gene expression and growth, with a concomitant effect on fetal growth
Mice of the FVB inbred strain were obtained from The Jackson Laboratories (Bar Harbor, ME) at the age of 5–6 weeks old and were accomodated to the animal facility for one week before any experimentation. Diabetes was induced in female mice by two injections of Streptozotocin within a week as previously described
At designated days, uterine horns were dissected out, and pairs of placentas and embryos were isolated. Placentas included embryo-derived and maternal tissue, and were dissected in PBS, briefly blotted on tissue paper to remove excess liquid, and then they were weighed
Details of the quantitative real-time PCR (Q-RT-PCR) method have been described elsewhere
Results were evaluated for statistical significance by using two-tailed T-tests for pairwise comparisons. P-values smaller than 0.05 were considered statistically significant. For the interaction analyses, two-factor repeated measures ANOVA was applied, with Bonferroni post-hoc correction for multiple testing, as implemented in GraphPad Prism version 4.
Cluster analyses were performed in Cluster 3 (
We wish to thank Jessica Wilson for help with animals and Xiaoying Zhang for RNA extractions and cDNA synthesis.