Limits...
Extensive shift in placental transcriptome profile in preeclampsia and placental origin of adverse pregnancy outcomes.

Sõber S, Reiman M, Kikas T, Rull K, Inno R, Vaas P, Teesalu P, Marti JM, Mattila P, Laan M - Sci Rep (2015)

Bottom Line: The transcriptome of LO-PE placentas was clearly distinct, showing statistically significant (after FDR) expressional disturbances for hundreds of genes.Taqman RT-qPCR validation of 45 genes in an extended sample (n = 24/group) provided concordant results.The dataset represent a rich catalogue for potential biomarkers and therapeutic targets.

View Article: PubMed Central - PubMed

Affiliation: Human Molecular Genetics Research Group, Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia.

ABSTRACT
One in five pregnant women suffer from gestational complications, prevalently driven by placental malfunction. Using RNASeq, we analyzed differential placental gene expression in cases of normal gestation, late-onset preeclampsia (LO-PE), gestational diabetes (GD) and pregnancies ending with the birth of small-for-gestational-age (SGA) or large-for-gestational-age (LGA) newborns (n = 8/group). In all groups, the highest expression was detected for small noncoding RNAs and genes specifically implicated in placental function and hormonal regulation. The transcriptome of LO-PE placentas was clearly distinct, showing statistically significant (after FDR) expressional disturbances for hundreds of genes. Taqman RT-qPCR validation of 45 genes in an extended sample (n = 24/group) provided concordant results. A limited number of transcription factors including LRF, SP1 and AP2 were identified as possible drivers of these changes. Notable differences were detected in differential expression signatures of LO-PE subtypes defined by the presence or absence of intrauterine growth restriction (IUGR). LO-PE with IUGR showed higher correlation with SGA and LO-PE without IUGR with LGA placentas. Whereas changes in placental transcriptome in SGA, LGA and GD cases were less prominent, the overall profiles of expressional disturbances overlapped among pregnancy complications providing support to shared placental responses. The dataset represent a rich catalogue for potential biomarkers and therapeutic targets.

No MeSH data available.


Related in: MedlinePlus

Placentas from the cases of late-onset preeclampsia (PE) with and without concomitant intra-uterine growth restriction (IUGR) exhibit distinct gene expression patterns.(a) Correlation plots for the fold changes of the highest ranked genes in the differential expression testing in each pregnancy complication compared to normal pregnancy (DESeq analysis). For each pairwise analysis of gestational complications, the lists of top-200 genes (circles) were united and plotted at the x,y-plane, where the axes correspond to log2(fold changes) in the two groups. Red circles represent genes, which are shared between the top gene lists. The linear regression line along with correlation coefficient R2 and statistical significance is given. (b) Numbers of shared genes among the top 200 highest ranked transcripts in differential expression testing. Detailed information on the pairwise overlaps among the study groups for the shared top-genes with altered placental expression is provided in Supplementary Fig. S4. (c) Hierarchical clustering based on transformed read counts of 283 differentially expressed genes in PE without IUGR, PE with IUGR, SGA, LGA and GD. Gene expression levels were subjected to variance stabilizing transformation in DESeq and standardized by subtracting the mean expression across all samples from its value for a given sample and then dividing by the standard deviation across all the samples. This scaled expression value, denoted as the row Z-score, is plotted in red-blue color scale with red indicating increased expression and blue indicating decreased expression. Hierarchical clustering of genes (rows) and samples (columns) was based on Pearson’s correlation. Hierarchical clustering trees are shown for the analyzed samples (top) and genes (left). For each sample are shown newborn sex (M, male; F, female), delivery by caesarean section (+/–) and gestational age at birth plotted in white-yellow-red color scale (white < 260, red  > 290 gestational days).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4542630&req=5

f6: Placentas from the cases of late-onset preeclampsia (PE) with and without concomitant intra-uterine growth restriction (IUGR) exhibit distinct gene expression patterns.(a) Correlation plots for the fold changes of the highest ranked genes in the differential expression testing in each pregnancy complication compared to normal pregnancy (DESeq analysis). For each pairwise analysis of gestational complications, the lists of top-200 genes (circles) were united and plotted at the x,y-plane, where the axes correspond to log2(fold changes) in the two groups. Red circles represent genes, which are shared between the top gene lists. The linear regression line along with correlation coefficient R2 and statistical significance is given. (b) Numbers of shared genes among the top 200 highest ranked transcripts in differential expression testing. Detailed information on the pairwise overlaps among the study groups for the shared top-genes with altered placental expression is provided in Supplementary Fig. S4. (c) Hierarchical clustering based on transformed read counts of 283 differentially expressed genes in PE without IUGR, PE with IUGR, SGA, LGA and GD. Gene expression levels were subjected to variance stabilizing transformation in DESeq and standardized by subtracting the mean expression across all samples from its value for a given sample and then dividing by the standard deviation across all the samples. This scaled expression value, denoted as the row Z-score, is plotted in red-blue color scale with red indicating increased expression and blue indicating decreased expression. Hierarchical clustering of genes (rows) and samples (columns) was based on Pearson’s correlation. Hierarchical clustering trees are shown for the analyzed samples (top) and genes (left). For each sample are shown newborn sex (M, male; F, female), delivery by caesarean section (+/–) and gestational age at birth plotted in white-yellow-red color scale (white < 260, red  > 290 gestational days).

Mentions: Recently, Redman and colleagues have suggested that there are two main placental causes for preeclampsia. PE caused by poor placentation in early pregnancy is frequently accompanied with fetal growth restriction, whereas at term PE may also develop when placental growth reaches its functional limits and is often linked to macrosomy26. To further dissect the relationship between LO-PE and fetal growth we divided the PE study sample according to the presence of concomitant intrauterine growth restriction (IUGR). The two subgroups (n =4/group) were separately tested for the differential placental gene expression compared to the normal gestation group (n = 8). We identified 199 and 98 differentially expressed genes in PE without IUGR and PE with IUGR, respectively (Supplementary Data S3). Only 20 genes overlapped between the two LO-PE subtypes with statistically significant alternations in transcript levels. Still, examination of the top 200 highest ranked genes in both analyses revealed substantial correlation in their expressional changes compared to normal pregnancy (R2 = 0.62; P = 7.82 × 10−77; 36 shared genes among the top-200; Fig. 6a–b). Notably, placental transcriptome profile in cases of LO-PE with IUGR showed the highest correlation with SGA group (R2 = 0.67; P = 2.81 × 10−85; 42 shared genes; Fig. 6a–b), whereas the LO-PE without IUGR bears the closest similarity to LGA cases (R2 = 0.62; P = 1.24 × 10−70; 53 shared genes; Fig. 6a–b). Hierarchical clustering analysis based on all 283 genes matching the statistical significance criteria across study groups also separated the transcriptome profiles of LO-PE with and without IUGR, supporting their distinct molecular signatures (Fig. 6c).


Extensive shift in placental transcriptome profile in preeclampsia and placental origin of adverse pregnancy outcomes.

Sõber S, Reiman M, Kikas T, Rull K, Inno R, Vaas P, Teesalu P, Marti JM, Mattila P, Laan M - Sci Rep (2015)

Placentas from the cases of late-onset preeclampsia (PE) with and without concomitant intra-uterine growth restriction (IUGR) exhibit distinct gene expression patterns.(a) Correlation plots for the fold changes of the highest ranked genes in the differential expression testing in each pregnancy complication compared to normal pregnancy (DESeq analysis). For each pairwise analysis of gestational complications, the lists of top-200 genes (circles) were united and plotted at the x,y-plane, where the axes correspond to log2(fold changes) in the two groups. Red circles represent genes, which are shared between the top gene lists. The linear regression line along with correlation coefficient R2 and statistical significance is given. (b) Numbers of shared genes among the top 200 highest ranked transcripts in differential expression testing. Detailed information on the pairwise overlaps among the study groups for the shared top-genes with altered placental expression is provided in Supplementary Fig. S4. (c) Hierarchical clustering based on transformed read counts of 283 differentially expressed genes in PE without IUGR, PE with IUGR, SGA, LGA and GD. Gene expression levels were subjected to variance stabilizing transformation in DESeq and standardized by subtracting the mean expression across all samples from its value for a given sample and then dividing by the standard deviation across all the samples. This scaled expression value, denoted as the row Z-score, is plotted in red-blue color scale with red indicating increased expression and blue indicating decreased expression. Hierarchical clustering of genes (rows) and samples (columns) was based on Pearson’s correlation. Hierarchical clustering trees are shown for the analyzed samples (top) and genes (left). For each sample are shown newborn sex (M, male; F, female), delivery by caesarean section (+/–) and gestational age at birth plotted in white-yellow-red color scale (white < 260, red  > 290 gestational days).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4542630&req=5

f6: Placentas from the cases of late-onset preeclampsia (PE) with and without concomitant intra-uterine growth restriction (IUGR) exhibit distinct gene expression patterns.(a) Correlation plots for the fold changes of the highest ranked genes in the differential expression testing in each pregnancy complication compared to normal pregnancy (DESeq analysis). For each pairwise analysis of gestational complications, the lists of top-200 genes (circles) were united and plotted at the x,y-plane, where the axes correspond to log2(fold changes) in the two groups. Red circles represent genes, which are shared between the top gene lists. The linear regression line along with correlation coefficient R2 and statistical significance is given. (b) Numbers of shared genes among the top 200 highest ranked transcripts in differential expression testing. Detailed information on the pairwise overlaps among the study groups for the shared top-genes with altered placental expression is provided in Supplementary Fig. S4. (c) Hierarchical clustering based on transformed read counts of 283 differentially expressed genes in PE without IUGR, PE with IUGR, SGA, LGA and GD. Gene expression levels were subjected to variance stabilizing transformation in DESeq and standardized by subtracting the mean expression across all samples from its value for a given sample and then dividing by the standard deviation across all the samples. This scaled expression value, denoted as the row Z-score, is plotted in red-blue color scale with red indicating increased expression and blue indicating decreased expression. Hierarchical clustering of genes (rows) and samples (columns) was based on Pearson’s correlation. Hierarchical clustering trees are shown for the analyzed samples (top) and genes (left). For each sample are shown newborn sex (M, male; F, female), delivery by caesarean section (+/–) and gestational age at birth plotted in white-yellow-red color scale (white < 260, red  > 290 gestational days).
Mentions: Recently, Redman and colleagues have suggested that there are two main placental causes for preeclampsia. PE caused by poor placentation in early pregnancy is frequently accompanied with fetal growth restriction, whereas at term PE may also develop when placental growth reaches its functional limits and is often linked to macrosomy26. To further dissect the relationship between LO-PE and fetal growth we divided the PE study sample according to the presence of concomitant intrauterine growth restriction (IUGR). The two subgroups (n =4/group) were separately tested for the differential placental gene expression compared to the normal gestation group (n = 8). We identified 199 and 98 differentially expressed genes in PE without IUGR and PE with IUGR, respectively (Supplementary Data S3). Only 20 genes overlapped between the two LO-PE subtypes with statistically significant alternations in transcript levels. Still, examination of the top 200 highest ranked genes in both analyses revealed substantial correlation in their expressional changes compared to normal pregnancy (R2 = 0.62; P = 7.82 × 10−77; 36 shared genes among the top-200; Fig. 6a–b). Notably, placental transcriptome profile in cases of LO-PE with IUGR showed the highest correlation with SGA group (R2 = 0.67; P = 2.81 × 10−85; 42 shared genes; Fig. 6a–b), whereas the LO-PE without IUGR bears the closest similarity to LGA cases (R2 = 0.62; P = 1.24 × 10−70; 53 shared genes; Fig. 6a–b). Hierarchical clustering analysis based on all 283 genes matching the statistical significance criteria across study groups also separated the transcriptome profiles of LO-PE with and without IUGR, supporting their distinct molecular signatures (Fig. 6c).

Bottom Line: The transcriptome of LO-PE placentas was clearly distinct, showing statistically significant (after FDR) expressional disturbances for hundreds of genes.Taqman RT-qPCR validation of 45 genes in an extended sample (n = 24/group) provided concordant results.The dataset represent a rich catalogue for potential biomarkers and therapeutic targets.

View Article: PubMed Central - PubMed

Affiliation: Human Molecular Genetics Research Group, Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia.

ABSTRACT
One in five pregnant women suffer from gestational complications, prevalently driven by placental malfunction. Using RNASeq, we analyzed differential placental gene expression in cases of normal gestation, late-onset preeclampsia (LO-PE), gestational diabetes (GD) and pregnancies ending with the birth of small-for-gestational-age (SGA) or large-for-gestational-age (LGA) newborns (n = 8/group). In all groups, the highest expression was detected for small noncoding RNAs and genes specifically implicated in placental function and hormonal regulation. The transcriptome of LO-PE placentas was clearly distinct, showing statistically significant (after FDR) expressional disturbances for hundreds of genes. Taqman RT-qPCR validation of 45 genes in an extended sample (n = 24/group) provided concordant results. A limited number of transcription factors including LRF, SP1 and AP2 were identified as possible drivers of these changes. Notable differences were detected in differential expression signatures of LO-PE subtypes defined by the presence or absence of intrauterine growth restriction (IUGR). LO-PE with IUGR showed higher correlation with SGA and LO-PE without IUGR with LGA placentas. Whereas changes in placental transcriptome in SGA, LGA and GD cases were less prominent, the overall profiles of expressional disturbances overlapped among pregnancy complications providing support to shared placental responses. The dataset represent a rich catalogue for potential biomarkers and therapeutic targets.

No MeSH data available.


Related in: MedlinePlus