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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

Estimated gene expression log2(fold change) of the 45 tested placental genes in preeclamptic placentas (PE) compared to normal gestation (NORM) is highly correlated between the RNA-Seq and Taqman RT-qPCR datasets.The correlation with RNA-Seq results (Y-axis) holds for the (a) technical replicate by the RT-qPCR performed in the discovery samples (PE, n = 8; NORM, n = 8), (b) for the biological replicate by RT-qPCR using an independent placental sample-set (PE, n = 16; NORM, n = 16) and (c) for the combined RT-qPCR data of discovery and follow-up samples (PE, n = 24; NORM, n = 24) (X-axis). (d) The estimated gene expression log2(fold change) of the 45 placental genes subjected to Taqman RT-qPCR in small-for-gestational-age (SGA, n = 24; Y-axis) cases compared to normal gestation (NORM, n = 24) is correlated with gene expression shifts in PE placentas (n = 24; X-axis). Note the difference in slope of the regression line due to more prominent fold changes of all genes in PE compared to SGA. Each dot represents one tested gene and the plots present linear regression lines, P values and correlation coefficients (R2).
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f3: Estimated gene expression log2(fold change) of the 45 tested placental genes in preeclamptic placentas (PE) compared to normal gestation (NORM) is highly correlated between the RNA-Seq and Taqman RT-qPCR datasets.The correlation with RNA-Seq results (Y-axis) holds for the (a) technical replicate by the RT-qPCR performed in the discovery samples (PE, n = 8; NORM, n = 8), (b) for the biological replicate by RT-qPCR using an independent placental sample-set (PE, n = 16; NORM, n = 16) and (c) for the combined RT-qPCR data of discovery and follow-up samples (PE, n = 24; NORM, n = 24) (X-axis). (d) The estimated gene expression log2(fold change) of the 45 placental genes subjected to Taqman RT-qPCR in small-for-gestational-age (SGA, n = 24; Y-axis) cases compared to normal gestation (NORM, n = 24) is correlated with gene expression shifts in PE placentas (n = 24; X-axis). Note the difference in slope of the regression line due to more prominent fold changes of all genes in PE compared to SGA. Each dot represents one tested gene and the plots present linear regression lines, P values and correlation coefficients (R2).

Mentions: The Taqman RT-qPCR (reverse transcription-qPCR) technical replicate assays performed for the discovery samples (PE, n = 8 vs NORM, n = 8) were highly consistent with RNA-Seq data. The correlation between the estimated log2(fold change) of the 45 tested genes in preeclamptic compared to normal placentas was R2 = 0.75 (linear regression, P = 2.08 × 10−14; Fig. 3a). RT-qPCR in an expanded sample-set (PE, n = 24 vs NORM, n =24; Table 1) further confirmed the altered gene expression in preeclampsia with concordant effect direction for 42 of 45 assessed genes (Supplementary Table S3). The estimated log2(fold change) in transcript levels significantly correlated with the RNA-Seq dataset (R2 = 0.78; P = 1.22 × 10−15; Fig. 3b,c). Four of the top confirmed loci (Supplementary Table S3) have been previously implicated in PE (FLT1, HSD17B1, DLX4, ADM). Other confirmed genes point to altered regulation of epigenetic (DOT1L, TET3), transcriptional (ZNF469) and apoptotic (RELL2) mechanisms as well as disturbances in the immune (IGHA1) and endocrine-metabolic systems (HSD17B1, ADM, GDPD5, MC1R). Multiplicity of affected biological systems supports the systematic malfunction of the placental genome in preeclampsia.


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)

Estimated gene expression log2(fold change) of the 45 tested placental genes in preeclamptic placentas (PE) compared to normal gestation (NORM) is highly correlated between the RNA-Seq and Taqman RT-qPCR datasets.The correlation with RNA-Seq results (Y-axis) holds for the (a) technical replicate by the RT-qPCR performed in the discovery samples (PE, n = 8; NORM, n = 8), (b) for the biological replicate by RT-qPCR using an independent placental sample-set (PE, n = 16; NORM, n = 16) and (c) for the combined RT-qPCR data of discovery and follow-up samples (PE, n = 24; NORM, n = 24) (X-axis). (d) The estimated gene expression log2(fold change) of the 45 placental genes subjected to Taqman RT-qPCR in small-for-gestational-age (SGA, n = 24; Y-axis) cases compared to normal gestation (NORM, n = 24) is correlated with gene expression shifts in PE placentas (n = 24; X-axis). Note the difference in slope of the regression line due to more prominent fold changes of all genes in PE compared to SGA. Each dot represents one tested gene and the plots present linear regression lines, P values and correlation coefficients (R2).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f3: Estimated gene expression log2(fold change) of the 45 tested placental genes in preeclamptic placentas (PE) compared to normal gestation (NORM) is highly correlated between the RNA-Seq and Taqman RT-qPCR datasets.The correlation with RNA-Seq results (Y-axis) holds for the (a) technical replicate by the RT-qPCR performed in the discovery samples (PE, n = 8; NORM, n = 8), (b) for the biological replicate by RT-qPCR using an independent placental sample-set (PE, n = 16; NORM, n = 16) and (c) for the combined RT-qPCR data of discovery and follow-up samples (PE, n = 24; NORM, n = 24) (X-axis). (d) The estimated gene expression log2(fold change) of the 45 placental genes subjected to Taqman RT-qPCR in small-for-gestational-age (SGA, n = 24; Y-axis) cases compared to normal gestation (NORM, n = 24) is correlated with gene expression shifts in PE placentas (n = 24; X-axis). Note the difference in slope of the regression line due to more prominent fold changes of all genes in PE compared to SGA. Each dot represents one tested gene and the plots present linear regression lines, P values and correlation coefficients (R2).
Mentions: The Taqman RT-qPCR (reverse transcription-qPCR) technical replicate assays performed for the discovery samples (PE, n = 8 vs NORM, n = 8) were highly consistent with RNA-Seq data. The correlation between the estimated log2(fold change) of the 45 tested genes in preeclamptic compared to normal placentas was R2 = 0.75 (linear regression, P = 2.08 × 10−14; Fig. 3a). RT-qPCR in an expanded sample-set (PE, n = 24 vs NORM, n =24; Table 1) further confirmed the altered gene expression in preeclampsia with concordant effect direction for 42 of 45 assessed genes (Supplementary Table S3). The estimated log2(fold change) in transcript levels significantly correlated with the RNA-Seq dataset (R2 = 0.78; P = 1.22 × 10−15; Fig. 3b,c). Four of the top confirmed loci (Supplementary Table S3) have been previously implicated in PE (FLT1, HSD17B1, DLX4, ADM). Other confirmed genes point to altered regulation of epigenetic (DOT1L, TET3), transcriptional (ZNF469) and apoptotic (RELL2) mechanisms as well as disturbances in the immune (IGHA1) and endocrine-metabolic systems (HSD17B1, ADM, GDPD5, MC1R). Multiplicity of affected biological systems supports the systematic malfunction of the placental genome in preeclampsia.

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