In our previous research we performed miRNA expression profiling of CVS samples from euploid and trisomic pregnancies [27]. A total of 80 CVS samples (40 with normal karyotype, 40 with trisomy of chromosome 21) were included. Seven miRNAs were finally verified using qPCR as significantly up-regulated in DS placentas (miR-99a, miR-542-5p, miR-10b, miR-125b, miR-
615, let-7c and miR-654), three of them were located on chromosome 21 (miR-99a, miR-125b, let-7c). Except for various essential biological processes, we identified many genes involved in placenta development (GJA1, CDH11, EGF, ERVW-1, ERVFRD-1, LEP or INHA) as being potentially altered by elevated miRNA levels.
It was found that human placenta expresses more than 500 different miRNAs, some of them specific for this tissue [34]. Placental-specific miRNAs are expressed from three main clusters - C14MC (chromosome 14 miRNA cluster), C19MC and miR-371-3 [35]. Typical changes in expression of miRNAs from these three clusters during pregnancy suggest their potential involvement in physiological processes [36]. For example, expression of miRNAs from cluster C19MC increases continually from first to third trimester and closely correlates with placenta growth [37]. miRNAs are released from placenta, primarily from placental trophoblast, into maternal and fetal circulation mainly via exosomes [28]. However, placenta is not the only determinant of pregnancy-associated miRNA levels in maternal and fetal blood, another source or mechanism influencing these levels is probably involved [29]. Hypothesis that miRNAs are somehow transported from fetus into the maternal circulation and vice versa is still unproven [26].
To further extend our knowledge about biological functions of miRNAs and assess their diagnostic potential, we focused in the follow-up study on maternal plasma samples. To our best knowledge, this is the first study performing genome-wide miRNA profiling in plasma samples of pregnant women with euploid and DS fetuses. All 70 plasma samples were obtained immediately before CVS sampling, so between 11th and 14th gestational week.
Methods analyzing genome-wide miRNA profiling (NGS or arrays) require a high miRNAs input, which is challenging in case of plasma samples. Therefore, most of the studies analyze only selected group of miRNAs in plasma using qPCR, where a much smaller input is needed or perform genome-wide analysis of whole maternal blood, where overwhelming background from maternal blood cells makes it virtually impossible to analyze cell-free nucleic acids from placenta [32].
To achieve the highest yield and purity of miRNAs from plasma for the purposes of Affymetrix miRNA array strips we performed exhaustive and systematic method optimization (Materials and Methods; S1). Utilization of miRNA arrays enabled us to evaluate all miRNAs listed in miRBase v.20 in one reaction. Twelve miRNAs were identified as being significantly dysregulated between compared groups of samples.
Nevertheless, promising results from the initial study phase were not verified in subsequent validation phase using more sensitive method RT-PCR and larger group of samples.
We could not select a single miRNA that would discriminate euploid and DS pregnancies on the plasma level. However, clear separation of compared groups is visible when comparing the levels of the larger group of most dysregulated miRNAs obtained from miRNA arrays (Figure 2).
Several articles comparing miRNA levels in plasma of pregnant women bearing euploid and DS fetuses have been published so far (Table 2). Nevertheless, these studies may have possibly come to different results due to different workflow used. The lack of a standardized normalization strategy represents a general issue in case of plasma miRNAs evaluation. Various reference miRNAs are used for normalization of raw expression data. For example, miR-16 is often selected as a reference target, but it was found to be very susceptible to hemolysis [38]. Small nuclear or nucleolar RNAs are suitable only for normalization of samples where nuclear material is expected, but not for plasma samples [39]. On the other hand, global mean normalization is applicable only for larger miRNA set (>100 miRNAs) [40]. To prevent distortion of our results, we decided to normalize our data with the same total miRNAs input as described previously [41].
Figure 2
Kotlabova et al. performed expression analysis of five miRNAs from chromosome 21 (miR-99a, let-7c, miR-125b-2, miR-155 and miR-802) using qPCR with normalization to reference miRNAs – miR-16 and let-7d [42]. Nevertheless, they found no differences between selected miRNA levels in compared groups of samples (12 pregnancies with DS fetuses; 12 control samples). Another study evaluating 14 miRNAs from Hsa21 (including five miRNAs which Kotlabova et al. focused on) also using qPCR with normalization to U6 snRNA was published by Erturk et al. [24]. They compared 33 euploid and 23 trisomic pregnancies and found two miRNAs - miR-99a and miR-3156, which were elevated in DS pregnancies. The most comprehensive study so far has been carried out by Kamhieh-Milz et al. [26]. A group of 1043 miRNAs were analyzed using high-throughput qPCR SmartChip Human miRNA Panel, nevertheless, a very small number of samples were included (7 DS fetuses; 7 controls). Using combination of three different normalization strategies (corrected threshold cycle values, normalized relative quantities and combination of both methods together) they found 36 miRNAs to be differentially expressed in DS versus control pregnancies, neither miR-99a nor miR-3156 were among them. The latest work on the topic was published by Zbucka-Kretowska et al. [43]. They examined levels of 800 miRNAs using NanoString technology within 12 DS pregnancies and 12 controls. Using normalization to geometric mean of top 100 probes (global mean), the group of 13 miRNAs was found to be deregulated.
Table 2
Except the study of Kotlabova, remaining three studies apparently did not apply any correction for multiple testing. Omitting this correction can lead to a false positive results, especially in the case of a high number of comparisons and small sample size, as in case of Kamhieh-Milz or Zbucka-Kretowska studies [44]. Moreover, Zbucka-Kretowska et al. themselves reported that using Benjamini-Hochberg's correction they would not reach any statistically significant results.
Our study included samples from early gestational weeks (11th-14th), which would allow potential utilization of miRNA markers found for early NIPT. However, our results from the validation study demonstrate, that levels of pregnancy associated miRNAs are apparently too low in such early pregnancies. Analysis of samples from later gestational weeks would potentially lead to different results, but without required potential for early diagnosis. Differences in gestational age could also contribute to the discrepancies between results of studies compared (Table 2).
Next to the different detection platforms, various preanalytical steps in sample handling, like sample storage conditions (time, temperature), type of preservative tube, concrete blood centrifugation conditions for plasma separation, plasma input volume to isolation or type of miRNA isolation (see supplement materials; S1), have also proven impact on the results achieved [38, 45, 46].
Regardless of different procedures and data processing, none of the studies comparing plasma samples from euploid and DS pregnancies found any miRNA, which could discriminate compared groups in all cases. So, it seems that miRNAs determination in plasma of pregnant women is not applicable for NIPT of fetal DS.
Since most of placental miRNAs are released to the circulation of pregnant woman via exosomes [28], it would be interesting in the future study to focus specifically on exosomal miRNAs. Exosomal miRNAs may be overlapped in the pool of total plasmatic miRNAs by other abundant miRNAs associated with RNA-binding proteins or derived from apoptotic cells. Exosomes are specific subtype of extracellular vesicles, which probably play a significant role in intercellular communication pathways involved in placentation, formation of vascular system between the mother and fetus or inducing of maternal immune tolerance to the fetus [47-50]. Therefore, exosomes could have potential as early non-invasive biomarkers of various pregnancy complications especially connected to placenta development. Indeed, exosomes are currently intensively studied in relation to preeclampsia [51, 52]. As Down syndrome pregnancies are also complicated by abnormal placentation [53], exosomes released from such an impaired placenta could be also promising markers for early detection of Down syndrome fetuses from maternal circulation. So far, miRNAs from circulating nanoparticles have only been studied in young individuals with DS and their siblings with promising results achieved [54].