Genetic Analysis for Correlation with Preeclamptic Progression

Noha Algahimi Author

04/05/2021 Added

6 Plays

Description

Clinical data is analyzed for glycolysis, TCA, and PPP genes to find any variance between expression in healthy and preeclamptic patients. Eventually, the findings will be applied to in vitro modeling using the novel BEASTS platform.

Searchable Transcript

Search:

[00:00:00.960]Hello.
[00:00:01.530]My name is Noha Algahimi and I am a junior chemical engineering major at the
[00:00:05.070]University of Nebraska Lincoln. Preeclampsia,
[00:00:08.580]PE is a major disease of human pregnancy characterized internally by high
[00:00:12.980]placental stiffness and affects roughly 3 to 8% of women worldwide.
[00:00:17.820]It remains one of the few fatal complications of pregnancy to date.
[00:00:21.990]There is no cure for PE and in severe cases,
[00:00:24.450]it often requires premature labor induction, which carries with it
[00:00:28.380]the inherent risks of premature neonates. PE manifests in the pregnant
[00:00:33.330]mother as high blood pressure, headaches, nausea, and breathing difficulties.
[00:00:37.620]Under preeclamptic conditions,
[00:00:39.130]placental development is inhibited preventing the fetus from receiving nutrition
[00:00:42.690]necessary for healthy development. Molecular mechanisms
[00:00:46.080]that account for the maternal placental stiffness associated with PE are
[00:00:49.890]underexplored and the full extent of the stiffness effects on trophoblast
[00:00:53.820],otherwise known as, placenta cells remains a gap in scientific knowledge
[00:00:58.560]around PE.
[00:01:00.360]The goal of my research this year has been to explore clinical data for patients
[00:01:05.010]with preeclampsia to determine any significant difference that might exist from
[00:01:09.180]the healthy controls. Three clinical data sets
[00:01:12.690]including genetic expression information for a variety of genes in preeclampsia
[00:01:17.160]patients and healthy controls were assessed. These datasets G S
[00:01:22.020]E three five five seven four G S E two five nine Oh six and
[00:01:26.460]GSE one Oh five
[00:01:27.780]eight eight were processed using geo2R software provided through NCBI
[00:01:33.270]log two fold change,
[00:01:34.500]which provides the logarithmic ratio of genetic expression between the control
[00:01:38.670]and the diseased state was found for all genes of interest.
[00:01:42.720]This included 15 causes related genes,
[00:01:45.450]three tricarboxylic acid genes,
[00:01:48.270]and three pentose phosphate pathway genes.
[00:01:51.690]The results were initially mapped using Microsoft Excel to give an initial
[00:01:55.980]picture of how log two fold change data could potentially be assessed.
[00:02:00.930]The initial mapping of log2 fold change showed that the values calculated for
[00:02:04.980]dataset GSE one Oh five, eight,
[00:02:07.020]eight were unusually large when compared to the other two datasets. While
[00:02:11.490]the reason for this is not explicitly known,
[00:02:14.280]it could be the result of the method in which the data was collected or the
[00:02:17.730]varied quantities of gene samples analyzed. To remedy the negative effects of
[00:02:22.260]having such a large difference in values between datasets,
[00:02:25.800]all three data sets were compared against each other once.
[00:02:29.130]And then data says G S E three five five seven four,
[00:02:32.580]and GSE25906 were compared separately.
[00:02:36.960]This made it easier to note which genes had a potential significant difference
[00:02:40.590]in genetic expression between the control and the pre-eclamptic state.
[00:02:45.600]This is shown in figure two,
[00:02:47.070]a with all three data sets and figure two b with only the two aforementioned
[00:02:51.420]datasets. Additionally,
[00:02:53.700]it must be noted that TCA and PPP genes were only found in two of the three
[00:02:58.110]datasets GSE, three five, five, seven, four, and GSE one Oh five,
[00:03:02.740]eight eight.
[00:03:03.970]So in analyzing the log2 fold change for these two metabolic pathways only
[00:03:08.260]the two mentioned data sets are used,
[00:03:10.630]this potentially means the findings for TCA and PPP do not have enough collected
[00:03:15.070]data to reasonably reach a conclusion.
[00:03:18.160]The data was then formatted into heat maps using prism software to present a
[00:03:21.970]visualization of potential significance. Once again,
[00:03:25.510]G S E 105 eight eight was admitted in a single visualization of glycolysis data
[00:03:30.220]to accurately maintain the variability within the other two datasets. Because the
[00:03:34.870]TCA and PPP genes were only found in two of the three datasets,
[00:03:39.280]one of which being the set with abnormally large log2 fold change values,
[00:03:43.540]it was not possible to create heat maps
[00:03:45.640]omitting said dataset from the two pathways.
[00:03:49.330]It was determined from heat maps that for the glycolysis pathway,
[00:03:52.780]Hexokinase 2 and glyceraldehyde-3-phosphate dehydrogenase showed
[00:03:57.280]potential significance in the variability of genetic expression between
[00:04:01.090]preeclampsia patients and healthy patients. In PPP
[00:04:05.980]glucose-six- phosphate dehydrogenase shows some promise,
[00:04:10.510]but due to lack of data, it is hard to draw a definite conclusion.
[00:04:14.470]The same can be said for pyruvate
[00:04:16.060]dehydrogenase in TCA. To further explore the potential significance of these
[00:04:20.560]genes
[00:04:21.010]It is pertinent that more data be analyzed so that the unusually large log
[00:04:24.910]two-fold change values in G S E one Oh five,
[00:04:28.240]eight eight are no longer an issue. Additionally, in future exploration,
[00:04:33.070]significance testing,
[00:04:34.270]using ANOVA in prism software, will be conducted to determine whether it worth
[00:04:39.250]creating in vitro essays of the indicated genes,
[00:04:43.150]or if it would be more appropriate to observe other genes. In the
[00:04:47.890]focus lab biomimetic stiffness modeling is conducted using the novel bio
[00:04:51.610]engineered adhesive siloxane substrate with tuneable stiffness (BEASTS)
[00:04:56.470]platform. To construct the platform polydimethylsiloxane precursors are
[00:05:01.450]mixed in ratio to produce variable stiffness plates.
[00:05:03.700]Stiffnesses are at eight kilo pascals,
[00:05:06.460]25 kilo pascals and 55 kilo pascals.
[00:05:10.210]These are then used to coat welled plates in seven millimeter increments.
[00:05:14.680]This can be seen in figure three,
[00:05:17.290]coated plates are incubated overnight at 65 degrees Celsius,
[00:05:21.190]and then treated with oxygen plasma to create a hydrophilic surface.
[00:05:25.510]The last step is to create 10 bi layers, alternating the positive
[00:05:30.100]polydiallyldimethylammonium (PDAC),
[00:05:33.880]and the negative suphonated polystyrene (SPS) polymers. Upon bilayer
[00:05:38.770]completion,
[00:05:39.490]Placenta cells are seeded on the plates and subjected to experimentation.
[00:05:43.780]This will be the platform I use in the next steps of my research,
[00:05:46.840]as I run in vitro assays of the genes of interest found through clinical data
[00:05:51.010]analysis.
[00:05:52.750]The noting of potential genetic variance occurring in the glycolysis
[00:05:56.080]metabolic pathway indicates the possibility that energy production and
[00:06:00.200]consumption in the placenta cells are negatively affected by the changing
[00:06:03.920]environment under preeclamptic conditions.
[00:06:06.350]This could aid in closing the knowledge gap associated with the progression
[00:06:09.620]and treatment of preeclampsia in pregnant women.

The screen size you are trying to search captions on is too small!

You can always jump over to MediaHub and check it out there.

Comments

0 Comments

Genetic Analysis for Correlation with Preeclamptic Progression

Description

Searchable Transcript

Comments icon comment

Related Channels

Comments