Oral Presentation 4 (IMAG-AND Futures)

2:20-2:40 pm               “Multiscale model of pregnancy-induced heart growth: Integrating hormonal signaling and mechanics

Kyoko Yoshida, Univ. of Virginia3:20-3:40 pm    

Kyoko Yoshida (photo)

 

 

 

 

Presentation:

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Q&A Session:

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Increased mortality rates in US are in part related to increase rates of advanced maternal age. Are there expected to be any sigificant cardiac changes associated with age in 30s and 40s? If so, how to take that into account in models and animal studies?

Submitted by Bill Lytton (not verified) on Tue, 03/17/2020 - 14:32

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I have not seen anything in the literature about significant cardiac changes associate with women in their 30s and 40s, but as cardiologists and OBGYNs are beginning to really collaborate, we will understand more about these patients. Based on what these data say, I'll have to consider whether I should account for these patients at the hemodynamics level, cell signaling level, or somewhere in between.

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Very elegant modeling! A key strength of your modeling is its simplicity. On place where you avoid simplicity is your detailed discretization of the heart. How important is this detail? Could you capture the same physics using cylindrical heart chambers? Thanks! Guy

Submitted by Guy Genin, Was… (not verified) on Tue, 03/17/2020 - 14:33

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Thank you I actually did not use a Finite element model for this study - instead I used the compartmental model, where we treat the Left and right ventricles as thin-walled spheres with a cavity volume and wall thickness. I think that moving forward, adding complexity to my model will be more focused on the intracellular signaling pathways both because this is where we need the details and also to save computational time.

Submitted by Anonymous (not verified) on Tue, 03/17/2020 - 14:57

In reply to by Guy Genin, Was… (not verified)

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Great talk - Indeed each presenter did a very good job. I am interested in the role of obesity. Have you investigated the impact of pregnancy on the mechanical and biological models?

Submitted by Ted Dick (not verified) on Tue, 03/17/2020 - 14:35

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One of the challenges you will face will be to distinguish between appropriate and healthy pregnancy-induced hypertrophy and pathological changes that lead to bad outcomes for the mother. Do you have an idea about what nodes in the network model might be different in pregnant women who suffer pathological hypertrophy?

Submitted by Eric Sobie (not verified) on Tue, 03/17/2020 - 14:36

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I don't know which nodes will be different between these patients yet - Most of the studies I have found so far focus mostly on estrogen and its effects on heart failure. Less studies have studied the effects on pregnancy.

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Great talk! I wonder if you can talk more about sensitivity of the biological model to the input parameters, and also thoughts about the effect of the inherent variation in the biological response to variation in the output. 

Submitted by abuganza on Tue, 03/17/2020 - 14:37

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Thank you! Right now, the smaller scale network model is pretty sensitive to the input parameters because there are not too many species interacting. Sensitivity will really come into play once we have more connections and interactions. How sensitive the model will be to individual inputs will depend on how connected a specific species is. In terms of inherent variation in the biological response, I think that conducting a sensitivity analysis will be key for understanding which variations we should care about and incorporate into the simulations.

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Congratulations on a wonderful presentation and your impressive new results Kyoko. I wonder whether the model could also be used to study the significant sex differences particularly between the incidence of HFpEF and HFrEF and also in RV remodeling in pulmonary arterial hypertension

Submitted by McCullochA on Tue, 03/17/2020 - 14:37

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Thank you, Andrew! I think this model would be great for understanding sex differences and hypertrophy. In fact, I think I will have better luck incorporating estrogen signaling into the model because most of the experimental studies report the effects of estrogen, not progesterone. Applying these models within the gender difference context might be an important intermediate step before pregnancy.

Submitted by Anonymous (not verified) on Tue, 03/17/2020 - 15:26

In reply to by McCullochA

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What are the computational tools you are using? I mean software tools. And how long are your computations?

Submitted by jbarhak on Tue, 03/17/2020 - 14:38

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Hi Jacob, we use MATLAB for running these simulations. The compartmental model is essentially a system of ODEs. The network model is generated using Netflux (https://github.com/saucermanlab/Netflux). Right now, simulating 21 days of growth takes about 5 minutes.

Submitted by Anonymous (not verified) on Tue, 03/17/2020 - 15:30

In reply to by jbarhak

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Great talk - You're interpreting mechanical stress into signalling responses - how did you quantitatively relate one to the other? Were there separate experiments done, data mined, or imputation by the model?

Thanks

Submitted by Ben B (not verified) on Tue, 03/17/2020 - 14:40

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Right now, we use a linear mapping between stretch calculated by the mechanical model into "Stretch" input into the network model - so NetworkStretch = m*MechStretch + b. I tuned the slope (m) and intercept (b) to the Volume overload study.