Peer review of: Core functional nodes and sex-specific pathways in human ischaemic and dilated (2020)


 

 

Reviewers' comments: 

 

Reviewer #2 (Remarks to the Author): 

 

The manuscript has been revised and improved substantially over the first version. Notably, 
inclusion of detailed tables (both patient data and omic), a commitment to detailed methods, and 
improved figures & analyses are a plus and serve the authors well. The authors have definitely been 
responsive. Thanks. 

 

The question remains whether the study is really much more informative than any of the large 
number of heart failure profiling studies that preceded it. The authors do note that this is probably 
the first profiling study of human ICM and DCM to include both proteomic and metabolomic data, 
which is nothing to sneeze at. 

 

But has the combined use of proteomics and metabolomics here really moved the needle in our 
understanding of ICM and DCM? Notwithstanding the substantial improvement in the manuscript, in 
my opinion, it still falls short in conveying the uniquely novel findings. 

 

In any event, here are some further observations. 

 

1. Inclusion of PCA and heatmaps in fig 2 are an improvement but could still use some cosmetic work 
to increase readability and bring data into line with commonly accepted practices. 

a. For the PCA plot, both the size and pastel colors of symbols make the graph difficult to read 
clearly. It would be great if the authors could increase symbol size and switch to a bolder color 
palate to make the symbols pop. Even after substantial magnification, distinguishing powder blue 
from mauve and rose blush is not easy. 

b. It is common practice on PCA plots to include ellipses that define the 95% confidence interval. 

c. For the heatmap, the color scale does not adhere to most common norms (red-black-green; 
yellow-black-blue; red-white-blue). The authors have chosen to use red-yellow-light blue where 
yellow is around 0. This is problematic since most people interpret yellow as a degree on the red 
scale, so at first glance it looks as though most proteins are mildly upregulated. 

 

2. The same critique applies to figure 3. 

 

3. Lines 151-152 are a bit cringe-worthy. “In general, the most down-regulated proteins in donor 
hearts were the most up-regulated in diseased hearts, and vice versa (Fig. 2f)” . If you think about it, 
this is true for all data in the universe that are presented as relative changes. If what you mean is 
that there was little divergence between ICM and DCM compared with Normals, you might want to 
say it that way. 

 

4. I would take issue with aspects and interpretations of the results, discussion, and conclusion. I’ll 
address each, though perhaps not in order. 

 

The biggest issue with the discussion is that, despite some improvement, the authors still have not 
done a great job summarizing and referencing the existing HF profiling literature and distinguishing 
precisely which of their observations are absolutely novel and which are largely confirmatory. Since 
there are fewer metabolomics studies, I presume most insight would be on on the metabolomic 
side. Nevertheless, proper contextualization is still lacking all around. 

 

Take line 442-444 of the conclusion. 

This is the first study to apply comprehensive “omic” screening to a large cohort of cryopreserved, 
advanced human ICM and DCM left ventricular myocardium with necessary comparison to 
appropriately-matched, histopathologically-normal donor hearts. 

 

Though technically true, in the sense that multi-omics including metabolomics has not been done, 
there is a vast literature of profiling studies using microarrays, NGS and even a few decent 
proteomics studies. The authors have not cited many of them or really attempted to summarize the 
pertinent biosignatures or dominant themes from those studies and explicitly lay out the insights 
that are unique to this study and which observations complement previous ones. 

 

For instance, extracellular matrix remodeling, inflammatory signaling, oxidative stress, mitochondrial 
dysfunction, and branched chain amino acid metabolism are all widely known and hotly studied. 

 

There is no discussion of convergence/divergence of their data with the recent human proteomic HF 
data set of Chen et al. Nat Med. 2018 Aug;24(8):1225-1233. doi: 10.1038/s41591-018-0046-2. Epub 
2018 Jun 11. 

 

Little mention of other profiling studies of DCM and ICM (of which there so many. i.e. >20 that 
would be directly pertinent, some dating back about 20 years) 

 

There is no comment on the convergence/divergences between their human study and what has 
previously been shown from animal models. 

 

No mention of any expression profiling revealing sex differences in HF or are pertinent to the topic 

Fermin et al Circulation: Cardiovascular Genetics. 2008;1:117–125 

Heidecker et al European Heart Journal, Volume 31, Issue 10, May 2010, Pages 1188–1196 

Kararigas et al Volume16, Issue11 November 2014 Pages 1160-1167 

Boheler et al. Volume16, Issue11, November 2014, Pages 1160-1167 

 

One of the observations the authors deem to be the primary novel one is high T4 levels in the heart 
suggestive of impaired T3 biosynthesis in the hearts of DCM/ICM patients, yet this has been shown 
already in human ICM and DCM before, as cited by the authors (Gil-Calyuela et al). In fact, the issue 
of intra or extra-cardiac thyroid hormone has been a hotbed of research for years, as reviewed by 
Gerdes, A. M. and G. Iervasi (2010). "Thyroid replacement therapy and heart failure." Circulation 
122(4): 385-393. 

 

line 447 We revealed numerous novel findings. OK, which ones explicitly have never been seen 
before? 

 

line 447- network analyses revealed many 448 functional nodes that are informative for future 
targeted research. Too many to name explicitly? 

 

 

 

Reviewer #3 (Remarks to the Author): 

 

My issues have been resolved satisfactorily in the revision