Reactive oxygen species have a causal role in multiple forms of insulin resistance
Authors: Eric S Lander
Nicholas Houstis
Evan D Rosen
Journal: Nature (2006)
Discipline: Multidisciplinary
Keywords: Insulin resistance; type 2 diabetes; cellular models; genomic analysis; cytokine
Affiliations: Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02141, USA.

Abstract:  Insulin resistance is a cardinal feature of type 2 diabetes and is characteristic of a wide range of other clinical and experimental settings. Little is known about why insulin resistance occurs in so many contexts. Do the various insults that trigger insulin resistance act through a common mechanism? Or, as has been suggested, do they use distinct cellular pathways? Here we report a genomic analysis of two cellular models of insulin resistance, one induced by treatment with the cytokine tumour-necrosis factor-alpha and the other with the glucocorticoid dexamethasone. Gene expression analysis suggests that reactive oxygen species (ROS) levels are increased in both models, and we confirmed this through measures of cellular redox state. ROS have previously been proposed to be involved in insulin resistance, although evidence for a causal role has been scant. We tested this hypothesis in cell culture using six treatments designed to alter ROS levels, including two small molecules and four transgenes; all ameliorated insulin resistance to varying degrees. One of these treatments was tested in obese, insulin-resistant mice and was shown to improve insulin sensitivity and glucose homeostasis. Together, our findings suggest that increased ROS levels are an important trigger for insulin resistance in numerous settings. 

Retracted: No

PubPeer comments:
 Figure 2D u2013 more similar than expected. Could the authors check please if these pictures have the same origin? ![file] Contrast enhanced: ![file] , 
 An anonymous correspondent asked whether two panels from Fig.2D of our paper might be a single duplicated image. The two panels assessed the phosphorylation status of S6-kinase in the absence of insulin (u201c-Insulinu201d) under two sets of conditions,u201c+Dexu201d and u201c+TNFu201d. The results showed a negligible level of S6K-phosphorylation in the absence of insulin under any condition, which is fully consistent with past work. To address whether the u201c+Dexu201d and u201c+TNFu201d panels are the same, we analyzed the images posted by the correspondent. In the figure below, we compared each image in the top row to a counterpart (same column) in the bottom row and displayed the difference in the center. Pixels that were identical were colored black in the overlay image, and pixels that were distinct were colored white (u201cthreshold=10u201d in Adobe Photoshop). As expected, when an image is subtracted from itself the overlay image is all black (middle row, 1st and 3rd columns). The comparison between u201c+Dexu201d vs. u201c+TNFu201d is shown in the center row and column. The overlay is dominated by white pixels, demonstrating that the images are clearly very different. Sensitivity analysis (not shown) demonstrated that this image difference persisted after varying the threshold for calling a difference between pixels. ![file] , 
 I thank the authors for engaging in the discussion. Disclaimer: my opinion on this particular issue is not set and I only want to discuss the image analytics. Deppea Microphylla wrote that the two images might be  *more similar than expected* , not that they are exact duplicates. This was already clear from the contrast enhanced figures they posted. So the pixel-by-pixel was not really necessary in my opinion since the two images are indeed not exactly the same. This does not mean however that they are not  *more similar than expected* . Let me explain. It is well known that a pixel-by-pixel analysis could identify two images as different even if they are actually copies of the same original figure. This is due to small differences that are in reality artifacts introduced during image processing (such as jpeg pdf compression). This [PubPeer thread] contains a well described such example. In particular, the posts [43] , [42] and [100] highlight the potential problem of looking for exact matches. [RetractionWatch](http: retractionwatch.com 2015 06 04 cell-press-investigating-possible-image-manipulation-in-influential-yeast-genetics-paper ) has also covered that case and briefly discusses the merit and drawbacks of pixel-by-pixel comparisons. The drawbacks of such approaches have also been highlighted by Dr John W. Krueger (from ORI) in the Fazlul Sarkar court case. The whole Krueger affidavit is [there] , but here are some extracts that have been collected by an anonymous poster at the [PubPeer thread mentioned above] . They are pasted here only for convenience. 15. It is critical to recognize that it is not necessary for two images to be pixel-for- pixel matches in order to conclude that they represent a record of the same experiment. This is so because two image files derived from the same source may u201ctravel different routesu201d to their destination towards separate publication or use in reporting research. For example, they may have been subjected to different forms of digital compressionu2014such as JPG compressionu2014 which would introduce differences. 17. Again, pixel-for-pixel perfection is not necessary in order to conclude that two images depict the same experiment. Instead, the question is whether there are characteristic features unexpectedly in common between the images that indicate that they are u201ctoo similar to be different.u201d 18. Relatedly, it is important to understand that affirmative similarities between images are more determinative than differences. In other words, the similarities between features in two images may lead to the conclusion that they derived from the experiment, even if there are differences between the images. 20. In assessing whether a scientific image or its components are authentic or, instead, depict conflicting results of the same experimental observation, the question to be answered is whether the content of each is u201ctoo similar to be differentu201du2014too similar, in other words, to have been derived from different experiments. In addition, I believe the dedicated [ORI page] contains useful hints on how to do image forensics properly. Last, I believe the original gel images could clear up any doubt, but I also understand that the paper is from a while ago (2006). , 
 Appears to be undeclared splicing in figure 1d and figure s3. , 
 #2 Nicholas Houstis, Frankly, the analysis you posted is not at all compelling; it is on par with those previously criticized by the last author (e.g., https: www.broadinstitute.org files sections about PCAST 2012%20Testimony%20Senate.pdf ). By adjusting the light levels of the images (from the paper PDF), it is plain to see that the  clearly very different features you have detected are the products of image compression and other post-capture degradation (re-sampling, etc.) See below. The best way to clarify these matters is to turn to the original source files, not images that have been repeatedly degraded during the publication process, which can be demonstrated to introduce differences in images with a shared origin (e.g.: https: pubpeer.com publications CB23306078D45C44C2E2F6E556506D#47 ) ![file] , 
 Illustrating the comment from Senecio Gnidioides. Which is the original? ![file] ,