The Sense of Smell Impacts Metabolic Health and Obesity
Authors: Mafalda M A Pereira
Kevin Tharp
Andreas Stahl
Brigitte Hampel
Courtney M Anderson
Oliver Hahn
Linda Engström Ruud
Carlos Daniel de Magalhaes Filho
Jens Alber
Andrew Dillin
Jens C Brüning
Patricia Follett
Eva Tsaousidou
Celine E Riera
Jonathan Halloran
Hella Brönneke
Journal: Cell metabolism (2017)
Discipline: MOLECULAR BIOLOGY & GENETICS
Keywords: diet-induced obesity; energy balance; hyperosmia; hyposmia; insulin resistance
Affiliations: Howard Hughes Medical Institute and Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Paul F. Glenn Center for Aging Research, University of California, Berkeley, Berkeley, CA, USA; Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA, USA., Department of Neuronal Control of Metabolism, Max Planck Institute for Metabolism Research, Gleueler Strasse 50, Cologne, Germany; Center for Endocrinology, Diabetes and Preventive Medicine (CEDP), University Hospital Cologne, Kerpener Strasse 26, Cologne, Germany; Max Planck Institute for Biology of Ageing, Cologne, Germany and Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (CECAD) Cologne, Germany; Department of Genetics and Complex Diseases and Sabri Ülker Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA., Howard Hughes Medical Institute and Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Paul F. Glenn Center for Aging Research, University of California, Berkeley, Berkeley, CA, USA., The Salk Institute for Biological Studies, 10010 North Torrey Pines Road, La Jolla, CA, USA., Max Planck Institute for Biology of Ageing, Cologne, Germany and Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (CECAD) Cologne, Germany., Department of Neuronal Control of Metabolism, Max Planck Institute for Metabolism Research, Gleueler Strasse 50, Cologne, Germany; Center for Endocrinology, Diabetes and Preventive Medicine (CEDP), University Hospital Cologne, Kerpener Strasse 26, Cologne, Germany., Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA, USA., Department of Neuronal Control of Metabolism, Max Planck Institute for Metabolism Research, Gleueler Strasse 50, Cologne, Germany; Center for Endocrinology, Diabetes and Preventive Medicine (CEDP), University Hospital Cologne, Kerpener Strasse 26, Cologne, Germany; Max Planck Institute for Biology of Ageing, Cologne, Germany and Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (CECAD) Cologne, Germany. Electronic address: ., Howard Hughes Medical Institute and Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Paul F. Glenn Center for Aging Research, University of California, Berkeley, Berkeley, CA, USA. Electronic address: .

Abstract:  Olfactory inputs help coordinate food appreciation and selection, but their role in systemic physiology and energy balance is poorly understood. Here we demonstrate that mice upon conditional ablation of mature olfactory sensory neurons (OSNs) are resistant to diet-induced obesity accompanied by increased thermogenesis in brown and inguinal fat depots. Acute loss of smell perception after obesity onset not only abrogated further weight gain but also improved fat mass and insulin resistance. Reduced olfactory input stimulates sympathetic nerve activity, resulting in activation of β-adrenergic receptors on white and brown adipocytes to promote lipolysis. Conversely, conditional ablation of the IGF1 receptor in OSNs enhances olfactory performance in mice and leads to increased adiposity and insulin resistance. These findings unravel a new bidirectional function for the olfactory system in controlling energy homeostasis in response to sensory and hormonal signals. 

Retracted: No

PubPeer comments:
 A look at the data presented in this paper does not support the interpretation put forwards by the authors. Indeed, if approaching these experiments with a decent prior one should not be surprised by any of it: Crucially, the hyposmic mice eat 10% less (in the HFD arm, Fig 1H) and spend at least twice the time looking for food (Fig 1B). The authors assert that this group does not have more overall  physical activity , however it is not clear how this is ascertained; there is only a brief mention of this in the methods. Even if inclined to accept that the total amount of physical activity doesn t change between the groups, there s a clear under-eating effect as well as a significant effect of the treatment that makes them hyposmic (Fig 1C, which shows that even on normal chow, treatment has a small, but significant effect). These results should be taken to show that mice that cannot smell, take longer to find food and eat less of it, thus slowing down their weight gain. Is this not what we would all have predicted? From this interpretation to  a new bidirectional function for the olfactory system in controlling energy homeostasis in response to sensory and hormonal signals is a long way to go. , 
 #2 Dear Alosa Sapidissima, thanks for your interest in this article. First of all, we want to draw your attention on the activity data. These hyposmic animals move as much as wild-type. In figure 1b data are not a physical activity assay, as mice can smell odors without moving. We later thoroughly measured physical activity using Columbus Instruments systems. http: www.colinst.com products clams-comprehensive-lab-animal-monitoring-system It measures triple axis detection of animal motion using IR photocell technology. Interruption of an IR beam will accrue one  count . Coverage in a single plane may be implemented with IR photocells located in the X or XY direction. The height of these beams is such that they intersect the animal midway vertically. Placement of IR photocells at a height above the animal detect rearing or jumping (Z-axis). Systems may be configured for X, XY, XZ or XYZ coverage. We do agree and report that the hyposmic animals eat less in figure 1, which participates in their lean phenotype. However, two weeks post toxin injections, oxygen consumption and energy expenditure are enhanced compared to controls relative to lean body mass (Figure 3 A and B). The entire figure 4 shows that thermogenesis is enhanced in these mice as well. We then carry on two different experiments where food intake in unaltered, and where we observe a lean phenotype. In figure 2, we ablate olfactory neurons using a viral approach and also observe a leaner phenotype as well as decreased olfactory acuity. In figure 5, we use the genetic model again but this time ablate olfactory neurons in fat mice to observe increased energy expenditure, fat loss without differences in food intake. , 
 #1 We thank the commenter for his her interest in our study. The commenter is perfectly right that physiologically a negative value for suppression of HGP (suppression below zero) is not plausible. Nevertheless, negative HGP values during euglycemic-hyperinsuninemic clamps have been descibed since more than 3 decades, and there have been numerous articles on this subject (Finegood et al., 1987; Finegood et al., 1988; Ayala et al., 2010). This occurs particularly at high glucose infusion rates (such as observed in our study) and relates to insufficient modeling. However, the recommendation of consensus papers from leading scientists in the field, clearly indicate not to remove negative values and not to automatically set those to zero (Ayala et al., 2010). Thus, when comparing genotypes in an identical experimental setup, a genotype-dependent difference in a systematically underestimated HGP still points towards a biological difference in this parameter. In addition, while glucose infusion rates during steady state were reduced in OMP-IGF-1R knockout mice, tissue-specific glucose uptake rates remained unaltered (Suppl. Fig. 7K), providing further evidence that reduced suppression of glucose production predominantly accounts for the insulin resistance observed in these mice. Nevertheless, we will continue our efforts to further improve our clamp protocol through the inclusion of hot GINF. , 
 It s striking that Dr. Dillon did not address the first comment about Fig 7G. I suspect that is because the commenter is 100% correct in commenting that comparing a negative HGP to ~0 is BS. Especially a negative HGP of 10! That s an error in the method. Not uncommon, but still not a meaningful number. , 
 #4 I m confused. The authors agree that negative HGP is not plausible. So why use them? It s a judgement call about how negative is too much, i.e. is comparing an unreal number to 0 valid? As Dr. Burning notes, this is point that has been discussed (see citations from him). It suggests an error with the tracer infusion, the pumps, and perhaps too high of an insulin dose. However, the point those authors make is to report them as negative, not 0, which some do (although this is never mentioned in the papers). The challenge here is that if there is no statistical difference in clamp HGP, then the clamp shows no differences at all and all claims about insulin resistance based on GTTs and ITTs are unsupported using a better technique. Another point to note is that steady state GIR is NOT statistically significant (7C) although the paper indicates that it is and Dr. Bruning reiterates above. GIR AUC in 7E is, but that is not solely steady state as far as one can tell. Also, basal blood glucose levels in both groups are ~ 250 mg dL likely indicating lots of stress due to restraint. So there s no difference in steady state GIR and the only different tracer data is questionable. Also... - 7H indicates the effect on HGP is due to the vagus and three papers are cited. There are also many to support a role for the SNS, but these are not mentioned and there were no experiments here to test that conclusion. - ITTs oddly use both raw numbers and percent change from basal. No rhyme or reason is given. - Dr. Bruning notes the glucose uptake data as 7K, but in the paper it s listed as S8H and insulin is in S8I. Yet there is no Supplemtsry Fig 8. Seems Cell Metab dropped the ball getting a knowledgeable reviewer for metabolic data. , 
 This is from the results:  When we assessed hepatic glucose production (HGP), IGF1RDOMP and control mice exhibited no significant differences in baseline, but IGF1RDOMP mice exhibited a reduced ability of insulin to suppress HGP (Figure 7G). And this from the discussion:  Strikingly, insulinu2019s ability to suppress HGP is impaired in these animals, pointing to a new role for IGF1 in OSNs in the control of peripheral insulin resistance (Figure 7G). Now here is the HGP data:![file] HGP is completely suppressed in both genotypes during the clamp. Negative HGP are not physiologically plausible (need to use hot GINF with clamp to avoid this) and therefore you cannot say that a negative HGP is different to a HGP of 0! Doesn t seem like a striking differences in the ability of insulin to suppress HGP at all. Just a failure of the authors to interpret the data properly and acknowledge the well-known issues of negative HGP values. Also, the serum FFAs (Fig 3 D) appear a touch low. ![file] , 
 #1 In 3E, leptin levels are way too high. Serum leptin should be in pg ml: http: phenome.jax.org measureset 17841 , 
 Starting glucose levels in 2F are also much higher than expected, when compared to the other performed GTT and ITT. , 
 #5 Totally agree with the above criticisms of the glucose clamp. Assuming that glucose production was completely suppressed, it is possible to obtain slightly negative values due to noise and experimental errors; however, -10 mg kg min looks like experimental failure or calculation mistake. Moreover, insulin levels during the clamp period should have been evaluated and reported. The data cannot be interpreted without this information. , 
 #7 To Nepenthes Chaniana. Indeed, this seems a big mistake for a journal such as Cell Metab. Moreover, the body weight curves in 1C and 2C are surprising;Whereas the average body weight seems identical between groups, the graphs claim statistically differences with a significance of p 0.001. , 
 In regards to the serum leptin levels, I think the JAX measurements quoted in reply #7 are wrong. Potentially they meant pg u00b5L. Leptin values in humans are in the ng mL range and all of the publications I could find in mice show the same thing (for example: , . , 
 #7 One would expect leptin to be a between 2 and 10 ng ml in a non-obese mouse, certainly not 60 mg ml. ,