Research
Theme 1 : Using genetic associations to identify causal mechanisms underlying cardio-metabolic phenotypes.
The failure of traditional SNP-centric analysis to reveal biological mechanisms underlying genetic susceptibility to common disorders has led to alternative analytic approaches. My group has extensively applied an ensemble-based approach, known as ‘systems genetics’, to interrogate the accumulated effect of genetic polymorphisms in biological pathways and functional interaction networks. These approaches have led to the identification of novel causal mechanisms underlying a variety of cardio-metabolic traits such as coronary artery disease, obesity and cardiorespiratory fitness.
Considerations on efforts needed to improve our understanding of the genetics of obesity.
Ghosh S, Bouchard C.
Int J Obes (Lond). 2024 Jun 7. doi:10.1038/s41366-024-01528-0. [Epub ahead of print] Review. PMID: 38849463
Exploring the underlying biology of intrinsic cardiorespiratory fitness through integrative analysis of genomic variants and muscle gene expression profiling.
Ghosh S, Hota M, Chai X, Kiranya J, et al.
J Appl Physiol (1985). 2019 May 1;126(5):1292-1314. doi:10.1152/japplphysiol.00035.2018. Epub 2019 Jan 3. PMID: 30605401; PMCID:PMC6589809
Convergence between biological, behavioural and genetic determinants of obesity.
Ghosh S, Bouchard C.
Nat Rev Genet. 2017 Dec;18(12):731-748. doi:10.1038/nrg.2017.72. Epub 2017 Oct 9. PMID: 28989171
Systems Genetics Analysis of Genome-Wide Association Study Reveals Novel Associations Between Key Biological Processes and Coronary Artery Disease.
Ghosh S, Vivar J, Nelson CP, Willenborg C, et al.
Arterioscler Thromb Vasc Biol. 2015 Jul;35(7):1712-22. doi:10.1161/ATVBAHA.115.305513. Epub 2015 May 14. PMID:25977570; PMCID: PMC4841833.
Theme 2 : Integrative bioinformatics analysis for elucidation of disease associated biology.
The challenge with high dimensional ‘omics’-datasets is their interpretability. My group applies advanced bioinformatic analysis methods involving functional class scoring and functional interactome analysis on a wide range of studies involving diverse phenotypes. These analyses have significantly increased our understanding of the global transcriptomic, proteomic and metabolomic changes in biological mechanisms that are associated with the studied outcomes.
Omics-driven investigation of the biology underlying intrinsic submaximal working capacity and its trainability.
Hota M, Barber JL, Ruiz-Ramie JJ, Schwartz CS, Lam DTUH, Rao P, Mi MY, Katz DH, Robbins JM, Clish CB, Gerszten RE, Sarzynski MA, Ghosh S, Bouchard C.
Physiol Genomics. 2023 Nov 1;55(11):517-543. doi: 10.1152/physiolgenomics.00163.2022. Epub 2023 Sep 4. PubMed [citation] PMID: 37661925, PMCID: PMC11178266
Human plasma proteomic profiles indicative of cardiorespiratory fitness.
Robbins JM, Peterson B, Schranner D, Tahir UA, et al..
Nat Metab. 2021 Jun;3(6):786-797. doi: 10.1038/s42255-021-00400-z. Epub 2021 May 27.
Extensive metabolic remodeling after limiting mitochondrial lipid burden is consistent with an improved metabolic health profile.
Ghosh S, Wicks SE, Vandanmagsar B, Mendoza TM, et al.
J Biol Chem. 2019 Aug 16;294(33):12313-12327. doi:10.1074/jbc.RA118.006074. Epub 2019 May 16. PMID: 31097541; PMCID: PMC6699851.
Siah2 modulates sex-dependent metabolic and inflammatory responses in adipose tissue to a high-fat diet challenge.
Ghosh S, Taylor JL, Mendoza TM, Dang T, Burk DH, Yu Y, Kilroy G, Floyd ZE.
Biol Sex Differ. 2019 Apr 15;10(1):19. doi: 10.1186/s13293-019-0233-y. Erratum in: Biol Sex Differ. 2019 Jul 22;10(1):38. doi: 10.1186/s13293-019-0252-8. PMID: 30987673; PMCID: PMC6466809.
Theme 3 : Genomic responses to nutrient variation in key metabolic tissues.
The response of the transcriptome to nutritional cues (e.g. excess or deficiency of nutrients, caloric restriction) allows one to infer metabolic adaptations to altered energy supply. In this context, we have investigated the effects of key metabolic enzyme deficiency and methionine restriction in key metabolic tissues in humans and animal models, as well as the effects of nutrient supplementation on adipocyte differentiation in culture. These studies have generated important insights into tissue-specific global transcriptomic responses to nutrient perturbations and helped explain the mechanistic bases underlying physiologic observations.
Naringenin and β-carotene convert human white adipocytes to a beige phenotype and elevate hormone- stimulated lipolysis.
Coulter AA, Greenway FL, Zhang D, Ghosh S, Coulter CR, James SL, He Y, Cusimano LA, Rebello CJ.
Front Endocrinol (Lausanne). 2023 Apr 17;14:1148954. doi: 10.3389/fendo.2023.1148954. PMID: 37143734, PMCID: PMC10153092
Implementation of dietary methionine restriction using casein after selective oxidative deletion of methionine.
Fang H, Stone KP, Forney LA, Sims LC, Gutierrez GC, Ghosh S, Gettys TW.
iScience. 2021 Apr 24;24(5):102470. doi:10.1016/j.isci.2021.102470. PMID: 34113817
FGF21 prevents low-protein diet-induced renal inflammation in aged mice.
Fang H, Ghosh S, Sims LC, Stone KP, Hill CM, Spires D, Ilatovskaya DV, Morrison CD, Gettys TW, Stadler K.
Am J Physiol Renal Physiol. 2021 Sep 1;321(3):F356-F368. doi: 10.1152/ajprenal.00107.2021. PMID: 34151592
An integrative analysis of tissue-specific transcriptomic and metabolomic responses to short-term dietary methionine restriction in mice.
Ghosh S, Forney LA, Wanders D, Stone KP, Gettys TW.
PLoS One. 2017 May 16;12(5):e0177513. doi:10.1371/journal.pone.0177513. PMID: 28520765