PPARG expression patterns and correlations in obesity
Open accessAbstract
Obesity is a result of excess fat storage in tissues and may lead to local insulin resistance and inflammation. Obesity is a multifactorial event and may include dysregulation of certain genes, such as peroxisome proliferator activated receptor gamma (PPARG). PPARG plays a key role in adipogenesis and adipocyte gene expression. Our study aimed to determine the regulatory role of PPARG in obesity. Serum samples from obese, non-obese(controls), diabetic obese and diabetic individuals were collected, and total RNA was extracted. RNA was reversed to cDNA and real time PCR technology was used to quantify differential PPARG gene expression in serum of obese patients and in diabetic obese patients (BMI > 30 kg/m2) versus non-obese and diabetic controls. Anthropometric parameters were recorded, and laboratory measurements were performed for each subject. Demographic and biochemical characteristics were studied for their correlation to PPARG mRNA in each group. The data were analyzed using an ANOVA analysis (p < 0.05). PPARG mRNA expression is most abundant in serum of obese patients both diabetic and non-diabetic. However, differential level of PPARG mRNA expression was seen in diabetic patients without obesity being only 40% of group subjects showed overexpressed PPARG in serum. A statistically significant differences were observed for mean TGs, TC, LDLc and HDLc levels among groups. There was a strong positive correlation between PPARG mRNA and the body mass index, waist circumference (WC) and waist–hip ratio (WHR) of obese patients.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Certain microbial profiles efficiently harvest energy from food and produce SCFAs like acetate, propionate, and butyrate, which can stimulate lipogenesis, particularly by activating SREBP-1c.
“Certain microbial profiles efficiently harvest energy from food and produce short-chain fatty acids (SCFAs) like acetate, propionate, and butyrate, which can stimulate lipogenesis, particularly by activating SREBP-1c [49].”
From Beyond Calories: Individual Metabolic and Hormonal Adaptations Driving Variability in Weight Management—A State-of-the-Art Narrative Review (2024) · cites this paper as [49]
Adipocytes vary in their ability to proliferate and differentiate in response to caloric surplus.
“Adipocytes vary not only in size but also in their ability to proliferate and differentiate in response to caloric surplus.”
From Beyond Calories: Individual Metabolic and Hormonal Adaptations Driving Variability in Weight Management—A State-of-the-Art Narrative Review (2024) · cites this paper as [49]
Individual differences in PPARγ expression and responsiveness influence adipogenic potential, affecting whether surplus calories are stored in adipose tissue or lead to ectopic fat accumulation.
“However, individual differences in PPARγ expression and responsiveness influence adipogenic potential, affecting whether surplus calories are efficiently stored in adipose tissue or lead to ectopic fat accumulation in non-adipose tissues like liver and muscle.”
From Beyond Calories: Individual Metabolic and Hormonal Adaptations Driving Variability in Weight Management—A State-of-the-Art Narrative Review (2024) · cites this paper as [49]
During overfeeding, PPARγ activation facilitates differentiation of preadipocytes into mature adipocytes, increasing the body's ability to store excess lipids.
“During overfeeding, PPARγ activation facilitates the differentiation of preadipocytes into mature adipocytes, increasing the body’s ability to store excess lipids.”
From Beyond Calories: Individual Metabolic and Hormonal Adaptations Driving Variability in Weight Management—A State-of-the-Art Narrative Review (2024) · cites this paper as [49]
Epigenetic modifications such as methylation of the PPARγ promoter can enhance or inhibit adipogenic capacity, influencing individual fat gain patterns.
“Epigenetic modifications, such as methylation of the PPARγ promoter, can either enhance or inhibit this capacity, further influencing individual fat gain patterns [49].”
From Beyond Calories: Individual Metabolic and Hormonal Adaptations Driving Variability in Weight Management—A State-of-the-Art Narrative Review (2024) · cites this paper as [49]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Friedewald, W. T., Levy, R. I., & Fredrickson, D. S. (1972) · Clinical Chemistry · doi:10.1093/clinchem/18.6.499 · Cited by 32,423 · see citing works
2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2021</i>
American Diabetes Association (2021) · Diabetes Care · doi:10.2337/dc21-s002 · Cited by 3,116 · see citing works
The Epidemiology of Obesity: A Big Picture
Hruby, A., & Hu, F. B. (2014) · PharmacoEconomics · doi:10.1007/s40273-014-0243-x · Cited by 3,006 · see citing works
Association between insulin resistance and the development of cardiovascular disease
Ormazábal, V., Nair, S., Elfeky, O. W. M., Aguayo, C. R., Salomón, C., & Zuñiga, F. A. (2018) · Cardiovascular Diabetology · doi:10.1186/s12933-018-0762-4 · Cited by 2,344 · see citing works
Inflammatory links between obesity and metabolic disease
Lumeng, C. N., & Saltiel, A. R. (2011) · Journal of Clinical Investigation · doi:10.1172/jci57132 · Cited by 2,319 · see citing works
Jung, U. J., & Choi, M. (2014) · International Journal of Molecular Sciences · doi:10.3390/ijms15046184 · Cited by 1,898 · see citing works
Adipose tissue dysfunction as determinant of obesity-associated metabolic complications
Longo, M., Zatterale, F., Naderi, J., Parrillo, L., Formisano, P., Raciti, G. A., Beguinot, F., & Miele, C. (2019) · International Journal of Molecular Sciences · doi:10.3390/ijms20092358 · Cited by 1,575 · see citing works
Manna, P., & Jain, S. K. (2015) · Metabolic Syndrome and Related Disorders · doi:10.1089/met.2015.0095 · Cited by 1,167 · see citing works
Acute-phase proteins: As diagnostic tool
Jain, S., Gautam, V., & Naseem, S. (2011) · Journal of Pharmacy And Bioallied Sciences · doi:10.4103/0975-7406.76489 · Cited by 656 · see citing works
PPARγ and the global map of adipogenesis and beyond
Lefterova, M. I., Haakonsson, A. K., Lazar, M. A., & Mandrup, S. (2014) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2014.04.001 · Cited by 629 · see citing works
Prevention of Overweight and Obesity: How Effective is the Current Public Health Approach
Chan, R., & Woo, J. (2010) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph7030765 · Cited by 459 · see citing works
Downregulation of Adipose Tissue Fatty Acid Trafficking in Obesity
McQuaid, S. E., Hodson, L., Neville, M. J., Dennis, A. L., Cheeseman, J., Humphreys, S. M., Ruge, T., Gilbert, M., Fielding, B. A., Frayn, K. N., et al. (2011) · Diabetes · doi:10.2337/db10-0867 · Cited by 366 · see citing works
Wagner, N., & Wagner, K. (2020) · Cells · doi:10.3390/cells9112367 · Cited by 279 · see citing works
Genetics of Obesity: What have we Learned?
Choquet, H., & Meyre, D. (2011) · Current Genomics · doi:10.2174/138920211795677895 · Cited by 238 · see citing works
Debey, S., Schoenbeck, U., Hellmich, M., Gathof, B. S., Pillai, R., Zander, T., & Schultze, J. L. (2004) · The Pharmacogenomics Journal · doi:10.1038/sj.tpj.6500240 · Cited by 214 · see citing works
Macrophage function in obesity-induced inflammation and insulin resistance
Lauterbach, M., & Wunderlich, F. T. (2017) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-017-1955-5 · Cited by 209 · see citing works
Peroxisome proliferator-activated receptors as targets to treat non-alcoholic fatty liver disease
Souza-Mello, V. (2015) · World Journal of Hepatology · doi:10.4254/wjh.v7.i8.1012 · Cited by 182 · see citing works
Decara, J. M., Rivera, P., López-Gambero, A. J., Serrano, A., Pavón, F. J., Baixerás, E., de Fonseca, F. R., & Suárez, J. (2020) · Frontiers in Pharmacology · doi:10.3389/fphar.2020.00730 · Cited by 182 · see citing works
PPARs-Orchestrated Metabolic Homeostasis in the Adipose Tissue
Sun, C., Mao, S., Chen, S., Zhang, W., & Liu, C. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22168974 · Cited by 140 · see citing works
Gene expression profiling of peripheral blood cells for early detection of breast cancer
Aarøe, J., Lindahl, T., Dumeaux, V., Sæbø, S., Tobin, D., Hagen, N., Skaane, P., Lönneborg, A., Sharma, P., & Børresen‐Dale, A. (2010) · Breast Cancer Research · doi:10.1186/bcr2472 · Cited by 117 · see citing works
PPARG (Pro12Ala) genetic variant and risk of T2DM: a systematic review and meta-analysis
Sarhangi, N., Sharifi, F., Hashemian, L., Doabsari, M. H., Heshmatzad, K., Rahbaran, M., Jamaldini, S. H., Meybodi, H. R. A., & Hasanzad, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-69363-7 · Cited by 100 · see citing works
Mechanistic Insight into PPARγ and Tregs in Atherosclerotic Immune Inflammation
Gao, Z., Xu, X.-R., Li, Y., Sun, K.-H., Yang, M.-F., Zhang, Q., Wang, S., Lin, Y., Lou, L., Wu, A., et al. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.750078 · Cited by 52 · see citing works
Whole blood vs PBMC: compartmental differences in gene expression profiling exemplified in asthma
He, D. X., Yang, C. X., Sahin, B., Singh, A., Shannon, C. P., Oliveria, J. P., Gauvreau, G. M., & Tebbutt, S. J. (2019) · Allergy Asthma and Clinical Immunology · doi:10.1186/s13223-019-0382-x · Cited by 47 · see citing works
Torres, J. L., Usategui‐Martín, R., Hernández‐Cosido, L., Bernardo, E., Manzanedo-Bueno, L., Hernández-García, I., Mateos-Díaz, A.-M., Rozo, O., Matesanz, N., Salete-Granado, D., et al. (2021) · Journal of Gastrointestinal Surgery · doi:10.1007/s11605-021-05216-6 · Cited by 36 · see citing works
Nair, A. R., Silva, S. D., Agbor, L. N., Wu, J. F., Nakagawa, P., Mukohda, M., Lu, K., Sandgren, J. A., Pierce, G. L., Santillan, M. K. O., et al. (2019) · Hypertension · doi:10.1161/hypertensionaha.119.13101 · Cited by 29 · see citing works
Odenigbo, U. M., Odenigbo, U., Oguejiofor, O., & Adogu, P. O. U. (2010) · Pakistan Journal of Nutrition · doi:10.3923/pjn.2011.15.18 · Cited by 26 · see citing works
Black, M. H., Wu, J., Takayanagi, M., Wang, N., Taylor, K. D., Haritunians, T., Trigo, E., Lawrence, J. M., Watanabe, R. M., Buchanan, T. A., et al. (2015) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2014-3246 · Cited by 25 · see citing works
Cataldi, S., Aprile, M., Melillo, D., Mucel, I., Giorgetti‐Peraldi, S., Cormont, M., Italiani, P., Blüher, M., Tanti, J., Ciccodicola, A., et al. (2021) · Cells · doi:10.3390/cells11010042 · Cited by 19 · see citing works
Adipocyte Biology from the Perspective of In Vivo Research: Review of Key Transcription Factors
Evseeva, M. N., Balashova, M. S., Kulebyakin, K. Y., & Rubtsov, Y. P. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms23010322 · Cited by 19 · see citing works
PPAR Gamma at the Crossroads of Health and Disease: A Masterchef in Metabolic Homeostasis
Akoum, S. E. (2014) · Endocrinology & Metabolic Syndrome · doi:10.4172/2161-1017.1000126 · Cited by 13 · see citing works
Darwish, N., Elnahas, Y. M., & AlQahtany, F. S. (2020) · Saudi Journal of Biological Sciences · doi:10.1016/j.sjbs.2020.10.039 · Cited by 13 · see citing works
Self-citationAbaj, F., Sotoudeh, G., Karimi, E., Rafiee, M., & Koohdani, F. (2021) · International Journal of Clinical Practice · doi:10.1111/ijcp.14307 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- Gahagan, S.R.M, Kliegman, R.E, Behrman, H.B, Jenson B.F. Overweight and obesity. Nelson textbook of paediatrics. 2011: 19th edition, Philadelphia, Pa: Saunders Elsevier. Chap., 44.
Cited by
Sorted by citations
Theodorakis, N., Kreouzi, M., Pappas, A., & Nikolaou, M. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms252413438 · Cited by 43 · see citing works
- Authors
- Darwish, N. M., Gouda, W., Almutairi, S. M., Elshikh, M. S., & Morcos, G. N. B.
- Affiliations
- Ain Shams University (EG)
- Al-Azhar University (EG)
- King Saud University (SA)
- King Salman International University (EG)
- Corresponding author
- Elshikh, Mohamed S.
- Venue
- Journal of King Saud University - Science
- Publisher
- Scientific Scholar
- Published
- 2022-08
- Volume
- 34
- Issue
- 6
- Pages
- 102116
- ISSN
- 1018-3647 (ISSN-L)
- OpenAlex
- W4281399700
- Cited by
- 24
- References
- 32
- Citations by year
- 2026: 4 · 2025: 12 · 2024: 4 · 2023: 1 · 2022: 3
- FWCI
- 1.63
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal of King Saud University - Science (publishedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- King Saud University (RSP2022R470)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Peroxisome Proliferator-Activated Receptors
- Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
- Keywords
- PPARγ, obesity, type 2 diabetes, serum gene expression, body mass index, waist circumference, waist-to-hip ratio, lipid profile, adipogenesis, insulin resistance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
