The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Fatty Pancreas, Insulin Resistance, and β-Cell Function: A Population Study Using Fat-Water Magnetic Resonance Imaging
Abstract
OBJECTIVES: Nonalcoholic fatty liver disease is the most common chronic liver disease. Fatty pancreas has also been described but is difficult to assess. It is now possible to measure pancreatic and liver fat accurately with magnetic resonance imaging (MRI). We aimed to define the normal range of pancreatic fat and identify factors associated with fatty pancreas. In addition, the effect of fatty liver and fatty pancreas on insulin resistance (IR) and pancreatic β-cell function was studied. METHODS: Fat-water MRI and proton-magnetic resonance spectroscopy were performed on 685 healthy volunteers from the general population to measure pancreatic and liver fat, respectively. On the basis of fasting plasma glucose and insulin levels, the IR and β-cell function were assessed using the homeostasis model assessment (HOMA). RESULTS: Among subjects without significant alcohol consumption or any component of metabolic syndrome, 90% had pancreatic fat between 1.8 and 10.4%. Using the upper limit of normal of 10.4%, 110 (16.1%; 95% confidence interval 13.3-18.8%) subjects had fatty pancreas. On multivariable analysis, high serum ferritin, central obesity, and hypertriglyceridemia were independent factors associated with fatty pancreas. Subjects with both fatty pancreas and fatty liver had higher HOMA-IR than did those with either condition alone. Fatty pancreas was not associated with HOMA-β after adjusting for liver fat and body mass index. CONCLUSIONS: In all, 16.1% of this community cohort of adult Hong Kong Chinese volunteers had a fatty pancreas by our definition. Central obesity, hypertriglyceridemia, and hyperferritinemia are associated with fatty pancreas. Individuals with fatty pancreas have increased IR.
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Alberti, K. G. M. M., Eckel, R. H., Grundy, S. M., Zimmet, P. Z., Cleeman, J. I., Donato, K. A., Fruchart, J.-C., James, W. P. T., Loria, C. M., & Smith, S. C. (2009) · Circulation · doi:10.1161/circulationaha.109.192644 · Cited by 14,860
Use and Abuse of HOMA Modeling
Wallace, T. M., Levy, J. C., & Matthews, D. R. (2004) · Diabetes Care · doi:10.2337/diacare.27.6.1487 · Cited by 5,114
Prevalence of Hepatic Steatosis in An Urban Population in the United States: Impact of Ethnicity
Browning, J. D., Szczepaniak, L. S., Dobbins, R., Nuremberg, P., Horton, J. D., Cohen, J. C., Grundy, S. M., & Hobbs, H. H. (2004) · Hepatology · doi:10.1002/hep.20466 · Cited by 3,664
Genetic variation in PNPLA3 confers susceptibility to nonalcoholic fatty liver disease
Romeo, S., Kozlitina, J., Xing, C., Pertsemlidis, A., Cox, D., Pennacchio, L. A., Boerwinkle, E., Cohen, J. C., & Hobbs, H. H. (2008) · Nature Genetics · doi:10.1038/ng.257 · Cited by 3,416
The Natural History of Nonalcoholic Fatty Liver Disease: A Population-Based Cohort Study
Adams, L. A., Lymp, J. F., St. Sauver, J., Sanderson, S. O., Lindor, K. D., Feldstein, A., & Angulo, P. (2005) · Gastroenterology · doi:10.1053/j.gastro.2005.04.014 · Cited by 2,890
Nonalcoholic Fatty Liver Disease
Marchesini, G., Brizi, M., Bianchi, G., Tomassetti, S., Bugianesi, E., Lenzi, M., McCullough, A. J., Natale, S., Forlani, G., & Melchionda, N. (2001) · Diabetes · doi:10.2337/diabetes.50.8.1844 · Cited by 2,581
Long-term follow-up of patients with NAFLD and elevated liver enzymes
Ekstedt, M., Franzén, L. E., Mathiesen, U. L., Thorelius, L., Holmqvist, M., Bodemar, G., & Kechagias, S. (2006) · Hepatology · doi:10.1002/hep.21327 · Cited by 2,302
Williams, C. D., Stengel, J., Asike, M. I., Torres, D. M., Shaw, J., Contreras, M., Landt, C. L., & Harrison, S. A. (2011) · Gastroenterology · doi:10.1053/j.gastro.2010.09.038 · Cited by 2,148
Ogden, C. L., Yanovski, S. Z., Carroll, M. D., & Flegal, K. M. (2007) · Gastroenterology · doi:10.1053/j.gastro.2007.03.052 · Cited by 1,561
Ascha, M. S., Hanouneh, I. A., Lopez, R., Tamimi, T. A.-R., Feldstein, A. F., & Zein, N. N. (2010) · Hepatology · doi:10.1002/hep.23527 · Cited by 1,296
Cited by
Garvey, W. T., Mechanick, J. I., Brett, E. M., Garber, A. J., Hurley, D. L., Jastreboff, A. M., Nadolsky, K., Pessah-Pollack, R., & Plodkowski, R. (2016) · Endocrine Practice · doi:10.4158/ep161365.gl · Cited by 1,914
Chait, A., & den Hartigh, L. J. (2020) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2020.00022 · Cited by 1,529
Lipid droplet biogenesis and functions in health and disease
Zadoorian, A., Du, X., & Yang, H. (2023) · Nature Reviews Endocrinology · doi:10.1038/s41574-023-00845-0 · Cited by 617
Contribution of Adipose Tissue Inflammation to the Development of Type 2 Diabetes Mellitus
Burhans, M. S., Hagman, D. K., Kuzma, J. N., Schmidt, K. A., & Kratz, M. (2018) · Comprehensive Physiology · doi:10.1002/cphy.c170040 · Cited by 373
Razavi Zade, M., Telkabadi, M. H., Bahmani, F., Salehi, B., Farshbaf, S., & Asemi, Z. (2016) · Liver International · doi:10.1111/liv.12990 · Cited by 277
Metadata
- Authors
- Wong, V. W.-S., Wong, G. L.-H., Yeung, D. K.-W., Abrigo, J. M., Kong, A. P.-S., Chan, R. S.-M., Chim, A. M.-L., Shen, J., Ho, C.-S., Woo, J., Chu, W. C.-W., & Chan, H. L.-Y.
- Venue
- American Journal of Gastroenterology
- Published
- 2014-04
- Volume
- 109
- Issue
- 4
- Pages
- 589-597
- ISSN
- 0002-9270 (ISSN-L)
- OpenAlex
- W1974990354
- Cited by
- 275
- References
- 43
- FWCI
- 10.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wong, V. W.-S., Wong, G. L.-H., Yeung, D. K.-W., Abrigo, J. M., Kong, A. P.-S., Chan, R. S.-M., Chim, A. M.-L., Shen, J., Ho, C.-S., Woo, J., Chu, W. C.-W., & Chan, H. L.-Y. (2014). Fatty Pancreas, Insulin Resistance, and β-Cell Function: A Population Study Using Fat-Water Magnetic Resonance Imaging. American Journal of Gastroenterology. https://doi.org/10.1038/ajg.2014.1
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