2015
DOI: 10.1507/endocrj.ej14-0431
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Age-related changes in the diurnal variation of ketogenesis in patients with type 2 diabetes and relevance to hypoglycemic medications

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Cited by 8 publications
(6 citation statements)
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References 35 publications
(30 reference statements)
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“…Recently, we have reported that the plasma levels of 3HB and FFA show marked diurnal fluctuation in patients with type 2 diabetes, with two obvious peaks before breakfast and before dinner. Furthermore, the peak levels were inversely correlated with age 28 . The administration of sulfonylureas or DPP-4 inhibitors was shown to suppress the plasma 3HB levels, likely through their insulinotropic and/or glucagonstatic action.…”
Section: Discussionmentioning
confidence: 93%
See 1 more Smart Citation
“…Recently, we have reported that the plasma levels of 3HB and FFA show marked diurnal fluctuation in patients with type 2 diabetes, with two obvious peaks before breakfast and before dinner. Furthermore, the peak levels were inversely correlated with age 28 . The administration of sulfonylureas or DPP-4 inhibitors was shown to suppress the plasma 3HB levels, likely through their insulinotropic and/or glucagonstatic action.…”
Section: Discussionmentioning
confidence: 93%
“…Furthermore, the peak levels were inversely correlated with age28. The administration of sulfonylureas or DPP-4 inhibitors was shown to suppress the plasma 3HB levels, likely through their insulinotropic and/or glucagonstatic action.…”
Section: Discussionmentioning
confidence: 93%
“…This suggests that 12.1% of those with an EI/BMR <1.35 and ketone body level ≥1.0 mmol/l included underreporters and those who reported extreme energy restriction practices at the time of the dietary survey and blood test. However, because ketone bodies are known to exhibit diurnal variation (24), further investigation is needed to determine the extent to which ketone body values in a single blood sample reflect temporary energy deficits in obese individuals. In recent years, ketone bodies have been measured simply and accurately using small devices (25).…”
Section: Discussionmentioning
confidence: 99%
“…The role of metabolites in explaining network differences is more nuanced, and this probably reflects the large biochemical diversity of these molecules [106]. In diseases-specific networks, key differentiating metabolites are ketone bodies, BCAAs, threonine, and tyrosine (in women networks only), and alanine: this can reflect the association with particular diseases, such as type 1 and 2 diabetes mellitus [91,[107][108][109][110], sarcopenia [69,71,72,111] and cognitive impairment [112,113]. Glutamine, glucose, proline, and BCAAs, increasing their metabolic activity, could be biomarkers to predict the emergence of neurodegenerative diseases [114], type 2 diabetes mellitus, and obesity conditions [91,108,109], and sarcopenia [69,71,72].…”
Section: Similarities and Dissimilarities In Different Sex-related Clinical Variables-specific Networkmentioning
confidence: 99%