Novel perspectives of sodium handling in type 2 diabetes mellitus

Hanson, Petra; Arkill, Kenton P.; Merry, Catherine L. R.; Hussain, Mohammed; Meersmann, Thomas; Randeva, Harpal S.; Pavlovskaya, Galina E.; O'Hare, Paul; Barber, Thomas M.

doi:10.1080/17446651.2022.2092094

Cited by 1 publication

(2 citation statements)

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“…In addition, T2D patients are known to be predisposed to sodium retention from the early stages of the disease 63 . It has been thought that hyperglycemia and the associated diuresis, glucosuria, and hyperinsulinemia cause upregulation of renal glucose transporters and sodium channels, leading to increased renal sodium reabsorption 64 , 65 . On the other hand, recent studies using 23 Na magnetic resonance imaging have reported that sodium can be stored in the skin in an osmotically inactive form and that this dermal Na-binding capacity is reduced in T2D patients 60 , 66 .…”

Section: Discussionmentioning

confidence: 99%

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Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients

Nakazato

Shimoyama

Cohen

et al. 2023

Sci Rep

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Increased intra-individual variability of a variety of biomarkers is generally associated with poor health and reflects physiological dysregulation. Correlations among these biomarker variabilities should then represent interactions among heterogeneous biomarker regulatory systems. Herein, in an attempt to elucidate the network structure of physiological systems, we probed the inter-variability correlations of 22 biomarkers. Time series data on 19 blood-based and 3 hemodynamic biomarkers were collected over a one-year period for 334 hemodialysis patients, and their variabilities were evaluated by coefficients of variation. The network diagram exhibited six clusters in the physiological systems, corresponding to the regulatory domains for metabolism, inflammation, circulation, liver, salt, and protein. These domains were captured as latent factors in exploratory and confirmatory factor analyses (CFA). The 6-factor CFA model indicates that dysregulation in each of the domains manifests itself as increased variability in a specific set of biomarkers. Comparison of a diabetic and non-diabetic group within the cohort by multi-group CFA revealed that the diabetic cohort showed reduced capacities in the metabolism and salt domains and higher variabilities of the biomarkers belonging to these domains. The variability-based network analysis visualizes the concept of homeostasis and could be a valuable tool for exploring both healthy and pathological conditions.

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Section: Discussionmentioning

confidence: 99%

“…In the diabetic HD patients, GA levels do not appear to be associated with dysregulation in any of the domains (Table 3 ), making it unlikely that hyperglycemia itself is causing sodium dysregulation. In this regard, the decreased dermal sodium-binding capacity seems to be one plausible cause of this dysregulation 64 .…”

Section: Discussionmentioning

confidence: 99%