Literature DB >> 8860944

Glycation index of hair for non-invasive estimation of diabetic control.

K Kobayashi1, H Igimi.   

Abstract

We propose a new indicator for diabetic control that shows the extent of glycation of hair protein (keratin), the glycation index (A(390)/A(412)) which is based on the ratio of glycated protein- to cystine-induced coloration, where A(390) and A(412) represent each absorbance in the color reactions of glycated protein and cystine in the hair protein. Samples can be quickly and non-invasively collected and easily stored. This index for the back and scalp hairs from hypercholesterolemic mice with hyperglycemia, diabetic rats and diabetic patients gave significantly higher values (2.0-6.0-fold) than those of normal subjects (p<0.01). The glycation indices (mean + or - S.D.) of hairs from diabetic and non-diabetic subjects were 3.00 + or - 0.96 (n = 21) and 1.51 + or - 0.45 (n = 30), respectively. These indices (y) correlated well with the levels of glycohemoglobin (HbA(1c), chi) in diabetic and non-diabetic subjects: y = 0.69 chi- 2.03 (r = 0.82, n = 31, p<0.01). Within-run precision (reproducibility, CV) for the assay of the glycation indices of hairs from the three groups was 6.7-9.4% (n = 10 each). The proposed glycation index of hair gave reasonable results for animals and humans with normo- and hyperglycemia, suggesting that it is reliable and can be diagnostically useful.

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Year:  1996        PMID: 8860944     DOI: 10.1248/bpb.19.487

Source DB:  PubMed          Journal:  Biol Pharm Bull        ISSN: 0918-6158            Impact factor:   2.233


  3 in total

1.  Correlation between saliva glycated and blood glycated proteins.

Authors:  Ichiro Nakamoto; Kanehisa Morimoto; Tatsuya Takeshita; Masahiro Toda
Journal:  Environ Health Prev Med       Date:  2003-07       Impact factor: 3.674

2.  Detection of a variant protein in hair: new diagnostic method in Portuguese type familial amyloid polyneuropathy.

Authors:  Y Ando; I Anan; O Suhr; G Holmgren; P M Costa
Journal:  BMJ       Date:  1998-05-16

3.  Predicting and preventing diabetes: Translational potential of Ayurveda information on pre-diabetes.

Authors:  Sanjeev Rastogi; Neelendra Singh; Manish Gutch; Arindam Bhattacharya
Journal:  J Ayurveda Integr Med       Date:  2021-07-16
  3 in total

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