Abstract
Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus, presented as a major teratogenic cause worldwide. This study discussed alternation and correlation of magnesium (Mg), calcium (Ca), copper (Cu), zinc (Zn), iron (Fe), chromium (Cr), and selenium (Se) among DPN patients and healthy people using multivariate statistical analysis. Fifty patients with DPN were recruited from endocrinology department, First Hospital of Jilin University between January 2010 and October 2011 and also 50 healthy subjects were enrolled at the same time. Inductively coupled plasma mass spectrometry (ICP-MS) was used to assay elements in serum and urine. Cluster analysis was used to clarify alternation of elements’ homogeneity. Factor analysis was performed to evaluate the most informative kinds of elements. Mg, Ca, Zn, and Cr in DPN patients were significantly lower in serum whereas significantly higher in urine. Elements were clustered into 4 or 5 clusters based on internal association using between-groups linkage algorithm. Serum Cr, Se, and Fe were grouped, and Mg related to Ca more closely in both serum and urine in DPN. Factor analysis revealed discrepancies of elements’ contribution. Cr, Se, and Fe appeared to be the most crucial factors contributing to DPN. Mg, Ca, Zn, and Cu were more influential, whereas Cr became less potent to disease. Contributed value of elements could be determined and specified using loadings in scree plot. Future studies and delicate statistical models should be applied.
Highlights
Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus [1], and about 50% patients are suffering from it [2, 3]
Some scholars predict that 10% or so newly diagnosed diabetes patients are with DPN [4], disorders presented as the major teratogenic cause worldwide [5]
We investigated imbalance characteristics of elements in serum and urine of patients with DPN using cluster analysis and factor analysis
Summary
Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus [1], and about 50% patients are suffering from it [2, 3]. Some scholars predict that 10% or so newly diagnosed diabetes patients are with DPN [4], disorders presented as the major teratogenic cause worldwide [5]. Besides symptoms such as pain and sensory deprivation, patients with DPN may suffer from ulcers at the extremities [6, 7]. It is a primary cause of amputation among the diabetic population [6] and damages their quality of life . Classification methods could aggregate certain elements which contain similar information and, identify some of the most effective ones that may efficiently refine content and be time and cost saving
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