International Journal of Clinical Biochemistry and Research

Asymmetric dimethyl arginine as a cardiovascular risk marker in patients with hyperthyroidism: a randomised case control study in a tertiary level health care centre

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Author Details: Priyanka Patra, Anitha M., HL Vishwanath

Volume : 4

Issue : 1

Online ISSN : 2394-6377

Print ISSN : 2394-6369

Article First Page : 99

Article End Page : 102


Background: Cardiovascular manifestations are frequent findings in patients with thyroid hormone disorders. Asymmetric dimethylarginine (ADMA), a inhibitor of endothelial nitric oxide synthase (eNOS), blocks nitric oxide (NO) synthesis from l-arginine. So, ADMA level can be considered as cardiovascular risk marker as it is a possible contributing factors for endothelial dysfunction in hyperthyroid patients.
Objectives: The aim of the study was to assess ADMA levels in hyperthyroidism patients free of cardiovascular risk associates and further comparison with healthy controls.
Methodology: The study took place in Victoria Hospital, attached to Bangalore Medical College and Research Institute. The study groups consisted of 30 patients with diagnosed hyperthyroidism and 30 healthy sex and age matched controls. The patients with renal failure, diabetes and severe hypertension were excluded. ADMA was estimated by double-antibody sandwich enzyme-linked immunosorbent assay (ELISA).
Results: The Mean ADMA level was higher in the hyperthyroid group (1.1346±0.6382μmol/L) than in the control group (0.584±0.2377μmol/L) and it was statistically significant (p<0.0001). 
Conclusion: ADMA represents a new and well-characterized marker that has been associated with many traditional and novel risk factors in the setting of cardiovascular risk. So, an elevation of ADMA levels of patients with hyperthyroidism compared with healthy controls may contribute to some cardiovascular alterations.

Keywords: ADMA= Asymmetric dimethylarginine, eNOS = endothelial nitric oxide synthase, NO= nitric oxide, ELISA= enzyme-linked immunosorbent assay, p = Probability of observing a test statistic