The relationship between eNOS gene expression and patients with type ۲ diabetes and depression

  • سال انتشار: 1400
  • محل انتشار: کنفرانس بین المللی ژنتیک و ژنومیکس انسانی
  • کد COI اختصاصی: CHGGE01_317
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 110
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نویسندگان

Mahsa Khosrogardi

Department of Biology, Payame Noor University, Tehran, Iran

Mahsa Mohammad Amoli

Department of Biology, Payame Noor University, Tehran, Iran

چکیده

Backgrounds: Type ۲ diabetes mellitus (T۲DM) is a metabolic disorder caused byhyperglycemia which is the most common form of diabetes and causes impairment in insulinsecretion and insulin resistance. Increased inflammatory elements such as eNOS can beassociated with type ۲ diabetes and depression. Multiple studies show that depression is morecommon in patients with type ۱ and type-۲ diabetes than in healthy people. Worldwide,depression in diabetics is linked to the culture or society of countries. It is reported that ۲۶% ofpatients with diabetes worldwide have depression.Materials and Methods: After sampling, RNA extraction was performed using TRIzol methodand qualitative analysis of RNA extracted by gel electrophoresis and also quantitative analysis ofRNA extracted by Nano drop spectrophotometers. GAPDH and eNOS primers were thendesigned. Then, PCR reaction and cDNA synthesis were performed in order to amplify thedesired fragments and finally, Real-time PCR was performed to evaluate the expression of thedesired gene. SPSS software was used for data analysis.Results: In the present paper, it was found that eNOS gene expression increased in case groupcompared to control group, which was not statistically significant (p> ۰.۰۵).Conclusion: Regarding the increase of this enzyme in the case group, it can be said that theconcentration of reactive oxygen or nitrogen species such as superoxide, nitric oxide andperoxynitric can increase in conditions such as inflammation that inhibit the body’s naturaldefense and antioxidant activities.

کلیدواژه ها

Gene expression, eNOS, Type ۲ diabetes, Depression, Real-time-PCR

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