Irisin And Diabetic Nephropathy

Irisin Level in Patients With Diabetic Nephropathy

Diabetes mellitus (DM) is a complex, multifactorial, chronic metabolic and endocrine disorder. It has become a threat to global health. It has two types. It is estimated that the number of people with type II will reach 700 million by 2045.

Study Overview

• Status: Not yet recruiting
• Conditions: Irisin
• Intervention / Treatment: Diagnostic test: Laboratory tests; Other: Estimated glomerular filtration rate (eGFR); Diagnostic test: Laboratory tests; Other: Anthropometric measurements; Procedure: Electrocardiogram and Fundus examination; Other: Brachial index; Radiation: Abdominal ultrasound.

Detailed Description

It is associated with acute and chronic complications, acute complications include hypoglycemia, diabetic ketoacidosis, hyperglycemic hyperosmolar state, and hyperglycemic diabetic coma. Chronic complications are further divided into microvascular and macrovascular complications. Chronic microvascular complications are neuropathy, retinopathy, and nephropathy. The later one firstly diagnosed by microalbuminuria. whereas chronic macrovascular complications are coronary artery disease (CAD), peripheral artery disease (PAD), and cerebrovascular disease.

The conventional medications in diabetes treatment, oral and insulin, are focusing on insulin secretion and insulin sensitisation. Oral antidiabetics include, Biguanides, Sulfonylureas, Thiazolidinediones, DPP4 inhibitors, GLP-1 analogue, and SGLT2 inhibitors.

Irisin, a myokin and adipokine secreted by muscles and subcutaneous fat, is an interesting peptide performing significant functions in human health. Irisin has been linked to human obesity and insulin resistance status.

Irisin is involved in regulating the mitochondrial function of muscle cells, so increases energy consumption of the body, promotes metabolism and reduces body weight so improves insulin sensetivity. In our study we aim to clarify the effect of antidiabetics on serum irisin in patients with typeII DM who developed diabetic nephropathy.

• Study Type: Observational
• Enrollment (Anticipated): 90

Contacts and Locations

• Study Contact: Name: Hala Khalah Allah Khalifa El-shereef, MD; Phone Number: 01120110000; Email: dr_hala_elshereef@yahoo.com
• Study Contact Backup: Name: Marwa Kamal Abdo Khair Allah, MD; Phone Number: 01097878113; Email: Marwa.kamal82@hotmail.com

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 40 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Probability Sample

Study Population

Any patients above 40 years with type 2 diabetes of at least two years duration complicated with diabetic nephropathy.

Description

Inclusion Criteria:

Any patients above 40 years with type 2 diabetes of at least two years duration complicated with diabetic nephropathy.

Exclusion Criteria:

• Patients below 40 yrs.
• Patients with type 1 diabetes complicated with diabetic nephropathy
• Type2 diabetes without nephropathy.
• Diabetic nephropathy cases on dialysis due to other causes
• Blood pressure more than 160/100
• Acute coronary syndrome in the past 6 months
• Non alcoholic fatty liver disease, impaired liver function.
• Malignancy.
• Pregnancy
• Acute infection, acute inflammation.
• Severe renal impairment, and urinary tract infection.

Study Plan

How is the study designed?

Design Details

• Observational Models: Other
• Time Perspectives: Cross-Sectional

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
Patient Group; The patient group will include 60 patients with type II DM. They will be subdivided into three groups according to albumin-creatinine ratio ,normoalbuminuric group(less than 30mg/g),which will include 20 patients, microalbuminuric group (ACR =30-300 mg/), which will include 20 patients, and macroalbuminuric group (ACR more than 300mg/g),which will include 20 patients.	Diagnostic test: Laboratory tests; Fasting blood glucose (FBG), postprandial blood glucose, total cholesterol (CHO), triglycerides (TG), high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (LDL-C), urea, creatinine, and uric acid by point colorimetric assay. Serum irisin.; Other: Estimated glomerular filtration rate (eGFR); Estimated glomerular filtration rate (eGFR) was calculated by EPI equation.; Diagnostic test: Laboratory tests; Glycosylated haemoglobin. ACR,urinary albumin (mg) and creatinine (g).
Control Group; control group will include 30 apparently healthy age-matched and sex-matched individuals.	Diagnostic test: Laboratory tests; Fasting blood glucose (FBG), postprandial blood glucose, total cholesterol (CHO), triglycerides (TG), high-density lipoprotein cholesterol and low-density lipoprotein cholesterol (LDL-C), urea, creatinine, and uric acid by point colorimetric assay. Serum irisin.; Diagnostic test: Laboratory tests; Glycosylated haemoglobin. ACR,urinary albumin (mg) and creatinine (g).; Other: Anthropometric measurements; Height, weight, waist circumference, and hip circumference were taken as a way of assessing the nutritional status and BMI; Procedure: Electrocardiogram and Fundus examination; Fundus examination by direct ophthalmoscope; Other: Brachial index; The ankle-brachial index test compares the blood pressure measured at your ankle with the blood pressure measured at your arm; Radiation: Abdominal ultrasound.; It will be performed for patients only.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The relation between different stages of diabetic nephropathy and irisin level.	measurement of irisin level in patients with diabetic nephropathy	1 year

Collaborators and Investigators

• Sponsor: Assiut University

Publications and helpful links

General Publications

• Xuan X, Lin J, Zhang Y, Zhou L, Xu L, Jia J, Zhao B, Lin Z, Zhu Q, Li L, Wu T, Zhang S, Jiang H, Wang Y. Serum Irisin Levels and Clinical Implication in Elderly Patients With Type 2 Diabetes Mellitus. J Clin Med Res. 2020 Sep;12(9):612-617. doi: 10.14740/jocmr4261. Epub 2020 Aug 15.
• Ravaut M, Sadeghi H, Leung KK, Volkovs M, Kornas K, Harish V, Watson T, Lewis GF, Weisman A, Poutanen T, Rosella L. Predicting adverse outcomes due to diabetes complications with machine learning using administrative health data. NPJ Digit Med. 2021 Feb 12;4(1):24. doi: 10.1038/s41746-021-00394-8.
• Tan SY, Mei Wong JL, Sim YJ, Wong SS, Mohamed Elhassan SA, Tan SH, Ling Lim GP, Rong Tay NW, Annan NC, Bhattamisra SK, Candasamy M. Type 1 and 2 diabetes mellitus: A review on current treatment approach and gene therapy as potential intervention. Diabetes Metab Syndr. 2019 Jan-Feb;13(1):364-372. doi: 10.1016/j.dsx.2018.10.008. Epub 2018 Oct 10.

Study record dates

Study Major Dates

• Study Start (Anticipated): January 1, 2022
• Primary Completion (Anticipated): April 30, 2023
• Study Completion (Anticipated): June 30, 2023

Study Registration Dates

• First Submitted: November 20, 2021
• First Submitted That Met QC Criteria: November 20, 2021
• First Posted (Actual): December 3, 2021

Study Record Updates

• Last Update Posted (Actual): December 3, 2021
• Last Update Submitted That Met QC Criteria: November 20, 2021
• Last Verified: October 1, 2021

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Kidney Diseases; Urologic Diseases; Endocrine System Diseases; Diabetes Complications; Diabetes Mellitus; Diabetic Nephropathies
• Other Study ID Numbers: AATHSH

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: Undecided

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No