Plasma homocysteine and insulin resistance in polycystic ovary syndrome
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Plasma Homocysteine and Insulin Resistance in Polycystic Ovary Syndrome. I. A. Hossain 1 , A. Sultana 2 , H. Chowdhury 1 , N. Sultana 1 , S. Akter 3 , F. Jebunnesa 3 , L. Ali 1,3 .

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Plasma homocysteine and insulin resistance in polycystic ovary syndrome
Plasma Homocysteine and Insulin Resistance in Polycystic Ovary Syndrome

I. A. Hossain1, A. Sultana2, H. Chowdhury1, N. Sultana1 , S. Akter3, F. Jebunnesa3, L. Ali1,3.

1Dept of Biochemistry and Cell Biology, Biomedical Research Group, Dhaka, Bangladesh, 2Dept of Obstetrics and Gynecology, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine and Metabolic disorders, Dhaka, Bangladesh, 3Dept of Biochemistry and Cell Biology, Bangladesh Institute of Health Sciences, Dhaka, Bangladesh.


Background
Background: Ovary Syndrome

  • Polycystic ovary syndrome (PCOS) is the commonest endocrine disorder affecting 5-10% women of reproductive age.

  • Both genetic and environmental factors contribute to the development of PCOS.


Cont….. Ovary Syndrome

  • Many studies suggest that PCOS may increase the risk of

    -Type 2 diabetes

    -Dyslipidemia

    -Hypertension

    -Cardiovascular disease

  • Exploration of the CVD risk factors in this disorder has lead to the suggestion that Hcy may be one of the important biochemical risk factors for PCOS and it is associated with insulin resistance and/or hyperinsulinemia

  • The observation has been debated and ethnic variation has also been reported


Cont…. Ovary Syndrome

  • Therefore, plasma Hcy level and insulin resistance in PCOS subjects in our population needs to be investigated


Hypothesis
Hypothesis Ovary Syndrome

  • Plasma homocysteine is raised in PCOS women and it is associated with insulin resistance.


Objectives
OBJECTIVES Ovary Syndrome

General Objective:

  • To investigate the homocysteinemic status in polycystic ovary syndrome and its association with insulin resistance

    Specific Objectives:

  • To measure the fasting plasma homocysteine level in subjects with PCOS.

  • To assess the glycemic and insulinemic status in polycystic ovary syndrome.

  • To investigate the association between plasma homocysteine and insulin resistance in polycystic ovary syndrome.


Materials and methods
MATERIALS AND METHODS Ovary Syndrome

Study Design:

  • Cross-sectional study with case-control design.

    Place of the Study:

  • Dept of Gynecology & Obstetrics, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka and Biomedical Research Group, (BIRDEM), Dhaka


Cont…. Ovary Syndrome

Study population

  • After taking informed consent a total number of 215 women (121 PCOS women and 94 controls) were included

  • The final sample size was 146 (88 cases and 58 controls).


Cont…. Ovary Syndrome

Inclusion Criteria:

  • Cases were Bangladeshi subjects with PCOS,

    age between 15-40 years.

  • Controls were healthy and age matched

    Exclusion Criteria:

  • PCOS with known diabetes.

  • Relatives of PCOS.

  • Liver and renal disease and

  • PCOS with known endocrinopathy like hyperadrenalism, hypo and hyperthyroidism etc.


Analytical methods and lab analysis
Analytical Methods and Lab Analysis: Ovary Syndrome

  • Serum glucose was estimated by Glucose Oxidase method

  • Total cholesterol, TG and HDL were measured by enzymatic colorimetric method.

  • The LDL- Cholesterol level was calculated by using Friedewald formula [Friedewald WT 1972].


Analytical methods and lab analysis1
Analytical Methods and Lab Analysis: Ovary Syndrome

  • Fasting serum C-peptide was estimated by ELISA (Millipore, USA)

  • Serum total L-homocysteine was measured by flourescence polarization immunoassay (FPIA)

  • Insulin secretion and sensitivity were calculated by homeostasis model assessment (HOMA) using HOMA–CIGMA software


Statistical method
Statistical method Ovary Syndrome

  • The data expressed as the mean±SD and median (range)

  • Student’s Unpaired t test, Spearman's correlation and multiple linear regression were used for data analysis

  • All statistical analysis were performed with the SPSS software for windows 11.5


Results
RESULTS Ovary Syndrome

Table 1: Anthropometric and Clinical characteristics of the study subjects



Table 3: Glycemic, insulinemic and homocysteinemic status of the study subjects

Results were expressed as Mean±SD. Means compared using Student’s Unpaired t-test. n=number of subjects; F Glu, Fasting glucose; AG, Serum glucose 2 hrs after 75 gm glucose load; C-pep:glu, C-peptide-glucose ratio; HOMA %B, B cell function assessed by homeostasis model assessment; HOMA %S, Insulin sensitivity assessed by homeostasis model assessment. Hcy, Homocysteine; PCOS, Polycystic ovary syndrome; R-PCOS, Relatives of PCOS subjects.


Table 4: Spearman’s Correlation of homocysteine with different variables in PCOS subjects

The level of significance at p<0.05; r, Correlation coefficient.


Table 5: Spearman’s Correlation of homocysteine with different variables in the Control subjects

The level of significance at p<0.05; r, Correlation coefficient


Table 6: Multiple linear regression taking serum homocysteine as dependent variable

Dependent Variable: Hcy; Adjusted R2 =0.015


Conclusions
Conclusions: homocysteine as dependent variable

  • PCOS is associated with hyperhomocysteinemia in Bangladeshi subjects

  • Both hyperinsulinemia and insulin resistance are present in PCOS, but the degree of hyperinsulinemia is disproportionately higher in PCOS compared to insulin resistance

  • Hyperhomocysteinemia in PCOS has mild degree of association with insulin resistance, but it seems to have strong association with hyperinsulinemia.


Recommendations
RECOMMENDATIONS homocysteine as dependent variable

  • Measurement of Hcy and insulinemic status in PCOS subjects may be introduced in clinical practice to assess cardiovascular risk.

  • Large scale prospective studies should be undertaken to address the causal relationship between Hcy and insulinemic status.


Thank you
Thank You homocysteine as dependent variable


Sample size calculation
Sample Size Calculation homocysteine as dependent variable

The sample size was calculated according to the following formula (Bland, 2000):

(µ1-µ2)2=f(α, P)σ2(1/n1+1/n2)

Where,

µ1-µ2=Difference between population means

f(α, P)=[µα+µ2(1-P)]2, P=Power (80%)

α=Significance level (0.05)

σ2=Variance/mean difference within the group, n=Sample size


homocysteine as dependent variable1-µ2)2=f(α, P)σ2(1/n1+1/n2)

(1.0)2= 7.9×(3.1)2(1/n+1/n)

n= 7.9×8.0×9.61×2

n=152

Where,

µ1-µ2=1.0

f(α, P)=[µα+µ2(1-P)]2, P= 7.9 (80%)

α=Significance level (0.05)

σ2=2.83,


Limitations
LIMITATIONS homocysteine as dependent variable

  • Due to lack of SHBG data Free Androgen Index could not be calculated and used in the diagnosis of PCOS.

  • Elaborate multivariate analysis, to get more insight regarding the risk factors, could not be done due to relatively smaller sample size.


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