The positive association of serum gamma-glutamyltranspeptidase with atherosclerosis in females, not in males: a population based large scale cross-sectional study

Objective: The purpose of this study was to determine the relationship between serum gamma-glutamyltranspeptidase (GGT) and brachial-ankle pulse wave velocity (baPWV) as an indicator for atherosclerosis in Japanese males and females after adjusting fatty liver. Design: A cross-sectional study. Setting: A health checkup center in Japan. Participants: 846 Japanese males and females aged 24-84 years recruited from people who received a medical health checkup program with a standardized questionnaire and an automatic waveform analyzer to measure baPWV. Main outcome measures: We measured serum GGT concentrations and baPWV. Fatty liver was diagnosed by a standardized criteria using with abdominal ultrasonography. The postmenopausal state was defined as beginning 1 year after the cessation of menses. Results: In females, log2 GGT was positively associated with baPWV (β=0.11, 95% confidence interval (CI) 0.02-0.19, p<0.05) independent on age, BMI, systolic blood pressure, fasting plasma glucose, triglycerides, estimated glomerular ratio, fatty liver, menopausal state and parameters of life styles. However, in males, the positive association of log2 GGT with baPWV was not significant (β=-0.04, 95% CI -0.10-0.03, p=0.28) in multivariable linear regression analyses. Conclusions: The serum GGT level was associated with baPWV independently on co -variate including fatty liver or menopausal state just in females, but not in males. When the elevation of GGT was observed in females at clinical practice, we should check them using with some screening tests for atherosclerosis including baPWV

Multiple regression models for factors related to ΔeGFR.

<p>Model 1: all variables, Model 2: all variables except total cholesterol, Model 3: significant variables in univariate analysis, Model 4: significant variables in univariate analysis except total cholesterol.</p><p>Abbreviations and symbols: eGFR, estimated glomerular filtration rate; Δ, change in the variable over 2 years; β, standardized regression coefficient; BMI, body mass index; BP, blood pressure; FPG, fasting plasma glucose; HbA_1c, hemoglobin A_1c; HDL, high density lipoprotein; LDL, low density lipoprotein; Hb, hemoglobin.</p><p>Multiple regression models for factors related to ΔeGFR.</p

Prevalence of hyperuricemia (male, n = 1,515; female, n = 1,257).

<p>Hyperuricemia: serum uric acid ≥7 mg/dL in males and ≥6 mg/dL in females.</p><p>Prevalence of hyperuricemia (male, n = 1,515; female, n = 1,257).</p

Disposition of the study population.

<p>Disposition of the study population.</p

Change in eGFR over 2 years.

<p>eGFR was classified from stage 1 to stage 3a according to the CKD stage. Note that eGFR changed over 2 years.</p

Simple linear regression analysis of factors related to ΔeGFR.

<p>All values are expressed as mean ± SD.</p><p>Abbreviations and symbols: eGFR, estimated glomerular filtration rate; Δ, change in the variable over 2 years; β, standardized regression coefficient; MetS, metabolic syndrome; BMI, body mass index; BP, blood pressure; FPG, fasting plasma glucose; HbA_1c, hemoglobin A_1c; HDL, high density lipoprotein; LDL, low density lipoprotein; Hb, hemoglobin.</p><p>Simple linear regression analysis of factors related to ΔeGFR.</p

Characteristics of subjects at baseline and 2 years.

<p>All values are expressed as mean ± SD. <i>P</i> values: a, paired <i>t</i>-test; b, McNemar's test comparing baseline with 2 years.</p><p>Abbreviations and symbols: Δ, change in the variable over 2 years; 95% CI, 95% confidence interval; BMI, body mass index; BP, blood pressure; FPG, fasting plasma glucose; HbA_1c, hemoglobin A_1c; eGFR, estimated glomerular filtration rate; HDL, high density lipoprotein; LDL, low density lipoprotein; Hb, hemoglobin.</p><p>Characteristics of subjects at baseline and 2 years.</p

Risk Score.

<p>Risk Score.</p

Prevalence and risk of colorectal neoplasia in each group.

<p>Prevalence and risk of colorectal neoplasia in each group.</p

Multivariate predictors of colorectal neoplasia analyzed using a multiple logistic regression analysis.

<p>The plot shows the odds ratios (black squares), and 95% CIs (horizontal lines). P-values show the interaction between the prevalence of colorectal neoplasia and any subgroup variable. a. Significant risk factor of colorectal neoplasia by the Pearson χ² test (P < 0.001). b. Significant risk factor of colorectal neoplasia by the Pearson χ² test (P < 0.01).</p