Association of Vitamin D Serum Levels and Its Common Genetic Determinants, With Severity of Liver Fibrosis in Genotype 1 Chronic Hepatitis C Patients

S. Petta; S. Grimaudo; V. D. Marco; C. Scazzone; F. S. Macaluso; C. Cammà; D. Cabibi; R. Pipitone; A. Craxì


J Viral Hepat. 2013;20(7):486-493. 

In This Article

Materials and Methods


Two hundred and sixty consecutive patients with G1 CHC, recruited at the Gastrointestinal and Liver Unit at the University Hospital in Palermo and fulfilling all inclusion and exclusion criteria detailed below, were assessed. Patients were included if they had a histological diagnosis of CHC (any degree of fibrosis, including cirrhosis) on a liver biopsy performed within 6 months prior to enrolment. G1 CHC patients were characterized by the presence of anti-HCV and HCV RNA, with persistently abnormal alanine aminotransferase (ALT) levels, and by alcohol consumption of <20 g/day in the last year or more, evaluated by a specific questionnaire. Exclusion criteria were (i) advanced cirrhosis (Child-Pugh B and C); (ii) hepatocellular carcinoma; (iii) other causes of liver disease of mixed aetiologies (excessive alcohol consumption, hepatitis B, autoimmune liver disease, Wilson's disease, hemochromatosis, α1-antitrypsin deficiency); (iv) HIV infection; (v) previous treatment with antiviral therapy, immunosuppressive drug and/or regular use of steatosis-inducing drugs (corticosteroids, valproic acid, tamoxifen, amiodarone); (vi) therapy with medications known to affect vitamin D3 metabolism, including vitamin/mineral supplements; and (vii) active IV drug addiction.

The study was performed in accordance with the principles of the Declaration of Helsinki and its appendices, and with local and national laws. Approval was obtained from the hospital's Institutional Review Board and Ethics Committee, and written informed consent was obtained from all patients.

Clinical and Laboratory Assessment

Clinical and anthropometric data were collected at the time of liver biopsy. BMI was calculated on the basis of weight in kilograms and height (in metres), and patients were classified as normal weight (BMI, 18.5–24.9 kg/m2), overweight (BMI, 25–29.9) or obese (BMI ≥ 30). The diagnosis of arterial hypertension was based on the following criteria: systolic blood pressure ≥135 mm Hg and/or diastolic blood pressure ≥85 mm Hg (measured three times within 30 min, in the sitting position and using a brachial sphygmomanometer) or use of blood pressure–lowering agents. The diagnosis of type 2 diabetes was based on the revised criteria of the American Diabetes Association, using a value of fasting blood glucose ≥126 mg/dL on at least two occasions.[11] In patients with a previous diagnosis of type 2 diabetes, current therapy with insulin or oral hypoglycaemic agents was documented.

A 12-hour overnight fasting blood sample was drawn at the time of biopsy to determine serum levels of ALT, total cholesterol, HDL and LDL cholesterol, triglycerides, plasma glucose concentration, insulin and platelet count. Insulin resistance (IR) was determined with the homoeostasis model assessment (HOMA), using the following equation:[12] insulin resistance (HOMA-IR) = fasting insulin (μU/mL) × fasting glucose (mm)/22.5. HOMA-IR has been validated in comparison with the euglycemic/hyperinsulinemic clamp technique in both diabetic and nondiabetic patients.[13]

The analysis of serum 25(OH) D was performed using a Chromosystem reagent kit and a chromatographic system equipped with a Waters 1525 Binary high-pressure liquid chromatography pump connected to a photo diode array detector, and detection was carried out at 265 nm. 25(OH)D serum levels <10 μg/L, from 10 to 30 μg/L, and >30 μg/L, were considered the threshold values for identifying deficiency, insufficiency and normality of vitamin D levels, respectively.

All patients were tested at the time of biopsy for HCV RNA (RT-PCR homemade; limit of detection: 12 IU/mL). Genotyping was performed by INNO-LiPA, HCV II, Bayer.

Genetic Analyses. DNA was purified using the QIAmp blood Mini Kit (Qiagen, Mainz, Germany), and DNA samples were quantified using spectrophotometric determination.

Genotyping for IL28B (rs12979860), PNPLA3 (rs738409), CYP2R1 (rs 10741657), NADSYN1(rs 12785878) and GC (rs 2282679) was carried out using the TaqMan SNP genotyping allelic discrimination method (Applied Biosystems, Foster City, CA, USA). Commercial genotyping assays were available for the SNPs: rs738409 (cat. C_7241_10), rs 10741657 (cat. C_2958430_10); rs 12785878 (cat. C_32063037_10); rs 2282679 (cat. C_26407519_10). Instead, a custom assay has been created by AB for rs12979860.

The genotyping call was performed with SDS software v.1.3.0 (ABI Prism 7500, Foster City, CA, USA). Genotyping was conducted in a blinded fashion relative to patient characteristics.


Slides were coded and read by one pathologist (D.C.), who was unaware of the patient's identity and history. A minimum length of 15 mm of biopsy specimen or the presence of at least 10 complete portal tracts was required.[14] Biopsies were classified according to the Scheuer numerical scoring system.[15] The percentage of hepatocytes containing macrovescicular fat was determined for each 10× field. An average percentage of steatosis was then determined for the entire specimen. Steatosis was assessed as the percentage of hepatocytes containing fat droplets (minimum 5%) and evaluated as a continuous variable. Steatosis was classified as absent-mild at <20% or moderate–severe at ≥20%.

Statistics. Continuous variables were summarized as mean ± standard deviation and categorical variables as frequency and percentage. The Student's t-test and analysis of variance were used when appropriate. Multiple linear regression analysis was performed to identify independent predictors of 25(OH)D serum levels as a continuous dependent variable. As candidate risk factors for low serum levels of 25(OH)D, we selected age, sex, body mass index, baseline ALT, platelet count, total cholesterol, high-density lipoprotein cholesterol, triglycerides, blood glucose, insulin, HOMA score, diabetes, arterial hypertension, DHCR7,CYP2R1 and CG SNPs, HCV RNA levels, steatosis and activity score.

Multiple logistic regression models were used to assess the relationship of fibrosis to the demographic, metabolic, genetic and histological characteristics of patients. In the model, the dependent variable was severe fibrosis coded as 1 = F3–F4 in the fibrosis score versus 0 = F1–F2. As candidate risk factors, we selected the same independent variables included in the 25(OH)D model and added 25(OH)D serum levels as an additional independent variable.

In all analyses, DHCR7 SNP was evaluated as TT/TG vs GG, CYP2R1 as AA/AG vs GG, and CG as TT/TG vs GG, according to published data on genotypes associated with lower vitamin D levels.[10]

Variables associated with the dependent variable at univariate analyses (probability threshold, P < 0.10) were included in the multivariate regression models. Regression analyses were performed by SAS.[16]