Study design, population selection and ethics approval
This cross-sectional research is nested within the South African arm of the Prospective Urban and Rural Epidemiology (PURE) study.(27) A three-stage sampling process was followed based on power calculations of a previous study.(28) After obtaining gatekeeper permission, 6000 houses were randomly selected from urban and rural strata. The head of each family unit gave voluntary written informed consent before completing an interviewer-based questionnaire used to screen for eligibility. From the households, 4000 individuals with no reported use of chronic medication (excluding blood pressure medication) and/or any self-reported acute illness were identified. During the baseline period, biological samples were collected from 1006 rural and 1004 urban, apparently healthy African men and women who provided written informed consent. The study protocol was approved by the Ethics Committee of the authors’ university (NWU-00016-10-A1 and NWU-00034-17-A1-02) honouring the Declaration of Helsinki of 1975 and 2000.
Lifestyle factor assessment
Questionnaires were interviewer-based in the participants’ home language and provided details regarding demographic and lifestyle factors, including tobacco. The physical activity index questionnaire, developed and validated locally, was completed.(29) Amounts of foods and beverages including alcohol consumed over the previous month were determined by a culture-sensitive, validated quantitative food frequency questionnaire (QFFQ)(30, 31) computerised using the FoodFinder3® programme based on the South African Food Composition Tables. Beer, homemade brews, spirits and wine were considered to contain 3.6 g, 3 g, 36 g and 9.4 g of pure alcohol per 100 g, respectively.
Anthropometrical and blood pressure assessment
Participants’ weight and height were measured to calculate body mass index (BMI; kg/m2). Waist circumference was measured at the narrowest point between the 10th rib and iliac crest. Blood pressure – systolic and diastolic – was measured with the OMRON HEM-757 apparatus (Omron Healthcare, Kyoto, Japan) with the cuff on the left arm.
Blood collection, sampling and storage
Fasting blood samples were collected between 07:00 and 11:00. Citrate-treated (3.8%) whole blood was centrifuged at 2000 x g for 15 minutes to yield buffy coat for DNA isolation and plasma specimens for coagulation markers. Ethylenediamine tetra-acetic acid-treated whole blood was used for glycated haemoglobin A1c (HbA1c) analysis. Coagulated blood was collected to yield serum for lipids, C-reactive protein (CRP), GGT, %CDT, ALT, and AST, analysis. Aliquots were frozen on dry ice, stored in the field at –18°C and then, after 2–4 days, at –80°C until analysed.
Biochemical analyses
Serum lipids [i.e. total cholesterol (TC), high density lipoprotein cholesterol (HDL-C) and triglycerides], high sensitivity CRP, GGT, ALT and AST concentrations were assayed using a Sequential Multiple Analyser (Konelab 20i, Thermo Fisher Scientific Oy, Vantaa, Finland). Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald formula. HbA1c concentrations were determined using the D-10 Haemoglobin testing system (Bio-Rad Laboratories, Hercules, CA, USA). Serum %CDT was quantified using an in vitro heterogeneous immunoassay with column separation followed by turbidimetric measurements (Axis-Shield %CDT kit, Oslo, Norway) with a measuring range of 1.5 – 24 mg/L of transferrin and a cut-off value of 2.6%. We used the following formula: 0.8 x ln(GGT)+1.3 x ln(%CDT) to calculate GGT-CDT.(25, 26, 32) Fibrinogen was determined using the adapted Clauss method (Multifibrin U-test, BCS coagulation analyser, Dade Behring, Deerfield, IL, USA). Fibrinogen g’ was quantified with an ELISA using a 2.G2.H9 mouse monoclonal coating antibody against the human g’ sequence (Santa Cruz Biotechnology, Santa Cruz, USA) for antigen capture and a goat polyclonal antibody against human fibrinogen (Antibody 7539, Abcam for development, Cambridge, USA).(33, 34) To obtain plasma fibrinolytic potential, reported as CLT, turbidimetric analysis (A405 nm) was used(35) with modified tissue factor and tissue-plasminogen activator (tPA) concentrations to attain CLTs of 60 minutes. Final concentrations were: tissue factor (125x diluted – an estimated final concentration of 59 pM; Dade Innovin, Siemens Healthcare Diagnostics Inc., Marburg, Germany), CaCl2 (17 mmol/L), tPA (100 ng/mL; Actilyse, Boehringer Ingelheim, Ingelheim, Germany) and phospholipid vesicles (10 μmol/L; Rossix, Mölndal, Sweden). Kinetics of clot formation (lag time and slope), and structural clot properties (maximum absorbance) were calculated from the turbidity curves.(33) Lag time represents the time required for fibrin fibres to grow to sufficient length to allow lateral aggregation as well as activation of the coagulation cascade. The slope represents the rate of lateral aggregation and maximum absorbance indicates clot density. The coefficient of variation for all assays was <10%. Using whole blood, a rapid first response HIV card test 1-2.0 (Transnational Technologies Inc. PMC Medical, Nani Daman, India) was done and the outcome confirmed with a Pareeshak test (BHAT Bio-tech, Bangalore, India).
DNA extraction, sequencing and genotyping
Genomic DNA was extracted using FlexiGene™ (QIAGEN, catalogue number 51206) and the Maxwell® 16 kits. FGA 2224G/A (rs2070011), FGA 6534A/G (rs6050), FGB 1038G/A (rs1800791), FGB Arg448Lys, G/A (rs4220), FGB –148C/T (rs1800787), FGG 10034C/T (rs2066865), FGG 9340T/C (rs1049636), the FXIII His95Arg A/G (rs6003) and FXIII Val34Leu, C/A (rs5985) were genotyped as described elsewhere.(36)
Downstream quality control included a check for individuals’ successfully genotyped (missingness), minor allele frequencies (MAF) and a tally of Mendelian error via Haploview (v4.2; http://www.broad.mit.edu/mpg/haploview) and PLINK (v1.07; http://pngu.mgh.harvard.edu/purcell/plink/) software. Pairwise linkage-disequilibrium (LD) between the SNPs have been reported previously.(36) Because three SNPs (rs7439150, rs1800789 and rs1800787) were not complete LD, they are reported separately.
Statistical analysis
Statistica® version 13.3 (TIBCO Software Inc., Tulsa, Oklahoma, USA) and SAS System for Windows (SAS Institute Inc., Cary, NC, USA) were used for analyses. Normally distributed data are expressed as mean (95% confidence intervals (CI)), and not-normally distributed data as median (lower and upper quartiles). Differences between the genders, HIV status and drinking status in terms of coagulation factors were determined by Mann–Whitney U tests and among tobacco use subgroups, using Kruskal–Wallis analysis of variance (ANOVA). Spearman correlations were performed to test for statistical dependence between variables and to identify confounders and/or co-variates for inclusion in subsequent analysis (LDL-C, age, HbA1c, gender, HIV status, tobacco use, BMI). Spearman partial correlations were conducted adjusting for fibrinogen to determine whether the relationship between alcohol intake or its markers and clot properties are influenced by fibrinogen concentration.
To investigate whether markers of alcohol consumption have interactive effects with the fibrinogen and FXIII gene polymorphisms in predicting total and %g’ fibrinogen concentration and clot properties, general linear models (adjusting for age, gender, HIV status, tobacco use, LDL-c, HbA1c and BMI) with interactions were performed. Interactions that remained after accounting for multiple testing and false discovery rates according to Hochberg and Benjamini are reported; the statistical threshold for significance was p < 0.004 (1/64(.25) = 0.004) when the false discovery rate was set at 25%.(37) To describe the interaction, Spearman partial correlations adjusting for LDL-C, age, HbA1c, gender, HIV status, tobacco use and BMI and additionally for fibrinogen, when the interaction was in relation to maximum absorbance, were used.