Optimization of early diagnosis of fibrosis in patients with non-alcoholic fatty liver disease with obesity and overweight

Abstract

Objective — to optimize of early diagnosis of fibrosis in patients with NAFLD with obesity and overweight based on ROC analysis of non‑invasive laboratory and instrumental diagnostic markers. Materials and methods. The study included 120 patients with NAFLD (main group) with 1 — 3 degrees of obesity or overweight (BMI ≥25.0 — 39.9 kg/m2) and 20 practically healthy volunteers (control group) 23.50 [21.35; 24.78] kg/m2. Patients in the main group were divided into two subgroups depending on BMI. The subgroup I included 85 patients with NAFLD with concomitant obesity, BMI 36.50 [32.00; 40.60] kg/m2, and the subgroup II included 35 patients with NAFLD and overweight 28.00 [27.10; 29.35] kg/m2. Determination of the degree of fibrosis according to the METAVIR scale by measuring the average stiffness of the liver parenchyma, in the mode of shear wave elastography (ultrasound scanning system Soneus P7). The composition of the gut microbiota at the level of the main phylotypes was studied by identifying total bacterial DNA and DNA of Bacteroidetes, Firmicutes, as well as their ratio (F/B ratio), by quantitative real‑time polymerase chain reaction using universal primers for the 16S rRNA gene and taxon‑specific primers. Statistical processing was performed using Statistica 13.1. The data are presented in the form of Me [LQ; UQ], where Me is the median, LQ and UQ are the lower and upper quartiles, respectively. Results. Determination of the characteristic curves obtained as a result of the analysis allowed us to identify the most informationally significant additional diagnostic indicators: CRP, TNF‑α, microRNA‑122, microRNA‑34a (RU), the percentage of visceral fat, and F/B ratio. The analysis of ROC curves allowed us to determine the cut‑off value for each of the additional diagnostic criteria: cut‑off value for serum CRP concentration — 4.5 mg/l (AUC=0.99, sensitivity 1.00, specificity 0.030; p <0.05); for the serum concentration of TNF‑α — 5.5 pg/mL (AUC=0.97, sensitivity 0.98, specificity 0.025; p <0.05). The cut‑off value for the serum level of ­microRNA‑122 — 12.50 RU (AUC=0.99, sensitivity 0.98, specificity 0.048; p <0.05); for the serum level of microRNA‑34a — 5.50 RU (AUC=0.98, sensitivity 0.98, specificity 0.106; p <0.05). The cut‑off value for the proportion of VF — 8.5% (AUC=0.99, sensitivity 1.00, specificity 0.175; p <0.05); for F/B ratio — 1.51 (AUC=0.95, sensitivity 0.83, specificity 0.021; p <0.05). The analysis of the studied parameters allowed us to develop an algorithm for early comprehensive diagnosis of fibrosis in patients with NAFLD with obesity and overweight. The algorithm we propose consists of the following 4 stages. Stage I includes assessment of hepatopathy and interviewing the patient to determine complaints and anamnesis to exclude etiologic factors of secondary fatty liver. Stage II includes the determination of cytolysis markers, namely ALT and GGT. Stage III includes the determination of metabolic and proinflammatory parameters: HOMA index; TC and LDL cholesterol; CRP and TNF‑α. Stage IV includes the assessment of genetic and biological factors: determination of the main phylotypes of the gut microbiota and measurement of serum concentrations of microRNA‑122 and microRNA‑34a. The algorithm allows screening patients with NAFLD with obesity and overweight and identifying patients with early stages of fibrosis through a phased examination. Conclusions. The generalization of traditional diagnostic algorithms with the results of our search for additional diagnostic criteria made it possible to create a 4‑stage algorithm for early comprehensive diagnosis of fibrosis in patients with NAFLD with concomitant obesity or overweight. The use of the developed algorithm allows stratifying patients with NAFLD with obesity and overweight by the presence of fibrosis in the early stages, including by level of care, and timely prescribing preventive and therapeutic measures to reduce the risk of development, improve prognosis and prevent progression.