LipidSIM: Inferring mechanistic lipid biosynthesis perturbations from lipidomics with a flexible, low-parameter, Markov modeling framework.

Lipid metabolism is a complex and dynamic system involving numerous enzymes at the junction of multiple metabolic pathways. Disruption of these pathways leads to systematic dyslipidemia, a hallmark of many pathological developments, such as nonalcoholic steatohepatitis and diabetes. Recent advances in computational tools can provide insights into the dysregulation of lipid biosynthesis, but limitations remain due to the complexity of lipidomic data, limited knowledge of interactions among involved enzymes, and technical challenges in standardizing across different lipid types. Here, we present a low-parameter, biologically interpretable framework named Lipid Synthesis Investigative Markov model (LipidSIM), which models and predicts the source of perturbations in lipid biosynthesis from lipidomic data. LipidSIM achieves this by accounting for the interdependency between the lipid species via the lipid biosynthesis network and generates testable hypotheses regarding changes in lipid biosynthetic reactions. This feature allows the integration of lipidomics with other omics types, such as transcriptomics, to elucidate the direct driving mechanisms of altered lipidomes due to treatments or disease progression. To demonstrate the value of LipidSIM, we first applied it to hepatic lipidomics following Keap1 knockdown and found that changes in mRNA expression of the lipid pathways were consistent with the LipidSIM-predicted fluxes. Second, we used it to study lipidomic changes following intraperitoneal injection of CCl4 to induce fast NAFLD/NASH development and the progression of fibrosis and hepatic cancer. Finally, to show the power of LipidSIM for classifying samples with dyslipidemia, we used a Dgat2-knockdown study dataset. Thus, we show that as it demands no a priori knowledge of enzyme kinetics, LipidSIM is a valuable and intuitive framework for extracting biological insights from complex lipidomic data.

The Non-Invasive Assessment of Circulating D-Loop and mt-ccf Levels Opens an Intriguing Spyhole into Novel Approaches for the Tricky Diagnosis of NASH.

Nonalcoholic fatty liver disease (NAFLD) is the commonest liver disease worldwide affecting both adults and children. Nowadays, no therapeutic strategies have been approved for NAFLD management, and hepatic biopsy remains the gold standard procedure for its diagnosis. NAFLD is a multifactorial disease whose pathogenesis is affected by environmental and genetic factors, and it covers a spectrum of conditions ranging from simple steatosis up to nonalcoholic steatohepatitis (NASH), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Several studies underlined the urgent need to develop an NAFLD risk prediction model based on genetics, biochemical indicators, and metabolic disorders. The loss of mitochondrial dynamics represents a typical feature of progressive NAFLD. The imbalance of mitochondrial lifecycle together with the impairment of mitochondrial biomass and function trigger oxidative stress, which in turn damages mitochondrial DNA (mtDNA). We recently demonstrated that the main genetic predictors of NAFLD led to mitochondrial dysfunction. Moreover, emerging evidence shows that variations in the displacement loop (D-loop) region impair mtDNA replication, and they have been associated with advanced NAFLD. Finally, lower levels of mitophagy foster the overload of damaged mitochondria, resulting in the release of cell-free circulating mitochondrial DNA (mt-ccf) that exacerbates liver injury. Thus, in this review we summarized what is known about D-loop region alterations and mt-ccf content during NAFLD to propose them as novel non-invasive biomarkers.

KLHL3 deficiency in mice ameliorates obesity, insulin resistance, and nonalcoholic fatty liver disease by regulating energy expenditure.

Obesity is a growing global epidemic that can cause serious adverse health consequences, including insulin resistance (IR) and nonalcoholic fatty liver disease (NAFLD). Obesity development can be attributed to energy imbalance and metabolic inflexibility. Here, we demonstrated that lack of Kelch-like protein 3 (KLHL3) mitigated the development of obesity, IR, and NAFLD by increasing energy expenditure. KLHL3 mutations in humans cause Gordon's hypertension syndrome; however, the role of KLHL3 in obesity was previously unknown. We examined differences in obesity-related parameters between control and Klhl3-/- mice. A significant decrease in body weight concomitant with fat mass loss and improved IR and NAFLD were observed in Klhl3-/- mice fed a high-fat (HF) diet and aged. KLHL3 deficiency inhibited obesity, IR, and NAFLD by increasing energy expenditure with augmentation of O2 consumption and CO2 production. Delivering dominant-negative (DN) Klhl3 using adeno-associated virus into mice, thereby dominantly expressing DN-KLHL3 in the liver, ameliorated diet-induced obesity, IR, and NAFLD. Finally, adenoviral overexpression of DN-KLHL3, but not wild-type KLHL3, in hepatocytes revealed an energetic phenotype with an increase in the oxygen consumption rate. The present findings demonstrate a novel function of KLHL3 mutation in extrarenal tissues, such as the liver, and may provide a therapeutic target against obesity and obesity-related diseases.

Assessment of Lifestyle Factors Helps to Identify Liver Fibrosis Due to Non-Alcoholic Fatty Liver Disease in Obesity.

Only some individuals with obesity develop liver fibrosis due to non-alcoholic fatty liver disease (NAFLD-fibrosis). We determined whether detailed assessment of lifestyle factors in addition to physical, biochemical and genetic factors helps in identification of these patients. A total of 100 patients with obesity (mean BMI 40.0 ± 0.6 kg/m2) referred for bariatric surgery at the Helsinki University Hospital underwent a liver biopsy to evaluate liver histology. Physical activity was determined by accelerometer recordings and by the Modifiable Activity Questionnaire, diet by the FINRISK Food Frequency Questionnaire, and other lifestyle factors, such as sleep patterns and smoking, by face-to-face interviews. Physical and biochemical parameters and genetic risk score (GRS based on variants in PNPLA3, TM6SF2, MBOAT7 and HSD17B13) were measured. Of all participants 49% had NAFLD-fibrosis. Independent predictors of NAFLD-fibrosis were low moderate-to-vigorous physical activity, high red meat intake, low carbohydrate intake, smoking, HbA1c, triglycerides and GRS. A model including these factors (areas under the receiver operating characteristics curve (AUROC) 0.90 (95% CI 0.84-0.96)) identified NAFLD-fibrosis significantly more accurately than a model including all but lifestyle factors (AUROC 0.82 (95% CI 0.73-0.91)) or models including lifestyle, physical and biochemical, or genetic factors alone. Assessment of lifestyle parameters in addition to physical, biochemical and genetic factors helps to identify obese patients with NAFLD-fibrosis.

Serum proteome assessment in nonalcoholic fatty liver disease in children: a preliminary study.

OBJECTIVES: Nonalcoholic fatty disease (NAFLD) affects 3-10% of the pediatric population, making it the most common chronic liver disease among children. The aim of the study is to identify potential biomarkers enabling the diagnosis of NAFLD and monitoring the course of the disease. METHODS: Proteome analysis was performed in a group of 30 patients (19 boys and 11 girls) in total, of whom 16 children had previously diagnosed NAFLD based on the abdominal ultrasound after excluding other diseases of this organ. RESULTS: A total of 297 proteins have been identified. Thirty-seven proteins (responsible for inflammation, stress response, and regulation of this process) differentiating both experimental groups were identified. Up-regulated proteins included afamin, retinol-binding protein-4, complement components, and hemopexin; while serum protease inhibitors, clusterin, immunoglobulin chains, and vitamin D binding protein were found in the down-regulated group. The correlation between selected proteins and indicators of noninvasive assessment of liver fibrosis (APRI, FIB-4) as well as differences between the serum proteome of patients with normal weight, overweight, and obesity were also assessed. CONCLUSION: The plasma protein profile is significantly altered in nonalcoholic liver disease in children and may prove to be a valuable source of biomarkers to evaluate the extent of liver disease.

Epidemiology of nonalcoholic fatty liver disease in non-obese populations: Meta-analytic assessment of its prevalence, genetic, metabolic, and histological profiles.

OBJECTIVE: As a subgroup of nonalcoholic fatty liver disease (NAFLD), patients with non-obese NAFLD may also have an increased risk of adverse hepatic and metabolic outcomes. We aimed to estimate the prevalence and incidence of non-obese NAFLD and to describe its clinical characteristics in this systematic review and meta-analysis. METHODS: We performed a systematic search of 1235 citations published up to Mar 2020. Meta-analyses, stratified analyses and meta-regression were all performed. RESULTS: Of the 46 studies included, 28 cross-sectional and longitudinal studies of 155 846 non-obese participants reported a pooled NAFLD prevalence of 14.5% (95% confidence interval [CI] 12.3%-17.1%). A multivariate meta-regression analysis showed the trend that the prevalence varied by their geographical location. Further stratified analyses showed that NAFLD was relatively prevalent among people aged ≥45 years (16.2%; 95% CI 10.8-23.4) and those in South America (25.7%; 95% CI 24.4-27.0). The PNPLA3 rs738409 gene polymorphism was more frequently observed in non-obese NAFLD than in both obese NAFLD and non-obese controls, while the metabolic profiles of non-obese NAFLD were less severe than those of the obese NAFLD group. Patients with non-obese NAFLD had 4.81-fold and 5.43-fold higher risk of diabetes mellitus and metabolic syndrome, respectively, than the non-obese controls. CONCLUSIONS: Non-obese NAFLD is common, particularly in South America and among people aged ≥45 years. Metabolic diseases and PNPLA3 rs738409 gene polymorphism are more frequent in the non-obese NAFLD group than in non-obese controls.

Overview of the Pathogenesis, Genetic, and Non-Invasive Clinical, Biochemical, and Scoring Methods in the Assessment of NAFLD.

Nonalcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease worldwide. It represents a range of disorders, including simple steatosis, nonalcoholic steatohepatitis (NASH), and liver cirrhosis, and its prevalence continues to rise. In some cases, hepatocellular carcinoma (HCC) may develop. The develop;ment of non-invasive diagnostic and screening tools is needed, in order to reduce the frequency of liver biopsies. The most promising methods are those able to exclude advanced fibrosis and quantify steatosis. In this study, new perspective markers for inflammation, oxidative stress, apoptosis, and fibrogenesis; emerging scoring models for detecting hepatic steatosis and fibrosis; and new genetic, epigenetic, and multiomic studies are discussed. As isolated biochemical parameters are not specific or sensitive enough to predict the presence of NASH and fibrosis, there is a tendency to use various markers and combine them into mathematical algorithms. Several predictive models and scoring systems have been developed. Current data suggests that panels of markers (NAFLD fibrosis score, Fib-4 score, BARD score, and others) are useful diagnostic modalities to minimize the number of liver biopsies. The review unveils pathophysiological aspects related to new trends in current non-invasive biochemical, genetic, and scoring methods, and provides insight into their diagnostic accuracies and suitability in clinical practice.

Identification of key genes in non­alcoholic fatty liver disease progression based on bioinformatics analysis.

Due to economic development and lifestyle changes, the incidence of non­alcoholic fatty liver disease (NAFLD) has gradually increased in recent years. However, the pathogenesis of NAFLD is not yet fully understood. To identify candidate genes that contribute to the development and progression of NAFLD, two microarray datasets were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified and functional enrichment analyses were performed. A protein­protein interaction network was constructed and modules were extracted using the Search Tool for the Retrieval of Interacting Genes and Cytoscape. The enriched functions and pathways of the DEGs included 'cellular macromolecule biosynthetic process', 'cellular response to chemical stimulus', 'extracellular matrix organization', 'metabolic pathways', 'insulin resistance' and 'forkhead box protein O1 signaling pathway'. The DEGs, including type­1 angiotensin II receptor, formin­binding protein 1­like, RNA­binding protein with serine­rich domain 1, Ras­related C3 botulinum toxin substrate 1 and polyubiquitin­C, were identified using multiple bioinformatics methods and validated in vitro with reverse transcription­quantitative polymerase chain reaction analysis. In conclusion, five hub genes were identified in the present study, and they may aid in understanding of the molecular mechanisms underlying the development and progression of NAFLD.

Association of PNPLA3 rs738409 and TM6SF2 rs58542926 with health services utilization in a population-based study.

BACKGROUND: Hepatic steatosis confers an increased risk of metabolic and cardiovascular disease and higher health services use. Associations of the single nucleotide polymorphisms (SNP) PNPLA3 rs738409 and TM6SF2 rs58542926 with hepatic steatosis have recently been established. This study investigates the association between rs738409 and rs58542926 with health services utilization in a general population. METHODS: Data of 3759 participants from Study of Health in Pomerania (SHIP), a population-based study in Germany, were obtained. The annual number of outpatient visits, hospitalization and length of hospital stay was regressed on rs738409 and rs58542926 and adjusted for socio-economic factors, lifestyle habits, clinical factors, and health status. RESULTS: Minor allele homozygous subjects of rs738409 had an increased odds of hospitalization as compared to major allele homozygous subjects (odds ratio [OR] 1.51; 95% confidence interval [CI], 1.02 to 2.15). Heterozygous subjects did not differ from major allele homozygous subjects with respect to their odds of hospitalization. The three genotype groups of rs738409 were similar with respect to the number of outpatient visits and inpatient days. Minor allele homozygous and heterozygous subjects of rs58542926 had higher outpatient utilization (+53.04% and +67.56%, p < 0.05, respectively) and inpatient days than major allele homozygous subjects. CONCLUSIONS: After adjustment for several confounding factors, PNPLA3 rs738409 and TM6SF2 rs58542926 were associated with the number of outpatient visits, hospitalization, and inpatient days. Further studies are warranted to replicate our findings and to evaluate whether genetic data can be used to identify subjects with excess health services utilization.