A Rare Nonsense Mutation in the Glucokinase Regulator Gene Is Associated With a Rapidly Progressive Clinical Form of Nonalcoholic Steatohepatitis

Trans-ancestral rare variant association study with machine learning-based phenotyping for metabolic dysfunction-associated steatotic liver disease

BACKGROUND

Genome-wide association studies (GWAS) have identified common variants associated with metabolic dysfunction-associated steatotic liver disease (MASLD). However, rare coding variant studies have been limited by phenotyping challenges and small sample sizes. We test associations of rare and ultra-rare coding variants with proton density fat fraction (PDFF) and MASLD case-control status in 736,010 participants of diverse ancestries from the UK Biobank, All of Us, and BioMe and performed a trans-ancestral meta-analysis. We then developed models to accurately predict PDFF and MASLD status in the UK Biobank and tested associations with these predicted phenotypes to increase statistical power.

RESULTS

The trans-ancestral meta-analysis with PDFF and MASLD case-control status identifies two single variants and two gene-level associations in APOB, CDH5, MYCBP2, and XAB2. Association testing with predicted phenotypes, which replicates more known genetic variants from GWAS than true phenotypes, identifies 16 single variants and 11 gene-level associations implicating 23 additional genes. Two variants were polymorphic only among African ancestry participants and several associations showed significant heterogeneity in ancestry and sex-stratified analyses. In total, we identified 27 genes, of which 3 are monogenic causes of steatosis (APOB, G6PC1, PPARG), 4 were previously associated with MASLD (APOB, APOC3, INSR, PPARG), and 23 had supporting clinical, experimental, and/or genetic evidence.

CONCLUSIONS

Our results suggest that trans-ancestral association analyses can identify ancestry-specific rare and ultra-rare coding variants in MASLD pathogenesis. Furthermore, we demonstrate the utility of machine learning in genetic investigations of difficult-to-phenotype diseases in trans-ancestral biobanks.

Exploring the role of genetic variations in NAFLD: implications for disease pathogenesis and precision medicine approaches

Non-alcoholic fatty liver disease (NAFLD) is one of the leading causes of chronic liver diseases, affecting more than one-quarter of people worldwide. Hepatic steatosis can progress to more severe forms of NAFLD, including NASH and cirrhosis. It also may develop secondary diseases such as diabetes and cardiovascular disease. Genetic and environmental factors regulate NAFLD incidence and progression, making it a complex disease. The contribution of various environmental risk factors, such as type 2 diabetes, obesity, hyperlipidemia, diet, and sedentary lifestyle, to the exacerbation of liver injury is highly understood. Nevertheless, the underlying mechanisms of genetic variations in the NAFLD occurrence or its deterioration still need to be clarified. Hence, understanding the genetic susceptibility to NAFLD is essential for controlling the course of the disease. The current review discusses genetics' role in the pathological pathways of NAFLD, including lipid and glucose metabolism, insulin resistance, cellular stresses, and immune responses. Additionally, it explains the role of the genetic components in the induction and progression of NAFLD in lean individuals. Finally, it highlights the utility of genetic knowledge in precision medicine for the early diagnosis and treatment of NAFLD patients.

Liver Involvement in Patients with Rare MBOAT7 Variants and Intellectual Disability: A Case Report and Literature Review

The membrane-bound O-acyltransferase domain-containing 7 (MBOAT7) protein is an acyltransferase catalyzing arachidonic acid incorporation into lysophosphatidylinositol. Patients with rare, biallelic loss-of-function variants of the MBOAT7 gene display intellectual disability with neurodevelopmental defects. The rs641738 inherited variant associated with reduced hepatic MBOAT7 expression has been linked to steatotic liver disease susceptibility. However, the impact of biallelic loss-of-function MBOAT7 variants on liver disease is not known. We report on a 2-year-old girl with MBOAT7-related intellectual disability and steatotic liver disease, confirming that MBOAT7 loss-of-function predisposes to liver disease.

Precision Medicine in Fatty Liver Disease/Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent chronic liver disease, and is related to fatal and non-fatal liver, metabolic, and cardiovascular complications. Its non-invasive diagnosis and effective treatment remain an unmet clinical need. NAFLD is a heterogeneous disease that is most commonly present in the context of metabolic syndrome and obesity, but not uncommonly, may also be present without metabolic abnormalities and in subjects with normal body mass index. Therefore, a more specific pathophysiology-based subcategorization of fatty liver disease (FLD) is needed to better understand, diagnose, and treat patients with FLD. A precision medicine approach for FLD is expected to improve patient care, decrease long-term disease outcomes, and develop better-targeted, more effective treatments. We present herein a precision medicine approach for FLD based on our recently proposed subcategorization, which includes the metabolic-associated FLD (MAFLD) (i.e., obesity-associated FLD (OAFLD), sarcopenia-associated FLD (SAFLD, and lipodystrophy-associated FLD (LAFLD)), genetics-associated FLD (GAFLD), FLD of multiple/unknown causes (XAFLD), and combined causes of FLD (CAFLD) as well as advanced stage fibrotic FLD (FAFLD) and end-stage FLD (ESFLD) subcategories. These and other related advances, as a whole, are expected to enable not only improved patient care, quality of life, and long-term disease outcomes, but also a considerable reduction in healthcare system costs associated with FLD, along with more options for better-targeted, more effective treatments in the near future.

Genetic Markers Predisposing to Nonalcoholic Steatohepatitis

The growing prevalence of nonalcoholic fatty liver disease (NAFLD) has sparked interest in understanding genetics and epigenetics associated with the development and progression of the disease. A better understanding of the genetic factors related to progression will be beneficial in the risk stratification of patients. These genetic markers can also serve as potential therapeutic targets in the future. In this review, we focus on the genetic markers associated with the progression and severity of NAFLD.

Geographical similarity and differences in the burden and genetic predisposition of NAFLD

NAFLD has become a major public health problem for more than 2 decades with a growing prevalence in parallel with the epidemic of obesity and type 2 diabetes (T2D). The disease burden of NAFLD differs across geographical regions and ethnicities. Variations in prevalence of metabolic diseases, extent of urban-rural divide, dietary habits, lifestyles, and the prevalence of NAFLD risk and protective alleles can contribute to such differences. The rise in NAFLD has led to a remarkable increase in the number of cases of cirrhosis, hepatocellular carcinoma, hepatic decompensation, and liver-related mortality related to NAFLD. Moreover, NAFLD is associated with multiple extrahepatic manifestations. Most of them are risk factors for the progression of liver fibrosis and thus worsen the prognosis of NAFLD. All these comorbidities and complications affect the quality of life in subjects with NAFLD. Given the huge and growing size of the population with NAFLD, it is expected that patients, healthcare systems, and the economy will suffer from the ongoing burden related to NAFLD. In this review, we examine the disease burden of NAFLD across geographical areas and ethnicities, together with the distribution of some well-known genetic variants for NAFLD. We also describe some special populations including patients with T2D, lean patients, the pediatric population, and patients with concomitant liver diseases. We discuss extrahepatic outcomes, patient-reported outcomes, and economic burden related to NAFLD.

Genetics in non-alcoholic fatty liver disease: The role of risk alleles through the lens of immune response

The knowledge on the genetic component of non-alcoholic fatty liver disease (NAFLD) has grown exponentially over the last 10 to 15 years. This review summarizes the current evidence and the latest developments in the genetics of NAFLD and non-alcoholic steatohepatitis (NASH) from the immune system's perspective. Activation of innate and or adaptive immune response is an essential driver of NAFLD disease severity and progression. Lipid and immune pathways are crucial in the pathophysiology of NAFLD and NASH. Here, we highlight novel applications of genomic techniques, including single-cell sequencing and the genetics of gene expression, to elucidate the potential involvement of NAFLD/NASH-risk alleles in modulating immune system cells. Together, our focus is to provide an overview of the potential involvement of the NAFLD/NASH-related risk variants in mediating the immune-driven liver disease severity and diverse systemic pleiotropic effects.

Exome-wide association analysis of CT imaging-derived hepatic fat in a medical biobank

Nonalcoholic fatty liver disease is common and highly heritable. Genetic studies of hepatic fat have not sufficiently addressed non-European and rare variants. In a medical biobank, we quantitate hepatic fat from clinical computed tomography (CT) scans via deep learning in 10,283 participants with whole-exome sequences available. We conduct exome-wide associations of single variants and rare predicted loss-of-function (pLOF) variants with CT-based hepatic fat and perform cross-modality replication in the UK Biobank (UKB) by linking whole-exome sequences to MRI-based hepatic fat. We confirm single variants previously associated with hepatic fat and identify several additional variants, including two (FGD5 H600Y and CITED2 S198_G199del) that replicated in UKB. A burden of rare pLOF variants in LMF2 is associated with increased hepatic fat and replicates in UKB. Quantitative phenotypes generated from clinical imaging studies and intersected with genomic data in medical biobanks have the potential to identify molecular pathways associated with human traits and disease.

A Multi-Gene Panel to Identify Lipedema-Predisposing Genetic Variants by a Next-Generation Sequencing Strategy

Lipedema is a disabling disease characterized by symmetric enlargement of the lower and/or upper limbs due to deposits of subcutaneous fat, that is easily misdiagnosed. Lipedema can be primary or syndromic, and can be the main feature of phenotypically overlapping disorders. The aim of this study was to design a next-generation sequencing (NGS) panel to help in the diagnosis of lipedema by identifying genes specific for lipedema but also genes for overlapping diseases, and targets for tailored treatments. We developed an NGS gene panel consisting of 305 genes potentially associated with lipedema and putative overlapping diseases relevant to lipedema. The genomes of 162 Italian and American patients with lipedema were sequenced. Twenty-one deleterious variants, according to 3 out of 5 predictors, were detected in PLIN1, LIPE, ALDH18A1, PPARG, GHR, INSR, RYR1, NPC1, POMC, NR0B2, GCKR, PPARA in 17 patients. This extended NGS-based approach has identified a number of gene variants that may be important in the diagnosis of lipedema, that may affect the phenotypic presentation of lipedema or that may cause disorders that could be confused with lipedema. This tool may be important for the diagnosis and treatment of people with pathologic subcutaneous fat tissue accumulation.

Computational Pipeline for Next-Generation Sequencing (NGS) Studies in Genetics of NASH

High-throughput sequencing (HTS) technologies have contributed to expand current knowledge of the biology of complex diseases, including nonalcoholic fatty liver disease (NAFLD). Genome-wide association studies, whole exome sequencing, and sequencing of entire genes are used to identify variants and/or mutations that predispose to the disease pathogenesis. Here, we present a tutorial that may guide readers to manage high volume of genetics data in the context of Next-Generation Sequencing (NGS) studies.

Precision medicine in nonalcoholic fatty liver disease: New therapeutic insights from genetics and systems biology

Despite more than two decades of extensive research focusing on nonalcoholic fatty liver disease (NAFLD), no approved therapy for steatohepatitis-the severe histological form of the disease-presently exists. More importantly, new drugs and small molecules with diverse molecular targets on the pathways of hepatocyte injury, inflammation, and fibrosis cannot achieve the primary efficacy endpoints. Precision medicine can potentially overcome this issue, as it is founded on extensive knowledge of the druggable genome/proteome. Hence, this review summarizes significant trends and developments in precision medicine with a particular focus on new potential therapeutic discoveries modeled via systems biology approaches. In addition, we computed and simulated the potential utility of the NAFLD polygenic risk score, which could be conceptually very advantageous not only for early disease detection but also for implementing actionable measures. Incomplete knowledge of the druggable NAFLD genome severely impedes the drug discovery process and limits the likelihood of identifying robust and safe drug candidates. Thus, we close this article with some insights into emerging disciplines, such as chemical genetics, that may accelerate accurate identification of the druggable NAFLD genome/proteome.

Validating a non-invasive, ALT-based non-alcoholic fatty liver phenotype in the million veteran program

BACKGROUND & AIMS

Given ongoing challenges in non-invasive non-alcoholic liver disease (NAFLD) diagnosis, we sought to validate an ALT-based NAFLD phenotype using measures readily available in electronic health records (EHRs) and population-based studies by leveraging the clinical and genetic data in the Million Veteran Program (MVP), a multi-ethnic mega-biobank of US Veterans.

METHODS

MVP participants with alanine aminotransferases (ALT) >40 units/L for men and >30 units/L for women without other causes of liver disease were compared to controls with normal ALT. Genetic variants spanning eight NAFLD risk or ALT-associated loci (LYPLAL1, GCKR, HSD17B13, TRIB1, PPP1R3B, ERLIN1, TM6SF2, PNPLA3) were tested for NAFLD associations with sensitivity analyses adjusting for metabolic risk factors and alcohol consumption. A manual EHR review assessed performance characteristics of the NAFLD phenotype with imaging and biopsy data as gold standards. Genetic associations with advanced fibrosis were explored using FIB4, NAFLD Fibrosis Score and platelet counts.

RESULTS

Among 322,259 MVP participants, 19% met non-invasive criteria for NAFLD. Trans-ethnic meta-analysis replicated associations with previously reported genetic variants in all but LYPLAL1 and GCKR loci (P<6x10-3), without attenuation when adjusted for metabolic risk factors and alcohol consumption. At the previously reported LYPLAL1 locus, the established genetic variant did not appear to be associated with NAFLD, however the regional association plot showed a significant association with NAFLD 279kb downstream. In the EHR validation, the ALT-based NAFLD phenotype yielded a positive predictive value 0.89 and 0.84 for liver biopsy and abdominal imaging, respectively (inter-rater reliability (Cohen's kappa = 0.98)). HSD17B13 and PNPLA3 loci were associated with advanced fibrosis.

CONCLUSIONS

We validate a simple, non-invasive ALT-based NAFLD phenotype using EHR data by leveraging previously established NAFLD risk-associated genetic polymorphisms.

Genetic Pathways in Nonalcoholic Fatty Liver Disease: Insights From Systems Biology

Nonalcoholic fatty liver disease (NAFLD) represents a burgeoning worldwide epidemic whose etiology reflects multiple interactions between environmental and genetic factors. Here, we review the major pathways and dominant genetic modifiers known to be relevant players in human NAFLD and which may determine key components of the heritability of distinctive disease traits including steatosis and fibrosis. In addition, we have employed general assumptions which are based on known genetic factors in NAFLD to build a systems biology prediction model that includes functional enrichment. This prediction model highlights additional complementary pathways that represent plausible intersecting signaling networks that we define here as an NAFLD-Reactome. We review the evidence connecting variants in each of the major known genetic modifiers (variants in patatin-like phospholipase domain containing 3, transmembrane 6 superfamily member 2, membrane-bound O-acyltransferase domain containing 7, glucokinase regulator, and hydroxysteroid 17-beta dehydrogenase 13) to NAFLD and expand the associated underlying mechanisms using functional enrichment predictions, based on both preclinical and cell-based experimental findings. These major candidate gene variants function in distinct pathways, including substrate delivery for de novo lipogenesis; mitochondrial energy use; lipid droplet assembly, lipolytic catabolism, and fatty acid compartmentalization; and very low-density lipoprotein assembly and secretion. The NAFLD-Reactome model expands these pathways and allows for hypothesis testing, as well as serving as a discovery platform for druggable targets across multiple pathways that promote NAFLD development and influence several progressive outcomes. In conclusion, we summarize the strengths and weaknesses of studies implicating selected variants in the pathophysiology of NAFLD and highlight opportunities for future clinical research and pharmacologic intervention, as well as the implications for clinical practice.

An intronic variant in the GCKR gene is associated with multiple lipids

Previous studies have shown that an intronic variant rs780094 of the GCKR gene (glucokinase regulatory protein) is significantly associated with several metabolites, but the associations of this genetic variant with different lipids is largely unknown. Therefore, we applied metabolomics approach to measure metabolites in a large Finnish population sample (METSIM study) to investigate their associations with rs780094 of GCKR. We measured metabolites by mass spectrometry from 5,181 participants. P < 5.8 × 10-5 was considered as statistically significant given 857 metabolites included in statistical analyses. We found novel negative associations of the T allele of GCKR rs780094 with serine and threonine, and positive associations with two metabolites of tryptophan, indolelactate and N-acetyltryptophan. Additionally, we found novel significant positive associations of this genetic variant with 12 glycerolipids and 19 glycerophospholipids. Significant negative associations were found for three glycerophospholipids (all plasmalogen-cholines), and two sphingolipids. Significant novel associations were also found with gamma-glutamylthreonine, taurocholenate sulfate, and retinol. Our study adds new information about the pleiotropy of the GCKR gene, and shows the associations of the T allele of GCKR rs780094 with lipids.