Liver and Statins: A Critical Appraisal of the Evidence

2019 ◽  
Vol 25 (42) ◽  
pp. 5835-5846 ◽  
Author(s):  
Anna Licata ◽  
Antonina Giammanco ◽  
Maria Giovanna Minissale ◽  
Salvatore Pagano ◽  
Salvatore Petta ◽  
...  
Keyword(s):  
Adverse Events ◽  
Association Studies ◽  
Organic Anion ◽  
Genome Wide Association Studies ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Organic Anion Transporting Polypeptide ◽  
Treatment And Prevention ◽  
Genome Wide ◽  
Underlying Mechanisms

Adverse drug reactions (ADRs) represent an important cause of morbidity and mortality worldwide. Statins are a class of drugs whose main adverse effects are drug-induced liver injury (DILI) and myopathy. Some of these may be predictable, due to their pharmacokinetic and pharmacodynamic properties, while others, unfortunately, are idiosyncratic. Genetic factors may also influence patient susceptibility to DILI and myopathy in the case of statins. This review will first discuss the role of statins in cardiovascular disease treatment and prevention and the underlying mechanisms of action. Furthermore, to explore the susceptibility of statin-induced adverse events such as myopathy and hepatotoxicity, it will then focus on the recent Genome-Wide Association Studies (GWAS) concerning the transporter genes, Cytochrome P450 (CYP), organic anion-transporting polypeptide (OATP) and ABCB1 and ABCC1, which seem to play a role in the development of clinically relevant adverse events. Finally, we appraise the evidence for and against the use of statins in metabolic syndrome and in HCV-infected patients, in terms of their safety and efficacy in cardiovascular events.

ABCB4 Gene Aberrations in Human Liver Disease: An Evolving Spectrum

2018 ◽  
Vol 38 (04) ◽  
pp. 299-307 ◽  
Author(s):  
Matthias Reichert ◽  
Frank Lammert
Keyword(s):  
Intrahepatic Cholestasis ◽  
Association Studies ◽  
Compound Heterozygous ◽  
Genome Wide Association Studies ◽  
Therapeutic Approaches ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Genome Wide ◽  
Abcb4 Gene ◽  
Type 3

AbstractATP-binding cassette subfamily B member 4 (ABCB4) is a phospholipid translocator at the canalicular membrane of the hepatocyte, which “flops” phosphatidylcholine into bile. Dysfunction of this transporter due to ABCB4 gene variants can cause liver diseases and has been called ABCB4 deficiency. Several diseases including progressive familial intrahepatic cholestasis type 3 (PFIC3), low phospholipid-associated cholelithiasis (LPAC), a subgroup of patients developing intrahepatic cholestasis of pregnancy (ICP), drug-induced liver injury and chronic cholangiopathy with biliary fibrosis and cirrhosis were attributed to ABCB4 deficiency and characterized in the past decade. LPAC and ICP are usually caused by monoallelic variants, whereas patients affected by PFIC3 are homozygous or compound heterozygous carriers of ABCB4 variants. Treatment with ursodeoxycholic acid is often effective, but as the more severe forms of ABCB4 deficiency progress, nevertheless, new diagnostic and therapeutic approaches are warranted. Current functional classifications for ABCB4 deficiency–associated mutations can guide the development of novel genotype–based targeted pharmacotherapies for these conditions. Recently, increasing evidence from genome-wide association studies is emerging on associations of ABCB4 variants with hepatobiliary malignancies.

Genome-Wide Association Studies of Drug-Induced Liver Injury Make Progress Beyond the HLA Region

2019 ◽  
Vol 157 (4) ◽  
pp. 1167-1168
Author(s):  
Galen E.B. Wright ◽  
Britt I. Drögemöller ◽  
Colin J.D. Ross ◽  
Bruce C. Carleton
Keyword(s):  
Liver Injury ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
Genome Wide

Genetics in Common Liver Diseases: From Pathophysiology to Precise Treatment

2016 ◽  
Vol 34 (4) ◽  
pp. 391-395 ◽  
Author(s):  
Frank Lammert
Keyword(s):  
Liver Disease ◽  
Liver Diseases ◽  
Association Studies ◽  
Clinical Care ◽  
Genome Wide Association Studies ◽  
Drug Induced ◽  
Drug Induced Liver Injury ◽  
The Past ◽  
Genomic Technologies ◽  
Genome Wide

In the past 2 decades, advances in genetics have improved our understanding of liver disease and physiology. Firstly, developments in genomic technologies drove the identification of genes responsible for monogenic (Mendelian) liver diseases. Over the last decade, genome-wide association studies allowed for the dissection of the genetic susceptibility to complex liver diseases such as fatty liver disease and drug-induced liver injury, in which environmental co-factors play critical roles. The findings have allowed the identification and elaboration of pathophysiological processes, have indicated the need for reclassification of liver diseases and risk factors and have already pointed to new disease treatments. This is illustrated by the interaction of alcohol, overnutrition and the PNPLA3 gene, which represents an ‘infernal triangle' for the liver. In the future, genetics will allow further stratification of liver diseases and contribute to personalized (precision) medicine, offering novel opportunities for translational research and clinical care of our patients.

scholarly journals Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Nature ◽  
2021 ◽  
Vol 590 (7845) ◽  
pp. 290-299 ◽  
Author(s):  
Daniel Taliun ◽  
◽  
Daniel N. Harris ◽  
Michael D. Kessler ◽  
Jedidiah Carlson ◽  
...  
Keyword(s):  
Rare Variants ◽  
Sequence Data ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Phenotypic Data ◽  
Treatment And Prevention ◽  
Genome Wide ◽  
Diverse Backgrounds ◽  
Unmapped Reads

AbstractThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

scholarly journals Genomic dissection of 43 serum urate-associated loci provides multiple insights into molecular mechanisms of urate control

2019 ◽  
Author(s):  
James Boocock ◽  
Megan Leask ◽  
Yukinori Okada ◽  
Hirotaka Matsuo ◽  
Yusuke Kawamura ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Organic Anion ◽  
Serum Urate ◽  
Regulatory Function ◽  
Eqtl Analysis ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Causal Genes

AbstractSerum urate is the end-product of purine metabolism. Elevated serum urate is causal of gout and a predictor of renal disease, cardiovascular disease and other metabolic conditions. Genome-wide association studies (GWAS) have reported dozens of loci associated with serum urate control, however there has been little progress in understanding the molecular basis of the associated loci. Here we employed trans-ancestral meta-analysis using data from European and East Asian populations to identify ten new loci for serum urate levels. Genome-wide colocalization with cis-expression quantitative trait loci (eQTL) identified a further five new loci. By cis- and trans-eQTL colocalization analysis we identified 24 and 20 genes respectively where the causal eQTL variant has a high likelihood that it is shared with the serum urate-associated locus. One new locus identified was SLC22A9 that encodes organic anion transporter 7 (OAT7). We demonstrate that OAT7 is a very weak urate-butyrate exchanger. Newly implicated genes identified in the eQTL analysis include those encoding proteins that make up the dystrophin complex, a scaffold for signaling proteins and transporters at the cell membrane; MLXIP that, with the previously identified MLXIPL, is a transcription factor that may regulate serum urate via the pentose-phosphate pathway; and MRPS7 and IDH2 that encode proteins necessary for mitochondrial function. Trans-ancestral functional fine-mapping identified six loci (RREB1, INHBC, HLF, UBE2Q2, SFMBT1, HNF4G) with colocalized eQTL that contained putative causal SNPs (posterior probability of causality > 0.8). This systematic analysis of serum urate GWAS loci has identified candidate causal genes at 19 loci and a network of previously unidentified genes likely involved in control of serum urate levels, further illuminating the molecular mechanisms of urate control.Author SummaryHigh serum urate is a prerequisite for gout and a risk factor for metabolic disease. Previous GWAS have identified numerous loci that are associated with serum urate control, however, only a small handful of these loci have known molecular consequences. The majority of loci are within the non-coding regions of the genome and therefore it is difficult to ascertain how these variants might influence serum urate levels without tangible links to gene expression and / or protein function. We have applied a novel bioinformatic pipeline where we combined population-specific GWAS data with gene expression and genome connectivity information to identify putative causal genes for serum urate associated loci. Overall, we identified 15 novel serum urate loci and show that these loci along with previously identified loci are linked to the expression of 44 genes. We show that some of the variants within these loci have strong predicted regulatory function which can be further tested in functional analyses. This study expands on previous GWAS by identifying further loci implicated in serum urate control and new causal mechanisms supported by gene expression changes.

scholarly journals Genome-wide Association Study Of Plasma Proteins Identifies Putatively Causal Genes, Proteins, And Pathways For Cardiovascular Disease

2017 ◽  
Author(s):  
Chen Yao ◽  
George Chen ◽  
Ci Song ◽  
Michael Mendelson ◽  
Tianxiao Huan ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Treatment And Prevention ◽  
Genome Wide ◽  
Causal Genes ◽  
Disease Associations ◽  
Long Term Follow Up

SummaryIdentifying genetic variants associated with circulating protein concentrations (pQTLs) and integrating them with variants from genome-wide association studies (GWAS) may illuminate the proteome’s causal role in disease and bridge a GWAS knowledge gap for hitherto unexplained SNP-disease associations. We conducted GWAS of 71 high-value proteins for cardiovascular disease in 6,861 Framingham Heart Study participants followed by external replication. We comprehensively mapped thousands of pQTLs, including functional annotations and clinical-trait associations, and created an integrated plasma-protein-QTL searchable database. We next identified 15 proteins with pQTLs coinciding with coronary heart disease (CHD)-related variants from GWAS or tested causal for CHD by Mendelian randomization; most of these proteins were associated with new-onset cardiovascular disease events in Framingham participants with long-term follow-up. Identifying pQTLs and integrating them with GWAS results yields insights into genes, proteins, and pathways that may be causally associated with disease and can serve as therapeutic targets for treatment and prevention.

scholarly journals Cross–trait analysis of Alzheimer’s disease and gastrointestinal tract disorders identifies shared loci highlighting immune-related and statin pathways

2021 ◽  
Author(s):  
Emmanuel Adewuyi ◽  
Eleanor O’Brien ◽  
Dale Nyholt ◽  
Tenielle Porter ◽  
Simon Laws
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Gastrointestinal Tract ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Ulcer Disease ◽  
Genome Wide ◽  
Underlying Mechanisms ◽  
Irritable Bowel

Abstract Several observational studies suggest a relationship between Alzheimer’s disease (AD) and gastrointestinal tract (GIT) disorders; however, their underlying mechanisms remain unclear. Here, we analysed several genome-wide association studies (GWAS) summary statistics (N = 34,652 – 456,327) to assess AD and GIT disorders relationships. We found a significant genetic overlap and correlation between AD and each of gastroesophageal reflux disease (GERD), peptic ulcer disease (PUD), medications for GERD or PUD (PGM), gastritis-duodenitis, irritable bowel syndrome and diverticulosis, but not inflammatory bowel disease. Our analysis suggests a partial causal association between AD and gastritis-duodenitis, diverticulosis and medication for PUD. GWAS meta-analysis identified seven loci (P < 5 × 10-8, PDE4B, CD46, SEMA3F, HLA-DRA, MTSS2, PHB, and APOE) shared by AD and PGM, six of which are novel. These loci were replicated using GERD and PUD GWAS and reinforced in gene-based analyses. Lipid metabolism, autoimmune system, lipase inhibitors, PD-1 signalling, and statin pathways were significantly enriched for AD and GIT disorders. These findings support shared genetic susceptibility in AD and GIT disorders. Lipase inhibitors and statins may provide novel therapeutic avenues for AD, GIT disorders, or their comorbidity.

scholarly journals Investigating Casual Associations among Gut Microbiota, Metabolites and Neurodegenerative Diseases: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Jin-Tai Yu ◽  
Jing Ning ◽  
Shu-Yi Huang ◽  
Shi-Dong Chen ◽  
Yu-Xiang Yang ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Neurodegenerative Diseases ◽  
Protective Factor ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Causal Relationships ◽  
Genome Wide ◽  
Underlying Mechanisms ◽  
Lateral Sclerosis

Abstract Background Recent studies had explored that the gut microbiota was associated with neurodegenerative diseases (including Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS)) through the gut-brain axis, among which metabolic pathways played an important role. However, the underlying causality remained unclear. Our study aimed to evaluate potential causal relationships between gut microbiota, metabolites and neurodegenerative diseases through Mendelian randomization (MR) approach. Methods We selected genetic variants associated with gut microbiota traits (N = 18340) and gut microbiota-derived metabolites (N = 7824) from genome-wide association studies (GWASs). Summary statistics of neurodegenerative diseases were obtained from IGAP (AD: 17008 cases; 37154 controls), IPDGC (PD: 37 688 cases; 141779 controls) and IALSC (ALS: 20806 cases; 59804 controls) respectively. Results A total of 19 gut microbiota traits were found to be causally associated with risk of neurodegenerative diseases, including 1 phylum, 2 classes, 2 orders, 2 families and 12 genera. We found genetically predicted greater abundance of Ruminococcus, at genus level (OR:1.245, 95%CI:1.103,1.405; P = 0.0004) was significantly related to higher risk of ALS. We also found suggestive association between 12 gut microbiome-dependent metabolites and neurodegenerative diseases. For serotonin pathway, our results revealed serotonin as protective factor of PD, and kynurenine as risk factor of ALS. Besides, reduction of glutamine was found causally associated with occurrence of AD. Conclusions Our study firstly applied a two-sample MR approach to detect causal relationships among gut microbiota, gut metabolites and the risk of AD, PD and ALS, and we revealed several causal relationships. These findings may provide new targets for treatment of these neurodegenerative diseases, and may offer valuable insights for further researches on the underlying mechanisms.

scholarly journals A practical view of fine-mapping and gene prioritization in the post-genome-wide association era

Open Biology ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 190221 ◽  
Author(s):  
R. V. Broekema ◽  
O. B. Bakker ◽  
I. H. Jonkers
Keyword(s):  
Fine Mapping ◽  
Complex Traits ◽  
Association Studies ◽  
Population Based ◽  
Gene Prioritization ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Underlying Mechanisms ◽  
The Impact

Over the past 15 years, genome-wide association studies (GWASs) have enabled the systematic identification of genetic loci associated with traits and diseases. However, due to resolution issues and methodological limitations, the true causal variants and genes associated with traits remain difficult to identify. In this post-GWAS era, many biological and computational fine-mapping approaches now aim to solve these issues. Here, we review fine-mapping and gene prioritization approaches that, when combined, will improve the understanding of the underlying mechanisms of complex traits and diseases. Fine-mapping of genetic variants has become increasingly sophisticated: initially, variants were simply overlapped with functional elements, but now the impact of variants on regulatory activity and direct variant-gene 3D interactions can be identified. Moreover, gene manipulation by CRISPR/Cas9, the identification of expression quantitative trait loci and the use of co-expression networks have all increased our understanding of the genes and pathways affected by GWAS loci. However, despite this progress, limitations including the lack of cell-type- and disease-specific data and the ever-increasing complexity of polygenic models of traits pose serious challenges. Indeed, the combination of fine-mapping and gene prioritization by statistical, functional and population-based strategies will be necessary to truly understand how GWAS loci contribute to complex traits and diseases.

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