Machine learning enables new insights into genetic contributions to liver fat accumulation

Prevalence of at-risk MASH, MetALD and alcohol-associated steatotic liver disease in the general population

BACKGROUND

The prevalence of at-risk metabolic dysfunction-associated steatohepatitis (at-risk MASH) has not been systematically assessed.

AIM

To delineate the prevalence of at-risk MASH in a large population-based cohort.

METHODS

We conducted a cross-sectional analysis of 40,189 patients in the UK Biobank who underwent liver MRI. Hepatic steatosis was determined by proton density fat fraction (PDFF) ≥5%. Based on AASLD criteria, participants were classified as alcohol-associated steatotic liver disease (ALD), metabolic dysfunction-associated steatotic liver disease (MASLD), combined metabolic alcoholic liver disease (MetALD) and at-risk MASH.

RESULTS

Among 40,189 patients, 10,886 (27.0%) had a PDFF ≥5%, indicating SLD. Among patients with SLD, 1% had ALD, 89.0% had MASLD, 7.9% had MetALD and 2.2% had at-risk MASH. The at-risk MASH group, which included 0.6% of the general population, had the highest mean liver fat on MRI and the highest BMI. Serum biomarkers highlighted increased inflammation and metabolic changes in at-risk MASH. The prevalence of MASLD was significantly higher among men with a BMI ≥30 kg/m2. Non-obese women showed only a 12% risk of MASLD. Conversely, MetALD had similar prevalence in obese men and women and was absent in non-obese women.

CONCLUSIONS

MASLD is prevalent among patients with elevated PDFF on MRI. There are different sex- and BMI-specific prevalence of different steatotic liver disorders. At-risk MASH demonstrates the most severe metabolic and inflammatory profiles. This study provides novel estimates for the at-risk MASH population that will be eligible for treatment with pharmacologic therapy when approved by regulatory authorities.

The contribution of genetics and epigenetics to MAFLD susceptibility

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most common liver disease worldwide. The risk of developing MAFLD varies among individuals, due to a combination of environmental inherited and acquired genetic factors. Genome-wide association and next-generation sequencing studies are leading to the discovery of the common and rare genetic determinants of MAFLD. Thanks to the great advances in genomic technologies and bioinformatics analysis, genetic and epigenetic factors involved in the disease can be used to develop genetic risk scores specific for liver-related complications, which can improve risk stratification. Genetic and epigenetic factors lead to the identification of specific sub-phenotypes of MAFLD, and predict the individual response to a pharmacological therapy. Moreover, the variant transcripts and protein themselves represent new therapeutic targets. This review will discuss the current status of research into genetic as well as epigenetic modifiers of MAFLD development and progression.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

The citrate transporter SLC13A5 as a therapeutic target for kidney disease: evidence from Mendelian randomization to inform drug development

BACKGROUND

Solute carrier family 13 member 5 (SLC13A5) is a Na+-coupled citrate co-transporter that mediates entry of extracellular citrate into the cytosol. SLC13A5 inhibition has been proposed as a target for reducing progression of kidney disease. The aim of this study was to leverage the Mendelian randomization paradigm to gain insight into the effects of SLC13A5 inhibition in humans, towards prioritizing and informing clinical development efforts.

METHODS

The primary Mendelian randomization analyses investigated the effect of SLC13A5 inhibition on measures of kidney function, including creatinine and cystatin C-based measures of estimated glomerular filtration rate (creatinine-eGFR and cystatin C-eGFR), blood urea nitrogen (BUN), urine albumin-creatinine ratio (uACR), and risk of chronic kidney disease and microalbuminuria. Secondary analyses included a paired plasma and urine metabolome-wide association study, investigation of secondary traits related to SLC13A5 biology, a phenome-wide association study (PheWAS), and a proteome-wide association study. All analyses were compared to the effect of genetically predicted plasma citrate levels using variants selected from across the genome, and statistical sensitivity analyses robust to the inclusion of pleiotropic variants were also performed. Data were obtained from large-scale genetic consortia and biobanks, with sample sizes ranging from 5023 to 1,320,016 individuals.

RESULTS

We found evidence of associations between genetically proxied SLC13A5 inhibition and higher creatinine-eGFR (p = 0.002), cystatin C-eGFR (p = 0.005), and lower BUN (p = 3 × 10-4). Statistical sensitivity analyses robust to the inclusion of pleiotropic variants suggested that these effects may be a consequence of higher plasma citrate levels. There was no strong evidence of associations of genetically proxied SLC13A5 inhibition with uACR or risk of CKD or microalbuminuria. Secondary analyses identified evidence of associations with higher plasma calcium levels (p = 6 × 10-13) and lower fasting glucose (p = 0.02). PheWAS did not identify any safety concerns.

CONCLUSIONS

This Mendelian randomization analysis provides human-centric insight to guide clinical development of an SLC13A5 inhibitor. We identify plasma calcium and citrate as biologically plausible biomarkers of target engagement, and plasma citrate as a potential biomarker of mechanism of action. Our human genetic evidence corroborates evidence from various animal models to support effects of SLC13A5 inhibition on improving kidney function.

ANGPTL3 Deficiency and Risk of Hepatic Steatosis

BACKGROUND

ANGPTL3 (angiopoietin-like 3) is a therapeutic target for reducing plasma levels of triglycerides and low-density lipoprotein cholesterol. A recent trial with vupanorsen, an antisense oligonucleotide targeting hepatic production of ANGPTL3, reported a dose-dependent increase in hepatic fat. It is unclear whether this adverse effect is due to an on-target effect of inhibiting hepatic ANGPTL3.

METHODS

We recruited participants with ANGPTL3 deficiency related to ANGPTL3 loss-of-function (LoF) mutations, along with wild-type (WT) participants from 2 previously characterized cohorts located in Campodimele, Italy, and St. Louis, MO. Magnetic resonance spectroscopy and magnetic resonance proton density fat fraction were performed to measure hepatic fat fraction and the distribution of extrahepatic fat. To estimate the causal relationship between ANGPTL3 and hepatic fat, we generated a genetic instrument of plasma ANGPTL3 levels as a surrogate for hepatic protein synthesis and performed Mendelian randomization analyses with hepatic fat in the UK Biobank study.

RESULTS

We recruited participants with complete (n=6) or partial (n=32) ANGPTL3 deficiency related to ANGPTL3 LoF mutations, as well as WT participants (n=92) without LoF mutations. Participants with ANGPTL3 deficiency exhibited significantly lower total cholesterol (complete deficiency, 78.5 mg/dL; partial deficiency, 172 mg/dL; WT, 188 mg/dL; P<0.05 for both deficiency groups compared with WT), along with plasma triglycerides (complete deficiency, 26 mg/dL; partial deficiency, 79 mg/dL; WT, 88 mg/dL; P<0.05 for both deficiency groups compared with WT) without any significant difference in hepatic fat (complete deficiency, 9.8%; partial deficiency, 10.1%; WT, 9.9%; P>0.05 for both deficiency groups compared with WT) or severity of hepatic steatosis as assessed by magnetic resonance imaging. In addition, ANGPTL3 deficiency did not alter the distribution of extrahepatic fat. Results from Mendelian randomization analyses in 36 703 participants from the UK Biobank demonstrated that genetically determined ANGPTL3 plasma protein levels were causally associated with low-density lipoprotein cholesterol (P=1.7×10-17) and triglycerides (P=3.2×10-18) but not with hepatic fat (P=0.22).

CONCLUSIONS

ANGPTL3 deficiency related to LoF mutations in ANGPTL3, as well as genetically determined reduction of plasma ANGPTL3 levels, is not associated with hepatic steatosis. Therapeutic approaches to inhibit ANGPTL3 production in hepatocytes are not necessarily expected to result in the increased risk for hepatic steatosis that was observed with vupanorsen.

Genetic variation and elevated liver enzymes during childhood, adolescence and early adulthood

BACKGROUND

Genetic factors influence the risk of fatty liver disease (FLD) in adults. The aim of this study was to test if, and when, genetic risk factors known to affect FLD in adults begin to exert their deleterious effects during childhood, adolescence and early adulthood.

METHODS

We included up to 4018 British children and adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Three genetic variants known to associate robustly with FLD in adults (PNPLA3 rs738409, TM6SF2 rs58542926 and HSD17B13 rs72613567) were tested for association with plasma levels of alanine transaminase (ALT) and aspartate transaminase (AST) during childhood (mean age: 9.9 years), early adolescence (15.5 years), late adolescence (17.8 years), and early adulthood (24.5 years). We also tested the associations of a 17-variant score and whole-genome polygenic risk scores (PRS) derived from associations in adults with plasma ALT and AST at the same four time points. Associations with elastography-derived liver steatosis and fibrosis were tested in early adulthood.

RESULTS

Genetic risk factors for FLD (individually, combined into a 3-variant score, a 17-variant score and as a genome-wide PRS), were associated with higher liver enzymes, beginning in childhood and throughout adolescence and early adulthood. The ALT-increasing effects of the genetic risk variants became larger with increasing age. The ALT-PRS was associated with liver steatosis in early adulthood. No genetic associations with fibrosis were observed.

CONCLUSIONS

Genetic factors that promote FLD in adults associate with elevated liver enzymes already during childhood, and their effects get amplified with increasing age.

Advancing diagnosis and management of liver disease in adults through exome sequencing

BACKGROUND

Whole-exome sequencing (WES) is an effective tool for diagnosis in patients who remain undiagnosed despite a comprehensive clinical work-up. While WES is being used increasingly in pediatrics and oncology, it remains underutilized in non-oncological adult medicine, including in patients with liver disease, in part based on the faulty premise that adults are unlikely to harbor rare genetic variants with large effect size. Here, we aim to assess the burden of rare genetic variants underlying liver disease in adults at two major tertiary referral academic medical centers.

METHODS

WES analysis paired with comprehensive clinical evaluation was performed in fifty-two adult patients with liver disease of unknown etiology evaluated at two US tertiary academic health care centers.

FINDINGS

Exome analysis uncovered a definitive or presumed diagnosis in 33% of patients (17/52) providing insight into their disease pathogenesis, with most of these patients (12/17) not having a known family history of liver disease. Our data shows that over two-thirds of undiagnosed liver disease patients attaining a genetic diagnosis were being evaluated for cholestasis or hepatic steatosis of unknown etiology.

INTERPRETATION

This study reveals an underappreciated incidence and spectrum of genetic diseases presenting in adulthood and underscores the clinical value of incorporating exome sequencing in the evaluation and management of adults with liver disease of unknown etiology.

FUNDING

S.V. is supported by the NIH/NIDDK (K08 DK113109 and R01 DK131033-01A1) and the Doris Duke Charitable Foundation Grant #2019081. This work was supported in part by NIH-funded Yale Liver Center, P30 DK34989.

Low LDL Cholesterol Is Not an Independent Risk Factor for Hepatic Steatosis

BACKGROUND

Genetic mutations causing defective VLDL secretion and low LDL cholesterol are associated with hepatic steatosis and nonalcoholic fatty liver disease (NAFLD).

AIMS

Determine if low LDL cholesterol (< 5th percentile) was an independent predictor of hepatic steatosis.

METHODS

Secondary data analysis of the Dallas Heart study (an urban, multiethnic, probability-based sample), we defined hepatic steatosis utilizing intrahepatic triglyceride (IHTG) analyzed using magnetic resonance spectroscopy in conjunction and available demographic, serological and genetic information. We exclude patients on lipid lowering medications.

RESULTS

Of the 2094 subjects that met our exclusion criteria, 86 had a low LDL cholesterol, of whom 19 (22%) exhibited hepatic steatosis. After matching for age, sex, BMI, and alcohol consumption, low LDL cholesterol was not a risk factor for hepatic steatosis compared to those with normal (50-180 mg/dL) or high (> 180 mg/dL) LDL. When analyzed as a continuous variable, we observed lower IHTG in the low LDL group compared to the normal or high LDL groups (2.2%, 3.5%, 4.6%; all pairwise comparisons p < 0.001). Subjects with both hepatic steatosis and low LDL cholesterol exhibited a more favorable lipid profile but similar insulin resistance and hepatic fibrosis risk compared to other subjects with hepatic steatosis. The distribution of variant alleles associated with NAFLD, including PNPLA3, GCKR, and MTTP was indistinguishable between subjects with hepatic steatosis and low versus high LDL cholesterol.

CONCLUSION

These findings suggest that low serum LDL levels are not a useful predictor of hepatic steatosis and NAFLD. Moreover, subjects with low LDL exhibit a more favorable lipid profile and lower IHTG.

An adult-based genetic risk score for liver fat associates with liver and plasma lipid traits in children and adolescents

BACKGROUND & AIMS

Genome-wide association studies have identified steatogenic variants that also showed pleiotropic effects on cardiometabolic traits in adults. We investigated the effect of eight previously reported genome-wide significant steatogenic variants, individually and combined in a weighted genetic risk score (GRS), on liver and cardiometabolic traits, and the predictive ability of the GRS for hepatic steatosis in children and adolescents.

APPROACH & RESULTS

Children and adolescents with overweight (including obesity) from an obesity clinic group (n = 1768) and a population-based group (n = 1890) were included. Cardiometabolic risk outcomes and genotypes were obtained. Liver fat was quantified using 1 H-MRS in a subset of 727 participants. Variants in PNPLA3, TM6SF2, GPAM and TRIB1 were associated with higher liver fat (p < .05) and with distinct patterns of plasma lipids. The GRS was associated with higher liver fat content, plasma concentrations of alanine transaminase (ALT), aspartate aminotransferase (AST) and favourable plasma lipid levels. The GRS was associated with higher prevalence of hepatic steatosis (defined as liver fat ≥5.0%) (odds ratio per 1-SD unit: 2.17, p = 9.7E-10). A prediction model for hepatic steatosis including GRS alone yielded an area under the curve (AUC) of 0.78 (95% CI 0.76-0.81). Combining the GRS with clinical measures (waist-to-height ratio [WHtR] SDS, ALT, and HOMA-IR) increased the AUC up to 0.86 (95% CI 0.84-0.88).

CONCLUSIONS

The genetic predisposition for liver fat accumulation conferred risk of hepatic steatosis in children and adolescents. The liver fat GRS has potential clinical utility for risk stratification.

Microtubule-Associated Serine/Threonine (MAST) Kinases in Development and Disease

Microtubule-Associated Serine/Threonine (MAST) kinases represent an evolutionary conserved branch of the AGC protein kinase superfamily in the kinome. Since the discovery of the founding member, MAST2, in 1993, three additional family members have been identified in mammals and found to be broadly expressed across various tissues, including the brain, heart, lung, liver, intestine and kidney. The study of MAST kinases is highly relevant for unraveling the molecular basis of a wide range of different human diseases, including breast and liver cancer, myeloma, inflammatory bowel disease, cystic fibrosis and various neuronal disorders. Despite several reports on potential substrates and binding partners of MAST kinases, the molecular mechanisms that would explain their involvement in human diseases remain rather obscure. This review will summarize data on the structure, biochemistry and cell and molecular biology of MAST kinases in the context of biomedical research as well as organismal model systems in order to provide a current profile of this field.

Association of Rare Protein-Truncating DNA Variants in APOB or PCSK9 With Low-density Lipoprotein Cholesterol Level and Risk of Coronary Heart Disease

Importance

Protein-truncating variants (PTVs) in apolipoprotein B (APOB) and proprotein convertase subtilisin/kexin type 9 (PCSK9) are associated with significantly lower low-density lipoprotein (LDL) cholesterol concentrations. The association of these PTVs with coronary heart disease (CHD) warrants further characterization in large, multiracial prospective cohort studies.

Objective

To evaluate the association of PTVs in APOB and PCSK9 with LDL cholesterol concentrations and CHD risk.

Design, Setting, and Participants

This studied included participants from 5 National Heart, Lung, and Blood Institute (NHLBI) studies and the UK Biobank. NHLBI study participants aged 5 to 84 years were recruited between 1971 and 2002 across the US and underwent whole-genome sequencing. UK Biobank participants aged 40 to 69 years were recruited between 2006 and 2010 in the UK and underwent whole-exome sequencing. Data were analyzed from June 2021 to October 2022.

Exposures

PTVs in APOB and PCSK9.

Main Outcomes and Measures

Estimated untreated LDL cholesterol levels and CHD.

Results

Among 19 073 NHLBI participants (10 598 [55.6%] female; mean [SD] age, 52 [17] years), 139 (0.7%) carried an APOB or PCSK9 PTV, which was associated with 49 mg/dL (95% CI, 43-56) lower estimated untreated LDL cholesterol level. Over a median (IQR) follow-up of 21.5 (13.9-29.4) years, incident CHD was observed in 12 of 139 carriers (8.6%) vs 3029 of 18 934 noncarriers (16.0%), corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.28-0.89; P = .02). Among 190 464 UK Biobank participants (104 831 [55.0%] female; mean [SD] age, 57 [8] years), 662 (0.4%) carried a PTV, which was associated with 45 mg/dL (95% CI, 42-47) lower estimated untreated LDL cholesterol level. Estimated CHD risk by age 75 years was 3.7% (95% CI, 2.0-5.3) in carriers vs 7.0% (95% CI, 6.9-7.2) in noncarriers, corresponding to an adjusted hazard ratio of 0.51 (95% CI, 0.32-0.81; P = .004).

Conclusions and Relevance

Among 209 537 individuals in this study, 0.4% carried an APOB or PCSK9 PTV that was associated with less exposure to LDL cholesterol and a 49% lower risk of CHD.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Impact of Measurement Imprecision on Genetic Association Studies of Cardiac Function

Background

Recent studies have leveraged quantitative traits from imaging to amplify the power of genome-wide association studies (GWAS) to gain further insights into the biology of diseases and traits. However, measurement imprecision is intrinsic to phenotyping and can impact downstream genetic analyses.

Methods

Left ventricular ejection fraction (LVEF), an important but imprecise quantitative imaging measurement, was examined to assess the impact of precision of phenotype measurement on genetic studies. Multiple approaches to obtain LVEF, as well as simulated measurement noise, were evaluated with their impact on downstream genetic analyses.

Results

Even within the same population, small changes in the measurement of LVEF drastically impacted downstream genetic analyses. Introducing measurement noise as little as 7.9% can eliminate all significant genetic associations in an GWAS with almost forty thousand individuals. An increase of 1% in mean absolute error (MAE) in LVEF had an equivalent impact on GWAS power as a decrease of 10% in the cohort sample size, suggesting optimizing phenotyping precision is a cost-effective way to improve power of genetic studies.

Conclusions

Improving the precision of phenotyping is important for maximizing the yield of genome-wide association studies.

BMI-adjusted adipose tissue volumes exhibit depot-specific and divergent associations with cardiometabolic diseases

For any given body mass index (BMI), individuals vary substantially in fat distribution, and this variation may have important implications for cardiometabolic risk. Here, we study disease associations with BMI-independent variation in visceral (VAT), abdominal subcutaneous (ASAT), and gluteofemoral (GFAT) fat depots in 40,032 individuals of the UK Biobank with body MRI. We apply deep learning models based on two-dimensional body MRI projections to enable near-perfect estimation of fat depot volumes (R2 in heldout dataset = 0.978-0.991 for VAT, ASAT, and GFAT). Next, we derive BMI-adjusted metrics for each fat depot (e.g. VAT adjusted for BMI, VATadjBMI) to quantify local adiposity burden. VATadjBMI is associated with increased risk of type 2 diabetes and coronary artery disease, ASATadjBMI is largely neutral, and GFATadjBMI is associated with reduced risk. These results - describing three metabolically distinct fat depots at scale - clarify the cardiometabolic impact of BMI-independent differences in body fat distribution.

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.

Effects of metabolic traits, lifestyle factors, and pharmacological interventions on liver fat: mendelian randomisation study

Objective

To investigate the effects of metabolic traits, lifestyle factors, and drug interventions on liver fat using the mendelian randomisation paradigm.

Design

Mendelian randomisation study.

Setting

Publicly available summary level data from genome-wide association studies.

Participants

Genome-wide association studies of 32 974 to 1 407 282 individuals who were predominantly of European descent.

Exposures

Genetic variants predicting nine metabolic traits, six lifestyle factors, four lipid lowering drug targets, three antihypertensive drug targets, and genetic association estimates formagnetic resonance imaging measured liver fat.

Main outcome measures

Mendelian randomisation analysis was used to investigate the effects of these exposures on liver fat, incorporating sensitivity analyses that relaxed the requisite modelling assumptions.

Results

Genetically predicted liability to obesity, type 2 diabetes, elevated blood pressure, elevated triglyceride levels, cigarette smoking, and sedentary time watching television were associated with higher levels of liver fat. Genetically predicted lipid lowering drug effects were not associated with liver fat; however, β blocker and calcium channel blocker antihypertensive drug effects were associated with lower levels of liver fat.

Conclusion

These analyses provide evidence of a causal effect of various metabolic traits, lifestyle factors, and drug targets on liver fat. The findings complement existing epidemiological associations, further provide mechanistic insight, and potentially supports a role for drug interventions in reducing the burden of hepatic steatosis and related disease. Further clinical study is now warranted to investigate the relevance of these genetic analyses for patient care.

Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy

BACKGROUND

Liver disease indicates any pathology that can harm or destroy the liver or prevent it from normal functioning. The global community has recently witnessed an increase in the mortality rate due to liver disease. This could be attributed to many factors, among which are human habits, awareness issues, poor healthcare, and late detection. To curb the growing threats from liver disease, early detection is critical to help reduce the risks and improve treatment outcome. Emerging technologies such as machine learning, as shown in this study, could be deployed to assist in enhancing its prediction and treatment.

AIM

To present a more efficient system for timely prediction of liver disease using a hybrid eXtreme Gradient Boosting model with hyperparameter tuning with a view to assist in early detection, diagnosis, and reduction of risks and mortality associated with the disease.

METHODS

The dataset used in this study consisted of 416 people with liver problems and 167 with no such history. The data were collected from the state of Andhra Pradesh, India, through https://www.kaggle.com/datasets/uciml/indian-liver-patient-records. The population was divided into two sets depending on the disease state of the patient. This binary information was recorded in the attribute "is_patient".

RESULTS

The results indicated that the chi-square automated interaction detection and classification and regression trees models achieved an accuracy level of 71.36% and 73.24%, respectively, which was much better than the conventional method. The proposed solution would assist patients and physicians in tackling the problem of liver disease and ensuring that cases are detected early to prevent it from developing into cirrhosis (scarring) and to enhance the survival of patients. The study showed the potential of machine learning in health care, especially as it concerns disease prediction and monitoring.

CONCLUSION

This study contributed to the knowledge of machine learning application to health and to the efforts toward combating the problem of liver disease. However, relevant authorities have to invest more into machine learning research and other health technologies to maximize their potential.

Artificial intelligence for precision medicine in autoimmune liver disease

Autoimmune liver diseases (AiLDs) are rare autoimmune conditions of the liver and the biliary tree with unknown etiology and limited treatment options. AiLDs are inherently characterized by a high degree of complexity, which poses great challenges in understanding their etiopathogenesis, developing novel biomarkers and risk-stratification tools, and, eventually, generating new drugs. Artificial intelligence (AI) is considered one of the best candidates to support researchers and clinicians in making sense of biological complexity. In this review, we offer a primer on AI and machine learning for clinicians, and discuss recent available literature on its applications in medicine and more specifically how it can help to tackle major unmet needs in AiLDs.

Variants in mitochondrial amidoxime reducing component 1 and hydroxysteroid 17-beta dehydrogenase 13 reduce severity of nonalcoholic fatty liver disease in children and suppress fibrotic pathways through distinct mechanisms

Genome-wide association studies in adults have identified variants in hydroxysteroid 17-beta dehydrogenase 13 (HSD17B13) and mitochondrial amidoxime reducing component 1 (MTARC1) as protective against nonalcoholic fatty liver disease (NAFLD). We aimed to test their association with pediatric NAFLD liver histology and investigate their function using metabolomics. A total of 1450 children (729 with NAFLD, 399 with liver histology) were genotyped for rs72613567T>TA in HSD17B13, rs2642438G>A in MTARC1, and rs738409C>G in patatin-like phospholipase domain-containing protein 3 (PNPLA3). Genotype-histology associations were tested using ordinal regression. Untargeted hepatic proteomics and plasma lipidomics were performed in a subset of children. We found rs72613567T>TA in HSD17B13 to be associated with lower odds of NAFLD diagnosis (odds ratio, 0.7; 95% confidence interval, 0.6-0.9) and a lower grade of portal inflammation (p < 0.001). rs2642438G>A in MTARC1 was associated with a lower grade of hepatic steatosis (p = 0.02). Proteomics found reduced expression of HSD17B13 in carriers of the protective -TA allele. MTARC1 levels were unaffected by genotype. Both variants were associated with down-regulation of fibrogenic pathways. HSD17B13 perturbs plasma phosphatidylcholines and triglycerides. In silico modeling suggested p.Ala165Thr disrupts the stability and metal binding of MTARC1. Conclusion: Both HSD17B13 and MTARC1 variants are associated with less severe pediatric NAFLD. These results provide further evidence for shared genetic mechanisms between pediatric and adult NAFLD.

Enzyme Electrode Biosensors for N-Hydroxylated Prodrugs Incorporating the Mitochondrial Amidoxime Reducing Component

Human mitochondrial amidoxime reducing component 1 and 2 (mARC1 and mARC2) were immobilised on glassy carbon electrodes using the crosslinker glutaraldehyde. Voltammetry was performed in the presence of the artificial electron transfer mediator methyl viologen, whose redox potential lies negative of the enzymes' Mo^VI/V and Mo^V/IV redox potentials which were determined from optical spectroelectrochemical and EPR measurements. Apparent Michaelis constants obtained from catalytic limiting currents at various substrate concentrations were comparable to those previously reported in the literature from enzymatic assays. Kinetic parameters for benzamidoxime reduction were determined from cyclic voltammograms simulated using Digisim. pH dependence and stability of the enzyme electrode with time were also determined from limiting catalytic currents in saturating concentrations of benzamidoxime. The same electrode remained active after at least 9 days. Fabrication of this versatile and cost-effective biosensor is effective in screening new pharmaceutically important substrates and mARC inhibitors.

A multiancestry genome-wide association study of unexplained chronic ALT elevation as a proxy for nonalcoholic fatty liver disease with histological and radiological validation

Nonalcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver disease. Using a proxy NAFLD definition of chronic elevation of alanine aminotransferase (cALT) levels without other liver diseases, we performed a multiancestry genome-wide association study (GWAS) in the Million Veteran Program (MVP) including 90,408 cALT cases and 128,187 controls. Seventy-seven loci exceeded genome-wide significance, including 25 without prior NAFLD or alanine aminotransferase associations, with one additional locus identified in European American-only and two in African American-only analyses (P < 5 × 10-8). External replication in histology-defined NAFLD cohorts (7,397 cases and 56,785 controls) or radiologic imaging cohorts (n = 44,289) replicated 17 single-nucleotide polymorphisms (SNPs) (P < 6.5 × 10-4), of which 9 were new (TRIB1, PPARG, MTTP, SERPINA1, FTO, IL1RN, COBLL1, APOH and IFI30). Pleiotropy analysis showed that 61 of 77 multiancestry and all 17 replicated SNPs were jointly associated with metabolic and/or inflammatory traits, revealing a complex model of genetic architecture. Our approach integrating cALT, histology and imaging reveals new insights into genetic liability to NAFLD.