Phenome-Wide Association Analysis Reveals Novel Links Between Genetically Determined Levels of Liver Enzymes and Disease Phenotypes

SPAGRM: effectively controlling for sample relatedness in large-scale genome-wide association studies of longitudinal traits

Sample relatedness is a major confounder in genome-wide association studies (GWAS), potentially leading to inflated type I error rates if not appropriately controlled. A common strategy is to incorporate a random effect related to genetic relatedness matrix (GRM) into regression models. However, this approach is challenging for large-scale GWAS of complex traits, such as longitudinal traits. Here we propose a scalable and accurate analysis framework, SPAGRM, which controls for sample relatedness via a precise approximation of the joint distribution of genotypes. SPAGRM can utilize GRM-free models and thus is applicable to various trait types and statistical methods, including linear mixed models and generalized estimation equations for longitudinal traits. A hybrid strategy incorporating saddlepoint approximation greatly increases the accuracy to analyze low-frequency and rare genetic variants, especially in unbalanced phenotypic distributions. We also introduce SPAGRM(CCT) to aggregate the results following different models via Cauchy combination test. Extensive simulations and real data analyses demonstrated that SPAGRM maintains well-controlled type I error rates and SPAGRM(CCT) can serve as a broadly effective method. Applying SPAGRM to 79 longitudinal traits extracted from UK Biobank primary care data, we identified 7,463 genetic loci, making a pioneering attempt to conduct GWAS for these traits as longitudinal traits.

Bruceine A alleviates alcoholic liver disease by inhibiting AIM2 inflammasome activation via activating FXR

BACKGROUND

Alcoholic liver disease (ALD), a public health challenge worldwide caused by long-term persistent drinking, is life-threatening with minimal approved therapies. Hepatic steatosis accompanied by inflammation is an initial and inevitable stage in the complex progression of simple alcoholic liver injury to more severe liver diseases such as hepatitis, liver fibrosis, cirrhosis and liver cancer.

PURPOSE

We aimed to identify the therapeutic role of Bruceine A (BA) in ALD whilst attempting to explore whether its protective effects depend specifically on the farnesoid X receptor (FXR).

METHODS

Autodock was applied to detect the affinity between BA and FXR. Lieber-DeCarli liquid diet with 5 % ethanol (v/v) was adopted to establish the mouse ALD model. The lentivirus mediating FXR (LV-FXR) was injected into mice via the tail vein to establish FXR-overexpressed mice. FXR silencing or overexpression plasmids were transfected into AML-12 cells prior to ethanol stimulation. Quantitative real-time PCR, Western blotting and immunofluorescence assays were employed to determine the expression of related genes. We subjected liver sections to H&E and Oil Red O staining to evaluate the liver histological injury and the deposition of lipid droplets.

RESULTS

BA significantly reduced body weight and liver-to-body weight ratios as well as biochemical indexes in mice. Ethanol-induced liver damage and lipid accumulation could be alleviated by BA treatment. BA bound to FXR by two hydrogen bonds. There was a positive correlation between BA administration and FXR expression. BA inhibited the expression of lipid synthesis genes and enhanced the expression of lipid metabolism genes by activating FXR, thus alleviating steatosis in ALD. Moreover, BA exerted an ameliorative effect against inflammation by inhibiting the activation of absent in melanoma 2 (AIM2) inflammasome by activating FXR. FXR overexpression possessed the ability to counter the accumulation of lipid and the activation of AIM2 inflammasome caused by ethanol. FXR deficiency exacerbated ethanol-induced liver steatosis and inflammation. The hepatoprotective effect of BA could be disrupted by FXR antagonist guggulsterone (GS) in vivo and FXR siRNA in vitro.

CONCLUSION

BA alleviated alcoholic liver disease by inhibiting AIM2 inflammasome activation through an FXR-dependent mechanism. This study may potentially represent a new therapeutic approach for ALD.

Elucidating the role of liver enzymes as markers and regulators in ovarian cancer: a synergistic approach using Mendelian randomization, single-cell analysis, and clinical evidence

OBJECTIVE

To investigate the association between liver enzymes and ovarian cancer (OC), and to validate their potential as biomarkers and their mechanisms in OC. Methods Genome-wide association studies for OC and levels of enzymes such as Alkaline phosphatase (ALP), Aspartate aminotransferase (AST), Alanine aminotransferase, and gamma-glutamyltransferase were analyzed. Univariate and multivariate Mendelian randomization (MR), complemented by the Steiger test, identified enzymes with a potential causal relationship to OC. Single-cell transcriptomics from the GSE130000 dataset pinpointed pivotal cellular clusters, enabling further examination of enzyme-encoding gene expression. Transcription factors (TFs) governing these genes were predicted to construct TF-mRNA networks. Additionally, liver enzyme levels were retrospectively analyzed in healthy individuals and OC patients, alongside the evaluation of correlations with cancer antigen 125 (CA125) and Human Epididymis Protein 4 (HE4).

RESULTS

A total of 283 single nucleotide polymorphisms (SNPs) and 209 SNPs related to ALP and AST, respectively. Using the inverse-variance weighted method, univariate MR (UVMR) analysis revealed that ALP (P = 0.050, OR = 0.938) and AST (P = 0.017, OR = 0.906) were inversely associated with OC risk, suggesting their roles as protective factors. Multivariate MR (MVMR) confirmed the causal effect of ALP (P = 0.005, OR = 0.938) on OC without reverse causality. Key cellular clusters including T cells, ovarian cells, endothelial cells, macrophages, cancer-associated fibroblasts (CAFs), and epithelial cells were identified, with epithelial cells showing high expression of genes encoding AST and ALP. Notably, TFs such as TCE4 were implicated in the regulation of GOT2 and ALPL genes. OC patient samples exhibited decreased ALP levels in both blood and tumor tissues, with a negative correlation between ALP and CA125 levels observed.

CONCLUSION

This study has established a causal link between AST and ALP with OC, identifying them as protective factors. The increased expression of the genes encoding these enzymes in epithelial cells provides a theoretical basis for developing novel disease markers and targeted therapies for OC.

Protein truncating variants in mitochondrial-related nuclear genes and the risk of chronic liver disease

BACKGROUND

Mitochondrial (MT) dysfunction is a hallmark of liver diseases. However, the effects of functional variants such as protein truncating variants (PTVs) in MT-related genes on the risk of liver diseases have not been extensively explored.

METHODS

We extracted 60,928 PTVs across 2466 MT-related nucleus genes using whole-exome sequencing data obtained from 442,603 participants in the UK Biobank. We examined their associations with liver dysfunction that represented by the liver-related biomarkers and the risks of chronic liver diseases and liver-related mortality.

RESULTS

96.10% of the total participants carried at least one PTV. We identified 866 PTVs that were positively associated with liver dysfunction at the threshold of P value < 8.21e - 07. The coding genes of these PTVs were mainly enriched in pathways related to lipid, fatty acid, amino acid, and carbohydrate metabolisms. The 866 PTVs were presented in 1.07% (4721) of participants. Compared with participants who did not carry any of the PTVs, the carriers had a 5.33-fold (95% CI 4.15-6.85), 2.82-fold (1.69-4.72), and 4.41-fold (3.04-6.41) increased risk for fibrosis and cirrhosis of liver, liver cancer, and liver disease-related mortality, respectively. These adverse effects were consistent across subgroups based on age, sex, body mass index, smoking status, and presence of hypertension, diabetes, dyslipidemia, and metabolic syndrome.

CONCLUSIONS

Our findings revealed a significant impact of PTVs in MT-related genes on liver disease risk, highlighting the importance of these variants in identifying populations at risk of liver diseases and facilitating early clinical interventions.

Comparison of post-resection survival between hepatocellular carcinoma patients in BCLC stage A or B who experience tumor rupture and patients in BCLC stage C who do not

BACKGROUND AND AIM

Spontaneous rupture of hepatocellular carcinoma (HCC) is a life-threatening complication, and patients who experience it are formally assigned to stage T4 in the TNM system, while many clinicians informally assign them to stage C in the more widely used Barcelona Clinic Liver Cancer (BCLC) system. The present study explored whether these re-staging practices are appropriate for HCC patients who suffer tumor rupture.

METHODS

We retrospectively reviewed the records of 1952 HCC patients who underwent hepatic resection at our hospital between January 2017 and June 2021. We compared recurrence-free and overall survival between 143 patients who had BCLC stage A or B disease at the time of spontaneous rupture and 449 patients who had BCLC stage C disease without rupture.

RESULTS

Overall survival rate was significantly higher among the 143 patients (1, 3, 5-year survival rate was 80.3%, 60.4%, 51.4%) with rupture than among the 449 (1, 3, 5-year survival rate was 69.5%, 41.5%, 32.4%) with BCLC stage C disease (hazard ratio 1.65, 95% confidence interval 1.29 to 2.12). The two groups had similar recurrence-free survival (hazard ratio 1.19, 95% confidence interval 0.92 to 1.53), but most patients with rupture were able to receive interventional and potentially curative treatments after recurrence, whereas most patients in BCLC stage C received interventional or supportive care. Similar results were obtained after propensity score matching.

CONCLUSION

HCC patients who experience spontaneous rupture tumor while in BCLC stage A or B have better prognosis than patients in BCLC stage C without rupture. Our results suggest that HCC patients who suffer rupture in BCLC stage A or B should not be assigned to BCLC stage C.

Causal associations between liver enzymes and diabetic microvascular complications: A univariable and multivariable Mendelian randomization

BACKGROUND

Observational studies show that liver enzymes are diabetes risk factors. However, previous observational investigations on the relationship between liver enzymes and diabetic microvascular complications produced contradictory results. The purpose of this research is to examine the independent causal effects of liver enzymes on diabetic microvascular complications.

METHODS

Univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were utilized to disentangle the causal effects. The genome-wide association study (GWAS) summary-level statistics were collected from the UK biobank and the FinnGen consortium. Single nucleotide polymorphisms (SNPs) were selected as genetic instruments with genome-wide significance (p < 5 ×10-8). Five UVMR approaches, including inverse variance weighted (IVW), Bayesian weighted Mendelian randomization, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO), weighted median, and MR-Egger, and three MVMR approaches, including the extended versions of IVW, MR-Egger, and the Q-minimization methods, were performed to evaluate the causal effects. The robustness of the MR results was further confirmed using several sensitivity analyses.

RESULTS

UVMR revealed that a genetically predisposed per standard deviation increase in serum alanine aminotransferase (ALT) level increased the risk of diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) (IVW OR = 1.489, 95% CI = 1.206-1.772, p = 0.006). Likewise, serum aspartate aminotransferase (AST) levels showed similar results (IVW OR = 1.376, 95% CI = 1.115-1.638, p = 0.017). Furthermore, these effects were consistent after controlling for glycemia and blood pressure using MVMR analysis. Additionally, sensitivity analyses further strengthened the causality. However, no significant associations were found between alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), and diabetic microvascular complications.

CONCLUSIONS

Robust evidence was demonstrated for an independent causal effect of serum ALT or AST concentration on the risk of DR in T2DM. Further investigations are necessary to elucidate the potential biological mechanisms and confirm their clinical significance for early prevention and intervention.

Association between serum urea concentrations and the risk of colorectal cancer, particularly in individuals with type 2 diabetes: A cohort study

Dysregulation of the urea cycle (UC) has been detected in colorectal cancer (CRC). However, the impact of the UC's end product, urea, on CRC development remains unclear. We investigated the association between serum urea and CRC risk based on the data of 348 872 participants cancer-free at recruitment from the UK Biobank. Multivariable Cox proportional hazards models were fitted to conduct risk estimates. Stratification analyses based on sex, diet pattern, metabolic factors (including body mass index [BMI], the estimated glomerular filtration rate [eGFR] and type 2 diabetes [T2D]) and genetic profiles (the polygenic risk score [PRS] of CRC) were conducted to find potential modifiers. During an average of 9.0 years of follow-up, we identified 3408 (1.0%) CRC incident cases. Serum urea showed a nonlinear relationship with CRC risk (P-nonlinear: .035). Lower serum urea levels were associated with a higher CRC risk, with a fully-adjusted hazard ratio (HR) of 1.26 (95% confidence interval [CI]: 1.13-1.41) in the first quartile (Q1) of urea, compared to the Q4. This association was largely consistent across subgroups of sex, protein diet, BMI, eGFR and CRC-PRSs (P-interaction >.05); however, it was stronger in the T2D, with an interaction between urea and T2D on both additive (synergy index: 3.32, [95% CI: 1.24-8.88]) and multiplicative scales (P-interaction: .019). Lower serum urea concentrations were associated with an increased risk of CRC, with a more pronounced effect observed in individuals with T2D. Maintaining stable levels of serum urea has important implications for CRC prevention, particularly in individuals with T2D.

Identification of genetic profile and biomarkers involved in acute respiratory distress syndrome

PURPOSE

The purpose of this study was to profile genetic causal factors of acute respiratory distress syndrome (ARDS) and early predict patients at high ARDS risk.

METHODS

We performed a phenome-wide Mendelian Randomization analysis through summary statistics of an ARDS genome-wide association study (1250 cases and 1583 controls of European ancestry) and 33,150 traits. Transcriptomic data from human blood and lung tissues of a preclinical mouse model were used to validate biomarkers, which were further used to construct a prediction model and nomogram.

RESULTS

A total of 1736 traits, including 1223 blood RNA, 159 plasma proteins, and 354 non-gene phenotypes (classified by Biochemistry, Anthropometry, Disease, Nutrition and Habit, Immunology, and Treatment), exhibited a potentially causal relationship with ARDS development, which were accessible through a user-friendly interface platform called CARDS (Causal traits for Acute Respiratory Distress Syndrome). Regarding candidate blood RNA, four genes were validated, namely TMEM176B, SLC2A5, CDC45, and VSIG8, showing differential expression in blood of ARDS patients compared to controls, as well as dynamic expression in mouse lung tissues. Importantly, the addition of four blood genes and five immune cell proportions significantly improved the prediction performance of ARDS development, with 0.791 of the area under the curve from receiver-operator characteristic, compared to 0.725 for the basic model consisting of Acute Physiology and Chronic Health Evaluation (APACHE) III Score, sex, body mass index, bacteremia, and sepsis. A model-based nomogram was also developed for the clinical practice.

CONCLUSION

This study identifies a wide range of ARDS relevant factors and develops a promising prediction model, enhancing early clinical management and intervention for ARDS development.

Metabolic crosstalk between skeletal muscle cells and liver through IRF4-FSTL1 in nonalcoholic steatohepatitis

Inter-organ crosstalk has gained increasing attention in recent times; however, the underlying mechanisms remain unclear. In this study, we elucidate an endocrine pathway that is regulated by skeletal muscle interferon regulatory factor (IRF) 4, which manipulates liver pathology. Skeletal muscle specific IRF4 knockout (F4MKO) mice exhibited ameliorated hepatic steatosis, inflammation, and fibrosis, without changes in body weight, when put on a nonalcoholic steatohepatitis (NASH) diet. Proteomics analysis results suggested that follistatin-like protein 1 (FSTL1) may constitute a link between muscles and the liver. Dual luciferase assays showed that IRF4 can transcriptionally regulate FSTL1. Further, inducing FSTL1 expression in the muscles of F4MKO mice is sufficient to restore liver pathology. In addition, co-culture experiments confirmed that FSTL1 plays a distinct role in various liver cell types via different receptors. Finally, we observed that the serum FSTL1 level is positively correlated with NASH progression in humans. These data indicate a signaling pathway involving IRF4-FSTL1-DIP2A/CD14, that links skeletal muscle cells to the liver in the pathogenesis of NASH.

Accumulation of Linoleic Acid by Altered Peroxisome Proliferator-Activated Receptor-α Signaling Is Associated with Age-Dependent Hepatocarcinogenesis in Ppara Transgenic Mice

Long-term ligand activation of PPARα in mice causes hepatocarcinogenesis through a mechanism that requires functional PPARα. However, hepatocarcinogenesis is diminished in both Ppara-null and PPARA-humanized mice, yet both lines develop age-related liver cancer independently of treatment with a PPARα agonist. Since PPARα is a master regulator of liver lipid metabolism in the liver, lipidomic analyses were carried out in wild-type, Ppara-null, and PPARA-humanized mice treated with and without the potent agonist GW7647. The levels of hepatic linoleic acid in Ppara-null and PPARA-humanized mice were markedly higher compared to wild-type controls, along with overall fatty liver. The number of liver CD4+ T cells was also lower in Ppara-null and PPARA-humanized mice and was negatively correlated with the elevated linoleic acid. Moreover, more senescent hepatocytes and lower serum TNFα and IFNγ levels were observed in Ppara-null and PPARA-humanized mice with age. These studies suggest a new role for PPARα in age-associated hepatocarcinogenesis due to altered lipid metabolism in Ppara-null and PPARA-humanized mice and the accumulation of linoleic acid as part of an overall fatty liver that is associated with loss of CD4+ T cells in the liver in both transgenic models. Since fatty liver is a known causal risk factor for liver cancer, Ppara-null and PPARA-humanized mice are valuable models for examining the mechanisms of PPARα and age-dependent hepatocarcinogenesis.

Unsupervised Machine Learning of MRI Radiomics Features Identifies Two Distinct Subgroups with Different Liver Function Reserve and Risks of Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma

OBJECTIVE

To identify subgroups of patients with hepatocellular carcinoma (HCC) with different liver function reserves using an unsupervised machine-learning approach on the radiomics features from preoperative gadoxetic-acid-enhanced MRIs and to evaluate their association with the risk of post-hepatectomy liver failure (PHLF).

METHODS

Clinical data from 276 consecutive HCC patients who underwent liver resections between January 2017 and March 2019 were retrospectively collected. Radiomics features were extracted from the non-tumorous liver tissue at the gadoxetic-acid-enhanced hepatobiliary phase MRI. The reproducible and non-redundant features were selected for consensus clustering analysis to detect distinct subgroups. After that, clinical variables were compared between the identified subgroups to evaluate the clustering efficacy. The liver function reserve of the subgroups was compared and the correlations between the subgroups and PHLF, postoperative complications, and length of hospital stay were evaluated.

RESULTS

A total of 107 radiomics features were extracted and 37 were selected for unsupervised clustering analysis, which identified two distinct subgroups (138 patients in each subgroup). Compared with subgroup 1, subgroup 2 had significantly more patients with older age, albumin-bilirubin grades 2 and 3, a higher indocyanine green retention rate, and a lower indocyanine green plasma disappearance rate (all p < 0.05). Subgroup 2 was also associated with a higher risk of PHLF, postoperative complications, and longer hospital stays (>18 days) than that of subgroup 1, with an odds ratio of 2.83 (95% CI: 1.58-5.23), 2.41(95% CI: 1.15-5.35), and 2.14 (95% CI: 1.32-3.47), respectively. The odds ratio of our method was similar to the albumin-bilirubin grade for postoperative complications and length of hospital stay (2.41 vs. 2.29 and 2.14 vs. 2.16, respectively), but was inferior for PHLF (2.83 vs. 4.55).

CONCLUSIONS

Based on the radiomics features of gadoxetic-acid-enhanced MRI, unsupervised clustering analysis identified two distinct subgroups with different liver function reserves and risks of PHLF in HCC patients. Future studies are required to validate our findings.

Phenomic Studies on Diseases: Potential and Challenges

The rapid development of such research field as multi-omics and artificial intelligence (AI) has made it possible to acquire and analyze the multi-dimensional big data of human phenomes. Increasing evidence has indicated that phenomics can provide a revolutionary strategy and approach for discovering new risk factors, diagnostic biomarkers and precision therapies of diseases, which holds profound advantages over conventional approaches for realizing precision medicine: first, the big data of patients' phenomes can provide remarkably richer information than that of the genomes; second, phenomic studies on diseases may expose the correlations among cross-scale and multi-dimensional phenomic parameters as well as the mechanisms underlying the correlations; and third, phenomics-based studies are big data-driven studies, which can significantly enhance the possibility and efficiency for generating novel discoveries. However, phenomic studies on human diseases are still in early developmental stage, which are facing multiple major challenges and tasks: first, there is significant deficiency in analytical and modeling approaches for analyzing the multi-dimensional data of human phenomes; second, it is crucial to establish universal standards for acquirement and management of phenomic data of patients; third, new methods and devices for acquirement of phenomic data of patients under clinical settings should be developed; fourth, it is of significance to establish the regulatory and ethical guidelines for phenomic studies on diseases; and fifth, it is important to develop effective international cooperation. It is expected that phenomic studies on diseases would profoundly and comprehensively enhance our capacity in prevention, diagnosis and treatment of diseases.