Observational and genetic association of non-alcoholic fatty liver disease and calcific aortic valve disease.

Background: Non-alcoholic fatty liver disease (NAFLD) has emerged as a predominant driver of chronic liver disease globally and is associated with increased cardiovascular disease morbidity and mortality. However, the association between NAFLD and calcific aortic valve disease remains unclear. We aimed to prospectively investigate the association between NAFLD and incident aortic valve calcification (AVC), as well as its genetic relationship with incident calcific aortic valve stenosis (CAVS). Methods: A post hoc analysis was conducted on 4226 participants from the Multi-Ethnic Study of Atherosclerosis (MESA) database. We employed the adjusted Cox models to assess the observational association between NAFLD and incident AVC. Additionally, we conducted two-sample Mendelian randomization (MR) analyses to investigate the genetic association between genetically predicted NAFLD and calcific aortic valve stenosis (CAVS), a severe form of CAVD. We repeated the MR analyses by excluding NAFLD susceptibility genes linked to impaired very low-density lipoprotein (VLDL) secretion. Results: After adjustment for potential risk factors, participants with NAFLD had a hazard ratio of 1.58 (95% CI: 1.03-2.43) for incident AVC compared to those without NAFLD. After excluding genes associated with impaired VLDL secretion, the MR analyses consistently showed the significant associations between genetically predicted NAFLD and CAVS for 3 traits: chronic elevation of alanine aminotransferase (odds ratio = 1.13 [95% CI: 1.01-1.25]), imaging-based NAFLD (odds ratio = 2.81 [95% CI: 1.66-4.76]), and biopsy-confirmed NAFLD (odds ratio = 1.12 [95% CI: 1.01-1.24]). However, the association became non-significant when considering all NAFLD susceptibility genes. Conclusions: NAFLD was independently associated with an elevated risk of incident AVC. Genetically predicted NAFLD was also associated with CAVS after excluding genetic variants related to impaired VLDL secretion.

Genetic insights into serum cathepsins as diagnostic and therapeutic targets in knee and hip osteoarthritis.

Osteoarthritis (OA) is a chronic disease due to the deterioration of cartilage structure and function, involving the progressive degradation of the cartilage extracellular matrix. Cathepsins, lysosomal cysteine proteases, play pivotal roles in various biological and pathological processes, particularly in protein degradation. Excess cathepsins levels are reported to contribute to the development of OA. However, the causal relationship between the cathepsin family and knee and hip OA remains uncertain. Therefore, this study utilized bidirectional Mendelian Randomization (MR) analyses to explore this causal association. Our results indicated that elevated serum levels of cathepsin O increase the overall risk of knee OA, while increased serum levels of cathepsin H enhance the risk of hip OA. Conversely, the reverse MR analyses did not reveal a reverse causal relationship between them. In summary, OA in different anatomical locations may genetically result from pathological elevations in different serum cathepsin isoforms, which could be utilized as diagnostic and therapeutic targets in clinical practice.

Muscle-origin creatinine-cystatin C ratio is an osteoporosis marker in individuals with normal renal function: evidence from observational and Mendelian randomization analysis.

Background: Creatinine-cystatin C ratio (CCR) has been demonstrated as an objective marker of sarcopenia in clinical conditions but has not been evaluated as an osteoporosis marker in individuals with normal renal function. Methods: We selected 271,831 participants with normal renal function from UK Biobank cohort. Multivariable linear/logistic regression and Cox proportional hazards model were used to investigate the phenotypic relationship between CCR and osteoporosis in total subjects and gender-stratified subjects. Based on the genome-wide association study (GWAS) data, linkage disequilibrium regression (LDSC) and Mendelian randomization (MR) analysis were performed to reveal the shared genetic correlations and infer the causal effects, respectively. Results: Amongst total subjects and gender-stratified subjects, serum CCR was positively associated with eBMD after adjusting for potential risk factors (all P<0.05). The multivariable logistic regression model showed that the decrease in CCR was associated with a higher risk of osteoporosis/fracture in all models (all P<0.05). In the multivariable Cox regression analysis with adjustment for potential confounders, reduced CCR is associated with the incidence of osteoporosis and fracture in both total subjects and gender-stratified subjects (all P<0.05). A significant non-linear dose-response was observed between CCR and osteoporosis/fracture risk (P non-linearity < 0.05). LDSC found no significant shared genetic effects by them, but PLACO identified 42 pleiotropic SNPs shared by CCR and fracture (P<5×10-8). MR analyses indicated the causal effect from CCR to osteoporosis/fracture. Conclusions: Reduced CCR predicted increased risks of osteoporosis/fracture, and significant causal effects support their associations. These findings indicated that the muscle-origin serum CCR was a potential biomarker to assess the risks of osteoporosis and fracture.

Deciphering the complex relationship between type 2 diabetes and fracture risk with both genetic and observational evidence.

The 'diabetic bone paradox' suggested that type 2 diabetes (T2D) patients would have higher areal bone mineral density (BMD) but higher fracture risk than individuals without T2D. In this study, we found that the genetically predicted T2D was associated with higher BMD and lower risk of fracture in both weighted genetic risk score (wGRS) and two-sample Mendelian randomization (MR) analyses. We also identified ten genomic loci shared between T2D and fracture, with the top signal at SNP rs4580892 in the intron of gene RSPO3. And the higher expression in adipose subcutaneous and higher protein level in plasma of RSPO3 were associated with increased risk of T2D, but decreased risk of fracture. In the prospective study, T2D was observed to be associated with higher risk of fracture, but BMI mediated 30.2% of the protective effect. However, when stratified by the T2D-related risk factors for fracture, we observed that the effect of T2D on the risk of fracture decreased when the number of T2D-related risk factors decreased, and the association became non-significant if the T2D patients carried none of the risk factors. In conclusion, the genetically determined T2D might not be associated with higher risk of fracture. And the shared genetic architecture between T2D and fracture suggested a top signal around RSPO3 gene. The observed effect size of T2D on fracture risk decreased if the T2D-related risk factors could be eliminated. Therefore, it is important to manage the complications of T2D to prevent the risk of fracture.

Genetically predicted mood swings increased risk of cardiovascular disease: Evidence from a Mendelian randomization analysis.

BACKGROUND: Mood swings is linked to a higher risk of cardiovascular diseases (CVDs). However, the causal relationships between them remain unknown. METHODS: We conducted this Mendelian randomization (MR) analysis to evaluate the causal associations between mood swings (n = 373,733) and 5 CVDs, including CAD, MI, HF, AF, and stroke using summary data of large-scale genome-wide association studies (GWAS). FinnGen datasets validated the results. Various MR approaches, sensitivity analyses, multivariable MR (MVMR), and two-step MR mediation analyses were applied. RESULTS: The MR analysis revealed significant causal effects of mood swings on CAD (OR = 1.45, 95 % CI 1.24-1.71; P = 5.52e-6), MI (OR = 1.60, 95 % CI 1.32-1.95; P = 1.77e-6), HF (OR = 1.42, 95 % CI 1.18-1.71; P = 2.32e-4), and stroke (OR = 1.48, 95 % CI 1.19-1.83; P = 3.46e-4), excluding AF (P = 0.16). In the reverse MR analysis, no causal relationships were observed. The results were reproducible using FinnGen data. In the MVMR analysis, the causal effects of mood swings on CAD, MI, HF and stroke still remain significant after adjusting potential confounding factors including BMI, smoking and T2DM, but not for LDL and hypertension. Further mediation analysis indicated hypertension may mediate the causal pathways from mood swings to CAD (18.11 %, 95 % CI: 8.83 %-27.39 %), MI (16.40 %, 95 % CI: 7.93 %-24.87 %), HF (13.06 %, 95 % CI: 6.25 %-19.86 %), and stroke (18.04 %, 95 % CI: 8.73 %-27.34 %). CONCLUSION: Mood swings has a significant causal impact on the development of CAD, MI, HF, and stroke, partly mediated by hypertension.

Gut microbiota associated with appetite suppression in high-temperature and high-humidity environments.

BACKGROUND: Food is crucial for maintaining vital human and animal activities. Disorders in appetite control can lead to various metabolic disturbances. Alterations in the gut microbial composition can affect appetite and energy metabolism. While alterations in the gut microbiota have been observed in high-temperature and high-humidity (HTH) environments, the relationship between the gut microbiota during HTH and appetite remains unclear. METHODS: We utilised an artificial climate box to mimic HTH environments, and established a faecal bacteria transplantation (FMT) mouse model. Mendelian randomisation (MR) analysis was used to further confirm the causal relationship between gut microbiota and appetite or appetite-related hormones. FINDINGS: We found that, in the eighth week of exposure to HTH environments, mice showed a decrease in food intake and body weight, and there were significant changes in the intestinal microbiota compared to the control group. After FMT, we observed similar changes in food intake, body weight, and gut bacteria. Appetite-related hormones, including ghrelin, glucagon-like peptide-1, and insulin, were reduced in DH (mice exposed to HTH conditions) and DHF (FMT from mice exposed to HTH environments for 8 weeks), while the level of peptide YY initially increased and then decreased in DH and increased after FMT. Moreover, MR analysis further confirmed that these changes in the intestinal microbiota could affect appetite or appetite-related hormones. INTERPRETATION: Together, our data suggest that the gut microbiota is closely associated with appetite suppression in HTH. These findings provide novel insights into the effects of HTH on appetite. FUNDING: This work was supported by the National Natural Science Foundation of China and Guangzhou University of Chinese Medicine.

Genetically predicted triglycerides mediate the relationship between type 2 diabetes Mellitus and intervertebral disc degeneration.

BACKGROUND: To validate the causal relationship between type 2 diabetes mellitus (T2DM) and intervertebral disc degeneration (IVDD) and to identify and quantify the role of triglycerides (TGs) as potential mediators. METHODS: A two-sample Mendelian randomization (MR) analyses of T2DM (61,714 cases and 1178 controls) and IVDD (20,001 cases and 164,682 controls) was performed using genome-wide association studies (GWAS). Moreover, two-step MR was employed to quantify the proportionate impact of TG-mediated T2DM on IVDD. RESULTS: MR analysis showed that T2DM increased IVDD risk (OR: 1.0466, 95% CI 1.0049-1.0899, P = 0.0278). Reverse MR analyses demonstrated that IVDD does not affect T2DM risk (P = 0.1393). The proportion of T2DM mediated through TG was 11.4% (95% CI 5.5%-17.4%). CONCLUSION: This work further validates the causality between T2DM and IVDD, with a part of the effect mediated by TG, but the greatest impacts of T2DM on IVDD remain unknown. Further studies are needed to identify other potential mediators.

Mendelian randomization analysis identified tumor necrosis factor as being associated with severe COVID-19.

Background: Observational studies have shown that anti-tumor necrosis factor (TNF) therapy may be beneficial for patients with coronavirus disease 2019 (COVID-19). Nevertheless, because of the methodological restrictions of traditional observational studies, it is a challenge to make causal inferences. This study involved a two-sample Mendelian randomization analysis to investigate the causal link between nine TNFs and COVID-19 severity using publicly released genome-wide association study summary statistics. Methods: Summary statistics for nine TNFs (21,758 cases) were obtained from a large-scale genome-wide association study. Correlation data between single-nucleotide polymorphisms and severe COVID-19 (18,152 cases vs. 1,145,546 controls) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by inverse variance-weighted (IVW), MR-Egger, and weighted median methods. Sensitivity tests were conducted to assess the validity of the causal relationship. Results: Genetically predicted TNF receptor superfamily member 6 (FAS) positively correlated with the severity of COVID-19 (IVW, odds ratio = 1.10, 95% confidence interval = 1.01-1.19, p = 0.026), whereas TNF receptor superfamily member 5 (CD40) was protective against severe COVID-19 (IVW, odds ratio = 0.92, 95% confidence interval = 0.87-0.97, p = 0.002). Conclusion: Genetic evidence from this study supports that the increased expression of FAS is associated with the risk of severe COVID-19 and that CD40 may have a potential protective effect against COVID-19.

Major depression disorder may causally associate with the increased atrial fibrillation risk: evidence from two-sample mendelian randomization analyses.

BACKGROUND: Observational studies have revealed a link between major depressive disorder (MDD) and a higher chance of developing atrial fibrillation (AF). It is still uncertain whether or not this correlation indicates a causal relationship. This research set out to evaluate the causal impact of MDD on AF. METHODS: To evaluate the causal relationship between MDD and AF, we employed a two-sample Mendelian randomization (MR) method. A new genome-wide association study (GWAS) with 500,199 participants was used to obtain an overview of the association of genetic variations with MDD. An additional GWAS incorporating 1,030,836 people provided data on the relationship between gene variants and AF. The inverse-variance weighted technique was utilized to assess the effect sizes. Sensitivity analysis included the use of other statistical approaches such as weighted median, Outlier, MR Pleiotropy Residual Sum, weighted mode, simple mode, and MR - Egger. RESULTS: By employing 47 single nucleotide polymorphisms (SNPs) as markers, MR analyses in random-effect inverse-variance weighted models found that genetically projected MDD was linked to an elevated incidence of AF (odds ratio [OR] = 1.098, 95% CI 1.000-1.206; P = 0.049). No gene pleiotropy was discovered as indicated by MR-Egger (intercept= -0.011, P = 0.169). Sensitivity analysis employing other MR techniques yielded reliable results. CONCLUSION: This MR study established a causal relationship between genetically predicted MDD and an elevated risk of AF.

Genetic predisposition to subjective well-being, depression, and suicide in relation to COVID-19 susceptibility and severity.

BACKGROUND: Epidemiological studies have reported associations between subjective well-being (SWB), depression, and suicide with COVID-19 illness, but the causality has not been established. We performed a two-sample Mendelian randomization (MR) analysis to investigate the causal link between SWB, depression, suicide and COVID-19 susceptibility and severity. METHODS: Summary statistics for SWB (298,420 cases), depression (113,769 cases) and suicide (52,208 cases) were obtained from three large-scale GWAS. Data on the associations between the Single Nucleotide Polymorphisms (SNPs) and COVID-19 (159,840 cases), hospitalized COVID-19 (44,986 cases), and severe COVID-19 (18,152 cases) were collected from the COVID-19 host genetics initiative. The causal estimate was calculated by the Inverse Variance Weighted, MR Egger and Weighted Median methods. Sensitivity tests were used to evaluate the validity of the causal relationship. RESULTS: Our results showed that genetically predicted SWB (OR = 0.98, 95 % CI: 0.86-1.10, P = 0.69), depression (OR = 0.76, 95 % CI: 0.54-1.06, P = 0.11), and suicide (OR = 0.99, 95 % CI: 0.96-1.02, P = 0.56) were not causally related to COVID-19 susceptibility. Similarly, we did not find a potential causal relationship between SWB, depression, suicide and COVID-19 severity. CONCLUSIONS: This indicated that positive or negative emotions would not make COVID-19 better or worse, and strategies that attempted to use positive emotions to improve COVID-19 symptoms may be useless. Improving knowledge about the SARS-CoV-2 and timely medical intervention to reduce panic during a pandemic is one of the effective measures to deal with the current decrease in well-being and increase in depression and suicide rates.

Causal Effects of Genetically Predicted Iron Status on Sepsis: A Two-Sample Bidirectional Mendelian Randomization Study.

Background/Aim: Several observational studies showed a significant association between elevated iron status biomarkers levels and sepsis with the unclear direction of causality. A two-sample bidirectional mendelian randomization (MR) study was designed to identify the causal direction between seven iron status traits and sepsis. Methods: Seven iron status traits were studied, including serum iron, ferritin, transferrin saturation, transferrin, hemoglobin, erythrocyte count, and reticulocyte count. MR analysis was first performed to estimate the causal effect of iron status on the risk of sepsis and then performed in the opposite direction. The multiplicative random-effects and fixed-effects inverse-variance weighted, weighted median-based method and MR-Egger were applied. MR-Egger regression, MR pleiotropy residual sum and outlier (MR-PRESSO), and Cochran's Q statistic methods were used to assess heterogeneity and pleiotropy. Results: Genetically predicted high levels of serum iron (OR = 1.21, 95%CI = 1.13-1.29, p = 3.16 × 10-4), ferritin (OR = 1.32, 95%CI = 1.07-1.62, p =0.009) and transferrin saturation (OR = 1.14, 95%CI = 1.06-1.23, p = 5.43 × 10-4) were associated with an increased risk of sepsis. No significant causal relationships between sepsis and other four iron status biomarkers were observed. Conclusions: This present bidirectional MR analysis suggested the causal association of the high iron status with sepsis susceptibility, while the reverse causality hypothesis did not hold. The levels of transferrin, hemoglobin, erythrocytes, and reticulocytes were not significantly associated with sepsis. Further studies will be required to confirm the potential clinical value of such a prevention and treatment strategy.

Association between Lipid Levels and Risk for Different Types of Aneurysms: A Mendelian Randomization Study.

BACKGROUND: Although the associations between serum lipid levels and aneurysms have been investigated in epidemiological studies, causality remains unknown. Thus, this study aimed to investigate the causal relationships of serum high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglyceride (TG) levels on five types of aneurysms, using genetic variants associated with four lipid traits as instrumental variables in a Mendelian randomization (MR) analysis. METHODS: We performed two-sample Mendelian randomization (MR) analyses to evaluate the associations of HDL-C, LDL-C, TC, and TG levels with risks for five types of aneurysms and those of LDL-C- (HMGCR, NPC1L1, PCSK9, CETP, and LDLR) and TG-lowering targets (ANGPTL3 and LPL) with aneurysms. RESULTS: The sample sizes of the included studies ranged from nearly 80,000 to 410,000. We found inverse associations between genetically predicted HDL-C levels and aortic (OR = 0.74, 95% CI = 0.65-0.85) and abdominal aortic aneurysms (0.58, 0.45-0.75). A 1-SD increase in LDL-C and TC levels was associated with increased risks for aortic (1.41, 1.26-1.58 and 1.36, 1.18-1.56, respectively) and abdominal aortic aneurysms (1.82, 1.48-2.22 and 1.55, 1.25-1.93, respectively). TG levels were significantly associated with aortic (1.36, 1.18-1.56) and lower extremity artery aneurysms (2.76, 1.48-5.14), but limited to cerebral aneurysm (1.23, 1.06-1.42). Secondary analyses revealed a relationship between genetically proxied LDL-C-lowering targets and all types of aneurysms; however, the drug targets remained heterogeneous. We found a weak association between TG-lowering therapies and aortic (ANGPTL3, 0.51, 0.29-0.89) and abdominal aortic aneurysms (LPL, 0.64, 0.44-0.94). CONCLUSION: According to genetic evidence, lipid dysfunction is a causal risk factor for aneurysms. Lipid-lowering drugs may be a potential effective strategy in preventing and managing aneurysms.

Meta-Analyses of Splicing and Expression Quantitative Trait Loci Identified Susceptibility Genes of Glioma.

BACKGROUND: The functions of most glioma risk alleles are unknown. Very few studies had evaluated expression quantitative trait loci (eQTL), and insights of susceptibility genes were limited due to scarcity of available brain tissues. Moreover, no prior study had examined the effect of glioma risk alleles on alternative RNA splicing. OBJECTIVE: This study explored splicing quantitative trait loci (sQTL) as molecular QTL and improved the power of QTL mapping through meta-analyses of both cis eQTL and sQTL. METHODS: We first evaluated eQTLs and sQTLs of the CommonMind Consortium (CMC) and Genotype-Tissue Expression Project (GTEx) using genotyping, or whole-genome sequencing and RNA-seq data. Alternative splicing events were characterized using an annotation-free method that detected intron excision events. Then, we conducted meta-analyses by pooling the eQTL and sQTL results of CMC and GTEx using the inverse variance-weighted model. Afterward, we integrated QTL meta-analysis results (Q < 0.05) with the Glioma International Case Control Study (GICC) GWAS meta-analysis (case:12,496, control:18,190), using a summary statistics-based mendelian randomization (SMR) method. RESULTS: Between CMC and GTEx, we combined the QTL data of 354 unique individuals of European ancestry. SMR analyses revealed 15 eQTLs in 11 loci and 32 sQTLs in 9 loci relevant to glioma risk. Two loci only harbored sQTLs (1q44 and 16p13.3). In seven loci, both eQTL and sQTL coexisted (2q33.3, 7p11.2, 11q23.3 15q24.2, 16p12.1, 20q13.33, and 22q13.1), but the target genes were different for five of these seven loci. Three eQTL loci (9p21.3, 20q13.33, and 22q13.1) and 4 sQTL loci (11q23.3, 16p13.3, 16q12.1, and 20q13.33) harbored multiple target genes. Eight target genes of sQTLs (C2orf80, SEC61G, TMEM25, PHLDB1, RP11-161M6.2, HEATR3, RTEL1-TNFRSF6B, and LIME1) had multiple alternatively spliced transcripts. CONCLUSION: Our study revealed that the regulation of transcriptome by glioma risk alleles is complex, with the potential for eQTL and sQTL jointly affecting gliomagenesis in risk loci. QTLs of many loci involved multiple target genes, some of which were specific to alternative splicing. Therefore, quantitative trait loci that evaluate only total gene expression will miss many important target genes.

The interplay between host genetics and the gut microbiome reveals common and distinct microbiome features for complex human diseases.

BACKGROUND: Interest in the interplay between host genetics and the gut microbiome in complex human diseases is increasing, with prior evidence mainly being derived from animal models. In addition, the shared and distinct microbiome features among complex human diseases remain largely unclear. RESULTS: This analysis was based on a Chinese population with 1475 participants. We estimated the SNP-based heritability, which suggested that Desulfovibrionaceae and Odoribacter had significant heritability estimates (0.456 and 0.476, respectively). We performed a microbiome genome-wide association study to identify host genetic variants associated with the gut microbiome. We then conducted bidirectional Mendelian randomization analyses to examine the potential causal associations between the gut microbiome and complex human diseases. We found that Saccharibacteria could potentially decrease the concentration of serum creatinine and increase the estimated glomerular filtration rate. On the other hand, atrial fibrillation, chronic kidney disease and prostate cancer, as predicted by host genetics, had potential causal effects on the abundance of some specific gut microbiota. For example, atrial fibrillation increased the abundance of Burkholderiales and Alcaligenaceae and decreased the abundance of Lachnobacterium, Bacteroides coprophilus, Barnesiellaceae, an undefined genus in the family Veillonellaceae and Mitsuokella. Further disease-microbiome feature analysis suggested that systemic lupus erythematosus and chronic myeloid leukaemia shared common gut microbiome features. CONCLUSIONS: These results suggest that different complex human diseases share common and distinct gut microbiome features, which may help reshape our understanding of disease aetiology in humans. Video Abstract.