CELSR2 deficiency suppresses lipid accumulation in hepatocyte by impairing the UPR and elevating ROS level

Proteome-wide Mendelian randomization provides novel insights into the pathogenesis and druggable targets of osteoporosis

Background

With the aging population, the prevalence and impact of osteoporosis are expected to rise, and existing anti-osteoporosis agents have limitations due to adverse events. This study aims to discover novel drug targets for osteoporosis.

Methods

The protein data were obtained from the latest proteome-wide association studies (PWAS) including 54, 219 participants. The osteoporosis data were extracted from a GWAS meta-analysis, characterized by heel bone mineral density (HBMD) comprising 426,824 individuals. Mendelian randomization (MR) was the primary approach used to establish genetic causality between specific traits. Summary-data-based MR (SMR), colocalization analysis, heterogeneity test, and external validation were applied to ensure the findings were reliable. The underlying mechanisms behind these causal associations were investigated by additional analyses. Finally, the druggability of the identified proteins was assessed.

Results

After Bonferroni correction, a total of 84 proteins were found to have a genetic association with osteoporosis. With strong colocalization evidence, proteins such as ACHE, HS6ST1, LRIG1, and LRRC37A2 were found to negatively influence HBMD, whereas CELSR2, CPE, FN1, FOXO1, and FSHB exhibited a positive association with HBMD. No significant heterogeneity was found. Additionally, CELSR2, FN1, FSHB, HS6ST1, LRIG1, and LRRC37A2 were replicated in the external validation. The effect of FSHB on HBMD was more pronounced in females compared to males. Interestingly, ACHE, LRIG1, FN1, and FOXO1 were observed to partially act on HBMD through BMI. Phewas analysis indicated that CPE and FOXO1 did not have genetic associations with any phenotypes other than osteoporosis. FN1 was highlighted as the most significant protein by protein-protein interaction network analysis.

Conclusion

In conclusion, this study offers valuable insights into the role of specific proteins in the development of osteoporosis, and underscores potential therapeutic targets. Future studies should emphasize exploring these causal relationships and elucidating their underlying mechanisms.

SCAMPI: A scalable statistical framework for genome-wide interaction testing harnessing cross-trait correlations

Family-based heritability estimates of complex traits are often considerably larger than their single-nucleotide polymorphism (SNP) heritability estimates. This discrepancy may be due to non-additive effects of genetic variation, including variation that interacts with other genes or environmental factors to influence the trait. Variance-based procedures provide a computationally efficient strategy to screen for SNPs with potential interaction effects without requiring the specification of the interacting variable. While valuable, such variance-based tests consider only a single trait and ignore likely pleiotropy among related traits that, if present, could improve power to detect such interaction effects. To fill this gap, we propose SCAMPI (Scalable Cauchy Aggregate test using Multiple Phenotypes to test Interactions), which screens for variants with interaction effects across multiple traits. SCAMPI is motivated by the observation that SNPs with pleiotropic interaction effects induce genotypic differences in the patterns of correlation among traits. By studying such patterns across genotype categories among multiple traits, we show that SCAMPI has improved performance over traditional univariate variance-based methods. Like those traditional variance-based tests, SCAMPI permits the screening of interaction effects without requiring the specification of the interaction variable and is further computationally scalable to biobank data. We employed SCAMPI to screen for interacting SNPs associated with four lipid-related traits in the UK Biobank and identified multiple gene regions missed by existing univariate variance-based tests. SCAMPI is implemented in software for public use.

Pleiotropic effects of an eQTL in the CELSR2/PSRC1/SORT1 cluster that associates with LDL-C and resting metabolic rate

CONTEXT

The locus CELSR2-PSRC1-SORT1, a primary genetic signal for lipids, has recently been implicated in different metabolic processes. Our investigation identified its association with energy metabolism.

OBJECTIVE

To determine biological mechanisms that govern diverse functions of this locus.

METHODS

Genotypes for 491,265 variants in 7,000 clinically characterized American Indians were previously determined using a custom-designed array specific for this longitudinally studied American Indian population. Among the genotyped individuals, 5,205 had measures of fasting lipid levels and 509 had measures of resting metabolic rate (RMR) and substrate oxidation rate assessed through indirect calorimetry. A genome-wide association study (GWAS) for LDL-C levels identified a variant in CELSR2 and the molecular impact of this variant on gene expression was assessed in skeletal muscle biopsies from 207 participants, followed by functional validation in mouse myoblasts using a luciferase assay.

RESULTS

A GWAS in American Indians identified rs12740374 in CELSR2 as the top signal for LDL-C levels (P = 1 × 10-22); further analysis of this variant identified an unexpected correlation with reduced RMR (effect = -44.3 kcal/day/minor-allele) and carbohydrate oxidation rate (effect = -5.21 mg/hour/kg-EMBS). Tagged variants showed a distinct linkage disequilibrium architecture in American Indians, highlighting a potential functional variant, rs6670347 (minor-allele frequency = 0.20). Positioned in the glucocorticoid receptor's core binding motif, rs6670347 is part of a skeletal muscle-specific enhancer. Human skeletal muscle transcriptome analysis showed CELSR2 as the most differentially expressed gene (P = 1.9 × 10-7), with the RMR-lowering minor allele elevating gene expression. Experiments in mouse myoblasts confirmed enhancer-based regulation of CELSR2 expression, dependent on glucocorticoids. Rs6670347 also associated with increased oxidative phosphorylation gene expression; CELSR2 as a regulator of these genes, suggests potential influence on energy metabolism through muscle oxidative capacity.

CONCLUSION

Variants in the CELSR2/PSRC1/SORT1 locus exhibit tissue-specific effects on metabolic traits, with an independent role in muscle metabolism through glucocorticoid signaling.

Novel ancestry-specific primary open-angle glaucoma loci and shared biology with vascular mechanisms and cell proliferation

Primary open-angle glaucoma (POAG), a leading cause of irreversible blindness globally, shows disparity in prevalence and manifestations across ancestries. We perform meta-analysis across 15 biobanks (of the Global Biobank Meta-analysis Initiative) (n = 1,487,441: cases = 26,848) and merge with previous multi-ancestry studies, with the combined dataset representing the largest and most diverse POAG study to date (n = 1,478,037: cases = 46,325) and identify 17 novel significant loci, 5 of which were ancestry specific. Gene-enrichment and transcriptome-wide association analyses implicate vascular and cancer genes, a fifth of which are primary ciliary related. We perform an extensive statistical analysis of SIX6 and CDKN2B-AS1 loci in human GTEx data and across large electronic health records showing interaction between SIX6 gene and causal variants in the chr9p21.3 locus, with expression effect on CDKN2A/B. Our results suggest that some POAG risk variants may be ancestry specific, sex specific, or both, and support the contribution of genes involved in programmed cell death in POAG pathogenesis.

Bidirectional causal relationship between hypercholesterolemia and ischemic heart disease: a Mendelian randomization study

Background

Ischemic Heart Disease (IHD) is a leading cause of morbidity and mortality worldwide. Hypercholesterolaemia, a metabolic syndrome distinguished by elevated cholesterol levels, is positively correlated with IHD, yet the precise causal relationship between these two health conditions remains to be clearly defined.

Methods

We conducted a two-sample MR analysis using genetic variants associated with hypercholesterolemia and IHD. Various statistical techniques including MR-Egger, Weighted Median, Inverse Variance Weighted (IVW), Simple Mode, and Weighted Mode were employed. We also performed sensitivity analyses to assess pleiotropy, heterogeneity, and influence of individual SNPs. Furthermore, genetic co-localization analysis was performed to identify shared genes between hypercholesterolemia and IHD.

Results

Our MR study illuminated a bidirectional causal relationship between hypercholesterolaemia and ischaemic heart disease. Utilising the IVW with multiplicative random effects, upon considering IHD as the outcome, we identified an OR of 2.27 (95% CI: 1.91-2.70, p = 1.68 × 10-20). Conversely, when hypercholesterolaemia was viewed as the outcome, the OR detected was 1.80 (95% CI: 1.58-2.05, p = 2.79 × 10-19). These findings remained consistent across various MR methods and sensitivity analyses. Additionally, our research pinpointed four co-localised genes CELSR2, PCSK9, LPA, and APOE as integral candidates implicated in the pathogenesis of both conditions, thereby suggesting shared common genetic causal variants and offering potential targets for innovative therapeutic strategies.

Conclusion

bidirectional MR studies reveal genetic evidence of a potential causal link between hypercholesterolaemia and IHD. Notably, these findings also lend credence to the less traditional hypothesis that IHD may instigate hypercholesterolaemia episodes. Moreover, co-localisation analyses intimate the presence of shared genetic causal variants, paving the way for the development of new therapeutic strategies.

Genetic and Lifestyle-Related Factors Influencing Serum Hyper-Propionylcarnitine Concentrations and Their Association with Metabolic Syndrome and Cardiovascular Disease Risk

The genetic and environmental determinants of serum propionylcarnitine concentrations (PC) remain largely unexplored. This study investigated the impact of genetic and environmental factors on serum propionylcarnitine levels in middle-aged and elderly participants from the Ansan/Ansung cohort of the Korean Genome and Epidemiology Study. Our goal was to understand the role of PC on the risk of metabolic syndrome (MetS) leading to cardiovascular disease, particularly concerning branched-chain amino acid (BCAA) metabolism. We analyzed participants' demographic, lifestyle, and biochemical data with and without MetS. Serum metabolite concentrations, including carnitine, acylcarnitine, and amino acid concentrations, were measured, and the components of MetS were evaluated. Genetic variants associated with low and high PC were selected using genome-wide association studies after adjusting for MetS-related parameters. Further, genetic variants and lifestyle factors that interacted with the polygenic risk score (PRS) were analyzed. Participants with MetS were older and less educated, and their alcohol intake was higher than non-MetS participants. PC was significantly associated with the MetS risk and increased the serum levels of BCAAs and other amino acids. Higher PC positively correlated with MetS components, insulin resistance, and cardiovascular risk factors. Intake of calcium, sodium, and vitamin D were inversely associated with PC, but coffee consumption was positively linked to PC. Multiple C2 And Transmembrane Domain Containing-1 (MCTP1)_rs4290997, Kinesin Family Member-7 (KIF7)_rs2350480, Coagulation Factor-II (F2)_rs2070850, Peroxisomal Biogenesis Factor-3 (PEX3)_rs223231, TBC1 Domain Family Member-22A (TBC1D22A)_rs910543, and Phospholipase A2 Group-IV-C (PLA2G4C)_rs7252136 interact with each other to have a threefold influence on PC. The PRS for the six-genetic variant model also interacted with age; the diet rich in beans, potato, and kimchi; and smoking status, influencing PC. In conclusion, elevated PC was associated with MetS and cardiovascular disease risk, suggesting their potential as disease biomarkers.

C11orf54 promotes DNA repair via blocking CMA-mediated degradation of HIF1A

C11orf54 is an ester hydrolase highly conserved across different species. C11orf54 has been identified as a biomarker protein of renal cancers, but its exact function remains poorly understood. Here we demonstrate that C11orf54 knockdown decreases cell proliferation and enhances cisplatin-induced DNA damage and apoptosis. On the one hand, loss of C11orf54 reduces Rad51 expression and nuclear accumulation, which results in suppression of homologous recombination repair. On the other hand, C11orf54 and HIF1A competitively interact with HSC70, knockdown of C11orf54 promotes HSC70 binding to HIF1A to target it for degradation via chaperone-mediated autophagy (CMA). C11orf54 knockdown-mediated HIF1A degradation reduces the transcription of ribonucleotide reductase regulatory subunit M2 (RRM2), which is a rate-limiting RNR enzyme for DNA synthesis and DNA repair by producing dNTPs. Supplement of dNTPs can partially rescue C11orf54 knockdown-mediated DNA damage and cell death. Furthermore, we find that Bafilomycin A1, an inhibitor of both macroautophagy and chaperone-mediated autophagy, shows similar rescue effects as dNTP treatment. In summary, we uncover a role of C11orf54 in regulating DNA damage and repair through CMA-mediated decreasing of HIF1A/RRM2 axis.

METTL3-dependent m6A methylation facilitates uterine receptivity and female fertility via balancing estrogen and progesterone signaling

Infertility is a worldwide reproductive health problem and there are still many unknown etiologies of infertility. In recent years, increasing evidence emerged and confirmed that epigenetic regulation played a leading role in reproduction. However, the function of m⁶A modification in infertility remains unknown. Here we report that METTL3-dependent m⁶A methylation plays an essential role in female fertility via balancing the estrogen and progesterone signaling. Analysis of GEO datasets reveal a significant downregulation of METTL3 expression in the uterus of infertile women with endometriosis or recurrent implantation failure. Conditional deletion of Mettl3 in female reproductive tract by using a Pgr-Cre driver results in infertility due to compromised uterine endometrium receptivity and decidualization. m⁶A-seq analysis of the uterus identifies the 3'UTR of several estrogen-responsive genes with METTL3-dependent m⁶A modification, like Elf3 and Celsr2, whose mRNAs become more stable upon Mettl3 depletion. However, the decreased expression levels of PR and its target genes, including Myc, in the endometrium of Mettl3 cKO mice indicate a deficiency in progesterone responsiveness. In vitro, Myc overexpression could partially compensate for uterine decidualization failure caused by Mettl3 deficiency. Collectively, this study reveals the role of METTL3-dependent m⁶A modification in female fertility and provides insight into the pathology of infertility and pregnancy management.

Exploring the genetic basis of coronary artery disease using functional genomics

Genome-wide Association Studies (GWAS) have identified more than 300 loci associated with coronary artery disease (CAD), defining the genetic risk map of the disease. However, the translation of the association signals into biological-pathophysiological mechanisms constitute a major challenge. Through a group of examples of studies focused on CAD, we discuss the rationale, basic principles and outcomes of the main methodologies implemented to prioritize and characterize causal variants and their target genes. Additionally, we highlight the strategies as well as the current methods that integrate association and functional genomics data to dissect the cellular specificity underlying the complexity of disease mechanisms. Despite the limitations of existing approaches, the increasing knowledge generated through functional studies helps interpret GWAS maps and opens novel avenues for the clinical usability of association data.

Genomic study of maternal lipid traits in early pregnancy concurs with four known adult lipid loci

BACKGROUND

Blood lipids during pregnancy are associated with cardiovascular diseases and adverse pregnancy outcomes. Genome-wide association studies (GWAS) in predominantly male European ancestry populations have identified genetic loci associated with blood lipid levels. However, the genetic architecture of blood lipids in pregnant women remains poorly understood.

OBJECTIVE

Our goal was to identify genetic loci associated with blood lipid levels among pregnant women from diverse ancestry groups and to evaluate whether previously known lipid loci in predominantly European adults are transferable to pregnant women.

METHODS

The trans-ancestry GWAS were conducted on serum levels of total cholesterol, high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL) and triglycerides during first trimester among pregnant women from four population groups (608 European-, 623 African-, 552 Hispanic- and 235 East Asian-Americans) recruited in the NICHD Fetal Growth Studies cohort. The four GWAS summary statistics were combined using trans-ancestry meta-analysis approaches that account for genetic heterogeneity among populations.

RESULTS

Loci in CELSR2 and APOE were genome-wide significantly associated (p-value < 5×10-8) with total cholesterol and LDL levels. Loci near CETP and ABCA1 approached genome-wide significant association with HDL (p-value = 2.97×10-7 and 9.71×10-8, respectively). Less than 20% of previously known adult lipid loci were transferable to pregnant women.

CONCLUSION

This trans-ancestry GWAS meta-analysis in pregnant women identified associations that concur with four known adult lipid loci. Limited replication of known lipid-loci from predominantly European study populations to pregnant women underlines the need for genomic studies of lipids in ancestrally diverse pregnant women.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, NCT00912132.

Genetic Determinants of Plasma Low-Density Lipoprotein Cholesterol Levels: Monogenicity, Polygenicity, and "Missing" Heritability

Changes in plasma low-density lipoprotein cholesterol (LDL-c) levels relate to a high risk of developing some common and complex diseases. LDL-c, as a quantitative trait, is multifactorial and depends on both genetic and environmental factors. In the pregenomic age, targeted genes were used to detect genetic factors in both hyper- and hypolipidemias, but this approach only explained extreme cases in the population distribution. Subsequently, the genetic basis of the less severe and most common dyslipidemias remained unknown. In the genomic age, performing whole-exome sequencing in families with extreme plasma LDL-c values identified some new candidate genes, but it is unlikely that such genes can explain the majority of inexplicable cases. Genome-wide association studies (GWASs) have identified several single-nucleotide variants (SNVs) associated with plasma LDL-c, introducing the idea of a polygenic origin. Polygenic risk scores (PRSs), including LDL-c-raising alleles, were developed to measure the contribution of the accumulation of small-effect variants to plasma LDL-c. This paper discusses other possibilities for unexplained dyslipidemias associated with LDL-c, such as mosaicism, maternal effect, and induced epigenetic changes. Future studies should consider gene-gene and gene-environment interactions and the development of integrated information about disease-driving networks, including phenotypes, genotypes, transcription, proteins, metabolites, and epigenetics.