Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach

Exploring the Causal Relationship and Molecular Mechanisms Between Fasting Insulin and Androgenetic Alopecia: A Mendelian Randomization Study with Bioinformatics Analysis

Background

Prior studies have suggested a significant connection between fasting insulin (FI) and androgenetic alopecia (AGA), but the exact cause of this connection and underlying molecular mechanism has not been clarified. In this study, a Mendelian randomization (MR) analysis was utilized to discover the causal associations between FI and AGA.

Methods

Genome-wide association study (GWAS) data for FI and AGA were retrieved, and bidirectional MR analysis was conducted. FI-associated genes were identified through expression quantitative trait loci (eQTL) analysis, with enrichment analysis and a protein-protein interaction (PPI) network used to explore potential pathways and core genes.

Results

Forward MR analysis revealed a significant causal relationship between elevated FI levels and AGA (P=0.027, OR=43.944). Reverse MR analysis found no causal effect of AGA on FI (P=0.808, OR=1.0001). A total of 92 FI-associated genes were analyzed, with enrichment results indicating involvement in glycine, serine, and threonine metabolic pathways. EIF2B4 and NRBP1 were identified as potential core genes linking FI and AGA.

Conclusion

By using MR analysis, this study verified the possible causative connection between FIns and AGA by MR analysis. The core genes EIF2B4 and NRBP1, along with biological processes such as glycosylation and amino acid metabolism, may serve as crucial links.

Age effect on the shared etiology of glycemic traits and serum lipids: evidence from a Chinese twin study

PURPOSE

Diabetes and dyslipidemia are among the most common chronic diseases with increasing global disease burdens, and they frequently occur together. The study aimed to investigate differences in the heritability of glycemic traits and serum lipid indicators and differences in overlapping genetic and environmental influences between them across age groups.

METHODS

This study included 1189 twin pairs from the Chinese National Twin Registry and divided them into three groups: aged ≤ 40, 41-50, and > 50 years old. Univariate and bivariate structural equation models (SEMs) were conducted on glycemic indicators and serum lipid indicators, including blood glucose (GLU), glycated hemoglobin A1c (HbA1c), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), in the total sample and three age groups.

RESULTS

All phenotypes showed moderate to high heritability (0.37-0.64). The heritability of HbA1c demonstrated a downward trend with age (HbA1c: 0.50-0.79), while others remained relatively stable (GLU: 0.55-0.62, TC: 0.58-0.66, TG: 0.50-0.63, LDL-C: 0.24-0.58, HDL-C: 0.31-0.57). The bivariate SEMs demonstrated that GLU and HbA1c were correlated with each serum lipid indicator (0.10-0.17), except HDL-C. Except for HbA1c and LDL-C, as well as HbA1c and HDL-C, differences in genetic correlations underlying glycemic traits and serum lipids between age groups were observed, with the youngest group showing a significantly higher genetic correlation than the oldest group.

CONCLUSION

Across the whole adulthood, genetic influences were consistently important for GLU, TC, TG, LDL-C and HDL-C, and age may affect the shared genetic influences between glycemic traits and serum lipids. Further studies are needed to elucidate the role of age in the interactions of genes related to glycemic traits and serum lipids.

Changes in environmental stress over COVID-19 pandemic likely contributed to failure to replicate adiposity phenotype associated with Krtcap3

We previously identified keratinocyte-associated protein 3, Krtcap3, as an obesity-related gene in female rats where a whole body Krtcap3 knockout (KO) led to increased adiposity compared to wild-type (WT) controls when fed a high-fat diet (HFD). We sought to replicate this work to better understand the function of Krtcap3 but were unable to reproduce the adiposity phenotype. In the current work, WT female rats ate more compared to WT in the prior study, with corresponding increases in body weight and fat mass, while there were no changes in these measures in KO females between the studies. The prior study was conducted before the COVID-19 pandemic, while the current study started after initial lockdown orders and was completed during the pandemic in a generally less stressful environment. We hypothesize that the environmental changes impacted stress levels and may explain the failure to replicate our results. Analysis of corticosterone (CORT) at euthanasia showed a significant study-by-genotype interaction where WT had significantly higher CORT relative to KO in study 1, with no differences in study 2. These data suggest that decreasing Krtcap3 expression may alter the environmental stress response to influence adiposity. We also found that KO rats in both studies, but not WT, experienced a dramatic increase in CORT after their cage mate was removed, suggesting a separate connection to social behavioral stress. Future work is necessary to confirm and elucidate the finer mechanisms of these relationships, but these data indicate the possibility of Krtcap3 as a novel stress gene.NEW & NOTEWORTHY Obesity is linked to both genetics and environmental factors such as stress. Krtcap3 has previously been identified as a gene associated with adiposity, and our work here demonstrates that environmental stress may influence the role of Krtcap3 on both food intake and adiposity. Obesity is strongly influenced by stress in humans, so the identification of novel genes that link stress and obesity will greatly advance our understanding of the disease.

Changes in Environmental Stress over COVID-19 Pandemic Likely Contributed to Failure to Replicate Adiposity Phenotype Associated with Krtcap3

We previously identified Keratinocyte-associated protein 3, Krtcap3, as an obesity-related gene in female rats where a whole-body Krtcap3 knock-out (KO) led to increased adiposity compared to wild-type (WT) controls when fed a high-fat diet (HFD). We sought to replicate this work to better understand the function of Krtcap3 but were unable to reproduce the adiposity phenotype. In the current work, WT female rats ate more compared to WT in the prior study, with corresponding increases in body weight and fat mass, while there were no changes in these measures in KO females between the studies. The prior study was conducted before the COVID-19 pandemic, while the current study started after initial lock-down orders and was completed during the pandemic with a generally less stressful environment. We hypothesize that the environmental changes impacted stress levels and may explain the failure to replicate our results. Analysis of corticosterone (CORT) at euthanasia showed a significant study by genotype interaction where WT had significantly higher CORT relative to KO in Study 1, with no differences in Study 2. These data suggest that decreasing Krtcap3 expression may alter the environmental stress response to influence adiposity. We also found that KO rats in both studies, but not WT, experienced a dramatic increase in CORT after their cage mate was removed, suggesting a separate connection to social behavioral stress. Future work is necessary to confirm and elucidate the finer mechanisms of these relationships, but these data indicate the possibility of Krtcap3 as a novel stress gene.

Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats

Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.

Keratinocyte-associated protein 3 plays a role in body weight and adiposity with differential effects in males and females

Despite the obesity crisis in the United States, the underlying genetics are poorly understood. Our lab previously identified Keratinocyte-associated protein 3, Krtcap3, as a candidate gene for adiposity through a genome-wide association study in outbred rats, where increased liver expression of Krtcap3 correlated with decreased fat mass. Here we seek to confirm that Krtcap3 expression affects adiposity traits. To do so, we developed an in vivo whole-body Krtcap3 knock-out (KO) rat model. Wild-type (WT) and KO rats were placed onto a high-fat (HFD) or low-fat diet (LFD) at 6 weeks of age and were maintained on diet for 13 weeks, followed by assessments of metabolic health. We hypothesized that Krtcap3-KO rats will have increased adiposity and a worsened metabolic phenotype relative to WT. We found that KO male and female rats have significantly increased body weight versus WT, with the largest effect in females on a HFD. KO females also ate more and had greater adiposity, but were more insulin sensitive than WT regardless of diet condition. Although KO males weighed more than WT under both diet conditions, there were no differences in eating behavior or fat mass. Interestingly, KO males on a HFD were more insulin resistant than WT. This study confirms that Krtcap3 plays a role in body weight regulation and demonstrates genotype- and sex-specific effects on food intake, adiposity, and insulin sensitivity. Future studies will seek to better understand these sex differences, the role of diet, and establish a mechanism for Krtcap3 in obesity.

Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population

While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.

Identifying Shared Risk Genes for Asthma, Hay Fever, and Eczema by Multi-Trait and Multiomic Association Analyses

Asthma, hay fever and eczema are three comorbid diseases with high prevalence and heritability. Their common genetic architectures have not been well-elucidated. In this study, we first conducted a linkage disequilibrium score regression analysis to confirm the strong genetic correlations between asthma, hay fever and eczema. We then integrated three distinct association analyses (metaCCA multi-trait association analysis, MAGMA genome-wide and MetaXcan transcriptome-wide gene-based tests) to identify shared risk genes based on the large-scale GWAS results in the GeneATLAS database. MetaCCA can detect pleiotropic genes associated with these three diseases jointly. MAGMA and MetaXcan were performed separately to identify candidate risk genes for each of the three diseases. We finally identified 150 shared risk genes, in which 60 genes are novel. Functional enrichment analysis revealed that the shared risk genes are enriched in inflammatory bowel disease, T cells differentiation and other related biological pathways. Our work may provide help on treatment of asthma, hay fever and eczema in clinical applications.

Multifaceted Aspects of Metabolic Plasticity in Human Cholangiocarcinoma: An Overview of Current Perspectives

Cholangiocarcinoma (CCA) is a deadly tumor without an effective therapy. Unique metabolic and bioenergetics features are important hallmarks of tumor cells. Metabolic plasticity allows cancer cells to survive in poor nutrient environments and maximize cell growth by sustaining survival, proliferation, and metastasis. In recent years, an increasing number of studies have shown that specific signaling networks contribute to malignant tumor onset by reprogramming metabolic traits. Several evidences demonstrate that numerous metabolic mediators represent key-players of CCA progression by regulating many signaling pathways. Besides the well-known Warburg effect, several other different pathways involving carbohydrates, proteins, lipids, and nucleic acids metabolism are altered in CCA. The goal of this review is to highlight the main metabolic processes involved in the cholangio-carcinogeneis that might be considered as potential novel druggable candidates for this disease.

Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis

Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.

CoMM: A Collaborative Mixed Model That Integrates GWAS and eQTL Data Sets to Investigate the Genetic Architecture of Complex Traits

Genome-wide association study (GWAS) analyses have identified thousands of associations between genetic variants and complex traits. However, it is still a challenge to uncover the mechanisms underlying the association. With the growing availability of transcriptome data sets, it has become possible to perform statistical analyses targeted at identifying influential genes whose expression levels correlate with the phenotype. Methods such as PrediXcan and transcriptome-wide association study (TWAS) use the transcriptome data set to fit a predictive model for gene expression, with genetic variants as covariates. The gene expression levels for the GWAS data set are then 'imputed' using the prediction model, and the imputed expression levels are tested for their association with the phenotype. These methods fail to account for the uncertainty in the GWAS imputation step, and we propose a collaborative mixed model (CoMM) that addresses this limitation by jointly modelling the multiple analysis steps. We illustrate CoMM's ability to identify relevant genes in the Northern Finland Birth Cohort 1966 data set and extend the model to handle the more widely available GWAS summary statistics.

Comprehensive identification of pleiotropic loci for body fat distribution using the NHGRI-EBI Catalog of published genome-wide association studies

We conducted a hypothesis-free cross-trait analysis for waist-to-hip ratio adjusted for body mass index (WHR_adjBMI ) loci derived through genome-wide association studies (GWAS). Summary statistics from published GWAS were used to capture all WHR_adjBMI single-nucleotide polymorphisms (SNPs), and their proxy SNPs were identified. These SNPs were used to extract cross-trait associations between WHR_adjBMI SNPs and other traits through the NHGRI-EBI GWAS Catalog. Pathway analysis was conducted for pleiotropic WHR_adjBMI SNPs. We found 160 WHR_adjBMI SNPs and 3675 proxy SNPs. Cross-trait analysis identified 239 associations, of which 100 were for obesity traits. The remaining 139 associations were filtered down to 101 unique linkage disequilibrium block associations, which were grouped into 13 categories: lipids, red blood cell traits, white blood cell counts, inflammatory markers and autoimmune diseases, type 2 diabetes-related traits, adiponectin, cancers, blood pressure, height, neuropsychiatric disorders, electrocardiography changes, urea measurement, and others. The highest number of cross-trait associations were found for triglycerides (n = 10), high-density lipoprotein cholesterol (n = 9), and reticulocyte counts (n = 8). Pathway analysis for WHR_adjBMI pleiotropic SNPs found immune function pathways as the top canonical pathways. Results from our original methodology indicate a novel genetic association between WHR_adjBMI and reticulocyte counts and highlight the pleiotropy between abdominal obesity, immune pathways, and other traits.