scholarly journals Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Adriaan van der Graaf ◽  
◽  
Annique Claringbould ◽  
Antoine Rimbert ◽  
Harm-Jan Westra ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Summary Statistics ◽  
Low Density Lipoprotein Cholesterol ◽  
Causal Inferences ◽  
Individual Level ◽  
Level Data

Abstract Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data, even when only one eQTL variant is present. In simulations, MR-link shows false-positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other tested MR methods and coloc. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals with expression and protein QTL summary statistics from blood and liver identifies 25 genes causally linked to LDL-C. These include the known SORT1 and ApoE genes as well as PVRL2, located in the APOE locus, for which a causal role in liver was not known. Our results showcase the strength of MR-link for transcriptome-wide causal inferences.

scholarly journals A novel Mendelian randomization method identifies causal relationships between gene expression and low-density lipoprotein cholesterol levels

2019 ◽  
Author(s):  
Adriaan van der Graaf ◽  
Annique Claringbould ◽  
Antoine Rimbert ◽  
Harm-Jan Westra ◽  
Yang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Low Density ◽  
Causal Relationships ◽  
Low Density Lipoprotein Cholesterol ◽  
Individual Level

AbstractRobust inference of causal relationships between gene expression and complex traits using Mendelian Randomization (MR) approaches is confounded by pleiotropy and linkage disequilibrium (LD) between gene expression quantitative loci (eQTLs). Here we propose a new MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data. In simulations, MR-link shows false positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other MR methods we tested, even when only one eQTL variant is present. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals and eQTLs summary statistics from whole blood and liver identified 19 genes causally linked to LDL-C. These include the previously functionally validatedSORT1gene, and thePVRL2gene, located in theAPOElocus, for which a causal role in liver was yet unknown. Our results showcase the strength of MR-link for transcriptome-wide causal inferences.

scholarly journals An Approach to Identify New Pleiotropic Genetic Loci From Publicly Available Univariate GWAS Results

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 130-130
Author(s):  
Yury Loika ◽  
Alexander Kulminski
Keyword(s):  
Complex Traits ◽  
Metabolic Networks ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Reproductive Age ◽  
Summary Statistics ◽  
Omnibus Test ◽  
Individual Level ◽  
Age Related ◽  
Level Data

Abstract The connections between genes and multifactorial polygenic age-related traits are not trivial due to complexity of metabolic networks in an organism, which were primarily adapted to maximize fitness at reproductive age in ancient environments. Given this complexity, pleiotropy in predisposition to complex traits appears to be common phenomenon. Identifying mechanisms of pleiotropic predisposition to multiple age-related traits can be a key factor in developing strategies for extending health-span and lifespan. Correlation between complex traits may be a factor shedding light on these mechanisms. Recently, we used an omnibus test leveraging correlation between multiple age-related traits to gain insights into pleiotropic predisposition to them. The analysis using individual-level data identified large number of new pleiotropic loci and highlighted a novel phenomenon of antagonistic genetic heterogeneity, which was characterized by antagonistic directions of genetic effects for directly correlated traits. Here, we demonstrate feasibility of our approach using summary statistics from univariate genome-wide (GW) association studies (GWAS). Our analysis focused on the results for high density lipoprotein cholesterol (HDL-C) and triglycerides (TG) from the Global Lipids Genetic Consortium, which reported 94 GW significant loci (p≤5×10-8). The traits’ correlation was estimated from the individual level data. Our approach identified 28 loci with pleiotropic predisposition to HDL-C and TG at p≤5×10-8, which did not attain univariate GW significance with either of these traits. Fifteen of them (53%) demonstrated antagonistic heterogeneity. These results show that our approach can be efficiently used in the analysis of summary statistics from published studies to identify novel pleiotropic loci.

scholarly journals CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies

2019 ◽  
Author(s):  
Yi Yang ◽  
Xingjie Shi ◽  
Yuling Jiao ◽  
Jian Huang ◽  
Min Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Complex Traits ◽  
Mixed Model ◽  
Association Studies ◽  
Gwas Data ◽  
Supplementary Information ◽  
Summary Statistics ◽  
Individual Level ◽  
The Relationship

AbstractMotivationAlthough genome-wide association studies (GWAS) have deepened our understanding of the genetic architecture of complex traits, the mechanistic links that underlie how genetic variants cause complex traits remains elusive. To advance our understanding of the underlying mechanistic links, various consortia have collected a vast volume of genomic data that enable us to investigate the role that genetic variants play in gene expression regulation. Recently, a collaborative mixed model (CoMM) [42] was proposed to jointly interrogate genome on complex traits by integrating both the GWAS dataset and the expression quantitative trait loci (eQTL) dataset. Although CoMM is a powerful approach that leverages regulatory information while accounting for the uncertainty in using an eQTL dataset, it requires individual-level GWAS data and cannot fully make use of widely available GWAS summary statistics. Therefore, statistically efficient methods that leverages transcriptome information using only summary statistics information from GWAS data are required.ResultsIn this study, we propose a novel probabilistic model, CoMM-S2, to examine the mechanistic role that genetic variants play, by using only GWAS summary statistics instead of individual-level GWAS data. Similar to CoMM which uses individual-level GWAS data, CoMM-S2 combines two models: the first model examines the relationship between gene expression and genotype, while the second model examines the relationship between the phenotype and the predicted gene expression from the first model. Distinct from CoMM, CoMM-S2 requires only GWAS summary statistics. Using both simulation studies and real data analysis, we demonstrate that even though CoMM-S2 utilizes GWAS summary statistics, it has comparable performance as CoMM, which uses individual-level GWAS [email protected] and implementationThe implement of CoMM-S2 is included in the CoMM package that can be downloaded from https://github.com/gordonliu810822/CoMM.Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals Comparative Effects of Flaxseed Sources on the Egg ALA Deposition and Hepatic Gene Expression in Hy-Line Brown Hens

Foods ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1663
Author(s):  
Muhammad Suhaib Shahid ◽  
Tausif Raza ◽  
Yuqin Wu ◽  
Mazhar Hussain Mangi ◽  
Wei Nie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Egg Production ◽  
Laying Hens ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Egg Yolk ◽  
Lipoprotein Cholesterol ◽  
Egg Mass ◽  
Low Density ◽  
Low Density Lipoprotein Cholesterol

Healthy diets are necessary for both humans and animals, including poultry. These diets contain various nutrients for maintenance and production in laying hens. Therefore, research was undertaken to explore the efficiency of various dietary flaxseed sources on the n-3 deposition in the egg yolk and gene expression in laying hens. Five dietary groups were analyzed, i.e., (i) a corn-based diet with no flaxseed (FS) as a negative control (NC), (ii) a wheat-based diet supplemented with 10% whole FS without multi-carbohydrase enzymes (MCE) as a positive control (PC), (iii) ground FS supplemented with MCE (FS), (iv) extruded flaxseed meal was supplemented with MCE (EFM), (v) flaxseed oil supplemented with MCE (FSO). Results indicated that egg weight was highest in the NC, FS, EFM, and FSO groups as compared to PC in the 12th week. Egg mass was higher in enzyme supplemented groups as compared to the PC group, but lower than NC. In the 12th week, the HDEP (hen day egg production) was highest in the FS and EFM groups as compared to FSO, PC, and NC. The FCR (feed conversion ratio) was better in enzyme supplemented groups as compared to the PC group. Enzyme addition enhanced the egg quality as compared to PC in the 12th week. The HDL-C (high-density lipoprotein cholesterol) was increased, while LDL-C (low-density lipoprotein cholesterol), VLDL-C (very-low-density lipoprotein cholesterol), TC (total cholesterol), and TG (total triglycerides) were reduced in the enzyme supplemented groups as compared to PC and NC. The FSO deposit more n-3 PUFA and docosahexaenoic acid (DHA) in the egg yolk as compared to FS and EFM groups. The expression of ACOX1, LCPT1, FADS1, FADS2, and ELOV2 genes were upregulated, while PPAR-α was downregulated in the FSO group. The LPL mRNA expression was upregulated in the FS, EFM, and FSO groups as compared to the PC and NC groups. It was inferred that FSO with enzymes at 2.5% is cost-effective, improves the hen performances, upregulated the fatty acid metabolism and β-oxidation genes expression, and efficiently deposits optimal n-3 PUFA in the egg as per consumer’s demand.

scholarly journals Integrative analysis of multi-omics data for discovering low-frequency variants associated with low-density lipoprotein cholesterol levels

2020 ◽  
Author(s):  
Tianzhong Yang ◽  
Peng Wei ◽  
Wei Pan
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Low Density Lipoprotein ◽  
Low Frequency ◽  
Density Lipoprotein ◽  
Low Density ◽  
Omics Data ◽  
Common Variants ◽  
Low Density Lipoprotein Cholesterol ◽  
Cholesterol Levels

Abstract Motivation The abundance of omics data has facilitated integrative analyses of single and multiple molecular layers with genome-wide association studies focusing on common variants. Built on its successes, we propose a general analysis framework to leverage multi-omics data with sequencing data to improve the statistical power of discovering new associations and understanding of the disease susceptibility due to low-frequency variants. The proposed test features its robustness to model misspecification, high power across a wide range of scenarios and the potential of offering insights into the underlying genetic architecture and disease mechanisms. Results Using the Framingham Heart Study data, we show that low-frequency variants are predictive of DNA methylation, even after conditioning on the nearby common variants. In addition, DNA methylation and gene expression provide complementary information to functional genomics. In the Avon Longitudinal Study of Parents and Children with a sample size of 1497, one gene CLPTM1 is identified to be associated with low-density lipoprotein cholesterol levels by the proposed powerful adaptive gene-based test integrating information from gene expression, methylation and enhancer–promoter interactions. It is further replicated in the TwinsUK study with 1706 samples. The signal is driven by both low-frequency and common variants. Availability and implementation Models are available at https://github.com/ytzhong/DNAm. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Sign in / Sign up

Export Citation Format

Share Document