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Human metabolic individuality in biomedical and pharmaceutical research

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TLDR
A comprehensive analysis of genotype-dependent metabolic phenotypes using a genome-wide association study with non-targeted metabolomics to identify genetic loci associated with blood metabolite concentrations and generates many new hypotheses for biomedical and pharmaceutical research.
Abstract
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.

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Innovation: Metabolomics: the apogee of the omics trilogy

TL;DR: By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and are shaping the understanding of cell biology, physiology and medicine.
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Emerging applications of metabolomics in drug discovery and precision medicine

TL;DR: This Review discusses some of the latest technological advances in metabolomics, focusing on the application of metabolomics towards uncovering the underlying causes of complex diseases, the growing role of metabolites in drug discovery and its potential effect on precision medicine.
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HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease.

TL;DR: A use case of HaploReg is illustrated for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms, and the number of chromatin state maps to 127 reference epigenomes is greatly expanded.
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Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us?

TL;DR: The broad impact of metabolism in cellular function and how modern concepts of metabolism can inform the authors' understanding of common diseases like cancer are discussed and the prospects of developing new metabolic approaches to disease treatment are considered.
References
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Journal ArticleDOI

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
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Potential etiologic and functional implications of genome-wide association loci for human diseases and traits

TL;DR: An online catalog of SNP-trait associations from published genome-wide association studies for use in investigating genomic characteristics of trait/disease-associated SNPs (TASs) is developed, well-suited to guide future investigations of the role of common variants in complex disease etiology.
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A flexible and accurate genotype imputation method for the next generation of genome-wide association studies.

TL;DR: It is found that imputation accuracy can be greatly enhanced by expanding the reference panel to contain thousands of chromosomes and that IMPUTE v2 outperforms other methods in this setting at both rare and common SNPs, with overall error rates that are 15%–20% lower than those of the closest competing method.
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Biological, clinical and population relevance of 95 loci for blood lipids

Tanya M. Teslovich, +218 more
- 05 Aug 2010 - 
TL;DR: The results identify several novel loci associated with plasma lipids that are also associated with CAD and provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
Journal ArticleDOI

Merlin--rapid analysis of dense genetic maps using sparse gene flow trees.

TL;DR: The multipoint engine for rapid likelihood inference (Merlin) is a computer program that uses sparse inheritance trees for pedigree analysis; it performs rapid haplotyping, genotype error detection and affected pair linkage analyses and can handle more markers than other pedigree analysis packages.
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Biological, clinical and population relevance of 95 loci for blood lipids

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