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Genomics: Variations in blood lipids
  Alan R. Shuldiner & Toni I. Pollin Alan R. Shuldiner and Toni I. Pollin are at the Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA. Alan R. Shuldiner is also at the Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore.
Nature 04 August 2010
What is the new gold standard for genome-wide association studies? As exemplified by analyses of blood lipids, it is collaboration to amass huge sample sizes and functional studies of the genes identified.
Cardiovascular disease is a leading cause of death. In the United States, for example, it accounted for 1 in every 2.8 deaths in 2005 (ref. 1). Disruptions in the amounts of blood lipids greatly increase the risk of this disease. On page 707 of this issue, Teslovich et al.2 report on one of the largest meta-analyses of genome-wide association studies so far, involving 46 cohorts and more than 100,000 human subjects. They identify 95 distinct gene variants and/or chromosomal locations - 59 of them new - associated with lipid traits in the blood. What's more, the authors go a step further to validate the biological relevance of three of the novel genes in mice.
Cells need cholesterol and triglycerides - derived from dietary sources and the liver - for membrane synthesis and energy. These lipids circulate in the blood as part of lipoprotein particles, which are made of various proportions of cholesterol, triglycerides, phospholipids and proteins. Low-density lipoproteins (LDLs), for example, shuttle cholesterol from the liver to other tissues, whereas high-density lipoproteins (HDLs) scavenge cholesterol from blood vessels and other tissues, returning it to the liver.
Much of what we know about lipid metabolism and the treatment of dyslipidaemia (disruptions in blood-lipid levels) comes from the ongoing discovery and characterization of numerous, relatively rare genetic variants with large effects on lipid levels (reviewed in ref. 3). Brown and Goldstein's landmark studies identifying mutations in the LDL receptor pioneered such work4. More recently, however, researchers have focused on identifying genetic variants that influence the more common causes of increased blood-lipid levels, apparently resulting from the interaction of multiple small genetic effects with environmental and life-style factors such as diet and physical activity3.
An earlier meta-analysis of genome-wide association studies (GWAS) involving more than 8,000 individuals5, for instance, implicated 36 genes and chromosomal loci in common variation in the levels of blood lipids. But to detect smaller effects of genetic variants, even larger sample sizes are needed in GWAS that evaluate the association of lipid levels with millions of single nucleotide polymorphisms (SNPs) distributed throughout the genome. Pooling several GWAS in a larger meta-analysis enables detection of yet smaller effects.
This is exactly the approach Teslovich et al.2 took - a strategy that led to several insights. Many of the variants the authors discovered are in, or near, genes known to mediate lipid metabolism. They include common variants in genes previously known to harbour rare variants that cause extremely low or extremely high blood-lipid levels; variants identified through 'candidate-gene' studies; and variants in genes that are targets of lipid-lowering drugs. Among the remaining variants, many are in, or near, genes with no known function in lipid metabolism. Identifying these genes and elucidating their functions could lead to information about lipid metabolism and, potentially, to new drug targets. Notably, the effects of individual variants on lipid levels tend to be additive, with people carrying more 'risk' variants being more likely to have dyslipidaemia than those carrying fewer risk variants.
Teslovich and colleagues' results also begin to unravel the complex genetic architecture of lipid homeostasis. Some gene variants or loci seem to have gender-specific effects. Moreover, most - but not all - of the variants discovered in this large sample of individuals of European ancestry apparently affect blood-lipid levels in Asians and African Americans too.
The authors find that many of the genetic variants affecting blood-lipid levels also associate with coronary artery disease. This is especially true for variants associated with increased LDL-cholesterol, and to a lesser extent for SNPs associated with decreased HDL-cholesterol or increased triglycerides. These observations support the notion that alterations in blood lipids pave the way for coronary artery disease6.
Despite the outstanding power of this study to detect common variants of very small effect, the 95 loci identified explain only about 10-12% of the total variance in blood-lipid levels, which corresponds to about 25-30% of the genetic variance. Thus, as with other large-scale GWAS for complex diseases and traits, most of the genetic variance remains unexplained7. Nonetheless, the huge sample size and excellent genomic coverage of this work2 hint that additional modest-effect common variants are unlikely to contribute significantly to the 'missing' heritability. Further genomic sequencing could lead to the discovery of many rare (large-effect) variants or other types of variants (microdeletions, duplications and inversions) not tagged - or imprecisely tagged - by current genotyping platforms used in GWAS.
A highlight of Teslovich and co-workers' paper is their analysis of the biological significance of several of the genes and loci they identified, including a systematic evaluation of the effects of the associated SNPs on gene expression in the liver and in fat tissue. Of the three genes they investigated further, one, GALNT2, which encodes a member of the N-acetylgalactosamine-transferase enzyme family, was not previously known to be involved in lipid metabolism. Decreasing the expression of Galnt2 in mouse liver significantly decreased levels of HDL-cholesterol. Similarly, reduced expression of Ttc39b (function unknown) increased HDL-cholesterol levels, and increased expression of Ppp1r3b (which encodes an inhibitory subunit of protein phosphatase 1) decreased HDL-cholesterol levels.
An accompanying paper on page 714 of this issue8 also takes functional validation as its focus. It dissects the biological consequences of genetic variation in a locus on chromosome 1p13 that has been strongly associated, by previous GWAS, with elevated LDL-cholesterol levels in the blood and myocardial infarction in humans. Through studies of human subjects and human-derived liver cells, this study shows that rs12740374 - a common non-protein-coding variant located within this locus - creates a binding site for the transcription factor C/EBP, altering the expression of the SORT1 gene in the liver. In mice, Sort1 alters secretion of very low-density lipoproteins (VLDLs) by liver cells, thus affecting blood levels of LDL-cholesterol and VLDL particles. This work8 is yet another example of how information from GWAS can be used to unravel new regulatory pathways that alter the risk of human disease, in this case myocardial infarction.
Teslovich and colleagues' analysis leads to many clinically relevant questions. For example, would it be of diagnostic value to include a panel of 95 genetic tests, based on their results, beyond conventional measurements of blood-lipid levels? Which of the gene variants they identify affect other disease-related features of lipoprotein particles such as their size and lipid-protein composition? For the novel genes, what mechanisms underlie their effect? Are any of them drug-responsive targets? This work2 was made possible thanks to the Human Genome Project and an unprecedentedly large collaborative effort among an international multidisciplinary genomics team. Now, scientists interested in translational aspects - disease-related mechanisms and clinical relevance - can roll up their sleeves.
1. Rosamond, W. et al. Circulation 117, e25-e146 (2008).
2. Teslovich, M. et al. Nature 466, 707-713 (2010).
3. Hegele, R. A. Nature Rev. Genet. 10, 109-121 (2009).
4. Brown, M. S., Hobbs, H. H. & Goldstein, J. L. in Metabolic and Molecular Bases of Inherited Disease 8th edn (eds Scriver, C. R. et al.) Ch. 120.I (McGraw-Hill, 2000).
5. Willer, C. J. et al. Nature Genet. 40, 161-169 (2008).
6. Davey Smith, G. & Ebrahim, S. Int. J. Epidemiol. 32, 1-22 (2003).
7. Goldstein, D. B. N. Engl. J. Med. 360, 1696-1698 (2009).
8. Musunuru, K. et al. Nature 466, 714-719 (2010).
Competing financial interests
Alan R. Shuldiner is a consultant for ISIS Pharmaceuticals.
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