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RNAi-based functional profiling of loci from blood lipid genome-wide association studies identifies genes with cholesterol-regulatory function.

Blattmann P, Schuberth C, Pepperkok R, Runz H - PLoS Genet. (2013)

Bottom Line: Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease.Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions.By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.

View Article: PubMed Central - PubMed

Affiliation: Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.

ABSTRACT
Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL-receptor levels and/or that overexpression as GFP-tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.

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Comparison of multiparametric datasets for neighboring genes within lipid-trait-associated loci.Shown are parameters “total cellular intensity” (“total”) of the two strongest effector siRNAs/gene and relative genomic position of lead SNPs (arrowheads) for seven (A–G) selected lipid-trait/CAD/MI loci in which multiple neighboring candidate genes (±50 kB up-/downstream of lead SNP) were functionally analyzed (see Figure S2 and Table S4 for comprehensive datasets). Phenotypes (red, increasing; blue, decreasing) meeting statistical criteria as described in Materials and Methods are framed in orange.
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pgen-1003338-g003: Comparison of multiparametric datasets for neighboring genes within lipid-trait-associated loci.Shown are parameters “total cellular intensity” (“total”) of the two strongest effector siRNAs/gene and relative genomic position of lead SNPs (arrowheads) for seven (A–G) selected lipid-trait/CAD/MI loci in which multiple neighboring candidate genes (±50 kB up-/downstream of lead SNP) were functionally analyzed (see Figure S2 and Table S4 for comprehensive datasets). Phenotypes (red, increasing; blue, decreasing) meeting statistical criteria as described in Materials and Methods are framed in orange.

Mentions: The identification of genes with relevance for lipid traits and/or CAD/MI from GWAS is complicated by the fact that many lead SNPs locate to gene rich regions [7], [24]. We therefore assessed whether for selected GWAS loci our unbiased approach could help prioritizing functional effectors among several possible candidate genes in such loci. Indeed, in six of the 30 loci for which more than one candidate gene/locus was functionally analyzed, our results suggested one prominent effector gene. Most surprisingly, in 9 of these 30 loci knockdown of more than one gene per locus affected cellular cholesterol homeostasis (Figure 3). For instance, of the 8 genes analyzed at the 7q11.23 locus (Figure 3D) not only MLXIPL as the most likely candidate to explain association with TG [8], but also five other genes scored as significantly increasing FC, among them TBL2, knockdown of which also induced the strongest observed stimulation of LDL-uptake. Similar observations for novel effectors in addition to genes with well-characterized lipid-regulatory functions were made for loci 1p36.11, 11q23.3 or 12q24.11 among others (Figure 3). Furthermore, while none of the 16 candidate genes at the 19p12 locus was previously ascribed a lipid-regulatory function, ten scored as effectors with two independent siRNAs in at least one of the two functional assays, which might reflect the substantial pleiotropy at this locus in six different GWAS [1], [6], [7], [17], [20], [21] (Table S1).


RNAi-based functional profiling of loci from blood lipid genome-wide association studies identifies genes with cholesterol-regulatory function.

Blattmann P, Schuberth C, Pepperkok R, Runz H - PLoS Genet. (2013)

Comparison of multiparametric datasets for neighboring genes within lipid-trait-associated loci.Shown are parameters “total cellular intensity” (“total”) of the two strongest effector siRNAs/gene and relative genomic position of lead SNPs (arrowheads) for seven (A–G) selected lipid-trait/CAD/MI loci in which multiple neighboring candidate genes (±50 kB up-/downstream of lead SNP) were functionally analyzed (see Figure S2 and Table S4 for comprehensive datasets). Phenotypes (red, increasing; blue, decreasing) meeting statistical criteria as described in Materials and Methods are framed in orange.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3585126&req=5

pgen-1003338-g003: Comparison of multiparametric datasets for neighboring genes within lipid-trait-associated loci.Shown are parameters “total cellular intensity” (“total”) of the two strongest effector siRNAs/gene and relative genomic position of lead SNPs (arrowheads) for seven (A–G) selected lipid-trait/CAD/MI loci in which multiple neighboring candidate genes (±50 kB up-/downstream of lead SNP) were functionally analyzed (see Figure S2 and Table S4 for comprehensive datasets). Phenotypes (red, increasing; blue, decreasing) meeting statistical criteria as described in Materials and Methods are framed in orange.
Mentions: The identification of genes with relevance for lipid traits and/or CAD/MI from GWAS is complicated by the fact that many lead SNPs locate to gene rich regions [7], [24]. We therefore assessed whether for selected GWAS loci our unbiased approach could help prioritizing functional effectors among several possible candidate genes in such loci. Indeed, in six of the 30 loci for which more than one candidate gene/locus was functionally analyzed, our results suggested one prominent effector gene. Most surprisingly, in 9 of these 30 loci knockdown of more than one gene per locus affected cellular cholesterol homeostasis (Figure 3). For instance, of the 8 genes analyzed at the 7q11.23 locus (Figure 3D) not only MLXIPL as the most likely candidate to explain association with TG [8], but also five other genes scored as significantly increasing FC, among them TBL2, knockdown of which also induced the strongest observed stimulation of LDL-uptake. Similar observations for novel effectors in addition to genes with well-characterized lipid-regulatory functions were made for loci 1p36.11, 11q23.3 or 12q24.11 among others (Figure 3). Furthermore, while none of the 16 candidate genes at the 19p12 locus was previously ascribed a lipid-regulatory function, ten scored as effectors with two independent siRNAs in at least one of the two functional assays, which might reflect the substantial pleiotropy at this locus in six different GWAS [1], [6], [7], [17], [20], [21] (Table S1).

Bottom Line: Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease.Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions.By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.

View Article: PubMed Central - PubMed

Affiliation: Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany.

ABSTRACT
Genome-wide association studies (GWAS) are powerful tools to unravel genomic loci associated with common traits and complex human disease. However, GWAS only rarely reveal information on the exact genetic elements and pathogenic events underlying an association. In order to extract functional information from genomic data, strategies for systematic follow-up studies on a phenotypic level are required. Here we address these limitations by applying RNA interference (RNAi) to analyze 133 candidate genes within 56 loci identified by GWAS as associated with blood lipid levels, coronary artery disease, and/or myocardial infarction for a function in regulating cholesterol levels in cells. Knockdown of a surprisingly high number (41%) of trait-associated genes affected low-density lipoprotein (LDL) internalization and/or cellular levels of free cholesterol. Our data further show that individual GWAS loci may contain more than one gene with cholesterol-regulatory functions. Using a set of secondary assays we demonstrate for a number of genes without previously known lipid-regulatory roles (e.g. CXCL12, FAM174A, PAFAH1B1, SEZ6L, TBL2, WDR12) that knockdown correlates with altered LDL-receptor levels and/or that overexpression as GFP-tagged fusion proteins inversely modifies cellular cholesterol levels. By providing strong evidence for disease-relevant functions of lipid trait-associated genes, our study demonstrates that quantitative, cell-based RNAi is a scalable strategy for a systematic, unbiased detection of functional effectors within GWAS loci.

Show MeSH
Related in: MedlinePlus