Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10−204) and 10 loci for sphingolipids (smallest P-value = 3.10×10−57). After a correction for multiple comparisons (P-value<2.2×10−9), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits

Novel loci associated with eGFRcrea.

<p>SNPs are listed in the stratum where the smallest <i>P</i> value in the discovery analysis was observed. Sample size/number of studies in the discovery phase: 74,354/26 (overall, direction test), 66,931/24 (No Diabetes), 46,435/23 (age ≤65 years); replication phase: 56,246/19 (overall, direction test), 41,218/17 (No Diabetes), 28,631/16 (age ≤65 years); combined analysis: 130,600/45 (overall, direction test), 108,149/41 (No Diabetes), 75,066/39 (age ≤65 years).</p><p>Chr.: chromosome; bp: base-pairs; Ref./Non-Ref. All.: reference/non-reference alleles; RAF: reference allele frequency; SE: standard error.</p>‡<p>Genes nearby were based on RefSeq genes (build 36). The gene closest to the SNP is listed first and is in boldface if the SNP is located within the gene.</p>§<p>Effects on log(eGFRcrea); post GWAS meta-analysis genomic control correction applied to <i>P</i> values and SEs.</p>*<p>While being uncovered in the younger samples, this locus showed consistent results in the non-diabetic group (combined-analysis <i>P</i> value 5.7×10⁻¹⁶) and in the overall population (<i>P</i> value 9.5×10⁻²²) - see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002584#pgen.1002584.s028" target="_blank">Tables S16</a> and <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002584#pgen.1002584.s022" target="_blank">S10</a> for additional details.</p>**<p>The direction test was performed in the overall dataset; the genomic control corrected <i>P</i> value from the direction test for the SNP rs2928148 was 4.0×10⁻⁷. In the combined analysis, the largest effect size (0.0054 on log eGFR in ml/min/1.73 m²) and the smallest <i>P</i> value (3.7×10⁻⁸) were observed in the non-diabetic group.</p>†<p>All results were confirmed by random-effect meta-analysis.</p

Genetic association and LD distribution of the <i>MPPED2</i> gene locus in European and African ancestry populations.

<p>Regional association plots in the CKDGen European ancestry discovery analysis (N = 74,354) (A) and in the CARe African ancestry discovery analysis (N = 8,110) (B). LD structure: comparison between the HapMap release II – CEU and YRI samples in the region included within +/−100 kb from the target SNP rs3925584 identified in the CKDGen GWAS. The green circle highlights a stream of high LD connecting the two blocks, indicating the presence of common haplotypes (C).</p

Interrogation of the six novel loci uncovered in the European ancestry (EA) individuals (CKDGen consortium) in individuals of African ancestry (AA) from the CARe consortium for the trait eGFRcrea.

<p>Ref./Non-Ref. All.: reference/non-reference alleles; RAF: reference allele frequency; SE: standard error.</p>*<p>Characteristics of the six lead SNPs in the EA individuals from the CKDGen consortium can be found in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1002584#pgen-1002584-t001" target="_blank">Table 1</a>.</p>§<p>The gene closest to the SNP is listed first and is in boldface if the SNP is located within the gene.</p>**<p>S = number of independent, typed SNPs interrogated.</p>†<p>No LD information available in the HapMap database between the target SNP and the best SNP in the DDX1 region.</p>‡<p>The SNP rs11078903 was not present in the CARe consortium database.</p

Genes of biological interest within 500 kb of lead SNPs associated with WC_adjBMI or WHR_adjBMI.

<p>Genes of biological interest within 500 kb of lead SNPs associated with WC_adjBMI or WHR_adjBMI.</p

Age-dependent BMI loci.

<p>Effect estimates (beta ±95CI) per standard deviation in BMI and risk allele for loci showing age-differences in men & women ≤50y compared to men & women >50y. Loci are ordered by greater magnitude of effect in men & women ≤50y compared to men & women >50y. (95%CI: 95% confidence interval; BMI: body mass index; SD: standard deviation, *Newly identified loci).</p

Forty-four WHR_adjBMI loci showing significant sex-differences.

<p>Chr: Chromosome; Pos: position; EAF: Effect Allele Frequency; EA: Effect allele; OA: Other allele</p><p>^a ‘Yes’ if the locus is mentioned as WHR_adjBMI locus for the first time</p><p>^b ‘Yes’ if the sex-difference in the effect on WHR_adjBMI is reported for the first time</p><p>^c Effect allele is according to the WHR_adjBMI increasing allele according to the associated sex.</p><p>The table shows the sex-specific (age-group combined) results, ordered by largest, positive effect in women to largest, negative effect in women. The age- and sex-specific results (four strata), more detailed information on the loci and on the screens for which they were detected are given in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s021" target="_blank">S5 Table</a></b>.</p

Power heatplots.

<p>Power for the combination of screens and gain through a priori filtering for varying configurations of effect sizes across the 4 strata. The figures illustrate (A) the power to detect age-difference, sex-difference or age-sex-difference in at least one of our scans (on <i>P</i>_{<i>agediff</i>}, <i>P</i>_{<i>sexdiff</i>} and <i>P</i>_{<i>agesexdiff</i>}, with and without a priori filtering); and (B) a power comparison, comparing approaches with and without a priori filtering on <i>P</i>_{<i>Overall</i>} < 1x10^-5. We here assume four equally sized strata and a total sample size of N = 300,000 (comparable to the sample size in our BMI analyses). We set b_F≤50y = 0.033 (corresponding to a known and mean BMI effect in <i>MAP2K5</i> region with R² = 0.037%), b_M>50y = 0, and vary b_F>50y and b_M≤50 on the axes. This strategy allows us to cover the most interesting and plausible interaction effects: Two-way interactions, such as (i) pure age-difference (b_≤50y = 0.033, b_>50y = 0) and (ii) pure sex-difference (b_F = 0.033, b_M = 0); and three-way interactions, such as (iii) extreme three-way interaction with opposite direction across AGE and SEX, (iv) 1-strata interaction (b_F≤50y = 0.033, b_F>50y = b_M≤50y = b_M>50y = 0), and (v) 3-strata interaction (b_F≤50y = b_F>50y = b_M≤50y = 0.033, b_M>50y = 0).</p

Fifteen BMI loci showing significant age-differences in adults ≤50y compared to adults >50y.

<p>Chr: Chromosome; Pos: position; EAF: Effect Allele Frequency; EA: Effect allele; OA: Other allele</p><p>^a ‘Yes’ if the locus is mentioned as BMI locus for the first time</p><p>^b Effect allele is according to the BMI increasing allele according to the associated sex.</p><p>The table shows the age-group specific (sex-combined) results, ordered by largest to smallest effect in adults ≤50y. All loci were detected by the screen on age-difference that included the a-priori filter on <i>P</i>_{<i>Overall</i>} < 10⁻⁵. The age- and sex-specific results (four strata) and more detailed information on the loci are given in <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005378#pgen.1005378.s020" target="_blank">S4 Table</a></b>.</p

Sex-dependent WHR_adjBMI loci.

<p>Effect estimates (beta ± 95CI) per standard deviation in WHR_adjBMI and risk allele for loci showing sex-differences in women compared to men. Loci are ordered by greater magnitude of effect in women compared to men. (95%CI: 95% confidence interval; SD: standard deviation. *Newly identified loci. † Newly identified sex-differences)</p