A Gene Variant in CERS2 Is Associated with Rate of Increase in Albuminuria in Patients with Diabetes from ONTARGET and TRANSCEND

<div><p>Although albuminuria and subsequent advanced stage chronic kidney disease are common among patients with diabetes, the rate of increase in albuminuria varies among patients. Since genetic variants associated with estimated glomerular filtration rate (eGFR) were identified in cross sectional studies, we asked whether these variants were also associated with rate of increase in albuminuria among patients with diabetes from ONTARGET and TRANSCEND—randomized controlled trials of ramipril, telmisartan, both, or placebo. For 16 genetic variants associated with eGFR at a genome-wide level, we evaluated the association with annual rate of increase in albuminuria estimated from urine albumin:creatinine ratio (uACR). One of the variants (rs267734) was associated with rate of increase in albuminuria. The annual rate of increase in albuminuria among risk homozygotes (69% of the study population) was 11.3% (95%CI; 7.5% to 15.3%), compared with 5.0% (95%CI; 3.3% to 6.8%) for heterozygotes (27% of the population), and 1.7% (95%CI; −1.7% to 5.3%) for non-risk homozygotes (4% of the population); P = 0.0015 for the difference between annual rates in the three genotype groups. These estimates were adjusted for age, sex, ethnicity, and principal component of genetic heterogeneity. Among patients without albuminuria at baseline (uACR<30 mg/g), each risk allele was associated with 50% increased risk of incident albuminuria (OR = 1.50; 95%CI 1.15 to 1.95; P = 0.003) after further adjustment for traditional risk factors including baseline uACR and eGFR. The rs267734 variant is in almost perfect linkage-disequilibrium (r² = 0.94) with rs267738, a single nucleotide polymorphism encoding a glutamic acid to alanine change at position 115 of the ceramide synthase 2 (CERS2) encoded protein. However, it is unknown whether CERS2 function influences albuminuria. In conclusion, we found that rs267734 in CERS2 is associated with rate of increase in albuminuria among patients with diabetes and elevated risk of cardiovascular disease.</p></div

Association between SNPs and change in albuminuria.

<p>Results were adjusted for age, sex, 10 largest principal components of genetic variation and self-reported ethnicity (for “all ethnic groups” results).</p><p>Association between SNPs and change in albuminuria.</p

SNPs associated with eGFR in cross-sectional studies.

<p>LD, linkage disequilibrium.</p><p>SNPs associated with eGFR in cross-sectional studies.</p

Association between SNPs and baseline albuminuria.

<p>β is the expected change in log-transformed baseline albuminuria for each risk allele. Models are adjusted for age, sex, 10 largest principal components of genetic variation, and self-reported ethnicity.</p><p>Association between SNPs and baseline albuminuria.</p

Baseline characteristics.

<p>SD, standard deviation. IQR, inter-quartile range. NA, not applicable.</p><p>Baseline characteristics.</p

Association between SNPs and baseline eGFR.

<p>β is the expected change in log-transformed baseline eGFR for each risk allele. Models are adjusted for age, sex, 10 largest principal components of genetic variation, and self-reported ethnicity.</p><p>Association between SNPs and baseline eGFR.</p

Regional plot for the CERS2 locus.

<p>SNPs are plotted by association P value of linear mixed models adjusted for age, sex, and principal components of genetic variation for the association between SNP and annual rate of change in albuminuria. and genomic position (NCBI Build 36). The original hit (rs267734) is labeled. The magnitude of linkage disequilibrium (r²) between each SNP and rs267734 is indicated by the intensity of the red coloring. Estimates of recombination rates are shown by the blue line. Gene positions are indicated by green arrows. Gene names are labeled. Linkage disequilibrium and recombination rates were estimated from the Utah residents of Northern and Western European ancestry (CEU) HapMap population (release 22). Plots were prepared using SNAP <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106631#pone.0106631-Laviad1" target="_blank">[22]</a>. Panel A: P values adjusted for rs267734. Panel B: P values not adjusted for rs267734.</p

Twenty four SNPs associated with MI in Study 1 and Study 2

*<p>1 sided P value</p

Risk factors for MI in three case–control studies

†<p>Data available for 254 cases.</p>‡<p>Individuals with diabetes were excluded from control group.</p>§<p>Dyslipidemia was defined in Study 1 and Study 2 to be self-reported history of a physician diagnosis of dyslipidemia or the use of lipid lowering prescription medication(s) and defined in Study 3 to be the use of lipid lowering prescription medication(s), LDL cholesterol >129 mg/dL, triglycerides >149 mg/dL or HDL cholesterol <45 mg/dL .</p>||<p>Hypertension was defined in Study 1 and Study 2 to be a self–reported history of a physician diagnosis of hypertension or use of antihypertensive prescription medication(s) and defined in Study 3 to be the use of antihypertensive prescription medication(s), systolic blood pressure >160 mmHg, or diastolic blood pressure >90 mmHg.</p><p>NA; not applicable.</p

Baseline characteristics of study participants.

<p>± values are standard deviation.</p