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Association of a fasting glucose genetic risk score with subclinical atherosclerosis: The Atherosclerosis Risk in Communities (ARIC) study.

Rasmussen-Torvik LJ, Li M, Kao WH, Couper D, Boerwinkle E, Bielinski SJ, Folsom AR, Pankow JS - Diabetes (2010)

Bottom Line: The FGGRS was significantly associated (P = 0.009) with mean IMT.The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT.Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third.

View Article: PubMed Central - PubMed

Affiliation: Department of Preventive Medicine, Northwestern University, Chicago, Illinois, USA. ljrtorvik@northwestern.edu

ABSTRACT

Objective: Elevated fasting glucose level is associated with increased carotid intima-media thickness (IMT), a measure of subclinical atherosclerosis. It is unclear if this association is causal. Using the principle of Mendelian randomization, we sought to explore the causal association between circulating glucose and IMT by examining the association of a genetic risk score with IMT.

Research design and methods: The sample was drawn from the Atherosclerosis Risk in Communities (ARIC) study and included 7,260 nondiabetic Caucasian individuals with IMT measurements and relevant genotyping. Components of the fasting glucose genetic risk score (FGGRS) were selected from a fasting glucose genome-wide association study in ARIC. The score was created by combining five single nucleotide polymorphisms (SNPs) (rs780094 [GCKR], rs560887 [G6PC2], rs4607517 [GCK], rs13266634 [SLC30A8], and rs10830963 [MTNR1B]) and weighting each SNP by its strength of association with fasting glucose. IMT was measured through bilateral carotid ultrasound. Mean IMT was regressed on the FGGRS and on the component SNPs, individually.

Results: The FGGRS was significantly associated (P = 0.009) with mean IMT. The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT. Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third.

Conclusions: The significant association of the FGGRS with IMT suggests a possible causal association of elevated fasting glucose with atherosclerosis, although it may be that these loci influence IMT through nonglucose pathways.

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Related in: MedlinePlus

Distribution of the FGGRS (A) and mean fasting glucose by FGGRS (B). FGGRS = {[(no. of rs780094 risk alleles) × 0.0463] + [(no. of rs560887 risk alleles) × 0.0685] + [(no. of rs4607517 risk alleles) × 0.0673] + [(no. of rs13266634 risk alleles) × 0.0433] + [(no. of rs10830963 risk alleles) × 0.0796]}/0.061. To create these plots, all individuals with an FGGRS <1 were included in the first category, all individuals with a FGGRS ≥1 but <2 were included in the second category, etc. Means of fasting glucose in B are adjusted for age, sex, and ARIC study center and presented with 95% CI.
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Figure 1: Distribution of the FGGRS (A) and mean fasting glucose by FGGRS (B). FGGRS = {[(no. of rs780094 risk alleles) × 0.0463] + [(no. of rs560887 risk alleles) × 0.0685] + [(no. of rs4607517 risk alleles) × 0.0673] + [(no. of rs13266634 risk alleles) × 0.0433] + [(no. of rs10830963 risk alleles) × 0.0796]}/0.061. To create these plots, all individuals with an FGGRS <1 were included in the first category, all individuals with a FGGRS ≥1 but <2 were included in the second category, etc. Means of fasting glucose in B are adjusted for age, sex, and ARIC study center and presented with 95% CI.

Mentions: All analyses were performed in SAS v9.1 (Cary, NC). To create the FGGRS, the number of risk (glucose-increasing) alleles from SNPs rs10830963, rs560887, rs4607517, rs780094, and rs13266634 was summed. To account for the differing effect sizes of the SNPs, the number of risk alleles from each SNP was multiplied by the predicted effect size from regression of baseline fasting glucose on that SNP (7). The total score was then divided by the average effect size to rescale the score with a possible range of 0–10 (the range of the possible number of glucose-increasing alleles for each individual). An equation for the calculation of the risk score can be found in Fig. 1.


Association of a fasting glucose genetic risk score with subclinical atherosclerosis: The Atherosclerosis Risk in Communities (ARIC) study.

Rasmussen-Torvik LJ, Li M, Kao WH, Couper D, Boerwinkle E, Bielinski SJ, Folsom AR, Pankow JS - Diabetes (2010)

Distribution of the FGGRS (A) and mean fasting glucose by FGGRS (B). FGGRS = {[(no. of rs780094 risk alleles) × 0.0463] + [(no. of rs560887 risk alleles) × 0.0685] + [(no. of rs4607517 risk alleles) × 0.0673] + [(no. of rs13266634 risk alleles) × 0.0433] + [(no. of rs10830963 risk alleles) × 0.0796]}/0.061. To create these plots, all individuals with an FGGRS <1 were included in the first category, all individuals with a FGGRS ≥1 but <2 were included in the second category, etc. Means of fasting glucose in B are adjusted for age, sex, and ARIC study center and presented with 95% CI.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3012190&req=5

Figure 1: Distribution of the FGGRS (A) and mean fasting glucose by FGGRS (B). FGGRS = {[(no. of rs780094 risk alleles) × 0.0463] + [(no. of rs560887 risk alleles) × 0.0685] + [(no. of rs4607517 risk alleles) × 0.0673] + [(no. of rs13266634 risk alleles) × 0.0433] + [(no. of rs10830963 risk alleles) × 0.0796]}/0.061. To create these plots, all individuals with an FGGRS <1 were included in the first category, all individuals with a FGGRS ≥1 but <2 were included in the second category, etc. Means of fasting glucose in B are adjusted for age, sex, and ARIC study center and presented with 95% CI.
Mentions: All analyses were performed in SAS v9.1 (Cary, NC). To create the FGGRS, the number of risk (glucose-increasing) alleles from SNPs rs10830963, rs560887, rs4607517, rs780094, and rs13266634 was summed. To account for the differing effect sizes of the SNPs, the number of risk alleles from each SNP was multiplied by the predicted effect size from regression of baseline fasting glucose on that SNP (7). The total score was then divided by the average effect size to rescale the score with a possible range of 0–10 (the range of the possible number of glucose-increasing alleles for each individual). An equation for the calculation of the risk score can be found in Fig. 1.

Bottom Line: The FGGRS was significantly associated (P = 0.009) with mean IMT.The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT.Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third.

View Article: PubMed Central - PubMed

Affiliation: Department of Preventive Medicine, Northwestern University, Chicago, Illinois, USA. ljrtorvik@northwestern.edu

ABSTRACT

Objective: Elevated fasting glucose level is associated with increased carotid intima-media thickness (IMT), a measure of subclinical atherosclerosis. It is unclear if this association is causal. Using the principle of Mendelian randomization, we sought to explore the causal association between circulating glucose and IMT by examining the association of a genetic risk score with IMT.

Research design and methods: The sample was drawn from the Atherosclerosis Risk in Communities (ARIC) study and included 7,260 nondiabetic Caucasian individuals with IMT measurements and relevant genotyping. Components of the fasting glucose genetic risk score (FGGRS) were selected from a fasting glucose genome-wide association study in ARIC. The score was created by combining five single nucleotide polymorphisms (SNPs) (rs780094 [GCKR], rs560887 [G6PC2], rs4607517 [GCK], rs13266634 [SLC30A8], and rs10830963 [MTNR1B]) and weighting each SNP by its strength of association with fasting glucose. IMT was measured through bilateral carotid ultrasound. Mean IMT was regressed on the FGGRS and on the component SNPs, individually.

Results: The FGGRS was significantly associated (P = 0.009) with mean IMT. The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT. Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third.

Conclusions: The significant association of the FGGRS with IMT suggests a possible causal association of elevated fasting glucose with atherosclerosis, although it may be that these loci influence IMT through nonglucose pathways.

Show MeSH
Related in: MedlinePlus