Genetic predisposition to long-term nondiabetic deteriorations in glucose homeostasis: Ten-year follow-up of the GLACIER study.
OBJECTIVE
To assess whether recently discovered genetic loci associated with hyperglycemia also predict long-term changes in glycemic traits.


METHODS
Sixteen fasting glucose-raising loci were genotyped in middle-aged adults from the Gene x Lifestyle interactions And Complex traits Involved in Elevated disease Risk (GLACIER) Study, a population-based prospective cohort study from northern Sweden. Genotypes were tested for association with baseline fasting and 2-h postchallenge glycemia (N = 16,330), and for changes in these glycemic traits during a 10-year follow-up period (N = 4,059).


RESULTS
Cross-sectional directionally consistent replication with fasting glucose concentrations was achieved for 12 of 16 variants; 10 variants were also associated with impaired fasting glucose (IFG) and 7 were independently associated with 2-h postchallenge glucose concentrations. In prospective analyses, the effect alleles at four loci (GCK rs4607517, ADRA2A rs10885122, DGKB-TMEM195 rs2191349, and G6PC2 rs560887) were nominally associated with worsening fasting glucose concentrations during 10-years of follow-up. MTNR1B rs10830963, which was predictive of elevated fasting glucose concentrations in cross-sectional analyses, was associated with a protective effect on postchallenge glucose concentrations during follow-up; however, this was only when baseline fasting and 2-h glucoses were adjusted for. An additive effect of multiple risk alleles on glycemic traits was observed: a weighted genetic risk score (80th vs. 20th centiles) was associated with a 0.16 mmol/l (P = 2.4 × 10⁻⁶) greater elevation in fasting glucose and a 64% (95% CI: 33-201%) higher risk of developing IFG during 10 years of follow-up.


CONCLUSIONS
Our findings imply that genetic profiling might facilitate the early detection of persons who are genetically susceptible to deteriorating glucose control; studies of incident type 2 diabetes and discrete cardiovascular end points will help establish whether the magnitude of these changes is clinically relevant.
Renström
Frida
F
Department of Public Health and Clinical Medicine, Umeå University Hospital, Sweden.
Shungin
Dmitry
D
Johansson
Ingegerd
I
Florez
Jose C
JC
Hallmans
Göran
G
Hu
Frank B
FB
Franks
Paul W
PW
D001786:Blood Glucose / Q000378:metabolism; D001794:Blood Pressure; D015992:Body Mass Index; D002874:Chromosome Mapping; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000235:genetics; D005215:Fasting; D005260:Female; D005500:Follow-Up Studies; D020869:Gene Expression Profiling; D020022:Genetic Predisposition to Disease; D005947:Glucose / Q000378:metabolism*; D006706:Homeostasis; D006801:Humans; D006943:Hyperglycemia / Q000235:genetics*; D008297:Male; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide; D012016:Reference Values; D018570:Risk Assessment; D013997:Time Factors; D014280:Triglycerides / Q000097:blood
D001786:Blood Glucose; D014280:Triglycerides; D005947:Glucose