Genetic risk score constructed using 14 susceptibility alleles for type 2 diabetes is associated with the early onset of diabetes and may predict the future requirement of insulin injections among Japanese individuals.
OBJECTIVE
We evaluated the clinical usefulness of a genetic risk score (GRS) based on 14 well-established variants for type 2 diabetes.


METHODS
We analyzed 14 SNPs at HHEX, CDKAL1, CDKN2B, SLC30A8, KCNJ11, IGF2BP2, PPARG, TCF7L2, FTO, KCNQ1, IRS-1, GCKR, UBE2E2, and C2CD4A/B in 1,487 Japanese individuals (724 patients with type 2 diabetes and 763 control subjects). A GRS was calculated according to the number of risk alleles by counting all 14 SNPs (T-GRS) as well as 11 SNPs related to β-cell function (β-GRS) and then assessing the association between each GRS and the clinical features.


RESULTS
Among the 14 SNPs, 4 SNPs were significantly associated with type 2 diabetes in the present Japanese sample (P < 0.0036). The T-GRS was significantly associated with type 2 diabetes (P = 5.9 × 10(-21)). Among the subjects with type 2 diabetes, the β-GRS was associated with individuals receiving insulin therapy (β = 0.0131, SE = 0.006, P = 0.0431), age at diagnosis (β = -0.608, SE = 0.204, P = 0.0029), fasting serum C-peptide level (β = -0.032, SE = 0.0140, P = 0.022), and C-peptide index (β = -0.031, SE = 0.012, P = 0.0125).


CONCLUSIONS
Our data suggest that the β-GRS is associated with reduced β-cell functions and may be useful for selecting patients who should receive more aggressive β-cell-preserving therapy.
First Department of Internal Medicine, Faculty of Medicine, Toyama University, Toyama, Japan. iwamino-tym@umin.ac.jp
Minoru
M
Iwata
Shiro
S
Maeda
Yutaka
Y
Kamura
Atsuko
A
Takano
Hiromi
H
Kato
Shihou
S
Murakami
Kiyohiro
K
Higuchi
Atsushi
A
Takahashi
Hayato
H
Fujita
Kazuo
K
Hara
Takashi
T
Kadowaki
Kazuyuki
K
Tobe
D048868:Adaptor Proteins, Signal Transducing / Q000235:genetics; D017668:Age of Onset; D000368:Aged; D000483:Alleles; D000071516:Alpha-Ketoglutarate-Dependent Dioxygenase FTO; D044466:Asian People; D027682:Cation Transport Proteins / Q000235:genetics; D051360:Cyclin-Dependent Kinase 5 / Q000235:genetics; D050762:Cyclin-Dependent Kinase Inhibitor p15 / Q000235:genetics; D003924:Diabetes Mellitus, Type 2 / Q000453:epidemiology* / Q000235:genetics*; D005260:Female; D020022:Genetic Predisposition to Disease / Q000235:genetics; D018398:Homeodomain Proteins / Q000235:genetics; D006801:Humans; D007328:Insulin / Q000627:therapeutic use*; D055504:Insulin Receptor Substrate Proteins / Q000235:genetics; D051657:KCNQ1 Potassium Channel / Q000235:genetics; D008297:Male; D008875:Middle Aged; D047495:PPAR gamma / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D024661:Potassium Channels, Inwardly Rectifying / Q000235:genetics; D011506:Proteins / Q000235:genetics; D058118:Transcription Factor 7-Like 2 Protein / Q000235:genetics; D014157:Transcription Factors / Q000235:genetics; D044763:Ubiquitin-Conjugating Enzymes / Q000235:genetics; D000075703:Zinc Transporter 8; D012359:tRNA Methyltransferases; D000099161:Kcnj11 Channel
D048868:Adaptor Proteins, Signal Transducing; D000071516:Alpha-Ketoglutarate-Dependent Dioxygenase FTO; D027682:Cation Transport Proteins; D051360:Cyclin-Dependent Kinase 5; D050762:Cyclin-Dependent Kinase Inhibitor p15; D018398:Homeodomain Proteins; D007328:Insulin; D055504:Insulin Receptor Substrate Proteins; D051657:KCNQ1 Potassium Channel; D047495:PPAR gamma; D024661:Potassium Channels, Inwardly Rectifying; D011506:Proteins; D058118:Transcription Factor 7-Like 2 Protein; D014157:Transcription Factors; D044763:Ubiquitin-Conjugating Enzymes; D000075703:Zinc Transporter 8; D012359:tRNA Methyltransferases; D000099161:Kcnj11 Channel; C493966:CDKN2B protein, human; C485100:GCKR protein, human; C078492:HHEX protein, human; C526292:IRS1 protein, human; C492522:SLC30A8 protein, human; C526492:FTO protein, human; C106347:UBE2E2 protein, human; C525110:CDKAL1 protein, human