A genotype risk score predicts type 2 diabetes from young adulthood: The CARDIA study

J. L. Vassy; N. H. Durant; E. K. Kabagambe; M. R. Carnethon; L. J. Rasmussen-Torvik; M. Fornage; C. E. Lewis; D. S. Siscovick; J. B. Meigs

doi:10.1007/s00125-012-2637-7

A genotype risk score predicts type 2 diabetes from young adulthood: The CARDIA study

J. L. Vassy^*, N. H. Durant, E. K. Kabagambe, M. R. Carnethon, L. J. Rasmussen-Torvik, M. Fornage, C. E. Lewis, D. S. Siscovick, J. B. Meigs

^*Corresponding author for this work

Preventive Medicine

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Abstract

Aims/hypothesis: Genotype does not change over the life course and may thus facilitate earlier identification of individuals at high risk for type 2 diabetes. We hypothesised that a genotype score predicts incident type 2 diabetes from young adulthood and improves diabetes prediction models based on clinical risk factors alone. Methods: The Coronary Artery Risk Development in Young Adults (CARDIA) study followed young adults (aged 18-30 years, mean age 25) serially into middle adulthood. We used Cox regression to build nested prediction models for incident type 2 diabetes based on clinical risk factors assessed in young adulthood (age, sex, race, parental history of diabetes, BMI, mean arterial pressure, fasting glucose, HDL-cholesterol and triacylglyercol), without and with a 38-variant genotype score. Models were compared with C statistics and continuous net reclassification improvement indices (NRI). Results: Of 2,439 participants, 830 (34%) were black and 249 (10%) had a BMI ≥30 kg/m² at baseline. Over a mean 23.9 years of follow-up, 215 (8.8%) participants developed type 2 diabetes. The genotype score significantly predicted incident diabetes in all models, with an HR of 1.08 per risk allele (95% CI 1.04, 1.13) in the full model. The addition of the score to the full model modestly improved reclassification (continuous NRI 0.285; 95% CI 0.126, 0.433) but not discrimination (C statistics 0.824 and 0.829 in full models with and without score). Race-stratified analyses were similar. Conclusions/ interpretation: Knowledge of genotype predicts type 2 diabetes over 25 years in white and black young adults but may not improve prediction over routine clinical measurements.

Original language	English (US)
Pages (from-to)	2604-2612
Number of pages	9
Journal	Diabetologia
Volume	55
Issue number	10
DOIs	https://doi.org/10.1007/s00125-012-2637-7
State	Published - Oct 2012

Funding

Funding JLV is supported by National Institutes of Health (NIH) National Research Service Award grant T32 HP12706 from the Health Resources and Services Administration and the NIH Loan Repayment Program (NIDDK). JB Meigs is supported by NIH grants K24 DK080140 and R01 DK078616. CE Lewis is supported by NIH grant P60 DK07626 to the University of Alabama at Birmingham Diabetes Research and Training Center. The CARDIA study is supported by grant 5 R01 HL078972 from the National Heart Lung and Blood Institute (NHLBI) and was partially supported by contracts N01-HC-48047 (University of Alabama at Birmingham), N01-HC-48048 (University of Minnesota), N01-HC-48049 (Northwestern University), N01-HC-48050 (Kaiser Foundation Research Institute) and N01-HC-95095 (University of Alabama at Birmingham) from the NHLBI/NIH.

Keywords

Genetic susceptibility
Risk prediction
Type 2 diabetes
Young adults

ASJC Scopus subject areas

Internal Medicine
Endocrinology, Diabetes and Metabolism

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10.1007/s00125-012-2637-7

Cite this

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title = "A genotype risk score predicts type 2 diabetes from young adulthood: The CARDIA study",

abstract = "Aims/hypothesis: Genotype does not change over the life course and may thus facilitate earlier identification of individuals at high risk for type 2 diabetes. We hypothesised that a genotype score predicts incident type 2 diabetes from young adulthood and improves diabetes prediction models based on clinical risk factors alone. Methods: The Coronary Artery Risk Development in Young Adults (CARDIA) study followed young adults (aged 18-30 years, mean age 25) serially into middle adulthood. We used Cox regression to build nested prediction models for incident type 2 diabetes based on clinical risk factors assessed in young adulthood (age, sex, race, parental history of diabetes, BMI, mean arterial pressure, fasting glucose, HDL-cholesterol and triacylglyercol), without and with a 38-variant genotype score. Models were compared with C statistics and continuous net reclassification improvement indices (NRI). Results: Of 2,439 participants, 830 (34%) were black and 249 (10%) had a BMI ≥30 kg/m2 at baseline. Over a mean 23.9 years of follow-up, 215 (8.8%) participants developed type 2 diabetes. The genotype score significantly predicted incident diabetes in all models, with an HR of 1.08 per risk allele (95% CI 1.04, 1.13) in the full model. The addition of the score to the full model modestly improved reclassification (continuous NRI 0.285; 95% CI 0.126, 0.433) but not discrimination (C statistics 0.824 and 0.829 in full models with and without score). Race-stratified analyses were similar. Conclusions/ interpretation: Knowledge of genotype predicts type 2 diabetes over 25 years in white and black young adults but may not improve prediction over routine clinical measurements.",

keywords = "Genetic susceptibility, Risk prediction, Type 2 diabetes, Young adults",

author = "Vassy, {J. L.} and Durant, {N. H.} and Kabagambe, {E. K.} and Carnethon, {M. R.} and Rasmussen-Torvik, {L. J.} and M. Fornage and Lewis, {C. E.} and Siscovick, {D. S.} and Meigs, {J. B.}",

note = "Funding Information: Funding JLV is supported by National Institutes of Health (NIH) National Research Service Award grant T32 HP12706 from the Health Resources and Services Administration and the NIH Loan Repayment Program (NIDDK). JB Meigs is supported by NIH grants K24 DK080140 and R01 DK078616. CE Lewis is supported by NIH grant P60 DK07626 to the University of Alabama at Birmingham Diabetes Research and Training Center. The CARDIA study is supported by grant 5 R01 HL078972 from the National Heart Lung and Blood Institute (NHLBI) and was partially supported by contracts N01-HC-48047 (University of Alabama at Birmingham), N01-HC-48048 (University of Minnesota), N01-HC-48049 (Northwestern University), N01-HC-48050 (Kaiser Foundation Research Institute) and N01-HC-95095 (University of Alabama at Birmingham) from the NHLBI/NIH.",

year = "2012",

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doi = "10.1007/s00125-012-2637-7",

language = "English (US)",

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T1 - A genotype risk score predicts type 2 diabetes from young adulthood

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AU - Vassy, J. L.

AU - Durant, N. H.

AU - Kabagambe, E. K.

AU - Carnethon, M. R.

AU - Rasmussen-Torvik, L. J.

AU - Fornage, M.

AU - Lewis, C. E.

AU - Siscovick, D. S.

AU - Meigs, J. B.

N1 - Funding Information: Funding JLV is supported by National Institutes of Health (NIH) National Research Service Award grant T32 HP12706 from the Health Resources and Services Administration and the NIH Loan Repayment Program (NIDDK). JB Meigs is supported by NIH grants K24 DK080140 and R01 DK078616. CE Lewis is supported by NIH grant P60 DK07626 to the University of Alabama at Birmingham Diabetes Research and Training Center. The CARDIA study is supported by grant 5 R01 HL078972 from the National Heart Lung and Blood Institute (NHLBI) and was partially supported by contracts N01-HC-48047 (University of Alabama at Birmingham), N01-HC-48048 (University of Minnesota), N01-HC-48049 (Northwestern University), N01-HC-48050 (Kaiser Foundation Research Institute) and N01-HC-95095 (University of Alabama at Birmingham) from the NHLBI/NIH.

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N2 - Aims/hypothesis: Genotype does not change over the life course and may thus facilitate earlier identification of individuals at high risk for type 2 diabetes. We hypothesised that a genotype score predicts incident type 2 diabetes from young adulthood and improves diabetes prediction models based on clinical risk factors alone. Methods: The Coronary Artery Risk Development in Young Adults (CARDIA) study followed young adults (aged 18-30 years, mean age 25) serially into middle adulthood. We used Cox regression to build nested prediction models for incident type 2 diabetes based on clinical risk factors assessed in young adulthood (age, sex, race, parental history of diabetes, BMI, mean arterial pressure, fasting glucose, HDL-cholesterol and triacylglyercol), without and with a 38-variant genotype score. Models were compared with C statistics and continuous net reclassification improvement indices (NRI). Results: Of 2,439 participants, 830 (34%) were black and 249 (10%) had a BMI ≥30 kg/m2 at baseline. Over a mean 23.9 years of follow-up, 215 (8.8%) participants developed type 2 diabetes. The genotype score significantly predicted incident diabetes in all models, with an HR of 1.08 per risk allele (95% CI 1.04, 1.13) in the full model. The addition of the score to the full model modestly improved reclassification (continuous NRI 0.285; 95% CI 0.126, 0.433) but not discrimination (C statistics 0.824 and 0.829 in full models with and without score). Race-stratified analyses were similar. Conclusions/ interpretation: Knowledge of genotype predicts type 2 diabetes over 25 years in white and black young adults but may not improve prediction over routine clinical measurements.

AB - Aims/hypothesis: Genotype does not change over the life course and may thus facilitate earlier identification of individuals at high risk for type 2 diabetes. We hypothesised that a genotype score predicts incident type 2 diabetes from young adulthood and improves diabetes prediction models based on clinical risk factors alone. Methods: The Coronary Artery Risk Development in Young Adults (CARDIA) study followed young adults (aged 18-30 years, mean age 25) serially into middle adulthood. We used Cox regression to build nested prediction models for incident type 2 diabetes based on clinical risk factors assessed in young adulthood (age, sex, race, parental history of diabetes, BMI, mean arterial pressure, fasting glucose, HDL-cholesterol and triacylglyercol), without and with a 38-variant genotype score. Models were compared with C statistics and continuous net reclassification improvement indices (NRI). Results: Of 2,439 participants, 830 (34%) were black and 249 (10%) had a BMI ≥30 kg/m2 at baseline. Over a mean 23.9 years of follow-up, 215 (8.8%) participants developed type 2 diabetes. The genotype score significantly predicted incident diabetes in all models, with an HR of 1.08 per risk allele (95% CI 1.04, 1.13) in the full model. The addition of the score to the full model modestly improved reclassification (continuous NRI 0.285; 95% CI 0.126, 0.433) but not discrimination (C statistics 0.824 and 0.829 in full models with and without score). Race-stratified analyses were similar. Conclusions/ interpretation: Knowledge of genotype predicts type 2 diabetes over 25 years in white and black young adults but may not improve prediction over routine clinical measurements.

KW - Genetic susceptibility

KW - Risk prediction

KW - Type 2 diabetes

KW - Young adults

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A genotype risk score predicts type 2 diabetes from young adulthood: The CARDIA study

Abstract

Funding

Keywords

ASJC Scopus subject areas

UN SDGs

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