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Genetic Effects on Longitudinal Changes from Healthy to Adverse Weight and Metabolic Status – The HUNT Study.

Kvaløy K, Holmen J, Hveem K, Holmen TL - PLoS ONE (2015)

Bottom Line: DRD2 was not associated with BMI on a cross-sectional level.When testing for association to longitudinal adverse developments with regard to blood pressure, blood lipids and glucose, only rs964184 (ZNF259/APOA5) was significantly associated to unfavourable triglyceride changes (OR: 1.66, 95% CI: 1.36-2.03, P = 5.7x10(-7), adj.Pleiotropic effects on metabolic traits, however, were observed for several genetic loci cross-sectionally, ZNF259/APOA5, LPL and GRB14 being the most important.

View Article: PubMed Central - PubMed

Affiliation: HUNT Research Center, Department of Public Health and General Practice, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway.

ABSTRACT

Introduction: The complexity of obesity and onset and susceptibility of cardio-metabolic disorders are still poorly understood and is addressed here through studies of genetic influence on weight gain and increased metabolic risk longitudinally.

Subjects/methods: Twenty seven previously identified obesity, eating disorder or metabolic risk susceptibility SNPs were tested for association with weight or metabolically related traits longitudinally in 3999 adults participating both in the HUNT2 (1995-97) and HUNT3 (2006-08) surveys. Regression analyses were performed with changes from normal weight to overweight/obesity or from metabolically healthy to adverse developments with regards to blood pressure, glucose, HDL cholesterol, triglycerides or metabolic syndrome as outcomes. Additionally, a sub-sample of 1380 adolescents was included for testing association of nine SNPs with longitudinal weight gain into young adulthood.

Results: The most substantial effect on BMI-based weight gain from normal to overweight/obesity in adults was observed for the DRD2 variant (rs6277)(OR: 0.79, 95% CI: 0.69-0.90, P = 3.9x10(-4), adj. P = 0.015). DRD2 was not associated with BMI on a cross-sectional level. In the adolescent sample, FTO (rs1121980) was associated with change to overweight at adulthood in the combined male-female sample (OR: 1.27, 95% CI: 1.09-1.49, P = 3.0x10(-3), adj. P = 0.019) and in females (OR: 1.53, 95% CI: 1.23-1.91, P = 1.8x10(-4), adj. P = 0.003). When testing for association to longitudinal adverse developments with regard to blood pressure, blood lipids and glucose, only rs964184 (ZNF259/APOA5) was significantly associated to unfavourable triglyceride changes (OR: 1.66, 95% CI: 1.36-2.03, P = 5.7x10(-7), adj. P = 0.001). Pleiotropic effects on metabolic traits, however, were observed for several genetic loci cross-sectionally, ZNF259/APOA5, LPL and GRB14 being the most important.

Conclusions: DRD2 exhibits effects on weight gain from normal weight to overweight/obesity in adults, while, FTO is associated to weight gain from adolescence to young adulthood. Unhealthy longitudinal triglyceride development is strongly affected by ZNF259/APOA. Our main finding, linking the DRD2 variant directly to the longitudinal weight gain observed, has not previously been identified. It suggests a genetic pre-disposition involving the dopaminergic signalling pathways known to play a role in food reward and satiety linked mechanisms.

No MeSH data available.


Related in: MedlinePlus

Flow diagram of individuals included in the adult longitudinal study.Overweight/obesity was defined as having a BMI ≥ 25 kg/m2 or as ≥ 94 cm 102 cm (male) and ≥ 80 (female) with regards to waist circumference (WC). Unhealthy blood pressure (BP) was defined as systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥ 85 mmHg, or antihypertensive drug treatment. Unhealthy blood glucose (GLU) level was defined as ≥7.0 mmol/l or use of or diabetes medical treatment and triglyceride (TG) level as ≥2.1 mmol/l (both cut-offs modified due to non-fasting measurements). An unhealthy HDL cholesterol (HDL-C) level was defined below <1.0 mmol/l (male) or <1.3 mmol/l (female). Metabolic syndrome (MetS) phenotype cut-offs were based on the original NCEP—ATP III definition taking into account WC, BP, GLU, HDL-C and TG levels. MetS-cases were those scoring below cut-off for all five measures at baseline, but above cut-off for at least three components at follow-up. Controls scored below cut-offs for all five measures both at base-line and at follow-up.
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pone.0139632.g001: Flow diagram of individuals included in the adult longitudinal study.Overweight/obesity was defined as having a BMI ≥ 25 kg/m2 or as ≥ 94 cm 102 cm (male) and ≥ 80 (female) with regards to waist circumference (WC). Unhealthy blood pressure (BP) was defined as systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥ 85 mmHg, or antihypertensive drug treatment. Unhealthy blood glucose (GLU) level was defined as ≥7.0 mmol/l or use of or diabetes medical treatment and triglyceride (TG) level as ≥2.1 mmol/l (both cut-offs modified due to non-fasting measurements). An unhealthy HDL cholesterol (HDL-C) level was defined below <1.0 mmol/l (male) or <1.3 mmol/l (female). Metabolic syndrome (MetS) phenotype cut-offs were based on the original NCEP—ATP III definition taking into account WC, BP, GLU, HDL-C and TG levels. MetS-cases were those scoring below cut-off for all five measures at baseline, but above cut-off for at least three components at follow-up. Controls scored below cut-offs for all five measures both at base-line and at follow-up.

Mentions: Individual changes over time from HUNT2 to HUNT3 were evaluated using ANOVA repeated measures (SPSS, version 20). Additionally, association between SNPs and changes from healthy to adverse metabolic status (HUNT2 to HUNT3) in individuals with cut-offs defined above for BP/antihypertensive medication, GLU/diabetes medication, HDL-C and TG were tested by logistic regression. Likewise, logistic regression was employed testing associations between genes and longitudinal changes from normal weight to overweight (HUNT2 to HUNT3). Controls were defined as participants categorized as healthy (below cut-off) with regard to the outcome variables both at baseline and follow-up, while cases were defined as those who displayed healthy values at baseline and above cut-off metabolically or categorized as overweight at follow-up. Participants not categorized as cases or controls were excluded from the analyses (study design outlined in Fig 1). PLINK Software was used for genetic analyses [33]. Nominal significance was considered at P<0.05 and for defining sex-specific interactions (SNP*sex). A PLINK-based permutation-based test (max(T)) with 1000 permutations per analysis was used in order to adjust for multiple testing of the SNPs (equals stringency of Bonferroni correction when single SNPs are tested).


Genetic Effects on Longitudinal Changes from Healthy to Adverse Weight and Metabolic Status – The HUNT Study.

Kvaløy K, Holmen J, Hveem K, Holmen TL - PLoS ONE (2015)

Flow diagram of individuals included in the adult longitudinal study.Overweight/obesity was defined as having a BMI ≥ 25 kg/m2 or as ≥ 94 cm 102 cm (male) and ≥ 80 (female) with regards to waist circumference (WC). Unhealthy blood pressure (BP) was defined as systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥ 85 mmHg, or antihypertensive drug treatment. Unhealthy blood glucose (GLU) level was defined as ≥7.0 mmol/l or use of or diabetes medical treatment and triglyceride (TG) level as ≥2.1 mmol/l (both cut-offs modified due to non-fasting measurements). An unhealthy HDL cholesterol (HDL-C) level was defined below <1.0 mmol/l (male) or <1.3 mmol/l (female). Metabolic syndrome (MetS) phenotype cut-offs were based on the original NCEP—ATP III definition taking into account WC, BP, GLU, HDL-C and TG levels. MetS-cases were those scoring below cut-off for all five measures at baseline, but above cut-off for at least three components at follow-up. Controls scored below cut-offs for all five measures both at base-line and at follow-up.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4596824&req=5

pone.0139632.g001: Flow diagram of individuals included in the adult longitudinal study.Overweight/obesity was defined as having a BMI ≥ 25 kg/m2 or as ≥ 94 cm 102 cm (male) and ≥ 80 (female) with regards to waist circumference (WC). Unhealthy blood pressure (BP) was defined as systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥ 85 mmHg, or antihypertensive drug treatment. Unhealthy blood glucose (GLU) level was defined as ≥7.0 mmol/l or use of or diabetes medical treatment and triglyceride (TG) level as ≥2.1 mmol/l (both cut-offs modified due to non-fasting measurements). An unhealthy HDL cholesterol (HDL-C) level was defined below <1.0 mmol/l (male) or <1.3 mmol/l (female). Metabolic syndrome (MetS) phenotype cut-offs were based on the original NCEP—ATP III definition taking into account WC, BP, GLU, HDL-C and TG levels. MetS-cases were those scoring below cut-off for all five measures at baseline, but above cut-off for at least three components at follow-up. Controls scored below cut-offs for all five measures both at base-line and at follow-up.
Mentions: Individual changes over time from HUNT2 to HUNT3 were evaluated using ANOVA repeated measures (SPSS, version 20). Additionally, association between SNPs and changes from healthy to adverse metabolic status (HUNT2 to HUNT3) in individuals with cut-offs defined above for BP/antihypertensive medication, GLU/diabetes medication, HDL-C and TG were tested by logistic regression. Likewise, logistic regression was employed testing associations between genes and longitudinal changes from normal weight to overweight (HUNT2 to HUNT3). Controls were defined as participants categorized as healthy (below cut-off) with regard to the outcome variables both at baseline and follow-up, while cases were defined as those who displayed healthy values at baseline and above cut-off metabolically or categorized as overweight at follow-up. Participants not categorized as cases or controls were excluded from the analyses (study design outlined in Fig 1). PLINK Software was used for genetic analyses [33]. Nominal significance was considered at P<0.05 and for defining sex-specific interactions (SNP*sex). A PLINK-based permutation-based test (max(T)) with 1000 permutations per analysis was used in order to adjust for multiple testing of the SNPs (equals stringency of Bonferroni correction when single SNPs are tested).

Bottom Line: DRD2 was not associated with BMI on a cross-sectional level.When testing for association to longitudinal adverse developments with regard to blood pressure, blood lipids and glucose, only rs964184 (ZNF259/APOA5) was significantly associated to unfavourable triglyceride changes (OR: 1.66, 95% CI: 1.36-2.03, P = 5.7x10(-7), adj.Pleiotropic effects on metabolic traits, however, were observed for several genetic loci cross-sectionally, ZNF259/APOA5, LPL and GRB14 being the most important.

View Article: PubMed Central - PubMed

Affiliation: HUNT Research Center, Department of Public Health and General Practice, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway.

ABSTRACT

Introduction: The complexity of obesity and onset and susceptibility of cardio-metabolic disorders are still poorly understood and is addressed here through studies of genetic influence on weight gain and increased metabolic risk longitudinally.

Subjects/methods: Twenty seven previously identified obesity, eating disorder or metabolic risk susceptibility SNPs were tested for association with weight or metabolically related traits longitudinally in 3999 adults participating both in the HUNT2 (1995-97) and HUNT3 (2006-08) surveys. Regression analyses were performed with changes from normal weight to overweight/obesity or from metabolically healthy to adverse developments with regards to blood pressure, glucose, HDL cholesterol, triglycerides or metabolic syndrome as outcomes. Additionally, a sub-sample of 1380 adolescents was included for testing association of nine SNPs with longitudinal weight gain into young adulthood.

Results: The most substantial effect on BMI-based weight gain from normal to overweight/obesity in adults was observed for the DRD2 variant (rs6277)(OR: 0.79, 95% CI: 0.69-0.90, P = 3.9x10(-4), adj. P = 0.015). DRD2 was not associated with BMI on a cross-sectional level. In the adolescent sample, FTO (rs1121980) was associated with change to overweight at adulthood in the combined male-female sample (OR: 1.27, 95% CI: 1.09-1.49, P = 3.0x10(-3), adj. P = 0.019) and in females (OR: 1.53, 95% CI: 1.23-1.91, P = 1.8x10(-4), adj. P = 0.003). When testing for association to longitudinal adverse developments with regard to blood pressure, blood lipids and glucose, only rs964184 (ZNF259/APOA5) was significantly associated to unfavourable triglyceride changes (OR: 1.66, 95% CI: 1.36-2.03, P = 5.7x10(-7), adj. P = 0.001). Pleiotropic effects on metabolic traits, however, were observed for several genetic loci cross-sectionally, ZNF259/APOA5, LPL and GRB14 being the most important.

Conclusions: DRD2 exhibits effects on weight gain from normal weight to overweight/obesity in adults, while, FTO is associated to weight gain from adolescence to young adulthood. Unhealthy longitudinal triglyceride development is strongly affected by ZNF259/APOA. Our main finding, linking the DRD2 variant directly to the longitudinal weight gain observed, has not previously been identified. It suggests a genetic pre-disposition involving the dopaminergic signalling pathways known to play a role in food reward and satiety linked mechanisms.

No MeSH data available.


Related in: MedlinePlus