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. 2014 Oct 28;9(10):e110890.
doi: 10.1371/journal.pone.0110890. eCollection 2014.

Interaction between genetic predisposition to adiposity and dietary protein in relation to subsequent change in body weight and waist circumference

Mikkel Z Ankarfeldt  1 , Sofus C Larsen  1 , Lars Ängquist  2 , Lise Lotte N Husemoen  3 , Nina Roswall  4 , Kim Overvad  5 , Marianne Uhre Jakobsen  6 , Jytte Halkjær  4 , Anne Tjønneland  4 , Allan Linneberg  3 , Ulla Toft  3 , Torben Hansen  7 , Oluf Pedersen  7 , Berit L Heitmann  8 , Arne Astrup  9 , Thorkild I A Sørensen  10
Affiliations

Interaction between genetic predisposition to adiposity and dietary protein in relation to subsequent change in body weight and waist circumference

Mikkel Z Ankarfeldt et al. PLoS One. .

Abstract

Background: Genetic predisposition to adiposity may interact with dietary protein in relation to changes of anthropometry.

Objective: To investigate the interaction between genetic predisposition to higher body mass index (BMI), waist circumference (WC) or waist-hip ratio adjusted for BMI (WHRBMI) and dietary protein in relation to subsequent change in body weight (ΔBW) or change in WC (ΔWC).

Design: Three different Danish cohorts were used. In total 7,054 individuals constituted the study population with information on diet, 50 single-nucleotide polymorphisms (SNPs) associated with BMI, WC or WHRBMI, as well as potential confounders. Mean follow-up time was ∼5 years. Four genetic predisposition-scores were based on the SNPs; a complete-score including all selected adiposity- associated SNPs, and three scores including BMI, WC or WHRBMI associated polymorphisms, respectively. The association between protein intake and ΔBW or ΔWC were examined and interactions between SNP-score and protein were investigated. Analyses were based on linear regressions using macronutrient substitution models and meta-analyses.

Results: When protein replaced carbohydrate, meta-analyses showed no associations with ΔBW (41.0 gram/y/5 energy% protein, [95% CI: -32.3; 114.3]) or ΔWC (<-0.1 mm/y/5 energy % protein, [-1.1; 1.1]). Similarly, there were no interactions for any SNP-scores and protein for either ΔBW (complete SNP-score: 1.8 gram/y/5 energy% protein/risk allele, [-7.0; 10.6]) or ΔWC (complete SNP-score: <0.1 mm/y/5 energy% protein/risk allele, [-0.1; 0.1]). Similar results were seen when protein replaced fat.

Conclusion: This study indicates that the genetic predisposition to general and abdominal adiposity, assessed by gene-scores, does not seem to modulate the influence of dietary protein on ΔBW or ΔWC.

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Conflict of interest statement

Competing Interests: MZA, SCL LÄ, LLNH, NR, KO, MUJ, JH, AT, AL, UT, TH, OP, BLH and TIAS have no conflicts of interest. AA is currently member of external scientific advisory boards for Global Dairy Platform and MacDonald’s (both USA), AA is member of McDonald’s Global Advisory Council in nutrition and health. The role is to critically review the company’s research and development plans in the area, and provide new insight with the nutrition area. AA is PI of research projects funded by Global Dairy Platform, the Danish Dairy Research Foundation and by Arla Foods A/S, Denmark. AA has received a sponsorship of congress attendance, and a honorarium for speaking at an industry-sponsored satellite symposia from National Cattlemen’s Beef Association, USA and Danone Inc, Europe. None of these grants supported the present study. The support by Novo Nordisk and The Danish Pharmaceutical Association were unconditional grants. None of the funders had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Figures

Figure 1
Figure 1. Interaction of SNP-scores and protein intake.
Average, yearly weight change (gram/y/5 E% protein/risk allele). A: protein replacing carbohydrate. B: protein replacing fat. SNP-score×protein interactions were calculated using linear regression and pooled estimates were calculated using random effect meta-analysis. The effect-estimates from the individual cohorts were weighted by the inverses of their variance (% weight). The results were adjusted for baseline weight, height, sex, smoking status, physical activity, education and menopausal status for women. Abbreviations: BMI-score, sum of body mass index associated risk-alleles; WC-score, sum of waist circumference associated risk-alleles; WHRBMI-score, sum of waist-hip ratio adjusted for BMI associated risk-alleles.
Figure 2
Figure 2. Interaction of SNP-scores and protein intake.
Average, yearly waist change (mm/y/5 E% protein/risk allele). A: protein replacing carbohydrate. B: protein replacing fat. SNP-score×protein interactions were calculated using linear regression and pooled estimates were calculated using random effect meta-analysis. The effect-estimates from the individual cohorts were weighted by the inverses of their variance (% weight). The results were adjusted for baseline waist circumference, height, sex, smoking status, physical activity, education, menopausal status for women and concurrent change in body weight. Abbreviations: BMI-score, sum of body mass index associated risk-alleles; WC-score, sum of waist circumference associated risk-alleles; WHRBMI-score, sum of waist-hip ratio adjusted for BMI associated risk-alleles.
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Grants and funding

This work is carried out as a part of the research program of Gene-Diet Interactions in Obesity (GENDINOB). GENDINOB is supported by the Danish Council for Strategic Research (Grant 09-067111). Data collection in the INTER99 study was supported economically by The Danish Medical Research Council, The Danish Centre for Evaluation and Health Technology Assessment, Novo Nordisk, Copenhagen County, The Danish Heart Foundation, The Danish Pharmaceutical Association, Augustinus foundation, Ib Henriksen foundation and Becket foundation. The support by Novo Nordisk and The Danish Pharmaceutical Association were unconditional grants. None of the funders had any role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.