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A genetic based algorithm for personalised resistance training

For this study the team from the Exercise & Nutritional Genomics Research Centre looked at whether the DNAFit Peak Performance Algorithm ™ could be used to give us a better idea of how to design the optimal resistance training program for an individual, using their genetic profile.

Association studies have identi ed dozens of genetic variants linked to training responses and sport-related traits. However, no intervention studies utilizing the idea of personalised training based on athlete’s genetic pro le have been conducted. Here we propose an algorithm that allows achieving greater results in response to high- or low-intensity resistance training programs by predicting athlete’s potential for the development of power and endurance qualities with the panel of 15 performance-associated gene polymorphisms.

Our results indicate that matching the individual’s genotype with the appropriate training modality leads to more effective resistance training. The developed algorithm may be used to guide individualised resistance-training interventions.

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Genome Wide Association Studies Identify 15 Genetic Markers Associated with Marmite Taste Preference

Marmite, a yeast extract, is a popular food eaten around the world - to which individuals have commonly considered themselves either “lovers” or “haters”. In this research, we aimed to determine whether this food preference has a genetic basis. We performed a genome-wide association study (GWAS) for Marmite taste preference using genotype and questionnaire data from a cohort of 261 healthy adults. There is evidence in the nutrigenomics literature showing that there is a genetic basis for human taste perception. In particular that single nucleotide polymorphisms (SNPs) in taste receptor genes are associated with bitter tasting ability and umami tasting ability.

In this research, the Exercise and Nutritional Genomics Research Centre found that a number of genetic variants were correlated with a user’s preference for ‘loving’ or ‘hating’ Marmite, exploring the genetic factors around taste preference for this iconic food brand.

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Are the Current Guidelines on Caffeine Use in Sport Optimal for Everyone?

Caffeine use is widespread in sport, with a strong evidence base demonstrating its effect on performance. Based on existing research, current guidelines recommend ingestion of 3–9 mg/kg approximately 60 min prior to exercise. However, the magnitude of performance enhancement following caffeine ingestion differs substantially between individuals, with the spectrum of responses differing greatly. These inter-individual response distinctions are a result of a number of factors, including an individual’s genetic profile. In this review, we focus on exploring the genetic factors that have an impact on our caffeine response, looking at common variations in two genes - CYP1A2 and ADORA2A.

When we take individual response into account, the general guidelines on caffeine use appear to be inadequate for recommendations in elite sport. In this review, we look at how clearer understanding of the factors underpinning inter-individual variation potentially allows a more nuanced, individual and context-specific customisation of caffeine ingestion guidelines, specific to an individual’s biology, history, and competitive situation. Finally, we identify current knowledge deficits in this area, along with future associated research questions.

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Recovery speed white paper

Training causes a number of physical challenges the body which cause the improvements we see from exercise. There is a fine balancing act between not enough challenge, which leads to no improvement from exercise, and too much challenge, which can lead to under-recovery, illness, and injury. Whilst most exercise research focuses on the training process itself, far less is focused on exercise recovery. We also know that differences in our genes can determine how quickly we recover from exercise. In this study, we put 18 male soccer players through a sprint session, and monitored how well they recovered. What we found is that those predicted by the DNAFit Recovery Algorithm to have a slower recovery speed did indeed have a slower rate of recovery than those with a higher predicted recovery speed. These results illustrate the use of the DNAFit recovery algorithm in predicting the speed of recovery to a training session.

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运动与营养基因组学研究中心

我们对基因组学的理解已有显著进展,但仍有很多东西需要学习。

凭借运动与营养基因组学研究中心,我们正在将“不知道”变成“知道”。

研究手段日益发展。为了每一个人。

自 2003 年人类基因组计划完成以来,基因所蕴含的潜力令科学界及更广泛的社区激动不已。遵守 DNAFit 严格的科学标准,我们确定了已知会影响我们对运动和营养的反应的少数遗传变异。在运动与营养基因组学研究中心,我们正在进一步了解基因具体如何与我们的训练和饮食相互作用,从发现新的基因变异,到探索在健康和营养生活方式中使用遗传信息的新方法。

基于基因的算法用于个体化阻力训练

Jones 等,2016

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Marmite gene study

Roos et al 2017

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Caffeine gene study

Pickering et al 2017

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Recovery speed white paper

Pickering et al 2017

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