運動和營養基因組研究中心

我們對基因組的理解已經取得了很大進展,但是還有更長的路要走。

我們透過運動和營養基因組研究中心,幫助將「未知」變成「已知」。

研究意味著進步。惠及每個人。

自2003年完成人類基因組計畫以來,基因組具有的潛力已經讓科學界和更廣泛的社區興奮不已。我們使用DNAFit的嚴格科學列入協議,已經確定了少量我們知道會影響運動和營養反應的基因變體。在運動和營養基因組研究中心,從發現新基因變體,到探索在我們健身和營養生活方式中利用基因的新方式,我們一直在進一步了解基因與我們訓練和飲食之間的明確關聯。

A genetic based algorithm for personalised resistance training

A genetic based algorithm for personalised resistance training

Jones et al 2016

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Marmite gene study

Marmite gene study

Roos et al 2017

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Caffeine gene study

Caffeine gene study

Pickering et al 2017

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Recovery speed white paper

Recovery speed white paper

Pickering et al 2017

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Exercise genetics: seeking clarity from noise

Exercise genetics: seeking clarity from noise

Pickering et al 2017

Read More

Understanding personalized training responses

Understanding personalized training responses

Pickering et al 2017

Read More

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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Exercise genetics: seeking clarity from noise

The potential of recent advances in genetics research to supplement elite sport decision-making has potentially extensive implications, but remains highly controversial. One potential application is the use of genetic information to enhance exercise prescription, thereby positively influencing athletic performance and public health domains. Recent research suggests that this is both feasible and potentially beneficial.

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Understanding personalized training responses

Traditional exercise prescription is based on the assumption that exercise adaptation is predictable and standardised across individuals. However, evidence has emerged in the past two decades demonstrating that large inter-individual variation exists regarding the magnitude and direction of adaption following exercise.

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