Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome.

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glucose intolerance 1 endocrinologydiseases
metabolic syndrome 10 endocrinologydiseases
obesity 28 endocrinologydiseases
phenylketonuria 1 endocrinologydiseases

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glucose intolerance 60385 Suez et al. [[138]]. In this study, an increase in the intake of sweeteners led to the development of glucose intolerance in the subgroup of individuals having a sensitive gut microbiota [[138]]. However, given the high dose
metabolic syndrome 1731 tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome . This review aims to discuss recent works in the field of precision nutrition analyzing most relevant
metabolic syndrome 5473 evidence for full implementation given its complexity, as will be reviewed below.Regarding obesity and metabolic syndrome , recent published studies focusing on gene-environment interactions have revealed important insights
metabolic syndrome 8424 isolation. In this regard, a recent work focused on the effect of the obesity-associated MC4R gene on metabolic syndrome has revealed a relevant gene-diet interaction with dietary patterns [[26]]. In this case-control study,
metabolic syndrome 8565 relevant gene-diet interaction with dietary patterns [[26]]. In this case-control study, participants with metabolic syndrome from the Tehran Lipid and Glucose Study [[27]] were randomly matched with controls by age and sex, leading
metabolic syndrome 9403 the highest score of the western dietary pattern had increased risk (odds ratio—OR) of developing metabolic syndrome (OR = 1.71 (1.04–2.41); Ptrend = 0.007), as compared to those having lower scores [[26]]. Similar
metabolic syndrome 43403 cytosine-phosphate-guanine (CpG) sites, common in VAT and BL, were shown to successfully discriminate men with or without metabolic syndrome [[100]]. These and other results suggest that BL methylation levels could be a good marker of VAT DNA
metabolic syndrome 55210 identified as potential risk factors for the development of several metabolic disorders including the metabolic syndrome , T2D and CVD [[127]]. In this regard, the previously discussed study of Zeevi et al. [[33]] is an example
metabolic syndrome 56560 intervention, mainly based on increasing fruit and vegetable consumption in young adults at risk for the metabolic syndrome . For that purpose, 36 participants were randomized into three intervention groups. The first one was
metabolic syndrome 57002 completed in 2019, preliminary results have suggested that individuals with a higher risk of developing metabolic syndrome also exhibited a higher Firmicutes to Bacteroidetes ratio before the intervention [[128],[129],[130]].
metabolic syndrome 57302 metabolic health, this type of trial is an example of group-based nutritional interventions (at-risk metabolic syndrome young adults). Studies like this have the potential of revealing novel biomarkers, both metabolomic
obesity 1525 at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored
obesity 5461 sufficient evidence for full implementation given its complexity, as will be reviewed below.Regarding obesity and metabolic syndrome, recent published studies focusing on gene-environment interactions have revealed
obesity 6043 regard, recent work by Goni et al. [[19]] analyzed the usefulness of a genetic risk score (GRS) on obesity prediction, and more interestingly, the impact of macronutrient intake in the predictive value of this
obesity 6326 genetic variants (according to the number of risk alleles for each variant) previously associated with obesity (rs9939609, FTO; rs17782313, MC4R; rs1801282, PPARG; rs1801133, MTHFR and rs894160, PLIN1) and lipid
obesity 7501 were reported by Rukh et al., where total protein intake was found to modulate GRS association with obesity in women (Pinteraction = 0.039) [[20]]. Other studies on gene-macronutrients interactions, in which
obesity 7880 [[21],[22],[23]], fried foods [[24]] or saturated fatty-acids [[25]] are also able to modulate the risk to develop obesity . Altogether, these results suggest that the accumulation of common polymorphisms at loci known to influence
obesity 8392 macronutrients intake considered in isolation. In this regard, a recent work focused on the effect of the obesity -associated MC4R gene on metabolic syndrome has revealed a relevant gene-diet interaction with dietary
obesity 14580 that nutrition science must face in next years to evolve in the context of an increasing prevalence of obesity and associated metabolic disorders, resulting largely from the wide-scale adoption of unhealthy feeding
obesity 30920 developing scheduled and personalized nutrition programs aimed to face metabolic disorders associated with obesity .4. Precision Physical Activity Physical Activity: A Key Factor to Proper Precision NutritionThere is
obesity 33986 have started to scrutinize the potential role of PA in previously detected genetic associations with obesity and related metabolic disturbances. For example, it has been reported that a sedentary behavior, estimated
obesity 34619 findings have also reported that the impact of gene variants within FTO gene, the first and most strongly obesity -associated gene [[73],[74]], on obesity development is in fact attenuated by PA, i.e., the increase
obesity 34659 gene variants within FTO gene, the first and most strongly obesity-associated gene [[73],[74]], on obesity development is in fact attenuated by PA, i.e., the increase in BMI is 76% more pronounced in inactive
obesity 34968 reported a protective effect of PA (assessed using self-administered questionnaires) on the impact of obesity -associated genetic variants in the form of aggregated GRS [[76],[77]]. Results from Li et al. [[76]]
obesity 35121 aggregated GRS [[76],[77]]. Results from Li et al. [[76]] revealed that the genetic predisposition to obesity in individuals with high-risk GRS could mitigated by higher levels of PA, as illustrated by BMI differences
obesity 35968 establish causal relationships between increased PA and decreased risk of genetic predisposition to develop obesity , or to use them in clinical practice, as reported by Ahmad et al. [[77]]. Likewise, a more recent GWAS
obesity 36321 suggesting that accounting for PA could facilitate the uncovering of novel biological determinants of obesity [[78]]. Nevertheless, the search for PA interactions with obesity-associated loci only provided significant
obesity 36387 novel biological determinants of obesity [[78]]. Nevertheless, the search for PA interactions with obesity -associated loci only provided significant results with the FTO gene, showing a decrease of 30% of FTO
obesity 37498 objectively measure PA levels has consistently revealed that both BMI-associated GRS [[80]] and FTO impact on obesity susceptibility [[81]] are attenuated by higher levels of objectively measured PA. With direct PA measurements,
obesity 37741 FTO-related work [[81]] are similar to previous findings [[75],[82]], but the attenuation of FTO impact on obesity -associated features, such as BMI and WC, is quantitatively more important. These findings could be explained,
obesity 40703 3). Complex diseases mean complex phenotypes. This is the case of most metabolic disorders, such as obesity , CVD or T2D. The development of new tools or methods with the ability to stratify and distinguish different
obesity 40976 mechanisms thus represents a challenge in the field of precision nutrition. In this regard, although obesity is a condition associated with increased risk of T2D, CVD and other metabolic complications, a significant
obesity 41629 tissue (VAT) accumulation and adipose tissue dysfunction are tightly related to the development of obesity -related metabolic complications [[94]], it has been proposed that the combined measure of WC and plasma
obesity 42620 [[94],[98]]. Assessment of VAT accumulation represents a challenge when stratifying subjects with abdominal obesity . In this regard, a recent study has shown that epigenetic factors, such as DNA methylation marks, could
obesity 42975 surrogate biomarkers in more accessible tissues such as blood, allowing a better characterization of obesity in addition to the traditional clinical outcomes, such as BMI or WC. Recent studies have also suggested
obesity 43814 Thus, knowledge of epigenetic variations predictive of metabolic complications among individuals with obesity could be of considerable relevance to the field of precision nutrition. For instance, recent studies
obesity 44303 be targeted in personalized nutritional programs focused on prevention, management and treatment of obesity .Robinson has defined deep phenotyping as the precise and comprehensive analysis of phenotypic abnormalities
obesity 45391 associated metabolic disturbances [[108]]. In this study, traditional (hypertension, dyslipidemia, obesity or inflammation status) and advanced phenotyping techniques (body composition by dual energy X-ray absorptiometry,
obesity 61780 NutritionGenetics have been frequently considered in association studies as an independent factor predisposing to obesity , increased adiposity, T2D and CVD [[143],[144],[145],[146]]. Both GWAS and candidate gene studies have
phenylketonuria 4074 sectors. On one hand, the hypolactasia diagnosis [[10]], the celiac disease ruling out [[11]] or the phenylketonuria screening [[12]], have allowed the implementation of tailored nutritional advices based on genetic makeup

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