In the Headlines – ‘Smart cities’ can improve individual and community-wide health, but pulling it off is no easy feat.
Identification of a TMEM182 rs141764639 polymorphism associated with central obesity by regulating tumor necrosis factor-α in a Korean population
This study aimed to “investigate the effect of a single nucleotide polymorphism (SNP) in transmembrane protein 182 (TMEM182) on the risk of having central obesity and the related phenotype”, in a Korean population. The results have shown that “the polymorphism of TMEM182 rs141764639 might have an effect on the incidence of central obesity in the Korean population by interacting with the upregulation of TNF-α, a proinflammatory cytokine”.
Leptin gene polymorphism (rs 7799039;G2548A) is associated with changes in lipid profile during a partial meal‐replacement hypocaloric diet
This study aimed to analyse the effects of the rs7799039 genetic variant of the LEP gene on metabolic parameters after weight loss secondary to a partial meal‐replacement (pMR) hypocaloric diet. Subjects with an A allele of the rs7799039 variant in the LEPR gene showed a significant improvement in low‐density lipoprotein‐cholesterol and triglycerides levels after weight loss secondary to a pMR hypocaloric diet.
This study “examined associations between carbohydrate (CHO) and fat (FAT) intake, as percentages of total diet energy, and the CHO/FAT ratio with CPT1A-cg00574958, and the risk of metabolic diseases in 3 populations (Genetics of Lipid Lowering Drugs and Diet Network, n = 978; Framingham Heart Study, n = 2331; and REgistre GIroní del COR study, n = 645)”. The results “confirmed strong associations of cg00574958 methylation with metabolic phenotypes (BMI, triglyceride, glucose) and diseases in all 3 populations”. Also, “the CHO intake and CHO/FAT ratio were positively associated with cg00574958 methylation, whereas FAT intake was negatively correlated (…) Furthermore, CPT1A mRNA expression was negatively associated with CHO intake, and positively associated with FAT intake, and metabolic phenotypes. Mediation analysis supports the hypothesis that CHO intake induces CPT1A methylation, hence reducing the risk of metabolic diseases, whereas FAT intake inhibits CPT1A methylation, thereby increasing the risk of metabolic diseases”.
A comparison of a ketogenic diet with a LowGI/nutrigenetic diet over 6 months for weight loss and 18-month follow-up
This study performed on 114 overweight and obese subjects compared the effects of a standardized ketogenic diet (n = 53), with a personalised low-glycemic index (GI) nutrigenetic diet utilising information from 28 single nucleotide polymorphisms (n = 61), during 24 weeks with additional monitorization of 18 months. The results showed that: “After 24 weeks, the keto group lost more weight: − 26.2 ± 3.1 kg vs − 23.5 ± 6.4 kg. However, at 18-month follow up, the subjects in the low-GI nutrigenetic diet had lost significantly more weight (− 27.5 ± 8.9 kg) than those on the ketogenic diet who had regained some weight (− 19.4 ± 5.0 kg). Additionally, after the 24-week diet and 18-month follow up the low-GI nutrigenetic diet group had significantly greater improvements in total cholesterol (ketogenic − 35.4 ± 32.2 mg/dl; low-GI nutrigenetic − 52.5 ± 24.3 mg/dl), HDL cholesterol (ketogenic + 4.7 ± 4.5 mg/dl; low-GI nutrigenetic + 11.9 ± 4.1 mg/dl), and fasting glucose (ketogenic − 13.7 ± 8.4 mg/dl; low-GI nutrigenetic − 24.7 ± 7.4 mg/dl). These findings demonstrate that the ketogenic group experienced enhanced weight loss during the 24-week dietary intervention. However, at 18-month follow up, the personalised nutrition group (lowGI/NG) lost significantly more weight and experienced significantly greater improvements in measures of cholesterol and blood glucose”.
The present study described qualitatively the experience of using a portable gluten sensor for 15 adults and 15 adolescents with coeliac disease participating in a 3‐month pilot clinical trial. Participants liked that the portable gluten sensor provided extra assurance to check foods presented as gluten‐free, the convenient size and portability, the added sense of control, and overall peace‐of‐mind. Participants disliked having attention drawn to them when using the sensor and feeling as if they were deterring others from eating. Participants also disliked the physical difficulty associated with using the capsules, questionable accuracy and the inability to test fermented foods.
Knowledge: 39% said that they have heard of the concept of nutrition genetic testing but only 11% say that they have conducted any form of research. When defining nutrition genetic testing, and how such information is something that can reduce the risk of disease and illness, 38% of global consumers say that they would be willing to use such technology;
Confidence: 51% said that they would not trust such information and 49% do not even believe health issues can be predicted before they occur.
Data privacy: 64% admit that they would be conscious of third parties holding sensitive information regarding their genetics.