The association of parental genetic, lifestyle, and social determinants of health with offspring overweight

In the UK, the number of comorbidities seen in children has increased along with the worsening obesity rate. These comorbidities worsen into adulthood. Genomewide association studies have highlighted single nucleotide polymorphisms associated with the weight status of adults and offspring individually. To date, in the UK, parental genetic, lifestyle, and social determinants of health have not been investigated alongside one another as influencers of offspring weight status. A comprehensive obesity prevention scheme would commence prior to conception and involve parental intervention including all known risk factors. This current study aims to identify the proportion of overweight that can be explained by known parental risk factors, including genetic, lifestyle, and social determinants of health with offspring weight status in the UK. Methods: A crosssectional study was carried out on 123 parents. Parental and offspring anthropometric data and parental lifestyle and social determinants of health data were self-reported. Parental genetic data were collected by use of GeneFiX saliva collection vials and genotype were assessed for brain-derived neurotrophic factor (BDNF) gene rs6265, melanocortin 4 receptor (MC4R) gene rs17782313, transmembrane protein 18 (TMEM18) gene rs2867125, and serine/threonine-protein kinase (TNN13K) gene rs1514175. Associations were assessed between parental data and the weight status of offspring. Results: Maternal body mass index modestly predicted child weight status (p < 0.015; R2 = 0.15). More mothers of overweight children carried the MC4R rs17782313 risk allele (77.8%; p = 0.007) compared to mothers of normal-weight children. Additionally, fathers who were not Caucasian and parents who slept for < 7 h/night had a larger percentage of overweight children when compared to their counterparts (p = 0.039; p = 0.014, respectively). Conclusion: Associations exist between the weight status of offspring based solely on parental genetic, lifestyle, and social determinants of health data. Further research is required to appropriately address future interventions based on genetic and lifestyle risk groups on a pre-parent cohort

Genetic differences in fat taste sensitivity and dietary intake in a UK female cohort

Over the past decade, a potential sixth taste, fat taste (“oleogustus”), has been identified. Studies in adults and children of various ethnicities have demonstrated that both lifestyle and genetic factors may contribute to fat taste sensitivity (FTS). Data on females in the UK is limited. The aim of this study was to determine, using an ethnically similar, healthy, female cohort, whether known genotypes related to fat taste and dietary intake lead to differences in FTS. A cross-sectional study was carried out on a UK cohort of Caucasian females (32.7 ± 11.4 years, 23.7 ± 3.6 kg/m2). We report that FTS differed in individuals with differing genotypes; genotypes that have previously been associated with differences in dietary intake. Specifically, FTS was lower in rs1514175 Troponin I-Interacting Protein Kinase (TNNI3K) gene AA/AG genotype and was higher in rs6265 Brain Derived Neurotrophic Factor (BDNF) gene TT/CT genotype (both p < 0.05). We also report that participants in the rs1514175 TNNI3K AA/AG genotype group had a higher energy intake, total fat intake, and subsequently, higher monounsaturated fat and saturated fat intake when compared to the GG genotype (all p < 0.05). To our knowledge, this is the first study showing associations between genotypes that have been previously associated to dietary intake are also associated to FTS. Due to the heterogeneity of previous research and the infancy of fat taste research, further research is required on a larger, ethnically similar cohort

Unpacking ecosystem service bundles: towards predictive mapping of synergies and trade-offs between ecosystem services

Multiple ecosystem services (ES) can respond similarly to social and ecological factors to form bundles. Identifying key social-ecological variables and understanding how they co-vary to produce these consistent sets of ES may ultimately allow the prediction and modelling of ES bundles, and thus, help us understand critical synergies and trade-offs across landscapes. Such an understanding is essential for informing better management of multi-functional landscapes and minimising costly trade-offs. However, the relative importance of different social and biophysical drivers of ES bundles in different types of social-ecological systems remains unclear. As such, a bottom-up understanding of the determinants of ES bundles is a critical research gap in ES and sustainability science. Here, we evaluate the current methods used in ES bundle science and synthesize these into four steps that capture the plurality of methods used to examine predictors of ES bundles. We then apply these four steps to a cross-study comparison (North and South French Alps) of relationships between social-ecological variables and ES bundles, as it is widely advocated that cross-study comparisons are necessary for achieving a general understanding of predictors of ES associations. We use the results of this case study to assess the strengths and limitations of current approaches for understanding distributions of ES bundles. We conclude that inconsistency of spatial scale remains the primary barrier for understanding and predicting ES bundles. We suggest a hypothesis-driven approach is required to predict relationships between ES, and we outline the research required for such an understanding to emerge