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Background: The liking for sweet taste is a powerful driver for consuming added sugars, and therefore, understanding how sweet liking is formed is a critical step in devising strategies to lower added sugars consumption. However, current research on the influence of genetic and environmental factors on sweet liking is mostly based on research conducted with individuals of European ancestry. Whether these results can be generalized to people of other ancestry groups warrants investigation. Methods: We will determine the differences in allele frequencies in sweet-related genetic variants and their effects on sweet liking in 426 adults of either African or East Asian ancestry, who have the highest and lowest average added sugars intake, respectively, among ancestry groups in the U.S. We will collect information on participants' sweet-liking phenotype, added sugars intake (sweetness exposure), anthropometric measures, place-of-birth, and for immigrants, duration of time living in the U.S. and age when immigrated. Ancestry-specific polygenic scores of sweet liking will be computed based on the effect sizes of the sweet-related genetic variants on the sweet-liking phenotype for each ancestry group. The predictive validity of the polygenic scores will be tested using individuals of African and East Asian ancestry from the UK Biobank. We will also compare sweet liking between U.S.-born individuals and immigrants within each ancestry group to test whether differences in environmental sweetness exposure during childhood affect sweet liking in adulthood. Discussion: Expanding genetic research on taste to individuals from ancestry groups traditionally underrepresented in such research is consistent with equity goals in sensory and nutrition science. Findings from this study will help in the development of a more personalized nutrition approach for diverse populations. Trial registration: This protocol has been preregistered with the Center for Open Science (https://doi.org/10.17605/OSF.IO/WPR9E). [ABSTRACT FROM AUTHOR]

Aims: In 2019, the Australian Academy of Science in collaboration with the nutrition community published the decadal plan for the science of nutrition. This article aims to review progress towards each of its pillar goals (societal determinants, nutrition mechanisms, precision and personalised nutrition, and education and training) and two enabling platforms (a national data capability and a trusted voice for nutrition science), prioritise actions, and conceptualise program logic implementation models. This process also brought together public health nutrition researchers to reflect on societal determinants of health, and advise how the next 5 years of the decadal plan could reflect contemporary issues. Methods: Two engagement events, in 2023, brought together experienced and mid‐ and early‐career nutrition professionals for co‐creation of implementation logic models. Results: One hundred and nine early and mid‐career professionals were involved. A revised model for the decadal plan pillars emerged from synthesis of all logic models. This new model integrated the precision and personalised nutrition pillar with nutrition mechanisms pillar. These combined pillars build towards the national data capability enabling platform and created new cross‐cutting themes for education and training. The need arose for greater focus on respectful engagement with Aboriginal and Torres Strait Islander communities and sustained effort to build cross‐disciplinary collaboration to realise the plan's societal determinants goals. A new alliance for nutrition science is proposed to become a unified advocacy voice and build trust in nutrition professionals. Conclusions: A programmatic approach provides a road map for implementing the decadal plan for the final 5 years. [ABSTRACT FROM AUTHOR]

Key Points: Question: Is the association between lower birth weight and offspring neurodevelopmental difficulties causal? Findings: In this conventional epidemiological cohort study of 46 970 offspring, lower birth weight was associated with neurodevelopmental difficulties across various offspring ages. However, mendelian randomization causal analyses of 44 134 mother-child dyads did not find evidence for a causal association between intrauterine growth (with maternal genetic factors influencing fetal growth as a proxy) and offspring neurodevelopmental difficulties. Meaning: This study found that maternal factors influencing intrauterine growth do not appear to drive the observational association between lower birth weight and offspring neurodevelopmental difficulties. Importance: Conventional epidemiological analyses have suggested that lower birth weight is associated with later neurodevelopmental difficulties; however, it is unclear whether this association is causal. Objective: To investigate the relationship between intrauterine growth and offspring neurodevelopmental difficulties. Design, Setting, and Participants: MoBa is a population-based pregnancy cohort that recruited pregnant women from June 1999 to December 2008 included approximately 114 500 children, 95 200 mothers, and 75 200 fathers. Observational associations between birth weight and neurodevelopmental difficulties were assessed with a conventional epidemiological approach. Mendelian randomization analyses were performed to investigate the potential causal association between maternal allele scores for birth weight and offspring neurodevelopmental difficulties conditional on offspring allele scores. Exposures: Birth weight and maternal allele scores for birth weight (derived from genetic variants robustly associated with birth weight) were the exposures in the observational and mendelian randomization analyses, respectively. Main Outcomes and Measures: Clinically relevant maternal ratings of offspring neurodevelopmental difficulties at 6 months, 18 months, 3 years, 5 years, and 8 years of age assessing language and motor difficulties, inattention and hyperactivity-impulsivity, social communication difficulties, and repetitive behaviors. Results: The conventional epidemiological sample included up to 46 970 offspring, whereas the mendelian randomization sample included up to 44 134 offspring (median offspring birth year, 2005 [range, 1999-2009]; mean [SD] maternal age at birth, 30.1 [4.5] years; mean [SD] paternal age at birth, 32.5 [5.1] years). The conventional epidemiological analyses found evidence that birth weight was negatively associated with several domains at multiple offspring ages (outcome of autism-related trait scores: Social Communication Questionnaire [SCQ]–full at 3 years, β = −0.046 [95% CI, −0.057 to −0.034]; SCQ–Restricted and Repetitive Behaviors subscale at 3 years, β = −0.049 [95% CI, −0.060 to −0.038]; attention-deficit/hyperactivity disorder [ADHD] trait scores: Child Behavior Checklist [CBCL]–ADHD subscale at 18 months, β = −0.035 [95% CI, −0.045 to −0.024]; CBCL-ADHD at 3 years, β = −0.032 [95% CI, −0.043 to −0.021]; CBCL-ADHD at 5 years, β = −0.050 [95% CI, −0.064 to −0.037]; Rating Scale for Disruptive Behavior Disorders [RS-DBD]–ADHD at 8 years, β = −0.036 [95% CI, −0.049 to −0.023]; RS-DBD–Inattention at 8 years, β = −0.037 [95% CI, −0.050 to −0.024]; RS-DBD–Hyperactive-Impulsive Behavior at 8 years, β = −0.027 [95% CI, −0.040 to −0.014]; Conners Parent Rating Scale–Revised [Short Form] at 5 years, β = −0.041 [95% CI, −0.054 to −0.028]; motor scores: Ages and Stages Questionnaire–Motor Difficulty [ASQ-MOTOR] at 18 months, β = −0.025 [95% CI, −0.035 to −0.015]; ASQ-MOTOR at 3 years, β = −0.029 [95% CI, −0.040 to −0.018]; and Child Development Inventory–Gross and Fine Motor Skills at 5 years, β = −0.028 [95% CI, −0.042 to −0.015]). Mendelian randomization analyses did not find any evidence for an association between maternal allele scores for birth weight and offspring neurodevelopmental difficulties. Conclusions and Relevance: This study found that the maternal intrauterine environment, as proxied by maternal birth weight genetic variants, is unlikely to be a major determinant of offspring neurodevelopmental outcomes. This cohort study investigates the association between lower birth weight and neurodevelopmental difficulties, as well as the causal association of intrauterine growth with measures of offspring neurodevelopmental difficulties. [ABSTRACT FROM AUTHOR]

The relationship between lifestyles and cardiometabolic outcomes varies between individuals. In 382,275 UK Biobank Europeans, we investigate how lifestyles interact with polygenic scores (PGS) of cardiometabolic risk factors. We identify six interactions (PGS for body mass index with meat diet, physical activity, sedentary behaviour and insomnia; PGS for high-density lipoprotein cholesterol with sedentary behaviour; PGS for triglycerides with meat diet) in multivariable linear regression models including an interaction term and show stronger associations between lifestyles and cardiometabolic risk factors among individuals with high PGSs than those with low PGSs. Genome-wide interaction analyses pinpoint three genetic variants (FTO rs72805613 for BMI; CETP rs56228609 for high-density lipoprotein cholesterol; TRIB2 rs4336630 for triglycerides; PInteraction < 5 × 10−8). The associations between lifestyles and cardiometabolic risk factors differ between individuals grouped by the genotype of these variants, with the degree of differences being similar to that between individuals with high and low values for the corresponding PGSs. This study demonstrates that associations between lifestyles and cardiometabolic risk factors can differ between individuals based upon their genetic profiles. It further suggests that genetic variants with interaction effects contribute more to such differences compared to those without interaction effects, which has potential implications for developing PGSs for personalised intervention. [ABSTRACT FROM AUTHOR]

Background: Coffee consumption has been associated with several adverse pregnancy outcomes, although data from randomized-controlled trials are lacking. We investigate whether there is a causal relationship between coffee consumption and miscarriage, stillbirth, birthweight, gestational age and pre-term birth using Mendelian randomization (MR).Methods: A two-sample MR study was performed using summary results data from a genome-wide association meta-analysis of coffee consumption (N = 91 462) from the Coffee and Caffeine Genetics Consortium. Outcomes included self-reported miscarriage (N = 49 996 cases and 174 109 controls from a large meta-analysis); the number of stillbirths [N = 60 453 from UK Biobank (UKBB)]; gestational age and pre-term birth (N = 43 568 from the 23andMe, Inc cohort) and birthweight (N = 297 356 reporting own birthweight and N = 210 248 reporting offspring's birthweight from UKBB and the Early Growth Genetics Consortium). Additionally, a one-sample genetic risk score (GRS) analysis of coffee consumption in UKBB women (N up to 194 196) and the Avon Longitudinal Study of Parents and Children (N up to 6845 mothers and 4510 children) and its relationship with offspring outcomes was performed.Results: Both the two-sample MR and one-sample GRS analyses showed no change in risk of sporadic miscarriages, stillbirths, pre-term birth or effect on gestational age connected to coffee consumption. Although both analyses showed an association between increased coffee consumption and higher birthweight, the magnitude of the effect was inconsistent.Conclusion: Our results suggest that coffee consumption during pregnancy might not itself contribute to adverse outcomes such as stillbirth, sporadic miscarriages and pre-term birth or lower gestational age or birthweight of the offspring. [ABSTRACT FROM AUTHOR]

Maternal genetic effects can be defined as the effect of a mother's genotype on the phenotype of her offspring, independent of the offspring's genotype. Maternal genetic effects can act via the intrauterine environment during pregnancy and/or via the postnatal environment. In this manuscript, we present a simple extension to the basic adoption design that uses structural equation modelling (SEM) to partition maternal genetic effects into prenatal and postnatal effects. We examine the power, utility and type I error rate of our model using simulations and asymptotic power calculations. We apply our model to polygenic scores of educational attainment and birth weight associated variants, in up to 5,178 adopted singletons, 943 trios, 2687 mother-offspring pairs, 712 father-offspring pairs and 347,980 singletons from the UK Biobank. Our results show the expected pattern of maternal genetic effects on offspring birth weight, but unexpectedly large prenatal maternal genetic effects on offspring educational attainment. Sensitivity and simulation analyses suggest this result may be at least partially due to adopted individuals in the UK Biobank being raised by their biological relatives. We show that accurate modelling of these sorts of cryptic relationships is sufficient to bring type I error rate under control and produce asymptotically unbiased estimates of prenatal and postnatal maternal genetic effects. We conclude that there would be considerable value in following up adopted individuals in the UK Biobank to determine whether they were raised by their biological relatives, and if so, to precisely ascertain the nature of these relationships. These adopted individuals could then be incorporated into informative statistical genetics models like the one described in our manuscript to further elucidate the genetic architecture of complex traits and diseases. [ABSTRACT FROM AUTHOR]

Observational epidemiological studies have reported that higher maternal blood pressure (BP) during pregnancy is associated with increased future risk of offspring cardiometabolic disease. However, it is unclear whether this association represents a causal relationship through intrauterine mechanisms. We used a Mendelian randomization (MR) framework to examine the relationship between unweighted maternal genetic scores for systolic BP and diastolic BP and a range of cardiometabolic risk factors in the offspring of up to 29 708 genotyped mother-offspring pairs from the UKB study (UK Biobank) and the HUNT study (Trøndelag Health). We conducted similar analyses in up to 21 423 father-offspring pairs from the same cohorts. We confirmed that the BP-associated genetic variants from the general population sample also had similar effects on maternal BP during pregnancy in independent cohorts. We did not detect any association between maternal (or paternal) unweighted genetic scores and cardiometabolic offspring outcomes in the meta-analysis of UKB and HUNT after adjusting for offspring genotypes at the same loci. We find little evidence to support the notion that maternal BP is a major causal risk factor for adverse offspring cardiometabolic outcomes in later life. [ABSTRACT FROM AUTHOR]

Recent studies have used Mendelian randomization (MR) to investigate the observational association between low birth weight (BW) and increased risk of cardiometabolic outcomes, specifically cardiovascular disease, glycemic traits, and type 2 diabetes (T2D), and inform on the validity of the Barker hypothesis. We used simulations to assess the validity of these previous MR studies, and to determine whether a better formulated model can be used in this context. Genetic and phenotypic data were simulated under a model of no direct causal effect of offspring BW on cardiometabolic outcomes and no effect of maternal genotype on offspring cardiometabolic risk through intrauterine mechanisms; where the observational relationship between BW and cardiometabolic risk was driven entirely by horizontal genetic pleiotropy in the offspring (i.e. offspring genetic variants affecting both BW and cardiometabolic disease simultaneously rather than a mechanism consistent with the Barker hypothesis). We investigated the performance of four commonly used MR analysis methods (weighted allele score MR (WAS-MR), inverse variance weighted MR (IVW-MR), weighted median MR (WM-MR), and MR-Egger) and a new approach, which tests the association between maternal genotypes related to offspring BW and offspring cardiometabolic risk after conditioning on offspring genotype at the same loci. We caution against using traditional MR analyses, which do not take into account the relationship between maternal and offspring genotypes, to assess the validity of the Barker hypothesis, as results are biased in favor of a causal relationship. In contrast, we recommend the aforementioned conditional analysis framework utilizing maternal and offspring genotypes as a valid test of not only the Barker hypothesis, but also to investigate hypotheses relating to the Developmental Origins of Health and Disease more broadly. [ABSTRACT FROM AUTHOR]

Alcohol consumption is correlated positively with risk for breast cancer in observational studies, but observational studies are subject to reverse causation and confounding. The association with epithelial ovarian cancer (EOC) is unclear. We performed both observational Cox regression and two‐sample Mendelian randomization (MR) analyses using data from various European cohort studies (observational) and publicly available cancer consortia (MR). These estimates were compared to World Cancer Research Fund (WCRF) findings. In our observational analyses, the multivariable‐adjusted hazard ratios (HR) for a one standard drink/day increase was 1.06 (95% confidence interval [CI]; 1.04, 1.08) for breast cancer and 1.00 (0.92, 1.08) for EOC, both of which were consistent with previous WCRF findings. MR ORs per genetically predicted one standard drink/day increase estimated via 34 SNPs using MR‐PRESSO were 1.00 (0.93, 1.08) for breast cancer and 0.95 (0.85, 1.06) for EOC. Stratification by EOC subtype or estrogen receptor status in breast cancers made no meaningful difference to the results. For breast cancer, the CIs for the genetically derived estimates include the point‐estimate from observational studies so are not inconsistent with a small increase in risk. Our data provide additional evidence that alcohol intake is unlikely to have anything other than a very small effect on risk of EOC. What's new?: While observational studies indicate that alcohol intake is a probable cause of breast cancer, confounding is problematic. For ovarian cancer, meanwhile, evidence linking risk to alcohol consumption remains inconclusive. Here, the authors examined links between alcohol intake and breast and ovarian cancer using observational data from population‐based cohorts combined with Mendelian randomization analyses on large cancer consortia. Observational data identify an association between elevated alcohol consumption and increased susceptibility to breast cancer but not ovarian cancer. Inclusion of genetically derived estimates, however, indicates that alcohol consumption is unlikely to be a major risk factor for breast or ovarian cancer. [ABSTRACT FROM AUTHOR]

Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset conditions, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating "virtual" mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We apply our approach to 19066 sibling pairs from the UK Biobank and show that a polygenic score consisting of imputed parental educational attainment SNP dosages is strongly related to offspring educational attainment even after correcting for offspring genotype at the same loci. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring. Author summary: Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to children. Estimating indirect parental genetic effects on offspring outcomes at the genotype level has been challenging because it requires large-scale, individual level genotypes from both parents and their offspring, and there is a paucity of cohorts around the world with this information. Here we present a new approach to estimate indirect parental genetic effects without the requirement of physically genotyped parents. Our method creates virtual parental genotypes based on the genotypes of offspring pairs, and then uses these virtual genotypes in downstream genetic association analyses. We developed a software package "IMPISH" that allows users to impute virtual parental genotypes in their own genome-wide datasets and then use these in downstream genome-wide association analyses, as well a series of power calculators to estimate the power to detect indirect parental genetic effects on offspring phenotypes. We apply our method to educational attainment data from the UK Biobank and show that indirect parental genetic effects are related to offspring educational attainment even after correcting for offspring genotype at the same loci. [ABSTRACT FROM AUTHOR]

Background: The intrauterine environment is critical for fetal growth and development. However, observational associations between maternal gestational lipid concentrations and offspring birth weight (BW) have been inconsistent and ascertaining causality is challenging.Methods: We used a novel two-sample Mendelian randomization (MR) approach to estimate the causal effect of maternal gestational high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglyceride concentrations on offspring BW. Single nucleotide polymorphisms (SNPs) associated with serum HDL-C, LDL-C and triglyceride concentrations identified in the Global Lipids Genetics Consortium genome-wide association study meta-analysis (n = 188 577 European-ancestry individuals; sample 1) were selected as instrumental variables. The effects of these SNPs on offspring BW were estimated using a structural equation model in the UK Biobank and Early Growth Genetics consortium (n = 230 069 European-ancestry individuals; sample 2) that enabled partitioning of the genetic associations into maternal- (intrauterine) and fetal-specific effects.Results: We found no evidence for a causal effect of maternal gestational HDL-C, LDL-C or triglyceride concentrations on offspring BW [standard deviation change in BW per standard deviation higher in HDL-C = -0.005 (95% confidence interval: -0.039, 0.029), LDL-C = 0.014 (-0.017, 0.045), and triglycerides = 0.014 (-0.025, 0.052)].Conclusions: Our findings suggest that maternal gestational HDL-C, LDL-C and triglyceride concentrations play a limited role in determining offspring BW. However, we cannot comment on the impact of these and other lipid fractions on fetal development more generally. Our study illustrates the power and flexibility of two-sample MR in assessing the causal effect of maternal environmental exposures on offspring outcomes. [ABSTRACT FROM AUTHOR]

Background: There is considerable interest in estimating the causal effect of a range of maternal environmental exposures on offspring health-related outcomes. Previous attempts to do this using Mendelian randomization methodologies have been hampered by the paucity of epidemiological cohorts with large numbers of genotyped mother-offspring pairs.Methods: We describe a new statistical model that we have created which can be used to estimate the effect of maternal genotypes on offspring outcomes conditional on offspring genotype, using both individual-level and summary-results data, even when the extent of sample overlap is unknown.Results: We describe how the estimates obtained from our method can subsequently be used in large-scale two-sample Mendelian randomization studies to investigate the causal effect of maternal environmental exposures on offspring outcomes. This includes studies that aim to assess the causal effect of in utero exposures related to fetal growth restriction on future risk of disease in offspring. We illustrate our framework using examples related to offspring birthweight and cardiometabolic disease, although the general principles we espouse are relevant for many other offspring phenotypes.Conclusions: We advocate for the establishment of large-scale international genetics consortia that are focused on the identification of maternal genetic effects and committed to the public sharing of genome-wide summary-results data from such efforts. This information will facilitate the application of powerful two-sample Mendelian randomization studies of maternal exposures and offspring outcomes. [ABSTRACT FROM AUTHOR]

Background: Coffee consumption has been shown to be associated with various health outcomes in observational studies. However, evidence for its association with epithelial ovarian cancer (EOC) is inconsistent and it is unclear whether these associations are causal.Methods: We used single nucleotide polymorphisms associated with (i) coffee and (ii) caffeine consumption to perform Mendelian randomization (MR) on EOC risk. We conducted a two-sample MR using genetic data on 44 062 individuals of European ancestry from the Ovarian Cancer Association Consortium (OCAC), and combined instrumental variable estimates using a Wald-type ratio estimator.Results: For all EOC cases, the causal odds ratio (COR) for genetically predicted consumption of one additional cup of coffee per day was 0.92 [95% confidence interval (CI): 0.79, 1.06]. The COR was 0.90 (95% CI: 0.73, 1.10) for high-grade serous EOC. The COR for genetically predicted consumption of an additional 80 mg caffeine was 1.01 (95% CI: 0.92, 1.11) for all EOC cases and 0.90 (95% CI: 0.73, 1.10) for high-grade serous cases.Conclusions: We found no evidence indicative of a strong association between EOC risk and genetically predicted coffee or caffeine levels. However, our estimates were not statistically inconsistent with earlier observational studies and we were unable to rule out small protective associations. [ABSTRACT FROM AUTHOR]

Perceived intensities of sweetness and bitterness are correlated with one another and each is influenced by genetics. The extent to which these correlations share common genetic variation, however, remains unclear. In a mainly adolescent sample (n = 1901, mean age 16.2 years), including 243 monozygotic (MZ) and 452 dizygotic (DZ) twin pairs, we estimated the covariance among the perceived intensities of 4 bitter compounds (6-n-propylthiouracil [PROP], sucrose octaacetate, quinine, caffeine) and 4 sweeteners (the weighted mean ratings of glucose, fructose, neohesperidine dihydrochalcone, aspartame) with multivariate genetic modeling. The sweetness factor was moderately correlated with sucrose octa-acetate, quinine, and caffeine (rp = 0.35-0.40). This was mainly due to a shared genetic factor (rg = 0.46-0.51) that accounted for 17-37% of the variance in the 3 bitter compounds' ratings and 8% of the variance in general sweetness ratings. In contrast, an association between sweetness and PROP only became evident after adjusting for the TAS2R38 diplotype (rp increased from 0.18 to 0.32) with the PROP genetic factor accounting for 6% of variance in sweetness. These genetic associations were not inflated by scale use bias, as the crosstrait correlations for both MZ and DZ twins were weak. There was also little evidence for mediation by cognition or behavioral factors. This suggests an overlap of genetic variance between perceptions of sweetness and bitterness from a variety of stimuli, which includes PROP when considering the TAS2R38 diplotype. The most likely sources of shared variation are within genes encoding postreceptor transduction mechanisms common to the various taste G protein-coupled receptors. [ABSTRACT FROM AUTHOR]

Investigations on the relationship between sweet taste perception and body mass index (BMI) have been inconclusive. Here, we report a longitudinal analysis using a genetically informative sample of 1,576 adolescent Australian twins to explore the relationship between BMI and sweet taste. First, we estimated the phenotypic correlations between perception scores for four different sweet compounds (glucose, fructose, neohesperidine dihydrochalcone (NHDC), and aspartame) and BMI. Then, we computed the association between adolescent taste perception and BMI in early adulthood (reported 9 years later). Finally, we used twin modeling and polygenic risk prediction analysis to investigate the genetic overlap between BMI and sweet taste perception. Our findings revealed that BMI in early adulthood was significantly associated with each of the sweet perception scores, with the strongest correlation observed in aspartame with r = 0.09 (p = .007). However, only limited evidence of association was observed between sweet taste perception and BMI that was measured at the same time (in adolescence), with the strongest evidence of association observed for glucose with a correlation coefficient of r = 0.06 (p = .029) and for aspartame with r = 0.06 (p = .035). We found a significant (p < .05) genetic correlation between glucose and NHDC perception and BMI. Our analyses suggest that sweet taste perception in adolescence can be a potential indicator of BMI in early adulthood. This association is further supported by evidence of genetic overlap between the traits, suggesting that some BMI genes may be acting through biological pathways of taste perception. [ABSTRACT FROM AUTHOR]

Background: Observational epidemiological studies suggest a link between several factors related to ovulation and reproductive function and endometrial cancer (EC) risk; however, it is not clear whether these relationships are causal, and whether the risk factors act independently of each other. The aim of this study was to investigate putative causal relationships between the number of live births, age at last live birth, and years ovulating and EC risk.  METHODS: We conducted a series of observational analyses to investigate various risk factors and EC risk in the UK Biobank (UKBB). Additionally, multivariate analysis was performed to elucidate the relationship between the number of live births, age at last live birth, and years ovulating and other related factors such as age at natural menopause, age at menarche, and body mass index (BMI). Secondly, we used Mendelian randomization (MR) to assess if these observed relationships were causal. Genome-wide significant single nucleotide polymorphisms (SNPs) were extracted from previous studies of woman's number of live births, age at menopause and menarche, and BMI. We conducted a genome-wide association analysis using the UKBB to identify SNPs associated with years ovulating, years using the contraceptive pill, and age at last live birth.Results: We found evidence for a causal effect of the number of live births (inverse variance weighted (IVW) odds ratio (OR): 0.537, p = 0.006), the number of years ovulating (IVW OR: 1.051, p = 0.014), in addition to the known risk factors BMI, age at menarche, and age at menopause on EC risk in the univariate MR analyses. Due to the close relationships between these factors, we followed up with multivariable MR (MVMR) analysis. Results from the MVMR analysis showed that number of live births had a causal effect on EC risk (OR: 0.783, p = 0.036) independent of BMI, age at menarche and age at menopause.Conclusions: MVMR analysis showed that the number of live births causally reduced the risk of EC. [ABSTRACT FROM AUTHOR]

The perception of sweetness varies among individuals but the sources of this variation are not fully understood. Here, in a sample of 1,901 adolescent and young adults (53.8% female; 243 MZ and 452 DZ twin pairs, 511 unpaired individuals; mean age 16.2 ± 2.8, range 12–26 years), we studied the variation in the perception of sweetness intensity of two monosaccharides and two high-potency sweeteners: glucose, fructose, neohesperidine dihydrochalcone (NHDC), and aspartame. Perceived intensity for all sweeteners decreased with age (2–5% per year) and increased with the history of otitis media (6–9%). Males rated aspartame slightly stronger than females (7%). We found similar heritabilities for sugars (glucose: h2 = 0.31, fructose: h2 = 0.34) and high-potency sweeteners (NHDC: h2 = 0.31, aspartame: h2 = 0.30); all were in the modest range. Multivariate modeling showed that a common genetic factor accounted for >75% of the genetic variance in the four sweeteners, suggesting that individual differences in perceived sweet intensity, which are partly due to genetic factors, may be attributed to a single set of genes. This study provided evidence of the shared genetic pathways between the perception of sugars and high-potency sweeteners. [ABSTRACT FROM PUBLISHER]

Background: The present study aimed to determine if salty and sweet taste preferences in children are related to each other, to markers of growth, and to genetic differences. Methods: We conducted a 2-day, single-blind experimental study using the Monell two-series, forced-choice, paired-comparison tracking method to determine taste preferences. The volunteer sample consisted of a racially/ethnically diverse group of children, 5–10 years of age (n = 108), and their mothers (n = 83). After excluding those mothers who did not meet eligibility and children who did not understand or comply with study procedures, the final sample was 101 children and 76 adults. The main outcome measures were most preferred concentration of salt in broth and crackers; most preferred concentration of sucrose in water and jelly; reported dietary intake of salty and sweet foods; levels of a bone growth marker; anthropometric measurements such as height, weight, and percent body fat; and TAS1R3 (sweet taste receptor) genotype. Results: Children preferred higher concentrations of salt in broth and sucrose in water than did adults, and for both groups, salty and sweet taste preferences were significantly and positively correlated. In children, preference measures were related to reported intake of sodium but not of added sugars. Children who were tall for their age preferred sweeter solutions than did those that were shorter and percent body fat was correlated with salt preference. In mothers but not in children, sweet preference correlated with TAS1R3 genotype. Conclusions and Relevance: For children, sweet and salty taste preferences were positively correlated and related to some aspects of real-world food intake. Complying with recommendations to reduce added sugars and salt may be more difficult for some children, which emphasizes the need for new strategies to improve children's diets. [ABSTRACT FROM AUTHOR]

This paper is about Nick's contribution to the field of taste genetics, how I became involved and how a study on the genetic association between the perception of sweetness and bitterness ended up examining the influence of intelligence on taste perception. [ABSTRACT FROM AUTHOR]

Individuals undergoing treatment for cancer can experience changes in taste or smell that are often assumed to affect constructs related to food behavior, although this relationship is rarely measured directly. To ascertain the extent to which measured changes in taste and smell during and after cancer treatment affect food behavior, we conducted a scoping review and completed a comparative analysis for studies that met our criteria, which were: they directly measured cancer patients' (a) psychophysical response to taste and/or olfactory stimuli, and (b) food behavior (including food enjoyment, food preference, dietary intake) in people affected by cancer. Eleven studies met these criteria and were included in the review. All 11 studies evaluated taste and five also measured smell. A comparative analysis exploring taste and food behavior shows that a reduced sweet taste function (decreased sensitivity) was associated with a reduced intake of a variety of different macro and micro nutrients, reduced appetite, and overall lower energy intake. One out of six studies that measured smell and food measured observed changes in olfactory function following cancer treatment. There were no significant relationships reported between olfactory measures and food behavior. Taste changes that arise from cancer treatment appear to have a direct effect on food behavior, although there is a need for more research using standardized measures and larger sample sizes. A better understanding of taste alterations and their implications for dietary intake and food enjoyment will support optimal nutritional health by identifying strategies to help patients eat well during and after cancer treatment. [ABSTRACT FROM AUTHOR]

It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N ​= ​1097) and the USA (N ​= ​723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R2 ​= ​0.006 and 0.016 respectively, p ​< ​0.001) but not average thickness. At the regional level, we identified seven cortical regions—in the frontal and temporal lobes—that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research. [ABSTRACT FROM AUTHOR]