Genetic associations with childhood brain growth, defined in two longitudinal cohorts

Genome-wide association studies (GWASs) are unraveling the genetics of adult brain neuroanatomy as measured by cross-sectional anatomic magnetic resonance imaging (aMRI). However, the genetic mechanisms that shape childhood brain development are, as yet, largely unexplored. In this study we identify common genetic variants associated with childhood brain development as defined by longitudinal aMRI. Genome-wide single nucleotide polymorphism (SNP) data were determined in two cohorts: one enriched for attention-deficit/hyperactivity disorder (ADHD) (LONG cohort: 458 participants; 119 with ADHD) and the other from a population-based cohort (Generation R: 257 participants). The growth of the brain's major regions (cerebral cortex, white matter, basal ganglia, and cerebellum) and one region of interest (the right lateral prefrontal cortex) were defined on all individuals from two aMRIs, and a GWAS and a pathway analysis were performed. In addition, association between polygenic risk for ADHD and brain growth was determined for the LONG cohort. For white matter growth, GWAS meta-analysis identified a genome-wide significant intergenic SNP (rs12386571, P = 9.09 × 10-9 ), near AKR1B10. This gene is part of the aldo-keto reductase superfamily and shows neural expression. No enrichment of neural pathways was detected and polygenic risk for ADHD was not associated with the brain growth phenotypes in the LONG cohort that was enriched for the diagnosis of ADHD. The study illustrates the use of a novel brain growth phenotype defined in vivo for further study

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6–17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.</p

Estimating cortical thickness trajectories in children across different scanners using transfer learning from normative models

This work illustrates the use of normative models in a longitudinal neuroimaging study of children aged 6–17 years and demonstrates how such models can be used to make meaningful comparisons in longitudinal studies, even when individuals are scanned with different scanners across successive study waves. More specifically, we first estimated a large-scale reference normative model using Hierarchical Bayesian Regression from N = 42,993 individuals across the lifespan and from dozens of sites. We then transfer these models to a longitudinal developmental cohort (N = 6285) with three measurement waves acquired on two different scanners that were unseen during estimation of the reference models. We show that the use of normative models provides individual deviation scores that are independent of scanner effects and efficiently accommodate inter-site variations. Moreover, we provide empirical evidence to guide the optimization of sample size for the transfer of prior knowledge about the distribution of regional cortical thicknesses. We show that a transfer set containing as few as 25 samples per site can lead to good performance metrics on the test set. Finally, we demonstrate the clinical utility of this approach by showing that deviation scores obtained from the transferred normative models are able to detect and chart morphological heterogeneity in individuals born preterm.</p

A prospective population-based study of gestational vitamin D status and brain morphology in preadolescents

Low vitamin D level during pregnancy has been associated with adverse neurodevelopmental outcomes such as autism spectrum disorders (ASD) in children. However, the underlying neurobiological mechanism remains largely unknown. This study investigated the association between gestational 25-hydroxyvitamin D [25(OH)D] concentration and brain morphology in 2597 children at the age of 10 years in the population-based Generation R Study. We studied both 25(OH)D in maternal venous blood in mid-gestation and in umbilical cord blood at delivery, in relation to brain volumetric measures and surface-based cortical metrics including cortical thickness, surface area, and gyrification using linear regression. We found exposure to higher maternal 25(OH)D concentrations in mid-gestation was associated with a larger cerebellar volume in children (b ​= ​0.02, 95%CI 0.001 to 0.04), however this association did not remain after co

Condensed Tannins in White Clover (Trifolium repens) Foliar Tissues Expressing the Transcription Factor TaMYB14-1 Bind to Forage Protein and Reduce Ammonia and Methane Emissions in vitro

Grazing ruminants contribute to global climate change through enteric methane and nitrous oxide emissions. However, animal consumption of the plant polyphenolics, proanthocyanidins, or condensed tannins (CTs) can decrease both methane emissions and urine nitrogen levels, leading to reduced nitrous oxide emissions, and concomitantly increase animal health and production. CTs are largely absent in the foliage of important temperate pasture legumes, such as white clover (Trifolium repens), but found in flowers and seed coats. Attempts at enhancing levels of CT expression in white clover leaves by mutagenesis and breeding have not been successful. However, the transformation of white clover with the TaMYB14-1 transcription factor from Trifolium arvense has resulted in the production of CTs in leaves up to 1.2% of dry matter (DM). In this study, two generations of breeding elevated foliar CTs to >2% of DM. The CTs consisted predominantly of prodelphinidins (PD, 75-93%) and procyanidins (PC, 17-25%) and had a mean degree of polymerization (mDP) of approximately 10 flavan-3-ol subunits. In vitro studies showed that foliar CTs were bound to bovine serum albumin and white clover proteins at pH 6.5 and were released at pH 2.-2.5. Using rumen in vitro assays, white clover leaves containing soluble CTs of 1.6-2.4% of DM significantly reduced methane production by 19% (p <= 0.01) and ammonia production by 60% (p <= 0.01) relative to non-transformed wild type (WT) controls after 6 h of incubation. These results provide valuable information for further studies using CT expressing white clover leaves for bloat prevention and reduced greenhouse gas emissions in vivo

Fish Oil Increases the Duodenal Flow of Long Chain Polyunsaturated Fatty Acids and trans-11 18:1 and Decreases 18:0 in Steers via Changes in the Rumen Bacterial Community

Ruminant fat is rich in SFA, partly due to the biohydrogenation of dietary PUFA to SFA in the rumen. This process can be inhibited by the dietary inclusion of fish oil. The only bacteria isolated from the rumen capable of converting PUFA to SFA are closely related to Clostridium proteoclasticum. The aim of this study was to investigate if a correlation could be found in vivo between dietary fish oil inclusions and the composition of the ruminal bacterial community and specifically of C. proteoclasticum. Six Hereford × Friesian steers, prepared with ruminal and duodenal cannulae, received grass silage plus 1 of 3 concentrates resulting in total dietary fish oil contents of 0, 1, or 3% of dry matter. A dual flow marker technique was employed to estimate the relative flow of fatty acids. Steers fed the 3% fish oil diet had 100% increases in trans 18:1 flow, whereas 18:0 flow declined to 39% of steers fed the control diet. 16S ribosomal RNA-based denaturing gradient gel electrophoresis profiles obtained from ruminal digesta showed major changes in the bacterial community within steers fed the 3% fish oil diet. Quantitative PCR indicated only a weak relation between numbers of C. proteoclasticum and 18:0 flow between treatments and in individual steers (P < 0.05, but the percentage variance accounted for only 22.8) and did not provide unambiguous evidence that numbers of C. proteoclasticum in the rumen dictate the ratios of SFA:PUFA available for absorption by the animal. Understanding which microbes biohydrogenate PUFA in the rumen is key to developing novel strategies to improve the quality of ruminant products

Prediction of enteric methane production, yield and intensity in dairy cattle using an intercontinental database

Enteric methane (CH4) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH4 is complex, expensive and impractical at large scales; therefore, models are commonly used to predict CH4 production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH4 production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH4 production (g/d per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross-validate their performance; and (4) assess the trade-off between availability of on-farm inputs and CH4 prediction accuracy. The intercontinental database covered Europe (EU), the US (US), Chile (CL), Australia (AU), and New Zealand (NZ). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6, 14.4, and 19.8% for intercontinental, EU, and US regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH4 production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH4 emission conversion factors for specific regions are required to improve CH4 production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary NDF concentration, improve the prediction. For enteric CH4 yield and intensity prediction, information on milk yield and composition is required for better estimation

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.</p

Genetic variants for head size share genes and pathways with cancer

The size of the human head is determined by growth in the first years of life, while the rest of the body typically grows until early adulthood1. Such complex developmental processes are regulated by various genes and growth pathways2. Rare genetic syndromes have revealed genes that affect head size3, but the genetic drivers of variation in head size within the general population remain largely unknown. To elucidate biological pathways underlying the growth of the human head, we performed the largest genome-wide association study on human head size to date (N = 79,107). We identified 67 genetic loci, 50 of which are novel, and found that these loci are preferentially associated with head size and mostly independent from height. In subsequent neuroimaging analyses, the majority of genetic variants demonstrated widespread effects on the brain, whereas the effects of 17 variants could be localized to one or two specific brain regions. Through hypothesis-free approaches, we find a strong overlap of head size variants with both cancer pathways and cancer genes. Gene set analyses showed enrichment for different types of cancer and the p53, Wnt and ErbB signalling pathway. Genes overlapping or close to lead variants – such as TP53, PTEN and APC – were enriched for genes involved in macrocephaly syndromes (up to 37-fold) and high-fidelity cancer genes (up to 9-fold), whereas this enrichment was not seen for human height variants. This indicates that genes regulating early brain and cranial growth are associated with a propensity to neoplasia later in life, irrespective of height. Our results warrant further investigations of the link between head size and cancer, as well as its clinical implications in the general population