Possible relationship between common genetic variation and white matter development in a pilot study of preterm infants

Background The consequences of preterm birth are a major public health concern with high rates of ensuing multisystem morbidity, and uncertain biological mechanisms. Common genetic variation may mediate vulnerability to the insult of prematurity and provide opportunities to predict and modify risk. Objective To gain novel biological and therapeutic insights from the integrated analysis of magnetic resonance imaging and genetic data, informed by prior knowledge. Methods We apply our previously validated pathway-based statistical method and a novel network-based method to discover sources of common genetic variation associated with imaging features indicative of structural brain damage. Results Lipid pathways were highly ranked by Pathways Sparse Reduced Rank Regression in a model examining the effect of prematurity, and PPAR (peroxisome proliferator-activated receptor) signaling was the highest ranked pathway once degree of prematurity was accounted for. Within the PPAR pathway, five genes were found by Graph Guided Group Lasso to be highly associated with the phenotype: aquaporin 7 (AQP7), malic enzyme 1, NADP(+)-dependent, cytosolic (ME1), perilipin 1 (PLIN1), solute carrier family 27 (fatty acid transporter), member 1 (SLC27A1), and acetyl-CoA acyltransferase 1 (ACAA1). Expression of four of these (ACAA1, AQP7, ME1, and SLC27A1) is controlled by a common transcription factor, early growth response 4 (EGR-4). Conclusions This suggests an important role for lipid pathways in influencing development of white matter in preterm infants, and in particular a significant role for interindividual genetic variation in PPAR signaling

Why are feasibility studies accessing routinely collected health data? A systematic review

BACKGROUND: Feasibility trials are often undertaken to determine whether a larger randomised controlled trial (RCT) is achievable. In a recent review, 15 feasibility trials accessed routinely collected health data (RCHD) from UK national databases and registries. This paper looks at attributes of these trials and the reasons why they accessed RCHD. METHODS: We extracted data from all publicly available sources for the 15 feasibility studies found in a previous review of trials successfully accessing RCHD in the UK between 2013–2018 for the purpose of informing or supplementing participant data. We extracted trial characteristics, the registry accessed, and the way the RCHD was used. RESULTS: The 15 feasibility RCTs were conducted in a variety of disease areas, and were generally small (median sample size 100, range 41–4061) and individually randomised (60%, 9/15). The primary trial outcome was predominantly administrative (non-clinical) (80%, 12/15) such as feasibility of patient recruitment. They were more likely to recruit from secondary care (67%, 10/15) settings than primary (33%, 5/15). NHS Digital was the most commonly accessed registry (33% (5/15)) with SAIL databank (20% (3/15)), electronic Data Research and Innovation Service (eDRIS) and Paediatric Intensive Care Audit Network (PICANET) (each 13% 2/15) also being accessed. Where the information was clear, the trials used RCHD for data collection during the trial (47%, 7/15), follow-up after the trial (27%, 4/15) and recruitment (13%, 2/15). CONCLUSIONS: Between 2013 and 2018, 15 feasibility trials successfully accessed UK RCHD. Feasibility trials would benefit, as with other trials, from guidance on reporting the use of RCHD in protocols and publications

Diffusion magnetic resonance imaging assessment of regional white matter maturation in preterm neonates

PURPOSE: Diffusion magnetic resonance imaging (dMRI) studies report altered white matter (WM) development in preterm infants. Neurite orientation dispersion and density imaging (NODDI) metrics provide more realistic estimations of neurite architecture in vivo compared with standard diffusion tensor imaging (DTI) metrics. This study investigated microstructural maturation of WM in preterm neonates scanned between 25 and 45 weeks postmenstrual age (PMA) with normal neurodevelopmental outcomes at 2 years using DTI and NODDI metrics. METHODS: Thirty-one neonates (n = 17 male) with median (range) gestational age (GA) 32+1 weeks (24+2-36+4) underwent 3 T brain MRI at median (range) post menstrual age (PMA) 35+2 weeks (25+3-43+1). WM tracts (cingulum, fornix, corticospinal tract (CST), inferior longitudinal fasciculus (ILF), optic radiations) were delineated using constrained spherical deconvolution and probabilistic tractography in MRtrix3. DTI and NODDI metrics were extracted for the whole tract and cross-sections along each tract to assess regional development. RESULTS: PMA at scan positively correlated with fractional anisotropy (FA) in the CST, fornix and optic radiations and neurite density index (NDI) in the cingulum, CST and fornix and negatively correlated with mean diffusivity (MD) in all tracts. A multilinear regression model demonstrated PMA at scan influenced all diffusion measures, GA and GAxPMA at scan influenced FA, MD and NDI and gender affected NDI. Cross-sectional analyses revealed asynchronous WM maturation within and between WM tracts.). CONCLUSION: We describe normal WM maturation in preterm neonates with normal neurodevelopmental outcomes. NODDI can enhance our understanding of WM maturation compared with standard DTI metrics alone

The specialty choices of graduates from Brighton and Sussex Medical School: a longitudinal cohort study

BACKGROUND Since 2007 junior doctors in the UK have had to make major career decisions at a point when previously many had not yet chosen a specialty. This study examined when doctors in this new system make specialty choices, which factors influence choices, and whether doctors who choose a specialty they were interested in at medical school are more confident in their choice than those doctors whose interests change post-graduation. METHODS Two cohorts of students in their penultimate year at one medical school (n = 227/239) were asked which specialty interested them as a career. Two years later, 210/227 were sent a questionnaire measuring actual specialty chosen, confidence, influence of perceptions of the specialty and experiences on choice, satisfaction with medicine, personality, self-efficacy, and demographics. Medical school and post-graduation choices in the same category were deemed 'stable'. Predictors of stability, and of not having chosen a specialty, were calculated using bootstrapped logistic regression. Differences between specialties on questionnaire factors were analysed. RESULTS 50% responded (n = 105/277; 44% of the 239 Year 4 students). 65% specialty choices were 'stable'. Factors univariately associated with stability were specialty chosen, having enjoyed the specialty at medical school or since starting work, having first considered the specialty earlier. A regression found doctors who chose psychiatry were more likely to have changed choice than those who chose general practice. Confidence in the choice was not associated with stability. Those who chose general practice valued lifestyle factors. A psychiatry choice was associated with needing a job and using one's intellect to help others. The decision to choose surgical training tended to be made early. Not having applied for specialty training was associated with being lower on agreeableness and conscientiousness. CONCLUSION Medical school experiences are important in specialty choice but experiences post-graduation remain significant, particularly in some specialties (psychiatry in our sample). Career guidance is important at medical school and should be continued post-graduation, with senior clinicians supported in advising juniors. Careers advice in the first year post-graduation may be particularly important, especially for specialties which have difficulty recruiting or are poorly represented at medical school

Exploring the multiple-hit hypothesis of preterm white matter damage using diffusion MRI.

Background: Preterm infants are at high risk of diffuse white matter injury and adverse neurodevelopmental outcome. The multiple hit hypothesis suggests that the risk of white matter injury increases with cumulative exposure to multiple perinatal risk factors. Our aim was to test this hypothesis in a large cohort of preterm infants using diffusion weighted magnetic resonance imaging (dMRI). Methods: We studied 491 infants (52% male) without focal destructive brain lesions born at < 34 weeks, who underwent structural and dMRI at a specialist Neonatal Imaging Centre. The median (range) gestational age (GA) at birth was 30+ 1 (23+ 2-33+ 5) weeks and median postmenstrual age at scan was 42+ 1 (38-45) weeks. dMRI data were analyzed using tract based spatial statistics and the relationship between dMRI measures in white matter and individual perinatal risk factors was assessed. We tested the hypothesis that increased exposure to perinatal risk factors was associated with lower fractional anisotropy (FA), and higher radial, axial and mean diffusivity (RD, AD, MD) in white matter. Neurodevelopmental performance was investigated using the Bayley Scales of Infant and Toddler Development, Third Edition (BSITD-III) in a subset of 381 infants at 20 months corrected age. We tested the hypothesis that lower FA and higher RD, AD and MD in white matter were associated with poorer neurodevelopmental performance. Results: Identified risk factors for diffuse white matter injury were lower GA at birth, fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition, necrotizing enterocolitis and male sex. Clinical chorioamnionitis and patent ductus arteriosus were not associated with white matter injury. Multivariate analysis demonstrated that fetal growth restriction, increased number of days requiring ventilation and parenteral nutrition were independently associated with lower FA values. Exposure to cumulative risk factors was associated with reduced white matter FA and FA values at term equivalent age were associated with subsequent neurodevelopmental performance. Conclusion: This study suggests multiple perinatal risk factors have an independent association with diffuse white matter injury at term equivalent age and exposure to multiple perinatal risk factors exacerbates dMRI defined, clinically significant white matter injury. Our findings support the multiple hit hypothesis for preterm white matter injury

Exploring multilocus associations of inflammation genes and colorectal cancer risk using hapConstructor

<p>Abstract</p> <p>Background</p> <p>In candidate-gene association studies of single nucleotide polymorphisms (SNPs), multilocus analyses are frequently of high dimensionality when considering haplotypes or haplotype pairs (diplotypes) and differing modes of expression. Often, while candidate genes are selected based on their biological involvement in a given pathway, little is known about the functionality of SNPs to guide association studies. Investigators face the challenge of exploring multiple SNP models to elucidate which variants, independently or in combination, might be associated with a disease of interest. A data mining module, hapConstructor (freely-available in Genie software) performs systematic construction and association testing of multilocus genotype data in a Monte Carlo framework. Our objective was to assess its utility to guide statistical analyses of haplotypes within a candidate region (or combined genotypes across candidate genes) beyond that offered by a standard logistic regression approach.</p> <p>Methods</p> <p>We applied the hapConstructor method to a multilocus investigation of candidate genes involved in pro-inflammatory cytokine IL6 production, <it>IKBKB</it>, <it>IL6</it>, and <it>NFKB1 </it>(16 SNPs total) hypothesized to operate together to alter colorectal cancer risk. Data come from two U.S. multicenter studies, one of colon cancer (1,556 cases and 1,956 matched controls) and one of rectal cancer (754 cases and 959 matched controls).</p> <p>Results</p> <p>HapConstrcutor enabled us to identify important associations that were further analyzed in logistic regression models to simultaneously adjust for confounders. The most significant finding (nominal <it>P </it>= 0.0004; false discovery rate <it>q </it>= 0.037) was a combined genotype association across <it>IKBKB </it>SNP rs5029748 (1 or 2 variant alleles), <it>IL6 </it>rs1800797 (1 or 2 variant alleles), and <it>NFKB1 </it>rs4648110 (2 variant alleles) which conferred an ~80% decreased risk of colon cancer.</p> <p>Conclusions</p> <p>Strengths of hapConstructor were: systematic identification of multiple loci within and across genes important in CRC risk; false discovery rate assessment; and efficient guidance of subsequent logistic regression analyses.</p

Elevated CO₂ does not increase eucalypt forest productivity on a low-phosphorus soil

Rising atmospheric CO2 stimulates photosynthesis and productivity of forests, offsetting CO2 emissions. Elevated CO2 experiments in temperate planted forests yielded ~23% increases in productivity over the initial years. Whether similar CO2 stimulation occurs in mature evergreen broadleaved forests on low-phosphorus (P) soils is unknown, largely due to lack of experimental evidence. This knowledge gap creates major uncertainties in future climate projections as a large part of the tropics is P-limited. Here,we increased atmospheric CO2 concentration in a mature broadleaved evergreen eucalypt forest for three years, in the first large-scale experiment on a P-limited site. We show that tree growth and other aboveground productivity components did not significantly increase in response to elevated CO2 in three years, despite a sustained 19% increase in leaf photosynthesis. Moreover, tree growth in ambient CO2 was strongly P-limited and increased by ~35% with added phosphorus. The findings suggest that P availability may potentially constrain CO2-enhanced productivity in P-limited forests; hence, future atmospheric CO2 trajectories may be higher than predicted by some models. As a result, coupled climate-carbon models should incorporate both nitrogen and phosphorus limitations to vegetation productivity in estimating future carbon sinks

Random Matrix Theory for the Hermitian Wilson Dirac Operator and the chGUE-GUE Transition

We introduce a random two-matrix model interpolating between a chiral Hermitian (2n+nu)x(2n+nu) matrix and a second Hermitian matrix without symmetries. These are taken from the chiral Gaussian Unitary Ensemble (chGUE) and Gaussian Unitary Ensemble (GUE), respectively. In the microscopic large-n limit in the vicinity of the chGUE (which we denote by weakly non-chiral limit) this theory is in one to one correspondence to the partition function of Wilson chiral perturbation theory in the epsilon regime, such as the related two matrix-model previously introduced in refs. [20,21]. For a generic number of flavours and rectangular block matrices in the chGUE part we derive an eigenvalue representation for the partition function displaying a Pfaffian structure. In the quenched case with nu=0,1 we derive all spectral correlations functions in our model for finite-n, given in terms of skew-orthogonal polynomials. The latter are expressed as Gaussian integrals over standard Laguerre polynomials. In the weakly non-chiral microscopic limit this yields all corresponding quenched eigenvalue correlation functions of the Hermitian Wilson operator.Comment: 27 pages, 4 figures; v2 typos corrected, published versio

Average distances on self-similar sets and higher order average distances of self-similar measures

The purpose of this paper is twofold: (1) we study different notions of the average distance between two points of a self-similar subset of ℝ, and (2) we investigate the asymptotic behaviour of higher order average moments of self-similar measures on self-similar subsets of ℝ