The effects of early-treated phenylketonuria on volumetric measures of the cerebellum

Past murine studies of phenylketonuria (PKU) have documented significant effects on cerebellum at both the gross and cellular levels. The profile of neurocognitive and motor difficulties associated with early-treated PKU (ETPKU) is also consistent with potential cerebellar involvement. Previous neuroanatomical studies of cerebellum in patients with PKU, however, have yielded mixed results. The objective of the present study was to further examine potential differences in cerebellar morphometry between individuals with and without ETPKU. To this end, we analyzed high resolution T1-weighted MR images from a sample of 20 individuals with ETPKU and an age-matched comparison group of 20 healthy individuals without PKU. Measurements of whole brain volume, whole cerebellum volume, cerebellar gray matter volume, and cerebellar white matter volume were collected by means of semiautomatic volumetric analysis. Data analysis revealed no significant group differences in whole brain volume, whole cerebellar volume, or cerebellar white matter volume. A significant reduction in cerebellar gray matter volume, however, was observed for the ETPKU group compared to the non-PKU comparison group. These findings expand on previous animal work suggesting that cerebellar gray matter is impacted by PKU. It is also consistent with the hypothesis that the cognitive difficulties experienced by individuals with ETPKU may be related to disruptions in gray matter. Additional studies are needed to fully elucidate the timing and extent of the impact of ETPKU on cerebellum and the associated neurocognitive consequences

FGF/FGFR Signaling Coordinates Skull Development by Modulating Magnitude of Morphological Integration: Evidence from Apert Syndrome Mouse Models

The fibroblast growth factor and receptor system (FGF/FGFR) mediates cell communication and pattern formation in many tissue types (e.g., osseous, nervous, vascular). In those craniosynostosis syndromes caused by FGFR1-3 mutations, alteration of signaling in the FGF/FGFR system leads to dysmorphology of the skull, brain and limbs, among other organs. Since this molecular pathway is widely expressed throughout head development, we explore whether and how two specific mutations on Fgfr2 causing Apert syndrome in humans affect the pattern and level of integration between the facial skeleton and the neurocranium using inbred Apert syndrome mouse models Fgfr2+/S252W and Fgfr2+/P253R and their non-mutant littermates at P0. Skull morphological integration (MI), which can reflect developmental interactions among traits by measuring the intensity of statistical associations among them, was assessed using data from microCT images of the skull of Apert syndrome mouse models and 3D geometric morphometric methods. Our results show that mutant Apert syndrome mice share the general pattern of MI with their non-mutant littermates, but the magnitude of integration between and within the facial skeleton and the neurocranium is increased, especially in Fgfr2+/S252W mice. This indicates that although Fgfr2 mutations do not disrupt skull MI, FGF/FGFR signaling is a covariance-generating process in skull development that acts as a global factor modulating the intensity of MI. As this pathway evolved early in vertebrate evolution, it may have played a significant role in establishing the patterns of skull MI and coordinating proper skull development

Facial phenotypes in subgroups of prepubertal boys with autism spectrum disorders are correlated with clinical phenotypes

<p>Abstract</p> <p>Background</p> <p>The brain develops in concert and in coordination with the developing facial tissues, with each influencing the development of the other and sharing genetic signaling pathways. Autism spectrum disorders (ASDs) result from alterations in the embryological brain, suggesting that the development of the faces of children with ASD may result in subtle facial differences compared to typically developing children. In this study, we tested two hypotheses. First, we asked whether children with ASD display a subtle but distinct facial phenotype compared to typically developing children. Second, we sought to determine whether there are subgroups of facial phenotypes within the population of children with ASD that denote biologically discrete subgroups.</p> <p>Methods</p> <p>The 3dMD cranial System was used to acquire three-dimensional stereophotogrammetric images for our study sample of 8- to 12-year-old boys diagnosed with essential ASD (<it>n </it>= 65) and typically developing boys (<it>n </it>= 41) following approved Institutional Review Board protocols. Three-dimensional coordinates were recorded for 17 facial anthropometric landmarks using the 3dMD Patient software. Statistical comparisons of facial phenotypes were completed using Euclidean Distance Matrix Analysis and Principal Coordinates Analysis. Data representing clinical and behavioral traits were statistically compared among groups by using χ²tests, Fisher's exact tests, Kolmogorov-Smirnov tests and Student's <it>t</it>-tests where appropriate.</p> <p>Results</p> <p>First, we found that there are significant differences in facial morphology in boys with ASD compared to typically developing boys. Second, we also found two subgroups of boys with ASD with facial morphology that differed from the majority of the boys with ASD and the typically developing boys. Furthermore, membership in each of these distinct subgroups was correlated with particular clinical and behavioral traits.</p> <p>Conclusions</p> <p>Boys with ASD display a facial phenotype distinct from that of typically developing boys, which may reflect alterations in the prenatal development of the brain. Subgroups of boys with ASD defined by distinct facial morphologies correlated with clinical and behavioral traits, suggesting potentially different etiologies and genetic differences compared to the larger group of boys with ASD. Further investigations into genes involved in neurodevelopment and craniofacial development of these subgroups will help to elucidate the causes and significance of these subtle facial differences.</p

Facial Structure Analysis Separates Autism Spectrum Disorders Into Meaningful Clinical Subgroups

Varied cluster analysis were applied to facial surface measurements from 62 prepubertal boys with essential autism to determine whether facial morphology constitutes viable biomarker for delineation of discrete Autism Spectrum Disorders (ASD) subgroups. Earlier study indicated utility of facial morphology for autism subgrouping (Aldridge et al. in Mol Autism 2(1):15, 2011). Geodesic distances between standardized facial landmarks were measured from three-dimensional stereo-photogrammetric images. Subjects were evaluated for autism-related symptoms, neurologic, cognitive, familial, and phenotypic variants. The most compact cluster is clinically characterized by severe ASD, significant cognitive impairment and language regression. This verifies utility of facially-based ASD subtypes and validates Aldridge et al.\u27s severe ASD subgroup, notwithstanding different techniques. It suggests that language regression may define a unique ASD subgroup with potential etiologic differences

Landmarking the brain for geometric morphometric analysis: An error study

Neuroanatomic phenotypes are often assessed using volumetric analysis. Although powerful and versatile, this approach is limited in that it is unable to quantify changes in shape, to describe how regions are interrelated, or to determine whether changes in size are global or local. Statistical shape analysis using coordinate data from biologically relevant landmarks is the preferred method for testing these aspects of phenotype. To date, approximately fifty landmarks have been used to study brain shape. Of the studies that have used landmark-based statistical shape analysis of the brain, most have not published protocols for landmark identification or the results of reliability studies on these landmarks. The primary aims of this study were two-fold: (1) to collaboratively develop detailed data collection protocols for a set of brain landmarks, and (2) to complete an intra- and inter-observer validation study of the set of landmarks. Detailed protocols were developed for 29 cortical and subcortical landmarks using a sample of 10 boys aged 12 years old. Average intra-observer error for the final set of landmarks was 1.9 mm with a range of 0.72 mm-5.6 mm. Average inter-observer error was 1.1 mm with a range of 0.40 mm-3.4 mm. This study successfully establishes landmark protocols with a minimal level of error that can be used by other researchers in the assessment of neuroanatomic phenotypes. © 2014 Chollet et al

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Cerebellar white matter abnormalities in phenylketonuria (PKU) [abstract]

Abstract only availablePhenylketonuria (PKU) is a recessive genetic disorder that is characterized by an individual's body being unable to utilize the amino acid phenylalanine because of a dysfunction with the enzyme phenylalanine hydroxylase. Previous studies have shown that the brains of individuals with PKU are decreased in overall size. Additionally, abnormalities of white matter have been previously documented in the cerebrum and periventricular areas. A study of rats with induced hyperphenylalaninemia (i.e., an excess of phenylalanine in the blood) showed cellular abnormalities in the cerebellum (Hogan and Coleman, 1981). We hypothesize that individuals with PKU will show abnormalities in measures of the cerebellum relative to typically developing individuals. The data presented here are from a pilot study examining white matter in the cerebella of individuals with PKU. We collected magnetic resonance images (MRIs) of 1mm³ voxel resolution from four individuals between 12-20 years of age. Overall cerebellar volume and cerebellar white matter volume data were collected using Analyze 8.1 and were then compared between controls and individuals with PKU. The small sample size prohibits statistical analysis so we present trends in our comparative data. Results suggest that overall cerebellar volume and cerebellar white matter volume are decreased in individuals with PKU. Future analysis of larger samples will determine whether these trends in cerebellar abnormalities in individuals with PKU are significant.Thompson Center Undergraduate Research Opportunit