NGF, Brain and Behavioral Plasticity

Nerve Growth Factor (NGF) was initially studied for its role as a key player in the regulation of peripheral innervations. However, the successive finding of its release in the bloodstream of male mice following aggressive encounters and its presence in the central nervous system led to the hypothesis that variations in brain NGF levels, caused by psychosocial stressor, and the related alterations in emotionality, could be functional to the development of proper strategies to cope with the stressor itself and thus to survive. Years later this vision is still relevant, and the body of evidence on the role of NGF has been strengthened and expanded from trophic factor playing a role in brain growth and differentiation to a much more complex messenger, involved in psychoneuroendocrine plasticity

Improving IQ measurement in intellectual disabilities using true deviation from population norms

BackgroundIntellectual disability (ID) is characterized by global cognitive deficits, yet the very IQ tests used to assess ID have limited range and precision in this population, especially for more impaired individuals.MethodsWe describe the development and validation of a method of raw z-score transformation (based on general population norms) that ameliorates floor effects and improves the precision of IQ measurement in ID using the Stanford Binet 5 (SB5) in fragile X syndrome (FXS; n = 106), the leading inherited cause of ID, and in individuals with idiopathic autism spectrum disorder (ASD; n = 205). We compared the distributional characteristics and Q-Q plots from the standardized scores with the deviation z-scores. Additionally, we examined the relationship between both scoring methods and multiple criterion measures.ResultsWe found evidence that substantial and meaningful variation in cognitive ability on standardized IQ tests among individuals with ID is lost when converting raw scores to standardized scaled, index and IQ scores. Use of the deviation z- score method rectifies this problem, and accounts for significant additional variance in criterion validation measures, above and beyond the usual IQ scores. Additionally, individual and group-level cognitive strengths and weaknesses are recovered using deviation scores.ConclusionTraditional methods for generating IQ scores in lower functioning individuals with ID are inaccurate and inadequate, leading to erroneously flat profiles. However assessment of cognitive abilities is substantially improved by measuring true deviation in performance from standardization sample norms. This work has important implications for standardized test development, clinical assessment, and research for which IQ is an important measure of interest in individuals with neurodevelopmental disorders and other forms of cognitive impairment

Psychometric properties of the revised children’s anxiety and depression scale (RCADS) for autistic youth without co-occurring intellectual disability

Autistic youth often present with comorbid anxiety and depression yet there is a dearth of validated assessment tools. The Revised Children’s Anxiety and Depression Scale (RCADS) assesses internalizing symptoms but there is little psychometric data in autistic youth. Treatment-seeking autistic youth with anxiety or obsessive-compulsive symptoms (N = 74; age 6–14 years), and caregivers, were administered the RCADS-Parent, RCADS-Child, and assessments of internalizing, externalizing symptoms and social impairment indicative of autism. RCADS-Parent and RCADS-Child total anxiety scores demonstrated excellent internal consistency, and the six subscales demonstrated acceptable-to-good internal consistency. The RCADS-Child and Parent total anxiety scores were weakly correlated, and neither child age nor gender altered the strength of this association. Convergent validity was supported by moderate-to-strong correlations with clinician and parent-reported anxiety symptoms. Support for divergent validity was mixed. Results provide support for the RCADS-Parent and RCADS-Child as reliable, valid measures of internalizing symptoms in autistic youth

Coronary Artery Aneurysms in Kawasaki Disease: Risk Factors for Progressive Disease and Adverse Cardiac Events in the US Population

Background: The natural history of coronary artery aneurysms (CAA) after intravenous immunoglobulin (IVIG) treatment in the United States is not well described. We describe the natural history of CAA in US Kawasaki disease (KD) patients and identify factors associated with major adverse cardiac events (MACE) and CAA regression. Methods and Results: We evaluated all KD patients with CAA at 2 centers from 1979 to 2014. Factors associated with CAA regression, maximum CA z‐score over time (zMax), and MACE were analyzed. We performed a matched analysis of treatment effect on likelihood of CAA regression. Of 2860 KD patients, 500 (17%) had CAA, including 90 with CAA z‐score >10. Most (91%) received IVIG within 10 days of illness, 32% received >1 IVIG, and 27% received adjunctive anti‐inflammatory medications. CAA regression occurred in 75%. Lack of CAA regression and higher CAA zMax were associated with earlier era, larger CAA z‐score at diagnosis, and bilateral CAA in univariate and multivariable analyses. MACE occurred in 24 (5%) patients and was associated with higher CAA z‐score at diagnosis and lack of IVIG treatment. In a subset of patients (n=132) matched by age at KD and baseline CAA z‐score, those receiving IVIG plus adjunctive medication had a CAA regression rate of 91% compared with 68% for the 3 other groups (IVIG alone, IVIG ≥2 doses, or IVIG ≥2 doses plus adjunctive medication). Conclusions: CAA regression occurred in 75% of patients. CAA z‐score at diagnosis was highly predictive of outcomes, which may be improved by early IVIG treatment and adjunctive therapies

Patterns of Fever in Children After Primary Treatment for Kawasaki Disease

OBJECTIVE: To determine if fever in the early post intravenous immunoglobulin (IVIG) time period (first 36 hours after IVIG completion) for Kawasaki disease (KD), with or without additional infliximab, can predict IVIG resistance and coronary artery abnormalities (CAA). METHODS: Acute KD subjects enrolled in a clinical trial of infliximab plus IVIG (n=96) versus placebo/IVIG (n=94) had temperatures recorded every 6 hours after completion of IVIG infusion. Fever was defined as temperature ≥38.0°C; patients with persistent or recrudescent fever ≥36 hours after completion of IVIG were classified as IVIG-resistant. Multivariable logistic regression by fever pattern was performed to predict outcomes (IVIG resistance and CAA). RESULTS: There was no difference in the time to defervescence between the infliximab/IVIG group (n=96) versus placebo/IVIG group (n= 94). There was no fever after completion of IVIG in the majority of subjects [66% of those with no CAA (n=139) and 76.5% of those with CAA, (n=51)]. Although subjects with at least one fever 24–36 hours post-IVIG had a higher probability of IVIG resistance (OR=30.6 [95%CI 6.7–139.8] p<0.0001), fever at 24–36 hours was not associated with higher likelihood of CAA. There were also 11% (n=19) of IVIG responders who had fever at 24–36 hours post-IVIG. The majority of subjects with CAA (43 of 51, 84.3%) were identified by the initial echocardiogram, so the effect of fever on development of CAA could not be assessed. CONCLUSION: Fever in the first 36 hours following IVIG completion is not predictive of CAA. Our data support refraining from re-treatment until 36 hours after completion of IVIG

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as "non-FLHS SRCAP-related NDD.'' All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations

Consistent patterns of common species across tropical tree communities

D.L.M.C. was supported by the London Natural Environmental Research Council Doctoral Training Partnership grant (grant no. NE/L002485/1). This paper developed from analysing data from the African Tropical Rainforest Observatory Network (AfriTRON), curated at ForestPlots.net. AfriTRON has been supported by numerous people and grants since its inception. We sincerely thank the people of the many villages and local communities who welcomed our field teams and without whose support this work would not have been possible. Grants that have funded the AfriTRON network, including data in this paper, are a European Research Council Advanced Grant (T-FORCES; 291585; Tropical Forests in the Changing Earth System), a NERC standard grant (NER/A/S/2000/01002), a Royal Society University Research Fellowship to S.L.L., a NERC New Investigators Grant to S.L.L., a Philip Leverhulme Award to S.L.L., a European Union FP7 grant (GEOCARBON; 283080), Leverhulme Program grant (Valuing the Arc); a NERC Consortium Grant (TROBIT; NE/D005590/), NERC Large Grant (CongoPeat; NE/R016860/1) the Gordon and Betty Moore Foundation the David and Lucile Packard Foundation, the Centre for International Forestry Research (CIFOR), and Gabon’s National Parks Agency (ANPN). This paper was supported by ForestPlots.net approved Research Project 81, ‘Comparative Ecology of African Tropical Forests’. The development of ForestPlots.net and data curation has been funded by several grants, including NE/B503384/1, NE/N012542/1, ERC Advanced Grant 291585—‘T-FORCES’, NE/F005806/1, NERC New Investigators Awards, the Gordon and Betty Moore Foundation, a Royal Society University Research Fellowship and a Leverhulme Trust Research Fellowship. Fieldwork in the Democratic Republic of the Congo (Yangambi and Yoko sites) was funded by the Belgian Science Policy Office BELSPO (SD/AR/01A/COBIMFO, BR/132/A1/AFRIFORD, BR/143/A3/HERBAXYLAREDD, FED-tWIN2019-prf-075/CongoFORCE, EF/211/TREE4FLUX); by the Flemish Interuniversity Council VLIR-UOS (CD2018TEA459A103, FORMONCO II); by L’Académie de recherche et d’enseignement supérieur ARES (AFORCO project) and by the European Union through the FORETS project (Formation, Recherche, Environnement dans la TShopo) supported by the XIth European Development Fund. EMV was supported by fellowship from the CNPq (Grant 308543/2021-1). RAPELD plots in Brazil were supported by the Program for Biodiversity Research (PPBio) and the National Institute for Amazonian Biodiversity (INCT-CENBAM). BGL post-doc grant no. 2019/03379-4, São Paulo Research Foundation (FAPESP). D.A.C. was supported by the CCI Collaborative fund. Plots in Mato Grosso, Brazil, were supported by the National Council for Scientific and Technological Development (CNPq), PELD-TRAN 441244/2016-5 and 441572/2020-0, and Mato Grosso State Research Support Foundation (FAPEMAT)—0346321/2021. We thank E. Chezeaux, R. Condit, W. J. Eggeling, R. M. Ewers, O. J. Hardy, P. Jeanmart, K. L. Khoon, J. L. Lloyd, A. Marjokorpi, W. Marthy, H. Ntahobavuka, D. Paget, J. T. A. Proctor, R. P. Salomão, P. Saner, S. Tan, C. O. Webb, H. Woell and N. Zweifel for contributing forest inventory data. We thank numerous field assistants for their invaluable contributions to the collection of forest inventory data, including A. Nkwasibwe, ITFC field assistant.Peer reviewe