Familial hypercholesterolaemia in children and adolescents from 48 countries: a cross-sectional study

Background: Approximately 450 000 children are born with familial hypercholesterolaemia worldwide every year, yet only 2·1% of adults with familial hypercholesterolaemia were diagnosed before age 18 years via current diagnostic approaches, which are derived from observations in adults. We aimed to characterise children and adolescents with heterozygous familial hypercholesterolaemia (HeFH) and understand current approaches to the identification and management of familial hypercholesterolaemia to inform future public health strategies. Methods: For this cross-sectional study, we assessed children and adolescents younger than 18 years with a clinical or genetic diagnosis of HeFH at the time of entry into the Familial Hypercholesterolaemia Studies Collaboration (FHSC) registry between Oct 1, 2015, and Jan 31, 2021. Data in the registry were collected from 55 regional or national registries in 48 countries. Diagnoses relying on self-reported history of familial hypercholesterolaemia and suspected secondary hypercholesterolaemia were excluded from the registry; people with untreated LDL cholesterol (LDL-C) of at least 13·0 mmol/L were excluded from this study. Data were assessed overall and by WHO region, World Bank country income status, age, diagnostic criteria, and index-case status. The main outcome of this study was to assess current identification and management of children and adolescents with familial hypercholesterolaemia. Findings: Of 63 093 individuals in the FHSC registry, 11 848 (18·8%) were children or adolescents younger than 18 years with HeFH and were included in this study; 5756 (50·2%) of 11 476 included individuals were female and 5720 (49·8%) were male. Sex data were missing for 372 (3·1%) of 11 848 individuals. Median age at registry entry was 9·6 years (IQR 5·8-13·2). 10 099 (89·9%) of 11 235 included individuals had a final genetically confirmed diagnosis of familial hypercholesterolaemia and 1136 (10·1%) had a clinical diagnosis. Genetically confirmed diagnosis data or clinical diagnosis data were missing for 613 (5·2%) of 11 848 individuals. Genetic diagnosis was more common in children and adolescents from high-income countries (9427 [92·4%] of 10 202) than in children and adolescents from non-high-income countries (199 [48·0%] of 415). 3414 (31·6%) of 10 804 children or adolescents were index cases. Familial-hypercholesterolaemia-related physical signs, cardiovascular risk factors, and cardiovascular disease were uncommon, but were more common in non-high-income countries. 7557 (72·4%) of 10 428 included children or adolescents were not taking lipid-lowering medication (LLM) and had a median LDL-C of 5·00 mmol/L (IQR 4·05-6·08). Compared with genetic diagnosis, the use of unadapted clinical criteria intended for use in adults and reliant on more extreme phenotypes could result in 50-75% of children and adolescents with familial hypercholesterolaemia not being identified. Interpretation: Clinical characteristics observed in adults with familial hypercholesterolaemia are uncommon in children and adolescents with familial hypercholesterolaemia, hence detection in this age group relies on measurement of LDL-C and genetic confirmation. Where genetic testing is unavailable, increased availability and use of LDL-C measurements in the first few years of life could help reduce the current gap between prevalence and detection, enabling increased use of combination LLM to reach recommended LDL-C targets early in life

Genome-wide analysis of the lignin toolbox of Eucalyptus grandis

Lignin, a major component of secondary cell walls, hinders the optimal processing of wood for industrial uses. The recent availability of the Eucalyptus grandis genome sequence allows comprehensive analysis of the genes encoding the 11 protein families specific to the lignin branch of the phenylpropanoid pathway and identification of those mainly involved in xylem developmental lignification. We performed genome-wide identification of putative members of the lignin gene families, followed by comparative phylogenetic studies focusing on bona fide clades inferred from genes functionally characterized in other species. RNA-seq and microfluid real-time quantitative PCR (RT-qPCR) expression data were used to investigate the developmental and environmental responsive expression patterns of the genes. The phylogenetic analysis revealed that 38 E. grandis genes are located in bona fide lignification clades. Four multigene families (shikimate O-hydroxycinnamoyltransferase (HCT), p-coumarate 3-hydroxylase (C3H), caffeate/5-hydroxyferulate O-methyltransferase (COMT) and phenylalanine ammonia-lyase (PAL)) are expanded by tandem gene duplication compared with other plant species. Seventeen of the 38 genes exhibited strong, preferential expression in highly lignified tissues, probably representing the E. grandis core lignification toolbox. The identification of major genes involved in lignin biosynthesis in E. grandis, the most widely planted hardwood crop world-wide, provides the foundation for the development of biotechnology approaches to develop tree varieties with enhanced processing qualities.This work, part of the LABEX project TULIP (ANR-10-LABX-41), was supported by grants from the Project Tree For Joules (ANR-2010-KBBE-007-01 and FCT-PKBBE/ AGR_GPL/0001/2010), the CNRS, the Toulouse III University (UPS), and the FCT project microEGo (PTDC/AGR-GPL/098179/2008). V.C. was supported by a FCT PhD grant (SFRH/BD/72982/2010). M.S. received a postdoctoral fellowship ‘Beatriu de Pinós’ from the DURSI de la Generalitat de Catalunya. J.A.P.P. acknowledges FCT for the research contract Ciência 2008 program and the postdoctoral fellowship SFRH/BPD/92207/2013. We are grateful to C. Araujo and L. Neves (Altri Florestal, Portugal), C. Marques (RAIZ, Portugal) and L. Harvengt (FCBA, France) for kindly providing and/or allowing collection of Eucalyptus samples, and C. Graça (IBET, IICT), N. Saidi, H. Yu and E. Camargo (all LRSV) for help with sample design/collection and RNA extraction. We also thank N. Ladouce (LRSV) and the Genotoul Genomic platform http://get.genotoul.fr/ for technical assistance with the Biomark Fluidigm RT-qPCR amplifications, and E. Mizrachi for assistance with RNA-seq data analysis. RNA-seq was funded by Mondi and Sappi through the FMG Program, the THRIP Program (UID 80118), the NRF (UID 71255 and 86936) and the DST of South Africa.http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1469-8137hb2016Genetic

Consensus-based management protocol (CREVICE protocol) for the treatment of severe traumatic brain injury based on imaging and clinical examination for use when intracranial pressure monitoring is not employed

Globally, intracranial pressure (ICP) monitoring use in severe traumatic brain injury (sTBI) is inconsistent and susceptible to resource limitations and clinical philosophies. For situations without monitoring, there is no published comprehensive management algorithm specific to identifying and treating suspected intracranial hypertension (SICH) outside of the one ad hoc Imaging and Clinical Examination (ICE) protocol in the Benchmark Evidence from South American Trials: Treatment of Intracranial Pressure (BEST:TRIP) trial. As part of an ongoing National Institutes of Health (NIH)-supported project, a consensus conference involving 43 experienced Latin American Intensivists and Neurosurgeons who routinely care for sTBI patients without ICP monitoring, refined, revised, and augmented the original BEST:TRIP algorithm. Based on BEST:TRIP trial data and pre-meeting polling, 11 issues were targeted for development. We used Delphi-based methodology to codify individual statements and the final algorithm, using a group agreement threshold of 80%. The resulting CREVICE (Consensus REVised ICE) algorithm defines SICH and addresses both general management and specific treatment. SICH treatment modalities are organized into tiers to guide treatment escalation and tapering. Treatment schedules were developed to facilitate targeted management of disease severity. A decision-support model, based on the group's combined practices, is provided to guide this process. This algorithm provides the first comprehensive management algorithm for treating sTBI patients when ICP monitoring is not available. It is intended to provide a framework to guide clinical care and direct future research toward sTBI management. Because of the dearth of relevant literature, it is explicitly consensus based, and is provided solely as a resource (a “consensus-based curbside consult”) to assist in treating sTBI in general intensive care units in resource-limited environments