Increased gene sampling strengthens support for higher-level groups within leaf-mining moths and relatives (Lepidoptera: Gracillariidae)

Background: Researchers conducting molecular phylogenetic studies are frequently faced with the decision of what to do when weak branch support is obtained for key nodes of importance. As one solution, the researcher may choose to sequence additional orthologous genes of appropriate evolutionary rate for the taxa in the study. However, generating large, complete data matrices can become increasingly difficult as the number of characters increases. A few empirical studies have shown that augmenting genes even for a subset of taxa can improve branch support. However, because each study differs in the number of characters and taxa, there is still a need for additional studies that examine whether incomplete sampling designs are likely to aid at increasing deep node resolution. We target Gracillariidae, a Cretaceous-age (similar to 100 Ma) group of leaf-mining moths to test whether the strategy of adding genes for a subset of taxa can improve branch support for deep nodes. We initially sequenced ten genes (8,418 bp) for 57 taxa that represent the major lineages of Gracillariidae plus outgroups. After finding that many deep divergences remained weakly supported, we sequenced eleven additional genes (6,375 bp) for a 27-taxon subset. We then compared results from different data sets to assess whether one sampling design can be favored over another. The concatenated data set comprising all genes and all taxa and three other data sets of different taxon and gene sub-sampling design were analyzed with maximum likelihood. Each data set was subject to five different models and partitioning schemes of non-synonymous and synonymous changes. Statistical significance of non-monophyly was examined with the Approximately Unbiased (AU) test. Results: Partial augmentation of genes led to high support for deep divergences, especially when non-synonymous changes were analyzed alone. Increasing the number of taxa without an increase in number of characters led to lower bootstrap support; increasing the number of characters without increasing the number of taxa generally increased bootstrap support. More than three-quarters of nodes were supported with bootstrap values greater than 80% when all taxa and genes were combined. Gracillariidae, Lithocolletinae + Leucanthiza, and Acrocercops and Parectopa groups were strongly supported in nearly every analysis. Gracillaria group was well supported in some analyses, but less so in others. We find strong evidence for the exclusion of Douglasiidae from Gracillarioidea sensu Davis and Robinson (1998). Our results strongly support the monophyly of a G.B.R.Y. clade, a group comprised of Gracillariidae + Bucculatricidae + Roeslerstammiidae + Yponomeutidae, when analyzed with non-synonymous changes only, but this group was frequently split when synonymous and non-synonymous substitutions were analyzed together. Conclusions: 1) Partially or fully augmenting a data set with more characters increased bootstrap support for particular deep nodes, and this increase was dramatic when non-synonymous changes were analyzed alone. Thus, the addition of sites that have low levels of saturation and compositional heterogeneity can greatly improve results. 2) Gracillarioidea, as defined by Davis and Robinson (1998), clearly do not include Douglasiidae, and changes to current classification will be required. 3) Gracillariidae were monophyletic in all analyses conducted, and nearly all species can be placed into one of six strongly supported clades though relationships among these remain unclear. 4) The difficulty in determining the phylogenetic placement of Bucculatricidae is probably attributable to compositional heterogeneity at the third codon position. From our tests for compositional heterogeneity and strong bootstrap values obtained when synonymous changes are excluded, we tentatively conclude that Bucculatricidae is closely related to Gracillariidae + Roeslerstammiidae + Yponomeutidae

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. Funding Pfizer, Amgen, Merck Sharp & Dohme, Sanofi–Aventis, Daiichi Sankyo, and Regeneron