Adult height, coronary heart disease and stroke: a multi-locus Mendelian randomization meta-analysis

BACKGROUND: We investigated causal effect of completed growth, measured by adult height, on coronary heart disease (CHD), stroke and cardiovascular traits, using instrumental variable (IV) Mendelian randomization meta-analysis. METHODS: We developed an allele score based on 69 single nucleotide polymorphisms (SNPs) associated with adult height, identified by the IBCCardioChip, and used it for IV analysis against cardiovascular risk factors and events in 21 studies and 60 028 participants. IV analysis on CHD was supplemented by summary data from 180 height-SNPs from the GIANT consortium and their corresponding CHD estimates derived from CARDIoGRAMplusC4D. RESULTS: IV estimates from IBCCardioChip and GIANT-CARDIoGRAMplusC4D showed that a 6.5-cm increase in height reduced the odds of CHD by 10% [odds ratios 0.90; 95% confidence intervals (CIs): 0.78 to 1.03 and 0.85 to 0.95, respectively],which agrees with the estimate from the Emerging Risk Factors Collaboration (hazard ratio 0.93; 95% CI: 0.91 to 0.94). IV analysis revealed no association with stroke (odds ratio 0.97; 95% CI: 0.79 to 1.19). IV analysis showed that a 6.5-cm increase in height resulted in lower levels of body mass index (P < 0.001), triglycerides (P < 0.001), non high-density (non-HDL) cholesterol (P < 0.001), C-reactive protein (P = 0.042), and systolic blood pressure (P = 0.064) and higher levels of forced expiratory volume in 1 s and forced vital capacity (P < 0.001 for both). CONCLUSIONS: Taller individuals have a lower risk of CHD with potential explanations being that taller people have a better lung function and lower levels of body mass index, cholesterol and blood pressure

The Human Phenotype Ontology in 2024: phenotypes around the world

\ua9 The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Phylogenetic Analysis of Glucosyltransferases and Implications for the Coevolution of Mutans Streptococci with Their Mammalian Hosts

<div><p>Glucosyltransferases (Gtfs) catalyze the synthesis of glucans from sucrose and are produced by several species of lactic-acid bacteria. The oral bacterium <em>Streptococcus mutans</em> produces large amounts of glucans through the action of three Gtfs. GtfD produces water-soluble glucan (WSG), GtfB synthesizes water-insoluble glucans (WIG) and GtfC produces mainly WIG but also WSG. These enzymes, especially those synthesizing WIG, are of particular interest because of their role in the formation of dental plaque, an environment where <em>S. mutans</em> can thrive and produce lactic acid, promoting the formation of dental caries. We sequenced the <em>gtfB</em>, <em>gtfC</em> and <em>gtfD</em> genes from several mutans streptococcal strains isolated from the oral cavity of humans and searched for their homologues in strains isolated from chimpanzees and macaque monkeys. The sequence data were analyzed in conjunction with the available Gtf sequences from other bacteria in the genera <em>Streptococcus</em>, <em>Lactobacillus</em> and <em>Leuconostoc</em> to gain insights into the evolutionary history of this family of enzymes, with a particular emphasis on <em>S. mutans</em> Gtfs. Our analyses indicate that streptococcal Gtfs arose from a common ancestral progenitor gene, and that they expanded to form two clades according to the type of glucan they synthesize. We also show that the clade of streptococcal Gtfs synthesizing WIG appeared shortly after the divergence of viviparous, dentate mammals, which potentially contributed to the formation of dental plaque and the establishment of several streptococci in the oral cavity. The two <em>S. mutans</em> Gtfs capable of WIG synthesis, GtfB and GtfC, are likely the product of a gene duplication event. We dated this event to coincide with the divergence of the genomes of ancestral early primates. Thus, the acquisition and diversification of <em>S. mutans</em> Gtfs predates modern humans and is unrelated to the increase in dietary sucrose consumption.</p> </div

Site specific profile of type I functional divergence posterior probability.

<p>Logos are shown for positions predicted to be critical for type I functional divergence between GtfB and GtfC (cutoff P>0.85). Residues are color coded by biochemical property and heights represent their relative frequency at each site. The Gtf protein domains are represented below the graph. I) signal peptide, II) N-terminal variable region, III) catalytic domain, IV) glucan binding domain.</p

Bayesian phylogeny of streptococcal Gtfs.

<p>Values represent mean node ages obtained from either the nucleotide (top) or the amino acid (bottom) sequences, with the node calibration from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0056305#pone.0056305-Wilkinson1" target="_blank">[31]</a>. The substitution models were TN93+Γ+I and WAG+Γ+I for nucleotide and amino acid data, respectively. The scale at the bottom represents time before present in millions of years. Bacterial species are indicated as follows: cr = <i>S. criceti</i>; dt = <i>S. dentirousetti</i>; do = <i>S. downei</i>; ma = <i>S. macacae</i>; mu = <i>S. mutans</i>; os = <i>S. orisuis</i>; tr = <i>S. troglodytae</i>. Strains isolated from Hu = human; Ch = chimpanzee; Ma = macaque; Ha = hamster; Pi = pig; Ba = bat.</p

Phylogenetic analysis of streptococcal glucosyltransferases.

<p>A) Maximum likelihood consensus tree of 39 streptococcal glucosyltransferases based on the amino acid sequence of the catalytic domain. Node values indicate bootstrap support from 500 replicates. Branches with less than 50% support were collapsed. Inset: tree topology for the <i>S. mutans</i> water-insoluble glucan cluster based on the full length amino acid sequence. Biochemical data on the type of glucan is indicated as circles for WIG, squares for WSG, and triangles for gtfs that synthesize both WIG and WGS. Bacterial species are indicated as follows: cr = <i>S. criceti</i>; dt = <i>S. dentirousetti</i>; dn = <i>S. dentisuis</i>; do = <i>S. downei</i>; eq = <i>S. equinus</i>; ga = <i>S. gallolyticus</i>; go = <i>S. gordonii</i>; in = <i>S. infantarius</i>; ma = <i>S. macacae</i>; mu = <i>S. mutans</i>; or = <i>S. oralis</i>; os = <i>S. orisuis</i>; sl = <i>S. salivarius</i>; sn = <i>S. sanguinis</i>; so = <i>S. sobrinus</i>; tr = <i>S. troglodytae</i>. The strains were isolated from human subjects unless indicated as follows: B = bat; C = chimpanzee; Co = cow; H = hamster; M = macaque; P = pig. B) Detail of the tree topology for the WIG cluster of <i>S. mutans</i> Gtfs based on the full length amino acid sequence. Reconstruction of character states is indicated by gray circles and triangles.</p