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New vaccines targeting meningococci expressing serogroup B polysaccharide have been developed, with some being licensed in Europe. Coverage depends on the distribution of disease-associated genotypes, which may vary by age. It is well established that a small number of hyperinvasive lineages account for most disease, and these lineages are associated with particular antigens, including vaccine candidates. A collection of 4,048 representative meningococcal disease isolates from 18 European countries, collected over a 3-year period, were characterized by multilocus sequence typing (MLST). Age data were available for 3,147 isolates. The proportions of hyperinvasive lineages, identified as particular clonal complexes (ccs) by MLST, differed among age groups. Subjects <1 year of age experienced lower risk of sequence type 11 (ST-11) cc, ST-32 cc, and ST-269 cc disease and higher risk of disease due to unassigned STs, 1- to 4-year-olds experienced lower risk of ST-11 cc and ST-32 cc disease, 5- to 14-year-olds were less likely to experience ST-11 cc and ST-269 cc disease, and ≥25-year-olds were more likely to experience disease due to less common ccs and unassigned STs. Younger and older subjects were vulnerable to a more diverse set of genotypes, indicating the more clonal nature of genotypes affecting adolescents and young adults. Knowledge of temporal and spatial diversity and the dynamics of meningococcal populations is essential for disease control by vaccines, as coverage is lineage specific. The nonrandom age distribution of hyperinvasive lineages has consequences for the design and implementation of vaccines, as different variants, or perhaps targets, may be required for different age groups.
Pathogenic Neisseria meningitidis isolates contain a polysaccharide capsule that is the main virulence determinant for this bacterium. Thirteen capsular polysaccharides have been described, and nuclear magnetic resonance spectroscopy has enabled determination of the structure of capsular polysaccharides responsible for serogroup specificity. Molecular mechanisms involved in N. meningitidis capsule biosynthesis have also been identified, and genes involved in this process and in cell surface translocation are clustered at a single chromosomal locus termed cps. The use of multiple names for some of the genes involved in capsule synthesis, combined with the need for rapid diagnosis of serogroups commonly associated with invasive meningococcal disease, prompted a requirement for a consistent approach to the nomenclature of capsule genes. In this report, a comprehensive description of all N. meningitidis serogroups is provided, along with a proposed nomenclature, which was presented at the 2012 XVIIIth International Pathogenic Neisseria Conference.
Background:
Heritable bleeding and platelet disorders (BPD) are heterogeneous and frequently have an unknown genetic basis. The BRIDGE-BPD study aims to discover new causal genes for BPD by high throughput sequencing using cluster analyses based on improved and standardised deep, multi-system phenotyping of cases.
Methods:
We report a new approach in which the clinical and laboratory characteristics of BPD cases are annotated with adapted Human Phenotype Ontology (HPO) terms. Cluster analyses are then used to characterise groups of cases with similar HPO terms and variants in the same genes. Results:
We show that 60% of index cases with heritable BPD enrolled at 10 European or US centres were annotated with HPO terms indicating abnormalities in organ systems other than blood or blood-forming tissues, particularly the nervous system. Cases within pedigrees clustered closely together on the bases of their HPO-coded phenotypes, as did cases sharing several clinically suspected syndromic disorders. Cases subsequently found to harbour variants in ACTN1 also clustered closely, even though diagnosis of this recently described disorder was not possible using only the clinical and laboratory data available to the enrolling clinician.
Conclusions:
These findings validate our novel HPO-based phenotype clustering methodology for known BPD, thus providing a new discovery tool for BPD of unknown genetic basis. This approach will also be relevant for other rare diseases with significant genetic heterogeneity.