Age-Related Immunity to Meningococcal Serogroup C Vaccination: An Increase in the Persistence of IgG2 Correlates with a Decrease in the Avidity of IgG

Contains fulltext : 97618.pdf (publisher's version ) (Open Access)Background All children and adolescents between 1 and 19 years of age in The Netherlands received a single meningococcal serogroup C conjugate (MenCC) vaccine in 2002. During follow-up 4–5 years later, the persistence of MenC polysaccharide-specific IgG was found to be dependent on age of vaccination with higher IgG levels in the oldest immunized age categories. Methods and Findings Two cross-sectional population-based serum banks, collected in 1995/1996 and in 2006/2007, were used for this study. We measured MenC polysaccharide-specific IgM, the IgG1 and IgG2 subclasses and determined the avidity of the IgG antibodies. We report that the age-related persistence of IgG after immunization with the MenCC vaccine seemed to result from an increase of IgG2 levels with age, while IgG1 levels remained stable throughout the different age-cohorts. Furthermore, an age-related increase in IgM levels was observed, correlating with the persistence of IgG antibodies with age. It is noteworthy that the increase in IgG2 correlated with a reduced IgG-avidity with age. Conclusion These date indicate that the classical characteristics of a T-cell-dependent antibody response as elicited by protein based vaccines might not be completely applicable when conjugate vaccines are administered to older children and adolescents up to 18 years of age. The response elicited by the MenCC vaccine seemed to be more a mixture of both T cell dependent and T cell independent responses in terms of humoral immunological characteristics

Parelsnoer institute biobank hereditary colorectal cancer: A joint infrastructure for patient data and biomaterial on hereditary colorectal cancer in the Netherlands

Each year approximately 15,000 patients are diagnosed with colorectal cancer (CRC) in the Netherlands, of whom 5-10% are associated with a hereditary syndrome. To enable future research into hereditary CRC, we established a collaborative biobank for hereditary CRC in all eight University Medical Centers (UMCs) in the Netherlands in 2009. This Biobank Hereditary CRC is part of the Parelsnoer Institute (PSI), which is funded by the Dutch Federation of UMCs and the Dutch Government. Besides the multicenter collaboration, the multidisciplinary nature of this biobank - involving Gastroenterology, Genetics and Surgery - is essential for its functionality and value.Patients at increased risk of hereditary CRC and/or Polyposis, or with a proven germline mutation causing CRC and/or Polyposis are included. Both clinical data (demographic data, details on medical and family history, information on surveillance, endoscopy and surgery, results of microsatellite instability and molecular genetic tests) and biomaterial (DNA, plasma, serum and tissue) are collected in a standardized manner.</p

Immunity against Neisseria meningitidis Serogroup C in the Dutch Population before and after Introduction of the Meningococcal C Conjugate Vaccine

Contains fulltext : 88187.pdf (publisher's version ) (Open Access)BACKGROUND: In 2002 a Meningococcal serogroup C (MenC) conjugate vaccine, with tetanus toxoid as carrier protein, was introduced in the Netherlands as a single-dose at 14 months of age. A catch-up campaign was performed targeting all individuals aged 14 months to 18 years. We determined the MenC-specific immunity before and after introduction of the MenC conjugate (MenCC) vaccine. METHODS AND FINDINGS: Two cross-sectional population-based serum banks, collected in 1995/1996 (n = 8539) and in 2006/2007 (n = 6386), were used for this study. The main outcome measurements were the levels of MenC polysaccharide(PS)-specific IgG and serum bactericidal antibodies (SBA) after routine immunization, 4-5 years after catch-up immunization or by natural immunity. There was an increasing persistence of PS-specific IgG and SBA with age in the catch-up immunized cohorts 4-5 years after their MenCC immunization (MenC PS-specific IgG, 0.25 microg/ml (95%CI: 0.19-0.31 microg/ml) at age 6 years, gradually increasing to 2.34 microg/ml,(95%CI: 1.70-3.32 microg/ml) at age 21-22 years). A comparable pattern was found for antibodies against the carrier protein in children immunized above 9 years of age. In case of vaccination before the age of 5 years, PS-specific IgG was rapidly lost. For all age-cohorts together, SBA seroprevalence (> or =8) increased from 19.7% to 43.0% in the pre- and post-MenC introduction eras, respectively. In non-immunized adults the SBA seroprevalence was not significantly different between the pre- and post-MenC introduction periods, whereas PS-specific IgG was significantly lower in the post-MenC vaccination (GMT, age > or =25 years, 0.10 microg/ml) era compared to the pre-vaccination (GMT, age > or =25 years, 0.43 microg/ml) era. CONCLUSION: MenCC vaccination administered above 5 years of age induced high IgG levels compared to natural exposure, increasing with age. In children below 14 months of age and non-immunized cohorts lower IgG levels were observed compared to the pre-vaccination era, whereas functional levels remained similar in adults. Whether the lower IgG poses individuals at increased risk for MenC disease should be carefully monitored. Large-scale introduction of a MenCC vaccine has led to improved protection in adolescents, but in infants a single-dose schedule may not provide sufficient protection on the long-term and therefore a booster-dose early in adolescence should be considered

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP’s Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

Mobile element insertions in rare diseases: a comparative benchmark and reanalysis of 60,000 exome samples

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES

Solving patients with rare diseases through programmatic reanalysis of genome-phenome data

Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP’s Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics

TINF2 is a haploinsufficient tumor suppressor that limits telomere length

Telomere shortening is a presumed tumor suppressor pathway that imposes a proliferative barrier (the Hayflick limit) during tumorigenesis. This model predicts that excessively long somatic telomeres predispose to cancer. Here, we describe cancer-prone families with two unique TINF2 mutations that truncate TIN2, a shelterin subunit that controls telomere length. Patient lymphocyte telomeres were unusually long. We show that the truncated TIN2 proteins do not localize to telomeres, suggesting that the mutations create loss-of-function alleles. Heterozygous knock-in of the mutations or deletion of one copy of TINF2 resulted in excessive telomere elongation in clonal lines, indicating that TINF2 is haploinsufficient for telomere length control. In contrast, telomere protection and genome stability were maintained in all heterozygous clones. The data establish that the TINF2 truncations predispose to a tumor syndrome. We conclude that TINF2 acts as a haploinsufficient tumor suppressor that limits telomere length to ensure a timely Hayflick limit

Solve-RD: systematic pan-European data sharing and collaborative analysis to solve rare diseases

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient’s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe

Parelsnoer institute biobank hereditary colorectal cancer: A joint infrastructure for patient data and biomaterial on hereditary colorectal cancer in the Netherlands

Each year approximately 15,000 patients are diagnosed with colorectal cancer (CRC) in the Netherlands, of whom 5-10% are associated with a hereditary syndrome. To enable future research into hereditary CRC, we established a collaborative biobank for hereditary CRC in all eight University Medical Centers (UMCs) in the Netherlands in 2009. This Biobank Hereditary CRC is part of the Parelsnoer Institute (PSI), which is funded by the Dutch Federation of UMCs and the Dutch Government. Besides the multicenter collaboration, the multidisciplinary nature of this biobank - involving Gastroenterology, Genetics and Surgery - is essential for its functionality and value.Patients at increased risk of hereditary CRC and/or Polyposis, or with a proven germline mutation causing CRC and/or Polyposis are included. Both clinical data (demographic data, details on medical and family history, information on surveillance, endoscopy and surgery, results of microsatellite instability and molecular genetic tests) and biomaterial (DNA, plasma, serum and tissue) are collected in a standardized manner