- Open Access
V-akt murine thymoma viral oncogene homolog 3 (AKT3) contributes to poor disease outcome in humans and mice with pneumococcal meningitis
- Mercedes Valls Serón†1,
- Bart Ferwerda†1,
- JooYeon Engelen-Lee1,
- Madelijn Geldhoff1,
- Valery Jaspers1,
- Aeilko H. Zwinderman2,
- Michael W. Tanck2,
- Frank Baas3,
- Arie van der Ende4, 5,
- Matthijs C. Brouwer†1 and
- Diederik van de Beek†1Email author
© Valls Serón et al. 2016
Received: 28 April 2016
Accepted: 28 April 2016
Published: 18 May 2016
Pneumococcal meningitis is the most common and severe form of bacterial meningitis. Fatality rates are substantial, and long-term sequelae develop in about half of survivors. Here, we have performed a prospective nationwide genetic association study using the Human Exome BeadChip and identified gene variants in encoding dynactin 4 (DCTN4), retinoic acid early transcript 1E (RAET1E), and V-akt murine thymoma viral oncogene homolog 3 (AKT3) to be associated with unfavourable outcome in patients with pneumococcal meningitis. No clinical replication cohort is available, so we validated the role of one of these targets, AKT3, in a pneumococcal meningitis mouse model. Akt3 deficient mice had worse survival and increased histopathology scores for parenchymal damage (infiltration) and vascular infiltration (large meningeal artery inflammation) but similar bacterial loads, cytokine responses, compared to wild-type mice. We found no differences in cerebrospinal fluid cytokine levels between patients with risk or non-risk alleles. Patients with the risk genotype (rs10157763, AA) presented with low scores on the Glasgow Coma Scale and high rate of epileptic seizures. Thus, our results show that AKT3 influences outcome of pneumococcal meningitis.
Bacterial meningitis is a severe infection of the central nervous system, which is caused by Streptococcus pneumoniae in 70 % of cases . Patients with pneumococcal meningitis are at high risk for complications, such as epileptic seizures and cerebral infarction, resulting in a high mortality rates, and neurologic sequelae, including hearing loss, focal neurological deficit, and cognitive impairment, in almost half of survivors [2–7]. Following the introduction of adjunctive dexamethasone treatment the mortality rate of pneumococcal meningitis has decreased from 30 to 20 % [8–10], but new treatments are urgently needed [11–13]. Interindividual differences in severity of disease and outcome may be determined by host genetic variation [14, 15]. So far, genetic association studies in pneumococcal meningitis have used a candidate gene approach in which variations in genes of interest were studied [15–17], focusing on genes in the immune system, for example the toll-like receptor signalling cascade and the complement system [14, 15].
Whole-genome association studies, using an unbiased approach, may identify new candidate genes and pathophysiological mechanisms leading to an unfavourable outcome in pneumococcal meningitis . Such studies should be performed prospectively, using a clear definition of cases with microbiological confirmation, and validated outcome scales . In 2006, we started a nationwide prospective cohort study to identify and characterize host genetic traits and bacterial genetic factors controlling occurrence and outcome of bacterial meningitis (MeninGene) [9, 18]. Here, we report our genome wide association study on the host side, analysing the associations between human genome variants and functional outcome in patients with pneumococcal meningitis using the Human Exome BeadChip. We subsequently validated the role of one of the top hits, AKT3, in a pneumococcal meningitis mouse model. Finally, we studied whether patients with the associated AKT3 rs10157763 risk allele had specific clinical characteristics or cerebrospinal fluid (CSF) inflammatory marker profiles.
Materials and methods
Dutch bacterial meningitis cohort
In a nationwide prospective cohort study (MeninGene) we included patients with community-acquired bacterial meningitis with an age of 16 years or older with positive CSF cultures who were identified by The Netherlands Reference Laboratory for Bacterial Meningitis (NRLBM) from March 2006 to October 2011 . The NRLBM receives bacterial isolates from approximately 85 % of bacterial meningitis patients in the Netherlands and provided the names of the hospitals where patients with bacterial meningitis had been admitted in the previous 2–6 days. Physicians of the hospitals were contacted after which the treating physician obtained informed consent from the patient or their legal representative. Online case record forms were collected through a secured website and included data on symptoms during the hospitalized period, treatment, complications and outcome. Patients with hospital-acquired bacterial meningitis and negative CSF cultures were excluded. Outcome was graded at discharge according to the Glasgow Outcome Scale (GOS), a well validated instrument with good inter-observer agreement . On this five-point scale a score of 1 indicates death, 2 a vegetative state, 3 severe disability, 4 moderate disability, and a score of 5 mild or no disability.
Blood for DNA extraction was collected in sodium/EDTA tubes and DNA-isolation was performed with the Gentra Puregene isolation kit (Qiagen) according to manufacturer’s protocol thereafter the yield and quality of the extractions were determined to ensure appropriate conditions for genotyping.
Genotyping and quality control
Patients were genotyped on the Illumina HumanExome BeadChip v1.1 consisting of >24,0000 markers, with approximately 75 % of these markers having a minor allele frequency (MAF) < 0.05. The genotyping was carried out in collaboration with the Human Genome Facility and the department of Epidemiology, Erasmus MC, the Netherlands as part of the Netherlands ExomeChip Project. After genotyping we performed genotype-calling on all our MeninGene samples (N = 1322) to improve calling accuracy and all non-pneumococcal meningitis patients were removed after quality control (QC). All autosomal SNPs were called using GenomeStudio software, from Illumina, with the GenTrain2.0 cluster algorithm using the protocol as described before .
Called data was exported in PLINK format for final sample and SNP QC . All samples with > 5 % missing genotypes were removed. High quality, independent SNPs with less than 1 % missing-genotypes, non-significant differences between cases and controls with respect to rate of missing genotypes, MAF >5 % and Hardy-Weinberg equilibrium (HWE) p-value > 1 × 10−3 were used to determine relatedness between patients, heterozygosity and ancestry. Individuals with second degree, or higher degree relatedness, heterozygosity above or below three standard deviations and non-European decent were left out. Finally QC was performed by removing all SNPs with >5 % missing genotypes and HWE p-value < 1 × 10−6.
8- to 12-week-old male C57BL/6 N mice were obtained from Charles River, whereas Akt3 -/- mice (backcrossed at least 10 times to a C57BL/6 N background), generated as described elsewhere  were bred and maintained at the animal facility at the Academic Medical Center of Amsterdam. The mice were kept to a controlled 12 h light/dark cycle and food and water were provided ad libitum.
Experimental pneumococcal meningitis model
Pneumococcal meningitis was induced by intracisternal inoculation with S. pneumoniae (serotype 3, American Type Culture Collection #6303) as described previously [18, 23–25]. In brief, wild-type and Akt3 -/- mice (n = 12 per group) were randomly and blind inoculated with 1 μl bacterial suspension containing 1 × 104 CFU S. pneumoniae into the cisterna magna under Isofluran (Baxter) anaesthesia. Six mice per group inoculated with sterile saline (Baxter) were used as controls. Cultures were adjusted such that each final 1 μl inoculum contained 1 × 104 CFU. Immediately after intracisternal inoculation, mice were assessed for neurologic damage as a result of the puncture. No mice suffered from neurological damage as a result of puncture and had to be excluded. Mice were observed during 48 h post infection and clinical signs of meningitis were blindly scored every four hours as previously described . In brief, the maximum score was determined by the estimated contribution of the variable to overall health of the mouse: weight loss (0–4 points), activity (0–4 points), time to return to upright position (0–6 points), state of skin/fur (0–3 points), posture (0–2 points), eye discharge or protrusion (0–4 points), respiration rate (0–4 points), irregular/labored breathing (0–4 points), epilepsy, limb paresis or ataxia (0–10 points). Animals reaching endpoint criteria were humanely killed. In another set of experiments, at 6, 24 and 30 h post infection, 12 mice/group were anesthetized by intraperitoneal injection of 190 mg/kg ketamine (Eurovet Animal Health) and 0.3 mg/kg dexmedetomidine (Pfizer Animal Health) followed by cardiac puncture for blood collection and perfusion of organs with sterile isotonic saline via the left ventricle. CSF was collected by puncture of the cisterna magna. Brain, lung and spleen were harvested, placed on ice, processed and stored as described before . EDTA blood was centrifuged at 2000 × g for 15 min. Plasma was stored at −80 °C for further analysis.
Total RNA was extracted from murine brain homogenates using TriPure reagent (Sigma-Aldrich). The purity of the RNA was assessed by the ratio of absorbance at 260 and 280 nm. RNA purity was within a range of 2.0–2.1. RNA was stored in aliquots at −80 °C until used for reverse transcription. For complementary DNA (cDNA) synthesis, RNA was treated with RQ1 RNase-free DNase (Promega) and reverse transcribed with SuperScript II Reverse Transcriptase and random hexamers (Life Technologies). The real-time polymerase chain reaction (RT-PCR) measurement of individual cDNAs was performed on a Bio-Rad MyiQ Single-Color RT-PCR Detection System using the Bio-Rad iQ SYBR Green Supermix (Bio-Rad Laboratories). The Non-POU-domain containing octamer binding protein (nono, housekeeping gene) primers were described previously . Akt3 cDNA was amplified with a forward 5′-CATCTGAAACAGACACCCGATA-3′ and a reverse 5′-GTCCGCTTGCAGAGTAGGAG-3′ primer for mouse akt3. Dctn4 cDNA was amplified with a forward 5′- CACCCATGTGACTGTGTTGG and a reverse 5′-TGAAGATGCCCACTTTGTTG primer for a mouse dctn4. Raet1E was amplified with a forward 5′-GGATACACCAACGGGCTG and a reverse 5′-GTCACACCCAGGGAAGGTC primer for a mouse raet1e (all Applied Biosystems). A negative control without the Reverse Transcriptase was also used. The expression data were normalized to the nono reference gene. Data were analyzed using the Bio-Rad MyiQ Optical system Software version 1.0.
Murine histopathology and immunohistochemistry
Histopathology was performed on the right cerebral hemisphere fixed in 4 % paraformaldehyde and paraffin embedded. Coronal 5 μm sections of the right hemisphere were cut for subsequent staining with hematoxylin and eosin (HE) according to standard procedures. HE staining were performed to visualize meningeal infiltration, parenchymal damage, vascular inflammation, thrombosis and ventriculitis on a three point scale (Additional file 1). Sections of mice 24 h after induction of pneumococcal meningitis (n = 12 per group) were scored. Tissue sections were stained for Caspase-3 using immunohistochemical procedures in order to assess hippocampal apoptosis, as described previously .
Determination of cytokines and chemokines
The murine cytokines interleukin (IL)-1β, IL-6, IL-10 and tumour-necrosis factor-α (TNF-α) and the chemokines keratinocyte chemoattractant (KC) and macrophage inflammatory protein (MIP)-2 were determined in plasma and brain homogenates by Luminex technology using a mouse Bioplex kit (Bio-Rad Laboratories) as described before . The human cytokines IL-1β, IL-6, IL-10 and TNF-α were determined in CSF collected from the diagnostic lumbar puncture. CSF samples were centrifuged and supernatant was aliquoted and stored at −80 °C until analysis. All analytes were measured with Luminex® xMAP® technology using Milliplex® map multiplex assay’s (Millipore Billerica). CSF was diluted 1:50 in assay buffer provided with the Multiplex assay and inflammatory mediators were measured according to the manufacturer’s instructions. CSF was available in 271 of the 689 (39 %) of pneumococcal meningitis patients.
All patients with pneumococcal meningitis were included in the genetic association analysis for meningitis disease severity/outcome. Severity/outcome was determined by grouping patients on their GOS score where score 1 until 4 together was labelled unfavourable and score 5 as favourable outcome. All calculations have been conducted using PLINK 1.9 . Differences between favourable and unfavourable outcome were calculated using the Fisher’s exact test on allelic association. For the genetic association study, based on 321 patients with a favourable outcome and 152 with unfavourable outcome, for 240,000 variants and a MAF of 0.25, we had 80 % power to detect variants with a OR of 3.4 or higher after Bonferroni correction. Cytokine level differences between genotypes were compared using a Mann-Whitney U test.
We used a multivariable logistic regression analysis to calculate OR and 95 % CI to assess the strength of the association among potential risk factors (including identified polymorphisms) and outcome. Murine gene expression, bacterial load and inflammatory response data were compared using Mann-Whitney U tests. Survival curves were compared using a log rank test and clinical scores were compared using a linear mixed model assuming an exponential and group specific time effect. For all analyses, SPSS (version 22) was used; differences were considered statistically significant at P < 0.05.
Nationwide prospective cohort study
Clinical characteristics of 472 patients with community-acquired pneumococcal meningitisa
Age – yr
58 ± 15
Indexes of CSF inflammationc
Male sex – no (%)
221 (47 %)
Opening pressure (mm H2O)
42 ± 11
Duration of symptoms <24 h
225/461 (49 %)
White blood cell count (/mm3)
2417 ± 5648
Pretreatment with antibiotics
58/459 (13 %)
130/454 (29 %)
322/472 (68 %)
Protein – g/L
4.7 ± 3.2
Otitis or sinusitis
218/471 (46 %)
CSF: blood glucose ratio
0.13 ± 0.18
124/472 (26 %)
Positive blood cultures
337/420 (80 %)
Symptoms and signs on presentationb
363/427 (85 %)
170/466 (36 %)
356/454 (78 %)
Focal neurologic deficits
109/455 (24 %)
33/454 (7 %)
69/460 (15 %)
Systolic blood pressure – mmHg
149 ± 29
Score on Glasgow Outcome Scale
Heart rate – beats/min
100 ± 21
1 – death
37 (8 %)
Body temperature – °C
38.8 ± 1.3
2 – vegetative state
1 (0.2 %)
Score on Glasgow Coma Scalec
11 ± 3
3 – severe disability
23 (5 %)
<8 indicating coma
4 – moderate disability
90 (19 %)
Focal neurologic deficits
109/455 (25 %)
5 – good recovery
321 (68 %)
Genetic association study
Novel SNPs associated with unfavorable outcome in patients with pneumococcal meningitis
OR (+/− 95 CI)
Upstream gene variant
2.4 × 10−05
F349L, F342L, F285L
2.4 × 10−05
9.4 × 10−05
9.4 × 10−05
9.9 × 10−05
Role of akt3 in the pneumococcal meningitis mouse model
AKT3 rs10157763 variant and risk factors for unfavourable outcome
Clinical characteristics and outcome per genotype in 396 white patients with community-acquired pneumococcal meningitisa
GG (n = 195)
AG (n = 162)
AA (n = 39)
p-value recessive model
58 ± 14
60 ± 13
56 ± 17
86 (44 %)
79 (49 %)
17 (44 %)
Glasgow Coma Scale Score
11 ± 3
11 ± 3
9 ± 3
Seizures on admission
12/188 (7 %)
10/158 (6 %)
6/36 (17 %)
168 (86 %)
123 (76 %)
26 (67 %)
Focal neurologic abnormalities
43 (22 %)
58 (36 %)
14 (36 %)
50 (26 %)
52 (32 %)
13 (36 %)
39/191 (21 %)
44/157 (29 %)
13 (33 %)
56/186 (30 %)
64/158 (41 %)
18/38 (47 %)
Seizures during admission
25/192 (14 %)
27/154 (18 %)
5/39 (13 %)
Focal neurologic deficit during admission
44/188 (23 %)
38/155 (24 %)
15/37 (41 %)
57/195 (29 %)
52/162 (32 %)
22/38 (58 %)
12/195 (6 %)
13/162 (8 %)
4/38 (11 %)
In the first genome wide association study on outcome in pneumococcal meningitis gene variants in AKT3, DCTN4 and RAET1E were associated with unfavourable outcome in adults with pneumococcal meningitis. As no clinical cohort is available for validation , we explored our findings in our pneumococcal meningitis mouse model. The identified downregulation and increased mortality during experimental meningitis confirmed a role of Akt3 during pneumococcal meningitis, although the exact mechanism remains unclear.
In pneumococcal meningitis, brain damage and unfavourable outcome result from massive neutrophil recruitment and inflammation of the brain, reflected by CSF pleocytosis, seizures, and cerebrovascular complications [30, 31]. Patients with the AKT3 risk allele had a higher level of disease severity, consisting of lower level of consciousness, and a higher risk for epileptic seizures. AKT3 is a critical signalling protein in the Phosphoinositide 3-kinase pathway involved in diverse cellular process such as cell survival, growth, proliferation, metabolism and migration . Inhibition of AKT has been shown to promote apoptosis in many cell types [33, 34].
AKT has been shown to be essential to induce neutrophil extracellular traps, which are pro-inflammatory and important to kill bacteria . In a model of myelin-oligodendrocyte glycoprotein–induced experimental autoimmune encephalomyelitis (EAE), Akt3 -/- mice were more severely affected than wild-type mice . Experiments using bone marrow chimeras demonstrated that Akt3 -/- mice receiving Akt3-deficient bone marrow cells had elevated clinical scores relative to control wild-type mice reconstituted with wild-type cells, indicating that altered function of both central nervous system (CNS) cells and bone marrow-derived immune cells contributed to the phenotype . These experiments showed that Akt3 -/- mice have increased inflammatory cytokine expression in spinal cord during acute EAE . In our experiments, Akt3 -/- mice had similar bacterial outgrowth and mild host inflammatory response as compared to wild-type mice. For neuropathology, we only evaluated a relatively early time-point (24 h) without antibiotic treatment in which gross pathology usually do not present yet. As knockout mice started to die after 24 h however, we were unable to postpone this time point without introducing selection bias in our results. Nevertheless, Akt3 -/- mice showed increased parenchymal infiltration and artery inflammation as compared to wild-type mice, suggesting an important role of AKT3 in brain integrity and inflammation. In line, a plausible mechanism in which AKT3 is involved in meningitis is by influencing the inflammatory response through influencing apoptosis of inflammatory cells.
An alternative explanation for the poor prognosis associated with AKT3 could be a decreased seizure threshold. Enhanced activation of the mammalian target of rapamycin (mTOR)-signalling cascade has been identified in focal malformations of cortical development subtypes, which have been collectively referred to as “mTORopathies.” Mutations in mTOR regulatory genes such as AKT3 have been associated with epilepsy [37, 38]. Upstream and downstream molecules involved in serine/threonine kinase AKT pathways, including Akt3, were found to be involved in epilepsy pathophysiology . Indeed, patients with the risk genotype presented with a high rate of epileptic seizures, but we did not observe a higher seizure rate in our animal model. The animals however, were checked every 4 h (24 h after inoculation) and we did not perform a continuous (video) surveillance for seizures. We previously described that community acquired bacterial meningitis is complicated by seizures in 17 % of episodes and seizures are associated with a high mortality rate (41 %) . Seizures have been associated with severe CNS inflammation and structural CNS lesions, but it is unclear whether the seizures are due to, or cause CNS damage .
The genetic variant rs10157763 in AKT3 has been previously associated with aggressive prostate carcinoma and renal cell carcinoma . rs10157763 variant has been described to alter the transcriptional factor binding sites (TFBS) for transcription factors that regulate AKT3 expression.
Genetic variants in DCTN4 and RAET1E were also associated with functional outcome in pneumococcal meningitis, but these findings will need to be validated. DCTN4 is a component of the dynein-dependent motor that moves autophagosomes along microtubules into lysosomes for degradation as part of the autophagy process - a highly conserved cellular quality control mechanism to transport and degrade damaged proteins and microbes [40, 41]. Exome sequencing of extreme phenotypes previously has identified DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in patients with cystic fibrosis . RAET1E is a major histocompatibility complex class 1-like molecule and is a functional ligand for an activating receptor expressed on the surface of immune antigen-presenting cells such as natural killer (NK) cells, CD8(+) T cells, and subsets of CD4(+) T cells . High levels of RAET1E expression on antigen-presenting cells induces down-regulation of NK cell activation by a regulatory T-cell subset . NK cells have been shown to be important for the protection against various microbial pathogens, including S. pneumoniae , and have shown to contribute to mortality in experimental pneumococcal pneumonia . We did not further study these genes in our animal model as we did not find the genes differentially expressed during meningitis, although this does not completely negate a role in the pathophysiology of pneumococcal meningitis.
Our study has several limitations. First, captured variations with the Human Exome BeadChip are mainly restricted to protein coding regions and used as stand-alone array for identification of the causal variant can be difficult.
Second, some selection bias was possibly introduced since DNA was not available for a considerable proportion of patients (34 %), particularly those with more severe disease. Inclusion of patients with less severe disease will decrease study power to detect genetic variants associated with outcome, resulting in more type II errors (accepting the null hypothesis when it is false). The nationwide design allowed us to detect this selection bias. Third, we could not validate our findings of the genetic association study in a different cohort. The candidate SNPs were associated with unfavourable outcome with a p-value lower than 1 × 10−4, indicating that findings could still be a type I error. However, no cohorts are currently available for outcome in adult pneumococcal meningitis to validate our results. Therefore, we validated one genetic variant that was upregulated during meningitis in our adult mouse pneumococcal meningitis model . Fourth, to further contribute to elucidate the underlying mechanism(s) on meningitis-associated brain pathology, information regarding tissue protein expression of Akt3 and TNF-α, phenotypical characterization of the cell infiltrate and experiments using TNF- α blocking agents should be assessed in further experiments.
In conclusion, we identified gene variants in AKT3, DCTN4 and RAET1E to be associated with unfavourable outcome in adults with pneumococcal meningitis. We validated the role of Akt3 in our experimental pneumococcal meningitis model. Our study show that a GWAS approach in pneumococcal meningitis provides new insights in the pathophysiology of pneumococcal disease and may provide new leads for the development of adjunctive therapies.
Ethics approval and consent to participate
Informed consent was obtained from all individual participants included in the study. The protocol used in this study was approved by the Academic Medical Center, Amsterdam and all local participating hospitals.
All applicable international, national, and/or institutional guidelines for the care and use of animals were followed. All procedures performed in studies involving animals were in accordance with the ethical standards of the institution or practice at which the studies were conducted.
Consent for publication
This study makes use of data generated by the Netherlands ExomeChip Project. A full list of the investigators is available from www.bbmri.nl. Funding for the project was provided by the Netherlands Organization for Scientific Research under award number 184021007, dated July 9, 2009 and made available as a Rainbow Project of the Biobanking and Biomolecular Research Infrastructure Netherlands. This work was supported by grants from the European Research Council (ERC Starting Grant [proposal/contract 281156]), Netherlands Organization for Health Research and Development (ZonMw; NWO-Vidi grant 2010 [proposal/contract 016.116.358]), both to DvdB. We thank Morris Birnbaum for providing the AKT3 KO mice.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Brouwer MC, Tunkel AR, van de Beek D. Epidemiology, diagnosis, and antimicrobial treatment of acute bacterial meningitis. Clin Microbiol Rev. 2010;23(3):467–92. doi:10.1128/CMR.00070-09.View ArticlePubMedPubMed CentralGoogle Scholar
- van de Beek D, de Gans J, Spanjaard L, Weisfelt M, Reitsma JB, Vermeulen M. Clinical features and prognostic factors in adults with bacterial meningitis. N Engl J Med. 2004;351(18):1849–59. doi:10.1056/NEJMoa040845.View ArticlePubMedGoogle Scholar
- Weisfelt M, de Gans J, van der Poll T, van de Beek D. Pneumococcal meningitis in adults: new approaches to management and prevention. Lancet Neurol. 2006;5(4):332–42. doi:10.1016/s1474-4422(06)70409-4.View ArticlePubMedGoogle Scholar
- van de Beek D, Schmand B, de Gans J, Weisfelt M, Vaessen H, Dankert J, Vermeulen M. Cognitive impairment in adults with good recovery after bacterial meningitis. J Infect Dis. 2002;186(7):1047–52. doi:10.1086/344229.View ArticlePubMedGoogle Scholar
- Schut ES, Lucas MJ, Brouwer MC, Vergouwen MD, van der Ende A, van de Beek D. Cerebral infarction in adults with bacterial meningitis. Neurocrit Care. 2012;16(3):421–7. doi:10.1007/s12028-011-9634-4.View ArticlePubMedGoogle Scholar
- Zoons E, Weisfelt M, de Gans J, Spanjaard L, Koelman JH, Reitsma JB, van de Beek D. Seizures in adults with bacterial meningitis. Neurology. 2008;70(22 Pt 2):2109–15. doi:10.1212/01.wnl.0000288178.91614.5d.View ArticlePubMedGoogle Scholar
- Hoogman M, van de Beek D, Weisfelt M, de Gans J, Schmand B. Cognitive outcome in adults after bacterial meningitis. J Neurol Neurosurg Psychiatry. 2007;78(10):1092–6. doi:10.1136/jnnp.2006.110023.View ArticlePubMedPubMed CentralGoogle Scholar
- de Gans J, van de Beek D. Dexamethasone in adults with bacterial meningitis. N Engl J Med. 2002;347(20):1549–56. doi:10.1056/NEJMoa021334.View ArticlePubMedGoogle Scholar
- Bijlsma MW, Brouwer MC, Kasanmoentalib ES, Kloek AT, Lucas MJ, Tanck MW, van der Ende A, van de Beek D. Community-acquired bacterial meningitis in adults in the Netherlands, 2006-14: a prospective cohort study. Lancet Infect Dis. 2016;16(3):339–47. doi:10.1016/s1473-3099(15)00430-2.View ArticlePubMedGoogle Scholar
- Schut ES, Brouwer MC, de Gans J, Florquin S, Troost D, van de Beek D. Delayed cerebral thrombosis after initial good recovery from pneumococcal meningitis. Neurology. 2009;73(23):1988–95. doi:10.1212/WNL.0b013e3181c55d2e.View ArticlePubMedGoogle Scholar
- Brouwer MC, Heckenberg SG, de Gans J, Spanjaard L, Reitsma JB, van de Beek D. Nationwide implementation of adjunctive dexamethasone therapy for pneumococcal meningitis. Neurology. 2010;75(17):1533–9. doi:10.1212/WNL.0b013e3181f96297.View ArticlePubMedGoogle Scholar
- van de Beek D, de Gans J, Tunkel AR, Wijdicks EF. Community-acquired bacterial meningitis in adults. N Engl J Med. 2006;354(1):44–53. doi:10.1056/NEJMra052116.View ArticlePubMedGoogle Scholar
- van de Beek D, Brouwer MC, Thwaites GE, Tunkel AR. Advances in treatment of bacterial meningitis. Lancet. 2012;380(9854):1693–702. doi:10.1016/s0140-6736(12)61186-6.View ArticlePubMedGoogle Scholar
- Woehrl B, Brouwer MC, Murr C, Heckenberg SG, Baas F, Pfister HW, Zwinderman AH, Morgan BP, Barnum SR, van der Ende A, Koedel U, van de Beek D. Complement component 5 contributes to poor disease outcome in humans and mice with pneumococcal meningitis. J Clin Invest. 2011;121(10):3943–53. doi:10.1172/JCI57522.View ArticlePubMedPubMed CentralGoogle Scholar
- Brouwer MC, de Gans J, Heckenberg SG, Zwinderman AH, van der Poll T, van de Beek D. Host genetic susceptibility to pneumococcal and meningococcal disease: a systematic review and meta-analysis. Lancet Infect Dis. 2009;9(1):31–44.View ArticlePubMedGoogle Scholar
- Kasanmoentalib ES, Brouwer MC, van de Beek D. Update on bacterial meningitis: epidemiology, trials and genetic association studies. Curr Opin Neurol. 2013;26(3):282–8. doi:10.1097/WCO.0b013e328360415c.View ArticlePubMedGoogle Scholar
- Brouwer MC, Read RC, van de Beek D. Host genetics and outcome in meningococcal disease: a systematic review and meta-analysis. Lancet Infect Dis. 2010;10(4):262–74. doi:10.1016/s1473-3099(10)70045-1.View ArticlePubMedGoogle Scholar
- van de Beek D. Progress and challenges in bacterial meningitis. Lancet. 2012;380(9854):1623–4. doi:10.1016/s0140-6736(12)61808-x.View ArticlePubMedGoogle Scholar
- Jennett B, Teasdale G, Braakman R, Minderhoud J, Knill-Jones R. Predicting outcome in individual patients after severe head injury. Lancet. 1976;1(7968):1031–4.View ArticlePubMedGoogle Scholar
- Guo Y, He J, Zhao S, Wu H, Zhong X, Sheng Q, Samuels DC, Shyr Y, Long J. Illumina human exome genotyping array clustering and quality control. Nat Protoc. 2014;9(11):2643–62. doi:10.1038/nprot.2014.174.View ArticlePubMedPubMed CentralGoogle Scholar
- Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3):559–75. doi:10.1086/519795.View ArticlePubMedPubMed CentralGoogle Scholar
- Easton RM, Cho H, Roovers K, Shineman DW, Mizrahi M, Forman MS, Lee VM, Szabolcs M, de Jong R, Oltersdorf T, Ludwig T, Efstratiadis A, Birnbaum MJ. Role for Akt3/protein kinase Bgamma in attainment of normal brain size. Mol Cell Biol. 2005;25(5):1869–78. doi:10.1128/mcb.25.5.1869-1878.2005.View ArticlePubMedPubMed CentralGoogle Scholar
- Mook-Kanamori B, Geldhoff M, Troost D, van der Poll T, van de Beek D. Characterization of a pneumococcal meningitis mouse model. BMC Infect Dis. 2012;12:71. doi:10.1186/1471-2334-12-71.View ArticlePubMedPubMed CentralGoogle Scholar
- Geldhoff M, Mook-Kanamori BB, Brouwer MC, Troost D, Leemans JC, Flavell RA, Van der Ende A, Van der Poll T, Van de Beek D. Inflammasome activation mediates inflammation and outcome in humans and mice with pneumococcal meningitis. BMC Infect Dis. 2013;13:358. doi:10.1186/1471-2334-13-358.View ArticlePubMedPubMed CentralGoogle Scholar
- Valls Seron M, Duitman J, Geldhoff M, Engelen-Lee J, Havik SR, Brouwer MC, van de Beek D, Spek CA. CCAAT/enhancer-binding protein delta (C/EBPdelta) aggravates inflammation and bacterial dissemination during pneumococcal meningitis. J Neuroinflammation. 2015;12:88. doi:10.1186/s12974-015-0309-5.View ArticlePubMedGoogle Scholar
- Arsenijevic T, Gregoire F, Delforge V, Delporte C, Perret J. Murine 3T3-L1 adipocyte cell differentiation model: validated reference genes for qPCR gene expression analysis. PLoS One. 2012;7(5):e37517. doi:10.1371/journal.pone.0037517.View ArticlePubMedPubMed CentralGoogle Scholar
- Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4:7. doi:10.1186/s13742-015-0047-8.View ArticlePubMedPubMed CentralGoogle Scholar
- Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR. A method and server for predicting damaging missense mutations. Nat Methods. 2010;7(4):248–9. doi:10.1038/nmeth0410-248.View ArticlePubMedPubMed CentralGoogle Scholar
- Weisfelt M, van de Beek D, Spanjaard L, Reitsma JB, de Gans J. Clinical features, complications, and outcome in adults with pneumococcal meningitis: a prospective case series. Lancet Neurol. 2006;5(2):123–9. doi:10.1016/s1474-4422(05)70288-x.View ArticlePubMedGoogle Scholar
- Mook-Kanamori BB, Geldhoff M, van der Poll T, van de Beek D. Pathogenesis and pathophysiology of pneumococcal meningitis. Clin Microbiol Rev. 2011;24(3):557–91. doi:10.1128/cmr.00008-11.View ArticlePubMedPubMed CentralGoogle Scholar
- Engelen-Lee JY, Brouwer MC, Aronica E, van de Beek D. Pneumococcal meningitis: Clinical-pathological correlations (meningene-path). Acta Neuropathol Commun. 2016;4(1):26. doi:10.1186/s40478-016-0297-4.View ArticlePubMedPubMed CentralGoogle Scholar
- Tokuda S, Mahaffey CL, Monks B, Faulkner CR, Birnbaum MJ, Danzer SC, Frankel WN. A novel Akt3 mutation associated with enhanced kinase activity and seizure susceptibility in mice. Hum Mol Genet. 2011;20(5):988–99. doi:10.1093/hmg/ddq544.View ArticlePubMedPubMed CentralGoogle Scholar
- Dudek H, Datta SR, Franke TF, Birnbaum MJ, Yao R, Cooper GM, Segal RA, Kaplan DR, Greenberg ME. Regulation of neuronal survival by the serine-threonine protein kinase Akt. Science. 1997;275(5300):661–5.View ArticlePubMedGoogle Scholar
- Datta SR, Brunet A, Greenberg ME. Cellular survival: a play in three Akts. Genes Dev. 1999;13(22):2905–27.View ArticlePubMedGoogle Scholar
- Brinkmann V, Reichard U, Goosmann C, Fauler B, Uhlemann Y, Weiss DS, Weinrauch Y, Zychlinsky A. Neutrophil extracellular traps kill bacteria. Science. 2004;303(5663):1532–5. doi:10.1126/science.1092385.View ArticlePubMedGoogle Scholar
- Tsiperson V, Gruber RC, Goldberg MF, Jordan A, Weinger JG, Macian F, Shafit-Zagardo B. Suppression of inflammatory responses during myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis is regulated by AKT3 signaling. J Immunol. 2013;190(4):1528–39. doi:10.4049/jimmunol.1201387.View ArticlePubMedPubMed CentralGoogle Scholar
- Crino PB. mTOR signaling in epilepsy: insights from malformations of cortical development. Cold Spring Harb Perspect Med. 2015;5(4). doi:10.1101/cshperspect.a022442.Google Scholar
- Cohen Jr MM. The AKT genes and their roles in various disorders. Am J Med Genet A. 2013;161a(12):2931–7. doi:10.1002/ajmg.a.36101.View ArticlePubMedGoogle Scholar
- Lavender NA, Rogers EN, Yeyeodu S, Rudd J, Hu T, Zhang J, Brock GN, Kimbro KS, Moore JH, Hein DW, Kidd LC. Interaction among apoptosis-associated sequence variants and joint effects on aggressive prostate cancer. BMC Med Genomics. 2012;5:11. doi:10.1186/1755-8794-5-11.View ArticlePubMedPubMed CentralGoogle Scholar
- Kimura S, Noda T, Yoshimori T. Dynein-dependent movement of autophagosomes mediates efficient encounters with lysosomes. Cell Struct Funct. 2008;33(1):109–22.View ArticlePubMedGoogle Scholar
- Haspel JA, Choi AM. Autophagy: a core cellular process with emerging links to pulmonary disease. Am J Respir Crit Care Med. 2011;184(11):1237–46. doi:10.1164/rccm.201106-0966CI.View ArticlePubMedPubMed CentralGoogle Scholar
- Emond MJ, Louie T, Emerson J, Zhao W, Mathias RA, Knowles MR, Wright FA, Rieder MJ, Tabor HK, Nickerson DA, Barnes KC, Gibson RL, Bamshad MJ. Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis. Nat Genet. 2012;44(8):886–9. doi:10.1038/ng.2344.View ArticlePubMedPubMed CentralGoogle Scholar
- Ogasawara K, Lanier LL. NKG2D in NK and T cell-mediated immunity. J Clin Immunol. 2005;25(6):534–40. doi:10.1007/s10875-005-8786-4.View ArticlePubMedGoogle Scholar
- Lin Z, Wang C, Xia H, Liu W, Xiao W, Qian L, Jia X, Ding Y, Ji M, Gong W. CD4(+) NKG2D(+) T cells induce NKG2D down-regulation in natural killer cells in CD86-RAE-1epsilon transgenic mice. Immunology. 2014;141(3):401–15. doi:10.1111/imm.12203.View ArticlePubMedPubMed CentralGoogle Scholar
- Zajonc DM, Girardi E. Recognition of microbial glycolipids by natural killer T cells. Front Immunol. 2015;6:400. doi:10.3389/fimmu.2015.00400.View ArticlePubMedPubMed CentralGoogle Scholar
- Christaki E, Diza E, Giamarellos-Bourboulis EJ, Papadopoulou N, Pistiki A, Droggiti DI, Georgitsi M, Machova A, Lambrelli D, Malisiovas N, Nikolaidis P, Opal SM. NK and NKT cell depletion alters the outcome of experimental pneumococcal pneumonia: relationship with regulation of interferon-gamma production. J Immunol Res. 2015;2015:532717. doi:10.1155/2015/532717.View ArticlePubMedPubMed CentralGoogle Scholar