Periodic Reporting for period 2 - I-PACE (Improving Prognosis by using innovative methods to diAgnose Causes of Encephalitis)
Período documentado: 2023-06-01 hasta 2024-11-30
Acute encephalitis is the syndrome of inflammation of the brain. Patients with encephalitis commonly have fever, a decreased level of consciousness, epileptic seizures and neurologic deficits. The cause of encephalitis can be difficult to detect and can include viruses, bacteria, fungi and parasitic infections, but also autoimmune disease.
Current diagnostics for encephalitis are insufficient. In a prospective pilot study I showed that the cause of encephalitis could be identified in only half of patients. The lack of early and cause-specific diagnosis results in a delay in adequate treatment and poor outcome.
The aim of the I-PACE project is to increase the proportion of patients with a cause-specific diagnosis of encephalitis from 50 to 80% and thereby improve the prognosis by facilitating early and targeted treatment.
To achieve this aim my objectives are to
- identify new infectious causes of encephalitis using next generation pathogen discovery sequencing;
- identify transcription patterns per cell type, specific for the different causes of encephalitis using single cell gene expression studies;
- identify new causes of auto-immune encephalitis using single cell immune profiling, rat brain immunohistochemistry and cell based antibody assays;
- identify new biomarkers enabling a syndromic diagnosis using CSF metabolomics and lipidomics studies
Current diagnostics for encephalitis are insufficient. In a prospective pilot study I showed that the cause of encephalitis could be identified in only half of patients. The lack of early and cause-specific diagnosis results in a delay in adequate treatment and poor outcome.
The aim of the I-PACE project is to increase the proportion of patients with a cause-specific diagnosis of encephalitis from 50 to 80% and thereby improve the prognosis by facilitating early and targeted treatment.
To achieve this aim my objectives are to
- identify new infectious causes of encephalitis using next generation pathogen discovery sequencing;
- identify transcription patterns per cell type, specific for the different causes of encephalitis using single cell gene expression studies;
- identify new causes of auto-immune encephalitis using single cell immune profiling, rat brain immunohistochemistry and cell based antibody assays;
- identify new biomarkers enabling a syndromic diagnosis using CSF metabolomics and lipidomics studies
Midterm milestones:
In the first half of the project multiple milestones have been reached, per 1st of June 2024:
- A total of 2000 patients suspected of a CNS infection have been included in the Netherlands;
- Since Jan 2022 the study has been expanded to also include children with suspected encephalitis;
- A total of 15 hospitals now participate in IPACE, of which 7 hospitals include both adults and children;
- The first batch of 300 validation CSF samples from Denmark has been received in 2023;
- A total of 600 CSF and blood validation samples were received from Zambia in 2024.
Clinical Characteristics:
In the I-PACE cohort of patients with suspected encephalitis we analyzed clinical characteristics to see which patients have a poor outcome. We found that patients with autoimmune encephalitis have a worse prognosis because the diagnosis is often delayed and treatment therefore started late. So for new diagnostic tests it is important to focus on this population and facilitate early recognition and treatment. Furthemore, we focused on patients admitted to the hospital in whom there is a suspicion of a brain infection. There is often a discussion on whether a lumbar puncture is really needed in patients with fever of unknown origin to rule out a brain infection. Our data show clearly that a lumbar puncture changed the medical management in half of the patients.
Biomarkers:
We have studied the diagnostic value of both the proportion and absolute number of granulocytes (acute inflammatory cells) in the cerebrospinal fluid, in contrast to the monocytes (late reponding inflammatory cells). We found that the proportion of granulocytes in the cerebrospinal fluid is highest in patients with a bacterial cause of encephalitis. However, as high and low granuloyctes proportion was present in all diagnostic categories, its diagnostic value is not optimal. In comparison to other markers of (bacterial) infection of the brain, it is however one of the best biomarkers.
Furthemore, we studied novel biomarkers in neonates with sepsis and meningitis to differentiate the two clinical entities use cerebrospinal fluid. We found inflammatory markers IL-1RA, TNF-α, and CXCL-10 in CSF to enable good discrimination between the two disease entities. We will prospectively validate these finding in a cohort of neonates with suspected meningitis.
Prediction models:
Over 30 prediction models have been published in the literature, but these often lack validation and also frequently do not focus on the clinically relevant population - patients with a suspected infection of the brain. We used patient data from adults and children included the IPACE cohort to validate the diagnostic prediction rules and found that these models often fail to accurately predict the diagnosis and new biomarkers or AI models are needed to improve diagnostic prediction. We developed and validated our own prediction model for bacterial meningitis, and validated novel models recently published.
In the first half of the project multiple milestones have been reached, per 1st of June 2024:
- A total of 2000 patients suspected of a CNS infection have been included in the Netherlands;
- Since Jan 2022 the study has been expanded to also include children with suspected encephalitis;
- A total of 15 hospitals now participate in IPACE, of which 7 hospitals include both adults and children;
- The first batch of 300 validation CSF samples from Denmark has been received in 2023;
- A total of 600 CSF and blood validation samples were received from Zambia in 2024.
Clinical Characteristics:
In the I-PACE cohort of patients with suspected encephalitis we analyzed clinical characteristics to see which patients have a poor outcome. We found that patients with autoimmune encephalitis have a worse prognosis because the diagnosis is often delayed and treatment therefore started late. So for new diagnostic tests it is important to focus on this population and facilitate early recognition and treatment. Furthemore, we focused on patients admitted to the hospital in whom there is a suspicion of a brain infection. There is often a discussion on whether a lumbar puncture is really needed in patients with fever of unknown origin to rule out a brain infection. Our data show clearly that a lumbar puncture changed the medical management in half of the patients.
Biomarkers:
We have studied the diagnostic value of both the proportion and absolute number of granulocytes (acute inflammatory cells) in the cerebrospinal fluid, in contrast to the monocytes (late reponding inflammatory cells). We found that the proportion of granulocytes in the cerebrospinal fluid is highest in patients with a bacterial cause of encephalitis. However, as high and low granuloyctes proportion was present in all diagnostic categories, its diagnostic value is not optimal. In comparison to other markers of (bacterial) infection of the brain, it is however one of the best biomarkers.
Furthemore, we studied novel biomarkers in neonates with sepsis and meningitis to differentiate the two clinical entities use cerebrospinal fluid. We found inflammatory markers IL-1RA, TNF-α, and CXCL-10 in CSF to enable good discrimination between the two disease entities. We will prospectively validate these finding in a cohort of neonates with suspected meningitis.
Prediction models:
Over 30 prediction models have been published in the literature, but these often lack validation and also frequently do not focus on the clinically relevant population - patients with a suspected infection of the brain. We used patient data from adults and children included the IPACE cohort to validate the diagnostic prediction rules and found that these models often fail to accurately predict the diagnosis and new biomarkers or AI models are needed to improve diagnostic prediction. We developed and validated our own prediction model for bacterial meningitis, and validated novel models recently published.
We have perfomed several studies that brought the field forward or are curerntly in the validation phase.
Biomakers:
First, in a study of blood and cerebrospinal fluid of patients with suspected encephalitis we found that blood markers of inflammation are not useful to discriminatie between causes of encephalitis. However, we did find that biomarkers CRP, IL-6, and Il-1β in cerebrospinal fluid were highly predictive of infections of the brain. Subsequently, we validated the resuls in the Danish validation cohort in IPACE and showed that CRP in cerebrospinal fluid has a high diagnostic accuracy to distinguish bacterial meningitis from other infections. For the validation we used the assay that is used in clinical practice to measure blood CRP levels, which we now showed can also be used for cerebrospinal fluid. The test has been introduced in clinical practice in our hospital and we currently perform an implementation study. We are very proud to have introduced a new test into clinical practice halfway this ERC project.
Pathogen discovery sequencing:
We were able to identify bacteria in cerebrospinal fluid using a viromics approach in CSF. Furthermore, we have performed a pilot study with a targeted metagenomics platform including 250 probes to enrich the metagenomics process. This pilot included 180 patients and the results are currently being analyzed. Preliminary data have been presented at the ESCMID global conference in April 2024.
CSF single cell sequencing/single cell antibody repertoire sequencing:
Single cell sequencing of CSF appeared to be more difficult than expected as the cells need to be sequenced alive. As the (8-plex) assay is too expensive to perform for a single sample we first had to design and test method for freezing and thawing the cells without too much cell death. We developed a protocol to do this, which results in a 90% survival rate. Successfully setting up this method took about 10 months. Currently, we have sequenced 12 samples with good results and are increasing the samples size with 8-10 samples per 2 months. As comparator we have sequenced RNA in 140 patients blood and cerebrospinal fluid samples.
Auto-antibody testing: We have tested all patients in whom an autoimmune encephalitis was suspected for anti-neuronal antibodies using rat brain immunohistochemistry and identified auto-antibodies in 9 of 59 patients. There was no additional yield of extensive testing for antineuronal antibodies in patients in whom during clinical course no antineuronal antibodies were identified.
Metabolomics: We have performed lipidomics and metabolomics in CSF of 200 patients and identified multiple interesting biomarkers for the diagnosis of bacterial and viral causes of encephalitis en autoimmune encephalitis. We are now developing the biomakers with the highest diagnostic accuracy in simpler assays that can be used in clinical practice.
Biomakers:
First, in a study of blood and cerebrospinal fluid of patients with suspected encephalitis we found that blood markers of inflammation are not useful to discriminatie between causes of encephalitis. However, we did find that biomarkers CRP, IL-6, and Il-1β in cerebrospinal fluid were highly predictive of infections of the brain. Subsequently, we validated the resuls in the Danish validation cohort in IPACE and showed that CRP in cerebrospinal fluid has a high diagnostic accuracy to distinguish bacterial meningitis from other infections. For the validation we used the assay that is used in clinical practice to measure blood CRP levels, which we now showed can also be used for cerebrospinal fluid. The test has been introduced in clinical practice in our hospital and we currently perform an implementation study. We are very proud to have introduced a new test into clinical practice halfway this ERC project.
Pathogen discovery sequencing:
We were able to identify bacteria in cerebrospinal fluid using a viromics approach in CSF. Furthermore, we have performed a pilot study with a targeted metagenomics platform including 250 probes to enrich the metagenomics process. This pilot included 180 patients and the results are currently being analyzed. Preliminary data have been presented at the ESCMID global conference in April 2024.
CSF single cell sequencing/single cell antibody repertoire sequencing:
Single cell sequencing of CSF appeared to be more difficult than expected as the cells need to be sequenced alive. As the (8-plex) assay is too expensive to perform for a single sample we first had to design and test method for freezing and thawing the cells without too much cell death. We developed a protocol to do this, which results in a 90% survival rate. Successfully setting up this method took about 10 months. Currently, we have sequenced 12 samples with good results and are increasing the samples size with 8-10 samples per 2 months. As comparator we have sequenced RNA in 140 patients blood and cerebrospinal fluid samples.
Auto-antibody testing: We have tested all patients in whom an autoimmune encephalitis was suspected for anti-neuronal antibodies using rat brain immunohistochemistry and identified auto-antibodies in 9 of 59 patients. There was no additional yield of extensive testing for antineuronal antibodies in patients in whom during clinical course no antineuronal antibodies were identified.
Metabolomics: We have performed lipidomics and metabolomics in CSF of 200 patients and identified multiple interesting biomarkers for the diagnosis of bacterial and viral causes of encephalitis en autoimmune encephalitis. We are now developing the biomakers with the highest diagnostic accuracy in simpler assays that can be used in clinical practice.