Abstract
Beyond its socio-economic impact, COVID-19 has been associated with respiratory, gastrointestinal, neurological and neuropsychiatric symptoms across many countries, including in Senegal. While the SARS-CoV-2 virus primarily targets the respiratory and cardiovascular systems, if not detected and treated early, it can invade the nervous system and lead to severe neurological complications. This study focuses on the molecular and serological characterization of the SARS-CoV-2 strains associated with encephalitis manifestations of the disease. The presence of the virus in the central nervous system was confirmed by RT-PCR and sequencing and also serological techniques. Genetic analysis identified Delta (B.1.617.2-like) and Eta (B.1.525-like) variants in encephalitis patients. In silico analysis revealed three mutations (p.Pro4619Leu, p.Ala103Pro and p.Thr40Ile) predicted to affect protein function, generating hypotheses regarding their possible involvement in neurological manifestations. Among 11 patients with SARS-CoV-2-associated encephalitis, 30% had SARS-CoV-2 IgG antibodies in their serum, and 20% had them in cerebrospinal fluid (CSF). As part of the surveillance system for infectious encephalitis in Senegal (ENSENE), our data provided evidence of SARS-CoV-2 involvement in the epidemiology of viral encephalitis during the COVID-19 pandemic. Similar approaches should be promoted in future studies to investigate the biological significance of these mutations and improve the diagnosis and management of neurological manifestations associated with SARS-CoV-2 infection.
Keywords: SARS-CoV-2, Viral encephalitis, Cerebrospinal fluid, Sequencing, Serology, Anti-SARS-CoV-2 immunoglobulins, Senegal
Background: In December 2019, several cases of unexplained pneumonia were reported in Wuhan (China). This epidemic was confirmed to be caused by a new coronavirus with genetic and symptomatic similarities to the virus responsible for the 2002-2003 severe acute respiratory syndrome epidemic that affected China and other countries worldwide [1]. The two viruses belonging to the beta coronavirus family share the same receptor, angiotensin-converting enzyme 2 (ACE2). Consequently, this virus was named SARS-CoV-2, and in February 2020, the World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19), a public health event of international concern. As of March 2023, a total of 759,408,703 confirmed cases of COVID-19 and 6,866,434 associated deaths had been reported worldwide. In Africa, a cumulative number of confirmed cases reached 12,521,507, with 257,664 fatalities. In Senegal, the first confirmed case of SARS-CoV-2 infection was detected in March 2020. The country experienced its initial epidemic wave between March and September 2020, with an epidemiological peak at the end of July. The second wave began in late November 2020, peaking in February 2021, followed by a third wave in late December 2021. As of March 2023, Senegal had reported 88,926 confirmed cases and 1971 deaths [2].
Although SARS-CoV-2 primarily causes respiratory disease, neurological manifestations including encephalopathy, seizures, stroke and encephalitis have increasingly been reported [3,4]. These neurological signs can occur before, during or after respiratory symptoms, and are unrelated to respiratory failure, suggesting an independent mechanism of brain damage. Follow-up's data in Germany and the Ukraine (UK) have revealed post-COVID-19 neurological disorders in 20-70% of patients, even in young people, and lasting for several months after respiratory symptoms have ceased [3].
Although encephalitis remains an uncommon complication of COVID-19, increasing evidence suggests that SARS-CoV-2 may affect the central nervous system through direct or indirect mechanisms. However, data regarding SARS-CoV-2-associated encephalitis remain limited, particularly in Africa, and little is known about the molecular characteristics of viral strains associated with neurological manifestations. Therefore, this study aimed to characterize the clinical, molecular and serological features of SARS-CoV-2-associated encephalitis cases identified through the surveillance system for infectious encephalitis in Senegal (ENSENE) and to describe the genetic diversity of circulating strains associated with these neurological complications.
1. Materials and methods
1.1. Ethical statement
The research project was conducted in accordance with the Declaration of Helsinki and has been approved by the National Ethics Committee for Health Research of the Ministry of Health and Social Action (Authorization N° 0094/MSAS/CNERS/SP, dated April 19, 2022). Specimens were collected as part of routine clinical care procedures for the management of patients presenting with encephalitis. Lumbar punctures were performed by experienced clinicians if recommended for the diagnosis of the cause of the encephalitis and to adapt the treatment consequently. All virology tests were performed at no cost for the patient. A unique identification number (ID) was assigned for each sample collected to anonymise data from included patients.
1.2. Population and study setting
A retrospective longitudinal study was conducted from January 2021 to December 2022, as part of the research project entitled " Surveillance of infectious encephalitis in Senegal (ENSENE)". Patients with COVID-19 and a clinical hallmark of encephalitis including fever, convulsion, coma among others [5], were recruited at the neurology departments of two referral hospitals in the Dakar region (National University Hospital Center (CHNU) of Fann and National Hospital (CHN) in Pikine).
1.3. Inclusion criteria
All patients with COVID-19 presenting with fever (≥38°C) accompanied by one or more clinically assessed signs of encephalitis requiring hospitalization were included in this study after obtaining the informed and signed consent from the patient or a close relative. These clinical signs of encephalitis were: convulsion, behavioral disturbance without antecedent and/or predisposing symptoms, motor deficit, recent memory loss, decreased or altered alertness, lethargy or personality changes lasting more than 24 h with no other cause identified, partial or generalized epileptic seizures not attributable to pre-existing epilepsy, new focal neurological abnormalities, neuroradiological abnormalities (MRI/CT) suggestive of recent acute encephalitis and EEG abnormalities compatible with encephalitis.
1.4. Non-inclusion criteria
Non-inclusion criteria for this study comprise: (i) refusal to participate by the patient or his/her guardian/representative, (ii) patients who presented and succumbed prior to any clinical diagnosis and paraclinical examination, and (iii) patients with a pathology requiring management in a speciality other than neurology (e.g. neurosurgery).
1.5. Exclusion criteria
Any patient who does not meet the case definition or for whom lumbar puncture is not recommended (e.g. in the case of haemorrhage) is excluded from the study.
1.6. Sample collection
For each of the 11 patients included in the study, the following samples were collected: cerebrospinal fluid (CSF), nasopharyngeal swabs (NP) and venous blood. These samples were accompanied by case investigation forms, which recorded patient information, including age, sex, sampling date and clinical symptoms.
Age groups are defined according as previously described: children (≤15 years), adolescents (15- 34 years), adults (35 - 59 years) and elderly (≥60 years) [6].
Samples were sent first to the medical biology laboratory (LBM) for some paraclinical examinations of the CSF (biochemical and cytological tests), then to the National Reference Center for Rabies and Viral Encephalitis to perform the various molecular and serological analyses (Supplementary Fig. S1).
1.7. Extraction of viral nucleic acids
Viral RNA was extracted from 200 μL of CSF and NP using the Veri-Q PREP M16 nucleic acid extraction system (MiCoBioMed, Gyeonggi-do, South Korea) according to the manufacturer's instructions [7]. Briefly the extraction included three steps: first, cell lysis by addition of lysis buffer, then precipitation of DNA/RNA with isopropanol, and finally washing and elution.
1.8. Detection of the SARS-CoV-2 virus using the VERI-Q kit
Detection of the SARS-CoV-2 virus was performed by RT-PCR (real-time polymerase chain reaction) using the Coronavirus Disease 2019 Detection Kit (nCoV-QS) on the Veri-Q PCR 316 instrument (Cat. No.9R501, MiCoBioMed Co., Ltd. Korea). This real-time PCR kit is an automated system for the qualitative detection of SARS-CoV-2 RNA ORF3a and N genes from sputum, nasopharyngeal or oropharyngeal swab samples from patients with signs and symptoms suggestive of COVID-19 (e.g. fever and/or symptoms of acute respiratory illness).
1.9. Detection of SARS-CoV-2 by TaqMan RT-PCR (mutation panel)
This real-time RT-PCR detection is achieved with the SARS-CoV-2 Mutation Panel (Applied Biosystems TaqMan), which uses specific primers and probes with the TaqMan 5′ nuclease chemistry to amplify and detect specific variants in purified genomic RNA samples.
1.10. Next Generation sequencing (NGS) of the SARS-CoV-2 virus
Whole genome sequencing was performed for SARS-CoV-2 positive samples (CSF/NP) by RT-PCR using Illumina technologies. Genomes were extracted by an amplicon-based approach using the Illumina COVID-Seq kit approved by the US Food and Drug Administration. Extracted RNAs were transcribed into single-stranded complementary DNA according to the manufacturer's instructions, and SARS-CoV-2 PCR was performed with two specific primer pools combined with proven Illumina sequencing technology, resulting in 98 genomes wide 400 base pairs (bp) mosaic amplicons. For each sample, PCR products were combined, and libraries were prepared using Illumina Nextera DNA UD indices according to the manufacturer's instructions. Libraries were purified with AMPure XP magnetic beads (Beckman Coulter, Brea, CA, USA) and concentration measured using a Qubit dsDNA HS Assay kit (Thermo Fisher Scientific, Waltham, MA, USA). The libraries were validated using a Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA) in accordance with the manufacturer's instructions. The 400 bp pool of libraries was diluted to 2 nM, denatured and diluted to 100 pM, then sequenced on an Illumina Iseq100 instrument. The consensus genomes were generated using the fully open-source EDGE Bioinformatics software [8].
1.11. Genetic analysis of the newly characterized SARS-CoV-2 sequences
The sequences obtained after sequencing were meticulously aligned and manually curated using the Alignment Program MAFFT version 7 (https://mafft.cbrc.jp/alignment/server/) and the software BioEdit version 7.2.5 [9] which uses the W-clustal algorithm [10], respectively.
1.11.1. Phylogenetic analysis
For phylogenetic analysis, previous sequences of the various SARS-CoV-2 strains circulating in Senegal were downloaded from GenBank (www.ncbi.nlm.nih.gov/genbank/) and aligned those obtained from the patients with encephalitis, with the addition of an outgroup (SARS-CoV reference sequence). Using our sequences alignment, a Bayesian analysis was performed to determine the most appropriate nucleotide substitution model, considering the lowest BIC (Bayesian Information Criterion) score. The phylogenetic tree was inferred using the online software IQtree (http://iqtree.cibiv.univie.ac.at/) with the Maximum-Likelihood (ML) method with the appropriate nucleotide substitution model to our dataset. The ML tree was rooted on midpoints and nodes were marked with bootstrap values.
1.11.2. Assessment of potential amino acid motifs of virulence
In order to detect the presence of new mutations, SARS-CoV-2 sequences circulating in Senegal during our study period were uploaded to GISAID (Global Initiative on Sharing Avian Influenza Data) (https://gisaid.org/) for comparison with previous SARS-CoV-2 strains associated with neurological forms. The pathogenicity of the variants was determined for the exonic region in relation to non-synonymous mutations using SIFT (Scale-Invariant Feature Transform) (https://sift.bii.a-star.edu.sg/) software. This software is a probabilistic classifier that calculates the functional significance of an allele change. The input options for this method are the protein sequence obtained from the UNIPROTKB (Universal Protein Resource Knowledgebase) database (https://www.uniprot.org/) and the mutation (position of the amino acid in the reference sequence and that of the mutated amino acid). Any mutation with a score greater than or equal to 0.05 is classified as a tolerated mutation.
1.12. Detection of SARS-CoV-2 virus-specific immunoglobulin G
We used a multiplex bead-based serological assay developed by Institut Pasteur in Paris [11], enabling the simultaneous detection of antibodies directed against five SARS-CoV-2 antigens in less than 5 μL serum or CSF samples that were heat-inactivated at 56°C for 30 min before use. Serum and CSF samples were analysed in duplicate for type G immunoglobulins (IgG) directed against SARS-CoV-2 (ancestral variant): whole trimeric spike (WTS), spike's receptor-binding domain (RBD), spike subunit 2 (S2), nucleocapsid protein (NP), and a membrane-envelope (ME) fusion protein. The assay was conducted as described previously. Serum samples were diluted at 1:100, while CSF samples were diluted at either 1:20 or 1:100. Each assay plate included two blank wells (only beads without serum), pool of negative control to assess background signal along with a standard curve generated from 2-fold serial dilutions (1:50 to 1:102,400) of a pool positive control (pool of 20 positive sera prepared from patients with RT-PCR-confirmed COVID-19. Plates were analysed using a Luminex MAGPIX system and the median fluorescence intensity (MFI) values were recorded for subsequent analysis. A five-parameter logistic regression model was applied to convert MFI values into relative antibody units (RAU), normalizing against the standard curve performed on the same plate to correct for interassay variability. A cohort of pre-pandemic (PP) serum samples (n = 78, cross-sectional survey performed in June 2018) obtained from a longitudinal cohort survey conducted in Dielmo village (Fatick region, Toubacouta district, Senegal), and ongoing since 1990 was used as negative controls [12]. For serum samples, the positivity threshold for IgG against each SARS-CoV-2 antigen was defined as the mean RAU plus 3 times the standard deviation (SD) of these negative controls. The RAU cutoff values for each antigen were as follows: WTS = 0.002, ME = 0.0004, RBD = 0.0009, NP = 0.0001, and S2 = 0.0032. For CSF samples, an arbitrary cutoff was defined as one-tenth of the corresponding serum cutoff value. A sample was classified as positive if it exhibited reactivity against at least 3 antigens. This method ensures that the cutoff accounts for natural variability in the negative population while minimizing the risk of false-positive results.
1.13. Statistical analysis
Statistical analyses were primarily descriptive because of the limited sample size. Continuous variables were summarized using means, standard deviations and ranges, whereas categorical variables were expressed as frequencies and percentages. Missing data were reported and excluded from percentage calculations when appropriate. No inferential analyses were performed because the study was exploratory and aimed to describe the clinical, molecular and serological characteristics of SARS-CoV-2-associated encephalitis cases. Statistical analyses were conducted using RStudio version 4.1.0, and tables and figures were generated using Microsoft Excel 2019.
2. Results
2.1. Socio-demographic characteristics
A total of 11 patients with a clinical picture of SARS-CoV-2 associated viral encephalitis was included in the study. The mean age was 34 years [6-79 years] with a standard deviation of 20, and the male/female sex ratio was 0.83 (5/6). The distribution of cases by age and gender shows that the age group [15 - 34 years] is more represented, with 60% male (3) and 40% female (2). The age group [≥65 years] is represented by only one woman (Table 1).
Table 1.
Characteristics of patients with SARS-CoV-2 associated encephalitis in the study, stratified by gender. Dakar, January 2021-December 2022.
| Characteristic | Male n (%) | Female n (%) | Total N (%) |
|---|---|---|---|
| Patient | 5 (45.45) | 6 (54.54) | 11 (100) |
| Age (year) | |||
| <15 | 1 (50) | 1 (50) | 2 (100) |
| [15-34] | 3 (60) | 2 (40) | 5 (100) |
| [35-59] | 1 (33.3) | 2 (66.6) | 3 (100) |
| ≥60 | - | 1 (100) | 1 (100) |
| Mean | 30.2 (14-53) | 37.5 (6-79) | 34.2 (6-79) |
| Standard deviation | 14.32 | 25.04 | 20.25 |
| Leukocytes (≥ 5 cells/mm3) | 3 (43) | 4 (57) | 7 (100) |
| Clinical signs | |||
| Fever | 5 (45.45) | 6 (54.54) | 11 (100) |
| Behavioural disorders | 3 (50) | 3 (50) | 6 (100) |
| Seizures | 2 (40) | 3 (60) | 5 (100) |
| Altered consciousness | 3 (60) | 2 (40) | 5 (100) |
| Headache | 3 (75) | 1 (25) | 4 (100) |
| Cranial nerve damage | 2 (66.6) | 1 (33.3) | 3 (100) |
| Hemiplegia | 2 (66.6) | 1 (33.3) | 3 (100) |
| Abnormal movements | 1 (100) | - | 1 (100) |
| Amnesic disorder | 1 (100) | - | 1 (100) |
N: number.
The time from onset of the first clinical/neurological symptoms to hospitalization ranged from 5 to 17 days. On admission, patients presented different symptoms. Apart from fever, which was an inclusion criterion, the most common symptoms were behavioural disorders, seizures and altered consciousness. Analysis of CSF biological parameters revealed viral meningitis (≥5 cells/mm3) in 63.6% (7/11) of patients. Among these cases, a predominantly leukocytes profile was observed in female (57%; 4/7) (Table 1).
2.2. Detection of SARS-CoV-2 virus and genetic classification of sequences obtained from NP and CSF samples
Eleven nasopharyngeal swab samples and two cerebrospinal fluid samples were positive for SARS-CoV-2 by Veri Q 316 COVID-19 RT-PCR with well-defined Ct values. The 11 positive NP samples were, for the most part, assigned to a specific SARS-CoV-2 variant by RT-PCR TaqMan screening, as shown in the table below (Table 2).
Table 2.
SARS-CoV-2 virus detection and genetic classification of sequences obtained from NP and CSF samples.
| Samples | Sampling date | NP |
CSF |
||||
|---|---|---|---|---|---|---|---|
| qRT-PCR | Ct value | Genotype/Variants | qRT-PCR | Ct value | Genotype/Variants | ||
| E1/366301 | 21-05-2021 | Positive | 19.98 | Eta (B.1.525-like) | Negative | - | - |
| E2/366306* | 02-06-2021 | Positive | 30.33 | Eta (B.1.525-like) | Negative | - | - |
| E3/366308 | 07-06-2021 | Positive | 29.4 | Undetermined | Positive | 33.29 | Undetermined |
| E4/366319 | 14-06-2021 | Positive | 28.82 | Wild type | Negative | - | - |
| E5/366324 | 28-06-2021 | Positive | 31.22 | Wild type | Negative | - | - |
| E6/366329 | 08-07-2021 | Positive | 26.82 | Undetermined | Negative | - | - |
| E7/366331 | 14-07-2021 | Positive | 20.41 | Delta (B.1.617.2-like) | Negative | - | - |
| E8/366336* | 27-07-2021 | Positive | 31.41 | Delta (B.1.617.2-like) | Negative | - | - |
| E9/366343 | 18-08-2021 | Positive | 29.05 | Wild type | Negative | - | - |
| E10/391815 | 25-02-2022 | Positive | 33 | Omicron (BA.1.1) | Negative | - | - |
| E11/391898 | 12-05-2022 | Positive | 33.02 | Omicron (BA.1.1) | Positive | 26.43 | Undetermined |
Ct: threshold cycle; NP: nasopharyngeal; CSF: cerebrospinal fluid.
Note: “Undetermined” indicates that TaqMan RT-PCR cannot characterize SARS-CoV-2 variants, as it only detects target regions regardless of viral load (Ct value).
2.3. Phylogenetic analysis
The ML phylogenetic tree was inferred using the online software IQtree (http://iqtree.cibiv.univie.ac.at/) with the TIM2+F + G4 as the best fitted nucleotide substitution model to our dataset. Four SARS-CoV-2 sequences corresponding to specific variants were identified from the sequencing of nasopharyngeal swab samples using the Illumina COVID-Seq method. These included two Delta (B.1.617.2-like) and two Eta (B.1.525-like) variants (Fig. 1).
Remark
Respiratory forms of SARS-CoV and SARS-CoV-2 have been downloaded from GenBank.
Fig. 1.
Maximum likelihood tree based on the complete sequences of SARS-CoV-2 virus strains circulating in Senegal in 2021-2022. The tree has a median root and nodes are labelled with bootstrap values. Isolate names are color-coded as follows: in purple, neurological forms of SARS-CoV-2 isolated from nasopharyngeal swabs from Senegal; in black, reference sequences of SARS-CoV-2 strains circulating in Senegal during our study period from Germany; in blue, the reference sequence of SARS-CoV-2 from the USA; in red, the reference sequence of SARS-CoV (outgroup) from the USA.
2.4. Genetic diversity and polymorphisms in sequences from the neurological forms
These sequences were compared with the SARS-CoV-2 reference sequence (NC_045512.2) downloaded from GenBank and with all sequences of the same variant detected in Senegal during the study period. The mutations listed (characteristic, specific and minority) and their respective positions are presented in the Supplementary Tables S1 and S2.
Evaluation of the impact of minor and specific mutations shows that the substitutions p.Pro4619Leu, p.Ala103Pro and p.Thr40Ile can affect the function of the Nsp12 and the accessory proteins 3a and 7b (Table 3).
Table 3.
Evaluation of the impact of minority and specific mutations in neurological forms of SARS-CoV-2 using SIFT software.
| Mutations | Protein | Protein impact | Scores |
|---|---|---|---|
| p.Pro4619Leu | Nsp 12 | APF | 0.01 |
| p.Thr609Ile | Nsp 2 | Tolerated | 0.58 |
| p.Leu681Phe | Nsp 2 | Tolerated | 0.08 |
| p.Cys3059Phe | Nsp 4 | Tolerated | 0.13 |
| p.Thr95Ile | Spike | Tolerated | 0.07 |
| p.Ala103Pro | Accessory 3a | APF | 0.00 |
| Ins.102Ala103 | Accessory 3a | - | - |
| p.Thr40Ile | Accessory 7b | APF | 0.00 |
| p.Leu230Phe | Nucleocapsid | Tolerated | 0.09 |
APF: Affect Protein Function.
The p.Pro4619Leu mutation is unique and has not been found in available databases. Mutations (p.Pro4619Leu, p.Ala103Pro and p.Thr40Ile) may affect the function of Nsp 12 and accessory proteins 3a-7b.
2.5. SARS-CoV-2 IgG levels in serum and CSF samples
Immunoglobulin G (IgG) response against five SARS-CoV-2 antigens (WTS, RBD, NP, S2 and ME) were simultaneously measured using a multiplex bead-based serological assay. Samples with IgG reactivity against at least three SARS-CoV-2 antigens were scored as positive. Among the 10 serum samples tested only 3 (30%) were positive on SARS-CoV-2: E2/366306, E8/366336 and E10/391815 (Fig. 2A and Table 4).
Fig. 2.
Detection of anti-SARS-CoV-2 antibodies in serum and CSF samples using multiplex bead-based serological assay. A bead-based multiplex Luminex assay was used to quantify IgG responses against multiple SARS-CoV-2 antigens. Panel A: IgG levels in serum samples from individuals with neurological COVID-19 (EN, triangles) and prepandemic negative controls (PP, circles). Medians are represented by red bars. Positive serum samples are highlighted: E2/366306 (blue triangle), E8/366336 (orange triangle) and E10/391815 (green triangle). Panel B: IgG levels in CSF samples diluted 1:20 or 1:100. Positive CSF samples were marked with an asterisk (*). Immunoglobulin G, RAU: relative antibody unit; WTS: whole trimeric spike; RBD: receptor-binding domain; S2: spike subunit 2; N: nucleocapsid; ME: membrane-envelop fusion protein.
Table 4.
Results of COVID-19 IgG ELISA serological tests on serum and CSF samples.
| Samples | Serum (IgG) | CSF (IgG) |
|---|---|---|
| E1/366301 | Negative | NA |
| E2/366306 | Positive | Positive |
| E3/366308 | Negative | Negative |
| E4/366319 | Negative | Negative |
| E5/366324 | Negative | Negative |
| E6/366329 | Negative | Positive |
| E7/366331 | Negative | Negative |
| E8/366336 | Positive | Positive |
| E9/366343 | Negative | Positive |
| E10/391815 | Positive | Negative |
| E11/391898 | NA | Negative |
IgG: Immunoglobulin G; NA: Not available (no serum or no CSF).
Given the lower concentration of IgG in CSF compared to serum, the CSF samples were tested at two dilutions: 1:20 and 1:100. Among the ten CSF samples analysed at 1:20, four were classified as positive (E2/366306, E6/366329, E8/366336, E9/366343) whereas only one remained positive at the 1:100 dilution (E8/366336). Notably, two CSF samples (E2/366306, E8/366336) with IgG reactivity to SARS-CoV-2 antigens corresponded to patients who had already demonstrated IgG positivity in serum (Fig. 2B and Table 4).
3. Discussion
In this study, we characterized the clinical, molecular and serological features of 11 SARS-CoV-2-associated encephalitis cases identified through the ENSENE surveillance system in Senegal. To our knowledge, this is one of the few reports from sub-Saharan Africa combining cerebrospinal fluid analyses, serological investigations and genomic characterization of SARS-CoV-2 strains in patients presenting with encephalitis. These findings provide additional evidence supporting the involvement of SARS-CoV-2 in neurological disease.
From January 2021 to December 2022, among patient enrolled during the surveillance of acute viral encephalitis, 11 patients hospitalized for suspicion of viral encephalitis were tested positives for SARS-CoV-2. The gender difference observed in our study reflected the sex ratio of the Senegalese population [13]. This may suggest that women in Senegal are at higher risk of developing viral encephalitis as previously reported [14] and could be explained by the possible involvement of intrinsic genetic factors. In addition, the gender-based immune response could have an impact on women's susceptibility to some autoimmune diseases and viral infections [15]. Although a previous study carried out in Senegal on viral encephalitis surveillance in the context of COVID-19 exhibited that adults [40 - 49 years] were more likely to develop viral encephalitis [14], our data showed that adolescents and young adults [15 - 34 years] are more exposed to the virus. However, this needs to be confirmed through a study including more patients. This could be associated to a lower application of barrier measures by adolescents during the COVID-19 pandemic.
Most of the COVID-19 patients included in our study showed CSF pleocytosis greater than 5 cells/mm3 (63.6%), consistent with viral encephalitis, as previously described in Vietnam in a study that used pleocytosis as part of the case definition for viral encephalitis [16]. Pleocytosis was also observed in around 80% of encephalitis cases, except for immunocompromised patients, at the first stage of an infectious or autoimmune encephalitis [17].
The detection of SARS-CoV-2 in only two CSF samples by qRT-PCR may be related to the low viral load in CSF samples, which could limit the sensitivity of molecular detection. In addition, no assignment to a variant could be made for the two SARS-COV-2 positive CSF samples, unlikely the isolate detected in the NP of the same patient, exhibited a higher viral load. Secondly, SARS-CoV-2 infection does not systematically pass the blood-brain barrier (BBB) and could be interrupted at the neural and capillary endothelial cells of frontal lobe tissue as previously reported [18]. In addition, SARS-COV-2 infected patients could probably develop post-infectious encephalitis due to an inflammation in the CNS as consequences of severe form or long COVID-19 infection [19].
The use of Illumina COVID-Seq enabled the identification of Delta (B.1.617.2-like) and Eta (B.1.525-like) variants among SARS-CoV-2-associated encephalitis cases. In silico analyses identified three amino acid substitutions (p.Pro4619Leu, p.Ala103Pro and p.Thr40Ile) predicted to affect the function of Nsp12 and accessory proteins 3a and 7b. These proteins are involved in viral replication and intracellular trafficking processes [20,21]. However, owing to the limited number of sequences analysed and the absence of comparison with SARS-CoV-2 strains isolated from patients without neurological manifestations, no causal relationship between these substitutions and neuroinvasion can be established. Therefore, these observations should be regarded as hypothesis-generating and warrant further functional studies.
Although most of the patients in our cohort tested negative for SARS-CoV-2 in the CSF, 30% (3/10) had IgG antibodies against this virus in serum samples and 40% (4/10) in CSF samples. However, the presence of antibodies against SARS-CoV-2 (anti-N-methyl-D-aspartate receptors [NMDAr], alpha-amino-3-hydroxy-5-methyl-isoxazole propionic acid receptors [AMPAr], gamma-aminobutyric acid receptors [GABAbr], contactin-associated protein-like 2 [CASPR2], dipeptidyl-peptidase-like protein [DPPX], and leucine-rich glioma-inactivated protein 1 [LGI1]) in CSF of COVID-19 patients was not associated with the classic forms of autoimmune encephalitis [22]. The detection of anti-SARS-CoV-2 IgG in CSF suggests intrathecal IgG synthesis or blood-brain barrier dysfunction, consistent with previous reports ([23]; [22]). In addition, previous preliminary data indicated a substantial role for SARS-COV-2 antibodies in CSF [24]. However, there is a crucial need to promote further similar studies in the context of epidemics at local or regional level or pandemics, including more patients with encephalitis and aiming to assess the presence of anti-SARS-CoV-2 antibodies in the CSF and specifically identify the underlining mechanisms. It would also be important to implement a country-wide longitudinal surveillance of viral encephalitis involving more intensive care units in Senegal for rapid detection and appropriate management of cases of encephalitis linked to major public health concern such as SARS-CoV-2.
This study has some limitations. First, the small number of patients means that our findings may not represent all cases of SARS-CoV-2-associated encephalitis. Second, only four complete genomes were obtained, which limited molecular comparisons. Third, no control group of COVID-19 patients without neurological symptoms was included, making it difficult to determine whether the identified mutations were specifically linked to encephalitis. Fourth, SARS-CoV-2 RNA was detected in only two cerebrospinal fluid samples, which limited the investigation of viral invasion of the central nervous system. Finally, because this was a retrospective study, we were unable to assess the long-term neurological outcomes of the patients.
Future studies should include viral isolation from SARS-CoV-2-positive cerebrospinal fluid samples to determine whether infectious virus is present and to better understand the mechanisms underlying central nervous system involvement.
In conclusion, our study provides clinical, molecular and serological evidence supporting the involvement of SARS-CoV-2 in encephalitis cases identified in Senegal during the COVID-19 pandemic. The mutations identified in sequenced strains should be regarded as hypothesis-generating observations rather than evidence of neurotropism. Larger studies including appropriate control groups and functional analyses are required to better understand the mechanisms underlying neurological involvement associated with SARS-CoV-2.
Use of artificial intelligence tools
None declared.
Funding statement
Jean-Michel Heraud received financial support from the Senegalese ministry for Research and high School. This research project was also supported by the Institut Pasteur de Dakar, the French Ministry for Europe and Foreign Affairs via the project REPAIR COVID-19 Africa and the CoronaSeroSurv project, both coordinated by the Pasteur Network association.
CRediT authorship contribution statement
Fatou Kiné Top: Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing – original draft, Writing – review & editing. Jamil Kahwagi: Investigation. Rokhaya Diagne: Investigation. Al Ousseynou Seye: Formal analysis, Methodology, Writing – review & editing. Rokhaya Faye: Data curation, Formal analysis. Moussa Moise Diagne: Formal analysis. Babacar Ndiaye: Writing – review & editing. Gamou Fall: Writing – review & editing. Amadou Alpha Sall: Writing – review & editing. Ousmane Faye: Writing – review & editing. Ndongo Dia: Conceptualization, Formal analysis. Inès Vigan-Womas: Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing. Martin Faye: Data curation, Formal analysis, Writing – original draft, Writing – review & editing. Jean-Michel Heraud: Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
The authors would like to express their deep gratitude to the study participants for their vital contribution. We would also like to thank all health workers at the hospital (Neurology Ward at Fann and Pikine) for their dedicated work during the COVID-19 epidemics. We also thank all staff of the Virology department that provide results to clinicians within 24 h despite excessive work associated with COVID-19 diagnoses and all the ENSENE Investigators. We thank Michael White and Stephane Pelleau (Institut Pasteur, Paris, for their kind provision of SARS-CoV-2 multiplex coated beads.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.nmni.2026.101816.
Appendix A. Supplementary data
The following is the Supplementary data to this article:
Data availability
Not applicable.
References
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