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The search for dementia treatments, including treatments for neuropsychiatric lupus (NPSLE), has not yet uncovered useful therapeutic targets that mitigate underlying inflammation. Currently, NPSLE\'s limited treatment options are often accompanied by severe toxicity. Blocking toll-like receptor (TLR) and IL-1 receptor signal transduction by inhibiting interleukin-1 receptor-associated kinase 4 (IRAK4) offers a new pathway for intervention. Using a pre-clinical NPSLE model, we compare lupus-like B6.MRL-Faslpr (MRL) mice with B6.MRL-Faslpr-IRAK4 kinase-dead (MRL-IRAK4-KD) mice, which are were less prone to \'general\' lupus-like symptoms. We demonstrate that lupus-prone mice with a mutation in the kinase domain of IRAK4 no longer display typical lupus hallmarks such as splenomegaly, inflammation, production of hormones, and anti-double-stranded (ds)DNA antibody. water maze behavioral testing, which measures contextual associative learning, revealed that mice without functional IRAK4 displayed a recovery in memory acquisition deficits. RNA-seq approach revealed that cytokine and hormone signaling converge on the JAK/STAT pathways in the mouse hippocampus. Ultimately, the targets identified in this work may result in broad clinical value that can fill the significant scientific and therapeutic gaps precluding development of cures for dementia.

OBJECTIVE: Neuropsychiatric SLE (NPSLE) has a broad spectrum and to date, there is no gold-standard biomarker. The diagnosis relies on clinical assessment, supporting examinations and exclusion of other possible aetiologies. One method that can be used to establish NPSLE is to conduct a re-evaluation by involving several fields of medical science. This study aims to reassess SLE cases with neuropsychiatric (NP) manifestations through multidisciplinary re-evaluation and determine the final diagnosis of NPSLE or non-NPSLE.
METHODS: This retrospective cross-sectional study used medical record data from patients with SLE with NP manifestations. Inclusion criteria included patients diagnosed with SLE, who had clinical manifestations of NP and were >18 years old. Multidisciplinary re-evaluation was conducted and agreed upon the diagnosis of NPSLE or non-NPSLE.
RESULTS: We included 94 subjects with a total of 132 NP events consisting of 69 NPSLE and 63 non-NPSLE. After re-evaluating NPSLE events, 33.3% were still concluded to be NPSLE. Meanwhile, from the non-NPSLE group, 22.2% were then declared as NPSLE. There were no significant differences in demographic characteristics between the NPSLE and non-NPSLE groups. The proportion of NP events in both groups was almost the same except for cerebrovascular disease manifestations which were more common in the NPSLE group. Higher Mexican SLE Disease Activity Index scores with (p<0.001) or without NP (p=0.02) were observed in the NPSLE group compared with the non-NPSLE group, as well as higher proportion of active disease (p=0.03), higher anti-double-stranded DNA titres (p<0.001) and lower values of C3 (p=0.018) and C4 (p=0.001).
CONCLUSIONS: Multidisciplinary re-evaluation can be used as a method to confirm the diagnosis of NPSLE. There is a tendency for overdiagnosis of NPSLE when clinicians are faced with NP events in patients with SLE. Complete clinical and supporting data are needed to determine the final diagnosis of NPSLE.

Surface-enhanced Raman spectroscopy (SERS) is a powerful optical technique for non-invasive and label-free bioanalysis of liquid biopsy, facilitating to diagnosis of potential diseases. Neuropsychiatric systemic lupus erythematosus (NPSLE) is one of the subgroups of systemic lupus erythematosus (SLE) with serious manifestations for a high mortality rate. Unfortunately, lack of well-established gold standards results in the clinical diagnosis of NPSLE being a challenge so far. Here we develop a novel Raman fingerprinting machine learning (ML-) assisted diagnostic method. The microsphere-coupled SERS (McSERS) substrates are employed to acquire Raman spectra for analysis via convolutional neural network (CNN). The McSERS substrates demonstrate better performance to distinguish the Raman spectra from serums between SLE and NPSLE, attributed to the boosted signal-to-noise ratio of Raman intensities due to the multiple optical regulation in microspheres and AuNPs. Eight statistically-significant (p-value <0.05) Raman shifts are identified, for the first time, as the characteristic spectral markers. The classification model established by CNN algorithm demonstrates 95.0% in accuracy, 95.9% in sensitivity, and 93.5% in specificity for NPSLE diagnosis. The present work paves a new way achieving clinical label-free serum diagnosis of rheumatic diseases by enhanced Raman fingerprints with machine learning.

Neuropsychiatric systemic lupus erythematosus (NPSLE) is a potentially serious and life-threatening complication of SLE. The presentation and severity of neuropsychiatric involvement in SLE may show considerable variability. The disease can affect the neural tissue directly or may be associated with vascular involvement, mainly associated with anti-phospholipid (aPL) antibodies. A direct causal link with SLE may sometimes be challenging since there are many confounding factors and the symptoms may be non-specific. Despite its remarkable sensitivity in detecting hemorrhagic and ischemic stroke, transverse myelitis and ischemic infarction, magnetic resonance imaging (MRI) lacks the spatial resolution required to identify microvascular involvement. When standard MRI fails to detect a suspicious lesion, it is advisable to use advanced imaging modalities such as positron emission tomography (PET), single photon emission computed tomography (SPECT) or quantitative MRI, if available. Even with these advanced modalities, the specificity of neuroimaging in NPSLE remains inadequate (60-82% for MRI). Neuropsychiatric syndromes, such as cerebrovascular events, seizures and cognitive impairments appear to be associated with serum aPL antibodies. Some studies have shown that anti-ribosomal P antibodies have a low sensitivity for NPSLE and a limited contribution to the differentiation of different clinical entities. Treatment has two main goals: symptomatic relief and treatment of the disease itself. Commonly used immunosuppressants for NPSLE include cyclophosphamide (CYC), azathioprine (AZA), and mycophenolate mofetil (MMF). According to EULAR\'s current recommendation, strong immunosuppressants such as CYC and rituximab (RTX) should be preferred. Biologics have also been used in NPSLE. Fingolimod, eculizumab, and JAK inhibitors are potential drugs in the pipeline. Developing targeted therapies will be possible by a better understanding of the pathological mechanisms.

Ictal epileptic headache, characterized by headache as the sole symptom of a seizure attack, is a rare condition. In this case report, we present a 52-year-old female with a history of systemic lupus erythematosus who sought medical attention at the headache clinic due to a new type of headache. The headache was described as an intense painful wave followed by a dull headache, without autonomic symptoms or migrainous features. Magnetic resonance imaging revealed an enhancing lesion in the left hippocampus in addition to two other lesions in the corpus callosum and left parieto-occipital lobe. Electroencephalography during the headache episodes showed epileptic discharges originating from the left fronto-temporal region. The patient was initiated on levetiracetam, which resulted in the resolution of both the epileptic discharges and the headaches. This case underscores the significance of considering ictal epileptic headache as a potential secondary cause for headaches, particularly in patients with underlying conditions that may predispose them to epilepsy, such as systemic lupus erythematosus.

OBJECTIVE: This study aimed to construct a predictive model for assessing the risk of development of neuropsychiatric systemic lupus erythematosus (NPSLE) among patients with SLE based on clinical, laboratory, and meteorological data.
METHODS: A total of 2232 SLE patients were included and were randomly assigned into training and validation sets. Variables such as clinical and laboratory data and local meteorological data were screened by univariate and least absolute shrinkage and selection operator (LASSO) logistic regression modelling. After 10-fold cross-validation, the predictive model was built by multivariate logistic regression, and a nomogram was constructed to visualize the risk of NPSLE. The efficacy and accuracy of the model were assessed by receiver operating characteristic (ROC) curve and calibration curve analysis. Net clinical benefit was assessed by decision curve analysis.
RESULTS: Variables that were included in the predictive model were anti-dsDNA, anti-SSA, lymphocyte count, hematocrit, erythrocyte sedimentation rate, pre-albumin, retinol binding protein, creatine kinase isoenzyme MB, Nterminal brain natriuretic peptide precursor, creatinine, indirect bilirubin, fibrinogen, hypersensitive C-reactive protein, CO, and mild contamination. The nomogram showed a broad prediction spectrum; the area under the curve (AUC) was 0.895 (0.858-0.931) for the training set and 0.849 (0.783-0.916) for the validation set.
CONCLUSIONS: The model exhibits good predictive performance and will confer clinical benefit in NPSLE risk calculation. Key Points • Clinical, laboratory, and meteorological data were incorporated into a predictive model for neuropsychiatric systemic lupus erythematosus (NPSLE) in SLE patients. • Anti-dsDNA, anti-SSA, LYM, HCT, ESR, hsCRP, IBIL, PA, RBP, CO, Fib, NT-proBNP, Crea, CO, and mild contamination are predictors of the development of NPSLE and may have potential for research. • The nomogram has good predictive performance and clinical value and can be used to guide clinical diagnosis and treatment.

Systemic lupus erythematosus is a complex autoimmune disease known for its diverse clinical manifestations, including neuropsychiatric systemic lupus erythematosus, which impacts a patient\'s quality of life. Our aim was to explore the relationships among brain MR imaging morphometric findings, neuropsychiatric events, and laboratory values in patients with systemic lupus erythematosus, shedding light on potential volumetric biomarkers and diagnostic indicators for neuropsychiatric systemic lupus erythematosus.
Twenty-seven patients with systemic lupus erythematosus (14 with neuropsychiatric systemic lupus erythematosus, 13 with systemic lupus erythematosus), 24 women and 3 men (average age, 43 years, ranging from 21 to 62 years) were included in this cross-sectional study, along with 10 neuropsychiatric patients as controls. An MR imaging morphometric analysis, with the VolBrain online platform, to quantitatively assess brain structural features and their differences between patients with neuropsychiatric systemic lupus erythematosus and systemic lupus erythematosus, was performed. Correlations and differences between MR imaging morphometric findings and laboratory values, including disease activity scores, such as the Systemic Lupus Erythematosus Disease Activity Index and the Systemic Lupus International Collaborating Clinics Damage Index, were explored. An ordinary least squares regression analysis further explored the Systemic Lupus Erythematosus Disease Activity Index and Systemic Lupus International Collaborating Clinics Damage Index relationship with MR imaging features.
For neuropsychiatric systemic lupus erythematosus and non-neuropsychiatric systemic lupus erythematosus, the brain regions with the largest difference in volumetric measurements were the insular central operculum volume (P value = .003) and the occipital cortex thickness (P = .003), which were lower in neuropsychiatric systemic lupus erythematosus. The partial correlation analysis showed that the most correlated morphometric features with neuropsychiatric systemic lupus erythematosus were subcallosal area thickness asymmetry (P < .001) and temporal pole thickness asymmetry (P = .011). The ordinary least squares regression analysis yielded an R 2 of 0.725 for the Systemic Lupus Erythematosus Disease Activity Index score, with calcarine cortex volume as a significant predictor, and an R 2 of 0.715 for the Systemic Lupus International Collaborating Clinics Damage Index score, with medial postcentral gyrus volume as a significant predictor.
The MR imaging volumetric analysis, along with the correlation study and the ordinary least squares regression analysis, revealed significant differences in brain regions and their characteristics between patients with neuropsychiatric systemic lupus erythematosus and those with systemic lupus erythematosus, as well as between patients with different Systemic Lupus Erythematosus Disease Activity Index and Systemic Lupus International Collaborating Clinics Damage Index scores.

BACKGROUND: Neuropsychiatric lupus (NPSLE) describes the cognitive, memory, and affective emotional burdens faced by many lupus patients. While NPSLE\'s pathogenesis has not been fully elucidated, clinical imaging studies and cerebrospinal fluid (CSF) findings, namely elevated interleukin-6 (IL-6) levels, point to ongoing neuroinflammation in affected patients. Not only linked to systemic autoimmunity, IL-6 can also activate neurotoxic glial cells the brain. A prior pre-clinical study demonstrated that IL-6 can acutely induce a loss of sucrose preference; the present study sought to assess the necessity of chronic IL-6 exposure in the NPSLE-like disease of MRL/lpr lupus mice.
METHODS: We quantified 1308 proteins in individual serum or pooled CSF samples from MRL/lpr and control MRL/mpj mice using protein microarrays. Serum IL-6 levels were plotted against characteristic NPSLE neurobehavioral deficits. Next, IL-6 knockout MRL/lpr (IL-6 KO; n = 15) and IL-6 wildtype MRL/lpr mice (IL-6 WT; n = 15) underwent behavioral testing, focusing on murine correlates of learning and memory deficits, depression, and anxiety. Using qPCR, we quantified the expression of inflammatory genes in the cortex and hippocampus of MRL/lpr IL-6 KO and WT mice. Immunofluorescent staining was performed to quantify numbers of microglia (Iba1 +) and astrocytes (GFAP +) in multiple cortical regions, the hippocampus, and the amygdala.
RESULTS: MRL/lpr CSF analyses revealed increases in IL-17, MCP-1, TNF-α, and IL-6 (a priori p-value < 0.1). Serum levels of IL-6 correlated with learning and memory performance (R2 = 0.58; p = 0.03), but not motivated behavior, in MRL/lpr mice. Compared to MRL/lpr IL-6 WT, IL-6 KO mice exhibited improved novelty preference on object placement (45.4% vs 60.2%, p < 0.0001) and object recognition (48.9% vs 67.9%, p = 0.002) but equivalent performance in tests for anxiety-like disease and depression-like behavior. IL-6 KO mice displayed decreased cortical expression of aif1 (microglia; p = 0.049) and gfap (astrocytes; p = 0.044). Correspondingly, IL-6 KO mice exhibited decreased density of GFAP + cells compared to IL-6 WT in the entorhinal cortex (89 vs 148 cells/mm2, p = 0.037), an area vital to memory.
CONCLUSIONS: The inflammatory composition of MRL/lpr CSF resembles that of human NPSLE patients. Increased in the CNS, IL-6 is necessary to the development of learning and memory deficits in the MRL/lpr model of NPSLE. Furthermore, the stimulation of entorhinal astrocytosis appears to be a key mechanism by which IL-6 promotes these behavioral deficits.

Early detection of neuropsychiatric systemic lupus erythematosus (NPSLE) remains a challenge in clinical settings. Previous studies have found different autoantibodies as markers for NPSLE. This study aimed to describe the distribution of psychiatric syndromes in a group of patients with systemic lupus erythematosus (SLE) and to investigate the association between psychiatric syndromes and specific autoantibodies.
This retrospective study was conducted at a single medical center in China. We reviewed medical records of hospitalized patients with SLE who were consulted by psychiatrists due to potential mental disorders. Results of serum autoantibodies and general laboratory tests were collected. The correlation between clinical variables was examined. Binary logistic regression analyses were used to determine factors related to NPSLE and different psychiatric diagnoses.
Among the 171 psychiatric manifestations in 160 patients, 141 (82.4%) were attributed to SLE. Acute confusional state (ACS) had the highest prevalence (57.4%). Anti-cardiolipin (ACL) antibody (X2 = 142.261, p < 0.001) and anti-β2 glycoprotein I (-β2GP1) antibody (X2 = 139.818, p < 0.001) varied significantly between groups, with the highest positive rate found in patients with mood disorders (27.3% and 18.2%). SLE disease activity index - 2000 (SLEDAI-2K) score excluding item ACS and item psychosis was a predictor of NPSLE (OR 1.172 [95% CI 1.105 - 1.243]).
Disease activity reflected by SLEDAI-2K score is a predictor for NPSLE. Antiphospholipid antibodies are associated with mood disorders in SLE. Further separate investigation of neuropsychiatric disorders is needed in order to better comprehend NPSLE\'s pathological mechanism.