{"paper_id":"107c3ec7-9970-49b5-b54a-144cd185cd57","body_text":"1 \n \nA severely affected MRL/Lpr mouse exhibits a divergent clinical–immune 1 \nprofile associated with a profound metabolic alteration. 2 \nKarim Matmat 1*, Carole Jamey 2, Daniel Brumaru 1,2, Ayikoé-Guy Mensah -Nyagan1, Hélène 3 \nJeltsch-David3* 4 \n1Inserm – Centre d’Investigation Clinique 1434, Neuroprotection and Remyelination – Centre 5 \nde Recherche en Biomédecine de Strasbourg, University of Strasbourg, Strasbourg, France.  6 \n2Laboratoire de Biochimie et de Biologie Moléculaire, Pôle de biologie, Hôpitaux  7 \nUniversitaires de Strasbourg, Strasbourg, France 8 \n3Laboratoire des Sciences de l’Ingénieur de l’Informatique et de l’Imagerie ICube, UMR 7357, 9 \nCNRS / Université de Strasbourg / INSA / ENGEES / INRIA, Strasbourg, France. 10 \n*Corresponding Authors: Karim Matmat ( matmat@unistra.fr – ORCID: 0009-0009-8226-11 \n4846); Hélène Jeltsch-David (hdavid@unistra.fr – ORCID: 0000-0003-3630-7242) 12 \nEthics approval statement: All procedures complied with the European Directive 2010/63/EU 13 \nand the French governmental decree 2013 -118. Experimental protocols were approved by the 14 \nlocal Animal Ethics Committee (APAFIS#35144) and conducted under the supervision of 15 \nauthorized investigators  in a certified animal facility (Faculty of Medicine, University of 16 \nStrasbourg). 17 \nConflict of interest statement: The authors declare no conflict of interest. 18 \nFunding statement: Not applicable. 19 \nData availability statement: All data supporting the findings of this study are available from 20 \nthe corresponding author upon reasonable request. 21 \nWord count: 1200 22 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n2 \n \nAbstract 23 \nSystemic lupus erythematosus (SLE) displays marked clinical and biological heterogeneity that 24 \nis incompletely captured by group-based analyses. Although the MRL/Lpr mouse is a well -25 \nestablished lupus model, individual -level divergence within this genetically homogeneous 26 \nstrain remains poorly characterized. 27 \nHere, we describe an MRL/Lpr mouse exhibiting an exceptionally severe s ystemic phenotype 28 \nand provide an integrative characterization combining clinical assessment, inflammatory 29 \nprofiling, neuroaxonal injury, and targeted metabolomics. Despite pronounced clinical 30 \ndeterioration, including severe proteinuria, reduced organ weigh ts, and marked neuroaxonal 31 \ndamage, this mouse did not show a globally exacerbated cytokine profile relative to other 32 \nMRL/Lpr animals. In contrast, plasma neurofilament light chain levels were massively 33 \nelevated, indicating substantial neuroaxonal injury. Targeted metabolomic analysis revealed a 34 \nprofoundly altered biochemical signature, with coordinated disruptions in nitrogen handling, 35 \nsulfur amino acid metabolism, and neurometabolic pathways, clearly separating this animal 36 \nfrom both control and lupus-prone peers. 37 \nThese findings illustrate that extreme disease severity can emerge independently of overt 38 \ncytokine escalation and identify metabolic dysregulation as a major dimension of pathological 39 \ndivergence at advanced disease stages. Although descriptive and based on a single individual, 40 \nthis work highlights the value of extreme phenotypes for uncovering biological inflection points 41 \nthat remain concealed in averaged analyses and supports the integration of metabolic readouts 42 \nalongside inflammatory markers in autoimmune disease research. 43 \nIntroduction 44 \nSystemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder marked by 45 \nfluctuating inflammatory activity, multisystem involvement, and substantial inter -individual 46 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n3 \n \nvariability in disease trajectories [1–3]. The MRL/MpJ-Faslpr (MRL/Lpr) mouse strain is one 47 \nof the most established spontaneous models of systemic autoimmunity, recapitulating key 48 \nfeatures such as lymphoproliferation, glomerulonephritis, neuro behavioral alterations, 49 \ndermatitis, and chronic inflammation  [4, 5] . Despite its genetic homogeneity  this model 50 \nnonetheless displays notable variability in disease onset and severity, thereby mirroring 51 \nessential aspects of human SLE heterogeneity  [6, 7] . Such intra -strain divergence is rarely 52 \nexplored at the individual level, although unusually severe presentations can reveal mechanisms 53 \nundetectable in group -averaged analyses  [8]. This is particularly relevant in chronic 54 \nautoimmune disease, in which inflammatory burden, metabolic stress, and tissue injury may 55 \ndiverge substantially between individuals [9].  56 \nIn this Short Communication, we describe an MRL/Lpr mouse exhibiting an exceptionally 57 \nsevere systemic phenotype. By integrating clinical, inflammatory, and metabolic assessments, 58 \nwe illustrate how disease severity can emerge independently of cytokine escalation. 59 \nMaterials & Methods 60 \nAnimals and pathological assessment 61 \nFemale MRL/Lpr and congenic MRL+/+ mice (The Jackson Laboratory , US ) were housed 62 \nunder standard conditions with ad libitum  access to food and water. At 17 -weeks of age , 63 \ncorresponding to the peak of systemic autoimmunity, animals were anesthetized with isoflurane 64 \nand euthanized by decapitation. Blood was collected immediately and plasma was obtained by 65 \ncentrifugation (2,000 g, 5 min). Kidneys, spleen, brain, and spinal cord were rapidly dissected 66 \nand weighed. Terminal proteinuria was assessed using Albustix® reagent strips (Siemens). One 67 \nMRL/Lpr mouse ( #15) displayed an unusually severe systemic phenotype and was therefore 68 \nexamined descriptively as an extreme case.  All procedures complied with EU Directive 69 \n2010/63/EU and were approved by the institutional ethics committee (APAFIS#35144). 70 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n4 \n \nCytokine and NfL quantification 71 \nPlasma cytokines levels were quantified using a custom U-PLEX multiplex assay (Meso Scale 72 \nDiscovery, MSD ®) and n eurofilament light chain (NfL) was measured using a U -PLEX 73 \nsingleplex kit from the same manufacturer. EDTA plasma samples were processed according to 74 \nthe manufacturer’s instructions, and electrochemiluminescence signals were acquired on a 75 \nMESO QuickPlex SQ 120. Concentrations were interpolated from standard curves and 76 \nexpressed in pg/mL. 77 \nTargeted metabolomic profiling 78 \nPlasma amino acids and related metabolites were quant ified using the MassChrom® Amino 79 \nAcids kit (Chromsystems), a standardized clinical LC -MS/MS method , following the 80 \nmanufacturer’s instructions. Final concentrations (µmol/L) were used for downstream analyses. 81 \nStatistical analysis 82 \nNormality was assessed using the Shapiro–Wilk test and variance homogeneity with Levene’s 83 \ntest. Depending on these assumptions, comparisons were performed between MRL+/+ and 84 \nMRL/Lpr mice using an unpaired t -test, Welch’s t-test, or a Mann –Whitney test. PCA  was 85 \ncomputed on scaled cytokine or metabolite data. The composite inflammatory score was 86 \ngenerated by z-normalizing each cytokine. Mouse #15 was included in the MRL/Lpr group for 87 \nall statistical analyses; its profile was then described qualitatively to il lustrate intra -group 88 \nvariability. Analyses were performed in R (v4.3). 89 \nResults 90 \nClinical phenotype reveals a severely affected MRL/Lpr mouse. 91 \nAt terminal assessment, MRL/Lpr mice showed the expected systemic alterations relative to 92 \nMRL+/+ controls. Body weight was broadly comparable within the MRL/Lpr group, although 93 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n5 \n \nmouse #15 exhibited the lowest weight of all animals  (Figure 1a). Kidney, spleen, and spinal 94 \ncord weights were  significantly increased in MRL/Lpr mice, along with elevated proteinuria  95 \n(Figure 1 b–c). Interestingly, mouse #15 displayed an atypical organ pattern : kidney weight 96 \nremained within the typical MRL/Lpr range, but spleen, brain, and spinal cord weights  were 97 \nthe lowest  of the group, together with a maximal proteinuria score (5/5). This animal also 98 \nshowed severe ulcerative dermatitis with complete loss of snout fur, associated with a visibly 99 \ndeteriorated general condition (Figure 1d). 100 \nInflammatory profiling shows limited cytokine dysregulation in mouse #15, but 101 \npronounced neuro-axonal injury. 102 \nPrincipal component analysis (PCA) of plasma cytokines did not separate mouse #15 from the 103 \nremainder of the MRL/Lpr group (Figure 1e), indicating that its marked clinical deterioration 104 \nwas not associated with an overtly exaggerated cytokine profile. Other animals, particularly 105 \n#20 and #22, exhibited more divergent inflammatory signatures.  Nevertheless, the radar plot 106 \nrevealed selective increases in TNF α and IL-1β in mouse #15, with values exceeding the 107 \nMRL/Lpr group mean and ranking among the highest in the cohort, notably, TNFα reached the 108 \nmaximum recorded level  (Figure 1 f–h). Consistently, t he composite inflammatory score 109 \nconfirmed this pattern, placing mouse #15 in the upper range of group variability without 110 \nexceeding the expected dispersion (Figure 1i). 111 \nIn contrast, plasma NfL levels showed a striking divergence: mouse #15 displayed a massive 112 \nelevation, far surpassing all other animals (Figure 1 j). This divergence indicates that neuro-113 \naxonal injury can escalate independently of systemic cytokine levels. 114 \nMetabolic profiling reveals a profoundly altered signature in mouse #15. 115 \nTargeted metabolomics showed a strongly altered biochemical profile in mouse #15. PCA 116 \nclearly isolated this animal from both  MRL+/+ controls and the remaining MRL/Lpr mice, 117 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n6 \n \nindicating a global shift in amino -acid homeostasis (Figure 2a). This separation re flects a 118 \ncoordinated shift across multiple metabolites rather than isolated abnormalities . Fold-change 119 \nanalysis (e.g., |log₂FC| > 2 ) identified major elevations in citrulline, alanine, and 3 -120 \nmethylhistidine, reflecting disruptions in nitrogen handling and muscle -derived metabolites, 121 \ntogether with marked increases in cystathionine and taurine, indicative of altered sulfur amino-122 \nacid metabolism  (Figure 2b –c). Conversely, several metabolites were markedly decreased, 123 \nincluding a near-complete depletion of GABA. Pathway enrichment of metabolites meeting the 124 \n|log₂FC| > 2 threshold highlighted significant over-representation of the urea cycle, glutamate 125 \nmetabolism, ammonia recycling, and related nitrogen-processing pathways (Figure 2d).  126 \nTogether, these alterations delineate a profoundly dysregulated metabolic phenotype.  This 127 \npattern suggests that severe metabolic dysregulation may better capture late-stage deterioration 128 \nthan inflammatory cytokine measures. An integrative schematic summarizing the constellation 129 \nof clinical, inflammatory, and metabolic abnormalities observed in mouse #15 is provided in 130 \nFigure 2e. 131 \nDiscussion 132 \nThis study illustrates that, even within a highly penetrant autoimmune model, an extrem e 133 \nsystemic phenotype can emerge without a corresponding escalation in inflammatory activity. 134 \nAlthough based on a single individual, documenting such an extreme presentation remains 135 \ninformative, highlighting biological divergence within a genetically homogeneous strain. These 136 \nfindings suggest that, at advanced disease stages, systemic inflammatory markers may reach a 137 \nplateau beyond which they no longer discriminate severity, thereby limiting their capacity to 138 \ncapture divergent pathological trajectories [9, 10].  139 \nIn contrast, metabolic profiling revealed a distinctly altered biochemical landscape that clearly 140 \nset this mouse apart from all other. The magnitude and coherence of these metabolic 141 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n7 \n \nabnormalities, including coordinated disruptions in urea-cycle–related nitrogen handling, sulfur 142 \namino-acid metabolism, and muscle -derived metabolites, indicate that downstream metabolic 143 \ndysfunction may serve as a more discriminating correlate of extreme systemic deterioration. 144 \nThis aligns with observations in human lupus, where  metabolic phenotypes often diverge 145 \nindependently of inflammatory indices  [11–13], supporting the notion that metabolic 146 \ndysregulation becomes a predominant dimension of disease heterogeneity associated with 147 \nextreme disease severity once inflammation stabilizes at chronically elevated levels.  In this 148 \ncontext, metabolic readouts may offer greater sensitivity for detecting late -stage systemic 149 \ndeterioration than cytokine measurements alone. 150 \nOverall, this work underlines the importance of integrating metabolic assessments alongside 151 \ninflammatory markers in autoimmune research. Extreme phenotypes  can reveal mechanistic 152 \ninflection points that remain concealed in group -averaged analyses, thereby enhancing the 153 \ntranslational relevance of preclinical models. Although causality cannot be inferred from a 154 \nsingle observation, the coherence of the clinical and metabolic alterations strengthens its value 155 \nas a representative extreme phenotype . Such rare divergences highlight t he importance of 156 \nconsidering individual-level variation when interpreting autoimmune phenotypes. 157 \n 158 \n 159 \n 160 \n 161 \nAuthor Contributions 162 \nKM: Conceptualization, data curation, formal analysis, investigation, visualization, writing –163 \noriginal draft, writing – review & editing. CJ: Investigation, writing – review & editing. DB: 164 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n8 \n \nInvestigation, writing – review & editing. AGMN: Investigation, writing – review & editing. 165 \nHJD: Conceptualization, investigation, writing –review & editing.  166 \nFigure legends 167 \nFigure 1. Systemic and behavioral profile of MRL/lpr mice at 17 weeks, illustratin g the 168 \nmarkedly aggravated condition of mouse #15. (a–c) Body and organs weights, and terminal 169 \nproteinuria in MRL +/+ and MRL/lpr mice. Brain and spinal cord weights are included to 170 \ndocument central nervous system tissue mass at endpoint. (d) Representative photographs 171 \nshowing the external phenotype of an MRL+/+ mouse, a typical MRL/lpr mouse, and mouse 172 \n#15 at sacrifice. (e) Principal component analysis (PCA) integrating all measured inflammatory 173 \ncytokines. (f) Radar plot summarizing cytokine levels across groups, with the profile of mouse 174 \n#15 highlighted. (g-h) Circulating concentrations of TNF α (g) and IL -1β (h). (i) Composite 175 \ninflammatory score derived from normalized cytokine values. (j) Plasma neurofilament light 176 \nchain (NfL) levels as a marker of neuroaxonal injury. Data are presented as individual values 177 \nwith mean ± SEM. Statistical procedures are detailed in the Met hods section.  Across all 178 \nscatterplots, mouse #15 is represented as a triangle and all other individuals as circles. Data are 179 \npresented as individual values with mean ± SEM. Statistical procedures are detailed in the 180 \nMethods section. 181 \nFigure 2. Metabolic profiling reveals a distinct biochemical signature in mouse #15.  (a) 182 \nPCA of plasma metabolites in MRL+/+ and MRL/lpr mice, highlighting the isolated metabolic 183 \nposition of mouse #15. (b) Log₂ fold -change distribution of all quantified metabolites 184 \ncomparing mouse #15 with the remaining MRL/lpr mice, illustrating the amplitude and 185 \ndirection of metabolic deviations. (c) Representative individual metabolite concentrations, 186 \nincluding markers of nitrogen handling (urea cycle), sulfur amino -acid metabolis m, muscle 187 \ncatabolism, and neurochemical imbalance . Mouse #15 is displayed as a triangle across all 188 \n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\n9 \n \nscatterplots. (d) Pathway enrichment analysis based on altered metabolites, highlighting over -189 \nrepresented metabolic pathways (FDR -adjusted). (e) Integrative schematic summarizing the 190 \nsystemic phenotype of mouse #15, linking major clinical features with the corresponding 191 \nmetabolic alterations. Data are shown as individual values with mean ± SEM. Statistical 192 \nprocedures are described in the Methods. 193 \nReferences 194 \n[1] Sammaritano LR, Askanase A, Bermas BL, et al. 2025 American College of 195 \nRheumatology ( ACR ) Guideline for the Treatment of Systemic Lupus Erythematosus. 196 \nArthritis Care & Research 2025; acr.25690. 197 \n[2] Tsokos GC. Systemic Lupus Erythematosus. N Engl J Med 2011; 365; 2110–21. 198 \n[3] Dai X, Fan Y , Zhao X. Systemic lupus erythematosus: updated insights on the 199 \npathogenesis, diagnosis, prevention and therapeutics. Sig Transduct Target Ther 2025; 10; 200 \n102. 201 \n[4] Jeltsch-David H, Muller S. Neuropsychiatric systemic lupus erythematosus and cognitive 202 \ndysfunction: The MRL -lpr mouse strain as a model. Autoimmunity Reviews  2014; 13; 203 \n963–73. 204 \n[5] Perry D, Sang A, Yin Y , et al. Murine models of systemic lupus erythematosus. J Biomed 205 \nBiotechnol 2011; 2011; 271694. 206 \n[6] Cabana-Puig X, Bond JM, Wang Z, et al. 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It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\nFigure 1\na b c\ne\n f h\ng\ni j\nd\nMRL/Lpr #15\nMRL/Lpr\nMRL+/+\n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint \n\nFigure 2\na b\nd\nc\ne\n.CC-BY 4.0 International licenseperpetuity. It is made available under a \npreprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in \nThe copyright holder for thisthis version posted January 9, 2026. ; https://doi.org/10.64898/2026.01.07.698139doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}