White adipose tissue undergoes pathological dysfunction in the TDP-43 A315T mouse model of amyotrophic lateral sclerosis (ALS)

White adipose tissue undergoes pathological dysfunction in the TDP-43 A315T mouse model of amyotrophic lateral sclerosis (ALS) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article White adipose tissue undergoes pathological dysfunction in the TDP-43 A315T mouse model of amyotrophic lateral sclerosis (ALS) Cristina Benito-Casado, Esther Durán-Mateos, Águeda Ferrer-Donato, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6984477/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Oct, 2025 Read the published version in Acta Neuropathologica Communications → Version 1 posted 10 You are reading this latest preprint version Abstract White adipose tissue (WAT) has a crucial role in maintaining systemic energy homeostasis. Numerous biological pathway studies have highlighted the importance of adipokines in regulating metabolic pathways and contributing to metabolic dysfunction in animal models and patients with ALS. Despite these associations, the specific molecular mechanisms remain poorly understood. Moreover, the direct contribution of WAT to the energy metabolism abnormalities observed in ALS has yet to be clearly defined. The current study sought to identify perturbances in WAT, main source of leptin, during the clinical course of the disease in TDP-43 A315T mice using histological, proteomic, and molecular biological techniques. We present the first evidence of a significant histological alteration in WAT prior to the symptomatic stage of the disease in TDP-43 A315T mice, providing novel insights into pathological features earlier in the onset of symptoms, and showing WAT as a target organ for ALS. In human ALS cases, we found that circulating leptin levels at the time of diagnosis were lower in the plasma of men with ALS who were overweight or obese and had rapidly progressive ALS, emphasizing the importance of considering sex-specific approaches when analysing adipokines essential for body weight control. Amyotrophic lateral sclerosis (ALS) TAR DNA binding protein (TDP-43) white adipose tissue (WAT) sporadic ALS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Amyotrophic lateral sclerosis (ALS) is the third most common neurodegenerative disease worldwide characterized by the selective loss of motor neurons both in the brain and spinal cord (Rowland & Shneider, 2001 ), leading to paralysis and respiratory failure. ALS is often rapidly progressive, incurable, and fatal. Over 60% of patients die within 3–5 years after diagnosis (Connolly et al., 2015 ). Although much effort has been made in the past two decades to understand the complexity and heterogeneity of ALS, the development of effective therapies remains elusive due to several challenges. One major obstacle is the limited understanding of the underlying mechanisms driving ALS disease. Identifying the mechanisms involved in maintaining energy homeostasis in ALS can help to elucidate the growing evidence supporting a strong metabolic component in ALS. Indeed, rapid weight loss is associated with worse disease outcomes in ALS (Janse van Mantgem et al., 2020), and fat mass loss correlates with faster disease progression (Lee et al., 2021 ). Conversely, higher initial body mass index (BMI) and obesity (Heritier et al., 2015 ), type 2 diabetes mellitus (Jawaid et al., 2010 ), and patients with higher triglyceride and cholesterol levels (Dorst et al., 2011 ) have been associated with longer survival in ALS, indicating fat content and lipid metabolism are important prognostic factors in ALS disease. However, despite these correlations, the underlying mechanisms driving these metabolic derangements remain unclear. Adipose tissue is an endocrine organ and constitute the major lipid store in mammals (Kershaw & Flier, 2004 ). Two main types of anatomically and physiologically different adipose tissue are present in adults: WAT, which is mainly an energy store (Luo & Liu, 2016 ); and the brown adipose tissue (BAT), with specialized functions in heat production (thermogenesis) (Li et al., 2019 ). Moreover, as an endocrine organ, adipose tissue secretes a variety of soluble mediators, with a critical role in the physiological regulation of the metabolism acting on the hypothalamus, a key integrative brain area that regulates neuronal and metabolic circuits involved in energy intake regulation (Goel et al., 2025 ). While dysfunctions in the hypothalamus have only recently been described (Rosina et al., 2025 ), studies have shown this brain structure is atrophied in ALS (Tse et al., 2023 ), even in premorbid stages, and correlates with BMI (Gorges et al., 2017 ). Altered eating behaviour have been reported in patients with ALS and frontotemporal dementia (FTD) (Ahmed et al., 2016 ). Indeed, we and others demonstrated increased mRNA expression levels of agouti-related peptide (AgRP), while levels of its antagonist pro-opiomelanocortin (POMC) were decreased in the hypothalamus in TDP-43 A315T mice (Ferrer-Donato et al., 2021 ) and mutant SOD1 G86R mice (Vercruysse et al., 2016 ), demonstrating of a hypothalamic involvement in ALS. Indeed, there are several adipokines involved in metabolism and regulation of food intake which act within the brain, specifically in the brainstem and hypothalamus, including, but not limited to, leptin, which is primarily produced by WAT in proportion to fat stores (Pico et al., 2022 ). Nevertheless, although clinical evidence suggests that the distribution and content of adipose tissue, and subsequently leptin levels, are significantly altered in ALS and have been correlated with functional status and survival in ALS (Ferrer-Donato et al., 2021 ; Ngo, S. T. et al., 2015; Picher-Martel et al., 2023 ), it is currently unclear whether metabolic changes in ALS are driven by the adipose tissue dysfunction, or whether hypothalamic neuronal dysfunction may contribute to disease processes in ALS. Notably, metabolic changes are also observed in FTD, which exists on a continuous clinical spectrum with ALS (Chen-Plotkin et al., 2010 ). Indeed, although the clinical manifestations of ALS and FTD differ (Chen-Plotkin et al., 2010 ), altered peripheral levels of leptin have been found in patients with FTD (Ahmed et al., 2019 ), while there is also limited information on the mechanism underlying the association between adiposity and brain metabolism. Furthermore, we have determined complex alterations in metabolic hormones, including leptin, in pathology-rich regions of post-mortem human ALS and FTD tissues (Atkinson et al., 2024 ), which is in agreement with our previous results in TDP-43 A315T mice showing that alterations to TDP-43 are linked to reduced circulating levels of leptin and the dysfunction of its signalling pathways at the central nervous system (CNS) (Ferrer-Donato et al., 2021 ). These data are of interest because studies have suggested that higher leptin levels are critical for survival in ALS disease, as leptin levels have been found to be lower in sporadic ALS patients with rapidly progressing disease (Picher-Martel et al., 2023 ), which is in agreement with our previous studies in TDP-43 A315T mice showing the potential benefit of leptin therapy against ALS (Ferrer-Donato et al., 2022 ). Thus, it will be important to study the possible alterations occurring in WAT, which could perturb peripheral to CNS communication, leading to skeletal muscle degeneration in ALS. Here we aimed to better understand whether the WAT plays a critical role in the pathophysiology of ALS, as most ALS patients have hypermetabolism (Fayemendy et al., 2021 ) and weight loss (Dardiotis et al., 2018 ) prior to the onset of motor symptoms. In this context, considering the potential remodelling of WAT and its important role in whole-body homeostasis, we comprehensively characterized changes in WAT at different stages of the disease (asymptomatic, onset and end-stage) in TDP-43 A315T mice compared to gender and age-matched wild-type (WT) littermates, using histology, proteomics method, and molecular biology techniques. In addition, as epidemiological evidence suggests, alterations in leptin levels are associated with changes in disease progression and survival in ALS. Plasma samples of patients with ALS were used to assess sex and BMI differences in leptin concentrations at the time of diagnoses, to determine if leptin may serve as prognostic biomarker in ALS. Exploring these links may help to better understand the mechanisms underlying the relationship between adiposity and disruption in leptin levels in ALS, because, although BMI is the most used measure of global adiposity, it does not represent adiposity in terms of regional fat distribution, which differs between sexes, races and ages. MATERIALS AND METHODS Experimental Animals Two cohorts of sex and age-matched WT non-transgenic littermates (C57Bl/6) and TDP-43 A315T mice (Wegorzewska et al., 2009a ) (n = 60/genotype) were used in this study to conduct histology (n = 30/genotype), proteomic and molecular biology techniques (n = 30/genotype). In both cases, the ALS-like disease was divided into three stages (n = 5/stage): asymptomatic, onset (defined as the last day of individual peak body weight before a gradual loss occurs) and the end-stage of disease (defined as when weight is 20% below the initial weight on three consecutive days), which is typically reached 2–4 weeks after symptom onset. To avoid the ambiguity associated with reported sex-related differences in mean survival time of this mouse model of ALS (Hatzipetros et al., 2014 ; Wegorzewska et al., 2009b ), only male mice were used. Animals were euthanized independently on each stage of disease. Animals expressing the human TDP-43 (hTDP-43) transgene were confirmed via PCR according to the distributor’s protocol. To monitor disease onset and progression, all mice were weighed and assessed three times per week until the disease onset-stage, after which they were checked daily in the morning until the disease end-stage. The maintenance and use of mice and all experimental procedures were approved by the Animal Ethics Committee of the Hospital Nacional de Parapléjicos, Toledo (Spain) (Approval No 26/OH 2018) in accordance with the Spanish Guidelines for the Care and Use of Animals for Scientific Purposes. All analyses were conducted by personnel blinded to the animal genotype. Perfusion and tissue collection Animals were terminally anesthetized with sodium pentobarbitone (140 mg/kg, intraperitoneally) and transcardially perfused with 0.01 M PBS (pH 7.4). For immunohistochemistry, subcutaneous WAT (scWAT) and perigonadal WAT (pgWAT) were immediately dissected, rinsed in cold phosphate buffered saline (PBS), postfixed 70% ethanol, and stored at 4ªC until paraffin embedding using an Automatic Tissue Processor (ATP 1000, Histo-line, Italy), for further use. For molecular biology experiments, scWAT and pgWAT tissues of each animal were split into two fractions and processed independently, for real time qPCR and Western blot analysis, or proteomics methods. Samples were immediately frozen on dry ice and stored at − 80°C for later analysis. Immunohistochemistry (IHC) Paraffin-embedded sections (4µm thick) of scWAT and pgWAT were deparaffinized in xylene and rehydrated through descending grades of ethanol (100%, 95%, 90%, 80% and 70%) to water. Sections were stained with hematoxylin and eosin (H&E), dehydrated through ascending grades of ethanol (75%, 95%, and 100%), cleared in xylene and finally mounted in dibutyl phthalate xylene (DPX). For analysis, digital photomicrographs of the entire scWAT and pgWAT tissue sections (20x; Leica CTR 6000, Leica, Mannheim, Germany) were used to quantify the histochemical staining in 10 random fields for each sample different regions to assess the regional heterogeneity in tissue samples. The regions were outlined using ImageJ software (Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, https://imagej.net/ij/ , 1997–2018). All slides were analysed using the same morphologic criteria for the quantification of crown-like structures (CLSs), defined by the clustering of macrophages (identified by each morphology) to surround a dying adipocyte, as a sign of adipose-tissue inflammation. This criterion was: presence of a ring of mononuclear cells surrounding an adipocyte vacuole. In addition, the number of blood vessels (BV) was also determined to assess vascularity as an index of angiogenesis. Finally, by semiquantitative methods we determined inflammatory markers such as mononuclear infiltrate and fibrosis, and necrosis markers such as adipocyte normal membrane shape and tissue integrity. Semiquantitative scores were assigned by an observer based on predefined morphologic criteria: 1 ( 75%). Measure 10 fields at 10x in simple scWAT and pgWAT tissues (n = 60). All analyses were conducted by personnel blinded to animal genotype. Total protein preparation and mass spectrometry analysis Sample preparation for library generation Proteins were separated on precast gel, 4–20% MiniPROTEAN TGX (BioRad) and visualized by Coomassie staining. The entire gel lane was manually cut into 8 sections and subjected to in-gel tryptic digestion. The digestion was performed according to Schevchenko et al . (Shevchenko et al., 1996 ) with minor modifications: gel slices were incubated with 10mM dithiothreitol (DTT; Sigma Aldrich) in 50mM ammonium bicarbonate (99% purity; Scharlau) for 60min at 37ºC and after reduction, alkylation with 55mM iodoacetamide (IAA; Sigma Aldrich) in 50mM ammonium bicarbonate was carried out for 20min at RT. Gel plugs were washed with 50mM ammonium bicarbonate in 50% methanol (gradient, HPLC grade, Scharlau), rinsed in acetonitrile (ACN, gradient, HPLC grade, Scharlau) and dried in a Speedvac. Dry gel pieces were then embedded in sequencing grade modified porcine trypsin (Promega, Madison, WI, USA) at a final concentration of 12.5ng/µL in 20 mM ammonium bicarbonate. After digestion at 37 ºC overnight, peptides were extracted with 60% acetonitrile in 0.5% formic acid (FA, 99.5% purity; Sigma Aldrich) and the samples were resuspended in 10µL [98% water with 2% formic acid and 2% ACN]. Sample preparation for SWATH analysis Samples lysates were digested using Single-pot solid-phase-enhanced sample preparation (SP3) according to the protocol of Hughes et al. The lysates were reduced and alkylated using DTT and IAA, respectively. After reduction and alkylation, 6 µL of the prepared bead mix was added to the lysate and made up to 30 µL using H2O. Afterward, EtOH was added to a final concentration of 70% (v / v) and the samples were left stirring at 1000rpm and room temperature for 20 min. Subsequently, the beads were immobilized by incubation on a magnetic rack for 2 min. The supernatant was recovered in a new vial and the entire procedure was repeated. The pellet was rinsed with 80% (v / v) EtOH in water several times. The beads were resuspended in 300 µl of 100mM NH4HCO3 supplemented with trypsin in an enzyme to protein ratio of 1:25 (w / w). After digestion overnight at 37°C and 1000 rpm, the samples are centrifuged at 20,000 g, the supernatant is collected and acidified using 2% FA. LCMSMS Analysis for library, DDA and SWATH In order to build the spectral library, the peptides extract were analysed by a shotgun approach by nanoLC-MS/MS. Samples were pooled and 3µg was separated into a Ekspert™ nanoLC425 (Eksigent, Dublin, CA, USA) using a C18 column (ChromXPC18, 3µm, 120Å 0.075 x 150 mm, Eksigent) at a flow rate of 300nL/min in combination with a precolumn (NanoLC Trap ChromXP C18, 3µm 120Å, Eksigent) at a flow rate of 5µL/min. The buffers being used were: A = 0.1%FA 2%ACN and B = 98% ACN in water with 0.1% FA. Peptide were desalted for 3 min with 0.1%FA/2% ACN on the precolumn, followed by a separation for 85min using gradient from 5–30% solvent B, 30%-95% for 0.1min, and finally 95%B for 5min. Column was then regenerated with 5%B for 10 additional minutes. Peptides eluted were directly injected into a hybrid quadrupole-TOF mass spectrometer TripleTOF® 6600+ (Sciex, Redwood City, CA, USA). Sample was ionized in a source type Optiflow < 1µL Nano applying 3.0kV to the spray emitter at 200ºC. Analysis was carried out in a data-dependent positive ion mode (DDA). Survey MS1 scans were acquired 350–1400 m/z for 250 ms. The TripleTOF was operated in SWATH mode, in which a 50 ms TOF MS scan from 350–1400 m/z was performed, followed by 50 ms product ion scans from 100–1500 m/z on the 70 variable windows from 350 to 1400 Da (2.20 sec/cycle). The individual SWATH injections were randomized. Protein Data Analysis Peptide and protein identifications were performed using ProteinPilot™ Software V 5.0 (Sciex) and the Paragon algorithm (Shilov et al., 2007 ). Each MS/MS spectrum was searched against the uniprot-proteome_MusMusculus_2021_04 database, with the fixed modification of carbamidomethyl -labelled cysteine parameter enabled. Other parameters such as the tryptic cleavage specificity, the precursor ion mass accuracy and the fragment ion mass accuracy, are TripleTOF® 6600plus built in functions of the ProteinPilot software. SWATH Acquisition MicroApp v.2.0 was used for building a peptide spectral library containing the peptide identified in the database search with confidence score above 95%. SWATH Acquisition MicroApp was used for extracting the ion chromatogram traces from the SWATH raw files and using the previously generated spectral library, and the following parameters: 20 peptides/protein; 6 fragment ions/peptide; extraction windows of 5 min and 25 ppm; peptide FDR of 1% and confidence score threshold of 95%. Normalisation of the protein abundance signal as measured by SWATH was carried out using MarkerView (v1.2.1, Sciex). RNA Isolation and qPCR analysis Total RNA was isolated from WAT using the RNeasy Mini Kit (Qiagen), according to the manufacturer's instructions. Complementary DNA (cDNA) (0.5 µg of total RNA) synthesis and the relative quantification of TDP-43 , UCP-1 , C/EBPβ and PPARγ were performed as described previously (Fernandez et al., 2009 ). The 18S rRNA was used as a control to normalize gene expression (Fernandez et al., 2010 ). The reactions were run on an CFX96 Real-Time System instrument and software (CFX Manager 3.0) (BioRad) according to the manufacturer's protocol. Primers were designed using NCBI/Primer-BLAST software (Table 1 ). Relative quantification for each gene was performed by the ∆∆Ct method (Livak & Schmittgen, 2001 ). Table 1 List of RT-qPCR primers. Gene Forward primer Reverse primer Acc no. TDP-43 GGGCGATGGTGTGACTGTAA GCTCGTCTGGGCTTTGCTTA NM_145556 UCP-1 GGCCTCTACGACTCAGTCCA TAAGCCGGCTGAGATCTTGT NM_009463 C/EBPβ GACAAGCTGAGCGACGAGT CGCACCGCGATGTTGTTG NM_001287738 PPARγ AGAGGTGGCCATCCGAATTT ACGGCTTCTACGGATCGAAA NM_011146 Primers used for RT-qPCR analysis of the genes assessed here, including the gene symbol, primer sequence (forward and reverse sequence respectively) and GenBank accession number. Protein extraction and western-blot analysis Proteins from WAT were extracted using RIPA buffer (Sigma Aldrich) containing a cocktail of protease inhibitors (Roche) as described previously (Ferrer-Donato et al., 2021 ). Denatured protein samples (20 µg) from each group were electrophoresed into Bolt® Bis–Tris Plus gels (Invitrogen), transferred to PVDF membranes (BioRad) and incubated with rabbit anti-TDP-43 (1:1000; Proteintech) overnight. Subsequently, anti-rabbit horseradish peroxidase (HRP)-conjugated secondary antibody (Vector Laboratories) was used as described previously ( 10.3390/ijms221910305 ). Mouse anti-actin (1:1000; Cell Signalling) was used as a loading control and band intensity was measured as the integrated intensity using ImageJ software (v1.4; NIH). All data were normalized to control values on each membrane. Human plasma samples All procedures performed in studies involving human samples (plasma) were in accordance with the Ethics Committee (783/23/98) of the University CEU-San Pablo, Madrid, Spain. Human plasma samples were provided by the Biobank HUB-ICO-IDIBELL, integrated in the ISCIII Biobanks and Biomodels Platform and they were processed following standard operating procedures with the appropriate approval of the Ethics and Scientic Committees. Patients were eligible for inclusion if they had diagnosis of ALS based on Gold Coast criteria (Shefner et al., 2020 ). Controls were also provided by the Biobank HUB-ICO-IDIBELL. Samples were collected at the hospital using Lithium heparin collecting tubes at the time of diagnosis. Samples were centrifuged at 10,000 RPM for 10 min. The supernatant was collected and frozen at -80 degrees Celsius. ALS patients were classified by sex, BMI and survival. Patients were classified as nonobese (BMI, < 25) and obese (BMI, ≥ 25). BMI was calculated at the time of diagnosis. Patients were classified as slow progressors when survival was higher than 5 years, as normal progressors when survival was between 3 and 5 years, and as fast progressors when survival was less than 3 years. All the human samples included were of patients who were already deceased at the time of the study. Measurement of plasma leptin by ELISA ELISAs were performed as suggested by the manufacturer’s protocol. Leptin plasma levels were measured using a Human Leptin ELISA Kit PicoKine® (Boster Biological Technology) with samples diluted 1:20 for males and 1:10 for females. Each patient’s samples were processed in duplicate. The limit of detection was 62.5 pg/mL, and the within-assay and between-assay coefficient of variability (CVs) were 7.8% and 6.5%, respectively. Statistical Analysis Statistical analyses were performed using GraphPad Prism software v10.2.0. Normality of datasets was assessed by Kolmogorov-Smirnov Test. Outliers were removed with ROUT method with Q = 1%. For IHC Mann-Whitney test was used. For molecular biology analysis, two-way ANOVA was used followed by Dunett’s post hoc test to compare all groups with control WT asymptomatic mice, while Tukey’s post hoc test was used for multiple comparisons between all groups. To compare within the same group, t-test test was used. For ELISA, two-way ANOVA was used followed by Tukey’s post hoc test for multiple comparisons between all groups. Mann-Whitney test was used to compare within the same group. A Spearman correlation coefficient (rho) was employed to assess the correlation between quantitative variables, with significance set at a p-value of ≤ 0.05 (n = 78). This analysis was performed with SPSS Statistics. Values were reported as means ± standard error of the mean (SEM). For all comparisons, significant results were taken when p value < 0.05. RESULTS Histological examination of WAT reveals significant alterations in TDP-43 A315T mice Given the limited understanding of how WAT is altered during the progression of ALS, we aimed to address this gap by performing a comprehensive histological characterization of scWAT and pgWAT tissues across the three stages of the disease -asymptomatic, onset and end-stage- in TDP-43 A315T mice, compared to age-matched WT littermates, using H&E staining analysis. We first evaluated CLSs and the number of BV in histological sections (Fig. 1 ; Suppl. Figures 1 and 2), and IHC analysis demonstrated marked differences in the number of both parameters in scWAT and pgWAT, respectively, during the clinical course of the disease in TDP-43 A315T mice compared with WT samples (Fig. 1 B; Suppl. Figure 1B and 2B). Although the number of CLSs was similar regardless of the location of the adipocytes (scWAT vs. pgWAT) (Fig. 1 B), Mann-Whitney test demonstrated a statistically significant increase in the number of CLSs in both scWAT and pgWAT tissues during the asymptomatic stage in TDP-43 A315T mice (Fig. 1 B). The number of BV were also similar regardless of the location of the adipocytes (scWAT vs. pgWAT) (Fig. 1 C), however, Mann-Whitney test demonstrated a statistically significant decrease in the number of BV in both scWAT and pgWAT in TDP-43 A315T mice compared to WT mice, suggesting an alteration in the vascularity of the WAT of TDP-43 A315T mice (Fig. 1 C). In contrast, at the onset stage of disease, no statistically differences were found in both parameters analysed between TDP-43 A315T vs. WT samples (Suppl. Figure 1B-C), however, Mann-Whitney test demonstrated a statistically significant increase in the number of CLSs and BV in both scWAT and pgWAT tissues at the end-stage of the disease in TDP-43 A315T mice compared to age-matched WT littermates (Suppl. Figure 2B-C). To gain deeper histological insight into the pathological modifications occurring in WAT during the progression of ALS, we further evaluated mononuclear infiltrate, fibrosis and necrosis in both scWAT and pgWAT tissues at the three stages of the disease in TDP-43 A315T mice vs. WT samples (Fig. 1 D-H; Suppl. Figures 1 and 2D-H, respectively). IHC analysis demonstrated a statistically significant increase on inflammatory marker of mononuclear infiltrate at the asymptomatic stage (Fig. 1 E) and during the symptomatic stage of disease (Suppl. Figures 1 and 2E, respectively) in TDP-43 A315T mice compared to WT mice. Mann-Whitney test demonstrated a statistically significant increase on the fibrosis in both scWAT and pgWAT tissues TDP-43 A315T mice compared to WT controls (Fig. 1 F; Suppl. Figures 1 and 2F, respectively). Regarding adipocyte shape and tissue integrity there was a significant decrease in both scWAT and pgWAT tissues in TDP-43 A315T mice (Fig. 1 G-H; Suppl. Figures 1 and 2G-H, respectively). Proteomics analysis of WAT from TDP-43 A315T mice highlighted the presence of mitochondrial alterations prior to the onset of motor symptoms To further elucidate the molecular alterations occurring in WAT of TDP-43 A315T mice, we conducted a proteomic analysis of pgWAT. We focused our analysis on pgWAT, as in this type of WAT fibrosis and inflammation is increasingly appreciated as a major player in adipose tissue dysfunction, and pgWAT had substantially higher pro-inflammatory characteristics than scWAT. In this context, using a significant threshold of p 2 were determined as up-regulated, whereas the ones with FC < 0.5 were down-regulated. Focusing on the asymptomatic stage of the disease, a total of 1528 proteins were detected as proteins differentially expressed (DEPs) in TDP-43 A315T mice compared to age-matched WT littermates. Of these DEPs, 38 showed to be upregulated, 24 downregulated, and 1466 showed no statistically significant differences (Fig. 2 A). Enrichment and ontology analyses were performed in Metascape, considering upregulated and downregulated DEPs. Enriched ontology cluster network showed significant enrichment of terms mainly related to two categories: carbon metabolism and monocarboxylic acid metabolic process (Fig. 2 C). MCODE clustering analysis recognized 4 different clusters in the protein-protein interaction (PPI) network (Fig. 2 D-E; Table 2 ). MCODE1 represented ontology terms related to mitochondrial fatty acid beta-oxidation and respiratory electron transport. MCODE2 represented ontology terms related with mitochondrial oxidoreductases and ligase and MCODE4 with oxidoreductase and transferases. Though, MCODE3 represents ontology terms related with heme-degradation, scavenging of heme from plasma, lipid-transport. Cellular enrichment analysis showed DEPs grouped together in mitochondria, peroxisome and cytosol (Fig. 2 F). Table 2 MCODE clustering details in asymptomatic and end-stage. Network Term ID Term Description p -value (-Log10) Asymptomatic MCODE_1 GO:0006635 Fatty acid beta-oxidation -12.9 MCODE_1 GO:0019395 Fatty acid oxidation -12.0 MCODE_1 GO:0009062 Fatty acid catabolic process -11.9 MCODE_2 Mmu00020 Citrate cycle (TCA cyle) – Mus musculus (house mouse) -11.4 MCODE_2 Mmu01210 2-Oxocarboxylyc acid metabolism – Mus musculus (house mouse) -11.3 MCODE_2 GO:0006099 Tricarboxylyc acid cycle -11.3 MCODE_3 WP63 Pentose phosphate pathway -10.7 MCODE_3 GO:0006098 Pentose-phosphate shunt -9.6 MCODE_3 R-MMU-71336 Pentose phosphate pathway -9.5 MCODE_4 R-MMU-2173782 Binding and Uptake of Ligands by Scavenger Receptors -8.4 MCODE_4 R-MMU-5653656 Vesicle-mediated transport -4.7 End-stage MCODE_1 GO:0048255 mRNA stabilization -5.6 MCODE_1 GO:0043489 RNA stabilization -5.4 MCODE_1 GO:1902373 Negative regulation of mRNA catabolic process -5.4 MCODE_2 Mmu00982 Drug metabolism – cytochrome P450 – Mus musculus (house mouse) -14.9 MCODE_2 Mmu00980 Metabolism of xenobiotics by cytochrome p450 – Mus musculus (house model) -14.8 MCODE_2 Mmu05204 Chemical carcinogenesis – DNA adducts – Mus musculus (house mouse) -14.3 Furthermore, focusing on the end-stage of the disease, 121 DEPs were identified from a total of 1569 proteins in TDP-43 A315T mice compared to age-matched WT littermates. Among these DEPs, 75 showed to be upregulated, 46 downregulated and 1448 showed no statistically significant differences (Fig. 3 A). Upregulated and downregulated DEPs were considered for the enrichment and ontology analyses performed in Metascape. Enriched ontology cluster network showed significant enrichment of terms mainly related to three categories: cellular catabolic process, terpenoid metabolic process and metabolism of xenobiotics by cytochrome p450 (Fig. 3 C). MCODE clustering analysis recognized 2 different clusters in the PPI network (Fig. 3 D-E; Table 2 ). MCODE1 represented ontology terms related to lyases, transferases, oxidoreductases, proteins transport, ribonucleoproteins and RNA and DNA binding. MCODE2 represented ontology terms related to transferases, monooxygenases and oxidoreductase. Cellular enrichment analysis showed DEPs grouped together in cytoplasm, endoplasmic reticulum and mitochondrion, among others (Fig. 3 F). Table 2 reports the list of MCODE cluster recognized by the integrated Metascape analysis of proteomic data showed in Fig. 2 D-E and Fig. 3 D-E. For each cluster, the top 3 enriched terms are reported, relatively to the lowest p -value. WAT of TDP-43 A315T mice display altered PPARγ mRNA expression levels concomitantly with an increase on the protein levels of TDP-43 Proteomic analysis highlighted several alterations in pgWAT at the asymptomatic stage in TDP-43 A315T mice, highlighting the presence of mitochondrial alterations, which could potentially impact both cellular differentiation and metabolism. Thus, to better characterize such defects we performed RT-qPCR in the pgWAT of TDP-43 A315T mice over the time course of the disease. RT-qPCR analysis demonstrated no statistically significant differences in the mRNA expression levels of C/EBPβ and PPARγ between TDP-43 A315T and WT mice at either of the time-points analysed (Fig. 4 A-B). In addition, RT-qPCR analysis detected no Ucp1 mRNA in the pgWAT. We then sought to better characterize the patterns of TDP-43 transgene expression in pgWAT of TDP-43 A315T mice compared to age-matched WT littermates. In concordance with the pathological modifications occurring in pgWAT prior to the onset of motor symptoms in TDP-43 A315T mice, endogenous TDP-43 mRNA levels (mTDP-43) were significantly upregulated in TDP-43 A315T mice compared to WT mice during the asymptomatic stage ( p = 0.005; Fig. 4 C), while no statistically significant differences were found between TDP-43 A315T and WT mice at both onset and end-stage. Interestingly, western blot analysis showed that TDP-43 protein levels in pgWAT, probed with a polyclonal antibody that recognizes both human and mouse TDP-43, were increased in TDP-43 A315T mice compared to WT mice at either of the time-points analysed (Fig. 4 D-F; Suppl. Figure 3). Distinct plasma leptin profile in obese men ALS cases with rapidly progressive disease It is unclear whether changes in WAT precede the first signs of ALS, and whether these alterations are manifested systemically through fluctuations in plasma leptin levels, which are known to be influenced by sex and age. Thus, to better understand the mechanisms regulating WAT disruption and the sexual dimorphism in circulating leptin levels in ALS patients. In total, we measured leptin levels in plasma samples of 62 ALS patients and 16 age-matched controls, with 37 men and 41 women of a wide age (30–87 year) and BMI (19.06–33.90 kg/m2) range. No statistically significant difference between patients and control groups was found regarding age ( p = 0.5749) nor BMI ( p = 0.6940) (Table 3 ). Table 3 Characteristics of ALS patients and controls. ALS CONTROL Number of patients 65 16 Age (mean ± SD) (years) 64.27 ± 11.44 65.85 ± 10.93 Sex ratio (male:female) 31:34 7:9 BMI (kg/m 2 ) 25.99 ± 3.42 25.51 ± 3.75 Disease duration (months) 39.36 ± 18.62 NA Survival rate slope 1.65 ± 1.04 NA ALS subtype Bulbar 26 NA Espinal 36 NA PMA 3 NA EVOLUTION FORM Slow evolution (DPR < 0.8) 8 NA Normal evolution (0.8 < DPR 1.35) 34 NA ELISA analysis showed that protein levels of leptin in plasma are increased in ALS patients compared to controls, while it is not significant (Fig. 5 A). Sorting data by sex, protein levels of leptin were significantly increased in plasma of men ALS patients compared to men controls, as well as in women ALS patients when compared to men ALS patients and to men controls (Fig. 5 B, p = 0.019, p < 0.001 and p < 0.001, respectively), while no statistically significant differences were found in women ALS patients compared to women controls. However, when stratifying patients by survival rate, it is observed that plasmatic leptin levels decreased significantly in men ALS patients that have had a fast disease progression when compared to women ALS patients with normal disease progression (Fig. 5 C, p = 0.040). On the contrary, leptin levels in women are similar across the different types of progression, being significantly increased in ALS fast progression women when compared with ALS fast progression men (Fig. 5 C, p < 0.001). Interestingly, when stratifying patients by BMI, for overweight ALS patients, the decrease in plasma leptin levels was significant in men ALS patients with fast disease progression when compared to women ALS patients with normal disease progression (Fig. 5 D, p = 0.006). Moreover, leptin levels of men ALS patients with normal disease progression were also significantly decreased when compared to women ALS patients with normal progression (Fig. 5 D, p = 0.013). For overweight women ALS patients, levels decreased in both slow and fast progression when compared to levels in women ALS patients with normal progression, although not significance was reached (Fig. 5 D). Furthermore, bivariate correlations performed are showed in Table 4 and both sex and BMI exhibit a monotonic relationship with leptin levels ( p < 0.001, r = 0.510 and p < 0.001, r = 0.434, respectively). The correlation of leptin plasma levels with survival rate, as well as the correlation between the qualitative variables, were also evaluated, but no significant differences were found. Table 4 Spearman correlations. Leptin BMI Sex Survival rate slope Leptin r p 0.488 < 0.001 0. 488 < 0.001 0.001 0.993 BMI r p 0.488 < 0.001 -0.027 0.830 -0.063 0.616 Sex r p 0. 488 < 0.001 -0.027 0.830 0.005 0.972 Survival rate slope r p 0.001 0.993 -0.063 0.616 0.005 0.972 DISCUSSION Although metabolic dysfunctions of the CNS in ALS have been widely studied (Rosina et al., 2025 ), metabolic alterations observed in ALS patients and animal models have not been well investigated in peripheral organs such as WAT, which play a key role in the endocrine control of energy homeostasis. The current study aimed to better understand whether the WAT plays a critical role in the pathophysiology of ALS, which is of interest as determining how restoring adipose tissue plasticity may contribute significantly to mitigate the hypermetabolism observed in patients with ALS. In this context, we identify for the first time evidence of a pathological dysfunction in WAT prior to the symptomatic stage of the disease in TDP-43 A315T mice, providing novel insights about the pathways that could link dysregulating systemic energy homeostasis to the progression of ALS. Additionally, an important finding of our study was that circulating leptin levels at the time of diagnosis, were lower in the plasma of men with ALS who were overweight or obese and had rapidly progressive ALS, emphasizing the importance of considering sex-specific approaches to guide the development of effective clinical therapies. At present, there is increasing interest in the use of hypercaloric diets (e.g. high-fat diet; HFD), as gaining weight and, subsequently fat mass has been associated with better survival in ALS (Heritier et al., 2015 ). Both preclinical and human research demonstrate a disease-modifying effect of nutritional state in ALS (Ngo, Shyuan T. et al., 2017). However, although epidemiological data suggest that supplementation with HFD may reduce the risk of developing ALS, as it provides positive survival outcomes (Morozova et al., 2008 ; Ngo, Shyuan T. et al., 2017; Okamoto et al., 2007 ; Veldink et al., 2007 ), the exact molecular mechanisms behind these effects remain elusive. Here, we report a significant pathological dysfunction of WAT prior to the symptomatic stage of the disease in TDP-43 A315T mice. We observed a significant increase in the number of CLSs in both scWAT and pgWAT tissues, concomitantly to a decrease in the number of BV, suggesting an alteration in the vascularity of the WAT prior to the onset of motor symptoms in TDP-43 A315T mice, which might negatively affect the mechanisms governing the expansion of this tissue. Our results also confirm stage-dependent alterations on inflammatory marker of mononuclear infiltrate in TDP-43 A315T mice. These observations are of interest because inflamed adipocytes are a key feature of this condition as they secrete, both locally and systemically, proinflammatory cytokines, such as tumor necrosis factor-alpha (TNFα), which in turn disrupt the normal function of adipose tissue itself and compromises the inefficient expandability of WAT. Indeed, we have previously reported in a more refined model of TDP-43 proteinopathy, the rNLS8 mice (Walker et al., 2015 ), that the ability of a short-term HFD therapy to improve prognosis in ALS mice is not a simple question of gaining weight, which produce a systemic low-grade inflammation itself, it may depend on the capacity of WAT to respond to a caloric excess by its healthy expansion (Romero-Muñoz L et al., 2024). Indeed, an impaired WAT remodelling results in alterations in lipid stored, leading to metabolic derangements, such as altering adipokines production and release (Martinez-Sanchez, 2020 ), which supports previous data from our group showing a significantly downregulation of peripheral leptin levels from the pre-onset stage of disease in TDP-43 A315T mice (Ferrer-Donato et al., 2021 ), thereby influencing metabolic circuits involved in energy intake regulation. Consistently with earlier findings, we also provided data showing significant changes in the proteomic profile of WAT in TDP-43 A315T mice, highlighting alterations such as mitochondrial dysfunction, which can alter the cellular homeostasis of WAT and the adipocytes (Chen et al., 2023 ), concomitantly with an increase on the protein levels of TDP-43 in different phases of the disease compared to age-matched WT littermates. This observation is of interest because the evidence supports that TDP-43 is a powerful regulator of body fat composition (Stallings et al., 2013 ) by mechanisms involving the transcriptional regulation of genes that impaired leptin signalling (Dokas et al., 2016 ), thereby contributing to leptin insensitivity. Thus, it is conceivable that increased protein levels of TDP-43 in WAT disrupt the production and release of leptin by the adipocytes and contribute to a dysfunction of metabolic homeostasis in the CNS in TDP-43 A315T mice, as we previously reported alterations in leptin signalling in the spinal cord and the hypothalamus compared to WT controls (Ferrer-Donato et al., 2021 ), which is in agreement with novel data from our group showing disruption to leptin signalling in pathology-rich brain regions of postmortem human tissue of ALS (Atkinson et al., 2024 ). However, future experiments should try to corroborate this hypothesis. In patients, adipose tissue distribution is altered and has been correlated with functional status and survival (Lindauer et al., 2013 ). Sex differences in disease-related endocrine dysfunction have also been confirmed (Grassano et al., 2024 ), which may explain, at least in part, the higher susceptibility to ALS in men than women (Handley et al., 2022 ). However, although the mechanisms driving this dimorphic incidence are still largely unknown, in accordance with previous published research conducted, both in humans (Hellstrom et al., 2000 ; Konukoglu et al., 2000 ) and mouse model of ALS (Picher-Martel et al., 2023 ), we observed marked sex differences in the plasma levels of leptin early on the symptoms in ALS patients. Accordingly, ELISA analysis demonstrated that leptin levels were significantly increased in the plasma of men, but not in women with ALS, compared to control subjects at the time of diagnosis, which is of interest because it has been established that leptin levels in females are generally higher than in male due to their higher percentage of body fat and their different hormonal profile (Hellstrom et al., 2000 ). However, when stratifying patients by progression of the disease, it is observed that plasmatic leptin levels decreased significantly in men ALS patients that have had a fast disease progression compared to women with ALS. Interestingly, when stratifying patients by BMI, for overweight patients, the decrease in plasma leptin levels was significant in men with fast disease progression compared to women with ALS and with both normal and fast disease progression, respectively. These data suggest that women may be more protected than men against ALS, due to at least two different potential mechanisms, which are not mutually exclusive. One possible mechanism could be the neuroprotective effect of female hormones in the early stages of ALS disease. Indeed, published data showed how sex dichotomy in ALS is only present in the pre-menopausal aged female population, indicating a potential protective role of circulating estrogen (Manjaly et al., 2010 ). Alternatively, sex-related differences in endocrine dysfunction associated with the disease could suggest that pathological dysfunction of WAT is less severe in women than in men ALS patients. Indeed, our unpublished new experimental data reveal a significant delay in the pathological disturbances observed in both scWAT and pgWAT tissues of female TDP-43 A315T mice compared to male ALS mice and WT samples, respectively, which is consistent with reported experimental data in SOD1 G93A mice (Picher-Martel et al., 2023 ). It is also noteworthy that leptin levels are higher in overweight or obese women than in overweight or obese men (Konukoglu et al., 2000 ), consistent with a state of relative leptin resistance, and reflecting differences in body fat composition. Thus, this data might indicate the differences in the physiological response of the hypothalamus to overcome WAT atrophy in ALS, highlighting both leptin and WAT as a putative target organ or to have a prognostic/diagnostic significance. In conclusion, we demonstrate an impairment of WAT during the manifestation of ALS phenotype, which undergoes significant alterations that could potentially impact on the normal physiology of the adipocytes. We showed a significant increase in the number of CLSs, a characteristic histopathology feature of inflamed WAT (Murano et al., 2013 ), an alteration in its vascularity, which promotes adipocyte dysfunction and induces oxidative stress, hypoxia and inflammation (AlZaim et al., 2023 ), a stage-dependent alteration on inflammatory marker of mononuclear infiltrate, and significant changes in the proteomic profile, highlighting mitochondrial alterations, which could significantly disrupt leptin levels (Cavaliere et al., 2023 ), during the clinical course of disease in TDP-43 A315T mice. These alterations in WAT could facilitate a powerful crosstalk between metabolically active organs (e.g. liver, brain, heart and kidneys), modulating energy homeostasis in TDP-43 A315T mice. Indeed, although it remains speculative that such alterations could be due to WAT developmental defects, and although it is important to bear in mind when interpreting our experimental results in TDP-43 mice, they may not be transferable to the clinical practitioner. Further research in ALS patients is crucial to deciphering the role of WAT and understanding the specific functions of leptin levels in the metabolic dysfunction caused by pathological TDP-43, the cause of which remains elusive. Abbreviations ACN acetonitrile AgRP agoute-related peptide ALS amyotrophic lateral sclerosis ATP Automatic Tissue Processor BAT brown adipose tissue BMI body mass index BV blood vessels cDNA complementary DNA CLSs crown-like structures CNS central nervous system CVs coefficient of variability DDA data-dependent positive ion mode DEPs proteins differentially expressed DPX dibutyl phthalate xylene DTT dithiothreitol FA formic acid FTD frontotemporal dementia H&E hematoxylin and eosin HFD high-fat diet HRP horseradish peroxidase hTDP-43 human TDP-43 IAA iodoacetamide IHC Immunohistochemistry mTDP-43 endogenous TDP-43 PBS phosphate buffered saline pgWAT perigonadal WAT POMC antagonist pro-opiomelanocortin PPI protein-protein interaction scWAT subcutaneous WAT SEM standard error of the mean SP3 single-pot, solid-phase-enhanced TDP-43 TAR DNA binding protein TNFα Tumor Necrosis Factor alpha UFMN Functional Motorneuron Unit WAT white adipose tissue WT wild-type Declarations Ethics approval and consent to participate All animal procedures were performed in accordance with the Animal Ethics Committee of the Hospital Nacional de Parapléjicos (Approval No 36OH/2019) (Spain) in accordance with the European Communities Council Directive (86/609/EEC) for the Care and Use of Animals for Scientific Purposes. Human samples described in this manuscript were collected under protocols that were reviewed and approved by the Functional Unit of Amyotrophic Lateral Sclerosis (UFELA), Service of Neurology, Bellvitge University Hospital, Hospitalet de Llobregat, (Spain). Subjects underwent informed consent prior to participating in research studies. Consent for publication All authors have read and agreed to the published version of the manuscript. Availability of data and materials The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding The project leading to these results is funded by “la Caixa” Banking Foundation and co-funded by Fundación Luzón under the project code (LCF/PR/HR19/52160016), Spain. Authors' contributions C-BC, A-FD collected the tissues; C-BC, E-DM performed histological data analysis; G-BG performed proteomic and provided expertise in data analysis; R-DM, MP provided clinical expertise in data analysis and patient information; C-BC, C-FM performed statistical analysis and prepared the figures. C-FM conceived and designed the study. C-FM drafted the manuscript. All authors critically reviewed the manuscript for intellectual content. All authors have read and agreed to the published version of the manuscript. Acknowledgments The authors would like to thank the Proteomics Unit of the Hospital Nacional de Parapléjicos for their invaluable technical and analytical assistance in the use of proteomic technology, and the Surgery Unit of the Hospital Nacional de Parapléjicos, Toledo (Spain) for their excellent technical support. In addition, the authors would like to thank patients and Biobank HUB-ICO-IDIBELL (PT20/00171) integrated in the ISCIII Biobanks and Biomodels Platform and Xarxa Banc de Tumors de Catalunya (XBTC) for their collaboration and provide human plasma samples. Finally, Cristina Benito-Casado is supported by a PhD Fellowship from the Consejería de Educación, Ciencia y Universidades Comunidad de Madrid (PIPF-2023/SAL-GL-29613). References Ahmed RM, Irish M, Piguet O, Halliday GM, Ittner LM, Farooqi S, Hodges JR, Kiernan MC (2016) Amyotrophic lateral sclerosis and frontotemporal dementia: distinct and overlapping changes in eating behaviour and metabolism. Lancet Neurol 15(3):332–342. 10.1016/S1474-4422(15)00380-4 Ahmed RM, Phan K, Highton-Williamson E, Strikwerda-Brown C, Caga J, Ramsey E, Zoing M, Devenney E, Kim WS, Hodges JR, Piguet O, Halliday GM, Kiernan MC (2019) Eating peptides: biomarkers of neurodegeneration in amyotrophic lateral sclerosis and frontotemporal dementia. 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Supplementary Files Suppl.Fig.1.jpg Suppl.Fig.2.jpg Suppl.Fig.3.jpg Cite Share Download PDF Status: Published Journal Publication published 09 Oct, 2025 Read the published version in Acta Neuropathologica Communications → Version 1 posted Editorial decision: Revision requested 16 Aug, 2025 Reviews received at journal 14 Jul, 2025 Reviews received at journal 13 Jul, 2025 Reviewers agreed at journal 06 Jul, 2025 Reviewers agreed at journal 06 Jul, 2025 Reviewers agreed at journal 06 Jul, 2025 Reviewers invited by journal 06 Jul, 2025 Editor assigned by journal 03 Jul, 2025 Submission checks completed at journal 03 Jul, 2025 First submitted to journal 26 Jun, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6984477","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":481224746,"identity":"ff99ef1d-d9a6-4488-bbe6-c27f179f4def","order_by":0,"name":"Cristina Benito-Casado","email":"","orcid":"","institution":"Universidad CEU-San Pablo","correspondingAuthor":false,"prefix":"","firstName":"Cristina","middleName":"","lastName":"Benito-Casado","suffix":""},{"id":481224747,"identity":"1b216973-44b9-419e-844f-0a09e2d8067d","order_by":1,"name":"Esther Durán-Mateos","email":"","orcid":"","institution":"Universidad CEU-San Pablo","correspondingAuthor":false,"prefix":"","firstName":"Esther","middleName":"","lastName":"Durán-Mateos","suffix":""},{"id":481224748,"identity":"d05919ae-8a1a-447f-a4a1-5c423c37417e","order_by":2,"name":"Águeda Ferrer-Donato","email":"","orcid":"","institution":"Universidad CEU-San Pablo","correspondingAuthor":false,"prefix":"","firstName":"Águeda","middleName":"","lastName":"Ferrer-Donato","suffix":""},{"id":481224752,"identity":"aaae9bae-4379-4a82-b173-a3ec8d6a5353","order_by":3,"name":"Gemma Barroso García","email":"","orcid":"","institution":"Hospital Nacional de Parapléjicos, SESCAM, SAI-HNP-IDISCAM","correspondingAuthor":false,"prefix":"","firstName":"Gemma","middleName":"Barroso","lastName":"García","suffix":""},{"id":481224755,"identity":"e05cf333-ca53-4b1a-a832-cc4d7e5946da","order_by":4,"name":"Raúl Domínguez-Rubio","email":"","orcid":"","institution":"Bellvitge University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Raúl","middleName":"","lastName":"Domínguez-Rubio","suffix":""},{"id":481224757,"identity":"feff28e6-5cdc-4fe8-bf40-9a6e81506d50","order_by":5,"name":"Mónica Povedano","email":"","orcid":"","institution":"Bellvitge University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mónica","middleName":"","lastName":"Povedano","suffix":""},{"id":481224758,"identity":"cdbca271-cc13-4af4-a29a-ca3b33d73d2c","order_by":6,"name":"Carmen M. Fernandez-Martos","email":"data:image/png;base64,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","orcid":"","institution":"Universidad CEU-San Pablo","correspondingAuthor":true,"prefix":"","firstName":"Carmen","middleName":"M.","lastName":"Fernandez-Martos","suffix":""}],"badges":[],"createdAt":"2025-06-26 14:38:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6984477/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6984477/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40478-025-02130-9","type":"published","date":"2025-10-09T15:58:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86625789,"identity":"89077208-2d60-48bc-b9cb-e504cb816b23","added_by":"auto","created_at":"2025-07-14 05:13:29","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":946318,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHematoxylin and eosin stained scWAT and pgWAT in asymptomatic stage of male TDP-43\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eA315T\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e mice.\u003c/strong\u003e (A) Representative images of CLSs and BV (section bar = 100 µm). (B) Semi-quantitative analysis of CLSs and (C) BV. (D) Representative images of mononuclear infiltrated, fibrosis and necrosis markers. (E) Semi-quantitative analysis of mononuclear infiltrated, (F) fibrosis, (G) normal membranes shape of AD and (H) integrity of WAT. Abbreviations: scWAT, subcutaneous adipose tissue; pgWAT, perigonadal adipose tissue, CLS, crown-like structures; BV, blood vessels; AD, adipocyte; WAT, white adipose tissue.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/6a28e2142fb90615595da3f9.jpg"},{"id":86625790,"identity":"291fdbdf-5287-45cd-a4f9-2a529da2227a","added_by":"auto","created_at":"2025-07-14 05:13:29","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":564303,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic analysis of WAT at asymptomatic stage in TDP-43\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eA315T\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e mice.\u003c/strong\u003e (A) Volcano plot. Each point represents an individual protein. (B) Enrichment map of representative enriched ontology terms. (C) PPI network colored by MCODE clusters colored by Metascape. (D) PPI network of the separated MCODE clusters from panel C. (E) Cellular component enrichment of DEPs generated with Gene Ontology Software. Abbreviations: WAT, white adipose tissue; PPI, protein-protein interaction; DEPs, proteins differentially expressed.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/412e97fa1f21386259d674ed.jpg"},{"id":86625792,"identity":"efaebd52-8ecb-49a7-9ddb-ad52e4c46c3e","added_by":"auto","created_at":"2025-07-14 05:13:29","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":412495,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic analysis of WAT at end-stage in TDP-43\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eA315T\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e mice.\u003c/strong\u003e (A) Volcano plot. Each point represents an individual protein. (B) Enrichment map of representative enriched ontology terms. (C) PPI network colored by MCODE clusters colored by Metascape. (D) PPI network of the separated MCODE clusters from panel C. (E) Cellular component enrichment of DEPs generated with Gene Ontology Software. Abbreviations: WAT, white adipose tissue; PPI, protein-protein interaction; DEPs, proteins differentially expressed.\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/13b21d72826ecd2a42493a98.jpg"},{"id":86626827,"identity":"eac00910-94ee-4e40-8a94-d6a4bcc19237","added_by":"auto","created_at":"2025-07-14 05:31:43","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1005206,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlterations in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eC/EBPβ, PPARγ\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eTDP-43\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e in WAT of TDP-43\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003eA315T\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e mice. \u003c/strong\u003e(A) \u003cem\u003eC/EBPβ\u003c/em\u003e (B) \u003cem\u003ePPARγ\u003c/em\u003e and (C) \u003cem\u003eTDP-43\u003c/em\u003e mRNA expression. Transcripts were assessed by RT-qPCR in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to age-matched WT littermates at asymptomatic, onset and end-stage of disease. Values are expressed as the mean ± SEM for the different groups. TDP-43 protein in WAT extracts of TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to age-matched WT littermates at asymptomatic (D), onset (E) and end-stage of disease (F). *\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.05, **\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.01, ***\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.001, ****\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.0001. Abbreviations: C/EBPβ, CCAAT Enhancer Binding Protein Beta; PPARγ, Peroxisome proliferator-activated receptor gamma; TDP-43, TAR DNA-binding protein 43; WAT, white adipose tissue; WT, wild-type.\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/82161a9e2ba36043597a1a95.jpg"},{"id":86625795,"identity":"1b394e14-79ad-4584-bd49-5781b54b0a76","added_by":"auto","created_at":"2025-07-14 05:13:29","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":487326,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of plasma leptin levels in ALS patients. \u003c/strong\u003e(A) Concentration of leptin levels at diagnosis measured by ELISA in healthy controls and ALS subgrouped by sex. (B) Concentration of leptin levels at diagnosis in ALS and controls subgrouped by sex and disease progression: slow, normal and fast progression patients. (C) Concentration of leptin levels at diagnosis in ALS and controls subgrouped by sex and rate of progression in overweight patients. *\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.05, **\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.01, ***\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.001, ****\u003cem\u003ep \u0026lt;\u003c/em\u003e 0.0001. Abbreviations: ALS, sporadic amyotrophic lateral sclerosis.\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/1dd4365ac847add96439bf3a.jpg"},{"id":93419771,"identity":"a5d0eee7-7b5a-468a-a862-164fdbefb953","added_by":"auto","created_at":"2025-10-13 16:07:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4717619,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/8eba5a9c-1f70-49dd-9b57-de20136946b2.pdf"},{"id":86626720,"identity":"e3a38890-8ecd-47a9-bbe8-69588d2ddc55","added_by":"auto","created_at":"2025-07-14 05:31:01","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5204776,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/424c517664c46d5564502b25.jpg"},{"id":86625810,"identity":"cb569815-47e6-4e80-a0e6-1c48a59141e3","added_by":"auto","created_at":"2025-07-14 05:13:30","extension":"jpg","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":5041815,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/561f082b85a84ec2bd6ae531.jpg"},{"id":86625803,"identity":"e67b6471-b030-494a-94a4-b27d51aad1db","added_by":"auto","created_at":"2025-07-14 05:13:29","extension":"jpg","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":163466,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6984477/v1/03b9690df6d2c42dcbd383bb.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"White adipose tissue undergoes pathological dysfunction in the TDP-43 A315T mouse model of amyotrophic lateral sclerosis (ALS)","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAmyotrophic lateral sclerosis (ALS) is the third most common neurodegenerative disease worldwide characterized by the selective loss of motor neurons both in the brain and spinal cord (Rowland \u0026amp; Shneider, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), leading to paralysis and respiratory failure. ALS is often rapidly progressive, incurable, and fatal. Over 60% of patients die within 3\u0026ndash;5 years after diagnosis (Connolly et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although much effort has been made in the past two decades to understand the complexity and heterogeneity of ALS, the development of effective therapies remains elusive due to several challenges. One major obstacle is the limited understanding of the underlying mechanisms driving ALS disease.\u003c/p\u003e\u003cp\u003eIdentifying the mechanisms involved in maintaining energy homeostasis in ALS can help to elucidate the growing evidence supporting a strong metabolic component in ALS. Indeed, rapid weight loss is associated with worse disease outcomes in ALS (Janse van Mantgem et al., 2020), and fat mass loss correlates with faster disease progression (Lee et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Conversely, higher initial body mass index (BMI) and obesity (Heritier et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), type 2 diabetes mellitus (Jawaid et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and patients with higher triglyceride and cholesterol levels (Dorst et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) have been associated with longer survival in ALS, indicating fat content and lipid metabolism are important prognostic factors in ALS disease. However, despite these correlations, the underlying mechanisms driving these metabolic derangements remain unclear. Adipose tissue is an endocrine organ and constitute the major lipid store in mammals (Kershaw \u0026amp; Flier, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Two main types of anatomically and physiologically different adipose tissue are present in adults: WAT, which is mainly an energy store (Luo \u0026amp; Liu, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e); and the brown adipose tissue (BAT), with specialized functions in heat production (thermogenesis) (Li et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Moreover, as an endocrine organ, adipose tissue secretes a variety of soluble mediators, with a critical role in the physiological regulation of the metabolism acting on the hypothalamus, a key integrative brain area that regulates neuronal and metabolic circuits involved in energy intake regulation (Goel et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). While dysfunctions in the hypothalamus have only recently been described (Rosina et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), studies have shown this brain structure is atrophied in ALS (Tse et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), even in premorbid stages, and correlates with BMI (Gorges et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Altered eating behaviour have been reported in patients with ALS and frontotemporal dementia (FTD) (Ahmed et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Indeed, we and others demonstrated increased mRNA expression levels of \u003cem\u003eagouti-related peptide\u003c/em\u003e (AgRP), while levels of its \u003cem\u003eantagonist pro-opiomelanocortin\u003c/em\u003e (POMC) were decreased in the hypothalamus in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice (Ferrer-Donato et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and mutant SOD1\u003csup\u003eG86R\u003c/sup\u003e mice (Vercruysse et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), demonstrating of a hypothalamic involvement in ALS. Indeed, there are several adipokines involved in metabolism and regulation of food intake which act within the brain, specifically in the brainstem and hypothalamus, including, but not limited to, leptin, which is primarily produced by WAT in proportion to fat stores (Pico et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nevertheless, although clinical evidence suggests that the distribution and content of adipose tissue, and subsequently leptin levels, are significantly altered in ALS and have been correlated with functional status and survival in ALS (Ferrer-Donato et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ngo, S. T. et al., 2015; Picher-Martel et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), it is currently unclear whether metabolic changes in ALS are driven by the adipose tissue dysfunction, or whether hypothalamic neuronal dysfunction may contribute to disease processes in ALS.\u003c/p\u003e\u003cp\u003eNotably, metabolic changes are also observed in FTD, which exists on a continuous clinical spectrum with ALS (Chen-Plotkin et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Indeed, although the clinical manifestations of ALS and FTD differ (Chen-Plotkin et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), altered peripheral levels of leptin have been found in patients with FTD (Ahmed et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while there is also limited information on the mechanism underlying the association between adiposity and brain metabolism. Furthermore, we have determined complex alterations in metabolic hormones, including leptin, in pathology-rich regions of post-mortem human ALS and FTD tissues (Atkinson et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which is in agreement with our previous results in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice showing that alterations to TDP-43 are linked to reduced circulating levels of leptin and the dysfunction of its signalling pathways at the central nervous system (CNS) (Ferrer-Donato et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These data are of interest because studies have suggested that higher leptin levels are critical for survival in ALS disease, as leptin levels have been found to be lower in sporadic ALS patients with rapidly progressing disease (Picher-Martel et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which is in agreement with our previous studies in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice showing the potential benefit of leptin therapy against ALS (Ferrer-Donato et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, it will be important to study the possible alterations occurring in WAT, which could perturb peripheral to CNS communication, leading to skeletal muscle degeneration in ALS.\u003c/p\u003e\u003cp\u003eHere we aimed to better understand whether the WAT plays a critical role in the pathophysiology of ALS, as most ALS patients have hypermetabolism (Fayemendy et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and weight loss (Dardiotis et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) prior to the onset of motor symptoms. In this context, considering the potential remodelling of WAT and its important role in whole-body homeostasis, we comprehensively characterized changes in WAT at different stages of the disease (asymptomatic, onset and end-stage) in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to gender and age-matched wild-type (WT) littermates, using histology, proteomics method, and molecular biology techniques. In addition, as epidemiological evidence suggests, alterations in leptin levels are associated with changes in disease progression and survival in ALS. Plasma samples of patients with ALS were used to assess sex and BMI differences in leptin concentrations at the time of diagnoses, to determine if leptin may serve as prognostic biomarker in ALS. Exploring these links may help to better understand the mechanisms underlying the relationship between adiposity and disruption in leptin levels in ALS, because, although BMI is the most used measure of global adiposity, it does not represent adiposity in terms of regional fat distribution, which differs between sexes, races and ages.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cb\u003eExperimental Animals\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTwo cohorts of sex and age-matched WT non-transgenic littermates (C57Bl/6) and TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice (Wegorzewska et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2009a\u003c/span\u003e) (n\u0026thinsp;=\u0026thinsp;60/genotype) were used in this study to conduct histology (n\u0026thinsp;=\u0026thinsp;30/genotype), proteomic and molecular biology techniques (n\u0026thinsp;=\u0026thinsp;30/genotype). In both cases, the ALS-like disease was divided into three stages (n\u0026thinsp;=\u0026thinsp;5/stage): asymptomatic, onset (defined as the last day of individual peak body weight before a gradual loss occurs) and the end-stage of disease (defined as when weight is 20% below the initial weight on three consecutive days), which is typically reached 2\u0026ndash;4 weeks after symptom onset. To avoid the ambiguity associated with reported sex-related differences in mean survival time of this mouse model of ALS (Hatzipetros et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Wegorzewska et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009b\u003c/span\u003e), only male mice were used. Animals were euthanized independently on each stage of disease. Animals expressing the human TDP-43 (hTDP-43) transgene were confirmed via PCR according to the distributor\u0026rsquo;s protocol.\u003c/p\u003e\u003cp\u003eTo monitor disease onset and progression, all mice were weighed and assessed three times per week until the disease onset-stage, after which they were checked daily in the morning until the disease end-stage. The maintenance and use of mice and all experimental procedures were approved by the Animal Ethics Committee of the Hospital Nacional de Parapl\u0026eacute;jicos, Toledo (Spain) (Approval No 26/OH 2018) in accordance with the Spanish Guidelines for the Care and Use of Animals for Scientific Purposes. All analyses were conducted by personnel blinded to the animal genotype.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePerfusion and tissue collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnimals were terminally anesthetized with sodium pentobarbitone (140 mg/kg, intraperitoneally) and transcardially perfused with 0.01 M PBS (pH 7.4). For immunohistochemistry, subcutaneous WAT (scWAT) and perigonadal WAT (pgWAT) were immediately dissected, rinsed in cold phosphate buffered saline (PBS), postfixed 70% ethanol, and stored at 4\u0026ordf;C until paraffin embedding using an Automatic Tissue Processor (ATP 1000, Histo-line, Italy), for further use. For molecular biology experiments, scWAT and pgWAT tissues of each animal were split into two fractions and processed independently, for real time qPCR and Western blot analysis, or proteomics methods. Samples were immediately frozen on dry ice and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for later analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmunohistochemistry (IHC)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eParaffin-embedded sections (4\u0026micro;m thick) of scWAT and pgWAT were deparaffinized in xylene and rehydrated through descending grades of ethanol (100%, 95%, 90%, 80% and 70%) to water. Sections were stained with hematoxylin and eosin (H\u0026amp;E), dehydrated through ascending grades of ethanol (75%, 95%, and 100%), cleared in xylene and finally mounted in dibutyl phthalate xylene (DPX). For analysis, digital photomicrographs of the entire scWAT and pgWAT tissue sections (20x; Leica CTR 6000, Leica, Mannheim, Germany) were used to quantify the histochemical staining in 10 random fields for each sample different regions to assess the regional heterogeneity in tissue samples. The regions were outlined using ImageJ software (Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://imagej.net/ij/\u003c/span\u003e\u003cspan address=\"https://imagej.net/ij/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, 1997\u0026ndash;2018). All slides were analysed using the same morphologic criteria for the quantification of crown-like structures (CLSs), defined by the clustering of macrophages (identified by each morphology) to surround a dying adipocyte, as a sign of adipose-tissue inflammation. This criterion was: presence of a ring of mononuclear cells surrounding an adipocyte vacuole. In addition, the number of blood vessels (BV) was also determined to assess vascularity as an index of angiogenesis.\u003c/p\u003e\u003cp\u003eFinally, by semiquantitative methods we determined inflammatory markers such as mononuclear infiltrate and fibrosis, and necrosis markers such as adipocyte normal membrane shape and tissue integrity. Semiquantitative scores were assigned by an observer based on predefined morphologic criteria: 1 (\u0026lt;\u0026thinsp;25%), 2 (25\u0026ndash;50%), 3 (51\u0026ndash;75%), and 4 (\u0026gt;\u0026thinsp;75%). Measure 10 fields at 10x in simple scWAT and pgWAT tissues (n\u0026thinsp;=\u0026thinsp;60). All analyses were conducted by personnel blinded to animal genotype.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTotal protein preparation and mass spectrometry analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSample preparation for library generation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProteins were separated on precast gel, 4\u0026ndash;20% MiniPROTEAN TGX (BioRad) and visualized by Coomassie staining. The entire gel lane was manually cut into 8 sections and subjected to in-gel tryptic digestion. The digestion was performed according to Schevchenko \u003cem\u003eet al\u003c/em\u003e. (Shevchenko et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1996\u003c/span\u003e) with minor modifications: gel slices were incubated with 10mM dithiothreitol (DTT; Sigma Aldrich) in 50mM ammonium bicarbonate (99% purity; Scharlau) for 60min at 37\u0026ordm;C and after reduction, alkylation with 55mM iodoacetamide (IAA; Sigma Aldrich) in 50mM ammonium bicarbonate was carried out for 20min at RT. Gel plugs were washed with 50mM ammonium bicarbonate in 50% methanol (gradient, HPLC grade, Scharlau), rinsed in acetonitrile (ACN, gradient, HPLC grade, Scharlau) and dried in a Speedvac. Dry gel pieces were then embedded in sequencing grade modified porcine trypsin (Promega, Madison, WI, USA) at a final concentration of 12.5ng/\u0026micro;L in 20 mM ammonium bicarbonate. After digestion at 37 \u0026ordm;C overnight, peptides were extracted with 60% acetonitrile in 0.5% formic acid (FA, 99.5% purity; Sigma Aldrich) and the samples were resuspended in 10\u0026micro;L [98% water with 2% formic acid and 2% ACN].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSample preparation for SWATH analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSamples lysates were digested using Single-pot solid-phase-enhanced sample preparation (SP3) according to the protocol of Hughes et al. The lysates were reduced and alkylated using DTT and IAA, respectively. After reduction and alkylation, 6 \u0026micro;L of the prepared bead mix was added to the lysate and made up to 30 \u0026micro;L using H2O. Afterward, EtOH was added to a final concentration of 70% (v / v) and the samples were left stirring at 1000rpm and room temperature for 20 min. Subsequently, the beads were immobilized by incubation on a magnetic rack for 2 min. The supernatant was recovered in a new vial and the entire procedure was repeated. The pellet was rinsed with 80% (v / v) EtOH in water several times. The beads were resuspended in 300 \u0026micro;l of 100mM NH4HCO3 supplemented with trypsin in an enzyme to protein ratio of 1:25 (w / w). After digestion overnight at 37\u0026deg;C and 1000 rpm, the samples are centrifuged at 20,000 g, the supernatant is collected and acidified using 2% FA.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLCMSMS Analysis for library, DDA and SWATH\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to build the spectral library, the peptides extract were analysed by a shotgun approach by nanoLC-MS/MS. Samples were pooled and 3\u0026micro;g was separated into a Ekspert\u0026trade; nanoLC425 (Eksigent, Dublin, CA, USA) using a C18 column (ChromXPC18, 3\u0026micro;m, 120\u0026Aring; 0.075 x 150 mm, Eksigent) at a flow rate of 300nL/min in combination with a precolumn (NanoLC Trap ChromXP C18, 3\u0026micro;m 120\u0026Aring;, Eksigent) at a flow rate of 5\u0026micro;L/min. The buffers being used were: A\u0026thinsp;=\u0026thinsp;0.1%FA 2%ACN and B\u0026thinsp;=\u0026thinsp;98% ACN in water with 0.1% FA. Peptide were desalted for 3 min with 0.1%FA/2% ACN on the precolumn, followed by a separation for 85min using gradient from 5\u0026ndash;30% solvent B, 30%-95% for 0.1min, and finally 95%B for 5min. Column was then regenerated with 5%B for 10 additional minutes. Peptides eluted were directly injected into a hybrid quadrupole-TOF mass spectrometer TripleTOF\u0026reg; 6600+ (Sciex, Redwood City, CA, USA). Sample was ionized in a source type Optiflow\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026micro;L Nano applying 3.0kV to the spray emitter at 200\u0026ordm;C. Analysis was carried out in a data-dependent positive ion mode (DDA). Survey MS1 scans were acquired 350\u0026ndash;1400 m/z for 250 ms. The TripleTOF was operated in SWATH mode, in which a 50 ms TOF MS scan from 350\u0026ndash;1400 m/z was performed, followed by 50 ms product ion scans from 100\u0026ndash;1500 m/z on the 70 variable windows from 350 to 1400 Da (2.20 sec/cycle). The individual SWATH injections were randomized.\u003c/p\u003e\u003cp\u003e\u003cb\u003eProtein Data Analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePeptide and protein identifications were performed using ProteinPilot\u0026trade; Software V 5.0 (Sciex) and the Paragon algorithm (Shilov et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Each MS/MS spectrum was searched against the uniprot-proteome_MusMusculus_2021_04 database, with the fixed modification of carbamidomethyl -labelled cysteine parameter enabled. Other parameters such as the tryptic cleavage specificity, the precursor ion mass accuracy and the fragment ion mass accuracy, are TripleTOF\u0026reg; 6600plus built in functions of the ProteinPilot software. SWATH Acquisition MicroApp v.2.0 was used for building a peptide spectral library containing the peptide identified in the database search with confidence score above 95%. SWATH Acquisition MicroApp was used for extracting the ion chromatogram traces from the SWATH raw files and using the previously generated spectral library, and the following parameters: 20 peptides/protein; 6 fragment ions/peptide; extraction windows of 5 min and 25 ppm; peptide FDR of 1% and confidence score threshold of 95%. Normalisation of the protein abundance signal as measured by SWATH was carried out using MarkerView (v1.2.1, Sciex).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRNA Isolation and qPCR analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was isolated from WAT using the RNeasy Mini Kit (Qiagen), according to the manufacturer's instructions. Complementary DNA (cDNA) (0.5 \u0026micro;g of total RNA) synthesis and the relative quantification of \u003cem\u003eTDP-43\u003c/em\u003e, \u003cem\u003eUCP-1\u003c/em\u003e, \u003cem\u003eC/EBPβ\u003c/em\u003e and \u003cem\u003ePPARγ\u003c/em\u003e were performed as described previously (Fernandez et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The 18S rRNA was used as a control to normalize gene expression (Fernandez et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The reactions were run on an CFX96 Real-Time System instrument and software (CFX Manager 3.0) (BioRad) according to the manufacturer's protocol. Primers were designed using NCBI/Primer-BLAST software (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Relative quantification for each gene was performed by the ∆∆Ct method (Livak \u0026amp; Schmittgen, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eList of RT-qPCR primers.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eForward primer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eReverse primer\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAcc no.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eTDP-43\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGGCGATGGTGTGACTGTAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGCTCGTCTGGGCTTTGCTTA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNM_145556\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eUCP-1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGGCCTCTACGACTCAGTCCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTAAGCCGGCTGAGATCTTGT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNM_009463\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eC/EBPβ\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGACAAGCTGAGCGACGAGT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCGCACCGCGATGTTGTTG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNM_001287738\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePPARγ\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAGAGGTGGCCATCCGAATTT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eACGGCTTCTACGGATCGAAA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNM_011146\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003ePrimers used for RT-qPCR analysis of the genes assessed here, including the gene symbol, primer sequence (forward and reverse sequence respectively) and GenBank accession number.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eProtein extraction and western-blot analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProteins from WAT were extracted using RIPA buffer (Sigma Aldrich) containing a cocktail of protease inhibitors (Roche) as described previously (Ferrer-Donato et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Denatured protein samples (20 \u0026micro;g) from each group were electrophoresed into Bolt\u0026reg; Bis\u0026ndash;Tris Plus gels (Invitrogen), transferred to PVDF membranes (BioRad) and incubated with rabbit anti-TDP-43 (1:1000; Proteintech) overnight. Subsequently, anti-rabbit horseradish peroxidase (HRP)-conjugated secondary antibody (Vector Laboratories) was used as described previously (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms221910305\u003c/span\u003e\u003cspan address=\"10.3390/ijms221910305\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Mouse anti-actin (1:1000; Cell Signalling) was used as a loading control and band intensity was measured as the integrated intensity using ImageJ software (v1.4; NIH). All data were normalized to control values on each membrane.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHuman plasma samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll procedures performed in studies involving human samples (plasma) were in accordance with the\u003c/p\u003e\u003cp\u003eEthics Committee (783/23/98) of the University CEU-San Pablo, Madrid, Spain. Human plasma samples were provided by the Biobank HUB-ICO-IDIBELL, integrated in the ISCIII Biobanks and Biomodels Platform and they were processed following standard operating procedures with the appropriate approval of the Ethics and Scientic Committees.\u003c/p\u003e\u003cp\u003ePatients were eligible for inclusion if they had diagnosis of ALS based on Gold Coast criteria (Shefner et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Controls were also provided by the Biobank HUB-ICO-IDIBELL. Samples were collected at the hospital using Lithium heparin collecting tubes at the time of diagnosis. Samples were centrifuged at 10,000 RPM for 10 min. The supernatant was collected and frozen at -80 degrees Celsius.\u003c/p\u003e\u003cp\u003eALS patients were classified by sex, BMI and survival. Patients were classified as nonobese (BMI, \u0026lt;\u0026thinsp;25) and obese (BMI, \u0026ge;\u0026thinsp;25). BMI was calculated at the time of diagnosis. Patients were classified as slow progressors when survival was higher than 5 years, as normal progressors when survival was between 3 and 5 years, and as fast progressors when survival was less than 3 years. All the human samples included were of patients who were already deceased at the time of the study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMeasurement of plasma leptin by ELISA\u003c/b\u003e\u003c/p\u003e\u003cp\u003eELISAs were performed as suggested by the manufacturer\u0026rsquo;s protocol. Leptin plasma levels were measured using a Human Leptin ELISA Kit PicoKine\u0026reg; (Boster Biological Technology) with samples diluted 1:20 for males and 1:10 for females. Each patient\u0026rsquo;s samples were processed in duplicate. The limit of detection was 62.5 pg/mL, and the within-assay and between-assay coefficient of variability (CVs) were 7.8% and 6.5%, respectively.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eStatistical analyses were performed using GraphPad Prism software v10.2.0. Normality of datasets was assessed by Kolmogorov-Smirnov Test. Outliers were removed with ROUT method with Q\u0026thinsp;=\u0026thinsp;1%. For IHC Mann-Whitney test was used. For molecular biology analysis, two-way ANOVA was used followed by Dunett\u0026rsquo;s post hoc test to compare all groups with control WT asymptomatic mice, while Tukey\u0026rsquo;s post hoc test was used for multiple comparisons between all groups. To compare within the same group, t-test test was used. For ELISA, two-way ANOVA was used followed by Tukey\u0026rsquo;s post hoc test for multiple comparisons between all groups. Mann-Whitney test was used to compare within the same group. A Spearman correlation coefficient (rho) was employed to assess the correlation between quantitative variables, with significance set at a p-value of \u0026le;\u0026thinsp;0.05 (n\u0026thinsp;=\u0026thinsp;78). This analysis was performed with SPSS Statistics. Values were reported as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error of the mean (SEM). For all comparisons, significant results were taken when p value\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eHistological examination of WAT reveals significant alterations in TDP-43\u003c/b\u003e\u003csup\u003e\u003cb\u003eA315T\u003c/b\u003e\u003c/sup\u003e \u003cb\u003emice\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven the limited understanding of how WAT is altered during the progression of ALS, we aimed to address this gap by performing a comprehensive histological characterization of scWAT and pgWAT tissues across the three stages of the disease -asymptomatic, onset and end-stage- in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, compared to age-matched WT littermates, using H\u0026amp;E staining analysis. We first evaluated CLSs and the number of BV in histological sections (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Suppl. Figures\u0026nbsp;1 and 2), and IHC analysis demonstrated marked differences in the number of both parameters in scWAT and pgWAT, respectively, during the clinical course of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared with WT samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB; Suppl. Figure\u0026nbsp;1B and 2B). Although the number of CLSs was similar regardless of the location of the adipocytes (scWAT \u003cem\u003evs.\u003c/em\u003e pgWAT) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB), Mann-Whitney test demonstrated a statistically significant increase in the number of CLSs in both scWAT and pgWAT tissues during the asymptomatic stage in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The number of BV were also similar regardless of the location of the adipocytes (scWAT \u003cem\u003evs.\u003c/em\u003e pgWAT) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC), however, Mann-Whitney test demonstrated a statistically significant decrease in the number of BV in both scWAT and pgWAT in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to WT mice, suggesting an alteration in the vascularity of the WAT of TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). In contrast, at the onset stage of disease, no statistically differences were found in both parameters analysed between TDP-43\u003csup\u003eA315T\u003c/sup\u003e \u003cem\u003evs.\u003c/em\u003e WT samples (Suppl. Figure\u0026nbsp;1B-C), however, Mann-Whitney test demonstrated a statistically significant increase in the number of CLSs and BV in both scWAT and pgWAT tissues at the end-stage of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to age-matched WT littermates (Suppl. Figure\u0026nbsp;2B-C).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo gain deeper histological insight into the pathological modifications occurring in WAT during the progression of ALS, we further evaluated mononuclear infiltrate, fibrosis and necrosis in both scWAT and pgWAT tissues at the three stages of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice \u003cem\u003evs.\u003c/em\u003e WT samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD-H; Suppl. Figures\u0026nbsp;1 and 2D-H, respectively). IHC analysis demonstrated a statistically significant increase on inflammatory marker of mononuclear infiltrate at the asymptomatic stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE) and during the symptomatic stage of disease (Suppl. Figures\u0026nbsp;1 and 2E, respectively) in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to WT mice. Mann-Whitney test demonstrated a statistically significant increase on the fibrosis in both scWAT and pgWAT tissues TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to WT controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF; Suppl. Figures\u0026nbsp;1 and 2F, respectively). Regarding adipocyte shape and tissue integrity there was a significant decrease in both scWAT and pgWAT tissues in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eG-H; Suppl. Figures\u0026nbsp;1 and 2G-H, respectively).\u003c/p\u003e\u003cp\u003e\u003cb\u003eProteomics analysis of WAT from TDP-43\u003c/b\u003e\u003csup\u003e\u003cb\u003eA315T\u003c/b\u003e\u003c/sup\u003e \u003cb\u003emice highlighted the presence of mitochondrial alterations prior to the onset of motor symptoms\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo further elucidate the molecular alterations occurring in WAT of TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, we conducted a proteomic analysis of pgWAT. We focused our analysis on pgWAT, as in this type of WAT fibrosis and inflammation is increasingly appreciated as a major player in adipose tissue dysfunction, and pgWAT had substantially higher pro-inflammatory characteristics than scWAT. In this context, using a significant threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, proteins having FC\u0026thinsp;\u0026gt;\u0026thinsp;2 were determined as up-regulated, whereas the ones with FC\u0026thinsp;\u0026lt;\u0026thinsp;0.5 were down-regulated.\u003c/p\u003e\u003cp\u003eFocusing on the asymptomatic stage of the disease, a total of 1528 proteins were detected as proteins differentially expressed (DEPs) in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to age-matched WT littermates. Of these DEPs, 38 showed to be upregulated, 24 downregulated, and 1466 showed no statistically significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Enrichment and ontology analyses were performed in Metascape, considering upregulated and downregulated DEPs. Enriched ontology cluster network showed significant enrichment of terms mainly related to two categories: carbon metabolism and monocarboxylic acid metabolic process (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). MCODE clustering analysis recognized 4 different clusters in the protein-protein interaction (PPI) network (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-E; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). MCODE1 represented ontology terms related to mitochondrial fatty acid beta-oxidation and respiratory electron transport. MCODE2 represented ontology terms related with mitochondrial oxidoreductases and ligase and MCODE4 with oxidoreductase and transferases. Though, MCODE3 represents ontology terms related with heme-degradation, scavenging of heme from plasma, lipid-transport. Cellular enrichment analysis showed DEPs grouped together in mitochondria, peroxisome and cytosol (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMCODE clustering details in asymptomatic and end-stage.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNetwork\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTerm ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTerm Description\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value (-Log10)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"10\" rowspan=\"11\"\u003e\u003cp\u003eAsymptomatic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0006635\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFatty acid beta-oxidation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-12.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0019395\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFatty acid oxidation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-12.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0009062\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFatty acid catabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-11.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMmu00020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCitrate cycle (TCA cyle) \u0026ndash; \u003cem\u003eMus musculus\u003c/em\u003e (house mouse)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-11.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMmu01210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2-Oxocarboxylyc acid metabolism \u0026ndash; \u003cem\u003eMus musculus\u003c/em\u003e (house mouse)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-11.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0006099\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTricarboxylyc acid cycle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-11.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eWP63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePentose phosphate pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-10.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0006098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePentose-phosphate shunt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-9.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR-MMU-71336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePentose phosphate pathway\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-9.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR-MMU-2173782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBinding and Uptake of Ligands by Scavenger Receptors\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-8.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR-MMU-5653656\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eVesicle-mediated transport\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-4.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eEnd-stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0048255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003emRNA stabilization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-5.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:0043489\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRNA stabilization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-5.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGO:1902373\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNegative regulation of mRNA catabolic process\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-5.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMmu00982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDrug metabolism \u0026ndash; cytochrome P450 \u0026ndash; \u003cem\u003eMus musculus\u003c/em\u003e (house mouse)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-14.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMmu00980\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMetabolism of xenobiotics by cytochrome p450 \u0026ndash; \u003cem\u003eMus musculus\u003c/em\u003e (house model)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-14.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMCODE_2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMmu05204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eChemical carcinogenesis \u0026ndash; DNA adducts \u0026ndash; \u003cem\u003eMus musculus\u003c/em\u003e (house mouse)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-14.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFurthermore, focusing on the end-stage of the disease, 121 DEPs were identified from a total of 1569 proteins in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to age-matched WT littermates. Among these DEPs, 75 showed to be upregulated, 46 downregulated and 1448 showed no statistically significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Upregulated and downregulated DEPs were considered for the enrichment and ontology analyses performed in Metascape. Enriched ontology cluster network showed significant enrichment of terms mainly related to three categories: cellular catabolic process, terpenoid metabolic process and metabolism of xenobiotics by cytochrome p450 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). MCODE clustering analysis recognized 2 different clusters in the PPI network (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD-E; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). MCODE1 represented ontology terms related to lyases, transferases, oxidoreductases, proteins transport, ribonucleoproteins and RNA and DNA binding. MCODE2 represented ontology terms related to transferases, monooxygenases and oxidoreductase. Cellular enrichment analysis showed DEPs grouped together in cytoplasm, endoplasmic reticulum and mitochondrion, among others (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports the list of MCODE cluster recognized by the integrated Metascape analysis of proteomic data showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD-E and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD-E. For each cluster, the top 3 enriched terms are reported, relatively to the lowest \u003cem\u003ep\u003c/em\u003e-value.\u003c/p\u003e\u003cp\u003e\u003cb\u003eWAT of TDP-43\u003c/b\u003e\u003csup\u003e\u003cb\u003eA315T\u003c/b\u003e\u003c/sup\u003e \u003cb\u003emice display altered\u003c/b\u003e \u003cb\u003ePPARγ\u003c/b\u003e \u003cb\u003emRNA expression levels concomitantly with an increase on the protein levels of TDP-43\u003c/b\u003e\u003c/p\u003e\u003cp\u003eProteomic analysis highlighted several alterations in pgWAT at the asymptomatic stage in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, highlighting the presence of mitochondrial alterations, which could potentially impact both cellular differentiation and metabolism. Thus, to better characterize such defects we performed RT-qPCR in the pgWAT of TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice over the time course of the disease. RT-qPCR analysis demonstrated no statistically significant differences in the mRNA expression levels of \u003cem\u003eC/EBPβ\u003c/em\u003e and \u003cem\u003ePPARγ\u003c/em\u003e between TDP-43\u003csup\u003eA315T\u003c/sup\u003e and WT mice at either of the time-points analysed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). In addition, RT-qPCR analysis detected no \u003cem\u003eUcp1\u003c/em\u003e mRNA in the pgWAT. We then sought to better characterize the patterns of TDP-43 transgene expression in pgWAT of TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to age-matched WT littermates. In concordance with the pathological modifications occurring in pgWAT prior to the onset of motor symptoms in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, endogenous \u003cem\u003eTDP-43\u003c/em\u003e mRNA levels (mTDP-43) were significantly upregulated in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to WT mice during the asymptomatic stage (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), while no statistically significant differences were found between TDP-43\u003csup\u003eA315T\u003c/sup\u003e and WT mice at both onset and end-stage. Interestingly, western blot analysis showed that TDP-43 protein levels in pgWAT, probed with a polyclonal antibody that recognizes both human and mouse TDP-43, were increased in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to WT mice at either of the time-points analysed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-F; Suppl. Figure\u0026nbsp;3).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDistinct plasma leptin profile in obese men ALS cases with rapidly progressive disease\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIt is unclear whether changes in WAT precede the first signs of ALS, and whether these alterations are manifested systemically through fluctuations in plasma leptin levels, which are known to be influenced by sex and age. Thus, to better understand the mechanisms regulating WAT disruption and the sexual dimorphism in circulating leptin levels in ALS patients. In total, we measured leptin levels in plasma samples of 62 ALS patients and 16 age-matched controls, with 37 men and 41 women of a wide age (30\u0026ndash;87\u0026nbsp;year) and BMI (19.06\u0026ndash;33.90 kg/m2) range. No statistically significant difference between patients and control groups was found regarding age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.5749) nor BMI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.6940) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of ALS patients and controls.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eALS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCONTROL\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (mean \u0026plusmn; SD) (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64.27 \u0026plusmn; 11.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65.85 \u0026plusmn; 10.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex ratio (male:female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e31:34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7:9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.99 \u0026plusmn; 3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.51 \u0026plusmn; 3.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease duration (months)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39.36 \u0026plusmn; 18.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurvival rate slope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.65 \u0026plusmn; 1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eALS subtype\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBulbar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEspinal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEVOLUTION FORM\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSlow evolution (DPR\u0026thinsp;\u0026lt;\u0026thinsp;0.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal evolution (0.8\u0026thinsp;\u0026lt;\u0026thinsp;DPR\u0026thinsp;\u0026lt;\u0026thinsp;1.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFast evolution (DPR\u0026thinsp;\u0026gt;\u0026thinsp;1.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eELISA analysis showed that protein levels of leptin in plasma are increased in ALS patients compared to controls, while it is not significant (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Sorting data by sex, protein levels of leptin were significantly increased in plasma of men ALS patients compared to men controls, as well as in women ALS patients when compared to men ALS patients and to men controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, p\u0026thinsp;=\u0026thinsp;0.019, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively), while no statistically significant differences were found in women ALS patients compared to women controls. However, when stratifying patients by survival rate, it is observed that plasmatic leptin levels decreased significantly in men ALS patients that have had a fast disease progression when compared to women ALS patients with normal disease progression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, p\u0026thinsp;=\u0026thinsp;0.040). On the contrary, leptin levels in women are similar across the different types of progression, being significantly increased in ALS fast progression women when compared with ALS fast progression men (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Interestingly, when stratifying patients by BMI, for overweight ALS patients, the decrease in plasma leptin levels was significant in men ALS patients with fast disease progression when compared to women ALS patients with normal disease progression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, p\u0026thinsp;=\u0026thinsp;0.006). Moreover, leptin levels of men ALS patients with normal disease progression were also significantly decreased when compared to women ALS patients with normal progression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, p\u0026thinsp;=\u0026thinsp;0.013). For overweight women ALS patients, levels decreased in both slow and fast progression when compared to levels in women ALS patients with normal progression, although not significance was reached (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurthermore, bivariate correlations performed are showed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and both sex and BMI exhibit a monotonic relationship with leptin levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.510 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, r\u0026thinsp;=\u0026thinsp;0.434, respectively). The correlation of leptin plasma levels with survival rate, as well as the correlation between the qualitative variables, were also evaluated, but no significant differences were found.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSpearman correlations.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLeptin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSurvival rate slope\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeptin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.488\u003c/p\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0. 488\u003c/p\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.488\u003c/p\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.027\u003c/p\u003e\u003cp\u003e0.830\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.063\u003c/p\u003e\u003cp\u003e0.616\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0. 488\u003c/p\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.027\u003c/p\u003e\u003cp\u003e0.830\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003cp\u003e0.972\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurvival rate slope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e0.993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.063\u003c/p\u003e\u003cp\u003e0.616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003cp\u003e0.972\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAlthough metabolic dysfunctions of the CNS in ALS have been widely studied (Rosina et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), metabolic alterations observed in ALS patients and animal models have not been well investigated in peripheral organs such as WAT, which play a key role in the endocrine control of energy homeostasis. The current study aimed to better understand whether the WAT plays a critical role in the pathophysiology of ALS, which is of interest as determining how restoring adipose tissue plasticity may contribute significantly to mitigate the hypermetabolism observed in patients with ALS. In this context, we identify for the first time evidence of a pathological dysfunction in WAT prior to the symptomatic stage of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, providing novel insights about the pathways that could link dysregulating systemic energy homeostasis to the progression of ALS. Additionally, an important finding of our study was that circulating leptin levels at the time of diagnosis, were lower in the plasma of men with ALS who were overweight or obese and had rapidly progressive ALS, emphasizing the importance of considering sex-specific approaches to guide the development of effective clinical therapies.\u003c/p\u003e\u003cp\u003eAt present, there is increasing interest in the use of hypercaloric diets (e.g. high-fat diet; HFD), as gaining weight and, subsequently fat mass has been associated with better survival in ALS (Heritier et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Both preclinical and human research demonstrate a disease-modifying effect of nutritional state in ALS (Ngo, Shyuan T. et al., 2017). However, although epidemiological data suggest that supplementation with HFD may reduce the risk of developing ALS, as it provides positive survival outcomes (Morozova et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Ngo, Shyuan T. et al., 2017; Okamoto et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Veldink et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), the exact molecular mechanisms behind these effects remain elusive. Here, we report a significant pathological dysfunction of WAT prior to the symptomatic stage of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice. We observed a significant increase in the number of CLSs in both scWAT and pgWAT tissues, concomitantly to a decrease in the number of BV, suggesting an alteration in the vascularity of the WAT prior to the onset of motor symptoms in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, which might negatively affect the mechanisms governing the expansion of this tissue. Our results also confirm stage-dependent alterations on inflammatory marker of mononuclear infiltrate in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice. These observations are of interest because inflamed adipocytes are a key feature of this condition as they secrete, both locally and systemically, proinflammatory cytokines, such as tumor necrosis factor-alpha (TNFα), which in turn disrupt the normal function of adipose tissue itself and compromises the inefficient expandability of WAT. Indeed, we have previously reported in a more refined model of TDP-43 proteinopathy, the rNLS8 mice (Walker et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), that the ability of a short-term HFD therapy to improve prognosis in ALS mice is not a simple question of gaining weight, which produce a systemic low-grade inflammation itself, it may depend on the capacity of WAT to respond to a caloric excess by its healthy expansion (Romero-Mu\u0026ntilde;oz L et al., 2024). Indeed, an impaired WAT remodelling results in alterations in lipid stored, leading to metabolic derangements, such as altering adipokines production and release (Martinez-Sanchez, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which supports previous data from our group showing a significantly downregulation of peripheral leptin levels from the pre-onset stage of disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice (Ferrer-Donato et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), thereby influencing metabolic circuits involved in energy intake regulation.\u003c/p\u003e\u003cp\u003eConsistently with earlier findings, we also provided data showing significant changes in the proteomic profile of WAT in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, highlighting alterations such as mitochondrial dysfunction, which can alter the cellular homeostasis of WAT and the adipocytes (Chen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), concomitantly with an increase on the protein levels of TDP-43 in different phases of the disease compared to age-matched WT littermates. This observation is of interest because the evidence supports that TDP-43 is a powerful regulator of body fat composition (Stallings et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) by mechanisms involving the transcriptional regulation of genes that impaired leptin signalling (Dokas et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), thereby contributing to leptin insensitivity. Thus, it is conceivable that increased protein levels of TDP-43 in WAT disrupt the production and release of leptin by the adipocytes and contribute to a dysfunction of metabolic homeostasis in the CNS in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, as we previously reported alterations in leptin signalling in the spinal cord and the hypothalamus compared to WT controls (Ferrer-Donato et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which is in agreement with novel data from our group showing disruption to leptin signalling in pathology-rich brain regions of postmortem human tissue of ALS (Atkinson et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, future experiments should try to corroborate this hypothesis.\u003c/p\u003e\u003cp\u003eIn patients, adipose tissue distribution is altered and has been correlated with functional status and survival (Lindauer et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Sex differences in disease-related endocrine dysfunction have also been confirmed (Grassano et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which may explain, at least in part, the higher susceptibility to ALS in men than women (Handley et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, although the mechanisms driving this dimorphic incidence are still largely unknown, in accordance with previous published research conducted, both in humans (Hellstrom et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Konukoglu et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) and mouse model of ALS (Picher-Martel et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), we observed marked sex differences in the plasma levels of leptin early on the symptoms in ALS patients. Accordingly, ELISA analysis demonstrated that leptin levels were significantly increased in the plasma of men, but not in women with ALS, compared to control subjects at the time of diagnosis, which is of interest because it has been established that leptin levels in females are generally higher than in male due to their higher percentage of body fat and their different hormonal profile (Hellstrom et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). However, when stratifying patients by progression of the disease, it is observed that plasmatic leptin levels decreased significantly in men ALS patients that have had a fast disease progression compared to women with ALS. Interestingly, when stratifying patients by BMI, for overweight patients, the decrease in plasma leptin levels was significant in men with fast disease progression compared to women with ALS and with both normal and fast disease progression, respectively. These data suggest that women may be more protected than men against ALS, due to at least two different potential mechanisms, which are not mutually exclusive. One possible mechanism could be the neuroprotective effect of female hormones in the early stages of ALS disease. Indeed, published data showed how sex dichotomy in ALS is only present in the pre-menopausal aged female population, indicating a potential protective role of circulating estrogen (Manjaly et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Alternatively, sex-related differences in endocrine dysfunction associated with the disease could suggest that pathological dysfunction of WAT is less severe in women than in men ALS patients. Indeed, our unpublished new experimental data reveal a significant delay in the pathological disturbances observed in both scWAT and pgWAT tissues of female TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice compared to male ALS mice and WT samples, respectively, which is consistent with reported experimental data in SOD1\u003csup\u003eG93A\u003c/sup\u003e mice (Picher-Martel et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It is also noteworthy that leptin levels are higher in overweight or obese women than in overweight or obese men (Konukoglu et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), consistent with a state of relative leptin resistance, and reflecting differences in body fat composition. Thus, this data might indicate the differences in the physiological response of the hypothalamus to overcome WAT atrophy in ALS, highlighting both leptin and WAT as a putative target organ or to have a prognostic/diagnostic significance.\u003c/p\u003e\u003cp\u003eIn conclusion, we demonstrate an impairment of WAT during the manifestation of ALS phenotype, which undergoes significant alterations that could potentially impact on the normal physiology of the adipocytes. We showed a significant increase in the number of CLSs, a characteristic histopathology feature of inflamed WAT (Murano et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), an alteration in its vascularity, which promotes adipocyte dysfunction and induces oxidative stress, hypoxia and inflammation (AlZaim et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), a stage-dependent alteration on inflammatory marker of mononuclear infiltrate, and significant changes in the proteomic profile, highlighting mitochondrial alterations, which could significantly disrupt leptin levels (Cavaliere et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), during the clinical course of disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice. These alterations in WAT could facilitate a powerful crosstalk between metabolically active organs (e.g. liver, brain, heart and kidneys), modulating energy homeostasis in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice. Indeed, although it remains speculative that such alterations could be due to WAT developmental defects, and although it is important to bear in mind when interpreting our experimental results in TDP-43 mice, they may not be transferable to the clinical practitioner. Further research in ALS patients is crucial to deciphering the role of WAT and understanding the specific functions of leptin levels in the metabolic dysfunction caused by pathological TDP-43, the cause of which remains elusive.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;acetonitrile\u003c/p\u003e\n\u003cp\u003eAgRP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;agoute-related peptide\u003c/p\u003e\n\u003cp\u003eALS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;amyotrophic lateral sclerosis\u003c/p\u003e\n\u003cp\u003eATP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Automatic Tissue Processor\u003c/p\u003e\n\u003cp\u003eBAT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;brown adipose tissue\u003c/p\u003e\n\u003cp\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;body mass index\u003c/p\u003e\n\u003cp\u003eBV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;blood vessels\u003c/p\u003e\n\u003cp\u003ecDNA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;complementary DNA\u003c/p\u003e\n\u003cp\u003eCLSs\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;crown-like structures\u003c/p\u003e\n\u003cp\u003eCNS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;central nervous system\u003c/p\u003e\n\u003cp\u003eCVs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;coefficient of variability\u003c/p\u003e\n\u003cp\u003eDDA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;data-dependent positive ion mode\u003c/p\u003e\n\u003cp\u003eDEPs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;proteins differentially expressed\u003c/p\u003e\n\u003cp\u003eDPX \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;dibutyl phthalate xylene\u003c/p\u003e\n\u003cp\u003eDTT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;dithiothreitol\u003c/p\u003e\n\u003cp\u003eFA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;formic acid\u003c/p\u003e\n\u003cp\u003eFTD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;frontotemporal dementia\u003c/p\u003e\n\u003cp\u003eH\u0026amp;E \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;hematoxylin and eosin\u003c/p\u003e\n\u003cp\u003eHFD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;high-fat diet\u003c/p\u003e\n\u003cp\u003eHRP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;horseradish peroxidase\u003c/p\u003e\n\u003cp\u003ehTDP-43 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;human TDP-43\u003c/p\u003e\n\u003cp\u003eIAA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;iodoacetamide\u003c/p\u003e\n\u003cp\u003eIHC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Immunohistochemistry\u003c/p\u003e\n\u003cp\u003emTDP-43 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;endogenous TDP-43\u003c/p\u003e\n\u003cp\u003ePBS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;phosphate buffered saline\u003c/p\u003e\n\u003cp\u003epgWAT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;perigonadal WAT\u003c/p\u003e\n\u003cp\u003ePOMC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;antagonist pro-opiomelanocortin\u003c/p\u003e\n\u003cp\u003ePPI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;protein-protein interaction\u003c/p\u003e\n\u003cp\u003escWAT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;subcutaneous WAT\u003c/p\u003e\n\u003cp\u003eSEM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;standard error of the mean\u003c/p\u003e\n\u003cp\u003eSP3 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;single-pot, solid-phase-enhanced\u003c/p\u003e\n\u003cp\u003eTDP-43\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;TAR DNA binding protein\u003c/p\u003e\n\u003cp\u003eTNF\u0026alpha; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Tumor Necrosis Factor alpha\u003c/p\u003e\n\u003cp\u003eUFMN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Functional Motorneuron Unit\u003c/p\u003e\n\u003cp\u003eWAT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;white adipose tissue\u003c/p\u003e\n\u003cp\u003eWT \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;wild-type\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal procedures were performed in accordance with the Animal Ethics Committee of the Hospital Nacional de Parapléjicos (Approval No 36OH/2019) (Spain) in accordance with the\u0026nbsp;European Communities Council Directive (86/609/EEC) for the Care and Use of\u0026nbsp;Animals for Scientific Purposes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHuman samples described in this manuscript were collected under protocols that were reviewed and approved by the Functional Unit of Amyotrophic Lateral Sclerosis (UFELA), Service of Neurology, Bellvitge University Hospital, Hospitalet de Llobregat, (Spain). Subjects underwent informed consent prior to participating in research studies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe project leading to these results is funded by “la Caixa” Banking Foundation and co-funded by Fundación Luzón under the project code (LCF/PR/HR19/52160016), Spain.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC-BC, A-FD collected the tissues; C-BC, E-DM performed histological data analysis; G-BG performed proteomic and provided expertise in data analysis; R-DM, MP provided clinical expertise in data analysis and patient information; C-BC, C-FM performed statistical analysis and prepared the figures. C-FM conceived and designed the study. C-FM drafted the manuscript. All authors critically reviewed the manuscript for intellectual content. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Proteomics Unit of the Hospital Nacional de Parapléjicos for their invaluable technical and analytical assistance in the use of proteomic technology, and the Surgery Unit of the Hospital Nacional de Parapléjicos, Toledo (Spain) for their excellent technical support. In addition, the authors would like to thank patients and Biobank HUB-ICO-IDIBELL (PT20/00171) integrated in the ISCIII Biobanks and Biomodels Platform and Xarxa Banc de Tumors de Catalunya (XBTC) for their collaboration and provide human plasma samples. Finally, Cristina Benito-Casado is supported by a PhD Fellowship from the Consejería de Educación, Ciencia y Universidades Comunidad de Madrid (PIPF-2023/SAL-GL-29613).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAhmed RM, Irish M, Piguet O, Halliday GM, Ittner LM, Farooqi S, Hodges JR, Kiernan MC (2016) Amyotrophic lateral sclerosis and frontotemporal dementia: distinct and overlapping changes in eating behaviour and metabolism. 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Proc Natl Acad Sci USA 106(44):18809\u0026ndash;18814. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.0908767106\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0908767106\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anec","sideBox":"Learn more about [Acta Neuropathologica Communications](https://actaneurocomms.biomedcentral.com/)","snPcode":"40478","submissionUrl":"https://submission.springernature.com/new-submission/40478/3","title":"Acta Neuropathologica Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Amyotrophic lateral sclerosis (ALS), TAR DNA binding protein (TDP-43), white adipose tissue (WAT), sporadic ALS","lastPublishedDoi":"10.21203/rs.3.rs-6984477/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6984477/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWhite adipose tissue (WAT) has a crucial role in maintaining systemic energy homeostasis. Numerous biological pathway studies have highlighted the importance of adipokines in regulating metabolic pathways and contributing to metabolic dysfunction in animal models and patients with ALS. Despite these associations, the specific molecular mechanisms remain poorly understood. Moreover, the direct contribution of WAT to the energy metabolism abnormalities observed in ALS has yet to be clearly defined. The current study sought to identify perturbances in WAT, main source of leptin, during the clinical course of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice using histological, proteomic, and molecular biological techniques. We present the first evidence of a significant histological alteration in WAT prior to the symptomatic stage of the disease in TDP-43\u003csup\u003eA315T\u003c/sup\u003e mice, providing novel insights into pathological features earlier in the onset of symptoms, and showing WAT as a target organ for ALS. In human ALS cases, we found that circulating leptin levels at the time of diagnosis were lower in the plasma of men with ALS who were overweight or obese and had rapidly progressive ALS, emphasizing the importance of considering sex-specific approaches when analysing adipokines essential for body weight control.\u003c/p\u003e","manuscriptTitle":"White adipose tissue undergoes pathological dysfunction in the TDP-43 A315T mouse model of amyotrophic lateral sclerosis (ALS)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-14 05:13:24","doi":"10.21203/rs.3.rs-6984477/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-16T16:00:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-14T14:53:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-13T16:50:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60855445309473841583433437371918083668","date":"2025-07-06T08:11:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"136189639449256005204276751294776437205","date":"2025-07-06T08:07:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"148873009839688004337795115686813449197","date":"2025-07-06T05:47:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-06T05:22:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-04T01:46:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-04T01:45:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Acta Neuropathologica Communications","date":"2025-06-26T14:35:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"acta-neuropathologica-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"anec","sideBox":"Learn more about [Acta Neuropathologica Communications](https://actaneurocomms.biomedcentral.com/)","snPcode":"40478","submissionUrl":"https://submission.springernature.com/new-submission/40478/3","title":"Acta Neuropathologica Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84941481-2eac-45db-b6c6-3a0f592c1561","owner":[],"postedDate":"July 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-13T16:02:19+00:00","versionOfRecord":{"articleIdentity":"rs-6984477","link":"https://doi.org/10.1186/s40478-025-02130-9","journal":{"identity":"acta-neuropathologica-communications","isVorOnly":false,"title":"Acta Neuropathologica Communications"},"publishedOn":"2025-10-09 15:58:05","publishedOnDateReadable":"October 9th, 2025"},"versionCreatedAt":"2025-07-14 05:13:24","video":"","vorDoi":"10.1186/s40478-025-02130-9","vorDoiUrl":"https://doi.org/10.1186/s40478-025-02130-9","workflowStages":[]},"version":"v1","identity":"rs-6984477","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6984477","identity":"rs-6984477","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}