The administration of modified immune cells (MIC) before kidney transplantation led to specific immunosuppression against the allogeneic donor and a significant increase in regulatory B lymphocytes. We wondered how this approach affected the continued clinical course of these patients.Ten patients from a phase I clinical trial who had received MIC infusions prior to kidney transplantation were retrospectively compared to 15 matched standard-risk recipients. Follow-up was until year five after surgery.P = 0.046) and more opportunistic infections (log rank P = 0.033). Importantly, MIC patients, and in particular the four patients who had received the highest cell number 7 days before surgery and received low immunosuppression during follow-up, continued to show a lack of anti-donor T lymphocyte reactivity in vitro and high CD19+CD24hiCD38hi transitional and CD19+CD24hiCD27+ memory B lymphocytes until year five after surgery.The 10 MIC patients had an excellent clinical course with stable kidney graft function, no donor-specific human leukocyte antigen antibodies (DSA) or acute rejections, and no opportunistic infections. In comparison, a retrospectively matched control group receiving standard immunosuppressive therapy had a higher frequency of DSA . EudraCT Number: 2014-002086-30. The long-term survival of kidney grafts continues to be hampered by two reasons. First, conventional immunosuppressive therapy is still unable to prevent long-term kidney graft loss, and a significant proportion of patients lose their grafts due to chronic (antibody-mediated) rejection . Second,8 MIC per kg body weight 7 days prior to surgery showed donor-specific immunosuppression, as evidenced by a lack of cellular stimulatory reactivity after transplantation when tested against their respective donors in vitro. These patients also had higher numbers of IL-10-producing CD19+CD24hiCD38hi transitional B lymphocytes as well as of other regulatory B lymphocyte subsets at various stages of maturation which are thought to have regulatory properties. The T-cell response against the donor was increased after depletion of B lymphocytes in vitro, suggesting that regulatory B lymphocytes were pathophysiologically relevant to establish donor-specific unresponsiveness. These results were also supported by a gene expression signature consistent with the COMBINED-g7 consensus signature of operational tolerance in three of the four patients, suggesting that we actively induced an operationally tolerant phenotype by high-dose MIC treatment one week before surgery  together with reduced standard immunosuppressive therapy to prevent rejection in 10 living donor kidney transplant recipients , 15. Fou surgery , 15. In From Aug 2015 to Feb 2017, 14 patients and their respective donors were screened for inclusion in the TOL-1 study. Ten patients eventually received MIC intravenously on the day of donor leukapheresis as a single administration as described previously  and crossmatch techniques (ELISA and CDC), lymphocyte proliferation assay (mixed lymphocyte culture), determination of lymphocyte subsets in peripheral blood (flow cytometry), and determination of cytokine and chemokine levels in plasma  were performed as previously described , 15.de novo DSA-free survival and opportunistic infection-free survival were calculated according to the Kaplan-Meier method.In the text and tables, continuous data are summarized as the median and range and categorical data as absolute and relative frequencies. In figures, the results are presented as individual measurements (and the median) or the median and interquartile range. For comparison of MIC patients  with the control group, the two group Mann Whitney U test and the Chi-Square test were used as deemed appropriate. Statistical comparisons of different MIC groups were not performed due to low patient numbers. Graft survival, The TOL-1 study was reviewed and approved by the ethics committee of the University of Heidelberg, Heidelberg, Germany, and the Paul-Ehrlich Institute, Langen, Germany . The study was performed in compliance with the provisions of the Declaration of Helsinki and Good Clinical Practice guidelines. Written informed consent was obtained from participants before inclusion in the study. During follow-up, patient data and biomaterials were collected and analyzed retrospectively according to protocols approved by the ethics committee of the University of Heidelberg .This is the 5-year follow up of 10 patients who participated in a phase I clinical trial of donor-derived MIC therapy for individualized immunosuppression in living donor kidney transplant recipients , a median estimated glomerular filtration rate (eGFR) according to CKD-EPI of 48 mL/min/1.73 m2 (range 30–87 mL/min/1.73 m2), and a median urinary protein excretion of 18 g/moL creatinine (range 3–144 g/moL creatinine), all not significantly different from transplanted controls  transplanted controls on full immunosuppressive therapy developed de novo DSA during the 5-year follow up . Delayed graft function (P=1.0), rehospitalization (P=0.25), PTLD or malignancy (P=1.0), cardiovascular events (P=1.0), surgical complications (P=0.70), total antihypertensive therapeutic intensity score at year 5 (P=0.65), and new-onset diabetes after transplantation (P=0.52) did not differ significantly between MIC patients and transplanted controls . Otherwise, no opportunistic infections were detected in the MIC patients during rigorous screening. In comparison, 8 transplanted controls (53%) developed opportunistic infections during follow up including 4 episodes of opportunistic pneumonia and 6 episodes of CMV- or BKV-replication  or were excluded during screening (N = 2) were analyzed, virtually the same results were obtained  during follow-up with no obvious differences between groups or compared to baseline . In contrast to regulatory T lymphocytes, analysis of CD19+CD24hiCD38hi transitional B lymphocytes showed persistently high frequencies of this regulatory cell type in group C patients beyond year 5 with a median of 7%  activated CD8+DR+ T lymphocytes , no immunological analyses were available for transplanted controls.We have recently shown that a single pretransplant infusion of MIC led to long-lasting donor-specific unresponsiveness , 20, 21.10 nucleated donor blood cells 2 or 7 days before surgery. Due to the introduction of the donor antigen already 7 days before transplantation, one would normally expect a sensitizing effect. A graft-protective effect similar to the one observed in our study was also observed by Marti et al. when infusing unmodified mononuclear cells twice before living donor kidney transplantation, but at the expense of sensitizing 6 of 61 (10%) patients by administering cells bearing donor HLA on their surface before surgery  .The original contributions presented in the study are included in the article/The studies involving human participants were reviewed and approved by Ethics committee of the University of Heidelberg, Heidelberg, Germany. The patients/participants provided their written informed consent to participate in this study.MSa, CMo, CK, GO, CS, DC, MZ, MSm, PT, and AS designed the study. MSa, CMo, and MZ recruited participants. CK, LW, AH-K, MSm, and AS produced MIC under GMP conditions and performed quality controls of the products. MSa, CMo, FK, CSp, LB, CN, CMa, LS, and MSa collected the data. MSa, CMo, LW, CK, TT, SS, LP, NE, CSü, GP, AM, CSc, RW, PS, UM, VS, MK, SK, MF, MSt, IH, A-IK, BK, GB, CM-T, JR, MSm, PT, AS, and VD analyzed the data. MSa, CMo, GO, TT, CSü, MZ, MSm, PT, AS, and VD interpreted the data. MSa and CMo designed the figures. MSa, CMo, GO, and VD wrote the first draft of the manuscript, and all authors revised it critically and approved the final version. All authors contributed to the article and approved the submitted version.


Brain innate immune activation is associated with Alzheimer’s disease (AD), but degrees of activation may vary between disease stages. Thus, brain innate immune activation must be assessed in longitudinal clinical studies that include biomarker negative healthy controls and cases with established AD pathology. Here, we employ longitudinally sampled cerebrospinal fluid (CSF) core AD, immune activation and glial biomarkers to investigate early (predementia stage) innate immune activation levels and biomarker profiles.n = 535) and follow-up (n = 213), between 1 and 6 years from baseline (mean 2.8 years). We measured Aβ42/40 ratio, p-tau181, and total-tau to determine Ab (A+), tau-tangle pathology (T+), and neurodegeneration (N+), respectively. We classified individuals into these groups: A−/T−/N−, A+/T−/N−, A+/T+ or N+, or A−/T+ or N+. Using linear and mixed linear regression, we compared levels of CSF sTREM2, YKL-40, clusterin, fractalkine, MCP-1, IL-6, IL-1, IL-18, and IFN-γ both cross-sectionally and longitudinally between groups. A post hoc analysis was also performed to assess biomarker differences between cognitively healthy and impaired individuals in the A+/T+ or N+ group.We included non-demented cases from a longitudinal observational cohort study, with CSF samples available at baseline . No significant group differences were observed for the cytokines CSF MCP-1, IL-6, IL-10, IL18 or IFN-γ. Longitudinally, CSF YKL-40, fractalkine and IFN-γ were all significantly lower in stable A+/T−/N− cases . CSF sTREM2, YKL-40, clusterin, fractalkine (p < 0.001) and MCP-1 (p < 0.05) were all higher in T or N+, with or without amyloidosis at baseline, but remained stable over time. High CSF sTREM2 was associated with preserved cognitive function within the A+/T+ or N+ group, relative to the cognitively impaired with the same A/T/N biomarker profile (p < 0.01).Cross-sectionally, CSF sTREM2, YKL-40, clusterin and fractalkine were higher only in groups with tau pathology, independent of amyloidosis (Immune hypoactivation and reduced neuron–microglia communication are observed in isolated amyloidosis while activation and increased fractalkine accompanies tau pathology in predementia AD. Glial hypo- and hyperactivation through the predementia AD continuum suggests altered glial interaction with Ab and tau pathology, and may necessitate differential treatments, depending on the stage and patient-specific activation patterns.The online version contains supplementary material available at 10.1186/s12974-023-02973-w. Inflammatory activation has been proposed as a target for precision medicine therapy in Alzheimer’s disease (AD) and a detailed characterization of each pre-dementia stage is warranted . AD stagTREM2) is a partial loss-of-function mutation and has been associated with a fourfold increase in the risk for LOAD. Partial loss-of-function (R47H variant) of the microglial membrane-bound triggering receptor expressed on myeloid cells 2 (TREM2) increases the risk for LOAD by fourfold, whereas common genetic variants associated with higher soluble TREM2 (sTREM2) levels are associated with lower LOAD risk and delayed age of onset -Flutemetamol PET scans as the standard of truth. For a visualization of CSF Aβ42/40 ratio values within and between A/T/N-groups, please see our recent publication [n = 62), (b) cases with amyloid pathology and at least one pathological T or N marker , (c) cases with evidence of tau-mediated neuropathology, but not amyloid pathology  and (d) CN (recruited as controls or SCD) with normal CSF AD biomarkers . For the cross-sectional analyses, CSF immune marker availability varied between groups, but all sample sizes were adequate for statistical comparison (see Table n = 18), (b) stable A+/T+ or N+ (n = 89), (c) stable A−/T+ or N+ (n = 29) and (d) stable CN A−/T−/N− participants (n = 77). Here, most had immune markers available at all available timepoints within the groups. However, three sTREM2 measurements were missing in each of the pathological stable A/T/N groups and one stable A−/T+ or N+ case was missing a baseline measurement for YKL-40, fractalkine, MCP1, IL-6, IL-10, IL-18 and IFN-γ, but had repeated measures. A total of n = 213 had available CSF samples at least one follow-up assessment , n = 74 had two follow-ups  and n = 12 had three follow-ups . The overall mean follow-up time was 2.83 years (SD = 1.31), ranging between 0.75 to 8.5 years from baseline . Nominal variables sex, diagnostic group (CN and MCI), and APOE-ε4 genotype were assessed with Chi-square tests. For ANOVA and ANCOVA, post-hoc comparisons with Bonferroni–Holm adjustments were applied for each model (6 tests per model). Effect sizes for ANOVA (eta-squared) and ANCOVA  are reported. Linear mixed models (LMMs) were used to assess longitudinal changes in CSF immune markers with the stable CN A−/T−/N− group as the reference, and all models were fitted with a random slope for time. Annual change over time for each group was also computed using the emmeans R package [All analyses were performed in Rstudio (R version 4.2.2) . Cross-s package . For eace α < 0.0. Nominal package –49.TableAPOE-ε4 genotypes than the CN A−/T−/N− group (33.33%), whereas the A−/T+ or N+ (38.61%) had similar frequencies as the CN A−/T−/N− group. While we saw a generally higher percentage of females in the A+/T−/N− group (66.13%) than the other groups (between 51.02% and 54.91%), these differences were not statistically significant. Please see Table The CN A−/T−/N− participants were younger than the pathological A/T/N cases (between 5 and 8 years on average). The A+/T−N− (68.75%) and A+/T+ or N+ (74.35%) groups had higher frequencies of r N+ 38.6% had simAPOE-ε4 genotype in the cross-sectional models, but only with IL-10 in the longitudinal models. Increasing age was significantly associated with higher CSF immune markers levels in both cross-sectional and longitudinal models, with the noted exceptions for IL-6, IL-10 and IFN-γ. Lower levels of MCP-1, IL-6, IL-18 and clusterin were found for females in the cross-sectional models, whereas in the longitudinal models, females had lower levels for MCP-1, IL-6 and IL-18, but not clusterin. Moreover, IFN-γ concentrations were higher for females in the longitudinal models. For a complete account of covariate associations to pertinent CSF immune markers, please see Additional file There were weak, albeit significant associations between lower clusterin, fractalkine, IL-6 and IL-10 and p < 0.001). No significant differences in sTREM2, YKL-40, clusterin or fractalkine levels were found between A−/T−/N− and A+/T−/N−. While no differences in concentrations between A+/T+ or N+ and A−/T+ or N+ were demonstrated for sTREM2, YKL-40, clusterin concentrations were higher in A−/T+ or N+ cases as compared to A+/T+ or N+ (p < 0.05). Following post-hoc adjustments, no significant between-group differences were found for the other CSF immune markers . See Table We found that the cross-sectional concentrations of both sTREM2, YKL-40, fractalkine and clusterin were higher in the A+/T+ or N+ and A−/T+ or N+ groups as compared to A−/T−/N− . Stable A+/T−/N− cases had lower baseline CSF YKL-40 (p < 0.05), fractalkine (p < 0.05) and IFN-γ (p < 0.05) concentrations than stable CN A−/T−/N−. The concentrations of these biomarkers remained stable over time. Moreover, while CSF IL-18 concentrations remained low over time in this group (unadjusted p < 0.01), this result was only at trend level following post-hoc adjustment for multiple testing (p = 0.064). While we observed an increase of clusterin concentrations over time (p < 0.01) in A+/T−/N− cases, this increase was not significantly different as compared to the stable CN A−/T−/N− cases. Both stable A+/T+ or N+ and A−/T+ or N+ had higher concentrations of sTREM2 , YKL-40 , clusterin , fractalkine  and MCP-1  that all remained stable over time, see Table Biomarkers in clinically stable A-/T-/N-cases remained stable over time except for fractalkine that increased at follow-up (p < 0.01). No significant between-group differences, or changes over time were found for the other markers  of the stable A+/T−/N− cases progressed to MCI, while n = 1 (5.55%) progressed to dementia. Within the stable A+/T+ or N+ group, n = 7 (7.86%) progressed to MCI, while n = 20 (22.47%) progressed to dementia. For the stable A−/T+ or N+ group, n = 4 (13.79%) progressed to MCI, while n = 1 (3.45%) progressed to dementia , sTREM2, YKL-40, clusterin, and fractalkine were all significantly higher at baseline, regardless of amyloidosis (A− or A+). Within the A+/T+ or N+ group, we observed significantly higher levels of CSF sTREM2 in cognitively normal cases as compared to MCI. All the analyzed biomarkers remained stable over time, with the exception of clusterin which increased from baseline to follow-up in stable A+/T−/N−, and CSF fractalkine, which increased over time in all A/T/N groups  attenuates neuroinflammation and protects against neurodegeneration [sTREM2 supports microglial Aβ phagocytosis, and increased CSF levels are associated with increased microglial activation in cross-sectional studies . In tranneration . HoweverFor interleukins  with pro- or anti-inflammatory properties, we neither found group-differences across A/T/N stages at baseline nor longitudinally, although a trend towards lower CSF IL-18 levels in isolated amyloidosis was observed which did not withstand correction for multiple comparisons. Though cases with tau pathology have significantly increased levels of glial activation markers, we do not see increased IL-18 levels, nor changes in the other inflammation linked cytokines (IL-10 and -6). Though this may be due to a limited set of markers, IL-18 is a key inflammasome activation marker, and we would expect to detect markedly increased inflammation . TreatmeAPOE-ε4 genotype, age and sex as covariates in our statistical models. Of particular interest, females had lower levels of MCP-1, IL-6, IL-18 and clusterin than males in cross-sectional models, and all but clusterin in longitudinal models for cases which remained A/T/N stable over time. Moreover, IFN-γ concentrations were higher for females in the longitudinal models. However, because sex was only included as a covariate, we cannot tell whether these sex-differences might be differentially altered in the AD-continuum, or how differences could influence disease progression. Indeed, differential innate immune activation related to sex could influence disease–phenotype and progression in LOAD [Finally, we included  in LOAD , 76, 77,This study has some limitations. First, dementia is the endpoint of the DDI longitudinal cohort study, and we do not have follow-up CSF data for cases after the onset of dementia. In contrast to most other AD cohorts, our cohort consists of relatively young, well-functioning individuals without dementia. Thus, evidence of further glia activation and inflammation at later stages of the AD clinical continuum cannot be ruled out. There is considerable heterogeneity in reported CSF alterations of immune activation  analyses, and longitudinal at baseline (B) and latest A/T/N measurement (C).Additional file 3: Figure S2. Shows all clinical change or stability within pathological A/T/N groups during the follow-up time.


Peroxidase (PO) is effective at mitigating or eliminating mycotoxins in fish feeds. However, the literature does not describe how the free radicals produced during oxidation by PO can interact with other nutrients and active compounds present in such feeds, affecting their bioavailability and modifying both the metabolism of the species and the quality of the final product. The objective of this study was to evaluate the impact of using PO as a treatment against mycotoxins on the nutritional quality of the fatty acids and polyphenols present in a fish feed. The results demonstrate that applying PO may have unwanted side effects on long-chain polyunsaturated fatty acids and the digestive bioaccessibility of polyphenols.1 in fish feeds. However, its potential negative interactions with the macro and micro components of feeds have not been evaluated. The aim of this study was to evaluate the impact of PO’s addition to a feed on compounds like fatty acids and polyphenols using an in vitro simulation of the digestive tract of the tilapia. The influence on fatty acids was determined by changes in the peroxide index, with the feed including PO presenting values four times higher than those of the control feed. On the other hand, the in vitro digestive simulation also evidenced an effect of PO on the bioaccessibility of polyphenols significantly influenced by the total digestion time and temperature. The bioaccessibility of polyphenol ranged from 2.09 to 16.23 μmol of the total Trolox equivalent antioxidant capacity for the combinations evaluated in the study. The greatest bioaccessibility was observed at the central point under the following conditions of digestive hydrolysis: pH of 7, 30 °C, 4.5 h of digestive hydrolysis and an absence of PO.Peroxidase (PO) has been applied in different areas of industrial biotechnology, including the control of contaminants like aflatoxin B Fish farming has shown remarkable development, representing 17% of all animal protein produced worldwide  and also2O2) [Peroxidase (PO) comprises a group of nonspecific and specific enzymes  . PO can 2O2) ,17. This2O2) ,19,20. D2O2) , develop2O2) , bleachi2O2) ,24,25,26Among enzymes, commercial peroxidase (PO) has shown that it is effective at mitigating mycotoxins in different feed matrices ,28. OtheAmong the components present in fish diets that can be negatively affected by PO oxidation, there are some important molecules, such as long chain polyunsaturated fatty acids (LC-PUFA) and polyphenols ,32,33,34Polyphenols are secondary metabolites of plants and are generally involved in defense against ultraviolet radiation or aggression. Increasing attention is currently being paid to the protective roles of polyphenols obtained from different sources in health and oxidative status in fish, since in addition to influencing the immune system, they present antioxidant, anti-inflammatory, immunomodulatory and hepatoprotective effects ,40,41,42Therefore, on one hand, the inclusion of PO in fish feeds may be beneficial for minimizing the negative effects of aflatoxins, and on the other, due to its high reactivity, it may negatively interact with the nutritional quality of the lipid fraction as well as polyphenols included in such feeds, thus reducing their beneficial effects. Nevertheless, since it may be difficult to assess such effects in vivo, alternative approaches can be used to obtain a preliminary estimation of the nature and extension of such interactions. In this sense, in vitro methodologies simulating the physiological conditions present in the digestive tract of fish, that have been widely applied to evaluate bioaccessibility of nutrients present in fish feeds  can be hOreochromis niloticus), with the selection of this species justified by its relevance in freshwater aquaculture worldwide as well as the great use of plant ingredients susceptible to mycotoxin contamination in its feeds.Considering the above-described points, the objective of this study was to evaluate the impact of using PO as a treatment against mycotoxins on the stability and potential bioavailability of fatty acids and polyphenols present in a fish feed. This study was based on the use of an in vitro model simulating the digestive tract of tilapia (The present study was developed through two different experiments aimed to (1) evaluate the potential oxidative effect of PO on the lipid fraction of a feed and (2) evaluate how the interactions of PO with the polyphenols included in a feed may affect their digestive bioaccessibility under different digestion conditions.Soybean meal used for PO extraction was provided by a company specialized in soybean processing located in the municipality of Rio Grande . Grape pomace was provided by the Bodega artisanal located in the municipality of Fondón . Sodium phosphate mono and dibasic were purchased from PanReac AppliChem  and Merck , respectively. Guaiacol and hydrogen peroxide were purchased from Sigma . Tannic acid, 2,2-diphenyl-1-picrylhydrazyl (DPPH), (±)-6-Hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic (Trolox) and carboxymethylcellulose (CMC) were purchased from Sigma . Butylhydroxytoluene (BHT) was obtained from Merck . Potassium chloride was obtained from PanReac AppliChem . Chloroform was purchased from Fisher Scientific . Methanol and potato starch were purchased from PanReac AppliChem . Sodium sulfate and bovine albumin were purchased from Sigma .g, 10 min, 4 °C) was filtered for evaluation of the enzymatic activity and protein content. The enzymatic activity was verified in a spectrophotometer at 470 nm through the oxidation of guaiacol substrate to tetraguaiacol. A unit (U) of PO activity was defined as the amount of enzyme that catalyzed the oxidation of 1 μmol of guaiacol per minute under the test conditions. The specific activity of the PO was determined in relation to the amount of soluble protein (mg mL−1) determined by the method of Lowry [The soybean meal PO extraction conditions were established according to the method described by Feltrin et al. , using p1 . For all formulations, solid ingredients were mixed from the lowest to the highest ratio. Then, liquid ingredients were added. The ingredients were manually homogenized to form a uniform mass, followed by incubation for 2 h at 32 °C. The masses resulting from all treatments were pelleted by a bench grinder. The pellets were dried in an oven at 60 °C for 8 h, packaged, identified and kept at −4 °C until used for the experiments.A model simplified diet was designed to carry on the experiments, being prepared with a few pure ingredients to avoid possible interference in the colorimetric measurements required for the assays. Four different formulations were prepared including or not including PO as well as BHT, an antioxidant compound routinely used in aquafeeds to assess the ability of this compound to counteract the oxidative effect produced by PO. The amount of BHT used was in accordance with that recommended by Lundebye et al. . The comFor the diets containing BHT, this was previously diluted in the oil fraction and then mixed with the rest of the ingredients. Once prepared and dried, samples (5 g) of the different diets were used to extract the lipid fraction and to measure the degree of oxidation.−1). The determination of the peroxide index followed the methodology established by Instituto Adolfo Lutz [−1) and homogenized until dissolution. Then, 125 μL of saturated potassium iodide solution was added, and the reaction was kept in the dark for 1 min. Then, 250 μL of starch solution (1%) was added and titrated with sodium thiosulphate (0.1 or 0.01 N).The feeds were subjected to extraction of the lipid fraction through the method of Folch et al.  using a lfo Lutz  with somThis experiment was developed in two parts: (1) A preliminary quantitative evaluation of the negative interaction of PO with the antioxidant capacity of the polyphenols present in a natural source (grape pomace) and (2) an evaluation of different factors that may significantly affect the digestive bioavailability of polyphenols after preincubation of PO together with a model polyphenol (tannic acid) within a feed matrix.g for 15 min to obtain the supernatant containing the bioactive compounds. The Trolox equivalent antioxidant capacity (TEAC) was determined by following the DPPH and ABTS method described by Brand-Williams et al. [Grape pomace (GP) was used as a natural source of polyphenols. The GP was dried in an oven for 72 h at 60 °C and subsequently finely grounded in a knife mill  until obtaining a particle size ≤0.5 mm. Characterization of the phenolic compounds was carried out according to Veskoukis et al.  with mods et al.  and Re es et al. , respect−1), with different amounts of a solution providing changing activities of PO: 0.01; 0.035; 0.06; 0.085 and 0.1 U mL−1. The assays were carried out using 2 mL Eppendorf tubes containing glass spheres to increase the interaction between the molecules. After adding the enzyme, both solutions were incubated at 32 °C for 2 h with rotary stirring (150 rpm) . At the end of the process, the antioxidant capacity of each test was determined according to This trial was carried out to evaluate the inhibitory effect of soybean meal PO on the TEAC present in GP extract. For this, a dose/response assay was designed by incubating a fixed amount of GP providing 171.7 μmol of TEAC (mLThe feed matrix used to develop the different in vitro digestion assays was prepared using the same ingredients and conditions described in O. niloticus). The fish  were kept in 500 L circular tanks with a skimmer, aeration supplementation, temperature control (19–22 °C) and photoperiod set at 12:12 h (light:dark) for 2 weeks. The pH and dissolved oxygen levels ranged from 6.5 to 7.0 and from 6.0 to 7.3 mg L−1, respectively. The animals were fed twice a day (8:00 a.m. and 5 p.m.) until apparent satiation with commercial feed containing 35% crude protein. At the end of a 2 week period, the fish were sacrificed 4 h after receiving a meal by immersion in a buffered solution of benzocaine hydrochloride (500 ppm) and dissected to obtain the digestive tract. Tissues were mechanically homogenized with distilled water , followed by centrifugation at 3220× g for 20 min at 4 °C, with the supernatant filtered and concentrated using a dialysis system with 10 kDa MWCO  coupled to a peristaltic pump . Concentrated extract was then lyophilized and stored at −20 °C until being used in the assays. The total activity of alkaline proteases in the lyophilized extract (U g−1 of fish) was measured using casein as a substrate according to the method described by Kunitz [The enzymatic extract used in the tests was obtained from adult specimens of tilapia . In the upper part, water, feed, enzyme extract and phosphate buffer were added and maintained under continuous agitation with the aid of a magnetic stirrer (300 rpm). The hydrolysis products were permeated through the membrane into the lower chamber containing a phosphate buffer and recovered for determination of the TEAC and ABTS according to −1), as well the average consumption of feed by a fish of such a size if received in a single meal (1% of body mass) containing 45% crude protein.In vitro assays involving the stomach and intestinal stages were carried out using membrane bioreactors . The devEvaluation of different factors that can significantly affect the digestive bioavailability of polyphenols after preincubation of PO, and a model polyphenol (tannic acid) within a food matrix described in This study considered two fixed factors (stomach pH and residence time) and four variable factors  . This rep ≤ 0.05. Both the PB factorial design and analysis of results were carried out with Minitab® 16 software .The assumptions of homoscedasticity and normality were tested for the results obtained. Statistical analysis of the effect of PO on lipid oxidation (n = 3) was carried out by one-way ANOVA followed by Tukey’s test at p ≤ 0.05) peroxide index (The oxidative effect of PO on the lipid fraction of the feed was evidenced by a significantly higher (de index . Neverth−1), determined by DPPH and ABTS, are shown in −1.The results of the preliminary assays of inhibition by PO of the bioactive compounds initially present in GP  could not be explained by the selected independent variables (X1–X4). Temperature (X2) had the most significant negative effect on polyphenol bioaccessibility . The other variables showed a positive effect, but pH (X1) did not show statistical significance in the bioaccessibility of polyphenol (p > 0.05). A negative value for the temperature (X2) means that the change from a level of −1 (25 °C) to +1 (35 °C) reduced the bioaccessibility of polyphenol, whereas the positive effect observed in the digestion time (X3) means that the change in the variable from a level of −1 (3 h) to +1 (6 h) increased bioaccessibility. Furthermore, the higher the t value and the lower the p value, the more significant the regression coefficient and influence on the process. Therefore, the presence (+1) or absence (−1) of PO (X4) had a direct impact on the bioaccessibility of the polyphenol present in the diet.The results of the ANOVA with the regression coefficient (RC), standard error (SE) and The results of Experiment 1 demonstrate that the presence of PO determined a significant peroxidation of the lipids included in the feed  and also1 in fish, its use is related to inhibition of the negative effects of this mycotoxin, such as bioavailability and inhibition of hepatocarcinogenesis in birds [1 metabolism, part of its protective effect may be related to its ability to inhibit hepatic epoxidation of AFB1 mediated by cytochrome P450 to exo-AFB1-8,9-epoxide [1 to cultivated species.Also, it must be noted that although there are no studies on using BHT as a protective agent against AFBin birds  and rodein birds , respect-epoxide . Further-epoxide . TherefoThe results in Experiment 2 demonstrate that preliminary treatment of feed ingredients with PO may negatively affect the antioxidant capacity of polyphenols, irrespective of if they were already present in such ingredients or specifically added as functional additives. In fact, due to their high reactivity with phenolics, peroxidases are used to remove these compounds in depuration of waste waters, since such enzyme treatment offers a high degree of specificity, operation under mild conditions and a high reaction velocity . Also, iIn the present study, the negative interaction between PO and the phenolic compounds present in grape pomace was evidenced by a significant reduction in the TEAC . This caSparus aurata) and herbivorous ). They demonstrated that a longer digestion time increased the bioavailability of different types of polyphenols and also that such a positive effect cannot be generalized to all the compounds present in wine bagasse. It follows that, in spite of the positive effect of a longer digestion time observed in the present study when using one type of polyphenol (tannic acid), a proper evaluation of the net effect of the digestion time on the potential bioavailability of a given polyphenol after interaction with PO should require specific assays. On the other hand, it can be deduced that rapid intestinal transit rates can significantly affect the bioaccessibility of bioactive compounds. Herbivorous fish typically have longer intestines but higher gastrointestinal transit rates than carnivorous or omnivorous species [On the other hand, the results obtained with the in vitro assays evidenced that the potential digestive bioavailability of dietary polyphenols may be significantly reduced if PO is used as an additive and also that the total length of the digestion process may positively influence such bioavailability, while a higher water temperature decreases it. The positive effect of a longer digestion time can be easily understood, since it correlates directly to a higher exposition of the feed matrix to the action of the digestive enzymes and hence to an increased opportunity for polyphenols to be released, even if a fraction of them has been irreversibly inactivated after their initial interaction with PO. In a recent study by Martínez-Antequera et al. , they de species . Althoug species . This maThe negative effect of an increasing temperature on the potential bioavailability of the polyphenol obtained in the model was more surprising. In the live fish, a higher temperature should have resulted in a general activation of metabolism, including increased activity of the digestive enzymes, which should have improved the release of tannic acid from the feed matrix. In contrast, the observed reduction in the total TEAC could be explained by considering that the formation of complexes between the highly reactive tannic acid and other components of the feed (protein and carbohydrates) could be enhanced at a higher temperature ,74,75. APractical application of PO as pretreatment to eliminate aflatoxins of plant ingredients used in fish feeds may present undesirable side effects in some highly reactive dietary compounds like LC-PUFA or polyphenols. The negative effects on the former can be avoided by using sequential processing, with the initial treatment of plant ingredients with PO followed by addition of the lipid fraction including BHT as a protective agent. Negative interactions with polyphenols taking place during feed preparation has an impact on further digestive bioavailability of such compounds, with the latter negatively affected by short gut transit times and high water temperatures, conditions that may be frequent in fish species reared in warm regions . These results must be considered in the optimization of the treatment with PO as well as knowing the doses of polyphenol sources provided with the feed.


P = 0.14). The multivariable regression model using cerebrospinal fluid neurofilament light chain and other basic clinical data achieved an area under the curve of 0.90 . In conclusion, neurofilament light chain classified causes of alteration of consciousness with moderate accuracy. Nevertheless, including other basic clinical data to construct a model improved the performance to a level that was comparable to clinical neurologists.Neurofilament light chain has become a promising biomarker for neuroaxonal injury; however, its diagnostic utility is limited to chronic disorders or specific contexts. Alteration of consciousness is a common clinical problem with diverse aetiologies, many of which require timely diagnoses. We evaluated the value of neurofilament light chain alone, as well as creating diagnostic models, in distinguishing causes of alteration of consciousness. Patients presenting with alteration of consciousness were enrolled. Initial clinical data of each participant were evaluated by a neurologist to give a provisional diagnosis. Each participant subsequently received advanced investigations and follow-up to conclude the final diagnosis. All diagnoses were classified into a structural or non-structural cause of alteration of consciousness. Plasma and cerebrospinal fluid levels of neurofilament light chain were measured. Cerebrospinal fluid neurofilament light chain and other clinical parameters were used to develop logistic regression models. The performance of cerebrospinal fluid neurofilament light chain, the neurologist’s provisional diagnosis, and the model to predict the final diagnosis were compared. For the results, among 71 participants enrolled, 67.6% and 32.4% of their final diagnoses were classified as structural and non-structural, respectively. Cerebrospinal fluid neurofilament light chain demonstrated an area under the curve of 0.75  which was not significantly different from a neurologist’s provisional diagnosis 0.85   is a valuable biomarker for neuroaxonal injury. Ongphichetmetha   Consequently, neurofilament may represent a biomarker for neuroaxonal injury.6 Because of technical reasons, reliable assessment of neurofilament has long been limited to measurements in the CSF and is applicable just for patients who undergo lumbar puncture.7 Recently, a single-molecule array (Simoa) has been developed as an ultrasensitive assay that allows quantification of neurofilament in blood with high sensitivity.8Neurofilament is a class of scaffolding proteins of the neuronal cytoskeleton which provides structural stability to neurons and enables radial growth of axons.9-15 For acute CNS disorders, e.g. stroke, encephalitides and traumatic brain injury, studies focused on severity prediction and long-term prognostication,16-19 although few diagnostic studies had been done in the most highly selected participants.20 In traditionally non-structural disorders, neurofilament can be elevated, but in only a few does it reach levels comparable to structural disorders.21 For instance, while blood neurofilament is elevated in primary psychiatric disorders (PPD) such as depression and schizophrenia,22 it can discriminate frontotemporal lobar degeneration from PPD with high accuracy.23 Physiological disturbances insufficient to cause neuronal injury do not seem to affect the neurofilament level. In the youngest patients with presumably the least underlying neuropathology, seizures are not associated with the elevation of this biomarker.24 How neurofilament might be implemented to clinical application in aetiology identification has been proposed;25 nonetheless, there has been no study directly evaluating the clinical use of neurofilament in patients presenting with AOC.Studies generally found that neurofilament level is elevated in structural CNS disorders. Most of them were done on chronic neurological disorders such as multiple sclerosis, neurodegenerative dementias, amyotrophic lateral sclerosis, atypical Parkinsonism and peripheral neuropathies.In the present study, we explore the value of the neurofilament light chain (NFL), which is one of the neurofilament subunits in the CSF and plasma, as a diagnostic biomarker in the aetiology differentiation of AOC. Our hypothesis is that NFL levels will be higher in patients suffering from structural causes of AOC. We expect it to be a diagnostic test with a higher performance than the conventional method, which is the combination of history taking, physical examination, initial laboratory investigation and initial brain imaging. We designed a diagnostic study that aims to use NFL to classify patients presenting with AOC into structural or non-structural causes.A prospective study at King Chulalongkorn Memorial Hospital was conducted between December 2020 and December 2021. The inclusion criteria were patients aged over 15 years who presented with AOC or developed AOC during admission, and their primary physicians decided to perform a lumbar puncture. Here, AOC is defined as either decreased level or content of consciousness. Decreased level of consciousness can range from drowsy to comatose or Glasgow coma scale <15, whereas impaired content of consciousness refers to any domain including, but not limited to, orientation, attention, speech, perception and thinking. The exclusion criteria were a history of CNS disorders within 1 year or an established neurodegenerative disease. The patients who met the eligibility criteria were consecutively enrolled in the study. History taking, complete neurological examination as well as general physical examination were done in all participants at enrolment (i.e. CSF collection). Basic investigations, such as blood chemistry and neuroimaging, were performed, as well as routine CSF analysis.26 for distinguishing boxers from controls, and the prevalence of structural aetiology, which was reported to be 42%.1 The power calculation was conducted using the presize package in R. Based on the power calculation, it was determined that a total of 71 participants would need to be enrolled in this study to achieve sufficient statistical power. This study followed the Standards for Reporting of Diagnostic Accuracy (STARD) reporting guideline.27 The protocol of this study was not preregistered in a publicly accessible source. However, the complete study protocol is available upon reasonable request from the ethics committee.A power calculation to determine the appropriate sample size for the study was performed. The calculation was based on the area under the receiver operating characteristics curve (AUC) of 0.96,The institutional review boards of Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand, approved the collection and the use of human subjects for this study (Med Chula IRB no. 930/63). All the methods in this study were performed in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants or, if incapable, from their proxy, prior to the inclusion in the study.28 The CSF NFL levels were measured with enzyme-linked immunosorbent assay (ELISA)  according to the manufacturer’s recommendations. NFL levels in plasma were measured using the Simoa platform . All samples were analysed in duplicates (CSF) or triplicates (plasma) using the same batch of reagents by two certificated laboratory technicians who were blinded to clinical information.Ten millilitres of CSF were collected into polypropylene tubes , whereas blood samples were collected by venipuncture into ethylenediaminetetraacetic acid tubes . All samples were centrifuged (10 min at 25°C 2000 × g), separated, divided into aliquots and stored at −80°C within 1 h of the collection according to consensus protocol pending for biochemical analysis.provisional diagnosis. We mark this time point for determining the diagnosis to make a comparison with CSF NFL relevant.All clinical, routine laboratory and initial neuroimaging  information available prior to lumbar puncture plus routine CSF analysis were assessed by the attending neurology consultant to give a final diagnosis for each participant. All diagnoses were finalized prior to the quantification of the NFL (i.e. blinded).Most participants received further investigations, such as CSF detection of microbial nucleic acids using polymerase chain reaction (PCR), autoantibodies, brain MRI, EEG or tissue diagnosis, which were decided by the neurology consultant ] for continuous variables and number (percentage) for categorical variables, respectively. The final diagnosis, categorized as structural or non-structural, served as the primary outcome. Shapiro–Wilk test was used to assess the normality of data. Acknowledging that the NFL level depends on multiple other factors (such as age or time from onset to measurement), we also tried to predict the final diagnosis category using logistic regression models.n = 35 for training, n = 36 for validation). The 2-fold cross-validation process was repeated 10 times to estimate the variability of performance scores.For practicality, independent variables included were diagnostic parameters that are available in most clinical settings. They included age, body mass index (BMI), number of days after onset, Glasgow coma scale score (GCS), presence of abnormal neurological examination (yes/no), CSF abnormality , open pressure, CSF leukocyte count, CSF erythrocyte count, CSF protein, CSF glucose, plasma glucose and CSF NFL. Continuous numerical features were log-transformed, which is generally recommended in intensity and gene and protein expression data. Features with missing values were imputed with the average values. Finally, the values of each feature were standardized to make their mean zero and their standard deviation one. As the data set size is small, 2-fold cross-validation was used to tune the logistic model and to evaluate the performance to ensure that the validation set was large enough  and ridge (L2) regularization was used to construct the predictive model. The regularization strength varied from 10P-value of <0.05. Analysis was performed using Stata 17  and Python programming language version 3.8.Comparisons of the AUC between CSF NFL alone, the conventional method  and the regression model (NFL plus a few other variables) were performed using DeLong statistics. Statistical significance was defined as a two-sided Seventy-one participants were included in our study. The median age was 57 years (range: 15–93 years), and 37 participants were female (52.1%). There was no significant difference in age, BMI and initial GCS between the definite structural group and the definite non-structural group. The number of days from symptoms onset to enrolment of the structural group and the proportion of abnormal neurological examination, CSF profile and initial neuroimaging were significantly different between the diagnostic groups .n = 8), acute ischaemic stroke (n = 5), autoimmune encephalitis (n = 4), viral encephalitis (n = 4), unspecified neurodegenerative dementia (n = 4), cryptococcal meningitis (n = 3), brain metastasis (n = 3), post-infectious encephalitis (n = 2), CNS lymphoma (n = 2), Creutzfeldt–Jakob disease (n = 2), cerebral amyloid angiopathy (n = 2), bacterial meningitis (n = 1), tuberculous meningitis (n = 1), mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes (n = 1), pachymeningitis secondary to systemic autoimmune disease (n = 1), CNS vasculitis (n = 1), aseptic meningitis (n = 1), non-tuberculous mycobacterial encephalitis (n = 1), posterior reversible encephalopathy syndrome with intracerebral haemorrhage (n = 1) and germinoma (n = 1).Forty-eight participants (67.6%) received the diagnoses that are classified into the structural group. The diagnoses were septic encephalopathy (n = 8), psychiatric disorders (n = 7), metabolic encephalopathy (n = 5), drug intoxication (n = 2) and Wernicke encephalopathy (n = 1). Details on the results of the investigations of each participant were included in Twenty-three participants were ultimately classified into the non-structural group. The diagnoses were seizures (P = 0.001) (P = 0.14). Plasma NFL was available in 62 participants, where it demonstrated only a moderate correlation with CSF NFL  and a relatively low AUC of 0.60 (95% CI 0.43–0.76). Therefore, we did not use plasma NFL in any further analysis.CSF NFL concentrations were significantly higher in the structural group  . CSF NFL= 0.001) . The opt= 0.001) . In cont= 0.001) . There wAmong 37 participants (52.1%) who were younger than 60 years old, 25 and 12 participants were classified into the structural group and non-structural group, respectively; CSF NFL showed a larger AUC . In comparison, the conventional method resulted in a sensitivity of 92% and specificity of 100% which can be transformed into an AUC of 0.915.P = 0.39). CSF NFL has the highest impact on the model , followed by the number of days after onset, CSF protein and CSF abnormality, respectively  . The equectively .NFL has emerged as a robust biomarker for neuroaxonal injury. However, its level only alters days after the onset of such an injury. Therefore, its diagnostic use is better established in diseases with chronic ongoing neuroaxonal loss, in which the rate of its release reaches a steady state. Moreover, its level in healthy people varies greatly and increases with age, vascular comorbidities and undiagnosed neurodegenerative pathology. It is difficult to determine a baseline level in an individual patient, particularly in an elderly individual. Using NFL as a diagnostic biomarker in non-chronic illnesses is therefore complicated.4 To illustrate this point, consider a young female presenting with acute psychosis. If the underlying cause is determined to be autoimmune encephalitis, treatment would involve intravenous corticosteroids. However, if the primary diagnosis is a PPD, treatment may primarily consist of antipsychotic drugs, as the use of corticosteroids can exacerbate the symptoms.30In this study of prospectively enrolled patients with AOC, we aimed to use NFL as a diagnostic biomarker for differential diagnosis. As is well-known, AOC often arises from widespread neuronal dysfunction. In cases where the underlying cause of this dysfunction is a structural brain disease, a high degree of neuroaxonal injury is typically anticipated. The rationale for classifying the diagnoses into two groups  is that it confers immediate application and affects further management. AOC resulting from structural causes typically necessitates immediate investigation to establish a definitive diagnosis, determine appropriate empirical treatment and potentially consider surgical interventions. Conversely, the diagnostic process for AOC stemming from non-structural causes is often more protracted and comprehensive.31 To demonstrate how this model can be implemented in aiding the differential diagnosis of AOC, we created an online tool at https://trceid.org/diagNFL, in which NFL-based individual probability of structural aetiology of AOC can be calculated.While CSF NFL alone predicts structural diagnoses relatively well for participants under 60 years of age, its performance with all participants is only moderate. This finding is not unexpected, considering the well-known variability of CSF NFL levels in older adults, especially in the presence of cerebrovascular burden. However, we tried to overcome these difficulties with a data-driven approach using additional clinical information readily available in most settings. Our model was able to distinguish structural CNS disorders with a high accuracy similar to, if not better than, medical school neurology consultants. Apart from NFL, the model heavily depends on routine CSF indices. This is probably because diseases primarily involving the meninges may affect consciousness without causing much neuroaxonal injury, and therefore, the model relies on CSF abnormality as a biomarker for such diagnoses. The fact that CSF NFL had the highest impact on the model despite being the only parameter that was truly blinded (i.e. no risk of incorporation bias) demonstrated that the success of this model was not due to the statistical handling of routine clinical data alone. Once NFL becomes widely available, like cardiac troponins, our model will provide a useful tool not only for resource-limited settings where a neurologist is not available but also possibly for tertiary care settings where neurologists can benefit from this complex biomarker. Indeed, point-of-care testing for a related biomarker, the astrocytic intermediate filament glial fibrillary acidic protein, has been developed and can deliver results within 15 min.25 It is interesting to see how following the guidance would improve the performance of the NFL in this study.There are some limitations to our study. Firstly, we used a relatively small sample size for a prediction model and still lacked external validation. This is mainly because our primary outcome was to test CSF NFL alone as a diagnostic marker, and our sample size was calculated for such. Consequently, until successful verification in an independent cohort, the implications of our initial findings probably do not immediately translate to clinical practice. Instead, the impressive accuracy of our model suggests that it holds considerable potential for exploring novel approaches to utilizing this biomarker. Moreover, as the molecular underpinning of NFL release is more extensively elucidated, it opens the possibility of incorporating other explanatory variables into our model, potentially leading to further improvements in diagnostic performance. The second limitation is that the reference diagnosis in this study is the practical final diagnosis which, for some participants, is not the criteria-based definite diagnosis. While we acknowledge that this affects the credibility of our study, we realized that most real-world neurological diagnoses are not criteria-based. Limiting our study analysis to those with definite diagnoses would substantially deteriorate the applicability of our study. On the other hand, we are certain that we had provided sufficient diagnostic tests and follow-up to declare our final diagnosis. In our consecutively enrolled participants, the duration of AOC prior to lumbar puncture differed significantly between the two diagnostic groups. While we believe that this represented a real-life clinical practice, this discrepancy can influence NFL levels. Because NFL is a dynamic biomarker which levels tend not to peak until the second week, our findings may have been affected. Consequently, caution should be exercised when interpreting NFL levels in acute settings, taking into account the potential impact of the time elapsed between symptom onset and CSF collection. Finally, our study started prior to the publication of the guidance on the general implementation of NFL to symptoms of unknown aetiology, which recommended serial measurement for patients without a baseline level.In conclusion, CSF NFL can distinguish structural aetiology from non-structural causes of AOC with moderate accuracy. Nevertheless, adding other clinical data to construct a data-driven model improved the performance to a level that matches clinical neurologists. CSF NFL is a useful biomarker for differential diagnosis of AOC that can be implemented in primary care and resource-limited settings.Brain Communications online.fcad278_Supplementary_DataClick here for additional data file.


We identified over 50 CSF proteins dysregulated in DLB, enriched in myelination processes among others. The dopamine biosynthesis enzyme DDC was the strongest dysregulated protein, and could efficiently discriminate DLB from controls and AD (AUC:0.91 and 0.81 respectively). Classification modeling unveiled a 7-CSF biomarker panel that better discriminate DLB from AD (AUC:0.93). A custom multiplex panel for six of these markers  was developed and validated in independent cohorts, including an AD and DLB autopsy cohort. This DLB CSF proteome study identifies DLB-specific protein changes and translates these findings to a practicable biomarker panel that accurately identifies DLB patients, providing promising diagnostic and clinical trial testing opportunities.Diagnosis of dementia with Lewy bodies (DLB) is challenging and specific biofluid biomarkers are highly needed. We employed proximity extension-based assays to measure 665 proteins in the cerebrospinal fluid (CSF) from patients with DLB ( This study characterizes the CSF proteome changes underlying Dementia with Lewy Bodies (DLB) and identifies pathophysiological and diagnostic leads associated to this cause of dementia. Findings have been translated into a biomarker panel that could identify DLB patients with high accuracy across different cohorts. DLB is pathologically characterized by the intraneuronal accumulation of α-synuclein (α-syn) in Lewy bodies in the neocortex2. The clinical and pathological presentation strongly overlap with AD, challenging differential diagnosis and leading to a large proportion of miss- or undiagnosed DLB patients5.Dementia with Lewy Bodies (DLB) is one of the most common forms of dementia in the aged population after Alzheimer’s disease (AD)8, recent developments using seed amplification assays allow to detect α-syn brain proteinopathy in CSF and skin12. These assays can discriminate DLB from control or AD patients with high accuracy12. However, α-syn pathology is not unique for DLB patients and more than 40% of AD cases can present with this comorbid pathology13. Similarly, previous studies have shown that the core CSF biomarkers used to support AD diagnosis (amyloid β peptide (Aβ1-42), total tau (tTau) and phosphorylated tau (pTau))14 provide limited diagnostic accuracy for discriminating DLB from AD since they are also abnormal in almost 25–40% of DLB patients due to the presence of comorbid AD pathology18. Additional markers reflecting different, specific, and unique aspects of DLB pathophysiology are needed, which could be useful for different contexts of use in both clinical settings  and trials .Limited number of biomarkers have been widely analyzed to date in DLB. Despite previous studies on α-syn in cerebrospinal fluid (CSF) showing conflicting results21. The few DLB proteomic studies performed to date did not yield many biomarker candidates, which could be due to the limited sample size (30–40 samples per group) relative to DLB heterogeneity25. We here employed a high-throughput proteomics method (immune-based proximity extension assay (PEA)) that allows analysis of large cohorts, with the additional advantage that custom multiplex immunoassays including the markers of interest can be smoothly developed for large-scale validation26. We have applied this workflow to (i) define CSF proteomic changes underlying DLB pathogenesis and (ii) to identify, develop and validate multiplex biomarker assays that could aid in the specific diagnosis of DLB.CSF proteome profiling allows to identify changes covering a wide range of biological processes in vivo. As observed within the AD field, such analysis can help to define the molecular mechanisms involved in disease pathogenesis and reveal promising biomarker candidates21. Custom multiplex panels were developed and validated in two independent clinical cohorts  and one AD/DLB autopsy-confirmed cohort (n = 76). The demographic characteristics and AD CSF biomarkers are described in Table 28 score was higher in DLB compared to controls. The total NPI score was also higher in DLB compared to AD in the discovery and clinical validation cohort 1, but not in the clinical validation cohort 2. The Unified Parkinson’s Disease Rating Scale (UPDRS-III)29 was similar across the clinical validation cohorts.An overview of the study design is presented in Fig. q < 0,05). Six of these proteins were upregulated in DLB  and eight proteins were downregulated  are involved in the biosynthesis of dopamine and serotonin , growth control (GH), corticotropin release from pituitary gland (CRH), immune function (FCER2) and extracellular remodeling (MMP1). DDC showed the strongest effects  followed by GH, MMP1, FCER2, and CRH  were reflecting different biological processes including myelination regulation, tooth development, Notch signaling, steroid metabolism, muscle structure development or ovulation cycle  were analyzed separately, indicating that AD pathology comorbidities did not influence the performance of the model , we observed that the performance of the CSF panel could better discriminate DLB from controls and showed similar AUCs for the discrimination of DLB from AD .DDC, the strongest dysregulated marker that is increased in DLB, could discriminate DLB from controls with high accuracy , immune function (FCER-2), intra and extracellular remodeling , regulation of the hypothalamic–pituitary–adrenal axis (CRH) and neuropeptide degradation (THOP1).r > 0.70, Fig. DDC DLBvs.CON: 0.81; AUCDDC DLBvs.AD: 0.59; AUCcustom panel DLBvs.CN: 0.90; AUCcustom panel DLBvs.AD: 0.68; Fig. DDC aDLBvs.CON: 0.95; AUCDDC DLBvs.AD: 0.86; AUCcustom panel aDLBvs.CN: 1.00; AUCcustom panel aDLBvs.aAD: 0.90; Fig. To validate the performance of our discovery findings, we developed custom multiplex PEA panels measuring six out of the seven proteins from the DLB diagnostic panel, including DDC. Custom assays showed low coefficients of variation (mean intra- and inter-assay CVs of 5% and 9% respectively) and >90% detectability (Supplementary Table 30 and DLB stage31). We observed that CSF DDC positively correlated with parkinsonism severity as measured by UPDRS-III in the clinical validation cohort 1 , but not in the clinical validation cohort 2  with different measures of DLB pathophysiology when available , which was validated in independent external cohorts, including one with neuropathology confirmation. The DLB-related markers were also dysregulated in the prodromal and symptomatic phase of patients with PD, further supporting that the proteins identified reflect known biological processes associated with DLB pathophysiology such as the biosynthesis of dopamine or α-synuclein proteopathy.33. To this end, in this large CSF proteome study, we analyzed more than 100 CSF samples from DLB and cognitively unimpaired controls, but also samples from patients with AD dementia. We detected up to 90 proteins dysregulated in the CSF of DLB cases, but only 14 survived correction for multiple testing. Larger sample sizes might still be required to detect additional biomarker candidates due to clinical heterogeneity in DLB. Thanks to the inclusion of the AD dementia group, we could show that up to 55% of these 90 proteins were dysregulated in DLB specifically . We identified an additional subset of CSF proteins (27%) that were differentially regulated in both DLB and AD patients compared to controls, but with different protein abundance also between DLB and AD. While some of these were decreased in DLB and increased in AD , some were especially dysregulated in AD as previously reported 21, and some were more prominently dysregulated in DLB . These last shared but different protein profiles might be explained by the clinicopathological overlap across these two dementias34. Most of the proteins identified were downregulated in DLB compared to controls, a pattern observed in a previous proteome study35 but also in recent DLB transcriptomic studies39. It has been suggested that such a strong downregulated pattern in DLB could be due to demyelination processes38. In line with those findings, we observed that the proteins dysregulated in DLB were especially enriched in processes associated with negative regulation of myelination. Furthermore, previous research indicates that α-syn can induce myelin loss in neurons and oligodendroglia (precursor) cells41. Importantly, α-syn-induced myelination deficits are involved in the development of multiple system atrophy41. It would be thus of interest to investigate how the identified proteins relate to potential magnetic resonance imaging abnormalities and the importance of myelination processes in the pathophysiology of DLB. Of note, the three top proteins dysregulated in DLB  can regulate the hypothalamic-pituitary-adrenal (HPA) axis43, suggesting that one of the major systems associated with stress response and behavioral dysfunction might be involved in DLB pathophysiology. This is in line with previous studies showing hypothalamic dysfunction in DLB45.Biofluid-based biomarkers specifically associated with DLB are strongly needed not only to improve timely diagnosis and diagnostic accuracy, but also to monitor the different biological mechanisms involved in DLB pathophysiology and as surrogate markers for clinical trials46. This marker was not identified in previous transcriptomics studies. However, these analyses were performed in the anterior cingulate cortex38, an area with limited DDC expression47. It should also be noticed that genetic expression is not per se a proxy reflecting protein abundance48, which might be affected by other post-translational factors . The use of different technologies  together with the limited sample size may also explain why DDC was not detected in the few CSF proteomics studies performed so far24. Of note, we have also developed a DDC immunoassay that have shown similar changes in the clinical validation cohort 1, supporting the robustness of the findings . Previous studies have shown that serum DDC enzyme activity is elevated in patients using levodopa with peripheral decarboxylase inhibitors (PDI), underpinning the effect of dopaminergic treatment on DDC activity49. It is important to note that the increase of CSF DDC levels detected in this study are likely not driven by PDI treatment as i) PDIs do not cross the blood-brain barrier and can thus not influence DDC activity/levels in the brain and ii) we obtained similar results when only DLB patients that did not have any parkinsonism medication were included in the analysis (n = 60). Dysfunction of the dopaminergic system due to nigrostriatal degeneration is a well-established pathophysiological feature of DLB50. Previous studies have shown that nigrostriatal degeneration as well as antagonist of dopamine receptors increase DDC mRNA and activity in different models46. These data do not only align with our findings but also suggest that the increased DDC levels might be a response to the nigrostriatal degeneration and could thus be a very relevant biomarker for DLB diagnosis and disease monitoring. We could validate the high discriminatory accuracy for DLB vs controls (AUC: 0.91) in three independent cohorts, including a neuropathological one (AUCs 0.81–0.95). Considering that current DLB diagnostic guidelines include supportive imaging biomarkers as proxy of nigrostriatal degeneration4, it would be of interest to specifically analyze whether CSF DDC measurements could be an alternative or complementary diagnostic test to classical imaging scans. DDC measurements have the additional advantage of being quantitative over the binary classification with α-syn seed amplification assays, meaning that, DDC measurements might be relevant to track disease staging and for monitoring treatment responses.The strongest dysregulated CSF protein in the DLB group was DDC, an enzyme involved in the biosynthesis of dopamine, which lends biological support to our biomarker discovery design56, likely explaining the higher performance to discriminate these two dementias compared to DDC alone. To validate these findings in independent cohorts, we successfully developed custom multiplex assays for six out of the seven selected markers. The protein effect sizes obtained with these custom assays in the three validation cohorts correlated well with those obtained in the discovery cohort (r coefficients ranging between 0.70 and 0.99), and the high discriminative values were mostly validated (AUCs ≥ 0.80), supporting the relevance and robustness of our findings. In the clinical validation cohort 2 we observed, however, lower accuracy when discriminating DLB vs. AD (AUC 0.68), which was not dependent on whether cases were DAT positive or negative. Sensitivity analysis using only RBD-positive DLB cases in the clinical validation cohort 2 showed a similar performance to that observed in the discovery cohort. We also observed that the total NPI score, in contrast to the different scores observed for the discovery or the clinical validation cohort 1, was similar between DLB and AD cases in clinical validation cohort 2. Overall, these data suggest that the heterogeneity of the clinical diagnosis of DLB based on different supportive features  may impact biomarker data; and that the panel is likely most sensitive and specific in typical DLB. Understanding which factors may influence CSF DDC levels is of paramount importance for the potential future implementation of this marker and the corresponding DLB diagnostic panel.To translate the CSF proteome findings into practical biomarker tools for routine diagnostics and clinical trials, we applied classification analysis and identified a panel of seven CSF proteins to discriminate DLB from controls and AD dementia with high accuracy (AUC of 0.95 and 0.93 respectively). This panel combined proteins associated to DLB  but also proteins specifically related to AD 8. We however explored the association between the CSF DLB markers identified in this study and specific DLB pathophysiological features. Even though these specific results should be interpreted with caution considering the limited sample size, the positive association of CSF DDC with UPDRS-III, α-syn load in different brain areas, α-syn Braak stage and DLB stages supports the potential of this marker to track disease progression already from very early stages. This is further supported by the data obtained from the PD cohorts in which CSF DDC was already increased in the prodromal stage of the disease. The other biomarkers within the DLB panel  also associated with some DLB pathophysiological features, but results were not consistent across cohorts. This calls for a systematic analysis of all these CSF markers in cohorts with large associated neuropathological characterization. These markers were also dysregulated in prodromal PD and showed nominal significance at the clinical stage. The fact that the DLB markers identified in this study are also dysregulated in PD is not surprising considering both disorders are characterized by α-syn pathology and dopaminergic cell loss in the substantia nigra57. Thus, despite the fact that the identified markers are specific for DLB in the context of neurodegenerative dementias, they might be dysregulated in other α-synucleopathies or disorders characterized by dopamine deficiency. Overall, all these data support that CSF DDC (and maybe the panel) could be a useful quantitative tool not only to track nigrostriatal degeneration and disease stage, but also to select prodromal cases or monitor treatment effects in clinical trials. Specific follow-up studies including different Parkinsonian disorders and Lewy bodies dementias in the same data set are needed to understand the role of these markers across the different disorders and define their potential context of use.We could not investigate the association between CSF DDC or the other DLB markers  and CSF α-syn levels, as this information was not available in our data sets. Still, the added value of such information might be limited considering the variable results on CSF α-syn observed across studiesn = 13), such data highlights the importance of including treatment information in biomarker studies. Additional analyses are needed to confirm the relevance of treatment effect on CSF FCER2 abundance. Importantly, medication did not drive the main differences observed between groups for the other DLB-related proteins . Considering the clinicopathological overlap with AD34, we cannot exclude that the potential misdiagnosis of DLB patients may have influenced our discovery results. However, samples were collected in well-characterized biobanks from specialized memory units, and DLB diagnosis was either autopsy confirmed or supported by DAT scans in more than one third of the patients. Moreover, our sensitivity analysis showed similar diagnostic accuracies in DLB cases with positive AD CSF biomarker profile, and we further validated the biomarker panel in a CSF AD/DLB autopsy confirmed cohort. The similar differences observed for CSF DDC, FCER2, CRH, and MMP3 also in the PD data sets call for additional studies that evaluate the performance of these markers in other α-synucleinopathies , other dementia types with motor dysfunctions  or other conditions with dopamine deficiency . This DLB study covers already three phases of the biomarker development workflow58 including the retrospective analysis of four cohorts coming from different memory clinics with their own intrinsic methodologies and clinical characteristics, which ultimately supports the reproducibility and robustness of the findings. Still, future studies are needed to define the clinicopathological correlations and trajectories between the biomarker panel and different measures associated with DLB pathophysiology, including other relevant markers, such as α-syn seed amplification assays59, in longitudinal and prospective studies using independent large and highly phenotyped cohorts. This will help to define their potential context of use within different settings in clinical practice and trials . We envision that CSF DDC and the panel developed within this study could be relevant complementary and quantitative diagnostic tests reflecting different biological aspects associated with DLB pathophysiology in the context of dementias. This quality may make them suitable to improve diagnosis and staging along the DLB continuum but also to monitor treatment response in clinical trials targeting different mechanisms61.Despite the large number of samples and proteins analyzed in this DLB-specific study, there are still relevant limitations. We observed that Parkinsonian medication moderately influenced the levels of some CSF proteins. Despite the number of cases that underwent Parkinsonian medication was limited . Informed consent was obtained from all subjects or their authorized representatives.n = 534) included CSF samples from patients diagnosed with DLB (n = 109), AD (n = 235) and 190 cognitively unimpaired controls 65. Three additional independent CSF cohorts were used for validation of the customized panels (see methods below): clinical validation cohort 1 63, clinical validation cohort 2 (from the Sant Pau Initiative on Neurodegeneration (SPIN) cohort: 55 DLB, 55 AD, and 55 controls)66 and an AD/DLB autopsy confirmed cohort (from BIODEM and the neurobiobank of the Institute Born-Bunge (IIB)/UAntwerp: 17 autopsied confirmed DLB (aDLB) and 30 autopsied confirmed AD (aAD))68. An additional 29 cognitively unimpaired controls from BIODEM-UAntwerp were included in this cohort but these were not autopsy confirmed68. CSF was collected by lumbar puncture and processed and stored at all sites in agreement with the JPND-BIOMARKAPD guidelines, thereby minimizing the influence of potential pre-analytical factors69.An overview of the study design is presented in Fig.  DLB n = 09, AD  with additionally negative AD CSF biomarkers in all cases75. Mini-Mental State Examination (MMSE) was used as a measure of global cognition. Motor parkinsonism was assessed using section III of the Unified Parkinson’s Disease Rating Scale (UPDRS)29. Core and supportive clinical features31 were recorded locally in each memory unit66. Evaluation of REM Sleep Behavior Disorder (RBD) includes an interview with a sleep specialist, a full nocturnal video-polysomnography, the Mayo Sleep questionnaire (cutoff ≥1) or caregivers reporting that a patient would ‘act out’ their dreams and moves extensively during their sleep as previously described76. Supportive neuropsychiatry symptoms  were compiled according to the Neuropsychiatry Inventory and summarized in one single score 28. Levels of CSF Aβ42, tTau and pTau(181) (‘AD CSF biomarkers’) were used to support AD diagnoses. These markers were analyzed locally as part of the diagnostic procedure using commercially available kits (VUmc and UAntwerp: ELISA INNOTEST Aβ(1-42), hTAUAg, phospho-Tau or VUmc: Aβ(1-42), t-TAUAg, phospho-Tau181 Elecsys biomarker assays (Roche Diagnostics GmbH); Penn: Luminex xMAP INNO-BIA AlzBio3; Luminex Corp, Austin, TX; SPIN: Lumipulse G600, Fujirebio)78. Positive CSF AD biomarker profile was defined locally as increased tTau/Aβ42 ratio in the cohorts from ADC (>0.46) and Pennsylvania (>0.30); and low Aβ42/40 ratio (<0.062) and high total tau (>456 pg/ml) or p-tau (>63 pg/ml) in the SPIN cohort80.All participants of every cohort underwent standard neurological and cognitive assessments and diagnosis was assigned according to international consensus criteria for DLB31. Comorbid AD pathology, which is common in DLB patients18, was present in up to 34 DLB patients (32%) as measured by AD CSF biomarker profile. From all the DLB patients, only 13 DLB patients had medication for parkinsonian symptoms, 60 did not have such a treatment and this information was not available for 36 cases.In the discovery cohort, DLB neuropathology was confirmed in 14 DLB patients 13%) by autopsy .In the clinical validation cohorts 1 and 2, DAT scans supported DLB diagnoses in 18 and 21 patients respectively  or cerebrovascular lesions (n = 3) were reported in 10 cases. Coexisting cerebrovascular lesions (n = 8), TDP pathology (n = 1) or cerebral amyloid angiopathy (n = 1) were reported within the aAD neuropathological group. The control group of this cohort was not autopsy confirmed. It consisted of volunteers, mainly spouses of patients who visited the memory clinic. The inclusion criteria for these volunteers were: (1) no neurological or psychiatric antecedents; (2) no organic disease involving the central nervous system following extensive clinical examination; and (3) normal neuropsychological exam. Exclusion criteria consisted of brain tumors, large cerebral infarction/bleeding, strategic infarctions, other neurodegenerative diseases, severe head trauma, epilepsy, brain infections, severe depression, unregulated diabetes mellitus, untreated thyroid disorders, or any severe somatic comorbidity that interferes with study participation81.The AD/DLB autopsy validation cohort included cases with a definite diagnosis according to international neuropathological examination guidelines for DLBPatient demographics and clinical and biochemical values from all cohorts used in this study are listed in Table 21, CSF proteins (979) were quantified using the 11 specific and validated multiplex antibody-based protein panels based on the proximity extension assay (PEA) that were available at the time in which the analysis was performed as previously described  were calculated using the 4 CSF QC samples. No cross-reactivity between assays for specific proteins was detected. Assay parameters including LOD, detectability and CVs are included in Supplementary Table Custom-designed multiplex-PEA assays were developed by the manufacturer following standardized protocols32 (http://www.ppmi-info.org/data) on March 28th, 2023. The PPMI study is registered with ClinicalTrials.gov (number NCT01141023). The study protocols and the manuals related to different procedures for clinical assessment, biochemical phenotyping as well as sample handling, collection and storage is described online (http://www.ppmi-info.org/study-design). Data from samples collected at baseline were used for the analysis. Two different sets were available with PEA CSF proteome  from the Parkinson´s Progressive Markers Initiative PPMI82. For each pairwise comparison, multiplicity was taken into account by controlling the False Discovery Rate (FDR)83 at q ≤ 0.05 based on the number of features analyzed. We next evaluated which CSF protein combination (CSF panels) could best discriminate the groups of interest while keeping the number of markers to the minimum, so that they can be ultimately translated into small, practical custom panel21. For this purpose, binary classification signatures (DLB vs. CON and DLB vs. AD) were constructed by way of penalized generalized linear modeling (GLM) with an elastic net penalty  in the discovery CSF cohort using the glmnet package and including age and sex as covariates84. This penalty enables estimation in settings where the feature-to-sample ratio is too high for standard generalized linear regression. Moreover, it performs automatic feature decorrelation as well as feature selection. For each classification exercise, we compare multiple models which reflect (a) a grid of values for the elastic-net mixing parameter, reflecting strong decorrelation to a pure logistic lasso regression and (b) a grid of values reflecting the maximum number of proteins that may be selected under each model (21 markers maximum). The former grid (a) considers that we have little information on the collinearity burden in the data. The latter grid (b) considers that we want to keep the number of selected proteins relatively low for the future development of customized panels. The optimal penalty parameters in the penalized models were determined based on  10-fold cross-validation of the model likelihood82. The cross-validation was performed with balanced folds, by which each fold has an outcome group ratio close to the corresponding ratio in the full data set, also referred to as stratified cross-validation. The predictive performance of all models was assessed by way of (the comparison of) Receiver Operating Characteristic (ROC) curves and Area Under the ROC Curves (AUCs). The model with the highest AUC and lowest number of markers for each classification signature was selected. The fold-based selection proportions for each marker were assessed to identify and select the most promising markers within each model . To reflect the manual selection pressure for these final marker sets, each final logistic signature was subjected to a ridge-regularization with a penalty parameter of 0.1. The performance (AUC) was evaluated by internal validation: repeated 5-fold cross-validation with 1000 repeats. The 95% confidence interval around the resulting AUCs was based on resampling quantiles (percentile method). External validations assessed the performance of the final models with the markers of interest in the validation cohorts using ROC analysis.All data preprocessing and analyses were conducted using R version 3.5.3 and SPSS version 25. Between-group analyses for the demographic variables were performed using two-sided one-way analysis of variance in normally distributed continuous data or Pearson’s chi-square test for categorical variables. Analysis of covariance was performed when an association between classical AD CSF biomarker and age and/or sex were detected. Adjustment for multiple testing was performed using Bonferroni method. Non-Gaussian distributed data were analyzed using Kruskal-Wallis Test. For the CSF proteome data, differences in protein abundance between pairs of clinical groups were evaluated using nested linear models as previously described, in which for each individual protein feature, we assessed if its addition to a base model containing age and gender contributed to model fit85. UPENN values had lower means for Aβ42 on the Innotest, which were first linearly transformed to normalize to the same mean. Passing-Bablock transformation formulas were calculated based on individuals with both Luminex and Innotest values for Aβ42 (n = 32), tTau (n = 32) and pTau (n = 27) and used the formulas to estimate the equivalent Innotest values for those samples measured with Luminex platform only (transformed_ Aβ42 = (Luminex_ Aβ42*4.65) − 36.23; transformed_tTau = (Luminex_tTau*5.28) − 2.03; transformed_ptau = (Luminex_pTau*1.88) + 27.36). The association between the markers of interest with DLB pathophysiological features  was analyzed by either correlation analysis or ANOVA. Stratification or post-hoc analysis with DLB pathophysiological features could not be performed due to the limited sample size of some subgroups.Non-parametric correlation analysis was performed to understand the associations between the proteins within the CSF panels and the classical AD CSF biomarkers or cognitive function (MMSE score) using the complete discovery cohort without stratifying per diagnostic category and conditioning on age and sex as covariates. Innotest values generated for the Amsterdam Dementia Cohort were adjusted for drift over time as previously described86 selecting GO Biological Processes as ontology source. All the CSF proteins optimally analyzed with Olink arrays (n = 645 protein gene products) were included as the enrichment background. Default parameters were used for the analysis in which terms with a p-value < 0.01, a minimum count of 3, and an enrichment factor > 1.5 were collected and grouped into clusters based on their membership similarities.Functional enrichment analysis was performed using MetascapeFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Recent studies have emphasized the role of microglia in the progression of many neurodegenerative diseases. The colony stimulating factors, CSF-1 (M-CSF), granulocyte-macrophage CSF (GM-CSF) and granulocyte CSF (G-CSF) regulate microglia through different cognate receptors. While the receptors for GM-CSF (GM-CSFR) and G-CSF (G-CSFR) are specific for their ligands, CSF-1 shares its receptor, the CSF-1 receptor-tyrosine kinase (CSF-1R), with interleukin-34 (IL-34). All four cytokines are expressed locally in the CNS. Activation of the CSF-1R in macrophages is anti-inflammatory. In contrast, the actions of GM-CSF and G-CSF elicit different activated states. We here review the roles of each of these cytokines in the CNS and how they contribute to the development of disease in a mouse model of CSF-1R-related leukodystrophy. Understanding their roles in this model may illuminate their contribution to the development or exacerbation of other neurodegenerative diseases. They comprise ~10% of the brain cells and are distributed throughout the central nervous system (CNS)  reviewe. Their CCSF-1R, GM-CSFR and G-CSFR are all expressed on microglia. While their expression has been reported on some neural lineage cells [reviewed in 1.1.In blood, CSF-1 circulates at physiological concentrations of 4.5 ng/mL , while cCsf2 gene) and G-CSF (encoded by the Csf3 gene) are also expressed in brain at steady state, but at low levels [reviewed in via local production and utilization.In normal brain, CSF-1 and IL-34 are primarily expressed by CNS neurons, in a largely non-overlapping manner . CSF-1 i1.2.via both circulating and locally expressed CSF-1R ligands that regulate macrophage development and maintain tissue macrophage densities  in the yolk sac give rise to microglia and meningeal, perivascular and some choroid plexus macrophages in a CSF-1R-dependent manner  reviewe. CSF-1R Regulation by the CSF-1R ligands differs temporally and spatially. Temporally, CSF-1 alone is required for microglial colonization and maintenance in fetal brain, while IL-34 begins to be required postnatally . SpatialInhibition of CSF-1R signaling in the adult brain leads to massive (90–99%) microglial death . FollowiIn vitro, CSF-1 induces the proliferation of murine  and the high affinity βc (encoded by Csf2rb), exhibit different patterns of expression in the brain, with Csf2ra transcripts being expressed both in microglia and neural lineage cells, and Csf2rb transcripts being largely restricted to microglia and having sporadic expression in the neural lineage.Reduction of GM-CSF expression leads to decreased cognitive function , indicatCsf2ra and Csf2rb and the downregulation of Csf1r transcripts   . Despitee-brain) , its adme-brain) , to actie-brain) . Togethe1.5.Csf1r  and are therefore expected to result in haploinsufficiency  was caused by dominantly inherited, mono-allelic, utations . This diutations . Over 10ficiency . No cleaficiency . The penignaling . Apart fignaling , co-tranto CSF-1 , indicatThe most common initial complaint of CRL patients is cognitive impairment followed by gait disorders and dyskinesia which tend to be more common in females [reviewed in 2.2.2.2.1.Csf1r heterozygous C57BL6/J mouse as a model of CRL was catalyzed by the first description of CSF1R haploinsufficiency as a cause of CRL , depression- and anxiety- like behavior  of CRL [reviewed in greater detail in tic mice , that arpression . In sympe matter . Clustere matter  has recee matter  and mighe matter . Also sie matter , there ie matter . Csf1r+/callosum . Overall2.2.3.Csf1r heterozygosity in the microglial and neuronal lineages to CRL development in the mouse model by studying disease development in fl/+; Cx3cr1Cre/+Csf1r and fl/+; NestinCre/+Csf1r mice, in which one allele of the Csf1r was deleted in the mononuclear phagocytes and neural lineages, respectively  male and female mice (CSF2 and CSF3 mRNAs were also shown to be elevated in the brains of post-mortem CRL patients and alterations in CSF-3 signaling were also noted in an independent study (Early studies of the elopment . This inelopment . Thus, ttic mice . These rale mice , discussnt study .2.2.5.+/−Csf1r mice progressively develop cognitive and sensorimotor deficits that are associated with the loss of callosal white matter (+/−; Csf2+/−Csf1r mice revealed a substantial contribution of GM-CSF to microglia activation and demyelination in the callosal white matter (+/−; Csf2+/−Csf1r mice was associated with attenuation of both cognitive and motor deficits. In contrast, targeting G-CSF did not improve myelination and had no effect on cognition. However, monoallelic disruption of Csf3 selectively rescued the motor coordination deficits of female +/−Csf1r mice, while it also tended to worsen motor function in males (Starting from 7 months of age, e matter . By conne matter . Improvein males . This imin males . Togethe2.2.6.+/−Csf1r mice exhibit a slight early increase in microglial densities (Csf2 normalized microglia densities in most brain regions of +/−Csf1r mice, with the exception of the cerebellum (Csf2rb in microglia also prevented the increase in forebrain microglial densities, provided formal evidence that the GM-CSF-induced microgliosis is due to direct signaling in microglia (Csf3 in +/−Csf1r mice had limited effects on microglia densities, normalizing their levels only in the corpus callosum, cerebellum and ventral hippocampus (Csf3 heterozygosity normalized the densities but not morphological alterations of microglia in the corpus callosum while having the reverse effect in the cortex of +/−Csf1r mice (Csf3 (Csf1r, Csf2ra, Csf2rb and Csf3r among mouse and human microglia (+/−Csf1r microglia. Transcriptomic profiling of microglia isolated from +/−Csf1r mice suggested a maladaptive phenotype which was significantly attenuated following monoallelic inactivation of Csf2. The expression of gene products that mediate synapse removal, trigger cellular senescence, neurotoxicity and oxidative stress was restored with consequent reduction of the histological evidence of oxidative damage and active demyelination/remyelination (+/−; Csf3+/−Csf1r mice revealed that monoallelic targeting of Csf3 reduced the production of C1q and its deposition on glutamatergic synapses and their consequent excessive removal by microglia (ensities . This inensities  and, unlrebellum . Furthericroglia . In contpocampus . This efpocampus . Further+/− mice . The fac+/− mice , a findice (Csf3 . Anothericroglia . Irrespelination . Similaricroglia . Overall2.2.7.+/−Csf1r male mice, to reduce myelin phagocytosis by +/−Csf1r microglia to wt levels and to contribute to the preservation of callosal myelin structure and of synaptic densities in the hippocampus (+/−Csf1r female mice, who were unaffected at the same age and have not been evaluated or treated at a later time point.Accumulation of evidence that CRL is a primary microgliopathy has sparked an interest in evaluating the therapeutic potential of agents known to suppress microglia activation. Recently, a one-month course of minocycline, a suppressor of the inflammatory activation of microglia, was reported to partially rescue the cognitive dysfunction in 8-month-old pocampus . It is uCSF1R variants associated with CRL (ex vivo showed that prednisone administration suppressed a series of biological processes relevant to microglial activation and oligodendrocyte senescence (Csf2 in the mouse model of CRL prevented the development of cognitive, motor and olfactory deficits and the loss of myelin (+/−Csf1r mice also prevents the loss of myelin (Clinical studies suggested that pre-symptomatic immunosuppression with glucocorticoids is protective in patients carrying pathogenic with CRL . Furthernescence . These dnescence  suggestsnescence . Thus, tnescence  and suppf myelin . Importaf myelin , indicat3.+/−Csf1r mice suggest that normal CNS homeostasis requires balanced signaling through all three microglial receptors (Csf1r (Colony-stimulating factors regulate microglial development, maintenance and function in a non-overlapping and sometimes antagonistic fashion. A summary of the outcomes of their actions is presented in eceptors . CSF-1R eceptors  and G-CSeceptors  levels as (Csf1r  expressis (Csf1r . These fES: Conceptualization, Formal analysis, Funding acquisition, Project administration, Resources, Supervision, Visualization, Writing – original draft, Writing – review & editing. FB: Data curation, Formal analysis, Investigation, Methodology, Writing – review & editing. SG: Investigation, Methodology, Writing – review & editing. VC: Formal analysis, Investigation, Methodology, Writing – review & editing.