Handwashing is fundamentally an inexpensive means of reducing the spread of communicable diseases. In developing countries, many people die due to infectious diseases that could be prevented by proper hand hygiene. The recent coronavirus (COVID-19) pandemic is a threat to people who are living in resource-limited countries including sub-Saharan Africa (SSA). Effective hand hygiene requires sufficient water from reliable sources, preferably accessible on premises, and access to handwashing facility (water and or soap) that enable hygiene behaviors. Therefore, this study aims to determine the prevalence of limited handwashing facility and its associated factors in sub-Saharan Africa.Data from the Demographic and Health Surveys (DHS) were used, which have been conducted in 29 sub-Saharan African countries since January 1, 2010. A two-stage stratified random cluster sampling strategy was used to collect the data. This study comprised a total of 237,983 weighted samples. The mixed effect logistic regression model with a cluster-level random intercept was fitted. Meta-analysis and sub-group analysis were performed to establish the pooled prevalence.The pooled prevalence of limited handwashing facility was found to be 66.16% . Based on the final model, household head with age group between 35 and 60 , households with mobile type of hand washing facility , unimproved sanitation facility , water access more than 30 min round trip , urban residential area , low media exposure , low educational level , low income level  as well as lower middle-income level  and households who had more than three children  were associated with having limited handwashing facility.The pooled coverage of limited handwashing facility was high in sub-Saharan Africa. Raising awareness of the community and promoting access to handwashing materials particularly in poorer and rural areas will reduce its coverage.The online version contains supplementary material available at 10.1186/s12889-022-14390-4. Handwashing is a fundamental principle and a low-cost method of minimizing communicable diseases transmission , 2. HandBased on WHO report, over 270 million confirmed cases of coronavirus and more than 5 million confirmed deaths were registered globally . The recPrevious studies found that, factors such as educational level of the household head , media eThe Demographic and Health Surveys (DHS) program began in 1984 . It is aThe outcome of this study was a limited handwashing facility. DHS collected information on handwashing facility, such as the place where handwashing facility found, whether fixed (such as Sink with tap and Tube with outlets) or mobile . Furthermore, data on the presence of water, soap, and any detergents  on the premises were gathered through face-to-face interviews and observation. Based on this information, households with both fixed and mobile places and household members washing their hands without water and or soap (confirmed by observation) at the time of the interview, were considered as “having limited handwashing facility” .Individual and household level variables for limited handwashing facility extraction included the following; age of household head, sex of household head, marital status of the household head, household size, household wealth index, educational status of household head, floor material type (standard vs. substandard) , place oWe have used STATA version 14.0 software to extract and analyze the data. After the samples were weighted, descriptive statistics were performed. Because of the hierarchical and clustering nature of the DHS data, a mixed effect multilevel logistic model was used. A cluster-level random intercept was utilized to determine the difference in limited handwashing facility between clusters. Meta-analysis was conducted to determine the pooled prevalence of limited handwashing facility in sub-Saharan Africa, as well as sub-group analysis by region, income level, and year of the survey were also employed.Four models were fitted in the multilevel analysis. The first was a null model (Model 1) that was designed to check the variability in limited handwashing facility and which only contains the outcome variable. Model 2 and Model 3 were for individual/household and community-level variables, respectively. In the fourth model (Model 4), both the community and individual/ household variables were fitted simultaneously. Model comparison was done using deviance and the model with the lowest deviance was chosen as the best-fitting model.https://dhsprogram.com/data/available-datasets.cfm). On the website, a request was made. The researchers had no ethical concerns since the DHS program handled ethical issues both before and throughout the survey.Permission for data was obtained from the DHS program  was found over the age of 60 years. Overall, about 72.86% of the households were headed by men, and among them, 68.95% of household heads had limited handwashing facility. Around thirty-two percent (31.63%) of household heads had no formal education, and 82.46% of those household heads had limited handwashing facility. Less than one-fourth of households had a family size of seven or more, and 72.89% of those households had limited handwashing facility.Among a respondents, 75.76% of households had improved water sources and 56.78% of households had improved sanitation facility. Three-fourths (76.32%) of the households had a mobile type of handwashing facility. Around twenty-seven 26.81%) of households spent more than 30 min in collecting water, of which 75.15% of households had a limited handwashing facility. The results of individual and household factors of limited handwashing facility are summarized in the table below  of respondents live in urban areas. The community level education was the aggregate data from the educational status of the individual household head, and in this study, communties with low educational status accounted for 49.03%. Approximately half of the communities had high media exposure (50.80%) Table .Table 2C2) was 99.9%, which indicates that results for individual countries might vary to a larger extent from the pooled estimate. The pooled prevalence of having limited handwashing facility is summarized in the figure below “Fig. In this study, the pooled prevalence of limited handwashing facility (households that lacked water and/or soap) was found to be 66.16% . I square  in southern Africa to 69.77%  in West Africa. The Central African region has fewer countries and a wider confidence interval. The following figure below summarizes the sub-group analysis of limited handwashing facility in region We also conducted a sub-group analysis based on countries income level. According to the findings, the prevalence of limited handwashing facility was 71.64%  in low-income countries, 60.95%  in lower middle-income countries, and 43.90%  in upper-middle countries. The findings revealed that the prevalence of limited handwashing facility decreases as a country's income level rises. The figure below shows that a sub-group analysis based on countries income level “Fig. . .We divided the survey year into two categories: above 2015 and below 2015. The prevalence of limited handwashing facility was 68.09%  among countries whose DHS survey was conducted above 2015 and 63.01%  among countries whose DHS survey was conducted below 2015. Burundi had the highest prevalence of limited handwashing facility at 94.68%  in the year 2016/2017, whereas Angola had the lowest prevalence at 35.67%  in the year 2015/2018. The sub-group analysis of limited handwashing facility by survey year is summarized in the figure below “FigAs shown in Table This study covered factors at the individual, household, and community levels. Variables with p values less than 0.25 were eligible for further multilevel analysis. Individual and household variables such as the age of the household head, the sex of the household head, household size, location of handwashing facility, source of water, sanitation facility, time taken to get water, and the number of under-five children were selected while community-level factors such as residence, community media exposure, income level and community level education were selected for further analysis.In the final model (model 4), age of the household head, place of handwashing facility, sanitation facility, time taken to get water, number of under-five children, residence, media exposure, income status and level of education were all associated with limited handwashing facility.Household heads aged between thirty-five and sixty had 11% of limited handwashing facility with . Households with a mobile type of handwashing facility were 1.73  times more likely to have limited handwashing facility than those with a fixed location.In terms of sanitation, households with unimproved sanitation were 1.58  times more likely to have limited handwashing facility than those with improved sanitation. The odds of having a limited handwashing facility were 1.16  times higher in households that had to travel more than 30 min to get water than in households that got water within 30 min. When we compared urban household residents, the odds of having a limited handwashing facility in rural areas was 2 times higher . Communities with low media exposure had 1.47  times higher odds of having limited handwashing facility than those communities with higher media exposure. The likelihood of having a limited handwashing facility was 1.3  times higher in low educated communities than in higher educated communities. The likelihood of having a limited handwashing facility was 2.41  and 2.1  times higher among low-income and lower-middle-income countries as compared with upper-middle countries, respectively.The odds of having limited handwashing facility was 1.11  and 1.25  times higher in households with at least two and three or more children, respectively, than in households without children [Table The pooled prevalence of limited handwashing facility (lack of water and/or soap) in this study was 66.16%, with a 95% confidence interval of (59.67%—72.65%).This result was higher than that of a surveys conducted in 44 countries , where tIndividual, household, and community-level factors for handwashing facility were all included in this study. Based on multilevel regression model, household heads with older age was significant and a protective factor of limited handwashing facility. The finding is supported by different studies –25, wherAccording to the current study, having low media exposure in the community had higher effect on the presence of limited handwashing facility. The result was supported by different studies , 24, wheCountries with low and lower middle-income levels were associated with the presence of limited handwashing facilities; this finding was supported by different studies , 26–29, Households who travel more than 30 min round trip to get their water source had a limited handwashing facility. This finding was reinforced by research in Kenya . But it Our study also found that communities with a low educational level were more likely to have limited handwashing facility. This finding is supported by evidence that those who received basic handwashing education were more likely to have handwashing facility . It was According to our findings, households with more children have limited handwashing facility. This is a contradictory pattern from East African countries , where hResidence was also another factor for the limited handwashing facility. In this study, being rural residents were more likely to have limited handwashing facility than urban areas. The finding was supported by other evidences , 24, 27.Unimproved sanitation facilities were associated with limited handwashing facility. The finding was supported by suggested evidences , 28, houThis study's findings are critical because it will assist the government and WASH stakeholders in improving the educational status of households and determining the best alternative choices for the affordability problem, which mostly affects handwashing practices. Work on handwashing minimizes costs associated with the treatment of infectious diseases, including the present COVID-19 pandemic, because prevention is better than cure. The COVID-19 pandemic is a severe disease, and handwashing with soap and water, in conjunction with other measures, will be a useful strategy for avoiding further COVID-19 transmission. Since good handwashing is extremely difficult in the absence of adequate handwashing facility, the pandemic disease will persist.We used DHS (secondary) data, which is cross-sectional in nature and reflects the handwashing status that exists only at the time of the survey. DHS does not collect all of the variables that must be considered when it comes to handwashing facility . As a result, despite our findings expressing existing evidence, other confounding factors may exist. We were only interested in the presence or absence of a handwashing facility, not handwashing practice, so having limited handwashing may not be considered poor handwashing practice.In this study, the pooled prevalence of limited handwashing facility (without water and or soap) is 66.16%. West African region had the highest prevalence of limited handwashing facility when compared to others regions in sub-Saharan Africa. The prevalence of limited handwashing facility increase when income level reduced. The age of the household head, location of the handwashing facility, number of under-five children, household size, sanitation facility, residence, income level, community-level media exposure, and education were a determinant factors for limited handwashing facility.Organizations and government agencies of low and low-middle-income countries should better to build handwashing water infrastructure and providing or supplying soap with low cost for households that cannot buy soap. The Global Handwashing Partnership and other respected health sectors in each country should promote handwashing for rural residents, for whom washing hands with soap may be considered luxurious due to poor educational levels. Furthermore enhancing the knowledge of risks related to poor handwashing practice is very important. For researchers, focusing on personal behaviors as well as societal and cultural determinants of limited handwashing facility through qualitative research will be more informative. Finally, governments in each country should prioritize handwashing programs based on the observed factors.Additional file 1: Supplementary table (S1). Individual level variables extracted from DHS data set for studying factors associated with limited handwashing facility. Supplementary table 2 (S2). Community level variables extracted from Demographic and Health Survey data set for studying factors associated with limited handwashing facility.


In the cerebrospinal fluid (CSF) dynamics, the pulsations of cerebral arteries and brain is considered the main driving force for the reciprocating bidirectional CSF movements. However, measuring these complex CSF movements on conventional flow-related MRI methods is difficult. We tried to visualize and quantify the CSF motion by using intravoxel incoherent motion (IVIM) MRI with low multi-b diffusion-weighted imaging.2) was performed on 132 healthy volunteers aged ≥ 20 years and 36 patients with idiopathic normal pressure hydrocephalus (iNPH). The healthy volunteers were divided into three age groups . In the IVIM analysis, the bi-exponential IVIM fitting method using the Levenberg–Marquardt algorithm was adapted. The average, maximum, and minimum values of ADC, D, D*, and fraction of incoherent perfusion (f) calculated by IVIM were quantitatively measured in 45 regions of interests in the whole ventricles and subarachnoid spaces.Diffusion-weighted sequence with six b values (0, 50, 100, 250, 500, and 1000 s/mmCompared with healthy controls aged ≥ 60 years, the iNPH group had significantly lower mean f values in all the parts of the lateral and 3rd ventricles, whereas significantly higher mean f value in the bilateral foramina of Luschka. In the bilateral Sylvian fossa, which contain the middle cerebral bifurcation, the mean f values increased gradually with increasing age, whereas those were significantly lower in the iNPH group. In the 45 regions of interests, the f values in the bilateral foramina of Luschka were the most positively correlated with the ventricular size and indices specific to iNPH, whereas that in the anterior part of the 3rd ventricle was the most negatively correlated with the ventricular size and indices specific to iNPH. Other parameters of ADC, D, and D* were not significantly different between the two groups in any locations.f value on IVIM MRI is useful for evaluating small pulsatile complex motion of CSF throughout the intracranial CSF spaces. Patients with iNPH had significantly lower mean f values in the whole lateral ventricles and 3rd ventricles and significantly higher mean f value in the bilateral foramina of Luschka, compared with healthy controls aged ≥ 60 years.The  The cerebrospinal fluid (CSF) motion is composed of a steady microflow produced by the rhythmic wavy movement of motile cilia on the ventricular wall surface , 2, a dy2 in DWI was useful for evaluating CSF motion in the whole cranium [2, which applies the phenomenon that the motion-related signal dephasing of the CSF in a wider area with small-to-large CSF motion increases as the b value in DWI increases from 0 s/mm2 [A diffusion weighted image (DWI) with a lower b value could detect CSF motion as a signal attenuation or dephasing . Taoka e cranium , 21. The 0 s/mm2 . As an i 0 s/mm2 , 23 has  0 s/mm2 . IncoherThe study design and protocol have been approved by the ethics committees for human research at our institute (IRB number: R2019-227). This study followed a prospective and observational design. The study was performed in accordance with the approved guidelines of the Declaration of Helsinki. From November 2020 to February 2022, 133 healthy volunteers aged ≥ 20 years underwent MRI after providing written informed consent explaining the potential for detection of brain disease. Volunteers were recruited from medical staff and students, and their families by open recruitment. Inclusion criteria for this study were those who had no history of brain injury, brain tumor or cerebrovascular disease on previous brain MRI, or those who had never undergone brain MRI and no neurological symptoms including cognitive function. One volunteer aged 84 years old was excluded from this study because of a history of head surgery due to a head injury over 30 years ago. In addition, three volunteers were incidentally found small unruptured intracranial aneurysms with a maximum diameter of < 2 mm on this MRI. They were included in this study, because small unruptured aneurysms might not affect CSF motion.Patients’ MRI data was used in an opt-out method, after their personal information was anonymized in a linkable manner. Among 44 patients suspected with NPH, 5 patients diagnosed with secondary NPH  that dev2). The DWI sequence parameters were as follows: repetition time, 6666 ms; echo time, 78 ms; flip angle, 90°; bandwidth, 1305 Hz/Px; slice thickness, 3.0 mm; field of view, 220 mm; acquisition matrix size, 128 × 192; pixel size, 1.7 × 1.1 mm; acquisition time, around 2 min for total acquisition; motion-probing gradient, bipolar type. The isotropic images were created from 3 orthogonal diffuse gradient pulse images. The sequence parameters for 3D T2-weighted fast spin-echo Cube sequence were as follows: TR, 2,000 ms; TE, 85.3 ms; matrix 288 × 288; voxel size, 0.8 × 0.8 × 0.8 mm; and acquisition time, approximately 4 min.All MRI examinations were performed using a 3-Tesla MRI system . DWI was performed in axial planes by using six b values , true diffusion coefficient , pseudo-diffusion coefficient , and fraction of incoherent perfusion  in one voxel were automatically created approximately 30 s after reading the multi-b DWI sequence on the IVIM application, as shown in Fig. IVIM analysis was performed using the IVIM application on an independent 3D volume analyzer workstation . Four maps of apparent diffusion coefficient . In the normal brain, f has been reported to be generally less than 5% and D is approximately 0.002 mm2/s [f maps  were measured as the maximum width of the brain just above the lateral ventricles divided by the maximum width of the lateral ventricles on the reference coronal planes at the anterior commissure and posterior commissure levels, respectively . The calf were automatically measured in each ROI. The numbers indicate the following regions: the foramen magnum [The average, maximum, and minimum values of ADC, D, D*, and n magnum , bilatern magnum , 4th venn magnum , 3rd venf values due to aging in healthy controls, mean values ± SD for several measurements among three age groups  were compared using the Kruskal–Wallis test. Significance was assumed at a probability (P) value of < 0.001. All missing data points were treated as deficit data that did not affect other variables. Statistical analyses were performed using the R software version 4.1.0 .Mean values ± standard deviations (SD) for age and several measurements in patients with iNPH were compared with those in healthy controls using the Mann–Whitney–Wilcoxon test. Fisher’s exact test was used to compare the proportions of the two groups. To investigate the trends in mean In total, the study included 168 participants, comprising 36 patients diagnosed with iNPH  and 132 healthy volunteers   and interpeduncular cistern , all parts of the subarachnoid spaces showed significantly lower mean f values in the iNPH group, compared with the healthy controls aged ≥ 60 years. Among the three age groups in healthy controls, the mean f values in the cerebral aqueduct, upper and middle parts of 4th ventricle, bilateral foramina of Luschka, ambient cistern, Sylvian fossa, Sylvian sulcus, and superior frontal sulcus increased significantly with increasing age , total volume of the subarachnoid spaces (0.43 and 0.34), Evans index (0.30 and 0.32), Z-Evans index (0.62 and 0.48), and negatively correlated with the BVR at AC (-0.62 and -0.47), BVR at PC (-0.60 and -0.47), and callosal angle (-0.49 and -0.42).In the 45 ROIs, the mean f value in the anterior part of the 3rd ventricle was the most negatively correlated with the ventricular volume (Pearson’s correlation coefficient: − 0.62), Z-Evans index (− 0.56), and the most positively correlated with the BVR at AC (0.54), and callosal angle (0.53). Conversely, the mean  D* were not significantly different between any two groups in any locations.Other parameters of ADC, D, andf value calculated by IVIM MRI is useful as a quantitative value of incoherent motion of the CSF. The fact that the IVIM parameter, f, measures CSF movements has been reported,[f values being measured both in the whole ventricles and subarachnoid spaces. The mean f values in all parts of the lateral ventricles and anterior part of the 3rd ventricle were significantly decreased in the iNPH group compared with the healthy group. These findings suggest that the CSF around the ventricular walls of the lateral ventricle flows rarely in iNPH because of a reduction in brain pulsations and a weakness or dysfunction of ciliary movements of ependymal cells on the ventricle surfaces [f value in the bilateral foramina of Luschka was significantly higher in the iNPH group than in the healthy group, although the values in the foramen of Magendie were high in both groups. Previous studies on CSF motions measured by conventional phase-contrast MRI and four-dimensional flow MRI have shown a significant increase in CSF stroke volumes at the cerebral aqueduct, foramen of Magendie, and foramen magnum in the iNPH group compared with the healthy group [IVIM MRI with low multi-b DWI could visualize and quantify the small pulsatile complex CSF motion that could not be evaluated by conventional flow-related MRI. Because IVIM MRI does not require synchronization of heartbeat or respiration, it has the potential to provide an overview of all CSF movements driven by arterial pulsations, brain pulsations produced by the cerebral blood circulation, respiration, and coordinated directional beating of the motile cilia, other than head movements. In addition, the mean reported,, 23, 36 surfaces , 2, 7. Thy group , 18. Howf values in the Sylvian fissure, which contains the middle cerebral arteries increased gradually with increasing age, whereas those were significantly lower in the iNPH group. The increase in pulsatile CSF motion in the Sylvian fissure with aging would be associated with the increased pulsatile blood flow in cerebral arteries due to aortic stiffness [2 [Compared with the healthy aging brain, the iNPH had a small amount of the CSF that barely flows in the central sulcus and marginal sulcus because of compression by the simultaneous expansion of the ventricles and Sylvian fissure toward the top of the head , 34, 37.tiffness , and thetiffness , 14, Taofness [2 .IVIM MRI has several advantages compared with the four-dimensional flow MRI or time-SLIP MRI. The most important advantage is a short acquisition time of approximately 2 min in this study. The quantitativeness of CSF motion in a wide range of flow velocity and wide area including the whole ventricles and subarachnoid spaces is also an important advantage. Therefore, IVIM MRI is a potentially useful and convenient technique for the evaluation of CSF dynamics. The disadvantages of IVIM MRI are its low resolution and inability to measure the flow direction of the CSF movements.f value between iNPH and healthy aging brain. Second, how much the f value of the CSF reflects the flow velocity was not evaluated. Le Bihan et al. reported that the f value of water decreases as its flow velocity decreases, but no linear relationship was observed in the phantom study [f value on IVIM MRI, especially in a small lumen structure such as the cerebral aqueduct.This study has some other limitations. First, the distributions of gender and age in the healthy controls aged ≥ 60 years did not match those in the iNPH group. The mean age in the iNPH group was significantly higher than that in the healthy controls aged ≥ 60 years group. A sufficient number of older controls could have shown more clearly the difference in om study . Third, f value on IVIM MRI is a potential index useful for evaluating complex CSF motion, although their direction and flow velocity could not be examined. Quantitative measurement of small CSF motions in the whole intracranial CSF spaces may contribute to the elucidation of the CSF dynamics and glymphatic function in iNPH and aging effects. We hope to establish a simulation model of the intracranial biological and metabolic environment by integrating f values on IVIM MRI and 3D-flow velocities on 4D Flow MRI in addition to 3D morphology information.IVIM MRI could visualize and quantify the small pulsatile complex motion of the CSF in the whole intracranial CSF spaces, including the central sulcus. The mean


Background: Obstructive sleep apnea syndrome (OSAS) is a widespread respiratory disease that is associated with recurrent breathing intermissions at night. The corresponding oxidative stress triggers a low-grade systemic inflammation which leads to alterations of different immune cells in the peripheral blood. The current standard treatment for OSAS is continuous positive airway pressure (CPAP), whereas hypoglossal nerve stimulation (HNS) has been established as a second-line treatment option for CPAP failure. The aim of the study was to investigate the influence of HNS for OSAS patients on the distribution and differentiation of circulating monocyte subsets in connection with the clinical parameters. Materials and Methods: Therefore, a detailed analysis of the distribution of CD14/CD16 characterized monocyte subsets in the peripheral blood of OSAS patients before and after HNS therapy was performed by flow cytometry. Furthermore, values of BMI (body mass index), ODI (oxygen desaturation index), and ESS  were measured. Results: These OSAS patients significantly improved AHI and ESS scores under HNS. In addition, HNS revealed the potential to ensure normal distributions of blood monocyte subsets and even improved the monocyte dynamics in selected OSAS patients, but there were no significant correlations with AHI, ODI, HNS usage, and daytime sleepiness. Conclusions: We conclude that HNS-related positive effects on the oxygenation of the peripheral blood as well as affect the distribution of circulating monocyte subsets, but clinical OSAS correlations are missing. Far more individual clinical, cellular and molecular factors are involved in this sensitive and complex regulatory network and have to be elucidated in further studies. OSAS is characterized by a nocturnal reduction (hypopnea) or total stoppage (apnea) of the airflow in the upper airways and subsequent reoxygenation . In addi++CD16− classical monocytes in OSAS patients in correlation with increased abundances of both CD16+ monocyte subsets and a disturbed PD-1/PD-L1 crosstalk with peripheral blood T cells compared to healthy individuals [OSAS-associated intermitted hypoxia and oxidative stress are known to induce low-grade systemic inflammation and trigger increased activity of different types of immune cells, for example, lymphocytes and monocytes, and increased levels of pro-inflammatory cytokines and surface adhesion molecules ,12,13,14ividuals .++CD16− “classical” monocytes are classified as “naïve-like” monocytes. The CD14+CD16+ “intermediate” and CD14dim+CD16+ “non-classical” monocyte subsets are more differentiated and pro-inflammatory monocytes that reveal specific immune functions such as viral defense and patrolling [+ subsets have been associated with different acute and chronic inflammatory diseases [Monocytes come from bone marrow hematopoietic stem cells and are part of the mononuclear phagocyte system . They catrolling ,24. In hdiseases ,26. The diseases . Furtherdiseases . HoweverPatients with OSAS were selected, implanted, and examined during follow-up at the Department of Otorhinolaryngology, University Hospital Schleswig-Holstein, Campus Luebeck, after their written informed consent. The study was approved by the ethics committee of the University of Luebeck  and performed according to the ethical principles of the WMA Declaration of Helsinki.Blood samples were obtained from OSAS patients before HNS implantation and after 6 to 12 months after surgical treatment. BMI (body mass index), AHI (apnea–hypopnea index), ODI (oxygen desaturation index), and HNS usage time were recorded before and after HNS therapy. Additionally, daytime sleepiness of OSAS patients was evaluated before and after HNS treatment using the established Epworth Sleepiness Scale (ESS) questionnaire , which mg for 5 min and supernatant was discarded. Next, cell sediments were resuspended in 100 µL fresh PBS and analyzed by flow cytometry. Flow cytometry was performed using a MACSQuant 10 flow cytometer  and raw data were analyzed with FlowJoTM software version 10.0 .Peripheral blood samples were collected by venipuncture into sodium citrate containing S-Monovette . Within 4 h after blood collection, 20 µL of citrate blood was diluted in 80 µL phosphate-buffered saline (PBS). Blood cells were stained with the listed antibodies: CD45-PE, CD14-FITC, CD16-BV-510, HLA-DR-APC-Cy7, and CD3-PerCP . After 25 min staining in the dark, 650 µL RBC Lysis Buffer (Biolegend) was added, and samples were further incubated for 20 min. Afterward, the samples were centrifuged at 400× t-tests for pairwise comparison of data before and after HNS treatment. The correlation between different clinical or cellular parameters was calculated using multivariate regression with Pearson correlation coefficient. p < 0.05 (*), p < 0.01 (**), and p < 0.001 (***).Statistical analyses were conducted using GraphPad Prism Version 7.0f  and paired Student’s In this study, we analyzed the abundance of blood monocyte subsets of 16 OSAS patients  with a median age of 56.8 years. Blood samples were collected from OSAS patients before HNS surgical treatment as well as after 6 to 12 months of HNS therapy. BMI (body mass index), AHI (apnea–hypopnea index), ODI (oxygen desaturation index), and HNS usage time were measured before and after HNS therapy.2), whereas seven patients were overweight (BMI 26 to 30 kg/m2), and seven had adiposity I° (BMI 31to 35 kg/m2).Initial ESS values showed a mean of 13.9 points, whereas values below 11 are considered normal. About 44% of the patients suffered from a moderate (AHI 15–30/h) and 56% presented a severe OSAS (AHI ≥ 30/h). According to WHO guidelines two patients displayed a normal weight  was assessed by telemetry read-out from the implant. Data revealed an overall average use of 45.8 h per week (range 13 h to 67 h), whereas 13 of 16 examined patients used HNS for at least 4 h per night which is considered sufficient for successful therapy with regard to daytime sleepiness and quality of life. Three patients revealed an HNS usage time of less than 4 h per night. Further correlation analysis revealed significant correlations between HNS usage time (h/week) and measured AHI and ODI values, respectively .++CD16− , CD14++CD16+ (intermediate) and CD14dim+CD16+  monocyte subsets prior and 6 to 12 month after surgical HNS treatment. The gating strategy of CD14- and CD16-defined monocyte subsets was performed as published before [We analyzed the abundances of CD14d before . All anaThus, most patients (n = 10) revealed a normal distribution of blood monocyte subsets prior to HNS treatment. Six patients showed a severe drop in classical monocytes accompanied by an increase in intermediate and non-classical monocytes prior to HNS treatment. After 6 to 12 months of HNS treatment flow cytometric measurements revealed a reduced number of patients (n = 3) with monocyte subset alterations .Additional individual patient-related investigations identified a significant reconstitution of the monocyte subset abundances of five OSAS patients  and unchanged levels of one patient (O71) upon HNS therapy for at least 6 months. On the other hand, flow cytometric analysis revealed a significant drop in classical monocytes accompanied by increased abundances of intermediate and non-classical subsets in two OSAS patients  after HNS therapy .Next, correlation analysis between the different initial clinical parameters measured in OSAS patients prior to HNS treatment and the identified monocyte subsets distribution was performed with the Pearson correlation coefficient. Data revealed no significant overall correlations between monocyte subset abundances and BMI, AHI, ODI, or ESS, respectively .In summary, our data indicate that CPAP pretreated OSAS patients who did not tolerate this therapeutic option, revealed significantly improved AHI and ESS values upon HNS treatment. Furthermore, HNS treatment has the potential to ensure normal distributions of blood monocyte subsets and even improve the monocyte dynamics in certain OSAS patients. On the other hand, two patients revealed a drop in classical monocyte percentages, without any significant correlation with OSAS-related clinical parameters.+ subsets [+ monocyte subsets has been linked to various inflammatory conditions [The aim of the present study was to investigate the influence of HNS therapy on percentages of monocyte subsets in the peripheral blood of OSAS patients using flow cytometry. In a recent study, we have shown that OSAS leads to a significant decrease in circulating classical monocytes associated with increased percentages of the CD16 subsets . An incrnditions , whereasnditions . OSAS-renditions . The impnditions . Severalnditions ,32,33.It is well known that there is a coherence between obesity and obstructive sleep apnea syndrome (OSAS). OSAS gives rise to reduced physical activity and metabolic dysfunction and thus promotes obesity. The other way round, obesity is a major risk factor for OSAS . The synWe have recently shown, that OSAS patients revealed a significant restoration of monocyte subsets and monocytic PD-L1 expression upon CPAP treatment . The preWe found a normal distribution of blood monocyte subsets in the majority of CPAP pretreated OSAS patients which could be successfully obtained over the analyzed period of 6 to 12 months of HNS treatment. Here, it is unclear what time period is needed for diminishing the CPAP effect, even in insufficient but minimal usage before HNS implantation. Further, five patients revealed decreased levels of classical monocytes prior to HNS treatment and a significant improvement after 6 to 12 months of therapy. These findings are most likely associated with better oxygenation at night and reduced oxidative stress as seen by the improved AHI. On the other hand, one patient showed no effects and two patients revealed worsened values of monocyte subset abundances, although these patients also revealed improved AHI and ODI values. Overall correlation analysis did not reveal significant correlations between monocyte distribution and the different clinical parameters measured in OSAS patients. These data suggest that in addition to the investigated clinical parameters BMI, AHI, or ODI, many other clinical, as well as individual molecular factors and comorbidities such as atherosclerosis, diabetes, fatty liver or chronic inflammations, must be taken into account in further future investigations in larger patient cohorts. Additionally, the normalization of the monocyte patterns which we found in PAP therapy  needs a A limitation of our study is the relatively small patient cohort analyzed. Further comprehensive investigations on larger cohorts of OSAS patients are required to better understand the interplay of circulating immune cells and the different clinical parameters of HNS therapy. A larger patient cohort could also identify further correlations between monocyte subset abundances and clinical parameters such as BMU, AHI, or ODI. Our data underline that respiratory support of OSAS patients using HNS is able to counteract and stabilize the oxidative stress-related imbalance on circulating monocytes whereas the responsible molecular mechanisms remain elusive. We assume that improved oxygenation of the peripheral blood in response to HNS treatment as well improves the distribution of circulating monocyte subsets, but that a holistic view of the clinical, cellular, and molecular individual parameters is required to understand the mechanisms of OSAS-related immune alterations and their treatment.


The identification of molecular biomarkers in CSF from individuals affected by Huntington disease may help improve predictions of disease onset, better define disease progression and could facilitate the evaluation of potential therapies. The primary objective of our study was to investigate novel CSF protein candidates and replicate previously reported protein biomarker changes in CSF from Huntington disease mutation carriers and healthy controls. Our secondary objective was to compare the discriminatory potential of individual protein analytes and combinations of CSF protein markers for stratifying individuals based on the severity of Huntington disease. We conducted a hypothesis-driven analysis of 26 pre-specified protein analytes in CSF from 16 manifest Huntington disease subjects, eight premanifest Huntington disease mutation carriers and eight healthy control individuals using parallel-reaction monitoring mass spectrometry. In addition to reproducing reported changes in previously investigated CSF biomarkers , we also identified novel exploratory CSF proteins  whose levels were altered in Huntington disease mutation carriers and/or across stages of disease. Moreover, we report strong associations of select CSF proteins with clinical measures of disease severity in manifest Huntington disease subjects  and with years to predicted disease onset in premanifest Huntington disease mutation carriers . Using receiver operating characteristic curve analysis, we identified PENK as being the most discriminant CSF protein for stratifying Huntington disease mutation carriers from controls. We also identified exploratory multi-marker CSF protein panels that improved discrimination of premanifest Huntington disease mutation carriers from controls , early/mid-stage Huntington disease from premanifest mutation carriers , and late-stage from early/mid-stage Huntington disease  compared with individual CSF proteins. In this study, we demonstrate that combinations of CSF proteins can outperform individual markers for stratifying individuals based on Huntington disease mutation status and disease severity. Moreover, we define exploratory multi-marker CSF protein panels that, if validated, may be used to improve the accuracy of disease-onset predictions, complement existing clinical and imaging biomarkers for monitoring the severity of Huntington disease, and potentially for assessing therapeutic response in clinical trials. Additional studies with CSF collected from larger cohorts of Huntington disease mutation carriers are needed to replicate these exploratory findings. et al. report novel multi-marker CSF protein combinations that accurately discriminate between individuals based on Huntington’s disease mutation status and disease severity. These exploratory CSF biomarker panels may improve the accuracy of disease-onset predictions and complement clinical and imaging biomarkers for monitoring disease severity and therapeutic response.Caron   HTT gene that codes for an abnormal polyglutamine tract in the huntingtin protein (HTT).1 Polyglutamine-expanded mutant huntingtin (mHTT), the primary pathogenic cause of HD, leads to the progressive loss of neuronal populations in the striatum, as well as other structures of the basal ganglia and the cerebral cortex.2–7Huntington disease (HD) is an autosomal dominant neurodegenerative disease caused by a cytosine–adenine–guanine (CAG) expansion in the 8 Prior to clinical diagnosis, there is a premanifest or prodromal stage of HD when cellular dysfunction and progressive neurodegeneration are occurring in the brain but no overt symptoms are present. Age-of-onset, a time point when HD mutation carriers develop unequivocal motor signs of HD, is inversely correlated with CAG repeat length in expanded HTT,9 enabling broad predictions of disease onset.10 However, CAG repeat length only accounts for 50–60% of the variability,11 with other genetic and environmental factors reported to modify age-of-onset.12–15HD typically manifests in the clinic as an adult-onset disease with affected individuals presenting with cognitive, motor and psychiatric disturbances.HTT gene and its products, or downstream processes associated with the pathogenesis of HD, are currently in clinical development. Such therapies may be most effective if intervention is initiated prior to clinical onset and significant neurodegeneration in the brain.To date, there are no approved therapies to delay the onset or slow the progression of HD. Therapeutic approaches targeting the cause of HD, the CAG expanded 17 and imaging-based19 biomarkers for monitoring disease progression and assessing the efficacy of candidate therapies in HD clinical trials.CSF is an accessible biofluid whose molecular composition reflects structural and functional changes in the brain, making it a promising biofluid for biomarker discovery in HD and other neurodegenerative disorders. In HD, CSF biomarkers may offer the potential to monitor cell-type and/or pathway-specific pathophysiological alterations in the CNS over the natural history of the disease. Sensitive CSF biomarkers that reflect early cellular dysfunction or neurodegeneration in the brain during the premanifest stage of HD may help improve the accuracy of disease-onset predictions and could potentially guide the appropriate timing for therapeutic intervention. Moreover, such biomarkers could be used to complement existing clinical21). However, only mHTT22–26 and NEFL27–32 have been used in HD clinical trials.Several promising molecular biomarkers have been identified in CSF and/or blood that is altered in HD  delivered by intrathecal infusion, suggesting that CSF mHTT could be a valuable biomarker to assess target engagement in the CNS.33 However, preliminary findings from the halted Phase III trial evaluating the efficacy of tominersen (NCT03761849) suggest that a reduction of CSF mHTT alone may not predict clinical benefit.CSF mHTT increases with disease progression27–31 as well as other neurological diseases (reviewed in34). In HD, NEFL levels in biofluids are correlated with clinical and imaging measures of disease27 and are a strong prognostic biomarker of disease onset, progression and brain atrophy in HD patients.29 Notably, NEFL is being used in HD clinical trials as an exploratory biomarker to monitor disease progression and to assess therapeutic efficacy. However, it remains unknown if NEFL in biofluids will respond to candidate therapies in a manner that reflects clinical benefit.NEFL in biofluids is a biomarker of neuronal injury, with elevated NEFL levels in CSF and blood reported in HD,35–37 allowing for reliable monitoring of CSF proteins with high specificity and sensitivity. An initial list of protein candidates was prioritized based on existing literature demonstrating altered levels in the CSF of HD mutation carriers, including C1QC,38 C4B,38 CHI3L1 ,39 CLU,41 CTSD,38 FAT2,41 NEFL, PDYN,42 PENK,41 and TTR.43 Additional protein candidates were selected that, to our knowledge, have not been previously measured in HD CSF but were either reported to have altered expression in the striatum of HD patients,44–46 animal models of HD,48 or have been implicated in the pathogenesis of HD.50We conducted a hypothesis-driven analysis of 26 pre-specified proteins in the CSF from 16 manifest HD (manHD) patients, 8 premanifest HD (preHD) and 8 control individuals using nanoflow liquid chromatography-coupled parallel-reaction monitoring mass spectrometry (nanoLC-PRM-MS). This methodology allows for the simultaneous identification and quantification of more than 30 peptides at attomole concentrations within a single run,In this study, we sought to investigate novel CSF protein candidates and replicate previously reported molecular biomarker changes in CSF from HD mutation carriers and healthy controls. We assess potential associations between levels of CSF protein analytes, as well as correlations of candidate CSF proteins with clinical measures of disease severity. Finally, we compare the discriminatory potential of individual CSF proteins and combinations of CSF protein markers to assess their sensitivity and specificity for stratifying subjects based on HD mutation status and disease severity.HTT CAG repeat expansions >36 and a Unified Huntington’s Disease Rating Scale (UHDRS) diagnostic confidence level (DCL) < 3, whereas manHD was defined as individuals with a HTT CAG repeat expansion >36 and a DCL = 4. HD mutation carriers refer to both preHD and manHD individuals. Healthy control individuals with no neurological abnormalities and HTT CAG repeat lengths <36 were selected to span the range of ages of HD mutation carriers.A hypothesis-driven analysis of protein analytes was performed in CSF from 16 manHD, eight preHD and eight healthy control individuals recruited through the University of British Columbia’s Centre for Huntington Disease. PreHD was defined as individuals with 16 CAG-age product (CAP) score or disease burden score was calculated using the formula: (CAG length—35.5) × age.51 Predicted age-of-onset estimates in preHD individuals were calculated according to the formula: 21.54 + EXP(9.556—0.146 CAG) and years to predicted disease onset was estimated by subtracting the individual’s age at the time of CSF collection.10Clinical outcomes including total functional capacity (TFC), total motor score (TMS), verbal fluency (VF), symbol digit modality test (SDMT), and Stroop word reading (SWR) were scored by a trained neurologist using the UHDRS.CSF samples from Huntington disease mutation carriers and control individuals were collected at the University of British Columbia’s Centre for Huntington Disease. CSF was obtained by lumbar puncture, examined qualitatively by microscopy and centrifuged to remove cells. The acellular supernatant was aliquoted and frozen at −80°C.All CSF samples were collected under an approved protocol (H14-03131) in accordance with the guidelines of the institutional review board of the University of British Columbia and with the full informed consent of the subjects.53 and cleaned using detergent removal spin columns  as per the manufacturer’s protocol. The samples were acidified with 1% formic acid (EMD Millipore) and loaded on a reversed-phase UltiMate™ 3000 RSLC-nano System with ProFlow Meter (Thermo Fisher) coupled with Orbitrap Eclipse™ Tribrid™ mass spectrometer (Thermo Fisher) for analysis with a nano-electrospray interface operated in positive ion mode. Prior to PRM analysis, 112 peptides corresponding to 2–15 peptides per protein (https://skyline.ms) and MatchRx software version 3.0 as previously described.53 The extracted peptide intensities (peak areas) were normalized against a median intensity value calculated from all peptide intensities in each run.A panel of 26 proteins was measured in CSF by nanoLC-PRM-MS. For sample preparation, each CSF sample was reduced, alkylated, and trypsin digested as previously described protein  were ide54 using the Caret55 and MixOmics56 packages for modelling. Alpha values of <0.05 were considered significant for all analyses.Statistical analyses were performed using GraphPad Prism 9 (GraphPad) and R statistical software,t-test. Differences in gender distributions between groups were assessed using Pearson’s χ2 test.Comparisons of demographic characteristics and clinical measures between groups were assessed by ANOVA and Fisher’s least significant difference test. Mean values ± standard deviation (SD) for each group are presented. CAP scores were compared between preHD and manHD individuals using a two-tailed t-tests, respectively. The association of CSF protein levels with CAG repeat length in all HD mutation carriers was assessed using Pearson’s correlation. Only age was found to be significantly associated with CSF protein levels and was included as a covariate for all subsequent analyses. Normalized CSF protein concentrations for all individuals were adjusted for age using linear regression.Age, sex and CAG repeat length were considered potential confounding factors for comparisons of CSF protein levels between groups. The relationship of normalized CSF protein concentrations with age and sex was evaluated in control individuals using either Pearson’s correlation or independent unpaired P-values and the percentage of events in 1000 bootstrap repetitions that the variable was selected with P < 0.05 are reported for each comparison. Odds ratios (OR) and 95% confidence intervals (CIs) for statistically significant comparisons are presented.Pre-specified analyses comparing age-adjusted CSF protein levels between controls and all HD mutation carriers were performed using general linear models (GLMs) bootstrapped with 1000 repetitions. F statistics, degrees of freedom, and P-values for each comparison are reported. Post hoc tests between disease stages were performed using Tukey’s test to correct for multiple comparisons and mean difference (MD) effect sizes, 95% CI and P-values for statistically significant comparisons are reported.Comparisons across disease stages were performed by analysis of covariance (ANCOVA) including age as a covariate, and ρ or Pearson’s r) from ±0.50 to ±1 were considered strong correlations, ± 0.30 to ±0.49 were considered moderate correlations and ±0.10 to ±0.29 were considered weak correlations. P-values <0.05 define correlations significantly different than 0.Associations of clinical measures of disease severity with CSF protein levels were assessed in manHD individuals using Spearman’s partial rank correlation including age as a covariate, with the exception of CAP score which was evaluated in all HD mutation carriers using unadjusted data. The relationship of CSF protein levels with years to predicted disease onset was assessed in preHD subjects using Pearson’s correlation on unadjusted data. Associations between each of the 26 CSF protein analytes were evaluated in all HD mutation carriers using Pearson’s partial correlation including age as a covariate. Coefficient values  and specificity  of each individual CSF protein for discriminating between disease groups/stages were assessed using receiver operating characteristic (ROC) curve analysis, and the corresponding area under the curve (AUC) values were computed as a measure of discriminatory performance or accuracy. CSF proteins with AUC = 0.8–1 were considered as being classifiers with high discriminatory ability, values of 0.7–0.8 as having moderate discriminatory ability, and 0.6–0.7 as classifiers with weak discriminatory ability. AUC values, AUC 95% CIs and P-values are reported.Sparse partial least squares discriminant analysis (sPLS-DA) is a supervised machine learning method that examines the discriminative capacity of multi-dimensional data while selecting features best able to classify samples. For each comparison, the sPLS-DA model was tuned to find the appropriate number of components and variables using 50 × 3-fold repeated cross-validation. Then, a final sPLS-DA model was fit using the optimal number of proteins for the respective optimal number of components, as determined during the tuning phase to avoid overfitting. This entire process was bootstrapped with 1000 repetitions to assess the variability and stability of the final models. ROC curves for the final sPLS-DA model were then generated and AUC values, AUC 95% CI and 58 Data sets comprising age-adjusted values from up to 10 CSF proteins were uploaded into the web-based interface, and analysis was performed without further processing of the data. Test-signal cut-offs, as well as sensitivity and selectivity thresholds, were adjusted for different group comparisons. ROC curves with combinations of up to five proteins were plotted and AUC values are reported.Multi-marker ROC curves were generated using the CombiROC analytical tool.P = 0.011). Healthy controls were selected to span the age range of HD mutation carriers and no significant age differences were observed compared with either preHD (P = 0.119) or manHD subjects (P = 0.398). There were no significant differences in sex distributions between groups  or CAG repeat lengths between preHD and manHD patients (mean CAG ± SD = 43.64 ± 1.51 versus 44.50 ± 2.78. P = 0.196).Study participant demographics and clinical scores are summarized in We pre-specified 26 protein analytes to measure in CSF from controls and HD mutation carriers, including previously investigated CSF proteins, as well as exploratory candidate proteins that, to our knowledge, have never been investigated in HD CSF .We utilized a nanoLC-PRM-MS method to quantify unique peptides derived from each of the 26 CSF proteins with high sensitivity and specificity. For each protein, 2–15 unique peptides were measured in parallel. A complete list of peptide sequences measured by nanoLC-PRM-MS is presented in P = 0.031), GNAL , IGF2 , and IGHG1  were significantly increased, whereas CTSD , PDYN , and PENK  were significantly decreased in CSF from HD mutation carriers compared with controls. We also observed trends towards increased levels DRD1  and ALB , and decreased levels of BDNF  in HD mutation carriers but these did not reach statistical significance.We first compared age-adjusted values of CSF proteins in all HD mutation carriers  and controls using bootstrapped GLMs . We founpost hoc analysis using Tukey’s test to correct for multiple comparisons  and manHD groups (DCL = 4), and the manHD group was further stratified based on TFC score into early/mid HD (TFC > 5) and late HD (TFC < 5) groups. A comparison of age-adjusted CSF protein levels was performed between controls, preHD, early/mid HD and late HD groups by ANCOVA followed by parisons . We idenparisons .P = 0.010), and late HD compared with early/mid HD (##P = 0.008). CNR1 levels were significantly reduced in late HD compared with early/mid HD (##P = 0.008) and a strong trend towards a reduction in late HD compared with controls was observed but did not reach post hoc significance .Levels of C1QB were significantly decreased in late HD compared with controls , whereas IGF2 (P = 0.012), IGHG1 (P = 0.004) and NEFL (P = 0.002) were significantly increased in late HD compared with control individuals. Trends towards increased NEFL in early/mid HD compared with controls  and late HD compared with preHD  were observed but did not reach post hoc significance.IDO1 levels were significantly decreased , early/mid HD , and late HD compared with controls .Levels of PDYN  and PENKP = 0.042) and showed a trend towards decreased levels in late HD compared with early/mid HD groups . BDNF levels showed a strong trend towards a reduction in late HD compared with controls, but this difference did not reach statistical significance .PPP1R1B  levels were significantly altered across disease stages , NEFL , IDO1 , and PENK  showed significant correlations with this measure of disease burden.Correlations of CSF protein levels with CAP score, an age-dependent measure of cumulative exposure to CAG expanded carriers . C4B , PPP1R1B , and PDYN  were strongly correlated with TFC in manHD individuals, whereas BDNF , IDO1  and IGF2  showed moderate correlations. TTR  showed a strong significant negative correlation, and DRD2  and IGF2  were moderately correlated with TMS in manHD subjects.The relationship of CSF protein levels with clinical measures of disease severity in manHD individuals was evaluated using Spearman’s partial rank correlation including age as a covariate . CNR1 , CNR1  and IDO1  were strongly correlated with VF score, whereas TTR  and PPP1R1B  showed moderate positive correlations. PDYN , CNR1 , PPP1R1B  and C1QB  showed strong significant correlations, whereas BDNF , PENK  and TTR  showed moderate correlations with SDMT in manHD individuals. Finally, NEFL  and TTR  showed strong correlations with SWR score, whereas PDYN  and IGF2  were moderately correlated with this clinical measure in manHD individuals.PDYN (10 in preHD mutation carriers (mean years to predicted onset ± SD = 8.41 ± 8.04) using Pearson’s correlation and found that ALB , C4B , CTSD , IGHG1  and TTR  showed strong associations with these estimates , accurately classifying 79.2% of HD mutation carriers and 100% of control individuals. PENK was also the most discriminant CSF protein for distinguishing preHD from controls (P = 0.005), correctly classifying 75% of preHD and 100% of control individuals. CHI3L1 showed moderate discriminatory power for distinguishing between manHD and preHD individuals (P = 0.111), accurately classifying 93.8% of manHD but only 62.5% of preHD individuals.PENK showed the strongest discriminatory ability of any CSF protein for distinguishing between HD mutations carriers and controls (24 We observed that NEFL showed a strong discriminatory ability for distinguishing between HD mutation carriers and controls (P = 0.009), but relatively weak discrimination of manHD from preHD subjects in our cohort (P = 0.142). By comparison, PENK showed a superior discriminatory ability to NEFL for distinguishing between HD mutation carriers and controls, but this did not reach statistical significance (P = 0.121).CSF NEFL was previously shown to have high accuracy for stratifying HD mutation carriers from controls and manHD from preHD individuals.We next performed sPLS-DA to evaluate the discriminatory potential of combining all 26 CSF proteins. The relative discriminatory importance of individual CSF proteins to each sPLS-DA model is presented in P = 0.0006), similar to what was observed with PENK alone , similar to PENK alone , superior to CHI3L1 alone , that could provide the highest discriminatory ability for stratifying individuals based on HD mutation status and disease severity. Each of the most discriminant multi-marker combinations is presented in We next performed a combinatorial ROC curve analysis using the combiROC analytical toolThe combination of PENK, IGHG1, and GNAL was able to accurately classify 88% of HD mutation carriers and 100% of control individuals, and improved discriminatory performance . Notably, fourteen unique combinations of four CSF proteins, including combination 4A: PPP1R1B, TTR, CHI3L1 and CTSD, showed perfect classification of preHD and early/mid HD individuals , whereas we identified five unique combinations of five CSF proteins that perfectly classified individuals with late HD and early/mid HD, including combination 5A: CNR1, PPP1R1B, BDNF, APOE and IGHG1  highlighting its utility as a biomarker of neuronal injury, but one that is not specific to HD. NEFL is currently being used in HD clinical trials as an exploratory biomarker of disease progression and to assess therapeutic efficacy.Multiple studies have reproducibly shown increased levels of blood and CSF NEFL in HD.P = 0.002), and trends towards elevated NEFL in early/mid HD compared with controls (P = 0.073) and late HD compared with preHD (P = 0.068). We did not observe a significant increase of CSF NEFL in manHD compared with the preHD, as reported previously using immunoassays to measure NEFL.30 We did however measure significant associations of CSF NEFL with CAP (ρ = 0.44) and SWR scores (ρ = −0.50).30 Our findings support the continued use of NEFL as an exploratory biomarker for monitoring disease severity in clinical trials for HD.We found NEFL levels to be significantly increased in the CSF of late HD subjects compared with control individuals , early/mid HD (P = 0.012) and late HD (P = 0.0002) compared with controls and observed moderate correlations with CAP score (ρ = −0.48) and SDMT (ρ = 0.42).PENK and PDYN are highly expressed in distinct striatal medium spiny neuron (MSN) populations42 This study found that levels of PDYN were not decreased in other neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, suggesting that changes of CSF PDYN may be unique to HD.42 We found PDYN to be significantly reduced in preHD (P = 0.004), early/mid HD (P = 0.012) and late HD (P = 0.0003) compared with controls. PDYN also showed strong associations with TFC (ρ = 0.53), VF (ρ = 0.55) and SDMT (ρ = 0.57) in manHD individuals. We postulate that reduced CSF PENK and PDYN in preHD individuals may reflect early functional disturbances in the health of MSNs prior to disease onset and differential loss of specific MSN sub-populations at more advanced stages of HD.Reduced CSF PDYN was recently reported in manHD patients compared with controls using targeted LC-MS.60 Levels of CTSD in the CSF were reported in one study to be significantly decreased in HD mutation carriers by MS38 and in another to be unchanged between manHD, preHD and controls using PRM-MS.61 Consistent with these reports, we found CTSD to be significantly reduced in the CSF of HD mutation carriers compared with controls (P = 0.044) but not significantly changed across disease stages.CTSD is a lysosomal protease expressed in the brain that has been shown to promote the degradation of mHTT in primary neurons.38 C4B,38 CHI3L1,39 CLU,41 FAT241 or TTR43 protein levels in the CSF of HD mutation carriers compared with controls. These discordant findings could be due to differences in patient demographics and clinical characteristics, methodology used for the detection of protein analytes in CSF, and/or the specific peptides that were selected for analysis by PRM-MS in our study.In contrast to previous reports, we did not detect significant changes in C1QC,62 Levels of BDNF in the CSF were previously reported to be unchanged across HD stages using an immunoassay.63 We observed a strong trend towards a reduction of BDNF in late HD compared with controls (P = 0.053) and moderate correlations with TFC (ρ = 0.45) and SDMT (ρ = 0.48). These findings suggest that reduced CSF BDNF may reflect the depletion of BDNF production/release64 or even the loss of cortical neurons at advanced stages of HD.5 Additional studies to investigate CSF BDNF as a potential biomarker for HD may be warranted.BDNF is a growth factor required for the survival of various neuronal populations in the CNS and is downregulated in the caudate and putamen of post-mortem HD brains compared with age-matched controls.66 and IgG quotients,65 routinely used to measure blood–brain barrier (BBB)/blood–CSF barrier (BCSFB) dysfunction and intrathecal IgG production, were previously found to be unchanged in the CSF of HD mutation carriers compared with controls. Our data showed a strong trend towards increased ALB in HD mutation carriers compared with controls (P = 0.068) and a significant increase of CSF IGHG1 (heavy chain constant domain of IgG) in the late HD compared with controls (P = 0.004). The increased CSF albumin and IGHG1 could reflect neurovascular abnormalities and BBB/BCSFB dysfunction which have been reported in HD.67–69 Moreover, elevated CSF IGHG1 at advanced stages of HD may suggest increased local CNS IgG synthesis, a marker of CNS inflammation.CSF to blood ALB70 Reduced levels of GNAL have been reported in the caudate and putamen of HD patients.45 We found GNAL to be significantly elevated in the CSF of HD mutation carriers compared with controls (P = 0.043), which could reflect an increased release from degenerating striatal MSNs.In addition to reproducing reported changes in previously investigated CSF biomarkers, we also identified novel candidate CSF proteins whose levels were altered in HD CSF. GNAL, which is highly expressed in the basal ganglia, plays an important role in MSN dopamine signalling.71–73 Importantly, reduced IGF2 levels have been reported in the striatum and plasma from HD patients.50 We detected significantly elevated IFG2 levels in late HD compared with controls (P = 0.012), and moderate correlations with TFC (ρ = −0.40), TMS (ρ = 0.40), and SWR (ρ = −0.42) in manHD individuals. The unexpected increase of CSF IGF2 in HD mutation carriers is consistent with reports from Alzheimer’s disease.75 We postulate that elevated CSF IGF2 may reflect increased release from IGF2-producing cells  or potentially a compensatory neuroprotective mechanism in the brain.IGF2 is a regulator of neurogenesis, synaptic formation and spine maturation in the brain that plays a role in learning and memory functions.76 Early downregulation of CNR1 has been reported in the striatum of HD patients.44 Levels of CNR1 were decreased in late HD compared with controls (P = 0.055) and preHD (P = 0.108) and were significantly reduced in CSF from late HD compared early/mid HD (P = 0.008). Moreover, CSF CNR1 levels were strongly correlated with TFC (ρ = 0.58), VF (ρ = 0.52) and SDMT (ρ = 0.56) in manHD. Reduced CSF CNR1 could be a marker that reflects the loss of CNR1-expressing neurons in the basal ganglia at advanced stages of HD.CNR1 is highly expressed in the basal ganglia where it modulates synaptic functions involved in motor behaviour.77). In HD, upregulation of early complement activators and regulators from reactive microglia has been reported in the striatum of HD patients.78 We found CSF C1QB to be modestly increased in early/mid HD compared with preHD and significantly reduced in late HD compared with early/mid HD (P = 0.008) and controls (P = 0.010). Surprisingly, we did not find C1QC to be significantly altered, although similar trends in levels were observed. C1QB also showed a strong association with SDMT (ρ = 0.51) in manHD individuals. These findings suggest that CSF C1QB levels may reflect early HD-associated complement activation in the brain and potential dysregulation of this pathway at more advanced stages of disease.C1Q , a component of the complement C1 recognition complex of the classical pathway, is released from CNS cells in response to inflammatory stimuli in neurodegenerative diseases (reviewed in49 IDO1 levels were significantly decreased in late HD compared with controls (P = 0.020), and showed moderate to strong correlations with CAP score (ρ = −0.45), TFC (ρ = 0.43) and VF (ρ = 0.50). The reduction of IDO1 in the CSF could suggest dysregulation of the kynurenine pathway in the brain or it may be a marker of cell loss in the striatum in lateHD.IDO1, a rate-limiting enzyme in the kynurenine pathway, was reported to be upregulated and have increased activity in the striatum of an HD mouse model.Together our data suggest that GNAL, IGF2, CNR1, C1QB and IDO1 may represent promising CSF biomarker candidates that reflect distinct HD-associated pathophysiological alterations in the CNS.A secondary objective of our study was to compare the discriminatory potential of individual CSF markers and combinations of CSF markers for distinguishing individuals based on HD mutation status and disease severity. We identified PENK and PDYN as being the most discriminant individual CSF proteins for distinguishing HD mutation carriers from controls. Notably, PENK (AUC = 0.94) and PDYN (AUC = 0.84) each showed superior discrimination of HD mutation carriers from controls compared with NEFL alone (AUC = 0.81). Moreover, PENK (AUC = 0.92) also showed the highest discriminatory power for distinguishing preHD from controls. No individual CSF protein showed high discriminatory accuracy for distinguishing between preHD and manHD individuals in our cohort, with CHI3L1 (AUC = 0.70) showing only moderate discriminatory power.sPLS-DA models incorporating all 26 CSF markers used to stratify either HD mutation carriers and controls (AUC = 0.90) or preHD and controls (AUC = 0.88) showed discriminatory performances similar to PENK alone. In contrast, the combination of all CSF proteins improved the stratification of manHD from preHD (AUC = 0.95) compared with CHI3L1 (AUC = 0.70) or any other individual protein, highlighting the increased discriminatory value of combining multiple CSF markers.We also performed a combinatorial ROC curve analysis and identified exploratory multi-marker CSF panels with up to five proteins that, in all instances, showed superior discriminatory performance compared with individual proteins for distinguishing individuals based on HD mutation status and disease severity.The combination of PENK, NEFL and ALB showed perfect discrimination between preHD and control individuals in our cohort suggesting that changes in these CSF proteins represent early events in disease pathogenesis, prior to overt symptomatic onset. Furthermore, all eight lead three marker combinations included PENK, highlighting the importance of this protein for distinguishing between preHD and controls.The panel consisting of CHI3L1, C4B, IGHG1, and ALB showed high discriminatory power (AUC = 0.91) for distinguishing preHD from manHD individuals, with sensitivity and specificity superior to CHI3L1 alone (AUC = 0.70) and similar to that observed with all 26 CSF markers by sPLS-DA (AUC = 0.95). These data highlight the additive classification performance that is possible even when combining markers that individually have a weak or moderate discriminatory ability.r = 0.75), C4B (r = −0.74), CTSD (r = 0.66) and TTR (r = 0.86) were strongly correlated with years to predicted disease onset in preHD individuals.10 We postulate that panels of CSF markers could be used in conjunction with CAG repeat length to improve the accuracy of disease-onset estimates.Moreover, we identified 14 unique 4 marker CSF protein panels that showed perfect discrimination of early/mid HD from preHD individuals, including combinations of C4B, TTR, ALB, and CYCS, as well as PPP1R1B, C4B, TTR and CTSD. Notably, ALB  which is difficult to achieve with conventional assays (e.g. immunoassays).81 Although MS-based assays may not be practical or cost-effective for routine clinical use, the exploratory multi-marker CSF protein panels identified in this study could be used to help guide the design of multiplex immunoassays that would be more amenable to clinical practice. To enable this translation, longitudinal observational studies would be needed to quantify absolute concentrations of individual CSF proteins and define biomarker signatures in HD mutation carriers over the natural history of the disease. We also identified multiple unique CSF protein combinations that are different in composition but that show equivalent discriminatory performance for stratifying subjects based on disease severity which may provide additional flexibility for assay development and could help validation of such assays for clinical use.MS-based methods are capable of sensitive detection of proteins in biofluids, comparable to other analytical assays, but may provide superior specificity through the identification of multiple specific peptide sequences for any individual protein.The major limitation of our study was the relatively small number of CSF samples analysed. Replication studies with CSF collected from larger cohorts of HD mutation carriers  would be needed to validate our exploratory findings. Furthermore, studies to assess whether any of the candidate CSF proteins studied here are also altered in other biofluids (e.g. blood) may be warranted.In this study, we show compelling evidence to suggest that combinations of CSF markers can outperform individual markers for stratifying individuals based on HD mutation status and disease severity. We postulate that the multi-marker CSF protein panels defined herein may be useful for improving the accuracy of age-of-onset estimates for HD and complement clinical biomarkers for monitoring disease severity.fcac309_Supplementary_DataClick here for additional data file.


For the effect of CSF proteins, data shows an increased risk of death for spinal ALS patients as the value of CSF proteins increases. The same model replicated for CSF albumin yielded similar results. Statistical models determined that the lowest cut-off value for CSF proteins able to differentiate patients with a good prognosis and worse prognosis corresponds to CSF proteins ≥ 0.5 g/L . For the CSF albumin, the QAlb ≥0.65 is associated with elevated probability of death . High levels of QAlb are a bad prognostic indicator for the spinal phenotype, in addition to high CSF proteins levels that also act as a marker of poor prognosis.Amyotrophic lateral sclerosis (ALS) is a heterogeneous disease, both in its onset phenotype and in its rate of progression. The aim of this study was to establish whether the dysfunction of the blood–brain barrier (BBB) and blood–spinal cord barrier (BSCB) measured through cerebrospinal fluid (CSF) proteins and the albumin-quotient (QAlb) are related to the speed of disease progression. An amount of 246 patients diagnosed with ALS were included. CSF and serum samples were determined biochemically for different parameters. Survival analysis based on phenotype shows higher probability of death for bulbar phenotype compared to spinal phenotype ( Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that predominantly affects upper and lower motor neurons, producing focal onset motor deficits. The course of the disease is rapidly progressive, leading to death, usually due to respiratory failure, in three to five years from the onset of symptoms . A largeALS is a heterogeneous disease, both in its onset phenotype and in its rate of progression. Because of this, it is very important to find out what factors are associated with a good prognosis as well as with a bad prognosis. In addition to the importance this has for the patient and their environment, since it is often helpful for family planning, the prognosis of the disease at the time of diagnosis is also of great importance for clinical trials ,5.Currently, we have sufficient evidence of vascular involvement in ALS as another etiopathogenic mechanism. The alterations described at this level include endothelial cells, tight junctions, pericytes, aquaporin 4, matrix metalloproteinases and cytokines, as well as the expression of VEGF receptors ,7,8. TheC9ORF72 gene  years. The diagnostic delay from the onset of symptoms was 9.87  months. A percentage of 70.2% of the patients presented with spinal phenotype, 28.5% bulbar, and 1.24% respiratory; 8.1% of the patients presented pathological expansion (>30 repetitions) in the F72 gene .The analytical results for CSF proteins, cholesterol, creatine kinase (CK), CSF albumin, serum albumin and QAlb are detailed in p = 0.054). We performed a survival analysis based on the phenotype at the time of diagnosis. We observed that patients with bulbar phenotype at the onset of the disease had a higher probability of death compared to patients with spinal onset, with statistically significant differences   and 384.65 days (291.84) for patients with normal CSF protein, with a difference approaching statistical significance ( 0.0006) .In fact, the risk of death at a given time of a patient with a bulbar phenotype is 65.02%, greater than that for a spinal phenotype patient (HR 1.65 (95% CI 1.18 to 2.32) .p = 0.17 and 0.75, respectively). Next, we analyzed the patient’s death probability from the onset of symptoms based on whether the CK and cholesterol values were high or normal, and we did not find statistically significant differences  with respect to the mean (increased 0.15 with respect to 0.41), it was expected that the risk of death would be 22% (HR 1.22 (95% CI 1.05 to 1.43)) greater than if there had been no increase given. For the model adjusted for the interaction with the phenotype, in the case of patients with the spinal phenotype, the elevation of the CSF proteins had a significant effect (HR 1.26 (95% CI 1.03 to 1.54)); however, for patients with the bulbar phenotype, with the effect of the interaction at 0.78 (95% CI 0.56 to 1.07), there was no significant effect, with the HR at 0.98 (95% CI 0.58 to 1.65). In other words, if the value of the CSF proteins increased by one SD of the mean (increased 0.15 with respect to 0.41), and if the patient had a spinal phenotype, the increase entailed an increase in the risk of death of 25.66%. In contrast, with the bulbar phenotype, we did not observe a statistically significant effect .In the same manner, we analyzed the effect of elevated CSF albumin on patient survival using a crude and an adjusted Cox model and obtained results similar to those previously obtained using CSF proteins. For the crude model, if the CSF albumin value increased one standard deviation (SD) with respect to the mean (increased 118.2 with respect to 273.45), it could be expected that the risk of death would increase by 27.7% (HR 1.28 (95% CI 1.04 to 1.57).For the model adjusted for the interaction with the phenotype, in the case of patients with the spinal phenotype, the elevation of the CSF albumin had a significant effect of HR 1.66 (95% CI 1.22 to 2.26). However, for patients with the bulbar phenotype, with the effect of the interaction being 0.63 (95% CI 0.41 to 0.96), it did not have a significant effect, with the HR being 1.04 (95% CI 0.50 to 2.17). In other words, if the CSF albumin value increased by one SD compared to the mean (117.26 compared to 273.77), and if the patient had a spinal phenotype, this increase meant an increase in the risk of death of 66.12%. In contrast, if the patient had a bulbar phenotype, we did not observe a statistically significant effect .p-value = 0.1282). Given this, in the model used previously in which the patient’s death probability was directly proportional to the increase in CSF proteins, we successively increased the cut-off point until we reached statistically significant differences with the CSF protein cut-off value> 0.5 g/L; Log-rank test, p-value: 0.0189 , essential for synaptic function as well as for offering a form of protection against bloodborne pathogens . HoweverIn From a clinical point of view, we clearly see that a patient with a bulbar phenotype has a poor prognosis for the disease , but it Patients’ inclusion and clinical classification criteria: Medical records of patients who were diagnosed with ALS and who were undergoing quarterly check-ups in the multidisciplinary unit of motor neuron diseases at the Bellvitge University Hospital were reviewed. These patients were ambispectively followed. Later, patients with a diagnosis given within the period between 2012 and 2019 were included; they were followed up with prospectively from 2012 to 2022. All the patients included met the El Escorial criteria for a definite and/or probable category ,51. PatiALS patients were evaluated clinically according to the main signs at onset . We define spinal onset ALS as when the weakness starts in the lower or upper limbs. Clinical examination must show atrophy, weakness of muscles, fasciculations and hyperreflexia. In bulbar onset ALS, the disease starts with dysarthria, dysphagia and sometimes, tongue fasciculations. Disease spread involving the limbs and clinical examinations reveals the presence of limb hyperreflexia. In respiratory onset ALS, the patients begin with orthopnea or dyspnea, sometimes accompanied by mild spinal or bulbar signs. All the diagnoses were confirmed by electromyography and the monitoring of their evolution.Clinical variables: We calculated the diagnostic delay as the diagnosis date minus the start date, the start age as the start date minus the date of birth and the disease duration as the death date minus the start date.Cerebrospinal fluid analysis: Lumbar puncture (LP) was performed by neurologists in outpatient clinics, as LP is performed routinely in all patients with suspected motor neuron diseases to rule out other diseases of the peripheral nervous system. LP was performed in parallel to serum and plasma extraction and analysis in all patients after they had given informed consent. CSF was prospectively collected from patients undergoing lumbar puncture due to the clinical suspicion of motor neuron disease at the functional unit of amyotrophic lateral sclerosis (UFELA) of the Neurology Service of the Bellvitge University Hospital at the time of diagnosis. A routine analysis of CSF did not detect the presence of red blood cells in any case. In these patients, 1.5 ± 0.5 mL of CSF was collected in polypropylene tubes. The CSF was centrifuged at 3000 rpm for 15 min at room temperature. The supernatant was collected and aliquoted in volumes of 220 μL, and it was either used immediately for analysis in the laboratory of the same hospital or stored at −80 °C for future use. Results included glucose, proteins, cells, and albumin in cerebrospinal fluid (CSF), as well as cholesterol, creatine kinase, and albumin in blood serum. The albumin quotient (QAlb) was calculated with the formula QAlb = CSF albumin/serum albumin. The abnormality value for CSF proteins was established at ≥ 0.46 g/L according to the parameters of the clinical analysis laboratory of the Bellvitge Hospital .C9ORF72 was analyzed with PCR with subsequent fragment analysis and repeat primed-PCR. GGGGCC hexanucleotide with a repeat length of > 30 was used as the standard threshold for distinguishing between neutral and pathogenic expansions [Genetic analysis: DNA extraction was performed through peripheral blood obtained by venipuncture. The hexanucleotide expansion in pansions .C9ORF72. Age was introduced in the model as a time-dependent covariate, considering age at the time of onset and at the time of diagnosis. The application conditions of the models were validated and confidence intervals at 95% of the estimators were calculated whenever possible. All analyses were carried out with the statistical package R version 4.0.5 (2021-03-31) for Windows.Statistical analysis: The demographic and clinical profiles of included subjects were described by counts and percentages for categorical variables and the mean with standard deviation or the median with the first and last quartile for numerical variables. Cumulative incidence of death per 100 subjects and incidence per 1000 subjects a year were estimated using the onset symptoms as a baseline time. The Kaplan–Meier estimator of the probability of death by time was represented. Raw and adjusted hazard ratios (HR) were used to assess the association between death and a number of risk factors, such as phenotype, creatine-kinase (CK), cholesterol, albumin, and CSF protein levels. HR was estimated using a Cox regression model. Adjusting variables were age, sex and The best prognostic indicator of the spinal phenotype is QAlb. In the absence of QAlb, a level of CSF proteins ≥ 0.5 g/L is a clear marker of poor prognosis in the spinal phenotype. Our data suggest that blood–brain barrier dysfunction does not increase as the disease progresses, because patients with normal proteins had the longest diagnostic delay, and therefore, CSF collection was performed at a more advanced stage of the disease.