However, it is often challenging to infer correct and complete pedigrees even when genome‐wide information is available. For example, inbreeding can obscure genetic differences between individuals, making it difficult to even distinguish first‐degree relatives such as parent‐offspring from full siblings. Similarly, genotyping errors can interfere with the detection of genetic similarity between parents and their offspring. Inbreeding is common in natural, domesticated, and experimental populations and genotyping of these populations often has more errors than in human data sets, so efficient methods for building pedigrees under these conditions are necessary. Here, we present a new method for parent‐offspring inference in inbred pedigrees called specific parent‐offspring relationship estimation ( For example, in trait‐mapping studies based on linkage , that is robust to high levels of inbreeding and errors in genotyping. It is designed to use genome‐wide genotypes from a variety of sources, such as those derived from high‐coverage sequencing, imputation, or genotyping arrays. Instead of the commonly used IBD1 and IBD2, our method relies on related allele‐sharing metrics that have large expected differences between parent‐offspring and other types of relationships, even in highly inbred individuals. We show that spore is more sensitive and accurate than other commonly used methods that are not designed for inbred populations and that spore is more tolerant to genotyping errors, making it a robust tool for detecting relatives and building pedigrees using genetic data.Here, we present a new method, which we call specific parent‐offspring relationship estimation (2spore as a robust method for parent‐offspring inference and pedigree building in inbred populations and to be tolerant to genotyping errors. The main differences with existing methods are (1) the focus on variables that are expected to be zero in parent‐offspring relationships but higher in other relationships (with the exception of monozygotic twins) and (2) the automatic adjustment of thresholds below which a relationship is classified as parent‐offspring. This contrasts with other methods' use of fixed thresholds derived from theory assuming outbred populations  relationships from genome‐wide genotypes of a set of individuals, we use three variables  Detection of putative parent‐offspring (PO) relationships , the “assumed average PO relationships per individual” (APO) in the data set (see Performance of varying APO section). This input is used to automatically adjust the thresholds of IBD0, IBD0 IQR, and HM, below which a relationship is declared as putative PO , the one with fewest errors is assigned as true.10.2 Li, . With th2.2.3spore aims to infer PO relations in the remaining set of putative PO relationships that were so far not detected as a complete father–mother‐offspring trio. Because these relationships can only be detected on a one‐to‐one rather than a more powerful trio basis, spore requires them to pass all three HM, IBD0, IBD0 IQR thresholds  were possible for these two individuals, are output as “undirected PO relationships.”2.2.4spore calculates the number of individuals that have ≥ 1 PO relationship and > APO PO relationships at levels of IBD0, IBD0 IQR, and HM, separately. This is tested in up to 10,000 increments from the lowest value to the highest, with the first 9000 increments being exactly the 9000 lowest values, and the last 1000 increments being equally sized from the 9000th lowest value to the highest value. We do not exclude high values from this algorithm so spore remains flexible to various levels of genotyping errors at the cost of slightly longer runtime (see 3.3 Cattle population results). Fewer than 10,000 increments are used if fewer than 10,000 unique values exist of the variable that is looked at. The value at which the greatest distance between the fraction of individuals having at least one PO relationship and those that have more than the APO number of PO relationships is then set as the threshold of that variable below which relationships are classified as putative PO . This could be useful if genotype quality varies between individuals, which could increase the errors in both the true and false trios. In the second case, we seek to analyse how low a trio's Mendelian errors are, compared to all evaluated trios  across the data set. The resulting variable is simply the percentile of the relative error compared to all relative error counts (“data set‐relative trio errors”).spore then estimates the thresholds below which a trio is considered as true. Since only one set of parents can be true per offspring and only trios comprised of putative PO relationships are tested, spore makes use of two values to estimate the thresholds, (1) the fraction of putative offspring that would have exactly one set of parents, and (2) the fraction of putative offspring that would have more than one set of parents at each threshold. This is tested in up to 10,000 increments from the lowest value to the highest, with the first 9000 increments being exactly the 9000 lowest values, and the last 1000 increments being equally sized from the 9000th lowest value to the highest value. Fewer than 10,000 increments are used if fewer than 10,000 unique values exist of the variable being analysed. The threshold is then set at the trio‐errors value at which the highest fraction of putative offspring are part of exactly one trio that falls below the threshold, but this fraction cannot be lower than the fraction of putative offspring that are part of more than one trio that passes the threshold  of relationships, while king does not. Table To evaluate the performance of Huisman, . Unlike We used three data sets to compare the methods: (1) a subset of a population of wild house mice from a long‐term study, (2) five simulated data sets based on the genotypes of the founders of the long‐term house mice study, and (3) a published data set of a cattle pedigree and its genotypes  correctly and assigned two parents incorrectly when birthdates were made available and 295 correct with four wrong assignments when birthdates were not used  in the last generation  of randomly breeding mice of 50 overlapping generations based on the genotypes of the founders  of the real house mouse population analysed in the previous section. There were on average 2369.2 (SD = 32.4) individuals per pedigree. Due to the overlapping of generations, offspring were at most at a pedigree depth of 35 equivalents of full generations, which is the unit we refer to in the analysis of specific generations. The pedigrees were simulated without any immigration and hence increasing levels of inbreeding to ~60% of their genome in runs of homozygosity  of the true parents (five simulations with n = 4443 ± 70.5 true parents) correctly and detected on average 3.8 ± 1.8 wrong parents . crest still detected too many false PO calls . king's performance was worse in these late generations than overall, detecting only 4.7% ± 4 versus 32.3% of true parents with 6.64% ± 5.8 versus 3.6% PO calls being wrong. sequoia was the second most reliable algorithm after spore, with 48.8% ± 8.5 parents in generations 21–30 detected versus 65.7% parents in all generations and 10.1% ± 1.7 versus 4.7% false PO calls. Together, the results indicate that spore is superior at inferring PO correctly compared to other methods in controlled simulations with low and also with increasing levels of inbreeding.We also evaluated the impact of increased inbreeding, decreased genotyping quality, and incomplete population sampling through simulated pedigrees. To test performance on inbred individuals, we analysed pedigree generations 21–30 Figure . These ispore still found 84.5% ± 1.2 of true parents with 4.9% ± 2.1 false PO calls. In contrast, crest now only found 0.02% ± 0.05 of the true parents with 92.5% ± 11.2 false PO calls. Similarly, king was reduced to finding 0.3% ± 0.4 of true parents and 6.4% ± 8.8 false PO calls. sequoia found 11.6% ± 1.3 of true parents with 81.8% ± 1.8 false PO calls. Thus, spore is considerably more robust to genotyping errors than other methods.With decreased genotyping quality Figure , but an FROH = 0.17 ± 0.1) with and without decreased genotyping quality  without decreased genotyping quality to detecting almost no true parents (0.03% ± 0.07 of true parents) with decreased genotyping quality. On the other hand, king detected 80.7% ± 8.4 and 0.5% ± 1 of true parents with 2.7% ± 1.3 and 24.4% ± 43.3 wrong PO calls, respectively, showing a marked difference in performance between data sets with varying genotyping quality. Similarly, sequoia detected 86.6% ± 4.7 of true parents with 0.9% ± 0.2 false PO calls without decreased genotyping quality, but only 21.7% ± 1.8 of true parents with 60.1% ± 4.2 false PO calls with decreased genotyping quality. These results are qualitatively similar to results based on individuals with minimal inbreeding  and hence no longer including the entire simulated pedigree, also affected the quality of inference . king found 33% ± 9 of true parents, but also 4.4% ± 1.4 false PO calls. sequoia found 30.4% ± 4 of true parents and also 14.2% ± 3.5 false PO calls. When sampling is even less complete (50%), spore still detected 93.1% ± 3.1 of PO relationships but false positives also increased to 21.9% ± 8.5 , we set it to a range from the lowest possible (1) to quintuple (30) of the value we used otherwise (6). Overall, s Figure . In the s Figure . In sum,spore's APO‐based thresholding is also robust to reproductive skew between the sexes, with APO best set at the assumed average PO relations overall, independent of sex, or a low value in general  correctly and detected six wrong parents  its reliance on an integrated combination of robust metrics, such as identity‐by‐descent of chromosomal segments, incompatible genotypes within trios and within parent‐offspring pairs; (2) on the focus on parameters that have fixed expected values in parent‐offspring relationships regardless of inbreeding levels; and (3) on the automatic adjustment of thresholds to be flexible to genotyping errors, which is a key difference to many other approaches.Our results based on data from a real house mouse population, a real cattle pedigree, and simulated pedigrees, show that spore is that it has few requirements. It does not need a genetic map and can optionally leverage sex information and birthdates. The minimal input—a VCF and a simple config file—also facilitates use by less bioinformatics‐experienced investigators. More advanced use is also supported by the ability to incorporate additional metrics with fixed expected values in parent‐offspring pairs, but not other relationships.Another advantage of spore is that it works on the assumption that there are parent‐offspring trios in the analysed data set. When ~15% or more of individuals are part of a trio, false positive calls achieve an asymptotic low value < 1%  and to assemble multigenerational pedigrees. Pedigrees could be further completed using other methods such as sequoia's full‐sibling inference, although we have not evaluated its performance under inbreeding or imperfect genotypes.A caveat of % Figure . This asspore will be a useful tool for researchers monitoring experimental , 31003A_176114 (BK), 31003A_120444 & 31003A_160328 (AL). Searle Scholarship, Klingenstein‐Simons Fellowship, Sloan Foundation Fellowship, and National Institutes of Health award R35GM143051 (AB).Appendix S1Click here for additional data file.


Are cerebrospinal fluid (CSF) SARS-CoV-2 antigens associated with central nervous system inflammation in patients with COVID-19?Of 44 patients with COVID-19 (23 neurosymptomatic) included in this hospital-based cross-sectional study, CSF nucleocapsid antigen was detectable in 89% of patients with available data and was significantly correlated with immune activation markers (neopterin and interferon γ). Moreover, neurosymptomatic patients had a more pronounced inflammatory CSF profile compared with neuroasymptomatic patients that could not be attributed to differences in COVID-19 severity.These results suggest that viral components may contribute to central nervous system immune responses without direct viral invasion and highlight the clinical importance of neurologic symptoms. This cross-sectional study assesses whether viral antigens are detectable in the cerebrospinal fluid of patients with COVID-19 and compares cerebrospinal fluid biomarker profiles of patients with and without neurologic symptoms and with moderate vs severe COVID-19. Neurologic symptoms are common in COVID-19, but the central nervous system (CNS) pathogenesis is unclear, and viral RNA is rarely detected in cerebrospinal fluid (CSF).To measure viral antigen and inflammatory biomarkers in CSF in relation to neurologic symptoms and disease severity.This cross-sectional study was performed from March 1, 2020, to June 30, 2021, in patients 18 years or older who were admitted to Sahlgrenska University Hospital, Gothenburg, Sweden, with COVID-19. All patients had CSF samples taken because of neurologic symptoms or within a study protocol. Healthy volunteer and prepandemic control groups were included.SARS-CoV-2 infection.2-microglobulin, and cytokines) and neuronal injury (neurofilament light protein [NfL]).Outcomes included CSF SARS-CoV-2 nucleocapsid antigen (N-Ag) using an ultrasensitive antigen capture immunoassay platform and CSF biomarkers of immune activation  and interferon γ . No differences in CSF N-Ag concentrations were found between patient groups. Patients had markedly increased CSF neopterin, β2-microglobulin, interleukin (IL) 2, IL-6, IL-10, and tumor necrosis factor α compared with controls. Neurosymptomatic patients had significantly higher median (IQR) CSF interferon γ  and had a significantly higher inflammatory biomarker profile using principal component analysis compared with neuroasymptomatic patients . Age-adjusted median (IQR) CSF NfL concentrations were higher in patients compared with controls . No differences were seen in any CSF biomarkers in moderate compared with severe disease.Forty-four patients , 10 healthy controls , and 41 patient controls (COVID negative without evidence of CNS infection)  were included in the study. Twenty-one patients were neuroasymptomatic and 23 were neurosymptomatic . In 31 of 35 patients for whom data were available (89%), CSF N-Ag was detected; viral RNA test results were negative in all. Nucleocapsid antigen was significantly correlated with CSF neopterin (In this study of Swedish adults with COVID-19 infection and neurologic symptoms, compared with control participants, viral antigen was detectable in CSF and correlated with CNS immune activation. Patients with COVID-19 had signs of neuroaxonal injury, and neurosymptomatic patients had a more marked inflammatory profile that could not be attributed to differences in COVID-19 severity. These results highlight the clinical relevance of neurologic symptoms and suggest that viral components can contribute to CNS immune responses without direct viral invasion. Furthermore, viral detection in brain tissue is often sporadic, of low levels, and not clearly linked to neuropathologic signs of infection.8 In cerebrospinal fluid (CSF), viral RNA can only be detected at very low levels in a few cases, and characteristic signs of neurotropic viral infections (CSF pleocytosis and blood-brain barrier injury) are often mild or absent.9 Although viral RNA is rarely detected, intrathecal immune activation has been a distinguishing feature in patients with neurologic symptoms.11 Biomarker signs of neuroaxonal injury have also been observed, most evident in patients with encephalitis or stroke.14The neuroinvasive capacity of SARS-CoV-2 is questionable. Although virus has been suggested to enter the CNS via olfactory sensory neurons, neuropathologic studies15 However, little is known about the presence of viral antigens in CSF. The aims of this study were to investigate whether viral antigens could be detected in CSF in patients with COVID-19 and to compare CSF biomarker profiles of patients with or without neurologic symptoms as well as in patients with moderate compared with severe COVID-19.The cause of the CSF immune response in COVID-19 in the absence of detectable viral RNA is not clear. SARS-CoV-2 viral nucleocapsid antigen (N-Ag) can be detected in plasma during the acute phase of infection and is potentially useful as a diagnostic as well as prognostic marker in COVID-19.16 The study protocol was approved by the Swedish Ethical Review Authority. The report follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.This prospective cross-sectional study included adult (≥18 years of age) patients with confirmed SARS-CoV-2 infection admitted to Sahlgrenska University Hospital in Gothenburg, Sweden, who had undergone a diagnostic lumbar puncture because of neurologic symptoms or as part of a research protocol. This study was performed from March 1, 2020, to June 30, 2021. All participants (or next of kin if the patient was not able) provided written informed consent according to the Declaration of Helsinki.17 Serum SARS-CoV-2 antibodies were used as complementary diagnostic tests and were analyzed using commercial assays . SARS-CoV-2–specific IgG was not analyzed in CSF.SARS-CoV-2 infection was confirmed by viral RNA detection in real-time polymerase chain reaction assays of nasopharyngeal swab or plasma (n = 1) specimens or in-hospital seroconversion (n = 1). SARS-CoV-2 RNA was analyzed by real-time polymerase chain reaction in swab specimens and cell-free CSF and plasma samples as previously described  in an electronic medical records database. Participant ethnicity was investigator observed using electronic medical records. The patient cohort was divided into groups according to neurologic status: neuroasymptomatic or neurosymptomatic. Disease severity was evaluated according to the World Health Organization Clinical Progression Scale.Two separate control groups were included in the study. At the time of antigen and cytokine analysis, prospective control samples were unavailable. Consequently, we used archived (−80 °C) CSF and serum samples from age-matched COVID-19–negative patient controls who had undergone a diagnostic lumbar puncture because of initial suspicion of CNS infection, with CSF analyses indicating no sign of ongoing CNS disease. For the other included CSF analyses, additional archived samples were unavailable. Instead, a second control group of healthy COVID-19–negative volunteers recruited prospectively during the pandemic was used.Detection of SARS-CoV-2 nucleocapsid and spike proteins was performed using MSD SPLEX CoV-2 N and MSD S-PLEX CoV-2 S assay kits . The assays were run according to protocols in the kit package inserts .20 Cerebrospinal fluid β2-microglobulin (β2M) was measured using the N latex β2M kit on the Atellica NEPH 630 System . The CSF NfL was measured using a previously described in-house sandwich enzyme-linked immunosorbent assay.21 The NfL concentrations were age adjusted and reported as the equivalent for 65 years of age as previously described.22 The CSF glial fibrillary acidic protein concentration was measured using an in-house enzyme-linked immunosorbent assay as previously described.23 Cytokine concentrations were measured using the novel S-PLEX Proinflammatory Panel I. The S-PLEX format provides signal enhancement that achieves sensitivity in femtograms per milliliters . The IgG index and albumin ratio were calculated as previously described.10 transformed where appropriate. Differences between patients with COVID and controls and differences in CSF NfL concentrations between the groups of patients with COVID-19 were estimated by Welch 2-sided t tests. Comparisons of other CSF biomarkers, as well as the first principal component of the cytokines neopterin and β2M, between the groups of patients with COVID-19 were performed using analysis of covariance, adjusting for time from symptom onset to CSF sampling. Because CSF NfL is known to increase gradually during the weeks after a CNS injury, this analysis was not adjusted for sampling time to avoid overadjustment. Correlations among CSF biomarkers were analyzed using partial correlation, adjusting for time of CSF sampling. Partial correlation coefficients are reported as r unless otherwise stated. Differences in baseline characteristics between patient groups were analyzed using t tests for continuous variables and Fisher exact test for categorical variables. All tests were 2-sided, and P < .05 was considered statistically significant.All statistical analyses were performed using Prism software, version 9.0.0 (GraphPad Software) or SPSS, version 26 (IBM Inc). Numerical variables were log18 Twenty-one patients with COVID-19 were neuroasymptomatic, and 23 were neurosymptomatic. The neurosymptomatic group included patients with encephalopathy (n = 21), encephalitis (n = 1), and Guillain-Barré syndrome (n = 1). Encephalitis was defined as altered mental status and CSF pleocytosis , viral detection in CSF, or supporting evidence of CNS infection . Baseline characteristics in the different groups are shown in Forty-four patients , 10 healthy controls , and 41 patient controls (COVID negative without evidence of CNS infection)  were included in the study. All patients were admitted to the hospital with moderate (n = 26) or severe (n = 18) COVID-19 according to the World Health Organization Clinical Progression Scale.P = .02). The time from any COVID-19 symptom onset to CSF sampling was significantly shorter compared with the neuroasymptomatic group . The CSF samples were acellular  in all patients except in 2 neuroasymptomatic patients  and 1 patient with encephalitis . Three patients in the neurosymptomatic group died during hospitalization. Neuroimaging was performed in a subset of participants  had detectable viral RNA in plasma. The median cycle threshold (Ct) value for detectable plasma samples was 36.0 . Concentrations of serum and CSF SARS-CoV-2 nucleocapsid and spike antigens are given in 2M, interleukin (IL) 2, IL-6, IL-10, and tumor necrosis factor α (TNF-α) compared with controls , whereas CSF neopterin , IL-6 , and TNF-α  fell just above the threshold for significance , which remained significant after adjustment for time of sampling .Comparing the groups of patients with COVID-19, significantly higher concentrations of several biomarkers were seen in neurosymptomatic compared with neuroasymptomatic patients . Howeverificance . We compP = .002), whereas no significant difference was found between the groups of patients with COVID-19 (Age-adjusted median (IQR) CSF NfL concentrations were significantly higher in patients with COVID-19 compared with controls . Initial analysis also indicated a significant association between CSF N-Ag and the immune activation markers CSF neopterin, β2M, and IFN-γ, but after adjusting for CSF sampling day, correlations remained significant only for CSF neopterin  and IFN-γ  (A close correlation was found between serum and CSF concentrations of SARS-CoV-2 N-Ag (P = .01) .2M, TNF-α, IFN-γ, IL-4, and IL-2 were seen between the groups of patients with COVID-19, with higher concentrations found in neurosymptomatic patients. Compared with controls, patients with COVID-19 had higher serum concentrations of all biomarkers except IL-12p70 and IL-1β , suggesting that CNS symptoms were not associated with selective intrathecal production of the inflammatory biomarkers.We used an albumin ratio–adjusted biomarker index  to explore differences in intrathecal biomarker proportions between the patient groups. Of all studied biomarkers, only IL-4 showed a significant difference  and a median serum-CSF ratio of 42 , suggesting that CSF N-Ag originates from systemic sources, either by passive diffusion across the blood-brain barrier or as a consequence of viral interaction with the neurovascular unit, possibly including infection of neurovascular pericytes.32 The markedly lower serum concentrations in combination with the potential loss of S-Ag by binding to angiotensin-converting enzyme 2 on cells lining the ventricular system may have influenced the low detection rate of S-Ag in CSF.Although the neuroinvasive capacity of SARS-CoV-2 is questionable,2M, IL-2, IL-6, IL-10, and TNF-α compared with controls, indicating CNS-specific inflammation and confirming previous findings of increased neopterin and β2M in patients with COVID-19 with neurologic symptoms.11 Although increased CSF concentrations of IL-6 and TNF-α have also been described previously,33 results are less consistent across studies.34 Although other CNS infections and inflammatory conditions can generate significantly higher inflammatory CSF biomarker concentrations,35 the CSF inflammatory biomarker profile seen in patients with COVID-19 in our study remains a consistent finding and adds to previous reports37 indicating the importance of CNS immune activation in the neuropathogenesis of COVID-19.Patients with COVID-19 had significantly increased CSF concentrations of neopterin, β38 The principal difference between patient groups appeared to be in the magnitude of the immune response, suggesting that neuropathogenesis in COVID-19 with neurologic symptoms represents a continuum of inflammation, where the intensity of the inflammatory response  may be a determining factor in the development of CNS symptoms. In turn, CNS symptoms may reflect harmful effects on the brain measurable as neuroaxonal injury (CSF NfL). Notably, CSF biomarkers followed a similar pattern compared with serum, where differences in biomarkers between groups of patients with COVID-19 as well as controls were more evident, indicating that the CNS inflammatory response likely constitutes a continuous part of the systemic infection. However, qualitative differences in the immune response in neurosymptomatic compared with neuroasymptomatic patients remains a possibility that needs to be investigated further. As described by others,14 no significant differences were found in CSF glial fibrillary acidic protein concentrations between any of the patient groups and controls, indicating that astrocyte activation may not be a major contributor to CNS pathogenesis in COVID-19.The underlying mechanism of neurologic symptoms  during COVID-19 is not clear. Of interest, we found that patients with neurologic symptoms had significantly higher time-adjusted CSF concentrations of IFN-γ and a more marked inflammatory biomarker profile compared with neuroasymptomatic patients. Age-adjusted CSF NfL, representing neuroaxonal injury, was also significantly higher in patients with COVID-19 compared with controls. In addition, all patients with CSF NfL concentrations above the upper normal reference were found in the neurosymptomatic group. Overall, we found a notable correlation between CSF NfL and CSF TNF-α, IL-1β, and IL-17A, suggesting that immune cell activation and the CNS inflammatory response may result in neuroaxonal injury. Altogether, these findings indicate that the CNS immune response may be an important driver of CNS pathogenesis, similar to other CNS inflammatory conditions or infections.33 of patients in the intensive care unit, neurologic syndromes were associated with higher CSF concentrations of several cytokines and chemokines. However, observations made exclusively in patients in the intensive care unit may be subject to bias that can be attributed to critical illness and organ failure. We did not find any significant differences in CSF biomarkers in patients with moderate compared with severe COVID-19. Moreover, the lower proportion of patients with severe COVID-19 in those with neurologic symptoms compared with the neuroasymptomatic group (30% vs 52%) further suggests that neurologic manifestations represent a specific pathological process within the CNS that cannot be attributed solely to systemic infection.Few previous reports have included CSF analyses from patients with COVID-19 without neurologic symptoms. In a small study39 Given the inflammatory character of acute COVID-19, sampling at a later time may not reflect the processes that initiate CNS pathology. Moreover, few studies have adjusted for CSF sampling day, which may have influenced results.13 In the current study, all CSF samples were collected during the acute phase of COVID-19 (median of 12 days from symptom onset). Although we believe this timing is important for evaluating viral antigen detection and initial CNS immune responses, the CSF NfL is known to have a slower initial kinetic and longer half-life, where additional CSF sampling later in the disease course would be of interest for further evaluating the association of CNS inflammation with markers of neuronal injury.41The time from symptom onset to CSF sampling was an important covariate for CSF biomarker concentrations. The timing of CSF sampling has varied considerably in previous studies.42 is still relatively small, and neuroimaging was not included consistently. Encephalopathy was the dominating neurologic manifestation, although the definition of encephalitis differed slightly from those used in some previous studies43 of COVID-19 with neurologic symptoms. Furthermore, the study did not include nonhospitalized patients with mild COVID-19. The small study size and exploratory approach prohibited evaluation of the potential prognostic value of the studied biomarkers. Of necessity, the study included 2 different control groups. Notably, the patient controls used for antigen and cytokine analyses had CSF samples drawn for clinical suspicion of CNS infection. Although no infection was subsequently diagnosed, some individuals may have had other undiagnosed CNS conditions that potentially affected CSF biomarker concentrations. It is highly unlikely that this would exaggerate differences compared with the COVID-19 samples, although we cannot rule out an opposite effect. In addition, we cannot exclude that other residual confounding factors may have influenced results.Strengths of this study include the prospective design, the inclusion of neuroasymptomatic as well as neurosymptomatic patients, and the inclusion of control groups. However, the study also has several limitations. The sample size, although large in comparison with other published reports,In this cross-sectional study of Swedish adults with COVID-19 infection and neurologic symptoms, compared with control participants, SARS-CoV-2 N-Ag was detectable in CSF in most patients with COVID-19, despite the absence of detectable CSF viral RNA, and was correlated with CNS immune activation. Furthermore, neurosymptomatic patients had a more pronounced immune activation profile compared with neuroasymptomatic patients, and patients with COVID-19 had signs of neuroaxonal injury compared with controls. These observations could not be attributed to differences in COVID-19 severity, where no differences in CSF biomarkers were seen in patients with moderate compared with severe disease.Although confirmatory studies evaluating the significance of viral antigen detection in CSF are needed, these results suggest that viral components may contribute to CNS immune responses without direct viral invasion into the CSF compartment, which could partly explain the apparent discrepancy between the scarcity of CSF viral RNA detection and the marked CNS inflammatory response seen in patients with COVID-19 with neurologic symptoms. The results of this study also highlight the importance of neurologic symptoms, including encephalopathy. These findings have important potential implications for clinical treatment of patients with COVID-19, including the use of antiviral therapies, as well as for the continued importance of including CSF analyses in future studies of CNS pathogenesis and treatment strategies.


Mass spectrometry (MS), with its immense technological developments over the last two decades, has emerged as an unavoidable technique in analyzing biomolecules such as proteins and peptides. Its multiplexing capability and explorative approach make it a valuable tool for analyzing complex clinical samples concerning biomarker research and investigating pathophysiological mechanisms. Peptides regulate various biological processes, and several of them play a critical role in many disease-related pathological conditions. One important example in neurodegenerative diseases is the accumulation of amyloid-beta peptides (Aβ) in the brain of Alzheimer’s disease (AD) patients. When investigating brain function and brain-related pathologies, such as neurodegenerative diseases, cerebrospinal fluid (CSF) represents the most suitable sample because of its direct contact with the brain. In this review, we evaluate publications applying peptidomics analysis to CSF samples, focusing on neurodegenerative diseases. We describe the methodology of peptidomics analysis and give an overview of the achievements of CSF peptidomics over the years. Finally, publications reporting peptides regulated in AD are discussed. Peptides have been the object of investigation for more than 100 years ,3,4,5. ONeuropeptides are the most studied peptides. They are the largest signaling molecules in the nervous system and, by modulating the critical processes in the brain, influence the processes in the entire organism . NeuropeCerebrospinal fluid (CSF) is in direct contact with the brain and makes it a collector of many biomolecules. Changes in CSF composition might mirror the perturbation in brain-related physiological processes, for instance, as a result of a pathological condition. The CSF peptidome did not show substantial overlap with plasma or serum peptidome depicting its unique composition and regulates processes related to protein activation cascade, blood coagulation, complement activation, regulation of axogenesis, and macromolecular complex remodeling . TherefoIn this review, we evaluate studies applying the peptidomics approach to analyze CSF in neurodegenerative diseases. We provide an overview of the analytical steps of CSF peptidomics analysis and a chronological recapitulation of the CSF peptidome regarding neurodegenerative diseases. Reports on potential biomarkers of AD are discussed in detail, including those analyzing the plasma and serum.In the PubMed database, we searched combinations of the following terms: peptidomics or peptidome, cerebrospinal fluid or CSF, and neurodegenerative diseases. In the next step, we searched for specific neurodegenerative diseases separately. Neurodegenerative diseases included in the search were as follows: Alzheimer’s disease, frontotemporal dementia, Lewy body dementia, Huntington’s disease, amyotrophic lateral sclerosis (ALS), Parkinson’s disease, Creutzfeldt-Jakob disease, frontotemporal lobar degeneration (FTDL), multiple system atrophy, prion diseases, Batten disease, and spinal muscular atrophy. Any search combination contained at least either the term cerebrospinal fluid or peptidomics. By replacing the term cerebrospinal fluid with plasma or serum, only a few additional entries were added to the existing list; therefore, they were included and discussed in the AD section. Based on these criteria, 82 publications were identified.As we focused on neurodegenerative diseases and in experiments with CSF samples, in the next step we excluded publications containing the following terms in their title or abstract: cancer, cardiac arrest, liver, lung, heart, tissue, brain, culture, or cell. We were predominantly interested in works analyzing peptidome; therefore, publications reporting the measurement of a single or only a few peptides in their title or abstact were additionally excluded from further evaluation. The exclusion criteria were applied directly on PubMed and titles and abstracts were also manually inspected. To this end, publications reporting work on proteomics, inflammatory diseases, workshops, and conference articles were removed as well. The number of entries was reduced to 63.A deeper evaluation of the remaining articles by applying the above criteria reduced the number of articles to 45. From them, 21 reviews and two book chapters were excluded. Two of the remaining publications analyzed the serum samples and another one plasma.Although there are antibody-based assays measuring selected peptides , nowadayThe complexity of clinical samples containing several hundred and thousand biomolecules at a concentration range of up to 10 orders of magnitude represents a massive challenge in their analysis . AlthougTechnological progress in MS instrumentations and particularly the increased resolution power empowered scientists to use MS to characterize intact proteins with a noted interest in analyzing antibodies. However, in conventional proteomics experiments, proteins prior to LC-MS analysis are digested to lower molecular weight molecules, peptides ,31. HencAn untargeted approach with its explorative character aims to screen for all possible peptides in a clinical sample. In a data-dependent analysis (DDA) after a survey scan of unfragmented ions, top intense m/z peaks are selected for separation and consecutive isolation, followed by ion fragmentation and the acquisition of MS/MS spectra . BecauseMS-based analysis generates a vast amount of very complex data. Consequently, software packages are needed for high-throughput data analysis ,49,54. TA two-phase extraction system of organic solvents was used for peptide isolation in one of the first peptidomics screening experiments aiming to characterize the CSF peptidome by means of MS. Prior to MS analysis, peptides were fractionated by liquid chromatography. In total, eight peptides and four peptide fragments were identified: fibrinopeptide A, C4A anaphylatoxin; N-terminal fragments of neuroendocrine specific protein VGF, ribonuclease 1; internal fragments of endothelin-binding receptor-like protein 2, chromogranin B/secretogranin I, chromogranin A, proenkephalin; and C-terminal fragments of neuroendocrine protein 7B2, pro-IGF-II, testican, and osteopontin . All of A comprehensive and in-depth characterization of the CSF peptidome significantly increased the number of identified peptides to 563 . The folTechnological improvement on MS instrumentation over the years has enabled deepening the coverage of the CSF peptidome ,60,61. CThe first study applying the peptidomics approach for investigating AD biomarkers identified five peptide signals with altered abundance in the CSF samples of AD patients compared with healthy controls . Four oun = 312) and investigating AD biomarkers, after extensive sample fractionation among 6000 detected MS signals identified 14 peptides derived from two proteins, one peptide from complement factor C3 (C3f) and the others were from VGF [The very first study comprising a large number of subjects  analysis applied to CSF led to an AD diagnostic panel consisting of 12 signals, and only 5 of them were identified as following peptides or peptides fragments: ProSAAS precursor (217–242): AADHDVGSELPPEGVLGALLRV, chromogranin A (322–339): SGELEQEEERLSKEWEDS, phospholemman (21–41): ESPKEHDPFTYDYQSLQIGGL, clusterin (apolipoprotein-J) (22–49): DQTVSDNELQEMSNQGSKYVNKEIQNA, and VGF (26–59): GRPEAQPPPLSSEHKEPVAGDAVPGPKDGSAPEV . The AD PTMs can be decisive in determining peptide function or its activation state. The high number of modified neuropeptides, 88 of the total 276 peptides listed in the NeuroPep database , is stroThe main challenge in the peptidomics analysis remains database search, which, through the study, of PTMs reaches another stage of complexity with search space expanding further. Nevertheless, a three-step database searching strategy and utilizing a softer dissociation technique (electron-transfer and higher-energy collision dissociation—EthcD) provided in-depth characterization of peptides glycosylation sites in CSF samples . In totaAn ideal biomarker would support the determination of a diagnosis in the best scenario at an early disease stage. A biomarker could also be suitable for monitoring disease progression or treatment response. In both cases, animal models represent a valuable option in the discovery part of biomarker research, but also in the understanding of the disease pathology and disease development. In CSF samples of a transgenic rat model for tauopathy and control animals from 345 identified peptides, those derived from 17 proteins showed abundance alteration: neurofilament light and medium chain, apolipoprotein E, gamma-synuclein, chromogranin A, reticulon-4, secretogranin-2, calsyntein-1 and -3, endothelin-3, neuroendocrine protein B72A, alpha-1-macroglobulin, fibrinogen beta chain, prosaposin receptor GPR37, receptor-type tyrosine-protein phosphatase zeta, small nuclear ribonucleoprotein-associated protein N and augurin . ProteinAttempts for monitoring of drug response administrated to humans are also known. Plaque formation from Aβ peptides associated predominantly with neuronal degeneration and cognitive decline is the central aspect of AD . γ-secreCSF is an ideal sample when processes related to brain and neuronal function are investigated. However, the collection of a CSF sample is more invasive compared with a routine clinical sample, such as of the plasma and serum. In this view, several studies have been conducted utilizing plasma and serum samples for biomarker discovery. So, the abundance of fibrinogen α chain (FIBA) derived peptide fibrinopeptide A  and αC-domain , in combination with age, showed an area under the curve (AUC) of 0.717 in a small validation cohort of AD patients and controls . The incPeptides in peptidomics experiments are much larger than those generated in conventional proteomics experiments after tryptic digestion . As a coAnother source of variation in peptidomics experiments is contamination with blood-derived peptides during CSF collection from patients. It might be a good strategy not to consider further interpreting the peptides identified in blood. However, there are known neuropeptides that act in organs other than the brain and that can also be found in the blood. Additionally, the presence of blood peptides in CSF might indicate a pathological condition such as impairment of the blood−CSF barrier. Although the normalization of data to the total identified proteins is widely spread in label-free proteomics experiments, it is questionable whether it is also suitable for peptidomics experiments considering the low number of identified peptides. Data normalization to the sample volume used for peptide extraction should be prioritized and is comparable with validation studies where targeted analysis is applied with volume-based data normalization.Over the last two decades, the number of identified peptides in CSF increased tremendously. Achievement in MS technology has facilitated the determination of thousands of peptides in CSF. The introduction of the fourth dimension of peptide separation according to their mobility properties and, in addition to molecular weight separation at sample preparation, separation based on their hydrophobic properties in LC systems and mass to charge ratio in MS instrument, promises further deepening of the coverage of the CSF peptidome by MS-based analysis ,89. The main effort of the peptidomics community has been directed to AD, and all other neurodegenerative diseases are so far highly underrepresented, which is a potential to be explored in the future when considering the role of peptides in brain physiology. Although several hundreds of peptides derived from 42 proteins  have bee


Alzheimer’s disease (AD) associated proteins exist in cerebrospinal fluid (CSF). This paper evidences that protein aggregate morphology distinctly differs in CSF of patients with AD dementia (ADD), mild cognitive impairment due to AD (MCI AD), with subjective cognitive decline without amyloid pathology (SCD) and with non-AD MCI using liquid-based atomic force microscopy (AFM). Spherical-shaped particles and nodular-shaped protofibrils were present in the CSF of SCD patients, whereas CSF of ADD patients abundantly contained elongated mature fibrils. Quantitative analysis of AFM topographs confirms fibril length is higher in CSF of ADD than in MCI AD and lowest in SCD and non-AD dementia patients. CSF fibril length is inversely correlated with CSF amyloid beta (Aβ) 42/40 ratio and CSF p-tau protein levels  to predict amyloid and tau pathology with an accuracy of 94% and 82%, respectively, thus identifying ultralong protein fibrils in CSF as a possible signature of AD pathology. Liquid-based AFM on protein aggregates at single-fibril resolution from the cerebrospinal fluid of patients at various stages of AD reveals that mature fibrils from patients at advanced stage AD have longer length, distinct morphology and spatial organization. Chiefly, CSF reflects neuropathological changes upon interfacing with the extracellular brain regions, thus serving as a rich source for screening PD and AD biomarkers. Still, it has only been in the recent past that the quantification of Aβ42 and 40 and their ratio, total-tau (t-tau) and phosphorylated-tau (p-tau) protein levels in CSF using enzyme-linked immunosorbent assay (ELISA) have become a cornerstone of the routine diagnostics of patients with cognitive complaints as they allow for an early and reliable diagnosis of AD pathology11. In particular, the Aβ42 to Aβ40 ratio is decreased early in the progression of AD and is inversely correlated with plaque formation found on Amyloid-PET12, while phosphorylated tau protein levels are increased in AD patients and reflect disease severity14. The advent of digital immunoassays further enabled the realisation of an accurate assessment of pathologic amyloid and p-tau isoforms also in blood plasma17. Especially, Aβ42, P-tau181, P-tau217, and P-tau231 levels in plasma were shown to be highly correlated with CSF- and PET AD biomarkers19. Alternative techniques such as immuno-infrared sensors were demonstrated to reliably detect the formation of β-sheet structures indicative of pathologic Aβ-oligomerization20. Analysis of the changes associated with the secondary Aβ structure allowed the detection of AD pathology with a high accuracy21 even in preclinical and prodromal AD patients already up to 17 years before clinical conversion to AD23. Regarding the tertiary structure of insoluble Aβ aggregates, in the past, fluorescence correlation spectroscopy was demonstrated to identify amyloid-beta aggregates in CSF24 but it has been shown that fluorophore labels can modify oligomer size distribution25. Cryo-electron microscopy is another powerful tool employed to capture the polymorphism in brain-derived amyloid fibrils27 but the sample preparation steps required for protein fibril analysis at cryogenic conditions could affect the fibril structure29.CSF analytics is central in the diagnosis of neurodegenerative disorders including Parkinson’s disease (PD)Although crucial qualitative and quantitative information on protein aggregates can be obtained from the above-discussed methods, it is becoming increasingly important to characterise single protein aggregates in CSF in a label-free manner under physiological conditions.32 and chemical signature34 of oligomers and fibrillar aggregates of proteins involved in the pathogenesis of AD in CSF31 and in blood35. Clearly, AFM operated at ambient conditions cannot provide atomic-scale details on protein aggregates on par with cryo-electron microscopy (cryo-EM) but it offers a facile route to profile the full spectrum of pathological protein aggregates with single-particle specificty39 without the need for complex sample preparation. Knowledge on the differences in protein aggregate types in body fluids from small oligomers, and protofibrils to mature fibrils could augment current AD diagnostics and treatment decisions. For example, antibodies against Aβ that have been developed in the past years for the treatment of AD seem to target different protein aggregates of Aβ. In particular, the anti-amyloid antibody lecanemab, which mainly binds to soluble protofibrils (short fibrillar aggregates that appear with a distinct nodular morphology40) showed positive results on clinical endpoints in a large phase-III trial41. In contrast, previous phase III studies on anti-amyloid antibodies which mainly bind to mature amyloid fibrils (elongated with smooth surface topology) such as gantenerumab, crenezumab and aducanumab showed no  or uncertain (aducanumab) effects on clinical endpoints43. Thus, the question of which kind of protein aggregates are most prevalent in body fluids such as the CSF of an individual patient could be of major importance for the selection of patients for clinical trials or treatment decisions.In this context, AFM, infrared spectroscopy and Raman spectroscopy are promising preclinical techniques to examine in a label-free manner the nanoscale morphologyn = 7, age = 61.0 ± 8.9 years, MoCA score = 26.7 ± 1.5), mild cognitive impairment (MCI) without specified aetiology , MCI due to AD , patients with AD dementia , Lewy Body dementia  as well a patient with vascular dementia  were analysed using AFM. The individual patient details are presented in Table Here, we used liquid-based AFM . The details on CSF extraction, storage, and preparation of CSF samples on the gold surface for AFM imaging are provided in the materials and methods section. Patient KSSG:38  was clinically diagnosed with severe AD and classified as A + T + N +  according to the NIA-AA research frameworkril Fig.  did not 49.Next, we investigated CSF from patients with early-onset, mild AD dementia , with MCI due to AD  and SCD with no signs of AD pathology or neurodegeneration  using AFM. Figure Figure n: 78, (0.4 ± 0.1) µm, n: 63, (0.34 ± 0.1) µm, n: 75 and, (0.35 ± 0.0.7) µm, n: 72, respectively. Likewise, the corresponding mean protofibril height was calculated based on the box plot shown in Fig. Figure 53, as depicted in the schematic Fig. 54 and those with AD pathology54. Such protein aggregates represent toxic soluble amyloid-oligomers which could drive neurodegeneration55. Based on the box plot shown in Fig. n: 120 particles for each patient) detected in CSF of patients KSSG 19, 57, 84, 129, 46 and 95 to be (44.5 ± 13.5) nm, (2.8 ± 0.8) nm, (2.5 ± 0.75) nm, (3.8 ± 1.6) nm, (66.6 ± 17.5) nm and (51.8 ± 13.0) nm, respectively.In addition to protofibrillar aggregates in the CSF of patients with SCD, the presence of spherical particles was also detected during the AFM measurements  = −4.4, p < 0.001, see Fig. r = 0.4, t(31) = 2.8, p < 0.01, see Fig. p < 0.001, see Fig. pHolm-adj < 0.001) and SCD . The difference in fibril length between the MCI AD and SCD groups was also significant (pHolm-adj < 0.001). In a linear regression model of fibril length in which age, the disease group and the interaction between age and disease group were the predictors, only the disease group  and the age disease interaction  were significant predictors of CSF fibril length, but not the main effect of age . Simple slope analyses of this linear regression model revealed that age was only significantly correlated with fibril length in patients with MCI AD  or ADD .Differences in protein aggregate morphology recorded in CSF using AFM and the clinical evaluation all patients enroled in this study are detailed in Table 56 motivates the need for complementary techniques such as AFM to directly examine the CSF composition. Protein aggregate size, shape profile and structure varied between patients with SCD, MCI AD and ADD. CSF fibril length was observed to be increased in patients with MCI AD and highest in patients with ADD as compared to patients with SCD and non-AD dementia. A surprising result was the presence of a stable and abundant population of micrometre length-sized fibrils detected in CSF from several patients with ADD. These ultralong protein fibrils showed a distinct morphology  and spatial organisation (the fibrils were closely packed in a mostly non-overlapping format) that was nearly identical across thousands of measured single fibrils. Based on our data and previous reports on the morphology of purified Aβ4040, Aβ4246 and tau48 protein fibrils we posit that the observed ultralong protein fibrils detected in CSF from patients with ADD could be attributed to Aβ protein isoform. Although oligomeric and small protofibrillar aggregates have been previously resolved in CSF from MCI and AD patients using AFM31, the new insights gained from our work for the presence of ultralong fibrils in CSF of ADD patients could trigger further discussion on amyloid clearance mechanisms. Furthermore, the observed increase in fibril length with age in the group of MCI AD patients could indicate a link between fibril growth and AD disease progression. However, fibril length did not change with age in the group with only SCD and manifest ADD suggesting that it is mainly determined by AD pathology and has reached a plateau in patients with manifest dementia. Next, comparing the quantitative morphological data of fibrils in CSF obtained from AFM with biochemical assay based analysis of Aβ and tau protein isoforms in CSF revealed that fibril length parameter was highly correlated with the CSF Aβ42/40 ratio and to a lesser degree with p-tau 181 and predicted amyloid, and to a lesser degree for p-tau pathology, with high accuracy.In this study, we demonstrate that liquid-based AFM is well suited to morphologically discern between individual protein aggregates in CSF. Protein fibrils were resolved in CSF and their morphology quantified at a single-fibril level. The ability to clearly quantify protein fibril length and diameter in CSF at physiological conditions validates the usefulness of AFM for monitoring AD onset and progression. Especially, in light of evidence that CSF analysis can be used to detect cerebral Aβ accumulation earlier than PET scansOur study has limitations. While we demonstrate the morphological characterisation of protein fibrils in CSF, details on the molecular composition of the fibrillar aggregates detected in CSF remain to be clarified. The chemical nature of the fibrils can be obtained by combing AFM with fluorescence microscopy, which requires the usage of specific fluorophores that can selectively bind to either Aβ or tau protein isoforms in CSF. An alternative strategy to chemically identify protein aggregates in CSF could be to integrate AFM with Raman/IR spectroscopy and then to compare the morphology and spectrochemical signature of the protein aggregates in CSF (unlabelled data) with synthetically purified and prepared amyloid and tau isoforms (labelled data) deposited on a solid substrate. The labelled datasets can then be used as a training layer in a convolutional neural network scheme to classify the unlabelled datasets into either Aβ or tau protein isoforms. In addition to the above-outlined experimental approaches, future efforts will also require larger sample sizes in order to determine whether fibril formation in CSF can also be found in other neurodegenerative diseases or is only specific to AD. We anticipate that a longitudinal follow-up of the patient could further validate whether CSF fibril length can be an indicator for predicting future cognitive decline in patients with MCI AD.n = 3), mild cognitive impairment due to AD (n = 1) and patients with only subjective cognitive decline without amyloid pathology  from the well-characterized cohort described in our previous publication35. The nine patients were selected as they span the AD continuum from patients with only subjective cognitive complaints without biomarker evidence for amyloid-, tau-pathology or neurodegeneration (A-T-N-) to severe dementia due to AD (A + T + N + ) according to the NIA-AA research framework44. In a second step, an additional 24 patients were randomly selected from the overall cohort by P.N.N with the clinical information unbeknownst to them, resulting in an analysed total cohort of 33 patients. All participants gave informed consent to participate in the pilot study. When there were doubts concerning patient’s ability to give informed consent, we additionally obtained the informed consent of the relative accompanying the patient. The experimental procedures were approved by the ethics committee of East Switzerland (Number: 202000558) and were performed following the Declaration of Helsinki. All patients received a comprehensive diagnostic workup comprising a neurological and neuropsychological examination, structural MRI imaging and CSF analyses. LUMIPULSE G assays  were used to measure hTau Ag, pTau 181, β-amyloid 1–42, β-amyloid 1–40 and the corresponding Aβ 1–42/Aβ 1–40 ratio. Standard laboratory cutoffs were used to define a positive amyloid status (CSF-β-Amyloid 1–42/1–40 ratio < 0.068) and tau status (pCSF p-tau >59 ng/l), whereas atrophy in structural MRI imaging, hypometabolism in FDG-PET imaging or elevated total tau levels (>410 ng/l) were regarded as evidence of neurodegeneration. Clinical diagnoses were reached in an interdisciplinary consensus. Overall, seven patients presented with solely subjective cognitive decline (SCD) and one patient had mild cognitive impairment of unspecified aetiology. Ten were diagnosed with mild cognitive impairment due to AD (MCI AD) and eleven patients with probable AD dementia with biomarker evidence (ADD) according to the NIA-AA criteria of 201157. One patient was diagnosed with Parkinson’s disease dementia (PDD), two with Lewy Body dementia (LBD)58 and one patient with dementia due to vascular disease (VDD)59 according to the respective diagnostic criteria.In total, 238 patients who presented for an initial or follow-up assessment of cognitive complaints at the memory clinic of the Department of Neurology at the Cantonal Hospital St. Gallen were enroled in a pilot study on AFM imaging of blood and CSF in neurodegenerative diseases. For the presented analyses, we initially selected nine patients with either AD dementia (2). Only atomically flat samples  with an overall surface roughness was ≤0.5 nm over an area of 5 µm2  were used for CSF deposition. Gold thin films with surface defects60 were also observed in some of gold samples as-received from Phasis Inc and such samples were excluded from usage for protein imaging experiments.Directly after the lumbar puncture, CSF samples were stored at −80 °C at the laboratory, Zentrum für Labormedizin St. Gallen. Following the CSF retrieval, the samples were thawed under standard laboratory conditions to a liquified state before deposition on gold thin films. The gold thin films (~100 nm of Au (111) on mica substrate) were commercially purchased from Phasis, Inc. Before deposition of CSF, the as-received gold substrates were thoroughly cleaned . Before inserting the AFM tip in the holder, the AFM tip was cleaned by rinsing in acetone for 30 s followed by rinsing in isopropyl alcohol for ~1 min followed by blow-drying with compressed air. AFM measurements were conducted directly in the CSF medium (without air-drying process) by injecting ~10 µL of CSF into the closed type liquid-cell holder placed over the gold substrate. For the AFM measurements at the liquid-solid interface, the AFM tip and cantilever were immersed in CSF and the resonant frequency of the tip was reduced by ~30%, due to the damping of cantilever dynamics. AFM measurements were also conducted on air-dried samples by first depositing ~10 µL of CSF on the clean gold thin films followed by drying in the air (~2 h) and then placing the air-dried CSF on gold disks on top of the E-scanner for AFM imaging. No differences in fibril length or prevalence were detected for CSF samples that were air-dried and when the same CSF was analysed under hydrated conditions. In particular, we monitored the shrinking factor by directly comparing the fibril height measured in the CSF medium retained in a hydrated condition and the same CSF samples analysed upon air drying. From such comparative analysis, we derived a shrinking factor of 0.8 ± 0.1. The AFM images were analysed using Nanoscope software (Bruker), subjected to flattening for extraction of surface roughness values of gold thin films, and height and length analysis of the protein fibrils. The orientation map of ultralong fibrils in CSF shown in Fig. 61  for cutpoints which yielded the highest Youden-index (sensitivity + specificity -1) using the ‘cutpointr’ package63. A linear regression model of CSF fibrillar length with the predictors’ age, disease and the age x disease interaction was fitted and the model estimate was tested with an ANOVA. Simple age regression slopes were analysed for each disease group using the ‘interaction’ package.Statistical analyses were performed in the R environment for statistical computing , R Project for Statistical Computing). To compare the clinical characteristic between disease groups exploratory analyses of variance (ANOVA) tests for numerical data and chi-square tests for categorical data were conducted as implemented in the ‘arsenal’ packageFurther information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Data 1Reporting Summary


Despite the excellent prognosis for children and adolescents with acute lymphoblastic lymphoma (ALL), the involvement of the central nervous system (CNS) represents a major therapeutic challenge. Patients who develop CNS relapse have a very poor prognosis, and since current methods cannot reliably identify patients with CNS involvement or patients at high risk of CNS relapse, all children with ALL receive CNS-directed treatment. The current golden standard for detecting CNS involvement is the assessment of cytomorphology on cytospin slides of cerebrospinal fluid (CSF). This technique is inadequate due to low sensitivity and reproducibility. Flow cytometric analysis of CSF represent a novel, highly specific and sensitive technique for the detection of leukemic cells in the CNS. In prospective studies, CSF flow cytometry demonstrated two to three times higher rates of CNS involvement at diagnosis of childhood ALL than conventional cytospin, and especially demonstrated superior sensitivity in detecting low-level CNS disease. CNS involvement determined via flow cytometry has been linked to a higher risk of CNS relapse and poor outcomes in several studies. In this review, we discuss the central analytical concepts of CSF flow cytometry and summarize the current evidence supporting the use of flow cytometric detection of malignant blasts as a biomarker of CNS involvement in childhood ALL. Over the past decades, improved therapy and supportive care have resulted in overall survival rates or 90% or more for patients with childhood 1–17.9 years) acute lymphoblastic leukemia (ALL) . However.9 years Recently, flow cytometric analysis of CSF has been proposed as an alternative technique for the detection of CNS leukemia. Flow cytometry can detect malignant cells in the CSF with high sensitivity and reproducibility and thus holds potential for directing risk-adapted CNS-directed therapy in childhood ALL. The purpose of this article is to review central analytical concepts in CSF flow cytometry and the current evidence supporting the use of the measured blast count as a prognostic biomarker in childhood ALL.Disseminated leukemic cells predominantly reside within the leptomeninges that cover the surface of the brain and spinal cord and only invade the brain parenchyma in late-stage disease . The leuKMT2A gene, t[BCR-ABL1] and t[TCF3-PBX1]  . LeukemiF3-PBX1] ,15,16. HF3-PBX1] . CNS invF3-PBX1] . HoweverF3-PBX1] ,15, undeF3-PBX1] . These tF3-PBX1] ,9,17.Today, the conventional method for diagnosing CNS involvement in childhood ALL is based on cytomorphology ,6. AfterMicroscopy-based analysis has low sensitivity in the detection of rare cells, such as malignant blasts in the CSF of patients with disseminated CNS disease ,19. OfteAs part of the immune surveillance in the CNS, the CSF also contains normal lymphocytes, especially T-lymphocytes . ActivatCNS leukemia is diagnosed based on CSF cytospin results, together with leukocyte counts and, in some cases, observation of the clinical signs of CNS leukemia. CNS leukemia is diagnosed if at least one blast cell is observed on cytospin. Patients without CNS involvement are classified as CNS1 (<5 leukocytes/µL CSF with no blasts on cytospin) and patients with CNS involvement as CNS2 (<5 leukocytes/µL CSF with blasts on cytospin) or CNS3 , depending of the level of CNS infiltration . ClinicaRecently, multicolor flow cytometric analysis of CSF has been proposed as a more sensitive method for detecting CNS involvement in hematological malignancies. When performing immunophenotyping via flow cytometry, cells are stained with fluorochrome-conjugated antibodies against multiple markers, and the fluorescent properties of each individual cell are determined with a flow cytometer. Malignant cells are identified based on aberrant expression patterns not observed in non-malignant cells, making this technique highly specific . Flow cyAs part of the diagnostic workup for a patient with suspected leukemia, flow cytometric analysis is performed on bone marrow cell preparations with several pre-determined antibody panels. The lymphoblasts are identified based on their abnormal expression of these markers, a so-called leukemia-associated immunophenotype . The floOne of the challenges of CSF flow cytometric analysis is the paucity of malignant cells in the CSF. For bone marrow MRD analysis via flow cytometry, a requirement of a minimum of 10 identified blasts has been applied to ensure that the events represent an actual leukemic cell population . SimilarFlow cytometry requires intact cells for analysis, and therefore the sensitivity of the analysis will also decrease with the degradation of lymphocytes in the CSF. However, the cells can be fixed prior to flow cytometry, e.g., via the collection of CSF directly into specialized Transfix tubes containing an optimized formaldehyde solution with EDTA for the preservation of CSF cells . Our groIn childhood ALL, several studies have used flow cytometry for the detection of leukemic blasts in CSF . CNS invIn several studies, samples with discrepant CSF flow and cytospin results were reported, i.e., cases that are positive based on cytospin analysis but not based on flow analysis. In all studies, the discrepant results affected less than 5% (range 0.5%–4.4%) of samples ,37,38,41n = 17), three patients (17.6%) were identified with CNS involvement via cytospin analysis compared to two patients via flow cytometry (11.7%) [n = 13), only patients with isolated bone marrow relapse were included, and more than half of these seemingly CNS disease-free patients were positive via CSF flow cytometry [Two studies also collected CSF samples for flow cytometric analysis at relapse. In one of these studies ( (11.7%) . In the ytometry . Two stuytometry ,39. Afteytometry . In our ytometry . Thus, CAccumulating evidence supports the prognostic significance of CSF flow cytometry in childhood ALL. Out of six studies reporting relapse or survival estimates for flow-positive versus flow-negative patients , five stn = ~700 patients) by the NOPHO group, multivariate analysis including known risk factors  confirmed that CNS positivity via flow analysis was an independent risk factor for relapse (HR 2.2 (95% CI 1.0–4.7)) [Since CNS involvement in childhood ALL is more prevalent among patients with other high-risk factors, it is important to confirm that the prognostic significance of flow positivity is an independent risk factor for relapse. In a large study (.0–4.7)) . A few s.0–4.7)) ,36. MultA traumatic lumbar puncture (TLP) refers to artificial blood contamination of the CSF (≥10 erythrocytes per µL CSF) that can occur during the puncture procedure. TLP has previously been associated with blasts in the CSF and an increased risk of CNS relapse in childhood ALL ,28,43,44p < 0.001) [p = 0.027) [p = 0.173) [Four studies showed that flow cytometry could detect low-level CNS disease in follow-up samples ,35,37,39= 0.027) . The sam= 0.173) .The current literature clearly shows that CSF flow cytometry markedly increases the detection rates of CNS involvement in childhood ALL compared to cytospin, supporting the proposition that CSF flow cytometry should be incorporated as part of routine diagnostics to increase the sensitivity of CNS leukemia detection. Several studies have also reported a small fraction of samples (<5%) with discrepant cytospin and flow cytometry results, i.e., samples that were only classified as CNS-positive via cytospin analyses, which might largely be attributed to technical issues in relation to sampling and transportation.Increasing evidence supports that CNS involvement determined via CSF flow cytometry is associated with poorer prognosis and a higher risk of CNS relapse. However, the question of how this knowledge should be translated into risk stratification and the allocation of CNS-directed treatment currently remains unanswered. Not all patients who are CSF flow-positive at diagnosis develop relapse and further research is needed to clarify if CNS involvement at very low levels translates into a higher risk of relapse to determine which patients will benefit from more intensive CNS-directed therapy. Furthermore, it is also important to determine if negative CSF flow cytometry at diagnosis can identify very-low-risk patients in whom CNS-directed therapy can be reduced or even omitted.High-sensitivity monitoring of CNS involvement during treatment and the question of how the slow clearance of leukemic blasts correlates to outcomes represent interesting prospects related to the use of CSF flow cytometry in childhood ALL. If slow clearance indicates a higher risk of treatment failure or CNS relapse, this technique could be used for the monitoring of treatment and risk assignment by means of “CSF MRD”, similarly to bone marrow MRD, performed as part of current treatment protocols. However, the existing data are scarce, and this concept should be explored in larger patient cohorts to determine if low-level CNS involvement during treatment signifies high-risk patients who require intensified CNS-directed therapy.Despite the large body of data supporting the superior sensitivity of CSF flow cytometry compared to cytospin, the current cytospin methodology could be significantly improved. Increasing the volume of CSF used for cytospin, reducing the time to sample processing or developing methods for the better preservation of cells compatible with May–Grunwald–Giemsa staining will improve the sensitivity of cytospin analysis. However, discriminating between atypical lymphocytes and malignant blasts will still be difficult when few blasts are present, and in terms of specificity, CSF flow analysis remains superior to cytospin. A drawback of flow cytometry is that this technique is more expensive than cytospin in terms of reagents and instrumentation, and therefore less accessible in lower-income countries. Both techniques should therefore be further developed to ensure access to CNS leukemia diagnostics in all parts of the world.ALL is the childhood malignancy in which CSF flow cytometry has been most extensively studied. However, this technique also holds potential for the detection of disseminated malignant cells in other hematological and solid cancers characterized by CNS involvement. CSF flow cytometry has demonstrated promising results in adults with acute myeloid leukemia (AML) ,46 and n


We report here the identification and validation of prefoldin 5-alpha (PFDN5-α) for the first time as prognostic biomarker for prediction of central nervous system (CNS) leukemia of B cell acute lymphoblastic leukemia (B-ALL) origin. Since cerebrospinal fluid (CSF) cytology being the gold standard of diagnosis for CNS leukemia with poor sensitivity, mandatory prophylactic intrathecal chemotherapy is administered irrespective of patients develop CNS leukemia. Thus, using interactome studies, we identified PFDN5-α as a prognostic biomarker for predicting CNS leukemia by interacting lymphoblastic proteins and CSF from B-ALL patients using far-western clinical proteomics approach. Validation by both western and ELISA methods confirmed our results. For further clinical translation, we performed Receiver Operating Characteristic (ROC) curve analysis generated from CNS +ve (n = 25) and −ve (n = 40) CSF samples from B-ALL patients and identified PFDN5-α-CSF reactivity cut-off value as 0.456. Values below 0.456 indicate the patient is at risk of developing CNS leukemia and suggestive of having intrathecal chemotherapy. Further flow cytometry validation for CNS leukemia positivity revealed that with increasing blast cells, a decrease in PFDN5-α-CSF reactivity confirming ELISA based PFDN5α-CSF reactivity assay. Predicting CNS leukemia development risk by ELISA based PFDN5-α-CSF reactivity assay could have potential in the clinical management of CNS leukemia. Despite CSF cytology being the gold standard for diagnosing CNS leukemia4, the poor sensitivity results in mandatory prophylactic intrathecal chemotherapy irrespective of patients developing CNS leukemia with substantial neurological consequences6. Thus, discovering prognostic markers towards predicting CNS leukemia is essential. Despite polymerase chain reaction and flow cytometric evaluation of CSF could identify 50% of CNS leukemia in B-ALL patients at presentation, lack of clinically correlative standardized data makes CNS leukemia prediction challenging2. Similarly, T-cell immunophenotype and cytogenetic abnormalities also failed to predict CNS involvement8. However, different molecular interactions seen in CNS leukemia11 could be explored towards identifying prognostic markers. Therefore, we hypothesized that sub-microscopic disease specific biochemical CSF entities may interact with lymphoblastic proteins and these interactions could assist in discovering potential markers for predicting CNS leukemia. Though the daunting challenge of identifying interactions between two unknown molecules belonging to CSF and lymphoblastic proteins exists, the established far-western interactome technology was effective in deciphering molecules belonging to such interactions12. Thus, lymphoblastic proteins and CSF components of B-ALL patients at CNS positivity (presentation/relapse) and at remission (CNS negative) were interacted using far-western technique to obtain an interactome profile to identify specific interactions of clinical significance. In this report, we identified the protein PFDN5-α and validated its prognostic significance in predicting CNS leukemia in B-ALL patients. Further, we derived a cut-off value to predict the risk of developing CNS leukemia that prophylactic intrathecal chemotherapy could be avoided.Central nervous system B-ALLUrea and Thiourea, Bromophenol blue, Tris-base, Ammonium persulfate, Bradford protein assay reagent CHAPS, Iodoacetamide, DTT, E64, IPTG, Sodium carbonate, Sodium bicarbonate, TMB, DMSO, Aprotinin, Tryptone, SDS, Ni-agarose beads, Trypsin and Trypsin reaction buffer were from Sigma-Aldrich, USA. ASB-14-4 , Ampholyte (pH 3–10), IPG strips pH 3–10 and Mineral oil (biotechnology grade) (Bio-Rad), TEMED, Ethanol , Methanol . Penicillin/streptomycin, Hybridoma serum free medium and Fetal bovine serum (FBS) and TOP10 from Invitrogen, USA. Protogel , Amicon ultra-4 centrifugal filter unit, PVDF , Streptavidin-HRP conjugate Biotin , X-ray film and X-ray Cassette , Developer and Fixer , Acetonitrile and Ammonium bicarbonate , ESI-Q-TOF , Ampicillin and Kanamycin , pCMV-XL5- gene construct of PFDN5α, CIP29, ECH1 and PRDX6 . EcoRI, NotI, DNA ladder and T4 Ligase , QIAquick kit , BL21 , pET28a vector , DH5α , Ammonium acetate, NaCl, Tween 20, Acetone, Yeast extract, Disodium hydrogen phosphate and HCl , Multiplate reader .The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of Amrita Institute of Medical Sciences (IEC-AIMS-2016 Dated 25-01-2016). CSF samples from B-ALL patients were collected at CNS +ve (presentation/relapse positive for blast cells)/CNS –ve remission status with written informed consent from all subjects involved in the study according to institutional human ethics committee guidelines with approval. CSF includes sequential samples from B-ALL patients of various age groups, both genders with different cytogenetics abnormalities and treatments Table .g for 5 min at 4 °C) to remove any cells and were kept as aliquots at − 80 °C until processed. CSF biotinylation were carried out with 20 mM biotin (10% v/v) to CSF for 3.5 h at room temperature and then stored at − 20 °C as per Menon et al.12.The CSF samples obtained from the same  and different patients were spun down . Cells were cultured in serum-free hybridoma medium containing 10% FBS and 1% penicillin/streptomycin at 37 °C in 5% COProtein estimation of concentrated cell lysate was assayed using Bradford reagent and absorbance was measured at 595 nm using micro plate reader.13. Briefly, 200 µg total proteins from lysate sample were taken in 125 µL of rehydration buffer and rehydrated actively at 50 V/20 °C for 18 h using IEF cell (Bio-Rad). After rehydration, the strip was subjected to IEF as described before13. This is followed by incubation in equilibration buffer  with 0.3% DTT for 10 min. Subsequently, incubated with 4.5% iodoacetamide containing equilibration buffer for 10 min and subjected to SDS-PAGE. Proteins resolved in the gel were visualized by silver staining or used for western blotting12.2D-PAGE was performed essentially the same way as described in Xavier et al.13. For far western, biotinylated CSF sample (2.0 µg concentration CSF proteins in 1 mL of 5% gelatin at 4 °C overnight) from patient was probed against lymphoblastic proteins on a 2D western blot. The blots were washed 3 times 10 min each in TBST  and subjected to streptavidin-HRP staining (1 in 3000 dilutions with 5% milk in TBST). The chemiluminescence signal following CSF reactivity to protein spots was captured on X-ray film. Subsequently, the CSF reactivity pattern obtained with CNS +ve at presentation was compared with sequential CSF samples reactivity pattern from the same patient collected at different periods of remission respectively. The procedure was repeated for other patient CSF samples. The sequential samples from patients varied in time frame from 3 weeks to 1.5 years. The intra and inter patient reactivity pattern analysis between three patients resulted in identification of 4 specific spots with consistent reactivity to CNS +ve/−ve CSF.2D-PAGE was performed using 200 µg total proteins as described aboveThe CSF reactive spots corresponding to the spots marked in Fig. 12. The gel piece was dehydrated by incubation for 30 min at room temperature in 100% acetonitrile with occasional vortexing. Then the gel piece was dried in vacuum and ice cold trypsin reaction buffer was added to cover the gel piece. The mixture was incubated at 37 °C for overnight till the gel piece becomes saturated with trypsin. The supernatant containing digested protein in the spot was collected. The proteins were identified by mass spectroscopy analysis using ESI Q-TOF mass spectrometry12.Based on the comparison of the CSF reactivity profile towards proteins of lymphoblastic origin on a 2D blot, the protein spots which showed differential reactivity to CSF (spot 1–4) were cut out from the Coomassie stained gel and de-stained with 100 mM ammonium bicarbonate/Acetonitrile (1:1 vol/vol) solution and spun downThe pCMV6-XL5-PFDN5α was transformed to DH5α competent cells for plasmid amplification and subsequently purified by alkaline lysis method. The gene insert (PFDN5α) was excised from pCMV6-XL5 vector and ligated to pET28a bacterial expression vector. Subsequently transformed into BL21 strain and optimized the conditions for expression of protein/s.200 mL culture of transformed BL21 (with pET28a-PFDN5α) was induced using 0.5 mM IPTG at 37 °C for protein production. After 5 h of induction, cells were pelleted down, lysed in lysis buffer of pH 8.0  containing protease inhibitors, sonicated to remove the aggregates and centrifuged at 14,000 rpm for 5 min. Supernatant containing the expressed protein was collected and subjected to Ni-NTA column purification as described by the manufacturer Sigma.The purified recombinant PFDN5α (2 µg) was western blotted to PVDF membrane and probed with biotinylated CSF samples from B-ALL patients as before and the reactivity was quantified using Image J software. For ELISA, 300 ng of purified recombinant PFDN5α protein coated on 96 well plates were incubated with 35 ng of biotinylated CSF samples from the patients for 1 h at room temperature. Washed three times with TBST (TBS with 0.05% Tween 20) and incubated with Streptavidin HRP for 1 h at room temperature (1/7000 dilutions in 1% BSA). Washed in TBST for three times and incubated with HRP substrate TMB for 10 min. The reaction was stopped by adding 1 N HCl and the color was measured at 450 nm.g for 5 min at 4 °C. The supernatant was stored at − 80 °C for PFDN5α ELISA validation and the cells were resuspended in 100 µL of remaining CSF. The antibody combination was added to the tubes for immunostaining. After staining 2 mL sheath fluid (BD) was added to the tube and centrifuged at 2500 rpm for 3 min, resuspended the pellet in 100 µL of sheath fluid, and acquired immediately on BD FACS Canto II. The tubes were acquired until empty to collect all the events. After acquisition the debris were excluded from the events by setting up the forward scatter and side scatter threshold. For B-ALL, cells were identified using CD45 plots. A gate was generated using CD19 and CD34 antibody channels and events showing CD19/CD34 positive cell cluster as well as CD34 alone positive cells were considered as blast/aberrant phenotypes.A minimum of 1 mL of CSF was collected in a tube and processed within 24 h of collection. CSF was centrifuged at 800t test assuming equal variances utilizing Graphpad Prism were carried out and statistical significance were set at p ≤ 0.05 and represented with star (*). Receiver operating characteristic curve (ROC) analysis was performed using SPSS software version 22.0 to identify a cut off value to predict CNS positivity in B-ALL patients. For flow cytometry-based samples and respective ELISA, one tailed unpaired analysis was carried out with unequal variance. For flow cytometry-based samples and respective ELISA, one tailed unpaired analysis was carried out with unequal variance.Unpaired two-tailed Students 12. Since biotin forms covalent bonds with primary amines of CSF proteins, unified protein tagging was achieved demonstrated by detection of the same proteins bands resolved in SDS-PAGE by silver staining and streptavidin-HRP staining on far-western blots following SDS-PAGE . In contrast, proteins spots 2, 3 and 4 showed significantly high reactivity with CNS +ve CSF compared to CNS −ve (Fig. Further, far-western analysis was performed by interacting biotinylated CSF from CNS +ve/−ve samples with 2D profiled JM-1 pre-B lymphoblast cell line proteinsins Fig. . Quantif12. The spots 1–4 was identified as PFDN5α, CIP29, ECH1 and PRDX6 respectively (Table Based on the above interactome analysis showing promising difference in reactivity between CNS +ve and CNS −ve B-ALL CSF samples, protein spots 1–4 was excised out and subjected to mass spectrometry analysisly Table . Among tly Table . Using pp = 0.0018, Fig. This observation is similar to the results of 2D-far-western blots seen in Fig. p = 0.0001 (Fig. To further consolidate the significance of CSF-PFDN5α reactivity and to identify a cut-off value useful to predict CNS leukemia, we tested the CNS +ve/−ve B-ALL CSF reactivity using alternative ELISA platform. A total of 25 CNS +ve and 40 CNS −ve B-ALL CSF patient samples were evaluated for its differential CSF-PFDN5α interaction between CNS +ve and CNS −ve CSF patient samples and plotted to identify a cut-off value for CNS leukemia prediction Fig. A, S4B. T001 Fig.  towards 15 if there is discrete clonal population of cells with both CD19+/CD34+ with percentage of blast population should be ≥ 1% and below this value is considered negative by flow. In order to perform flow-based analysis, a total of seventeen B-ALL patient samples that are negative for CNS leukemia as per CSF cytomorphology were collected. Fourteen samples met our criteria and considered as flow positive and the remaining 3 were considered flow negative. All CSF samples were validated for their reactivity to PFDN5-α using ELISA quantitative assay as described in our manuscript. Following analysis by flow cytometry, we found that with increasing number of cells that are CD34+ and CD19+, the CSF reactivity to PFDN5-α decreases (Table Based on the ELISA reactivity to PFDN5-α, we verified whether flow cytometric approach of determining CNS positivity in terms of cell number correlates with ELISA based CSF reactivity to PFDN5-α. All the cases used in this study were negative by cytomorphology. We categorized the samples as flow positive or negative based on two criteria. The samples are considered as flow positive12 and identified four spots that showed differential CSF reactivity to CNS +ve/−ve B-ALL CSF among the many protein spots profiled on 2D-western blot [Fig. 17. Moreover, point mutations in PFDN5α lead to abolition of above activities and are associated with leukemia and lymphoma16. Thus, validation of PFDN5α-CSF reactivity is crucial in proving its role as a prognostic marker. Our results on validation analysis clearly show that PFDN5α could serve as a potential prognostic marker in predicting CNS leukemia in B-ALL patients following 1D western analysis against purified recombinant proteins (Fig. 18. Thus, PFDN5α-CSF interactions in B-ALL could turn out to be an important tool in the prognostication of CNS leukemia and reduce the burden and side effects associated with prophylactic intrathecal chemotherapy to some extent. In order to further develop an assay, and identify a cut-off value for prediction of risk of a B-ALL patient developing CNS leukemia in addition to its validation, we further assessed PFDN5α-CSF reactivity using ELISA platform (Fig. In the quest towards identifying a potential biomarker for predicting CNS leukemia in B-ALL patients, we used our established far-western clinical proteomics approachins Fig. . The datorm Fig. A, S4B. Torm Fig. . This obAnother important observation we noticed was the PFDN5-α ELISA assay is not dependent on the leukemia cell concentration in the CSF Table . CNS leuSupplementary Information.