Utilization of fluid-based biomarkers as endpoints in disease-modifying clinical trials for Alzheimer's disease: a systematic review.

BACKGROUND: Clinical trials in Alzheimer's disease (AD) had high failure rates for several reasons, including the lack of biological endpoints. Fluid-based biomarkers may present a solution to measure biologically relevant endpoints. It is currently unclear to what extent fluid-based biomarkers are applied to support drug development. METHODS: We systematically reviewed 272 trials (clinicaltrials.gov) with disease-modifying therapies starting between 01-01-2017 and 01-01-2024 and identified which CSF and/or blood-based biomarker endpoints were used per purpose and trial type. RESULTS: We found that 44% (N = 121) of the trials employed fluid-based biomarker endpoints among which the CSF ATN biomarkers (Aß (42/40), p/tTau) were used most frequently. In blood, inflammatory cytokines, NFL, and pTau were most frequently employed. Blood- and CSF-based biomarkers were used approximately equally. Target engagement biomarkers were used in 26% (N = 72) of the trials, mainly in drugs targeting inflammation and amyloid. Lack of target engagement markers is most prominent in synaptic plasticity/neuroprotection, neurotransmitter receptor, vasculature, epigenetic regulators, proteostasis and, gut-brain axis targeting drugs. Positive biomarker results did not always translate to cognitive effects, most commonly the small significant reductions in CSF tau isoforms that were seen following anti-Tau treatments. On the other hand, the positive anti-amyloid trials results on cognitive function were supported by clear effect in most fluid markers. CONCLUSIONS: As the field moves towards primary prevention, we expect an increase in the use of fluid-based biomarkers to determine disease modification. Use of blood-based biomarkers will rapidly increase, but CSF markers remain important to determine brain-specific treatment effects. With improving techniques, new biomarkers can be found to diversify the possibilities in measuring treatment effects and target engagement. It remains important to interpret biomarker results in the context of the trial and be aware of the performance of the biomarker. Diversifying biomarkers could aid in the development of surrogacy biomarkers for different drug targets.

Clinical Accuracy of Serum Neurofilament Light to Differentiate Frontotemporal Dementia from Primary Psychiatric Disorders is Age-Dependent.

BACKGROUND: Symptoms of behavioral variant frontotemporal dementia (bvFTD) overlap with primary psychiatric disorders (PPD) making diagnosis challenging. Serum neurofilament light (sNfL) is a candidate biomarker to distinguish bvFTD from PPD, but large-scale studies in PPD are lacking. OBJECTIVE: Determine factors that influence sNfL from a large database of PPD patients, and test its diagnostic accuracy. DESIGN, SETTINGS, SUBJECTS, MEASUREMENTS: Clinical data of people aged 40-81 were obtained from healthy subjects (n = 69), and patients with PPD (n = 848) or bvFTD (n = 82). sNfL was measured using Simoa technology on an HD-X instrument. Data were analyzed using general linear models, and Receiver Operating Characteristic (ROC) curve analyses to determine global and age-specific sNfL cutoffs to distinguish bvFTD from PPD, using the Youden Index. RESULTS: sNfL increased with age, while sex, BMI and diabetes status were modestly associated with sNfL. sNfL was slightly higher in PPD than healthy subjects (14.1 versus 11.7 pg/mL), when controlling for covariates. sNfL was markedly lower in PPD than bvFTD (14.1 versus 44.1 pg/mL). sNfL could differentiate PPD from bvFTD with an AUC = 0.868, but the effect was driven by the younger subjects between age 40-60 years at a cutoff of 16.0 pg/mL. No valid cutoff was detected over age 60, however, values of sNfL above 38.5 pg/mL, or below 13.9 pg/mL, provided 90% diagnostic certainty of bvFTD or PPD, respectively. CONCLUSION: PPD have mildly elevated sNfL compared to healthy subjects but much lower than bvFTD. Results support the use of sNfL as a biomarker to differentiate PPD from bvFTD at age 60 or below, but accuracy decreases in older ages.

Connecting dementia risk loci to the CSF proteome identifies pathophysiological leads for dementia.

Genome-wide association studies have successfully identified many genetic risk loci for dementia, but exact biological mechanisms through which genetic risk factors contribute to dementia remains unclear. Integrating CSF proteomic data with dementia risk loci could reveal intermediate molecular pathways connecting genetic variance to the development of dementia. We tested to what extent effects of known dementia risk loci can be observed in CSF levels of 665 proteins (proximity extension-based (PEA) immunoassays) in a deeply-phenotyped mixed-memory clinic cohort (n=502, mean age (sd) = 64.1 [8.7] years, 181 female [35.4%]), including patients with Alzheimer's disease (AD, n=213), dementia with Lewy bodies (DLB, n=50) and frontotemporal dementia (FTD, n=93), and controls (n=146). Validation was assessed in independent cohorts (n=99 PEA platform, n=198, MRM-targeted mass spectroscopy and multiplex assay). We performed additional analyses stratified according to diagnostic status (AD, DLB, FTD and controls separately), to explore whether associations between CSF proteins and genetic variants were specific to disease or not. We identified four AD risk loci as protein quantitative trait loci (pQTL): CR1-CR2 (rs3818361, P=1.65e-08), ZCWPW1-PILRB (rs1476679, P=2.73e-32), CTSH-CTSH (rs3784539, P=2.88e-24) and HESX1-RETN (rs186108507, P=8.39e-08), of which the first three pQTLs showed direct replication in the independent cohorts. We identified one AD-specific association between a rare genetic variant of TREM2 and CSF IL6 levels (rs75932628, P = 3.90e-7). DLB risk locus GBA showed positive trans effects on seven inter-related CSF levels in DLB patients only. No pQTLs were identified for frontotemporal dementia, either for the total sample as for analyses performed within FTD only. pQTL variants were involved in the immune system, highlighting the importance of this system in the pathophysiology of dementia. We further identified pQTLs in stratified analyses for AD and DLB, hinting at disease-specific pQTLs in dementia. Dissecting the contribution of risk loci to neurobiological processes aids in understanding disease mechanisms underlying dementia.

Neurofilament light protein as a biomarker for spinal muscular atrophy: a review and reference ranges.

Spinal muscular atrophy (SMA) is the leading genetic cause of infant mortality, characterized by progressive neuromuscular degeneration resulting from mutations in the survival motor neuron (SMN1) gene. The availability of disease-modifying therapies for SMA therapies highlights the pressing need for easily accessible and cost-effective blood biomarkers to monitor treatment response and for better disease management. Additionally, the wide implementation of newborn genetic screening programs in Western countries enables presymptomatic diagnosis of SMA and immediate treatment administration. However, the absence of monitoring and prognostic blood biomarkers for neurodegeneration in SMA hinders effective disease management. Neurofilament light protein (NfL) is a promising biomarker of neuroaxonal damage in SMA and reflects disease progression in children with SMA undergoing treatment. Recently, the European Medicines Agency issued a letter of support endorsing the potential utilization of NfL as a biomarker of pediatric neurological diseases, including SMA. Within this review, we comprehensively assess the potential applications of NfL as a monitoring biomarker for disease severity and treatment response in pediatric-onset SMA. We provide reference ranges for normal levels of serum based NfL in neurologically healthy children aged 0-18 years. These reference ranges enable accurate interpretation of NfL levels in children and can accelerate the implementation of NfL into clinical practice.

Cerebrospinal fluid proteomics in patients with Alzheimer's disease reveals five molecular subtypes with distinct genetic risk profiles.

Alzheimer's disease (AD) is heterogenous at the molecular level. Understanding this heterogeneity is critical for AD drug development. Here we define AD molecular subtypes using mass spectrometry proteomics in cerebrospinal fluid, based on 1,058 proteins, with different levels in individuals with AD (n = 419) compared to controls (n = 187). These AD subtypes had alterations in protein levels that were associated with distinct molecular processes: subtype 1 was characterized by proteins related to neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood-brain barrier impairment. Each subtype was related to specific AD genetic risk variants, for example, subtype 1 was enriched with TREM2 R47H. Subtypes also differed in clinical outcomes, survival times and anatomical patterns of brain atrophy. These results indicate molecular heterogeneity in AD and highlight the need for personalized medicine.

Delirium pathophysiology in cancer: neurofilament light chain biomarker - narrative review.

Background Delirium is a debilitating disorder with high prevalence near the end of life, impacting quality of life of patients and their relatives. Timely recognition of delirium can lead to prevention and/or better treatment of delirium. According to current hypotheses delirium is thought to result from aberrant inflammation and neurotransmission, with a possible role for neuronal damage. Neurofilament light chain (NfL) is a protein biomarker in body fluids that is unique to neurons, with elevated levels when neurons are damaged, making NfL a viable biomarker for early detection of delirium. This narrative review summarises current research regarding the pathophysiology of delirium and the potential of NfL as a susceptibility biomarker for delirium and places this in the context of care for patients with advanced cancer.Results Six studies were conducted exclusively on NfL in patients with delirium. Three of these studies demonstrated that high plasma NfL levels preoperatively predict delirium in older adult patients postoperatively. Two studies demonstrated that high levels of NfL in intensive care unit (ICU) patients are correlated with delirium duration and severity. One study found that incident delirium in older adult patients was associated with increased median NfL levels during hospitalisation.Conclusions Targeted studies are required to understand if NfL is a susceptibility biomarker for delirium in patients with advanced cancer. In this palliative care context, better accessible matrices, such as saliva or urine, would be helpful for repetitive testing. Improvement of biological measures for delirium can lead to improved early recognition and lay the groundwork for novel therapeutic strategies.

CSF proteome profiling reveals biomarkers to discriminate dementia with Lewy bodies from Alzheimer´s disease.

Diagnosis of dementia with Lewy bodies (DLB) is challenging and specific biofluid biomarkers are highly needed. We employed proximity extension-based assays to measure 665 proteins in the cerebrospinal fluid (CSF) from patients with DLB (n = 109), Alzheimer´s disease (AD, n = 235) and cognitively unimpaired controls (n = 190). We identified over 50 CSF proteins dysregulated in DLB, enriched in myelination processes among others. The dopamine biosynthesis enzyme DDC was the strongest dysregulated protein, and could efficiently discriminate DLB from controls and AD (AUC:0.91 and 0.81 respectively). Classification modeling unveiled a 7-CSF biomarker panel that better discriminate DLB from AD (AUC:0.93). A custom multiplex panel for six of these markers (DDC, CRH, MMP-3, ABL1, MMP-10, THOP1) was developed and validated in independent cohorts, including an AD and DLB autopsy cohort. This DLB CSF proteome study identifies DLB-specific protein changes and translates these findings to a practicable biomarker panel that accurately identifies DLB patients, providing promising diagnostic and clinical trial testing opportunities.

Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias.

Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.

Clinical Value of Longitudinal Serum Neurofilament Light Chain in Prodromal Genetic Frontotemporal Dementia.

BACKGROUND AND OBJECTIVES: Elevated serum neurofilament light chain (NfL) is used to identify carriers of genetic frontotemporal dementia (FTD) pathogenic variants approaching prodromal conversion. Yet, the magnitude and timeline of NfL increase are still unclear. Here, we investigated the predictive and early diagnostic value of longitudinal serum NfL for the prodromal conversion in genetic FTD. METHODS: In a longitudinal observational cohort study of genetic FTD pathogenic variant carriers, we examined the diagnostic accuracy and conversion risk associated with cross-sectional and longitudinal NfL. Time periods relative to prodromal conversion (>3, 3-1.5, 1.5-0 years before; 0-1.5 years after) were compared with values of participants who did not convert. Next, we modeled longitudinal NfL and MRI volume trajectories to determine their timeline. RESULTS: We included 21 participants who converted (5 chromosome 9 open-reading frame 72 [C9orf72], 10 progranulin [GRN], 5 microtubule-associated protein tau [MAPT], and 1 TAR DNA-binding protein [TARDBP]) and 61 who did not (20 C9orf72, 30 GRN, and 11 MAPT). Participants who converted had higher NfL levels at all examined periods before prodromal conversion (median values 14.0-18.2 pg/mL; betas = 0.4-0.7, standard error [SE] = 0.1, p < 0.046) than those who did not (6.5 pg/mL) and showed further increase 0-1.5 years after conversion (28.4 pg/mL; beta = 1.0, SE = 0.1, p < 0.001). Annualized longitudinal NfL change was only significantly higher in participants who converted (vs. participants who did not) 0-1.5 years after conversion (beta = 1.2, SE = 0.3, p = 0.001). Diagnostic accuracy of cross-sectional NfL for prodromal conversion (vs. nonconversion) was good-to-excellent at time periods before conversion (area under the curve range: 0.72-0.92), improved 0-1.5 years after conversion (0.94-0.97), and outperformed annualized longitudinal change (0.76-0.84). NfL increase in participants who converted occurred earlier than frontotemporal MRI volume change and differed by genetic group and clinical phenotypes. Higher NfL corresponded to increased conversion risk (hazard ratio: cross-sectional = 6.7 [95% CI 3.3-13.7]; longitudinal = 13.0 [95% CI 4.0-42.8]; p < 0.001), but conversion-free follow-up time varied greatly across participants. DISCUSSION: NfL increase discriminates individuals who convert to prodromal FTD from those who do not, preceding significant frontotemporal MRI volume loss. However, NfL alone is limited in predicting the exact timing of prodromal conversion. NfL levels also vary depending on underlying variant-carrying genes and clinical phenotypes. These findings help to guide participant recruitment for clinical trials targeting prodromal genetic FTD.

CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease.

Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.

Urine as matrix for analysis of neurofilament light chain is not suitable to distinguish frontotemporal dementia from psychiatric diseases.

The clinical overlap of frontotemporal dementia and primary psychiatric diseases hampers diagnostic distinction, leading to frequent misdiagnosis and diagnostic delay. Neurofilament light chain has shown great potential in CSF and blood for the distinction of frontotemporal dementia from primary psychiatric diseases. Measurement of neurofilament light chain in urine would be even more patient-friendly. We aimed to test the performance of neurofilament light chain urine measurements for diagnostics in frontotemporal dementia and to assess their correlation with serum levels. Fifty-five subjects (n = 19 frontotemporal dementia, n = 19 primary psychiatric diseases and n = 17 controls) were included with available paired urine and serum samples. All subjects underwent standardized extensive diagnostic assessment. Samples were analysed with the ultrasensitive single molecule array neurofilament light chain assay. Neurofilament light chain group comparisons were performed adjusted for age, sex and geriatric depression scale. In the majority of the cohort, neurofilament light chain concentrations were not detectable in urine (n = 6 samples above lower limit of detection (0.038 pg/ml): n = 5 frontotemporal dementia, n = 1 primary psychiatric disease). The frequency of a detectable neurofilament light chain level in urine in the frontotemporal dementia group did not differ from psychiatric disorders (Fisher Exact-test P = 0.180). In the individuals with detectable urine neurofilament light chain values, there was no correlation between the urine and serum neurofilament light chain levels. As expected, serum neurofilament light chain levels were higher in frontotemporal dementia compared to primary psychiatric diseases and controls (P < 0.001), adjusted for age, sex and geriatric depression scale. Receiver operating characteristic curve analysis of serum neurofilament light chain of frontotemporal dementia versus primary psychiatric diseases showed an area under the curve of 0.978 95% confidence interval 0.941-1.000, P < 0.001. Urine is not suitable as a matrix for neurofilament light chain analysis and serum neurofilament light chain is still the most patient-friendly matrix for differentiation between frontotemporal dementia and primary psychiatric diseases.

Discovery of novel CSF biomarkers to predict progression in dementia using machine learning.

Providing an accurate prognosis for individual dementia patients remains a challenge since they greatly differ in rates of cognitive decline. In this study, we used machine learning techniques with the aim to identify cerebrospinal fluid (CSF) biomarkers that predict the rate of cognitive decline within dementia patients. First, longitudinal mini-mental state examination scores (MMSE) of 210 dementia patients were used to create fast and slow progression groups. Second, we trained random forest classifiers on CSF proteomic profiles and obtained a well-performing prediction model for the progression group (ROC-AUC = 0.82). As a third step, Shapley values and Gini feature importance measures were used to interpret the model performance and identify top biomarker candidates for predicting the rate of cognitive decline. Finally, we explored the potential for each of the 20 top candidates in internal sensitivity analyses. TNFRSF4 and TGF [Formula: see text]-1 emerged as the top markers, being lower in fast-progressing patients compared to slow-progressing patients. Proteins of which a low concentration was associated with fast progression were enriched for cell signalling and immune response pathways. None of our top markers stood out as strong individual predictors of subsequent cognitive decline. This could be explained by small effect sizes per protein and biological heterogeneity among dementia patients. Taken together, this study presents a novel progression biomarker identification framework and protein leads for personalised prediction of cognitive decline in dementia.

Protein disulfide isomerases as CSF biomarkers for the neuronal response to tau pathology.

INTRODUCTION: Cerebrospinal fluid (CSF) biomarkers for specific cellular disease processes are lacking for tauopathies. In this translational study we aimed to identify CSF biomarkers reflecting early tau pathology-associated unfolded protein response (UPR) activation. METHODS: We employed mass spectrometry proteomics and targeted immunoanalysis in a combination of biomarker discovery in primary mouse neurons in vitro and validation in patient CSF from two independent large multicentre cohorts (EMIF-AD MBD, n = 310; PRIDE, n = 771). RESULTS: First, we identify members of the protein disulfide isomerase (PDI) family in the neuronal UPR-activated secretome and validate secretion upon tau aggregation in vitro. Next, we demonstrate that PDIA1 and PDIA3 levels correlate with total- and phosphorylated-tau levels in CSF. PDIA1 levels are increased in CSF from AD patients compared to controls and patients with tau-unrelated frontotemporal and Lewy body dementia (LBD). HIGHLIGHTS: Neuronal unfolded protein response (UPR) activation induces the secretion of protein disulfide isomerases (PDIs) in vitro. PDIA1 is secreted upon tau aggregation in neurons in vitro. PDIA1 and PDIA3 levels correlate with total and phosphorylated tau levels in CSF. PDIA1 levels are increased in CSF from Alzheimer's disease (AD) patients compared to controls. PDIA1 levels are not increased in CSF from tau-unrelated frontotemporal dementia (FTD) and Lewy body dementia (LBD) patients.

Plasma glial fibrillary acidic protein in autosomal dominant Alzheimer's disease: Associations with Aß-PET, neurodegeneration, and cognition.

BACKGROUND: Glial fibrillary acidic protein (GFAP) is a promising candidate blood-based biomarker for Alzheimer's disease (AD) diagnosis and prognostication. The timing of its disease-associated changes, its clinical correlates, and biofluid-type dependency will influence its clinical utility. METHODS: We evaluated plasma, serum, and cerebrospinal fluid (CSF) GFAP in families with autosomal dominant AD (ADAD), leveraging the predictable age at symptom onset to determine changes by stage of disease. RESULTS: Plasma GFAP elevations appear a decade before expected symptom onset, after amyloid beta (Aß) accumulation and prior to neurodegeneration and cognitive decline. Plasma GFAP distinguished Aß-positive from Aß-negative ADAD participants and showed a stronger relationship with Aß load in asymptomatic than symptomatic ADAD. Higher plasma GFAP was associated with the degree and rate of neurodegeneration and cognitive impairment. Serum GFAP showed similar relationships, but these were less pronounced for CSF GFAP. CONCLUSION: Our findings support a role for plasma GFAP as a clinical biomarker of Aß-related astrocyte reactivity that is associated with cognitive decline and neurodegeneration. HIGHLIGHTS: Plasma glial fibrillary acidic protein (GFAP) elevations appear a decade before expected symptom onset in autosomal dominant Alzheimer's disease (ADAD). Plasma GFAP was associated to amyloid positivity in asymptomatic ADAD. Plasma GFAP increased with clinical severity and predicted disease progression. Plasma and serum GFAP carried similar information in ADAD, while cerebrospinal fluid GFAP did not.

Age- and disease-specific reference values for neurofilament light presented in an online interactive support interface.

Interpretation of axonal damage biomarker Neurofilament Light chain (NfL) concentrations is difficult due to the lack of age-specific and disease-specific reference values. We here developed an interactive interface to support interpretation of NfL results in human body fluids. We used NfL values of 1698 individuals without a neurological disorder, aged 19-85 years, and patients with MS and dementias. Percentile regression estimates per diagnosis populate interactive graphs, alongside NfL background information (available on: https://mybiomarkers.shinyapps.io/Neurofilament). This accessible interface provides reference for interpretation of the individual patient results for clinicians. It showcases an adaptable method to support interpretation of age-dependent biomarkers in neurology.

Abnormal cerebrospinal fluid levels of amyloid and tau are associated with cognitive decline over time in cognitively normal older adults: A monozygotic twin study.

Introduction: The contribution of genetic and environmental factors to the relation between cerebrospinal fluid (CSF) biomarkers and cognitive decline in preclinical Alzheimer's disease remains unclear. We studied this in initially cognitively normal monozygotic twins. Methods: We included 122 cognitively normal monozygotic twins (51 pairs) with a follow-up of 4.3 ± 0.4 years. We first tested associations of baseline CSF Aß1-42/1-40 ratio, total tau (t-tau), and 181-phosphorylated-tau (p-tau) status with subsequent cognitive decline using linear mixed models, and then performed twin specific analyses. Results: Baseline abnormal amyloid-ß and tau CSF markers predicted steeper decline on memory (p ≤ .003) and language (p ≤ 0.04). Amyloid-ß and p-tau markers in one twin predicted decline in memory in the co-twin and tau markers in one twin predicted decline in language in the co-twin (r range -0.26,0.39; p's ≤ .02). Discussion: These results suggest that memory and language decline are early features of AD that are in part determined by the same genetic factors that influence amyloid-ß and tau regulation.

Detection and localization of early- and late-stage cancers using platelet RNA.

Cancer patients benefit from early tumor detection since treatment outcomes are more favorable for less advanced cancers. Platelets are involved in cancer progression and are considered a promising biosource for cancer detection, as they alter their RNA content upon local and systemic cues. We show that tumor-educated platelet (TEP) RNA-based blood tests enable the detection of 18 cancer types. With 99% specificity in asymptomatic controls, thromboSeq correctly detected the presence of cancer in two-thirds of 1,096 blood samples from stage I-IV cancer patients and in half of 352 stage I-III tumors. Symptomatic controls, including inflammatory and cardiovascular diseases, and benign tumors had increased false-positive test results with an average specificity of 78%. Moreover, thromboSeq determined the tumor site of origin in five different tumor types correctly in over 80% of the cancer patients. These results highlight the potential properties of TEP-derived RNA panels to supplement current approaches for blood-based cancer screening.

Neurofilament light increases over time in severe COVID-19 and is associated with delirium.

Neurological monitoring in sedated Intensive Care Unit patients is constrained by the lack of reliable blood-based biomarkers. Neurofilament light is a cross-disease biomarker for neuronal damage with potential clinical applicability for monitoring Intensive Care Unit patients. We studied the trajectory of neurofilament light over a month in Intensive Care Unit patients diagnosed with severe COVID-19 and explored its relation to clinical outcomes and pathophysiological predictors. Data were collected over a month in 31 Intensive Care Unit patients (166 plasma samples) diagnosed with severe COVID-19 at Amsterdam University Medical Centre, and in the first week after emergency department admission in 297 patients with COVID-19 (635 plasma samples) admitted to Massachusetts General hospital. We observed that Neurofilament light increased in a non-linear fashion in the first month of Intensive Care Unit admission and increases faster in the first week of Intensive Care Unit admission when compared with mild-moderate COVID-19 cases. We observed that baseline Neurofilament light did not predict mortality when corrected for age and renal function. Peak neurofilament light levels were associated with a longer duration of delirium after extubation in Intensive Care Unit patients. Disease severity, as measured by the sequential organ failure score, was associated to higher neurofilament light values, and tumour necrosis factor alpha levels at baseline were associated with higher levels of neurofilament light at baseline and a faster increase during admission. These data illustrate the dynamics of Neurofilament light in a critical care setting and show associations to delirium, disease severity and markers for inflammation. Our study contributes to determine the clinical utility and interpretation of neurofilament light levels in Intensive Care Unit patients.

Blood-based biomarkers for Alzheimer's disease: towards clinical implementation.

For many years, blood-based biomarkers for Alzheimer's disease seemed unattainable, but recent results have shown that they could become a reality. Convincing data generated with new high-sensitivity assays have emerged with remarkable consistency across different cohorts, but also independent of the precise analytical method used. Concentrations in blood of amyloid and phosphorylated tau proteins associate with the corresponding concentrations in CSF and with amyloid-PET or tau-PET scans. Moreover, other blood-based biomarkers of neurodegeneration, such as neurofilament light chain and glial fibrillary acidic protein, appear to provide information on disease progression and potential for monitoring treatment effects. Now the question emerges of when and how we can bring these biomarkers to clinical practice. This step would pave the way for blood-based biomarkers to support the diagnosis of, and development of treatments for, Alzheimer's disease and other dementias.

CSF proteome profiling across the Alzheimer's disease spectrum reflects the multifactorial nature of the disease and identifies specific biomarker panels.

Development of disease-modifying therapies against Alzheimer's disease (AD) requires biomarkers reflecting the diverse pathological pathways specific for AD. We measured 665 proteins in 797 cerebrospinal fluid (CSF) samples from patients with mild cognitive impairment with abnormal amyloid (MCI(Aß+): n = 50), AD-dementia (n = 230), non-AD dementias (n = 322) and cognitively unimpaired controls (n = 195) using proximity ligation-based immunoassays. Here we identified >100 CSF proteins dysregulated in MCI(Aß+) or AD compared to controls or non-AD dementias. Proteins dysregulated in MCI(Aß+) were primarily related to protein catabolism, energy metabolism and oxidative stress, whereas those specifically dysregulated in AD dementia were related to cell remodeling, vascular function and immune system. Classification modeling unveiled biomarker panels discriminating clinical groups with high accuracies (area under the curve (AUC): 0.85-0.99), which were translated into custom multiplex assays and validated in external and independent cohorts (AUC: 0.8-0.99). Overall, this study provides novel pathophysiological leads delineating the multifactorial nature of AD and potential biomarker tools for diagnostic settings or clinical trials.