Cerebrospinal Fluid Neurofilament Light Chain (NfL) Predicts Disease Aggressiveness in Amyotrophic Lateral Sclerosis: An Application of the D50 Disease Progression Model

Serum neurofilament light chain in distinct phenotypes of amyotrophic lateral sclerosis: A longitudinal, multicenter study

OBJECTIVE

To assess the performance of serum neurofilament light chain (sNfL) in clinical phenotypes of amyotrophic lateral sclerosis (ALS).

METHODS

In 2949 ALS patients at 16 ALS centers in Germany and Austria, clinical characteristics and sNfL were assessed. Phenotypes were differentiated for two anatomical determinants: (1) upper and/or lower motor involvement (typical, typMN; upper/lower motor neuron predominant, UMNp/LMNp; primary lateral sclerosis, PLS) and (2) region of onset and propagation of motor neuron dysfunction (bulbar, limb, flail-arm, flail-leg, thoracic onset). Phenotypes were correlated to sNfL, progression, and survival.

RESULTS

Mean sNfL was - compared to typMN (75.7 pg/mL, n = 1791) - significantly lower in LMNp (45.1 pg/mL, n = 413), UMNp (58.7 pg/mL n = 206), and PLS (37.6 pg/mL, n = 84). Also, sNfL significantly differed in the bulbar (92.7 pg/mL, n = 669), limb (64.1 pg/mL, n = 1305), flail-arm (46.4 pg/mL, n = 283), flail-leg (53.6 pg/mL, n = 141), and thoracic (74.5 pg/mL, n = 96) phenotypes. Binary logistic regression analysis showed highest contribution to sNfL elevation for faster progression (odds ratio [OR] 3.24) and for the bulbar onset phenotype (OR 1.94). In contrast, PLS (OR 0.20), LMNp (OR 0.45), and thoracic onset (OR 0.43) showed reduced contributions to sNfL. Longitudinal sNfL (median 12 months, n = 2862) showed minor monthly changes (<0.2%) across all phenotypes. Correlation of sNfL with survival was confirmed (p < 0.001).

CONCLUSIONS

This study underscored the correlation of ALS phenotypes - differentiated for motor neuron involvement and region of onset/propagation - with sNfL, progression, and survival. These phenotypes demonstrated a significant effect on sNfL and should be recognized as independent confounders of sNfL analyses in ALS trials and clinical practice.

Diagnostic value of isolated plasma biomarkers and its combination in neurodegenerative dementias: A multicenter cohort study

BACKGROUND

Plasma amyloid-β (Aβ), phosphorylated tau-181 (p-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) potentially aid in the diagnosis of neurodegenerative dementias. We aim to conduct a comprehensive comparison between different biomarkers and their combination, which is lacking, in a multicenter Chinese dementia cohort consisting of Alzheimer's disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP).

METHODS

We enrolled 92 demented patients [64 AD, 16 FTD, and 12 PSP with dementia] and 20 healthy controls (HC). Their plasma Αβ, p-tau181, NfL, and GFAP were detected by highly sensitive-single molecule immunoassays. Αβ pathology in patients was measured by cerebrospinal fluid or/and amyloid positron emission tomography.

RESULTS

All plasma biomarkers tested were significantly altered in dementia patients compared with HC, especially Aβ42/Aβ40 and NfL showed significant performance in distinguishing AD from HC. A combination of plasma Aβ42/Aβ40, p-tau181, NfL, and GFAP could discriminate FTD or PSP well from HC and was able to distinguish AD and non-AD (FTD/PSP).

CONCLUSIONS

Our results confirmed the diagnostic performance of individual plasma biomarkers Aβ42/Aβ40, p-tau181, NfL, and GFAP in Chinese dementia patients and noted that a combination of these biomarkers may be more accurate in identifying FTD/PSP patients and distinguishing AD from non-AD dementia.

Cerebrospinal fluid neurofilament light predicts longitudinal diagnostic change in patients with psychiatric and neurodegenerative disorders

OBJECTIVE

People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown.

METHODS

We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other.

RESULTS

Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone.

CONCLUSIONS

CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice.

Fluid biomarkers for amyotrophic lateral sclerosis: a review

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the loss of upper and lower motor neurons. Presently, three FDA-approved drugs are available to help slow functional decline for patients with ALS, but no cure yet exists. With an average life expectancy of only two to five years after diagnosis, there is a clear need for biomarkers to improve the care of patients with ALS and to expedite ALS treatment development. Here, we provide a review of the efforts made towards identifying diagnostic, prognostic, susceptibility/risk, and response fluid biomarkers with the intent to facilitate a more rapid and accurate ALS diagnosis, to better predict prognosis, to improve clinical trial design, and to inform interpretation of clinical trial results. Over the course of 20 + years, several promising fluid biomarker candidates for ALS have emerged. These will be discussed, as will the exciting new strategies being explored for ALS biomarker discovery and development.

Emerging perspectives of synaptic biomarkers in ALS and FTD

Amyotrophic Lateral Sclerosis (ALS) and Frontotemporal Dementia (FTD) are debilitating neurodegenerative diseases with shared pathological features like transactive response DNA-binding protein of 43 kDa (TDP-43) inclusions and genetic mutations. Both diseases involve synaptic dysfunction, contributing to their clinical features. Synaptic biomarkers, representing proteins associated with synaptic function or structure, offer insights into disease mechanisms, progression, and treatment responses. These biomarkers can detect disease early, track its progression, and evaluate therapeutic efficacy. ALS is characterized by elevated neurofilament light chain (NfL) levels in cerebrospinal fluid (CSF) and blood, correlating with disease progression. TDP-43 is another key ALS biomarker, its mislocalization linked to synaptic dysfunction. In FTD, TDP-43 and tau proteins are studied as biomarkers. Synaptic biomarkers like neuronal pentraxins (NPs), including neuronal pentraxin 2 (NPTX2), and neuronal pentraxin receptor (NPTXR), offer insights into FTD pathology and cognitive decline. Advanced technologies, like machine learning (ML) and artificial intelligence (AI), aid biomarker discovery and drug development. Challenges in this research include technological limitations in detection, variability across patients, and translating findings from animal models. ML/AI can accelerate discovery by analyzing complex data and predicting disease outcomes. Synaptic biomarkers offer early disease detection, personalized treatment strategies, and insights into disease mechanisms. While challenges persist, technological advancements and interdisciplinary efforts promise to revolutionize the understanding and management of ALS and FTD. This review will explore the present comprehension of synaptic biomarkers in ALS and FTD and discuss their significance and emphasize the prospects and obstacles.

Trajectories and contributing factors of neural compensation in healthy and pathological aging

Neural degeneration is a hallmark of healthy aging and can be associated with specific cognitive impairments. However, neural degeneration per se is not matched by unremitting declines in cognitive abilities. Instead, middle-aged and older adults typically maintain surprisingly high levels of cognitive functioning, suggesting that the human brain can adapt to structural degeneration by neural compensation. Here, we summarize prevailing theories and recent empirical studies on neural compensation with a focus on often neglected contributing factors, such as lifestyle, metabolism and neural plasticity. We suggest that these factors moderate the relationship between structural integrity and neural compensation, maintaining psychological well-being and behavioral functioning. Finally, we discuss that a breakdown in neural compensation may pose a tipping point that distinguishes the trajectories of healthy vs pathological aging, but conjoint support from psychology and cognitive neuroscience for this alluring view is still scarce. Therefore, future experiments that target the concomitant processes of neural compensation and associated behavior will foster a comprehensive understanding of both healthy and pathological aging.

Neurofilament light chain in spinal fluid and plasma in multiple system atrophy: a prospective, longitudinal biomarker study

PURPOSE

There is a critical need for reliable diagnostic biomarkers as well as surrogate markers of disease progression in multiple system atrophy (MSA). Neurofilament light chain (NfL) has been reported to potentially meet those needs. We therefore sought to explore the value of NfL in plasma (NfL-p) in contrast to cerebrospinal fluid (NfL-c) as a diagnostic marker of MSA, and to assess NfL-p and NfL-c as markers of clinical disease progression.

METHODS

Well-characterized patients with early MSA (n = 32), Parkinson's disease (PD; n = 21), and matched controls (CON; n = 15) were enrolled in a prospective, longitudinal study of synucleinopathies with serial annual evaluations. NfL was measured using a high-sensitivity immunoassay, and findings were assessed by disease category and relationship with clinical measures of disease progression.

RESULTS

Measurements of NfL-c were highly reproducible across immunoassay platforms (Pearson, r = 0.99), while correlation between NfL-c and -p was only moderate (r = 0.66). NfL was significantly higher in MSA compared with CON and PD; the separation was essentially perfect for NfL-c, but there was overlap, particularly with PD, for NfL-p. While clinical measures of disease severity progressively increased over time, NfL-c and -p remained at stable elevated levels within subjects across serial measurements. Neither change in NfL nor baseline NfL were significantly associated with changes in clinical markers of disease severity.

CONCLUSIONS

These findings confirm NfL-c as a faithful diagnostic marker of MSA, while NfL-p showed less robust diagnostic value. The significant NfL elevation in MSA was found to be remarkably stable over time and was not predictive of clinical disease progression.

Neurofilament Light Chain in Spinal Fluid and Plasma in Multiple System Atrophy - A Prospective, Longitudinal Biomarker Study

Purpose There is a critical need for reliable diagnostic biomarkers as well as surrogate markers of disease progression in multiple system atrophy (MSA). Neurofilament light chain (NfL) has been reported to potentially meet those needs. We therefore sought to explore the value of NfL in plasma (NfL-p) in contrast to CSF (NfL-c) as diagnostic marker of MSA, and to assess NfL-p and NfL-c as markers of clinical disease progression. Methods Well-characterized patients with early MSA (n=32), Parkinson's disease (PD, n=21), and matched controls (CON, n=15) were enrolled in a prospective, longitudinal study of synucleinopathies with serial annual evaluations. NfL was measured using a high sensitivity immunoassay, and findings were assessed by disease category and relationship with clinical measures of disease progression. Results Measurements of NfL-c were highly reproducible across immunoassay platforms (Pearson,r=0.99), while correlation between NfL-c and -p was only moderate (r=0.66). NfL was significantly higher in MSA compared to CON and PD; the separation was essentially perfect for NfL-c, but there was overlap, particularly with PD, for NfL-p. While clinical measures of disease severity progressively increased over time, NfL-c and -p remained at stable elevated levels within subjects across serial measurements. Neither change in NfL nor baseline NfL were significantly associated with changes in clinical markers of disease severity. Conclusions These findings confirm NfL-c as faithful diagnostic marker of MSA, while NfL-p showed less robust diagnostic value. The significant NfL elevation in MSA was found to be remarkably stable over time and was not predictive of clinical disease progression.

Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review

BACKGROUND

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterised by the progressive loss of motor neurons in the brain and spinal cord. The fact that ALS's disease course is highly heterogeneous, and its determinants not fully known, combined with ALS's relatively low prevalence, renders the successful application of artificial intelligence (AI) techniques particularly arduous.

OBJECTIVE

This systematic review aims at identifying areas of agreement and unanswered questions regarding two notable applications of AI in ALS, namely the automatic, data-driven stratification of patients according to their phenotype, and the prediction of ALS progression. Differently from previous works, this review is focused on the methodological landscape of AI in ALS.

METHODS

We conducted a systematic search of the Scopus and PubMed databases, looking for studies on data-driven stratification methods based on unsupervised techniques resulting in (A) automatic group discovery or (B) a transformation of the feature space allowing patient subgroups to be identified; and for studies on internally or externally validated methods for the prediction of ALS progression. We described the selected studies according to the following characteristics, when applicable: variables used, methodology, splitting criteria and number of groups, prediction outcomes, validation schemes, and metrics.

RESULTS

Of the starting 1604 unique reports (2837 combined hits between Scopus and PubMed), 239 were selected for thorough screening, leading to the inclusion of 15 studies on patient stratification, 28 on prediction of ALS progression, and 6 on both stratification and prediction. In terms of variables used, most stratification and prediction studies included demographics and features derived from the ALSFRS or ALSFRS-R scores, which were also the main prediction targets. The most represented stratification methods were K-means, and hierarchical and expectation-maximisation clustering; while random forests, logistic regression, the Cox proportional hazard model, and various flavours of deep learning were the most widely used prediction methods. Predictive model validation was, albeit unexpectedly, quite rarely performed in absolute terms (leading to the exclusion of 78 eligible studies), with the overwhelming majority of included studies resorting to internal validation only.

CONCLUSION

This systematic review highlighted a general agreement in terms of input variable selection for both stratification and prediction of ALS progression, and in terms of prediction targets. A striking lack of validated models emerged, as well as a general difficulty in reproducing many published studies, mainly due to the absence of the corresponding parameter lists. While deep learning seems promising for prediction applications, its superiority with respect to traditional methods has not been established; there is, instead, ample room for its application in the subfield of patient stratification. Finally, an open question remains on the role of new environmental and behavioural variables collected via novel, real-time sensors.

Molecular Biomarkers for the Diagnosis, Prognosis, and Pharmacodynamics of Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is a progressive degenerative illness that affects 1 in every 6 to 11,000 live births. This autosomal recessive disorder is caused by homozygous deletion or mutation of the SMN1 gene (survival motor neuron). As a backup, the SMN1 gene has the SMN2 gene, which produces only 10% of the functional SMN protein. Nusinersen and risdiplam, the first FDA-approved medications, act as SMN2 pre-mRNA splicing modifiers and enhance the quantity of SMN protein produced by this gene. The emergence of new therapies for SMA has increased the demand for good prognostic and pharmacodynamic (response) biomarkers in SMA. This article discusses current molecular diagnostic, prognostic, and pharmacodynamic biomarkers that could be assessed in SMA patients' body fluids. Although various proteomic, genetic, and epigenetic biomarkers have been explored in SMA patients, more research is needed to uncover new prognostic and pharmacodynamic biomarkers (or a combination of biomarkers).

Performance of serum neurofilament light chain in a wide spectrum of clinical courses of amyotrophic lateral sclerosis-a cross-sectional multicenter study

BACKGROUND AND PURPOSE

The objective was to assess the performance of serum neurofilament light chain (sNfL) in amyotrophic lateral sclerosis (ALS) in a wide range of disease courses, in terms of progression, duration and tracheostomy invasive ventilation (TIV).

METHODS

A prospective cross-sectional study at 12 ALS centers in Germany was performed. sNfL concentrations were age adjusted using sNfL Z scores expressing the number of standard deviations from the mean of a control reference database and correlated to ALS duration and ALS progression rate (ALS-PR), defined by the decline of the ALS Functional Rating Scale.

RESULTS

In the total ALS cohort (n = 1378) the sNfL Z score was elevated (3.04; 2.46-3.43; 99.88th percentile). There was a strong correlation of sNfL Z score with ALS-PR (p < 0.001). In patients with long (5-10 years, n = 167) or very long ALS duration (>10 years, n = 94) the sNfL Z score was significantly lower compared to the typical ALS duration of <5 years (n = 1059) (p < 0.001). Furthermore, in patients with TIV, decreasing sNfL Z scores were found in correlation with TIV duration and ALS-PR (p = 0.002; p < 0.001).

CONCLUSIONS

The finding of moderate sNfL elevation in patients with long ALS duration underlined the favorable prognosis of low sNfL. The strong correlation of sNfL Z score with ALS-PR strengthened its value as progression marker in clinical management and research. The lowering of sNfL in correlation with long TIV duration could reflect a reduction either in disease activity or in the neuroaxonal substrate of biomarker formation during the protracted course of ALS.

Motor unit number index (MUNIX) loss of 50% occurs in half the time of 50% functional loss according to the D50 disease progression model of ALS

Capturing disease progression in amyotrophic lateral sclerosis (ALS) is challenging and refinement of progression markers is urgently needed. This study introduces new motor unit number index (MUNIX), motor unit size index (MUSIX) and compound muscle action potential (CMAP) parameters called M50, MUSIX200 and CMAP50. M50 and CMAP50 indicate the time in months from symptom onset an ALS patient needs to lose 50% of MUNIX or CMAP in relation to the mean values of controls. MUSIX200 represents the time in months until doubling of the mean MUSIX of controls. We used MUNIX parameters of Musculi abductor pollicis brevis (APB), abductor digiti minimi (ADM) and tibialis anterior (TA) of 222 ALS patients. Embedded in the D50 disease progression model, disease aggressiveness and accumulation were analyzed separately. M50, CMAP50 and MUSIX200 significantly differed among disease aggressiveness subgroups (p < 0.001) regardless of disease accumulation. ALS patients with a low M50 had a significantly shorter survival compared to high M50 (median 32 versus 74 months). M50 preceded the loss of global function (median of about 14 months). M50, CMAP50 and MUSIX200 characterize the disease course in ALS in a new way and may be applied as early measures of disease progression.

Current State and Future Directions in the Diagnosis of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by loss of upper and lower motor neurons, resulting in progressive weakness of all voluntary muscles and eventual respiratory failure. Non-motor symptoms, such as cognitive and behavioral changes, frequently occur over the course of the disease. Considering its poor prognosis with a median survival time of 2 to 4 years and limited causal treatment options, an early diagnosis of ALS plays an essential role. In the past, diagnosis has primarily been determined by clinical findings supported by electrophysiological and laboratory measurements. To increase diagnostic accuracy, reduce diagnostic delay, optimize stratification in clinical trials and provide quantitative monitoring of disease progression and treatment responsivity, research on disease-specific and feasible fluid biomarkers, such as neurofilaments, has been intensely pursued. Advances in imaging techniques have additionally yielded diagnostic benefits. Growing perception and greater availability of genetic testing facilitate early identification of pathogenic ALS-related gene mutations, predictive testing and access to novel therapeutic agents in clinical trials addressing disease-modified therapies before the advent of the first clinical symptoms. Lately, personalized survival prediction models have been proposed to offer a more detailed disclosure of the prognosis for the patient. In this review, the established procedures and future directions in the diagnostics of ALS are summarized to serve as a practical guideline and to improve the diagnostic pathway of this burdensome disease.

Safety and Clinical Effects of a Muse Cell-Based Product in Patients With Amyotrophic Lateral Sclerosis: Results of a Phase 2 Clinical Trial

Amyotrophic lateral sclerosis (ALS) is characterized by progressive loss of motor neurons. Multilineage-differentiating stress-enduring (Muse) cells are unique endogenous stem cells that show therapeutic effects on motor function in ALS mouse models. We conducted a single-center open phase II clinical trial to evaluate the safety and clinical effects of repeated intravenous injections of an allogenic Muse cell-based product, CL2020, in patients with ALS. Five patients with ALS received CL2020 intravenously once a month for a total of six doses. The primary endpoints were safety and tolerability, and the secondary endpoint was the rate of change in the Revised Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS-R) score. In addition, serum tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), sphingosine-1-phosphate (S1P), cerebrospinal fluid chitotriosidase-1 (CHIT-1), and neurofilament light chain (NfL) levels were evaluated. The CL2020 treatment was highly tolerated without serious side effects. The ALSFRS-R score change trended upward at 12 months post-CL2020 treatment compared with that at 3 months pre-administration, but the difference was not statistically significant. Among five patients diagnosed with ALS, three exhibited a decrease in the rate of ALSFRS-R score change, one demonstrated an increase, and another showed no change. In addition, the patients' serum IL-6 and TNF-α levels and cerebrospinal fluid CHIT-1 and NfL levels increased for up to 6 months post-treatment; however, their serum S1P levels continuously decreased over 12 months. These findings indicate a favorable safety profile of CL2020 therapy. In the near future, a double-blind study of a larger number of ALS patients should be conducted to confirm the efficacy of ALS treatment with CL2020.

Biomarkers for amyotrophic lateral sclerosis

PURPOSE OF REVIEW

Amyotrophic lateral sclerosis (ALS) is an incurable, devastating neurodegenerative disease. Still, the diagnosis is mainly based on clinical symptoms, and the treatment options are strongly limited. However, the pipeline of potential treatments currently tested in clinical trials is promising. This review will discuss developments in ALS biomarker research and applications within the last 2 years and suggest future directions and needs.

RECENT FINDINGS

The diagnostic and prognostic utility of neurofilaments, a general marker for axoneuronal degeneration, has been confirmed by further studies in patients with ALS, and neurofilaments are finding their way into routine diagnostic and clinical trials. Additionally, there have been advancements in developing and implementing disease-specific biomarkers, especially in patients with a genetic variant, such as SOD1 or C9orf72 . Here, biomarkers have already been used as target markers and outcome parameters for novel treatment approaches. In addition, several novel biomarkers have shown encouraging results but should be discussed in the context of their early stage of assay and clinical establishment.

SUMMARY

The first biomarkers have found their way into clinical routine in ALS. In light of an increasing pipeline of potential treatments, further progress in discovering and implementing novel and existing biomarkers is crucial.

Motor unit number index (MUNIX) in the D50 disease progression model reflects disease accumulation independently of disease aggressiveness in ALS

The neurophysiological technique motor unit number index (MUNIX) is increasingly used in clinical trials to measure loss of motor units. However, the heterogeneous disease course in amyotrophic lateral sclerosis (ALS) obfuscates robust correlations between clinical status and electrophysiological assessments. To address this heterogeneity, MUNIX was applied in the D50 disease progression model by analyzing disease aggressiveness (D50) and accumulation (rD50 phase) in ALS separately. 237 ALS patients, 45 controls and 22 ALS-Mimics received MUNIX of abductor pollicis brevis (APB), abductor digiti minimi (ADM) and tibialis anterior (TA) muscles. MUNIX significantly differed between controls and ALS patients and between ALS-Mimics and controls. Within the ALS cohort, significant differences between Phase I and II revealed in MUNIX, compound muscle action potential (CMAP) and motor unit size index (MUSIX) of APB as well as in MUNIX and CMAP of TA. For the ADM, significant differences occurred later in CMAP and MUNIX between Phase II and III/IV. In contrast, there was no significant association between disease aggressiveness and MUNIX. In application of the D50 disease progression model, MUNIX can demonstrate disease accumulation already in early Phase I and evaluate effects of therapeutic interventions in future therapeutic trials independent of individual disease aggressiveness.

Cortical and subcortical grey matter atrophy in Amyotrophic Lateral Sclerosis correlates with measures of disease accumulation independent of disease aggressiveness

There is a growing demand for reliable biomarkers to monitor disease progression in Amyotrophic Lateral Sclerosis (ALS) that also take the heterogeneity of ALS into account. In this study, we explored the association between Magnetic Resonance Imaging (MRI)-derived measures of cortical thickness (CT) and subcortical grey matter (GM) volume with D50 model parameters. T1-weighted MRI images of 72 Healthy Controls (HC) and 100 patients with ALS were analyzed using Surface-based Morphometry for cortical structures and Voxel-based Morphometry for subcortical Region-Of-Interest analyses using the Computational Anatomy Toolbox (CAT12). In Inter-group contrasts, these parameters were compared between patients and HC. Further, the D50 model was used to conduct subgroup-analyses, dividing patients by a) Phase of disease covered at the time of MRI-scan and b) individual overall disease aggressiveness. Finally, correlations between GM and D50 model-derived parameters were examined. Inter-group analyses revealed ALS-related cortical thinning compared to HC located mainly in frontotemporal regions and a decrease in GM volume in the left hippocampus and amygdala. A comparison of patients in different phases showed further cortical and subcortical GM atrophy along with disease progression. Correspondingly, regression analyses identified negative correlations between cortical thickness and individual disease covered. However, there were no differences in CT and subcortical GM between patients with low and high disease aggressiveness. By application of the D50 model, we identified correlations between cortical and subcortical GM atrophy and ALS-related functional disability, but not with disease aggressiveness. This qualifies CT and subcortical GM volume as biomarkers representing individual disease covered to monitor therapeutic interventions in ALS.

Alzheimer's Disease: A Silent Pandemic - A Systematic Review on the Situation and Patent Landscape of the Diagnosis

BACKGROUND

Alzheimer's disease (AD) is characterized by cognitive impairment, tau protein deposits, and amyloid beta plaques. AD impacted 44 million people in 2016, and it is estimated to affect 100 million people by 2050. AD is disregarded as a pandemic compared with other diseases. To date, there is no effective treatment or diagnosis.

OBJECTIVE

We aimed to discuss the current tools used to diagnose COVID-19, to point out their potential to be adapted for AD diagnosis, and to review the landscape of existing patents in the AD field and future perspectives for AD diagnosis.

METHOD

We carried out a scientific screening following a research strategy in PubMed; Web of Science; the Derwent Innovation Index; the KCI-Korean Journal Database; SciELO; the Russian Science Citation index; and the CDerwent, EDerwent, and MDerwent index databases.

RESULTS

A total of 326 from 6,446 articles about AD and 376 from 4,595 articles about COVID-19 were analyzed. Of these, AD patents were focused on biomarkers and neuroimaging with no accurate, validated diagnostic methods, and only 7% of kit development patents were found. In comparison, COVID-19 patents were 60% about kit development for diagnosis; they are highly accurate and are now commercialized.

CONCLUSION

AD is still neglected and not recognized as a pandemic that affects the people and economies of all nations. There is a gap in the development of AD diagnostic tools that could be filled if the interest and effort that has been invested to tackle the COVID-19 emergency could also be applied for innovation.

Cerebrospinal fluid biomarkers of disease activity and progression in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a relentlessly progressive neurodegenerative disease, and only modest disease-modifying strategies have been established to date. Numerous clinical trials have been conducted in the past years, but have been severely hampered by the wide-ranging heterogeneity of both the biological origins and clinical characteristics of the disease. Thus, reliable biomarkers of disease activity are urgently needed to stratify patients into homogenous groups with aligned disease trajectories to allow a more effective design of clinical trial. In this review, the most promising candidate biomarkers in the cerebrospinal fluid (CSF) of patients with ALS will be summarised. Correlations between biomarker levels and clinical outcome parameters are discussed, while highlighting potential pitfalls and intercorrelations of these clinical parameters. Several CSF molecules have shown potential as biomarkers of progression and prognosis, but large, international, multicentric and longitudinal studies are crucial for validation. A more standardised choice of clinical endpoints in these studies, as well as the application of individualised models of clinical progression, would allow the quantification of disease trajectories, thereby allowing a more accurate analysis of the clinical implications of candidate biomarkers. Additionally, a comparative analysis of several biomarkers and ideally the application of a multivariate analysis including comprehensive genotypic, phenotypic and clinical characteristics collectively contributing to biomarker levels in the CSF, could promote their verification. Thus, reliable prognostic markers and markers of disease activity may improve clinical trial design and patient management in the direction of precision medicine.

Plasma and CSF Neurofilament Light Chain in Amyotrophic Lateral Sclerosis: A Cross-Sectional and Longitudinal Study

Background: Neurofilament light chain (NfL) is a validated biofluid marker of neuroaxonal damage with great potential for monitoring patients with neurodegenerative diseases. We aimed to further validate the clinical utility of plasma (p) vs. CSF (c) NfL for distinguishing patients with Amyotrophic Lateral Sclerosis (ALS) from ALS mimics. We also assessed the association of biomarker values with clinical variables and survival and established the longitudinal changes of pNfL during the disease course.

Methods: We studied 231 prospectively enrolled patients with suspected ALS who underwent a standardized protocol including neurological examination, electromyography, brain MRI, and lumbar puncture. Patients who received an alternative clinical diagnosis were considered ALS mimics. We classified the patients based on the disease progression rate (DPR) into fast (DPR > 1), intermediate (DPR 0.5–1), and slow progressors (DPR < 0.5). All patients were screened for the most frequent ALS-associated genes. Plasma and CSF samples were retrospectively analyzed; NfL concentrations were measured with the SIMOA platform using a commercial kit.

Results: ALS patients (n = 171) showed significantly higher pNfL (p < 0.0001) and cNfL (p < 0.0001) values compared to ALS mimics (n = 60). Both cNfL and pNfL demonstrated a good diagnostic value in discriminating the two groups, although cNfL performed slightly better (cNfL: AUC 0.924 ± 0.022, sensitivity 86.8%, specificity 92.4; pNfL: AUC 0.873 ± 0.036, sensitivity 84.7%, specificity 83.3%). Fast progressors showed higher cNfL and pNfL as compared to intermediate (p = 0.026 and p = 0.001) and slow progressors (both p < 0.001). Accordingly, ALS patients with higher baseline cNfL and pNfL levels had a shorter survival (highest tertile of cNfL vs. lowest tertile, HR 4.58, p = 0.005; highest tertile of pNfL vs. lowest tertile, HR 2.59, p = 0.015). Moreover, there were positive associations between cNfL and pNfL levels and the number of body regions displaying UMN signs (rho = 0.325, p < 0.0001; rho = 0.308, p = 0.001). Finally, longitudinal analyses in 57 patients showed stable levels of pNfL during the disease course.

Conclusion: Both cNfL and pNfL have excellent diagnostic and prognostic performance for symptomatic patients with ALS. The stable longitudinal trajectory of pNfL supports its use as a marker of drug effect in clinical trials.

Circulating Biomarkers in Neuromuscular Disorders: What Is Known, What Is New

The urgent need for new therapies for some devastating neuromuscular diseases (NMDs), such as Duchenne muscular dystrophy or amyotrophic lateral sclerosis, has led to an intense search for new potential biomarkers. Biomarkers can be classified based on their clinical value into different categories: diagnostic biomarkers confirm the presence of a specific disease, prognostic biomarkers provide information about disease course, and therapeutic biomarkers are designed to predict or measure treatment response. Circulating biomarkers, as opposed to instrumental/invasive ones (e.g., muscle MRI or nerve ultrasound, muscle or nerve biopsy), are generally easier to access and less “time-consuming”. In addition to well-known creatine kinase, other promising molecules seem to be candidate biomarkers to improve the diagnosis, prognosis and prediction of therapeutic response, such as antibodies, neurofilaments, and microRNAs. However, there are some criticalities that can complicate their application: variability during the day, stability, and reliable performance metrics (e.g., accuracy, precision and reproducibility) across laboratories. In the present review, we discuss the application of biochemical biomarkers (both validated and emerging) in the most common NMDs with a focus on their diagnostic, prognostic/predictive and therapeutic application, and finally, we address the critical issues in the introduction of new biomarkers.