An update on blood-based biomarkers for non-Alzheimer neurodegenerative disorders

High Levels of NfL, GFAP, TAU, and UCH-L1 as Potential Predictor Biomarkers of Severity and Lethality in Acute COVID-19

Few studies showed that neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), total tubulin-associated unit (TAU), and ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1) may be related to neurological manifestations and severity during and after SARS-CoV-2 infection. The objective of this work was to investigate the relationship among nervous system biomarkers (NfL, TAU, GFAP, and UCH-L1), biochemical parameters, and viral loads with heterogeneous outcomes in a cohort of severe COVID-19 patients admitted in Intensive Care Unit (ICU) of a university hospital. For that, 108 subjects were recruited within the first 5 days at ICU. In parallel, 16 mild COVID-19 patients were enrolled. Severe COVID-19 group was divided between "deceased" and "survivor." All subjects were positive for SARS-CoV-2 detection. NfL, total TAU, GFAP, and UCH-L1 quantification in plasma was performed using SIMOA SR-X platform. Of 108 severe patients, 36 (33.33%) presented neurological manifestation and 41 (37.96%) died. All four biomarkers - GFAP, NfL, TAU, and UCH-L1 - were significantly higher among deceased patients in comparison to survivors (p < 0.05). Analyzing biochemical biomarkers, higher Peak Serum Ferritin, D-Dimer Peak, Gamma-glutamyltransferase, and C-Reactive Protein levels were related to death (p < 0.0001). In multivariate analysis, GFAP, NfL, TAU, UCH-L1, and Peak Serum Ferritin levels were correlated to death. Regarding SARS-CoV-2 viral load, no statistical difference was observed for any group. Thus, Ferritin, NFL, GFAP, TAU, and UCH-L1 are early biomarkers of severity and lethality of SARS-COV-2 infection and may be important tools for therapeutic decision-making in the acute phase of disease.

Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease

Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) analysis of blood-based biomarkers is a convenient alternative to rapidly obtain spectral information from biofluids. However, despite the rapid acquisition of spectral information from biofluids, it is challenging to distinguish spectral features of biomarkers due to interference from biofluidic components. Here, we introduce a deep learning-assisted, SERS-based platform for separate analysis of blood-based amyloid β (1-42) and metabolites, enabling the diagnosis of Alzheimer's disease. SERS substrates consisting of Au nanowire arrays are fabricated and functionalized in two characteristic ways to compare the validity of different Alzheimer's disease biomarkers measured on our SERS system. The 6E10 antibody is immobilized for the capture of amyloid β (1-42) and analysis of its oligomerization process, while various self-assembled monolayers are attached for different dipole interactions with blood-based metabolites. Ultimately, SERS spectra of blood plasma of Alzheimer's disease patients and human controls are measured on the substrates and classified via advanced deep learning techniques that automatically extract informative features to learn generalizable representations. Accuracies up to 99.5% are achieved for metabolite-based analyses, which are verified with an explainable artificial intelligence technique that identifies key spectral features used for classification and for deducing significant biomarkers.

Associations of plasma neurofilament light chain with cognition and neuroimaging measures in community-dwelling early old age men

BACKGROUND

Plasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations.

METHODS

We examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter.

RESULTS

After adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals.

CONCLUSIONS

These results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.

Detection of elevated levels of PINK1 in plasma from patients with idiopathic Parkinson's disease

Backgrounds

Numerous lines of evidence support the intricate interplay between Parkinson's disease (PD) and the PINK1-dependent mitophagy process. This study aimed to evaluate differences in plasma PINK1 levels among idiopathic PD, PD syndromes (PDs), and healthy controls.

Methods

A total of 354 participants were included, consisting of 197 PD patients, 50 PDs patients, and 107 healthy controls were divided into two cohorts, namely the modeling cohort (cohort 1) and the validated cohort (cohort 2). An enzyme-linked immunosorbent assay (ELISA)-based analysis was performed on PINK1 and α-synuclein oligomer (Asy-no). The utilization of the area under the curve (AUC) within the receiver-operating characteristic (ROC) curves served as a robust and comprehensive approach to evaluate and quantify the predictive efficacy of plasma biomarkers alone, as well as combined models, in distinguishing PD patients from controls.

Results

PINK1 and Asy-no were elevated in the plasma of PD and PDs patients compared to healthy controls. The AUCs of PINK1 (0.771) and Asy-no (0.787) were supposed to be potentially eligible plasma biomarkers differentiating PD from controls but could not differentiate PD from PDs. Notably, the PINK + Asy-no + Clinical RBD model showed the highest performance in the modeling cohort and was comparable with the PINK1 + Clinical RBD in the validation cohort. Moreover, there is no significant correlation between PINK1 and UPDRS, MMSE, HAMD, HAMA, RBDQ-HK, and ADL scores.

Conclusion

These findings suggest that elevated PINK1 in plasma holds the potential to serve as a non-invasive tool for distinguishing PD patients from controls. Moreover, the outcomes of our investigation lend support to the plausibility of implementing a feasible blood test in future clinical translation.

Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease

Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-β and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.

Beyond CSF and Neuroimaging Assessment: Evaluating Plasma miR-145-5p as a Potential Biomarker for Mild Cognitive Impairment and Alzheimer's Disease

Alzheimer's disease (AD) is the most common cause of dementia. New strategies for the early detection of MCI and sporadic AD are crucial for developing effective treatment options. Current techniques used for diagnosis of AD are invasive and/or expensive, so they are not suitable for population screening. Cerebrospinal fluid (CSF) biomarkers such as amyloid β1-42 (Aβ1-42), total tau (T-tau), and phosphorylated tau181 (P-tau181) levels are core biomarkers for early diagnosis of AD. Several studies have proposed the use of blood-circulating microRNAs (miRNAs) as potential novel early biomarkers for AD. We therefore applied a novel approach to identify blood-circulating miRNAs associated with CSF biomarkers and explored the potential of these miRNAs as biomarkers of AD. In total, 112 subjects consisting of 28 dementia due to AD cases, 63 MCI due to AD cases, and 21 cognitively healthy controls were included. We identified seven Aβ1-42-associated plasma miRNAs, six P-tau181-associated plasma miRNAs, and nine Aβ1-42-associated serum miRNAs. These miRNAs were involved in AD-relevant biological processes, such as PI3K/AKT signaling. Based on this signaling pathway, we constructed an miRNA-gene target network, wherein miR-145-5p has been identified as a hub. Furthermore, we showed that miR-145-5p performs best in the prediction of both AD and MCI. Moreover, miR-145-5p also improved the prediction performance of the mini-mental state examination (MMSE) score. The performance of this miRNA was validated using different datasets including an RT-qPCR dataset from plasma samples of 23 MCI cases and 30 age-matched controls. These findings indicate that blood-circulating miRNAs that are associated with CSF biomarkers levels and specifically plasma miR-145-5p alone or combined with the MMSE score can potentially be used as noninvasive biomarkers for AD or MCI screening in the general population, although studies in other AD cohorts are necessary for further validation.

Early Diagnosis of Neurodegenerative Diseases: What Has Been Undertaken to Promote the Transition from PET to Fluorescence Tracers

Alzheimer's Disease (AD) and Parkinson's Disease (PD) represent two among the most frequent neurodegenerative diseases worldwide. A common hallmark of these pathologies is the misfolding and consequent aggregation of amyloid proteins into soluble oligomers and insoluble β-sheet-rich fibrils, which ultimately lead to neurotoxicity and cell death. After a hundred years of research on the subject, this is the only reliable histopathological feature in our hands. Since AD and PD are diagnosed only once neuronal death and the first symptoms have appeared, the early detection of these diseases is currently impossible. At present, there is no effective drug available, and patients are left with symptomatic and inconclusive therapies. Several reasons could be associated with the lack of effective therapeutic treatments. One of the most important factors is the lack of selective probes capable of detecting, as early as possible, the most toxic amyloid species involved in the onset of these pathologies. In this regard, chemical probes able to detect and distinguish among different amyloid aggregates are urgently needed. In this article, we will review and put into perspective results from ex vivo and in vivo studies performed on compounds specifically interacting with such early species. Following a general overview on the three different amyloid proteins leading to insoluble β-sheet-rich amyloid deposits (amyloid β1-42 peptide, Tau, and α-synuclein), a list of the advantages and disadvantages of the approaches employed to date is discussed, with particular attention paid to the translation of fluorescence imaging into clinical applications. Furthermore, we also discuss how the progress achieved in detecting the amyloids of one neurodegenerative disease could be leveraged for research into another amyloidosis. As evidenced by a critical analysis of the state of the art, substantial work still needs to be conducted. Indeed, the early diagnosis of neurodegenerative diseases is a priority, and we believe that this review could be a useful tool for better investigating this field.

Extracellular vesicle microRNA-mediated transcriptional regulation may contribute to dementia with Lewy bodies molecular pathology

OBJECTIVE

Dementia with Lewy bodies (DLB) is the second most common dementia. Advancing our limited understanding of its molecular pathogenesis is essential for identifying novel biomarkers and therapeutic targets for DLB. DLB is an α-synucleinopathy, and small extracellular vesicles (SEV) from people with DLB can transmit α-synuclein oligomerisation between cells. Post-mortem DLB brains and serum SEV from those with DLB share common miRNA signatures, and their functional implications are uncertain. Hence, we aimed to investigate potential targets of DLB-associated SEV miRNA and to analyse their functional implications.

METHODS

We identified potential targets of six previously reported differentially expressed miRNA genes in serum SEV of people with DLB (MIR26A1, MIR320C2, MIR320D2, MIR548BA, MIR556, and MIR4722) using miRBase and miRDB databases. We analysed functional implications of these targets using EnrichR gene set enrichment analysis and analysed their protein interactions using Reactome pathway analysis.

RESULTS

These SEV miRNA may regulate 4278 genes that were significantly enriched among the genes involved in neuronal development, cell-to-cell communication, vesicle-mediated transport, apoptosis, regulation of cell cycle, post-translational protein modifications, and autophagy lysosomal pathway, after Benjamini-Hochberg false discovery rate correction at 5%. The miRNA target genes and their protein interactions were significantly associated with several neuropsychiatric disorders and with multiple signal transduction, transcriptional regulation, and cytokine signalling pathways.

CONCLUSION

Our findings provide in-silico evidence that potential targets of DLB-associated SEV miRNAs may contribute to Lewy pathology by transcriptional regulation. Experimental validation of these dysfunctional pathways is warranted and could lead to novel therapeutic avenues for DLB.

Novel aspects of the phosphorylation and structure of pathological tau: implications for tauopathy biomarkers

The deposition of highly phosphorylated and aggregated tau is a characteristic of tauopathies, including Alzheimer's disease. It has long been known that different isoforms of tau are aggregated in different cell types and brain regions in each tauopathy. Recent advances in analytical techniques revealed the details of the biochemical and structural biological differences of tau specific to each tauopathy. In this review, we explain recent advances in the analysis of post-translational modifications of tau, particularly phosphorylation, brought about by the development of mass-spectrometry and Phos-tag technology. We then discuss the structure of tau filaments in each tauopathy revealed by the advent of cryo-EM. Finally, we describe the progress in biofluid and imaging biomarkers for tauopathy. This review summarizes current efforts to elucidate the characteristics of pathological tau and the landscape of the use of tau as a biomarker to diagnose and determine the pathological stage of tauopathy.

Investigating the Association Between Extended Participation in Collision Sports and Fluid Biomarkers Among Masters Athletes

Traumatic brain injuries (TBIs) and concussions are prevalent in collision sports, and there is evidence that levels of exposure to such sports may increase the risk of neurological abnormalities. Elevated levels of fluid-based biomarkers have been observed after concussions or among athletes with a history of participating in collision sports, and certain biomarkers exhibit sensitivity toward neurodegeneration. This study investigated a cohort of 28 male amateur athletes competing in "Masters" competitions for persons >35 years of age. The primary objective of this study was to compare the levels of blood and saliva biomarkers associated with brain injury, inflammation, aging, and neurodegeneration between athletes with an extensive history of collision sport participation (i.e., median = 27 years; interquartile range = 18-44, minimum = 8) and those with no history. Plasma proteins associated with neural damage and neurodegeneration were measured using Simoa® assays, and saliva was analyzed for markers associated with inflammation and telomere length using quantitative real-time polymerase chain reaction. There were no significant differences between collision and non-collision sport athletes for plasma levels of glial fibrillary acidic protein, neurofilament light, ubiquitin C-terminal hydrolase L1, tau, tau phosphorylated at threonine 181, and brain-derived neurotrophic factor. Moreover, salivary levels of genes associated with inflammation and telomere length were similar between groups. There were no significant differences between groups in symptom frequency or severity on the Sport Concussion Assessment Tool-5th Edition. Overall, these findings provide preliminary evidence that biomarkers associated with neural tissue damage, neurodegeneration, and inflammation may not exhibit significant alterations in asymptomatic amateur athletes with an extensive history of amateur collision sport participation.

Induced pluripotent stem cell models as a tool to investigate and test fluid biomarkers in Alzheimer's disease and frontotemporal dementia

Neurodegenerative diseases are increasing in prevalence and comprise a large socioeconomic burden on patients and their caretakers. The need for effective therapies and avenues for disease prevention and monitoring is of paramount importance. Fluid biomarkers for neurodegenerative diseases have gained a variety of uses, including informing participant selection for clinical trials, lending confidence to clinical diagnosis and disease staging, determining prognosis, and monitoring therapeutic response. Their role is expected to grow as disease-modifying therapies start to be available to a broader range of patients and as prevention strategies become established. Many of the underlying molecular mechanisms of currently used biomarkers are incompletely understood. Animal models and in vitro systems using cell lines have been extensively employed but face important translatability limitations. Induced pluripotent stem cell (iPSC) technology, where a theoretically unlimited range of cell types can be reprogrammed from peripheral cells sampled from patients or healthy individuals, has gained prominence over the last decade. It is a promising avenue to study physiological and pathological biomarker function and response to experimental therapeutics. Such systems are amenable to high-throughput drug screening or multiomics readouts such as transcriptomics, lipidomics, and proteomics for biomarker discovery, investigation, and validation. The present review describes the current state of biomarkers in the clinical context of neurodegenerative diseases, with a focus on Alzheimer's disease and frontotemporal dementia. We include a discussion of how iPSC models have been used to investigate and test biomarkers such as amyloid-β, phosphorylated tau, neurofilament light chain or complement proteins, and even nominate novel biomarkers. We discuss the limitations of current iPSC methods, mentioning alternatives such as coculture systems and three-dimensional organoids which address some of these concerns. Finally, we propose exciting prospects for stem cell transplantation paradigms using animal models as a preclinical tool to study biomarkers in the in vivo context.

Body composition and plasma total-tau, neurofilament light chain, and amyloid-β: A population-based study

A higher body mass at older age has been linked to a lower risk of dementia. This unexpected trend may be explained by age-related lean mass depletion, or methodological issues such as the long preclinical phase of dementia or competing risks. Focusing on preclinical markers of dementia may overcome these issues. Between 2002 and 2005, body composition and plasma total-tau, neurofilament light chain (NfL), amyloid-β40, and amyloid-β42 were measured in 3408 dementia-free participants from the population-based Rotterdam Study. The cross-sectional associations between body composition and plasma markers were determined using linear regression models. Whole body and fat mass, but not lean mass, were positively associated with total-tau, while all these measures were inversely associated with NfL. Apart from an inverse association between lean mass and amyloid-β40, body composition measures were not associated with plasma amyloid-β. Our findings suggest distinct effects of body composition on neurodegeneration.

Advances in the prevention and treatment of Alzheimer's disease based on oral bacteria

With the global population undergoing demographic shift towards aging, the prevalence of Alzheimer's disease (AD), a prominent neurodegenerative disorder that primarily afflicts individuals aged 65 and above, has increased across various geographical regions. This phenomenon is accompanied by a concomitant decline in immune functionality and oral hygiene capacity among the elderly, precipitating compromised oral functionality and an augmented burden of dental plaque. Accordingly, oral afflictions, including dental caries and periodontal disease, manifest with frequency among the geriatric population worldwide. Recent scientific investigations have unveiled the potential role of oral bacteria in instigating both local and systemic chronic inflammation, thereby delineating a putative nexus between oral health and the genesis and progression of AD. They further proposed the oral microbiome as a potentially modifiable risk factor in AD development, although the precise pathological mechanisms and degree of association have yet to be fully elucidated. This review summarizes current research on the relationship between oral bacteria and AD, describing the epidemiological and pathological mechanisms that may potentially link them. The purpose is to enrich early diagnostic approaches by incorporating emerging biomarkers, offering novel insights for clinicians in the early detection of AD. Additionally, it explores the potential of vaccination strategies and guidance for clinical pharmacotherapy. It proposes the development of maintenance measures specifically targeting oral health in older adults and advocates for guiding elderly patients in adopting healthy lifestyle habits, ultimately aiming to indirectly mitigate the progression of AD while promoting oral health in the elderly.

Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia

With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice. HIGHLIGHTS: Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real-world validation, and interdisciplinary collaboration are required.

Association of periodontitis with cognitive decline and its progression: Contribution of blood-based biomarkers of Alzheimer's disease to this relationship

AIM

To assess whether periodontitis is associated with cognitive decline and its progression as well as with certain blood-based markers of Alzheimer's disease.

MATERIALS AND METHODS

Data from a 2-year follow-up prospective cohort study (n = 101) was analysed. Participants with a previous history of hypertension and aged ≥60 years were included in the analysis. All of them received a full-mouth periodontal examination and cognitive function assessments (Addenbrooke's Cognitive Examination (ACE) and Mini-Mental State Examination [MMSE]). Plasma levels of amyloid beta (Aβ)1-40 , Aβ1-42 , phosphorylated and total Tau (p-Tau and t-Tau) were determined at baseline, 12 and 24 months.

RESULTS

Periodontitis was associated with poor cognitive performance (MMSE: β = -1.5 [0.6]) and progression of cognitive impairment (hazard ratio [HR] = 1.8; 95% confidence interval: 1.0-3.1). Subjects with periodontitis showed greater baseline levels of p-Tau (1.6 [0.7] vs. 1.2 [0.2] pg/mL, p < .001) and Aβ1-40 (242.1 [77.3] vs. 208.2 [73.8] pg/mL, p = .036) compared with those without periodontitis. Concentrations of the latter protein also increased over time only in the periodontitis group (p = .005).

CONCLUSIONS

Periodontitis is associated with cognitive decline and its progression in elderly patients with a previous history of hypertension. Overexpression of p-Tau and Aβ1-40 may play a role in this association.

Systematic review: fluid biomarkers and machine learning methods to improve the diagnosis from mild cognitive impairment to Alzheimer's disease

Mild cognitive impairment (MCI) is often considered an early stage of dementia, with estimated rates of progression to dementia up to 80-90% after approximately 6 years from the initial diagnosis. Diagnosis of cognitive impairment in dementia is typically based on clinical evaluation, neuropsychological assessments, cerebrospinal fluid (CSF) biomarkers, and neuroimaging. The main goal of diagnosing MCI is to determine its cause, particularly whether it is due to Alzheimer's disease (AD). However, only a limited percentage of the population has access to etiological confirmation, which has led to the emergence of peripheral fluid biomarkers as a diagnostic tool for dementias, including MCI due to AD. Recent advances in biofluid assays have enabled the use of sophisticated statistical models and multimodal machine learning (ML) algorithms for the diagnosis of MCI based on fluid biomarkers from CSF, peripheral blood, and saliva, among others. This approach has shown promise for identifying specific causes of MCI, including AD. After a PRISMA analysis, 29 articles revealed a trend towards using multimodal algorithms that incorporate additional biomarkers such as neuroimaging, neuropsychological tests, and genetic information. Particularly, neuroimaging is commonly used in conjunction with fluid biomarkers for both cross-sectional and longitudinal studies. Our systematic review suggests that cost-effective longitudinal multimodal monitoring data, representative of diverse cultural populations and utilizing white-box ML algorithms, could be a valuable contribution to the development of diagnostic models for AD due to MCI. Clinical assessment and biomarkers, together with ML techniques, could prove pivotal in improving diagnostic tools for MCI due to AD.

Blood-Based Transcriptomic Biomarkers Are Predictive of Neurodegeneration Rather Than Alzheimer's Disease

Alzheimer's disease (AD) is a growing global health crisis affecting millions and incurring substantial economic costs. However, clinical diagnosis remains challenging, with misdiagnoses and underdiagnoses being prevalent. There is an increased focus on putative, blood-based biomarkers that may be useful for the diagnosis as well as early detection of AD. In the present study, we used an unbiased combination of machine learning and functional network analyses to identify blood gene biomarker candidates in AD. Using supervised machine learning, we also determined whether these candidates were indeed unique to AD or whether they were indicative of other neurodegenerative diseases, such as Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS). Our analyses showed that genes involved in spliceosome assembly, RNA binding, transcription, protein synthesis, mitoribosomes, and NADH dehydrogenase were the best-performing genes for identifying AD patients relative to cognitively healthy controls. This transcriptomic signature, however, was not unique to AD, and subsequent machine learning showed that this signature could also predict PD and ALS relative to controls without neurodegenerative disease. Combined, our results suggest that mRNA from whole blood can indeed be used to screen for patients with neurodegeneration but may be less effective in diagnosing the specific neurodegenerative disease.

Assessment of brain-derived extracellular vesicle enrichment for blood biomarker analysis in age-related neurodegenerative diseases: An international overview

INTRODUCTION

Brain-derived extracellular vesicles (BEVs) in blood allows for minimally- invasive investigations of CNS-specific markers of age-related neurodegenerative diseases (NDDs). Polymer-based EV- and immunoprecipitation (IP)-based BEV-enrichment protocols from blood have gained popularity. We systematically investigated protocol consistency across studies, and determined CNS-specificity of proteins associated with these protocols.

METHODS

NDD articles investigating BEVs in blood using polymer-based and/or IP-based BEV enrichment protocols were systematically identified, and protocols compared. Proteins used for BEV-enrichment and/or post-enrichment were assessed for CNS- and brain-cell-type- specificity; extracellular domains (ECD+); and presence in EV-databases.

RESULTS

82.1% of studies used polymer-based (ExoQuick) EV-enrichment, and 92.3% used L1CAM for IP-based BEV-enrichment. Centrifugation times differed across studies. 26.8% of 82 proteins systematically identified were CNS-specific: 50% ECD+, 77.3% were listed in EV- databases.

DISCUSSION

We identified protocol steps requiring standardization, and recommend additional CNS-specific proteins that can be used for BEV-enrichment or as BEV-biomarkers.

Plasma biomarkers identify older adults at risk of Alzheimer's disease and related dementias in a real-world population-based cohort

INTRODUCTION

Plasma biomarkers-cost effective, non-invasive indicators of Alzheimer's disease (AD) and related disorders (ADRD)-have largely been studied in clinical research settings. Here, we examined plasma biomarker profiles and their associated factors in a population-based cohort to determine whether they could identify an at-risk group, independently of brain and cerebrospinal fluid biomarkers.

METHODS

We measured plasma phosphorylated tau181 (p-tau181), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and amyloid beta (Aβ)42/40 ratio in 847 participants from a population-based cohort in southwestern Pennsylvania.

RESULTS

K-medoids clustering identified two distinct plasma Aβ42/40 modes, further categorizable into three biomarker profile groups: normal, uncertain, and abnormal. In different groups, plasma p-tau181, NfL, and GFAP were inversely correlated with Aβ42/40, Clinical Dementia Rating, and memory composite score, with the strongest associations in the abnormal group.

DISCUSSION

Abnormal plasma Aβ42/40 ratio identified older adult groups with lower memory scores, higher dementia risks, and higher ADRD biomarker levels, with potential implications for population screening.

HIGHLIGHTS

Population-based plasma biomarker studies are lacking, particularly in cohorts without cerebrospinal fluid or neuroimaging data. In the Monongahela-Youghiogheny Healthy Aging Team study (n = 847), plasma biomarkers associated with worse memory and Clinical Dementia Rating (CDR), apolipoprotein E ε4, and greater age. Plasma amyloid beta (Aβ)42/40 ratio levels allowed clustering participants into abnormal, uncertain, and normal groups. Plasma Aβ42/40 correlated differently with neurofilament light chain, glial fibrillary acidic protein, phosphorylated tau181, memory composite, and CDR in each group. Plasma biomarkers can enable relatively affordable and non-invasive community screening for evidence of Alzheimer's disease and related disorders pathophysiology.

Morphometric and Nanomechanical Screening of Peripheral Blood Cells with Atomic Force Microscopy for Label-Free Assessment of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis

Neurodegenerative disorders (NDDs) are complex, multifactorial disorders with significant social and economic impact in today's society. NDDs are predicted to become the second-most common cause of death in the next few decades due to an increase in life expectancy but also to a lack of early diagnosis and mainly symptomatic treatment. Despite recent advances in diagnostic and therapeutic methods, there are yet no reliable biomarkers identifying the complex pathways contributing to these pathologies. The development of new approaches for early diagnosis and new therapies, together with the identification of non-invasive and more cost-effective diagnostic biomarkers, is one of the main trends in NDD biomedical research. Here we summarize data on peripheral biomarkers, biofluids (cerebrospinal fluid and blood plasma), and peripheral blood cells (platelets (PLTs) and red blood cells (RBCs)), reported so far for the three most common NDDs-Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). PLTs and RBCs, beyond their primary physiological functions, are increasingly recognized as valuable sources of biomarkers for NDDs. Special attention is given to the morphological and nanomechanical signatures of PLTs and RBCs as biophysical markers for the three pathologies. Modifications of the surface nanostructure and morphometric and nanomechanical signatures of PLTs and RBCs from patients with AD, PD, and ALS have been revealed by atomic force microscopy (AFM). AFM is currently experiencing rapid and widespread adoption in biomedicine and clinical medicine, in particular for early diagnostics of various medical conditions. AFM is a unique instrument without an analog, allowing the generation of three-dimensional cell images with extremely high spatial resolution at near-atomic scale, which are complemented by insights into the mechanical properties of cells and subcellular structures. Data demonstrate that AFM can distinguish between the three pathologies and the normal, healthy state. The specific PLT and RBC signatures can serve as biomarkers in combination with the currently used diagnostic tools. We highlight the strong correlation of the morphological and nanomechanical signatures between RBCs and PLTs in PD, ALS, and AD.

Delirium, neurofilament light chain, and progressive cognitive impairment: analysis of a prospective Norwegian population-based cohort

BACKGROUND

Previous population-based, longitudinal studies have shown that delirium is associated with an increased risk of dementia and cognitive decline. However, the underlying biological mechanisms are largely unknown. We aimed to assess the effects of delirium on both cognitive trajectories and any neuronal injury, measured via neurofilament light chain (NfL).

METHODS

In this analysis of a prospective, 2-year follow-up, cohort study of participants aged 65 years or older living in Sandefjord municipality, Norway, we included cohort participants who were receiving domiciliary care services at least once per week between May 12, 2015, and July 8, 2016. Individuals with a life expectancy of less than 1 week, with Lewy body dementia, with psychiatric illness (except dementia), or for whom substance misuse was the principal indication for domiciliary services were excluded. Participants had a comprehensive assessment at 6-month intervals for 2 years, which included the Montreal Cognitive Assessment (MoCA) and a blood sample for NfL to measure neuronal injury. All information on clinical diagnoses and medications were cross-referenced with medical records. During any acute change in mental status or hospitalisation (ie, admission to hospital), participants were assessed once per day for delirium with Diagnostic and Statistical Manual of Mental Disorders, fifth edition criteria. We also measured NfL from blood samples taken from participants who were acutely hospitalised.

FINDINGS

Between May 12, 2015, and July 8, 2016, 210 participants were eligible for inclusion and assessed at baseline (138 [66%] of whom were female and 72 [34%] of whom were male), 203 completed cognitive assessment, and 141 were followed up for 2 years. 160 (76%) of 210 had moderate or severe frailty and 112 (53%) were living with dementia. During the 2-year follow-up, 89 (42%) of 210 participants were diagnosed with one or more episodes of delirium. Incident delirium was independently associated with a decrease in MoCA score at the next 6-month follow-up, even after adjustment for age, sex, education, previous MoCA score, and frailty (adjusted mean difference -1·5, 95% CI -2·9 to -0·1). We found an interaction between previous MoCA score and delirium (β -0·254, 95% CI -0·441 to -0·066, p=0·010), with the largest decline being observed in people with better baseline cognition. Participants with delirium and good previous cognitive function and participants with a high peak concentration of NfL during any hospitalisation had increased NfL at the next 6-month follow-up. Mediation analyses showed independent pathways from previous MoCA score to follow-up MoCA score with contributions from incident delirium (-1·7, 95% CI -2·8 to -0·6) and from previous NfL to follow-up MoCA score with contributions from acute NfL concentrations (-1·8, -2·5 to -1·1). Delirium was directly linked with a predicted value of 1·2 pg/mL (95% CI 1·02 to 1·40, p=0·029) increase in NfL.

INTERPRETATION

In people aged 65 years or older, an episode of delirium was associated with a decline in MoCA score. Greater neuronal injury during acute illness and delirium, measured by NfL, was associated with greater cognitive decline. For clinicians, our finding of delirium associated with both signs of acute neuronal injury, measured via NfL, and cognitive decline is important regarding the risk of long-term cognitive deterioration and to acknowledge that delirium is harmful for the brain.

FUNDING

South-Eastern Norway Health Authorities, Old Age Psychiatry Research Network, Telemark Hospital Trust, Vestfold Hospital Trust, and Norwegian National Centre for Ageing and Health.

TRANSLATION

For the Norwegian translation of the abstract see Supplementary Materials section.

High sensitivity of asymmetric 18F-THK5351 PET abnormality in patients with corticobasal syndrome

Corticobasal syndrome (CBS) is characterized by symptoms related to the asymmetric involvement of the cerebral cortex and basal ganglia. However, early detection of asymmetric imaging abnormalities can be challenging. Previous studies reported asymmetric ¹⁸F-THK5351 PET abnormalities in CBS patients, but the sensitivity for detecting such abnormalities in larger patient samples, including early-stage cases, remains unclear. Patients clinically diagnosed with CBS were recruited. All patients displayed asymmetric symptoms in the cerebral cortex and basal ganglia. Asymmetric THK5351 PET abnormalities were determined through visual assessment. Brain MRI, perfusion SPECT, and dopamine transporter (DAT) SPECT results were retrospectively reviewed. The 15 patients had a median age of 72 years (59-86 years) and a disease duration of 2 years (0.5-7 years). Four patients met the probable and 11 met the possible CBS criteria according to Armstrong criteria at the time of PET examination. All patients, including early-stage cases, exhibited asymmetric tracer uptake contralateral to their symptom-dominant side in the cerebral cortex/subcortical white matter and striatum (100%). The sensitivity for detecting asymmetric imaging abnormalities contralateral to the symptom-dominant side was 86.7% for brain MRI, 81.8% for perfusion SPECT, and 90% for DAT SPECT. White matter volume reduction was observed in the subcortical region of the precentral gyrus with increased THK5351 uptake, occurring significantly more frequently than gray matter volume reduction. THK5351 PET may be a sensitive imaging technique for detecting asymmetric CBS pathologies, including those in early stages.

Neurological manifestations of post-acute sequelae of COVID-19: which liquid biomarker should we use?

Long COVID syndrome, also known as post-acute sequelae of COVID-19 (PASC), is characterized by persistent symptoms lasting 3-12 weeks post SARS-CoV-2 infection. Patients suffering from PASC can display a myriad of symptoms that greatly diminish quality of life, the most frequent being neuropsychiatric. Thus, there is an eminent need to diagnose and treat PASC related neuropsychiatric manifestation (neuro-PASC). Evidence suggests that liquid biomarkers could potentially be used in the diagnosis and monitoring of patients. Undoubtedly, such biomarkers would greatly benefit clinicians in the management of patients; however, it remains unclear if these can be reliably used in this context. In this mini review, we highlight promising liquid (blood and cerebrospinal fluid) biomarkers, namely, neuronal injury biomarkers NfL, GFAP, and tau proteins as well as neuroinflammatory biomarkers IL-6, IL-10, TNF-α, and CPR associated with neuro-PASC and discuss their limitations in clinical applicability.

Presenilin-1 (PSEN1) Mutations: Clinical Phenotypes beyond Alzheimer's Disease

Presenilin 1 (PSEN1) is a part of the gamma secretase complex with several interacting substrates, including amyloid precursor protein (APP), Notch, adhesion proteins and beta catenin. PSEN1 has been extensively studied in neurodegeneration, and more than 300 PSEN1 mutations have been discovered to date. In addition to the classical early onset Alzheimer's disease (EOAD) phenotypes, PSEN1 mutations were discovered in several atypical AD or non-AD phenotypes, such as frontotemporal dementia (FTD), Parkinson's disease (PD), dementia with Lewy bodies (DLB) or spastic paraparesis (SP). For example, Leu113Pro, Leu226Phe, Met233Leu and an Arg352 duplication were discovered in patients with FTD, while Pro436Gln, Arg278Gln and Pro284Leu mutations were also reported in patients with motor dysfunctions. Interestingly, PSEN1 mutations may also impact non-neurodegenerative phenotypes, including PSEN1 Pro242fs, which could cause acne inversa, while Asp333Gly was reported in a family with dilated cardiomyopathy. The phenotypic diversity suggests that PSEN1 may be responsible for atypical disease phenotypes or types of disease other than AD. Taken together, neurodegenerative diseases such as AD, PD, DLB and FTD may share several common hallmarks (cognitive and motor impairment, associated with abnormal protein aggregates). These findings suggested that PSEN1 may interact with risk modifiers, which may result in alternative disease phenotypes such as DLB or FTD phenotypes, or through less-dominant amyloid pathways. Next-generation sequencing and/or biomarker analysis may be essential in clearly differentiating the possible disease phenotypes and pathways associated with non-AD phenotypes.

Predicting amyloid PET and tau PET stages with plasma biomarkers

Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.

Evolution of Detecting Early Onset of Alzheimer's Disease: From Neuroimaging to Optical Immunoassays

Alzheimer's disease (AD) is a pathological disorder defined by the symptoms of memory loss and deterioration of cognitive abilities over time. Although the etiology is complex, it is mainly associated with the accumulation of toxic amyloid-β peptide (Aβ) aggregates and tau protein-induced neurofibrillary tangles (NFTs). Even now, creating non-invasive, sensitive, specific, and cost-effective diagnostic methods for AD remains challenging. Over the past few decades, polymers, and nanomaterials (e.g., nanodiamonds, nanogold, quantum dots) have become attractive and practical tools in nanomedicine for diagnosis and treatment. This review focuses on current developments in sensing methods such as enzyme-linked immunosorbent assay (ELISA) and surface-enhanced Raman scattering (SERS) to boost the sensitivity in detecting related biomarkers for AD. In addition, optical analysis platforms such as ELISA and SERS have found increasing popularity among researchers due to their excellent sensitivity and specificity, which may go as low as the femtomolar range. While ELISA offers easy technological usage and high throughput, SERS has the advantages of improved mobility, simple electrical equipment integration, and lower cost. Both portable optical sensing techniques are highly superior in terms of sensitivity, specificity, human application, and practicality, enabling the early identification of AD biomarkers.

Plasma NfL is associated with the APOE ε4 allele, brain imaging measurements of neurodegeneration, and lower recall memory scores in cognitively unimpaired late-middle-aged and older adults

BACKGROUND

Plasma neurofilament light (NfL) is an indicator of neurodegeneration and/or neuroaxonal injury in persons with Alzheimer's disease (AD) and a wide range of other neurological disorders. Here, we characterized and compared plasma NfL concentrations in cognitively unimpaired (CU) late-middle-aged and older adults with two, one, or no copies of the APOE ε4 allele, the major genetic risk factor for AD. We then assessed plasma NfL associations with brain imaging measurements of AD-related neurodegeneration (hippocampal atrophy and a hypometabolic convergence index [HCI]), brain imaging measurements of amyloid-β plaque burden, tau tangle burden and white matter hyperintensity volume (WMHV), and delayed and total recall memory scores.

METHODS

Plasma NfL concentrations were measured in 543 CU 69 ± 9 year-old participants in the Arizona APOE Cohort Study, including 66 APOE ε4 homozygotes (HM), 165 heterozygotes (HT), and 312 non-carriers (NC). Robust regression models were used to characterize plasma NfL associations with APOE ε4 allelic dose before and after adjustment for age, sex, and education. They were also used to characterize plasma NfL associations with MRI-based hippocampal volume and WMHV measurements, an FDG PET-based HCI, mean cortical PiB PET measurements of amyloid-β plaque burden and meta-region-of-interest (meta-ROI) flortaucipir PET measurements of tau tangle burden, and Auditory Verbal Learning Test (AVLT) Delayed and Total Recall Memory scores.

RESULTS

After the adjustments noted above, plasma NfL levels were significantly greater in APOE ε4 homozygotes and heterozygotes than non-carriers and significantly associated with smaller hippocampal volumes (r =  - 0.43), greater tangle burden in the entorhinal cortex and inferior temporal lobes (r = 0.49, r = 0.52, respectively), and lower delayed (r =  - 0.27), and total (r =  - 0.27) recall memory scores (p < 0.001). NfL levels were not significantly associated with PET measurements of amyloid-β plaque or total tangle burden.

CONCLUSIONS

Plasma NfL concentrations are associated with the APOE ε4 allele, brain imaging biomarkers of neurodegeneration, and less good recall memory in CU late-middle-aged and older adults, supporting its value as an indicator of neurodegeneration in the preclinical study of AD.

Nanosensor-Driven Detection of Neuron-Derived Exosomal Aβ42 with Graphene Electrolyte-Gated Transistor for Alzheimer's Disease Diagnosis

Blood-based tests have sparked tremendous attention in non-invasive early diagnosis of Alzheimer's disease (AD), a most prevalent neurodegenerative malady worldwide. Despite significant progress in the methodologies for detecting AD core biomarkers such as Aβ₄₂ from serum/plasma, there remains cautious optimism going forward due to its controversial diagnostic value and disease relevance. Here, a graphene electrolyte-gated transistor biosensor is reported for the detection of serum neuron-derived exosomal Aβ₄₂ (NDE-Aβ₄₂), which is an emerging, compelling trove of blood biomarker for AD. Assisted by the antifouling strategy with the dual-blocking process, the noise against complex biological background was considerably reduced, forging an impressive sensitivity gain with a limit of detection of 447 ag/mL. An accurate detection of SH-SY5Y-derived exosomal Aβ₄₂ was also achieved with highly conformable enzyme-linked immunosorbent assay results. Importantly, the clinical analysis for 27 subjects revealed the immense diagnostic value of NDE-Aβ₄₂, which can outclass that of serum Aβ₄₂. The developed electronic assay demonstrates, for the first time, nanosensor-driven NDE-Aβ₄₂ detection, which enables a reliable discrimination of AD patients from non-AD individuals and even the differential diagnosis between AD and vascular dementia patients, with an accuracy of 100% and a Youden index of 1. This NDE-Aβ₄₂ biosensor defines a robust approach for blood-based confident AD ascertain.

Plasma phospho-tau in Alzheimer's disease: towards diagnostic and therapeutic trial applications

As the leading cause of dementia, Alzheimer's disease (AD) is a major burden on affected individuals, their families and caregivers, and healthcare systems. Although AD can be identified and diagnosed by cerebrospinal fluid or neuroimaging biomarkers that concord with neuropathological evidence and clinical symptoms, challenges regarding practicality and accessibility hinder their widespread availability and implementation. Consequently, many people with suspected cognitive impairment due to AD do not receive a biomarker-supported diagnosis. Blood biomarkers have the capacity to help expand access to AD diagnostics worldwide. One such promising biomarker is plasma phosphorylated tau (p-tau), which has demonstrated specificity to AD versus non-AD neurodegenerative diseases, and will be extremely important to inform on clinical diagnosis and eligibility for therapies that have recently been approved. This review provides an update on the diagnostic and prognostic performances of plasma p-tau181, p-tau217 and p-tau231, and their associations with in vivo and autopsy-verified diagnosis and pathological hallmarks. Additionally, we discuss potential applications and unanswered questions of plasma p-tau for therapeutic trials, given their recent addition to the biomarker toolbox for participant screening, recruitment and during-trial monitoring. Outstanding questions include assay standardization, threshold generation and biomarker verification in diverse cohorts reflective of the wider community attending memory clinics and included in clinical trials.

Plasma biomarkers for neurodegenerative disorders: ready for prime time?

PURPOSE OF REVIEW

Several plasma biomarkers for Alzheimer's disease and related disorders (ADRD) have demonstrated clinical and technical robustness. However, are they ready for clinical implementation? This review critically appraises current evidence for and against the immediate use of plasma biomarkers in clinical care.

RECENT FINDINGS

Plasma biomarkers have significantly improved our understanding of ADRD time-course, risk factors, diagnosis and prognosis. These advances are accelerating the development and in-human testing of therapeutic candidates, and the selection of individuals with subtle biological evidence of disease who fit the criteria for early therapeutic targeting. However, standardized tests and well validated cut-off values are lacking. Moreover, some assays (e.g., plasma Aβ methods) have poor robustness to withstand inevitable day-to-day technical variations. Additionally, recent reports suggest that common comorbidities of aging (e.g., kidney disease, diabetes, hypertension) can erroneously affect plasma biomarker levels, clinical utility and generalizability. Furthermore, it is unclear if health disparities can explain reported racial/ethnic differences in biomarker levels and functions. Finally, current clinically approved plasma methods are more expensive than CSF assays, questioning their cost effectiveness.

SUMMARY

Plasma biomarkers have biological and clinical capacity to detect ADRD. However, their widespread use requires issues around thresholds, comorbidities and diverse populations to be addressed.

Thermodynamic Signatures of Blood Plasma Proteome in Neurodegenerative Pathologies

Discovery of diagnostic biomarkers for age-related neurodegenerative pathologies (NDDs) is essential for accurate diagnosis, following disease progression and drug development. Blood plasma and blood cells are important peripheral sources for NDDs' biomarkers that, although present in lower concentrations than in cerebrospinal fluid, would allow noninvasive diagnostics. To identify new biomarkers for Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS), in this work we have evaluated the modifications in the thermodynamic behavior of blood plasma proteome exploring differential scanning calorimetry. The plasma thermodynamics reflected the complexity and heterogeneity of the two pathologies. The unfolding temperature of the most abundant plasma protein albumin and the weighted average center of the calorimetric profile appeared as the two thermodynamic signatures that reflected modifications of the plasma proteome, i.e., strong thermal stabilization of albumin and plasma proteins' interaction network, related to both pathologies. Based on those two signatures, both PD and ALS patients were stratified in two sets, except several cases with thermodynamic parameters that strongly differed from those of the calorimetric sets. Along with modifications of the plasma thermodynamic behavior, we found altered globulin levels in all PD and ALS patients' plasma (higher level of α- and β-globulin fractions and lower level of γ-globulin fraction than the respective reference values) employing capillary electrophoresis. The presented results reveal the potential of calorimetry to indirectly identify NDDs' biomarkers in blood plasma.

Serum Neurofilament Light Chain in the Diagnostic Evaluation of Patients with Cognitive Symptoms in the Neurological Consultation of a Tertiary Center

Serum light-chain neurofilaments (sNfL) have been investigated as a potential minimally invasive biomarker that could help in the diagnosis of patients with cognitive symptoms. We assessed the correlation between sNfL and cerebrospinal fluid (CSF) biomarkers (sNfL versus CSF NfL, ρ= 0.70, p < 0.001), the performance of sNfL in distinguishing controls from patients (controls versus frontotemporal dementia, area under curve 0.86), and sNfL differences in mild cognitive impairment according to amyloid-β (Aβ) deposition (Aβ versus non-Aβ, p = 0.017). Our results support the role of this biomarker in the screening and risk stratification of patients followed in a neurological consultation of a tertiary center.

Plasma Phosphorylated Tau181 and Amyloid-β42 in Dementia with Lewy Bodies Compared with Alzheimer's Disease and Cognitively Healthy People

BACKGROUND

Increasing evidence illustrates the value of plasma biomarkers of Alzheimer's disease (AD) to screen for and identify dementia with Lewy bodies (DLB). However, confirmatory studies are needed to demonstrate the feasibility of these markers.

OBJECTIVE

To determine the feasibility of plasma tau phosphorylated at threonine 181 (p-tau181) and amyloid-β42 (Aβ42) as potential biomarkers to differentiate AD and DLB.

METHODS

We evaluated plasma samples from patients with DLB (n = 47) and AD (n = 55) and healthy controls (HCs, n = 30), using ELISAs to measure p-tau181 and Aβ42. Additionally, we examined neuropsychological assessment scores for participants. The plasma biomarkers were investigated for correlation with neuropsychological assessments and discriminant ability to identify DLB.

RESULTS

Plasma p-tau181 was significantly lower in DLB than in AD and HCs. Plasma Aβ42 was significantly higher in DLB than in AD but lower in DLB than in HCs. We found good correlations between plasma Aβ42 and neuropsychological scores in the whole cohort, while p-tau181 was associated with cognitive status in DLB. In the distinction between DLB and HCs, plasma p-tau181 and Aβ42 showed similar accuracy, while Aβ42 showed better accuracy than p-tau181 in discriminating DLB and AD.

CONCLUSION

In a single-center clinical cohort, we confirmed the high diagnostic value of plasma p-tau181 and Aβ42 for distinguishing patients with DLB from HCs. Plasma Aβ42 improved the differential diagnosis of DLB from AD.

IGF1 deficiency integrates stunted growth and neurodegeneration in Down syndrome

Down syndrome (DS), the genetic condition caused by trisomy 21 (T21), is characterized by stunted growth, cognitive impairment, and increased risk of diverse neurological conditions. Although signs of lifelong neurodegeneration are well documented in DS, the mechanisms underlying this phenotype await elucidation. Here we report a multi-omics analysis of neurodegeneration and neuroinflammation biomarkers, plasma proteomics, and immune profiling in a diverse cohort of more than 400 research participants. We identified depletion of insulin growth factor 1 (IGF1), a master regulator of growth and brain development, as the top biosignature associated with neurodegeneration in DS. Individuals with T21 display chronic IGF1 deficiency downstream of growth hormone production, associated with a specific inflammatory profile involving elevated tumor necrosis factor alpha (TNF-α). Shorter children with DS show stronger IGF1 deficiency, elevated biomarkers of neurodegeneration, and increased prevalence of autism and other conditions. These results point to disruption of IGF1 signaling as a potential contributor to stunted growth and neurodegeneration in DS.

Brain-derived tau: a novel blood-based biomarker for Alzheimer's disease-type neurodegeneration

Blood-based biomarkers for amyloid beta and phosphorylated tau show good diagnostic accuracies and agreements with their corresponding CSF and neuroimaging biomarkers in the amyloid/tau/neurodegeneration [A/T/(N)] framework for Alzheimer's disease. However, the blood-based neurodegeneration marker neurofilament light is not specific to Alzheimer's disease while total-tau shows lack of correlation with CSF total-tau. Recent studies suggest that blood total-tau originates principally from peripheral, non-brain sources. We sought to address this challenge by generating an anti-tau antibody that selectively binds brain-derived tau and avoids the peripherally expressed 'big tau' isoform. We applied this antibody to develop an ultrasensitive blood-based assay for brain-derived tau, and validated it in five independent cohorts (n = 609) including a blood-to-autopsy cohort, CSF biomarker-classified cohorts and memory clinic cohorts. In paired samples, serum and CSF brain-derived tau were significantly correlated (rho = 0.85, P < 0.0001), while serum and CSF total-tau were not (rho = 0.23, P = 0.3364). Blood-based brain-derived tau showed equivalent diagnostic performance as CSF total-tau and CSF brain-derived tau to separate biomarker-positive Alzheimer's disease participants from biomarker-negative controls. Furthermore, plasma brain-derived tau accurately distinguished autopsy-confirmed Alzheimer's disease from other neurodegenerative diseases (area under the curve = 86.4%) while neurofilament light did not (area under the curve = 54.3%). These performances were independent of the presence of concomitant pathologies. Plasma brain-derived tau (rho = 0.52-0.67, P = 0.003), but not neurofilament light (rho = -0.14-0.17, P = 0.501), was associated with global and regional amyloid plaque and neurofibrillary tangle counts. These results were further verified in two memory clinic cohorts where serum brain-derived tau differentiated Alzheimer's disease from a range of other neurodegenerative disorders, including frontotemporal lobar degeneration and atypical parkinsonian disorders (area under the curve up to 99.6%). Notably, plasma/serum brain-derived tau correlated with neurofilament light only in Alzheimer's disease but not in the other neurodegenerative diseases. Across cohorts, plasma/serum brain-derived tau was associated with CSF and plasma AT(N) biomarkers and cognitive function. Brain-derived tau is a new blood-based biomarker that outperforms plasma total-tau and, unlike neurofilament light, shows specificity to Alzheimer's disease-type neurodegeneration. Thus, brain-derived tau demonstrates potential to complete the AT(N) scheme in blood, and will be useful to evaluate Alzheimer's disease-dependent neurodegenerative processes for clinical and research purposes.

Early Diagnosis of Brain Diseases Using Artificial Intelligence and EV Molecular Data: A Proposed Noninvasive Repeated Diagnosis Approach

Brain-derived extracellular vesicles (BDEVs) are released from the central nervous system. Brain-related research and diagnostic techniques involving BDEVs have rapidly emerged as a means of diagnosing brain disorders because they are minimally invasive and enable repeatable measurements based on body fluids. However, EVs from various cells and organs are mixed in the blood, acting as potential obstacles for brain diagnostic systems using BDEVs. Therefore, it is important to screen appropriate brain EV markers to isolate BDEVs in blood. Here, we established a strategy for screening potential BDEV biomarkers. To collect various molecular data from the BDEVs, we propose that the sensitivity and specificity of the diagnostic system could be enhanced using machine learning and AI analysis. This BDEV-based diagnostic strategy could be used to diagnose various brain diseases and will help prevent disease through early diagnosis and early treatment.

A Step Forward for Smart Clothes─Fabric-Based Microfluidic Sensors for Wearable Health Monitoring

We report the first demonstration of fabric-based microfluidics for wearable sensing. A new technology to develop microfluidics on fabrics, as a part of an undergarment, is described here. Compared to conventional microfluidics from polydimethylsiloxane, fabric-based microfluidics are simple to make, robust, and suitable for efficient sweat delivery. Specifically, acrylonitrile butadiene styrene (ABS) films with precut microfluidic patterns were infused through fabrics to form hydrophobic areas in a specially controlled sandwich structure. Experimental tests and simulations confirmed the sweat delivery efficiency of the microfluidics. Electrodes were screen-printed onto the fabric-based microfluidic. A novel wearable potentiometer based on Arduino was also developed as the transducer and signal readouts, which was low-cost, standardized, open-source, and capable of wireless data transfer. We applied the sensor system as a standalone or as a module of a T-shirt to quantify [Ca²⁺] in a wearer's sweat, with physiological and accurate results generated. Overall, this work represents a critical step in turning regular undergarments into biochemically smart platforms for health monitoring, which will broadly benefit human healthcare.

Association of neurofilament light chain with renal function: mechanisms and clinical implications

BACKGROUND

Blood-based neurofilament light chain (NfL) is a promising biomarker of neurodegeneration across multiple neurodegenerative diseases. However, blood-based NfL is highly associated with renal function in older adults, which leads to the concern that blood-based NfL levels may be influenced by renal function, rather than neurodegeneration alone. Despite growing interest in using blood-based NfL as a biomarker of neurodegeneration in research and clinical practices, whether renal function should always be accounted for in these settings remains unclear. Moreover, the mechanisms underlying this association between blood-based measures of NfL and renal function remain elusive. In this study, we first evaluated the effect of renal function on the associations of plasma NfL with other measures of neurodegeneration. We then examined the extent of genetic and environmental contributions to the association between plasma NfL and renal function.

METHODS

In a sample of 393 adults (mean age=75.22 years, range=54-90), we examined the associations of plasma NfL with cerebrospinal fluid (CSF) NfL and brain volumetric measures before and after adjusting for levels of serum creatinine (an index of renal function). In an independent sample of 969 men (mean age=67.57 years, range=61-73) that include monozygotic and dizygotic twin pairs, we replicated the same analyses and leveraged biometrical twin modeling to examine the genetic and environmental influences on the plasma NfL and creatinine association.

RESULTS

Plasma NfL's associations with cerebrospinal fluid NfL and brain volumetric measures did not meaningfully change after adjusting for creatinine levels. Both plasma NfL and creatinine were significantly heritable (h2=0.54 and 0.60, respectively). Their phenotypic correlation (r=0.38) was moderately explained by shared genetic influences (genetic correlation=0.46) and unique environmental influences (unique environmental correlation=0.27).

CONCLUSIONS

Adjusting for renal function is unnecessary when assessing associations between plasma NfL and other measures of neurodegeneration but is necessary if plasma NfL is compared to a cutoff for classifying neurodegeneration-positive versus neurodegeneration-negative individuals. Blood-based measures of NfL and renal function are heritable and share common genetic influences.

Blood Tests for Alzheimer's Disease: Increasing Efforts to Expand and Diversify Research Participation Is Critical for Widespread Validation and Acceptance

The recent academic and commercial development, and regulatory approvals, of blood-based Alzheimer's disease (AD) biomarkers are breakthrough developments of immense potential. However, clinical validation studies and therapeutic trial applications are limited almost exclusively to non-Hispanic White cohorts often including highly-educated, high-earning participants. This commentary argues that the true benefits of blood tests for AD will be realized by active inclusion of diverse groups including minoritized populations, people of socioeconomic status different from those included in existing cohorts, and residents of low- and middle-income countries. The article discusses key factors that are critical for a successful implementation of diversity programs.

Human variation in population-wide gene expression data predicts gene perturbation phenotype

Population-scale datasets of healthy individuals capture genetic and environmental factors influencing gene expression. The expression variance of a gene of interest (GOI) can be exploited to set up a quasi loss- or gain-of-function "in population" experiment. We describe here an approach, huva (human variation), taking advantage of population-scale multi-layered data to infer gene function and relationships between phenotypes and expression. Within a reference dataset, huva derives two experimental groups with LOW or HIGH expression of the GOI, enabling the subsequent comparison of their transcriptional profile and functional parameters. We demonstrate that this approach robustly identifies the phenotypic relevance of a GOI allowing the stratification of genes according to biological functions, and we generalize this concept to almost 16,000 genes in the human transcriptome. Additionally, we describe how huva predicts monocytes to be the major cell type in the pathophysiology of STAT1 mutations, evidence validated in a clinical cohort.

Plasma p-tau181, neurofilament light chain and association with cognition in Parkinson’s disease

Early identification of cognitive impairment in Parkinson’s disease (PD) has important clinical and research implications. The aim of our study was to investigate the role of plasma tau phosphorylated at amino acid 181 (p-tau181) and plasma neurofilament light chain (NfL) as biomarkers of cognition in PD. Baseline concentrations of plasma p-tau181 and NfL were measured in a cohort of 136 patients with PD and 63 healthy controls (HC). Forty-seven PD patients were followed up for up to 2 years. Cross-sectional and longitudinal associations between baseline plasma biomarkers and cognitive progression were investigated using linear regression and linear mixed effects models. At baseline, plasma p-tau181 concentration was significantly higher in PD subjects compared with HC (p = 0.026). In PD patients, higher plasma NfL was associated with lower MMSE score at baseline, after adjusting for age, sex and education (p = 0.027). Baseline plasma NfL also predicted MMSE decline over time in the PD group (p = 0.020). No significant association between plasma p-tau181 concentration and baseline or longitudinal cognitive performance was found. While the role of p-tau181 as a diagnostic biomarker for PD and its relationship with cognition need further elucidation, plasma NfL may serve as a feasible, non-invasive biomarker of cognitive progression in PD.

Fluid biomarkers in Alzheimer's disease

Alzheimer's disease (AD) characterization has progressed from being indexed using clinical symptomatology followed by neuropathological examination at autopsy to in vivo signatures using cerebrospinal fluid (CSF) biomarkers and positron emission tomography. The core AD biomarkers reflect amyloid-β plaques (A), tau pathology (T) and neurodegeneration (N), following the ATN schedule, and are now being introduced into clinical routine practice. This is an important development, as disease-modifying treatments are now emerging. Further, there are now reproducible data on CSF biomarkers which reflect synaptic pathology, neuroinflammation and common co-pathologies. In addition, the development of ultrasensitive techniques has enabled the core CSF biomarkers of AD pathophysiology to be translated to blood (e.g., phosphorylated tau, amyloid-β and neurofilament light). In this chapter, we review where we stand with both core and novel CSF biomarkers, as well as the explosion of data on blood biomarkers. Also, we discuss potential applications in research aiming to better understand the disease, as well as possible use in routine clinical practice and therapeutic trials.

Serum Metabolomic Profiling in Aging Mice Using Liquid Chromatography-Mass Spectrometry

BACKGROUND

The process of aging and metabolism are intricately linked, thus rendering the identification of reliable biomarkers related to metabolism crucial for delaying the aging process. However, research of reliable markers that reflect aging profiles based on machine learning is scarce.

METHODS

Serum samples were obtained from aged mice (18-month-old) and young mice (3-month-old). LC-MS was used to perform a comprehensive analysis of the serum metabolome and machine learning was used to screen potential aging-related biomarkers.

RESULTS

In total, aging mice were characterized by 54 different metabolites when compared to control mice with criteria: VIP ≥ 1, q-value < 0.05, and Fold-Change ≥ 1.2 or ≤0.83. These metabolites were mostly involved in fatty acid biosynthesis, cysteine and methionine metabolism, D-glutamine and D-glutamate metabolism, and the citrate cycle (TCA cycle). We merged the comprehensive analysis and four algorithms (LR, GNB, SVM, and RF) to screen aging-related biomarkers, leading to the recognition of oleic acid. In addition, five metabolites were identified as novel aging-related indicators, including oleic acid, citric acid, D-glutamine, trypophol, and L-methionine.

CONCLUSIONS

Changes in the metabolism of fatty acids and conjugates, organic acids, and amino acids were identified as metabolic dysregulation related to aging. This study revealed the metabolic profile of aging and provided insights into novel potential therapeutic targets for delaying the effects of aging.

Selective Detection and Characterization of Small Cysteine-Containing Peptides with Cluster-Modified Nanopore Sensing

It was recently demonstrated that one can monitor ligand-induced structure fluctuations of individual thiolate-capped gold nanoclusters using resistive-pulse nanopore sensing. The magnitude of the fluctuations scales with the size of the capping ligand, and it was later shown one can observe ligand exchange in this nanopore setup. We expand on these results by exploring the different types of current fluctuations associated with peptide ligands attaching to tiopronin-capped gold nanoclusters. We show here that the fluctuations can be used to identify the attaching peptide through either the magnitude of the peptide-induced current jumps or the onset of high-frequency current fluctuations. Importantly, the peptide attachment process requires that the peptide contains a cysteine residue. This suggests that nanopore-based monitoring of peptide attachments with thiolate-capped clusters could provide a means for selective detection of cysteine-containing peptides. Finally, we demonstrate the cluster-based protocol with various peptide mixtures to show that one can identify more than one cysteine-containing peptide in a mixture.

Plasma proteome profiling identifies changes associated to AD but not to FTD

BACKGROUND

Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process.

METHODS

Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 ± 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 ± 7.9; 45% female), AD patients (n = 57; age = 65.5 ± 8.0; 39% female), and non-demented controls (n = 148; 61.3 ± 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 ± 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 ± 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 ± 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis.

RESULTS

Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified.

CONCLUSIONS

We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts.

Decision making under uncertainty in the diagnosis and management of Alzheimer's Disease in primary care: A study protocol applying concepts from neuroeconomics

Background

The current management of patients with Dementia, primarily with Alzheimer's Disease (AD) is rapidly evolving. However, limited information is available about the current gaps and decision-making in primary care.

Objectives

To evaluate factors associated with gaps, risk preferences regarding diagnostic and therapeutic choices in the management of patients with AD by primary care physicians (PCP) from across Canada.

Methods

We propose a non-interventional, cross-sectional pilot study involving 120 primary care physicians referred from the College of Family Physicians of Canada to assess diagnostic and therapeutic decisions in the management of ten simulated AD-related case-scenarios commonly encountered in clinical practice. We initially describe the current landscape and gaps regarding diagnostic and therapeutic challenges in the management of patients with AD in primary care. Then, we provide concepts from behavioral economics and neuroeconomics applied to medical decision-making. Specifically, we include standardized tests to measure risk aversion, physicians' reactions to uncertainty, and questions related to risk preferences in different domains. Finally, we summarize the protocol to be implemented to address our goals. The primary study outcome is the proportion of participants that elect to defer initial investigations to the specialist and the associated factors. Secondary outcomes include the proportion of PCP willing to order cerebral spinal fluid studies, PET scans, or initiate treatment according to the simulated case-scenarios. The study will be conducted in English and French.

Conclusions

The study findings will contribute a better understanding of relevant factors associated with diagnostic and therapeutic decisions of PCP in the management of AD, identifying participant's preferences and evaluating the role of behavioral aspects such tolerance to uncertainty, aversion to ambiguity, and therapeutic inertia.

Diagnostic value of plasma p-tau181, NfL, and GFAP in a clinical setting cohort of prevalent neurodegenerative dementias

Background

Increasing evidence supports the use of plasma biomarkers of neurodegeneration and neuroinflammation to screen and diagnose patients with dementia. However, confirmatory studies are required to demonstrate their usefulness in the clinical setting.

Methods

We evaluated plasma and cerebrospinal fluid (CSF) samples from consecutive patients with frontotemporal dementia (FTD) (n = 59), progressive supranuclear palsy (PSP) (n = 31), corticobasal syndrome (CBS) (n = 29), dementia with Lewy bodies (DLB) (n = 49), Alzheimer disease (AD) (n = 97), and suspected non-AD physiopathology (n = 51), as well as plasma samples from 60 healthy controls (HC). We measured neurofilament light chain (NfL), phospho-tau181 (p-tau181), and glial fibrillary acid protein (GFAP) using Simoa (all plasma biomarkers and CSF GFAP), CLEIA (CSF p-tau181), and ELISA (CSF NfL) assays. Additionally, we stratified patients according to the A/T/N classification scheme and the CSF α-synuclein real-time quaking-induced conversion assay (RT-QuIC) results.

Results

We found good correlations between CSF and plasma biomarkers for NfL (rho = 0.668, p < 0.001) and p-tau181 (rho = 0.619, p < 0.001). Plasma NfL was significantly higher in disease groups than in HC and showed a greater increase in FTD than in AD [44.9 (28.1–68.6) vs. 21.9 (17.0–27.9) pg/ml, p < 0.001]. Conversely, plasma p-tau181 and GFAP levels were significantly higher in AD than in FTD [3.2 (2.4–4.3) vs. 1.1 (0.7–1.6) pg/ml, p < 0.001; 404.7 (279.7–503.0) vs. 198.2 (143.9–316.8) pg/ml, p < 0.001]. GFAP also allowed discriminating disease groups from HC. In the distinction between FTD and AD, plasma p-tau181 showed better accuracy (AUC 0.964) than NfL (AUC 0.791) and GFAP (AUC 0.818). In DLB and CBS, CSF amyloid positive (A+) subjects had higher plasma p-tau181 and GFAP levels than A− individuals. CSF RT-QuIC showed positive α-synuclein seeding activity in 96% DLB and 15% AD patients with no differences in plasma biomarker levels in those stratified by RT-QuIC result.

Conclusions

In a single-center clinical cohort, we confirm the high diagnostic value of plasma p-tau181 for distinguishing FTD from AD and plasma NfL for discriminating degenerative dementias from HC. Plasma GFAP alone differentiates AD from FTD and neurodegenerative dementias from HC but with lower accuracy than p-tau181 and NfL. In CBS and DLB, plasma p-tau181 and GFAP levels are significantly influenced by beta-amyloid pathology.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01093-6.