Application of fiber loop ringdown spectroscopy technique for a new approach to beta-amyloid monitoring for Alzheimer Disease's early detection.

A novel fiber optic biosensor was purposed for a new approach to monitor amyloid beta protein fragment 1-42 (Aß42) for Alzheimer's Disease (AD) early detection. The sensor was fabricated by etching a part of fiber from single mode fiber loop in pure hydrofluoric acid solution and utilized as a Local Optical Refractometer (LOR) to monitor the change Aß42 concentration in Artificial Cerebrospinal Fluid (ACSF). The Fiber Loop Ringdown Spectroscopy (FLRDS) technique is an ultra-sensitive measurement technique with low-cost, high sensitivity, real-time measurement, continuous measurement and portability features that was utilized with a fiber optic sensor for the first time for the detection of a biological signature in an ACSF environment. Here, the measurement is based on the total optical loss detection when specially fabricated sensor heads were immersed into ACSF solutions with and without different concentrations of Aß42 biomarkers since the bulk refractive index change was performed. Baseline stability and the reference ring down times of the sensor head were measured in the air as 0.87% and 441.6µs ± 3.9µs, respectively. Afterward, the total optical loss of the system was measured when the sensor head was immersed in deionized water, ACSF solution, and ACSF solutions with Aß42 in different concentrations. The lowest Aß42 concentration of 2 ppm was detected by LOR. Results showed that LOR fabricated by single-mode fibers for FLRDS system design are promising candidates to be utilized as fiber optic biosensors after sensor head modification and have a high potential for early detection applications of not only AD but possibly also several fatal diseases such as diabetes and cancer.

Plasma GFAP, NfL and pTau 181 detect preclinical stages of dementia.

Background: Plasma biomarkers are preferable to invasive and expensive diagnostic tools, such as neuroimaging and lumbar puncture that are gold standard in the clinical management of Alzheimer's Disease (AD). Here, we investigated plasma Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light Chain (NfL) and Phosphorylated-tau-181 (pTau 181) in AD and in its early stages: Subjective cognitive decline (SCD) and Mild cognitive impairment (MCI). Material and methods: This study included 152 patients (42 SCD, 74 MCI and 36 AD). All patients underwent comprehensive clinical and neurological assessment. Blood samples were collected for Apolipoprotein E (APOE) genotyping and plasma biomarker (GFAP, NfL, and pTau 181) measurements. Forty-three patients (7 SCD, 27 MCI, and 9 AD) underwent a follow-up (FU) visit after 2 years, and a second plasma sample was collected. Plasma biomarker levels were detected using the Simoa SR-X technology (Quanterix Corp.). Statistical analysis was performed using SPSS software version 28 (IBM SPSS Statistics). Statistical significance was set at p < 0.05. Results: GFAP, NfL and pTau 181 levels in plasma were lower in SCD and MCI than in AD patients. In particular, plasma GFAP levels were statistically significant different between SCD and AD (p=0.003), and between MCI and AD (p=0.032). Plasma NfL was different in SCD vs MCI (p=0.026), SCD vs AD (p<0.001), SCD vs AD FU (p<0.001), SCD FU vs AD (p=0.033), SCD FU vs AD FU (p=0.011), MCI vs AD (p=0.002), MCI FU vs AD (p=0.003), MCI FU vs AD FU (p=0.003) and MCI vs AD FU (p=0.003). Plasma pTau 181 concentration was significantly different between SCD and AD (p=0.001), MCI and AD (p=0.026), MCI FU and AD (p=0.020). In APOE ϵ4 carriers, a statistically significant increase in plasma NfL (p<0.001) and pTau 181 levels was found (p=0.014). Moreover, an association emerged between age at disease onset and plasma GFAP (p = 0.021) and pTau181 (p < 0.001) levels. Discussion and conclusions: Plasma GFAP, NfL and pTau 181 are promising biomarkers in the diagnosis of the prodromic stages and prognosis of dementia.

CSF biomarkers of immune activation and Alzheimer's disease for predicting cognitive impairment risk in the elderly.

The immune system substantially influences age-related cognitive decline and Alzheimer's disease (AD) progression, affected by genetic and environmental factors. In a Mayo Clinic Study of Aging cohort, we examined how risk factors like APOE genotype, age, and sex affect inflammatory molecules and AD biomarkers in cerebrospinal fluid (CSF). Among cognitively unimpaired individuals over 65 (N = 298), we measured 365 CSF inflammatory molecules, finding age, sex, and diabetes status predominantly influencing their levels. We observed age-related correlations with AD biomarkers such as total tau, phosphorylated tau-181, neurofilament light chain (NfL), and YKL40. APOE4 was associated with lower Aß42 and higher SNAP25 in CSF. We explored baseline variables predicting cognitive decline risk, finding age, CSF Aß42, NfL, and REG4 to be independently correlated. Subjects with older age, lower Aß42, higher NfL, and higher REG4 at baseline had increased cognitive impairment risk during follow-up. This suggests that assessing CSF inflammatory molecules and AD biomarkers could predict cognitive impairment risk in the elderly.

Integrating Biomarkers From Virtual Reality and Magnetic Resonance Imaging for the Early Detection of Mild Cognitive Impairment Using a Multimodal Learning Approach: Validation Study.

BACKGROUND: Early detection of mild cognitive impairment (MCI), a transitional stage between normal aging and Alzheimer disease, is crucial for preventing the progression of dementia. Virtual reality (VR) biomarkers have proven to be effective in capturing behaviors associated with subtle deficits in instrumental activities of daily living, such as challenges in using a food-ordering kiosk, for early detection of MCI. On the other hand, magnetic resonance imaging (MRI) biomarkers have demonstrated their efficacy in quantifying observable structural brain changes that can aid in early MCI detection. Nevertheless, the relationship between VR-derived and MRI biomarkers remains an open question. In this context, we explored the integration of VR-derived and MRI biomarkers to enhance early MCI detection through a multimodal learning approach. OBJECTIVE: We aimed to evaluate and compare the efficacy of VR-derived and MRI biomarkers in the classification of MCI while also examining the strengths and weaknesses of each approach. Furthermore, we focused on improving early MCI detection by leveraging multimodal learning to integrate VR-derived and MRI biomarkers. METHODS: The study encompassed a total of 54 participants, comprising 22 (41%) healthy controls and 32 (59%) patients with MCI. Participants completed a virtual kiosk test to collect 4 VR-derived biomarkers (hand movement speed, scanpath length, time to completion, and the number of errors), and T1-weighted MRI scans were performed to collect 22 MRI biomarkers from both hemispheres. Analyses of covariance were used to compare these biomarkers between healthy controls and patients with MCI, with age considered as a covariate. Subsequently, the biomarkers that exhibited significant differences between the 2 groups were used to train and validate a multimodal learning model aimed at early screening for patients with MCI among healthy controls. RESULTS: The support vector machine (SVM) using only VR-derived biomarkers achieved a sensitivity of 87.5% and specificity of 90%, whereas the MRI biomarkers showed a sensitivity of 90.9% and specificity of 71.4%. Moreover, a correlation analysis revealed a significant association between MRI-observed brain atrophy and impaired performance in instrumental activities of daily living in the VR environment. Notably, the integration of both VR-derived and MRI biomarkers into a multimodal SVM model yielded superior results compared to unimodal SVM models, achieving higher accuracy (94.4%), sensitivity (100%), specificity (90.9%), precision (87.5%), and F1-score (93.3%). CONCLUSIONS: The results indicate that VR-derived biomarkers, characterized by their high specificity, can be valuable as a robust, early screening tool for MCI in a broader older adult population. On the other hand, MRI biomarkers, known for their high sensitivity, excel at confirming the presence of MCI. Moreover, the multimodal learning approach introduced in our study provides valuable insights into the improvement of early MCI detection by integrating a diverse set of biomarkers.

Clusterization of Behavioral and Psychological Symptoms of Dementia as Assessed by Neuropsychiatric Inventory: A Case Against the Use of Principal Component Analysis.

Background: The term Behavioral and Psychological Symptoms of Dementia (BPSD) covers a group of phenomenologically and medically distinct symptoms that rarely occur in isolation. Their therapy represents a major unmet medical need across dementias of different types, including Alzheimer's disease. Understanding of the symptom occurrence and their clusterization can inform clinical drug development and use of existing and future BPSD treatments. Objective: The primary aim of the present study was to investigate the ability of a commonly used principal component analysis to identify BPSD patterns as assessed by Neuropsychiatric Inventory (NPI). Methods: NPI scores from the Aging, Demographics, and Memory Study (ADAMS) were used to characterize reported occurrence of individual symptoms and their combinations. Based on this information, we have designed and conducted a simulation experiment to compare Principal Component analysis (PCA) and zero-inflated PCA (ZI PCA) by their ability to reveal true symptom associations. Results: Exploratory analysis of the ADAMS database revealed overlapping multivariate distributions of NPI symptom scores. Simulation experiments have indicated that PCA and ZI PCA cannot handle data with multiple overlapping patterns. Although the principal component analysis approach is commonly applied to NPI scores, it is at risk to reveal BPSD clusters that are a statistical phenomenon rather than symptom associations occurring in clinical practice. Conclusions: We recommend the thorough characterization of multivariate distributions before subjecting any dataset to Principal Component Analysis.

Diagnostic value and cognitive regulatory roles of long non-coding RNA UCA1 in Alzheimer's disease.

BACKGROUND: To explore the diagnostic role and potential mechanism of serum lncRNA UCA1 in Alzheimer's disease (AD). METHODS: UCA1 concentration was determined using quantitative RT-PCR. The receiver operating characteristic curve was plotted to assess the diagnostic value. Cell viability and apoptotic capacity were assessed by cell counting kit-8 (CCK-8) and flow cytometry. Water maze experiments were used to test cognitive function in mice. The target genes of UCA1 were identified with a dual luciferase reporter assay. Functional and pathway analysis of miR-342-3p target genes was determined using enrichment analysis. RESULTS: The concentration of UCA1 was elevated in the AD group and represented a diagnostic possibility of AD. The silenced UCA1 reduced the roles of Aß on viability and apoptosis of SH⁃SY5Y cells by sponging miR-342-3p. The impaired cognitive impairment was partly recovered by the knockdown of the UCA1/miR-342-3p axis. Potential targets of miR-342-3p were enriched in function and pathways related to AD progression. CONCLUSION: The UCA1/miR-342-3p axis contributed to the occurrence of AD by regulating cognitive ability.

[Cortico-basal syndrome and cortico-basal degeneration: From the clinical diagnosis to the lesional substrate for an adapted care]. / Le syndrome cortico-basal et la dégénérescence cortico-basale : du diagnostic clinique au substrat lésionnel pour une prise en charge adaptée.

Cortico-basal degeneration is a relatively uncommon cause of degenerative parkinsonism in the elderly. From a clinical point of view, it manifests as a cortico-basal syndrome (CBS), featuring a highly asymmetrical akinetic-rigid syndrome, dystonia, myoclonus and cognitive-behavioral impairment with predominant apraxia. Other clinical phenotypes are possible, including variants with mainly language or behavioral impairment, or with axial, symmetrical parkinsonism resembling progressive supranuclear palsy (PSP). Current diagnostic criteria take into account the heterogeneity of clinical presentations. However, a diagnosis of certainty can only be reached by a pathological study, with the evidence of TAU-positive intraneuronal inclusions. Indeed SCB may be underpinned by other lesional substrates, ranging from frontotemporal degeneration to Alzheimer's disease. Symptom management must be early, multidisciplinary and adapted to the progression of the disorder. The identification of the pathological substrate is an essential prerequisite for pathophysiological therapeutic trials.

Human in vivo evidence of associations between herpes simplex virus and cerebral amyloid-beta load in normal aging.

BACKGROUND: Mounting data suggests that herpes simplex virus type 1 (HSV-1) is involved in the pathogenesis of AD, possibly instigating amyloid-beta (Aß) accumulation decades before the onset of clinical symptoms. However, human in vivo evidence linking HSV-1 infection to AD pathology is lacking in normal aging, which may contribute to the elucidation of the role of HSV-1 infection as a potential AD risk factor. METHODS: To shed light into this question, serum anti-HSV IgG levels were correlated with 18F-Florbetaben-PET binding to Aß deposits and blood markers of neurodegeneration (pTau181 and neurofilament light chain) in cognitively normal older adults. Additionally, we investigated whether associations between anti-HSV IgG and AD markers were more evident in APOE4 carriers. RESULTS: We showed that increased anti-HSV IgG levels are associated with higher Aß load in fronto-temporal regions of cognitively normal older adults. Remarkably, these cortical regions exhibited abnormal patterns of resting state-functional connectivity (rs-FC) only in those individuals showing the highest levels of anti-HSV IgG. We further found that positive relationships between anti-HSV IgG levels and Aß load, particularly in the anterior cingulate cortex, are moderated by the APOE4 genotype, the strongest genetic risk factor for AD. Importantly, anti-HSV IgG levels were unrelated to either subclinical cognitive deficits or to blood markers of neurodegeneration. CONCLUSIONS: All together, these results suggest that HSV infection is selectively related to cortical Aß deposition in normal aging, supporting the inclusion of cognitively normal older adults in prospective trials of antimicrobial therapy aimed at decreasing the AD risk in the aging population.

Associations Between Blood-Based Biomarkers and Cognitive and Functional Trajectories Among Participants of the MEMENTO Cohort.

BACKGROUND AND OBJECTIVES: Elevated levels of Alzheimer disease (AD) blood-based biomarkers are associated with accelerated cognitive decline. However, their distinct relationships with specific cognitive and functional domains require further investigation. We aimed at estimating the associations between AD blood-based biomarkers and the trajectories of distinct cognitive and functional domains over a 5-year follow-up period. METHODS: We conducted a clinic-based prospective study using data from the MEMENTO study, a nationwide French cohort. We selected dementia-free individuals at baseline aged 60 years or older. Baseline measurements of ß-amyloid (Aß) 40 and 42, phosphorylated tau (p-tau181), and neurofilament light chain (NfL) concentrations were obtained using the Simoa HD-X analyzer. Mini-Mental State Examination (MMSE), Free and Cued Selective Reminding Test (FCSRT), animal fluency, Trail Making Tests A and B, Short Physical Performance Battery (SPPB), and Instrumental Activities of Daily Living were administered annually for up to 5 years. We used linear mixed models, adjusted for potential confounders, to model AD biomarkers' relation with cognitive and functional decline. RESULTS: A total of 1,938 participants were included in this study, with a mean (SD) baseline age of 72.8 (6.6) years, and 62% were women. Higher baseline p-tau181 and NfL were associated with significantly faster decline in most cognitive, physical, and functional outcomes (+1 SD p-tau181: ßMMSE = -0.055, 95% CI -0.067 to -0.043, ßFCSRT = -0.034, 95% CI -0.043 to -0.025, ßfluency = -0.029, 95% CI -0.038 to -0.020, ßSPPB = -0.040, 95% CI -0.057 to -0.022, and ß4IADL = -0.115, 95% CI 0.091-0.140. +1 SD NfL: ßMMSE = -0.039, 95% CI -0.053 to -0.025, ßFCSRT = -0.022, 95% CI -0.032 to -0.012, ßfluency = -0.014, 95% CI -0.024 to -0.004, and ß4IADL = 0.077, 95% CI 0.048-0.105). A multiplicative association of p-tau181 and NfL with worsening cognitive and functional trajectories was evidenced. Lower Aß42/40 ratio was only associated with slightly faster cognitive decline in FCSRT and semantic fluency (+1 SD: ß = 0.011, 95% CI 0.002-0.020, and ß = 0.011, 95% CI 0.003-0.020, respectively). These associations were not modified by APOE ε4, sex, nor education level. DISCUSSION: In a memory clinic sample, p-tau181 and NfL, both independently and jointly, are linked to more pronounced cognitive, physical and functional declines. Blood-based biomarker measurement in AD research may provide useful insights regarding biological processes underlying cognitive, physical, and functional declines in at-risk individuals.

Difference of Cerebrospinal Fluid Biomarkers and Neuropsychiatric Symptoms Profiles among Normal Cognition, Mild Cognitive Impairment, and Dementia Patient.

The delineation of biomarkers and neuropsychiatric symptoms across normal cognition, mild cognitive impairment (MCI), and dementia stages holds significant promise for early diagnosis and intervention strategies. This research investigates the association of neuropsychiatric symptoms, evaluated via the Neuropsychiatric Inventory (NPI), with cerebrospinal fluid (CSF) biomarkers (Amyloid-ß42, P-tau, T-tau) across a spectrum of cognitive states to enhance diagnostic accuracy and treatment approaches. Drawing from the National Alzheimer's Coordinating Center's Uniform Data Set Version 3, comprising 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. To assess neuropsychiatric symptoms, we employed the NPI to understand the behavioral and psychological symptoms associated with each cognitive category. For the analysis of CSF biomarkers, we measured levels of Amyloid-ß42, P-tau, and T-tau using the enzyme-linked immunosorbent assay (ELISA) and Luminex multiplex xMAP assay protocols. These biomarkers are critical in understanding the pathophysiological underpinnings of Alzheimer's disease and its progression, with specific patterns indicative of disease stage and severity. This study cohort consists of 1896 participants, which is composed of 977 individuals with normal cognition, 270 with MCI, and 649 with dementia. Dementia is characterized by significantly higher NPI scores, which are largely reflective of mood-related symptoms (p < 0.001). In terms of biomarkers, normal cognition shows median Amyloid-ß at 656.0 pg/mL, MCI at 300.6 pg/mL, and dementia at 298.8 pg/mL (p < 0.001). Median P-tau levels are 36.00 pg/mL in normal cognition, 49.12 pg/mL in MCI, and 58.29 pg/mL in dementia (p < 0.001). Median T-tau levels are 241.0 pg/mL in normal cognition, 140.6 pg/mL in MCI, and 298.3 pg/mL in dementia (p < 0.001). Furthermore, the T-tau/Aß-42 ratio increases progressively from 0.058 in the normal cognition group to 0.144 in the MCI group, and to 0.209 in the dementia group (p < 0.001). Similarly, the P-tau/Aß-42 ratio also escalates from 0.305 in individuals with normal cognition to 0.560 in MCI, and to 0.941 in dementia (p < 0.001). The notable disparities in NPI and CSF biomarkers among normal, MCI and Alzheimer's patients underscore their diagnostic potential. Their combined assessment could greatly improve early detection and precise diagnosis of MCI and dementia, facilitating more effective and timely treatment strategies.

Feasibility of Oral Function Evaluation According to Dementia Severity in Older Adults with Alzheimer's Disease.

Oral function evaluation in older adults with dementia is important for determining appropriate and practical dietary support plans; however, it can be challenging due to their difficulties in comprehending instructions and cooperating during assessments. The feasibility of oral function evaluation has not been well studied. This cross-sectional study aimed to determine the feasibility of oral function evaluation in older adults with Alzheimer's disease (AD) according to Functional Assessment Staging of Alzheimer's Disease (FAST) stages. In total, 428 older adults with AD (45 men and 383 women; mean age: 87.2 ± 6.2 years) were included. Multilevel logistic regression models were used to examine the prevalence of participants who were unable to perform oral function evaluations, including oral diadochokinesis (ODK), repeated saliva swallow test (RSST), and modified water swallow test (MWST). In comparison to the reference category (combined FAST stage 1-3), FAST stage 7 was associated with the infeasibility of ODK (adjusted odds ratio, 95% confidence interval = 26.7, 4.2-168.6), RSST (5.9, 2.2-16.1), and MWST (8.7, 1.6-48.5, respectively). Oral function evaluation is difficult in older adults with severe AD. Simpler and more practical swallowing function assessments and indicators that can be routinely observed are required.

Synaptic vesicle glycoprotein 2 A in serum is an ideal biomarker for early diagnosis of Alzheimer's disease.

BACKGROUND: Previous studies have demonstrated that early intervention was the best plan to inhibit the progression of Alzheimer's disease (AD), which relied on the discovery of early diagnostic biomarkers. In this study, synaptic vesicle glycoprotein 2 A (SV2A) was examined to improve the early diagnostic efficiency in AD. METHODS: In this study, biomarker testing was performed through the single-molecule array (Simoa). A total of 121 subjects including cognitively unimpaired controls, amnestic mild cognitive impairment (aMCI), AD and other types of dementia underwent cerebrospinal fluid (CSF) SV2A testing; 430 subjects including health controls, aMCI, AD and other types of dementia underwent serum SV2A, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL) and p-tau217 testing; 92 subjects including aMCI and AD underwent both CSF SV2A and serum SV2A testing; 115 cognitively unimpaired subjects including APOE ε4 carriers and APOE ε4 non-carriers were tested for serum SV2A, GFAP, NfL and p-tau217. Then, the efficacy of SV2A for the early diagnosis of AD and its ability to identify those at high risk of AD from a cognitively unimpaired population were further analyzed. RESULTS: Both CSF and serum SV2A significantly and positively correlated with cognitive performance in patients with AD, and their levels gradually decreased with the progression of AD. Serum SV2A demonstrated excellent diagnostic efficacy for aMCI, with a sensitivity of 97.8%, which was significantly higher than those of NfL, GFAP, and p-tau217. The SV2A-positive rates ranged from 92.86 to 100% in aMCI cases that were negative for the above three biomarkers. Importantly, of all the biomarkers tested, serum SV2A had the highest positivity rate (81.82%) in individuals at risk for AD. CONCLUSIONS: Serum SV2A was demonstrated to be a novel and ideal biomarker for the early diagnosis of AD, which can effectively distinguish those at high risk of AD in cognitively unimpaired populations.

Feasibility of Using Magnetic Resonance Spectroscopy Test Biomarkers to Diagnose Alzheimer's Disease: Systematic Evaluation and Meta-Analysis.

BACKGROUND: Alzheimer's disease (AD) is the leading cause of dementia, resulting in impairments in memory, cognition, decision-making, and social skills. Thus, accurate preclinical diagnosis of Alzheimer's disease is paramount. The identification of biomarkers for Alzheimer's disease through magnetic resonance spectroscopy (MRS) represents a novel adjunctive diagnostic approach. OBJECTIVE: This study conducted a meta-analysis of the diagnostic results of this technology to explore its feasibility and accuracy. METHODS: PubMed, Cochrane Library, EMBASE, and Web of Science databases were searched without restrictions, with the search period extending up to July 31, 2022. The search strategy employed a combination of subject headings and keywords. All retrieved documents underwent screening by two researchers, who selected them for meta-analysis. The included literature was analyzed using Review Manager 5.4 software, with corresponding bias maps, forest plots, and summary receiver operating characteristic (SROC) curves generated and analyzed. RESULTS: A total of 344 articles were retrieved initially, with 11 articles meeting the criteria for inclusion in the analysis. The analysis encompassed data from approximately 1766 patients. In the forest plot, both sensitivity (95% CI) and specificity (95% CI) approached 1. Examining the true positive rate, false positive rate, true negative rate, and false negative rate, all studies on the summary receiver operating characteristic (SROC) curve clustered in the upper left quadrant, suggesting a very high accuracy of biomarkers detected by MRS for diagnosing Alzheimer's disease. CONCLUSION: The detection of biomarkers by MRS demonstrates feasibility and high accuracy in diagnosing AD. This technology holds promise for widespread adoption in the clinical diagnosis of AD in the future.

Surface protein profiling and subtyping of extracellular vesicles in body fluids reveals non-CSF biomarkers of Alzheimer's disease.

Noninvasive and effortless diagnosis of Alzheimer's disease (AD) remains challenging. Here we report the multiplexed profiling of extracellular vesicle (EV) surface proteins at the single EV level in five types of easily accessible body fluids using a proximity barcoding assay (PBA). A total of 183 surface proteins were detected on the EVs from body fluids collected from APP/PS1 transgenic mice and patients with AD. The AD-associated differentially expressed EV proteins could discriminate between the control and AD/AD model samples with high accuracy. Based on machine learning predictive models, urinary EV proteins exhibited the highest diagnostic potential compared to those on other biofluid EVs, both in mice and humans. Single EV analysis further revealed AD-associated EV subpopulations in the tested body fluids, and a urinary EV subpopulation with the signature proteins PLAU, ITGAX and ANXA1 could diagnose patients with AD in blinded datasets with 88% accuracy. Our results suggest that EVs and their subpopulations from noninvasive body fluids, particularly urine, are potential diagnostic biomarkers for AD.

Impact of genetic predisposition to late-onset neurodegenerative diseases on early life outcomes and brain structure.

Most patients with late-onset neurodegenerative diseases such as Alzheimer's and Parkinson's have a complex aetiology resulting from numerous genetic risk variants of small effects located across the genome, environmental factors, and the interaction between genes and environment. Over the last decade, genome-wide association studies (GWAS) and post-GWAS analyses have shed light on the polygenic architecture of these diseases, enabling polygenic risk scores (PRS) to estimate an individual's relative genetic liability for presenting with the disease. PRS can screen and stratify individuals based on their genetic risk, potentially years or even decades before the onset of clinical symptoms. An emerging body of evidence from various research studies suggests that genetic susceptibility to late-onset neurodegenerative diseases might impact early life outcomes, including cognitive function, brain structure and function, and behaviour. This article summarises recent findings exploring the potential impact of genetic susceptibility to neurodegenerative diseases on early life outcomes. A better understanding of the impact of genetic susceptibility to neurodegenerative diseases early in life could be valuable in disease screening, detection, and prevention and in informing treatment strategies before significant neural damage has occurred. However, ongoing studies have limitations. Overall, our review found several studies focused on APOE haplotypes and Alzheimer's risk, but a limited number of studies leveraging polygenic risk scores or focused on genetic susceptibility to other late-onset conditions.

Cognitive impairment, neurodegenerative disorders, and olfactory impairment: A literature review.

<br><b>Introduction:</b> The early detection and diagnosis of dementia are of key importance in treatment, slowing disease progression, or suppressing symptoms. The possible role of changes in the sense of smell is considered with regard to potential markers for early detection of Alzheimer's disease (AD).</br> <br><b>Materials and methods:</b> A literature search was conducted using the electronic databases PubMed, Scopus, and Web of Science between May 30, 2022 and August 2, 2022. The term "dementia" was searched with keyword combinations related to olfaction.</br> <br><b>Results:</b> A total of 1,288 records were identified through the database search. Of these articles, 49 were ultimately included in the analysis. The results showed the potential role of changes in the sense of smell as potential biomarkers for early detection of AD. Multiple studies have shown that olfactory impairment may be observed in patients with AD, PD, MCI, or other types of dementia. Even though smell tests are able to detect olfactory loss caused by neurodegenerative diseases, they cannot reliably distinguish between certain diseases.</br> <br><b>Conclusions:</b> In individuals with cognitive impairment or neurodegenerative diseases, olfactory assessment has repeatedly been reported to be used for early diagnosis, but not for differential diagnosis.</br>.

Development of a smartphone screening test for preclinical Alzheimer's disease and validation across the dementia continuum.

BACKGROUND: Dementia prevalence is predicted to triple to 152 million globally by 2050. Alzheimer's disease (AD) constitutes 70% of cases. There is an urgent need to identify individuals with preclinical AD, a 10-20-year period of progressive brain pathology without noticeable cognitive symptoms, for targeted risk reduction. Current tests of AD pathology are either too invasive, specialised or expensive for population-level assessments. Cognitive tests are normal in preclinical AD. Emerging evidence demonstrates that movement analysis is sensitive to AD across the disease continuum, including preclinical AD. Our new smartphone test, TapTalk, combines analysis of hand and speech-like movements to detect AD risk. This study aims to [1] determine which combinations of hand-speech movement data most accurately predict preclinical AD [2], determine usability, reliability, and validity of TapTalk in cognitively asymptomatic older adults and [3], prospectively validate TapTalk in older adults who have cognitive symptoms against cognitive tests and clinical diagnoses of Mild Cognitive Impairment and AD dementia. METHODS: Aim 1 will be addressed in a cross-sectional study of at least 500 cognitively asymptomatic older adults who will complete computerised tests comprising measures of hand motor control (finger tapping) and oro-motor control (syllabic diadochokinesis). So far, 1382 adults, mean (SD) age 66.20 (7.65) years, range 50-92 (72.07% female) have been recruited. Motor measures will be compared to a blood-based AD biomarker, phosphorylated tau 181 to develop an algorithm that classifies preclinical AD risk. Aim 2 comprises three sub-studies in cognitively asymptomatic adults: (i) a cross-sectional study of 30-40 adults to determine the validity of data collection from different types of smartphones, (ii) a prospective cohort study of 50-100 adults ≥ 50 years old to determine usability and test-retest reliability, and (iii) a prospective cohort study of ~1,000 adults ≥ 50 years old to validate against cognitive measures. Aim 3 will be addressed in a cross-sectional study of ~200 participants with cognitive symptoms to validate TapTalk against Montreal Cognitive Assessment and interdisciplinary consensus diagnosis. DISCUSSION: This study will establish the precision of TapTalk to identify preclinical AD and estimate risk of cognitive decline. If accurate, this innovative smartphone app will enable low-cost, accessible screening of individuals for AD risk. This will have wide applications in public health initiatives and clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT06114914, 29 October 2023. Retrospectively registered.

Cluster analysis dissecting cognitive deficits in older adults with major depressive disorder and the association with neurofilament light chain.

BACKGROUND: Cognitive impairment is a growing problem with increasing burden in global aging. Older adults with major depressive disorder (MDD) have higher risk of dementia. Neurofilament light chain (NfL) has been proven as a potential biomarker in neurodegenerative disease, including dementia. We aimed to investigate the association between cognitive deficits and NfL levels in older adults with MDD. METHODS: In this cross-sectional study, we enrolled 39 MDD patients and 15 individuals with mild neurocognitive disorder or major neurocognitive disorder, Alzheimer's type, as controls, from a tertiary psychiatric hospital. Both groups were over age 65 and with matched Mini-Mental State Examination (MMSE) score. Demographic data, clinical variables, and plasma NfL levels were obtained. We used cluster analysis according to their cognitive profile and estimated the correlation between plasma NfL levels and each cognitive domain. RESULTS: In the MDD group, participants had higher rate of family psychiatry history and current alcohol use habit compared with controls. Control group of neurocognitive disorders showed significantly lower score in total MMSE and higher plasma NfL levels. Part of the MDD patients presented cognitive deficits clustered with that of neurocognitive disorders (cluster A). In cluster A, the total MMSE score (r=-0.58277, p=0.0287) and the comprehension domain (r=-0.71717, p=0.0039) were negatively correlated to NfL levels after adjusting for age, while the associations had not been observed in the other cluster. CONCLUSIONS: We noted the negative correlation between NfL levels and cognition in MDD patients clustered with neurodegenerative disorder, Alzheimer's type. NfL could be a promising candidate as a biomarker to predict subtype of patients in MDD to develop cognitive decline. Further longitudinal studies and within MDD cluster analysis are required to validate our findings for clinical implications.

Biomarker profiling to determine clinical impact of microRNAs in cognitive disorders.

Alzheimer's disease (AD) and post-stroke cognitive impairment (PSCI) are the leading causes of progressive dementia related to neurodegenerative and cerebrovascular injuries in elderly populations. Despite decades of research, patients with these conditions still lack minimally invasive, low-cost, and effective diagnostic and treatment methods. MicroRNAs (miRNAs) play a vital role in AD and PSCI pathology. As they are easily obtained from patients, miRNAs are promising candidates for the diagnosis and treatment of these two disorders. In this study, we performed complete sequencing analysis of miRNAs from 24 participants, split evenly into the PSCI, post-stroke non-cognitive impairment (PSNCI), AD, and normal control (NC) groups. To screen for differentially expressed miRNAs (DE-miRNAs) in patients, we predicted their target genes using bioinformatics analysis. Our analyses identified miRNAs that can distinguish between the investigated disorders; several of them were novel and never previously reported. Their target genes play key roles in multiple signaling pathways that have potential to be modified as a clinical treatment. In conclusion, our study demonstrates the potential of miRNAs and their key target genes in disease management. Further in-depth investigations with larger sample sizes will contribute to the development of precise treatments for AD and PSCI.